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Questionnaire – Definition, Types, and Examples

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Questionnaire

Definition:

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

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

History of Questionnaire

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

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

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

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

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

Types of Questionnaire

Types of Questionnaires are as follows:

Structured Questionnaire

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

Unstructured Questionnaire

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

Open-ended Questionnaire

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

Close-ended Questionnaire

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

Mixed Questionnaire

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

Pictorial Questionnaire:

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

Types of Questions in Questionnaire

The types of Questions in Questionnaire are as follows:

Multiple Choice Questions

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

• a. Red b . Blue c. Green d . Yellow

Rating Scale Questions

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

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

Open-Ended Questions

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

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

Likert Scale Questions

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

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

“I enjoy exercising regularly.”

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

Demographic Questions

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

• What is your age?

Yes/No Questions

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

Have you ever traveled outside of your home country?

Ranking Questions

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

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

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

Matrix Questions

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

Dichotomous Questions

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

Do you support the death penalty?

How to Make a Questionnaire

Step-by-Step Guide for Making a Questionnaire:

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

Questionnaire Administration Modes

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

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

Example of Questionnaire

Title of the Survey: Customer Satisfaction Survey

Introduction:

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

Instructions:

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

1. How satisfied are you with our product quality?

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

2. How satisfied are you with our customer service?

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

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

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

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

• Somewhat easy
• Somewhat difficult
• Very difficult

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

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

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

Conclusion:

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

Applications of Questionnaire

Some common applications of questionnaires include:

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

Purpose of Questionnaire

Some common purposes of questionnaires include:

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

When to use Questionnaire

Here are some situations when questionnaires might be used:

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

Characteristics of Questionnaire

Here are some of the characteristics of questionnaires:

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

Advantage of Questionnaire

Some Advantage of Questionnaire are as follows:

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

Limitations of Questionnaire

Limitations of Questionnaire are as follows:

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

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Questionnaires

Questionnaires can be classified as both, quantitative and qualitative method depending on the nature of questions. Specifically, answers obtained through closed-ended questions (also called restricted questions) with multiple choice answer options are analyzed using quantitative methods. Research findings in this case can be illustrated using tabulations, pie-charts, bar-charts and percentages.

Answers obtained to open-ended questionnaire questions (also known as unrestricted questions), on the other hand, are analyzed using qualitative methods. Primary data collected using open-ended questionnaires involve discussions and critical analyses without use of numbers and calculations.

There are following types of questionnaires:

Computer questionnaire . Respondents are asked to answer the questionnaire which is sent by mail. The advantages of the computer questionnaires include their inexpensive price, time-efficiency, and respondents do not feel pressured, therefore can answer when they have time, giving more accurate answers. However, the main shortcoming of the mail questionnaires is that sometimes respondents do not bother answering them and they can just ignore the questionnaire.

Telephone questionnaire .  Researcher may choose to call potential respondents with the aim of getting them to answer the questionnaire. The advantage of the telephone questionnaire is that, it can be completed during the short amount of time. The main disadvantage of the phone questionnaire is that it is expensive most of the time. Moreover, most people do not feel comfortable to answer many questions asked through the phone and it is difficult to get sample group to answer questionnaire over the phone.

In-house survey .  This type of questionnaire involves the researcher visiting respondents in their houses or workplaces. The advantage of in-house survey is that more focus towards the questions can be gained from respondents. However, in-house surveys also have a range of disadvantages which include being time consuming, more expensive and respondents may not wish to have the researcher in their houses or workplaces for various reasons.

Mail Questionnaire . This sort of questionnaires involve the researcher to send the questionnaire list to respondents through post, often attaching pre-paid envelope. Mail questionnaires have an advantage of providing more accurate answer, because respondents can answer the questionnaire in their spare time. The disadvantages associated with mail questionnaires include them being expensive, time consuming and sometimes they end up in the bin put by respondents.

Questionnaires can include the following types of questions:

Open question questionnaires . Open questions differ from other types of questions used in questionnaires in a way that open questions may produce unexpected results, which can make the research more original and valuable. However, it is difficult to analyze the results of the findings when the data is obtained through the questionnaire with open questions.

Multiple choice question s. Respondents are offered a set of answers they have to choose from. The downsize of questionnaire with multiple choice questions is that, if there are too many answers to choose from, it makes the questionnaire, confusing and boring, and discourages the respondent to answer the questionnaire.

Dichotomous Questions .  Thes type of questions gives two options to respondents – yes or no, to choose from. It is the easiest form of questionnaire for the respondent in terms of responding it.

Scaling Questions . Also referred to as ranking questions, they present an option for respondents to rank the available answers to questions on the scale of given range of values (for example from 1 to 10).

For a standard 15,000-20,000 word business dissertation including 25-40 questions in questionnaires will usually suffice. Questions need be formulated in an unambiguous and straightforward manner and they should be presented in a logical order.

Questionnaires as primary data collection method offer the following advantages:

• Uniformity: all respondents are asked exactly the same questions
• Cost-effectiveness
• Possibility to collect the primary data in shorter period of time
• Minimum or no bias from the researcher during the data collection process
• Usually enough time for respondents to think before answering questions, as opposed to interviews
• Possibility to reach respondents in distant areas through online questionnaire

At the same time, the use of questionnaires as primary data collection method is associated with the following shortcomings:

• Random answer choices by respondents without properly reading the question.
• In closed-ended questionnaires no possibility for respondents to express their additional thoughts about the matter due to the absence of a relevant question.
• Collecting incomplete or inaccurate information because respondents may not be able to understand questions correctly.
• High rate of non-response

Survey Monkey represents one of the most popular online platforms for facilitating data collection through questionnaires. Substantial benefits offered by Survey Monkey include its ease to use, presentation of questions in many different formats and advanced data analysis capabilities.

Survey Monkey as a popular platform for primary data collection

There are other alternatives to Survey Monkey you might want to consider to use as a platform for your survey. These include but not limited to Jotform, Google Forms, Lime Survey, Crowd Signal, Survey Gizmo, Zoho Survey and many others.

My  e-book,  The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step approach  contains a detailed, yet simple explanation of quantitative methods. The e-book explains all stages of the research process starting from the selection of the research area to writing personal reflection. Important elements of dissertations such as research philosophy, research approach, research design, methods of data collection and data analysis are explained in simple words.

John Dudovskiy

Questionnaire Method In Research

Saul McLeod, PhD

Editor-in-Chief for Simply Psychology

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

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

Learn about our Editorial Process

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

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

On This Page:

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

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

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

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

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

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

Closed Questions

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

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

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

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

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

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

Limitations

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

Open Questions

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

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

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

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

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

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

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

Questionnaire Design

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

There are several important factors in questionnaire design.

Pilot Study

Question order.

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

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

Question order effects

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

Terminology

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

Presentation

Ethical issues.

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

Problems with Postal Questionnaires

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

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

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

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

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

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

Benefits of a Pilot Study

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

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

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

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

Frequently Asked Questions 

How do psychological researchers analyze the data collected from questionnaires.

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

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

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

Are questionnaires effective in gathering accurate data?

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

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

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

Can questionnaires be used with diverse populations and cultural contexts?

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

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

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

Are questionnaires the only method used in psychological research?

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

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

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

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

What is a semantic differential scale?

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

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

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

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

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

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

Further Information

• Questionnaire design and scale development
• Questionnaire Appraisal Form

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Your ultimate guide to questionnaires and how to design a good one

The written questionnaire is the heart and soul of any survey research project. Whether you conduct your survey using an online questionnaire, in person, by email or over the phone, the way you design your questionnaire plays a critical role in shaping the quality of the data and insights that you’ll get from your target audience. Keep reading to get actionable tips.

What is a questionnaire?

A questionnaire is a research tool consisting of a set of questions or other ‘prompts’ to collect data from a set of respondents.

When used in most research, a questionnaire will consist of a number of types of questions (primarily open-ended and closed) in order to gain both quantitative data that can be analyzed to draw conclusions, and qualitative data to provide longer, more specific explanations.

A research questionnaire is often mistaken for a survey - and many people use the term questionnaire and survey, interchangeably.

But that’s incorrect.

Which is what we talk about next.

Get started with our free survey maker with 50+ templates

Survey vs. questionnaire – what’s the difference?

Before we go too much further, let’s consider the differences between surveys and questionnaires.

These two terms are often used interchangeably, but there is an important difference between them.

Survey definition

A survey is the process of collecting data from a set of respondents and using it to gather insights.

Survey research can be conducted using a questionnaire, but won’t always involve one.

Questionnaire definition

A questionnaire is the list of questions you circulate to your target audience.

In other words, the survey is the task you’re carrying out, and the questionnaire is the instrument you’re using to do it.

By itself, a questionnaire doesn’t achieve much.

It’s when you put it into action as part of a survey that you start to get results.

Advantages vs disadvantages of using a questionnaire

While a questionnaire is a popular method to gather data for market research or other studies, there are a few disadvantages to using this method (although there are plenty of advantages to using a questionnaire too).

Let’s have a look at some of the advantages and disadvantages of using a questionnaire for collecting data.

Advantages of using a questionnaire

1. questionnaires are relatively cheap.

Depending on the complexity of your study, using a questionnaire can be cost effective compared to other methods.

You simply need to write your survey questionnaire, and send it out and then process the responses.

You can set up an online questionnaire relatively easily, or simply carry out market research on the street if that’s the best method.

2. You can get and analyze results quickly

Again depending on the size of your survey you can get results back from a questionnaire quickly, often within 24 hours of putting the questionnaire live.

It also means you can start to analyze responses quickly too.

3. They’re easily scalable

You can easily send an online questionnaire to anyone in the world and with the right software you can quickly identify your target audience and your questionnaire to them.

4. Questionnaires are easy to analyze

If your questionnaire design has been done properly, it’s quick and easy to analyze results from questionnaires once responses start to come back.

This is particularly useful with large scale market research projects.

Because all respondents are answering the same questions, it’s simple to identify trends.

5. You can use the results to make accurate decisions

As a research instrument, a questionnaire is ideal for commercial research because the data you get back is from your target audience (or ideal customers) and the information you get back on their thoughts, preferences or behaviors allows you to make business decisions.

6. A questionnaire can cover any topic

One of the biggest advantages of using questionnaires when conducting research is (because you can adapt them using different types and styles of open ended questions and closed ended questions) they can be used to gather data on almost any topic.

There are many types of questionnaires you can design to gather both quantitative data and qualitative data - so they’re a useful tool for all kinds of data analysis.

Disadvantages of using a questionnaire

1. respondents could lie.

This is by far the biggest risk with a questionnaire, especially when dealing with sensitive topics.

Rather than give their actual opinion, a respondent might feel pressured to give the answer they deem more socially acceptable, which doesn’t give you accurate results.

