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How to... use questionnaires effectively

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Constructing the questions

We come now to discuss the actual part of the questionnaire which elicits data from the respondent. According to N. Synodinos, in "" (Integrated Manufacturing Systems , Vol. 14 No. 3), question contruction is a "highly developed art form within the practice of scientific enquiry", and even small changes in wording can have a considerable effect on the resultant data.  

The anatomy of a questionnaire question

There are three parts to the wording of questions, as shown in the illustration below:

Image: Questionnaire extract

As the illustration shows, the parts are:

  • The question stem, which sets the framework for the data, which may be a statement followed by a number of alternatives, as in the examples above, or a straightforward question, such as "What type of library do you work in?" or a statement, such as "since our firm began to implement a TQM programme".
  • The alternatives, which are the range of possible answers from which the respondent selects – a range of library types, a number on a scale of values, etc.
  • The responses , which are the actions which the respondent has to undertake in order to input to the questionnaire – circling a number on a scale of values, clicking a radio button, filling in a text field, or just ticking "yes", "no".

Some ground rules for writing questions

Here we are concerned with very basic general issues; we will deal with question formats and answers in the next section.

Some general guidelines:

  • Each question should relate to one issue only. If you find the question becomes too complicated, then consider splitting it into two.


Synodinos cites "" (Gardiner, G.S. and Gregory, M.J., Integrated Manufacturing Systems , Vol. 7 No. 2) as including two issues in the following questions:

Image: Audit questionnaire extract

  • Relate your questions to your objectives at all times – ask yourself for each question, "How will it help me achieve my research objective?"
  • Don't use any difficult or technical terms without an explanation, and avoid slang and jargon.
  • Avoid questions that are complex, or which tax the respondent's memory, or which call for information which is not easily to hand.
  • Make sure that you don't have any questions which indicate bias – for example 'Do you think that every school should have access to the internet in order that children have the best possible chance of growing up IT literate?'
  • Avoid negatives, especially double negatives, in questions – frame them in a positive way!
  • Remember the KISS principle! Questions should be short, clear, and unambiguous.
  • Avoid asking for highly confidential information, as well as questions that may appear intrusive.
  • Avoid asking people to predict the future.
  • If the survey is based on a past survey, make sure that cultural and linguistic assumptions are still correct. For example, if repeating a study of telephone use that was conducted a number of years ago, remember that the frequency of telephone use has increased.
  • When dealing with populations in different cultures, make sure that the question wording means the same thing in each context.


Joseph Janes, in "" (Library Hi Tech, Vol. 17 No. 3), has an excellent list of points to remember in constructing questions, under the heading "Writing good questions", as does Nicolaos Synodinos, in "" (Integrated Manufacturing Systems , Vol. 14 No. 3), in the section "Question wording".

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