| Types of Bias |
| Bias | Description | Mitigation |
| Accumulation Effect | patients sometimes must be exposed to a risk factor for a prolonged period of time before they develop a clinically detectable resulte.g., patients must smoke for many pack-years before bronchogenic carcinoma develops | try to follow study participants for as long as is feasible |
| Confounding | a third factor is either positively or negatively associated with both the exposure and outcome confounders are not in the causal pathwayif not adjusted for can distort true association either towards or away from the null hypothesis | randomization ensures similar baseline characteristics between control and exposure/experimental groupsuse intention-to-treat analysis to preserve randomization even if participants change study treatments matchinggroup similar participants into study pairsstratificationanalyze in separate subgroups determined by a potential confounderrestrictiononly include groups with specific features in the sampleadjustmentcan only adjust for confounders that are known and measureablecrossover studies subject acts as own control |
| Selection Bias | sampled population is not representative of the population researchers are trying to study due to non-random selection of study participantssampling (ascertainment) biascertain individuals are more or less likely to be selected for a study group, leading to incorrect conclusionsnon-response biase.g., participants who pick up the phone may be less sick than participants who don’thealthy worker effectsamples with employed subjects only may be healthiervolunteer biaspeople who volunteer for a study may be different in some fundamental way from those who do not volunteerlate-look biaspatients with severe disease are less likely to be studied, because they die or are otherwise unavailable, making a disease look less severee.g., a group of HIV+ individuals are all asymptomaticalso can have opposite effecte.g., people with more mild disease are cured before the study takes place and only persistently sick folks are included in the study, making a disease seem more severeBerkson biashospitalized study subjects are more likely to have a greater burden of illness than other possible subjectsattrition biasthose lost to follow-up may be different from those who remain in the study | randomizationinclude patients in multiple settings (outpatient, hospitalized)study designs that are longitudinal in nature rather than cross-sectionalgather maximal information on participants |
| Measurement Bias | information is gathered in a way that distorts the information or misclassifies study participants interviewer biassubjects in one group are interviewed in a different way than anotherdifferences due to interviewing style disrepencies are falsely attributed to group differences | standardize data collection |
| Recall Bias | subjects with the disease are more likely to recall the exposure of interest e.g., parents of children with cancer recall exposure to a chemical | reducing follow-up time in retrospective studies |
| Performance Bias | researchers treat groups differently or subjects alter their behavior/responses due to study group awarenessHawthorne effect subjects alter their behavior when they know they are being studied procedure biasresearcher decides assigment of treatment versus control and assigns particular patients to one group or the other nonrandomlypatient decides assigment of treatment versus control | blinding |
| Lead-Time Bias | subjects appear to survive longer when in reality their disease was detected earliercommon with improved screening e.g., a cancer screening test is deemed to increase survival when in reality the disease was picked up earlier, increasing the time from detection to death | use mortality rate instead of survival time in screening studiesestimate lead time and add that to survival in unscreened group |
| Design Bias | the control group is inappropriately non-comparable to the intervention groupallocation biasdifference in the way participants are placed in control versus experimental groupse.g., all zebras in control group and all lions in exposure group | randomizationmatching |
| Cognitive Bias | observer bias (pygmalion effect) investigator inadvertently conveys her high expectations to subjects, who then produce the expected resulta “self-fulfilling prophecy”golem effect is the opposite: study subjects decrease their performance to meet low expectations of investigatorconfirmation biasresearcher ignores results that do not support their hypothesisresponse biasparticipants do not respond accurately because they are concerned about the social desirability of their responses or misinterpret the question | double blindinginclude positive and negative results |
| Surveillance Bias | outcomes are more likely to be detected in certain groups because of increased monitoringe.g., a certain skin disease being detected more often in hypertensive patients because they have more physician visits than non-hypertensive patientsresearchers may falsely attribute hypertension to causing the skin disease |
match participants on similar likelihood of surveillance |
