research study with questionnaire

Questionnaire Method In Research

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

A questionnaire is a research instrument consisting of a series of questions for the purpose of gathering information from respondents. Questionnaires can be thought of as a kind of written interview . They can be carried out face to face, by telephone, computer, or post.

Questionnaires provide a relatively cheap, quick, and efficient way of obtaining large amounts of information from a large sample of people.

Data can be collected relatively quickly because the researcher would not need to be present when completing the questionnaires. This is useful for large populations when interviews would be impractical.

However, a problem with questionnaires is that respondents may lie due to social desirability. Most people want to present a positive image of themselves, and may lie or bend the truth to look good, e.g., pupils exaggerate revision duration.

Questionnaires can effectively measure relatively large subjects’ behavior, attitudes, preferences, opinions, and intentions more cheaply and quickly than other methods.

Often, a questionnaire uses both open and closed questions to collect data. This is beneficial as it means both quantitative and qualitative data can be obtained.

Closed Questions

A closed-ended question requires a specific, limited response, often “yes” or “no” or a choice that fit into pre-decided categories.

Data that can be placed into a category is called nominal data. The category can be restricted to as few as two options, i.e., dichotomous (e.g., “yes” or “no,” “male” or “female”), or include quite complex lists of alternatives from which the respondent can choose (e.g., polytomous).

Closed questions can also provide ordinal data (which can be ranked). This often involves using a continuous rating scale to measure the strength of attitudes or emotions.

For example, strongly agree / agree / neutral / disagree / strongly disagree / unable to answer.

Closed questions have been used to research type A personality (e.g., Friedman & Rosenman, 1974) and also to assess life events that may cause stress (Holmes & Rahe, 1967) and attachment (Fraley, Waller, & Brennan, 2000).

• They can be economical. This means they can provide large amounts of research data for relatively low costs. Therefore, a large sample size can be obtained, which should represent the population from which a researcher can then generalize.
• The respondent provides information that can be easily converted into quantitative data (e.g., count the number of “yes” or “no” answers), allowing statistical analysis of the responses.
• The questions are standardized. All respondents are asked exactly the same questions in the same order. This means a questionnaire can be replicated easily to check for reliability . Therefore, a second researcher can use the questionnaire to confirm consistent results.

Limitations

• They lack detail. Because the responses are fixed, there is less scope for respondents to supply answers that reflect their true feelings on a topic.

Open Questions

Open questions allow for expansive, varied answers without preset options or limitations.

Open questions allow people to express what they think in their own words. Open-ended questions enable the respondent to answer in as much detail as they like in their own words. For example: “can you tell me how happy you feel right now?”

Open questions will work better if you want to gather more in-depth answers from your respondents. These give no pre-set answer options and instead, allow the respondents to put down exactly what they like in their own words.

Open questions are often used for complex questions that cannot be answered in a few simple categories but require more detail and discussion.

Lawrence Kohlberg presented his participants with moral dilemmas. One of the most famous concerns a character called Heinz, who is faced with the choice between watching his wife die of cancer or stealing the only drug that could help her.

Participants were asked whether Heinz should steal the drug or not and, more importantly, for their reasons why upholding or breaking the law is right.

• Rich qualitative data is obtained as open questions allow respondents to elaborate on their answers. This means the research can determine why a person holds a certain attitude .
• Time-consuming to collect the data. It takes longer for the respondent to complete open questions. This is a problem as a smaller sample size may be obtained.
• Time-consuming to analyze the data. It takes longer for the researcher to analyze qualitative data as they have to read the answers and try to put them into categories by coding, which is often subjective and difficult. However, Smith (1992) has devoted an entire book to the issues of thematic content analysis that includes 14 different scoring systems for open-ended questions.
• Not suitable for less educated respondents as open questions require superior writing skills and a better ability to express one’s feelings verbally.

Questionnaire Design

With some questionnaires suffering from a response rate as low as 5%, a questionnaire must be well designed.

There are several important factors in questionnaire design.

Pilot Study

Question order.

Questions should progress logically from the least sensitive to the most sensitive, from the factual and behavioral to the cognitive, and from the more general to the more specific.

The researcher should ensure that previous questions do not influence the answer to a question.

Question order effects

• Question order effects occur when responses to an earlier question affect responses to a later question in a survey. They can arise at different stages of the survey response process – interpretation, information retrieval, judgment/estimation, and reporting.
• Types of question order effects include: unconditional (subsequent answers affected by prior question topic), conditional (subsequent answers depend on the response to the prior question), and associational (correlation between two questions changes based on order).
• Question order effects have been found across different survey topics like social and political attitudes, health and safety studies, vignette research, etc. Effects may be moderated by respondent factors like age, education level, knowledge and attitudes about the topic.
• To minimize question order effects, recommendations include avoiding judgmental dependencies, separating potentially reactive questions, randomizing questions, following good survey design principles, considering respondent characteristics, and intentionally examining question context and order.

Terminology

• There should be a minimum of technical jargon. Questions should be simple, to the point, and easy to understand. The language of a questionnaire should be appropriate to the vocabulary of the group of people being studied.
• Use statements that are interpreted in the same way by members of different subpopulations of the population of interest.
• For example, the researcher must change the language of questions to match the social background of the respondent’s age / educational level / social class/ethnicity, etc.

Presentation

Ethical issues.

• The researcher must ensure that the information provided by the respondent is kept confidential, e.g., name, address, etc.
• This means questionnaires are good for researching sensitive topics as respondents will be more honest when they cannot be identified.
• Keeping the questionnaire confidential should also reduce the likelihood of psychological harm, such as embarrassment.
• Participants must provide informed consent before completing the questionnaire and must be aware that they have the right to withdraw their information at any time during the survey/ study.

Problems with Postal Questionnaires

At first sight, the postal questionnaire seems to offer the opportunity to get around the problem of interview bias by reducing the personal involvement of the researcher. Its other practical advantages are that it is cheaper than face-to-face interviews and can quickly contact many respondents scattered over a wide area.

However, these advantages must be weighed against the practical problems of conducting research by post. A lack of involvement by the researcher means there is little control over the information-gathering process.

The data might not be valid (i.e., truthful) as we can never be sure that the questionnaire was completed by the person to whom it was addressed.

That, of course, assumes there is a reply in the first place, and one of the most intractable problems of mailed questionnaires is a low response rate. This diminishes the reliability of the data

Also, postal questionnaires may not represent the population they are studying. This may be because:

• Some questionnaires may be lost in the post, reducing the sample size.
• The questionnaire may be completed by someone not a member of the research population.
• Those with strong views on the questionnaire’s subject are more likely to complete it than those without interest.

Benefits of a Pilot Study

A pilot study is a practice / small-scale study conducted before the main study.

It allows the researcher to try out the study with a few participants so that adjustments can be made before the main study, saving time and money.

It is important to conduct a questionnaire pilot study for the following reasons:

• Check that respondents understand the terminology used in the questionnaire.
• Check that emotive questions are not used, as they make people defensive and could invalidate their answers.
• Check that leading questions have not been used as they could bias the respondent’s answer.
• Ensure the questionnaire can be completed in an appropriate time frame (i.e., it’s not too long).

Frequently Asked Questions 

How do psychological researchers analyze the data collected from questionnaires.

Psychological researchers analyze questionnaire data by looking for patterns and trends in people’s responses. They use numbers and charts to summarize the information.

They calculate things like averages and percentages to see what most people think or feel. They also compare different groups to see if there are any differences between them.

By doing these analyses, researchers can understand how people think, feel, and behave. This helps them make conclusions and learn more about how our minds work.

Are questionnaires effective in gathering accurate data?

Yes, questionnaires can be effective in gathering accurate data. When designed well, with clear and understandable questions, they allow individuals to express their thoughts, opinions, and experiences.

However, the accuracy of the data depends on factors such as the honesty and accuracy of respondents’ answers, their understanding of the questions, and their willingness to provide accurate information. Researchers strive to create reliable and valid questionnaires to minimize biases and errors.

It’s important to remember that while questionnaires can provide valuable insights, they are just one tool among many used in psychological research.

Can questionnaires be used with diverse populations and cultural contexts?

Yes, questionnaires can be used with diverse populations and cultural contexts. Researchers take special care to ensure that questionnaires are culturally sensitive and appropriate for different groups.

This means adapting the language, examples, and concepts to match the cultural context. By doing so, questionnaires can capture the unique perspectives and experiences of individuals from various backgrounds.

This helps researchers gain a more comprehensive understanding of human behavior and ensures that everyone’s voice is heard and represented in psychological research.

Are questionnaires the only method used in psychological research?

No, questionnaires are not the only method used in psychological research. Psychologists use a variety of research methods, including interviews, observations , experiments , and psychological tests.

Each method has its strengths and limitations, and researchers choose the most appropriate method based on their research question and goals.

Questionnaires are valuable for gathering self-report data, but other methods allow researchers to directly observe behavior, study interactions, or manipulate variables to test hypotheses.

By using multiple methods, psychologists can gain a more comprehensive understanding of human behavior and mental processes.

What is a semantic differential scale?

The semantic differential scale is a questionnaire format used to gather data on individuals’ attitudes or perceptions. It’s commonly incorporated into larger surveys or questionnaires to assess subjective qualities or feelings about a specific topic, product, or concept by quantifying them on a scale between two bipolar adjectives.

It presents respondents with a pair of opposite adjectives (e.g., “happy” vs. “sad”) and asks them to mark their position on a scale between them, capturing the intensity of their feelings about a particular subject.

It quantifies subjective qualities, turning them into data that can be statistically analyzed.

Ayidiya, S. A., & McClendon, M. J. (1990). Response effects in mail surveys. Public Opinion Quarterly, 54 (2), 229–247. https://doi.org/10.1086/269200

Fraley, R. C., Waller, N. G., & Brennan, K. A. (2000). An item-response theory analysis of self-report measures of adult attachment. Journal of Personality and Social Psychology, 78, 350-365.

Friedman, M., & Rosenman, R. H. (1974). Type A behavior and your heart . New York: Knopf.

Gold, R. S., & Barclay, A. (2006). Order of question presentation and correlation between judgments of comparative and own risk. Psychological Reports, 99 (3), 794–798. https://doi.org/10.2466/PR0.99.3.794-798

Holmes, T. H., & Rahe, R. H. (1967). The social readjustment rating scale. Journal of psychosomatic research, 11(2) , 213-218.

Schwarz, N., & Hippler, H.-J. (1995). Subsequent questions may influence answers to preceding questions in mail surveys. Public Opinion Quarterly, 59 (1), 93–97. https://doi.org/10.1086/269460

Smith, C. P. (Ed.). (1992). Motivation and personality: Handbook of thematic content analysis . Cambridge University Press.

Further Information

• Questionnaire design and scale development
• Questionnaire Appraisal Form

How to Design Effective Research Questionnaires for Robust Findings

As a staple in data collection, questionnaires help uncover robust and reliable findings that can transform industries, shape policies, and revolutionize understanding. Whether you are exploring societal trends or delving into scientific phenomena, the effectiveness of your research questionnaire can make or break your findings.

In this article, we aim to understand the core purpose of questionnaires, exploring how they serve as essential tools for gathering systematic data, both qualitative and quantitative, from diverse respondents. Read on as we explore the key elements that make up a winning questionnaire, the art of framing questions which are both compelling and rigorous, and the careful balance between simplicity and depth.

Table of Contents

The Role of Questionnaires in Research

So, what is a questionnaire? A questionnaire is a structured set of questions designed to collect information, opinions, attitudes, or behaviors from respondents. It is one of the most commonly used data collection methods in research. Moreover, questionnaires can be used in various research fields, including social sciences, market research, healthcare, education, and psychology. Their adaptability makes them suitable for investigating diverse research questions.

Questionnaire and survey  are two terms often used interchangeably, but they have distinct meanings in the context of research. A survey refers to the broader process of data collection that may involve various methods. A survey can encompass different data collection techniques, such as interviews , focus groups, observations, and yes, questionnaires.