2. Respondents might not answer every question

There are all kinds of reasons respondents might not answer every question, from questionnaire length, they might not understand what’s being asked, or they simply might not want to answer it.

If you get questionnaires back without complete responses it could negatively affect your research data and provide an inaccurate picture.

3. They might interpret what’s being asked incorrectly

This is a particular problem when running a survey across geographical boundaries and often comes down to the design of the survey questionnaire.

If your questions aren’t written in a very clear way, the respondent might misunderstand what’s being asked and provide an answer that doesn’t reflect what they actually think.

Again this can negatively affect your research data.

4. You could introduce bias

The whole point of producing a questionnaire is to gather accurate data from which decisions can be made or conclusions drawn.

But the data collected can be heavily impacted if the researchers accidentally introduce bias into the questions.

This can be easily done if the researcher is trying to prove a certain hypothesis with their questionnaire, and unwittingly write questions that push people towards giving a certain answer.

In these cases respondents’ answers won’t accurately reflect what is really happening and stop you gathering more accurate data.

5. Respondents could get survey fatigue

One issue you can run into when sending out a questionnaire, particularly if you send them out regularly to the same survey sample, is that your respondents could start to suffer from survey fatigue.

In these circumstances, rather than thinking about the response options in the questionnaire and providing accurate answers, respondents could start to just tick boxes to get through the questionnaire quickly.

Again, this won’t give you an accurate data set.

Questionnaire design: How to do it

It’s essential to carefully craft a questionnaire to reduce survey error and optimize your data . The best way to think about the questionnaire is with the end result in mind.

How do you do that?

Start with questions, like:

• What is my research purpose ?
• What data do I need?
• How am I going to analyze that data?
• What questions are needed to best suit these variables?

Once you have a clear idea of the purpose of your survey, you’ll be in a better position to create an effective questionnaire.

Here are a few steps to help you get into the right mindset.

1. Keep the respondent front and center

A survey is the process of collecting information from people, so it needs to be designed around human beings first and foremost.

In his post about survey design theory, David Vannette, PhD, from the Qualtrics Methodology Lab explains the correlation between the way a survey is designed and the quality of data that is extracted.

“To begin designing an effective survey, take a step back and try to understand what goes on in your respondents’ heads when they are taking your survey.

This step is critical to making sure that your questionnaire makes it as likely as possible that the response process follows that expected path.”

From writing the questions to designing the survey flow, the respondent’s point of view should always be front and center in your mind during a questionnaire design.

2. How to write survey questions

Your questionnaire should only be as long as it needs to be, and every question needs to deliver value.

That means your questions must each have an individual purpose and produce the best possible data for that purpose, all while supporting the overall goal of the survey.

A question must also must be phrased in a way that is easy for all your respondents to understand, and does not produce false results.

To do this, remember the following principles:

Get into the respondent's head

The process for a respondent answering a survey question looks like this:

• The respondent reads the question and determines what information they need to answer it.
• They search their memory for that information.
• They make judgments about that information.
• They translate that judgment into one of the answer options you’ve provided. This is the process of taking the data they have and matching that information with the question that’s asked.

When wording questions, make sure the question means the same thing to all respondents. Words should have one meaning, few syllables, and the sentences should have few words.

Only use the words needed to ask your question and not a word more .

Note that it’s important that the respondent understands the intent behind your question.

If they don’t, they may answer a different question and the data can be skewed.

Some contextual help text, either in the introduction to the questionnaire or before the question itself, can help make sure the respondent understands your goals and the scope of your research.

Use mutually exclusive responses

Be sure to make your response categories mutually exclusive.

Consider the question:

What is your age?

Respondents that are 31 years old have two options, as do respondents that are 40 and 55. As a result, it is impossible to predict which category they will choose.

This can distort results and frustrate respondents. It can be easily avoided by making responses mutually exclusive.

The following question is much better:

This question is clear and will give us better results.

Ask specific questions

Nonspecific questions can confuse respondents and influence results.

Do you like orange juice?

• Like very much
• Neither like nor dislike
• Dislike very much

This question is very unclear. Is it asking about taste, texture, price, or the nutritional content? Different respondents will read this question differently.

A specific question will get more specific answers that are actionable.

How much do you like the current price of orange juice?

This question is more specific and will get better results.

If you need to collect responses about more than one aspect of a subject, you can include multiple questions on it. (Do you like the taste of orange juice? Do you like the nutritional content of orange juice? etc.)

Use a variety of question types

If all of your questionnaire, survey or poll questions are structured the same way (e.g. yes/no or multiple choice) the respondents are likely to become bored and tune out. That could mean they pay less attention to how they’re answering or even give up altogether.

Instead, mix up the question types to keep the experience interesting and varied. It’s a good idea to include questions that yield both qualitative and quantitative data.

For example, an open-ended questionnaire item such as “describe your attitude to life” will provide qualitative data – a form of information that’s rich, unstructured and unpredictable. The respondent will tell you in their own words what they think and feel.

A quantitative / close-ended questionnaire item, such as “Which word describes your attitude to life? a) practical b) philosophical” gives you a much more structured answer, but the answers will be less rich and detailed.

Open-ended questions take more thought and effort to answer, so use them sparingly. They also require a different kind of treatment once your survey is in the analysis stage.

3. Pre-test your questionnaire

Always pre-test a questionnaire before sending it out to respondents. This will help catch any errors you might have missed. You could ask a colleague, friend, or an expert to take the survey and give feedback. If possible, ask a few cognitive questions like, “how did you get to that response?” and “what were you thinking about when you answered that question?” Figure out what was easy for the responder and where there is potential for confusion. You can then re-word where necessary to make the experience as frictionless as possible.

If your resources allow, you could also consider using a focus group to test out your survey. Having multiple respondents road-test the questionnaire will give you a better understanding of its strengths and weaknesses. Match the focus group to your target respondents as closely as possible, for example in terms of age, background, gender, and level of education.

Note: Don't forget to make your survey as accessible as possible for increased response rates.

Questionnaire examples and templates

There are free questionnaire templates and example questions available for all kinds of surveys and market research, many of them online. But they’re not all created equal and you should use critical judgement when selecting one. After all, the questionnaire examples may be free but the time and energy you’ll spend carrying out a survey are not.

If you’re using online questionnaire templates as the basis for your own, make sure it has been developed by professionals and is specific to the type of research you’re doing to ensure higher completion rates. As we’ve explored here, using the wrong kinds of questions can result in skewed or messy data, and could even prompt respondents to abandon the questionnaire without finishing or give thoughtless answers.

You’ll find a full library of downloadable survey templates in the Qualtrics Marketplace , covering many different types of research from employee engagement to post-event feedback . All are fully customizable and have been developed by Qualtrics experts.

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How to Design Effective Research Questionnaires for Robust Findings

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

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

Table of Contents

The Role of Questionnaires in Research

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

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

Pros and Cons of Using Questionnaires in Research:

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

Structured vs Unstructured Questionnaires

Structured questionnaire:.

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

Advantages of Structured Questionnaires:

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

Limitations of Structured Questionnaires:

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

Unstructured Questionnaire:

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

Advantages of Unstructured Questionnaires:

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

Limitations of Unstructured Questionnaires:

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

Types of Questions in a Questionnaire

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

1. Open-Ended Questions:

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

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

2. Multiple-Choice Questions

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

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

• ResearchGate
• Academia.edu

3. Dichotomous Questions

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

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

4. Scaling Questions

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

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

i. Likert Scale:

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

• Strongly Agree
• Strongly Disagree

ii. Semantic Differential Scale:

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

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

iii. Numerical Rating Scale:

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

iv. Ranking Questions:

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

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

• User Interface
• Functionality
• Customer Support

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

Methods of Administering Questionnaires

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

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

How to Design a Questionnaire

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

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

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

3. Develop the Questions :

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

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

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

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

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

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

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

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

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

Characteristics of a Good Questionnaire

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

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

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

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

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

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

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

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

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

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

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

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

Frequently Asked Questions

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

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

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

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

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

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

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

Thank you, Dear Riya. This is quite helpful.

Great insights there Doc

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Qualitative study design: Surveys & questionnaires

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Surveys & questionnaires

Qualitative surveys use open-ended questions to produce long-form written/typed answers. Questions will aim to reveal opinions, experiences, narratives or accounts. Often a useful precursor to interviews or focus groups as they help identify initial themes or issues to then explore further in the research. Surveys can be used iteratively, being changed and modified over the course of the research to elicit new information. 

Structured Interviews may follow a similar form of open questioning.  

Qualitative surveys frequently include quantitative questions to establish elements such as age, nationality etc. 

Qualitative surveys aim to elicit a detailed response to an open-ended topic question in the participant’s own words.  Like quantitative surveys, there are three main methods for using qualitative surveys including face to face surveys, phone surveys, and online surveys. Each method of surveying has strengths and limitations.

Face to face surveys  

• Researcher asks participants one or more open-ended questions about a topic, typically while in view of the participant’s facial expressions and other behaviours while answering. Being able to view the respondent’s reactions enables the researcher to ask follow-up questions to elicit a more detailed response, and to follow up on any facial or behavioural cues that seem at odds with what the participants is explicitly saying.
• Face to face qualitative survey responses are likely to be audio recorded and transcribed into text to ensure all detail is captured; however, some surveys may include both quantitative and qualitative questions using a structured or semi-structured format of questioning, and in this case the researcher may simply write down key points from the participant’s response.

Telephone surveys

• Similar to the face to face method, but without researcher being able to see participant’s facial or behavioural responses to questions asked. This means the researcher may miss key cues that would help them ask further questions to clarify or extend participant responses to their questions, and instead relies on vocal cues.

Online surveys

• Open-ended questions are presented to participants in written format via email or within an online survey tool, often alongside quantitative survey questions on the same topic.
• Researchers may provide some contextualising information or key definitions to help ‘frame’ how participants view the qualitative survey questions, since they can’t directly ask the researcher about it in real time. 
• Participants are requested to responses to questions in text ‘in some detail’ to explain their perspective or experience to researchers; this can result in diversity of responses (brief to detailed).
• Researchers can not always probe or clarify participant responses to online qualitative survey questions which can result in data from these responses being cryptic or vague to the researcher.
• Online surveys can collect a greater number of responses in a set period of time compared to face to face and phone survey approaches, so while data may be less detailed, there is more of it overall to compensate.

Qualitative surveys can help a study early on, in finding out the issues/needs/experiences to be explored further in an interview or focus group. 

Surveys can be amended and re-run based on responses providing an evolving and responsive method of research. 

Online surveys will receive typed responses reducing translation by the researcher 

Online surveys can be delivered broadly across a wide population with asynchronous delivery/response. 

Limitations

Hand-written notes will need to be transcribed (time-consuming) for digital study and kept physically for reference. 

