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Qualitative vs Quantitative Research Methods & Data Analysis

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What is the difference between quantitative and qualitative?

The main difference between quantitative and qualitative research is the type of data they collect and analyze.

Quantitative research collects numerical data and analyzes it using statistical methods. The aim is to produce objective, empirical data that can be measured and expressed in numerical terms. Quantitative research is often used to test hypotheses, identify patterns, and make predictions.

Qualitative research , on the other hand, collects non-numerical data such as words, images, and sounds. The focus is on exploring subjective experiences, opinions, and attitudes, often through observation and interviews.

Qualitative research aims to produce rich and detailed descriptions of the phenomenon being studied, and to uncover new insights and meanings.

Quantitative data is information about quantities, and therefore numbers, and qualitative data is descriptive, and regards phenomenon which can be observed but not measured, such as language.

What Is Qualitative Research?

Qualitative research is the process of collecting, analyzing, and interpreting non-numerical data, such as language. Qualitative research can be used to understand how an individual subjectively perceives and gives meaning to their social reality.

Qualitative data is non-numerical data, such as text, video, photographs, or audio recordings. This type of data can be collected using diary accounts or in-depth interviews and analyzed using grounded theory or thematic analysis.

Qualitative research is multimethod in focus, involving an interpretive, naturalistic approach to its subject matter. This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them. Denzin and Lincoln (1994, p. 2)

Interest in qualitative data came about as the result of the dissatisfaction of some psychologists (e.g., Carl Rogers) with the scientific study of psychologists such as behaviorists (e.g., Skinner ).

Since psychologists study people, the traditional approach to science is not seen as an appropriate way of carrying out research since it fails to capture the totality of human experience and the essence of being human.  Exploring participants’ experiences is known as a phenomenological approach (re: Humanism ).

Qualitative research is primarily concerned with meaning, subjectivity, and lived experience. The goal is to understand the quality and texture of people’s experiences, how they make sense of them, and the implications for their lives.

Qualitative research aims to understand the social reality of individuals, groups, and cultures as nearly as possible as participants feel or live it. Thus, people and groups are studied in their natural setting.

Some examples of qualitative research questions are provided, such as what an experience feels like, how people talk about something, how they make sense of an experience, and how events unfold for people.

Research following a qualitative approach is exploratory and seeks to explain ‘how’ and ‘why’ a particular phenomenon, or behavior, operates as it does in a particular context. It can be used to generate hypotheses and theories from the data.

Qualitative Methods

There are different types of qualitative research methods, including diary accounts, in-depth interviews , documents, focus groups , case study research , and ethnography.

The results of qualitative methods provide a deep understanding of how people perceive their social realities and in consequence, how they act within the social world.

The researcher has several methods for collecting empirical materials, ranging from the interview to direct observation, to the analysis of artifacts, documents, and cultural records, to the use of visual materials or personal experience. Denzin and Lincoln (1994, p. 14)

Here are some examples of qualitative data:

Interview transcripts : Verbatim records of what participants said during an interview or focus group. They allow researchers to identify common themes and patterns, and draw conclusions based on the data. Interview transcripts can also be useful in providing direct quotes and examples to support research findings.

Observations : The researcher typically takes detailed notes on what they observe, including any contextual information, nonverbal cues, or other relevant details. The resulting observational data can be analyzed to gain insights into social phenomena, such as human behavior, social interactions, and cultural practices.

Unstructured interviews : generate qualitative data through the use of open questions.  This allows the respondent to talk in some depth, choosing their own words.  This helps the researcher develop a real sense of a person’s understanding of a situation.

Diaries or journals : Written accounts of personal experiences or reflections.

Notice that qualitative data could be much more than just words or text. Photographs, videos, sound recordings, and so on, can be considered qualitative data. Visual data can be used to understand behaviors, environments, and social interactions.

Qualitative Data Analysis

Qualitative research is endlessly creative and interpretive. The researcher does not just leave the field with mountains of empirical data and then easily write up his or her findings.

Qualitative interpretations are constructed, and various techniques can be used to make sense of the data, such as content analysis, grounded theory (Glaser & Strauss, 1967), thematic analysis (Braun & Clarke, 2006), or discourse analysis.

For example, thematic analysis is a qualitative approach that involves identifying implicit or explicit ideas within the data. Themes will often emerge once the data has been coded .

Key Features

• Events can be understood adequately only if they are seen in context. Therefore, a qualitative researcher immerses her/himself in the field, in natural surroundings. The contexts of inquiry are not contrived; they are natural. Nothing is predefined or taken for granted.
• Qualitative researchers want those who are studied to speak for themselves, to provide their perspectives in words and other actions. Therefore, qualitative research is an interactive process in which the persons studied teach the researcher about their lives.
• The qualitative researcher is an integral part of the data; without the active participation of the researcher, no data exists.
• The study’s design evolves during the research and can be adjusted or changed as it progresses. For the qualitative researcher, there is no single reality. It is subjective and exists only in reference to the observer.
• The theory is data-driven and emerges as part of the research process, evolving from the data as they are collected.

Limitations of Qualitative Research

• Because of the time and costs involved, qualitative designs do not generally draw samples from large-scale data sets.
• The problem of adequate validity or reliability is a major criticism. Because of the subjective nature of qualitative data and its origin in single contexts, it is difficult to apply conventional standards of reliability and validity. For example, because of the central role played by the researcher in the generation of data, it is not possible to replicate qualitative studies.
• Also, contexts, situations, events, conditions, and interactions cannot be replicated to any extent, nor can generalizations be made to a wider context than the one studied with confidence.
• The time required for data collection, analysis, and interpretation is lengthy. Analysis of qualitative data is difficult, and expert knowledge of an area is necessary to interpret qualitative data. Great care must be taken when doing so, for example, looking for mental illness symptoms.

Advantages of Qualitative Research

• Because of close researcher involvement, the researcher gains an insider’s view of the field. This allows the researcher to find issues that are often missed (such as subtleties and complexities) by the scientific, more positivistic inquiries.
• Qualitative descriptions can be important in suggesting possible relationships, causes, effects, and dynamic processes.
• Qualitative analysis allows for ambiguities/contradictions in the data, which reflect social reality (Denscombe, 2010).
• Qualitative research uses a descriptive, narrative style; this research might be of particular benefit to the practitioner as she or he could turn to qualitative reports to examine forms of knowledge that might otherwise be unavailable, thereby gaining new insight.

What Is Quantitative Research?

Quantitative research involves the process of objectively collecting and analyzing numerical data to describe, predict, or control variables of interest.

The goals of quantitative research are to test causal relationships between variables , make predictions, and generalize results to wider populations.

Quantitative researchers aim to establish general laws of behavior and phenomenon across different settings/contexts. Research is used to test a theory and ultimately support or reject it.

Quantitative Methods

Experiments typically yield quantitative data, as they are concerned with measuring things.  However, other research methods, such as controlled observations and questionnaires , can produce both quantitative information.

For example, a rating scale or closed questions on a questionnaire would generate quantitative data as these produce either numerical data or data that can be put into categories (e.g., “yes,” “no” answers).

Experimental methods limit how research participants react to and express appropriate social behavior.

Findings are, therefore, likely to be context-bound and simply a reflection of the assumptions that the researcher brings to the investigation.

There are numerous examples of quantitative data in psychological research, including mental health. Here are a few examples:

Another example is the Experience in Close Relationships Scale (ECR), a self-report questionnaire widely used to assess adult attachment styles .

The ECR provides quantitative data that can be used to assess attachment styles and predict relationship outcomes.

Neuroimaging data : Neuroimaging techniques, such as MRI and fMRI, provide quantitative data on brain structure and function.

This data can be analyzed to identify brain regions involved in specific mental processes or disorders.

For example, the Beck Depression Inventory (BDI) is a clinician-administered questionnaire widely used to assess the severity of depressive symptoms in individuals.

The BDI consists of 21 questions, each scored on a scale of 0 to 3, with higher scores indicating more severe depressive symptoms. 

Quantitative Data Analysis

Statistics help us turn quantitative data into useful information to help with decision-making. We can use statistics to summarize our data, describing patterns, relationships, and connections. Statistics can be descriptive or inferential.

Descriptive statistics help us to summarize our data. In contrast, inferential statistics are used to identify statistically significant differences between groups of data (such as intervention and control groups in a randomized control study).

• Quantitative researchers try to control extraneous variables by conducting their studies in the lab.
• The research aims for objectivity (i.e., without bias) and is separated from the data.
• The design of the study is determined before it begins.
• For the quantitative researcher, the reality is objective, exists separately from the researcher, and can be seen by anyone.
• Research is used to test a theory and ultimately support or reject it.

Limitations of Quantitative Research

• Context: Quantitative experiments do not take place in natural settings. In addition, they do not allow participants to explain their choices or the meaning of the questions they may have for those participants (Carr, 1994).
• Researcher expertise: Poor knowledge of the application of statistical analysis may negatively affect analysis and subsequent interpretation (Black, 1999).
• Variability of data quantity: Large sample sizes are needed for more accurate analysis. Small-scale quantitative studies may be less reliable because of the low quantity of data (Denscombe, 2010). This also affects the ability to generalize study findings to wider populations.
• Confirmation bias: The researcher might miss observing phenomena because of focus on theory or hypothesis testing rather than on the theory of hypothesis generation.

Advantages of Quantitative Research

• Scientific objectivity: Quantitative data can be interpreted with statistical analysis, and since statistics are based on the principles of mathematics, the quantitative approach is viewed as scientifically objective and rational (Carr, 1994; Denscombe, 2010).
• Useful for testing and validating already constructed theories.
• Rapid analysis: Sophisticated software removes much of the need for prolonged data analysis, especially with large volumes of data involved (Antonius, 2003).
• Replication: Quantitative data is based on measured values and can be checked by others because numerical data is less open to ambiguities of interpretation.
• Hypotheses can also be tested because of statistical analysis (Antonius, 2003).

Antonius, R. (2003). Interpreting quantitative data with SPSS . Sage.

Black, T. R. (1999). Doing quantitative research in the social sciences: An integrated approach to research design, measurement and statistics . Sage.

Braun, V. & Clarke, V. (2006). Using thematic analysis in psychology . Qualitative Research in Psychology , 3, 77–101.