Pros and Cons of Using Questionnaires in Research:

While questionnaires offer numerous advantages in research, they also come with some disadvantages that researchers must be aware of and address appropriately. Careful questionnaire design, validation, and consideration of potential biases can help mitigate these disadvantages and enhance the effectiveness of using questionnaires as a data collection method.

Structured vs Unstructured Questionnaires

Structured questionnaire:.

A structured questionnaire consists of questions with predefined response options. Respondents are presented with a fixed set of choices and are required to select from those options. The questions in a structured questionnaire are designed to elicit specific and quantifiable responses. Structured questionnaires are particularly useful for collecting quantitative data and are often employed in surveys and studies where standardized and comparable data are necessary.

Advantages of Structured Questionnaires:

• Easy to analyze and interpret: The fixed response options facilitate straightforward data analysis and comparison across respondents.
• Efficient for large-scale data collection: Structured questionnaires are time-efficient, allowing researchers to collect data from a large number of respondents.
• Reduces response bias: The predefined response options minimize potential response bias and maintain consistency in data collection.

Limitations of Structured Questionnaires:

• Lack of depth: Structured questionnaires may not capture in-depth insights or nuances as respondents are limited to pre-defined response choices. Hence, they may not reveal the reasons behind respondents’ choices, limiting the understanding of their perspectives.
• Limited flexibility: The fixed response options may not cover all potential responses, therefore, potentially restricting respondents’ answers.

Unstructured Questionnaire:

An unstructured questionnaire consists of questions that allow respondents to provide detailed and unrestricted responses. Unlike structured questionnaires, there are no predefined response options, giving respondents the freedom to express their thoughts in their own words. Furthermore, unstructured questionnaires are valuable for collecting qualitative data and obtaining in-depth insights into respondents’ experiences, opinions, or feelings.

Advantages of Unstructured Questionnaires:

• Rich qualitative data: Unstructured questionnaires yield detailed and comprehensive qualitative data, providing valuable and novel insights into respondents’ perspectives.
• Flexibility in responses: Respondents have the freedom to express themselves in their own words. Hence, allowing for a wide range of responses.

Limitations of Unstructured Questionnaires:

• Time-consuming analysis: Analyzing open-ended responses can be time-consuming, since, each response requires careful reading and interpretation.
• Subjectivity in interpretation: The analysis of open-ended responses may be subjective, as researchers interpret and categorize responses based on their judgment.
• May require smaller sample size: Due to the depth of responses, researchers may need a smaller sample size for comprehensive analysis, making generalizations more challenging.

Types of Questions in a Questionnaire

In a questionnaire, researchers typically use the following most common types of questions to gather a variety of information from respondents:

1. Open-Ended Questions:

These questions allow respondents to provide detailed and unrestricted responses in their own words. Open-ended questions are valuable for gathering qualitative data and in-depth insights.

Example: What suggestions do you have for improving our product?

2. Multiple-Choice Questions

Respondents choose one answer from a list of provided options. This type of question is suitable for gathering categorical data or preferences.

Example: Which of the following social media/academic networking platforms do you use to promote your research?

• ResearchGate
• Academia.edu

3. Dichotomous Questions

Respondents choose between two options, typically “yes” or “no”, “true” or “false”, or “agree” or “disagree”.

Example: Have you ever published in open access journals before?

4. Scaling Questions

These questions, also known as rating scale questions, use a predefined scale that allows respondents to rate or rank their level of agreement, satisfaction, importance, or other subjective assessments. These scales help researchers quantify subjective data and make comparisons across respondents.

There are several types of scaling techniques used in scaling questions:

i. Likert Scale:

The Likert scale is one of the most common scaling techniques. It presents respondents with a series of statements and asks them to rate their level of agreement or disagreement using a range of options, typically from “strongly agree” to “strongly disagree”.For example: Please indicate your level of agreement with the statement: “The content presented in the webinar was relevant and aligned with the advertised topic.”

• Strongly Agree
• Strongly Disagree

ii. Semantic Differential Scale:

The semantic differential scale measures respondents’ perceptions or attitudes towards an item using opposite adjectives or bipolar words. Respondents rate the item on a scale between the two opposites. For example:

• Easy —— Difficult
• Satisfied —— Unsatisfied
• Very likely —— Very unlikely

iii. Numerical Rating Scale:

This scale requires respondents to provide a numerical rating on a predefined scale. It can be a simple 1 to 5 or 1 to 10 scale, where higher numbers indicate higher agreement, satisfaction, or importance.

iv. Ranking Questions:

Respondents rank items in order of preference or importance. Ranking questions help identify preferences or priorities.

Example: Please rank the following features of our app in order of importance (1 = Most Important, 5 = Least Important):

• User Interface
• Functionality
• Customer Support

By using a mix of question types, researchers can gather both quantitative and qualitative data, providing a comprehensive understanding of the research topic and enabling meaningful analysis and interpretation of the results. The choice of question types depends on the research objectives , the desired depth of information, and the data analysis requirements.

Methods of Administering Questionnaires

There are several methods for administering questionnaires, and the choice of method depends on factors such as the target population, research objectives , convenience, and resources available. Here are some common methods of administering questionnaires:

Each method has its advantages and limitations. Online surveys offer convenience and a large reach, but they may be limited to individuals with internet access. Face-to-face interviews allow for in-depth responses but can be time-consuming and costly. Telephone surveys have broad reach but may be limited by declining response rates. Researchers should choose the method that best suits their research objectives, target population, and available resources to ensure successful data collection.

How to Design a Questionnaire

Designing a good questionnaire is crucial for gathering accurate and meaningful data that aligns with your research objectives. Here are essential steps and tips to create a well-designed questionnaire:

1. Define Your Research Objectives : Clearly outline the purpose and specific information you aim to gather through the questionnaire.

2. Identify Your Target Audience : Understand respondents’ characteristics and tailor the questionnaire accordingly.

3. Develop the Questions :

• Write Clear and Concise Questions
• Avoid Leading or Biasing Questions
• Sequence Questions Logically
• Group Related Questions
• Include Demographic Questions

4. Provide Well-defined Response Options : Offer exhaustive response choices for closed-ended questions.

5. Consider Skip Logic and Branching : Customize the questionnaire based on previous answers.

6. Pilot Test the Questionnaire : Identify and address issues through a pilot study .

7. Seek Expert Feedback : Validate the questionnaire with subject matter experts.

8. Obtain Ethical Approval : Comply with ethical guidelines , obtain consent, and ensure confidentiality before administering the questionnaire.

9. Administer the Questionnaire : Choose the right mode and provide clear instructions.

10. Test the Survey Platform : Ensure compatibility and usability for online surveys.

By following these steps and paying attention to questionnaire design principles, you can create a well-structured and effective questionnaire that gathers reliable data and helps you achieve your research objectives.

Characteristics of a Good Questionnaire

A good questionnaire possesses several essential elements that contribute to its effectiveness. Furthermore, these characteristics ensure that the questionnaire is well-designed, easy to understand, and capable of providing valuable insights. Here are some key characteristics of a good questionnaire:

1. Clarity and Simplicity : Questions should be clear, concise, and unambiguous. Avoid using complex language or technical terms that may confuse respondents. Simple and straightforward questions ensure that respondents interpret them consistently.

2. Relevance and Focus : Each question should directly relate to the research objectives and contribute to answering the research questions. Consequently, avoid including extraneous or irrelevant questions that could lead to data clutter.

3. Mix of Question Types : Utilize a mix of question types, including open-ended, Likert scale, and multiple-choice questions. This variety allows for both qualitative and quantitative data collections .

4. Validity and Reliability : Ensure the questionnaire measures what it intends to measure (validity) and produces consistent results upon repeated administration (reliability). Validation should be conducted through expert review and previous research.

5. Appropriate Length : Keep the questionnaire’s length appropriate and manageable to avoid respondent fatigue or dropouts. Long questionnaires may result in incomplete or rushed responses.

6. Clear Instructions : Include clear instructions at the beginning of the questionnaire to guide respondents on how to complete it. Explain any technical terms, formats, or concepts if necessary.

7. User-Friendly Format : Design the questionnaire to be visually appealing and user-friendly. Use consistent formatting, adequate spacing, and a logical page layout.

8. Data Validation and Cleaning : Incorporate validation checks to ensure data accuracy and reliability. Consider mechanisms to detect and correct inconsistent or missing responses during data cleaning.

By incorporating these characteristics, researchers can create a questionnaire that maximizes data quality, minimizes response bias, and provides valuable insights for their research.

In the pursuit of advancing research and gaining meaningful insights, investing time and effort into designing effective questionnaires is a crucial step. A well-designed questionnaire is more than a mere set of questions; it is a masterpiece of precision and ingenuity. Each question plays a vital role in shaping the narrative of our research, guiding us through the labyrinth of data to meaningful conclusions. Indeed, a well-designed questionnaire serves as a powerful tool for unlocking valuable insights and generating robust findings that impact society positively.

Have you ever designed a research questionnaire? Reflect on your experience and share your insights with researchers globally through Enago Academy’s Open Blogging Platform . Join our diverse community of 1000K+ researchers and authors to exchange ideas, strategies, and best practices, and together, let’s shape the future of data collection and maximize the impact of questionnaires in the ever-evolving landscape of research.

Frequently Asked Questions

A research questionnaire is a structured tool used to gather data from participants in a systematic manner. It consists of a series of carefully crafted questions designed to collect specific information related to a research study.

Questionnaires play a pivotal role in both quantitative and qualitative research, enabling researchers to collect insights, opinions, attitudes, or behaviors from respondents. This aids in hypothesis testing, understanding, and informed decision-making, ensuring consistency, efficiency, and facilitating comparisons.

Questionnaires are a versatile tool employed in various research designs to gather data efficiently and comprehensively. They find extensive use in both quantitative and qualitative research methodologies, making them a fundamental component of research across disciplines. Some research designs that commonly utilize questionnaires include: a) Cross-Sectional Studies b) Longitudinal Studies c) Descriptive Research d) Correlational Studies e) Causal-Comparative Studies f) Experimental Research g) Survey Research h) Case Studies i) Exploratory Research

A survey is a comprehensive data collection method that can include various techniques like interviews and observations. A questionnaire is a specific set of structured questions within a survey designed to gather standardized responses. While a survey is a broader approach, a questionnaire is a focused tool for collecting specific data.

The choice of questionnaire type depends on the research objectives, the type of data required, and the preferences of respondents. Some common types include: • Structured Questionnaires: These questionnaires consist of predefined, closed-ended questions with fixed response options. They are easy to analyze and suitable for quantitative research. • Semi-Structured Questionnaires: These questionnaires combine closed-ended questions with open-ended ones. They offer more flexibility for respondents to provide detailed explanations. • Unstructured Questionnaires: These questionnaires contain open-ended questions only, allowing respondents to express their thoughts and opinions freely. They are commonly used in qualitative research.

Following these steps ensures effective questionnaire administration for reliable data collection: • Choose a Method: Decide on online, face-to-face, mail, or phone administration. • Online Surveys: Use platforms like SurveyMonkey • Pilot Test: Test on a small group before full deployment • Clear Instructions: Provide concise guidelines • Follow-Up: Send reminders if needed

Thank you, Riya. This is quite helpful. As discussed, response bias is one of the disadvantages in the use of questionnaires. One way to help limit this can be to use scenario based questions. These type of questions may help the respondents to be more reflective and active in the process.

Thank you, Dear Riya. This is quite helpful.

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Home » Questionnaire – Definition, Types, and Examples

Questionnaire – Definition, Types, and Examples

Table of Contents

Questionnaire

Definition:

A Questionnaire is a research tool or survey instrument that consists of a set of questions or prompts designed to gather information from individuals or groups of people.

It is a standardized way of collecting data from a large number of people by asking them a series of questions related to a specific topic or research objective. The questions may be open-ended or closed-ended, and the responses can be quantitative or qualitative. Questionnaires are widely used in research, marketing, social sciences, healthcare, and many other fields to collect data and insights from a target population.

History of Questionnaire

The history of questionnaires can be traced back to the ancient Greeks, who used questionnaires as a means of assessing public opinion. However, the modern history of questionnaires began in the late 19th century with the rise of social surveys.

