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Writing Survey Questions

Perhaps the most important part of the survey process is the creation of questions that accurately measure the opinions, experiences and behaviors of the public. Accurate random sampling will be wasted if the information gathered is built on a shaky foundation of ambiguous or biased questions. Creating good measures involves both writing good questions and organizing them to form the questionnaire.

Questionnaire design is a multistage process that requires attention to many details at once. Designing the questionnaire is complicated because surveys can ask about topics in varying degrees of detail, questions can be asked in different ways, and questions asked earlier in a survey may influence how people respond to later questions. Researchers are also often interested in measuring change over time and therefore must be attentive to how opinions or behaviors have been measured in prior surveys.

Surveyors may conduct pilot tests or focus groups in the early stages of questionnaire development in order to better understand how people think about an issue or comprehend a question. Pretesting a survey is an essential step in the questionnaire design process to evaluate how people respond to the overall questionnaire and specific questions, especially when questions are being introduced for the first time.

For many years, surveyors approached questionnaire design as an art, but substantial research over the past forty years has demonstrated that there is a lot of science involved in crafting a good survey questionnaire. Here, we discuss the pitfalls and best practices of designing questionnaires.

Question development

There are several steps involved in developing a survey questionnaire. The first is identifying what topics will be covered in the survey. For Pew Research Center surveys, this involves thinking about what is happening in our nation and the world and what will be relevant to the public, policymakers and the media. We also track opinion on a variety of issues over time so we often ensure that we update these trends on a regular basis to better understand whether people’s opinions are changing.

At Pew Research Center, questionnaire development is a collaborative and iterative process where staff meet to discuss drafts of the questionnaire several times over the course of its development. We frequently test new survey questions ahead of time through qualitative research methods such as  focus groups , cognitive interviews, pretesting (often using an  online, opt-in sample ), or a combination of these approaches. Researchers use insights from this testing to refine questions before they are asked in a production survey, such as on the ATP.

Measuring change over time

Many surveyors want to track changes over time in people’s attitudes, opinions and behaviors. To measure change, questions are asked at two or more points in time. A cross-sectional design surveys different people in the same population at multiple points in time. A panel, such as the ATP, surveys the same people over time. However, it is common for the set of people in survey panels to change over time as new panelists are added and some prior panelists drop out. Many of the questions in Pew Research Center surveys have been asked in prior polls. Asking the same questions at different points in time allows us to report on changes in the overall views of the general public (or a subset of the public, such as registered voters, men or Black Americans), or what we call “trending the data”.

When measuring change over time, it is important to use the same question wording and to be sensitive to where the question is asked in the questionnaire to maintain a similar context as when the question was asked previously (see  question wording  and  question order  for further information). All of our survey reports include a topline questionnaire that provides the exact question wording and sequencing, along with results from the current survey and previous surveys in which we asked the question.

The Center’s transition from conducting U.S. surveys by live telephone interviewing to an online panel (around 2014 to 2020) complicated some opinion trends, but not others. Opinion trends that ask about sensitive topics (e.g., personal finances or attending religious services ) or that elicited volunteered answers (e.g., “neither” or “don’t know”) over the phone tended to show larger differences than other trends when shifting from phone polls to the online ATP. The Center adopted several strategies for coping with changes to data trends that may be related to this change in methodology. If there is evidence suggesting that a change in a trend stems from switching from phone to online measurement, Center reports flag that possibility for readers to try to head off confusion or erroneous conclusions.

Open- and closed-ended questions

One of the most significant decisions that can affect how people answer questions is whether the question is posed as an open-ended question, where respondents provide a response in their own words, or a closed-ended question, where they are asked to choose from a list of answer choices.

For example, in a poll conducted after the 2008 presidential election, people responded very differently to two versions of the question: “What one issue mattered most to you in deciding how you voted for president?” One was closed-ended and the other open-ended. In the closed-ended version, respondents were provided five options and could volunteer an option not on the list.

When explicitly offered the economy as a response, more than half of respondents (58%) chose this answer; only 35% of those who responded to the open-ended version volunteered the economy. Moreover, among those asked the closed-ended version, fewer than one-in-ten (8%) provided a response other than the five they were read. By contrast, fully 43% of those asked the open-ended version provided a response not listed in the closed-ended version of the question. All of the other issues were chosen at least slightly more often when explicitly offered in the closed-ended version than in the open-ended version. (Also see  “High Marks for the Campaign, a High Bar for Obama”  for more information.)

Researchers will sometimes conduct a pilot study using open-ended questions to discover which answers are most common. They will then develop closed-ended questions based off that pilot study that include the most common responses as answer choices. In this way, the questions may better reflect what the public is thinking, how they view a particular issue, or bring certain issues to light that the researchers may not have been aware of.

When asking closed-ended questions, the choice of options provided, how each option is described, the number of response options offered, and the order in which options are read can all influence how people respond. One example of the impact of how categories are defined can be found in a Pew Research Center poll conducted in January 2002. When half of the sample was asked whether it was “more important for President Bush to focus on domestic policy or foreign policy,” 52% chose domestic policy while only 34% said foreign policy. When the category “foreign policy” was narrowed to a specific aspect – “the war on terrorism” – far more people chose it; only 33% chose domestic policy while 52% chose the war on terrorism.

In most circumstances, the number of answer choices should be kept to a relatively small number – just four or perhaps five at most – especially in telephone surveys. Psychological research indicates that people have a hard time keeping more than this number of choices in mind at one time. When the question is asking about an objective fact and/or demographics, such as the religious affiliation of the respondent, more categories can be used. In fact, they are encouraged to ensure inclusivity. For example, Pew Research Center’s standard religion questions include more than 12 different categories, beginning with the most common affiliations (Protestant and Catholic). Most respondents have no trouble with this question because they can expect to see their religious group within that list in a self-administered survey.

In addition to the number and choice of response options offered, the order of answer categories can influence how people respond to closed-ended questions. Research suggests that in telephone surveys respondents more frequently choose items heard later in a list (a “recency effect”), and in self-administered surveys, they tend to choose items at the top of the list (a “primacy” effect).

Because of concerns about the effects of category order on responses to closed-ended questions, many sets of response options in Pew Research Center’s surveys are programmed to be randomized to ensure that the options are not asked in the same order for each respondent. Rotating or randomizing means that questions or items in a list are not asked in the same order to each respondent. Answers to questions are sometimes affected by questions that precede them. By presenting questions in a different order to each respondent, we ensure that each question gets asked in the same context as every other question the same number of times (e.g., first, last or any position in between). This does not eliminate the potential impact of previous questions on the current question, but it does ensure that this bias is spread randomly across all of the questions or items in the list. For instance, in the example discussed above about what issue mattered most in people’s vote, the order of the five issues in the closed-ended version of the question was randomized so that no one issue appeared early or late in the list for all respondents. Randomization of response items does not eliminate order effects, but it does ensure that this type of bias is spread randomly.

Questions with ordinal response categories – those with an underlying order (e.g., excellent, good, only fair, poor OR very favorable, mostly favorable, mostly unfavorable, very unfavorable) – are generally not randomized because the order of the categories conveys important information to help respondents answer the question. Generally, these types of scales should be presented in order so respondents can easily place their responses along the continuum, but the order can be reversed for some respondents. For example, in one of Pew Research Center’s questions about abortion, half of the sample is asked whether abortion should be “legal in all cases, legal in most cases, illegal in most cases, illegal in all cases,” while the other half of the sample is asked the same question with the response categories read in reverse order, starting with “illegal in all cases.” Again, reversing the order does not eliminate the recency effect but distributes it randomly across the population.

Question wording

The choice of words and phrases in a question is critical in expressing the meaning and intent of the question to the respondent and ensuring that all respondents interpret the question the same way. Even small wording differences can substantially affect the answers people provide.

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An example of a wording difference that had a significant impact on responses comes from a January 2003 Pew Research Center survey. When people were asked whether they would “favor or oppose taking military action in Iraq to end Saddam Hussein’s rule,” 68% said they favored military action while 25% said they opposed military action. However, when asked whether they would “favor or oppose taking military action in Iraq to end Saddam Hussein’s rule  even if it meant that U.S. forces might suffer thousands of casualties, ” responses were dramatically different; only 43% said they favored military action, while 48% said they opposed it. The introduction of U.S. casualties altered the context of the question and influenced whether people favored or opposed military action in Iraq.

There has been a substantial amount of research to gauge the impact of different ways of asking questions and how to minimize differences in the way respondents interpret what is being asked. The issues related to question wording are more numerous than can be treated adequately in this short space, but below are a few of the important things to consider:

First, it is important to ask questions that are clear and specific and that each respondent will be able to answer. If a question is open-ended, it should be evident to respondents that they can answer in their own words and what type of response they should provide (an issue or problem, a month, number of days, etc.). Closed-ended questions should include all reasonable responses (i.e., the list of options is exhaustive) and the response categories should not overlap (i.e., response options should be mutually exclusive). Further, it is important to discern when it is best to use forced-choice close-ended questions (often denoted with a radio button in online surveys) versus “select-all-that-apply” lists (or check-all boxes). A 2019 Center study found that forced-choice questions tend to yield more accurate responses, especially for sensitive questions.  Based on that research, the Center generally avoids using select-all-that-apply questions.

It is also important to ask only one question at a time. Questions that ask respondents to evaluate more than one concept (known as double-barreled questions) – such as “How much confidence do you have in President Obama to handle domestic and foreign policy?” – are difficult for respondents to answer and often lead to responses that are difficult to interpret. In this example, it would be more effective to ask two separate questions, one about domestic policy and another about foreign policy.

In general, questions that use simple and concrete language are more easily understood by respondents. It is especially important to consider the education level of the survey population when thinking about how easy it will be for respondents to interpret and answer a question. Double negatives (e.g., do you favor or oppose  not  allowing gays and lesbians to legally marry) or unfamiliar abbreviations or jargon (e.g., ANWR instead of Arctic National Wildlife Refuge) can result in respondent confusion and should be avoided.

Similarly, it is important to consider whether certain words may be viewed as biased or potentially offensive to some respondents, as well as the emotional reaction that some words may provoke. For example, in a 2005 Pew Research Center survey, 51% of respondents said they favored “making it legal for doctors to give terminally ill patients the means to end their lives,” but only 44% said they favored “making it legal for doctors to assist terminally ill patients in committing suicide.” Although both versions of the question are asking about the same thing, the reaction of respondents was different. In another example, respondents have reacted differently to questions using the word “welfare” as opposed to the more generic “assistance to the poor.” Several experiments have shown that there is much greater public support for expanding “assistance to the poor” than for expanding “welfare.”

We often write two versions of a question and ask half of the survey sample one version of the question and the other half the second version. Thus, we say we have two  forms  of the questionnaire. Respondents are assigned randomly to receive either form, so we can assume that the two groups of respondents are essentially identical. On questions where two versions are used, significant differences in the answers between the two forms tell us that the difference is a result of the way we worded the two versions.

One of the most common formats used in survey questions is the “agree-disagree” format. In this type of question, respondents are asked whether they agree or disagree with a particular statement. Research has shown that, compared with the better educated and better informed, less educated and less informed respondents have a greater tendency to agree with such statements. This is sometimes called an “acquiescence bias” (since some kinds of respondents are more likely to acquiesce to the assertion than are others). This behavior is even more pronounced when there’s an interviewer present, rather than when the survey is self-administered. A better practice is to offer respondents a choice between alternative statements. A Pew Research Center experiment with one of its routinely asked values questions illustrates the difference that question format can make. Not only does the forced choice format yield a very different result overall from the agree-disagree format, but the pattern of answers between respondents with more or less formal education also tends to be very different.

One other challenge in developing questionnaires is what is called “social desirability bias.” People have a natural tendency to want to be accepted and liked, and this may lead people to provide inaccurate answers to questions that deal with sensitive subjects. Research has shown that respondents understate alcohol and drug use, tax evasion and racial bias. They also may overstate church attendance, charitable contributions and the likelihood that they will vote in an election. Researchers attempt to account for this potential bias in crafting questions about these topics. For instance, when Pew Research Center surveys ask about past voting behavior, it is important to note that circumstances may have prevented the respondent from voting: “In the 2012 presidential election between Barack Obama and Mitt Romney, did things come up that kept you from voting, or did you happen to vote?” The choice of response options can also make it easier for people to be honest. For example, a question about church attendance might include three of six response options that indicate infrequent attendance. Research has also shown that social desirability bias can be greater when an interviewer is present (e.g., telephone and face-to-face surveys) than when respondents complete the survey themselves (e.g., paper and web surveys).

Lastly, because slight modifications in question wording can affect responses, identical question wording should be used when the intention is to compare results to those from earlier surveys. Similarly, because question wording and responses can vary based on the mode used to survey respondents, researchers should carefully evaluate the likely effects on trend measurements if a different survey mode will be used to assess change in opinion over time.

Question order

Once the survey questions are developed, particular attention should be paid to how they are ordered in the questionnaire. Surveyors must be attentive to how questions early in a questionnaire may have unintended effects on how respondents answer subsequent questions. Researchers have demonstrated that the order in which questions are asked can influence how people respond; earlier questions can unintentionally provide context for the questions that follow (these effects are called “order effects”).

One kind of order effect can be seen in responses to open-ended questions. Pew Research Center surveys generally ask open-ended questions about national problems, opinions about leaders and similar topics near the beginning of the questionnaire. If closed-ended questions that relate to the topic are placed before the open-ended question, respondents are much more likely to mention concepts or considerations raised in those earlier questions when responding to the open-ended question.

For closed-ended opinion questions, there are two main types of order effects: contrast effects ( where the order results in greater differences in responses), and assimilation effects (where responses are more similar as a result of their order).

An example of a contrast effect can be seen in a Pew Research Center poll conducted in October 2003, a dozen years before same-sex marriage was legalized in the U.S. That poll found that people were more likely to favor allowing gays and lesbians to enter into legal agreements that give them the same rights as married couples when this question was asked after one about whether they favored or opposed allowing gays and lesbians to marry (45% favored legal agreements when asked after the marriage question, but 37% favored legal agreements without the immediate preceding context of a question about same-sex marriage). Responses to the question about same-sex marriage, meanwhile, were not significantly affected by its placement before or after the legal agreements question.

Another experiment embedded in a December 2008 Pew Research Center poll also resulted in a contrast effect. When people were asked “All in all, are you satisfied or dissatisfied with the way things are going in this country today?” immediately after having been asked “Do you approve or disapprove of the way George W. Bush is handling his job as president?”; 88% said they were dissatisfied, compared with only 78% without the context of the prior question.

Responses to presidential approval remained relatively unchanged whether national satisfaction was asked before or after it. A similar finding occurred in December 2004 when both satisfaction and presidential approval were much higher (57% were dissatisfied when Bush approval was asked first vs. 51% when general satisfaction was asked first).