Carr, L. T. (1994). The strengths and weaknesses of quantitative and qualitative research : what method for nursing? Journal of advanced nursing, 20(4) , 716-721.

Denscombe, M. (2010). The Good Research Guide: for small-scale social research. McGraw Hill.

Denzin, N., & Lincoln. Y. (1994). Handbook of Qualitative Research. Thousand Oaks, CA, US: Sage Publications Inc.

Glaser, B. G., Strauss, A. L., & Strutzel, E. (1968). The discovery of grounded theory; strategies for qualitative research. Nursing research, 17(4) , 364.

Minichiello, V. (1990). In-Depth Interviewing: Researching People. Longman Cheshire.

Punch, K. (1998). Introduction to Social Research: Quantitative and Qualitative Approaches. London: Sage

Further Information

• Designing qualitative research
• Methods of data collection and analysis
• Introduction to quantitative and qualitative research
• Checklists for improving rigour in qualitative research: a case of the tail wagging the dog?
• Qualitative research in health care: Analysing qualitative data
• Qualitative data analysis: the framework approach
• Using the framework method for the analysis of
• Qualitative data in multi-disciplinary health research
• Content Analysis
• Grounded Theory
• Thematic Analysis

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About Research Methods

This guide provides an overview of research methods, how to choose and use them, and supports and resources at UC Berkeley. 

As Patten and Newhart note in the book Understanding Research Methods , "Research methods are the building blocks of the scientific enterprise. They are the "how" for building systematic knowledge. The accumulation of knowledge through research is by its nature a collective endeavor. Each well-designed study provides evidence that may support, amend, refute, or deepen the understanding of existing knowledge...Decisions are important throughout the practice of research and are designed to help researchers collect evidence that includes the full spectrum of the phenomenon under study, to maintain logical rules, and to mitigate or account for possible sources of bias. In many ways, learning research methods is learning how to see and make these decisions."

The choice of methods varies by discipline, by the kind of phenomenon being studied and the data being used to study it, by the technology available, and more.  This guide is an introduction, but if you don't see what you need here, always contact your subject librarian, and/or take a look to see if there's a library research guide that will answer your question. 

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Without question, the most comprehensive resource available from the library is SAGE Research Methods.  HERE IS THE ONLINE GUIDE  to this one-stop shopping collection, and some helpful links are below:

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A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.

INTRODUCTION

Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

• EXAMPLE 1. Descriptive research question (quantitative research)
• - Presents research variables to be assessed (distinct phenotypes and subphenotypes)
• “BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
• RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
• EXAMPLE 2. Relationship research question (quantitative research)
• - Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
• “Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
• Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
• EXAMPLE 3. Comparative research question (quantitative research)
• - Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
• “BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
• RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
• STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
• EXAMPLE 4. Exploratory research question (qualitative research)
• - Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
• “Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
• EXAMPLE 5. Relationship research question (quantitative research)
• - Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
• “Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

• EXAMPLE 1. Working hypothesis (quantitative research)
• - A hypothesis that is initially accepted for further research to produce a feasible theory
• “As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
• “In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
• EXAMPLE 2. Exploratory hypothesis (qualitative research)
• - Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
• “We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
• “Conclusion
• Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
• EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
• “We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
• Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
• EXAMPLE 4. Statistical hypothesis (quantitative research)
• - An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
• “Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
• “Statistical Analysis
• ( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27

EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS

• EXAMPLE 1. Background, hypotheses, and aims are provided
• “Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
• “ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
• “This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
• EXAMPLE 2. Background, hypotheses, and aims are provided
• “We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
• “ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
• EXAMPLE 3. Background, aim, and hypothesis are provided
• “In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
• “This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
• “ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Conceptualization: Barroga E, Matanguihan GJ.
• Methodology: Barroga E, Matanguihan GJ.
• Writing - original draft: Barroga E, Matanguihan GJ.
• Writing - review & editing: Barroga E, Matanguihan GJ.

Quantitative Methods

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• Juwel Rana 2 , 3 , 4 ,
• Patricia Luna Gutierrez 5 &
• John C. Oldroyd 6  

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Quantitative analysis ; Quantitative research methods ; Study design

Quantitative method is the collection and analysis of numerical data to answer scientific research questions. Quantitative method is used to summarize, average, find patterns, make predictions, and test causal associations as well as generalizing results to wider populations. It allows us to quantify effect sizes, determine the strength of associations, rank priorities, and weigh the strength of evidence of effectiveness.

Introduction

This entry aims to introduce the most common ways to use numbers and statistics to describe variables, establish relationships among variables, and build numerical understanding of a topic. In general, the quantitative research process uses a deductive approach (Neuman 2014 ; Leavy 2017 ), extrapolating from a particular case to the general situation (Babones 2016 ).

In practical ways, quantitative methods are an approach to studying a research topic. In research, the...

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Babones S (2016) Interpretive quantitative methods for the social sciences. Sociology. https://doi.org/10.1177/0038038515583637

Balnaves M, Caputi P (2001) Introduction to quantitative research methods: an investigative approach. Sage, London

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Brenner PS (2020) Understanding survey methodology: sociological theory and applications. Springer, Boston

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Creswell JW (2014) Research design: qualitative, quantitative, and mixed methods approaches. Sage, London

Leavy P (2017) Research design. The Gilford Press, New York

Mertens W, Pugliese A, Recker J (2018) Quantitative data analysis, research methods: information, systems, and contexts: second edition. https://doi.org/10.1016/B978-0-08-102220-7.00018-2

Neuman LW (2014) Social research methods: qualitative and quantitative approaches. Pearson Education Limited, Edinburgh

Treiman DJ (2009) Quantitative data analysis: doing social research to test ideas. Jossey-Bass, San Francisco

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Department of Public Health, School of Health and Life Sciences, North South University, Dhaka, Bangladesh

Department of Biostatistics and Epidemiology, School of Health and Health Sciences, University of Massachusetts Amherst, MA, USA

Department of Research and Innovation, South Asia Institute for Social Transformation (SAIST), Dhaka, Bangladesh

Independent Researcher, Masatepe, Nicaragua

Patricia Luna Gutierrez

School of Behavioral and Health Sciences, Australian Catholic University, Fitzroy, VIC, Australia

John C. Oldroyd

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Ali Farazmand

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Rana, J., Gutierrez, P.L., Oldroyd, J.C. (2021). Quantitative Methods. In: Farazmand, A. (eds) Global Encyclopedia of Public Administration, Public Policy, and Governance. Springer, Cham. https://doi.org/10.1007/978-3-319-31816-5_460-1

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Quantitative methods emphasize objective measurements and the statistical, mathematical, or numerical analysis of data collected through polls, questionnaires, and surveys, or by manipulating pre-existing statistical data using computational techniques . Quantitative research focuses on gathering numerical data and generalizing it across groups of people or to explain a particular phenomenon.

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Muijs, Daniel. Doing Quantitative Research in Education with SPSS . 2nd edition. London: SAGE Publications, 2010.

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Characteristics of Quantitative Research

Your goal in conducting quantitative research study is to determine the relationship between one thing [an independent variable] and another [a dependent or outcome variable] within a population. Quantitative research designs are either descriptive [subjects usually measured once] or experimental [subjects measured before and after a treatment]. A descriptive study establishes only associations between variables; an experimental study establishes causality.

Quantitative research deals in numbers, logic, and an objective stance. Quantitative research focuses on numeric and unchanging data and detailed, convergent reasoning rather than divergent reasoning [i.e., the generation of a variety of ideas about a research problem in a spontaneous, free-flowing manner].

Its main characteristics are :

• The data is usually gathered using structured research instruments.
• The results are based on larger sample sizes that are representative of the population.
• The research study can usually be replicated or repeated, given its high reliability.
• Researcher has a clearly defined research question to which objective answers are sought.
• All aspects of the study are carefully designed before data is collected.
• Data are in the form of numbers and statistics, often arranged in tables, charts, figures, or other non-textual forms.
• Project can be used to generalize concepts more widely, predict future results, or investigate causal relationships.
• Researcher uses tools, such as questionnaires or computer software, to collect numerical data.

The overarching aim of a quantitative research study is to classify features, count them, and construct statistical models in an attempt to explain what is observed.

  Things to keep in mind when reporting the results of a study using quantitative methods :

• Explain the data collected and their statistical treatment as well as all relevant results in relation to the research problem you are investigating. Interpretation of results is not appropriate in this section.
• Report unanticipated events that occurred during your data collection. Explain how the actual analysis differs from the planned analysis. Explain your handling of missing data and why any missing data does not undermine the validity of your analysis.
• Explain the techniques you used to "clean" your data set.
• Choose a minimally sufficient statistical procedure ; provide a rationale for its use and a reference for it. Specify any computer programs used.
• Describe the assumptions for each procedure and the steps you took to ensure that they were not violated.
• When using inferential statistics , provide the descriptive statistics, confidence intervals, and sample sizes for each variable as well as the value of the test statistic, its direction, the degrees of freedom, and the significance level [report the actual p value].
• Avoid inferring causality , particularly in nonrandomized designs or without further experimentation.
• Use tables to provide exact values ; use figures to convey global effects. Keep figures small in size; include graphic representations of confidence intervals whenever possible.
• Always tell the reader what to look for in tables and figures .

NOTE:   When using pre-existing statistical data gathered and made available by anyone other than yourself [e.g., government agency], you still must report on the methods that were used to gather the data and describe any missing data that exists and, if there is any, provide a clear explanation why the missing data does not undermine the validity of your final analysis.

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Brians, Craig Leonard et al. Empirical Political Analysis: Quantitative and Qualitative Research Methods . 8th ed. Boston, MA: Longman, 2011; McNabb, David E. Research Methods in Public Administration and Nonprofit Management: Quantitative and Qualitative Approaches . 2nd ed. Armonk, NY: M.E. Sharpe, 2008; Quantitative Research Methods. Writing@CSU. Colorado State University; Singh, Kultar. Quantitative Social Research Methods . Los Angeles, CA: Sage, 2007.

