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• What is The PATHS ® Programme for Schools (UK Version)

The PATHS ® Programme for Schools (UK Version) consists of a variety of lessons and is designed for use with primary school children.

Social Emotional Learning Skills

Conceptual units, developmentally appropriate, for all children.

The PATHS ® Programme for Schools (UK Version) is a programme for educators and counsellors designed to facilitate the development of self-control, emotional awareness and interpersonal problem-solving skills. The programme consists of a variety of lessons, and additional materials and charts.

The PATHS ® programme is designed for use with primary school children. The purposes of the PATHS ® programme are to enhance the social competence and social understanding of children, as well as to facilitate educational processes in the classroom. The PATHS ® Programme for Schools (UK Version) has been adapted for a UK audience by Barnardo’s NI.

An effective social-cognitive programme is important because children often show difficulties in social problem-solving, self-control, affective understanding and self-esteem. The PATHS ® Programme for Schools (UK Version) provides teachers and educators with a systematic developmental procedure for enhancing social competence and understanding in children. It addresses the following goals:

• Increased self-control, i.e., the ability to stop and think before acting when upset or confronted with a conflict situation. Lessons in this area also teach identification of problem situations through recognition of “upset” feelings.
• Attributional processes that lead to an appropriate sense of self-responsibility.
• Increased understanding and use of the vocabulary of logical reasoning and problem-solving, e.g., “if…then” and “why…because.”
• Increased understanding and use of the vocabulary of emotions and emotional states; e.g., excited, disappointed, confused, guilty, etc. Increased use of verbal mediation.
• Increased ability to recognise and interpret similarities and differences in the feelings, reactions and points of view of self and others.
• Increased understanding of how one’s behaviour affects others.
• Increased knowledge of, and skill in, the steps of social problem-solving: stopping and thinking; identifying problems and feelings; setting goals; generating alternative solutions; anticipating and evaluating consequences; planning, executing and evaluating a course of action; trying again if the first solution fails.
• Increased ability to apply social problem-solving skills to prevent and/or resolve problems and conflicts in social interactions.

The PATHS ® Programme for Schools (UK Version) Curriculum includes four conceptual units. The units are:

• Emotional understanding
• Self-control
• Social problem solving
• Peer relations and self-esteem

These units are integrated within the lessons and are covered at the appropriate developmental level during each year.

Emotional Understanding

The lessons on emotional understanding cover approximately 25 different affective states and are taught in a developmental hierarchy beginning with basic emotions (happy, sad, angry, etc.) and later introducing more complex emotional states. As the ability to label emotional states is a central focus, major emphasis is placed on encouraging such labelling as a precursor for effective self-control and optimal problem resolution. The children are also taught cues for the self-recognition of their own feelings and the recognition of emotions in others, affective self-monitoring techniques, training in attributions that link causes and emotions, perspective-taking skills in how and why to consider another’s point of view, and information regarding how the behaviour of others can affect oneself. These lessons include group discussions, role-playing, art activities, biographies, stories and educational games.

Self-Control

The second unit focuses on self-control, a prerequisite for effective problem-solving. In this section, emotions such as anger and frustration are discussed, differentiations are made between feelings (all feelings are OK to have) and behaviours (some are OK and some are NOT OK), and modelling and role-play are utilised to teach children new ways to recognise and control anger. Some methods for helping children to calm down and learn better self-control, the Turtle Technique, Three Steps for Calming Down and the Control Signals Poster (CSP) are also introduced in this sub-unit. The CSP is modelled on the notion of a traffic signal and is a revised version of the Stop Light used in the Yale-New Haven Middle School Social Problem Solving Program (Weissberg, Caplan, & Bennetto, 1988). The red light of the CSP focuses on self-control.

Social Problem-Solving

The third focus of the curriculum teaches interpersonal problem-solving. The skills in emotional awareness and self-control are prerequisites for learning competent interpersonal problem-solving, so lessons on this topic do not begin until the groundwork has been covered by previous instruction. Beginning in an informal, active manner (using the Control Signals Poster), children are taught the steps of social problem-solving. Beginning in Primary Five (Year 4), children receive formal lessons on each of the following steps:- Stop - What is Happening?

• Stopping and thinking
• Problem identification
• Feeling identification Get Ready - What Could I Do?
• Deciding on a goal
• Generating alternative solutions
• Evaluating the possible consequences of these solutions
• Selecting the best solution
• Planning the best solution Go! Try My Best Plan
• Trying the formulated plan Evaluate - How Did I Do?
• Evaluating the outcome
• Trying another solution and/or plan, or alternatively re-evaluating the goal, if an obstacle results in failure to reach the intended goal.

Peer Relations and Self-Esteem

Issues regarding friendship and peer relations are introduced throughout the PATHS ® curriculum. This occurs both in the context of feelings (i.e., angry, shy, lonely, etc.) as well as through role-playing and thinking about how to solve problems that arise with friends. The issue of self-esteem is covered in a variety of ways including the regular activity of giving compliments (Pupil of the Day).

The PATHS ® Programme for Schools (UK Version) is intended to be used across all year groups in Primary Schools. Beginning in Primary 1 (Reception) and extending to Primary 7 (Year 6), The programme is developmentally appropriate and universal for all children.

There are four major factors that are addressed by focusing on self-control, emotional understanding, problem-solving skills and creative self-expression. First, we teach children to “Stop and Think”, a response that facilitates the development and use of verbal thought. Second, we provide children with enriched linguistic experiences which will help mediate understanding of self and others. Third, we teach the children to integrate emotional understanding with cognitive and linguistic skills to analyse and solve problems. Fourth, and very critically, we encourage the development of verbally mediated self-control over behaviours.

The PATHS ® Programme for Schools (UK Version) provides teachers with a systematic and developmental procedure for reducing adverse factors which can negatively affect a child’s adaptive behaviour and ability to profit from his/her educational experiences. The programme is designed to help children:-

• develop specific strategies that promote reflective responses and mature thinking skills;
• become more self-motivated and enthusiastic about learning;
• obtain information necessary for social understanding and pro-social behaviour;
• increase their ability to generate creative alternative solutions to problems; and
• learn to anticipate and evaluate situations, behaviours and consequences.

These skills, in turn, increase the child’s access to positive social interactions and provide opportunities for a greater variety of learning experiences. Increasing self-control and reflective thinking skills also contribute to the amelioration of significant underachievement and promote skills which will be beneficial in preventing the genesis of other types of problem behaviours in the future (e.g. alcohol and drug abuse).

In addition, as programme activities become a regular part of the school day, less instructional time is apt to be used for correcting child behaviour problems; in this way, classroom climate can be improved and teacher frustration and “burnout” are reduced.

Next Steps…

For more information on how your school can benefit from the PATHS ® programme, training and coaching or to order a pack from us, get in touch.

• What is The PATHS{R} Programme for Schools (UK Version)?
• Across the UK
• SEL for Secondary Schools

PATHS ® teaches us how to feel other people’s feelings and treat them the way you would like to be treated

Sabrina, Year 3, Vauxhall Primary School, London

I like PATHS ® Pupil of the Day because people give me nice compliments

Melissa Year 5, St Alfege with St Peter’s Primary School, London

Control signals help you with your body language and help you to stay calm.

Aicha, Year 4, Vauxhall Primary School, London

PATHS ® has taught me that all feelings are OK but the way we react is sometimes not OK.

Oyinade, Year 5, St Alfege with St Peter’s Primary School, London

PATHS ® is a time when we all gather around in a calm and safe place and talk about what happens to us and different feelings.

Mariam, Year 4, Vauxhall Primary School, London

The children are more emotionally aware since the start of the programme.

Kat Vallely, Reception teacher, St Alfege with St Peter’s Primary School, London

PATHS ® has equipped the children with the vocabulary and skills to recognise their own and each others feelings/emotions

Natasha Tomlin, PATHS® Coordinator and Friendship Group leader, Grange Primary School, London

Well done – we were kept engaged. Course was very enjoyable. Great to have resources available in Irish. Very useful that the programme is so well laid out and follows on – gives teachers plenty to build on!

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The PATHS® Curriculum

About this program.

Target Population: Universal populations (all children) including those with more serious behavior problems and/or cognitive challenges

For children/adolescents ages: 3 – 12

Program Overview

The PATHS® (Promoting Alternative THinking Strategies) Curriculum is a comprehensive social-emotional learning program designed to reduce aggression and behavior problems and to increase emotional and social competencies in preschool and elementary school-aged children. This curriculum is intended to be used by educators and counselors in the classroom to simultaneously target prevention of future emotional and behavioral problems (all children), as well as intervention (e.g., students with poor classroom behavior and performance). In addition to detailed scripted lessons and materials, generalization and academic integration strategies are incorporated in the program to facilitate use of skills throughout the day (e.g., in the "teachable moments") and to promote the integration of social, emotional, and academic learning and development. Although primarily designed for use in the school setting (whole classroom or smaller groups), the program can be adapted for other locations. Information and activities are included for use with parents. An after-care version is also available.

PATHS® is a registered trademark of PATHS Program LLC, the distributor of The PATHS® Curriculum .

Program Goals

The goals of The PATHS® Curriculum are:

• Decreased internalizing symptoms (e.g., depression, anxiety, and withdrawal)
• Decreased externalizing symptoms (e.g., aggression, bullying, deficits in attention, hyperactivity, disruptive behavior, delinquency)
• Increased emotional understanding & self-awareness
• Increased use of cognitive abilities and strategies (e.g., executive functions)
• Increased self-control & emotion regulation
• Increased use of effective conflict-resolution strategies & problem-solving skills
• Increased prosocial behavior, social skills, & peer sociability
• Improved relationships with teacher & classroom atmosphere
• Increased engagement/attention in the classroom
• Higher test scores in reading, writing, and math

Logic Model

The program representative did not provide information about a Logic Model for The PATHS® Curriculum .

Essential Components

The essential components of The PATHS® Curriculum include:

• A set of separate grade level kits for Preschool/Kindergarten to Grade 5/6. Each kit includes one or two binders of lessons, an instruction manual, and most materials needed (e.g., posters, charts, Feeling Faces, photographs, illustrations, stickers stories or books, puppets, PATHS Feelings Thesaurus, etc.).
• The program is based on several logic models/theories including social cognitive neuroscience, psychoanalytic neuroscience, attachment theory, and the ABCD (Affect-Behavior-Cognition-Dynamic) Model of Development (importance of integration of emotions, cognition, & behavior during childhood).
• Each grade level includes an average of 40 lessons delivered by classroom teachers or counselors for at least 30 minutes for a minimum of two times a week (more sessions are recommended, as many lessons will take more than one session). All lessons are teacher-friendly, with objectives, complete scripts, and instructions, but teachers are encouraged to adapt the lessons to optimize them for their particular classrooms. Lessons are generally taught to entire classrooms, but can also be taught in smaller groups.
• Lessons are developmentally appropriate for each grade, with concepts building from year to year.
• Multimodal instruction includes didactics, discussions, role playing, games, writing, art, music, skills practice, original children's stories, puppets (preschool/kindergarten and grade 1), award winning novels (grades 4–6), projects, and more.
• Generalization techniques are included to promote the integration of social emotional learning with academics (e.g., writing exercises with a Feelings Dictionary or Feelings Thesaurus, original children's stories, social studies connections, etc.).
• Handouts and letters are included to keep parents informed and to promote generalization of skills at home.
• An after-care version of the curriculum (abridged and adapted for the after-care setting) is also available.
• Numerous topics are covered in four major domains to decrease problem behaviors and increase prosocial competency. Examples include:
• Emotional Literacy:
• Understanding and labeling one's own feelings
• Understanding and labeling feelings in others
• Self-regulation and managing emotions
• Self-awareness
• Feelings vs. behaviors
• Cultural display rules
• Understanding emotion cues and facial expressions
• Sharing & talking about feelings with others
• Coping with anxiety & stress
• Feelings & the brain
• Social Skills:
• Complimenting & caring about others (empathy)
• Cooperation, teamwork, & helping others
• Friendship & other relationship skills
• Communication skills
• Sharing & other prosocial behaviors
• Manners & why they're important
• Understanding & appreciating diversity
• Teasing & gossip
• Bullying prevention
• Social awareness
• Good citizenship
• Classroom Behavior:
• Rules & why they're important
• Listening skills & paying attention
• Self-control & self-management
• Organizational skills
• Study skills
• Student-teacher attachment
• Self-motivation
• Fair/unfair
• Attributions for success
• Rejection & inclusion
• Responsibility for self and others
• Problem Solving:
• 11-step problem-solving model
• Problem-solving meetings:
• Problem & conflict identification
• Making good choices
• Responsible decision-making
• Goal setting
• Generating solutions
• Understanding consequences
• Planning skills
• Handling & overcoming obstacles
• Dealing with stereotyping and discrimination
• Delinquency prevention
• Substance abuse prevention

Program Delivery

Child/adolescent services.

The PATHS® Curriculum directly provides services to children/adolescents and addresses the following:

• Aggression, emotional outbursts, hyperactive-disruptive behavior, attentional deficits, motivational issues, conduct problems, oppositional behavior, bullying, anxiety, depression, poor engagement in the classroom, social skill deficits, communication difficulties, stressful classroom atmosphere

Recommended Intensity:

Five 30-minute sessions per week (can be done in two to four sessions if necessary) and generalization throughout the day

Recommended Duration:

The full program is best utilized on a school-wide basis and is delivered throughout each school year from preschool or kindergarten through grade 6.

Delivery Settings

This program is typically conducted in a(n):

• Community-based Agency / Organization / Provider
• School Setting (Including: Day Care, Day Treatment Programs, etc.)

The PATHS® Curriculum includes a homework component:

Children and parents are given homework tasks and worksheets with some of the lessons. Parent handouts and letters are also provided for parent-child discussion and generalization for use of skills at home.

The PATHS® Curriculum has materials available in languages other than English :

Chinese, Croatian, Dutch, French, German, Italian, Portuguese, Spanish

For information on which materials are available in these languages, please check on the program's website or contact the program representative ( contact information is listed at the bottom of this page).

Resources Needed to Run Program

The typical resources for implementing the program are:

• The PATHS® Curriculum Kits
• A/V: In order to monitor implementation , it is necessary to have video and/or audio recording capabilities
• Space/room requirements: Classroom (or space for a small group meeting); space for posters & charts
• Personnel: Classroom teacher or school counselor/clinician

Manuals and Training

Prerequisite/minimum provider qualifications.

Teacher training or certification, school counselor, Bachelor's or equivalent degree, trained paraprofessionals, experience with children

Manual Information

There is a manual that describes how to deliver this program.

Program Manual(s)

Training Manuals:

• Kusché, C. A., & Greenberg, M. T. (1994). The PATHS curriculum . Developmental Research & Programs.
• Domitrovich, C. E., Greenberg, M. T., Kusché, C. A., & Cortes, R. (2005). The PATHS® program (Preschool/Kindergarten level) . PATHS® Program LLC.
• Kusché, C. A., Greenberg, M. T., & CPPRG. (2011). The PATHS® program (Grades 1-2) . PATHS® Program LLC.
• Greenberg, M. T., Kusché, C. A., & CPPRG. (2012). The PATHS® program (Grades 3-5) . PATHS® Program LLC.

For further information on ordering curricular materials, please go to the distributor's website: https://pathsprogram.com/ .

Training Information

There is training available for this program.

Training Contacts:

• Carol A. Kusché, PhD , Developer & Director PATHS® Training LLC [email protected] phone: (206) 323-6688
• Dorothy Morelli, M.Ed. , Partner SEL Worldwide www.selw.org [email protected] phone: (615) 364-6606

Training Type/Location:

On-site or online via Zoom, by arrangement

Number of days/hours:

• Initial 1 or 2-day workshop
• Optional one-day booster session 3-6 months later
• Optional monthly or bimonthly coaching calls available to improve/maintain quality
• Three-hour online video webinar training (self-paced) and three-hour booster video webinar are also available from the distributor.

Implementation Information

Pre-implementation materials.

There are pre-implementation materials to measure organizational or provider readiness for The PATHS® Curriculum as listed below:

A PATHS® Readiness Tool is available at the EpisCenter, Penn State University ( http://www.episcenter.psu.edu/sites/default/files/ebp/PATHS_ReadinessTool_2020-01-09.pdf ).

Formal Support for Implementation

There is formal support available for implementation of The PATHS® Curriculum as listed below:

PATHS® Training LLC provides active support for implementation onsite or through coaching calls. Support is available at any time by request. All consultation is optional and fees vary depending on services requested.

PATHS Program LLC offers a 3-hour video online training webinar and a 3-hour booster webinar.

Fidelity Measures

There are fidelity measures for The PATHS® Curriculum as listed below:

An Implementation Record and Evaluation Form is included in the PATHS® Evaluation Kit (included in the program kits). This measure is a practitioner self-report assessment . Use of the form is optional.

Evaluation and observation forms to assess fidelity and collect other data are available at EpisCenter, Penn State University ( http://www.episcenter.psu.edu/ebp/altthinking/evaltools ).

A PATHS® Program Monitoring Form for use by trained classroom observers is available by request from the distributor, PATHS Program LLC.

Video recordings of lessons can be submitted to trained staff at PATHS Program LLC for evaluation by arrangement. There is a fee for this service.

Established Psychometrics:

Conduct Problems Prevention Research Group. (1999). Initial impact of the Fast Track prevention trial for conduct problems: I. The high-risk sample. Journal of Consulting and Clinical Psychology, 67 (5), 631–647. https://doi.org/10.1037/0022-006X.67.5.631

Implementation Guides or Manuals

There are implementation guides or manuals for The PATHS® Curriculum as listed below:

An implementation manual is included with each curriculum kit (distributed by PATHS Program LLC):

• Kusché, C. A., & Greenberg, M. T. (2011). PATHS® : An introduction to the curriculum. PATHS Program LLC.

All instructions for delivering the lessons are included in the The PATHS® Curriculum lesson binders. The introduction guide is a separate manual that includes the following topics and more:

• Implementing The PATHS® Curriculum Effectively
• Training and Technical Support
• Implementation is a Multi-Year Process
• Who Should Receive PATHS® Lessons?
• Preparing to Teach The PATHS® Curriculum
• Some Common Problems in Implementation
• SEL and Educational Standards
• Bridging The PATHS® Curriculum with Other Academic Curricula
• Encouraging Parent Involvement
• Evidence of Program Effectiveness, a Summary of the Conceptual Framework

Research on How to Implement the Program

Research has been conducted on how to implement The PATHS® Curriculum as listed below:

Faria, A-M., Kendziora, K., Brown, L., O'Brien, B., & Osher, D. (2013). PATHS implementation and outcome study in the Cleveland Metropolitan School District: Final report . American Institutes for Research. https://www.air.org/sites/default/files/downloads/report/Evaluation_of_PATHS_in_CMSD_final_report_6_2413_0.pdf

Gibson, J. E., Werner, S. S., & Sweeney, A. (2015). Evaluating an abbreviated version of the PATHS curriculum implemented by school mental health clinicians. Psychology in the Schools, 52 (6), 549–561. https://doi.org/10.1002/pits.21844

Kam, C. M., Greenberg, M. T., & Walls, C. T. (2003). Examining the role of implementation quality in school-based prevention using the PATHS curriculum. Prevention Science, 4 , 55–63. https://doi.org/10.1023/A:1021786811186

Ross, S. R., Sheard, M. K., & Slavin, R. E. (2019). PATHS® Programme for Schools (NI Version) data collection: Data from the evaluation of Barnardos NI PATHS programme by the Institute for Effective Education at University of York and Johns Hopkins University, Baltimore . Children's Research Network. https://childrensresearchnetwork.org/knowledge/research/paths-programme-for-schools-ni-version-data-collection

Relevant Published, Peer-Reviewed Research

Child Welfare Outcome: Child/Family Well-Being

The CEBC reviews all of the articles that have been published in peer-review ed journals as part of the rating process. When there are more than 10 published, peer-review ed articles, the CEBC identifies the most relevant articles, with a focus on randomized controlled trial s (RCTs) and controlled studies that have an impact on the rating. The articles chosen for The PATHS® Curriculum are summarized below:

Greenberg, M. T., Kusché, C. A., Cook, E. T., & Quamma, J. P. (1995). Promoting emotional competence in school-aged children: The effects of The PATHS Curriculum. Development and Psychopathology, 7(1) , 117–136. https://doi.org/10.1017/S0954579400006374

Type of Study: Randomized controlled trial Number of Participants: 286

Population:

• Age — 6–10 years
• Race/Ethnicity — 165 Caucasian, 91 African American, 11 Asian American, 7 Filipino American, 7 Native American, 4 Other, and 1 Hispanic
• Gender — 167 Male and 119 Female
• Status — Participants were children in 2nd and 3rd grade.

Location/Institution: Seattle, Washington

Summary: (To include basic study design, measures, results, and notable limitations) The purpose of the study was to examine the effectiveness of the Promoting Alternative Thinking Strategies (PATHS®) curriculum [now called The PATHS Curriculum ] on the emotional development of school-aged children. Participants were randomly assigned to intervention or control conditions. Approximately 30% of the children were in a self-contained special needs classroom with the remainder in regular education. Measures utilized include the Recognition of Emotion Concepts subtest from the Kusche Affective Interview – Revised (KAI-R) and the Child Behavior Checklist –Teacher Report Form (CBCL- TRF) . Results indicate that PATHS was effective for both low-and high-risk (special needs) children in improving their range of vocabulary and fluency in discussing emotional experiences, their efficacy beliefs regarding the management of emotions, and their developmental understanding of some aspects of emotions. In some instances, greater improvement was shown in children with higher teacher ratings of psychopathology. Limitations include lack of follow-up.

Length of controlled postintervention follow-up: None.

McMahon, R. J., Bierman, K. L., Coie, J. D., Dodge, K. A., Greenberg, M. T., Lochman, J. E., & Pinderhughes, E. E. (1999). Initial impact of the Fast Track prevention trial for conduct problems: II. Classroom effects. Journal of Consulting and Clinical Psychology, 67 (5), 648–657. https://doi.org/10.1037/0022-006X.67.5.648

Type of Study: Randomized controlled trial Number of Participants: 6,715

• Age — Not specified
• Race/Ethnicity — Not specified
• Gender — Not specified
• Status — Participants were children in 1st grade public education classrooms (3 successive cohorts, at-risk students not included).

Location/Institution: Nashville, Tennessee; Durham, North Carolina; Seattle, Washington; and central Pennsylvania

Summary: (To include basic study design, measures, results, and notable limitations) The purpose of the study was to examine the effectiveness of the Promoting Alternative Thinking Strategies (PATHS®) curriculum [now called The PATHS Curriculum ] and teacher consultation. Participants in four targeted locations were randomized to the PATHS® intervention or the control group. Measures utilized include the Authority Acceptance Scale of the Teacher Observation of Classroom Adaptation —Revised (TOCA–R) and the Social Health Profile (SHP) . Results indicate that there were significant improvements in the domains of aggression and peer relations. Improvements were shown in the areas of better rule following, better classroom atmosphere, and more on-task behavior. Limitations include lack of inter-rater reliability information; and the removal of the highest risk students from the sample (as they received additional interventions), which may have impacted the classroom environment.

Kam, C. -M., Greenberg, M. T., & Walls, C. T. (2003). Examining the role of implementation quality in school-based prevention using The PATHS Curriculum. Prevention Science, 4 (1),    55–63. https://doi.org/10.1023/A:1021786811186

Type of Study: Other quasi-experimental Number of Participants: Intervention: 164

• Race/Ethnicity — Overall Study: 79% African American
• Gender — Overall Study: 47% Male
• Status — Participants were children in 1st grade with special needs.

Location/Institution: Three elementary schools in Harrisburg, Pennsylvania

Summary: (To include basic study design, measures, results, and notable limitations) The purpose of the study was to describe findings regarding quality of implementation in an effectiveness trial conducted in a high-risk, American urban community. The delinquency prevention trial used the Promoting Alternative Thinking Strategies (PATHS®) curriculum [now called The PATHS Curriculum ] as its major program component. Participants were three schools that implemented PATHS® and were compared to three other non-intervention schools in the same school district. Measures utilized include the Teacher Social Competence Rating Scale and measures of principal support and implementation quality. Results indicate that the intervention was effective in improving children’s emotional competence and reducing their aggression in schools. In addition, both principal support and the quality of teacher implementation at the classroom level were critical factors in determining the success of the program dissemination on child outcomes. Significant intervention effects were only found in those settings where both principal support and implementation quality was high; that is, neither high implementation quality nor high principal support by itself predicted intervention effectiveness. Limitations include the lack of direct measures of principal support or organizational climate.

Kam, C. -M., Greenberg, M. T., & Kusché, C. A. (2004). Sustained effects of The PATHS Curriculum on the social and psychological adjustment of children in special education. Journal of Emotional and Behavioral Disorders , 12 (2), 66–78. https://doi.org/10.1177/10634266040120020101

Type of Study: Randomized controlled trial Number of Participants: 133

• Age — Mean=8 years, 8 months
• Race/Ethnicity — 88 White, 27 African American, and 18 Other
• Gender — 97 Male and 36 Female
• Status — Participants were children in 1st through 3rd grade with special needs.

Location/Institution: Seattle, Highline, and Shoreline school districts

Summary: (To include basic study design, measures, results, and notable limitations) The study used a subset of the same sample as Greenberg et al. (1995). The purpose of the study was to examine the long-term effectiveness of the Promoting Alternative Thinking Strategies (PATHS®) curriculum [now called The PATHS Curriculum ] on the adjustment of school-age children with special needs. Participants were randomly assigned to either PATHS® or a control group. Measures utilized include the Kusche Emotional Inventory (KEI), the Children’s Depression Inventory (CDI), the Child Behavior Checklist Teacher Report Form (CBCL-TRF), and the Teacher-Child Rating Scale (TCRS) . Results indicate that the PATHS® curriculum reduced the rate of growth for teacher-reported internalizing and externalizing behaviors 2 years after PATHS and produced a sustained reduction in depressive symptoms reported by the children. Limitations include lack of generalizability beyond self-contained special needs classrooms, and other interventions may have occurred in the classrooms.

Length of controlled postintervention follow-up: 1 month, 1, 2, and 3 years.

Riggs, N. R., Greenberg, M. T., Kusché, C. A., & Pentz, M. A. (2006). The mediational role of neurocognition in the behavioral outcomes of a social-emotional prevention program in elementary school students: Effects of The PATHS Curriculum. Prevention Science, 7 (1), 91–102. https://doi.org/10.1007/s11121-005-0022-1

Type of Study: Randomized controlled trial Number of Participants: 318

• Age — 7–9 years
• Race/Ethnicity — 55% Caucasian, 33% African American, and 22% Other
• Gender — 50% Female

Summary: (To include basic study design, measures, results, and notable limitations) The study used a subset of the same sample as Greenberg et al. (1995). The purpose of the study was to examine the underlying neurocognitive conceptual theory of action of the Promoting Alternative Thinking Strategies (PATHS®) curriculum [now called The PATHS Curriculum ]. Participants were randomly assigned to either the intervention group or to a control group comparison. Measures utilized include the Wechsler Intelligence Scale for Children-Revised (WISC-R), the Stroop Test, the Verbal Fluency Subtest of the McCarthy Scales of Children Abilities, and the Child Behavior Checklist Teacher Report Form (CBCL-TRF) . Results indicate that at one-year follow-up, PATHS® intervention children demonstrated significantly fewer behavior problems both with regard to teacher-reported externalizing and internalizing behaviors. Results also indicate that children who participated in the PATHS® intervention demonstrated greater inhibitory control and verbal fluency at follow-up than did children in comparison classrooms. Limitations include that only a limited number of indicators of inhibitory control and verbal fluency were used.

Length of controlled postintervention follow-up: 1 year.

Domitrovich, C. E., Cortes, R. C., & Greenberg, M. T. (2007). Improving young children's social and emotional competence: A randomized trial of the Preschool "PATHS" curriculum. Journal of Primary Prevention, 28 (2) , 67–91. https://doi.org/10.1007/s10935-007-0081-0

Type of Study: Randomized controlled trial Number of Participants: 246

• Age — Mean=51.40 months
• Race/Ethnicity — 47% African American, 38% European American, 10% Hispanic, and 5% Other
• Gender — 126 Female and 120 Male
• Status — Participants were children enrolled in the Head Start program.

Location/Institution: Central Pennsylvania

Summary: (To include basic study design, measures, results, and notable limitations) The purpose of the study was to evaluate the efficacy of an adaptation of the Promoting Alternative Thinking Strategies (PATHS®) curriculum [now called The PATHS Curriculum ] for preschool-age children in Head Start. Participants were assigned to PATHS® or a wait-list control group. Child assessment s and teacher and parent reports of child behavior assessment s were collected at the beginning and end of the school year. Measures utilized include the Recognition of Emotion Concepts subtest from the Kusche Emotional Inventory (KEI), the Assessment of Children’s Emotions Scales (ACES), the Denham Puppet Interview (DPI), the Day/Night task, Luria’s tapping test, the Attention Sustained subtest from the Leiter-Revised Assessment Battery, the Challenging Situations Task (CST), Teacher-Report of Child: Preschool and Kindergarten Behavior Scales (PKBS), Parent-Report of Child: Head Start Competence Scale (HSCS), and the Peabody Picture Vocabulary Test-Third Edition (PPVT-III) . Results indicate that parents of preschool children who received the PATHS® preschool program described their children as significantly more socially and emotionally competent than did parents of children in comparison classrooms. Further, teachers rated PATHS® children as less socially withdrawn at the end of the school year compared to controls. Limitations include the use of behavior ratings by teachers who were not blinded to study assignment, rather than direct observations of child behavior; and analyses were conducted at the individual child level even though the unit of randomization was the classroom.

Bierman, K. L., Coie, J. D., Dodge, K. A., Greenberg, M. T., Lochman, J. E., McMahon, R. J., & Pinderhughes, E. (2010). The effects of a multiyear universal social–emotional learning program: The role of student and school characteristics. Journal of Consulting and Clinical Psychology, 78 (2), 156–168. https://doi.org/10.1037/a0018607

Type of Study: Randomized controlled trial Number of Participants: 2,937

• Status — Participants were children who had received the PATHS curriculum in Grades 1, 2 and 3 as part of the Fast Track project (at-risk students not included.

