A questionnaire is a research instrument consisting ofa series of questions for the purpose of gathering information from respondents. The questionnaire was invented by the Statistical Society of London in 1838. Although questionnaires are often designed for statistical analysis of the responses, this is not always the case. Questionnaires have advantages over some other types of surveys in that they are cheap, do not require as much effort from the questioner as verbal or telephone surveys, and often have standardized answers that make it simple to compile data. However, such standardized answers may frustrate users as the possible answers may not accurately represent their desired responses. Questionnaires are also sharply limited by the fact that respondents must be able to read the questions and respond to them. Thus, for some demographic groups conducting a survey by questionnaire may not be concretely feasible.
Types
A distinction can be made between questionnaires with questions that measure separate variables, and questionnaires with questions that are aggregated into either a scale or index. Questionnaires with questions that measure separate variables, could for instance include questions on:
preferences
behaviors
facts
Questionnaires with questions that are aggregated into either a scale or index, include for instance questions that measure:
latent traits
attitudes
an index
Examples
A food frequency questionnaire is a questionnaire the type of diet consumed in people, and may be used as a research instrument. Examples of usages include assessment of intake of vitamins or toxins such as acrylamide.
Questionnaire construction
Question type
Usually, a questionnaire consists of a number of questions that the respondent has to answer in a set format. A distinction is made between open-ended and closed-ended questions. An open-ended question asks the respondent to formulate his own answer, whereas a closed-ended question has the respondent pick an answer from a given number of options. The response options for a closed-ended question should be exhaustive and mutually exclusive. Four types of response scales for closed-ended questions are distinguished:
Dichotomous, where the respondent has two options
Nominal-polytomous, where the respondent has more than two unordered options
Ordinal-polytomous, where the respondent has more than two ordered options
Continuous, where the respondent is presented with a continuous scale
A respondent's answer to an open-ended question is coded into a response scale afterwards. An example of an open-ended question is a question where the testee has to complete a sentence.
Question sequence
In general, questions should flow logically from one to the next. To achieve the best response rates, questions should flow from the least sensitive to the most sensitive, from the factual and behavioural to the attitudinal, and from the more general to the more specific. There typically is a flow that should be followed when constructing a questionnaire in regards to the order that the questions are asked. The order is as follows:
Screens
Warm-ups
Transitions
Skips
Difficult
Classification
Screens are used as a screening method to find out early whether or not someone should complete the questionnaire. Warm-ups are simple to answer, help capture interest in the survey, and may not even pertain to research objectives. Transition questions are used to make different areas flow well together. Skips include questions similar to "If yes, then answer question 3. If no, then continue to question 5." Difficult questions are towards the end because the respondent is in "response mode." Also, when completing an online questionnaire, the progress bars lets the respondent know that they are almost done so they are more willing to answer more difficult questions. Classification, or demographic question should be at the end because typically they can feel like personal questions which will make respondents uncomfortable and not willing to finish survey.
Basic rules for questionnaire item construction
Use statements which are interpreted in the same way by members of different subpopulations of the population of interest.
Use statements where persons that have different opinions or traits will give different answers.
Think of having an "open" answer category after a list of possible answers.
Use only one aspect of the construct you are interested in per item.
Use positive statements and avoid negatives or double negatives.
Do not make assumptions about the respondent.
Use clear and comprehensible wording, easily understandable for all educational levels
Use correct spelling, grammar and punctuation.
Avoid items that contain more than one question per item.
Question should not be biased or even leading the participant towards an answer.
Multi-item scales
Within social science research and practice, questionnaires are most frequently used to collect quantitative data using multi-item scales with the following characteristics:
Multiple statements or questions are presented for each variable being examined.
Each statement or question has an accompanying set of equidistant response-points.
Each response point has an accompanying verbal anchor ascending from left to right.
Verbal anchors should be balanced to reflect equal intervals between response-points.
Collectively, a set of response-points and accompanying verbal anchors are referred to as a rating scale. One very frequently-used rating scale is a Likert scale.
Usually, for clarity and efficiency, a single set of anchors is presented for multiple rating scales in a questionnaire.
Collectively, a statement or question with an accompanying rating scale is referred to as an item.
When multiple items measure the same variable in a reliable and valid way, they are collectively referred to as a multi-item scale, or a psychometric scale.
Questionnaires used to collect quantitative data usually comprise several multi-item scales, together with an introductory and concluding section.
Questionnaire administration modes
Main modes of questionnaire administration include:
Face-to-face questionnaire administration, where an interviewer presents the items orally.
Paper-and-pencil questionnaire administration, where the items are presented on paper.
Computerized questionnaire administration, where the items are presented on the computer.
Adaptive computerized questionnaire administration, where a selection of items is presented on the computer, and based on the answers on those items, the computer selects following items optimized for the testee's estimated ability or trait.
Concerns with questionnaires
While questionnaires are inexpensive, quick, and easy to analyze, often the questionnaire can have more problems than benefits. For example, unlike interviews, the people conducting the research may never know if the respondent understood the question that was being asked. Also, because the questions are so specific to what the researchers are asking, the information gained can be minimal. Often, questionnaires such as the Myers-Briggs Type Indicator, give too few options to answer; respondents can answer either option but must choose only one response. Questionnaires also produce very low return rates, whether they are mail or online questionnaires. The other problem associated with return rates is that often the people who do return the questionnaire are those who have a really positive or a really negative viewpoint and want their opinion heard. The people who are most likely unbiased either way typically don't respond because it is not worth their time. One key concern with questionnaires is that there may contain quite large measurement errors. These errors can be random or systematic. Random errors are caused by unintended mistakes by respondents, interviewers and/or coders. Systematic error can occur if there is a systematic reaction of the respondents to the scale used to formulate the survey question. Thus, the exact formulation of a survey question and its scale are crucial, since they affect the level of measurement error. Different tools are available for the researchers to help them decide about this exact formulation of their questions, for instance estimating the quality of a question using MTMM experiments or predicting this quality using the Survey Quality Predictor software. This information about the quality can also be used in order to correct for measurement errors. Further, if the questionnaires are not collected using sound sampling techniques, often the results can be non-representative of the population—as such a good sample is critical to getting representative results based on questionnaires.