Basic Research Design for Quantitative Studies

Before designing a quantitative research study, you must decide whether it will be descriptive or experimental because this will dictate how you gather, analyze, and interpret the results. A descriptive study is governed by the following rules: subjects are generally measured once; the intention is to only establish associations between variables; and, the study may include a sample population of hundreds or thousands of subjects to ensure that a valid estimate of a generalized relationship between variables has been obtained. An experimental design includes subjects measured before and after a particular treatment, the sample population may be very small and purposefully chosen, and it is intended to establish causality between variables. Introduction The introduction to a quantitative study is usually written in the present tense and from the third person point of view. It covers the following information:

• Identifies the research problem -- as with any academic study, you must state clearly and concisely the research problem being investigated.
• Reviews the literature -- review scholarship on the topic, synthesizing key themes and, if necessary, noting studies that have used similar methods of inquiry and analysis. Note where key gaps exist and how your study helps to fill these gaps or clarifies existing knowledge.
• Describes the theoretical framework -- provide an outline of the theory or hypothesis underpinning your study. If necessary, define unfamiliar or complex terms, concepts, or ideas and provide the appropriate background information to place the research problem in proper context [e.g., historical, cultural, economic, etc.].

Methodology The methods section of a quantitative study should describe how each objective of your study will be achieved. Be sure to provide enough detail to enable the reader can make an informed assessment of the methods being used to obtain results associated with the research problem. The methods section should be presented in the past tense.

• Study population and sampling -- where did the data come from; how robust is it; note where gaps exist or what was excluded. Note the procedures used for their selection;
• Data collection – describe the tools and methods used to collect information and identify the variables being measured; describe the methods used to obtain the data; and, note if the data was pre-existing [i.e., government data] or you gathered it yourself. If you gathered it yourself, describe what type of instrument you used and why. Note that no data set is perfect--describe any limitations in methods of gathering data.
• Data analysis -- describe the procedures for processing and analyzing the data. If appropriate, describe the specific instruments of analysis used to study each research objective, including mathematical techniques and the type of computer software used to manipulate the data.

Results The finding of your study should be written objectively and in a succinct and precise format. In quantitative studies, it is common to use graphs, tables, charts, and other non-textual elements to help the reader understand the data. Make sure that non-textual elements do not stand in isolation from the text but are being used to supplement the overall description of the results and to help clarify key points being made. Further information about how to effectively present data using charts and graphs can be found here .

• Statistical analysis -- how did you analyze the data? What were the key findings from the data? The findings should be present in a logical, sequential order. Describe but do not interpret these trends or negative results; save that for the discussion section. The results should be presented in the past tense.

Discussion Discussions should be analytic, logical, and comprehensive. The discussion should meld together your findings in relation to those identified in the literature review, and placed within the context of the theoretical framework underpinning the study. The discussion should be presented in the present tense.

• Interpretation of results -- reiterate the research problem being investigated and compare and contrast the findings with the research questions underlying the study. Did they affirm predicted outcomes or did the data refute it?
• Description of trends, comparison of groups, or relationships among variables -- describe any trends that emerged from your analysis and explain all unanticipated and statistical insignificant findings.
• Discussion of implications – what is the meaning of your results? Highlight key findings based on the overall results and note findings that you believe are important. How have the results helped fill gaps in understanding the research problem?
• Limitations -- describe any limitations or unavoidable bias in your study and, if necessary, note why these limitations did not inhibit effective interpretation of the results.

Conclusion End your study by to summarizing the topic and provide a final comment and assessment of the study.

• Summary of findings – synthesize the answers to your research questions. Do not report any statistical data here; just provide a narrative summary of the key findings and describe what was learned that you did not know before conducting the study.
• Recommendations – if appropriate to the aim of the assignment, tie key findings with policy recommendations or actions to be taken in practice.
• Future research – note the need for future research linked to your study’s limitations or to any remaining gaps in the literature that were not addressed in your study.

Black, Thomas R. Doing Quantitative Research in the Social Sciences: An Integrated Approach to Research Design, Measurement and Statistics . London: Sage, 1999; Gay,L. R. and Peter Airasain. Educational Research: Competencies for Analysis and Applications . 7th edition. Upper Saddle River, NJ: Merril Prentice Hall, 2003; Hector, Anestine. An Overview of Quantitative Research in Composition and TESOL . Department of English, Indiana University of Pennsylvania; Hopkins, Will G. “Quantitative Research Design.” Sportscience 4, 1 (2000); "A Strategy for Writing Up Research Results. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper." Department of Biology. Bates College; Nenty, H. Johnson. "Writing a Quantitative Research Thesis." International Journal of Educational Science 1 (2009): 19-32; Ouyang, Ronghua (John). Basic Inquiry of Quantitative Research . Kennesaw State University.

Strengths of Using Quantitative Methods

Quantitative researchers try to recognize and isolate specific variables contained within the study framework, seek correlation, relationships and causality, and attempt to control the environment in which the data is collected to avoid the risk of variables, other than the one being studied, accounting for the relationships identified.

Among the specific strengths of using quantitative methods to study social science research problems:

• Allows for a broader study, involving a greater number of subjects, and enhancing the generalization of the results;
• Allows for greater objectivity and accuracy of results. Generally, quantitative methods are designed to provide summaries of data that support generalizations about the phenomenon under study. In order to accomplish this, quantitative research usually involves few variables and many cases, and employs prescribed procedures to ensure validity and reliability;
• Applying well established standards means that the research can be replicated, and then analyzed and compared with similar studies;
• You can summarize vast sources of information and make comparisons across categories and over time; and,
• Personal bias can be avoided by keeping a 'distance' from participating subjects and using accepted computational techniques .

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Brians, Craig Leonard et al. Empirical Political Analysis: Quantitative and Qualitative Research Methods . 8th ed. Boston, MA: Longman, 2011; McNabb, David E. Research Methods in Public Administration and Nonprofit Management: Quantitative and Qualitative Approaches . 2nd ed. Armonk, NY: M.E. Sharpe, 2008; Singh, Kultar. Quantitative Social Research Methods . Los Angeles, CA: Sage, 2007.

Limitations of Using Quantitative Methods

Quantitative methods presume to have an objective approach to studying research problems, where data is controlled and measured, to address the accumulation of facts, and to determine the causes of behavior. As a consequence, the results of quantitative research may be statistically significant but are often humanly insignificant.

Some specific limitations associated with using quantitative methods to study research problems in the social sciences include:

• Quantitative data is more efficient and able to test hypotheses, but may miss contextual detail;
• Uses a static and rigid approach and so employs an inflexible process of discovery;
• The development of standard questions by researchers can lead to "structural bias" and false representation, where the data actually reflects the view of the researcher instead of the participating subject;
• Results provide less detail on behavior, attitudes, and motivation;
• Researcher may collect a much narrower and sometimes superficial dataset;
• Results are limited as they provide numerical descriptions rather than detailed narrative and generally provide less elaborate accounts of human perception;
• The research is often carried out in an unnatural, artificial environment so that a level of control can be applied to the exercise. This level of control might not normally be in place in the real world thus yielding "laboratory results" as opposed to "real world results"; and,
• Preset answers will not necessarily reflect how people really feel about a subject and, in some cases, might just be the closest match to the preconceived hypothesis.

Research Tip

Finding Examples of How to Apply Different Types of Research Methods

SAGE publications is a major publisher of studies about how to design and conduct research in the social and behavioral sciences. Their SAGE Research Methods Online and Cases database includes contents from books, articles, encyclopedias, handbooks, and videos covering social science research design and methods including the complete Little Green Book Series of Quantitative Applications in the Social Sciences and the Little Blue Book Series of Qualitative Research techniques. The database also includes case studies outlining the research methods used in real research projects. This is an excellent source for finding definitions of key terms and descriptions of research design and practice, techniques of data gathering, analysis, and reporting, and information about theories of research [e.g., grounded theory]. The database covers both qualitative and quantitative research methods as well as mixed methods approaches to conducting research.

SAGE Research Methods Online and Cases

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A Comprehensive Guide to Quantitative Research: Types, Characteristics, Methods & Examples

Step into the fascinating world of quantitative research, where numbers reveal extraordinary insights!

By gathering and studying data in a systematic way, quantitative research empowers us to understand our ever-changing world better. It helps understand a problem or an already-formed hypothesis by generating numerical data. The results don’t end here, as you can process these numbers to get actionable insights that aid decision-making.

You can use quantitative research to quantify opinions, behaviors, attitudes, and other definitive variables related to the market, customers, competitors, etc. The research is conducted on a larger sample population to draw predictive, average, and pattern-based insights.

Here, we delve into the intricacies of this research methodology, exploring various quantitative methods, their advantages, and real-life examples that showcase their impact and relevance.

Ready to embark on a journey of discovery and knowledge? Let’s go!

What Is Quantitative Research?

Quantitative research is a method that uses numbers and statistics to test theories about customer attitudes and behaviors. It helps researchers gather and analyze data systematically to gain valuable insights and draw evidence-based conclusions about customer preferences and trends.

Researchers use online surveys , questionnaires , polls , and quizzes to question a large number of people to obtain measurable and bias-free data.

In technical terms, quantitative research is mainly concerned with discovering facts about social phenomena while assuming a fixed and measurable reality.

Offering numbers and stats-based insights, this research methodology is a crucial part of primary research and helps understand how well an organizational decision is going to work out.

Let’s consider an example.

Suppose your qualitative analysis shows that your customers are looking for social media-based customer support . In that case, quantitative analysis will help you see how many of your customers are looking for this support.

If 10% of your customers are looking for such a service, you might or might not consider offering this feature. But, if 40% of your regular customers are seeking support via social media, then it is something you just cannot overlook.

Characteristics of Quantitative Research

Quantitative research clarifies the fuzziness of research data from qualitative research analysis. With numerical insights, you can formulate a better and more profitable business decision.

Hence, quantitative research is more readily contestable, sharpens intelligent discussion, helps you see the rival hypotheses, and dynamically contributes to the research process.

Let us have a quick look at some of its characteristics.

• Measurable Variables

The data collection methods in quantitative research are structured and contain items requiring measurable variables, such as age, number of family members, salary range, highest education, etc.

These structured data collection methods comprise polls, surveys, questionnaires, etc., and may have questions like the ones shown in the following image:

As you can see, all the variables are measurable. This ensures that the research is in-depth and provides less erroneous data for reliable, actionable insights.

• Sample Size

No matter what data analysis methods for quantitative research are being used, the sample size is kept such that it represents the target market.

As the main aim of the research methodology is to get numerical insights, the sample size should be fairly large. Depending on the survey objective and scope, it might span hundreds of thousands of people.

• Normal Population Distribution

To maintain the reliability of a quantitative research methodology, we assume that the population distribution curve is normal.