Several studies also have shown that asking a more specific question before a more general question (e.g., asking about happiness with one’s marriage before asking about one’s overall happiness) can result in a contrast effect. Although some exceptions have been found, people tend to avoid redundancy by excluding the more specific question from the general rating.

Assimilation effects occur when responses to two questions are more consistent or closer together because of their placement in the questionnaire. We found an example of an assimilation effect in a Pew Research Center poll conducted in November 2008 when we asked whether Republican leaders should work with Obama or stand up to him on important issues and whether Democratic leaders should work with Republican leaders or stand up to them on important issues. People were more likely to say that Republican leaders should work with Obama when the question was preceded by the one asking what Democratic leaders should do in working with Republican leaders (81% vs. 66%). However, when people were first asked about Republican leaders working with Obama, fewer said that Democratic leaders should work with Republican leaders (71% vs. 82%).

The order questions are asked is of particular importance when tracking trends over time. As a result, care should be taken to ensure that the context is similar each time a question is asked. Modifying the context of the question could call into question any observed changes over time (see  measuring change over time  for more information).

A questionnaire, like a conversation, should be grouped by topic and unfold in a logical order. It is often helpful to begin the survey with simple questions that respondents will find interesting and engaging. Throughout the survey, an effort should be made to keep the survey interesting and not overburden respondents with several difficult questions right after one another. Demographic questions such as income, education or age should not be asked near the beginning of a survey unless they are needed to determine eligibility for the survey or for routing respondents through particular sections of the questionnaire. Even then, it is best to precede such items with more interesting and engaging questions. One virtue of survey panels like the ATP is that demographic questions usually only need to be asked once a year, not in each survey.

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How to Develop a Questionnaire for Research

Last Updated: July 21, 2024 Fact Checked

This article was co-authored by Alexander Ruiz, M.Ed. . Alexander Ruiz is an Educational Consultant and the Educational Director of Link Educational Institute, a tutoring business based in Claremont, California that provides customizable educational plans, subject and test prep tutoring, and college application consulting. With over a decade and a half of experience in the education industry, Alexander coaches students to increase their self-awareness and emotional intelligence while achieving skills and the goal of achieving skills and higher education. He holds a BA in Psychology from Florida International University and an MA in Education from Georgia Southern University. There are 12 references cited in this article, which can be found at the bottom of the page. This article has been fact-checked, ensuring the accuracy of any cited facts and confirming the authority of its sources. This article has been viewed 592,688 times.

A questionnaire is a technique for collecting data in which a respondent provides answers to a series of questions. [1] X Research source To develop a questionnaire that will collect the data you want takes effort and time. However, by taking a step-by-step approach to questionnaire development, you can come up with an effective means to collect data that will answer your unique research question.

Designing Your Questionnaire

• Come up with a research question. It can be one question or several, but this should be the focal point of your questionnaire.
• Develop one or several hypotheses that you want to test. The questions that you include on your questionnaire should be aimed at systematically testing these hypotheses.

• Dichotomous question: this is a question that will generally be a “yes/no” question, but may also be an “agree/disagree” question. It is the quickest and simplest question to analyze, but is not a highly sensitive measure.
• Open-ended questions: these questions allow the respondent to respond in their own words. They can be useful for gaining insight into the feelings of the respondent, but can be a challenge when it comes to analysis of data. It is recommended to use open-ended questions to address the issue of “why.” [2] X Research source
• Multiple choice questions: these questions consist of three or more mutually-exclusive categories and ask for a single answer or several answers. [3] X Research source Multiple choice questions allow for easy analysis of results, but may not give the respondent the answer they want.
• Rank-order (or ordinal) scale questions: this type of question asks your respondent to rank items or choose items in a particular order from a set. For example, it might ask your respondents to order five things from least to most important. These types of questions forces discrimination among alternatives, but does not address the issue of why the respondent made these discriminations. [4] X Research source
• Rating scale questions: these questions allow the respondent to assess a particular issue based on a given dimension. You can provide a scale that gives an equal number of positive and negative choices, for example, ranging from “strongly agree” to “strongly disagree.” [5] X Research source These questions are very flexible, but also do not answer the question “why.”

• Write questions that are succinct and simple. You should not be writing complex statements or using technical jargon, as it will only confuse your respondents and lead to incorrect responses.
• Ask only one question at a time. This will help avoid confusion
• Asking questions such as these usually require you to anonymize or encrypt the demographic data you collect.
• Determine if you will include an answer such as “I don’t know” or “Not applicable to me.” While these can give your respondents a way of not answering certain questions, providing these options can also lead to missing data, which can be problematic during data analysis.
• Put the most important questions at the beginning of your questionnaire. This can help you gather important data even if you sense that your respondents may be becoming distracted by the end of the questionnaire.

• Only include questions that are directly useful to your research question. [8] X Trustworthy Source Food and Agricultural Organization of the United Nations Specialized agency of the United Nations responsible for leading international efforts to end world hunger and improve nutrition Go to source A questionnaire is not an opportunity to collect all kinds of information about your respondents.
• Avoid asking redundant questions. This will frustrate those who are taking your questionnaire.

• Consider if you want your questionnaire to collect information from both men and women. Some studies will only survey one sex.
• Consider including a range of ages in your target demographic. For example, you can consider young adult to be 18-29 years old, adults to be 30-54 years old, and mature adults to be 55+. Providing the an age range will help you get more respondents than limiting yourself to a specific age.
• Consider what else would make a person a target for your questionnaire. Do they need to drive a car? Do they need to have health insurance? Do they need to have a child under 3? Make sure you are very clear about this before you distribute your questionnaire.

• Consider an anonymous questionnaire. You may not want to ask for names on your questionnaire. This is one step you can take to prevent privacy, however it is often possible to figure out a respondent’s identity using other demographic information (such as age, physical features, or zipcode).
• Consider de-identifying the identity of your respondents. Give each questionnaire (and thus, each respondent) a unique number or word, and only refer to them using that new identifier. Shred any personal information that can be used to determine identity.
• Remember that you do not need to collect much demographic information to be able to identify someone. People may be wary to provide this information, so you may get more respondents by asking less demographic questions (if it is possible for your questionnaire).
• Make sure you destroy all identifying information after your study is complete.

Writing your questionnaire

• My name is Jack Smith and I am one of the creators of this questionnaire. I am part of the Department of Psychology at the University of Michigan, where I am focusing in developing cognition in infants.
• I’m Kelly Smith, a 3rd year undergraduate student at the University of New Mexico. This questionnaire is part of my final exam in statistics.
• My name is Steve Johnson, and I’m a marketing analyst for The Best Company. I’ve been working on questionnaire development to determine attitudes surrounding drug use in Canada for several years.

• I am collecting data regarding the attitudes surrounding gun control. This information is being collected for my Anthropology 101 class at the University of Maryland.
• This questionnaire will ask you 15 questions about your eating and exercise habits. We are attempting to make a correlation between healthy eating, frequency of exercise, and incidence of cancer in mature adults.
• This questionnaire will ask you about your recent experiences with international air travel. There will be three sections of questions that will ask you to recount your recent trips and your feelings surrounding these trips, as well as your travel plans for the future. We are looking to understand how a person’s feelings surrounding air travel impact their future plans.

• Beware that if you are collecting information for a university or for publication, you may need to check in with your institution’s Institutional Review Board (IRB) for permission before beginning. Most research universities have a dedicated IRB staff, and their information can usually be found on the school’s website.
• Remember that transparency is best. It is important to be honest about what will happen with the data you collect.
• Include an informed consent for if necessary. Note that you cannot guarantee confidentiality, but you will make all reasonable attempts to ensure that you protect their information. [11] X Research source

• Time yourself taking the survey. Then consider that it will take some people longer than you, and some people less time than you.
• Provide a time range instead of a specific time. For example, it’s better to say that a survey will take between 15 and 30 minutes than to say it will take 15 minutes and have some respondents quit halfway through.
• Use this as a reason to keep your survey concise! You will feel much better asking people to take a 20 minute survey than you will asking them to take a 3 hour one.

• Incentives can attract the wrong kind of respondent. You don’t want to incorporate responses from people who rush through your questionnaire just to get the reward at the end. This is a danger of offering an incentive. [12] X Research source
• Incentives can encourage people to respond to your survey who might not have responded without a reward. This is a situation in which incentives can help you reach your target number of respondents. [13] X Research source
• Consider the strategy used by SurveyMonkey. Instead of directly paying respondents to take their surveys, they offer 50 cents to the charity of their choice when a respondent fills out a survey. They feel that this lessens the chances that a respondent will fill out a questionnaire out of pure self-interest. [14] X Research source
• Consider entering each respondent in to a drawing for a prize if they complete the questionnaire. You can offer a 25$ gift card to a restaurant, or a new iPod, or a ticket to a movie. This makes it less tempting just to respond to your questionnaire for the incentive alone, but still offers the chance of a pleasant reward.

• Always proof read. Check for spelling, grammar, and punctuation errors.
• Include a title. This is a good way for your respondents to understand the focus of the survey as quickly as possible.
• Thank your respondents. Thank them for taking the time and effort to complete your survey.

Distributing Your Questionnaire

• Was the questionnaire easy to understand? Were there any questions that confused you?
• Was the questionnaire easy to access? (Especially important if your questionnaire is online).
• Do you feel the questionnaire was worth your time?
• Were you comfortable answering the questions asked?
• Are there any improvements you would make to the questionnaire?

• Use an online site, such as SurveyMonkey.com. This site allows you to write your own questionnaire with their survey builder, and provides additional options such as the option to buy a target audience and use their analytics to analyze your data. [18] X Research source
• Consider using the mail. If you mail your survey, always make sure you include a self-addressed stamped envelope so that the respondent can easily mail their responses back. Make sure that your questionnaire will fit inside a standard business envelope.
• Conduct face-to-face interviews. This can be a good way to ensure that you are reaching your target demographic and can reduce missing information in your questionnaires, as it is more difficult for a respondent to avoid answering a question when you ask it directly.
• Try using the telephone. While this can be a more time-effective way to collect your data, it can be difficult to get people to respond to telephone questionnaires.

• Make your deadline reasonable. Giving respondents up to 2 weeks to answer should be more than sufficient. Anything longer and you risk your respondents forgetting about your questionnaire.
• Consider providing a reminder. A week before the deadline is a good time to provide a gentle reminder about returning the questionnaire. Include a replacement of the questionnaire in case it has been misplaced by your respondent.

Community Q&A

You Might Also Like

• ↑ https://www.questionpro.com/blog/what-is-a-questionnaire/
• ↑ https://www.hotjar.com/blog/open-ended-questions/
• ↑ https://www.questionpro.com/a/showArticle.do?articleID=survey-questions
• ↑ https://surveysparrow.com/blog/ranking-questions-examples/
• ↑ https://www.lumoa.me/blog/rating-scale/
• ↑ http://www.sciencebuddies.org/science-fair-projects/project_ideas/Soc_survey.shtml
• ↑ http://www.fao.org/docrep/W3241E/w3241e05.htm
• ↑ http://managementhelp.org/businessresearch/questionaires.htm
• ↑ https://www.surveymonkey.com/mp/survey-rewards/
• ↑ http://www.ideafit.com/fitness-library/how-to-develop-a-questionnaire
• ↑ https://www.surveymonkey.com/mp/take-a-tour/?ut_source=header

About This Article

To develop a questionnaire for research, identify the main objective of your research to act as the focal point for the questionnaire. Then, choose the type of questions that you want to include, and come up with succinct, straightforward questions to gather the information that you need to answer your questions. Keep your questionnaire as short as possible, and identify a target demographic who you would like to answer the questions. Remember to make the questionnaires as anonymous as possible to protect the integrity of the person answering the questions! For tips on writing out your questions and distributing the questionnaire, keep reading! Did this summary help you? Yes No

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• Questionnaire Design Tip Sheet

This PSR Tip Sheet provides some basic tips about how to write good survey questions and design a good survey questionnaire.

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Designing a Questionnaire for a Research Paper: A Comprehensive Guide to Design and Develop an Effective Questionnaire

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Creating a Questionnaire

Create the perfect questionnaire and collect actionable data using our online guide!

Table of Contents

• How to Create

Questionnaire Types

• Collecting Responses
• Analyzing Results
• Getting Started

What is a Questionnaire?

Definition: A questionnaire is a convenient way to collect feedback. A questionnaire can be used to measure customer satisfaction, capture employee feedback, or even conduct product research. Responses can be collected via email, web link, QR code, or using a survey panel.

The term "survey" and "questionnaire" are commonly used interchangeably. A questionnaire refers to the questions used to collect feedback (the form itself). A survey relates to the entire research process, including summarizing and analyzing questionnaire data.

Getting Started + Tips

How to make a questionnaire: Keep questions short and focused on one topic at a time. Use multiple-choice questions to fit answers into a specific category. Use an open-ended question to capture comments. A Likert scale or MaxDiff question can be used for market research. Collect responses for your questionnaire using an email collector, an anonymous link, or even a QR code.

The following 6 tips will help you create the perfect questionnaire:

1) Use 10 Questions or Less

The shorter you keep your survey, the higher your completion rates. Longer questionnaires usually tend to have a high drop-off percentage. Keeping your surveys to 10 questions or fewer forces you to draft a study that only includes important questions; you should remove trivial questions during the draft process.

2) One Idea Per Question

Make sure each question only covers one topic. Try to include only one topic at a time. For example, in an employee survey, you would not want to ask, "Do you feel satisfied with your compensation and career advancement?". Instead, you would like to separate "compensation" and "career advancement" into two questions or use a Likert scale , putting each question on a separate row.

3) Group Similar Questions Together

Suppose the survey is more than ten questions; similar questions should be grouped on separate pages. If you don't want to use more than one page, add extra spacing between groups of the question; extra white space can increase the increase the readability of your questionnaire.

4) Use Skip/Display Logic

If you have questions that only apply to certain people, consider using skip or display logic to show those questions conditionally. This will help reduce the length of your survey and boost response rates.

If you have questions that only apply to certain people, consider using skip or display logic to show those questions conditionally. This will help reduce the length of your survey and boost response rates. For example, if you asked, "Are you currently looking for new employment opportunities?". If the answer were "yes," a follow-up question would ask, "Why?"

5) Use Research Questions Like MaxDiff

Research questions are an excellent tool for customer or product questionnaires. Instead of asking multiple questions on which features are essential or what price is desirable, question types like MaxDiff and Conjoint will provide you with high-quality, actionable data that can be used for feature prioritization and product pricing. In addition, these question types will reduce the length of your questionnaire.

6) Keep the Audience in Mind

An employee questionnaire should use an anonymous link to collect responses; this will help boost trust and increase honest answers. If doing a customer study, consider adding custom data to the weblink to help identify responses. A survey panel and current customers can lend fresh perspectives for general market research.

Questionnaire Templates

Adding customer surveys to your Google review strategy will add additional data points to improve customer satisfaction. In addition, surveys are a valuable tool to identify ways to improve, establish internal benchmarks, and conduct pricing and product research to improve your company's products.