Location/Institution: Nashville, Tennessee; Seattle, Washington; and Central Pennsylvania

Summary: (To include basic study design, measures, results, and notable limitations) The study used a subset of the same sample as McMahon et al. (1999). The purpose of the study was to examine the impact of a universal social–emotional learning program, the Promoting Alternative Thinking Strategies (PATHS®) curriculum [now called The PATHS Curriculum ] and teacher consultation, and to examine the main effects of the intervention as well as how outcomes were affected by characteristics of the child (baseline level of problem behavior, gender) and by the school environment (student poverty). Participants were randomized within 3 U.S. locations; the longitudinal analysis involved children of multiple ethnicities who remained in the same intervention or control schools for Grades 1, 2, and 3. Measures utilized include the T eacher Observation of Classroom Adaptation —Revised (TOCA–R), the Teacher Report Form of the Child Behavior Checklist, and the Social Health Profile (SHP) . Results indicate that there were modest positive effects of sustained PATHS® exposure that included reduced aggression and increased prosocial behavior (according to both teacher and peer report) and improved academic engagement (according to teacher report). Peer report effects were moderated by gender, with significant effects only for boys. Most intervention effects were moderated by school environment, with effects stronger in less disadvantaged schools, and effects on aggression were larger with students who showed higher baseline levels of aggression. Limitations include the removal of the highest risk students from the sample (as they received additional interventions) – this may have impacted the school environment. In addition, differences across classrooms in teacher ratings of behavior may be less than accurate estimates, and teachers and peer raters were not blinded to the condition assignment.

Malti, T., Ribeaud, D., & Eisner, M. P. (2011). The effectiveness of two universal preventive interventions in reducing children's externalizing behavior: A cluster randomized controlled trial . Journal of Clinical Child & Adolescent Psychology, 40 (5), 677–692. https://doi.org/10.1080/15374416.2011.597084

Type of Study: Randomized controlled trial Number of Participants: 1,675

• Age — Mean=7.45 years
• Status — Participants were children entering Grade 1.

Location/Institution: Zurich, Switzerland

Summary: (To include basic study design, measures, results, and notable limitations) The purpose of the study was to examine the effectiveness of two universal prevention programs in reducing externalizing behavior in elementary school children. Participants were randomly allocated to one of the four treatment conditions (Promoting Alternative Thinking Strategies [PATHS®] [now called The PATHS Curriculum ], Triple-P, PATHS + Triple-P, or control). Measures utilized include the Social Behavior Questionnaire (SBQ) . Results indicate that intention-to-treat analyses revealed that long-term effects on teacher- and parent-rated externalizing behavior were greater for the PATHS® group than for the control group. However, for most outcomes, no statistically significant positive effects were observed. Limitations include missing data; and results may not generalize to schools where children do not have the same teacher and peers across the first school grades, because teachers and students in Swiss schools are likely to have continued to use the PATHS® skills.

Length of controlled postintervention follow-up: 2 years.

Crean, H. F., & Johnson, D. B. (2013). Promoting Alternative Thinking Strategies (PATHS) and elementary school aged children's aggression: Results from a cluster randomized trial. American Journal of Community Psychology , 52 (1–2), 56–72. https://doi.org/10.1007/s10464-013-9576-4

Type of Study: Randomized controlled trial Number of Participants: 779

• Race/Ethnicity — 389 White/Caucasian, 291 African-American, 147 Hispanic, and 79 Other
• Gender — 442 Female and 337 Male
• Status — Participants were children in 3rd grade at the start of the study.

Location/Institution: Eight schools in a Northeastern urban school district, 4 in a Northeastern suburban school district, and 2 in a Midwestern suburban school district

Summary: (To include basic study design, measures, results, and notable limitations) The purpose of the study was to examine the effectiveness of the Promoting Alternative Thinking Strategies (PATHS®) curriculum [now called The PATHS Curriculum ] in reducing aggression and externalizing behavioral problems. Participants were randomly assigned to the PATHS® intervention or a control condition that received traditional education as usual. Measures utilized include the Teacher Report on Students (TRS); Teacher-Child Rating Scales (TCRS); Aggression Conduct Problems Subscales, Teacher Version of the Behavior Assessment Scale for Children-2 (BASC-2); and the What Would I Do? assessment . Results indicate that PATHS® had beneficial effects on student aggressive outcomes at the end of fifth grade. Teachers noted less aggressive behavior, less conduct problems, and less acting out problems. Limitations include that students only received a portion of the PATHS® curriculum (the intervention typically begins in Kindergarten or First grade, and some students entered the school after the intervention began); raters were not blind to condition; and lack of postintervention follow-up.

Panayiotou, M., Humphrey, N., & Hennessey, A. (2020). Implementation matters: Using complier average causal effect estimation to determine the impact of the Promoting Alternative Thinking Strategies (PATHS) curriculum on children's quality of life. Journal of Educational Psychology, 112 (2), 236–253. https://doi.org/10.1037/edu0000360

Type of Study: Randomized controlled trial Number of Participants: 5,218

• Age — 7–9 years (Mean= 8.12 years)
• Race/Ethnicity — 68% Caucasian, 11% Asian, 7% Afro-Caribbean, 6% Mixed Race, 5% Unknown, 3% Other/Unclassified Race, and 1% Chinese
• Gender — 51% Male
• Status — Participants were children in Year 3–5 in the English elementary school system.

Location/Institution: 45 schools in England

Summary: (To include basic study design, measures, results, and notable limitations) The purpose of the study was to evaluate the impact of the Promoting Alternative Thinking Strategies (PATHS) curriculum [now called The PATHS Curriculum ] on children’s psychological well-being, peer social support, and school connectedness. Participants were randomly assigned to a treatment group that implemented PATHS or a control group that continued their usual provision for 2 years. Measures utilized include the Kidscreen-27 (KS27), Strength and Difficulties Questionnaire (SDQ), and the Social Skills Improvement System . Results indicate that PATHS led to a small, statistically significant improvement in children’s psychological wellbeing, but had no discernible impact on their peer social support or school connectedness. Multilevel complier average causal effect estimation using dosage as a compliance marker increased PATHS effect size for psychological wellbeing and revealed significant medium to large effects for peer social support and school connectedness. Limitations include the use of solely self-reported outcome measures; raters were not blind to condition; inability to model teacher characteristics, because of the lack of classroom membership information for the control schools; and the limitations of the implementation measure in that it provided only a relative “snapshot” of implementation .

Additional References

Kusché, C. A., & Greenberg, M. T. (2006). Brain development and social-emotional learning: An introduction for educators. In M. J. Elias & H. Arnold, (Eds.), The educator's guide to emotional intelligence and academic achievement social-emotional learning in the classroom (pp. 15–34). Corwin Press.

Kusché, C. A., & Greenberg, M. T. (2006). Teaching emotional literacy in elementary school classrooms: The PATHS Curriculum. In M. Elias & H. Arnold (Eds.), The educator's guide to emotional intelligence and academic achievement social-emotional learning in the classroom (pp.150–160). Corwin.

Kusché, C. A., & Greenberg, M. T. (2012). The PATHS curriculum: Promoting emotional literacy, prosocial behavior, and caring classrooms. In S. R. Jimerson, A. B. Nickerson, M. J. Mayer, & M. J. Furlong (Eds.), The handbook of school violence and school safety: International research and practice (pp.435-446). Rutledge.

Contact Information

Date Research Evidence Last Reviewed by CEBC: July 2020

Date Program Content Last Reviewed by Program Staff: March 2021

Date Program Originally Loaded onto CEBC: April 2014

Glossary | Sitemap | Limitations & Disclosures

The CEBC is funded by the California Department of Social Services’ (CDSS’) Office of Child Abuse Prevention and is one of their targeted efforts to improve the lives of children and families served within child welfare system.

© copyright 2006-2024 The California Evidence-Based Clearinghouse for Child Welfare www.cebc4cw.org

Problem-Solving Flowchart: A Visual Method to Find Perfect Solutions

Lucid Content

Reading time: about 7 min

“People ask me questions Lost in confusion Well, I tell them there's no problem Only solutions” —John Lennon, “Watching the Wheels”

Despite John Lennon’s lyrics, nobody is free from problems, and that’s especially true in business. Chances are that you encounter some kind of problem at work nearly every day, and maybe you’ve had to “put out a fire” before lunchtime once or twice in your career.

But perhaps what Lennon’s saying is that, no matter what comes our way, we can find solutions. How do you approach problems? Do you have a process in place to ensure that you and your co-workers come to the right solution?

In this article, we will give you some tips on how to find solutions visually through a problem-solving flowchart and other methods.

What is visual problem-solving?

If you are a literal thinker, you may think that visual problem-solving is something that your ophthalmologist does when your vision is blurry. For the rest of us, visual problem-solving involves executing the following steps in a visual way:

• Define the problem.
• Brainstorm solutions.
• Pick a solution.
• Implement solutions.
• Review the results.

How to make your problem-solving process more visual

Words pack a lot of power and are very important to how we communicate on a daily basis. Using words alone, you can brainstorm, organize data, identify problems, and come up with possible solutions. The way you write your ideas may make sense to you, but it may not be as easy for other team members to follow.

When you use flowcharts, diagrams, mind maps, and other visuals, the information is easier to digest. Your eyes dart around the page quickly gathering information, more fully engaging your brain to find patterns and make sense of the data.

Identify the problem with mind maps

So you know there is a problem that needs to be solved. Do you know what that problem is? Is there only one problem? Is the problem sum total of a bunch of smaller problems?

You need to ask these kinds of questions to be sure that you are working on the root of the issue. You don’t want to spend too much time and energy solving the wrong problem.

To help you identify the problem, use a mind map. Mind maps can help you visually brainstorm and collect ideas without a strict organization or structure. A mind map more closely aligns with the way a lot of our brains work—participants can bounce from one thought to the next defining the relationships as they go.

Mind mapping to solve a problem includes, but is not limited to, these relatively easy steps:

• In the center of the page, add your main idea or concept (in this case, the problem).
• Branch out from the center with possible root causes of the issue. Connect each cause to the central idea.
• Branch out from each of the subtopics with examples or additional details about the possible cause. As you add more information, make sure you are keeping the most important ideas closer to the main idea in the center.
• Use different colors, diagrams, and shapes to organize the different levels of thought.

Alternatively, you could use mind maps to brainstorm solutions once you discover the root cause. Search through Lucidchart’s mind maps template library or add the mind map shape library to quickly start your own mind map.

Create a problem-solving flowchart

A mind map is generally a good tool for non-linear thinkers. However, if you are a linear thinker—a person who thinks in terms of step-by-step progression making a flowchart may work better for your problem-solving strategy. A flowchart is a graphical representation of a workflow or process with various shapes connected by arrows representing each step.

Whether you are trying to solve a simple or complex problem, the steps you take to solve that problem with a flowchart are easy and straightforward. Using boxes and other shapes to represent steps, you connect the shapes with arrows that will take you down different paths until you find the logical solution at the end.

Flowcharts or decision trees are best used to solve problems or answer questions that are likely to come up multiple times. For example, Yoder Lumber , a family-owned hardwood manufacturer, built decision trees in Lucidchart to demonstrate what employees should do in the case of an injury.

To start your problem-solving flowchart, follow these steps:

• Draw a starting shape to state your problem.
• Draw a decision shape where you can ask questions that will give you yes-or-no answers.
• Based on the yes-or-no answers, draw arrows connecting the possible paths you can take to work through the steps and individual processes.
• Continue following paths and asking questions until you reach a logical solution to the stated problem.
• Try the solution. If it works, you’re done. If it doesn’t work, review the flowchart to analyze what may have gone wrong and rework the flowchart until you find the solution that works.

If your problem involves a process or workflow , you can also use flowcharts to visualize the current state of your process to find the bottleneck or problem that’s costing your company time and money.

Lucidchart has a large library of flowchart templates to help you analyze, design, and document problem-solving processes or any other type of procedure you can think of.

Draw a cause-and-effect diagram

A cause-and-effect diagram is used to analyze the relationship between an event or problem and the reason it happened. There is not always just one underlying cause of a problem, so this visual method can help you think through different potential causes and pinpoint the actual cause of a stated problem.

Cause-and-effect diagrams, created by Kaoru Ishikawa, are also known as Ishikawa diagrams, fishbone diagrams , or herringbone diagrams (because they resemble a fishbone when completed). By organizing causes and effects into smaller categories, these diagrams can be used to examine why things went wrong or might go wrong.

To perform a cause-and-effect analysis, follow these steps.

1. Start with a problem statement.

The problem statement is usually placed in a box or another shape at the far right of your page. Draw a horizontal line, called a “spine” or “backbone,” along the center of the page pointing to your problem statement.

2. Add the categories that represent possible causes.

For example, the category “Materials” may contain causes such as “poor quality,” “too expensive,” and “low inventory.” Draw angled lines (or “bones”) that branch out from the spine to these categories.

3. Add causes to each category.

Draw as many branches as you need to brainstorm the causes that belong in each category.

Like all visuals and diagrams, a cause-and-effect diagram can be as simple or as complex as you need it to be to help you analyze operations and other factors to identify causes related to undesired effects.

Collaborate with Lucidchart

You may have superior problem-solving skills, but that does not mean that you have to solve problems alone. The visual strategies above can help you engage the rest of your team. The more involved the team is in the creation of your visual problem-solving narrative, the more willing they will be to take ownership of the process and the more invested they will be in its outcome.

In Lucidchart, you can simply share the documents with the team members you want to be involved in the problem-solving process. It doesn’t matter where these people are located because Lucidchart documents can be accessed at any time from anywhere in the world.

Whatever method you decide to use to solve problems, work with Lucidchart to create the documents you need. Sign up for a free account today and start diagramming in minutes.

Lucidchart, a cloud-based intelligent diagramming application, is a core component of Lucid Software's Visual Collaboration Suite. This intuitive, cloud-based solution empowers teams to collaborate in real-time to build flowcharts, mockups, UML diagrams, customer journey maps, and more. Lucidchart propels teams forward to build the future faster. Lucid is proud to serve top businesses around the world, including customers such as Google, GE, and NBC Universal, and 99% of the Fortune 500. Lucid partners with industry leaders, including Google, Atlassian, and Microsoft. Since its founding, Lucid has received numerous awards for its products, business, and workplace culture. For more information, visit lucidchart.com.

Related articles

Sometimes you're faced with challenges that traditional problem solving can't fix. Creative problem solving encourages you to find new, creative ways of thinking that can help you overcome the issue at hand more quickly.

Dialogue mapping is a facilitation technique used to visualize critical thinking as a group. Learn how you and your team can start dialogue mapping today to solve problems and bridge gaps in knowledge and understanding (plus get a free template!).

Bring your bright ideas to life.

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Promoting Alternative Thinking Strategies (PATHS)

A classroom-based social emotional learning program for elementary school students to reduce aggression and behavior problems.

Program Outcomes

• Antisocial-aggressive Behavior
• Conduct Problems
• Externalizing

Program Type

• Cognitive-Behavioral Training
• School - Individual Strategies
• Skills Training
• Social Emotional Learning

Program Setting

Continuum of intervention.

• Universal Prevention
• Late Childhood (5-11) - K/Elementary

Race/Ethnicity

Endorsements.

Blueprints: Promising Crime Solutions: Effective OJJDP Model Programs: Effective SAMHSA : 2.6-3.2

Program Information Contact

For curriculum and materials: PATHS ® Program Phone: 1-877-71PATHS or 1-877-717-2847 pathsprogram.com

For training: PATHS ® Training pathstraining.com

SEL Worldwide selworldwide.org  Contact: Dorothy Morelli [email protected] [email protected] Phone: 615-364-6606

Program Developer/Owner

Mark Greenberg and Carol Kusché Co-developers

Brief Description of the Program

The PATHS curriculum is a comprehensive program for promoting emotional and social competencies and reducing aggression and behavior problems in elementary school-aged children (grades K-6) while simultaneously enhancing the educational process in the classroom. The evaluation of the preschool version, called Head Start REDI, is treated separately by Blueprints.

The Grade Level PATHS Curriculum consists of separate volumes of lessons for each grade level (K - 6), all of which include developmentally appropriate pictures, photographs, posters, and additional materials. Five conceptual domains, integrated in a hierarchical manner, are included in PATHS lessons at each grade level: self-control, emotional understanding, positive self-esteem, relationships, and interpersonal problem-solving skills. Throughout the lessons, a critical focus of PATHS involves facilitating the dynamic relationship between cognitive-affective understanding and real-life situations. PATHS is designed to be taught two to three times per week (or more often if desired, but not less than twice weekly), with daily activities to promote generalization and support ongoing behavior. PATHS lessons follow lesson objectives and provide scripts to facilitate instruction, but teachers have flexibility in adapting these for their particular classroom needs. Although each unit of PATHS focuses on one or more skill domains (e.g., emotional recognition, friendship, self-control, problem solving), aspects of all five major areas are integrated into each unit. Moreover, each unit builds hierarchically upon and synthesizes the learning which preceded it.

The PATHS curriculum is designed to be used by educators and counselors in a multi-year, universal prevention model. To encourage parent involvement and support, parent letters, home activity assignments, and information are also provided.

The PATHS curriculum is a comprehensive program for promoting emotional and social competencies and reducing aggression and behavior problems in elementary school-aged children (grades K-6) while simultaneously enhancing the educational process in the classroom.

PATHS is now available by grade level in the following grades: Kindergarten, Grade 1, Grade 2, Grade 3, Grade 4, and Grade 5/6. The original multi-year version is also available from the publisher. The grade level versions maintain all key elements of the original version and now organize them more discretely by grade levels. The preschool version of the program, called Head Start REDI, is treated separately by Blueprints.

PATHS targets five major conceptual domains: (1) self control; (2) emotional understanding; (3) positive self-esteem; (4) relationships; and (5) interpersonal problem solving skills. In addition, a 30-lesson non-mandatory supplementary unit reviews and extends PATHS concepts that are covered in other units.

The PATHS curriculum is designed for use by regular classroom teachers. Lessons are sequenced according to increasing developmental difficulty and designed for implementation in approximately 20-30 minutes 2 to 3 times per week. The curriculum provides detailed lesson plans, exact scripts, suggested guidelines, and general and specific objectives for each lesson. However, the curriculum has considerable flexibility so that it can also be integrated with an individual teacher's style. Lessons include such activities as dialoguing, role-playing, story-telling by teachers and peers, social and self-reinforcement, attribution training, and verbal mediation. Learning is promoted in a multi-method manner through the combined use of visual, verbal, and kinesthetic modalities.

Primary Evidence Base for Certification

Study 7 (Malti et al., 2012) found that by the beginning of grade 5 (just over two years after program commencement), the intervention condition, relative to a control group, showed:

• Fewer externalizing behaviors (e.g., aggression)
• A reduction in ADHD symptoms

Brief Evaluation Methodology

Of the 19 studies Blueprints has reviewed, one (Study 7) meets Blueprints evidentiary standards (specificity, evaluation quality, impact, dissemination readiness). Study 7 was conducted by independent evaluators.

Malti et al. (2011, 2012) and Averdijk et al. (2016) used a cluster randomized controlled trial with 56 public primary schools in Zurich assigned to four treatment conditions: PATHS ( n = 442), Triple-P ( n = 422), PATHS+Triple-P ( n = 397), and control ( n = 414). The program was implemented with grades K-2, and students were followed for eight years, from ages 7-8 to when the children were 11 years old (grade 4; Malti et al., 2011, 2012) to age 13 and age 15 (Averdijk et al., 2016). Assessments measured externalizing behavior and social competence (Malti et al., 2011, 2012) and delinquency (Averdijk et al., 2016).

Blueprints Certified Studies

Malti, T., Ribeaud, D., & Eisner, M. (2012). Effectiveness of a universal school-based social competence program: The role of child characteristics and economic factors. International Journal of Conflict and Violence, 6, 249-259.

Risk and Protective Factors

Risk factors.

Individual: Antisocial/aggressive behavior*, Early initiation of antisocial behavior, Favorable attitudes towards antisocial behavior, Hyperactivity*

School: Low school commitment and attachment, Repeated a grade

Protective Factors

Individual: Clear standards for behavior, Problem solving skills, Prosocial behavior, Skills for social interaction

Peer: Interaction with prosocial peers

School: Opportunities for prosocial involvement in education, Rewards for prosocial involvement in school

* Risk/Protective Factor was significantly impacted by the program

See also: Promoting Alternative Thinking Strategies (PATHS) Logic Model (PDF)

Race/Ethnicity/Gender Details

Subgroup differences in program effects by race, ethnicity, or gender (coded in binary terms as male/female) or program effects for a sample of a specific racial, ethnic, or gender group:

Study 7 (Malti et al., 2011, 2012; Averdijk et al., 2016) did not examine differences in program effects by race, ethnicity, or gender.

Sample demographics including race, ethnicity, and gender for Blueprints-certified studies:

The Swiss sample for Study 7 included similar percentages of boys and girls.

Training and Technical Assistance

PATHS program training is usually done on site at a school or school district. The initial training workshop consists of two separate days scheduled approximately 4-8 weeks apart. The first day provides teachers/trainees with theory, research background, lessons modeled by the trainer, practice to prepare teachers to use PATHS lessons, and implementation planning. During the 4-8 week period prior to the second day of training, teachers gain initial experience with the curriculum. This leads to a more interactive learning experience on the second workshop day since teachers have had some realistic experiences with lesson implementation. Trainer and teachers discuss advanced curriculum issues, trade ideas and engage in problem solving, and teachers model interactive lessons. Another option is to schedule training for two consecutive days.

For optimal implementation, sites should consider additional training/technical assistance activities each year. Ongoing consultation and booster visits are available and are often desired by comprehensive, long-term implementations. The trainer can provide a booster visit each year (one day in length) to meet with the staff and provide continued professional development. One day of fidelity visits is another option, in which the trainer visits schools, observes lessons, etc. The trainer can also provide ongoing consultation by means of regularly scheduled phone calls/conference calls and on-call email consultation with the school's or agency's PATHS coordinator.

In addition to training for teachers, when a multi-school site implementation is conducted, separate training workshops are also provided to school principals on issues in building-wide use and principal leadership. Additional trainings can be arranged for other school staff.

Training for PATHS coaches-a position often utilized by larger implementations to provide feedback, ideas, and encouragement to classroom teachers implementing the PATHS program-typically involves six on-site trainer visits per year, for training, observation, and continued professional development in social-emotional learning. Every-other-week team conference calls typically take place in between on-site training sessions, with everyone checking in to engage in problem-solving and receive additional professional development.

Training and technical assistance is available from two sources:

PATHS™ Education Worldwide Dorothy Morelli, CEO 615-364-6606 [email protected]

Carol A. Kusché, Ph.D. PATHS ® Training LLC 927 10th Ave. East Seattle, WA 98102 206-323-6688 [email protected]

Training Certification Process

The PATHS Training Program is designed to develop highly experienced, high quality trainers who are fully competent to provide training in the PATHS Curriculum to their local educational entity. Trainers can include staff (teachers, support staff, staff developers) from local school districts/boards, Local Education Agencies (LEAs) and non-profit agencies focused on the promotion of children's mental health and youth development. PATHS Training LLC trains these qualified "educators" to conduct school-based or regional workshops for the preparation of teachers and school support staff who plan to implement PATHS Curricula within these educational entities. Once certified, PATHS Trainers conduct workshops and provide follow-up technical assistance and coaching services for their district or regional personnel in accordance with the PATHS workshop training materials, agenda and guidelines.

To be considered as an Affiliate Trainer requires meeting the following prerequisites:

• High Quality Performance for at least two years as a PATHS teacher or PATHS Coach
• Master's degree (or comparable credentials)
• Classroom experience with students in a learner role (teaching, administration, and school counseling preferred)
• Training experience with educators

After meeting the pre-requisites above, the requirements to be certified as a trainer include participation in the following four-step training/certification process. The AT candidate(s) receive four days of coaching from a PATHS Senior Trainer in addition to participation in an Observation Workshop and two Shared Workshops. The first day of coaching follows the Observation Workshop. The second day precedes the Shared Workshop. The third day follows the Shared Workshop in preparation for the second Shared Workshop. The fourth day follows the second Shared Workshop in preparation for certification as a PATHS trainer. The primary purpose of the coaching days are to provide detailed and personalized instruction in how to conduct the PATHS workshop and to observe and provide feedback on candidates' training skills. Candidates who successfully complete the program are certified as Affiliate Trainers.

Benefits and Costs

Program Benefits (per individual): $8,360 Program Costs (per individual): $378 Net Present Value (Benefits minus Costs, per individual): $7,981 Measured Risk (odds of a positive Net Present Value): 62%

Source: Washington State Institute for Public Policy All benefit-cost ratios are the most recent estimates published by The Washington State Institute for Public Policy for Blueprint programs implemented in Washington State. These ratios are based on a) meta-analysis estimates of effect size and b) monetized benefits and calculated costs for programs as delivered in the State of Washington. Caution is recommended in applying these estimates of the benefit-cost ratio to any other state or local area. They are provided as an illustration of the benefit-cost ratio found in one specific state. When feasible, local costs and monetized benefits should be used to calculate expected local benefit-cost ratios. The formula for this calculation can be found on the WSIPP website .

Program Costs

Start-up costs, initial training and technical assistance.

$4,000 + trainer travel costs for initial two-day teacher training for up to 40 teachers. There is usually another day for training set up and meeting with the school administration at $2,000.

Curriculum and Materials

$350 to $600 per classroom, depending on the grade level.

Materials Available in Other Language: Parent and home materials have been translated to Spanish and are free of charge with the curriculum.

PATHS is available in the following languages: German British English (http://www.pathseducation.co.uk/what-is-paths-across-the-uk) Croatian (some grades) Chinese (some grades) Swedish (preK and K) Dutch Welsh Portuguese French (under development as of 9/20/17) For these translations, interested persons can contact Mark Greenberg or Channing-Bete.

Other Start-Up Costs

Intervention implementation costs, ongoing curriculum and materials.

$100 per year per classroom for photocopying activity sheets, poster replacement and books.

Qualifications : None required but typically delivered by classroom teachers or school counselors.

Ratios : None required. Program designed for classroom delivery with typical classroom ratios of 15 - 25 students per teacher, depending on grade level.

Time to Deliver Intervention : Curriculum is taught three times per week for a minimum of 20 - 30 minutes and ideally should be taught throughout the school year from kindergarten through grade five.

Other Implementation Costs

A local coach is recommended for at least the first year. Coaches are usually teachers with special PATHS training. Whether a full- or part-time coach is needed depends upon how many teachers need the support.

Implementation Support and Fidelity Monitoring Costs

Ongoing training and technical assistance.

Technical assistance by email and phone is available from PATHS Training, LLC. While coaches are used, funds should be budgeted for annual site visits by national trainers at a cost of $4,000 plus travel.

Fidelity Monitoring and Evaluation

Local coach takes the lead in fidelity monitoring. If site does not have a coach, a local coordinator responsible for fidelity monitoring should be designated.

Ongoing License Fees

Other implementation support and fidelity monitoring costs.

No information is available

Other Cost Considerations

The size of implementation is key to lowering costs. Training many teachers at one time is most cost effective.

Year One Cost Example

This example will be to implement PATHS in two elementary schools using 20 teachers and their classes of 25 students each. Schools can expect to incur the following costs:

With 500 students participating, the cost per student is $119.

Funding Strategies

Funding overview.

It is relatively inexpensive to get PATHS started in schools, with districts only needing to identify funds for initial training and curriculum purchase. To be most effective, the ongoing implementation of PATHS requires a relatively significant commitment of classroom time in grades K-5. District and school administrators must view the development of social and emotional competence and reduction of disruptive behavior as a priority in order to commit the time.

Improving the Use of Existing Public Funds

Sustaining this program requires the ongoing allocation of existing classroom teaching time for the intervention to be delivered by teachers or counselors. To the extent that existing interventions in schools aimed at fostering the development of social and emotional competence and the reduction of disruptive behavior are not evidence-based, funding for these interventions can be considered for re-direction to PATHS.

Allocating State or Local General Funds

State and local funds, most typically from school budgets, are often allocated to purchase the initial training and curriculum. State departments of education or health may also allocate state funds toward prevention programs, and administer them to school districts competitively or through formula. Some states have put in place legislative set-asides requiring a certain portion of state agency budgets be dedicated to evidence-based programs and/or prevention programs.

Maximizing Federal Funds

Formula Funds:

• Title I can potentially support curricula purchase, training, and teacher salaries in schools that are operating schoolwide Title I programs (at least 40% of the student population is eligible for free and reduced lunch). In order for Title I to be allocated, PATHS would have to be viewed as contributing to overall academic achievement.
• Office of Juvenile Justice and Delinquency Prevention (OJJDP) Formula Funds support a variety of improvements to delinquency prevention programs and juvenile justice programs in states. Evidence-based programs are an explicit priority for these funds, which are typically administered on a competitive basis from the administering state agency to community-based programs.
• The Mental Health Services Block Grant (MHSBG) can fund a variety of mental health promotion and intervention activities and is a potential source of support for school-based mental health promotion programs, depending on the priorities of the administering state agency.

Discretionary Grants: There are relevant federal discretionary grants administered by SAMHSA (Department of Health and Human Services) , OJJDP (Department of Justice), and the Department of Education that could support the PATHS program.

Foundation Grants and Public-Private Partnerships

Since the initial training and curriculum purchases, while inexpensive, may still be prohibitive to districts interested in implementing the program, a public-private partnership in which private foundations or local education funds provide funding for initial training and curriculum and schools agree to commit staff time to implementation can be an effective approach for financing PATHS.

Generating New Revenue

New revenue streams are not typically created for this program, though the program is so low-cost that interested schools could potentially consider community fundraising through Parent Teacher Associations, student civic societies, or partnerships with local businesses and civic organizations as a means of raising dollars to support the initial training and curriculum purchases.

Data Sources

All information comes from the responses to a questionnaire submitted by the developer of the program, Mark Greenberg, to the Annie E. Casey Foundation.

Evaluation Abstract

Mark Greenberg and Carol Kusché Co-developers Prevention Research Center Penn State University University Park, PA 16802-6504 (814) 863-0112 [email protected] [email protected]

Program Specifics

Program goals, population demographics.