This type of population distribution curve is preferred over a non-normal distribution as the sample size is large, and the characteristics of the sample vary with its size.

This requires adhering to the random sampling principle to avoid the researcher’s bias in result interpretation. Any bias can ruin the fairness of the entire process and defeats the purpose of research.

• Well-Structured Data Representation

Data analysis in quantitative research produces highly structured results and can form well-defined graphical representations. Some common examples include tables, figures, graphs, etc., that combine large blocks of data.

This way, you can discover hidden data trends, relationships, and differences among various measurable variables. This can help researchers understand the survey data and formulate actionable insights for decision-making.

• Predictive Outcomes

Quantitative analysis of data can also be used for estimations and prediction outcomes. You can construct if-then scenarios and analyze the data for the identification of any upcoming trends or events.

However, this requires advanced analytics and involves complex mathematical computations. So, it is mostly done via quantitative research tools that come with advanced analytics capabilities.

8 Best Practices to Conduct Quantitative Research

Here are some best practices to keep in mind while conducting quantitative research:

1. Define Research Objectives

There can be many ways to collect data via quantitative research methods that are chosen as per the research objective and scope. These methods allow you to build your own observations regarding any hypotheses – unknown, entirely new, or unexplained. 

You can hypothesize a proof and build a prediction of outcomes supporting the same. You can also create a detailed stepwise plan for data collection, analysis, and testing. 

Below, we explore quantitative research methods and discuss some examples to enhance your understanding of them.

2. Keep Your Questions Simple

The surveys are meant to reach people en-masse, and that includes a wide demographic range with recipients from all walks of life. Asking simple questions will ensure that they grasp what’s being asked easily.

Read More: Proven Tips to Avoid Leading and Loaded Questions in Your Survey

3. Develop a Solid Research Design

Choose an appropriate research design that aligns with your objectives, whether it’s experimental, quasi-experimental, or correlational. You also need to pay attention to the sample size and sampling technique such that it represents the target population accurately.

4. Use Reliable & Valid Instruments

It’s crucial to select or develop measurement instruments such as questionnaires, scales, or tests that have been validated and are reliable. Before proceeding with the main study, pilot-test these instruments on a small sample to assess their effectiveness and make any necessary improvements.

5. Ensure Data Quality

Implement data collection protocols to minimize errors and bias during data gathering. Double-check data entries and cleaning procedures to eliminate any inconsistencies or missing values that may affect the accuracy of your results. For instance, you might regularly cross-verify data entries to identify and correct any discrepancies.

6. Employ Appropriate Data Analysis Techniques

Select statistical methods that match the nature of your data and research questions. Whether it’s regression analysis, t-tests, ANOVA, or other techniques, using the right approach is important for drawing meaningful conclusions. Utilize software tools like SPSS or R for data analysis to ensure the accuracy and reproducibility of your findings.

7. Interpret Results Objectively

Present your findings in a clear and unbiased manner. Avoid making unwarranted causal claims, especially in correlational studies. Instead, focus on describing the relationships and patterns observed in your data.

8. Address Ethical Considerations

Prioritize ethical considerations throughout your research process. Obtain informed consent from participants, ensuring their voluntary participation and confidentiality of data. Comply with ethical guidelines and gain approval from a governing body if necessary.

Read More: How to Find Survey Participants & Respondents

Types of Quantitative Research Methods

Quantitative research is usually conducted using two methods. They are-

• Primary quantitative research methods
• Secondary quantitative research methods

1. Primary Methods

Primary quantitative research is the most popular way of conducting market research. The differentiating factor of this method is that the researcher relies on collecting data firsthand instead of relying on data collected from previous research.

There are multiple types of primary quantitative research. They can be distinguished based on three distinctive aspects, which are:

A. Techniques & Types of Studies:

• Survey Research

Surveys are the easiest, most common, and one of the most sought-after quantitative research techniques. The main aim of a survey is to widely gather and describe the characteristics of a target population or customers. Surveys are the foremost quantitative method preferred by both small and large organizations.

They help them understand their customers, products, and other brand offerings in a proper manner.

Surveys can be conducted using various methods, such as online polls, web-based surveys, paper questionnaires, phone calls, or face-to-face interviews. Survey research allows organizations to understand customer opinions, preferences, and behavior, making it crucial for market research and decision-making.

You can watch this quick video to learn more about creating surveys.

Surveys are of two types:

• Cross-Sectional Surveys Cross-sectional surveys are used to collect data from a sample of the target population at a specific point in time. Researchers evaluate various variables simultaneously to understand the relationships and patterns within the data.
• Cross-sectional surveys are popular in retail, small and medium-sized enterprises (SMEs), and healthcare industries, where they assess customer satisfaction, market trends, and product feedback.
• Longitudinal Surveys Longitudinal surveys are conducted over an extended period, observing changes in respondent behavior and thought processes.
• Researchers gather data from the same sample multiple times, enabling them to study trends and developments over time. These surveys are valuable in fields such as medicine, applied sciences, and market trend analysis.

Surveys can be distributed via various channels. Some of the most popular ones are listed below:

• Email: Sending surveys via email is a popular and effective method. People recognize your brand, leading to a higher response rate. With ProProfs Survey Maker’s in-mail survey-filling feature, you can easily send out and collect survey responses.
• Embed on a website: Boost your response rate by embedding the survey on your website. When visitors are already engaged with your brand, they are more likely to take the survey.
• Social media: Take advantage of social media platforms to distribute your survey. People familiar with your brand are likely to respond, increasing your response numbers.
• QR codes: QR codes store your survey’s URL, and you can print or publish these codes in magazines, signs, business cards, or any object to make it easy for people to access your survey.
• SMS survey: Collect a high number of responses quickly with SMS surveys. It’s a time-effective way to reach your target audience.

Read More: 24 Different Types of Survey Methods With Examples

2. Correlational Research:

Correlational research aims to establish relationships between two or more variables.

Researchers use statistical analysis to identify patterns and trends in the data, but it does not determine causality between the variables. This method helps understand how changes in one variable may impact another.

Examples of correlational research questions include studying the relationship between stress and depression, fame and money, or classroom activities and student performance.

3. Causal-Comparative Research:

Causal-comparative research, also known as quasi-experimental research, seeks to determine cause-and-effect relationships between variables.

Researchers analyze how an independent variable influences a dependent variable, but they do not manipulate the independent variable. Instead, they observe and compare different groups to draw conclusions.

Causal-comparative research is useful in situations where it’s not ethical or feasible to conduct true experiments.

Examples of questions for this type of research include analyzing the effect of training programs on employee performance, studying the influence of customer support on client retention, investigating the impact of supply chain efficiency on cost reduction, etc.

4. Experimental Research:

Experimental research is based on testing theories to validate or disprove them. Researchers conduct experiments and manipulate variables to observe their impact on the outcomes.

This type of research is prevalent in natural and social sciences, and it is a powerful method to establish cause-and-effect relationships. By randomly assigning participants to experimental and control groups, researchers can draw more confident conclusions.

Examples of experimental research include studying the effectiveness of a new drug, the impact of teaching methods on student performance, or the outcomes of a marketing campaign.

B. Data collection methodologies

After defining research objectives, the next significant step in primary quantitative research is data collection. This involves using two main methods: sampling and conducting surveys or polls.

Sampling methods:

In quantitative research, there are two primary sampling methods: Probability and Non-probability sampling.

Probability Sampling

In probability sampling, researchers use the concept of probability to create samples from a population. This method ensures that every individual in the target audience has an equal chance of being selected for the sample.

There are four main types of probability sampling:

• Simple random sampling: Here, the elements or participants of a sample are selected randomly, and this technique is used in studies that are conducted over considerably large audiences. It works well for large target populations.
• Stratified random sampling: In this method, the entire population is divided into strata or groups, and the sample members get chosen randomly from these strata only. It is always ensured that different segregated strata do not overlap with each other.
• Cluster sampling: Here, researchers divide the population into clusters, often based on geography or demographics. Then, random clusters are selected for the sample.
• Systematic sampling: In this method, only the starting point of the sample is randomly chosen. All the other participants are chosen using a fixed interval. Researchers calculate this interval by dividing the size of the study population by the target sample size.

Non-probability Sampling

Non-probability sampling is a method where the researcher’s knowledge and experience guide the selection of samples. This approach doesn’t give all members of the target population an equal chance of being included in the sample.

There are five non-probability sampling models:

• Convenience sampling: The elements or participants are chosen on the basis of their nearness to the researcher. The people in close proximity can be studied and analyzed easily and quickly, as there is no other selection criterion involved. Researchers simply choose samples based on what is most convenient for them.
• Consecutive sampling: Similar to convenience sampling, researchers select samples one after another over a significant period. They can opt for a single participant or a group of samples to conduct quantitative research in a consecutive manner for a significant period of time. Once this is over, they can conduct the research from the start.
• Quota sampling: With quota sampling, researchers use their understanding of target traits and personalities to form groups (strata). They then choose samples from each stratum based on their own judgment.
• Snowball sampling: This method is used where the target audiences are difficult to contact and interviewed for data collection. Researchers start with a few participants and then ask them to refer others, creating a snowball effect.
• Judgmental sampling: In judgmental sampling, researchers rely solely on their experience and research skills to handpick samples that they believe will be most relevant to the study.

Read More: Data Collection Methods: Definition, Types & Examples

C. Data analysis techniques

To analyze the quantitative data accurately, you’ll need to use specific statistical methods such as:

• SWOT Analysis: This stands for Strengths, Weaknesses, Opportunities, and Threats analysis. Organizations use SWOT analysis to evaluate their performance internally and externally. It helps develop effective improvement strategies.
• Conjoint Analysis: This market research method uncovers how individuals make complex purchasing decisions. It involves considering trade-offs in their daily activities when choosing from a list of product/service options.
• Cross-tabulation: A preliminary statistical market analysis method that reveals relationships, patterns, and trends within various research study parameters.
• TURF Analysis: Short for Totally Unduplicated Reach and Frequency Analysis, this method helps analyze the reach and frequency of favorable communication sources. It provides insights into the potential of a target market.
• By using these statistical techniques and inferential statistics methods like confidence intervals and margin of error, you can draw meaningful insights from your primary quantitative research that you can use in making informed decisions.