The first social survey was conducted in the United States in 1874 by Francis A. Walker, who used a questionnaire to collect data on labor conditions. In the early 20th century, questionnaires became a popular tool for conducting social research, particularly in the fields of sociology and psychology.

One of the most influential figures in the development of the questionnaire was the psychologist Raymond Cattell, who in the 1940s and 1950s developed the personality questionnaire, a standardized instrument for measuring personality traits. Cattell’s work helped establish the questionnaire as a key tool in personality research.

In the 1960s and 1970s, the use of questionnaires expanded into other fields, including market research, public opinion polling, and health surveys. With the rise of computer technology, questionnaires became easier and more cost-effective to administer, leading to their widespread use in research and business settings.

Today, questionnaires are used in a wide range of settings, including academic research, business, healthcare, and government. They continue to evolve as a research tool, with advances in computer technology and data analysis techniques making it easier to collect and analyze data from large numbers of participants.

Types of Questionnaire

Types of Questionnaires are as follows:

Structured Questionnaire

This type of questionnaire has a fixed format with predetermined questions that the respondent must answer. The questions are usually closed-ended, which means that the respondent must select a response from a list of options.

Unstructured Questionnaire

An unstructured questionnaire does not have a fixed format or predetermined questions. Instead, the interviewer or researcher can ask open-ended questions to the respondent and let them provide their own answers.

Open-ended Questionnaire

An open-ended questionnaire allows the respondent to answer the question in their own words, without any pre-determined response options. The questions usually start with phrases like “how,” “why,” or “what,” and encourage the respondent to provide more detailed and personalized answers.

Close-ended Questionnaire

In a closed-ended questionnaire, the respondent is given a set of predetermined response options to choose from. This type of questionnaire is easier to analyze and summarize, but may not provide as much insight into the respondent’s opinions or attitudes.

Mixed Questionnaire

A mixed questionnaire is a combination of open-ended and closed-ended questions. This type of questionnaire allows for more flexibility in terms of the questions that can be asked, and can provide both quantitative and qualitative data.

Pictorial Questionnaire:

In a pictorial questionnaire, instead of using words to ask questions, the questions are presented in the form of pictures, diagrams or images. This can be particularly useful for respondents who have low literacy skills, or for situations where language barriers exist. Pictorial questionnaires can also be useful in cross-cultural research where respondents may come from different language backgrounds.

Types of Questions in Questionnaire

The types of Questions in Questionnaire are as follows:

Multiple Choice Questions

These questions have several options for participants to choose from. They are useful for getting quantitative data and can be used to collect demographic information.

• a. Red b . Blue c. Green d . Yellow

Rating Scale Questions

These questions ask participants to rate something on a scale (e.g. from 1 to 10). They are useful for measuring attitudes and opinions.

• On a scale of 1 to 10, how likely are you to recommend this product to a friend?

Open-Ended Questions

These questions allow participants to answer in their own words and provide more in-depth and detailed responses. They are useful for getting qualitative data.

• What do you think are the biggest challenges facing your community?

Likert Scale Questions

These questions ask participants to rate how much they agree or disagree with a statement. They are useful for measuring attitudes and opinions.

How strongly do you agree or disagree with the following statement:

“I enjoy exercising regularly.”

• a . Strongly Agree
• c . Neither Agree nor Disagree
• d . Disagree
• e . Strongly Disagree

Demographic Questions

These questions ask about the participant’s personal information such as age, gender, ethnicity, education level, etc. They are useful for segmenting the data and analyzing results by demographic groups.

• What is your age?

Yes/No Questions

These questions only have two options: Yes or No. They are useful for getting simple, straightforward answers to a specific question.

Have you ever traveled outside of your home country?

Ranking Questions

These questions ask participants to rank several items in order of preference or importance. They are useful for measuring priorities or preferences.

Please rank the following factors in order of importance when choosing a restaurant:

• a. Quality of Food
• c. Ambiance
• d. Location

Matrix Questions

These questions present a matrix or grid of options that participants can choose from. They are useful for getting data on multiple variables at once.

Dichotomous Questions

These questions present two options that are opposite or contradictory. They are useful for measuring binary or polarized attitudes.

Do you support the death penalty?

How to Make a Questionnaire

Step-by-Step Guide for Making a Questionnaire:

• Define your research objectives: Before you start creating questions, you need to define the purpose of your questionnaire and what you hope to achieve from the data you collect.
• Choose the appropriate question types: Based on your research objectives, choose the appropriate question types to collect the data you need. Refer to the types of questions mentioned earlier for guidance.
• Develop questions: Develop clear and concise questions that are easy for participants to understand. Avoid leading or biased questions that might influence the responses.
• Organize questions: Organize questions in a logical and coherent order, starting with demographic questions followed by general questions, and ending with specific or sensitive questions.
• Pilot the questionnaire : Test your questionnaire on a small group of participants to identify any flaws or issues with the questions or the format.
• Refine the questionnaire : Based on feedback from the pilot, refine and revise the questionnaire as necessary to ensure that it is valid and reliable.
• Distribute the questionnaire: Distribute the questionnaire to your target audience using a method that is appropriate for your research objectives, such as online surveys, email, or paper surveys.
• Collect and analyze data: Collect the completed questionnaires and analyze the data using appropriate statistical methods. Draw conclusions from the data and use them to inform decision-making or further research.
• Report findings: Present your findings in a clear and concise report, including a summary of the research objectives, methodology, key findings, and recommendations.

Questionnaire Administration Modes

There are several modes of questionnaire administration. The choice of mode depends on the research objectives, sample size, and available resources. Some common modes of administration include:

• Self-administered paper questionnaires: Participants complete the questionnaire on paper, either in person or by mail. This mode is relatively low cost and easy to administer, but it may result in lower response rates and greater potential for errors in data entry.
• Online questionnaires: Participants complete the questionnaire on a website or through email. This mode is convenient for both researchers and participants, as it allows for fast and easy data collection. However, it may be subject to issues such as low response rates, lack of internet access, and potential for fraudulent responses.
• Telephone surveys: Trained interviewers administer the questionnaire over the phone. This mode allows for a large sample size and can result in higher response rates, but it is also more expensive and time-consuming than other modes.
• Face-to-face interviews : Trained interviewers administer the questionnaire in person. This mode allows for a high degree of control over the survey environment and can result in higher response rates, but it is also more expensive and time-consuming than other modes.
• Mixed-mode surveys: Researchers use a combination of two or more modes to administer the questionnaire, such as using online questionnaires for initial screening and following up with telephone interviews for more detailed information. This mode can help overcome some of the limitations of individual modes, but it requires careful planning and coordination.

Example of Questionnaire

Title of the Survey: Customer Satisfaction Survey

Introduction:

We appreciate your business and would like to ensure that we are meeting your needs. Please take a few minutes to complete this survey so that we can better understand your experience with our products and services. Your feedback is important to us and will help us improve our offerings.

Instructions:

Please read each question carefully and select the response that best reflects your experience. If you have any additional comments or suggestions, please feel free to include them in the space provided at the end of the survey.

1. How satisfied are you with our product quality?

• Very satisfied
• Somewhat satisfied
• Somewhat dissatisfied
• Very dissatisfied

2. How satisfied are you with our customer service?

3. How satisfied are you with the price of our products?

4. How likely are you to recommend our products to others?

• Very likely
• Somewhat likely
• Somewhat unlikely
• Very unlikely

5. How easy was it to find the information you were looking for on our website?

• Somewhat easy
• Somewhat difficult
• Very difficult

6. How satisfied are you with the overall experience of using our products and services?

7. Is there anything that you would like to see us improve upon or change in the future?

…………………………………………………………………………………………………………………………..

Conclusion:

Thank you for taking the time to complete this survey. Your feedback is valuable to us and will help us improve our products and services. If you have any further comments or concerns, please do not hesitate to contact us.

Applications of Questionnaire

Some common applications of questionnaires include:

• Research : Questionnaires are commonly used in research to gather information from participants about their attitudes, opinions, behaviors, and experiences. This information can then be analyzed and used to draw conclusions and make inferences.
• Healthcare : In healthcare, questionnaires can be used to gather information about patients’ medical history, symptoms, and lifestyle habits. This information can help healthcare professionals diagnose and treat medical conditions more effectively.
• Marketing : Questionnaires are commonly used in marketing to gather information about consumers’ preferences, buying habits, and opinions on products and services. This information can help businesses develop and market products more effectively.
• Human Resources: Questionnaires are used in human resources to gather information from job applicants, employees, and managers about job satisfaction, performance, and workplace culture. This information can help organizations improve their hiring practices, employee retention, and organizational culture.
• Education : Questionnaires are used in education to gather information from students, teachers, and parents about their perceptions of the educational experience. This information can help educators identify areas for improvement and develop more effective teaching strategies.

Purpose of Questionnaire

Some common purposes of questionnaires include:

• To collect information on attitudes, opinions, and beliefs: Questionnaires can be used to gather information on people’s attitudes, opinions, and beliefs on a particular topic. For example, a questionnaire can be used to gather information on people’s opinions about a particular political issue.
• To collect demographic information: Questionnaires can be used to collect demographic information such as age, gender, income, education level, and occupation. This information can be used to analyze trends and patterns in the data.
• To measure behaviors or experiences: Questionnaires can be used to gather information on behaviors or experiences such as health-related behaviors or experiences, job satisfaction, or customer satisfaction.
• To evaluate programs or interventions: Questionnaires can be used to evaluate the effectiveness of programs or interventions by gathering information on participants’ experiences, opinions, and behaviors.
• To gather information for research: Questionnaires can be used to gather data for research purposes on a variety of topics.

When to use Questionnaire

Here are some situations when questionnaires might be used:

• When you want to collect data from a large number of people: Questionnaires are useful when you want to collect data from a large number of people. They can be distributed to a wide audience and can be completed at the respondent’s convenience.
• When you want to collect data on specific topics: Questionnaires are useful when you want to collect data on specific topics or research questions. They can be designed to ask specific questions and can be used to gather quantitative data that can be analyzed statistically.
• When you want to compare responses across groups: Questionnaires are useful when you want to compare responses across different groups of people. For example, you might want to compare responses from men and women, or from people of different ages or educational backgrounds.
• When you want to collect data anonymously: Questionnaires can be useful when you want to collect data anonymously. Respondents can complete the questionnaire without fear of judgment or repercussions, which can lead to more honest and accurate responses.
• When you want to save time and resources: Questionnaires can be more efficient and cost-effective than other methods of data collection such as interviews or focus groups. They can be completed quickly and easily, and can be analyzed using software to save time and resources.

Characteristics of Questionnaire

Here are some of the characteristics of questionnaires:

• Standardization : Questionnaires are standardized tools that ask the same questions in the same order to all respondents. This ensures that all respondents are answering the same questions and that the responses can be compared and analyzed.
• Objectivity : Questionnaires are designed to be objective, meaning that they do not contain leading questions or bias that could influence the respondent’s answers.
• Predefined responses: Questionnaires typically provide predefined response options for the respondents to choose from, which helps to standardize the responses and make them easier to analyze.
• Quantitative data: Questionnaires are designed to collect quantitative data, meaning that they provide numerical or categorical data that can be analyzed using statistical methods.
• Convenience : Questionnaires are convenient for both the researcher and the respondents. They can be distributed and completed at the respondent’s convenience and can be easily administered to a large number of people.
• Anonymity : Questionnaires can be anonymous, which can encourage respondents to answer more honestly and provide more accurate data.
• Reliability : Questionnaires are designed to be reliable, meaning that they produce consistent results when administered multiple times to the same group of people.
• Validity : Questionnaires are designed to be valid, meaning that they measure what they are intended to measure and are not influenced by other factors.

Advantage of Questionnaire

Some Advantage of Questionnaire are as follows:

• Standardization: Questionnaires allow researchers to ask the same questions to all participants in a standardized manner. This helps ensure consistency in the data collected and eliminates potential bias that might arise if questions were asked differently to different participants.
• Efficiency: Questionnaires can be administered to a large number of people at once, making them an efficient way to collect data from a large sample.
• Anonymity: Participants can remain anonymous when completing a questionnaire, which may make them more likely to answer honestly and openly.
• Cost-effective: Questionnaires can be relatively inexpensive to administer compared to other research methods, such as interviews or focus groups.
• Objectivity: Because questionnaires are typically designed to collect quantitative data, they can be analyzed objectively without the influence of the researcher’s subjective interpretation.
• Flexibility: Questionnaires can be adapted to a wide range of research questions and can be used in various settings, including online surveys, mail surveys, or in-person interviews.