PATHS is implemented with elementary school age youth (grades K-6). A modified version to be age-appropriate for preschool students (called Head Start REDI) is treated separately by Blueprints. PATHS has been shown to be effective for both males and females, different ethnic and socio-demographic populations, and a wide variety of populations, including students in regular education and special needs settings.

Target Population

Other risk and protective factors.

Protective : prosocial orientation, positive peer relations, bonding to school.

Risk/Protective Factor Domain

Risk/protective factors, description of the program, theoretical rationale.

• an integration of a variety of successful approaches and promising theories
• a developmental model, including neuropsychological brain development
• a multi-grade level paradigm
• a strong focus on the role of emotions and emotional development
• generalization of skills to everyday situations
• ongoing training and support for implementation
• multiple measures of both process and outcome for assessing program effectiveness

PATHS is based on five conceptual models. The first, the ABCD (Affective-Behavioral-Cognitive-Dynamic) Model of Development focuses on the promotion of optimal developmental growth for each individual. The ABCD model places primary importance on the developmental integration of affect (i.e., emotion, feeling, mood) and emotion language, behavior, and cognitive understanding to promote social and emotional competence. The second model incorporates an eco-behavioral systems orientation and emphasizes the manner in which the teacher uses the curriculum model and generalizes the skills to build a healthy classroom atmosphere (i.e., one that supports the children's use and internalization of the material they have been taught). The third model involves the domains of neurobiology and brain structuralization/organization. PATHS incorporates strategies to optimize the nature and quality of teacher-child and peer-peer interactions that are likely to impact brain development as well as learning. The fourth paradigm involves psychodynamic education (derived from Developmental Psychodynamic Theory) which aims to coordinate social, emotional, and cognitive growth. Finally, the fifth model includes psychological issues related to emotional awareness, or as it is more popularly labeled, emotional intelligence. As such, a central focus of PATHS is encouraging children to discuss feelings, experiences, opinions, and needs that are personally meaningful, and making them feel listened to, supported, and respected by both teachers and peers. As a result, the internalization of feeling valued, cared for, appreciated, and part of a social group is facilitated, which, in turn, motivates children to value, care for, and appreciate themselves, their environment, their social groups, other people, and their world.

Theoretical Orientation

• Skill Oriented
• Cognitive Behavioral
• Biological - Neurobiological
• Self Efficacy
• Social Learning

Outcomes (Brief, over all studies)

Malti et al. (2012) found that, relative to students in the control schools, students in the intervention schools had significantly fewer externalizing behaviors (e.g., aggression) and ADHD symptoms by the beginning of grade 5 (more than two years after program commencement).

Effect Size

In Study 7 (Malti et al., 2012), the effect sizes of significant results were small to moderate. Specifically, compared to a control group, PATHS significantly reduced aggressive behavior (effect size = 0.42) and ADHD symptoms (effect size = 0.46).

Generalizability

One study Blueprints standards for high-quality methods with strong evidence of program impact (i.e., "certified" by Blueprints): Study 7 (Malti et al., 2011, 2012; Averdijk et al., 2016). The study examined a sample of elementary schools in Zurich, Switzerland, in which the treatment group was compared to a business-as-usual control group.

Potential Limitations

Additional Studies (not certified by Blueprints)

Studies 1-2 ( Greenberg et al., 1995; Riggs et al., 2006)

Sample attrition in the first year of implementation was high and reduced the sample size significantly, thus reducing the power to accurately detect differences. High levels of student mobility further limited comparisons between students receiving one or two years of the intervention. No analysis of differential attrition or mobility was conducted for the full sample (although this was done for the regular classroom subsample), which would further inform the interpretations of the analyses.

Greenberg, M. T., Kusche, C. A., Cook, E. T., & Quamma, J. P. (1995). Promoting emotional competence in school-aged children: The effects of the PATHS curriculum. Development and Psychopathology, 7 , 117-136.

Riggs, N. R., Greenberg, M. T., Kusché, C. A., & Pentz, M. A. (2006). The mediational role of neurocognition in the behavioral outcomes of a social-emotional prevention program in elementary school students: Effects of the PATHS curriculum. Prevention Science, 7 , 91-102.

Studies 3-6 ( Kam et al., 2004; Greenberg & Kusche, 1998; Kam et al., 2003; Curtis & Norgate, 2007)

Small sample sizes within treatment groups make it difficult to generalize the outcomes to larger, more diverse populations. No analyses of differential attrition were performed.

Kam, C., Greenberg, M. T., & Kusché, C. A. (2004). Sustained effects of the PATHS curriculum on the social and psychological adjustment of children in special education. Journal of Emotional and Behavioral Disorders, 12 , 66-78.

Greenberg, M. T., & Kusche, C. A. (1998). Preventive intervention for school-aged deaf children: The PATHS curriculum. Journal of Deaf Studies and Deaf Education, 3, 49-63.

Kam, C., Greenberg, M. T., & Walls, C. T. (2003). Examining the role of implementation quality in school-based prevention using PATHS curriculum. Prevention Science, 4, 55-63.

Curtis, C., & Norgate, R. (2007). An evaluation of the Promoting Alternative Thinking Strategies curriculum at key stage 1. Educational Psychology in Practice, 23 , 33-44.

Study 8 (Seifert et al., 2004)

• No pretest assessment, assessment of baseline equivalence, or information on attrition
• The comparisons across cohorts may be confounded by time
• Only outcomes based on interviewer ratings reached significance, not outcomes based on child self-reports
• Interviewers rating children likely were not blinded to the condition
• Reports of teacher dissatisfaction with the program suggest implementation problems

Seifert, R., Gouley, K., Miller, A. L., & Zabriski, A. (2004). Implementation of the PATHS curriculum in an urban elementary school. Early Education & Development, 15 (4), 471-486.

Study 9 ( Bierman et al., 2010)

• A concurrent intervention for high-risk students meant that the sample excluded the worst behaving students and that the other ongoing intervention might have influenced the program outcomes
• Baseline tests for equivalence compared schools but not children
• Teachers who delivered the intervention also did ratings of classroom children, and results proved stronger for teacher ratings than child ratings
• Attrition was high because the study was limited to children who had stayed in the same school for all three years, and differential attrition was apparent on several baseline measures
• Contrary to intent-to-treat procedures, only students who participated in the program for all three years were followed and used in the analysis

Bierman, K. L., Coie, J. D., Dodge, K. A., Greenberg, M. T., Lochman, J. E., McMahon, R. J., & Pinderhughes, E. (2010). The effects of a multiyear universal social-emotional learning program: The role of student and school characteristics. Journal of Consulting and Clinical Psychology , 78 (2), 156.

Study 10 ( Crean & Johnson, 2013; SCDRC, 2010)

• Teachers who delivered the program also provided some student measures
• Models adjusted for clustering but may have too few schools to obtain reliable estimates
• No effects on independent behavioral outcomes
• Some evidence of iatrogenic effects on conduct problems in first two years of the program

Crean, H. F., & Johnson, D. B. (2013). Promoting Alternative THinking Strategies (PATHS) and elementary school aged children's aggression: Results from a cluster randomized trial. American Journal of Community Psychology, 52 , 56-72.

Social and Character Development Research Consortium (SCDRC) (2010). Efficacy of schoolwide programs to promote social and character development and reduce problem behavior in elementary school children (NCER 2011-2001). Washington, DC: National Center for Education Research, Institute of Education Sciences, U.S. Department of Education.

Study 11 (Little et al., 2012; Berry et al., 2016)

• Randomized 64 schools but eight dropped out before baseline
• Most measures of children came from teachers who delivered the program
• Measures validated by others but no study-specific figures
• Incomplete tests for differential attrition
• No significant effects on behavioral outcomes

Little, M., Berry, V., Morpeth, L., Blower, S., Axford, N., Taylor, R., . . . Tobin, K. (2012). The impact of three evidence-based programmes delivered in public systems in Birmingham, UK. International Journal of Conflict and Violence , 6 (2), 260-272.

Berry, V., Axford, N., Blower, S., Taylor, R. S., Edwards, R. T., Tobin, K., . . . Bywater, T. (2016). The effectiveness and micro-costing analysis of a universal, school- based, social-emotional learning programme in the UK: A cluster-randomised controlled trial. School Mental Health, 8, 238-256.

Study 12 (Schonfeld et al., 2015)

• Not an intent-to-treat study - excluded those not participating in all four program years
• No tests for baseline equivalence of outcomes
• No controls for baseline scores
• Tests for differential attrition incomplete
• Sample from one large, urban school district

Schonfeld, D. J., Adams, R. E., Fredstrom, B. K., Weissberg, R. P., Gilman, R., Voyce, C., ... & Speese-Linehan, D. (2015). Cluster-randomized trial demonstrating impact on academic achievement of elementary social-emotional learning. School Psychology Quarterly , 30 (3), 406.

Study 13 (Fishbein et al., 2016)

• No information on student-level attrition
• No information on reliability/validity provided for 8 of the 14 outcome measures
• Teachers who delivered the program also completed the assessments (with effects in favor of the treatment on 13 of the 13 teacher-rated measures)
• There was an effect on 15 out of 23 measures, but only 2 of these effects were assessed using independent measures (and it still wasn't clear whether those collecting these data were blind to condition)
• Small sample size (n = 4 schools, and schools were the unit of assignment)
• Incorrect level of analysis with no adjustment for unit of randomization (schools)

Fishbein, D. H., Domitrovich, C., Williams, J., Gitukui, S., Guthrie, C., Shapiro, D., & Greenberg, M. (2016). Short-term intervention effects of the PATHS curriculum in young low-income children: Capitalizing on plasticity. Journal of Primary Prevention, 37 , 493-511.

Study 14 (Goossens et al., 2012)

• Non-random assignment of schools
• Many student measures came from teachers who delivered the program
• Adjusted for clustering, but the sample of 18 clusters may be too small for reliable estimates
• Tests for baseline equivalence showed many differences
• No reliable program effects

Goossens, F., Gooren, E., Orobio de Castro, B., Overveld, K., Buijs, G., Monshouwer, K., … Paulussen, T. (2012). Implementation of PATHS through Dutch municipal health services: A quasi-experiment. International Journal of Conflict and Violence, 6 , 234-248.

Study 15 (David, 2014)

• Non-random assignment of schools with only one control school
• Some student measures came from teachers who delivered the program
• Low reliabilities for some measures
• Incorrect level of analysis
• No tests for differential attrition
• No significant program effects
• Small sample of only three schools

David, M. D. (2014). The effect of Promoting Alternative THinking Strategies on social competence and reading achievement in elementary school children . Master's Thesis. Halifax, Nova Scotia: Mount Saint Vincent University.

Study 16 (Barlow et al., 2015; Hennessey & Humphrey, 2020; Humphrey et al., 2016; Humphrey, Barlow, & Lendrum, 2018; Humphrey, Hennessey et al., 2018; Panayiotou et al., 2020)

• Some posttest child measures provided by teachers who delivered the program
• Evidence of differential attrition
• Few ITT effects at posttest, though stronger effects in QED complier analysis
• No program effects at long-term follow-up

Barlow, A., Wigelsworth, M., Lendrum, A., Pert, K., Joyce, C., Stephens, E., . . . Humphrey, N. (2015). Promoting Alternative Thinking Strategies (PATHS): Evaluation report and executive summary . The Education Endowment Fund. Available online: https://files.eric.ed.gov/fulltext/ED581278.pdf .

Hennessey, A., & Humphrey, N. (2020). Can social and emotional learning improve children's academic progress? Findings from a randomised controlled trial of the Promoting Alternative Thinking Strategies (PATHS) curriculum. European Journal of Psychology of Education, 35 (4), 751-774.

Humphrey, N., Barlow, A., & Lendrum, A. (2018). Quality matters: Implementation moderates student outcomes in the PATHS curriculum. Prevention Science, 19 , 197-208.

Humphrey, N., Barlow, A., Wigelsworth, M., Lendrum, A., Pert, K., Joyce, C., . . . Turner, A. (2016). A cluster randomized controlled trial of the Promoting Alternative Thinking Strategies (PATHS) curriculum. Journal of School Psychology, 58 , 73-89.

Humphrey, N., Hennessey, A., Lendrum, A., Wigelsworth, M., Turner, A., Panayiotou, M., . . . Calam, R. (2018). The PATHS curriculum for promoting social and emotional well-being among children aged 7-9 years: A cluster RCT. Public Health Research, 6 (10), 1-116.

Panayiotou, M., Humphrey, N., & Hennessey, A. (2020). Implementation matters: Using complier average causal effect estimation to determine the impact of the Promoting Alternative Thinking Strategies (PATHS) curriculum on children's quality of life. Journal of Educational Psychology, 112 (2), 236-253.

S tudy 17 (Novak et al., 2017)

• Teachers who delivered the program provided all child measures
• Adjusted for clustering within classrooms but not within schools, the unit of randomization
• No significant baseline differences for outcomes but no tests for sociodemographic characteristics
• No significant main effects at posttest, only effects for a low-risk subgroup

Novak, M., Mihic, J., Bašic, J., & Nix, R. L. (2017). PATHS in Croatia: A school-based randomised-controlled trial of a social and emotional learning curriculum. International Journal of Psychology, 52 (2), 87-95.

Study 18 (Hindley & Reed, 1999)

• Non-random assignment of schools/units ( n = 7)
• Some measures came from teachers who delivered the program
• No reliability or validity information
• Unclear if used intent-to-treat sample
• Incomplete tests for baseline equivalence

Hindley, P., & Reed, H. (1999). Promoting alternative thinking strategies: Mental health promotion with deaf children in school. In S. Decker, S. Kirby, A. Greenwood, & D. Moore (Eds.), Taking children seriously ( pp. 113-130). London: Cassel Publications.

Study 19 (Ross, Sheard et al., 2011; Ross, Cheung et al., 2011)

• Cluster RCT but one of 13 schools dropped out right after assignment and comparison schools adopted the program before the posttest
• Teachers who delivered programs provided behavioral measures of children
• Little information on reliability and validity of measures
• Did not attempt to follow the oldest students after they left middle school
• Baseline controls not always used
• Some baseline differences between conditions
• No significant effects on independently measured behavioral outcomes

A preschool version of PATHS called Head Start REDI is treated as a separate program in Blueprints.

Peer Implementation Sites

Denine Goolsby Executive Director Humanware Cleveland Public Schools 1111 Superior Avenue Cleveland, OH 44114 PH: 216-838-0107

Flavia Hernandez, Principal McCormick Elementary School Chicago Public Schools 2712 S. Sawyer Avenue Chicago, IL 60623 PH: 773-535-7252

Carmen Navarro, Principal Mariano Azuela Elementary School Chicago Public Schools 3707 W. Marquette Road Chicago, IL 60629 PH: 773-535-7395

Caroline Boxmeyer, Associate Professor University of Alabama Hale County/Sawyerville Head Start Center 850th 5th Avenue East Box 870326 Tuscaloosa, Alabama PH: 205-348-1325

Averdijk, M., Zirk-Sadowski, J., Ribeaud, D., & Eisner, M. (2016). Long-term effects of two childhood psychosocial interventions on adolescent delinquency, substance use, and antisocial behavior: A cluster randomized controlled trial. Journal of Experimental Criminology, 12 , 21-47.

Certified Malti, T., Ribeaud, D., & Eisner, M. (2012). Effectiveness of a universal school-based social competence program: The role of child characteristics and economic factors. International Journal of Conflict and Violence, 6, 249-259.

Malti, T., Ribeaud, D., & Eisner, M. P. (2011). The effectiveness of two universal preventive interventions in reducing children's externalizing behavior: A cluster randomized controlled trial. Journal of Clinical Child & Adolescent Psychology, 40 (5), 677-692.

Bierman, K. L., Coie, J. D., Dodge, K. A., Greenberg, M. T., Lochman, J. E., McMahon, R. J., & Pinderhughes, E. (2010). The effects of a multiyear universal social-emotional learning program: The role of student and school characteristics.  Journal of Consulting and Clinical Psychology ,  78 (2), 156.

Social and Character Development Research Consortium (SCDRC) (2010).  Efficacy of schoolwide programs to promote social and character development and reduce problem behavior in elementary school children  (NCER 2011-2001). Washington, DC: National Center for Education Research, Institute of Education Sciences, U.S. Department of Education.

Berry, V., Axford, N., Blower, S., Taylor, R. S., Edwards, R. T., Tobin, K., . . . Bywater, T. (2016). The effectiveness and micro-costing analysis of a universal, school- based, social-emotional learning programme in the UK: A cluster-randomised controlled trial.  School Mental Health, 8, 238-256.

Schonfeld, D. J., Adams, R. E., Fredstrom, B. K., Weissberg, R. P., Gilman, R., Voyce, C., ... & Speese-Linehan, D. (2015). Cluster-randomized trial demonstrating impact on academic achievement of elementary social-emotional learning.  School Psychology Quarterly ,  30 (3), 406.

Fishbein, D. H., Domitrovich, C., Williams, J., Gitukui, S., Guthrie, C., Shapiro, D., & Greenberg, M. (2016). Short-term intervention effects of the PATHS curriculum in young low-income children: Capitalizing on plasticity.  Journal of Primary Prevention, 37 , 493-511.

Goossens, F., Gooren, E., Orobio de Castro, B., Overveld, K., Buijs, G., Monshouwer, K., … Paulussen, T. (2012). Implementation of PATHS through Dutch municipal health services: A quasi-experiment.  International Journal of Conflict and Violence, 6 , 234-248.

David, M. D. (2014).  The effect of Promoting Alternative THinking Strategies on social competence and reading achievement in elementary school children . Master's Thesis. Halifax, Nova Scotia: Mount Saint Vincent University.

Humphrey, N., Barlow, A., & Lendrum, A. (2018). Quality matters: Implementation moderates student outcomes in the PATHS curriculum.  Prevention Science, 19 , 197-208.

Humphrey, N., Barlow, A., Wigelsworth, M., Lendrum, A., Pert, K., Joyce, C., . . . Turner, A. (2016). A cluster randomized controlled trial of the Promoting Alternative Thinking Strategies (PATHS) curriculum.  Journal of School Psychology, 58 , 73-89.

Humphrey, N., Hennessey, A., Lendrum, A., Wigelsworth, M., Turner, A., Panayiotou, M., . . . Calam, R. (2018). The PATHS curriculum for promoting social and emotional well-being among children aged 7-9 years: A cluster RCT.  Public Health Research, 6 (10), 1-116.

Panayiotou, M., Humphrey, N., & Hennessey, A. (2020). Implementation matters: Using complier average causal effect estimation to determine the impact of the Promoting Alternative Thinking Strategies (PATHS) curriculum on children's quality of life.  Journal of Educational Psychology, 112 (2), 236-253.

Novak, M., Mihic, J., Bašic, J., & Nix, R. L. (2017). PATHS in Croatia: A school-based randomised-controlled trial of a social and emotional learning curriculum.  International Journal of Psychology, 52 (2), 87-95.

Hindley, P., & Reed, H. (1999). Promoting alternative thinking strategies: Mental health promotion with deaf children in school. In S. Decker, S. Kirby, A. Greenwood, & D. Moore (Eds.),  Taking children seriously ( pp. 113-130). London: Cassel Publications.

Ross, S. M., Cheung, A., Slavin, R., Sheard, M. K., & Elliott, L. (2011). Promoting primary pupils' social-emotional learning and pro-social behaviour: Longitudinal evaluation of the Together 4 All Programme in Northern Ireland.  Effective Education,  3, 61-81.

Ross, S. M., Sheard, M. K., Slavin, R., Elliott, L., Cheung, A., Hanley, P., & Tracey, L. (2011).  Evaluation of Together 4 All programme for schools . Institute for Effective Education, The University of York.

Greenberg et al. (1995) used a randomized control trial with two schools assigned to the intervention group ( n = 130 students) and two schools to the control group ( n = 156 students). A posttest after one year of the program measured children's self-reported emotional understanding and teacher-reported emotional problems.

Greenberg et al. (1995) found that, relative to the control group, the intervention group showed significantly greater improvements in

• Affective vocabulary
• Understanding of feelings in others
• Comprehension of complex feeling states.

Evaluation Methodology Design : Participants were selected in different ways for the regular and special needs subsamples. Regular education children were drawn from the second and third grades of four schools in the Seattle school district. These schools were representative of the district profile, with the exception of having a lower percentage of Asian-American students. The prevention model was initially described to principals and teachers at each school. After faculty discussion, building-based decisions were made regarding participation. Schools were aware that once they decided to participate, they had a 50% chance of being randomized as a control school. All four schools that were approached decided to participate and two were randomly assigned as intervention schools.

Classrooms for special need children were drawn from the Seattle, Highline, and Shoreline school districts. A presentation was made to interested special needs teachers. Each teacher was free to participate or decline, knowing that participation ensured only a 50% chance of receiving the intervention. Fourteen teachers elected to participate and were then randomized to either a treatment or control condition. Informed consent was received from approximately 70% of eligible students. Although the study assessed 426 students at the spring pre-test, 96 subjects were lost to follow-up due to school moves between spring of pre- and spring of post-test.

Of the 286 participating children, 130 received the intervention (83 regular education, 47 special education) and 156 were in control classrooms (109 regular education, 47 special education). Children were initially tested in either the spring or fall prior to the intervention year; most children were tested in the spring in order not to delay the onset of the intervention during the first few weeks of class. The children were then interviewed during the following spring, approximately one month post-intervention.

Sample : The final study sample included 286 children (167 males, 119 females) who attended school in the metropolitan Seattle area and were available for both pre- and post-testing. The children were attending first and second grade at pre-test, and second and third grade at the time of post-test. Ages ranged from 6 years, 5 months to 10 years, 6 months at pre-test, with a mean age of 8 years, 0 months. The mean age at post-test was 8 years, 10 months, with a range from 7 years, 0 months to 11 years, 2 months. The sample consisted of 165 Caucasians, 91 African Americans, 11 Asian Americans, 7 Filipino Americans, 7 Native Americans, and 1 Hispanic. Four children were of unknown ethnic origin. Sixty-seven percent of the children ( n = 192) were in a regular education program, and 33% ( n = 94) were in self-contained special education classrooms. Within the special education sample, children were classified in the following categories according to school records: learning disabilities ( n = 44), mild mental retardation ( n = 23), severe behavior disorders ( n = 22), or multihandicaps ( n = 5).

Measures : Each child was individually assessed using the Kusche Affective Interview Revised (KAI-R). This interview was developed as an expansion of previous interviews to assess children's emotional understanding at both an experiential and at a metacognitive level to probe a wide range of affective states and situations. Five domains of emotional understanding were assessed: ability to discuss one's own emotional experiences, cues used to recognize emotions, issues regarding the simultaneity of emotions, display rules for emotions, and whether and how emotions can change.

1. Students' feelings vocabularies were measured by summary counts of total positive and negative feelings stated at the start of the interview and by accurate definitions of five complex feelings (proud, guilty, jealous, nervous/anxious, and lonely). Definitions were coded on a trilevel scale analogous to that of the Wechsler Intelligence Scale for Children-Revised (WISC-R). Two questions were used to assess children's general knowledge of feelings. First, they were asked "Are feelings OK to have?" with follow up questions based on either an affirmative or negative response. Children's abilities to discuss personal emotional experiences were assessed by asking them to provide examples of times when they had felt ten specific emotions (happy, sad, mad, scared, love, proud, guilty, jealous, nervous/anxious, and lonely).

2. Children's ability to identify three specific emotional states in themselves and other people were assessed. They were asked "How do you know when you are feeling ____?" (happy, mad, or jealous), with a follow-up question asking how they know when others are feeling happy, mad or jealous. Responses were scored based on children's use of facial cues, situational cues, and internal feeling states.

3. For issues of simultaneity of emotions, three pairs of feelings were probed. Children were asked "Can someone feel _____ and _____ at the very same time?" (sad/mad, happy/sad, and love/anger). Children were asked to provide examples in support of their responses, which were scored based on the level at which the child was able to report simultaneous feelings directed toward the same target.

4. Assessment of whether and how emotions are hidden included children's understanding about their own ability to hide feelings as well as whether or not other's can hide feelings. In addition, children were asked if feelings should sometimes be hidden. Children were first asked: "Can you hide your feelings?" Percentages of this response were used as a measure of children's understanding of hiding feelings. Children who responded affirmatively were additionally asked how they could hide them, and this was coded using a developmental stage level system based on responses. Parallel questions were asked regarding others hiding feelings from the child, and similar response categories were used. Finally, children were asked: "Do you think there are times when people should hide their feelings?" which was coded using a simple yes or no format.

5. Children were also asked a series of questions to probe their understanding of whether and how emotions can change using yes/no questions. To assess the efficiency of problem-solving, the WISC-R subtests of Coding and Block Design were used.

In addition, the 112-item CBCL-TRF checklist was used to measure behavioral and emotional problems commonly seen by teachers. Responses yield eight narrow-band and two broad-band scores: Internalizing and Externalizing. Separate norms are utilized for boys and girls aged 6-11. To assess individualized changes in behavior, the Teacher Goal-Oriented Rating Form (TGOR) was utilized.

Analysis : A series of three-way repeated measures ANOVAs were conducted to assess the general effects of the intervention. The two between-subjects factors were Intervention Status (intervention vs. control) and Educational Placement (regular vs. special needs); the within subjects factor was Time. As the special needs population was a heterogeneous grouping that included different types of students, further exploratory analyses were conducted to examine potential differential effects of type of special education classification. Using the same analytic model as above, a series of three-way repeated measures ANOVAs were conducted with two between-subjects factors; intervention status (intervention or control) and educational placement (learning disability, behavior disorder, mild mental retardation, and multiple disabilities), the within subjects factor was time.

Post-test : Feelings vocabulary : Children who received the PATHS curriculum significantly increased the number of feeling words they could generate between pre- and post-tests as compared to children in the control group. Both intervention and control children demonstrated a significant developmental change in terms of the number of positive and negative feeling words listed from pre- to post-test. Treatment group children in regular education classrooms showed a significant increase in knowledge of the five complex emotions relative to regular education children in the comparison group. No intervention effect was found for special needs students. A significant main effect of time indicated a developmental advancement across the year for all students.

General questions about feelings : There were no significant effects of the intervention on children's level of reasoning regarding why (or why not) all feelings were OK.

Discussion of own emotional experiences : Children in the intervention group significantly improved their ability to provide appropriate personal examples of the five basic feelings, but not of the five complex feelings (happy, sad, mad, scared, love, proud, guilty, jealous, nervous/anxious, and lonely) from pre- to post-test as compared to children in the control group. A significant effect for time indicated a general developmental increase in children's ability to give more appropriate examples of complex feelings at post-test.

Cues to recognize emotions : No effects of the intervention were found on children's ability to describe cues used to recognize their own emotions. A main effect for time, however, indicated a general developmental advance in the level of children's reasoning about recognizing their own emotions between pre- and post-test. Children in the intervention group improved their level of reasoning with regard to knowing how others feel more than did children in the control group. In addition, a significant time effect indicated a general developmental advance in the level of children's reasoning about recognizing the feelings of others.

Understanding simultaneous feelings : There were no significant intervention effects. However, a significant time effect indicated developmental increases over the one year period.

Display rules for emotions : Children in the intervention group said "yes" significantly more often at post-test when asked if feelings could be hidden by themselves and by others when compared to children in the control group. No developmental change was noted for these responses. No intervention effects were found for children's level of reasoning about hiding their own feelings. Intervention children in special needs classrooms increased their level of understanding for other people's strategies for hiding feelings as compared to special needs children in the control group. A significant time effect indicated general developmental improvement in the level of reasoning about both themselves and others.

Changing feelings : Children in the intervention group were significantly more likely to respond positively to questions about changes in feeling states than were children in the control group. However, significant Time x Intervention Status x Educational Placement effects indicated that much of the Time x Intervention Status effect was the result of a large change in the special needs intervention group. Intervention children also showed a higher level of reasoning in their examples of how feelings can change when a picture cue was not provided compared to children in the control group. Special needs children in the intervention group improved significantly more than intervention children in regular education classrooms, as well as more than children in the control group.

Differential effects within special needs : There were fewer differential effects of intervention than would be expected by chance, indicating that improvements in special needs children were shown equally across the three identified groups.

Differential effects related to level of teacher-rated psychopathology : In order to examine the question of differential effects related to level of child behavior problems, two sets of analyses were conducted; one on the level of externalizing problems and the other on the level of internalizing problems. Among intervention students, those with low and moderate scores showed significant improvement for externalizing problems. Intervention children with high TRF scores showed the greatest relative improvement in the number of appropriate examples given for basic emotions, but comparison children with high TRG scores showed the greatest relative decline during the intervention period. Similarly, for both questions concerning efficacy regarding changing feelings, intervention children with moderate and high scores showed the greatest relative improvement, while control children with high TRF scores showed significant declines.

Intervention children with the lowest scores for internalizing problems demonstrated the greatest improvement on providing appropriate examples of advanced emotions, and comparison children with moderate and high TRF scores declined during the intervention period. These findings were repeated for both questions concerning efficacy regarding changing feelings. Similarly, intervention children with moderate or high TRF scores showed significant change in developmental level of understanding regarding how feelings change, and children in the control group with high internalizing scores showed declines during the same period. Regular education boys in the intervention group scored significantly higher on social competence scales as assessed by teacher, parent, and child ratings.

Riggs et al. (2006) used a randomized controlled trial with two schools assigned to the intervention group ( n = 153) and two schools to the control group ( n = 165). Assessments at posttest (nine months after baseline) and one year after posttest measured executive function and teacher-reported behavior problems.

Riggs et al. (2006) found that, relative to students in the control group, students in the intervention group showed significantly greater improvements in

• Teacher-reported externalizing and internalizing behavior.

Evaluation Methodology

Design : Four schools were randomly assigned to treatment or comparison conditions. The total recruited sample was 329 students enrolled in the second and third grade at the time of pretesting, and the final sample was 318 students. The sample sizes equaled 153 for the intervention group and 165 for the control group. A total of 68 classroom sessions were devoted to PATHS teaching.

Data were collected at pretest, nine months later (posttest), and one year follow-up.

Sample Characteristics . About 50% were girls, 55% were Caucasian, 33% were African American, and 22% were from other racial backgrounds.