II. Secondary Quantitative Research Methods

• Secondary quantitative research, also known as desk research, is a valuable method that uses existing data, called secondary data.
• Instead of collecting new data, researchers analyze and combine already available information to enhance their research. This approach involves gathering quantitative data from various sources such as the internet, government databases, libraries, and research reports.
• Secondary quantitative research plays a crucial role in validating data collected through primary quantitative research. It helps reinforce or challenge existing findings.

Here are five commonly used secondary quantitative research methods:

A. Data Available on the Internet:

The Internet has become a vast repository of data, making it easier for researchers to access a wealth of information. Online databases, websites, and research repositories provide valuable quantitative data for researchers to analyze and validate their primary research findings.

B. Government and Non-Government Sources:

Government agencies and non-government organizations often conduct extensive research and publish reports. These reports cover a wide range of topics, providing researchers with reliable and comprehensive data for quantitative analysis.

C. Public Libraries:

While less commonly used in the digital age, public libraries still hold valuable research reports, historical data, and publications that can contribute to quantitative research.

D. Educational Institutions:

Educational institutions frequently conduct research on various subjects. Their research reports and publications can serve as valuable sources of information for researchers, validating and supporting primary quantitative research outcomes.

E. Commercial Information Sources:

Commercial sources such as local newspapers, journals, magazines, and media outlets often publish relevant data on economic trends, market research, and demographic analyses. Researchers can access this data to supplement their own findings and draw better conclusions.

Advantages of Quantitative Research Methods

Quantitative research data is often standardized and can be easily used to generalize findings for making crucial business decisions and uncover insights to supplement the qualitative research findings.

Here are some core benefits this research methodology offers.

Direct Result Comparison

As the studies can be replicated for different cultural settings and different times, even with different groups of participants, they tend to be extremely useful. Researchers can compare the results of different studies in a statistical manner and arrive at comprehensive conclusions for a broader understanding.

Replication

Researchers can repeat the study by using standardized data collection protocols over well-structured data sets. They can also apply tangible definitions of abstract concepts to arrive at different conclusions for similar research objectives with minor variations.

Large Samples

As the research data comes from large samples, the researchers can process and analyze the data via highly reliable and consistent analysis procedures. They can arrive at well-defined conclusions that can be used to make the primary research more thorough and reliable.

Hypothesis Testing

This research methodology follows standardized and established hypothesis testing procedures. So, you have to be careful while reporting and analyzing your research data , and the overall quality of results gets improved.

Proven Examples of Quantitative Research Methods

Below, we discuss two excellent examples of quantitative research methods that were used by highly distinguished business and consulting organizations. Both examples show how different types of analysis can be performed with qualitative approaches and how the analysis is done once the data is collected.

1. STEP Project Global Consortium / KPMG 2019 Global Family Business survey

This research utilized quantitative methods to identify ways that kept the family businesses sustainably profitable with time.

The study also identified the ways in which the family business behavior changed with demographic changes and had “why” and “how” questions. Their qualitative research methods allowed the KPMG team to dig deeper into the mindsets and perspectives of the business owners and uncover unexpected research avenues as well.

It was a joint effort in which STEP Project Global Consortium collected 26 cases, and KPMG collected 11 cases.

The research reached the stage of data analysis in 2020, and the analysis process spanned over 4 stages.

The results, which were also the reasons why family businesses tend to lose their strength with time, were found to be:

• Family governance
• Family business legacy

2. EY Seren Teams Research 2020

This is yet another commendable example of qualitative research where the EY Seren Team digs into the unexplored depths of human behavior and how it affected their brand or service expectations.

The research was done across 200+ sources and involved in-depth virtual interviews with people in their homes, exploring their current needs and wishes. It also involved diary studies across the entire UK customer base to analyze human behavior changes and patterns.

The study also included interviews with professionals and design leaders from a wide range of industries to explore how COVID-19 transformed their industries. Finally, quantitative surveys were conducted to gain insights into the EY community after every 15 days.

The insights and results were:

• A culture of fear, daily resilience, and hopes for a better world and a better life – these were the macro trends.
• People felt massive digitization to be a resourceful yet demanding aspect as they have to adapt every day.
• Some people wished to have a new world with lots of possibilities, and some were looking for a new purpose.

Enhance Your Quantitative Research With Cutting-Edge Software

While no single research methodology can produce 100% reliable results, you can always opt for a hybrid research method by opting for the methods that are most relevant to your objective.

This understanding comes gradually as you learn how to implement the correct combination of qualitative and quantitative research methods for your research projects. For the best results, we recommend investing in smart, efficient, and scalable research tools that come with delightful reporting and advanced analytics to make every research initiative a success.

These software tools, such as ProProfs Survey Maker, come with pre-built survey templates and question libraries and allow you to create a high-converting survey in just a few minutes.

So, choose the best research partner, create the right research plan, and gather insights that drive sustainable growth for your business.

About the author

Emma David is a seasoned market research professional with 8+ years of experience. Having kick-started her journey in research, she has developed rich expertise in employee engagement, survey creation and administration, and data management. Emma believes in the power of data to shape business performance positively. She continues to help brands and businesses make strategic decisions and improve their market standing through her understanding of research methodologies.

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Open Access

Peer-reviewed

Research Article

YouTube and the implementation and discontinuation of the oral contraceptive pill: A mixed-method content analysis

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliations Institute for Medical Sociology and Rehabilitation Science, Charité Universitätsmedizin Berlin, Berlin, Berlin, Germany, Medical Faculty, Institute of Medical Sociology, Institute of Medical Sociology (IMS), Martin Luther University Halle Wittenberg, Interdisciplinary Centre for Health Sciences, Halle (Saale), Saxony-Anhalt, Germany

Roles Formal analysis, Investigation, Methodology, Writing – review & editing

Affiliation Osnabrück University, School of Human Sciences, Osnabrück, Lower Saxony, Germany

Roles Formal analysis

Affiliation Medical Faculty, Institute of Medical Sociology, Institute of Medical Sociology (IMS), Martin Luther University Halle Wittenberg, Interdisciplinary Centre for Health Sciences, Halle (Saale), Saxony-Anhalt, Germany

Roles Supervision

Affiliation Institute for Medical Sociology and Rehabilitation Science, Charité Universitätsmedizin Berlin, Berlin, Berlin, Germany

Affiliation Institute for Gender Research in Medicine (GiM), Charité Universitätsmedizin Berlin, Berlin, Berlin, Germany

Affiliations Medical Faculty, Institute of Medical Sociology, Institute of Medical Sociology (IMS), Martin Luther University Halle Wittenberg, Interdisciplinary Centre for Health Sciences, Halle (Saale), Saxony-Anhalt, Germany, Department of Sport and Health Sciences, Technical University of Munich, Munich, Bavaria, Germany

• Jana Niemann, 
• Lea Wicherski, 
• Lisa Glaum, 
• Liane Schenk, 
• Getraud Stadler, 
• Matthias Richter

• Published: May 24, 2024
• https://doi.org/10.1371/journal.pone.0302316
• Peer Review
• Reader Comments

Women living in high-quality healthcare systems are more likely to use oral contraceptives at some point in their lives. Research findings have sparked controversial discussions about contraception in the scientific community and the media, potentially leading to higher rates of method discontinuation. Understanding the underlying motives for method discontinuation is crucial for reproductive health equity and future programming interventions. To address this question, this study aims to explore women’s experiences of oral contraceptive use and discontinuation on YouTube.

A concurrent explanatory mixed-methods design was used to conduct content analysis of German YouTube videos. The information from 175 videos of 158 individuals was extracted through quantitative descriptive content analysis. Twenty-one individuals were included in the qualitative content analysis.

The body was a recurring theme in the pill biographies. Women described, for example, bodily sensations as reasons for taking and stopping the pill. They also described positive and negative side effects while taking the pill and after stopping. The most common side effects of taking the pill mentioned by YouTubers were mood swings (76/158), weight gain (45/158), headaches (33/158), and depressed mood (45/158). The symptoms after discontinuation reported most were facial skin impurities (108/158), decreased mood swings (47/158), hair loss (42/158), and weight loss (36/158). Overall, women overwhelmingly rated their discontinuation experience as positive (87/91).

Conclusions

The study identified key symptoms of oral contraceptive initiation and discontinuation by portraying the experiences of female YouTubers, adding valuable insights to the understanding of method initiation and discontinuation. Further research is needed to explore women’s personal experiences with method discontinuation beyond the YouTube platform.

Citation: Niemann J, Wicherski L, Glaum L, Schenk L, Stadler G, Richter M (2024) YouTube and the implementation and discontinuation of the oral contraceptive pill: A mixed-method content analysis. PLoS ONE 19(5): e0302316. https://doi.org/10.1371/journal.pone.0302316

Editor: Deidre Pretorius, Wits University: University of the Witwatersrand Johannesburg, SOUTH AFRICA

Received: January 13, 2024; Accepted: April 1, 2024; Published: May 24, 2024

Copyright: © 2024 Niemann et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Full data are available from the corresponding author or the Institute for Medical Sociology at the Martin-Luther-University Halle-Wittenberg ( [email protected] ) upon reasonable request.

Funding: This publication was supported by the Open Access Publication Fund of the Martin Luther University Halle-Wittenberg. The funders did not influence the data analysis and the results.

Competing interests: The authors have declared that no competing interests exist.

Abbreviations: IUD, Intrauterine device; OCP, Oral contraceptive pill; SNSs, Social networking sites; VTE, Venous thromboembolism

Introduction

The oral contraceptive pill (OCP) is a crucial contraceptive in high-quality healthcare systems in Northern and Western Europe [ 1 – 3 ]. Since its introduction 60 years ago, women have continued to report on the side effects of the pill [ 4 ]. Recent research has supported these claims, particularly regarding associations with side effects such as depression or venous thromboembolism (VTE) risk (e.g. [ 5 – 10 ]). However, most of these studies have reported associations, not causality. This has led to increasing criticism, especially by mainstream media [ 2 , 11 – 13 ].

The pill and mainstream media–a problematic relationship?

History of the relationship between the pill and mainstream media..