While there are numerous types of questionnaires (or survey types), these are the five most common general categories:

1) Customer Satisfaction

Capturing customer feedback is one of the most common uses of questionnaires. A good customer satisfaction survey will always revolve around a Net Promoter Score question. When the Net Promoter Score question results are tallied, one number from -100 is 100 is displayed. This number is ideal for benchmarks. Net Promoter provides quick and actionable feedback when combined with an open-ended text question.

2) Customer Effort

Measuring how easily customers can complete a purchase or take a specific action is crucial for the customer experience strategy. A customer effort score question is a rating scale from 1 to 7 (disagree to agree). Results for this question are averaged; the higher the score, the easier it is for your customers to complete tasks.

3) Employee Satisfaction & Engagement

Employee satisfaction and engagement are often used interchangeably but measure different things. Both types of surveys often use opinion scales to ask questions.

Employee satisfaction measures how satisfied employees are with their job and work environment. Standard measures of employee satisfaction include salary, benefits, and co-worker relationships.

Employee engagement relates to the emotional commitment employees have to an organization. It goes beyond simple satisfaction. Standard measures of engagement include belief in the company mission, opportunities for career growth, and being inspired to perform at a high level.

4) Employee Exit Interviews

When employees leave for new opportunities, sending a questionnaire is a great way to understand why that employee is leaving. The feedback obtained here can be used to improve the workplace and reduce employee turnover.

5) Product Research

MaxDiff is used to identify what is most important to your audience. For example, if building a new mobile application, asking a group of users what they think is least and most important will help guide product strategy; your team should only focus on the important areas.

For pricing a new product, Van Westendorp will give you a range of prices the market is willing to expect. You could price your product too high or too low without a question like this, reducing your market penetration.

Collecting Responses For Your Questionnaire

There are a few different ways to collect feedback for questionnaires. Depending on your needs, each one could have an advantage.

With email distribution, you would upload a list of email addresses, and the platform would automatically place a link to your questionnaire inside the email body. One advantage is sending email reminders to respondents who still need to complete your survey. In addition, the email links are unique for each respondent, so you can track email open and click rates. As a result, email surveys are ideal for customer research.

A web link is a convenient way to collect feedback at your convenience. You can place a web link on social media, your website, or even inside your CRM email program (instead of an email collector with a unique link to each person). Custom data can be included in the link, such as store location. This custom data can be used to segment and filter results.

Anonymous Link

When you want to protect your respondents' identities, you use an anonymous link . Anonymous inks do not store respondent information, IP address, or email address. Because of this, anonymous survey links are perfect for employee surveys.

QR code Surveys

QR code surveys can be placed on paper receipts, product packaging, or flyers. In addition, QR codes are a great way to collect feedback after or during an event or even during in-person focus groups.

Survey Panels

If you're conducting market research and need access to a customer base, using a survey panel will get you the responses required. A good survey panel will allow you to target specific demographics, job titles, or interest levels (such as car enthusiasts). When using survey panels, you'll want to double-check and clean your data for low-quality responses. People who speed through your survey or mark the first answer for all questions should be removed.

How to Analyze Questionnaire Data

When analyzing the data from a questionnaire, consider a few advanced techniques like the ones below. These techniques will give you better insights than just simple graphs and charts.

Creating a segment or a cross-tabulation is the easiest way to dive deeper into your results. For example, if you conducted an employee satisfaction survey, the overall scores for the company could be high. But that might only tell part of the story. For example, if your company has multiple departments, you should create a cross-tabulation for each department. You might notice that there is one department with low scores. or one department with high scores.

If your company conducted its first Net Promoter Score survey and the results were -10, that score would be your benchmark. Each subsequent customer survey you run should be compared against that initial number to improve it each time.

TURF Analysis

This is an advanced research technique but very valuable. TURF analysis analysis stands for "Total Unduplicated Reach and Frequency" and is used to find the combination of items that would provide the highest reach level. For example, suppose you ask, "Which of the following flavor of ice cream would you buy?" If you run a TURF analysis on the results, you could find the top 3 or 4 combinations of flavors that would result in the highest sales.

Unsure Where to Start?

Creating a questionnaire can be a challenging process. However, these three suggestions can help you with the perfect questionnaire strategy.

1) Talk With Your Team

Some departments might want to conduct pricing research and do simple Net Promoter Score surveys. Having your organization aligned on strategy will simplify the process and eliminate any possibility of re-work. An aligned strategy will also mean a shorter study with fewer overlapping questions.

2) Start with a Template

A pre-made template will show you how to format and word questions. Next, try multiple templates to understand the various question types.

3) Look at Competitor Surveys

You might notice competitors asking specific questions - this would be a sign that those questions provide valuable metrics. If you can incorporate the great things your competition does while making it more efficient for respondents, your questionnaire campaigns will have a greater chance of success.

Get Started Now

We have you covered on anything from customer surveys, employee surveys, to market research. Get started and create your first survey for free.

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World Leaders in Research-Based User Experience

Writing good survey questions: 10 best practices.

August 20, 2023 2023-08-20

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Unfortunately, there is no simple formula for cranking out good, unbiased questionnaires.

That said, there are certainly common mistakes in survey design that can be avoided if you know what to look for. Below, I’ve provided the 10 most common and dangerous errors that can be made when designing a survey and guidelines for how to avoid them.

In This Article:

1. ask about the right things, 2. use language that is neutral, natural, and clear, 3. don’t ask respondents to predict behavior, 4. focus on closed-ended questions, 5. avoid double-barreled questions, 6. use balanced scales, 7. answer options should be all-inclusive and mutually exclusive, 8. provide an opt-out, 9. allow most questions to be optional, 10. respect your respondents, ask only questions that you need answered.

One of the easiest traps to fall into when writing a survey is to ask about too much. After all, you want to take advantage of this one opportunity to ask questions of your audience, right?

The most important thing to remember about surveys is to keep them short . Ask only about the things that are essential for answering your research questions. If you don’t absolutely need the information, leave it out.

Don’t Ask Questions that You Can Find the Answer to

When drafting a survey, many researchers slip into autopilot and start by asking a plethora of demographic questions . Ask yourself: do you need all that demographic information? Will you use it to answer your research questions? Even if you will use it, is there another way to capture it besides asking about it in a survey? For example, if you are surveying current customers, and they are providing their email addresses, could you look up their demographic information if needed?

Don’t Ask Questions that Respondents Can’t Answer Accurately

Surveys are best for capturing quantitative attitudinal data . If you’re looking to learn something qualitative or behavioral, there’s likely a method better suited to your needs. Asking the question in a survey is, at best, likely to introduce inefficiency in your process, and, at worst, will produce unreliable or misleading data.

For example, consider the question below:

If I were asked this question, I could only speculate about what might make a button stand out. Maybe a large size? Maybe a different color, compared to surrounding content? But this is merely conjecture. The only reliable way to tell if the button actually stood out for me would be to mock up the page and show it to me. This type of question would be better studied with other research methods, such as usability testing or A/B testing , but not with a survey.

Avoid Biasing Respondents

There are endless ways in which bias can be introduced into survey data , and it is the researcher’s task to minimize this bias as much as possible. For example, consider the wording of the following question.

By initially providing the context that the organization is committed to achieving a 5-star satisfaction rating , the survey creators are, in essence, pleading with the respondent to give them one. The respondent may feel guilty providing an honest response if they had a less than stellar experience.

Note also the use of the word satisfaction . This wording subtly biases the participant into framing their experience as a satisfactory one.

An alternative wording of the question might remove the first sentence altogether, and simply ask respondents to rate their experience.

Use Natural, Familiar Language

We must always be on the lookout for jargon in survey design. If respondents cannot understand your questions or response options, you will introduce bad data into your dataset. While we should strive to keep survey questions short and simple, it is sometimes necessary to provide brief definitions or descriptions when asking about complex topics, to prevent misunderstanding. Always pilot your questionnaires with the target audience to ensure that all jargon has been removed.

Speak to Respondents Like Humans

For some reason, when drafting a questionnaire, many researchers introduce unnecessary formality and flowery language into their questions. Resist this urge. Phrase questions as clearly and simply as possible, as though you were asking them in an interview format.

People are notoriously unreliable predictors of their own behavior. For various reasons, predictions are almost bound to be flawed, leading Jakob Nielsen to remind us to never listen to users .

Yet, requests for behavioral predictions are rampant in insufficiently thought-out UX surveys. Consider the question:  How likely are you to use this product? While a respondent may feel likely to use a product based on a description or a brief tutorial, their answer does not constitute a reliable prediction and should not be used to make critical product decisions.

Often, instead of future-prediction requests , you will see present-estimate requests : How often do you currently use this product in an average week? While this type of question avoids the problem of predictions, it still is unreliable. Users struggle to estimate based on some imaginary “average” week and will often, instead, recall outlier weeks, which are more memorable.

The best way to phrase a question like this is to ask for specific, recent memories : Approximately how many times did you use this product in the past 7 days? It is important to include the word approximately and to allow for ranges rather than exact numbers. Reporting an exact count of a past behavior is often either challenging or impossible, so asking for it introduces imprecise data. It can also make respondents more likely to drop off if they feel incapable of answering the question accurately.

Surveys are, at their core, a quantitative research method . They rely upon closed-ended questions (e.g., multiple-choice or rating-scale questions) to generate quantitative data. Surveys can also leverage open-ended questions (e.g., short-answer or long-answer questions) to generate qualitative data. That said, the best surveys rely upon closed-ended questions, with a smattering of open-ended questions to provide additional qualitative color and support to the mostly quantitative data.

If you find that your questionnaire relies overly heavily on open-ended questions, it might be a red flag that another qualitative-research method (e.g., interviews ) may serve your research aims better.

On the subject of open-ended survey questions, it is often wise to include one broad open-ended question at the end of your questionnaire . Many respondents will have an issue or piece of feedback in mind when they start a survey, and they’re simply waiting for the right question to come up. If no such question exists, they may end the survey experience with a bad taste. A final, optional, long-answer question with a prompt like Is there anything else you’d like to share? can help to alleviate this frustration and supply some potentially valuable data.

A double-barreled question asks respondents to answer two things at once. For example: How easy and intuitive was this website to use? Easy and intuitive , while related, are not synonymous, and, therefore, the question is asking the respondent to use a single rating scale to assess the website on two distinct dimensions simultaneously. By necessity, the respondent will either pick one of these words to focus on or try to assess both and estimate a midpoint “average” score. Neither of these will generate fully accurate or reliable data.

Therefore, double-barreled questions should always be avoided and, instead, split up into two separate questions.

Rating-scale questions are tremendously valuable in generating quantitative data in survey design. Often, a respondent is asked to rate their agreement with a statement on an agreement scale (e.g., Strongly Agree, Agree, Neutral, Disagree, Strongly Disagree ), or otherwise to rate something using a scale of adjectives (e.g., Excellent, Good, Neutral, Fair, Poo r).

You’ll notice that, in both of the examples given above, there is an equal number of positive and negative options (2 each), surrounding a neutral option. The equal number of positive and negative options means that the response scale is balanced and eliminates a potential source of bias or error.

In an unbalanced scale, you’ll see an unequal number of positive and negative options (e.g., Excellent, Very Good, Good, Poor, Very Poor ). This example contains 3 positive options and only 2 negative ones. It, therefore, biases the participant to select a positive option.

Answer options for a multiple-choice question should include all possible answers (i.e., all inclusive) and should not overlap (i.e., mutually exclusive). For example, consider the following question:

In this formulation, some possible answers are skipped (i.e., anyone who is over 50 won’t be able to select an answer). Additionally, some answers overlap (e.g., a 20-year-old could select either the first or second response).

Always doublecheck your numeric answer options to ensure that all numbers are included and none are repeated .

No matter how carefully and inclusively you craft your questions, there will always be respondents for whom none of the available answers are acceptable. Maybe they are an edge case you hadn’t considered. Maybe they don’t remember the answer. Or maybe they simply don’t want to answer that particular question. Always provide an opt-out answer in these cases to avoid bad data.

Opt-out answers can include things like the following: Not applicable , None of the above , I don’t know, I don’t recall , Other , or Prefer not to answer . Any multiple-choice question should include at least one of these answers. However, avoid the temptation to include one catch-all opt-out answer containing multiple possibilities . For example, an option labeled I don’t know / Not applicable  covers two very different responses with different meanings; combining them fogs your data.

It is so tempting to make questions required in a questionnaire. After all, we want the data! However, the choice to make any individual question required will likely lead to one of two unwanted results:

• Bad Data: If a respondent is unable to answer a question accurately, but the question is required, they may select an answer at random. These types of answers will be impossible to detect and will introduce bad data into your study, in the form of random-response bias.
• Dropoffs: The other option available to a participant unable to correctly answer a required question is to abandon the questionnaire. This behavior will increase the effort needed to reach the desired number of responses.

Therefore, before deciding to make any question required, consider if doing so is worth the risks of bad data and dropoffs.

In the field of user experience, we like to say that we are user advocates. That doesn’t just mean advocating for user needs when it comes to product decisions. It also means respecting our users any time we’re fortunate enough to interact with them.

Don’t Assume Negativity

This is particularly important when discussing health issues or disability. Phrasings such Do you suffer from hypertension? may be perceived as offensive. Instead, use objective wording such as Do you have hypertension?

Be Sensitive with Sensitive Topics

When asking about any topics that may be deemed sensitive, private, or offensive, first ask yourself: Does it really need to be asked? Often, we can get plenty of valuable information while omitting that topic.

Other times, it is necessary to delve into potentially sensitive topics. In these cases, be sure to choose your wording carefully. Ensure you’re using the current preferred terminology favored by members of the population you’re addressing. If necessary, consider providing a brief explanation for why you are asking about that particular topic and what benefit will come from responding.

Use Inclusive and Appropriate Wording for Demographic Questions

When asking about topics such as race, ethnicity, sex, or gender identity, use accurate and sensitive terminology. For example, it is no longer appropriate to offer a simple binary option for gender questions. At a minimum, a third option indicating an Other or Non-binary category is expected, as well as an opt-out answer for those that prefer not to respond.

An inclusive question is respectful of your users’ identities and allows them to answer only if they feel comfortable.

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Hands-on guide to questionnaire research

Administering, analysing, and reporting your questionnaire, petra m boynton.

1 Department of Primary Care and Population Sciences, University College London, London N19 5LW [email protected]

Associated Data

Short abstract.