Measures . Student surveys: 1) IQ was estimated using a two subtest short form of the WISC-R, which includes Vocabulary and Block Design; 2) Inhibitory Control was measured using the Stroop Test, which activates the anterior cingulated in adults, a neural region that interacts with both the limbic and prefrontal function; and 3) the Verbal Fluency subtest of the McCarthy Scales of Children's Abilities, which requires children to name as many items as they can in four common categories.

Teacher Surveys: Child behavior problems were assessed using the Teacher Report Form of the Child Behavior Checklist.

Analysis . First, hierarchical regression models were estimated to determine the effects of the PATHS Curriculum on teacher-reported behavior outcomes. Covariates for these models included pretest behavior scores, age, and IQ. Next, hierarchical regression models estimated the effects of the PATHS Curriculum on children's inhibitory control and verbal fluency 9 months later. Covariates included pretest neurocognitive scores, age, and IQ. Third, hierarchical linear models estimated the effects of both the intervention and the neurocognitive mediators on the behavioral outcomes, again including pretest covariates. The mediators in this third model should significantly influence the outcomes and attenuate the effect of the intervention found in the first model.

Missing data were replaced with sample means.

Implementation Fidelity . Treatment teachers attended a three-day training and received weekly consultation and observation from project staff. Fidelity assessments were conducted.

Baseline Equivalence and Attrition . Paired t-tests revealed group differences at pretest for Verbal Fluency and IQ, with the control group scoring higher. No analysis of differential attrition was reported, perhaps because missing data were replaced with sample means.

Posttest and Long-Term . The results based on both the posttest and one-year follow-up focused on each step of the mediation analysis.

(1) Regression analyses indicated that there was a significant prevention effect on both inhibitory control and verbal fluency.

(2) Posttest inhibitory control was negatively related to teacher-reported externalizing and internalizing behavior at 1-year follow-up. Posttest verbal fluency was negatively related to teacher ratings of internalizing behavior at 1-year follow-up. That is, children who had greater inhibitory control at posttest demonstrated fewer externalizing and internalizing behavior problems and children who were more verbally fluent demonstrated fewer internalizing behavior problems at 1-year follow-up. After taking these neurocognitive variables into account, the intervention condition continued to have a significant effect on externalizing behavior and internalizing behavior.

(3) Sobel tests for mediation demonstrated that inhibitory control at immediate posttest significantly mediated the relation between experimental condition and both teacher-reported externalizing and internalizing behavior at 1-year follow-up. These findings demonstrate that the direct effect of the PATHS program on inhibitory control significantly reduced the relation between PATHS and both outcomes. However, a Sobel test demonstrated that the mediating role of verbal fluency in the relation between the experimental condition and teacher-reported internalizing behavior only approached significance.

Kam et al. (2004) used a randomized controlled trial with 18 teachers of special education classes and 133 special need children assigned to intervention or control groups. Assessments in the spring over the next three years measured depression, problem behavior, and social competence.

Kam et al. (2004) found that, for a sample of special-needs students, the intervention group relative to the control group had significantly lower scores on

• Internalizing
• Externalizing behavior
• Self-control.

Design : This study examined the effects of the PATHS Curriculum on diverse outcomes at post-test, 1-year, 2-year, and 3-year follow-up. The sample consisted of 133 special needs children (in grades 1-3 at time of pretest) who had been previously assigned by their schools to special education classes. Eighteen teachers of special education classes elected to participate and were randomly assigned to either the intervention or control group. About 70% of the parents of children in the classes consented to testing. Children were initially tested in either the spring or fall prior to the intervention year; they were assessed again each spring for the next three years.

The rate of missing data varied by outcome, but large attrition generally occurred in the follow-up years. All participating children had baseline and posttest data, but from 6% to 48% were missing data on some measures for the follow-ups.

Sample : The sample included 52% White, 40% African American, and 8% children from other ethnic minority populations. All children had been previously assigned by their schools to special education classes. Of the 133 children, most had learning disabilities (53), but the sample also included children with mild mental retardation (23), physical disabilities (21), emotional and behavioral disorders (31), and multiple handicaps (5).

Measures : Measures are described in Study 1:

• Feelings Vocabulary
• Social Problem-Solving Skills
• Child Self-Report of Depression
• Teacher Ratings of Problem Behavior (Externalizing and Internalizing)
• Teacher Ratings of Social Competence

Analyses : Students' outcome trajectories were modeled across the early elementary grades using individual growth-curve analyses and multilevel models. Trajectories for students in the intervention group were compared to those for students in the control group. Sustained intervention effects were indicated as positive changes in trajectories above and beyond those observed in the control group.

In estimating outcome trajectories in the multilevel models, the analysis used all available data for subjects, even if not complete for all assessments. The analysis thus meets the intent-to-treat criterion.

Baseline Equivalence and Differential Attrition. At baseline, the intervention and control groups were equivalent on all outcomes except internalizing behaviors (where the intervention group had higher scores). The study made no mention of tests for differences across the groups on sociodemographic characteristics or types of disability.

The study did not report on differential attrition. It noted that the multilevel models used the maximum amount of information that, under the assumption of data missing at random, gives unbiased and efficient estimates. However, the study did not compare the rate of attrition across groups or the baseline values of those having missing data with those having complete data,

Posttest and Long-Term. Separate analyses were not done for posttest and follow-ups. Rather, the results examined linear changes in outcomes over the full period from baseline to 3-year follow-up.

Trajectories of teacher-rated behaviors : Teachers' ratings of students externalizing and internalizing behaviors can best be described as changing linearly from Time 1 (baseline) to Time 4 (3-year follow-up). A significant difference was found between the intervention and control groups in the estimated mean rate of growth in both types of behaviors, with teacher ratings of behaviors decreasing over time in the intervention group whereas those in the control group increased over time in both cases. No significant group differences were found for the trajectories of teacher-reported social competencies (frustration tolerance, assertive skills, task orientation, and peer sociability).

Trajectories of self-reported depression : A linear growth curve model fit the Child Depression Inventory (CDI) data relatively well. Depression scores reported by children in the intervention group declined at a significantly greater rate than did the scores reported by children in the control group.

Affective vocabulary : Linear trend models fit well with both positive and negative feelings vocabulary data. A significant difference between the two groups was found in the size of the negative feelings vocabulary at Time 4. There was no significant difference in the rates of change in the size of negative and positive feelings vocabulary.

Social problem-solving skills : No significant intervention group difference was found in the growth curve analyses of efficacy in social problem solving among children in the special needs classrooms. Children in the intervention displayed a marginally significant reduction in the percentage of aggressive solutions they generated and a significant increase in the percentage of solutions that were nonconfrontational and indicated self-control.

Greenberg and Kusche (1998) combined a randomized controlled trial and a quasi-experimental design. The study randomly assigned six Seattle-area schools with 79 severely and profoundly hearing-impaired children to an intervention group or a waitlisted control group. The one-year posttest compared the two conditions on measures of academic achievement and behavioral difficulties, but the long-term analysis occurred after some control schools had joined the program.

Greenberg and Kusche (1998) found that, for a sample of deaf children, the intervention group relative to the control group showed significantly greater improvements in

• Social problem-solving skills
• Emotional recognition skills
• Reading achievement
• Non-verbal planning skills
• Teacher and parent-rated social competence.

Design : The participants in this project consisted of 79 severely and profoundly hearing-impaired children who were enrolled in self-contained classrooms for deaf children (grades 1-6) in 6 local elementary schools in the Seattle area. The study design was quasi-experimental. Schools were randomly assigned to intervention vs. waitlist control group status. After the first year, the intervention was replicated on the wait-list control children. Teachers were trained in the intervention model and implemented PATHS lessons during most of one school year. The participants represented approximately 85% of all of the deaf children who were served in the area and who also met the following criteria: (1) basic education occurred using both sign language and speech (Total Communication), (2) unaided hearing loss was >60 decibels in the better ear averaged across the speech range, (3) deafness was diagnosed prior to 36 months of age, (4) non-verbal intelligence was greater than 75, and (5) no known significant additional handicaps were present. The intervention and comparison groups did not differ significantly on relevant pretest variables.

Sample : The children ranged in age from 67 to 146 months of age. The sample was primarily White (84%), and the average child had a profound unaided hearing loss.

Measures : Measures included an interview of social-problem solving, tests of non-verbal cognitive abilities, achievement testing, and teacher and parent ratings of behavioral difficulties and competencies.

Analysis : Mediational analyses were conducted to test the theoretical model that changes in understanding of emotions, ability to take others' perspectives, and social problem-solving skills were related to changes in behavioral outcome. For a detailed overview of the analyses used in all of the PATHS evaluations, please see the description above for the pilot study.

Post-test : Results indicated that the intervention led to significant improvement in students' social problem-solving skills, emotional recognition skills, and teacher and parent-rated social competence. Teacher ratings of behavior indicated that there were significant improvements in social competence and in frustration tolerance. Results also indicated significant improvement in reading achievement and non-verbal planning skills in the intervention sample. There was no effect in this normative sample on teacher or parent-rated psychopathology.

Mediational analyses : Results indicated that (a) improvement in emotional understanding was related to lower parent report of lowered externalizing problems at home; (b) improvement in role-taking skills was related to higher teacher ratings of emotional adjustment, and reductions in behavior problems at school and at home; and (c) improvement in problem-solving was related to higher teacher ratings of emotional adjustment and social competence and decreases in behavior problems at home and school.

Long-term : One- and two-year post-test results indicated maintenance of effects. Results with the wait-list control group indicated replication of effects in the second sample.

Kam et al. (2003) used a quasi-experimental matched-group design with three high-risk schools assigned to the intervention group ( n = 164 students) and three lower-risk schools assigned to the control group ( n = 186 students). The intervention combined PATHS with Big Brothers/Big Sisters. The study followed first-grade students from fall to spring, with teachers rating the students on social competence, aggression, and attentional control.

Kam et al. (2003) found that, in a study of PATHS combined with Big Brothers/Big Sisters, the intervention group relative to the control group showed significantly greater reductions in

• Behavioral dysregulation.

Design : This evaluation used a quasi-experimental matched-group design. Random assignment to intervention groups was not carried out because the local funding source required that schools in neighborhoods with the most high-risk profile receive the intervention. The sample in the overall intervention consisted of 350 first graders in six elementary schools in Harrisburg, Pennsylvania. Three of the schools received the intervention and three other schools served as comparison schools. A total of 13 classrooms with 164 students received the intervention. All of the participating schools served neighborhoods with very high rates of poverty and crime. Due to high family mobility and school reorganizations, student mobility averaged approximately 35-40% during the 1999 school year. A psychological consultation agency was contracted to coordinate the program implementation in targeted schools in the Harrisburg school district. Teachers received training from the program developers in two one-day workshops held approximately six weeks apart. Additional support for implementing the PATHS Curriculum was provided by an on-site PATHS Coordinator. The support included a weekly visit by the coordinator to PATHS classrooms and continuous consultation with the teachers, and logistics/materials support. The PATHS coordinator met with the school building principals on a monthly basis; principals were also strongly encouraged to attend workshop training. The PATHS Coordinator received, as needed, ongoing consultation from the program developers. The first year intervention is more brief than a "standard" implementation of the PATHS Curriculum. Because of the timing of funding, the curriculum was taught for only four months, from January to April, as compared to a full school year.

**While the PATHS Curriculum was the major component of the intervention (see above studies for a detailed description of the Curriculum), the Dauphin County project also had a second component of intervention provided by the Big Brothers and Big Sisters in the area. The latter provided mentoring to 14 students in the intervention schools who teachers identified to have special needs.

Sample : The sample was 47.14% male and 79.42% African American. Approximately 85% of the children in the schools sampled came from low-income families (as indexed by participation in the free lunch program). More than 65% of the students in the participating schools performed below the 30th national percentile in reading and mathematics.

Measures : Students behaviors at school were assessed by teachers at both the pre- and post-testing period using the 31-item Teacher Social Competence Rating Scale (TSCRS). Behaviors measured included: aggression, dysregulated behaviors, attentional control, and social-emotional competence. The quality of PATHS program implementation in classrooms was measured by observations made by the local PATHS Coordinator. Two aspects of classroom environment and implementation quality were rated: (1) How well are PATHS concepts and skills taught by the teacher? and (2) How well is the teacher generalizing PATHS skills across the school day? Principal support for PATHS implementation was measured by PATHS Coordinator and PATHS Supervisor ratings. Two measures of ratings were used: (1) quality of principal support for PATHS, and (2) quality of support for the PATHS technical assistance team (PATHS Coordinator and Supervisor).

Analysis : Analysis of covariance was used to analyze each outcome separately. A baseline measure of the outcome was entered in to the regression as well as the two dummy variables representing principal support. The classroom implementation measure was included as a continuous variable, as well as interaction terms between principal support and implementation. Planned comparisons were made on the predicted changes in classrooms that had a high and low degree of implementation, but had different levels of principal support. Due to a high rate of intercorrelation, observational ratings of PATHS program implementation were averaged over a four-month period.

Post-test : There was no significant main effect for implementation quality in predicting any of the four outcomes. Significant main effects were found, however, for principal support. In addition, significant interaction effects were found between the effects of principal support and implementation in the changes in all four domains (aggression, behavior dysregulation, social-emotional competence, and on-task behaviors). These results indicate that the effects of implementation work differently in schools with different degrees of principal support. When both the quality of implementation and principal support were high, students demonstrated significantly greater reductions in aggression and behavioral dysregulation, and significant increases in emotional competence when compared to students in the school with the lowest principal support. Similarly significant, but weaker differences on the same student outcomes were also shown when the school with the lowest principal support was compared to the average of the two schools with higher principal support.

Long-term : No long-term data was collected or analyzed in this evaluation.

Curtis and Norgate (2007) used a quasi-experimental design with five intervention schools ( n = 114 students) matched to three control schools ( n = 173 students) in the United Kingdom. The sample students, ages 5-7, were assessed at the end of one academic year on emotional symptoms, conduct problems, hyperactivity, peer problems, and consideration.

Curtis and Norgate (2007) found that the intervention group relative to the control group showed significantly greater improvements on

• Emotional symptoms
• Conduct problems
• Hyperactivity
• Peer problems.

Design : This quasi-experimental project (labeled by the investigators as a pilot project) implemented PATHS in five schools, with three control schools. Random assignment was not conducted, though groups were matched on age range and catchment area. At least two members of staff from each school attended two days of initial training provided by educational psychologists, and these staff then conducted the training in their own schools. Sample : PATHS was administered to the children in Key Stage 1 (the term for Year 1 and Year 2 in England and Wales, ages 5 to 7) in five treatment schools and three comparison schools. It is not noted how many students received the curriculum. Surveys were completed by 287 students (114 PATHS and 173 control), and a semi-structured interview was completed with 17 teachers in the PATHS schools. Measures : The Strengths and Difficulties Questionnaire (SDQ, Goodman, 1997) was administered to the 287 students, and a semi-structured interview was completed with 17 teachers. The SDQ is composed of five constructs: (1) Emotional symptoms; (2) Conduct problems; (3) Hyperactivity; (4) Peer problems; and (5) Consideration. Analyses : Student surveys: Independent t -tests were conducted to compare the pretest scores on the five constructs of the SDQ between the intervention and control group. Pretest scores were significantly different for the treatment and comparison groups. Mixed analyses of variance (ANOVAs) and paired t -tests were conducted to compare the mean scores before and after intervention for both groups on each of the five constructs. Analyses examining mediating variables were not conducted.

Teacher interviews: Interviews were recorded and transcribed, and then analyzed using a content analysis approach (Weber, 1990). Major categories were identified and changed until they were able to accommodate all of the data. The material from these categories was then organized into subcategories. Outcomes Posttest (School Surveys) : The ANOVA indicated that the change over time in mean scores was statistically significant, as was the interaction between the two conditions, in all of the dimensions within the SDQ (Emotional symptoms, Conduct problems, Hyperactivity, Peer problems, and consideration, all p values <.0001). The change in scores from pretest to posttest was significant for the intervention group but not for the comparison group. Teacher Interviews : Results indicated that in all schools using PATHS, a whole-school emphasis had been adopted, PATHS materials were displayed in hallways and classrooms, staff showed flexibility in the use of sessions, and all staff were knowledgeable about the program. Teachers particularly felt that the introduction of the "pupil of the day" had a positive impact on the students. Teachers also noted their own ideas to keep the curriculum fresh and interesting (e.g., role-play, social and self-reinforcement, story-telling, and modeling). All schools using PATHS worked to get parents involved so that the ideas and skills in PATHS were recognized and reinforced at home. Perceptions of how PATHS helped (despite that it was one of many programs being delivered across schools): Building a vocabulary of feelings, Developing the ability to describe own feelings, Recognizing emotions in others, Empathy, Developing self-control/managing emotions, Developing cooperation, and Dealing with problems. Finally, teachers felt that PATHS was a good fit for their schools. Criticisms included that teachers wanted more ideas on how to keep the curriculum "fresh and exciting," and practical ideas as the curriculum involved much sitting listening, and discussion, which was not appropriate for all children.

Malti et al. (2012) found that by the beginning of grade 5 (just over two years after program commencement), the intervention condition, relative to a control group, showed

• A reduction in ADHD symptoms.

Recruitment: The data for this study were obtained from the Zurich Project on the Social Development of Children (Z-Proso), an ongoing prospective longitudinal study of a cohort of children who entered elementary school in the city of Zurich, Switzerland, in 2004. The final sample consisted of 1,675 first graders from 56 elementary schools.

Assignment: Sampling was based on a cluster randomized approach involving all 90 public primary schools in Zurich. Schools were blocked by school size and socio-economic background of the catchment area, then a stratified sample of 56 schools (comprising 1,675 children) was drawn. All selected schools participated, and 14 "quadruplets" of similar size and socio-economic background were formed. Schools in each quadruplet were randomly allocated to four treatment conditions: PATHS (n = 442), Triple-P (n = 422), PATHS+Triple-P (n = 397), control (n = 414). The programs were delivered sequentially: Level 4 of Triple P was implemented between waves 1 and 2 (i.e., year 1 of primary school) whereas PATHS was implemented between waves 2 and 3 (i.e., year 2). Malti et al. (2011) used student-, parent- and teacher-reported data at annual intervals between 2004/2005 and 2006/2007 (T1-T3); Wave 4 (T4) was conducted 2 years later in 2008/2009, so either at the end of grade 4 (two years after program commencement) or at the beginning of grade 5. Malti et al. (2012) used teacher-reported results at Wave 4 (T4). It is unclear whether the data collection for Malti et al. (2011, 2012) was conducted at the beginning or the end of the particular academic year. Averdijk (2016) used data from the baseline assessment collected in 2004/2005 (wave 1, when students were 7 or 8) and follow up data collected in 2011 (wave 5, when students were 13 years old) and 2013 (wave 6, when students were 15 years of age).

The version of PATHS used in this study was the "Fast Track Project" version. This school-based 1-year program included 46 primary lessons addressing problem-solving skills, social relationships, self-regulation, rule understanding, emotion understanding, and positive self-esteem. The PATHS classes consumed about 67 min per week during the 1-year implementation phase with an average of 2.4 sessions per week. PATHS was implemented in year 2 (2005/2006) when students were in second grade. Trained teachers implemented the lessons, and five trained coaches were also available to visit each class four to six times during the implementation period to give teachers feedback. Implementation was monitored using teacher and child questionnaires developed by the program designers. Teachers were also observed by the coaches. Content, methods, and materials were culturally adapted to the Swiss school system.

Attrition: As reported in Malti et al. (2011), at T1 the response rates were 81% for the child interviews (n = 1,361), 74% for the parent interviews (n = 1,240), and 81% for the teacher assessments (n = 1,350). At T2 the respective response rates were 97%, 95%, 96%; at T3 96%, 95%, 94%, and at T4 83%, 86%, and 92%. (Note - as Malti et al., 2012, reported teacher outcomes at T4, the completion rate was therefore 92%). The computer-assisted, face-to-face interviews with parents were conducted at the parent's home. In the first three waves, computer-assisted child assessments were conducted at the school. In the fourth wave, classroom-based paper-and-pencil surveys were utilized. The child's teacher completed questionnaires on the child's social development and returned it by mail. The interviews were conducted by 44 trained interviewers. It is unclear whether interviewers were blind to group membership. The overall attrition rate reported in Averdijk (2016) for the control group was 27% in wave 5 and 30% in wave 6. For the PATHS group, overall attrition was 29% (wave 5) and 30% (wave 6).

Sample: At study commencement for wave 1, the sample consisted of first graders (mean age 7 years) with 48% girls and 52% boys. About 91% of the students were in regular classes, whereas the other 9% were in special-needs classes. About 78% lived with their biological parents, 20% with their biological mother only, and 2% with their biological father only or with foster parents. As for the socioeconomic background of the primary caregiver, 25% had little or no secondary education, 30% had vocational training, 29% had attended vocational school or had a baccalaureate degree or advanced vocational diploma, and 16% had a university degree. Socio-economic status was assessed through the International Socio-Economic Index of occupational status (ISEI) with an average score of 44.56 for households in the sample. In only half of the households (55%) at least one parent was of Swiss nationality, demonstrating the cultural diversity of the sample.

Measures: Primary outcome measures reported in Malti et al. (2011, 2012) include:

• Externalizing behavior : The teachers and parents evaluated the externalizing behavior of the children using Tremblay's Social Behavior Questionnaire (SBQ). Three subscales of the SBQ were employed measuring aggressive behavior (alpha = .72-.93), impulsivity/attention deficit hyperactive disorder (ADHD; alpha = .62-.91), and non-aggressive conduct disorders (NACD; alpha = .69-.78 for teacher's reports). For youth self-reports, the children were shown drawings of specific behaviors of a child and asked whether (s)he sometimes does what is shown in the pictures (answer options yes/no).
• Social competence : Social competence of children was measured using the Prosocial Behavior subscale of the Social Behavior Questionnaire (7-10 items, alpha = .59-.93). Children were presented with hypothetical scenarios and their responses were rated as aggressive strategies and socially competent strategies (interrater agreement .80-.87).

Averdijk et al. 2016 included 13 measures, five of which reported reliability statistics for the sample. These measures, eight from the youth and five from the teachers, included:

• Self-reported delinquency (15 items constructed into a "total variety scale" which the author reports has been termed the preferred criminal offending scale as they display high reliability and validity).
• Teacher-reported deviance (7 items constructed into a total variety scale).
• Self-reported police contacts related to an offense.
• Self-reported substance use (the sum of 4 items) and teacher-reported substance use (the sum of 3 items on smoking, drinking, and illegal drugs).
• Teacher- and self-reported aggressive behavior, as measured by the Social Behavior Questionnaire (SBQ). The reliabilities were α=0.84 (wave 5) and α=0.83 (wave 6) for the youths and α=0.93 (wave 5) and α=0.92 (wave 6) for the teachers.
• Self-reported peer aggression derived from Olweus (1993). The reliabilities were α=0.78 (wave 5) and α=0.75 (wave 6).
• Teacher- and self-reported prosocial behavior, as measured by the Social Behavior Questionnaire (SBQ). The reliabilities were α=0.82 (wave 5) and α=0.80 (wave 6) for the youths and α=0.93 (wave 5) and α=0.90 (wave 6) for the teachers.
• Self-reported conflict resolution, an eight-item scale adapted from Wetzels et al. (2001). Four items were used to create a measure for aggressive conflict resolution strategies (α=0.72 at wave 5, α=0.67 at wave 6) and 4 items comprised the competent conflict resolution strategies scale (α=0.71 at wave 5, α=0.71 at wave 6).
• Teacher-reported non-aggressive conduct disorder, as measured by the Social Behavior Questionnaire (SBQ). The reliabilities were α=0.83 (wave 5) and α=0.85 (wave 6).

Analysis: Malti et al. (2011) employed longitudinal multilevel models to account for the hierarchical data structure (time was nested within children and children were nested within schools). Treatment assignment, measured at the school-level, was coded as two dummy variables to compare the PATHS and Triple-P conditions separately with the control condition. This design allowed for specifying different timings of the interventions as well as the inclusion of an interaction term between PATHS and Triple-P conditions. The models implicitly accounted for baseline scores.

Malti et al. (2012) used hierarchical linear modeling (HLM Version 6.08) to assess the intervention effects at the fourth time point (when children were in fifth grade). Treatment was coded as a dummy variable to compare the PATHS and Triple-P conditions separately with the control condition. Thus, a standard approach to coding a 2 x 2 design (two levels of factor A crossed with two levels of factor B) was used to analyze program effects. The model incorporated three levels: data-collection wave (level 1), child (level 2), and school (level 3). These levels were employed in conjunction with a two-way interaction between time and intervention to measure the treatment effects.

Averdijk et al. (2016) conducted multilevel modeling with youths at level 1 and schools at level 2. Effects were estimated with the inclusion of several baseline sociodemographic covariates. Because the teen outcomes had little meaning at the age 7 pretest, the models used teacher and child measures of externalizing behavior as proxies for baseline outcomes.

Intention-to-treat : Malti et al. (2011, 2012) followed the intent-to-treat principle. For the Malti et al. (2011) analyses, multiple imputation was used to account for missing data for children and parents. However, because Little's MCAR test was not significant for the teacher's data, multiple imputation was not necessary (for both Malti et al., 2011, 2012). Averdijk et al. (2016) handled missing data with robust full-information maximum-likelihood (FIML). Two sets of analyses were performed. The first used the dataset with all available data points of the target sample (n = 1,580 of 1,675). The second used stricter inclusion criteria, including only participants who participated both at age 7 years and at either age 13 years or age 15 years (n = 1,275 of 1,675). Results below are reported for the first set of analyses.

Implementation fidelity: The five PATHS coaches visited each class four to six times during the implementation period, after which they discussed the lesson with the teacher. The checklists completed by the coaches indicated high implementation quality and quantity. On average, 27 of the 30 obligatory lessons, 30 of the recommended vignettes, and 25 small-group activities were completed in the classes. The quality of classroom leadership, child motivation, and teaching of PATHS concepts received marks of 88%, 82%, 74%, respectively.

Baseline Equivalence: Analyses reported by Malti et al. (2011) revealed no statistically significant baseline differences on any of the teacher, parent, or child outcome measures across treatment conditions. However, results for a baseline comparison of socio-demographic factors were not presented. Malti et al. (2012) appears to have reported the same figures as Malti et al. (2011). Averdijk et al. (2016) noted only that baseline measures of externalizing did not differ significantly across conditions.

Differential attrition: Malti et al. (2011) compared attrition rates by condition, reported the Little test, and used imputation when the Little test was significant. Malti et al. (2012) noted that the rates of attrition did not differ significantly across conditions for any of the four waves. Blueprints calculations also showed that, based on What Works Clearinghouse standards, the attrition rates did not indicate likely bias. Averdijk et al. (2016) reported similar rates of attrition by condition at wave 5 and wave 6, used FIML for missing data due to attrition, and conducted a sensitivity test to demonstrate that missing data did not change the findings.

Posttest and Long-Term :

As reported by Malti et al. (2011), the employed growth curve models do not allow for the separation between results for posttest and follow-up. As such, results were reported for time x group interactions.

Malti et al. (2011) reported a few program effects for children's externalizing behavior across time. For the intervention group, 2 of 3 tests were significant based on teachers report, 1 of 2 was significant based on parent reports, and none of 2 were significant based on child reports. Compared to a control group, the intervention group significantly reduced aggressive behavior across time. This result was observed for both teacher ( d =0.42) and parent reports ( d =0.26, p <.05) but not for child reported behavior. Since parents and teachers both delivered the intervention, these are considered non-independent measures. The intervention group also evidenced a significantly greater reduction in ADHD symptoms compared to the control group ( d =0.46), but only based on measures that included teacher reports across time points 1-3 from teachers who delivered the program combined with a fourth time point from teachers who did not deliver the program. Because teachers who deliver the program have a stake in good outcomes, Blueprints would need additional types of independent measures (such as data collected by researchers who are blind to study condition and/or student reports) to certify the ADHD outcome. Finally, no significant change was observed for nonaggressive externalizing behavior for the intervention group compared to the control group.

Malti et al. (2011) found evidence for the moderating role of baseline behavior on program effectiveness. Three of the four significant effects (three-way interactions) suggested that children with high levels of baseline problem behavior benefitted more from either or both interventions than children with low levels of baseline problem behavior.

In Malti et al. (2012), compared to the control group, children in the intervention group were reported by their teachers as having a greater decrease in aggressive problem behaviors (effect size = 0.42) and ADHD related problems (effect size = 0.46). These outcomes were reported when children were in fourth grade by teachers who were not involved in delivering the program (in grades K-3). As such, they are considered independent outcome measures. Meanwhile the results suggest that overall, children in the intervention group did not differ from children in the control condition on prosocial behavior.

Treatment effects reported in Malti et al. (2012) were moderated by level of moral emotions at baseline, where children who exhibited higher levels of moral emotions and received the intervention showed larger reductions in aggression at follow-up than children who initially had low levels of moral emotions. Other moderator variables that predicted higher aggression at follow-up included baseline aggression, financial problems, single parent household, and non-Swiss nationality. Finally, SES and female gender predicted lower aggression at follow-up. On the measure of ADHD, there was a significant teacher-reported decrease in ADHD-related problems among children who received PATHS, compared to the children in the control condition. However, these treatment effects were moderated by the level of moral emotions at baseline and by initial level of competent problem-solving strategies, where intervention students who exhibited higher levels of moral emotions and competent problem-solving strategies showed larger reductions in teacher-reported ADHD. Additionally, aggressive problem-solving strategies, baseline ADHD, family financial problems and single-parent household predicted higher ADHD at follow-up.

In the study conducted by Averdijk et al. (2016), only 1 of 13 tests at age 13 (seven years after program commencement) emerged as significant. Results showed a reduction in adolescent delinquency (i.e., fewer self-reported police contacts) for the intervention group (effect size =−0.225). In addition, there were no significant effects at age 15 (nine years after program commencement).

Seifert et al. (2004) used a quasi-experimental design with one elementary school in Rhode Island and two cohorts of children - one younger cohort receiving the one-year intervention in 2001 during first grade ( n = 62), and one older cohort not receiving the intervention ( n = 75). Both cohorts were assessed in second grade, but in different years, on depression, socio-emotional competence, and peer relationships.

Seifert et al. (2004) found that, relative to the control cohort, the intervention cohort showed significantly greater improvements on

• Global social competence
• Social-emotional competence.

