Bias

Bias describes the situation in a trial where one outcome is systematically favoured. It should be noted that there is considerable variation in the definitions and classification of bias. The table below lists some of the more common types of bias.

Type _ Description| Selection bias _ Error in assigning individuals to groups leading to differences which may influence the outcome. Subtypes include sampling bias where the subjects are not representative of the population. This may be due to volunteer bias. An example of volunteer bias would be a study looking at the prevalence of Chlamydia in the student population. Students who are at risk of Chlamydia may be more, or less, likely to participate in the study. A similar concept is non-responder bias. If a survey on dietary habits was sent out in the post to random households it is likely that the people who didn't respond would have poorer diets than those who did. Other examples include

• loss to follow up bias
• prevalence/incidence bias (Neyman bias): when a study is investigating a condition that is characterised by early fatalities or silent cases. It results from missed cases being omitted from calculations
• admission bias (Berkson's bias): cases and controls in a hospital case control study are systematically different from one another because the combination of exposure to risk and occurrence of disease increases the likelihood of being admitted to the hospital
• healthy worker effect|

Recall bias _ Difference in the accuracy of the recollections retrieved by study participants, possibly due to whether they have disorder or not. E.g. a patient with lung cancer may search their memories more thoroughly for a history of asbestos exposure than someone in the control group. A particular problem in case-control studies.| Publication bias _ Failure to publish results from valid studies, often as they showed a negative or uninteresting result. Important in meta-analyses where studies showing negative results may be excluded.| Work-up bias (verification bias)_ In studies which compare new diagnostic tests with gold standard tests, work-up bias can be an issue. Sometimes clinicians may be reluctant to order the gold standard test unless the new test is positive, as the gold standard test may be invasive (e.g. tissue biopsy). This approach can seriously distort the results of a study, and alter values such as specificity and sensitivity. Sometimes work-up bias cannot be avoided, in these cases it must be adjusted for by the researchers.| Expectation bias (Pygmalion effect) _ Only a problem in non-blinded trials. Observers may subconsciously measure or report data in a way that favours the expected study outcome.| Hawthorne effect _ Describes a group changing it's behaviour due to the knowledge that it is being studied| Late-look bias _ Gathering information at an inappropriate time e.g. studying a fatal disease many years later when some of the patients may have died already | Procedure bias _ Occurs when subjects in different groups receive different treatment| Lead-time bias _ Occurs when two tests for a disease are compared, the new test diagnoses the disease earlier, but there is no effect on the outcome of the disease|