Understanding your study group is key to getting a good response to a questionnaire; dealing with the resulting mass of data is another challenge

The first step in producing good questionnaire research is getting the right questionnaire. 1 However, even the best questionnaire will not get adequate results if it is not used properly. This article outlines how to pilot your questionnaire, distribute and administer it; and get it returned, analysed, and written up for publication. It is intended to supplement published guidance on questionnaire research, three quarters of which focuses on content and design. 2

Questionnaires tend to fail because participants don't understand them, can't complete them, get bored or offended by them, or dislike how they look. Although friends and colleagues can help check spelling, grammar, and layout, they cannot reliably predict the emotional reactions or comprehension difficulties of other groups. Whether you have constructed your own questionnaire or are using an existing instrument, always pilot it on participants who are representative of your definitive sample. You need to build in protected time for this phase and get approval from an ethics committee. 3

During piloting, take detailed notes on how participants react to both the general format of your instrument and the specific questions. How long do people take to complete it? Do any questions need to be repeated or explained? How do participants indicate that they have arrived at an answer? Do they show confusion or surprise at a particular response—if so, why? Short, abrupt questions may unintentionally provoke short, abrupt answers. Piloting will provide a guide for rephrasing questions to invite a richer response (box 1). ​ 1).

Box 1: Patient preference is preferable

I worked on a sexual health study where we initially planned to present the questionnaire on a computer, since we had read people were supposedly more comfortable “talking” to a computer. Although this seemed to be the case in practices with middle class patients, we struggled to recruit in practices where participants were less familiar with computers. Their reasons for refusal were not linked to the topic of the research, but because they saw our laptops as something they might break, could make them look foolish, or would feed directly to the internet (which was inextricably linked to computers in some people's minds). We found offering a choice between completing the questionnaire on paper or the laptop computer greatly increased response rates.

Planning data collection

You should be aware of the relevant data protection legislation (for United Kingdom see www.informationcommissioner.gov.uk ) and ensure that you follow internal codes of practice for your institution—for example, obtaining and completing a form from your data protection officer. Do not include names, addresses, or other identifying markers within your electronic database, except for a participant number linked to a securely kept manual file.

The piloting phase should include planning and testing a strategy for getting your questionnaire out and back—for example, who you have invited to complete it (the sampling frame), who has agreed to do so (the response rate), who you've had usable returns from (the completion rate), and whether and when you needed to send a reminder letter. If you are employing researchers to deliver and collect the questionnaire it's important they know exactly how to do this. 4

Administrative errors can hamper the progress of your research. Real examples include researchers giving the questionnaire to wrong participants (for example, a questionnaire aimed at men given to women); incomplete instructions on how to fill in the questionnaire (for example, participants did not know whether to tick one or several items); postal surveys in which the questionnaire was missing from the envelope; and a study of over 3000 participants in which the questionnaire was sent out with no return address.

Administering your questionnaire

The choice of how to administer a questionnaire is too often made on convenience or cost grounds (see table A on bmj.com ). Scientific and ethical considerations should include:

• The needs and preferences of participants, who should understand what is required of them; remain interested and cooperative throughout completion; be asked the right questions and have their responses recorded accurately; and receive appropriate support during and after completing the questionnaire
• The skills and resources available to your research team
• The nature of your study—for example, short term feasibility projects, clinical trials, or large scale surveys.

Maximising your response rate

Sending out hundreds of questionnaires is a thankless task, and it is sometimes hard to pay attention to the many minor details that combine to raise response and completion rates. Extensive evidence exists on best practice (box 2), and principal investigators should ensure that they provide their staff with the necessary time and resources to follow it. Note, however, that it is better to collect fewer questionnaires with good quality responses than high numbers of questionnaires that are inaccurate or incomplete. The third article in this series discusses how to maximise response rates from groups that are hard to research. 15

Accounting for those who refuse to participate

Survey research tends to focus on people who have completed the study. Yet those who don't participate are equally important scientifically, and their details should also be recorded (remember to seek ethical approval for this). 4 , 16 , 17

Box 2: Factors shown to increase response rates

• The questionnaire is clearly designed and has a simple layout 5
• It offers participants incentives or prizes in return for completion 6
• It has been thoroughly piloted and tested 5
• Participants are notified about the study in advance with a personalised invitation 7
• The aim of study and means of completing the questionnaire are clearly explained 8 , 9
• A researcher is available to answer questions and collect the completed questionnaire 10
• If using a postal questionnaire, a stamped addressed envelope is included 7
• The participant feels they are a stakeholder in the study 11
• Questions are phrased in a way that holds the participant's attention 11
• Questionnaire has clear focus and purpose and is kept concise 7 , 8 , 11
• The questionnaire is appealing to look at, 12 as is the researcher 13
• If appropriate, the questionnaire is delivered electronically 14

One way of reducing refusal and non-completion rates is to set strict exclusion criteria at the start of your research. For example, for practical reasons many studies exclude participants who are unable to read or write in the language of the questionnaire and those with certain physical and mental disabilities that might interfere with their ability to give informed consent, cooperate with the researcher, or understand the questions asked. However, research that systematically excludes hard to reach groups is increasingly seen as unethical, and you may need to build additional strategies and resources into your study protocol at the outset. 15 Keep a record of all participants that fit the different exclusion categories (see bmj.com ).

Collecting data on non-participants will also allow you to monitor the research process. For example, you may find that certain researchers seem to have a higher proportion of participants refusing, and if so you should work with those individuals to improve the way they introduce the research or seek consent. In addition, if early refusals are found to be unusually high, you might need to rethink your overall approach. 10

Entering, checking, and cleaning data

Novice researchers often assume that once they have selected, designed, and distributed their questionnaire, their work is largely complete. In reality, entering, checking, and cleaning the data account for much of the workload. Some principles for keeping quantitative data clean are listed on bmj.com .

Even if a specialist team sets up the database(s), all researchers should be taught how to enter, clean, code, and back up the data, and the system for doing this should be universally agreed and understood. Agree on the statistical package you wish to use (such as SPSS, Stata, EpiInfo, Excel, or Access) and decide on a coding system before anyone starts work on the dataset.

It is good practice to enter data into an electronic database as the study progresses rather than face a mountain of processing at the end. The project manager should normally take responsibility for coordinating and overseeing this process and for ensuring that all researchers know what their role is with data management. These and other management tasks are time consuming and must be built into the study protocol and budget. Include data entry and coding in any pilot study to get an estimate of the time required and potential problems to troubleshoot.

Analysing your data

You should be able to predict the type of analysis required for your different questionnaire items at the planning stage of your study by considering the structure of each item and the likely distribution of responses (box 3). 1 Table B on bmj.com shows some examples of data analysis methods for different types of responses. 18 , 19 w1

Writing up and reporting

Once you have completed your data analysis, you will need to think creatively about the clearest and most parsimonious way to report and present your findings. You will almost certainly find that you have too much data to fit into a standard journal article, dissertation, or research report, so deciding what to include and omit is crucial. Take statistical advice from the outset of your research. This can keep you focused on the hypothesis or question you are testing and the important results from your study (and therefore what tables and graphs to present).

Box 3: Nasty surprise from a simple questionnaire

Moshe selected a standardised measure on emotional wellbeing to use in his research, which looked easy to complete and participants answered readily. When he came to analysing his data, he discovered that rather than scoring each response directly as indicated on the questionnaire, a complicated computer algorithm had to be created, and he was stumped. He found a statistician to help with the recoding, and realised that for future studies it might be an idea to check both the measure and its scoring system before selecting it.

Box 4: An unexpected result

Priti, a specialist registrar in hepatology, completed an attitude questionnaire in patients having liver transplantation and those who were still waiting for a donor. She expected to find that those who had received a new liver would be happier than those awaiting a donor. However, the morale scale used in her questionnaire showed that the transplantation group did not have significantly better morale scores. Priti felt that this negative finding was worth further investigation.

Methods section

The methods section should give details of your exclusion criteria and discuss their implications for the transferability of your findings. Data on refusals and unsuitable participants should also be presented and discussed, preferably using a recruitment diagram. w2 Finally, state and justify the statistical or qualitative analyses used. 18 , 19 w2

Results section

When compiling the results section you should return to your original research question and set out the findings that addressed this. In other words, make sure your results are hypothesis driven. Do not be afraid to report non-significant results, which in reality are often as important as significant results—for example, if participants did not experience anxiety in a particular situation (box 4). Don't analyse and report on every question within your questionnaire

Choose the most statistically appropriate and visually appealing format for graphs ( table ). w3 Label graphs and their axes adequately and include meaningful titles for tables and diagrams. Refer your reader to any tables or graphs within your text, and highlight the main findings.

Examples of ways of presenting data and when to use them

If you have used open ended questions within your questionnaire, do not cherry pick quotes for your results section. You need to outline what main themes emerged, and use quotes as necessary to illustrate the themes and supplement your quantitative findings.

Discussion section

The discussion should refer back to the results section and suggest what the main findings mean. You should acknowledge the limitations of your study and couch the discussion in the light of these. For example, if your response rate was low, you may need to recommend further studies to confirm your preliminary results. Your conclusions must not go beyond the scope of your study—for example, if you have done a small, parochial study do not suggest changes in national policy. You should also discuss any questions your participants persistently refused to answer or answered in a way you didn't expect.

Taking account of psychological and social influences

Questionnaire research (and indeed science in general) can never be completely objective. Researchers and participants are all human beings with psychological, emotional, and social needs. Too often, we fail to take these factors into account when planning, undertaking, and analysing our work. A questionnaire means something different to participants and researchers. w4 Researchers want data (with a view to publications, promotion, academic recognition, and further grant income). Junior research staff and administrators, especially if poorly trained and supervised, may be put under pressure, leading to critical errors in piloting (for example, piloting on friends rather than the target group), sampling (for example, drifting towards convenience rather than random samples) and in the distribution, collection, and coding of questionnaires. 15 Staff employed to assist with a questionnaire study may not be familiar with all the tasks required to make it a success and may be unaware that covering up their ignorance or skill deficits will make the entire study unsound.

Summary points

Piloting is essential to check the questionnaire works in the study group and identify administrative and analytical problems

The method of administration should be determined by scientific considerations not just costs

Entering, checking, and cleaning data should be done as the study progresses

Don't try to include all the results when reporting studies

Do include exclusion criteria and data on non-respondents

Research participants, on the other hand, may be motivated to complete a questionnaire through interest, boredom, a desire to help others (particularly true in health studies), because they feel pressurised to do so, through loneliness, or for an unconscious ulterior motive (“pleasing the doctor”). All of these introduce potential biases into the recruitment and data collection process.

Supplementary Material

This is the second in a series of three articles edited by Trisha Greenhalgh

I thank Alicia O'Cathain, Trish Greenhalgh, Jill Russell, Geoff Wong, Marcia Rigby, Sara Shaw, Fraser Macfarlane, and Will Callaghan for their helpful feedback on earlier versions of this paper and Gary Wood for advice on statistics and analysis.

PMB has taught research methods in a primary care setting for the past 13 years, specialising in practical approaches and using the experiences and concerns of researchers and participants as the basis of learning. This series of papers arose directly from questions asked about real questionnaire studies. To address these questions she and Trisha Greenhalgh explored a wide range of sources from the psychological and health services research literature.

Competing interests: None declared.

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How to write a survey questionnaire

The questionnaire is a researcher’s most important tool! You need to ask the right questions, in the right way to get the insight you need. This guide explains what makes a good survey, be it online or telephone, and what pitfalls to avoid.

Starting the questionnaire

Before starting to write your survey, you should revisit the original project objectives to keep your line of questioning on-track.

It’s a good idea to start with a ‘wish list’ – noting down all the questions that you and your stakeholders would like to include. It’s helpful to have everything in contention written down so you can prioritise which are the most important questions. It’s also helpful to start grouping these questions together by broad topic area to have an overview of what you’re covering and help get the order right.

Top tip: Once you have written the first draft of your questionnaire go through and note next to each question which objective it helps to answer. If a question doesn’t help answer any of the objectives – ditch it!

The key things to consider when structuring a questionnaire are:

• Introduction and screening:  In a few sentences, explain what the research is about, how you will use the answers and how long it will take to complete. Be honest, if you say it will take 5 minutes to complete but actually it’s going to take 10 minutes, people are likely to drop out halfway through.

You might also need to ask some screening questions which collect basic profiling characteristics to make sure you are talking to the right type or enough of a certain type of student (e.g. subject area or home / overseas) or business (e.g. location or sector).

• Create a natural flow:  It’s useful to think about the order in which people would normally talk about a topic. For example, if you are running a survey to measure student satisfaction during the pandemic, you might want to consider structuring your questionnaire chronologically, starting with arrival in Freshers’ Week through to current views on course delivery.

Linked to this, if you need to tackle harder or more sensitive topics, ‘warm up’ respondents by asking easier or more general questions first. Likewise, if you need to collect more personal information, then place these questions at the end, unless the information is needed to screen at the beginning of the survey. And remember to include a ‘Prefer not to say’ option.

• Vary question types:  Try and add different types of question to maintain interest, for example, when capturing how satisfied students are with various aspects of their learning experience, you could combine agree-disagree statements with questions that ask them to rank different elements of learning by level of satisfaction.

Top tip: Consider ‘routing’ respondents through the survey so that they are only asked questions that are relevant to them. For example, you’ve already established earlier in the survey whether or not a local employer is able to offer a work placement to your students. If they are, you’ll want to ask them a series of follow-up questions to collect more details. If they aren’t, then they should skip past these questions. Be aware not all survey platforms allow for routing, so if you can’t apply this, make sure you acknowledge this at the follow-up questions by including an appropriate response option like ‘Not applicable’.

Types of question.

How you ask your questions will determine the sort of data you collect and the type of analysis you can conduct. Think about how you will use your survey data at the end and what this means for how you ask your questions. Some common question types include:

• Scales with labels or numbers , for example ‘very good, fairly good, neither good nor poor, fairly poor, very poor’ or a scale of 1 to 5 with 1 being ‘very good’ and 5 being ‘very poor’. Scales should always be balanced with the same number of ‘positive’ options as ‘negative’ options and the two ends of the scales should be genuine polar opposites (e.g. ‘very good’ and ‘very poor’ rather than ‘excellent’ at one end and ‘very poor’ at the other end).
• Open questions , where a respondent answers in their own words and are best used when you don’t have a good idea of what the answer might be or if you want to collect quotes for example, ‘What have you enjoyed most about your time at university?’
• Closed questions , where an answer is selected from a pre-determined list. Be careful not to introduce any response bias by rotating the order in which response options appear so the same answer doesn’t always appear at the top of the list. Make sure important answers aren’t missing from the list – add an ‘Other (specify) as a safety net – or that two or more contradictory answers can’t both be selected.
• Ranking  used to find order of preference for items on a list. This type of question is most useful to differentiate between items when everything is obviously either a ‘good thing’ or a ‘bad thing’. The list should be limited to 7 or 8 items – for longer lists, asking for 1 st , 2 nd  and 3 rd  preference would be a better option.

Top Tip: Consider limiting the number of open questions you include in your survey – firstly they are more burdensome for the respondent to answer and secondly, they are more time consuming for you to analyse.

Question wording.