Limitations of Questionnaire

Limitations of Questionnaire are as follows:

• Limited depth: Questionnaires are typically designed to collect quantitative data, which may not provide a complete understanding of the topic being studied. Questionnaires may miss important details and nuances that could be captured through other research methods, such as interviews or observations.
• R esponse bias: Participants may not always answer questions truthfully or accurately, either because they do not remember or because they want to present themselves in a particular way. This can lead to response bias, which can affect the validity and reliability of the data collected.
• Limited flexibility: While questionnaires can be adapted to a wide range of research questions, they may not be suitable for all types of research. For example, they may not be appropriate for studying complex phenomena or for exploring participants’ experiences and perceptions in-depth.
• Limited context: Questionnaires typically do not provide a rich contextual understanding of the topic being studied. They may not capture the broader social, cultural, or historical factors that may influence participants’ responses.
• Limited control : Researchers may not have control over how participants complete the questionnaire, which can lead to variations in response quality or consistency.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Surveys & Questionnaires

Surveys involve asking a series of questions to participants. They can be administered online, in person, or remotely (e.g. by post/mail). The data collected can be analysed quantitatively or qualitatively (or both). Researchers might carry out statistical surveys to make statistical inferences about the population being studied. Such inferences depend strongly on the survey questions used (Solomon, 2001) meaning that getting the wording right is crucial. For this reason, many test out surveys in pilot studies with smaller populations and use the results to refine their survey instrument.

Sampling for surveys can range between self-selection (e.g. where a link is shared with members of a target population in the hope they and others contribute data and share the survey) through to the use of specialised statistical techniques (“probability sampling”) that analyse results from a carefully selected sample to draw statistical conclusions about the wider population. Survey methodologies therefore cover a range of considerations including sampling, research instrument design, improving response rates, ensuring quality in data, and methods of analysis (Groves et al., 2011).

One common question format is to collect quantitative data alongside qualitative questions. This allows a more detailed description or justification for the answer given to be provided. Collecting ordinal data (e.g. ranking of preferences through a Likert scale) can be a way to make qualitative data more amenable to quantitative analysis. But there is no one superior approach: the crucial thing is that the survey questions and their phrasing aligns with the research question(s) correctly.

Surveys are widely used in education science and in the social sciences more generally. Surveys are highly efficient (both in terms of time and money) compared with other methods, and can be administered remotely. They can provide a series of data points on a subject which can be compared across the sample group(s). This provides a considerable degree of flexibility when it comes to analysing data as several variables may be tested at once. Surveys also work well when used alongside other methods, perhaps to provide a baseline of data (such as demographics) for the first step in a research study. They are also commonly used in evaluations of teaching & learning (i.e. after an intervention to assess the impact). However, there are some noteworthy disadvantages to using surveys. Respondents may not feel encouraged to provide accurate answers, or may not feel comfortable providing answers that present themselves in a unfavourable manner (particularly if the survey is not anonymous). “Closed” questions may have a lower validity rate than other question types as they might be interpreted differently. Data errors due to question non-responses may exist creating bias. Survey answer options should be selected carefully because they may be interpreted differently by respondents (Vehovar & Katja Lozar, 2008).

Surveys & Questionnaires: GO-GN Insights

Marjon Baas collected quantitative data through a questionnaire among teachers within an OER Community of Practice to explore the effect of the activities undertaken to encourage the use of the community on teachers’ behaviour in relation to OER.

“I used several theoretical models (Clements and Pawlowski, 2012; Cox and Trotter, 2017; Armellini and Nie, 2013) to conceptualise different aspects (that relate to) OER adoption. This enabled me as a researcher to design my specific research instruments.”

Judith Pete had a deliberate selection of twelve Sub-Saharan African universities across Kenya, Ghana and South Africa with randomly sampled students and lecturers to develop a representative view of OER. Separate questionnaires were used for students (n=2249) and lecturers (n=106).

“We used surveys to collect data across three continents. Online survey tools were very helpful in online data collection and, where that was not possible, local coordinators used physical copies of the survey and later entered the information into the database. This approach was cost-effective, versatile and quick and easy to implement. We were able to reach a wide range of respondents in a short time. Sometimes we wondered, though, whether all those who responded had enough time to fully process and understand the questions that they were being asked. We had to allocate a significant amount of time to curating the data afterwards.”

Samia Almousa adopted Unified Theory of Acceptance and Use of Technology (UTAUT) survey questionnaire, along with additional constructs (relating to information quality and culture) as a lens through which her research data is analysed.

“In my research, I have employed a Sequential Explanatory Mixed Methods Design (online questionnaires and semi-structured interviews) to examine the academics’ perceptions of OERs integration into their teaching practices, as well as to explore the motivations that encourage them to use and reuse OERs, and share their teaching materials in the public domain. The online questionnaire was an efficient and fast way to reach a large number of academics. I used the online survey platform, which does not require entering data or coding as data is input by the participants and answers are saved automatically (Sills & Song, 2002). Using questionnaires as a data collection tool has some drawbacks. In my study, the questionnaire I developed was long, which made some participants choose their answers randomly. In addition, I have received many responses from academics in other universities although the questionnaire was sent to the sample university. Since I expected this to happen, I required the participants to write the name of their university in the personal information section of the questionnaire, then excluded the responses from outside the research sample. My advice for any researcher attempting to use questionnaires as a data collection tool is to ensure that their questionnaire is as short and clear as possible to help the researcher in analysing the findings and the participants in answering all questions accurately. Additionally, personal questions should be as few as possible to protect the identity and privacy of the participants, and to obtain the ethical approval quickly.”

Olawale Kazeeem Iyikolakan adopted a descriptive survey of the correlational type. The author research design examines the relationship among the key research variables (technological self-efficacy, perception, and use of open educational resources) and to identify the most significant factors that influence academic performance of LIS undergraduates without a causal connection.

“The descriptive research design is used as a gathering of information about prevailing conditions or situations for the purpose of description and interpretation (Aggarwal, 2008). My research design examines the relationship among the key research variables (technological self-efficacy, perception, and use of open educational resources) to identify the most significant factors that influence academic performance of Library & Information Science undergraduates without a causal connection. Ponto (2015) describes that descriptive survey research is a useful and legitimate  approach to research that has clear benefits in helping to describe and explore variables and constructs of interest by using quantitative research strategies (e.g., using a survey with numerically rated items. “The reason for the choice of descriptive survey research instead of ex-post-facto quasi-experimental design is that this type of research design is used to capture people’s perceptions, views, use, about a current issue, current state of play or movements such as perception and use of OER. This research design comes with several merits as it enables the researcher to obtain the needed primary data directly from the respondents. Other advantages include: (1) Using this method, the researcher has no control over the variable; (2) the researcher can only report what has happened or what is happening. One of the demerits of this type of research design is that research results may reflect a certain level of bias due to the absence of statistical tests.”

Useful references for Surveys & Questionnaires: Aggarwal (2008); Fowler (2014); Groves et al., 2011); Lefever, Dal & Matthíasdóttir (2007); Ponto (2015); Sills & Song (2002); Solomon (2001); Vehovar & Manfreda (2008); Vehovar, Manfreda, & Berzelak (2018)

Research Methods Handbook Copyright © 2020 by Rob Farrow; Francisco Iniesto; Martin Weller; and Rebecca Pitt is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

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• Questionnaire Design | Methods, Question Types & Examples

Questionnaire Design | Methods, Question Types & Examples

Published on 6 May 2022 by Pritha Bhandari . Revised on 10 October 2022.

A questionnaire is a list of questions or items used to gather data from respondents about their attitudes, experiences, or opinions. Questionnaires can be used to collect quantitative and/or qualitative information.

Questionnaires are commonly used in market research as well as in the social and health sciences. For example, a company may ask for feedback about a recent customer service experience, or psychology researchers may investigate health risk perceptions using questionnaires.

Table of contents

Questionnaires vs surveys, questionnaire methods, open-ended vs closed-ended questions, question wording, question order, step-by-step guide to design, frequently asked questions about questionnaire design.

A survey is a research method where you collect and analyse data from a group of people. A questionnaire is a specific tool or instrument for collecting the data.

Designing a questionnaire means creating valid and reliable questions that address your research objectives, placing them in a useful order, and selecting an appropriate method for administration.

But designing a questionnaire is only one component of survey research. Survey research also involves defining the population you’re interested in, choosing an appropriate sampling method , administering questionnaires, data cleaning and analysis, and interpretation.

Sampling is important in survey research because you’ll often aim to generalise your results to the population. Gather data from a sample that represents the range of views in the population for externally valid results. There will always be some differences between the population and the sample, but minimising these will help you avoid sampling bias .

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Questionnaires can be self-administered or researcher-administered . Self-administered questionnaires are more common because they are easy to implement and inexpensive, but researcher-administered questionnaires allow deeper insights.

Self-administered questionnaires

Self-administered questionnaires can be delivered online or in paper-and-pen formats, in person or by post. All questions are standardised so that all respondents receive the same questions with identical wording.

Self-administered questionnaires can be:

• Cost-effective
• Easy to administer for small and large groups
• Anonymous and suitable for sensitive topics

But they may also be:

• Unsuitable for people with limited literacy or verbal skills
• Susceptible to a nonreponse bias (most people invited may not complete the questionnaire)
• Biased towards people who volunteer because impersonal survey requests often go ignored

Researcher-administered questionnaires

Researcher-administered questionnaires are interviews that take place by phone, in person, or online between researchers and respondents.

Researcher-administered questionnaires can:

• Help you ensure the respondents are representative of your target audience
• Allow clarifications of ambiguous or unclear questions and answers
• Have high response rates because it’s harder to refuse an interview when personal attention is given to respondents

But researcher-administered questionnaires can be limiting in terms of resources. They are:

• Costly and time-consuming to perform
• More difficult to analyse if you have qualitative responses
• Likely to contain experimenter bias or demand characteristics
• Likely to encourage social desirability bias in responses because of a lack of anonymity

Your questionnaire can include open-ended or closed-ended questions, or a combination of both.

Using closed-ended questions limits your responses, while open-ended questions enable a broad range of answers. You’ll need to balance these considerations with your available time and resources.

Closed-ended questions

Closed-ended, or restricted-choice, questions offer respondents a fixed set of choices to select from. Closed-ended questions are best for collecting data on categorical or quantitative variables.

Categorical variables can be nominal or ordinal. Quantitative variables can be interval or ratio. Understanding the type of variable and level of measurement means you can perform appropriate statistical analyses for generalisable results.

Examples of closed-ended questions for different variables

Nominal variables include categories that can’t be ranked, such as race or ethnicity. This includes binary or dichotomous categories.

It’s best to include categories that cover all possible answers and are mutually exclusive. There should be no overlap between response items.

In binary or dichotomous questions, you’ll give respondents only two options to choose from.

White Black or African American American Indian or Alaska Native Asian Native Hawaiian or Other Pacific Islander

Ordinal variables include categories that can be ranked. Consider how wide or narrow a range you’ll include in your response items, and their relevance to your respondents.

Likert-type questions collect ordinal data using rating scales with five or seven points.

When you have four or more Likert-type questions, you can treat the composite data as quantitative data on an interval scale . Intelligence tests, psychological scales, and personality inventories use multiple Likert-type questions to collect interval data.

With interval or ratio data, you can apply strong statistical hypothesis tests to address your research aims.

Pros and cons of closed-ended questions

Well-designed closed-ended questions are easy to understand and can be answered quickly. However, you might still miss important answers that are relevant to respondents. An incomplete set of response items may force some respondents to pick the closest alternative to their true answer. These types of questions may also miss out on valuable detail.

To solve these problems, you can make questions partially closed-ended, and include an open-ended option where respondents can fill in their own answer.