The dynamic between mainstream media and the OCP has had a long history: women’s right to sexual self-determination and the OCP’s side effects have been discussed in the media for more than half a century [ 14 , 15 ]. An important example is the “pill scare” phenomenon of 1995 [ 16 – 18 ], focusing on high-income countries. In this case, the dissemination and interpretation of scientific research regarding the risk of VTE associated with the OCP led to an increased number of discontinuations [ 16 ]. This was followed by individual contraceptive use and increased unintended pregnancies and abortions (e.g. in New Zealand [ 17 ], Britain [ 15 ], and Norway [ 18 ]). Media-critical discourse continued to emphasize the increased risk of VTE in the 2000s and early 2010s [ 15 ], while ignoring studies that found no increased risk [ 15 ]. This stance was also taken up in the OCP report [ 11 ] in Germany in 2015, which lacked scientific rigor [ 19 ]. The authors concluded there was a higher risk of thrombosis with the more modern 3rd and 4th generation OCPs. This was further disseminated by the media [ 20 – 22 ].

In 2016 and 2017, the media focused on the findings of increased risk of depression [ 23 , 24 ], based on two Danish studies [ 9 , 25 ]. These studies were, however, criticized in the scientific community due to methodological weaknesses [ 24 ]. Bitzer (2017), for example, criticized the lack of sensitivity analysis and questioned the biological plausibility [ 24 ]. Women shared their personal experiences with the OCP during this wave of OCP-skepticism under the #MyPillStory on social networking sites (SNSs) [ 26 , 27 ]. The VTE risk associated with the OCP was compared to that associated with the Vaxzervria vaccine (formerly COVID-19 Vaccine AstraZeneca) during the SARS-CoV-19 crisis. This is a difficult comparison because the VTE associated with OCPs is deep vein thrombosis and pulmonary embolism, whereas the VTE risk associated with the AstraZeneca vaccine is cerebral venous sinus thrombosis [ 13 ].

In summary, the media discussion of OCPs has underrepresented studies that do not show correlations with adverse side effects and have often failed to distinguish between absolute and relative risks [ 15 , 23 ]. The scientific analysis and evaluation of online contraceptive information has, therefore, become particularly important.

Researching SNSs and hormonal contraception.

The relationship between media journalism and healthcare decision-making has increased significantly with the advent of the Internet [ 14 , 28 ]. Greater access to online resources and SNSs has expanded the range of information available to women and increased their autonomy to choose contraception [ 13 , 14 ]. Hence, they have emerged as powerful tools for health communication.

This increase has also necessitated an exploration of the content, narratives, and quality of online information regarding (hormonal) contraception. Vieth et al. (2021) found that the internet was the most common source of contraceptive information among German women [ 29 ]. Studies, for instance, researched the experiences of birth control on YouTube [ 30 – 33 ], TikTok [ 34 , 35 ], and Reddit [ 36 ]. An analysis of German SNSs’ contraception content on YouTube, Instagram, and TikTok found clear shortcomings in the quality and completeness of information on these sites [ 37 ]. Additionally, a study by Alves and colleagues [ 38 ] found that most of the websites mentioning the VTE risk associated with OCPs do not refer to information from accredited health agency sources. In terms of health communication science, so-called health laypeople (users of a contraceptive method) can disseminate information on the Internet [ 39 ]. Döring et al. (2023) showed that most German contraceptive content on YouTube, Instagram, and TikTok was uploaded by health laypeople, sharing personal contraception stories [ 37 ].

Informed choice regarding contraceptive methods is an important component of the Sexual and Reproductive Justice Framework [ 26 , 40 ]. Knowledge and information can contribute to achieving justice through increased reproductive agency and contraceptive choice [ 26 ]. However, the biased media attention and misinformation might lead to higher discontinuation rates among OCP users.

OCP discontinuation.

Contraceptive discontinuation can be defined as “ starting contraceptive use and then stopping for any reason while still at risk of an unintended pregnancy ” [ 41 ]. A German study on the knowledge and perceptions about OCPs among young women showed that 64.5% (n = 1480) of those who used OCPs at some point discontinued the method [ 29 ]. Simmons et al. examined the cessation of contraceptive methods as part of a person’s Contraceptive Journey [ 42 ]. They defined key factors contributing to this decision: physiological factors, values, experiences, circumstances, and relationships (e.g. family, (sex) partners, friends, healthcare professionals). The discontinuation of OCPs deprives the body of an external source of artificial progesterone and estrogen, resulting in a change in the hormone levels in the body [ 43 , 44 ]. Current medical research on OCP discontinuation is limited to fertility restoration [ 45 , 46 ], fecundability [ 44 ], cycle characteristics [ 45 , 47 ], and reasons for discontinuation [ 29 , 42 , 48 ].

Contributing to the narrative of OCP discontinuation, Kissling explored posts of individual experiences on blogs and websites through a postfeminist lens [ 49 ]. Furthermore, Döring conducted a content analysis of German posts about the OCP on TikTok and YouTube [ 23 ]. She was interested in who the authors of the posts were, what the messages were about the OCP, and what the audience’s reactions were. She found that most of the posts on YouTube came from health laypeople. She characterizes them as “pill-weary women” who give autobiographical accounts of taking and stopping the OCP. Viewers’ reactions to these posts are mostly very positive, with many views and likes, very few dislikes, and lots of friendly comments. Adding to this, a recent study on birth control content on YouTube found that most women in 50 videos talked about their discontinuation experience with the OCP: the main outcomes after discontinuation were worsened acne (22%), improved mood (18%), cycle irregularities (14%), and increased energy (14%) [ 33 ].

However, the health consequences of discontinuing OCPs generally and on social media have not been adequately studied in the German context. There is also, as noted by Inoue et al., a lack of research on women’s own experiences after stopping OCPs [ 48 ].

Content analysis objectives and research questions

YouTube has established itself since 2005 as a way for individuals to share information and present themselves online. It is a video-sharing platform that is constantly changing [ 50 ]. Based on Döring’s and Pfender and Devlin’s analyses, YouTube videos uploaded by health laypeople, provide an opportunity to scientifically examine these personal experiences and determine the health consequences of initiating and discontinuing OCPs [ 33 , 39 ].

The overall objective of this content analysis was to investigate the personal physiological and psychological changes and lived experiences of German-speaking YouTubers after initiation and discontinuation of OCP treatment. We, therefore, aim to examine

• the reasons for starting and discontinuing the use of the OCP,
• to document any side effects experienced during and after use, and
• how the women describe their history with the OCP.

The study follows the Open Science movement, i.e. the pre-registration, and all data are stored on the Open Science Foundation server ( https://osf.io/fekdh/ ). It was designed as an (almost) simultaneous exploratory mixed-methods content analysis [ 51 ]. The quantitative component was primarily used to present overall video characteristics and estimates of video content data. The qualitative component explored YouTubers’ perceptions and beliefs as an in-depth analysis to complement the quantitative research. The qualitative and quantitative research strands were initially analyzed separately and then brought together for the interpretation and presentation of the results.

YouTube was initially searched from July 20 to 23, 2021. An updated search was performed on May 5, 2023. The internet browser and cookies history were cleared before the search to avoid biases from our laptop. The sample was examined by using common searches for videos of German-speaking women who explained their personal experiences with the discontinuation of the OCP. YouTube was searched using the autofill feature in the search bar (which uses an algorithm influenced by users’ popular searches to automatically fill search queries with root words) [ 52 ]. The following translated search terms were used: “stop taking the pill,” “stop taking the pill experience,” “discontinuation of the pill,” and “discontinuation of the pill experience” (the exact German terms are provided in [ S1 Table ]). This search was performed following previous YouTube analyses (e.g. [ 50 , 52 , 53 ]). The videos were sorted by the relevance filter (= year). All videos were included for each search term. They were then checked for duplicates.

Only videos that met our inclusion criteria, as shown in Table 1 , were included.

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

https://doi.org/10.1371/journal.pone.0302316.t001

If a YouTuber repeatedly uploaded more than one video, two to three videos were included: The first uploaded video (most likely to contain relevant information about the reasons for discontinuation or duration of OCP use) and the second and/or last uploaded video (probably the most recent version regarding immediate health consequences). If a YouTube video was uploaded with two women talking about their experiences, both individuals were included in the study. Different personal identifiers (see ethics) were assigned.

Fig 1 shows the flowchart of the search. A total of 1344 videos were initially collected by JN. After removing all duplicates, 591 videos were reviewed by JN and LW. After removing an additional 416 videos, a final number of 175 videos from 158 YouTubers were included in the sample for quantitative content analysis. All individuals could be identified as female.

https://doi.org/10.1371/journal.pone.0302316.g001

Hereinafter, 18 videos were included as an initial sample for the qualitative content analysis. These were selected by JN and LW after reviewing all 175 videos, based on stratification factors, to represent the variety of experiences of the study sample:

• reasons for initiation and discontinuation,
• length of initiation,
• age at initiation and discontinuation, and
• experienced side effects during intake and after discontinuation.

After JN and LW coded the initial sample, three additional videos were included to reach the point of data saturation [ 54 ]. This resulted in a total qualitative sample of 21 videos.

Procedure and analysis of the content analysis

The uploaded videos (audio and text presentation) and the person(s) who reported on their personal experiences with stopping the OCP on the online platform YouTube were the units of analysis for the media content.

Procedure and analysis of the quantitative content analysis.

A predefined, theoretically driven codebook ( S1 File ) was developed. The quantitative content analysis consisted of coding content data related to the video (e.g. V001) and the person(s) reporting their experience (e.g. P001):

• Typical YouTube video characteristics , including posting date, video length, number of views, likes, and comments.
• General content data regarding the OCP persistence and discontinuation , such as the time of video recording after discontinuing the OCP (weeks), length of OCP persistence (years), age at initiation and OCP discontinuation, second discontinuation, reasons for initiation and discontinuation (0 = not mentioned, 1 = mentioned), and current contraceptive method (0 = not mentioned, 1 = mentioned).
• Content data regarding the OCP implementation , including the mention (0 = not mentioned, 1 = mentioned) of improvements (e.g. facial skin) and side effects (e.g. migraine).
• Content data regarding the OCP discontinuation , including the mention (0 = not mentioned, 1 = mentioned) of the physiological and psychological changes (e.g. mood swings).

The translated codebook is available as ( S1 File ). JN and LG independently assessed the intercoder reliability of the codebooks based on 17 randomly selected videos from the sample. The Krippen-Dorff’s Alpha reliability coefficient was calculated for all content variables in the codebook. The following average reliability value was obtained for the codebook: 0.813, indicating good measurement accuracy [ 55 ].