The way a question is worded is critical in how it is interpreted. Badly worded questions can lead to careless, inaccurate or dishonest answers. Keep in mind the following:

• Simplicity – keep language simple, but tailor it accordingly, how you ask questions to students will be different to how you ask them to employers.
• Length – use short sentences, but say enough to be specific (e.g. rather than ‘Where do you live?’ use ‘In what town or city do you live?’)
• Ambiguity – be aware of common words that are ambiguous and use definitions wherever necessary (for example, if asking ‘Do you  regularly  travel to the university campus by bus?’ include ‘By regularly, we mean at least twice a week).
• Assumption – keep in mind not everyone will be able to answer the question or know something (for example if asking an employer, ‘How often do you take on apprentices?’ this should be split into ‘Have you ever taken on an apprentice?’ and then  if yes  ‘In the last three years, how many apprentices have you taken on?’).
• Leading wording – Steer clear of phrasing that guides the respondent to an answer or implies certain responses are more ‘normal’ or expected.
• Avoid asking about more than one thing in the same question e.g. How would you rate your accommodation and the on-site support services? You won’t know if a student is rating the overall accommodation, the on-site support services or giving an average across the two.
• Avoid double-negatives, for example ‘Do you disagree with the university’s decision not to run face to face lectures this term? – Yes or No’ Such questions are difficult to understand and are likely to cause confusion and yield inaccurate answers.
• Memory limitations – err on the side of using shorter reference periods and avoid ambiguity by stating precise timeframes you are interested in.

Top tip: Once drafted, get a colleague to complete the survey to test comprehension and understanding and to see how long it takes to complete!

A few final pointers on format, accessibility and length.

As part of planning the project, you will have already decided how you are going to run your survey –online, telephone, or indeed a mix of these.

Remember,  how you run your survey can influence how questions are answered . For example, you want to ask an applicant a closed question – Why did you shortlist this university in your application?  When you display this question on an online survey, the applicant will see a list of response options to choose from. However, unless you  read out  these options in the equivalent telephone survey, they will not ‘have sight’ of them. Their exposure to the list of response options is different depending on how they are surveyed which may result in different answers being given.

Make sure you cater for all needs, for example large font or high contrast colours when completing an online survey for those with visual impairments or advance sight of the questions for those completing a telephone survey but are hard of hearing.

Typically, the shorter the questionnaire, the better. The longer a questionnaire is, the higher the dropout rate. As rule of thumb it is good practice to keep an online questionnaire to no more than 10 minutes, and a telephone questionnaire to 15 minutes.

Top tip: If you are running an online survey you should think about how each question will look visually. Make sure questions display correctly for all devices including mobile phones. Don’t let bad formatting put respondents off completing the survey!

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How to create an effective survey in 15 simple tips

Updated August 15, 2023

You don’t have to be an expert to create a survey, but by following a few survey best practices you can make sure you’re collecting the best data possible.

Access 50+ expert-designed survey templates with a free Qualtrics Surveys account

From working out what you want to achieve to providing incentives for respondents, survey design can take time.

But when you don’t have hours to devote to becoming a survey-creation guru, a quick guide to the essentials is a great way to get started.

In this article, we’re going to reveal how to create a survey that’s easy to complete, encourages collecting feedback, hits the research questions you’re interested in, and produces data that’s easy to work with at the analysis stage .

15 Tips when creating surveys

1. define the purpose of the survey.

Before you even think about your survey questions , you need to define their purpose.

The survey’s purpose should be a clear, attainable, and relevant goal. For example, you might want to understand why customer engagement is dropping off during the middle of the sales process.

Your goal could then be something like: “I want to understand the key factors that cause engagement to dip at the middle of the sales process, including both internal and external elements.”

Or maybe you want to understand customer satisfaction post-sale. If so, the goal of your survey could be: “I want to understand how customer satisfaction is influenced by customer service and support post-sale, including through online and offline channels.”

The idea is to come up with a specific, measurable, and relevant goal for your survey. This way you ensure that your questions are tailored to what you want to achieve and that the data captured can be compared against your goal.

2. Make every question count

You’re building your survey questionnaire to obtain important insights, so every question should play a direct role in hitting that target.

Make sure each question adds value and drives survey responses that relate directly to your research goals. For example, if your participant’s precise age or home state is relevant to your results, go ahead and ask. If not, save yourself and your respondents some time and skip it.

It’s best to plan your survey by first identifying the data you need to collect and then writing your questions.

You can also incorporate multiple-choice questions to get a range of responses that provide more detail than a solid yes or no. It’s not always black and white.

For a deeper dive into the art and science of question-writing and survey best practices, check out Survey questions 101 .

3. Keep it short and simple

Although you may be deeply committed to your survey, the chances are that your respondents... aren’t.

As a survey designer, a big part of your job is keeping their attention and making sure they stay focused until the end of the survey.

Respondents are less likely to complete long surveys or surveys that bounce around haphazardly from topic to topic. Make sure your survey follows a logical order and takes a reasonable amount of time to complete.

Although they don’t need to know everything about your research project, it can help to let respondents know why you’re asking about a certain topic. Knowing the basics about who you are and what you’re researching means they’re more likely to keep their responses focused and in scope.

Access 50+ expert-designed survey templates now

4. Ask direct questions

Vaguely worded survey questions confuse respondents and make your resulting data less useful. Be as specific as possible, and strive for clear and precise language that will make your survey questions easy to answer.

It can be helpful to mention a specific situation or behavior rather than a general tendency. That way you focus the respondent on the facts of their life rather than asking them to consider abstract beliefs or ideas .

See an example:

Good survey design isn’t just about getting the information you need, but also encouraging respondents to think in different ways.

Get access to the top downloaded survey templates here

5. Ask one question at a time

Although it’s important to keep your survey as short and sweet as possible, that doesn’t mean doubling up on questions. Trying to pack too much into a single question can lead to confusion and inaccuracies in the responses.

Take a closer look at questions in your survey that contain the word “and” – it can be a red flag that your question has two parts. For example: “Which of these cell phone service providers has the best customer support and reliability?” This is problematic because a respondent may feel that one service is more reliable, but another has better customer support.

Also, if you want to go beyond surveys and develop a multi-faceted listening approach to drive meaningful change and glean actionable insights, make sure to download our guide .

6. Avoid leading and biased questions

Although you don’t intend them to, certain words and phrases can introduce bias into your questions or point the respondent in the direction of a particular answer.

As a rule of thumb, when you conduct a survey it’s best to provide only as much wording as a respondent needs to give an informed answer. Keep your question wording focused on the respondent and their opinions, rather than introducing anything that could be construed as a point of view of your own.

In particular, scrutinize adjectives and adverbs in your questions. If they’re not needed, take them out.

7. Speak your respondent's language

This tip goes hand in hand with many others in this guide – it’s about making language only as complex or as detailed as it needs to be when conducting great surveys.

Create surveys that use language and terminology that your respondents will understand. Keep the language as plain as possible, avoid technical jargon and keep sentences short. However, beware of oversimplifying a question to the point that its meaning changes.

8. Use response scales whenever possible

Response scales capture the direction and intensity of attitudes, providing rich data. In contrast, categorical or binary response options, such as true/false or yes/no response options, generally produce less informative data.

If you’re in the position of choosing between the two, the response scale is likely to be the better option.

Avoid using scales that ask your target audience to agree or disagree with statements, however. Some people are biased toward agreeing with statements , and this can result in invalid and unreliable data.

9. Avoid using grids or matrices for responses

Grids or matrices of answers demand a lot more thinking from your respondent than a scale or multiple choice question. They need to understand and weigh up multiple items at once, and oftentimes they don’t fill in grids accurately or according to their true feelings .

Another pitfall to be aware of is that grid question types aren’t mobile-friendly. It’s better to separate questions with grid responses into multiple questions in your survey with a different structure such as a response scale.

See an example using our survey tool:

10. Rephrase yes/no questions if possible in online survyes

As we’ve described, yes/no questions provide less detailed data than a response scale or multiple-choice, since they only yield one of two possible answers.

Many yes/no questions can be reworked by including phrases such as “How much,” “How often,” or “How likely.” Make this change whenever possible and include a response scale for richer data.

By rephrasing your questions in this way, your survey results will be far more comprehensive and representative of how your respondents feel.

Next? Find out how to write great questions .

11. Start with the straightforward stuff

Ease your respondent into the survey by asking easy questions at the start of your questionnaire, then moving on to more complex or thought-provoking elements once they’re engaged in the process.

This is especially valuable if you need to cover any potentially sensitive topics in your survey. Never put sensitive questions at the start of the questionnaire where they’re more likely to feel off-putting.

Your respondent will probably become more prone to fatigue and distraction towards the end of the survey, so keep your most complex or contentious questions in the middle of the survey flow rather than saving them until last.

12. Use unbalanced scales with care

Unbalanced response scales and poorly worded questions can mislead respondents.

For example, if you’ve asked them to rate a product or service and you provide a scale that includes “poor”, “satisfactory”, “good” and “excellent”, they could be swayed towards the “excellent” end of the scale because there are more positive options available.

Make sure your response scales have a definitive, neutral midpoint (aim for odd numbers of possible responses) and that they cover the whole range of possible reactions to the question .

13. Consider adding incentives

To increase the number of responses, incentives — discounts, offers, gift cards, or sweepstakes — can prove helpful.

Of course, while the benefits of offering incentives sound appealing (more respondents), there’s the possibility of attracting the opinions of the wrong audiences, such as those who are only in it for the incentive.

With this in mind, make sure you limit your surveys to your target population and carefully assess which incentives would be most valuable to them.

14. Take your survey for a test drive

Want to know how to make a survey a potential disaster? Send it out before you pre-test .

However short or straightforward your questionnaire is, it’s always a good idea to pre-test your survey before you roll it out fully so that you can catch any possible errors before they have a chance to mess up your survey results.

Share your survey with at least five people, so that they can test your survey to help you catch and correct problems before you distribute it.

15. Let us help you

Survey design doesn’t have to be difficult — even less so with the right expertise, digital solutions, and survey templates.

At Qualtrics, we provide survey software that’s used by more than 11,000 of the top brands and 99 of the top business schools worldwide.

Furthermore, we have a library of high-quality, ready-to-use, and easy-to-configure survey templates that can improve your surveys significantly.

You can check out our template marketplace here . As a free or existing customer, you have access to the complete collection and can filter by the core experiences you want to drive.

As for our survey software , it’s completely free to use and powers more than 1 billion surveys a year. Using it, you can get answers to your most important brand, market, customer, and product questions, build your own surveys, get insights from your audience wherever they are, and much, much more.

If you want to learn more about how to use our survey tool to create a survey, as well as what else it can do — check out our blog on how to create a free online survey using Qualtrics .

See instant results with our online free survey maker

Sarah Fisher

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• Aug 21, 2020
• 10 min read

How To Design A Good Questionnaire

Updated: 3 days ago

Many people tend to have the perception that it’s really easy to write a questionnaire until they actually try to then have difficulty in structuring the questionnaire, when they had only a few questions in mind or don’t know where to start. There is an art in knowing how to design a good questionnaire but it is more straight forward, once you know how. This post will run through the steps with questionnaire examples to help you along the way.

Table of contents:

What is a questionnaire?

4 key parts in designing a good research questionnaire (organising the questionnaire layout), different types of questions to use, 3 types of questionnaire structures to use, top 10 common mistakes to avoid when writing a questionnaire, pre-test questionnaire, remember the main benefits of a questionnaire.

[Disclosure: This post contains affiliate links, meaning we get a commission if you decide to make a purchase through these links at no additional cost to you.]

The table above shows the top 10 tips for how to write a good questionnaire design.

A questionnaire is a data collection technique consisting of a series of questions that are structured to be asked of people taking part using different forms of communication whether it’s verbal or written. The feedback from a questionnaire can be measurable or used to delve deeper into people’s minds.

There are 4 key parts in knowing how to write a good research questionnaire:

1. A short introduction at the beginning stating the purpose of the questionnaire

At the beginning of the questionnaire, there should be an introduction that is short, to the point in stating the purpose of the survey and sound appealing to entice people to take part. Ensure legitimacy is also included and their answers will not be shared to outside parties.

2. Screening section to filter through the target audience of the research

The first questions should be part of the screening section to ensure you are interviewing your target audience by setting criteria specific questions, which maybe a couple of demographic questions if relevant as well as topic specific. Otherwise you don’t want to be interviewing someone for car buying if they don’t drive or are not looking to buy a car in the next 12 months. Keep in mind, the screening section should not be too long.

3. Main body of the questionnaire will be different types of questions of interest to help achieve the market research objectives that have been outlined

The main body of the questionnaire should follow the screening section with all the questions you’re interested in asking your target audience by using many of the question types mentioned previously. It’s best to do a mix but not too much to keep it consistent as well as engaging for the people your interviewing. This section will help to answer the objectives you have set in writing the questionnaire.

Remember if you are using list for multiple choice or scale questions, don’t go crazy and make it too long, otherwise a lot people will drop out of the interview . For a list of behavioural or attitudinal statements it’s best to use a maximum of 10 statements. You have to see it from the participant’s perspective, would you get bored of answering endless lists of statements?

It’s good to get creative with the questionnaire to keep up engagement levels and receive better responses.

4. The final part of the questionnaire tends to be for classification purposes of the target audience such as demographic questions

The final part of the questionnaire tends to be for classification purposes and asking any sensitive questions like income. Normally it includes the rest of the demographic questions you have not asked at the screening section. Don’t forget the closing of the questionnaire survey in thanking the participants for their time and the feedback they have given will be kept confidential.

There are two main question types that you need to be aware of – open ended questions and closed ended questions , where a number of sub type of questions fall under. These questions serve three main purposes behavioural, attitudinal and classification.

Open ended questions

Open ended questions give participants the opportunity to answer the question in their own words, where they can express the reasons why they bought a certain brand or what they don’t like about an advert rather than being prompted to select an answer. The open responses are either recorded by the interviewer or written down/typed by the participant depending on the method used (telephone, face to face, video call or online).

This can add a lot of time to the interview especially if more than two open questions are used in a quantitative survey that will affect whether the questionnaire gets completed or not by many of the participants.

The other thing to keep in mind is it will generate a lot of verbatim comments to analyse, so additional tasks of grouping these comments into the most popular themes let alone taking a further step in coding responses will take a lot time to do. However, verbatim comments can bring results to life through snippets to help back up certain measurable findings.

EXAMPLE – Q. Please tell us your first impressions of this ad. What did you make of it?

Closed ended questions

Closed questions give participants a choice of options to choose from like a single response with a yes or no answer to multiple responses to a question like mobile brands you are aware of from a list.

Below are a number of types of closed questions you can use in your questionnaire.

Single response

Single response as the name suggests is where only one answer is allowed like what gender they are. Even many questions covering attitudes of the participant are single response from a pre-determined list.

EXAMPLE - Q. Have you seen this ad before?

Multiple choice questions

Multiple choice questions allow participants to offer more than one answer. This could be from a list of brands that they may be aware of, consider, bought or used and is easy for people to fill out. If your using a list of answer options, please make sure the list is randomised to avoid bias.