Open-ended questions

Open-ended, or long-form, questions allow respondents to give answers in their own words. Because there are no restrictions on their choices, respondents can answer in ways that researchers may not have otherwise considered. For example, respondents may want to answer ‘multiracial’ for the question on race rather than selecting from a restricted list.

• How do you feel about open science?
• How would you describe your personality?
• In your opinion, what is the biggest obstacle to productivity in remote work?

Open-ended questions have a few downsides.

They require more time and effort from respondents, which may deter them from completing the questionnaire.

For researchers, understanding and summarising responses to these questions can take a lot of time and resources. You’ll need to develop a systematic coding scheme to categorise answers, and you may also need to involve other researchers in data analysis for high reliability .

Question wording can influence your respondents’ answers, especially if the language is unclear, ambiguous, or biased. Good questions need to be understood by all respondents in the same way ( reliable ) and measure exactly what you’re interested in ( valid ).

Use clear language

You should design questions with your target audience in mind. Consider their familiarity with your questionnaire topics and language and tailor your questions to them.

For readability and clarity, avoid jargon or overly complex language. Don’t use double negatives because they can be harder to understand.

Use balanced framing

Respondents often answer in different ways depending on the question framing. Positive frames are interpreted as more neutral than negative frames and may encourage more socially desirable answers.

Use a mix of both positive and negative frames to avoid bias , and ensure that your question wording is balanced wherever possible.

Unbalanced questions focus on only one side of an argument. Respondents may be less likely to oppose the question if it is framed in a particular direction. It’s best practice to provide a counterargument within the question as well.

Avoid leading questions

Leading questions guide respondents towards answering in specific ways, even if that’s not how they truly feel, by explicitly or implicitly providing them with extra information.

It’s best to keep your questions short and specific to your topic of interest.

• The average daily work commute in the US takes 54.2 minutes and costs $29 per day. Since 2020, working from home has saved many employees time and money. Do you favour flexible work-from-home policies even after it’s safe to return to offices?
• Experts agree that a well-balanced diet provides sufficient vitamins and minerals, and multivitamins and supplements are not necessary or effective. Do you agree or disagree that multivitamins are helpful for balanced nutrition?

Keep your questions focused

Ask about only one idea at a time and avoid double-barrelled questions. Double-barrelled questions ask about more than one item at a time, which can confuse respondents.

This question could be difficult to answer for respondents who feel strongly about the right to clean drinking water but not high-speed internet. They might only answer about the topic they feel passionate about or provide a neutral answer instead – but neither of these options capture their true answers.

Instead, you should ask two separate questions to gauge respondents’ opinions.

Strongly Agree Agree Undecided Disagree Strongly Disagree

Do you agree or disagree that the government should be responsible for providing high-speed internet to everyone?

You can organise the questions logically, with a clear progression from simple to complex. Alternatively, you can randomise the question order between respondents.

Logical flow

Using a logical flow to your question order means starting with simple questions, such as behavioural or opinion questions, and ending with more complex, sensitive, or controversial questions.

The question order that you use can significantly affect the responses by priming them in specific directions. Question order effects, or context effects, occur when earlier questions influence the responses to later questions, reducing the validity of your questionnaire.

While demographic questions are usually unaffected by order effects, questions about opinions and attitudes are more susceptible to them.

• How knowledgeable are you about Joe Biden’s executive orders in his first 100 days?
• Are you satisfied or dissatisfied with the way Joe Biden is managing the economy?
• Do you approve or disapprove of the way Joe Biden is handling his job as president?

It’s important to minimise order effects because they can be a source of systematic error or bias in your study.

Randomisation

Randomisation involves presenting individual respondents with the same questionnaire but with different question orders.

When you use randomisation, order effects will be minimised in your dataset. But a randomised order may also make it harder for respondents to process your questionnaire. Some questions may need more cognitive effort, while others are easier to answer, so a random order could require more time or mental capacity for respondents to switch between questions.

Follow this step-by-step guide to design your questionnaire.

Step 1: Define your goals and objectives

The first step of designing a questionnaire is determining your aims.

• What topics or experiences are you studying?
• What specifically do you want to find out?
• Is a self-report questionnaire an appropriate tool for investigating this topic?

Once you’ve specified your research aims, you can operationalise your variables of interest into questionnaire items. Operationalising concepts means turning them from abstract ideas into concrete measurements. Every question needs to address a defined need and have a clear purpose.

Step 2: Use questions that are suitable for your sample

Create appropriate questions by taking the perspective of your respondents. Consider their language proficiency and available time and energy when designing your questionnaire.

• Are the respondents familiar with the language and terms used in your questions?
• Would any of the questions insult, confuse, or embarrass them?
• Do the response items for any closed-ended questions capture all possible answers?
• Are the response items mutually exclusive?
• Do the respondents have time to respond to open-ended questions?

Consider all possible options for responses to closed-ended questions. From a respondent’s perspective, a lack of response options reflecting their point of view or true answer may make them feel alienated or excluded. In turn, they’ll become disengaged or inattentive to the rest of the questionnaire.

Step 3: Decide on your questionnaire length and question order

Once you have your questions, make sure that the length and order of your questions are appropriate for your sample.

If respondents are not being incentivised or compensated, keep your questionnaire short and easy to answer. Otherwise, your sample may be biased with only highly motivated respondents completing the questionnaire.

Decide on your question order based on your aims and resources. Use a logical flow if your respondents have limited time or if you cannot randomise questions. Randomising questions helps you avoid bias, but it can take more complex statistical analysis to interpret your data.

Step 4: Pretest your questionnaire

When you have a complete list of questions, you’ll need to pretest it to make sure what you’re asking is always clear and unambiguous. Pretesting helps you catch any errors or points of confusion before performing your study.

Ask friends, classmates, or members of your target audience to complete your questionnaire using the same method you’ll use for your research. Find out if any questions were particularly difficult to answer or if the directions were unclear or inconsistent, and make changes as necessary.

If you have the resources, running a pilot study will help you test the validity and reliability of your questionnaire. A pilot study is a practice run of the full study, and it includes sampling, data collection , and analysis.

You can find out whether your procedures are unfeasible or susceptible to bias and make changes in time, but you can’t test a hypothesis with this type of study because it’s usually statistically underpowered .

A questionnaire is a data collection tool or instrument, while a survey is an overarching research method that involves collecting and analysing data from people using questionnaires.

Closed-ended, or restricted-choice, questions offer respondents a fixed set of choices to select from. These questions are easier to answer quickly.

Open-ended or long-form questions allow respondents to answer in their own words. Because there are no restrictions on their choices, respondents can answer in ways that researchers may not have otherwise considered.

A Likert scale is a rating scale that quantitatively assesses opinions, attitudes, or behaviours. It is made up of four or more questions that measure a single attitude or trait when response scores are combined.

To use a Likert scale in a survey , you present participants with Likert-type questions or statements, and a continuum of items, usually with five or seven possible responses, to capture their degree of agreement.

You can organise the questions logically, with a clear progression from simple to complex, or randomly between respondents. A logical flow helps respondents process the questionnaire easier and quicker, but it may lead to bias. Randomisation can minimise the bias from order effects.

Questionnaires can be self-administered or researcher-administered.

Researcher-administered questionnaires are interviews that take place by phone, in person, or online between researchers and respondents. You can gain deeper insights by clarifying questions for respondents or asking follow-up questions.

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How to Design and Validate A Questionnaire: A Guide

Affiliations.

• 1 Department of Pharmacology, Government Institute of Medical Sciences, Greater Noida, Uttar Pradesh, 201310, India.
• 2 Department of Pharmacology, AIIMS, Jodhpur, Rajasthan, 342005, India.
• 3 Department of Gynaecology and Obstetrics, AIIMS Jodhpur, Rajasthan, India.
• PMID: 30084336
• DOI: 10.2174/1574884713666180807151328

Background: A questionnaire is a commonly used data collection method and is a very crucial part of the research. However, designing a questionnaire can be a daunting task for postgraduate students.

Methods: This manuscript illustrates the various steps required in questionnaire designing and provides an insight into the essentials of questionnaire construction and validation. Data from a questionnaire should be able to comprehend the objectives of the study; else it may lead to wrong interpretation or bias, decreased power of study and inability to generalize the study results.

Conclusion: Since it is equally important to verify the usefulness of the designed questionnaire, the article briefly describes the process of psychometric evaluation of a questionnaire.

Keywords: Questionnaire validation; WOMAC; pragmatic research; psychometric assessment; questionnaire designing; validity..

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• The making of Asian American identity and knowledge of Asian history in the U.S.
• Immigrant ties shape Asian Americans' identities and their life in the U.S.
• Asians in the U.S. share similar views among themselves and with the U.S. public on what it means to be American
• How Asians in the U.S. describe their identity
• Asian adults and the general public agree: U.S. Asians have many different cultures
• Whom do U.S. Asians consider Asian?
• A majority of Asian adults say others would describe them as Asian when walking past them on the street
• For many Asian adults, where they were born shapes friendships formed in the U.S.
• Most Asian adults are comfortable with intermarriage
• Some Asians say they have hidden their heritage
• Connections with other Asian Americans, politics and political parties
• Need for a national leader advancing the concerns of Asian Americans
• Asian American registered voters and political party
• About one-quarter of Asian adults say they are informed about U.S. Asian history
• What being ‘truly American’ means to U.S. Asians
• Fewer than half of U.S. Asians consider themselves typical Americans
• What do Asian Americans view as important for the American dream?
• Most Asian adults say the American dream is within reach, but about a quarter say they will never achieve it
• Acknowledgments
• Sample design
• Data collection
• Weighting and variance estimation
• Largest origin groups
• Educational attainment
• Immigration status
• Length of time living in the U.S. among immigrants
• Citizenship status among immigrants

Pew Research Center conducted this analysis to understand the rich diversity of people of Asian origin or ancestry living in the United States and their views of identity. The study is part of the Center’s multiyear, comprehensive, in-depth quantitative and qualitative research effort focused on the nation’s Asian population. Its centerpiece is this nationally representative survey of 7,006 Asian adults exploring the experiences, attitudes and views of Asians living in the U.S. The survey sampled U.S. adults who self-identify as Asian, either alone or in combination with other races or Hispanic ethnicity. It was offered in six languages: Chinese (Simplified and Traditional), English, Hindi, Korean, Tagalog and Vietnamese. Responses were collected from July 5, 2022, to Jan. 27, 2023, by Westat on behalf of Pew Research Center.

The Center recruited a large sample to examine the diversity of the U.S. Asian population, with oversamples of the Chinese, Filipino, Indian, Korean and Vietnamese populations. These are the five largest origin groups among Asian Americans. The survey also includes a large enough sample of self-identified Japanese adults, making findings about them reportable. In this report, the six largest ethnic groups include those who identify with one Asian ethnicity only, either alone or in combination with a non-Asian race or ethnicity. Together, these six groups constitute 81% of all U.S. Asian adults, according to a Pew Research Center analysis of the Census Bureau’s 2021 American Community Survey (ACS), and are the six groups whose attitudes and opinions are highlighted throughout the report. Survey respondents were drawn from a national sample of residential mailing addresses, which included addresses from all 50 states and the District of Columbia. Specialized surnames list frames maintained by the Marketing Systems Group were used to supplement the sample. Those eligible to complete the survey were offered the opportunity to do so online or by mail with a paper questionnaire. For more details, see the Methodology . For questions used in this analysis, see the Topline Questionnaire .

The survey research plan and questionnaire were reviewed and approved by Westat’s institutional review board (IRB), which is an external and independent committee of experts specializing in protecting the rights of research participants.

Even though the U.S. Asian population was the fastest growing racial and ethnic group in the country from 2000 to 2019 , it is still a relatively small population. According to the 2021 American Community Survey, the country’s Asian population constitutes 7% of the U.S. population (of all ages) and 7% of adults (those ages 18 and older).

Pew Research Center designed this study with these details in mind to be as inclusive as possible of the diversity of Asian American experiences. Even so, survey research is limited when it comes to documenting the views and attitudes of the less populous Asian origin groups in the U.S. To address this, the survey was complemented by 66 pre-survey focus groups of Asian adults , conducted from Aug. 4 to Oct. 14, 2021, with 264 recruited participants from 18 Asian origin groups. Focus group discussions were conducted in 18 different languages and moderated by members of their origin groups.