Data was collected by downloading the videos and the text presentation. These were transferred directly into MAXQDA 2020, where the material was coded by JN. The data were then transferred to an Excel spreadsheet. Quantification was performed by JN using descriptive data analysis (frequencies and percentages) in STATA 14.2.

Procedure and analysis of the qualitative content analysis.

This analysis consisted of coding the content data related to the person sharing their experiences (e.g. P001) in the uploaded video. After selection, the videos of YouTubers were transcribed verbatim. Their content was then analyzed by JN and LW according to Mayring’s qualitative content analysis [ 56 ]. A category system was developed beforehand, according to which, the content-related aspects of the material were examined. The category system is available as ( S2 Table ).

The categories were developed based on the current state of research and by considering the codebook of the quantitative research strand. Further subcategories were created based on the research questions and inductively from the material. Coding rules were subsequently defined, and anchor examples were added. The videos were transcribed and coded by LW and JN in MAXQDA 2020.

Reflexibility . The two main researchers involved in the qualitative research (JN and LW) have taken and stopped the OCP themselves. Although we were not required to participate in interviews, our lived experiences were part of the knowledge production in this study. Both researchers talked about the process of coding and creating categories throughout the data analysis.

The ethical approval for this study has been granted by the Ethical Review Committee of the Medical Faculty at Martin Luther University Halle-Wittenberg. The German Society for Online Research [ 57 ] states that the use of publicly available data for scientific research is ethically appropriate even without informed consent. Before a person uploads a video on YouTube, they have to consent that their data can be reused through third parties [ 58 ]. Therefore, a certain level of awareness can be assumed [ 59 ]. We are aware that this requires a certain level of maturity. Therefore, we decided to only include adult YouTubers who are aware of their publicity (e.g. through follower numbers) and the publicly available works.

All videos and individuals were pseudonymized at the beginning of the data collection to minimize the risk of identification. This makes it impossible or very difficult to identify them in the research process: All videos were assigned a video identification number (e.g. V001). All people have a personal identification number (e.g. P001). The personal data (e.g. title, YouTube channel name) were separated from the factual data (e.g. time of posting, views) and stored on different media (USB key).

The collection and analysis method complied with the terms and conditions for the source of the data.

The 175 Videos analyzed in this study were posted between 2014 and 2023. The mean video length was 14.8 minutes. The detailed general characteristics are available in the ( S3 Table ).

General characteristics of the OCP persistence

The mean duration of OCP use was 8.2 years. Women started using OCPs at a mean age of 14.8 years. The mean age of discontinuation was 23.1 years. See Table 2 for details.

https://doi.org/10.1371/journal.pone.0302316.t002

The OCP implementation and discontinuation

The following results show that embodiment and effects on the body play a central role in OCP use and discontinuation. This recurs in the detailed descriptions of the psychological and physical aspects of each phase of the OCP autobiographies uploaded.

Characteristics of the OCP implementation.

Table 3 details all the information on the OCP implementation. A total of 57 of 158 YouTubers changed their type of OCP during the implementation period. Aspects of this are that switching may have occurred because of side effects of the OCP (P018, P149), side effects that occurred after switching (P010, P100), or side effects persisted and worsened after switching (P149).

https://doi.org/10.1371/journal.pone.0302316.t003

The reasons for taking the OCP were varied and included facial skin impurities (35/158), contraception (30/158), and/or painful menstruation (27/158). Many felt that the OCP was the only option available to them and were unaware of alternative contraceptive methods. The women expressed the normality of the OCP as a solution for treating facial skin impurities (P002) and the gynecologist’s recommendation for easing menstrual cramps (P010). According to the average age at initiation, it was stated that pregnancy was not an option due to the young age and that the OCP was considered a safe method of contraception (P006, P018, P149).

Positive side effects during implementation.

Overall, 45 of the 158 women experienced improvements while using OCPs. The improvements were consistent with the main reasons for initiation: facial skin impurities (25/158), painful bleeding (19/158), and decreased bleeding (12/158). The OCP appears to be particularly convenient as it combines the treatment of medical problems, such as painful bleeding, with the need for contraception (P007, P010).

Negative side effects during implementation.

Physiological side effects were reported by 101 of the YouTubers in the study. The most common side effects were weight gain (45/158), headaches (33/158), and water retention (30/158). Headaches seemed to be very distressing and interfered with women’s lives (e.g. P001, P007, P100). A total of 103 women reported psychological side effects. The most common psychological side effects were mood swings (76/158), depressed mood (45/158), and deterioration of libido (31/158). Mood swings were characterized as being moody, irritable, unrelaxed, aggressive, or angry (e.g. P010, P032, P054). Women also reported feeling that something was missing or feeling emotionally numb while on the OCP (e.g. P032, P085, P148).

Characteristics of the OCP treatment discontinuation

As described in Table 4 , the main reasons given by YouTubers for discontinuing the use of OCPs were the side effects experienced (74/158), increased awareness of the topic (21/158), and the desire to stop taking hormones (34/158). Qualitatively, side effects that led to discontinuation could include a tipping point where a user could no longer tolerate the side effects. In particular, the severe impact of headaches while taking the OCP was reported as a side effect leading to discontinuation (P001, P007, P018). A total of 27 of all YouTubers in the study reported discontinuing the OCP for the second time. The reasons for resuming the OCP were changes (e.g. facial blemishes) after the first discontinuation. However, as one YouTuber explained in P018, the side effects of the OCP were even worse, which then led to the final discontinuation of the method. Ultimately, former users of the OCP had a variety of reasons for stopping, but all prioritized their overall health and well-being.

https://doi.org/10.1371/journal.pone.0302316.t004

Improvements after discontinuation.

Out of 158 YouTubers, 54 mentioned physiological improvements and 82 mentioned psychological improvements from discontinuation. The most common improvements mentioned were weight loss (37/158), the disappearance of headaches (23/158), decreased fatigue (13/158), decreased mood swings (47/158), increased libido (40/158), and decreased depressive mood (19/158). Women reported that discontinuation improved their psychological mood: They felt more relaxed and had a more positive attitude (P001, P002, P036, P048, P054). They also reported a return or increase in their libido (P002, P100, P140, P149). Many expressed that they did not expect how intense this return would be (P010). They reported feeling more in tune with their bodies and experiencing a greater sense of euphoria after weaning off the OCP.

Negative changes after discontinuation.

In general, 123 of all women in the study experienced negative physiological and 32 experienced psychological changes after discontinuation. An increase in facial skin impurities was the negative physiological change most reported after discontinuation (108/158). This was followed by hair loss (42/158), painful menstruation (36/158), and menstrual cycle irregularities (31/158). Negative psychological changes included mood swings (16/158) or the onset of premenstrual syndrome (10/158). The YouTubers claimed that their facial skin impurities were never as bad as they were after stopping the OCP. They mostly described their facial blemishes as “normal” and not as severe as in people with “real” acne. Conversely, they also described the onset of facial skin deterioration as a major challenge and burden. Due to the strong identification with their facial skin and external appearance, this had become a problem. Thus, good make-up and the thought that others also have facial skin imperfections should help to conceal and accept one’s facial skin, which is seen as a flaw (P002, P018, P100). A minority of women stated that discontinuing the product caused a worsening of their psychological state (P085).

Evaluation of contraceptive discontinuation.

Overall, 87 of 91 YouTubers rated their experience of discontinuation as positive. The women reflected on the strong influence of the OCP on their bodies and health (P002, P010). They described how happy they were to have freed their bodies from artificial hormones (P079), and that they were more in tune with their bodies and more aware of themselves (P010, P044, P100, P149). Words that appeared frequently in the conclusions were “liberated” and “freer.” Women felt freer after weaning off the OCP, for example, even though they said it was difficult to put this into words (P032, P036, P054).

Current contraceptive method.

The most common contraceptive currently used by YouTubers is the condom (26/84). This is followed by the copper intrauterine device (IUD), chain, or ball (24/84) and the natural family planning (NFP) method (14/84).

Critical views on the OCP treatment

Looking back on their time on the OCP, women also expressed critical views. It was emphasized that the first sexual experiences in life were made under the influence of the pill (P010, P044). As one YouTuber explained:

“One of the things I think is very fatal about very young girls being prescribed the pill is that many start taking it before they even have a sex life. That’s exactly what happened to me. That is, every sexual experience I had was under the influence of the pill, so I didn’t even know what sex and my sexuality would be like without the pill. So, for years I thought a lot of things were normal.” (P010)

The pill was also seen as a moneymaker for the medical/pharmaceutical market (P032) and as a beauty product (P119, P149). The method of prescribing hormones to young girls at the beginning of puberty was questioned. They YouTubers also criticized the fact that the OCP was/is prescribed as a solution to non-contraceptive problems, such as facial blemishes or cycle irregularities. As this woman explained:

“And then I really wonder if it’s necessary to try to influence that with drugs and hormones. Or, maybe you could approach it differently or go in the direction of facial skin care and see a dermatologist to see if that might help […]. Instead of just taking these hormones, especially at a young age, to get a better picture, I find it a little bit critical, to be honest, because I always think to myself, I don’t know, it’s coming from something else in your body. And you’re just not treating the cause, you’re just treating the problem at that moment.” (P119)

The general cost of contraception as a female burden was also mentioned. P130 described that:

“Of course, it costs money, and you shouldn’t forget that either. It’s also really absurd that we women have to pay for it and the men don’t. Not because of men and women, but I think the health insurance should pay for it. I can’t even think about paying that much a month. And I never go to the doctor. Never. I never have anything. I don’t even know what for.”

What is interesting here is that they see the financial burden as something that should be negotiated and shared between men and women. She goes one step further and demands that health insurance should cover contraception. Women described different aspects of stopping the OCP in several videos.

Recommendations regarding the OCP

The first recommendation was that women should not stop taking the OCP without information and indiscriminately (P018, P050). Women should make up their minds, seek medical advice (P002, P007), and not stop taking the OCP overnight, especially if it is being used for contraception. It was also mentioned that both starting and stopping the OCP is a very individual matter (P018, P032).