Design . This QED examined one urban elementary school, a magnet school in inner-city Providence, Rhode Island. The design compared two cohorts of children - one younger cohort receiving the 1-year intervention in 2001 during first grade, the other older cohort not receiving the intervention. The intervention group was thus tested in 2002 in second grade, while the control group was tested in 2001 in second grade. Rather than randomization, the study assumed that the intervention second graders in 2002 were equivalent to control second graders in 2001 except for experiencing the intervention.

All available children from the three first-grade and three second-grade classrooms participated. The first cohort undergoing the 1-year intervention had 62 students. The second cohort or control group began with 75 students. However, a group of 13 students entered the school in 2002 and did not experience the intervention during the previous year. Although part of the intervention cohort and tested in second grade (2002), their results were combined with the control group to increase the control group n to 88. The list below contrasts the three cohorts:

• Cohort 1 (Treatment n=62): 2001 (first grade) PATHS; 2002 (second grade) assessment
• Cohort 2 (Control n=75): 2001 (second grade) assessment; 2002 (third grade) not participating
• Cohort 3 (Control n=13): 2001 (not attending); 2002 (second grade) assessment

No pretest assessments were conducted, and no information on attrition is available.

Sample Characteristics . The students were 68% Hispanic and 14% black. About 25% were interviewed in Spanish. Across the full school, 94% qualified for subsidized lunch programs; 31% received bilingual programs; and less than 40% met state standards for reading, mathematics, and writing.

Measures . Ten measures came from the students and interviewers.

Sociometric Status . Each child was asked to nominate classmates on 17 positive and negative descriptors. Using the first seven nominations of each student, the measures summed the number of times a student was nominated. Principal components analysis of 15 of the items produced scales for positive peer nominations such as "want to sit next to" (alpha = .82), and negative peer nominations such as "starts fights" (alpha = .85).

Emotion Understanding . The first measure taps spontaneous emotion naming skills or the number of emotions identified when asked to name all the different feelings they could think of. The second measure taps accuracy of emotion recognition or the score on matching pictures to emotions.

Social Status Self-Reports . The first measure taps perceived meanness of treatment by other children (e.g., kids say mean things to me), and the second taps perceived rejection (e.g., kids blame me when things go wrong). The alphas equaled .75 for perceived meanness and .76 for perceived rejection. A third measure taps negative feelings toward school ("I feel alone at school") and positive feelings toward school ("school is fun for me"). The eight items in the scale have an alpha of .63.

Child Depression Symptoms . The Childhood Depression Inventory measures the frequency of different depression symptoms and has been used reliably with children as young as first grade (alpha = .78 for this sample).

Global Competence Scale . After the 30-minute child interview, interviewers used the Psychological Impairment Rating Scale to assign a global rating of social competence (alpha = .93). Given the different timing of assessment for the intervention and control cohorts, the interviewers likely knew the assignment of the children they rated.

Social-Emotional Competence Composite . The composite combined standardized scores on the nine previously listed measures (alpha = .64).

Analysis. The analysis performed t-tests (without controls) on the posttest scores of the two groups.

Implementation Fidelity . All teachers participated in two training sessions. At the beginning and end of the school year, interviews with teachers revealed only modest enthusiasm for the program. Complaints about dissatisfaction with the PATHS materials, lack of support, and time and effort needed to implement the program suggest poor fidelity.

Baseline Equivalence and Differential Attrition . Lacking pretest assessment, the study could not examine baseline equivalence. No information was provided on whether all children who started in the intervention and control groups completed the posttest.

Posttest . Of the ten outcome measures, two showed significant differences between the intervention and control cohorts: the global social competence rating done by the interviewers and the social-emotional competence composite. The results did not differ between students interviewed in Spanish and students interviewed in English.

Long-Term . None

Bierman et al. (2010) used a cluster randomized controlled trial that assigned six schools to the intervention group and six schools to the control group. The sample of 2,937 students came from three cohorts and three different cities. A posttest assessment at the end of the three-year program included measures of social competence and peer relationships.

Bierman et al. (2010) found that the intervention group relative to the control group showed significantly greater reductions in

• Teacher-rated scores on authority acceptance, cognitive concentration, and social competence
• Peer ratings of aggression and hyperactivity but for boys only.

Design . The cluster randomized design studied schools and children over three years.

Schools . Participating schools came from Nashville, Seattle, and rural central Pennsylvania. Within each site, investigators invited about 12 elementary schools in high-risk areas (i.e., with high delinquency and juvenile arrests) to participate. Schools had to reach consensus among principals and teachers to participate. For those schools agreeing, three cohorts of students participated in the program, each beginning in first grade and participating for three years. The exact number of schools was not listed, but in each grade there were approximately 190 intervention classrooms and 180 comparison classrooms across the three cohorts. Note that schools in Durham, North Carolina, began the project but dropped out after the city and county schools merged and reassigned many children.

Students . Participating students in the classrooms needed to remain in the same school building from the beginning of grade 1 to the end of grade 3 and needed to have supplied information on the Social Health Profile and sociometric outcomes. These criteria produced a sample of 2,937 children across the three cities. However, this sample appears truncated. The study noted (p. 159) that "Children who were selected in kindergarten for additional intervention from the Fast Track project (and their high-risk control counterparts) were not included." The sample thus excluded (p. 166) "the worst behaving children."

Randomization . After being grouped on size, achievement levels, poverty, and ethnic/racial diversity, schools were randomly assigned to intervention and control groups. For the intervention group, this version of the program contained 57 lessons in grade 1, 46 in grade 2, and 48 in grade 3. The lessons were adapted to the needs of regular students in high-risk schools and lasted from September to May of each school year. The related version of the program for high-risk children, although not examined in this study, occurred simultaneously with the universal intervention.

Attrition . Limiting students to those who stayed in the same school over three years produced high attrition. In Nashville, only 30.9% of the original 1,560 children remained in the same school over three years. In Seattle, only 41.6% of the original sample of 1,825 children remained in the same school. In rural Pennsylvania, 75.0% of the 1,696 children remained in the same school. Further, the study may have violated the intent-to-treat principle by examining only students receiving the full intervention and failing to follow any student who did not remain in the same school over three years.

Assessment . Assessments occurred in the fall of the first year, and the spring of the first, second, and third year. The last assessment served as a posttest for the three-year program.

Sample Characteristics . The school characteristics differed across sites. The mean percentage of children receiving free or reduced lunch was 57% but ranged from 39% in rural Pennsylvania to 78% in Nashville. The mean percentage of ethnic minority students (primarily African American) was 36% but ranged from 1% in rural Pennsylvania to 55% in Nashville. The mean reading percentile was 45 th but ranged from 32 nd in Nashville to 57 th in rural Pennsylvania. The study did not report on the characteristics of the sampled students.

Measures . Outcomes came from teacher ratings and peer sociometric nominations.

Teacher Ratings. Teachers were interviewed regarding the behavior of each individual child in their class at the four assessment points (pretest, after year 1, after year 2, and posttest). The interviews used two instruments, the Teacher Observation of Classroom Adaptation - Revised (TOCA-R) and the Social Health Profile (SHR), and produced three measures:

• authority acceptance (alpha = .93) on oppositional and conduct problems from the TOCA-R,
• cognitive concentration (alpha = .97) on attention and work completion from the TOCA-R, and
• social competence (alpha = .87) from the SHR.

For all three measures, high scores indicated more problems.

Peer Nominations . Interviews with children asked them to nominate classroom peers who fit descriptions of aggressive, hyperactive-disruptive, and prosocial behaviors. Scores for each child came from the average ratings given by classmates.

Analysis. The investigators recoded some variables into ordered categories to reduce skewness (e.g., social competence) and truncated others to reduce the influence of large values (e.g., peer nominations). The analyses then estimated hierarchical models using three levels: time, child, and school. Time was centered so that the intervention main effect showed group differences at the end of the intervention. Time-by-intervention effects showed how the trend varied across groups.

The models controlled for baseline values of the teacher-rated measures but not for the peer nomination measures, which were not gathered at the start of the study.

Implementation Fidelity . More than 90% of the teachers attended a 2-day training workshop. Educational consultants spent an average of 1 to 1.5 hours in each classroom observing, demonstrating, and providing feedback. They also met individually with teachers.

On average, teachers completed 48.2 lessons in the first grade (85%), 39.6 in the second grade (86%), and 38.4 in the third grade (80%). Fidelity ratings from educational consultants ranged from 3.0 to 3.2 on a scale from 1 (low skilled performance) to 4 (highly skilled performance).

Baseline Equivalence and Differential Attrition . A series of analyses of variance indicated no significant differences between intervention and control schools on the percent of children who received free and reduced lunch, the percentage of ethnic minority children, or academic achievement scores. Tests for baseline equivalence did not compare the baseline characteristics of students in the intervention and control groups.

To assess differential attrition, analyses compared baseline scores for the sample students who remained in their school for all three years with other students who left the school between grades 1 and 3. The groups showed no significant differences on gender or pretest authority acceptance at any of the sites, but differed on other characteristics for at least one site. Dropouts were more likely to be African American, have lower pretest scores on social competence, and have lower pretest scores on cognitive concentration.

Since attrition was lower in rural Pennsylvania (25%) than in the other two sites (58% and 69%), the study replicated the models separately for the rural Pennsylvania sample. The results were similar, perhaps even stronger for the rural Pennsylvania sample. However, it's hard to know if the stronger results indicate the lack of bias from attrition or general differences in the Pennsylvania sample.

Posttest . For all three teacher-rated outcome measures, the intervention group had better scores at the posttest and improved more over the three years than the control group. The intervention main effects were positive and significant for authority acceptance (effect size = .24), cognitive concentration (effect size = .12), and social competence (effect size = .34). The time-by-intervention effects were statistically significant as well, indicating that intervention children experienced less of an increase over time in problems.

In addition, tests for moderation revealed weaker intervention benefits in low-income schools for authority acceptance and social competence. They also indicated that, for the outcome of authority acceptance, the intervention had stronger benefits for children with higher baseline problems.

For the peer nominations, the intervention failed overall to affect outcomes of aggressive, prosocial, and hyperactive ratings, but it reduced aggressive and hyperactive outcomes for boys.

The two articles came from the same project, but the Social and Character Development Research Consortium (SCDRC, 2010) examined only the first cohort of schools ( n = 10), while Crean & Johnson (2013) examined two cohorts of schools ( n = 14). Both studies evaluated PATHS when delivered starting in third grade rather than in kindergarten.

Crean and Johnson (2013) and the SCDRCC (2010) used a randomized controlled trial with 14 schools assigned to intervention or control groups. The study followed third grade students ( n = 779) for three years and included teacher-rated and child-reported measures of aggression, conduct problems, and delinquent behavior.

Crean & Johnson (2013) found that, relative to the control group, the intervention group showed significantly greater reductions in

• Teacher-reported conduct problems
• Student reported aggressive social problem solving, hostile attribution bias, and aggressive interpersonal negotiation strategies.

Recruitment : This study, one part of the Social and Character Development Research Program that evaluated six other programs, recruited 14 public elementary schools, 10 in the first cohort and four in a second cohort. The schools represented one school district in Minnesota (two schools) and two school districts in New York (12 schools). The sample came from third-grade students in the schools. Of the 1,024 eligible students, 607 (59%) had consent and completed the baseline assessment. In addition, the sample added new students entering the schools during the study period.

Assignment : The 14 schools were randomly assigned within districts to treatment ( n = 7) or control ( n = 7) conditions after matching pairs of schools on the basis of nine school characteristics. The control schools continued their standard practices, some of which included using other social and character development programs. After randomization, 63.9% ( n = 328) of the students in the intervention schools consented and 57.5% ( n = 294) of students in the control schools consented. Among the new students entering the schools, 49% consented in the intervention group and 39% consented in the control group.

Assessments/Attrition : Assessments came in fall of third grade (baseline), the spring of third grade (year 1), the fall, winter, and spring of fourth grade, (year 2), and the fall, winter, and spring of fifth grade (year 3). SCDRC (2010) noted that baseline data collection came on average six weeks after the program start. Of the initial sample of 607 students with consent and baseline data, 38% ( n = 231) left the schools or withdrew from the study. Helping to balance that loss, 172 (28%) new students with consent joined the study. Across all assessments and data sources (see Crean & Johnson, 2013, Table 2), the analysis sample sizes ranged from 429 to 630 students.

Sample Characteristics : Data from Crean & Johnson (2013) showed more female (57%) than male (43%) participants. About half of the students were white (51%), more than one-third were African-American (38%), and the remaining were classified as other (10%). Additionally, 17% of students identified themselves as Hispanic. About one third (33%) of students came from single parent households. The distribution of family income indicated a large proportion of families were poor (39% of families reported earning less than $20,000/year and 39% of families reported earning between $20,000 and $39,000 per year). By contrast, 21% of families reported earning over $70,000 per year. Most households had a family member who had graduated high school (19%), had some college (38%), or had obtained a college degree (33%).

Measures : Measures were collected from teachers and students, but teachers both rated the children and delivered the program. The timing and number of data points varied depending on the instrument and source of data.

Teacher-reported measures came from the Teacher-Child Rating Scales (TCRS) and the Behavior Assessment Scale for Children-2 (BASC-2). The three measures included aggression, conduct problems, and acting out behaviors. Internal consistency on these measures ranged from .72 to .94.

Child self-reports provided seven measures of aggression, delinquent behavior, victimization at school, normative beliefs about aggression, aggressive social problem solving, hostile attribution bias, and aggressive interpersonal negotiation strategies. Internal reliability on these measures ranged from .68 to .93.

The main analyses in Crean & Johnson (2013) used three-level growth models for time, students, and schools. The authors defined significance at p < .10, but the tables also listed significance at p < .05. Because curvilinear change appeared for most outcomes, the growth models included linear and quadratic terms (except for outcomes with only three time points). The multilevel models used random intercepts and slopes to adjust for clustering, and a time variable controlled for change from baseline. However, the sample size of 14 schools was likely not large enough to accurately estimate the standard errors, and the result may be to overstate the significance of the tests.

Intent to Treat : The analyses used all available data, with exclusions coming only from those moving schools, withdrawing, or not completing specific measures. In addition, sensitivity tests used multiple imputation for missing data on baseline covariates.

Implementation Fidelity :

Teachers reported teaching an average of 34.8 lessons per year. Observers rated teachers on 1) quality of teaching program concepts; 2) modeling and generalization of concepts throughout the school day; 3) quality of student compliance during lessons; and 4) openness to consultation. Reliability on these four measures was high (.87-.90). Six of the seven schools averaged greater than three (out of four) on quality of teaching concepts, modeling and generalization of concepts, and openness to consultation. Five of the seven schools also attained a three or better average on quality of student compliance during the program lessons.

Baseline Equivalence :

At the school level, a significant imbalance existed in the percent of students with limited English proficiency. At the student level, two-level mixed models found no significant condition differences in baseline demographics, but there was a statistical difference in parent-rated inter-generational closure at p < .05, and several marginal differences at p < .10. Overall, of the 69 measures collected, only seven showed significant or marginal baseline differences. In all instances, baseline differences favored the control group.

Differential Attrition :

Two-level binomial models including the aggression outcome variables (teacher and self-report), conduct disorder, acting out behavior problems, and minor delinquency were used to predict attrition as well as new enterer status. There was a higher level of attrition among students in the urban schools, but individual-level aggression measures predicted neither attrition nor entrance. Further, the authors stated that "none of the aggression by condition interaction terms were significant."

For the three teacher-reported measures, one (conduct problems) differed significantly across conditions in the linear and quadratic changes over time ( p < .05). Effect sizes listed in Table 3 show initial iatrogenic effects: The intervention group had more conduct problems than the control group in the first four follow-ups. However, the last assessment at the end of fifth grade, after three years of the program, indicated fewer conduct problems for the intervention group ( d = -.15).

For the seven child-reported measures, three risk and protective factors showed significant condition differences in the linear changes over time ( p < .05). Relative to the control group, the intervention group had lower aggressive problem solving ( d = -.27), hostile attribution bias ( d = -.27), and aggressive interpersonal negotiation strategies ( d = -.28).  

Sensitivity tests using baseline covariates and multiple imputation did not lead to substantive changes in the findings.

The SCDAC (2010) analysis of 10 schools found weaker effects. In 60 tests for mean differences between conditions across grades 3-5 (Table 6.18), there were no significant differences. Further, in 18 tests for growth rates across the three years, only one reached statistical significance. The intervention group did better on academic competence than the control group ( d = .08).

Long-Term :

Not examined.

This study was registered at www.controlled-trials.com: ISRCTN 32534848. It used the pre-school version of PATHS but included students in the early years of elementary school. Little et al. (2012) offered a shortened summary of the study, while Berry et al. (2016) presented more details.

Little et al. (2012) and Berry et al. (2016) used a randomized controlled trial with 64 schools in Birmingham, England, that were assigned to intervention or control groups. The 5,397 children in the schools were followed for two years. Teachers provided measures of strengths and difficulties.

Little et al. (2012) and Berry et al. (2016) found no significant effects on youth strengths and difficulties or on teacher and classroom behaviors.

All mainstream (i.e. not special schools) primary schools in Birmingham, England, were invited to take part in the study ( n = 299), and 64 schools expressed an initial commitment. Berry et al. (2016, p. 19) stated that "Eight schools dropped out shortly after randomisation and collected no baseline children level data." The study therefore reported on the remaining 56 schools. Participants were boys and girls in reception (i.e., pre-kindergarten) and year one (i.e., kindergarten) at the participating schools in the 2009/2010 academic year who went on to year one and year two, respectively, in 2010/2011. The 56 schools included 5,397 children ages 4-7 and 196 classes (Little et al., 2012, p. 265).

Assignment : The 64 schools were stratified by percentage of free school meals and size of school and then randomly allocated to an intervention or control group. However, as shown in the CONSORT diagram (Berry et al., 2016), the loss of six control schools versus two intervention schools before the baseline assessment may have compromised the randomization.

For the remaining 56 schools ( n = 5,397 students) used in the study, 29 intervention schools received two years of the pre-school version of PATHS. The 27 control schools continued as usual, which typically involved use of a nationally recommended social and emotional competence program called SEAL. In most cases, the intervention replaced the usual social and emotional competence program with PATHS.

Assessments/Attrition : Data were collected at three points: baseline ( n = 183 classes and 5,074 children), mid-intervention at one year ( n = 176 classes and 4,998 children), and posttest at two years ( n = 178 classes and 4,994 children). Among the 5,397 children in the 56 schools, completion rates were 93-94% for each of the assessments.

The students in the sample averaged five years of age and were 68% non-white. About 4-10% exceeded the clinical cutoffs for behavior problems, emotional problems, or total difficulties.

Teachers provided all child measures. The children were rated by two different teachers over the two post-baseline assessments, but each teacher delivered the program before rating the children.

The primary outcomes came from the teacher-completed Strengths and Difficulties Questionnaire (SDQ), which included four subscales, one impact scale, and one total scale. The study cited other studies that had demonstrated good internal consistency for the measures.

The secondary outcomes came from the PATHS Teacher Rating Survey and included 11 subscales.

One other set of nine measures came from trained independent observers, who were masked to condition. They rated teacher and classroom behavior using the Teacher-Pupil Observation Tool (T-POT). However, only 19 of the 56 schools (10 intervention, 9 control) had data, the baseline assessment for this measure came 1-2 months after the intervention began, and the only follow-up assessment came at six months after baseline.

Most analyses used three-level linear hierarchical or mixed models to account for clustering at the classroom and school levels as well as to control for covariates. For the 56 schools used in the study, data were analyzed both with and without missing data imputed, and the imputation used both multiple imputation and the last observation carried forward. The authors noted that all results were similar, with the imputed findings somewhat weaker.

Intent to Treat : Although data were analyzed with missing data imputed and all participants with baseline data were included, the eight randomized schools that failed to collect baseline data could not be included.

On average, teachers delivered 55% of the 47 lessons in the year 2 curriculum, and they reported that lessons were delivered as specified in the program materials. However, the fidelity ratings done by the coaches (expressed as a percentage of the total possible score) ranged from 21% to 100%, with a mean of 79%. Using an 80% threshold, about half could be said to have delivered the program with high fidelity.

There were no statistically significant differences between the intervention and control groups at baseline on seven demographic and behavioral measures (Berry et al., 2016, Table 2).

Although the text is unclear, it appears that the influence of attrition was assessed by comparing the complete-case results with missing data excluded to the imputed results with all data included. The similarity of the results suggested minimal bias from attrition.

At 12 months (mid-intervention) and 24 months (posttest), the primary measures of strengths and difficulties did not differ significantly across conditions. For the secondary measures of the PATHS teacher ratings of children, the intervention group did significantly better than the control group on six of 11 tests at mid-intervention. However, at the 24-month posttest, these effects had disappeared.

At six months, observer ratings of teacher and classroom behavior showed better scores for the intervention group than the control group on three of nine tests: total positive behaviors ( d = .304), class behavior negative to teacher ( d = .307), and class off-task behavior ( d = .227). However, these measures were available for only about one-third of the schools and the first year of the two-year study.

Moderation tests (Table 6) showed four significant subgroup differences in the program effects. Most consistently, the intervention group did significantly better than the control group for students with emotional difficulties.

Schonfeld et al. (2015) used a randomized controlled trial with 24 schools assigned to an intervention group ( n = 692 students) or control group ( n = 702 students). The students were followed from third grade (baseline) to sixth grade (posttest) and assessed with statewide achievement tests.

Schonfeld et al. (2015) found that, relative to the control group, the intervention group showed significantly higher

• Test score proficiency in reading, writing, and math.

Recruitment : All 24 schools in a large, high-risk, urban school district in the Northeast were included in the study.

Assignment : Schools in the study were divided into two clusters balanced for race/ethnicity, proportion of students qualifying for free or reduced price lunch, and school size. Using a block randomization procedure, the study then assigned one cluster to the treatment group and the other cluster to the control group. The 12 schools in the treatment group had 692 students, and the 12 schools in the control group had 702 students.

Attrition : The longitudinal study followed the same cohort of students from 3rd grade to 6th grade. Assessments occurred at the end of 4th, 5th, and 6th grade, with the 6th-grade assessment representing a posttest. The analysis included only students who remained in the same treatment group (although not necessarily the same school) for the entirety of the 4-year program. This excluded 49% of the originally assigned students.

Sample : The sample was approximately half male (51%) and more than half (68%) received free or reduced price lunches. Black students made up 48% of the sample; Latino students made up 41%; White students made up 9%; and other races made up the remaining 2%. Although the study reports no socioeconomic information, the school district is described as high-risk.

Measures : The State Mastery Test, a statewide achievement test administered annually in the spring in Grades 4 to 8, measured problem-solving skills for academic tasks separately for math, reading, and writing. The test showed good validity and reliability.

Analysis : The study used multilevel logistic regressions to account for student-level information nested within schools (but not within the clusters used for assignment). Variability of the student defines level 1 analysis and variability of schools defines level 2. Because testing began in 4th grade, after the program start, the study did not have baseline test scores.

Intent-to-Treat : The study included only students who participated in the full program period and therefore does not conform to intent-to-treat.

Implementation Fidelity : The study measured fidelity and the effect of exposure to the intervention on outcome scores. Teachers presented about two-thirds of the available lessons, and exposure to more lessons predicted achievement.

Baseline Equivalence : At baseline, there were no significant differences between conditions in sociodemographic measures. There were no differences between control and treatment schools for achievement test results the year before the beginning of the program, but those scores did not include program participants.

Differential Attrition : The study found no differences between completers and dropouts for four sociodemographic measures but could not test for differences by baseline outcomes and did not analyze attrition by condition.

Posttest : Fourth grade students in the treatment group had significantly higher odds of attaining basic proficiency in reading and math, but not writing. Students in the treatment group in 5th and 6th grades had higher odds of attaining basic proficiency in writing, but not reading or math. None of the control measures moderated these intervention effects.

Long-Term : The study did not conduct any long-term follow-up.

Fishbein et al. (2016) found that, relative to the control group, the intervention group showed significantly greater improvements in

• Researcher-rated outcomes of inhibition task accuracy and impulsivity
• Teacher-rated outcomes of aggression, internalizing, social competence, emotion regulation, prosocial behavior, impulsivity, inattention, closeness and conflict with teacher, peer relationship problems, and academic skills.

Recruitment: Four public elementary schools from highly disadvantaged Baltimore City neighborhoods with poor school readiness participated in the evaluation. Consent was sought from all children in the schools' kindergarten classrooms. Of 464 eligible children, 327 provided consent and entered the trial, though children not receiving consent still received the intervention.

Assignment: Schools were randomly assigned to treatment (n=2) or control conditions (n=2). The preschool/kindergarten version of the PATHS curriculum was used as the primary intervention, which was taught by all kindergarten teachers in treatment schools, while kindergarten teachers in control schools provided instruction as usual. Since the treatment was administered grade-wise within school, randomization could not occur by classroom.

Assessment: Students were assessed using teacher-rated measures of behavior (e.g., attention, concentration, aggression) and peer-reported nominations (e.g., likability, aggression, acceptance) at baseline and posttest, in the spring of the academic year. Attrition was not described for the baseline sample.

The majority of students at participating schools were eligible for free lunches and nearly all students were African American. Household income in the areas served by the schools averaged about $40,000 a year, and areas had moderately high crime rates (~70/1000 residents).

All instruments were administered at the beginning of the fall semester and end of the spring semester, after the program had concluded.

Kindergarten teachers completed a series of measures (listed below) assessing child competencies.

• Aggression was assessed with seven modified items from the Teacher Observation of Child Adaptation-Revised. Despite the modifications, no psychometric properties were described.
• Internalizing was measured using five items from the Teacher Observation of Child Adaptation-Revised. Reliability was not reported for the subscale.
• Social Competence was defined using 13 items from the Social Competence Scale. No measures of validity or reliability were reported.
• Emotion Regulation was assessed with six items regarding the selected student's coping mechanisms and temper control ( a =.88).
• Prosocial Behavior was examined with a subscale of seven items that displayed good reliability ( a =.96).
• Child Impulsivity and Inattention were measured using the Diagnostic and Statistical Manual's ADHD Rating Scale ( a= .92-.94).
• Student-Teacher Closeness and Conflict were assessed with eight items from the Student-Teacher Relationship Scale ( a =.92).
• Positive Peer Relationships were assessed with the Peer Relations Questionnaire ( a =.79).
• Academic Skill was measured with four items drawn from the Academic Competence Evaluation Scales. Psychometric properties for the instrument were not reported.

Though not explicitly stated, it appears that child cognitive functioning outcomes (listed below) were administered by the research team. It was not clear whether these researchers were blind to condition.

• Delayed Gratification was assessed across four dimensions using the Delay of Gratification tasks. Reliability was not reported for the measure.
• Behavioral Inhibition was tested using the computerized Whack-A-Mole game, which yielded four total measures. No psychometric properties were described.
• General Intelligence was measured using the KBIT-2 composite measure, which demonstrated high reliability ( a =.89-.96).
• Emotional Intelligence was assessed using "FACES task" at posttest, only. The validity of the measure was not described.
• Motor-Skills Impulsivity was tested with the Peg-Tapping Task. No measures of validity or reliability were reported.

Multilevel growth models were used to evaluate the intervention, with two observations nested in each student. The models control for student gender and inherently adjust for baseline outcomes. A secondary analysis applied similar methods to a propensity score matched subsample (114 of 327 cases) to adjust for baseline differences in baseline differences in several behavioral outcomes. There was no adjustment for clustering in classrooms, which were the unit of delivery, or schools (the unit of randomization) beyond the condition difference.

Intent-to-Treat: Subject attrition was not discussed.

Implementation Fidelity: The teachers delivering the intervention all completed at least 80% of the lessons affiliated with the treatment. However, observation-based fidelity ratings made by the program coordinator suggested some deviation from content, with an average score of 3.8 (76%) across all classrooms on a 5-point scale.

Baseline Equivalence: The groups were not equivalent at baseline, with "preliminary analyses reveal[ing] significant baseline differences across treatment condition for multiple behavioral outcomes," (pp.503) and several apparent differences in school and neighborhood characteristics in Table 1 with no significance tests (pp.497); See, for example, household income (control mean=$31,053 vs. treatment mean=$50,592) and overall crime rates (control=73.69 per 1000 vs. treatment=45.17).

Differential Attrition: There was no discussion of student attrition, though all schools were retained.

Posttest: At posttest, the treatment group showed improvement on 13 of 13 teacher-rated outcomes compared to controls. Gains were observed for aggression, internalizing, social competence, emotion regulation, prosocial behavior, impulsivity, inattention, teacher-child closeness and conflict, peer relationship problems and academic skills, as rated by the teachers who delivered the intervention. All but two of these impacts (academic skills and teacher-student closeness) were maintained in the propensity score-matched subsample.

In the overall sample, treatment students significantly improved 2 of 10 direct cognitive functioning outcomes over the control group, including inhibition task accuracy and motor-skills impulsivity performance. However, these gains were not evident in the matched subsample.

The version of PATHS used in this study was implemented by health-promotion professionals and consisted of 161 lessons spread over the eight years of elementary school. It updated a Dutch translation of the U.S. curriculum that had been used for several years in the Netherlands. In this two-year effectiveness study, all children in the program received about 40 PATHS lessons over two years, but children in the higher grades, who did not start the lessons from kindergarten, received extra lessons.

Goossens et al. (2012) used a quasi-experimental design that non-randomly assigned 18 Dutch schools and 1,331 students in kindergarten and grade 1 to intervention and comparison groups ( n = 9 schools each) and followed the students over two-years. Teacher-rated and child-reported measures included problem behaviors, depression, and emotional regulation.

Goossens et al. (2012) found only one significant effect in 27 tests. The intervention group compared to the comparison group showed significantly higher

• Emotional awareness.

Recruitment : Of 30 Dutch Municipal Health Services approached, three agreed to participate in the study. Health promotion professionals at each location then recruited all elementary schools in their region. The 18 schools that joined were located in rural areas and provincial towns in the Netherlands. In total, 1,331 children (ages 5-11) from four cohorts - kindergarten and grades 1, 3, and 5 - were eligible for the study.

Assignment : The quasi-experimental design began with randomizing the 18 elementary schools to an intervention condition or a waitlist comparison condition. However, four schools deviated from the randomization. The authors allowed two to start two years later for organizational reasons and agreed to demands of two to start the program directly. The intervention group included nine schools with 695 eligible students, and the comparison group included nine schools with 636 eligible students.