Findings for less populous Asian origin groups in the U.S., those who are not among the six largest Asian origin groups, are grouped under the category “Other” in this report and are included in the overall Asian adult findings in the report. These ethnic origin groups each make up about 2% or less of the Asian population in the U.S., making it challenging to recruit nationally representative samples for each origin group. The group “Other” includes those who identify with one Asian ethnicity only, either alone or in combination with a non-Asian race or Hispanic ethnicity. Findings for those who identify with two or more Asian ethnicities are not presented by themselves in this report but are included in the overall Asian adult findings.

To learn more about how members of less populous Asian origin groups in the U.S. identify, see the quote sorter based on our focus group discussions. There, you can read how participants describe their identity in their own words.

For this analysis, an additional national survey of 5,132 U.S. adults was conducted from Dec. 5 to 11, 2022, using Pew Research Center’s American Trends Panel . The survey of U.S. adults was conducted in English and Spanish. Respondents are recruited through national, random sampling of residential addresses.

Pew Research Center has conducted multiple studies that focus on Asian Americans. Previous demographic studies examined the diversity of origins , key facts , and rising income inequality among Asians living in the U.S. and key findings about U.S. immigrants. Qualitative studies have focused on what it means to be Asian in America as well as barriers to English language learning among Asian immigrants. Previous surveys have focused on concerns over discrimination and violence against Asian Americans, as well as studies about their religious beliefs . Find these publications and more on the Center’s Asian Americans topic page .

Pew Research Center is a subsidiary of The Pew Charitable Trusts, its primary funder. The Center’s Asian American portfolio was funded by The Pew Charitable Trusts, with generous support from The Asian American Foundation; Chan Zuckerberg Initiative DAF, an advised fund of the Silicon Valley Community Foundation; the Robert Wood Johnson Foundation; the Henry Luce Foundation; the Doris Duke Foundation; The Wallace H. Coulter Foundation; The Dirk and Charlene Kabcenell Foundation; The Long Family Foundation; Lu-Hebert Fund; Gee Family Foundation; Joseph Cotchett; the Julian Abdey and Sabrina Moyle Charitable Fund; and Nanci Nishimura.

We would also like to thank the Leaders Forum for its thought leadership and valuable assistance in helping make this survey possible.

The strategic communications campaign used to promote the research was made possible with generous support from the Doris Duke Foundation.

The terms Asian, Asians living in the United States , U.S. Asian population and Asian Americans are used interchangeably throughout this report to refer to U.S. adults who self-identify as Asian, either alone or in combination with other races or Hispanic identity.

Ethnicity and ethnic origin labels, such as Chinese and Chinese origin, are used interchangeably in this report for findings for ethnic origin groups, such as Chinese, Filipino, Indian, Japanese, Korean or Vietnamese. For this report, ethnicity is not nationality. For example, Chinese in this report are those self-identifying as of Chinese ethnicity, rather than necessarily being a current or former citizen of the People’s Republic of China. Ethnic origin groups in this report include those who self-identify as one Asian ethnicity only, either alone or in combination with a non-Asian race or ethnicity.

Less populous Asian origin groups in this report are those who self-identify with ethnic origin groups that are not among the six largest Asian origin groups. The term includes those who identify with only one Asian ethnicity. These ethnic origin groups each represent about 2% or less of the overall Asian population in the U.S. For example, those who identify as Burmese, Hmong or Pakistani are included in this category. These groups are unreportable on their own due to small sample sizes, but collectively they are reportable under this category.

The terms Asian origins and Asian origin groups are used interchangeably throughout this report to describe ethnic origin groups.

Immigrants in this report are people who were not U.S. citizens at birth – in other words, those born outside the U.S., Puerto Rico or other U.S. territories to parents who are not U.S. citizens. I mmigrant , first generation and foreign born are used interchangeably to refer to this group.  

Naturalized citizens are immigrants who are lawful permanent residents who have fulfilled the length of stay and other requirements to become U.S. citizens and who have taken the oath of citizenship.

U.S. born refers to people born in the 50 U.S. states or the District of Columbia, Puerto Rico or other U.S. territories.

Second generation refers to people born in the 50 states or the District of Columbia, Puerto Rico or other U.S. territories with at least one first-generation (immigrant) parent.

Third or higher generation refers to people born in the 50 states or the District of Columbia, Puerto Rico or other U.S. territories with both parents born in the 50 states, D.C., Puerto Rico or other U.S. territories.

The nation’s Asian population is fast growing and diverse. Numbering more than 23 million, the population has ancestral roots across the vast, ethnically and culturally rich Asian continent. For Asians living in the United States, this diversity is reflected in how they describe their own identity. According to a new, nationwide, comprehensive survey of Asian adults living in the U.S., 52% say they most often use ethnic labels that reflect their heritage and family roots, either alone or together with “American,” to describe themselves. Chinese or Chinese American, Filipino or Filipino American, and Indian or Indian American are examples of these variations.

There are other ways in which Asians living in the U.S. describe their identity. About half (51%) of Asian adults say they use American on its own (10%), together with their ethnicity (25%) or together with “Asian” as Asian American (16%) when describing their identity, highlighting their links to the U.S.

And while pan-ethnic labels such as Asian and Asian American are commonly used to describe this diverse population broadly, the new survey shows that when describing themselves, just 28% use the label Asian (12%) on its own or the label Asian American (16%).

The survey also finds that other labels are used by Asian Americans. Some 6% say they most often prefer regional terms such as South Asian and Southeast Asian when describing themselves.

Asian adults see more cultural differences than commonalities across their group as well. When asked to choose between two statements – that Asians in the U.S. share a common culture, or that Asians in the U.S. have many different cultures – nearly all (90%) say U.S. Asians have many different cultures. Just 9% say Asians living in the U.S. share a common culture. This view is widely held across many demographic groups among Asian Americans, according to the survey.

The view that Asian Americans have many different cultures is also one held by the general public, according to another Pew Research Center survey of U.S. adults, conducted in December 2022. Among all U.S. adults, 80% say Asians in the U.S. have many different cultures, while 18% say they share a common culture. 1

Though Asian Americans’ identities reflect their diverse cultures and origins, Asian adults also report certain shared experiences. A majority (60%) say most people would describe them as “Asian” while walking past them on the street, indicating most Asian adults feel they are seen by others as a single group, despite the population’s diversity. One-in-five say they have hidden a part of their heritage (their ethnic food, cultural practices, ethnic clothing or religious practices) from others who are not Asian, in some cases out of fear of embarrassment or discrimination. Notably, Asian adults ages 18 to 29 are more likely to say they have done this than Asians 65 and older (39% vs. 5%).

Asian adults in the U.S. also feel connected with other Asian Americans. About six-in-ten (59%) say that what happens to Asians in the U.S. affects their own lives, at least to some extent. 2 And about two-thirds (68%) of Asian Americans say it is extremely or very important to have a national leader advocating for the concerns and needs of the Asian population in the U.S.

The new survey also shows that large majorities of Asian adults share similar views on what it takes to be considered truly American. And they consider many of the same factors to be important in their views of the American dream.

These are among the key findings from Pew Research Center’s new survey of Asian American adults, conducted by mail and online from July 5, 2022, to Jan. 27, 2023. This is the largest nationally representative survey of its kind to date that focused on Asian Americans. The survey was conducted in English and five Asian languages, among a representative sample of 7,006 Asian adults living in the United States. 

Asian Americans are 7% of the U.S. population, according to a Pew Research Center analysis of the 2021 American Community Survey. Their population is diverse, with roots in more than 20 countries in East Asia, Southeast Asia and the Indian subcontinent. About 54% of the national Asian population are immigrants. The six largest origin groups (Chinese, Filipino, Indian, Japanese, Korean and Vietnamese), a focus of this survey and report, together account for 79% of all Asian Americans.

Overall, about 34% of Asian Americans are the U.S.-born children of immigrant parents, and another 14% are of third or higher generation (meaning their parents were born in the U.S. as well), according to a Pew Research Center analysis of the 2022 Current Population Survey, March Annual Social and Economic Supplement.

This survey and report focus on Asian adults in the U.S. The six largest origin groups together account for 81% of Asian adults. And 68% of Asian American adults are immigrants, according to Center analysis of the 2021 American Community Survey. Additionally, 25% are the U.S.-born children of immigrant parents and 10% are of third or higher generation, according to Center analysis of government data.

The pan-ethnic term “Asian American” emerged in Berkeley, California, in the 1960s as part of a political movement to organize the diverse U.S. Asian population. The creation of an Asian American identity was in reaction to a long history of exclusion of Asians in the country, including the 1882 Chinese Exclusion Act and a pair of Supreme Court cases in the 1920s clarifying that Asians, including South Asians, are not “free White persons” and therefore were excluded from becoming naturalized U.S. citizens. 3 Subsequently, the term was adopted by the federal government and today is the principal identity label used by media, academics, researchers and others to describe today’s diverse Asian American population.

In most cases today, someone is considered Asian or Asian American if they self-identify as such. But Asian Americans do not necessarily agree on which regional or ethnic groups from the Asian continent they consider to be Asian, according to the new survey. The vast majority of Asian adults say they consider those from East Asia, such as Chinese or Koreans (89%); Southeast Asia, such as Vietnamese or Filipinos (88%); and to a lesser extent South Asia such as Indians or Pakistanis (67%) to be Asian.

But Asian adults are split on whether they consider Central Asians such as Afghans or Kazakhs to be Asian (43% of Asian adults say they are). While about half of Indian adults (56%) say they would include Central Asians in the category Asian, fewer than half of Filipino (40%), Chinese (39%), Japanese (34%), Korean (32%) and Vietnamese (30%) adults consider them Asian.

Few Asians say they are knowledgeable about U.S. Asian history

Asian Americans have a long history in the United States. From Chinese laborers who helped build the first transcontinental railroad, to Japanese immigrants who arrived as plantation workers in what is now the state of Hawaii, to the incarceration of Japanese Americans during World War II, to Filipinos being treated as U.S. nationals while the Philippines was a U.S. territory, the Asian American experience has been a part of U.S. history.

With the passage of the landmark Immigration and Nationality Act of 1965, a new wave of immigrants from Asia began arriving in the United States, creating a new, contemporary U.S. Asian history. The Vietnam War and other conflicts in Southeast Asia brought Vietnamese and other Southeast Asian refugees to the U.S. , first with the passage of the 1975 Indochina Migration and Refugee Assistance Act and then with the Refugee Act of 1980. The 1990 Immigration Act raised immigration ceilings and set in place processes that allowed the flows of Asian immigrants, particularly of high-skilled immigrants, to continue and expand. The U.S. technology boom of the 1990s and 2000s attracted many high-skilled immigrants, particularly from India and China, to tech centers around the country.

This rich history, however, is little-known to Asian adults, according to the new survey. One-in-four (24%) say they are very or extremely informed about history of Asians in the United States, while an equal share (24%) say they are little or not at all informed.

The majority of those very or extremely informed about the history of Asians in the U.S. say they learned about this history through informal channels: internet (82%), media (76%) and family and friends (70%). In contrast, 49% learned about it from college or university courses and 39% from elementary through high school.

Immigrant ties shape Asian Americans’ identities and their life in the U.S.

Immigration experiences, connections with home countries, and how long someone has lived in the U.S. shape many Asian Americans’ identities. Among Asian adults in the U.S., immigrants are more likely than those who are U.S. born to describe their identity most often with their ethnic labels, either alone or together with the label American (56% vs. 41%).

Meanwhile, Asian immigrants are less likely than U.S.-born Asians (46% vs. 65%) to say they most often describe themselves as American in some way – whether by their ethnic label combined with American, as Asian American, or simply as American. Still, nearly half of Asian immigrants describe themselves in one of these three ways.

When it comes to identifying with the label Asian – either alone or as Asian American – immigrant and U.S.-born Asians are about equally likely to say they do so (28% and 29% respectively). Immigrant Asians are less likely than U.S.-born Asians to identify most often as Asian American (14% vs. 21%).