The second recommendation emphasized that discontinuation is an individual decision. The YouTubers explained that the choice of contraception is a private matter (P006). You should not be talked into it (P018, P054) and make your own informed decision:

“It doesn’t have to be for everyone and I would say to you don’t let anybody talk you into something if you feel comfortable with it and it doesn’t have to be the pill, it actually applies to all situations in life. If you feel comfortable with something and you think it works for you, then stick with it. Don’t let anybody talk you into something that you don’t feel is right for you.” (P085)

Finally, some YouTubers also recommended stopping the OCP (P140, P010). They were extremely positive about their experience of stopping, describing how it is better to do without:

“That’s why I can advise every woman and every girl to think about whether you take the pill, whether you start taking it or whether you continue taking it. Do some research. Pay attention to your body, pay attention to possible side effects, and think twice. So if you are thinking about going off the pill, I wish you perseverance and I promise you it will have a positive impact on your life and you will not regret it.” (P010)

This analysis demonstrates that bodily experiences and the body itself are significant components in OCP autobiographies, from initiation to the period after discontinuation. The primary reasons for initiation are to address facial skin impurities, use as a contraceptive method, and to alleviate painful menstrual cramps. Common side effects experienced during the use of OCPs include mood swings, weight gain, headaches, depressed mood, decreased libido, water retention, and migraines. Women have described these effects as burdensome, despite the OCPs serving both medical and contraceptive purposes. Women predominantly discontinue OCPs due to side effects, a desire to cease hormone intake, and increased awareness of related issues. After discontinuation, individuals commonly reported deterioration in facial skin impurities and hair. But noted weight loss, reduced mood swings, increased libido, and a generally positive experience of feeling more connected to their bodies and freer. To the best of the authors’ knowledge, this is one of the few studies on the personal views and experiences of women who have discontinued the OCP. The combination of quantitative description and qualitative analysis in interpreting the results was not only helpful in measuring experiences with the OCP, they showed how these experiences are perceived and lived. The results of this study are consistent with scientific research on the positive and negative side effects [ 60 – 62 ] of OCPs, the reasons for discontinuation [ 29 , 48 , 63 ], and embodiment [ 64 , 65 ].

Puberty is the time when most girls in quality healthcare systems visit a gynecologist for the first time. This may be for specific health problems, such as menstrual cramps, acne, and cycle irregularities, or contraceptive advice [ 66 , 67 ]. In our sample, most women initiated the OCP during puberty, an age when physical and hormonal development from girl to woman is not yet complete. The OCP, therefore, acts as a drug in an organism that is not yet fully developed [ 68 ]. In this context, health professionals must provide information and advice on the costs and benefits of contraception.

The side effects reported by the YouTubers during OCP treatment are generally consistent with the associated side effects reported in other studies [ 43 , 61 , 69 ] and listed on the OCP’s package inserts [ 70 ]. However, the high number of side effects experienced by YouTubers was striking. This may be because YouTubers may be more likely to report discontinuing the pill if they have experienced side effects while either taking or discontinuing the OCP. Thus, there may be a publication bias in the YouTube videos and the results should be interpreted with caution.

The strata of this analysis are characterized by their young age at quitting. This may reflect the medium of YouTube as a YouTube consumer, which is specific to the sample of this study. However, it could also reflect the fact that women stop using the OCP at a relatively young age, particularly compared to the average age of women at first birth in the European Union (29.4 years) and Germany (31.2 years) in 2019 [ 71 ].

The main reasons for discontinuing OCP use reported were side effects and the desire to stop taking hormones. This is consistent with the quantitative literature, where side effects [ 29 , 48 , 63 ] or concerns about long-term effects [ 29 ] are predominantly cited as the main reasons for discontinuation. Additionally, Pfender and Devlin’s analysis (2023) reported that 22 out of 50 YouTubers discontinued hormonal contraception in favor of “being more natural” [ 33 ]. A systematic review of medical and epidemiologic studies in 2015 [ 48 ], which examined OCP discontinuation, found that pregnancy was among the top two reasons for discontinuation. This discrepancy could be explained by the young age at discontinuation of the sample included in this study. However, it may be some of the other reasons for discontinuation mentioned above that prompted the women to create a YouTube video.

Scientific studies show that women especially are under social pressure when it comes to their external appearance [ 72 – 74 ]. Even mild forms of acne, for instance, are associated with a reduced quality of life [ 75 ]. The study showed that facial skin impurities were the most common symptom after discontinuation of OCP therapy. Even the mild symptoms reported by women were associated with reduced self-esteem and discomfort. Accordingly, medically harmless facial skin complaints after discontinuation represent a major psychological burden for female YouTubers. The literature also describes that women, on average, experience longer cycles and more variability in cycle length after discontinuation [ 46 , 47 , 76 ]. This is consistent with the experience of female YouTubers. The OCP has also been questioned and studied for its possible negative association with mental [ 10 , 25 , 61 , 77 ] and sexual health [ 10 , 62 , 69 ]. Research on these topics should still be interpreted with caution, as there is limited consistency in the direction of the evidence [ 10 ]. Although it did not seem to be a central theme among the YouTubers, women in our sample reported mood swings and a decrease in libido as side effects of OCPs and their improvement after discontinuation. Interestingly, the prescription of OCPs before young girls have a regular sex life was also criticized. Despite the negative impact of health symptoms after discontinuation, such as facial skin impurities, the women overwhelmingly experienced discontinuation as positive.

When OCPs are discontinued for reasons other than pregnancy, the use of other effective contraceptive methods is very important for reproductive health, otherwise, women are at high risk of becoming pregnant. The data show that most YouTubers switch to condoms or a copper implant (IUD, ball, or chain). However, NFP, a modern fertility awareness-based method, is also used quite frequently. Both copper implants [ 78 ] and modern fertility awareness-based methods are effective ways to prevent pregnancy [ 79 , 80 ]. In addition, research shows that women have an increasing desire for more autonomy in their contraceptive choices [ 81 – 84 ]. Informed women’s choices are associated with better contraceptive adherence and fewer contraceptive failures [ 85 ]. However, there may be differences in the counseling and recommendations of healthcare providers regarding contraceptive methods. Research by Irala et al. (2011), for example, suggests that OCPs and the IUD were predominantly chosen as contraceptive methods because of the doctor’s suggestion/recommendation rather than because of the women’s wishes [ 86 ]. The opposite was true for the male condom or modern fertility awareness-based methods. A German study (2022) found that participants said they would like to be better informed about the OCP [ 29 ], and that women who received information from their gynecologist were more likely to feel well-informed (OR 1.59, CI: 1.10–2.30) than those who received information from the Internet [ 29 ]. Healthcare providers should be made more aware of alternative contraceptive methods other than OCPs to increase the autonomy in contraceptive choice and ensure contraceptive effectiveness.

Looking at all the results, the body and bodily perception seem to play a central role in all phases of the OCP autobiography. The embodiment is reflected in the reasons for initiating and weaning off OCPs, the side effects experienced, and the changes that occur after stopping the OCP [ 79 ] . This role of bodies and contraception is consistent with other research: the OCP and other contraceptive methods, for example, have led to women having greater control over their reproductive bodies [ 80 , 81 ] , and the importance of the (gendered) body in women’s contraceptive decision-making [ 36 , 80 , 82 ] .

Future research directions

The framing of health information can influence health-related beliefs, attitudes, and behaviors [ 87 ]. The increase in information and interpretation of scientific evidence in the media can improve informed contraceptive choices. Conversely, they can also negatively affect public health through misinterpretation of scientific evidence [ 28 ]. We emphasize the need to further investigate the relationship between SNSs and individual contraceptive method choice discontinuation. There is a need for longitudinal and qualitative research to examine and explore the underlying processes and how these choices change over the life course [ 42 ]. In the context of our study design, it would be interesting to investigate if and how the private experiences of influencers on YouTube and other SNSs platforms (e.g. Instagram & TikTok) are used as health information regarding method discontinuation choices. In particular, women who seek contraceptive information online appear to have lower levels of trust in information provided by their gynecologists [ 29 ]. It would also be interesting to explore the underlying motivations and phenomena behind the public uploading of such private information, especially within the dynamics of self-presentation and online marketing.

Strengths and limitations

The methodological strength of this study was its mixed methods design. It allowed for a greater contextual understanding of the descriptive data presented through the qualitative analysis. In addition, the findings represent the personal views and experiences of the women. These are naturally expressed and not biased by the research design itself. However, because these findings are based on YouTube, they may have limited generalizability and transferability to the general population. The sample may be biased because the women who post content on YouTube may be different from the average woman who discontinues hormonal contraception. This recruitment method did not allow us to collect important background information (e.g. socioeconomic status, gender, ethnicity). Furthermore, for a large proportion of our study participants, we had to assume from looks and past upload history that they were adults. The study is also limited in terms of validating the qualitative aspect of this study as the data is retrospective, thus, preventing iteration and triangulation as additional validation methods. In addition, women who experience severe side effects during use and health symptoms after discontinuation may be more likely to post their experiences on YouTube than women with no side effects or symptoms. Thus, we do not know which of the data is factual and which might be influenced by self-presentation on SNSs. The reach of the videos may also have led women to be less open about this sensitive topic than, for example, in face-to-face interviews. This study is also limited to the content of what women report in their videos. It cannot, for example, consider changes in life circumstances (e.g. change of life/sexual partner, facial skin care routine).

This content analysis of YouTube videos portrayed the personal implementation and discontinuation experiences of OCPs among female YouTubers. In doing so, the study provided valuable insights into the lived experiences, perceptions, and opinions of women who discontinued OCPs in the context of quality healthcare systems. Future qualitative and quantitative research is needed to provide information on the motivations, subsequent health symptoms, and healthcare needs associated with discontinuing OCPs.

Supporting information

S1 table. german search terms..

https://doi.org/10.1371/journal.pone.0302316.s001

S2 Table. Qualitative coding scheme.

https://doi.org/10.1371/journal.pone.0302316.s002

S3 Table. Video descriptives, detail (N = 175).

https://doi.org/10.1371/journal.pone.0302316.s003

S1 File. Translated codebook for the quantitative content analysis.

https://doi.org/10.1371/journal.pone.0302316.s004

Acknowledgments

We recognize that people other than cisgender women have menstrual periods and use birth control to prevent pregnancy. In this article, we understand the word “women” to be an inclusive term. However, when referencing research, we use the term used to describe the participants throughout the publication.

We want to thank the thoughtful comments of the reviewers of this study for their encouraging thoughts and comments on this publication.

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