Questionnaire Surveys

Few readers of this journal will not have received a request to take part in a questionnaire survey. Many will receive such requests on a fairly regular basis given that this method is widely used by the scientific community and the commercial world of market research. Surveys are widely used in health services research for data collection and can be administered by postal questionnaire, face-to-face or telephone interview. They have the advantage of being cost-effective and easy to administer to large-scale populations. However, poorly-designed questionnaire surveys do more than waste the time and effort of those who conduct them. The regular receipt of poorly designed questionnaires is likely to discourage individuals from completing and returning those that might be of considerably greater merit. Furthermore, it has been argued that conducting studies that have no immediate impact on improving health care is a serious ethical problem [1]. This journal is almost certainly not alone in consistently having a high rejection rate of studies using survey methodology and therefore this editorial focuses on the underlying principles of design and conduct of survey research. As with any research study, proper planning, preparation and attention to detail are essential if the results are going to be valid and reliable. The most important first task is to define the research question and clearly identify where this lies within the conceptual framework of current knowledge. Is it really worth knowing the answer to the question? For example, does it matter if 91% of day case anaesthetics in a particular speciality are carried out using a laryngeal mask airway or if the figure is 85% or 95%? What might be of interest are the factors that influence non-use in around 10% or why this figure varies for example with the seniority of the anaesthetist. The research question must be refined prior to considering study design methodology, sampling of participants (healthcare professionals, patients or community), data collection and analysis. The survey sample is a proportion of a larger defined population and usually the only means we have of making inferences about the full population, given time, logistic and financial constraints [2]. Sampling techniques include simple random sampling, where each participant has an equal chance of being selected for the sample. Often it is not possible to select a random sample from the target population and samples are made up of those subjects available for study (‘convenience sampling’). For example, it may be convenient to survey anaesthetists registered with a particular organisation but they may not be representative of all anaesthetists; consequently the findings, if generalised to the wider population, would have to be interpreted with caution. Selection bias occurs if individuals for whom data are available are not representative of the target population (non-coverage) or from non-response to questionnaires. Calculation of sample size will be based upon study power, significance level and magnitude of effect deemed clinically important. Power increases with increasing sample size, so that a larger sample has a greater ability to detect a clinically important effect, if it exists, than a small sample [3]. The appropriate sample size should be calculated in advance of undertaking the survey and a full description of the sampling process and justification for sample size should be provided within the methods section of a publication. Many submitted manuscripts fail to consider response bias and make no attempt to compare the characteristics of responders with what is known or can be inferred about nonresponders. Studies of surveys with response rates of around 50% are published but ideally the proportion of responders should be 70–80% for meaningful inferences to be made. The demographic and clinical characteristics of the sample should be described to allow the reader to assess whether the sample is representative of the type of patients (or other subjects) they encounter. The development of a questionnaire needs careful attention. In general, researchers should not need to develop a new data collection instrument if a validated instrument already exists. There are several excellent textbooks that critique existing generic, diseasespecific and health-related quality of life measurement scales [4–6]. Scaling methods are widely used in healthcare research, to assess, for example, pain, mood, satisfaction and functional capacity. Commonly used scales include visual analogue scales (VAS), Likert scales (measurement of level of agreement or disagreement), numerical rating scales (e.g. mark between 0 and 10) and semantic differential scales [7]. Rating scales generally include between five to seven items, an odd number providing a neutral or central position whereas an even number of options forces direction of attitude (e.g. strongly agree ⁄ agree ⁄ disagree ⁄ strongly disagree). Visual analogue scales are often used to record subjective pain intensity. Although validation studies report good correlation between visual analogue pain scales and verbal pain rating scales, a single VAS item will be less reliable than more detailed assessment scales [8]. Single item analogue scales are not recommended for assessment of change over time and are thus not suited for use in repeated surveys. Essential stages for developing a new questionnaire include deciding on the data for collection, selection of items to be included, and the design and wording of individual questions. Questions should be as unambiguous, simple and straightforward as possible. Fundamental considerations include logical Anaesthesia, 2002, 57, pages 1049–1051 .