Distance (or online) communication can be open to misinterpretations that cannot be corrected at the time. 

Questions can be leading/misleading, eliciting answers that are not core to the research subject. Researchers must aim to write a neutral question which does not give away the researchers expectations. 

Even with transcribed/digital responses analysis can be long and detailed, though not as much as in an interview. 

Surveys may be left incomplete if performed online or taken by research assistants not well trained in giving the survey/structured interview. 

Narrow sampling may skew the results of the survey. 

Example questions

Here are some example survey questions which are open ended and require a long form written response:

• Tell us why you became a doctor? 
• What do you expect from this health service? 
• How do you explain the low levels of financial investment in mental health services? (WHO, 2007) 

Example studies

• Davey, L. , Clarke, V. and Jenkinson, E. (2019), Living with alopecia areata: an online qualitative survey study. British Journal of Dermatology, 180 1377-1389. Retrieved from https://onlinelibrary-wiley-com.ezproxy-f.deakin.edu.au/doi/10.1111%2Fbjd.17463    
• Richardson, J. (2004). What Patients Expect From Complementary Therapy: A Qualitative Study. American Journal of Public Health, 94(6), 1049–1053. Retrieved from http://ezproxy.deakin.edu.au/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=s3h&AN=13270563&site=eds-live&scope=site  
• Saraceno, B., van Ommeren, M., Batniji, R., Cohen, A., Gureje, O., Mahoney, J., ... & Underhill, C. (2007). Barriers to improvement of mental health services in low-income and middle-income countries. The Lancet, 370(9593), 1164-1174. Retrieved from https://www-sciencedirect-com.ezproxy-f.deakin.edu.au/science/article/pii/S014067360761263X?via%3Dihub  

Below has more detail of the Lancet article including actual survey questions at: 

• World Health Organization. (2007.) Expert opinion on barriers and facilitating factors for the implementation of existing mental health knowledge in mental health services. Geneva: World Health Organization. https://apps.who.int/iris/handle/10665/44808
• Green, J. 1961-author., & Thorogood, N. (2018). Qualitative methods for health research. SAGE. Retrieved from http://ezproxy.deakin.edu.au/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=cat00097a&AN=deakin.b4151167&authtype=sso&custid=deakin&site=eds-live&scope=site   
• JANSEN, H. The Logic of Qualitative Survey Research and its Position in the Field of Social Research Methods. Forum Qualitative Sozialforschung, 11(2), Retrieved from http://www.qualitative-research.net/index.php/fqs/article/view/1450/2946  
• Neilsen Norman Group, (2019). 28 Tips for Creating Great Qualitative Surveys. Retrieved from https://www.nngroup.com/articles/qualitative-surveys/     
• << Previous: Documents
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• Last Updated: Jul 3, 2024 11:46 AM
• URL: https://deakin.libguides.com/qualitative-study-designs

Surveys & Questionnaires

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

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

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

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

Surveys & Questionnaires: GO-GN Insights

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

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

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

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

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

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

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

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

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

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

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What Is a Questionnaire and How Is It Used in Research?

2022-06-29 Market Research

The importance of questionnaires in research is immense, helping researchers gain relevant information quickly and effectively. Before creating a questionnaire for your study, you should first understand the meaning of questionnaires and the advantages and disadvantages of using them.

What Is a Questionnaire?

A questionnaire is a research tool featuring a series of questions used to collect useful information from respondents. These instruments include either written or oral questions and comprise an interview-style format. Questionnaires may be qualitative or quantitative and can be conducted online, by phone, on paper or face-to-face, and questions don’t necessarily have to be administered with a researcher present.

Questionnaires feature either open or closed questions and sometimes employ a mixture of both. Open-ended questions enable respondents to answer in their own words in as much or as little detail as they desire. Closed questions provide respondents with a series of predetermined responses they can choose from.

Is “Questionnaire” Just Another Word for “Survey”?

While the two terms seem synonymous, there are not quite the same. A questionnaire is a set of questions created for the purpose of gathering information; that information may not be used for a survey. However, all surveys  do  require questionnaires. If you are using a questionnaire for survey sampling, it’s important to ensure that it is designed to gather the most accurate answers from respondents.

Why Are Questionnaires Effective in Research?

Questionnaires are popular  research methods  because they offer a fast, efficient and inexpensive means of gathering large amounts of information from sizeable sample volumes. These tools are particularly effective for measuring subject behavior, preferences, intentions, attitudes and opinions. Their use of open and closed research questions enables researchers to obtain both qualitative and quantitative data, resulting in more comprehensive results.

Pros and Cons of Using Questionnaires in Research

Though the importance of questionnaires in research is clear, there are both pros and cons to using these instruments to gather information. Learn more about questionnaire advantages and disadvantages to determine if they’re suitable for your study.

Advantages of Questionnaires

Some of the many benefits of using questionnaires as a research tool include:

• Practicality:  Questionnaires enable researchers to strategically manage their target audience, questions and format while gathering large data quantities on any subject.
• Cost-efficiency: You don’t need to hire surveyors to deliver your survey questions — instead, you can place them on your website or email them to respondents at little to no cost.
• Speed:  You can gather survey results quickly and effortlessly using mobile tools, obtaining responses and insights in 24 hours or less.
• Comparability:  Researchers can use the same questionnaire yearly and compare and contrast research results to gain valuable insights and minimize translation errors.
• Scalability:  Questionnaires are highly scalable, allowing researchers to distribute them to demographics anywhere across the globe.
• Standardization:  You can standardize your questionnaire with as many questions as you want about any topic.
• Respondent comfort: When taking a questionnaire, respondents are completely anonymous and not subject to stressful time constraints, helping them feel relaxed and encouraging them to provide truthful responses.
• Easy analysis:  Questionnaires often have built-in tools that automate analyses, making it fast and easy to interpret your results.

Disadvantages of Questionnaires

Questionnaires also have their disadvantages, such as:

• Answer dishonesty: Respondents may not always be completely truthful with their answers — some may have hidden agendas, while others may answer how they think society would deem most acceptable.
• Question skipping:  Make sure to require answers for all your survey questions. Otherwise, you may run the risk of respondents leaving questions unanswered.
• Interpretation difficulties:  If a question isn’t straightforward enough, respondents may struggle to interpret it accurately. That’s why it’s important to state questions clearly and concisely, with explanations when necessary.
• Survey fatigue:  Respondents may experience survey fatigue if they receive too many surveys or a questionnaire is too long.
• Analysis challenges:  Though closed questions are easy to analyze, open questions require a human to review and interpret them. Try limiting open-ended questions in your survey to gain more quantifiable data you can evaluate and utilize more quickly.
• Unconscientious responses:  If respondents don’t read your questions thoroughly or completely, they may offer inaccurate answers that can impact data validity. You can minimize this risk by making questions as short and simple as possible.

Types of Questionnaires in Research

There are various types of questionnaires in survey research, including:

• Postal:  Postal questionnaires are paper surveys that participants receive through the mail. Once respondents complete the survey, they mail them back to the organization that sent them.
• In-house:  In this type of questionnaire, researchers visit respondents in their homes or workplaces and administer the survey in person.
• Telephone:  With telephone surveys, researchers call respondents and conduct the questionnaire over the phone.
• Electronic:  Perhaps the most common type of questionnaire, electronic surveys are presented via email or through a different online medium.

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• Questionnaire Design | Methods, Question Types & Examples

Questionnaire Design | Methods, Question Types & Examples

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

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

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

Table of contents

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

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

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

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

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

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

Self-administered questionnaires

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

Self-administered questionnaires can be:

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

But they may also be:

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

Researcher-administered questionnaires

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

Researcher-administered questionnaires can:

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

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

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

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

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

Closed-ended questions

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

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

Examples of closed-ended questions for different variables

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

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

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

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

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

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

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

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

Pros and cons of closed-ended questions

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

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

Open-ended questions

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

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

Open-ended questions have a few downsides.

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

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

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

Use clear language

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

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

Use balanced framing

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

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

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

Avoid leading questions

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

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

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

Keep your questions focused

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

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

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

Strongly Agree Agree Undecided Disagree Strongly Disagree

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

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

Logical flow

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

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

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

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

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

Randomisation

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

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

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

Step 1: Define your goals and objectives

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

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

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

Step 2: Use questions that are suitable for your sample

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

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

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

Step 3: Decide on your questionnaire length and question order

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

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

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

Step 4: Pretest your questionnaire

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

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

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

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

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

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

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

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

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

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

Questionnaires can be self-administered or researcher-administered.

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

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Methodology

• What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

Published on June 19, 2020 by Pritha Bhandari . Revised on June 22, 2023.

Qualitative research involves collecting and analyzing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research.

Qualitative research is the opposite of quantitative research , which involves collecting and analyzing numerical data for statistical analysis.

Qualitative research is commonly used in the humanities and social sciences, in subjects such as anthropology, sociology, education, health sciences, history, etc.

• How does social media shape body image in teenagers?
• How do children and adults interpret healthy eating in the UK?
• What factors influence employee retention in a large organization?
• How is anxiety experienced around the world?
• How can teachers integrate social issues into science curriculums?

Table of contents

Approaches to qualitative research, qualitative research methods, qualitative data analysis, advantages of qualitative research, disadvantages of qualitative research, other interesting articles, frequently asked questions about qualitative research.

Qualitative research is used to understand how people experience the world. While there are many approaches to qualitative research, they tend to be flexible and focus on retaining rich meaning when interpreting data.

Common approaches include grounded theory, ethnography , action research , phenomenological research, and narrative research. They share some similarities, but emphasize different aims and perspectives.

Note that qualitative research is at risk for certain research biases including the Hawthorne effect , observer bias , recall bias , and social desirability bias . While not always totally avoidable, awareness of potential biases as you collect and analyze your data can prevent them from impacting your work too much.

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Each of the research approaches involve using one or more data collection methods . These are some of the most common qualitative methods:

• Observations: recording what you have seen, heard, or encountered in detailed field notes.
• Interviews:  personally asking people questions in one-on-one conversations.
• Focus groups: asking questions and generating discussion among a group of people.
• Surveys : distributing questionnaires with open-ended questions.
• Secondary research: collecting existing data in the form of texts, images, audio or video recordings, etc.
• You take field notes with observations and reflect on your own experiences of the company culture.
• You distribute open-ended surveys to employees across all the company’s offices by email to find out if the culture varies across locations.
• You conduct in-depth interviews with employees in your office to learn about their experiences and perspectives in greater detail.

Qualitative researchers often consider themselves “instruments” in research because all observations, interpretations and analyses are filtered through their own personal lens.

For this reason, when writing up your methodology for qualitative research, it’s important to reflect on your approach and to thoroughly explain the choices you made in collecting and analyzing the data.

