How can we control and limit or reduce the socially desirable responses in questionnaire of Survey type research?

03 July 2023 8 3K Report

In the field of research, survey type research is very popular and widely used as a research method. But some times I felt that collecting data by closed ended questionnaire may lead to socially desirable responses or behavior, example - if anyone is conducting a research on "Current Status Professional Development of Secondary Teacher" and the researcher is putting questions about the activities like - Are you a enrolling in refresher courses, are you participating in seminar, workshop or Faculty development programme etc

Then the respondent here may answer in his positive side whether he/she is doing these activities or not (So these type of socially desirable behavior they are giving and happening also). It is very much affecting the authenticity of the data we got from our sample and what we report for the development of the society may be wrong and we are providing to some extend the wrong data. So how can we mitigate or limit or reduce this effect.

Ajit Singh

There are several strategies that researchers can use to control and reduce the socially desirable responses in questionnaire-based survey research:

Anonymity: Ensure that respondents know that their identity will not be revealed. This can help reduce the social desirability bias as respondents are more likely to give honest answers when they are confident that their answers will not be traced back to them.

Framing the Questions: The way questions are phrased can influence responses. Avoid leading questions and make sure that the wording is free from any bias towards any specific answer.

Reverse Questions: Use reverse questions which are the opposite of the socially desirable responses. For example, instead of asking "How often do you attend seminars, workshops or faculty development programs?"; ask "How often do you miss seminars, workshops or faculty development programs?".

Include open-ended questions: Including open-ended questions can help researchers to gain more in-depth insights and also provide respondents a chance to share their actual experiences, even if they don't fit into the predefined questions.

Pilot testing: Always pilot-test your survey before deployment to get feedback and make necessary revisions. This can help researchers to identify any issues with the questionnaire, including the presence of social desirability bias.

Mixed-Method Design: Incorporating multiple methods such as face-to-face interviews, observations or focus groups, can help researchers cross-validate findings and provide nuanced insights beyond survey responses.

By employing these strategies, researchers can mitigate or reduce the impact of social desirability bias in their survey-based research and produce more reliable and authentic results.

Mansur Bello

Participants would be always put into practice before answered the queastionn

Ma'Mon Abu Hammad

you have rightly identified a common concern regarding socially desirable responses in survey research. Respondents may feel pressured to provide answers that they believe are socially acceptable or align with societal expectations, rather than their true thoughts or behaviors. This can potentially compromise the authenticity and accuracy of the data collected. However, there are several strategies you can employ to mitigate this effect:

Anonymous Surveys: Ensure that the survey is anonymous, meaning respondents cannot be identified based on their responses. This can encourage participants to be more honest and reduce the likelihood of socially desirable responses.

Use of Indirect Questions: Instead of asking respondents directly about their behaviors or attitudes, consider using indirect questions or more subtle approaches. For example, rather than asking if they are enrolling in refresher courses, you can ask about the perceived importance of such courses or their opinions on the benefits of professional development.

Multiple Data Sources: Rely on multiple sources of data to triangulate your findings. In addition to surveys, consider using other research methods such as observations, interviews, or focus groups. These approaches can provide additional insights and help validate or challenge the survey results.

Controlled Environments: If possible, conduct surveys in controlled environments where respondents are less likely to feel judged or influenced by others. This might involve ensuring privacy, using online surveys instead of face-to-face interviews, or employing professional moderators or researchers to create a neutral and non-threatening atmosphere.

Questionnaire Design: Carefully craft your questionnaire to minimize bias and social desirability effects. Avoid leading or loaded questions that may sway respondents toward certain responses. Pilot testing your questionnaire with a small sample can help identify potential issues and refine the survey instrument.

Use of Mixed Methods: Combine quantitative survey data with qualitative data to better understand the topic. Qualitative methods can uncover nuances, contradictions, or inconsistencies that quantitative data alone may not capture.

Analyze Subgroups: Analyze the data across different subgroups (e.g., age, gender, experience) to identify potential discrepancies. If socially desirable responses are prevalent in one subgroup but not in others, it could indicate the presence of bias or social desirability effects.

By implementing these strategies, you can help reduce the impact of socially desirable responses in survey research and enhance the accuracy and authenticity of the data collected.

David L Morgan

Adding reversed questions is no longer recommended because research comparing two versions of the same scale, with and without reversed items, shows that using reversed items reduces the reliability of the scale.

Soumya Ranjan Das

Thank you for your answer to clarify this query (@ Ajit Singh, David L Morgan, Ma'Mon Abu Hammad, Mansur Bello).

Gholamreza Latifi

Hello The questionnaire needs validity and reliability and 10% should be pre-tested before implementation and 10% should be tested post test, and it can be understood based on the frequency of the questions.

Omid Mahdieh

I think there is no clear cut way to avoid this problem. Maybe a good strategy is to choose good samples and their voluntary participation.

James R Knaub

There has been a lot of work done on "randomized response sampling" where a random element is introduced to hide a yes/no answer even to an interviewer. You might want to research that.

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