Recall bias is most commonly associated with which study design:
Correct Answer: Case control study
Description: Case control study Recall bias is associated with Case-control studies. Park writes- "When cases and controls are asked questions about their past history, it may be more likely for the cases to recall the existence of ceain events or factors than the controls who are healthy persons. For example, those who have had a myocardial infarction might be more likely to remember and recall ceain habits or events than those who have not. Thus cases may have a different recall of past events than controls" Recall bias is an error due to the differences in accuracy or completeness of recall to memory of past events or experiences. As a hypothetical example, suppose one is studying the possible relationship of congenital malformations to prenatal infections. A case-control study is conducted and interview is done of mothers of children with congenital malformations (cases) and mothers of children without malformations (controls). Each mother is questioned about infections she may have had during the pregnancy. A mother who has had a child with a bih defect tries to identify some unusual event that occurred during her pregnancy with that child. She wants to know whether the abnormality was caused by something she did. Why did it happen? Such a mother may even recall an event, such as a mild respiratory infection, that a mother of a child without a bih defect may not even notice or may have forgotten completely. This type of bias is known as recall bias. Bias is said to have occurred when there is a systematic difference between the results from a study and the true state of affairs. Bias may be introduced at all stages of the research process, from study design, through to analysis and publication. Bias can create a spurious association (i.e. overestimation of an effect) or mask a real one (underestimation of an effect). While appropriate statistical methods can reduce the effect of bias, they may not be able to eliminate it entirely. Innumerable number of bias have been listed. Bias associated with coho study: Selection Confounding Interviewer's bias Bias associated with Case-control study: Selection Confounding Recall bias Berkesonian bias Interviewer's bias Interviewer bias is a type of information bias that arises when an interviewer consciously or unconsciously elicits inaccurate information from study subjects. Interviewer bias can result in differential error, which can seriously disto disease-exposure associations, if the interviewer is aware of the disease status and exposure hypothesis in a case-control study, or if the interviewer is aware of the exposure status and outcome hypothesis in a coho study. In the former case, the interviewer may probe more deeply for evidence of exposure among cases than among controls. In the latter case, the interviewer may try to elicit evidence of health effects more assiduously in exposed than in unexposed coho members. Selection bias occurs when patients included in the study are not representative of the population to which the results will be applied. Confounding bias occurs when we find a spurious association between a potential risk factor and a disease outcome or miss a real association between them because we have failed to adjust for any confounding variables. A confounding variable or confounder is an exposure variable that is related to both the outcome variable (e.g. disease) and to one or more of the other exposure variables. For example in the study of the role of alcohol in the etiology of esophageal cancer, smoking is the confounding factor because it is associated with the consumption of alcohol and it is also an independent risk factor for esophageal cancer. Thus the effects of alcohol consumption on esophageal cancer can only be determined when the influence of smoking is neutralized by matching. Berkesonian bias: It occurs when patient admission rates vary between the experimental and control groups, especially in studies that use hospitalized patients for both groups. For example, this type of bias is present when hospitalized patients with the risk factor (experimental group) are admitted at a higher rate than the control group.
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