Qualitative data can take the form of texts, photos, videos and audio. For example, you might be working with interview transcripts, survey responses, fieldnotes, or recordings from natural settings.

Most types of qualitative data analysis share the same five steps:

• Prepare and organize your data. This may mean transcribing interviews or typing up fieldnotes.
• Review and explore your data. Examine the data for patterns or repeated ideas that emerge.
• Develop a data coding system. Based on your initial ideas, establish a set of codes that you can apply to categorize your data.
• Assign codes to the data. For example, in qualitative survey analysis, this may mean going through each participant’s responses and tagging them with codes in a spreadsheet. As you go through your data, you can create new codes to add to your system if necessary.
• Identify recurring themes. Link codes together into cohesive, overarching themes.

There are several specific approaches to analyzing qualitative data. Although these methods share similar processes, they emphasize different concepts.

Qualitative research often tries to preserve the voice and perspective of participants and can be adjusted as new research questions arise. Qualitative research is good for:

• Flexibility

The data collection and analysis process can be adapted as new ideas or patterns emerge. They are not rigidly decided beforehand.

• Natural settings

Data collection occurs in real-world contexts or in naturalistic ways.

• Meaningful insights

Detailed descriptions of people’s experiences, feelings and perceptions can be used in designing, testing or improving systems or products.

• Generation of new ideas

Open-ended responses mean that researchers can uncover novel problems or opportunities that they wouldn’t have thought of otherwise.

Prevent plagiarism. Run a free check.

Researchers must consider practical and theoretical limitations in analyzing and interpreting their data. Qualitative research suffers from:

• Unreliability

The real-world setting often makes qualitative research unreliable because of uncontrolled factors that affect the data.

• Subjectivity

Due to the researcher’s primary role in analyzing and interpreting data, qualitative research cannot be replicated . The researcher decides what is important and what is irrelevant in data analysis, so interpretations of the same data can vary greatly.

• Limited generalizability

Small samples are often used to gather detailed data about specific contexts. Despite rigorous analysis procedures, it is difficult to draw generalizable conclusions because the data may be biased and unrepresentative of the wider population .

• Labor-intensive

Although software can be used to manage and record large amounts of text, data analysis often has to be checked or performed manually.

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.

• Chi square goodness of fit test
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Inclusion and exclusion criteria

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

There are five common approaches to qualitative research :

• Grounded theory involves collecting data in order to develop new theories.
• Ethnography involves immersing yourself in a group or organization to understand its culture.
• Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
• Phenomenological research involves investigating phenomena through people’s lived experiences.
• Action research links theory and practice in several cycles to drive innovative changes.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

There are various approaches to qualitative data analysis , but they all share five steps in common:

• Prepare and organize your data.
• Review and explore your data.
• Develop a data coding system.
• Assign codes to the data.
• Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

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• Published: 25 August 2024

Comparison of the SBAR method and modified handover model on handover quality and nurse perception in the emergency department: a quasi-experimental study

• Atefeh Alizadeh-risani 1 ,
• Fatemeh Mohammadkhah 2 ,
• Ali Pourhabib 2 ,
• Zahra Fotokian 2 , 4 &
• Marziyeh Khatooni 3  

BMC Nursing volume  23 , Article number:  585 ( 2024 ) Cite this article

Metrics details

Effective information transfer during nursing shift handover is a crucial component of safe care in the emergency department (ED). Examining nursing handover models shows that they are frequently associated with errors. Disadvantages of the SBAR handover model include uncertainty of nursing staff regarding transfer of responsibility and non-confidentiality of patient information. To increase reliability of handover, written forms and templates can be used in addition to oral handover by the bedside.

The purpose of this study is to compare the ‘Situation, Background, Assessment, Recommendation (SBAR) method and modified handover model on the handover quality and nurse perception of shift handover in the ED.

This research was designed as a semi-experimental study, with census survey method used for sampling. In order to collect data, Nurse Perception of Hanover Questionnaire (NPHQ) and Handover Quality Rating Tool (HQRT) were used after translating and confirming validity and reliability used to direct/collect data. A total of 31 nurses working in the ED received training on the modified shift handover model in a one-hour theory session and three hands-on bedside training sessions. This model was implemented by the nurses for one month. Data was analyzed with SPSS (version 26) using paired t-tests and analysis of covariance.

Results indicated significant difference between the modified handover model and SBAR in components of information transfer ( P  < 0.001), shared understanding ( P  < 0.001), working atmosphere ( P  = 0.004), handover quality ( P  < 0.001), and nurse perception of handover ( P  < 0.001). The univariate covariance test did not show demographic variables to be significantly correlated with handover perception or handover quality in SBAR and modified methods ( P  > 0.05).

Conclusions

The results of this study can be presented to nursing managers as a guide in improving the quality of nursing care via implementing and applying the modified handover model in the nursing handover. The resistance of nurses against executing a new handover method was one of the limitations of the research, which was resolved by explanation of the plan and goals, as well as the cooperation of the hospital matron, and the ward supervisor. It is suggested to carry out a similar investigation in other hospital departments and contrast the outcomes with those obtained in the current study.

Peer Review reports

Introduction

One of the professional responsibilities of nurses in delivering high-quality and safe nursing care is the handover process [ 1 ]. This concept refers to the process of transferring the responsibility of care and patient information from one caregiver to another, in order to continue the care of the patient [ 2 ]. Effective information transfer during nursing shift handover is considered a vital component of safe care in the Emergency Department (ED). Some challenges in providing accurate information during handover include providing excessive or insufficient information, lack of a checklist, and delays in handover [ 3 ]. Incomplete transmission of information increases the occurrence of errors, leads to inappropriate treatment, delays diagnosis and treatment, and increases physician and nursing errors and treatment costs [ 4 ]. A study by Spooner showed that 80% of serious medical care errors are related to nursing handovers, and one fifth of patients suffer from complications due to handover errors [ 5 ]. A review of 3000 sentinel events demonstrated that a communication breakdown occurred 65–70% of the time. It has been demonstrated that poor communication handovers result in adverse events, delays in treatment, redundancies that impact efficiencies and effectiveness, low patient and healthcare provider satisfaction, and more admissions [ 3 ].

There are various nursing handover methods, including oral handover, and the use of special forms [ 6 ]. The oral handover method at the bedside can lead to better communication, improved patient care, and increased patient satisfaction [ 7 ]. So far, several shift handover tools have been developed in hospital departments, including: ISOBAR [ 8 ], ISBAR [ 9 ], SBAR [ 3 ], REED [ 10 ], ICCCO [ 11 ], VITAL and PVITAL [ 12 ] and the modified nursing handover model [ 13 ]. Examining nursing handover models shows that they are frequently associated with errors [ 14 ]. While a format to use for a handover was the topic of study in several of the nursing studies [ 15 , 16 , 17 , 18 ], accuracy of content and outcomes were not included. Barriers and facilitators to nursing handovers were identified, but evidence for best practice was not evident. Various strategies have been developed to enhance the effectiveness and efficiency of nursing handover, including standardized approaches, bedside handover and technology. The majority of these models have been evaluated in inpatient settings; few have been conducted in the ED. Among these shift handover models, the PVITAL model was specifically designed for the ED and includes components of Present patient, Intake and output, Treatment and diagnosis, Admission and discharge, and Legal and documentation. Despite the positive aspects, this model has inconsistencies that question its effectiveness in nursing shift handovers [ 13 ]. Also, one of the most widely used shift handover is the SBAR model [ 19 ]. The SBAR model includes Situation, Background, Assessment, and Recommendation components. SBAR is an information tool that transmits standardized information and makes reports concise, targeted and relevant, and facilitates information exchanges, and can be improved by involving the patient in delivery and transformation [ 20 ]. The SBAR handover model was proposed by the joint commission with the aim of reducing errors and increasing the quality of care. This model was initially designed by Leonard and Graham for use in health care systems [ 3 ]. In 2013, adoption of this model for nursing handovers was announced mandatory by the Deputy Minister of Nursing of Iran Ministry of Health [ 21 ]. Currently, this model is only implemented orally at the patient bedside [ 22 ]. Disadvantages of this model include uncertainty of nursing staff regarding transfer of responsibility and non-confidentiality of patient information. To increase reliability of handover, written forms and templates can be used in addition to oral and face-to-face handover by the bedside [ 23 ]. In this regard, the modified nursing handover model was first designed by Klim et al. (2013) for shift handover in the ED. This method has a written form and template and includes components of identification and alert, assessment and progress, nursing care need, plan, and alerting the nurse in charge/medical officer based on vital sign parameters or clinical deterioration [ 24 ]. Findings of a study by Kerr (2016) showed that implementation of this model improves transmission of important information to nurses in subsequent shifts, leading to an increase in participation of patients and their companions in the handover process [ 13 ].

The use of a simple, structured, and standard model with a written template in nursing handovers is one of the elements influencing provision of appropriate services. According to research, implementation of the modified handover model in Iran has not been investigated to date. Despite the widespread use of SBAR, there is limited comparative research on its effectiveness relative to modified handover models in emergency settings. We hypothesize that the modified model will result in fewer handover errors compared to the SBAR method. This study aims to compare the effectiveness of the SBAR method and modified handover model on handover quality and nurse perception in the ED.

Materials and methods

This research was designed as a pre-post intervention, semi-experimental study, with census survey method used for sampling.

Participants

The study location was the ED of Zakaria Razi Social Security Hospital in Qazvin, Iran. The sample size was selected through a census of nurses working in the ED of Zakariya Razi Hospital in Qazvin. There were 45 nurses working in the emergency department, including 38 nurses, one head nurse, one assistant head nurse (staff), three triage nurses and two outpatient operating room nurses. Six nurses had less than six months of work experience in the ED and were not included in the study according to the inclusion criteria. Considering a Cohen’s effect size of 0.52 (based on a pilot sample of the dependent variable, quality of shift handover), with a Type I error rate of 5% and a statistical power of test 80%, the sample size was estimated to be 32 individuals using GPOWER software. A total of 32 nurses were included in the study, but one nurse withdrew from participation, resulting in a final sample size of 31 nurses. The inclusion criteria comprised willingness to participate in the study, and at least 6 months of working experience in the ED. Unwillingness to continue cooperation was set as one of the exclusion criteria.