Assessments/Attrition : Assessments occurred over the two years of program implementation: baseline (T0), end of the first year (T1), start of the second year (T2), and end of the second year (T3). Due to missing data, moving to other schools, and parent refusal, 1,294 (97% of those eligible) students completed the baseline assessment. By the last assessment at the end of two years, 1,223 students provided data (92% of the randomized sample, 95% of the baseline sample). Attrition came from moving to other schools or from repeating and skipping grades.

Nearly all students in the sample came from a Dutch background (92-99% across the cohorts and conditions). The distribution by gender was close to even (44-57% male), and the students varied in mean age from 5.4 years to 10.6 years across the four cohorts.

Teachers who delivered the program also rated their students. Child questionnaires were completed in face-to-face interviews with the three youngest cohorts and by self-report with the oldest cohort. Trained graduate psychology students who did not know of the school assignment conducted the child assessments. The study used 27 outcome measures in total.

Problem Behaviors . Six teacher-rated scales from the Problem Behavior at School Interview measured four externalizing problems (attention deficit and hyperactivity, oppositional defiant disorder, conduct problems, and relational aggression), and two internalizing problems (anxiety and depression). Cronbach's alphas varied between .78 and .92.

Social Experiences . Three teacher-rated scales measured relational victimization, physical victimization, and prosocial behavior. Cronbach's alphas were .87 (relational victimization), .85 (physical victimization), and .75 (prosocial behavior).

Depression . Five child self-report scales, obtained only for the oldest (grade 5) cohort, came from the Dimensions of Depression Profile for Children instrument. The measures included one total score (alpha = .85) and four subscales: depressed mood (alpha = .69), self-blame (alpha = .59), low energy/interest (alpha = .75), and low global self-worth (alpha = .77).

Peer Nominations . One measure of peer social preference was obtained using peer nominations of the most liked and least liked.  

Social Behavior . Three teacher-rated scales obtained for the youngest two cohorts (kindergarten and grade 1) came from the Preschool and Kindergarten Behavior Scale. The three subscales included social cooperation (following instructions, getting along with peers), social interaction (gaining and keeping friendships), and social independence. The internal consistency of the subscales ranged from .86 to .89.

Social and Emotional Skills . A single teacher-rated measure obtained for the two youngest cohorts (kindergarten and grade 1) came from the Head Start Competence Scale. It measured children's social and emotional skills in interpersonal relationships and emotion regulation (alpha = .95).

Emotional Awareness . A single teacher-rated measure came from the Levels of Emotional Awareness Scale for Children, which assessed the complexity of children's emotional awareness. Cronbach's alpha ranged from .89 to .92 over the assessments.

Emotional Regulation . Six child-rated scales obtained for the oldest cohort (grade 5) came from the Difficulties in Emotion Regulation Scale and measured non-acceptance of emotional responses (alpha = .73), difficulties engaging in goal-directed behavior (alpha = .82), impulse control difficulties (alpha = .80), lack of emotional awareness (alpha = .78), limited access to emotion regulation strategies (alpha = .74), and lack of emotional clarity (alpha = .61).

Empathy . One-child-rated measure from Bryant's Empathy Index was used for the youngest and oldest cohorts only. Cronbach's alpha was .68.

Multilevel mixed models nested the four measurement waves within students, the students within classes, and classes within schools. Although the mixed models adjusted for clustering within schools, the unit of assignment, the sample size of 18 clusters was likely not large enough to accurately estimate the standard errors and may result in the overestimation of program effects. The authors stated that they calculated "three change scores (T0 - T1, T1 - T2, and T2 - T3) for each variable." To test for the program effect over the full period, these three change scores were then included in the mixed models for each outcome. Missing data were handled through Full Information Maximum Likelihood estimation (FIML). Because of multiple testing (27 outcomes), the level of statistical significance was set at p < .01 in all tests.

Intent-to-Treat: The FIML estimation used all participants with baseline data. Also, the authors minimized follow-up attrition by attempting to collect data via mail from children who moved schools or who repeated or skipped a grade.

Mean completeness, which measured teacher reports of coverage of the lessons, was only 50% in the first year and 49% in the second year. A measure of "conceptual use" of the program principles ranged from 1-4. The mean was around 3.05 in the first year and 3.07 in the second year.

Age, gender, ethnicity, and verbal ability did not differ significantly between the intervention and comparison groups at baseline. However, significant baseline differences ( p < .05) were present for the level of attention deficit and hyperactivity, oppositional defiant disorder, conduct problems, relational aggression, anxiety, relational victimization, physical victimization, prosocial behavior, low energy, social interaction, social independence, and social and emotional skills. Problem behaviors tended to be higher and social and emotional skills tended to be lower in the intervention condition.

Attrition was low, only 5% of the baseline sample.

In 27 tests, the intervention group did significantly ( p < .01) better than the comparison group only for emotional awareness. Additional moderation tests showed, with few exceptions, no differences in program effects between subgroups. The authors attributed the sparse effects to poor program implementation.

David (2014) non-randomly assigned three Canadian schools and 98 students to an intervention and comparison group and followed the students over 14 months. The measures include reading achievement and social competence.

David (2014) found no significant program effects on measures of social competence or reading achievement.

Recruitment : The study examined 98 students in three elementary schools, all part of the same school board in Eastern Canada. The students were enrolled in grades primary, one, and two and were required to have parental consent, but the study did not report consent rates.

Assignment : The school board administration determined assignment of schools. Two schools received the intervention ( n = 57 students), and one school served as a waitlist comparison ( n = 41 students). The single comparison school confounded the no treatment with any unique characteristics of the school.

Assessments/Attrition : Assessments occurred at baseline and after 14 months. Nearly all students with baseline data had posttest reading data (98%). However, only 79% of data from teachers was complete (N = 77).

The study lacked socio-demographic information on the students. It reported only that the genders were evenly split and that grade 2 had more students than the other grades.

The two measures of reading achievement came from the Woodcock-Johnson III: Tests of Achievement Letter-Word Identification and the Woodcock-Johnson III: Tests of Achievement Word Attack. Trained research assistants conducted the student assessments, but the study did not say if they were aware of condition assignment. Three measures of social competence came from the teacher-rated PATHS Student Evaluation Questionnaire and included 1) aggressive/disruptive behaviors, 2) attention and concentration, and 3) social and emotional competence. The social competence alpha values were low, ranging from .51 to .73, and came from teachers who delivered the program.

The analyses used repeated-measures ANOVA models that controlled for the baseline outcome but no other covariates. It did not appear that the models accounted for the assignment of schools with adjustments for clustering.

Intent-to-Treat: The analyses used all available data.

The study noted the reluctance of some teachers to implement the program but provided no quantitative measures of implementation fidelity.

Tests found no significant baseline differences in age, aggression, attention, social-emotional competence, letter-word identification, or word attack.

No tests presented.

The study found no effects of condition on any of the three social competence outcomes or the two reading outcomes.

This evaluation examined the impact of a two-year program that teachers delivered twice-weekly in 30-40 minute lessons on two different groups of students - years 3-5 and years 5-6.

The Manchester study (Barlow et al., 2015; Hennessey & Humphrey, 2020; Humphrey et al., 2016; Humphrey, Barlow, & Lendrum, 2018; Humphrey, Hennessey et al., 2018) was a cluster randomized controlled trial with a sample of 45 schools and 5,218 students in years 3-5 and 3,336 students in years 5-6. Measures of socio-emotional competence, mental health, and academic performance came at posttest (after two years of the program) and at 12- and 24-month follow-ups. An additional QED analysis (Panayiotou et al., 2020) examined program effects for students receiving most of the program lessons relative to those who did not.

Barlow et al. (2015), Hennessey & Humphrey (2020), Humphrey et al. (2016), Humphrey, Barlow, & Lendrum et al. (2018), Humphrey, Hennessey et al. (2018), and Panayiotou et al. (2020) found only two significant program benefits in numerous tests for measures of socio-emotional competence, mental health, and English and math achievement tests. The intervention group relative to the control group had significantly higher

• Teacher ratings of socio-emotional competence
• Child self-reported psychological well-being.

Recruitment : Mainstream primary schools in the 10 Local Authorities that make up the Greater Manchester region were eligible to participate. Children in years 3, 4, and 5 (ages 7-9) on the school's full-time roll at the start of the 2012-13 academic year defined the initial target population for the study (another sample of children in years 5 and 6 is described below). From a pool of 58 schools, 45 met the eligibility criteria. *Although the reported figures differed across studies, only 133 or 140 (2.5-2.6%) of 5,218 students did not receive parental consent to participate. The schools were generally representative of schools in England, although they had higher proportions of children eligible for free school meals and speaking English as an additional language than national averages (Hennessey & Humphrey, 2019, Tables 1-2).

Assignment : An independent team randomly allocated the 45 schools to an intervention group ( n = 23) or control group ( n = 22). The studies did not report the number of randomized students in each condition, only the total of 5,218. The randomization used a minimization algorithm to ensure balance in eligibility for free school meals and speaking English as an additional language. From 2012/13 to 2013/14, the intervention group received the program curriculum during health education classes, while the control group continued usual teaching practices.

Assessments/Attrition : The baseline assessment took place in May-July 2012. Humphrey et al. (2016, Figure 1) reported that 4,516 children (89%) and 4,498 teachers (89%) provided baseline data. The posttest took place in May-July 2014, after two years of the program, with 3,505 children (69%) and 3,317 teachers (65%) providing data. Humphrey, Hennessey et al. (2018) reported somewhat different figures: 4,400 children (84%) had baseline data and 3,888 children (75%) had posttest data. The higher posttest figure came from the addition of new students to the sample.

For the assessments at 12 and 24 months, Humphrey, Hennessey et al. (2018) examined a subsample of students who had transferred to secondary school following the posttest ( n = 1,631). Attrition for this group was high: At 24 months, teacher and child measures were available for only 28% ( n = 463) of the subgroup.

For the baseline sample of students ages 7-9, about 30% were eligible for free school meals and about 22% spoke English as an additional language. About 70% were white, 12% Asian, and 8% black. The gender distribution was about equal.

The study obtained teacher reports and child self-report surveys. Teachers who rated the children at posttest - but not at follow-up - also delivered the program.

Child-rated social-emotional competence or social skills was assessed using the 46-item social skills domain of the self-report version of the Social Skills Improvement System. The instrument contained seven subscales and a total scale. Alphas ranged from .67 (Assertion and Responsibility, baseline) to .83 (Self-Control, follow-up).

Teacher-rated mental health difficulties was assessed using the 25-item Strength and Difficulties Questionnaire. The instrument contained five subscales and a total scale. Alphas ranged from .68 (Peer Problems, baseline) to .90 (Hyperactivity/Inattention, baseline) in Humphrey et al. (2016) and from .79-.89 for subscales of internalizing, externalizing, and prosocial behavior in Humphrey, Hennessey et al. (2018).

Teacher-rated changes in children's social-emotional competence was assessed at posttest using the five-item Social and Emotional Competence Change Index, which was derived from the PATHS program evaluation tools. The alpha for the single scale was .93.

Child-reported psychological well-being was assessed using the Kidscreen-27. It contained subscales on psychological well-being (alpha = .77), peer and social support (alpha = .78), and school environment (alpha = .71).

Child school measures in Humphrey, Hennessey et al. (2018) came from the National Pupil Database and included school exclusions and attendance for all students and reading/writing and math attainment for the transition sample of students moving to secondary school.

Several analyses used three-level hierarchical linear modeling for school, child, and time. Controls included school- and child-level eligibility for free school meals and speaking English as an additional language, child sex, school use of other SEL practices, and child baseline risk status. Tests for program effects used condition-by-time interaction terms that included baseline scores. Other analyses used two-level hierarchical modeling for school and child with covariates for the baseline outcome and other baseline measures.

In a QED analysis, Panayiotou et al. (2020) used complier average causal effect estimation with randomization as an instrumental variable to compare those receiving high program dosage with others rather than to compare all intervention participants with all control participants.

Intent-to-Treat: The studies used FIML estimation or multiple imputation for all available data, including participants without complete data. The non-ITT complier analysis of Panayiotou et al. (2020) was an exception.

On a scale of 1 to 10, measures were generally high for fidelity (8.20), quality (8.48), participant responsiveness (7.34) and reach (9.08). However, classes on average fell 20 lessons behind schedule. Analyses showed that higher levels of implementation quality and reach were associated with better academic outcomes but not better psychological outcomes. Humphrey, Hennessey et al. (2018) noted that despite its very modest impact, the program offered value given its low cost.

In a detailed study of the intervention group only, Humphrey, Barlow, & Lendrum (2018) found that implementation quality and participant responsiveness was associated with significantly lower ratings of students' externalizing problems. However, higher dosage was associated with lower prosocial behavior and social competence, and procedural fidelity had no association with student outcomes.

Humphrey et al. (2016) reported that "Assessment of balance on key observables between the trial groups at baseline revealed negligible differences - with only the Pro-Social Behavior subscale of the SDQ exhibiting a difference of greater than d = 0.1 (see Table 1). After accounting for data clustering and multiple comparisons, there were no statistically significant differences between the two trial groups at baseline on any outcome measure."  Humphrey, Hennessey et al. (2018) similarly found that standardized mean differences across conditions were no more than .16 for baseline sociodemographic and outcome measures.

Humphrey et al. (2016) presented no tests for differential attrition, but retention differed substantially across conditions. Of those with baseline data, 86% of the intervention students and 69% of the control students had posttest data. Humphrey, Hennessey et al. (2018) noted that all intervention schools completed the posttest, but five of 22 control schools failed to complete the posttest. For students, they reported that 97% of the intervention group had posttest data compared to 79% of the control group.

Humphrey et al. (2016) found that the intervention teachers reported significantly greater changes in socio-emotional competence than the control teachers ( d = .47). For teacher-reported mental health outcomes, the six tests found two significant group-by-time coefficients, but both favored the control group rather than the intervention group. For child-reported socio-emotional competence, the eight tests found no significant effects. Subgroup analyses of those at high baseline risk demonstrated mixed effects, with some favoring the intervention group and some favoring the control group.

Humphrey, Hennessey et al. (2018) examined 11 posttest outcomes in Tables 7A-7C, with only one significant effect. The intervention group self-reported better psychological well-being than the control group ( d = .15)

At the 12 and 24-month follow-ups of the transition sample of students who had moved to secondary school, Humphrey, Hennessey et al. (2018, Tables 9 and 11) found no significant effects in 10 tests. Additional mediation tests using structural equation models (Figure 4) did not include condition as a predictor.

Academic Performance among Year 5 and Year 6 Students (Barlow et al., 2015; Hennessey & Humphrey, 2019)

Although part of the same study and project, these two articles examined older students. Using the same randomized schools (23 intervention, 22 control), the sample consisted of 1,705 year 5 students and 1,631 year 6 students. The posttest assessment came in the summer term of 2014, at the end of the two-year program. For year 5 students, 37 schools (82%) and 1,117 students (66%) had data. For year 6 students, 45 schools (100%) and 1,582 students (97%) had data.

The outcomes measured reading and math attainment. For the year 5 cohort, posttest measures came from the Interactive Computerised Assessment System. The measures had reliabilities exceeding .92 and predicted future external assessment scores ( r = .72). Assessments were administered by members of the research team, but an independent organization unaware of school or individual assignment graded the tests. For the year 6 cohort, both the pretest and posttest measures came from the Standardised Assessment Test English and Mathematics available from the National Pupil Database. Administration and scoring were done independently. Studies had shown that the test had strong internal consistency (alpha > .91) and classification accuracy (> 85%). Note that these test scores also served as the pretest measure for the year 5 cohort.

The analyses used either two-level hierarchical modeling for school and child or three-level hierarchical modeling for school, child, and time. Controls included school- and child-level eligibility for free school meals and speaking English as an additional language, child sex, school use of other socioemotional learning practices, and child baseline risk status. Barlow et al. (2015) lacked baseline outcome controls, while Hennessey & Humphrey (2019) used baseline outcome controls from the standardized tests given to students in year 2. To deal with missing data, the analyses used FIML estimation or multiple imputation, except for the year 6 cohort in Hennessey & Humphrey (2019), where attrition was only 3%.

Tests for baseline equivalence showed some school differences but few individual differences (Barlow et al., 2015, Table 1; Hennessey & Humphrey, 2019, Tables 1-2). The tables list effect sizes without significance tests. For six school characteristics, the three largest differences were for school size (.24), attainment (.43), and attendance (.48). The intervention schools had more students, lower attendance, and higher attainment. For five student characteristics, the largest effect size was .17, with the intervention students having higher scores on teacher-rated strengths and difficulties.

Differential attrition appeared in the substantial differences in condition completion rates for the year 5 students. According to Figure 1 in Barlow et al. (2015, p. 15), 96% of the intervention schools and 73% of the intervention students provided year 5 data, while only 68% of the control schools and 58% of the control students provided year 5 data. Hennessey & Humphrey (2019) reported that the comparison of schools lost to follow-up with those retained did not reveal significant differences on school characteristics. Children with complete versus incomplete data did not differ in terms of their gender, language group, or prior academic attainment, but those with incomplete data were significantly more likely to be eligible for free school meals.

For the four posttest academic attainment outcomes in Barlow et al. (2015, Table 3), only one of the tests proved significant, but the effect was iatrogenic. The multivariate coefficient for the English test in year 6 indicated that the control group improved more than the intervention group (Hedges g = -.106). Four other tests for the subgroup of students eligible for free-school meals were not significant. Hennessey & Humphrey (2019) found that the program had no significant impact on the attainment outcomes, regardless of year group (year 5, year 6), outcome measure, subject area (Math, English/Reading), or analysis sample (ITT,  subgroup).

Complier and Non-Compliers Analysis (Panayiotou et al., 2020)

As a supplement to the ITT analyses in other articles, Panayiotou et al. (2020) used a quasi-experimental design to examine the program effects for those who received a high dosage (i.e., compliers) relative to those who did not. Randomization served as an instrumental variable in estimating complier average casual effects that adjusted statistically for differences between the compliers and others.

The authors defined the high-dosage compliers in two ways. The first was defined as being in a class that delivered at least 67% of the scheduled lessons (50th percentile and higher), and the second was defined as being in class that delivered at least 79% of the scheduled lessons (75th percentile or higher). Independent observers coded dosage for each class near the end of the first year of implementation. In examining models for both measures of high-dosage compliers, the analysis used robust maximum likelihood estimation with full information and included all available data. Two-level models nested students at level 1 within schools at level 2 ( n = 45) and controlled for baseline scores, conduct problems, social-emotional competence, free school meal eligibility, sex, and three school characteristics (percent free-school meal eligibility, percent with English as an additional language, and size).

The ITT results confirmed previous findings that the program significantly improved psychological well-being for the intervention group relative to the control group ( d = .17) but did not improve peer social support or school connectedness. The non-ITT complier average causal effect estimates produced stronger results. Compliers did significantly better than others on all three outcomes of psychological well-being ( d = .43), peer social support ( d = .63), and school connectedness ( d = .80). The results confirmed findings of the benefits of high-quality program implementation in Humphrey, Barlow et al. (2018) but did so with strong QED methods.

The study evaluated a Croatian version of PATHS that consisted of 63 lessons, about two per week, delivered in the last half of first grade and during most of second grade.

Novak et al. (2017) used a cluster randomized controlled trial that assigned 60 Croatian schools and 600 first-grade students to intervention and control conditions. The assessment at the end of second grade included teacher-reported measures of prosocial behavior, emotional regulation, hyperactivity, and aggression.

Novak et al. (2017) found no significant main effects of the intervention for the full sample but found significant benefits for several outcomes among those classified as being low risk at baseline.

Recruitment : The study recruited 30 schools and two first grade classrooms within each school. Although all children within each of the 60 classrooms participated in PATHS or usual practice, only 10 children from each classroom were randomly selected for assessment. The parents of all 600 children gave consent.

Assignment : After matching pairs of schools within region on neighborhood characteristics, family socioeconomic status, percentage of children receiving free lunches, school size, class size, and average achievement scores, one school within each pair was randomly selected to receive the intervention, and the other school was assigned to continue its usual practice.

However, one intervention school (with 20 children) and one control classroom (with 10 children) had to be excluded because teachers failed to complete the initial assessment of children. In addition, one selected child in each of two other classrooms in the control condition had to be excluded because the teacher failed to complete the initial assessment. That left 568 of 600 students (95%) to participate.

Assessments/Attrition : The posttest came near the end of second grade, about 1.5 years after the baseline assessment. A total of 546 children completed the posttest, which was 91% of all eligible children and 96% of those with baseline data.

The Croatian sample had an average age at baseline of seven years and consisted of 47% girls. The study provided no other details on sociodemographic background.

Teachers who delivered the program provided all ratings of children. The nine measures came from commonly used instruments:

• Prosocial behavior (alpha = .88)
• Emotion regulation (alpha = .89)
• Learning behavior (alpha = .92)
• Inattention (alpha = .94)
• Hyperactivity (alpha = .95)
• Oppositional behavior (alpha = .91)
• Physical aggression (alpha = .93)
• Peer problems (alpha = .65)
• Withdrawn/depressed behavior (alpha = .81).

The analyses used two-level hierarchical linear models, with children nested within classrooms but without nesting within schools, the unit of assignment. The study reported examining three-level models, but the intraclass correlation coefficient for eight of nine outcomes was not significant (ranging from .02 to .06). For the other outcome, accounting for the variance at the school level did not change the intervention effect. The study therefore reported results from the two-level models. The models included the relevant baseline outcome and child sex as covariates.

Intent-to-Treat: The full-information maximum likelihood estimation included the 22 children with baseline assessments but missing posttest data (4% of the sample). It was not possible to include randomized schools and children lost before baseline.

Local coaches completed checklists of program implementation, which indicated that teachers delivered 90-95% of the PATHS curriculum.

There were no statistically significant baseline differences between the intervention and control groups for the nine outcomes (Table 1), but the study did not test for baseline equivalence on any sociodemographic variables.

Among the sample with baseline data, attrition was only 4%.

For the full sample, the intervention group did not differ significantly ( p < .05) from the control group on any of the nine outcome measures. A high-risk subgroup also showed no significant intervention effects, but a low-risk subgroup showed significantly better outcomes for the intervention group on seven of the nine outcomes ( d ranged from .22 to .38). The study did not test for the significance of the subgroup differences in intervention effects, however.

Hindley and Reed (1999) used a quasi-experimental design that non-randomly assigned four schools and three hearing-impaired units in northeast England to intervention and waitlisted control groups. The sample included 64 deaf children and assessments over the following year measured social and emotional adjustment, reading attainment, and self-control.

Hindley and Reed (1999) found that the intervention children improved significantly more than the control children on

• Emotional adjustment
• Ability to recognize, label and understand emotions.

Recruitment : The study included four schools for the deaf and three hearing-impaired units that were located in northeast England. A total of 64 severely to profoundly deaf students in school years 4 and 5 were involved in the study.

Assignment : Two schools and one unit were non-randomly assigned to receive PATHS ( n = 33 students), and two schools and two units continued their usual practices as a waitlisted control group ( n = 31 student).

Assessments/Attrition : Assessments came at baseline and three time points over the following year. The study reported that one hearing-impaired unit in the intervention group dropped out, leaving 55 of 64 students (86%) available for posttest.

Boys made up about 43% of the sample.

The eight outcomes included measures of emotional vocabulary, social and emotional adjustment, self-image, reading attainment, impulsivity, and self-concept. Teachers provided some of the measures, and no information on reliability and validity was presented.

The analysis used repeated-measures models with baseline controls but no adjustment for clustering within schools/units.

Intent-to-Treat: One unit dropped out, and it was unclear if the study attempted to gather or use information from the unit.

The study reported positive reactions from teachers, parents, and students but provided no quantitative measures of implementation fidelity.

Tests for baseline differences for the eight outcomes showed one significant difference.

The repeated-measures analyses found that the intervention group improved significantly more than the control group for five of the eight outcomes: children's ability to recognize, label and understand emotions, children's self-image, and the teacher's assessment of the children's emotional adjustment.

The study included results for an additional follow-up, but after the waitlisted control group had received the program.

Ross, Sheard et al. (2011) and Ross, Cheung et al. (2011) used a cluster randomized controlled trial with 12 schools in Northern Ireland, six in the intervention group ( n = 650 students), and six in the comparison group ( n = 780 students). Assessments of socio-emotional attitudes and prosocial behavior came yearly throughout the three years of the study, with the last assessment serving as a posttest.

Ross, Sheard et al. (2011) and Ross, Cheung et al. (2011) found that, relative to the control group, the intervention group did significantly better on

• Teacher-rated measures of empathy, perseverance, negative affect, and aggression
• Child-assessed measures of emotional understanding, responses to challenging scenarios, and mutual understanding.

Recruitment : The study recruited 13 primary schools in three communities of Northern Ireland. The schools served populations of mostly working class pupils and were in communities that had experienced religious conflict. According to Table 3 in Ross, Sheard et al. (2011), the initial sample included 1,430 students in grade levels P1 (ages 4-5), P2 (ages 5-6), P5 (ages 8-9), and P6 (ages 9-10).

Assignment : Six schools were randomly selected to implement the program ( n = 650 students) and the others served as a comparison group. One of the comparison schools dropped out shortly after the random assignment and before pretesting, leaving six schools ( n = 780 students). The comparison schools initially implemented a less structured and intensive socio-emotional education program that focused on accepting others and getting along.

However, the comparison schools implemented the Together 4 All (T4A) program in the fall of year 3, before the posttest in the spring of year 3. Ross, Sheard et al. (2011, p. 70) referred to the comparison group receiving the intervention as Cohort 2, and stated: "although continuing to be treated in the analyses as a comparison group, the teachers, pupils, and principals were being fully exposed to the T4A curriculum, activities, and expectations."

Assessments/Attrition : The study followed the students for three school years. The baseline assessment in November/December 2008 was followed by assessments in May/June 2009, October/November 2009, May/June 2010, and May/June 2011. The last assessment (called Sweep 5) represented a posttest for the ongoing program. Students in grades P1, P2, and P5 at baseline were in grades P3, P4, and P7 at posttest, but the P6 students at baseline were not available for assessment at posttest. Table 3 shows that at the last follow-up, the sample size fell to 981 (69%). Not counting the P6 students, the sample sizes fell to 91% for P1 and P2 students and 93% for P5 students. Also, some measures had substantial additional missing data.

The median percentage of students receiving free school meals was 29%, and the median percentage of students with special education needs was 19%. No other sociodemographic information on the students was provided.

The study examined a large number of measures but with few relating to child behavioral outcomes. The measures came from three sources: 1) teachers who delivered the program, 2) child assessments using done by researchers, 3) and observations of teacher and child behaviors by researchers. The study did not report on reliability or validity, although some of the measures were created by the researchers. It also did not report on the awareness of condition by researchers.

First, the teacher assessments of the children used the Strengths and Difficulties Questionnaire. The measures focused on child behaviors but were not independently rated.

Second, the child assessments used the Assessment of Children's Emotions Scale, the Challenging Situations Task, and the Mutual Respect and Understanding Survey to measure pupil skills in social problem solving and recognizing emotions. These measures reflected student attitudes and responses to hypothetical situations rather than behavior.

Third, the observations of teachers and children used the Classroom Observation of Behaviour and Playground Observation of Behaviour instruments. Inter-rater reliabilities for the measures were adequate. The study made no mention of the observers being masked to condition.

Ross, Sheard et al. (2011) presented chi-square tests and differences-of-means tests. The latter tests provided the more direct contrast of the outcomes for the intervention and control groups. Page 42 states that the results controlled for baseline scores. The tests did not adjust for clustering within schools - the unit of assignment. Ross, Cheung et al. (2011) used chi-square and Mann-Whitney tests, but the chi-square tests appear to include a category for not available. They also examined hierarchical models but said that the power was too low with only 12 schools.

Intent-to-Treat: The study did not attempt to follow the P7 students after they left middle school but otherwise used all available data.

The authors summarized a detailed implementation analysis by stating that, by the third year, implementation was fairly strong in all six schools and had significantly improved from the first year.

Ross, Sheard et al. (2011, p. 3) stated that "None of the demographic variables was found to differ statistically significantly across treatment groups." In regard to the outcome measures, they found several differences: "At baseline, comparison pupils were rated significantly more positively than T4A pupils on 19% of the items and were directionally higher on 69%." For the baseline differences reported in Tables 14, 16, 18, 20, 25, and 28, a count shows 19 significant differences in 79 tests.

For three of the grades included in the posttest assessment, attrition was modest, only 7-9%, but the study provided no analysis of differential attrition.

The two articles presented numerous tables and tests. Ross, Cheung et al. (2011) examined results only at the interim, year one assessment. The authors said the "programme effects on social-emotional learning were weak and inconsistent."

Ross, Sheard et al. (2011) analyzed results for a longer follow-up period (i.e., the posttest at Sweep 5). The results from their difference-in-means t-tests can be summarized as follows:

• Teacher observations (Table 8): No significant differences in 11 tests.
• Student observations (Table 10): Two significant differences in nine tests but both were iatrogenic.
• Playground observations (Table 12): No significant differences in 11 tests.
• Teacher ratings of children in grades P3-P4 (Table 15): Three significant differences in five tests for empathy, coping, and cooperation ( d = .24), more actively helping others ( d = .20), and being less socially withdrawn ( d = .17).
• Teacher ratings of children in grade P7 (Table 17): Four significant differences in four tests for empathy and cooperation ( d = .58), reflectivity and perseverance ( d = .43), negative affect ( d = .53), and fighting and aggression ( d = .41).
• Child assessment of emotions in grades P3-P4 (Table 18): One significant difference in two tests for correct emotional responses ( d = .17), but one significant iatrogenic difference for giving more incorrect anger responses ( d = .17).
• Child managing emotions in hypothetical challenging scenarios in grades P3-P4 (Table 20): No significant differences in eight tests.
• Child coping strategies in hypothetical scenarios in grades P3-P4 (Table 22): Two significant differences in three tests, but both were iatrogenic.
• Child attitudes of mutual respect and understanding in grades P3-P4 (Table 24): Two significant differences in seven tests for understanding differences between people ( d = .24) and total score ( d = .21).
• Child managing emotions in hypothetical scenarios in grade P7 (Table 25): Four significant differences in 16 tests for hit by ball ( d = .33), invitation turned down ( d = .37), lunchroom rejection ( d = .29), and greeting ignored ( d = .34).
• Child naming of feelings in grade P7 (Table 28): Two significant differences in three tests for total naming and positive naming.
• Child coping strategies in grade P7 (Table 29): No significant differences in three tests.
• Child attitudes of mutual respect and understanding in grade P7 (Table 31): Three significant differences in 10 tests for different opinions ( d = .20), not putting others down ( d = .29), and happily sharing ( d = .28).