On the question of seeing themselves more as a “typical American” or “very different from a typical American,” Asian immigrant adults are far less likely than those born in the U.S. to think of themselves as a typical American (37% vs. 69%).

Nativity is also tied to how Asians in the U.S. develop their friendships. Those who immigrated to the U.S. are more likely to have friends who are Asian or of the same ethnicity as them than are U.S.-born Asians (56% vs. 38%).

Asian immigrants (15%) are also less likely than U.S.-born Asians (32%) to have ever hidden a part of their heritage from people who are not Asian. When asked in an open-ended question to explain why they hide aspects of their culture, some U.S.-born respondents mentioned phrases such as “fear of discrimination,” “being teased” and “embarrassing.”

Views of identity among Asian American immigrants are often tied to time spent in the U.S.

How long Asian immigrants have lived in the U.S. also shapes their identity and experiences. Those who arrived in the U.S. in the past 10 years are more likely than those who arrived more than 20 years ago to say they most often use their ethnicity, such as Filipino or Vietnamese, to describe themselves. And about two-thirds (65%) of those who arrived in the U.S. in the past decade describe their identity most often with their ethnicity’s name, either alone or combined with American, compared with 54% among those who have been in the country for more than two decades.

Roughly half (54%) of those who have arrived in the past 10 years say they most often use only their ethnicity to describe themselves, compared with just 21% of those who arrived more than two decades ago who say the same.

On the other hand, just 17% of Asian immigrants who arrived in the country in the past 10 years describe themselves most often as American, by their ethnic label combined with American, or as Asian American, while 59% of those who arrived more than 20 years ago do so.

When it comes to their circle of friends, 60% of Asian immigrants who arrived in the past 10 years say most or all of their friends are also Asian Americans, while 50% of those who arrived more than 20 years ago say the same.

And when asked if they think of themselves as typical Americans or not, Asian immigrants who arrived in the U.S. in the past decade are substantially less likely than those who arrived more than two decades ago to say they are typical Americans (20% vs. 48%).

The new survey also explored the views Asian Americans have about traits that make one “truly American.” Overall, Asian Americans and the general U.S. population share similar views of what it means to be American. Nearly all Asian adults and U.S. adults say that accepting people of diverse racial and religious backgrounds (94% and 91%), believing in individual freedoms (92% and 94%) and respecting U.S. political institutions and laws (89% and 87%) are important for being truly American.

Similarly, Asian Americans and the U.S. general population share in their views about the American dream. They say having freedom of choice in how to live one’s life (96% and 97% respectively), having a good family life (96% and 94%), retiring comfortably (96% and 94%) and owning a home (both 86%) are important to their view of the American dream. Smaller shares of Asian and U.S. adults (30% and 27%) say owning a business is important to their view of the American dream.

Here are other survey findings highlighting the diverse views and attitudes of Asian adults living in the U.S.:

• Indian adults are the most likely of the six largest Asian origin groups to say they most often use their ethnicity, without the addition of “American,” to describe themselves. About four-in-ten Indian adults (41%) say they do this. By comparison, smaller shares of Korean (30%), Filipino (29%), Chinese (26%) and Vietnamese (23%) adults do the same. Japanese adults (14%) are the least likely among the largest groups to use their ethnic identity term alone.
• Japanese adults are the least likely among the largest Asian origin groups to say they have friendships with other Asians. About one-in-three Japanese adults (34%) say most or all their friends share their own ethnicity or are otherwise Asian. By contrast, about half of all Indian (55%), Vietnamese (55%), Chinese (51%), Korean (50%) and Filipino (48%) respondents say the same.
• One-in-four Korean adults (25%) say they have hidden part of their heritage from people who are not Asian. Some 20% of Indian, 19% of Chinese, 18% of Vietnamese, 16% of Filipino and 14% of Japanese adults say they have done the same.
• Across the largest ethnic groups, about half or more say that what happens to Asians in the U.S. affects what happens in their own lives. About two-thirds of Korean (67%) and Chinese (65%) adults say this. By comparison, 61% of Japanese, 54% of Filipino, 55% of Indian and 52% of Vietnamese adults say they are impacted by what happens to Asians nationally.
• Most Asian adults among the largest ethnic origin groups say a national leader advancing the U.S. Asian community’s concerns is important. Roughly three-in-four Filipino (74%) and Chinese (73%) adults say it is very or extremely important to for the U.S. Asian community to have a national leader advancing its concerns. A majority of Vietnamese (69%), Korean (66%), Japanese (63%) and Indian adults (62%) says the same.  
• About half of Vietnamese registered voters (51%) identify with or lean to the Republican Party. In contrast, about two-thirds of Indian (68%), Filipino (68%) and Korean (67%) registered voters identify with or lean toward the Democratic Party. And 56% of Chinese registered voters also associate with the Democratic Party. 
• This finding is from a nationally representative survey of 5,132 U.S. adults conducted by Pew Research Center from Dec. 5 to 11, 2022, using the Center’s American Trends Panel . ↩
• In recent years, a major source of concern and fear among many Asian adults in the U.S. has been the rise in reported violence against Asian Americans . ↩
• For more on the history of the creation of an Asian American identity, see Lee, Jennifer and Karthick Ramakrishnan. 2019. “ Who counts as Asian .” Ethnic and Racial Studies. ↩

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AI Index Report

Welcome to the seventh edition of the AI Index report. The 2024 Index is our most comprehensive to date and arrives at an important moment when AI’s influence on society has never been more pronounced. This year, we have broadened our scope to more extensively cover essential trends such as technical advancements in AI, public perceptions of the technology, and the geopolitical dynamics surrounding its development. Featuring more original data than ever before, this edition introduces new estimates on AI training costs, detailed analyses of the responsible AI landscape, and an entirely new chapter dedicated to AI’s impact on science and medicine.

Read the 2024 AI Index Report

The AI Index report tracks, collates, distills, and visualizes data related to artificial intelligence (AI). Our mission is to provide unbiased, rigorously vetted, broadly sourced data in order for policymakers, researchers, executives, journalists, and the general public to develop a more thorough and nuanced understanding of the complex field of AI.

The AI Index is recognized globally as one of the most credible and authoritative sources for data and insights on artificial intelligence. Previous editions have been cited in major newspapers, including the The New York Times, Bloomberg, and The Guardian, have amassed hundreds of academic citations, and been referenced by high-level policymakers in the United States, the United Kingdom, and the European Union, among other places. This year’s edition surpasses all previous ones in size, scale, and scope, reflecting the growing significance that AI is coming to hold in all of our lives.

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Ray Perrault

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Katrina Ligett

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Staff members.

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Letter from the co-directors.

A decade ago, the best AI systems in the world were unable to classify objects in images at a human level. AI struggled with language comprehension and could not solve math problems. Today, AI systems routinely exceed human performance on standard benchmarks.

Progress accelerated in 2023. New state-of-the-art systems like GPT-4, Gemini, and Claude 3 are impressively multimodal: They can generate fluent text in dozens of languages, process audio, and even explain memes. As AI has improved, it has increasingly forced its way into our lives. Companies are racing to build AI-based products, and AI is increasingly being used by the general public. But current AI technology still has significant problems. It cannot reliably deal with facts, perform complex reasoning, or explain its conclusions.

AI faces two interrelated futures. First, technology continues to improve and is increasingly used, having major consequences for productivity and employment. It can be put to both good and bad uses. In the second future, the adoption of AI is constrained by the limitations of the technology. Regardless of which future unfolds, governments are increasingly concerned. They are stepping in to encourage the upside, such as funding university R&D and incentivizing private investment. Governments are also aiming to manage the potential downsides, such as impacts on employment, privacy concerns, misinformation, and intellectual property rights.

As AI rapidly evolves, the AI Index aims to help the AI community, policymakers, business leaders, journalists, and the general public navigate this complex landscape. It provides ongoing, objective snapshots tracking several key areas: technical progress in AI capabilities, the community and investments driving AI development and deployment, public opinion on current and potential future impacts, and policy measures taken to stimulate AI innovation while managing its risks and challenges. By comprehensively monitoring the AI ecosystem, the Index serves as an important resource for understanding this transformative technological force.

On the technical front, this year’s AI Index reports that the number of new large language models released worldwide in 2023 doubled over the previous year. Two-thirds were open-source, but the highest-performing models came from industry players with closed systems. Gemini Ultra became the first LLM to reach human-level performance on the Massive Multitask Language Understanding (MMLU) benchmark; performance on the benchmark has improved by 15 percentage points since last year. Additionally, GPT-4 achieved an impressive 0.97 mean win rate score on the comprehensive Holistic Evaluation of Language Models (HELM) benchmark, which includes MMLU among other evaluations.

Although global private investment in AI decreased for the second consecutive year, investment in generative AI skyrocketed. More Fortune 500 earnings calls mentioned AI than ever before, and new studies show that AI tangibly boosts worker productivity. On the policymaking front, global mentions of AI in legislative proceedings have never been higher. U.S. regulators passed more AI-related regulations in 2023 than ever before. Still, many expressed concerns about AI’s ability to generate deepfakes and impact elections. The public became more aware of AI, and studies suggest that they responded with nervousness.

Ray Perrault Co-director, AI Index

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New EY US Consulting study: employees overwhelmingly expect empathy in the workplace, but many say it feels disingenuous

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The majority (86%) of employees believe empathetic leadership boosts morale while 87% of employees say empathy is essential to fostering an inclusive environment.

As many employees face downsizings, restructurings and a looming global recession, most say that empathic leadership is a desired attribute but feel it can be disingenuous when not paired with action, according to the 2023 Ernst & Young LLP ( EY US )  Empathy in Business Survey .

The study of more than 1,000 employed US workers examines how empathy affects leaders, employees, and operations in the workplace. The survey follows the initial EY Consulting analysis of empathy in 2021 and finds workers feel that mutual empathy between company leaders and employees leads to increased efficiency (88%), creativity (87%), job satisfaction (87%), idea sharing (86%), innovation (85%) and even company revenue (83%).

“A  transformation’s success  or failure is rooted in human emotions, and this research spotlights just how critical empathy is in leadership,” said  Raj Sharma , EY  Americas Consulting  Vice Chair. “Recent years taught us that leading with empathy is a soft and powerful trait that helps empower employers and employees to collaborate better, and ultimately create a culture of accountability.”

The evolving state of empathy in the workplace

There are many upsides to empathetic leadership in the workplace, including:

• Inspiring positive change within the workplace (87%)
• Mutual respect between employees and leaders (87%)
• Increased productivity among employees (85%)
• Reduced employee turnover (78%)

“Time and again we have found through our research that in order for businesses to successfully transform, they must put humans at the center with empathetic leadership to create transparency and provide employees with psychological safety,” said  Kim Billeter , EY Americas  People Advisory Services  Leader. “Empathy is a powerful force that must be embedded organically into every aspect of an organization, otherwise the inconsistency has a dramatic impact on the overall culture and authenticity of an organization.”

In fact, half (52%) of employees currently believe their company’s efforts to be empathetic toward employees are dishonest ― up from 46% in 2021, and employees increasingly report a lack of follow-through when it comes to company promises (47% compared to 42% in 2021).

To fulfill the authenticity equation, previous EY research indicates offering flexibility is essential. In the 2022 EY US Generation Survey, 92% of employees surveyed across all four workplace generations said that company culture has an impact on their decision to remain with their current  employer.

Lead with empathy  now  to combat the workplace challenges ahead

While leaders may experience lower employee attrition rates now when compared to the Great Resignation, a resurgence is brewing. Many economists expect a soft landing from the looming recession and with it may come turnover, particularly if employees already feel disconnected from their employer or from each other.

In fact, failing to feel a sense of belonging at work or connection with coworkers is a growing reason why employees quit their jobs. About half (50% and 48% in 2021) left a previous job because they didn’t feel like they belonged, and more employees now say they left a previous job because they had difficulty connecting with colleagues (42% vs. 37% in 2021).