Data collection (procedures)

Initially, the researcher made a list of the nurses employed in the ED. The nurses were then introduced to the study and its objectives, and participants were selected based on inclusion criteria and obtaining informed consent to participate in the study. The SBAR model was routinely implemented orally in the ED. At the beginning of the research, Nurse Perception of Hanover Questionnaire (NPHQ) and Handover Quality Rating Tool (HQRT) were completed by all participants. Owing to lack of familiarity with the modified handover model, nurses were educated via a one-hour theory session in the hospital conference hall, where the items of the modified nursing handover checklist and how to complete it were taught using PowerPoint and a whiteboard. Three hands-on training sessions was individually held for all nurses explaining the handover model, how to fill out the checklist and use the checklist during shift handover at the patient’s bedside. In order to resolve ambiguities and questions, we communicated with the participants through cyberspace. Brainstorming, clear explanations, effective communication, and receiving feedback were used for more productive training sessions. Moreover, the modified handover checklist was designed by the researcher and provided to the nurses for better understanding of the contents. Subsequently, the modified handover model was implemented by the participants for one month [ 13 ]. During this month, about 350 shift handovers were made with the modified handover method. In order to ensure proper implementation, the researcher attended and directly supervised all handover situations involving the target group. After implementation of the modified handover model, NPHQ and HQRT were completed once more by the participants (Fig.  1 ).

The process of implementing the modified nursing handover model

Data collection

Instruments

Demographic information : included variables of age, gender, marital status, level of education, employment type, years of work experience, years of work experience in the ED, working conditions in terms of shifts.

Nurse handover perception questionnaire (NHPQ) : This 22-item questionnaire reveals perception and performance of nurses regarding shift handover. The first half of the NHPQ examines perceptions regarding current practices and essential components of handover [ 15 ]. The second half of the NHPQ, reviews nurse views regarding bedside handover [ 23 ]. The items in the NHPQ questionnaire include a series of statements about nurses’ general understanding of shift handover and their experiences of clinical shift handover at the bedside. This tool is scored on a 4-point Likert scale, with scores ranging from 22 to 88. A higher score indicates a higher perception of handover. Eight items of this questionnaire [ 3 , 4 , 8 , 10 , 17 , 20 , 21 ] are scored negatively. Content validity was reported using a content validity index (CVI) of 0.92, which indicated satisfactory content validity. The internal reliability of the questionnaire items was determined using Cronbach’s alpha of 0.99. The one-dimensional Intraclass Correlation Coefficient (ICC) for the internal homogeneity test of the items was 0.92 [ 23 ].

Handover quality rating tool (HQRT) : The handover quality rating tool has been developed to evaluate the shift handover quality. This 16-item questionnaire includes five components of information transfer (items 1 to 7), shared understanding (items 8 to 10), working atmosphere (items 11 to 13), handover quality (item 14), and circumstances of the handover (items 15 and 16). This questionnaire is scored on a 4-point Likert scale, with the scores ranging from 16 to 64. A higher score indicates better handover quality [ 24 ]. A study reported the validity of this tool with a reliability coefficient of 0.67 [ 25 ].

The above questionnaires have not been used in Iran to date. Therefore, they were translated and validated in the present study, as part of a master’s thesis in internal-surgical nursing [ 26 ]. The results related to the process of translating the questionnaires are summarized as follows:

Getting permission from the tool designer;

Translation from the reference language (English) to the target language (Persian): In this study, two translators familiar with English performed the translation from the original language to Persian. The translation process was carried out independently by the two translators.

Consolidation and comparison of translations: At this stage, the researchers held a meeting to review the translated questionnaires in order to identify and eliminate inappropriate phrases or concepts in the translation. The original version and the translated versions were checked for any discrepancies. The translated versions were combined and a single version was developed.

Translation of the final translated version from the target language (Persian) to the original language (English): This translation was performed by two experts fluent in English. The translated versions were reviewed by the research team and discussed until a consensus was reached. Subsequently, the Persian questionnaires were distributed to ten faculty members to assess content validity, and to twenty nurses working in the ED to evaluate reliability. This process was conducted twice, with a gap of 10 days between each administration. After making necessary corrections, the final version of the questionnaire was prepared. In the present study, all items of the NHPQ and HQRT had a CVI above 0.88, which is acceptable. SCVI/UA was 0.86 and 0.87 for NHPQ and HQRT respectively. SCVI/AVE of both questionnaires was 0.98, which is in the acceptable range. CVR of all items of both questionnaires was above 0.62. Cronbach’s alpha coefficient was 0.93 for NHPQ and 0.96 for HQRT. Hence, the reliability of the tools was confirm [ 26 ].

Data analysis

Descriptive and inferential statistics were used for data analysis using SPSS software (version 24). Paired t-tests, chi-square and analysis of variance were used to compare the effect of SBAR and the modified handover models. P  Value of < 0.05 was considered significant.

Nurse characteristics

The average age of the participants was 33 ± 4 years. Seventeen (54.8%) were women, and 22 (71%) were married. Thirty (96.8%) had a bachelor’s degree, and 23 (74.2%) were officially employed. Fourteen (45.2%) had a work experience of 6–10 years, while 16 (51.6%) had less than 5 years of work experience (Table  1 ).

According to paired t-test results, significant difference existed between the average handover quality of the SBAR model and the modified handover model ( P  < 0.001). Accordingly, the average quality of handover in the modified handover model (57.64) was 8.09 units higher than the SBAR model (49.54). Also, based on paired t-test results, there was significant difference between the two models in components of information transfer ( P  < 0.001), shared understanding ( P  < 0.001), working atmosphere ( P  = 0.004), and handover quality ( P  < 0.001). Meanwhile, the component of circumstances of the handover, was not significantly different between the two models ( P  = 0.227). Therefore, our findings indicated that handover quality and its components (except circumstances of the handover) were higher in the modified handover model compared with the SBAR model. Findings from the analysis of Cohen’s d effect size indicated that the modified handover model has a significantly greater influence on the quality of handover, being 1.29 times higher than the SBAR model. According to results, the modified handover model had the largest effect on the information transfer component with an effect size of 1.56 units, and the smallest effect on the circumstances of the handover with an effect size of 0.23 units (Table  2 ).

Results of the paired t-test revealed significant difference between the average nurse perception of handover in two models of SBAR and modified handover ( P  < 0.001). The average nurse perception of handover was 9.64 units higher in the modified handover model (80.45) compared with the SBAR model (70.80). The results of Cohen’s d effect size showed that the modified handover model is 1.51 times more effective than the SBAR model on nurses’ perception of handover (Table  2 ).

The results of the paired t-test demonstrated that all items except “not enough time allowed”, “there was a tension between the team”, “the person handing over under pressure”, and “the person receiving under pressure”, were significantly different between the two models ( P  < 0.05). Hence, comparing the two models according to Cohen’s effect size, the largest and smallest effect sizes belonged to the items “use of available documentation (charts, etc.)” (1.39) and “the person receiving under pressure” (0.16), respectively (Table  3 ).

Most of the information I receive during shift handover is not related to the patient under my care.

Noise interferes with my ability to concentrate during shift handover.

I believe effective communication skills (such as clear and calm speech) should be used in handover.

In my experience, shift handover is often disrupted by patients, companions or other staff.

After handover, I seek additional information about patients from another nurse or the nurse in charge.

I believe this shift handover model is time consuming.

According to calculated Cohen’s effect sizes, the largest and smallest effect sizes of the modified handover model in comparison with the SBAR method belonged to “I receive sufficient information on nursing care (activity, nutrition, hydration, and pain) during the shift handover” (1.54) and “I believe this shift handover model is time consuming” (0.024), respectively (Table  4 ).

Univariate covariance analysis was used to determine the relationship of demographic variables with nurse perception of handover and the quality of handover. Due to a quantitative nature, the age variable was entered as a covariate and other variables as factors. The results revealed that demographic variables do not have a significant effect on nurses’ perception of handover or the quality of handover in either of the two models ( P  > 0.05).

The present study was conducted with the aim of comparing the effect of implementing SBAR and modified handover models on handover quality and nurse perception of handover in the ED. Based on our findings, implementation of the modified handover model has a more favorable effect on the average handover quality and nurse perception scores compared with the SBAR method. The modified handover model was first designed by Klim et al. (2013), by modifying the components of the SBAR model via group interviews in the ED (17). The modified handover model focused on a standardized approach, including checklists, with emphasis on nursing care and patient involvement. This handover model in the ED enhanced continuity of nursing care, and aspects of the way in which care was implemented and documented, which might translate to reduced incidence of adverse events in this setting. Improvements observed in this current study, such as application of charts for medication, vital signs, allergies, and fluid balance to review patient nursing care, and receiving sufficient information on nursing care (activity, nutrition, hydration, and pain) during the shift handover might help prevent adverse events, including medication errors and promoted handover quality.

Another component of the new handover model was that handover should be conducted in the cubicle at the bedside and involve the patient and/or their companion. More recently, it has been shown that family members also value the opportunity to participate in handover, which promotes family-centered care. Hence, there are disparate opinions between nurses, patients and their family about whether patients should participate in handover. Florin et al. suggest that nurses should establish patient preferences for the degree of their participation in care [ 27 ]. In a phenomenological study, Frank et al. found that ED patients want to be acknowledged; however, they struggle to become involved in their care. In this current study, handover was more likely to be conducted in front of the patient, and more patients had the opportunity to contribute to and/or listen to handover discussion after the introduction of the ED structured nursing handover framework [ 28 ].

Preliminary data showed that there was mixed opinion regarding the appropriate environment for inter-shift handover in the ED. The framework was specifically modified to address deficits in nursing care practice, effect on handover quality and nurse perception of handover. For example, emphasis was placed on viewing the patient’s charts for medication, vital signs and fluid balance. This provides an opportunity for omissions of information, documentation, or care to be identified and addressed at the commencement of a shift. The results of a study by Kerr (2016) demonstrated that implementation of this model improves the transfer of important information to nurses of subsequent shifts and does not possess the shortcomings of the SBAR model [ 13 ].

Accordingly, implementing the modified handover model, improves bedside handover quality from 62.5 to 93%, patient participation in the handover process from 42.1 to 80%, information transfer from 26.9 to 67.8%, identification of patients with allergies from 51.2 to 82%, the amount of documentation from 82.6 to 94.1%, and the use of charts and documentation during handover from 38.7 to 60.8%, meanwhile decreasing omission of essential information such as vital signs from 50 to 32.2%. The authors concluded that implementation of the modified handover model increases documentation, improves nursing care, improves receiving information, enhances patient participation during handover, reduces errors in care and documentation, and promotes bedside handover. A good quality handover facilitates the transfer of information, mutual understanding, and a good working environment [ 13 ]. These findings are consistent with the results of current study.

Moreover, Beigmoradi (2019) showed that in the SBAR model, less attention is paid to clinical records and evaluation of patient body systems during the handover [ 29 ].

Patients are treated urgently in the ED, with the goal of a comprehensive handover immediately. Meanwhile, the non-comprehensive handover model causes a halt in the flow of information, which reduces the handover efficiency. In contrast, the results of a study by Li et al. (2022) demonstrated that implementing a combined model of SBAR and mental map, leads to a significant improvement in the quality of handover and nurse perception of the patient, while reducing defects in shift handover [ 30 ]. Kazemi et al. (2016) showed that patient participation in the handover process increases patient and nurse satisfaction and helps inform patients of their care plan [ 22 ].