Overall, in 92 tests, there were 19 significant outcomes favoring the intervention group and five outcomes favoring the control group. The authors summarized the numerous findings by noting strong intervention effects for teacher ratings of prosocial behavior and for child responses in hypothetical situations (e.g., identifying emotions, demonstrating skills in hypothetical situations, and identifying feelings).

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What is a Problem-Solving Flowchart & How to Make One

By Danesh Ramuthi , Aug 10, 2023

Problem-Solving Flowcharts, contrary to what many believe aren’t just aesthetic wonders — they’re almost like magical blueprints for troubleshooting those pesky problems that many of us face.

Flowcharts take business challenges and turn them into a navigable pathway. In this post, I will guide you on key aspects of problem-solving flowcharts such as what it is, the advantages of problem-solving flowcharts, how to create one and more.

Besides, you’ll also discover how to create problem-solving flowcharts with the help of Venngage’s Flowchart Maker.

And for those of you thinking, “I’m no designer, how can I create one?” worry not! I’ve got you covered. Just hop on Venggage’s Flowchart Templates and you’ll be charting your way to problem-solving glory in no time.

Click to jump ahead:

What are problem-solving flowcharts?

When to use problem-solving flowcharts, what are the advantages of flowcharts in problem-solving, what are the 7 steps of problem-solving flowcharts.

• 5 different types of problem-solving flowcharts

Best practices for designing effective problem-solving flowcharts

How to make a flowchart using venngage , problem-solving flowcharts faqs.

• Final Thoughts

Problem-Solving Flowcharts is a graphical representation used to break down problem or process into smaller, manageable parts, identify the root causes and outline a step-by-step solution. 

It helps in visually organizing information and showing the relationships between various parts of the problem.

This type of flowcharts consists of different symbols and arrows, each representing different components or steps in the problem-solving process. 

By following the flow of the chart, individuals or teams can methodically approach problem, analyze different aspects of it and come to a well-informed solution.

Problem-Solving Flowcharts is a versatile tool that can be used in various scenarios. Here’s when to consider utilizing one:

• Complex Problems: When faced with a multifaceted issue that involves multiple steps or variables, flowcharts can help break down the complexity into digestible parts.
• Team Collaboration: If you’re working with a team and need a common understanding of problem and its potential solutions then a flowchart provides a visual that everyone can refer to.
• Analyzing Processes: In a situation where you need to understand a particular process, whether it’s within a project or a part of regular operations then mapping it out in a flowchart can offer clarity.
• Decision Making: When various paths or decisions might be taken, a flowchart can outline the potential outcomes of each aiding in making an informed choice.
• Training and Onboarding: Flowcharts can be used in training materials to help new employees understand complex processes or procedures which makes the learning curve smoother.
• Identifying Root Causes: If you’re looking to identify the underlying causes of problem then a flowchart can facilitate a systematic approach to reaching the root of the issue.

Related: How to Use Fishbone Diagrams to Solve Complex Problems

Problem-solving flowcharts can offer several benefits to the users who are looking to solve a particular problem. Few advantages of flowcharts in problem solving are: 

Visual Clarity

When you’re dealing with multifaceted problems or processes, words alone can make the situation seem even more tangled. Flowcharts distill these complexities into easily understandable visual elements. 

By mapping out each phase or component of problem, flowcharts offer a bird’s eye view enabling individuals to grasp the bigger picture and the finer details simultaneously.

Sequential Representation

Flowcharts excel in laying out the sequence of events or actions. By indicating a clear starting point and illustrating each subsequent step, they guide users through a process or solution path methodically. 

This linear representation ensures that no step is overlooked and each is executed in the right order.  

Collaboration

Problem-solving often requires team effort and flowcharts are instrumental in fostering collaborative environments. 

When a team is discussing potential solutions or trying to understand problem’s intricacies, a flowchart serves as a collective reference point. 

It aids in synchronizing everyone’s understanding, minimizing miscommunications and promoting constructive discussions. 

Read more about: Flowcharts Symbols and Meaning

1. Define the Problem  

Before anything else, it’s essential to articulate the problem or task you want to solve clearly and accurately. By understanding exactly what needs to be addressed you can ensure that subsequent steps align with the core issue.

2. Identify the Inputs and Outputs  

Determine what inputs (such as data, information or resources) will be required to solve the problem and what the desired outputs or outcomes are. Identifying these factors will guide you in structuring the steps needed to reach the end goal and ensure that all necessary resources are at hand.

3. Identify the Main Steps  

Break down the problem-solving process into its main steps or subtasks. This involves pinpointing the essential actions or stages necessary to reach the solution. Create a roadmap that helps in understanding how to approach the problem methodically.

4. Use Decision Symbols  

In problem-solving, decisions often lead to different paths or outcomes. Using standard symbols to represent these decision points in the flowcharts allows for a clear understanding of these critical junctures. It helps visually present various scenarios and their consequences.

5. Add Descriptions and Details  

A well-designed flowcharts is concise but clear in its labeling. Using arrows and short, descriptive phrases to explain what happens at each step or decision point ensures that the flowcharts communicates the process without unnecessary complexity. 

6. Revise and Refine  

Creating a flowcharts is not always a one-and-done process. It may require revisions to improve its clarity, accuracy or comprehensiveness. Necessary refinement ensures that the flowcharts precisely reflects the problem-solving process and is free from errors or ambiguities.

7. Use Flowchart Tool  

While it’s possible to draw a flowcharts manually, using a flowcharts tool like Venngage’s Flowchart Maker and Venngage’s Flowchart Templates can make the process more efficient and flexible. These tools come with pre-designed templates and intuitive interfaces that make it easy to create, modify and share flowcharts. 

5 different types of problem-solving flowcharts 

Let’s have a look at 5 most common types of flowcharts that individuals and organizations often use. 

1. Process Flowchart s

A process flowcharts is a visual representation of the sequence of steps and decisions involved in executing a particular process or procedure. 

It serves as a blueprint that showcases how different stages or functions are interconnected in a systematic flow and it highlights the direction of the process from its beginning to its end.

Process flowcharts are instrumental in training and onboarding, sales process , process optimization, documentation, recruitment and in any scenario where clear communication of a process is crucial.

2. Flowcharts Infographic 

A flowcharts infographic is a great way to showcase the process or a series of steps using a combination of graphics, icons, symbols and concise text. It aims to communicate complex information in a clear and easy-to-understand manner, making it a popular tool for conveying information, data and instructions in a visually engaging way.

For example, you can use this flowchart to illustrate a health insurance process that visually explains the steps involved from finding a provider to paying for your healthcare provider. 

3. Circular Flowcharts

A circular flowcharts is used to illustrate the flow of information, goods, services or money within a closed system or process. It gets its name from its circular shape, which emphasizes the continuous and cyclical nature of the flow. 

Circular flowcharts are widely used in various fields such as economics, business, engineering and process management to help visualize and understand complex systems.

In a circular flowcharts , elements are represented using various shapes and connected with arrows to indicate the direction of flow. The circular arrangement indicates that the process is ongoing and repeats itself over time.

4. Swimlane flowcharts

Swimlane flowcharts , also known as cross-functional flowcharts are a specific type of flowchart that organizes the process flow into lanes or “swimlanes.” 

Each lane represents a different participant or functional area involved in the process and the flowchart shows how activities or information move between these participants. 

Swimlane flowcharts are particularly useful for illustrating complex processes that involve multiple stakeholders or departments.

In a swimlane flowcharts, the process is divided horizontally into lanes and each lane is labeled with the name of the department, person or role responsible for that part of the process. Vertically, the flowchart displays the sequence of steps or actions taken in the process.

5. Decision Flowchart s

Decision flowcharts, also known as decision trees or flow diagrams are graphical representations that illustrate the process of making decisions or solving problems. 

They are widely used in various fields such as computer science, business mapping , engineering and problem-solving scenarios. 

Decision flowcharts help break down complex decision-making processes into simple, sequential steps, making it easier to understand and follow.

A decision tree is a specialized flowchart used to visually represent the process of decision-making. 

Businesses and other individuals can employ a decision tree analysis as a tool to aid in evaluating different options and the possible consequences associated with each choice.

Decision trees Infographics can be used to create a more nuanced type of flowchart that is more informative and visually appealing by combining a decision flowchart and the flowchart infographic. 

Decision flowcharts are valuable tools for visualizing decision-making processes, analyzing complex problems and communicating them effectively to others.

Designing effective problem-solving flowcharts involves careful consideration of various factors to ensure clarity, accuracy and usability. Here are some best practices to create efficient and useful problem-solving flowcharts:

• Understand the problem first & clearly define it
• Keep it simple
• Use standard & recognizable symbols
• Ensure that the flowchart follows a logical and sequential order
• Clearly label each decision point, action and outcome
• Verify the flowchart’s accuracy by testing it
• Clearly state the decision criteria that lead to different branches
• Provide context when the flowchart is part of a larger process or system
• Review and revise the flowchart

Creating problem-solving flowchart on Venngage is incredibly simple. All you have to do is:

• Start by Signing Up and Creating an Account with Venngage
• Choose a flowchart template that best suits your needs from our library.
• Start editing your flowchart by choosing the desired shapes, labels and colors.
• You can also enhance your flowchart by incorporating icons, illustrations or backgrounds all of which are readily available in our library.
• Once done, you will have 2 options to choose from, either sharing it online for free or downloading your flowchart to your desktop by subscribing to the Premium or Business Plan. 

Is flowchart the representation of problem solutions?

Flowcharts are not the representation of problem solutions per se; rather, they are a visual representation of processes, decision-making steps and actions taken to arrive at a solution to problem.

What are the 3 basic structures of flowcharts?

3 Basic Structures of Flowcharts are:

• Sequence: Simplify Complexity
• Selection (Decision): Embrace Choices
• Repetition (Loop): Emphasize Iteration

What are the elements of a good flowchart?

A good flowchart should exhibit clarity and simplicity, using consistent symbols and labels to depict a logical sequence of steps. It should be readable, with appropriate white space to avoid clutter while eliminating ambiguity through well-defined decision criteria and paths.

Can flowcharts be used for both simple and complex problem-solving?

Yes, flowcharts can be used for both simple and complex problem-solving scenarios. Flowcharts are versatile visual tools that can effectively represent various processes, decision-making steps and problem-solving approaches regardless of their complexity.

In both cases, flowcharts offer a systematic and visual means of organizing information, identifying potential problems and facilitating collaboration among team members.

Can problem-solving flowcharts be used in any industry or domain?

Problem-solving flowcharts can be used in virtually any industry or domain. The versatility and effectiveness of flowcharts make them applicable to a wide range of fields such as Business and Management, Software Development and IT, Healthcare, Education, Finance, Marketing & Sales and a lot more other industries. 

Final thoughts

Problem-solving flowcharts are a valuable and versatile tool that empowers individuals and teams to tackle complex problems with clarity and efficiency.

By visually representing the step-by-step process of identifying, analyzing and resolving issues, flowcharts serve as navigational guides simplifying intricate challenges into digestible parts.

With the aid of modern tools like Venngage’s Flowchart Maker and Venngage’s Flowchart Templates , designing impactful flowcharts becomes accessible to all while revolutionizing the way problems are approached and solved.

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Humphrey N, Hennessey A, Lendrum A, et al. The PATHS curriculum for promoting social and emotional well-being among children aged 7–9 years: a cluster RCT. Southampton (UK): NIHR Journals Library; 2018 Aug. (Public Health Research, No. 6.10.)

The PATHS curriculum for promoting social and emotional well-being among children aged 7–9 years: a cluster RCT.

Chapter 1 introduction.

• Social and emotional learning

Universal, school-based social and emotional learning (SEL) interventions aim to develop the social and emotional skills of children and young people through explicit instruction in the context of learning environments that are safe, caring, well-managed and participatory. 1 This is typically achieved through the delivery of a taught curriculum, activities and strategies to promote a more positive school environment or ethos, and/or work with parents and the wider community. 2 Three recent meta-analyses have demonstrated that high-quality, well-implemented SEL interventions can produce practically significant improvements in a range of outcomes, including children’s social and emotional skills, mental health and academic attainment. 3 – 5

Social and emotional learning therefore has significant potential utility as a vehicle for both promotion (of skills) and prevention (of problems). With regard to promotion, social and emotional skills can be thought of as comprising emotional competence and relational/pro-social domains. 6 Emotional competence includes self-awareness, self-regulation and social awareness. Relational/pro-social competence includes relationship skills and responsible decision-making. The emergence of these skills follows a developmental trajectory that is influenced by both implicit and explicit socialisation practices (e.g. ‘caught’ and ‘taught’) in primary developmental contexts such as the home and school. 7 Notwithstanding the importance of emotional and relational/pro-social competence for adaptive functioning within childhood and adolescence, longitudinal research consistently notes their utility in predicting a range of salient later-life outcomes. For example, when compared with cognitive ability, childhood social and emotional skills are (1) more strongly associated with adult general mental well-being (e.g. life satisfaction, mental health); (2) similarly associated with adult health and health-related outcomes (e.g. obesity, smoking); and (3) similarly associated with some labour market outcomes (e.g. employment status). 8 They are thus increasingly referred to as ‘skills for life and work’. 8

In relation to prevention, the extant evidence base also highlights the efficacy of SEL in stemming the maintenance or progression of nascent mental health difficulties. The onset of such difficulties is characterised by changes in thought, mood and/or behaviour that impair functioning. 9 The range of mental health difficulties are typically dichotomised in terms of their directionality, with a distinction made between those that are primarily internalising in nature (e.g. depression, anxiety) and those that are externalising in nature (e.g. conduct problems). 10 Prevalence estimates suggest that 1 in 10 children and adolescents experience clinically significant mental health difficulties. 11 Furthermore, up to half of all lifetime cases of mental ill health have their first onset by the age of 14 years. 12 The consequences of such difficulties include reduced quality of life, lost economic productivity, destabilisation of communities and higher rates of health, education and social care use. 13 Indeed, by 2030, depression alone is projected to yield the highest disease burden in high-income countries, accounting for nearly 10% of disability-adjusted-life-years. 14 In England, mental health care costs approximately £105B per annum. 15

Thus, there is a compelling rationale for school-based, universal SEL interventions. Developmental theory and research suggest that early life experiences influence later life outcomes: ‘prevention pays’ from both economic and quality-of-life perspectives. 16 In addition, schools have a central role in the lives of children and their families, with unparalleled reach. 17 This means that children with emergent difficulties can access much-needed support that is unavailable through standard care pathways. By definition, universal intervention is also more inclusive and there is less chance of harmful stigmatisation than in targeted/indicated approaches. 18 Finally, health economic analyses of the effects of early mental health problems on labour market outcomes suggest clear indirect effects that operate through education. 19

The aforementioned meta-analyses, in addition to related syntheses of the literature such as those published by the National Institute for Health and Care Excellence (NICE) 20 and the Early Intervention Foundation, 21 highlight the distinct lack of a rigorous evidence base for universal, school-based SEL interventions in the UK. In the most recently published analysis, for example, only 4 of 89 studies reviewed originated here. 5 Thus, in terms of a robust evidence base, universal SEL is still very much in its infancy in the UK.

More broadly, a number of important gaps in the literature are evident. First, a relative lack of follow-up data to assess the maintenance of intervention effects has been noted. For example, only 33 of the 213 studies reviewed by Durlak et al. 3 collected follow-up data at least 6 months after the intervention had ceased. Second, although most SEL trials now provide accompanying descriptive data on the implementation of the intervention being evaluated (e.g. fidelity, dosage), 5 relatively few formally assess the relationship between levels of implementation and outcome variability. Third, in spite of the noted health economic component of the rationale, a major review commissioned by NICE identified no published studies of the cost-effectiveness of SEL interventions. 22 Finally, the temporal relationships between intervention outcomes have been neglected, 3 limiting the extent to which underpinning SEL theory can be verified. These gaps are evident in the international SEL evidence base, but are brought into even sharper focus in the UK, which is limited to a much smaller number of trials from the outset. Thus, of the four UK-based studies included in the aforementioned meta-analysis, 5 none was a randomised controlled trial (RCT), none assessed the maintenance of intervention effects or the relationship between levels of implementation and intervention outcomes, none addressed cost-effectiveness, and none examined temporal relations between outcomes.

• The Promoting Alternative THinking Strategies curriculum

The Promoting Alternative THinking Strategies (PATHS) curriculum aims to promote self-control, emotional understanding, positive self-esteem, relationships and interpersonal problem-solving skills among children aged 4–11 years. This is primarily achieved through the implementation of a taught curriculum by the class teacher. Lessons on topics such as identifying and labelling feelings, controlling impulses and understanding the perspectives of others are delivered approximately twice a week throughout the year. The curriculum is supplemented by generalisation activities and techniques that support the application and consolidation of new skills throughout the day. Finally, supplementary parental materials are provided, the aim of which is to extend learning to the home environment. Teachers in PATHS schools receive 1 initial day and 1 half-day follow-up of training, and are aided by trained external coaches, who offer ongoing technical support and assistance (e.g. lesson modelling, observation and feedback) throughout the school year as a means to optimise delivery. A full description of the PATHS curriculum using an adapted version of the Template for Intervention Description and Replication (TIDieR) 23 can be found in Chapter 2 , Intervention .

The PATHS curriculum was originally developed in the USA by Mark Greenberg and Carol Kusche as an intervention to promote social and emotional competence among children with hearing impairments. It was subsequently adapted for use in other special education settings before being revised and applied as a universal intervention in mainstream schools. PATHS has a strong international evidence base. It is one of only 14 programmes from a review of > 1400 youth promotion approaches to be awarded ‘model program’ status by the Centre for the Study and Prevention of Violence [see www.blueprintsprograms.com/factsheet/promoting-alternative-thinking-strategies-paths (accessed 21 June 2017)]. Not including the current study, there have been 10 RCTs of PATHS to date. We note that there are also many quasi-experimental and other studies of PATHS. However, we restrict our discussion to RCTs here in the interests of prioritising studies that make use of more robust evaluation designs and comparing like with like. Six of these RCTs were conducted in the USA. 24 – 29 With one exception, 27 these US trials have consistently found small intervention effects across the range of outcomes noted at the outset of this chapter. Elsewhere in the world, RCTs of PATHS have been conducted in Switzerland, 30 Croatia 31 and the UK, 32 , 33 but have generally failed to replicate the positive effects noted above, with null intention-to-treat (ITT) results reported in all but one of the trials. The exception was a trial of PATHS conducted in Northern Ireland, which found small, positive effects for a range of outcomes, including pro-social and aggressive behaviour. 32 Of the trials reporting null findings, there was evidence of small subgroup effects in two, although these were not consistent. Thus, although a recent trial of PATHS in Birmingham, England (involving children aged 5–7 years) found some limited evidence of differential gains among children with elevated emotional symptoms at baseline, 33 a Croatian evaluation found positive effects only among children without mental health difficulties. Finally, a Swiss trial found evidence of a ‘sleeper’ effect on children’s externalising problems at 24-month post-intervention follow-up, having found no intervention effects immediately post intervention. 30

There are a number of reasons why PATHS may not be as successful when evaluated outside its country of origin, including issues of cultural transferability and/or the independence of such evaluations from the developer. One of the aforementioned meta-analyses offers some useful insights in this regard. Wigelsworth et al. 5 found that the transposition of SEL interventions from one country or culture to another led to significantly diluted impact in relation to outcomes such as social and emotional skills, pro-social behaviour and emotional distress. This ‘voltage drop’, which in the case of social and emotional skills equated to an average effect size difference of 0.5 between interventions trialled in their country of origin and those trialled elsewhere, could be the consequence of differences in education systems and policies, cultural beliefs and/or expectations of the roles of teachers and students. Each of these factors may act as a barrier to successful implementation and thus the achievement of intended intervention outcomes. 34 By contrast, the influence of developer involvement is less clear; in theory, this could lead to inflated intervention effects as a result of higher quality implementation and/or bias. 35 However, the same meta-analysis found no significant differences in any outcomes between SEL trials that were independent, involved the developer or were led by the developer. In relation to PATHS specifically, all developer-led or involved trials have yielded positive effects, compared with only around half of independent trials. However, it is difficult to draw firm conclusions about this pattern of findings because several of these independent studies were also conducted outside the USA, meaning that developer involvement and intercultural transferability issues are conflated.

• The current study

In the light of this, there is genuine uncertainty in relation to the likely effects of PATHS when implemented outside its country of origin and evaluated independently. In the year prior to the beginning of the trial reported herein, it had been recommended for widespread adoption in an influential report to the government on early intervention. 36 More broadly, interest in and implementation of SEL had been growing in the English education system for a number of years, driven primarily by governmental promotion of the Social and Emotional Aspects of Learning (SEAL) programme from 2005 onwards, in spite of the ultimately rather limited evidence of its effectiveness. 37 More recently, there has been a resurgence of interest in the role of schools in establishing and protecting the mental health of children and young people (as evidenced by the launch of a Commons Select Committee inquiry in late 2016). Alongside this, the ‘what works’ agenda has well and truly gathered pace and has a strong foothold in education, with > 140 school-based RCTs registered on the International Standard Randomised Controlled Trial Number (ISRCTN) registry (of which around two-thirds were registered from 2010 onwards). 38

The reporting of the current study is therefore particularly timely and significant. Each of the objectives outlined in Aims and objectives was selected based on identified gaps and inconsistencies in the literature noted earlier in the chapter. Thus, we sought to contribute to the extant literature by developing the UK (and by extension, international) evidence base for PATHS through further independent evaluation of its efficacy in promoting a broader range of outcomes than had been assessed previously, among a sample of children in Key Stage 2 (KS2) of primary education. The provision of analyses to determine the presence of maintenance and/or sleeper effects at longer-term (i.e. 12- and 24-month) follow-up, associations between levels of implementation and intervention outcomes, temporal relations between outcomes, and cost-effectiveness all map directly on to identified areas for development in relation to advancing the scientific base for SEL. 2 , 3

Aims and objectives

The primary aim of the trial was to examine the impact of the PATHS curriculum on the social and emotional well-being of children in primary schools in England. The version of PATHS used in the trial was subjected to a process of cultural adaptation by Barnardo’s [(London, UK) the children’s charity that owns the UK licence to distribute PATHS] in order to ‘Anglicise’ it. This entailed primarily surface-level changes (e.g. modified vocabulary, photographs and names, changes to cultural references) and did not substantively change the structure, delivery model or content of the intervention. The objectives of the trial were as follows.

• To determine the impact of PATHS on a variety of outcomes for children Hypothesis 1: children in primary schools that are implementing PATHS over a 2-year period will demonstrate significant improvements in social skills (1a) and pro-social behaviour (1b), mental health difficulties [specifically internalising symptoms (1c) and externalising problems (1d)] and health-related quality of life (HRQoL) [specifically psychological well-being (1e), social support and peers (1f) and school environment (1g), exclusions (1h), attendance (1i) and academic attainment (1j)], compared with those of children attending control schools.
• To determine whether or not the impact of PATHS is sustainable Hypothesis 2: the effects of PATHS on social skills (2a) and pro-social behaviour (2b), mental health difficulties [specifically internalising symptoms (2c); and externalising problems (2d)] and HRQoL [specifically psychological well-being (2e), social support and peers (2f) and school environment (2g)] will be sustained at the 24-month post-trial follow-up.
• To determine the impact of PATHS on children’s psychosocial adjustment to secondary school Hypothesis 3: children in primary schools implementing PATHS over a 2-year period will demonstrate significantly better psychosocial adjustment [specifically, psychological well-being (3a), social support and peers (3b) and school environment (3c)] upon transfer to secondary school (12-month post-trial follow-up) than those attending control schools.
• To assess the role of implementation variability in moderating the impact of PATHS on outcomes for children Hypothesis 4: variability in the implementation of PATHS [specifically, fidelity (4a), dosage (4b), quality (4c), participant responsiveness (4d) and reach (4e)] will be significantly associated with variability in intervention outcomes.
• To assess the validity of the logic model for SEL programmes Hypothesis 5: social skills and perceptions of peer and social support will be associated with later perceptions of the school environment and mental health difficulties, which in turn will predict later academic attainment.
• To examine the cost-effectiveness of PATHS Hypothesis 6: the PATHS curriculum will demonstrate cost-effectiveness.
• Cite this Page Humphrey N, Hennessey A, Lendrum A, et al. The PATHS curriculum for promoting social and emotional well-being among children aged 7–9 years: a cluster RCT. Southampton (UK): NIHR Journals Library; 2018 Aug. (Public Health Research, No. 6.10.) Chapter 1, Introduction.
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The Three Common Types of Flowcharts

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Also known as Flow Diagram, Activity Flowchart, Process Diagram.

Variants include Process Sequence Chart.

A flowchart is a visual representation tool that illustrates the flow of a business process and the interconnections between its activities. It allows to break up any process into individual activities and see how they fit together. The simplicity of flowcharts makes them useful for understanding any process and identifying areas of waste and inefficiency, thus facilitating targeted problem-solving efforts. They can be used across multiple industries and functions, making them universally applicable.

Flowcharts are ideal tools to visually representing business processes. For example, they are useful when trying to understand the step-by-step flow of activities in processes like purchase order or sales order in a company. They help in understanding what activities and decisions are involved, and thus, ensuring accurate execution in the right sequence. This is why they are often used to document how to do a particular job and can be found in procedures and quality manuals.

In addition to their role in documenting existing processes, flowcharts are also used when designing new processes aimed at facilitating organizational transformation. Software developers are using flowcharts to map out processes that need to be automated. Similarly, Kaizen teams are using them to identify and analyze problematic areas, subsequently streamlining the work and enhancing the performance .

Flowcharts are typically drawn with arrows and shapes of various kinds to denote different types of activities. While there is no universally prescribed format for flowcharts, adhering to a standardized set of shapes ensures they are drawn in a consistent manner. It is advisable to check whether your organization has established a standard set of shapes or symbols that must be adhered to.

The following outline the basic shapes that are applicable in most situations:

Activity – The most frequently used shape which represent the task or action to be performed (denoted as a plain rectangle).

Decision point – Requires a YES or NO response. Other options are also valid such as (TRUE or FALSE) and (LESS THAN, EQUAL or MORE THAN).

Start / End – Defines the process boundaries. Also used to indicate that a branch from a decision comes to an end.

Flow line – Connects the shapes and indicates the flow of the process as well as the loops.

A single flowchart can quickly become complex and lengthy. That’s why connectors are often used to link sub-processes and indicate converging paths. Moreover, additional shapes can be used to describe the type of activities more specifically. Additionally, flowcharts have the capability to incorporate supplementary information, such as assigning responsibility for each activity and specifying the time required for completing the activity.

Flowcharts are widely used in particular industries, such as software development, auditing and quality management. In each of these domains, industry-specific shapes and symbols are often used to ensure specific activity representation.

In the subsequent sections, we will discuss of the three common types of flowcharts.

Activity Flowcharts

An activity flowchart serves to illustrate the sequential order and progression of activities within a process, focusing on what happens. It represents the basic form of flowcharts and typically illustrates the flow of activities, their order, decision points, loops of rework and process boundaries. While there is no precise format for an activity flowchart, it is important that it is represented in a consistent and uniform manner.

Example – Making a Cup of Tea

Note: Cycle time refers to the duration from the initiation to the completion of a process. In the context of this example, it is the time required to prepare a cup of tea.

Example – Preparing Reports for Decision Makers

Note: Flowcharts have the capacity to incorporate additional information. In this particular example, performance indicators that need to be captured have been included above specific activities.

Example – Changeover

The following is an example of a flowchart that has been created for a changeover operation, specifically a size conversion, for a production line.

Note: There is a rework loop in this manufacturing process where the approver rejects to run the line until the specified requirements are met.

Swimlane Flowcharts

A process is described as a cross-functional when it involves multiple departments, and a swimlane flowchart illustrates the sequence of activities required to accomplish a cross-functional process. This type of flowchart is divided into multiple lanes , representing the multiple responsibilities within the process. Activities or decisions falling within a specific lane are under the control of the corresponding department, work group, or individual. This helps clarifying the responsible for executing activities and making decisions.

Swimlane flowcharts are particularly helpful for non-manufacturing processes that mainly involve the flow of information, knowledge, and documents across multiple functions. Such processes often involve many handoffs where information and documents are exchanged among departments, work groups or individuals. An excessive number of handoffs within a process can indicate potential waste due to unnecessary transporting, wasted motion or overprocessing.

Example – Acquiring New Equipment

The following example illustrates a cross-functional flowchart showcasing the process of equipment acquisition in a company.

Opportunity Flowcharts

An opportunity flowchart provides a way to analyze and study business processes by highlighting those steps that contribute to waste and complexity. This type of flowchart is typically divided into two sections to differentiate the activities and decisions that add value from those that do not.

These types of flowcharts will increase the awareness regarding what previously was accepted as normal and unavoidable waste . By isolating the non-value-added steps, the opportunity flowchart facilitates a clearer identification of areas for improvement. The elimination or reduction of non-value activities presents a significant opportunity to simplify and streamline the process, and this is one of the core objectives of the lean methodology.

Example – Use of an Office Copy Machine

With the development of this flowchart, it becomes clearer where continuous improvement efforts should be focused to maximize value delivery. For example, implementing regular cleaning of the copier glass and monitoring paper availability are potential improvement ideas for this process.

Constructing a Flowchart

Whether you want to draw an activity flowchart, a swimlane flowchart, or an opportunity flowchart, the following straightforward steps can help you construct your flowchart:

• With your team, describe the process and your objectives.
• Determine the type of flowchart, the level of detail, and the appropriate scope and boundaries.
• Brainstorm and identify all major process activities, decisions and the sequence of completion.
• Draft the flowchart using the standard set of shapes, Label each step appropriately.
• Prepare the final flowchart, check for missing activities or decisions, and add further details as necessary.
• Test the flowchart to make sure that it represents the process accurately and completely.
• Publish and distribute the completed final version of the flowchart to all concerned.
• Update the procedures and other documentation as necessary.
• Identify the areas that hinder the process or add little or no value for further process improvement.
• Plan and implement actions to reduce inefficiencies and waste.