EXAMPLE – Q. Thinking now about all financial products and services, which of these brands would you be prepared to consider for ANY financial products or services? RANDOMISE LIST

Select all that apply

Rating scale questions

Rating scale questions are a scale of numbers that tend to be from 1 to 10 and are used to ask participants to rate a product or service on a number of things. These types of questions are normally used for customer satisfaction .

EXAMPLE – Q. On a scale of 1 to 10 with 1 being not at all to 10 being extremely likely, how likely are you to recommend Brand X to friends or family?

Likert scale questions

Likert scale questions helps to determine the level of agreement from the participant for each statement on a 5 or 7 point scale about a brand or the participants behaviour. Normally this is “strongly agree” to “strongly disagree” but can also be the level of likelihood to buy as well.

EXAMPLE – Q. To what extent do you agree or disagree with the following statements?

I enjoy entertaining people at home

1. Strongly agree

2. Slightly agree

3. Neither agree nor disagree

4. Slightly disagree

5. Strongly disagree

Ranking questions

Ranking questions are needed to find out what aspects participants rate in order of importance for a website, product or service. It’s best practice to ask the participants their top 3 factors in order of first, second and third from a list of factors. The list of factors should be randomised for every interview to avoid any bias towards the factors at the top of the list.

EXAMPLE – Q. You will now be shown a list of factors that could be important to you when selecting a car to buy. Would you look at the list and tell me which is the most important factor in influencing your choice? RANK JUST 3 FACTORS

RANDOMISE LIST

And what would be the second most important factor?

And what would be the third most important factor?

Rank Factors

Competitive price

Model of the car

There are three types of questionnaires that meet the needs of how a questionnaire is administered, whether this is via telephone, face to face or online:

1. Structured questionnaire

This can be used for large surveys (from 30 to 200+) consisting of closed (like yes or no answers) and prompted questions. This is where you add all the possible answer options that a participant can give to your questionnaire. Can be used over the phone, video calls and online for quantitative research (measurable) .

2. Semi-structured questionnaire

This is a mix of open and closed questions, where like a structured questionnaire, you can get measurable results but it also gives the participant the opportunity to express themselves at certain points with open answers such as the reasons why they like brand X.

3. Unstructured questionnaire

This is more of an open way of allowing participants to express themselves through open questions that are not so rigid like the other two types of questionnaires but there is some order to it. The interviewer has the flexibility to probe to explore different lines of questioning around the subject area. This is used for qualitative research in focus groups or depth interviews.

In knowing how to make a questionnaire for research, you have to understand the common mistakes to avoid making them yourselves.

The following is a checklist of the top 10 mistakes to avoid when writing a questionnaire:

Mistake 1: Using two questions in one

Do not include more than one idea or question as this will cause confusion if you have multiple questions in one. Questions need to be short and not overcomplicated.

Mistake 2: Asking leading questions

Questions should not be leading the participants to give a certain answer. For example, excluding “poor” or “very poor” from the scale when asking customers to rate their recent experience of company B.

Mistake 3: Asking vague questions

There should not be any vagueness in the questions you use and need to be very specific as the words “frequently” or “usually” are not specific for a time period. Instead you should use words like “daily”, “weekly” and “monthly”. You can be even more specific by using numbers when asking questions like how often they go to the supermarket in a month.

Mistake 4: Using technical jargon, abbreviations and uncommon words

It’s important not to include jargon and acronyms unless they are used as everyday terms. If you have to include a technical term in the questionnaire, it’s best to include the definition of that term before the question.

Mistake 5: Including words that could be misheard

This is very relevant if the questionnaire is to be used over the phone, face to face or video calls. For example, if you are asking the question ‘what do you think are the differences between the sects?’ This could lead to interesting or amusing responses that are irrelevant to the actual question being asked.

Mistake 6: Asking questions with a negative in them

Understanding of the question will be more difficult if they are asked in a negative way such as “Do you never…?” when it should be “Do you ever…?”.

Mistake 7: Not applying bands for numeric data

This is really good for sensitive type of questions such as income, where bands can be applied for different levels of income like less than $100,000, $100,000-$200,000 and so on. The order of these bands should be sequential and don’t overlap.

Mistake 8: Not keeping in mind the frame of reference for the respondents

There is no point asking them how much milk they consumed in the last 6 months, when it’s better to ask them how many pints of milk they buy in a typical week as it will be hard for the participants to remember the true amount over a lengthy period of time. Besides you can make a simple calculation for a specific period of time from the feedback you get.

Mistake 9: Not including Other (specify) when you are presenting a list of options

Need to include other specify option when using list of options in a questionnaire, as you may not cover everything off such as a list of brands you buy from a supermarket.

Mistake 10: Asking sensitive type of questions at the start of the questionnaire

By having these questions like income or number of people in household at the back of the questionnaire, you have already developed some trust early on to complete the questionnaire rather than the other way round. Remember this is only if they are not an essential part of the screening process at the start of the questionnaire.

Once a questionnaire is drafted it's best to pre-test the questionnaire with colleagues, family or friends. A pre test uses a small number of respondents to help check if a questionnaire reads well, is easy to follow, see if there are any errors to fix, test the routing has been applied correctly and ensuring the survey length is not too long.

If your doing an online survey then it should not take more than 10 to 15 minutes to complete before people start dropping out.

Once all the relevant checks are made and any issues have been fixed then you are ready to go and launch your survey.

The main purpose of a questionnaire is obviously to get information out of participants but there are other benefits of a questionnaire, which are:

Serves as an aid for the interviewer without having to remember the questions.

To provide consistency in how all interviews are conducted.

Avoids having the interviewer using their own discretion throughout in making up questions.

Allows results to be recorded in a consistent way in order for results to be analysed easily later on.

Can be inexpensive when online and mobile survey methods are used.

Survey questionnaire allows you to collect information from a large audience.

An easy way to interview your target audience is by screening participants early on who meet your set criteria.

Allows comparability when questionnaire results are measurable and the questionnaire is asked of participants every quarter or yearly.

If you are considering DLY online survey then survey platforms like 123FormBuilder.com are great to use as they are inexpensive and are really intuitive to use. Plus, you can use them for more than just surveys with all kinds of online forms and templates for apps, tables, stores, approvals and more.

Another alternative if you just want to run a quick poll to compare or rank designs, ideas, logos, book covers or even Amazon sales pages including running short surveys then you should use PickFu, which is straight forward and not expensive to run (starting from $15). You can take advantage of their large online panel of 15 million across countries like the UK, US, Canada, Australia, Germany and Spain to ask questions to.

So give PickFu a try and get 50% off your first poll with the promo code - ANPAR.

Watch the video below for more information.

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• HOW TO GUIDES

Related Posts

How to write survey questions for research – with examples

• Post author: Marta Costa
• Post published: April 5, 2023
• Post category: Data Collection & Data Quality

A good survey can make or break your research. Learn how to write strong survey questions, learn what not to do, and see a range of practical examples.

The accuracy and relevance of the data you collect depend largely on the quality of your survey questions . In other words, good questions make for good research outcomes.  It makes sense then, that you should put considerable thought and planning into writing your survey or questionnaire.

In this article, we’ll go through what a good survey question looks like, talk about the different kinds of survey questions that exist, give you some tips for writing a good survey question, and finally, we’ll take a look at some examples. 

What is a good survey question?

A good survey question should contain simple and clear language. It should elicit responses that are accurate and that help you learn more about your target audience and their experiences. It should also fit in with the overall design of your survey project and connect with your research objective. There are many different types of survey questions. Let’s take a look at some of them now. 

New to survey data collection? Explore SurveyCTO for free with a 15-day trial.

Types of survey questions

Different types of questions are used for different purposes. Often questionnaires or surveys will combine several types of questions. The types you choose will depend on the overall design of your survey and your aims.  Here is a list of the most popular kinds of survey questions:  

These questions can’t be answered with a simple yes or no. They require the respondent to use more descriptive language to share their thoughts and answer the question. These types of questions result in qualitative data.

Closed-ended

A closed-ended question is the opposite of an open-ended question. Here the respondent’s answers are normally restricted to a yes or no, true or false, or multiple-choice answer. This results in quantitative data.

Dichotomous

This is a type of closed-ended question. The defining characteristic of these questions is that they have two opposing fields. For example, a question that can only be answered with a yes/no answer is a dichotomous question. 

Multiple choice

These are another type of closed-ended question. Here you give the respondent several possible ways, or options, in which they can respond. It’s also common to have an “other” section with a text box where the respondent can provide an unlisted answer.

Rating scale

This is again another type of close-ended question. Here you would normally present two extremes and the respondent has to choose between these extremes or an option placed along the scale.

Likert scale

A Likert scale is a form of a rating scale. These are generally used to measure attitudes towards something by asking the respondent to agree or disagree with a statement. They are commonly used to measure satisfaction. 

Ranking scale 

Here the respondents are given a few options and they need to order these different options in terms of importance, relevance, or according to the instructions.  

Demographic questions

These are often personal questions that allow you to better understand your respondents and their backgrounds. They normally cover questions related to age, race, marital status, education level, etc.

Ready to start creating your surveys? Sign up for a free 15-day trial.

7 Tips for writing a good survey question

The following 7 tips will help you to write a good survey question: 

1. Use clear, simple language

Your survey questions must be easy to understand. When they’re straight to the point, it’s more likely that your respondent will understand what you are asking of them and be able to respond accurately, giving you the data you need. 

2. Keep your questions (and answers) concise

When sentences or questions are convoluted or confusing, respondents might misunderstand the question. If your questions are too long, they may also get bored by the questions. And in your lists of answers for multiple choice questions, make sure your choice lists are concise as well.  If your questions are too long, or if you’ve provided too many options, you may receive responses that are inaccurate or that are not a true representation of how the respondent feels. To limit the number of options a respondent sees, you can use a survey platform like SurveyCTO to filter choice lists and make it easy for respondents to answer quickly. If you have an exceptionally long list of possible responses, like countries, implement search functionality in your list of choices so your respondents can quickly search for their selection.

3. Don’t add bias to your question

You should avoid leading your respondent in any particular direction with your questions, you want their response to be 100% their thoughts without being unduly influenced.  An example of a question that could lead the respondent in a particular direction would be:  How happy are you to live in this amazing area?  By adding the adjective amazing before area, you are putting the idea in the respondent’s head that the area is amazing. This could cloud their judgment and influence the way they answer the question. The word happy together with amazing may also be problematic. A better, less loaded way to ask this question might be something like this:  How satisfied are you living in this area?

4. Ask one question at a time

Asking multiple things in one question is confusing and will lead to inaccuracies in the answer. When you write your question you should know exactly what you want to achieve. This will help you to avoid combining two questions in one. Here is an example of a double-barrelled question that would be difficult for a respondent to answer: Please answer yes or no to the following question: Do you drive to work and do you carry any passengers? In this question, the respondent is being asked two things, yet they only have the opportunity to respond to one. Even then, they don’t know which one they should respond to. Avoid this kind of questioning to get clearer, more accurate data.

5. Account for all possible answer choices

You should give your respondent the ability to answer a question accurately. For instance, if you are asking a demographic question you’ll need to provide options that accurately reflect their experience. Below, you can see there is an “other” option with space where the respondent can answer how they see fit, in the case that they don’t fit into any of the other options. Which gender do you most identify with:

• Prefer not to say
• Other [specify]

6. Plan the question flow and choose your questions carefully

Question writing goes hand-in-hand with questionnaire design. So, when writing survey questions, you should consider the survey as a whole. For example, if you write a close-ended question like:  Were you satisfied with the customer service you received when you bought x product? You might want to follow it up with an open-ended question such as:   Please explain the reason for your answer: This will help you draw out more information from your respondent that can help you assess the strengths and weaknesses of your customer service team.  Making sure your questions flow in a logical order is also important. 

For instance, if you ask a question regarding the total cost of a person’s childcare arrangements, but you’re unaware if they have children, you should first ask if they have children and how many.  It’s also a good idea to start your survey with short, easy-to-answer, non-sensitive questions before moving on to something more complex. This way there is more chance you’ll engage your audience early on and make it more likely that they’ll continue with the survey. You should also consider whether you need qualitative or quantitative data for your research outcomes or a mix of the two. This will help you decide the balance of closed-ended and open-ended questions you use.   With close-ended questions, you get quantitative data. This data will be fairly conclusive and simple to analyze. It can be useful when you need to measure specific variables or metrics like population sizes, education levels, literacy levels, etc. 

On the other hand, qualitative data gained by open-ended questions can be full of insights. However, these questions can be more laborious for the respondent to complete making it more likely for them to skip through or give a token answer. They’re also more complex to analyze.

7. Test your surveys

Before a questionnaire goes anywhere near a respondent, it needs to be checked over. Mistakes in your survey questions can give inaccurate results. They can also waste time and resources.  Having an impartial person check your questions can also help prevent bias. So, not only should you check your work, but you should also share it with colleagues for them to check.  After checking your survey questions, make sure to check the functionality and flow of your survey. If you’re building your form in SurveyCTO, you can use our form testing interface to catch errors, make quick fixes, and test your workflows with real data.

Examples of good survey questions

Now that we’ve gone through some dos and don’ts for writing survey questions, we can move on to more practical examples of how a good survey question should look. To keep these specific to the research world we’ll look at three categories of questions. 

• Household survey questions 
• Monitoring and evaluation survey questions 
• Impact evaluation survey questions

1. Household Survey Questions

2. monitoring and evaluation survey questions , 3. impact evaluation questions .

Strong survey questions lead to better research outcomes

Writing good survey questions is essential if you want to achieve your research aims.  A good survey question should be clear, concise, and contain simple language. They should be free of bias and not lead the respondent in any direction. Your survey questions need to complement each other, engage your audience and connect back to the overall objectives of your research.  Creating survey questions and survey designs is a large part of your research, however, is just a part of the puzzle. When your questions are ready, you’ll need to conduct your survey and then find a way to manage your data and workflow. Take a look at this post to see more ways SurveyCTO can help you beyond writing your research survey questions. 

Your next steps: Explore more resources

To keep reading about how SurveyCTO can help you design better surveys, take a look at these resources:  

• Sign up here to get notified about our monthly webinars, where organizations like IDinsight  share best practices for effective surveys.
• Check out previous webinars from SurveyCTO about survey forms, like this one on high-frequency checks for monitoring surveys. 
• Sign up for a free trial of SurveyCTO for your next survey project.

To see how SurveyCTO can help you with your survey needs, start a free 15-day trial today. No credit card required. 

Marta Costa

Senior Product Specialist

Marta is a member of the Customer Success team for Dobility. She helps users working at NGOs, nonprofits, survey firms, universities and research institutes achieve their objectives using SurveyCTO, and works on new ways to help users get the most out of the platform.

Marta has worked in international development consultancy and research, supporting and coordinating impact evaluations, monitoring and evaluation projects, and data collection processes at the national level in areas such as education, energy access, and financial inclusion.

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Research Questionnaire

Questionnaire generator.