According to our findings, demographic variables do not have a significant effect on nurses’ perception of handover and the quality of handover in SBAR or modified handover models. The results of this study can be compared with the results of others in some aspects. Mamallalala et al. (2017) showed that there is significant difference between experience and information transfer of information during shift handover. Hence, nurses with an experience of more than 10 years show higher levels of shared communication and information transfer during shift handover [ 31 ]. The findings of the study by Zakrison et al. (2016) also demonstrated that more experienced nurses are more concerned about transferring information compared with the less experienced [ 32 ], which is not consistent with the results of the present study. The reason for this discrepancy may be the different characteristics of the study samples in the two studies.

The findings of the present study demonstrated that the modified handover model demonstrably improves Shift handover quality, Information transfer, Shared understanding and Perception of handover in the ED. Hence, the results of this study can be presented to nursing managers and quality improvement managers of hospitals as a guide in improving the quality of nursing care via implementing and applying this strategy in the nursing handover. The ED structured nursing modified handover framework focused on a standardized approach, including checklists, with emphasis on nursing care and patient involvement. This straightforward and easy-to-implement strategy has the potential to enhance continuity of care and completion of aspects of nursing care tasks and documentation in the ED.

Strengths and limitations

The present research is the first study to investigate the effect of the modified handover model on handover quality and nurses’ perception of handover in Iran.

The modified handover model tool is a reliable and validated tool that can be easily implemented in ED practice for sharing information among health care providers; however, there are limitations of use in patients with complex medical histories and care plans, especially in the critical care setting. In addition, the modified handover model tool requires training all clinical staff so that they can understand communication well. Future research might test whether introduction of this handover model in the ED setting results in actual enhanced patient safety, including reduction in medication errors.

The resistance of nurses against executing a new handover method was one of the limitations of the research, which was resolved by explanation of the plan and goals, as well as the cooperation of the hospital matron, and the ward supervisor.

Key points for policy, practice and/or research

The results of this study can provide nursing managers with a model of nursing shift handover that promotes the quality of nursing care and patient-related concepts. Interventions could target a combination of the content, communication method, and location aspects of the modified handover model.

Implementing a standardized handover framework such as the modified handover model method allows for concise and comprehensive information handoffs.

The modified handover model tool might be an adaptive tool that is suitable for many healthcare settings, in particular when clear and effective interpersonal communication is required.

The modified handover model provides an opportunity for omissions of information, documentation, or care to be identified and addressed at the commencement of a shift.

Future research

Future studies on the validation of the modified handover model tool in various medical fields, strategies to reinforce the use of the modified handover model tool during all patient-related communication among health care providers, and comparison studies on the modified handover model tool communication tool would be beneficial.

Translation of these findings for enhanced patient safety should be measured in the future, along with sustainability of the new nursing process and external validation of the findings in other settings.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request.

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Acknowledgements

This article was derived from a master thesis of aging nursing. The authors would like to acknowledge the research deputy at Babol University of medical sciences for their support.

This study was supported by research deputy at Babol University of medical sciences.

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Atefeh Alizadeh-risani

Nursing Care Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran

Fatemeh Mohammadkhah, Ali Pourhabib & Zahra Fotokian

Department of Critical Care Nursing, School of Nursing and Midwifery, Qazvin University of Medical Sciences, Qazvin, Iran

Marziyeh Khatooni

Correspondence: Zahra Fotokian; Nursing Care Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran

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All authors contributed to the study conception and design, also all authors read and approved the final manuscript. Atefe Alizadeh-riseni, Zahra Fotokian: Study concept and design, Acquisition of subjects and/or data, Analysis and interpretation of data. Fatemeh Mohammadkhah, Ali Pourhabib: Study design, Analysis and interpretation of data, Preparation of manuscript. Marziyeh Khatooni: Analysis and interpretation of data.

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Correspondence to Zahra Fotokian .

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The Ethics Committee of Babol University of Medical Sciences approved this research proposal (coded under IR.MUBABOL.REC.1401.162). This research was conducted in accordance with the Declaration of Helsinki and all study participants provided written informed consent. The participant rights were preserved (all data were kept anonymous and confidential).

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Alizadeh-risani, A., Mohammadkhah, F., Pourhabib, A. et al. Comparison of the SBAR method and modified handover model on handover quality and nurse perception in the emergency department: a quasi-experimental study. BMC Nurs 23 , 585 (2024). https://doi.org/10.1186/s12912-024-02266-4

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Understanding and Evaluating Survey Research

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

SURVEY RESEARCH

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

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

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

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

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

Sources of Error in Survey Research and Strategies to Reduce Error

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

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

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

DATA COLLECTION METHODS

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

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

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

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

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

FUJIMORI ET AL.: SURVEY RESEARCH

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

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

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

CONCLUSIONS

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

The author has no potential conflicts of interest to disclose.

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• Volume 41, Issue 9
• The RELIEF feasibility trial: topical lidocaine patches in older adults with rib fractures
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• Madeleine Clout 1 ,
• Nicholas Turner 1 ,
• Clare Clement 2 ,
• Philip Braude 3 ,
• http://orcid.org/0000-0001-6131-0916 Jonathan Benger 4 ,
• James Gagg 5 ,
• Emma Gendall 6 ,
• Simon Holloway 7 ,
• Jenny Ingram 8 ,
• Rebecca Kandiyali 9 ,
• Amanda Lewis 1 ,
• Nick A Maskell 10 ,
• David Shipway 11 ,
• http://orcid.org/0000-0002-6143-0421 Jason E Smith 12 ,
• Jodi Taylor 13 ,
• Alia Darweish Medniuk 14 ,
• http://orcid.org/0000-0002-2064-4618 Edward Carlton 15 , 16
• 1 Population Health Sciences , University of Bristol , Bristol , UK
• 2 University of the West of England , Bristol , UK
• 3 CLARITY (Collaborative Ageing Research) , North Bristol NHS Trust , Westbury on Trym , UK
• 4 Faculty of Health and Life Sciences , University of the West of England , Bristol , UK
• 5 Department of Emergency Medicine , Somerset NHS Foundation Trust , Taunton , UK
• 6 Research and Innovation , Southmead Hospital , Bristol , UK
• 7 Pharmacy Clinical Trials and Research , Southmead Hospital , Bristol , UK
• 8 Bristol Medical School , University of Bristol , Bristol , UK
• 9 Warwick Clinical Trials Unit , Warwick Medical School , Coventry , UK
• 10 Academic Respiratory Unit , University of Bristol , Bristol , UK
• 11 Department of Medicine for Older People, Southmead Hospital , North Bristol NHS Trust , Bristol , UK
• 12 Emergency Department , University Hospitals Plymouth NHS Trust , Plymouth , UK
• 13 Bristol Trials Centre, Population Health Sciences , University of Bristol , Bristol , UK
• 14 Department of Anaesthesia and Pain Medicine , Southmead Hospital , Bristol , UK
• 15 Emergency Department , Southmead Hospital , Bristol , UK
• 16 Department of Emergency Medicine, Translational Health Sciences , University of Bristol , Bristol , UK
• Correspondence to Dr Edward Carlton; eddcarlton{at}gmail.com

Background Lidocaine patches, applied over rib fractures, may reduce pulmonary complications in older patients. Known barriers to recruiting older patients in emergency settings necessitate a feasibility trial. We aimed to establish whether a definitive randomised controlled trial (RCT) evaluating lidocaine patches in older patients with rib fracture(s) was feasible.

Methods This was a multicentre, parallel-group, open-label, feasibility RCT in seven hospitals in England and Scotland. Patients aged ≥65 years, presenting to ED with traumatic rib fracture(s) requiring hospital admission were randomised to receive up to 3×700 mg lidocaine patches (Ralvo), first applied in ED and then once daily for 72 hours in addition to standard care, or standard care alone. Feasibility outcomes were recruitment, retention and adherence. Clinical end points (pulmonary complications, pain and frailty-specific outcomes) and patient questionnaires were collected to determine feasibility of data collection and inform health economic scoping. Interviews and focus groups with trial participants and clinicians/research staff explored the understanding and acceptability of trial processes.

Results Between October 23, 2021 and October 7, 2022, 206 patients were eligible, of whom 100 (median age 83 years; IQR 74–88) were randomised; 48 to lidocaine patches and 52 to standard care. Pulmonary complications at 30 days were determined in 86% of participants and 83% of expected 30-day questionnaires were returned. Pulmonary complications occurred in 48% of the lidocaine group and 59% in standard care. Pain and some frailty-specific outcomes were not feasible to collect. Staff reported challenges in patient compliance, unfamiliarity with research measures and overwhelming the patients with research procedures.

Conclusion Recruitment of older patients with rib fracture(s) in an emergency setting for the evaluation of lidocaine patches is feasible. Refinement of data collection, with a focus on the collection of pain, frailty-specific outcomes and intervention delivery are needed before progression to a definitive trial.

Trial registration number ISRCTN14813929 .

• feasibility studies
• frail elderly

Data availability statement

Data are available on reasonable request. Further information and patient-facing materials (including model consent forms) are available at https://relief.blogs.bristol.ac.uk/ . Data available on request.

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See:  https://creativecommons.org/licenses/by/4.0/ .

https://doi.org/10.1136/emermed-2024-213905

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WHAT IS ALREADY KNOWN ON THIS TOPIC

Studies have evaluated the use of lidocaine patches in patients with rib fractures showing reductions in opioid use, improvements in pain scores and reductions in length of hospital stay.

Importantly, none has focused on older patients, who stand to gain the most benefit from improved analgesic regimens to reduce adverse pulmonary complications.

WHAT THIS STUDY ADDS

In this feasibility trial, prespecified progression criteria around recruitment, follow-up and adherence were met, demonstrating it is feasible to conduct randomised controlled trials in older patients, who are in pain, in an emergency setting.

There were challenges in data collection for pain and frailty-specific measures, together with treatment crossover, that require consideration in definitive trial design.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

Researchers can adapt study processes to be inclusive of older patients in the emergency setting.

There are challenges in terms of data collection around pain and frailty-specific outcome measures which future research should consider.

