All epidemiological studies, even randomised clinical trials, are susceptible to bias (systematic error). The objective of the epidemiologist will be to minimise these biases. This can be done by considering, at the different stages of development and execution of a study, where and how bias may occur: the design stage (protocol writing), subject selection (case/control, exposed/unexposed, intervention/control group etc), data collection, data analysis and interpretation of results.
At the design stage, bias should be considered at the time of protocol writing. A lot of care should be given, at this stage of development of the study, to forecasting all potential selection and information biases that may be encountered. Despite all precautions taken, some biases will persist. They then need to be taken into account in the interpretation of the results of the study.
When writing the report or manuscript, sources of potential bias in the study absolutely need to be openly discussed. Particularly, the first part of the discussion section of a scientific paper should include a detailed paragraph in which authors discuss all potential biases which could have falsely led to the study results. If possible, the direction of the bias (overestimation or underestimation) and the magnitude of the bias also should be discussed.
While case-control and cohort studies are both susceptible to bias, the case-control study is affected by more sources of bias. Through our study design, we can try to minimise selection bias and prevent information bias in cohort and case-control studies.
In epidemiological studies, all efforts should be made to avoid biasing the selection of study participants. Selection bias can be reduced by paying attention to the following:
whether the randomisation has been successful or not can be checked by comparing baseline factors between the intervention and control groups afterwards, and seeing if the groups are similar in all other respects apart from receiving the intervention .
Non-response bias can be prevented by achieving high response rates (≥80% by convention) . High response rates may be facilitated by:
Information on characteristics of the non-responders should be obtained if possible e.g. by getting a subset of non-participants to complete a non-response questionnaire (NRQ), or by getting some demographic information on non-respondents, if this is possible (so that they can be compared with respondents). This can give important insights into the extent of selection bias. However, it should be noted that obtaining this information on non-respondents is time-consuming and not always successful.
Information (measurement) biases can be easier to prevent and measure than selection biases .
They can be prevented by:
Approaches taken to prevent recall bias include:
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