When a researcher creates a research paper using the scientific method they will need to use a gathering method that is adjacent to the research topic. This means that the researcher will use a quantitative research method for a quantitive topic and a qualitative method for a qualitative  one.  The research questionnaire is one of the quantitative data-gathering methods a researcher can use in their research paper.

1. Market Research Questionnaire Template Example

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2. Market Research Questionnaire Example

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3. Research Questionnaire Example

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5. Research Survey Questionnaire

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6. Research Survey Questionnaire Construction

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7. Research Questionnaire Survey of Consumers

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12. Developing Questionnaires for Educational Research

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13. Graudate Research Student Questionnaires

14. Sample Research Survey Questionnaires

Size: 46 KB

15. Market Research Questionnaire Example

16. Research Survey Questionnaire Example

17. Product X Research Study Questionnaire Example

What Is a Research Questionnaire?

A research questionnaire is a physical or digital questionnaire that researchers use to obtain quantitative data. The research questionnaire is a more in-depth version of a survey   as its questions often delve deeper than survey questions .

How to Write a Research Questionnaire

A well-made research questionnaire can effectively and efficiently gather data from the population. Creating a good research questionnaire does not require that many writing skills , soft skills , or hard skills , it just requires the person to properly understand the data set they are looking for.

Step 1: Select a Topic or Theme for the Research Questionnaire

Begin by choosing a topic or theme   for the research questionnaire as this will provide much-needed context for the research questionnaire. Not only that but the topic will also dictate the tone of the questions in the questionnaire.

Step 2: Obtain or Use a Research Questionnaire Outline

You may opt to use a research questionnaire outline or outline format for your research questionnaire. This outline will provide you with a structure you can use to easily make your research questionnaire.

Step 3: Create your Research Questionnaire

Start by creating questions that will help provide you with the necessary data to prove or disprove your research question. You may conduct brainstorming sessions to formulate the questions for your research questionnaire.

Step 4: Edit and Have Someone Proofread the Questionnaire

After you have created and completed the research questionnaire, you must edit the contents of the questionnaire. Not only that but it is wise to have someone proofread the contents of your questionnaire before deploying the questionnaire. 

How does a research questionnaire help businesses?

A successful business or company utilizes research questionnaires to not only obtain data from their customers but also to gather data about the performance and quality of the employees in the business. The research questionnaire provides the business or company with actionable data, which they can use to improve the product, service, or commodity to obtain more customers.

Do I need to provide a consent form when I ask someone to answer the research questionnaire?

Yes, consent is very important as without this the data you have gathered from your questionnaires or surveys are useless. Therefore it is important to provide a consent form with your research questionnaire when you are asking a participant to answer the document.

What type of answers are allowed in the research questionnaire?

Research questionnaires can host a multitude of types of questions each with its specific way of answering.  A questionnaire can use multiple-choice questions, open-ended questions, and closed questions. Just be sure to properly pace the questions as having too many different types of answering styles can demotivate or distract the target audience, which might lead to errors.

A research questionnaire is a data-gathering document people can use to obtain information and data from a specific group of people. Well-made and crafted research questionnaires will provide much-needed information one can use to answer a specific research question.

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How to Write a Thesis or Dissertation Questionnaire?

Published by Alvin Nicolas at August 7th, 2024 , Revised On August 7, 2024

Do you know the first questionnaire was developed in 1838? It was designed to collect responses from individuals to understand their behaviour towards various stimuli. Since then, scientists have been using questionnaires to collect statistical data. The invention of the questionnaire gave birth to subjects like Sociology and Statistics .

Nowadays, sociology or psychology students also collect statistical data and information using questionnaires to understand individuals’ behaviour. Excellent questionnaires help produce high-quality research results.

This blog comprehensively discusses what a thesis or dissertation questionnaire is and the steps involved in writing one. Learn how to write a questionnaire and optimise your research process .

What is a Thesis or Dissertation Questionnaire?

A questionnaire is a set of specific questions that are particularly designed to assess the preferences, intentions, experiences, opinions, and behaviour of the individuals. In a thesis or dissertation, students use questionnaires to collect qualitative or quantitative data relevant to their subjects.

However, using questionnaires to collect data and information is a very tiresome and hectic task because researchers have to wait for the respondents to answer all the questions.

Importance of Thesis & Dissertation Questionnaire

Imagine you want to ask one or two questions from an individual. You can easily ask him/her those questions. What would you do when you have to record their thorough response to multiple questions? In that case, the questionnaire is the best option for collecting individual responses.

A thesis or dissertation questionnaire does not specify precisely whether it is used for simple research or a survey. In the case of a survey, there would always be a questionnaire. Here are the reasons why a thesis or dissertation questionnaire is important during the research process:

• Questionnaires help researchers collect data in an organised and systematic manner.
• With questionnaires, data can be efficiently analysed and quick conclusions can be drawn.
• There are no extensive costs involved in to design research questionnaires. It is a cost-effective method to collect data.
• Researchers can ask multiple questions to record the response about a specific topic thoroughly.

Several formalities are involved in collecting data through a questionnaire. One basic consideration is the dissertation questionnaire consent form.

Dissertation Questionnaire Consent Form

The questionnaire consent form is the document the participants sign to indicate their consent to participate in the research process. It is crucial to ask for their consent because data and information are used for research purposes. Also, inform them about the topic so they can decide efficiently.

The questionnaire consent form is usually presented on the first page of the thesis or dissertation questionnaire. It contains the participant’s personal and contact information.

Online Dissertation Questionnaire

As you know, in this digital age, everything is shifting to digital platforms. There was a time when researchers had to wait for the individuals to fill out the questionnaire paper. No doubt, it was a tiresome task. Now, researchers send the thesis or dissertation questionnaires to digital platforms such as email, inbox, and social media.

Online dissertation questionnaire tools such as Google Forms, Microsoft Forms, and SurveyPlanet have made data analysis and collection much more convenient and reliable.

Components of an Excellent Dissertation Questionnaire

These are the components of an excellent thesis or dissertation questionnaire:

It has a Structured Design

The best property of a good dissertation questionnaire is its structured design. When questions and their categories are efficiently structured in a questionnaire, it provides an eye-catching look. This helps the participants to fill out the questionnaire more proficiently.

It Contains Unique and Exploratory Questions

An outstanding questionnaire always has unique and well-researched questions rather than overly used typical ones. Every question can provide a sufficient response. It contains exploratory questions to explore even minor information about the participants thoroughly.

It has Likert Scales

Likert scales are a measurement method in research to assess attitudes, opinions, and perceptions. They are widely used in the questionnaires to generate responses accurately. When a questionnaire has Likert scales, it makes it easy for the researchers to derive results from that.

It has Consistency of Questions

Another sign of an excellent question is its consistency. It contains perfectly categorised questions that make sense to the participants from start to end. Every question follows an appropriate question systematically.

Difference Between Questionnaire and Survey

Steps Involved in Writing a Dissertation Questionnaire

Writing a thesis or dissertation questionnaire requires different methods. These methods can be modified accordingly to make your questionnaire relevant to your research objectives. However, the essential steps involved in writing a dissertation questionnaire are given as follows:

Step 1: Establish Your Research Objectives To Ese Your Research Process

The first step in writing a thesis or dissertation question is establishing the research objectives. You have to be clear about your research goals. The research is usually done to fill an already-present gap in the data. It is done to find significant solutions to specific problems. It is crucial to have the goals to solve a problem.

Step 2: Assess the Requirements to Ensure They Are Achievable

It is also important to assess the research requirements. Requirements will help you know what you need and what you don’t need to write your research questionnaire. It is easy to start a research process when all the requirements are easily achievable. Also, the time and money spent on the questionnaire should be considered.

Step 3: Choose the Right Data Collection Method To Derive Authentic Results

There are many data collection methods , such as in-person, telephone, email, direct mail, and online platforms. It is essential to choose the proper data collection method that can be easily used to deliver authentic results. You should also design your questionnaire according to the collection method.

Methodology

Methodology is the collection of particular techniques for collecting and processing data. Create an efficient research methodology to collect data accurately. It will help you optimise and streamline your research process.

Step 4: Develop the Unique and Logical Questions for Data Collection

After selecting an appropriate data collection method, it is time to develop unique questionnaire questions. The questions should be logical and follow a series of numbers. Close-ended questions are used in the writing of dissertation or thesis questionnaires.

Step 5: Set the Perfect Scaling According to Your Questions

Scaling is used to calculate the response of the participants. Researchers should set the perfect scaling according to the nature of the questions. The Likert scale is the most widely used in questionnaires. It allows researchers to generate responses of participants from the right extreme to the left extreme.

Step 6: Creatively Design the Questionnaire to Enhance Its Visual Appeal

The next step is designing the layout of the questionnaire. It is crucial to enhance the visual appeal of the questionnaire. The design and colour of the questionnaire should be selected according to the theme of the topic. Moreover, a graphically appealing questionnaire also enhances the engagement of readers.

Step 7: Analysing & Evaluation the Questionnaire To Remove Discrepancies

The most important step after designing is analysing and evaluating. This step will allow you to fill gaps if there are any. Check the alignment of the questions and scaling. The numbering should be perfect. The colouring and design should also be on point. This step proceeds with the testing.

Step 8: Pretest With a Small Population and Collect Necessary Feedback

After completing the questionnaire, prepare to pretest it with a small population. Check the responses of the participants thoroughly. Be open to feedback and criticism. It will help you consider revisions and alterations and improve your questionnaire.

Step 9: Revise to Make Changes To Enhance the Quality

If there are any changes required in the questionnaire, make them immediately. Revise your questionnaire again and again to illuminate even a minor mistake. Also, take feedback from your peers to further enhance the quality of your questionnaire.

Step 10: Finalising the Questionnaire and Launching it for the Research

When all the required changes and revisions are made, it’s time to finalise the questionnaire. Again, go through all its important obligations and ensure everything is in perfect shape. When everything is done from your side, it’s time to finalise and launch it for the actual research.

Dissertation Questionnaire Examples

Here, we’ll discuss the sample and template of the dissertation questionnaire to understand how it looks. This will significantly help us create our dissertation questionnaire.

Dissertation Questionnaire Template

Here is a template of the dissertation questionnaire:

[Introduction of the Researcher with all the key objectives briefly explained.]

[Questionnaire consent Form]

Dissertation Questionnaire Example

Introduction: Hello. My name is ……….. I am currently studying at………………. and doing my …………………………. I am conducting this research to [agenda of the study].This research will help me to provide solutions to all these problems:

[Problems and solutions]

This questionnaire contains XX questions. It will just take 15 minutes to complete it. All your personal information and responses will be kept anonymous from other participants. There are both open-ended and close-ended questions. Answer them honestly. Thank you.

Part 1: Multiple Choice Questions

• Are you a male or a female?

• Have you completed your bachelor’s degree?

• Did you study your major according to your passion?
• Are you doing a job related to your degree?
• Are you satisfied with your current job?

Frequently Asked Questions

How long should a dissertation questionnaire be.

The length of your questionnaire should be according to your objectives. There is no fixed number of questions in a questionnaire. Some questionnaires are basic, some are exploratory, and some are in-depth. However, an ideal questionnaire should be completed in 25 to 30 minutes without losing the participant’s interest. 

How many questions should a dissertation questionnaire have?

It’s entirely up to you to add as many questions as you want. Remember that you should add enough questions to complete your research objectives. Avoid adding excessive questions, as they can be boring for participants.

How to analyse a questionnaire for a dissertation?

These are the necessary tips to analyse a questionnaire for a dissertation: 

• Pile up all the responses 
• Analyse all the questions
• Visualise the collected data
• Interpretation of results

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Here are the steps to make a theoretical framework for dissertation. You can define, discuss and evaluate theories relevant to the research problem.

Appendices or Appendixes are used to provide additional date related to your dissertation research project. Here we explain what is appendix in dissertation

Anyone who supports you in your research should be acknowledged in dissertation acknowledgments. Learn more on how to write dissertation acknowledgements.

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Doctoral Dissertations and Projects

A causal-comparative study of the writing motivational constructs of students with and without attention-deficit/ hyperactivity disorder in online college composition courses.

Michelle Bianco , Liberty University Follow

School of Education

Doctor of Philosophy

Maryna Svirska-Otero

attention-deficit/hyperactivity disorder, ADHD, self-efficacy, motivation, online college composition

Disciplines

Curriculum and Instruction | Education

Recommended Citation

Bianco, Michelle, "A Causal-Comparative Study of the Writing Motivational Constructs of Students With and Without Attention-Deficit/ Hyperactivity Disorder in Online College Composition Courses" (2024). Doctoral Dissertations and Projects . 5908. https://digitalcommons.liberty.edu/doctoral/5908

The purpose of this quantitative, non-experimental, causal-comparative study is to determine if there is a difference in the writing motivation of students with attention-deficit/ hyperactivity disorder (ADHD) and students without ADHD in online college composition I courses. The study of writing motivation in relation to ADHD in online college composition courses is significant as writing motivation is a crucial predictor of academic success and persistence. Data was collected from a population of approximately 1685 students enrolled in online college composition I at an accredited online university within a larger midwestern land-grant public university system. Using the Writing Motivation Questionnaire and the self-reported results of the covariate (Personal Writing Assessment score), students without ADHD were compared to students with ADHD to determine how writing motivation construct scores differed between the groups. The data was analyzed using a one-way analysis of covariance controlling for the effect of the covariate, and the results demonstrated that this sample of online college composition students with ADHD had lower levels of writing motivation, which correlated with lower previous writing abilities. Further discussion included the impact of ADHD on writing motivation, academic success, and the link to early assessment. The implications of the research suggest a need for accommodation. Limitations, such as the time constraints of the survey combined with the assessment, were also addressed, and recommendations for further research using essay writing as the covariate were made.

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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 .

Prevent plagiarism, run a free check.

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 cite ChatGPT

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We, the APA Style team, are not robots. We can all pass a CAPTCHA test , and we know our roles in a Turing test . And, like so many nonrobot human beings this year, we’ve spent a fair amount of time reading, learning, and thinking about issues related to large language models, artificial intelligence (AI), AI-generated text, and specifically ChatGPT . We’ve also been gathering opinions and feedback about the use and citation of ChatGPT. Thank you to everyone who has contributed and shared ideas, opinions, research, and feedback.

In this post, I discuss situations where students and researchers use ChatGPT to create text and to facilitate their research, not to write the full text of their paper or manuscript. We know instructors have differing opinions about how or even whether students should use ChatGPT, and we’ll be continuing to collect feedback about instructor and student questions. As always, defer to instructor guidelines when writing student papers. For more about guidelines and policies about student and author use of ChatGPT, see the last section of this post.

Quoting or reproducing the text created by ChatGPT in your paper

If you’ve used ChatGPT or other AI tools in your research, describe how you used the tool in your Method section or in a comparable section of your paper. For literature reviews or other types of essays or response or reaction papers, you might describe how you used the tool in your introduction. In your text, provide the prompt you used and then any portion of the relevant text that was generated in response.