Introduction

Rib fractures represent the most common non-spinal fracture in older people. 1 Age ≥65 years remains a predictor of morbidity and mortality in patients with rib fractures. 2 Pain can compromise normal respiratory function, with over 15% of older patients experiencing complications including pneumonia and death. 3

The mainstay for treatment of rib fracture pain remains strong opioid analgesia. However, as a result of poor physiological reserve, older patients are more vulnerable than younger people to the side effects of strong opioid medication such as nausea, constipation, sedation, delirium and respiratory depression. 4 Invasive approaches, such as thoracic epidural anaesthesia, have been used to reduce the likelihood of these side effects, but require specialist anaesthetic support, monitoring in a high-dependency environment and are only used in around 20% of admitted patients. 5 6

Lidocaine patches applied over rib fractures have been suggested as a non-invasive method of local anaesthetic delivery to improve respiratory function, reduce opioid consumption and consequently reduce pulmonary complications. 7 Studies have evaluated the use of lidocaine patches in patients with rib fractures showing reductions in opioid use, 8 improvements in pain scores 9 10 and reductions in length of hospital stay. 11 However, these studies are limited by retrospective design and low patient numbers with consequent bias and low precision. Importantly, none has focused on older patients, who are more susceptible to the development of pulmonary complications, 2 or tested lidocaine patches as an intervention in the ED where opioid analgesia is the mainstay of treatment.

Older people have often been excluded from research, relating to multiple long-term health conditions, social and cultural barriers and potentially impaired capacity to provide informed consent. 12 In addition, recruitment of older patients who are in pain in an emergency setting may pose further challenges around information provision and collection of clinical and patient-reported outcomes.

The aim of this trial was to establish whether a definitive randomised controlled trial (RCT) to evaluate the benefit of lidocaine patches, first applied in the ED, for older people requiring admission to hospital with rib fracture(s) is feasible.

Detailed methods, including detailed consent procedures, are described in full elsewhere. 13

Design, setting and participants

The Randomised Evaluation of topical Lidocaine patches in Elderly patients admitted to hospital with rib Fractures (RELIEF) study was a multicentre, parallel-group, open-label, individually randomised, feasibility RCT, conducted in seven NHS hospitals: five major trauma centres (Southmead Hospital; Royal Infirmary of Edinburgh; Derriford Hospital, Plymouth; Queen Elizabeth University Hospital, Glasgow; St George’s Hospital, London) and two trauma units (Musgrove Park Hospital, Taunton; Royal Devon and Exeter Hospital). The trial included a health economic scoping analysis and an integrated qualitative study. Patients were eligible for recruitment if they were aged ≥65 years, presented at any time after injury with traumatic rib fracture(s) (including multiple fractures, flail chest and traumatic haemothorax/pneumothorax even if this required intercostal chest drainage), confirmed radiologically (by CXR or CT conducted as part of routine care) and required hospital admission for ongoing care. Exclusion criteria are detailed in figure 1 .

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Exclusion criteria.

Randomisation and blinding

Participants were randomised in the ED by trained research or clinical staff, using an online randomisation system, with the randomisation sequence generated by Sealed Envelope (London, UK). Participants were allocated to the intervention or standard care in a 1:1 ratio. Randomisation was stratified by trial site and gender and blocked within strata. Allocations were blinded only to those performing central review of data for the assessment of outcomes.

Intervention

Participants randomised to the intervention received up to 3×700 mg lidocaine patches (Ralvo) at a time applied over the most painful area of rib injury. Patches were first applied in the ED, then once daily for 12 hours in accordance with the manufacturer’s (Grünenthal, Aachen, Germany) instructions. Treatment continued for up to 72 hours or until discharge from hospital. The intervention was additive to standard care (below). If participants subsequently underwent regional anaesthesia, patches were removed and no further patches were applied but data collection continued according to group allocation.

Standard care

All participants received standard local analgesic treatment for patients with rib fractures; this was not controlled for trial purposes. Data were collected on paracetamol, weak opioid, strong opioid and other non-opioid analgesia prescriptions in ED and for the 72-hour intervention period in both arms of the trial. 14

Patient and public involvement

Patient and public involvement was ensured at all stages of trial design, and continued throughout the trial’s lifetime via a patient advisory group and patient representation on the trial steering committees.

Clinical outcomes and measurement

Outcomes were measured at baseline, 72 hours (during or on completion of intervention) and 30-day postrandomisation. A full schedule of clinical data, questionnaires and end points is included in the published protocol. 13 Clinical end points were collected only to understand the feasibility of data collection and not to conduct hypothesis testing. Key clinical data and their measurement are briefly summarised as follows (further details on scales used are provided in the online supplemental material ):

Supplemental material

Demographics, injury details, relevant medical history and Clinical Frailty Scale (CFS) 15 : collected by researcher from clinical notes.

Retrospective pre-injury and baseline post-injury health EQ-5D-5L 16 : completed with participant/relative/carer.

Timed Up and Go test. 17

72 hours postrandomisation (intervention period) collected until discharge if sooner

Patient-reported pain scores: 4-hourly pain assessment using a Visual Analogue Scale (VAS) (scaled from 0 to 100). Recorded in a booklet provided to the patient.

Frailty-specific outcomes: Abbey Pain Scale, 18 4-AT delirium assessment tool, 19 constipation (Bristol Stool Chart), Timed Up and Go test. 17 Obtained by researchers.

Analgesia; ED and inpatient (72 hours) analgesic prescriptions, advanced analgesic provision (patient controlled analgesia (PCA), epidural, nerve block). Obtained by researchers from medical records.

30 days (+10 days) postrandomisation

Pulmonary complications: a priori proposed primary outcome for a definitive trial. Collected after review of medical records and adjudicated by site lead clinician.

Delirium: binary measure of any inpatient episode of delirium recorded in clinical notes.

Resource use: including admitted hospital length of stay, intensive care unit length of stay, unplanned readmission, discharge destination (notes review).

Questionnaires: booklets containing EQ-5D-5L and ICECAP-O 16 20 were sent by post to participants. Participants were permitted to complete these with the assistance of carers, although formal proxy versions of questionnaires were not provided.

Sample size

As this was a feasibility trial, it was not appropriate to calculate a sample size to detect a specified treatment effect size. In line with published ‘rules-of-thumb’, we determined that a total sample size of 100 would be sufficient to provide estimates of feasibility measures (recruitment, retention, data completion and adherence). 21 Recruitment was originally planned to take place over 18 months across three sites. However, trial set-up was delayed due to the COVID-19 pandemic. To achieve target recruitment within the funding period, the recruitment period was shortened to 12 months across seven sites.

Statistical methods

Feasibility measures were analysed and reported following the Consolidated Standards of Reporting Trials guidance extension for feasibility studies to include descriptive and summary statistics both overall and by treatment arm. 22

Descriptive statistics for participant characteristics and clinical outcome data were reported as means or medians with measures of dispersion for continuous outcomes and frequencies and percentages for categorical outcomes.

A priori thresholds for recruitment, follow-up and adherence were established to inform the feasibility of progression (table 2).

Integrated qualitative study

Telephone interviews were undertaken with trial participants around 1 month (and up to 90 days) postrandomisation. Interviews and focus groups were conducted with clinicians/research staff closely involved in the trial set-up, recruitment and follow-up. These explored trial participation experiences including understanding and acceptability of processes, pain control including perceived benefits of lidocaine patches and views on trial outcomes (topic guides are included in the online supplemental material ). Interviews and focus groups were audio-recorded, transcribed and analysed using thematic analysis. 23 Qualitative findings were integrated with other elements using a ‘following a thread’ approach. 24 This involved analysing each dataset and then using insights from the qualitative themes to contextualise and explain quantitative outcomes with data presented together.

Health economic scoping

An evaluation of the feasibility of identifying and measuring health economics outcome data was completed, with the focus on establishing the most appropriate outcome measures for inclusion in a future economic evaluation alongside the definitive trial. The EQ-5D-5L (health-related quality of life) patient-reported questionnaire 16 was completed at baseline, to capture retrospective pre-injury state and baseline post-injury state, and 30 days postrandomisation. In addition to the standard EQ-5D questionnaire, which typically elicits post-injury health status, we additionally assessed pre-injury status by making an approved change to the wording. The ICECAP-O (measure of capability in older people) 20 was also collected at 30 days. Information on key resources, including length of stay, intensive care use and medication prescribing, was also collected.

Between 23 October 2021 and 7 October 2022, 447 patients were assessed for eligibility, of which 206 were eligible; of these, 29 declined and 77 were not approached. Therefore, 100 patients were randomised; 48 participants were allocated to lidocaine patches and 52 to standard care ( figure 2 ). Six participants died prior to the 30-day follow-up timepoint and three participants withdrew from questionnaire completion, but had clinical data retained for analysis. Baseline characteristics were well balanced between groups ( table 1 ).

Screening, recruitment, allocation and follow-up (Consolidated Standards of Reporting Trials diagram).

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Baseline demographics and injury characteristics

Participants were predominantly women (47%), of white British ethnicity (92%), with a median age of 83 years (IQR 74–88). Participants were predominantly admitted from their own homes (92%), were independent (75%) but were living with very mild frailty (median CFS 4; IQR 3–5). The most common mechanism of injury was a fall from <2 m (81%). On average, participants sustained four rib fractures (SD 2.0)and they were at high risk of developing pulmonary complications at baseline (median STUMBL score 21 (IQR 16–33)), equating to a 70% risk. 3

Feasibility outcomes

Table 2 details the prespecified progression criteria around recruitment, follow-up and adherence together with observed results.

Prespecified progression criteria and observed results

Recruitment and consent

An average of 14 participants were recruited per site (range 3–37) in 12 months. Participants were predominately recruited from major trauma centres (n=87).

Agreement to participate was largely obtained from patients (70%): personal consultees (in England) or legal representatives (in Scotland) were approached in 27% of cases, and professional consultees were used in 3% of cases.

In the qualitative research, clinical and research staff closely involved in delivering the trial reported challenges in recruiting within the ED setting. These challenges included general ED pressures, reliance on referrals from wider clinical teams not directly engaged in the research, resource-intensive monitoring of ED attendances for potentially eligible patients, the necessity to rapidly attend ED (when not based in the department) to approach patients and lack of out-of-hours research staff (although some engaged clinicians were able to recruit out of hours). However, they were able to recruit well by raising awareness of the trial and fostering good collaborative relationships with the wider ED clinical team members, who were able to actively participate in patient identification. Insights from older patients were limited due to challenges with interview engagement (of 26 participants approached for interviews, 7 took part, 5 declined, 14 did not respond). However, older patients interviewed welcomed being approached and were willing to participate in the trial because they wanted to help, but were sometimes unsure of trial details. Staff needed to consider older patients’ vulnerability, and carefully manage consent processes to avoid overwhelming them, while ensuring their full understanding of involvement and the option not to participate.

Follow-up and data completeness

The proposed primary outcome of adverse pulmonary complications at 30 days was completed for 86% of participants (data missing in 14%, due to transfer to remote facilities or discharge home and no further records were available). For the 30-day patient-completed questionnaires, in total 71 were returned (fully or partially completed), 15 were unreturned despite repeated contact and 14 had reasons recorded for non-return (7 deaths, 4 remained unwell/confused, 3 withdrawals). This equates to an overall return rate of 71% but rising to 83% when return was anticipated. Qualitative findings regarding questionnaire completion highlighted the unblinded nature of the intervention, with standard care participants not feeling part of the trial, potentially impacting their understanding of completing questionnaires in future research.