Flowcharts and Document Management

Every company should establish a standardized way for documenting their procedures and processes. Flowcharts prove to be useful in summarizing a procedure, process or work instruction. They can play an important role in document management and may either be included under the relevant procedure or be placed in the appendix at the end of the document or manual.

Flowcharts and Software Applications

The process of drawing a detailed flowchart can be an overwhelming task. This is where applications and online services can offer the flexibility that a piece of paper cannot. While it is possible to create flowcharts by hand, it is often more convenient to use any of the drawing applications to create visually appealing flowcharts. A recommended practice is to initially draft the flowchart on paper before refining it using an application.

There are many software applications and online services that allow the creation of professional flowcharts including Microsoft Visio, SmartDraw and Micrografx. However, one of the simplest ways is to use this flowchart template .

Wrapping Up

Flowcharts facilitate documentation of current job procedures, and are useful when designing new processes aimed at facilitating organizational transformation. They are commonly utilized by system analysts, software developers, and Kaizen teams, and are often found in procedures and quality manuals. By addressing areas of inefficiency, such as unnecessary activities, bottlenecks, complex procedures and missing steps, flowcharts empower organizations to optimize their operations.

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Flow Charts

Identify and communicate your optimal process.

By the Mind Tools Content Team

How often have you thought about streamlining a process in your organization but not been sure where to start? Or perhaps you've struggled to understand a process when it's described to you in detail.

Flow charts are a useful tool in these situations, as they make a process easy to understand at a glance. Using just a few words and some simple symbols, they show clearly what happens at each stage and how this affects other decisions and actions.

In this article and video, we look at how to create and use flow charts, and explore how they can help you to solve problems in your processes.

What Is a Flow Chart?

Flow charts are easy-to-understand diagrams that show how the steps of a process fit together. American engineer Frank Gilbreth is widely believed to be the first person to document a process flow, having introduced the concept of a "Process Chart" to the American Society of Mechanical Engineers in 1921.

Flow charts tend to consist of four main symbols, linked with arrows that show the direction of flow:

1. Elongated circles, which signify the start or end of a process.

2. Rectangles, which show instructions or actions.

3. Diamonds, which highlight where you must make a decision.

4. Parallelograms, which show input and output. This can include materials, services or people.

You can use many other symbols in a flow chart but remember that these diagrams are used for communication . If you use symbols that only a few people understand, you may fail to get your message across. So, be sure to keep things simple !

When to Use a Flow Chart

All manner of organizations use flow charts to:

• Define a process.
• Standardize a process.
• Communicate a process.
• Identify bottlenecks or waste in a process.
• Solve a problem .
• Improve a process.

For example, software developers can use them to work out how the automated and manual parts of a process join up. Inexperienced team members might follow a flow chart to help them to complete activities in the right order. A manufacturer could ensure that it keeps to its values by applying a quality-control flow chart that presents questions and decision points. And an HR department might combine a flow chart with an organogram to show people who to contact about issues and when.

Why Use Flow Charts?

This tool's simplicity makes communicating and documenting a process quick and clear, so that the process will more likely be understood and applied correctly and consistently. It can also help you to estimate the timescale of the process, as you're better able to gauge the time needed for each task along the way. And you'll more likely identify who you should involve and at what stage, such as senior management or a compliance authority.

But you can also benefit from the process of creating a flow chart itself, as you build it step by step. You'll be able to focus on the detail of each individual stage, without feeling overwhelmed by the rest of the process, and then "zoom out" again to see the wider picture.

If your process or project involves several people or teams, you might find it more useful to use a Swim Lane Diagram rather than a flow chart – this helps you to show process flows between people and teams.

How to Create a Flow Chart

Follow these four steps:

Step 1: Identify Tasks

Begin by listing all of the tasks in a process in chronological order. Ask questions such as, "What happens next in the process?" or, "Do you need to make a decision before the next step?" or, "What approvals are required before you move on to the next task?"

Put yourself in the shoes of the person using the process, possibly for the first time. Talk to team members who work with the process directly, and get their opinions on where improvements could be made. Better yet, take a hands-on approach and go through the procedure yourself, and think about the practicalities of each stage. Use Customer Experience Mapping if your flow chart focuses on customer service, so that you can gain a better understanding of the process.

Step 2: Organize and Document Tasks

Next, start your flow chart by drawing the elongated circle shape and labeling it "Start."

Then, work through your whole process, and show the actions and decisions in the order that they happen. Link them with arrows to illustrate the flow of the process.

Where you need to make a decision, draw arrows from the decision diamond to each possible solution, and then label each arrow with the decision made. Remember to show the end of the process by using an elongated circle labeled "Finish."

Step 3: Double-Check the Process

When you've completed your flow chart, go back to the start and try it out to make sure that you haven't overlooked anything. Work through each step, and ask yourself whether you've represented the sequence of actions and the decisions involved correctly. Are there more decisions to be made at certain stages?

Then show your flow chart to other people, especially those who work directly with the process. Ask them to test that it works and to tell you if there are any problems or omissions.

Step 4: Challenge the Flow Chart

Finally, you might want to improve the process rather than just record it. So, see whether any of the steps that you've described are unnecessary or overly complicated. Identify any major bottlenecks , and deal with them to improve performance.

Are there any missing steps, no matter how small or seemingly insignificant, that you should add? And have you assigned tasks and decisions to the right people or automated them where it's most appropriate? Make any changes and then challenge the chart again.

As you challenge your flow chart, you might also be challenging your team members' tried and tested ways of working. So, take time to win support for your ideas, and don't expect to change people's habits overnight.

You may find that SIPOC diagrams will give you the detailed information that you need to introduce change in a controlled and effective way.

Flow Chart Software

You'll likely start with drawing flow charts by hand, but it's often more convenient to use a diagramming app to save, amend and share your charts.

Such apps vary from the simple and free, such as draw.io , creately and Pencil Project , to the more complex and paid-for, such as gliffy™ , Lucidchart , SmartDraw™ , and Visio® .

Flow charts can quickly become long and complicated, so that you can't represent them on a single piece of paper. This is where you can use "connectors" (shown as numbered circles) to link the flow when moving from one page to another. The user can follow the matching numbers to trace the flow of the process.

The image below shows part of a flow chart for how the receptionists in an example company should route incoming phone calls to the correct department:

Flow charts are simple diagrams that map out a process, so that you can easily communicate it to other people. You can also use them to define and analyze a process, build a step-by-step picture of it, and then standardize or improve it.

To draw a flow chart, identify the tasks and decisions that you make during a process, and write them down in order.

Then, arrange these steps in the flow chart format, using the appropriate symbols.

Finally, check and challenge your flow chart to make sure that it accurately represents the process, and that it shows the most efficient way of doing the job.

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So, what should the driver do next?

When asked, most people would respond “replace the tire.” Though they would be right in the general sense, the response ignores quite a few critical steps in the process such as safely pulling the car over, turning off the engine or even determining whether a flat tire is indeed the problem.

Just like any critical path method (CPM) plan for a project, a sequence of tasks emerges, though simple and largely intuitive, that must be performed in a specific order, one right after the other, to ensure a successful result. And so it is with many problems a project team is faced with on a daily basis. In essence, a critical path of steps must be taken to arrive at the proper solution to any given problem.

Any large scale IT project demands a very rigid, detailed means of solving problems. When JanCom Technologies is retained to consult for very complex IT infrastructure and data center projects, we rely upon dozens of experts who specialize in various subjects to solve problems that inevitably arise on every project. Asking general questions within such a diverse group of stakeholders will invariably result in answers that are as different as the people they are asked of.

Designing a data center, for instance, requires a variety of experts including the project’s architect and consultants, the general contractor and subcontractors, and the client’s own technology experts. Each of these parties have a stake in designing and delivering a state of the art data center, and each have their own perspective on how it should be done. To focus on problem resolution, I have adapted an analytical approach I call the critical path problem solving method. Like CPM scheduling, this approach effectively frames the issue and presents a clear path to resolution to all of the stakeholders. More importantly, however, this method also helps to efficiently arrive at a consensus solution.

Assessing the Problem

Though identifying and defining the problem would be self evident to many, it is also the most crucial step in the process. It sets the foundation for everything that follows. Returning to the example of a flat tire, there are a series of assessments that must be made to come to the proper solution. For instance, the driver needs to assess:

What is the extent of the damage? Can the problem be repaired on the road? Is the vehicle in a safe enough location to attempt a roadside repair? Is the spare tire in operable condition and does the driver have the necessary tools?

To answer any of these questions, the driver must get out and decipher what the vehicle’s issues really involve in order to assess the problem in more detail.

In many cases, when a specific issue or problem is inspected closely, more questions arise. For example, take the simple question: Can an end user install “X” number of servers in a particular row of cabinets? This question then yields a series of supporting questions such as is there adequate space, power or airflow? Although not exhaustive, these questions can help to produce an outline that can serve as a guide through the process.

Though the example above is very simple, a critical path of questions does emerge. Answering question A.1 provides an avenue to answer B.1 and C.1, and answers to B.2 and C.2 are simply mathematical extensions of B.1 and C.1 and so on. This is a good example how a very linear process of answering relevant questions begins to provide a very clear path to what is reality is a complex project with many interrelated components.

If we were to act quickly in an attempt to address the first problem that presented itself and ignored the tangential issues, it could take significantly more time and resources to install a series of servers within an existing data center. In essence, the critical path method of problem solving defines the problem not simply by evaluating a singular problem as much as it defines an entire situation that impacts the final solution.

Identifying Questions and Constraints

Once the problem is properly defined, it may be necessary to then define not only the questions that must be answered, but also what constraints or limitations will be faced while working to solve the problem. By identifying the questions that need to be answered, the direction of the critical path becomes clearer. There are a number of techniques that can help identify the questions that need to be answered within the problem solving process.

A common method utilized by many project managers is the program evaluation and review technique, better known as a PERT chart. Typically used in the context of scheduling, in our case, this technique lists out the questions that must be answered throughout the problem solving process.

Smaller bubbles connected by lines that are either questions-with-dependencies(one must be answered to progress to the next) or stand-alone questions that diverge from the original path if they represent mutually exclusive questions―all of which lead to the eventual solution. This particular technique not only helps to organize any thoughts on the problem, it also provides a visual representation of the theory behind the critical path problem solving method.

No problem exists in a vacuum. There are always parameters that exist within a problem that not only affect the outcome, but also the way in which a problem can be solved. Two good examples that present themselves in most problems are money and time. For instance, the unfortunate driver of that vehicle with a flat tire may prefer to have a mechanic in a tow truck help them with their problem, but they may not have the money to pay for the service or the time to wait for them to arrive. As a result, the driver of the vehicle is forced to fix the flat tire themselves. Conversely, if the driver has neither the skills nor the required tools, then waiting for a professional may well be the most efficient solution.

Identify Dependencies and Assumptions

In many cases, the answer to one question can provide the answer to others. To maximize the efficiency of the process, it is important to identify which questions in a given problem can help to answer others. This is an instance where using the PERT chart can really prove to be useful. By going through the exercise of thinking through the problem on paper and organizing the questions in the order they must be answered, it helps to identify exactly what the dependencies in a problem might be.

For the most part we are taught not to make assumptions. However, in context of solving very complex problems we do need to rely upon our expertise and experience. For instance, we know servers require space, power, cooling and connectivity. We also know it is necessary to verify these requirements before assuming a critical value. Though making the assumption is necessary, it is also important to verify each value as a small mistaken assumption will be a costly mistake in the context of a large deployment.

Check Your Work

Once the situation and questions are identified in previous steps, the critical path problem solving process truly begins to pay dividends. As defined earlier, the critical questions can be divided into stand-alone questions and questions-with-dependencies. As many of the questions get answered through establishing assumptions, dependencies and constraints, the questions that are truly critical can be established and efforts can be focused.

Though it would be nice to assume the answers derived from the process of analysis are correct, this is certainly a time when assumptions should not be made. For instance, prior to a data center being turned over for the deployment of hardware, it is very important to test whether each supporting system has been properly installed, calibrated, and tested. As new problems are discovered during this commissioning process we would be forced to go back through our process to identify what, specifically, the problem was. In the end, a very detailed and thorough problem solving process leads us to an equally thorough conclusion.

The true benefit to this process is not only the answers it renders, but also the fact that it arrives at the conclusion in a way that achieves a high level of agreement and consensus. In many ways, it is very similar to a mathematical proof. Not only is an answer established, but the work used to arrive at that answer is also very clear. This is particularly useful when working with individuals who possesses very different and diverse areas of expertise.

The critical path problem solving process helps to remove varied perspective from the equation. By presenting the problem, the steps to solve it, and the solution in a clear and concise way, you can achieve consensus on the more complex issues you face.

John Jankowski is the president and founder of JanCom Technologies, Inc. For over 15 years, John has specialized in applying proven principals and processes resulting in the implementation of cost effective, manageable telecommunications systems and data center designs. With his extensive experience in telecommunications systems technologies as well as the design and construction processes, John has excelled in the programming, design, and implementation of mission critical telecommunications reliant facilities, cabling systems, data centers, and campus master plans.

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Atlas of Public Management

Bardach’s Eightfold Path to More Effective Problem Solving

… a core concept in  Implementation and Delivery  and Atlas107

Concept description

Eugene Bardach, in his classic textbook (reference below), sets out eight steps to practical policy analysis.

The eight steps

The following are direct quotes:

• Define the problem . Your first problem definition is a crucial step: it gives you both a reason for doing all the work necessary to complete the project and a sense of direction for your evidence-gathering activity. And in the last phases of the policy analysis, your final problem definition will probably help you structure how you tell your story . (p. 1)
• Assemble some evidence . All of your time doing a policy analysis is spent on two activities: thinking (sometimes aloud and sometimes with others) and hustling data that can be turned into evidence. Of these two activities, thinking is generally the more important, but hustling data takes much more time: reading documents, hunting in libraries, poring over studies and statistics, interviewing people, traveling to interviews, waiting for appointments, and so on. … The real-world settings in which policy analysis is done rarely afford the time for a research effort that would please a careful academic researcher. In fact, time pressure is probably almost as dangerous an enemy of high-quality policy analysis as is politically motivated bias, if not more so. Therefore, economize on your data collection activities. The key to economizing is this: try to collect only those data that can be turned into “information” that, in turn, can be converted into “evidence” that has some bearing on your problem. (p. 11)
• Construct the alternatives . By alternatives I mean something like “policy options,” or “alternative courses of action,” or “alternative strategies of intervention to solve or mitigate the problem.” (p. 16)
• Select the criteria . It helps to think of any policy story (see Step Eight) as having two interconnected but separable plotlines, the analytic and the evaluative. The first is all about facts and disinterested projections of consequences, whereas the second is all about value judgments. Ideally, all analytically sophisticated and open-minded persons can agree, more or less, on the rights and wrongs in the analytic plotline and on the nature of its residual uncertainties. But this is not true with regard to the evaluative plotline – where we expect subjectivity and social philosophy to have freer play. The analytic plotline will reason about whether X, Y, or Z is likely to happen, but it is in the evaluative plotline that we learn whether we think X or Y or Z is good or bad for the world. (p. 31)
• Project the outcomes . For each of the alternatives on your current list, project all the outcomes (or impacts) that you or other interested parties might reasonably care about. This is the hardest step in the Eightfold Path. Even veteran policy analysts do not usually do it very well. Not surprisingly, analysts often duck it entirely, disguising their omission by a variety of subterfuges. Hence, the most important advice about this step is simple: do it. (p. 47)
• Confront the trade-offs . It sometimes happens that one of the policy alternatives under consideration is expected to produce a better outcome than any of the other alternatives with regard to every single evaluative criterion. In that case – called “dominance” – there are no trade-offs among the alternatives. Usually, though, you are less fortunate, and you must clarify the trade-offs between outcomes associated with different policy options for the sake of your client or audience. (p. 63)
• Decide! This step appears in the Eightfold Path as a check on how well you have done your work up to this point. Even though you personally may not be the decision maker, you should at this point pretend that you are. Then, decide what to do, based on your own analysis. If you find this decision difficult or troublesome, the reason may be that you have not clarified the trade-offs sufficiently, or that you have not thought quite enough about the probability of serious implementation problems emerging (or not emerging), or that a crucial cost estimate is still too fuzzy and uncertain, or that you have not approximated carefully enough the elasticity of some important demand curve, and so on. Think of it this way: unless you can convince yourself of the plausibility of some course of action, you probably won’t be able to convince your client – and rightly so. (p. 69)
• Tell your story . After many iterations of some or all of the steps recommended here – principally, redefining your problem, reconceptualizing your alternatives, reconsidering your criteria, reassessing your projections, reevaluating the trade-offs – you are ready to tell your story to some audience. The audience may be your client, or it may include a broader aggregation of stakeholders and interested parties. It may be hostile, or it may be friendly. Your presentation may be a one-time-only telling, or it may be merely the first effort in a planned long-term campaign to gather support behind a legislative or executive change. (p.70)

See also: Implementation Theory .

Atlas topic, subject, and course

The Study of Implementation and Delivery  (core topic) in  Implementation and Delivery and Atlas107

Eugene Bardach (2012), A Practical Guide for Policy Analysis – The Eightfold Path to More Effective Problem Solving , Fourth Edition, Sage, Los Angeles.

Page created by: Ian Clark, last modified 12 September 2017.

Image:  From cover of Bardach book, accessed 6 April 2017.

Problem Solving: Exploring Paths Less Traveled

By richard grassl and tabitha t. y. mingus.

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The inclusion of non-routine problems in the elementary and secondary school curriculum provides an opportunity for growth in mathematical maturing. This book illustrates the interfacing of NCTM Process Standards (2000): Problem Solving, Reasoning and Proof, Communication, Connections and Representation.

• A pre-service teacher course in problem solving.
• An in-service teacher’s workshop.
• A supplement for many mathematics courses in grades 6 – 12.
• A motivated student needing an unguided challenge.
• Your Math Counts participants – just give it to them, they will run with it.

Our approach here allows a student to enter into a situation where a certain level of difficulty is encountered, where a considerable number of tools are provided to attack that difficulty, and where a certain level of confidence is developed that persistence will be rewarded upon achieving a satisfactory resolution. What is most important, but also most difficult to achieve, is the final step in the Pólya process, the step we call TIE-TOGETHER, the inquiry about inquiry step. Inquiry-oriented teaching requires that a student engaged in exercising process skills reflect upon what has happened in a problem-solving episode and asks, “how did it happen, why did it happen, and will my technique apply in other situations?”

Fifteen problem-solving heuristics are illustrated with completely written out solutions, showing typical thought processes engaged in, followed by worksheets with brief hints given for another fifteen problems. These are followed by thirty problems, two per strategy. Finally, a large collection of a variety of problems is included separated into elementary and advanced classifications.

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These Printable Number Charts, Counting Charts, Number Paths, And Number Lines were created to help teach kindergarten-level counting and cardinality skills. Use these tools to help scaffold learning and encourage independent problem-solving as students count, write numbers, compare numbers, and answer “how many?” questions.

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2024 solar eclipse: 'New' path of totality map reveals Ohio will see less of the solar eclipse

Editor's note: This story has been updated to note NASA does not plan to change its calculations for the eclipse.

A total solar eclipse will cross North American skies on April 8, and Ohio residents will have a once-in-a-lifetime opportunity to view it. 

But now, fewer Ohioans will experience 100% darkness during the 2024 solar eclipse.

More: 'Don't wear your eclipse glasses while driving': Ohio officials share solar eclipse tips

That's because, despite modern technology, the sun's radius is difficult to measure. New data shows that the sun is a tad bigger than previously thought. These new calculations have slightly shifted the solar eclipse's path of totality – just a week before the event.

Expert John Irwin has recently published a new map with updated lines for the April 8 solar eclipse,  Forbes reported . The sun's morphing size and changes in the moon's surface mean no two eclipses are the same, but NASA's projections for the 2024 eclipse aren't changing.

Solar eclipse map: Updated path of totality in Ohio

The red lines shown below represent the original path of totality, while the orange lines show the path updated with the new data – which predicts a narrower path of totality for Ohio.

Zoom in on Ohio to see if you'll be inside the path of totality during the eclipse on April 8.

The path of totality will fall over Dublin, just a few miles north of Columbus

Ohio will get a slightly narrower path of totality by nearly a half mile on each side of the path, according to the new calculation. That shifts the fullest effects of the eclipse away from two of the state's largest cities.

Columbus remains outside the path of totality, but a few suburbs north of the city land on the path to experience complete darkness. Dublin still falls inside the path of totality, but nearby areas won't experience 100% darkness.

Riverlea now falls outside the path of totality, as does downtown Westerville, though the Otterbein University campus will straddle the path of totality.

On I-270, the exit at Cemetery Road was once inside the path of totality, but now sits just outside of it, based on the new data. 

The eclipse will shift slightly further away from Cincinnati

The new path of totality moves the fullest eclipse experience away from downtown Cincinnati, just as it does for Columbus.

In Liberty Township, for example, St. Maximilian Kolbe Parish sat inside the path of totality while nearby Center Pointe Christian Church was on the other side. Now, both fall outside the path of totality.

Downtown Canton is also further away from the full eclipse experience

Downtown Canton was never projected to be inside the path of totality, but the new data projects complete darkness to fall further away from the city. However, North Canton remains inside the zone set to experience 100% darkness.

Massillon sat comfortably inside the path of totality, but the new projections show the eclipse's shadow falling north of downtown.

Akron, Cleveland, Dayton, Toledo, other Ohio cities remain the path of totality

The new projections for the path of totality won't change the eclipse experience much for viewers close to the other big cities.

Akron, Cleveland, Dayton and Toledo will enjoy the full eclipse experience. So too will Ashland, Bucyrus, Mansfield, Marion and Sandusky.

What NASA says about the 'new' eclipse path of totality map

In speaking with the Detroit Free Press , NASA spokesman Tiernan Doyle acknowledged that even though the space agency is sticking with its original eclipse outlook in 2024, it aims to refine its eclipse predictions in the future by potentially taking into account the "topography of both the moon and the Earth."

Doyle added that there may be "a tiny but real uncertainty about the size of the sun," which could "yield an eclipse path that is slightly narrower."

And, he said, "uncertainty in the Earth’s rotation can also affect eclipse predictions on this level. Traveling toward the center of the path of totality – even a mile or two – will quickly increase the length of totality that people can see."

Whether or not the new path of totality is the correct one or the original prediction holds true, the overall difference would be minimal. As Doyle told the Free Press, "(It) would only affect cities on the very edge of the path of totality, where blanket predictions are difficult regardless – a few city blocks one way or the other could mean 20, 10, or zero seconds of totality."

Austin American-Statesman reporter Alexis Simmerman and Detroit Free Press reporter Frank Witsil contributed to this report .

Try for a high score on our Cincinnati Zoo quiz

When will solar eclipse reach your town? These maps show path's timing, how long it lasts.

Hundreds of cities in 13 u.s. states fall directly on the april 8 eclipse's path of totality as the moon blocks the sun's disc and ushers in darkness. these interactive maps offer a closer look..

Come Monday, millions of Americans from Texas to Maine will stop what they're doing to step outside and spend a few minutes gazing skyward .

Few celestial events have the power to capture our collective attention the way this upcoming total solar eclipse has managed to do. And for those making time to witness it, two questions are bound to be on their mind : Will totality reach my area and if so, how long will the resulting darkness last?

Most people across the country are bound to experience the eclipse in some form, but only 13 states fall directly on the path of totality, where the moon will appear large enough to shield all but the sun's outermost layer, the corona.

As you make your eclipse-viewing plans, these interactive maps should help you chart the time and duration for when totality will occur in cities along the path.

Solar eclipse experiment: Here's why NASA is launching 3 sounding rockets into space during the total solar eclipse

Total solar eclipse path of totality map

The 115-mile-wide path of totality will pass from southwest to northeast over portions of Mexico the United States and Canada.

Mexico's Pacific coast will be the first location in continental North America to experience totality, which will occur at about 11:07 a.m. PDT,  according to NASA .

As the moon's shadow travels northeast, totality in the U.S. will begin at 1:27 p.m. CDT in Eagle Pass, Texas. From there, the path will cut diagonally across the country before ending around 3:35 p.m. EDT in Lee, Maine.

Remember: If you plan to witness the eclipse, proper eyewear is a must until the eclipse reaches totality, then it can be viewed with the naked eye.

Here's a map of some of the larger cities in each of the 13 states on the path to show how the duration of totality will vary:

Cities, states on the path of totality

All told, nearly 500 cities in 13 U.S. states are located on the eclipse's path of totality. Here are some of the major cities in each of the 13 states:

• Dallas and San Antonio, Texas
• Idabel, Oklahoma
• Poplar Bluff, Missouri
• Little Rock, Arkansas
• Paducah, Kentucky
• Indianapolis and Evansville, Indiana
• Carbondale, Illinois
• Cleveland and Toledo, Ohio
• Buffalo, Rochester and Syracuse, New York
• Burlington, Vermont
• Lancaster, New Hampshire
• Caribou, Maine
• Erie, Pennsylvania

This interactive map provides a closer look at cities along the path, when totality will arrive there and how long totality will last:

Eclipse watch parties, festivals

Such a rare event is sure to attract skygazing tourists unlucky enough to live outside the path of totality. Fortunately, many cities that will experience the total eclipse are planning plenty of festivities for tourists and locals alike.

This map , courtesy of Kristian Campana at festivalguidesandreviews.com , includes locations of watch parties, music festivals and more all tied to the eclipse's arrival:

2024 total solar eclipse interactive map with zip code search

Perhaps the easiest way to see how the eclipse will impact your city or town, is to put your zip code into USA TODAY's interactive eclipse map .

Eric Lagatta covers breaking and trending news for USA TODAY. Reach him at [email protected]

• Solar Eclipse 2024

See the 2024 Solar Eclipse’s Path of Totality

A total solar eclipse is expected to pass through the United States on April 8, 2024, giving stargazers across the country the opportunity to view the celestial phenomenon in which the sun is completely covered by the moon.

The eclipse will enter the U.S. in Texas and exit in Maine. It is the last time a total solar eclipse will be visible in the contiguous United States until 2044.

Here's what to know about the path of the eclipse and where you can see it.

Read More : How Animals and Nature React to an Eclipse

Where can you see the total solar eclipse?

The eclipse will cross through North America, passing over parts of Mexico, the United States, and Canada. 

The eclipse will enter the United States in Texas, and travel through Oklahoma, Arkansas, Missouri, Illinois, Kentucky, Indiana, Ohio, Pennsylvania, New York, Vermont, New Hampshire, and Maine. Small parts of Tennessee and Michigan will also experience the total solar eclipse.

Much of the eclipse's visibility depends on the weather. A cloudy day could prevent visitors from seeing the spectacle altogether.

When does the solar eclipse start and end?

The solar eclipse will begin in Mexico’s Pacific coast at around 11:07 a.m. PDT. It will exit continental North America on the Atlantic coast of Newfoundland, Canada, at 5:16 p.m. NDT.

The longest duration of totality—which is when the moon completely covers the sun — will be 4 minutes, 28 seconds, near Torreón, Mexico. Most places along the path of totality will see a totality duration between 3.5 and 4 minutes.

Read More : The Eclipse Could Bring $1.5 Billion Into States on the Path of Totality

Where’s the best place to see the total solar eclipse?

The best place to witness the event is along the path of totality. Thirteen states will be along the path of totality, and many towns across the country are preparing for the deluge of visitors— planning eclipse watch parties and events in the days leading up to totality.

In Rochester, NY, the Rochester Museum and Science Center is hosting a multi-day festival that includes a range of events and activities. Russellville, Arkansas will host an event with activities including live music, science presentations, tethered hot-air balloon rides, and telescope viewings.

More Must-Reads From TIME

• Jane Fonda Champions Climate Action for Every Generation
• Passengers Are Flying up to 30 Hours to See Four Minutes of the Eclipse
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• Want Weekly Recs on What to Watch, Read, and More? Sign Up for Worth Your Time

Write to Simmone Shah at [email protected]

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The Sunday Read: ‘What Deathbed Visions Teach Us About Living’

Researchers are documenting a phenomenon that seems to help the dying, as well as those they leave behind..

By Phoebe Zerwick

Read by Samantha Desz

Produced by Jack D’Isidoro and Aaron Esposito

Narration produced by Anna Diamond and Emma Kehlbeck

Original music by Aaron Esposito

Engineered by Sophia Lanman and Sharon Kearney

Listen and follow The Daily Apple Podcasts | Spotify

Chris Kerr was 12 when he first observed a deathbed vision. His memory of that summer in 1974 is blurred, but not the sense of mystery he felt at the bedside of his dying father. Throughout Kerr’s childhood in Toronto, his father, a surgeon, was too busy to spend much time with his son, except for an annual fishing trip they took, just the two of them, to the Canadian wilderness. Gaunt and weakened by cancer at 42, his father reached for the buttons on Kerr’s shirt, fiddled with them and said something about getting ready to catch the plane to their cabin in the woods. “I knew intuitively, I knew wherever he was, must be a good place because we were going fishing,” Kerr told me.

Kerr now calls what he witnessed an end-of-life vision. His father wasn’t delusional, he believes. His mind was taking him to a time and place where he and his son could be together, in the wilds of northern Canada.

Kerr followed his father into medicine, and in the last 10 years he has hired a permanent research team that expanded studies on deathbed visions to include interviews with patients receiving hospice care at home and with their families, deepening researchers’ understanding of the variety and profundity of these visions.

There are a lot of ways to listen to ‘The Daily.’ Here’s how.

We want to hear from you. Tune in, and tell us what you think. Email us at [email protected] . Follow Michael Barbaro on X: @mikiebarb . And if you’re interested in advertising with The Daily, write to us at [email protected] .

Additional production for The Sunday Read was contributed by Isabella Anderson, Anna Diamond, Sarah Diamond, Elena Hecht, Emma Kehlbeck, Tanya Pérez and Krish Seenivasan.

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