Unfortunately, the results of a ChatGPT “chat” are not retrievable by other readers, and although nonretrievable data or quotations in APA Style papers are usually cited as personal communications , with ChatGPT-generated text there is no person communicating. Quoting ChatGPT’s text from a chat session is therefore more like sharing an algorithm’s output; thus, credit the author of the algorithm with a reference list entry and the corresponding in-text citation.

When prompted with “Is the left brain right brain divide real or a metaphor?” the ChatGPT-generated text indicated that although the two brain hemispheres are somewhat specialized, “the notation that people can be characterized as ‘left-brained’ or ‘right-brained’ is considered to be an oversimplification and a popular myth” (OpenAI, 2023).

OpenAI. (2023). ChatGPT (Mar 14 version) [Large language model]. https://chat.openai.com/chat

You may also put the full text of long responses from ChatGPT in an appendix of your paper or in online supplemental materials, so readers have access to the exact text that was generated. It is particularly important to document the exact text created because ChatGPT will generate a unique response in each chat session, even if given the same prompt. If you create appendices or supplemental materials, remember that each should be called out at least once in the body of your APA Style paper.

When given a follow-up prompt of “What is a more accurate representation?” the ChatGPT-generated text indicated that “different brain regions work together to support various cognitive processes” and “the functional specialization of different regions can change in response to experience and environmental factors” (OpenAI, 2023; see Appendix A for the full transcript).

Creating a reference to ChatGPT or other AI models and software

The in-text citations and references above are adapted from the reference template for software in Section 10.10 of the Publication Manual (American Psychological Association, 2020, Chapter 10). Although here we focus on ChatGPT, because these guidelines are based on the software template, they can be adapted to note the use of other large language models (e.g., Bard), algorithms, and similar software.

The reference and in-text citations for ChatGPT are formatted as follows:

• Parenthetical citation: (OpenAI, 2023)
• Narrative citation: OpenAI (2023)

Let’s break that reference down and look at the four elements (author, date, title, and source):

Author: The author of the model is OpenAI.

Date: The date is the year of the version you used. Following the template in Section 10.10, you need to include only the year, not the exact date. The version number provides the specific date information a reader might need.

Title: The name of the model is “ChatGPT,” so that serves as the title and is italicized in your reference, as shown in the template. Although OpenAI labels unique iterations (i.e., ChatGPT-3, ChatGPT-4), they are using “ChatGPT” as the general name of the model, with updates identified with version numbers.

The version number is included after the title in parentheses. The format for the version number in ChatGPT references includes the date because that is how OpenAI is labeling the versions. Different large language models or software might use different version numbering; use the version number in the format the author or publisher provides, which may be a numbering system (e.g., Version 2.0) or other methods.

Bracketed text is used in references for additional descriptions when they are needed to help a reader understand what’s being cited. References for a number of common sources, such as journal articles and books, do not include bracketed descriptions, but things outside of the typical peer-reviewed system often do. In the case of a reference for ChatGPT, provide the descriptor “Large language model” in square brackets. OpenAI describes ChatGPT-4 as a “large multimodal model,” so that description may be provided instead if you are using ChatGPT-4. Later versions and software or models from other companies may need different descriptions, based on how the publishers describe the model. The goal of the bracketed text is to briefly describe the kind of model to your reader.

Source: When the publisher name and the author name are the same, do not repeat the publisher name in the source element of the reference, and move directly to the URL. This is the case for ChatGPT. The URL for ChatGPT is https://chat.openai.com/chat . For other models or products for which you may create a reference, use the URL that links as directly as possible to the source (i.e., the page where you can access the model, not the publisher’s homepage).

Other questions about citing ChatGPT

You may have noticed the confidence with which ChatGPT described the ideas of brain lateralization and how the brain operates, without citing any sources. I asked for a list of sources to support those claims and ChatGPT provided five references—four of which I was able to find online. The fifth does not seem to be a real article; the digital object identifier given for that reference belongs to a different article, and I was not able to find any article with the authors, date, title, and source details that ChatGPT provided. Authors using ChatGPT or similar AI tools for research should consider making this scrutiny of the primary sources a standard process. If the sources are real, accurate, and relevant, it may be better to read those original sources to learn from that research and paraphrase or quote from those articles, as applicable, than to use the model’s interpretation of them.

We’ve also received a number of other questions about ChatGPT. Should students be allowed to use it? What guidelines should instructors create for students using AI? Does using AI-generated text constitute plagiarism? Should authors who use ChatGPT credit ChatGPT or OpenAI in their byline? What are the copyright implications ?

On these questions, researchers, editors, instructors, and others are actively debating and creating parameters and guidelines. Many of you have sent us feedback, and we encourage you to continue to do so in the comments below. We will also study the policies and procedures being established by instructors, publishers, and academic institutions, with a goal of creating guidelines that reflect the many real-world applications of AI-generated text.

For questions about manuscript byline credit, plagiarism, and related ChatGPT and AI topics, the APA Style team is seeking the recommendations of APA Journals editors. APA Style guidelines based on those recommendations will be posted on this blog and on the APA Style site later this year.

Update: APA Journals has published policies on the use of generative AI in scholarly materials .

We, the APA Style team humans, appreciate your patience as we navigate these unique challenges and new ways of thinking about how authors, researchers, and students learn, write, and work with new technologies.

American Psychological Association. (2020). Publication manual of the American Psychological Association (7th ed.). https://doi.org/10.1037/0000165-000

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Methodology

• Survey Research | Definition, Examples & Methods

Survey Research | Definition, Examples & Methods

Published on August 20, 2019 by Shona McCombes . Revised on June 22, 2023.

Survey research means collecting information about a group of people by asking them questions and analyzing the results. To conduct an effective survey, follow these six steps:

• Determine who will participate in the survey
• Decide the type of survey (mail, online, or in-person)
• Design the survey questions and layout
• Distribute the survey
• Analyze the responses
• Write up the results

Surveys are a flexible method of data collection that can be used in many different types of research .

Table of contents

What are surveys used for, step 1: define the population and sample, step 2: decide on the type of survey, step 3: design the survey questions, step 4: distribute the survey and collect responses, step 5: analyze the survey results, step 6: write up the survey results, other interesting articles, frequently asked questions about surveys.

Surveys are used as a method of gathering data in many different fields. They are a good choice when you want to find out about the characteristics, preferences, opinions, or beliefs of a group of people.

Common uses of survey research include:

• Social research : investigating the experiences and characteristics of different social groups
• Market research : finding out what customers think about products, services, and companies
• Health research : collecting data from patients about symptoms and treatments
• Politics : measuring public opinion about parties and policies
• Psychology : researching personality traits, preferences and behaviours

Surveys can be used in both cross-sectional studies , where you collect data just once, and in longitudinal studies , where you survey the same sample several times over an extended period.

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Before you start conducting survey research, you should already have a clear research question that defines what you want to find out. Based on this question, you need to determine exactly who you will target to participate in the survey.

Populations

The target population is the specific group of people that you want to find out about. This group can be very broad or relatively narrow. For example:

• The population of Brazil
• US college students
• Second-generation immigrants in the Netherlands
• Customers of a specific company aged 18-24
• British transgender women over the age of 50

Your survey should aim to produce results that can be generalized to the whole population. That means you need to carefully define exactly who you want to draw conclusions about.

Several common research biases can arise if your survey is not generalizable, particularly sampling bias and selection bias . The presence of these biases have serious repercussions for the validity of your results.

It’s rarely possible to survey the entire population of your research – it would be very difficult to get a response from every person in Brazil or every college student in the US. Instead, you will usually survey a sample from the population.

The sample size depends on how big the population is. You can use an online sample calculator to work out how many responses you need.

There are many sampling methods that allow you to generalize to broad populations. In general, though, the sample should aim to be representative of the population as a whole. The larger and more representative your sample, the more valid your conclusions. Again, beware of various types of sampling bias as you design your sample, particularly self-selection bias , nonresponse bias , undercoverage bias , and survivorship bias .

There are two main types of survey:

• A questionnaire , where a list of questions is distributed by mail, online or in person, and respondents fill it out themselves.
• An interview , where the researcher asks a set of questions by phone or in person and records the responses.

Which type you choose depends on the sample size and location, as well as the focus of the research.

Questionnaires

Sending out a paper survey by mail is a common method of gathering demographic information (for example, in a government census of the population).

• You can easily access a large sample.
• You have some control over who is included in the sample (e.g. residents of a specific region).
• The response rate is often low, and at risk for biases like self-selection bias .

Online surveys are a popular choice for students doing dissertation research , due to the low cost and flexibility of this method. There are many online tools available for constructing surveys, such as SurveyMonkey and Google Forms .

• You can quickly access a large sample without constraints on time or location.
• The data is easy to process and analyze.
• The anonymity and accessibility of online surveys mean you have less control over who responds, which can lead to biases like self-selection bias .

If your research focuses on a specific location, you can distribute a written questionnaire to be completed by respondents on the spot. For example, you could approach the customers of a shopping mall or ask all students to complete a questionnaire at the end of a class.

• You can screen respondents to make sure only people in the target population are included in the sample.
• You can collect time- and location-specific data (e.g. the opinions of a store’s weekday customers).
• The sample size will be smaller, so this method is less suitable for collecting data on broad populations and is at risk for sampling bias .

Oral interviews are a useful method for smaller sample sizes. They allow you to gather more in-depth information on people’s opinions and preferences. You can conduct interviews by phone or in person.

• You have personal contact with respondents, so you know exactly who will be included in the sample in advance.
• You can clarify questions and ask for follow-up information when necessary.
• The lack of anonymity may cause respondents to answer less honestly, and there is more risk of researcher bias.

Like questionnaires, interviews can be used to collect quantitative data: the researcher records each response as a category or rating and statistically analyzes the results. But they are more commonly used to collect qualitative data : the interviewees’ full responses are transcribed and analyzed individually to gain a richer understanding of their opinions and feelings.

Next, you need to decide which questions you will ask and how you will ask them. It’s important to consider:

• The type of questions
• The content of the questions
• The phrasing of the questions
• The ordering and layout of the survey

Open-ended vs closed-ended questions

There are two main forms of survey questions: open-ended and closed-ended. Many surveys use a combination of both.

Closed-ended questions give the respondent a predetermined set of answers to choose from. A closed-ended question can include:

• A binary answer (e.g. yes/no or agree/disagree )
• A scale (e.g. a Likert scale with five points ranging from strongly agree to strongly disagree )
• A list of options with a single answer possible (e.g. age categories)
• A list of options with multiple answers possible (e.g. leisure interests)

Closed-ended questions are best for quantitative research . They provide you with numerical data that can be statistically analyzed to find patterns, trends, and correlations .

Open-ended questions are best for qualitative research. This type of question has no predetermined answers to choose from. Instead, the respondent answers in their own words.

Open questions are most common in interviews, but you can also use them in questionnaires. They are often useful as follow-up questions to ask for more detailed explanations of responses to the closed questions.

The content of the survey questions

To ensure the validity and reliability of your results, you need to carefully consider each question in the survey. All questions should be narrowly focused with enough context for the respondent to answer accurately. Avoid questions that are not directly relevant to the survey’s purpose.

When constructing closed-ended questions, ensure that the options cover all possibilities. If you include a list of options that isn’t exhaustive, you can add an “other” field.

Phrasing the survey questions

In terms of language, the survey questions should be as clear and precise as possible. Tailor the questions to your target population, keeping in mind their level of knowledge of the topic. Avoid jargon or industry-specific terminology.

Survey questions are at risk for biases like social desirability bias , the Hawthorne effect , or demand characteristics . It’s critical to use language that respondents will easily understand, and avoid words with vague or ambiguous meanings. Make sure your questions are phrased neutrally, with no indication that you’d prefer a particular answer or emotion.

Ordering the survey questions

The questions should be arranged in a logical order. Start with easy, non-sensitive, closed-ended questions that will encourage the respondent to continue.

If the survey covers several different topics or themes, group together related questions. You can divide a questionnaire into sections to help respondents understand what is being asked in each part.

If a question refers back to or depends on the answer to a previous question, they should be placed directly next to one another.

Before you start, create a clear plan for where, when, how, and with whom you will conduct the survey. Determine in advance how many responses you require and how you will gain access to the sample.

When you are satisfied that you have created a strong research design suitable for answering your research questions, you can conduct the survey through your method of choice – by mail, online, or in person.

There are many methods of analyzing the results of your survey. First you have to process the data, usually with the help of a computer program to sort all the responses. You should also clean the data by removing incomplete or incorrectly completed responses.

If you asked open-ended questions, you will have to code the responses by assigning labels to each response and organizing them into categories or themes. You can also use more qualitative methods, such as thematic analysis , which is especially suitable for analyzing interviews.

Statistical analysis is usually conducted using programs like SPSS or Stata. The same set of survey data can be subject to many analyses.

Finally, when you have collected and analyzed all the necessary data, you will write it up as part of your thesis, dissertation , or research paper .

In the methodology section, you describe exactly how you conducted the survey. You should explain the types of questions you used, the sampling method, when and where the survey took place, and the response rate. You can include the full questionnaire as an appendix and refer to it in the text if relevant.

Then introduce the analysis by describing how you prepared the data and the statistical methods you used to analyze it. In the results section, you summarize the key results from your analysis.

In the discussion and conclusion , you give your explanations and interpretations of these results, answer your research question, and reflect on the implications and limitations of the research.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Student’s  t -distribution
• Normal distribution
• Null and Alternative Hypotheses
• Chi square tests
• Confidence interval
• Quartiles & Quantiles
• Cluster sampling
• Stratified sampling
• Data cleansing
• Reproducibility vs Replicability
• Peer review
• Prospective cohort study

Research bias

• Implicit bias
• Cognitive bias
• Placebo effect
• Hawthorne effect
• Hindsight bias
• Affect heuristic
• Social desirability bias

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

A Likert scale is a rating scale that quantitatively assesses opinions, attitudes, or behaviors. It is made up of 4 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 5 or 7 possible responses, to capture their degree of agreement.

Individual Likert-type questions are generally considered ordinal data , because the items have clear rank order, but don’t have an even distribution.

Overall Likert scale scores are sometimes treated as interval data. These scores are considered to have directionality and even spacing between them.

The type of data determines what statistical tests you should use to analyze your data.

The priorities of a research design can vary depending on the field, but you usually have to specify:

• Your research questions and/or hypotheses
• Your overall approach (e.g., qualitative or quantitative )
• The type of design you’re using (e.g., a survey , experiment , or case study )
• Your sampling methods or criteria for selecting subjects
• Your data collection methods (e.g., questionnaires , observations)
• Your data collection procedures (e.g., operationalization , timing and data management)
• Your data analysis methods (e.g., statistical tests  or thematic analysis )

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McCombes, S. (2023, June 22). Survey Research | Definition, Examples & Methods. Scribbr. Retrieved August 7, 2024, from https://www.scribbr.com/methodology/survey-research/

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Shona McCombes

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