Pain and frailty-specific outcomes (important secondary outcomes but not included in prespecified progression criteria) were not feasible to collect as completeness was <65%. Table 3 summarises data completeness on these measures and qualitative exploration of factors influencing data collection.

Pain and frailty-specific outcomes that were not feasible to collect and qualitative exploration of factors influencing data collection

In the intervention arm, 44/48 (92%) participants had at least one lidocaine patch applied in ED at a median time of 393.5 min after arrival. In the standard care arm, 17/52 (33%) participants also had a lidocaine patch applied in ED and were therefore classed as non-adherent. However, overall adherence was 79% meeting the prespecified green criteria for feasibility (>75%). Themes identified in the qualitative research with clinical/research staff addressing variation in care included standard care (some hospitals use patches as standard care, others do not), patch application (eg, where best to place patches in the presence of multiple fractures), provision of nerve blockade (the ongoing use of lidocaine patches when nerve blocks are subsequently used), equipoise (mixed views on the benefits of patches) and patch acceptability (perceived benefits of patches to patients) (see online supplemental material for details).

Clinical outcomes

72-hour outcomes

Data on ED and inpatient (72 hours) analgesic prescriptions, together with advanced analgesic provision (PCA, epidural, nerve blocks) were collected in >75% of participants ( table 4 ) Analgesic prescriptions within ED and as an inpatient were similar between arms. Overall, 33/97 (34%) participants had advanced analgesia with 21/97 (22%) receiving some form of nerve blockade and 12/97 (13%) receiving PCA within the 72-hour intervention period.

30-day outcomes

Overall, 46/86 (53%) participants with complete data met the outcome of composite pulmonary complications within 30 days; 20 (48%) in the lidocaine patch arm and 26 (59%) in the standard care arm. The median length of hospital stay was 9.1 days (IQR 5.2–15.4) and over 30% of participants did not return to their baseline level of function on discharge (requiring increased package of care, residential, nursing or rehabilitation). Descriptive data on all 30-day outcomes is included in table 4 .

We achieved our objectives in terms of piloting instruments of data collection: administration of EQ-5D-5L and ICECAP-O measures and case report forms to record length of stay, use of analgesia and discharge destination ( table 4 ).

As anticipated EQ-VAS at baseline (measuring overall health status with 100 being best imaginable health) were reported as higher pre-injury (median 80 (60–90)) compared with post-injury (median 50 (25–70)). At 30 days, EQ-5D-5L completeness was 44% and ICECAP-O was 65%. In terms of the trajectory of health status, as anticipated the baseline EQ-5D-5L post-injury tariff had the lowest median (0.44 (0.25–0.63)) while at 30 days these data indicated participants had only partially recovered in terms of health status (0.59 (0.27–0.74)) ( table 4 ). The overall median ICECAP-O tariff at 30 days was 0.77, which is slightly below a published population norm of 0.81. 25

This trial suggests it is feasible to recruit older patients with rib fracture(s) in an emergency setting. Consent processes modified for older patients were effective and acceptable to patients and carers. However, pain and frailty-specific outcomes were not feasible to collect. While these were not anticipated primary outcomes for a future trial, they are clearly important secondary outcomes in this population. Our qualitative work highlighted areas for improvement in this regard. These include bespoke training for researchers when unfamiliar with measures (Abbey Pain Scale, 4-AT delirium assessment tool), embedding measures such as 4-AT delirium assessment tool into clinical practice and increased recognition of the potential to overwhelm older injured patients through research procedures when designing trials. It should be noted that the World Hip Trauma Evaluation platform study appears to have overcome many of these barriers to data collection in a similar population. 26

Data collection for the suggested primary outcome of a definitive trial (adverse pulmonary complications) was feasible, and the high rates of this outcome within the population confirm that it remains a target outcome for early analgesic interventions in older patients with rib fracture(s).

Paper-based, mailed out, patient-completed questionnaires were returned at high rates, suggesting that this remains an acceptable option for older participants in research. This aligns with consensus recommendations that alternatives should be offered to digital data collection to avoid digital exclusion in older patients. 12 However, for those patients with cognitive impairment, consideration of formal proxy versions of questionnaires should be considered where available.

While adherence to the intervention was high and overall adherence was deemed feasible, significant crossover in the standard care arm was seen. This finding suggests clinicians may lack equipoise in sites where lidocaine patches are already in use; this was confirmed in our healthcare professional focus groups. However, these focus groups also highlighted discrepancies in prescribing/availability and a recognition of the potential harm of overuse of lidocaine patches (at the expense of other analgesic modalities). In order to overcome these challenges in equipoise, avoid crossover and fully understand the clinical effectiveness of topical lidocaine, a definitive trial would need to test active patches against placebo patches rather than standard care.

In this trial, older patients admitted to hospital with radiologically confirmed rib fracture(s) were living with very mild frailty (median CFS 4) and were predominantly injured after a fall from standing (<2 m), a finding consistent with previous reports. 27 Despite having isolated rib fracture(s), many participants had prolonged hospital stays (median 9 days) and >30% did not return to baseline functional status on discharge. STUMBL scores recorded at baseline suggested a population at high risk of developing adverse pulmonary complications and this finding was confirmed in 30-day outcome collection. Development of delirium appeared lower than reported in other cohorts, 6 but may reflect a lack of robust data collection. Notable findings that may provide targets for service improvements include prolonged times between injury and hospital arrival (20 hours) and low rates of prehospital analgesia administration. In addition, in-hospital (72 hours) analgesic prescriptions appear to rely heavily on strong opioid analgesia, with more advanced analgesic modalities being used in only around one-fifth of this vulnerable patient group.

Rib fracture(s) were diagnosed by CT in over 90% of cases. This may reflect a more liberal use of CT in older patients with suspected trauma following influential reports such as Trauma Audit Research Network Major Trauma in Older People 28 and the majority of sites being major trauma centres. However, this finding may also reflect selection bias towards more severely injured patients, given that our inclusion criteria required radiological confirmation of rib fracture(s) and prior studies have demonstrated a poor sensitivity of X-ray diagnosis, with only 40% accuracy in older patients. 29 Amending the inclusion criteria to include patients with clinically suspected (rather than radiologically confirmed) rib fractures may mitigate against this selection bias and also allow the inclusion of those patients who are less severely injured and potentially more frail.

Our health economic scoping revealed key findings to be considered in future research involving older adults in emergency settings. Modification of the standard EQ-5D to obtain retrospective pre-injury health status may be beneficial in assessing specific impacts of injury in economic modelling. However, since response rates to the ICECAP-O were higher than for the EQ-5D at 30 days, which may reflect a patient preference for completing a measure specifically designed for use in older people, it is possible that this is a more appropriate measure for use in a definitive trial.

Conclusions

This trial has demonstrated that recruitment of older patients with rib fracture(s) in an emergency setting for the evaluation of early analgesic interventions (in the form of lidocaine patches) is feasible. Refinement of data collection, with a focus on collecting pain and frailty-specific outcomes, as well as intervention delivery, is needed before progressing to a definitive trial.

Ethics statements

Patient consent for publication.

Not applicable.

Ethics approval

The protocol (V.4.0 4 March 2022) and other related participant-facing documents were approved by the UK Health Research Authority and UK Research Ethics Committees (REC): 21/SC/0019 (South Central—Oxford C REC; IRAS reference 285096) and 21/SS/0043 (Scotland A REC; IRAS reference 299793). Participants gave informed consent to participate in the study before taking part.

Acknowledgments

Sponsor: North Bristol NHS Trust (R&I reference: 4284). Trial management: this trial was designed and delivered in collaboration with the Bristol Trials Centre, a UKCRC registered clinical trials unit, which is in receipt of National Institute for Health Research CTU support funding. The trial management group included all authors and particular thanks are given to Gareth Williams who led patient and public contributions on the trial management group. Trial Steering Committee: the RELIEF trial team would like to thank all members of the independent members of the committee who gave up their time to provide oversight of this work: Fiona Lecky (Clinical Professor in Emergency Medicine and TSC Chair), Rachel Bradley (Consultant in General, Geriatric and Orthogeriatric Medicine), Sean Ewings (Associate Professor of Medical Statistics, Southampton Clinical Trials Unit, University of Southampton), Gordon Halford (Patient and Public Involvement Contributor). Participating sites: the RELIEF trial team would like to thank all staff involved at the seven participating sites (Southmead Hospital, North Bristol NHS Trust, Principal Investigator (PI): Edward Carlton, Associate PI: Fraser Birse; Royal Infirmary of Edinburgh, NHS Lothian, PI: Rachel O’Brien; Derriford Hospital, University Hospitals Plymouth NHS Trust, co-PIs: Jason Smith and Robert James, Associate PI: Rory Heath; Queen Elizabeth University Hospital, NHS Greater Glasgow and Clyde, co-PIs: Fraser Denny and David Lowe, Associate PI: Nathalie Graham; St George's Hospital London, St George's University Hospitals NHS Foundation Trust, PI: Melanie Lynn; Musgrove Park Hospital, Somerset NHS Foundation Trust, PI: James Gagg; Royal Devon and Exeter Hospital, Royal Devon University Healthcare NHS Foundation Trust, PI: Andy Appelboam).

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Supplementary materials

Supplementary data.

This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

• Data supplement 1

Handling editor Kirsty Challen

X @DrPhilipBraude, @eddcarlton

Presented at Results were presented in part at the Royal College of Emergency Medicine Annual Scientific Conference on 26 September 2023 and Age Anaesthesia Annual Scientific Meeting on 12 May 2023.

Contributors MC and NT have had full access to all data in the study and take full responsibility for the integrity of the data and accuracy of data analysis. Study concept and design: EC, NT, CC, PB, JB, JG, JI, RK, NAM, DS, JS, ADM. Analysis and interpretation of data: all authors. Drafting of manuscript: EC, CC, MC, RK, NT. Critical revision of manuscript for important intellectual content: all authors. Statistical analysis: NT. Obtained funding: EC, NT, CC, PB, JB, JG, JI, RK, NAM, DS, JS, ADM. EC is the guarantor of the study.

Funding This study is funded by the NIHR [Advanced Fellowship (NIHR300068)]. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care

Disclaimer The funder was not involved in the design, execution, analysis and interpretation of data or writing up of the trial.

Competing interests None declared.

Patient and public involvement Patients and/or the public were involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the 'Methods' section for further details.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

Linked Articles

• Commentary Commentary: The RELIEF feasibility trial: topical lidocaine patches in older adults with rib fractures Ceri Battle Emergency Medicine Journal 2024; 41 520-521 Published Online First: 02 Jun 2024. doi: 10.1136/emermed-2024-214244

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