“What happens outside of work has a direct impact on how people show up. It’s no longer enough for leaders to think of a person in one dimension – as an employee or as a professional within the organization,” said  Ginnie Carlier , EY Americas Vice Chair – Talent. “Leading with empathy helps move from the transactional and to the transformational Human Value Proposition, where people feel supported both personally and professionally.”

2023 EY Empathy in Business Survey methodology

EY US  commissioned a third-party vendor to conduct the 2023 EY Empathy in Business Survey, following the 2021 Empathy in Business Survey. The survey among 1,012 Americans who are employed, either full-time or part-time, was completed between October 23 and November 6, 2022. At the total level, the study has a margin of error of +/- 3 percentage points at the 95% confidence level.

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6 in 10 U.S. Catholics are in favor of abortion rights, Pew Research report finds

Jason DeRose

Pope Francis remains popular among U.S. Catholics, with 75% having favorable views of him, according to a Pew Research report. But many self-identified Catholics disagree with various teachings of their church. Andrew Medichini/AP hide caption

Pope Francis remains popular among U.S. Catholics, with 75% having favorable views of him, according to a Pew Research report. But many self-identified Catholics disagree with various teachings of their church.

Catholics in the U.S., one of the country's largest single Christian groups, hold far more diverse views on abortion rights than the official teaching of their church.

While the Catholic Church itself holds that abortion is wrong and should not be legal, 6 in 10 U.S. adult Catholics say abortion should be legal in all or most cases, according to a newly released profile of Catholicism by Pew Research .

Catholic opinion about abortion rights, according to the report, tends to align with political leanings: Fewer Catholic Republicans favor legal abortion than Catholic Democrats. And Pew says Hispanic Catholics, who make up one-third of the U.S. church, are slightly more in favor of legal abortion than white Catholics.

Despite church prohibitions, Catholics still choose IVF to have children

Pew found that 20% of the U.S. population identifies as Catholic, but only about 3 in 10 say they attend mass regularly. Opinions about abortion rights appear to be related to how often someone worships — just 34% of Catholics who attend mass weekly say abortion should be legal in all or most cases, whereas that number jumps to 68% among those who attend mass monthly or less.

Most U.S. Catholics are white (57%), but that number has dropped by 8 percentage points since 2007, according the new report. About 33% identify as Hispanic, 4% Asian, 2% Black, and 3% describe themselves as another race.

Pew Research also found that as of February, Pope Francis remains highly popular, with 75% of U.S. Catholics rating him favorably. However, there is a partisan divide, with Catholic Democrats more strongly supporting him.

About 4 in 10 U.S. Catholics view Francis as a major agent of change, with 3 in 10 saying he is a minor agent of change.

Catholic Church works to explain what same-sex blessings are and are not

Pew reports that many U.S. Catholics would welcome more change. Some 83% say they want the church to allow the use of contraception, 69% say priests should be allowed to get married, 64% say women should be allowed to become priests, and 54% say the Catholic Church should recognize same-sex marriage.

In December 2023, the Vatican issued guidance to priests that they may bless people in same-sex relationships. But the church insists those blessings not be construed in any way to be a form of marriage or even take place as part of a worship service.

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Understanding and Evaluating Survey Research

A variety of methodologic approaches exist for individuals interested in conducting research. Selection of a research approach depends on a number of factors, including the purpose of the research, the type of research questions to be answered, and the availability of resources. The purpose of this article is to describe survey research as one approach to the conduct of research so that the reader can critically evaluate the appropriateness of the conclusions from studies employing survey research.

SURVEY RESEARCH

Survey research is defined as "the collection of information from a sample of individuals through their responses to questions" ( Check & Schutt, 2012, p. 160 ). This type of research allows for a variety of methods to recruit participants, collect data, and utilize various methods of instrumentation. Survey research can use quantitative research strategies (e.g., using questionnaires with numerically rated items), qualitative research strategies (e.g., using open-ended questions), or both strategies (i.e., mixed methods). As it is often used to describe and explore human behavior, surveys are therefore frequently used in social and psychological research ( Singleton & Straits, 2009 ).

Information has been obtained from individuals and groups through the use of survey research for decades. It can range from asking a few targeted questions of individuals on a street corner to obtain information related to behaviors and preferences, to a more rigorous study using multiple valid and reliable instruments. Common examples of less rigorous surveys include marketing or political surveys of consumer patterns and public opinion polls.

Survey research has historically included large population-based data collection. The primary purpose of this type of survey research was to obtain information describing characteristics of a large sample of individuals of interest relatively quickly. Large census surveys obtaining information reflecting demographic and personal characteristics and consumer feedback surveys are prime examples. These surveys were often provided through the mail and were intended to describe demographic characteristics of individuals or obtain opinions on which to base programs or products for a population or group.

More recently, survey research has developed into a rigorous approach to research, with scientifically tested strategies detailing who to include (representative sample), what and how to distribute (survey method), and when to initiate the survey and follow up with nonresponders (reducing nonresponse error), in order to ensure a high-quality research process and outcome. Currently, the term "survey" can reflect a range of research aims, sampling and recruitment strategies, data collection instruments, and methods of survey administration.

Given this range of options in the conduct of survey research, it is imperative for the consumer/reader of survey research to understand the potential for bias in survey research as well as the tested techniques for reducing bias, in order to draw appropriate conclusions about the information reported in this manner. Common types of error in research, along with the sources of error and strategies for reducing error as described throughout this article, are summarized in the Table .

Sources of Error in Survey Research and Strategies to Reduce Error

The goal of sampling strategies in survey research is to obtain a sufficient sample that is representative of the population of interest. It is often not feasible to collect data from an entire population of interest (e.g., all individuals with lung cancer); therefore, a subset of the population or sample is used to estimate the population responses (e.g., individuals with lung cancer currently receiving treatment). A large random sample increases the likelihood that the responses from the sample will accurately reflect the entire population. In order to accurately draw conclusions about the population, the sample must include individuals with characteristics similar to the population.

It is therefore necessary to correctly identify the population of interest (e.g., individuals with lung cancer currently receiving treatment vs. all individuals with lung cancer). The sample will ideally include individuals who reflect the intended population in terms of all characteristics of the population (e.g., sex, socioeconomic characteristics, symptom experience) and contain a similar distribution of individuals with those characteristics. As discussed by Mady Stovall beginning on page 162, Fujimori et al. ( 2014 ), for example, were interested in the population of oncologists. The authors obtained a sample of oncologists from two hospitals in Japan. These participants may or may not have similar characteristics to all oncologists in Japan.

Participant recruitment strategies can affect the adequacy and representativeness of the sample obtained. Using diverse recruitment strategies can help improve the size of the sample and help ensure adequate coverage of the intended population. For example, if a survey researcher intends to obtain a sample of individuals with breast cancer representative of all individuals with breast cancer in the United States, the researcher would want to use recruitment strategies that would recruit both women and men, individuals from rural and urban settings, individuals receiving and not receiving active treatment, and so on. Because of the difficulty in obtaining samples representative of a large population, researchers may focus the population of interest to a subset of individuals (e.g., women with stage III or IV breast cancer). Large census surveys require extremely large samples to adequately represent the characteristics of the population because they are intended to represent the entire population.

DATA COLLECTION METHODS

Survey research may use a variety of data collection methods with the most common being questionnaires and interviews. Questionnaires may be self-administered or administered by a professional, may be administered individually or in a group, and typically include a series of items reflecting the research aims. Questionnaires may include demographic questions in addition to valid and reliable research instruments ( Costanzo, Stawski, Ryff, Coe, & Almeida, 2012 ; DuBenske et al., 2014 ; Ponto, Ellington, Mellon, & Beck, 2010 ). It is helpful to the reader when authors describe the contents of the survey questionnaire so that the reader can interpret and evaluate the potential for errors of validity (e.g., items or instruments that do not measure what they are intended to measure) and reliability (e.g., items or instruments that do not measure a construct consistently). Helpful examples of articles that describe the survey instruments exist in the literature ( Buerhaus et al., 2012 ).

Questionnaires may be in paper form and mailed to participants, delivered in an electronic format via email or an Internet-based program such as SurveyMonkey, or a combination of both, giving the participant the option to choose which method is preferred ( Ponto et al., 2010 ). Using a combination of methods of survey administration can help to ensure better sample coverage (i.e., all individuals in the population having a chance of inclusion in the sample) therefore reducing coverage error ( Dillman, Smyth, & Christian, 2014 ; Singleton & Straits, 2009 ). For example, if a researcher were to only use an Internet-delivered questionnaire, individuals without access to a computer would be excluded from participation. Self-administered mailed, group, or Internet-based questionnaires are relatively low cost and practical for a large sample ( Check & Schutt, 2012 ).

Dillman et al. ( 2014 ) have described and tested a tailored design method for survey research. Improving the visual appeal and graphics of surveys by using a font size appropriate for the respondents, ordering items logically without creating unintended response bias, and arranging items clearly on each page can increase the response rate to electronic questionnaires. Attending to these and other issues in electronic questionnaires can help reduce measurement error (i.e., lack of validity or reliability) and help ensure a better response rate.

Conducting interviews is another approach to data collection used in survey research. Interviews may be conducted by phone, computer, or in person and have the benefit of visually identifying the nonverbal response(s) of the interviewee and subsequently being able to clarify the intended question. An interviewer can use probing comments to obtain more information about a question or topic and can request clarification of an unclear response ( Singleton & Straits, 2009 ). Interviews can be costly and time intensive, and therefore are relatively impractical for large samples.

Some authors advocate for using mixed methods for survey research when no one method is adequate to address the planned research aims, to reduce the potential for measurement and non-response error, and to better tailor the study methods to the intended sample ( Dillman et al., 2014 ; Singleton & Straits, 2009 ). For example, a mixed methods survey research approach may begin with distributing a questionnaire and following up with telephone interviews to clarify unclear survey responses ( Singleton & Straits, 2009 ). Mixed methods might also be used when visual or auditory deficits preclude an individual from completing a questionnaire or participating in an interview.

FUJIMORI ET AL.: SURVEY RESEARCH

Fujimori et al. ( 2014 ) described the use of survey research in a study of the effect of communication skills training for oncologists on oncologist and patient outcomes (e.g., oncologist’s performance and confidence and patient’s distress, satisfaction, and trust). A sample of 30 oncologists from two hospitals was obtained and though the authors provided a power analysis concluding an adequate number of oncologist participants to detect differences between baseline and follow-up scores, the conclusions of the study may not be generalizable to a broader population of oncologists. Oncologists were randomized to either an intervention group (i.e., communication skills training) or a control group (i.e., no training).

Fujimori et al. ( 2014 ) chose a quantitative approach to collect data from oncologist and patient participants regarding the study outcome variables. Self-report numeric ratings were used to measure oncologist confidence and patient distress, satisfaction, and trust. Oncologist confidence was measured using two instruments each using 10-point Likert rating scales. The Hospital Anxiety and Depression Scale (HADS) was used to measure patient distress and has demonstrated validity and reliability in a number of populations including individuals with cancer ( Bjelland, Dahl, Haug, & Neckelmann, 2002 ). Patient satisfaction and trust were measured using 0 to 10 numeric rating scales. Numeric observer ratings were used to measure oncologist performance of communication skills based on a videotaped interaction with a standardized patient. Participants completed the same questionnaires at baseline and follow-up.

The authors clearly describe what data were collected from all participants. Providing additional information about the manner in which questionnaires were distributed (i.e., electronic, mail), the setting in which data were collected (e.g., home, clinic), and the design of the survey instruments (e.g., visual appeal, format, content, arrangement of items) would assist the reader in drawing conclusions about the potential for measurement and nonresponse error. The authors describe conducting a follow-up phone call or mail inquiry for nonresponders, using the Dillman et al. ( 2014 ) tailored design for survey research follow-up may have reduced nonresponse error.

CONCLUSIONS

Survey research is a useful and legitimate approach to research that has clear benefits in helping to describe and explore variables and constructs of interest. Survey research, like all research, has the potential for a variety of sources of error, but several strategies exist to reduce the potential for error. Advanced practitioners aware of the potential sources of error and strategies to improve survey research can better determine how and whether the conclusions from a survey research study apply to practice.

The author has no potential conflicts of interest to disclose.