How to design a questionnaire
BMJ 2001; 322 doi: https://doi.org/10.1136/sbmj.0106187 (Published 01 June 2001) Cite this as: BMJ 2001;322:0106187
- Wai-Ching Leung, lecturer in public health medicine1
- 1University of East Anglia
As discussed in a previous issue a survey involves directly collecting information from people (or sometimes organisations) whom we are interested in.1 The types of information will take account of the people's or organisations' level of knowledge, attitude, personalities, beliefs, or preferences. Questionnaires are widely used to collect such information. Well designed questionnaires are highly structured to allow the same types of information to be collected from a large number of people in the same way and for data to be analysed quantitatively and systematically. Questionnaires are best used for collecting factual data and appropriate questionnaire design is essential to ensure that we obtain valid responses to our questions.
Objectives in designing questionnaires
There are two main objectives in designing a questionnaire:
To maximise the proportion of subjects answering our questionnaire - that is, the response rate.
To obtain accurate relevant information for our survey.
To maximise our response rate, we have to consider carefully how we administer the questionnaire, establish rapport, explain the purpose of the survey, and remind those who have not responded. The length of the questionnaire should be appropriate. In order to obtain accurate relevant information, we have to give some thought to what questions we ask, how we ask them, the order we ask them in, and the general layout of the questionnaire.
Deciding what to ask
As discussed in last month's issue, there are three potential types of information:
Information we are primarily interested in-that is, dependent variables.
Information which might explain the dependent variables-that is, independent variables.
Other factors related to both dependent and independent factors which may distort the results and have to be adjusted for - that is, confounding variables.
Let us take as an example a national survey to find out students' factors predicting the level of certain knowledge, …
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