Steven Moustafa Kassem

Mitigating Researcher Bias

Steven Moustafa Kassem

Thank you!

unknown or unacknowledged error

created during the design,

measurement, sampling, procedure, or

choice of problem studied

What is Bias?

◦ bias is so pervasive because we want to confirm our beliefs

◦ science is organized around proving itself wrong not right

◦ key difference between qualitative and quantitative research is attempts to eliminate bias by quantitative researcher explicit acknowledgement of bias by qualitative

researchers

The Role of Bias in Science

when the study fails to identify the validity problems  

when publicity about the research fails to incorporate the researchers cautions

Design Bias

selecting the most or least of anything creates a regression effect

Design Bias 1: Regression Effect

selecting the lowest functioning mentally ill people to study the effects of a therapy program

selecting the poorest people to study the effects of an anti-poverty program    

selecting chronic homeless to study the effects of a housing program    

Unless your report addresses the problem of regression, it will be a biased report

Study Dropouts may be the ones who needed it most

People also drop out when the program works

Design Bias 2: Attrition effect

Occurs when researcher fails to control for the effects of data collection and measurement

using self report is often biased by social desirability

most clinical research is highly vulnerable to measurement bias

when the person perceives there is something to lose by their answer

Measurement Bias

Differential Bias occurs when one group of study participants is more likely to be misclassified than the other

Misclassification of exposure is non-differential if it is similar among cases and controls i.e. the exposure (mis)classification is not related to the person's disease status

Interviewer bias happens when interviewers ask questions differently in case-control or cohort studies

a histopathologist may be more likely to report on a biopsy specimen as mesothelioma if a history of asbestos exposure is reported (biased follow-up)

Salmonella cases may be more likely to remember exactly what they ate than controls, since they may already have suspected a particular food (recall bias)

Types of Measurement Bias

Occurs when we administer the research interview or questionnaire under adverse conditions

Poor layout, obligatory participation, uncomfortable settings, etc…

Procedural Bias

only cases within a limited range of a disease spectrum are included.

This more commonly occurs with more obvious or advanced disease.

For example, in a study investigating the ability of MR imaging to depict cirrhosis, if only advanced clinical cases are included the sensitivity will be overestimated.

Disease Spectrum Bias

occurs when individual preferences or local practices determine which subjects undergo a certain treatment or imaging study

New treatments or imaging studies that have not been universally accepted into clinical practice are particularly prone to this type of bias.

Referral Bias

Exists when study subjects are self-selected for enrollment for treatment or

imaging

Differences may exist between those who volunteer and those who refuse participation

Volunteers may be more health conscious or even healthier than the general population

Self-Selection Bias

may arise in studies in which subjects are interviewed by an investigator who is also involved in the interpretation of a test result or determination of disease classification.

The investigator may inadvertently “coach” subjects or selectively review entire medical records

Interviewer Bias

results when additional factors or variables are associated with exposure and disease status

Common confounding variables are age and sex

Stratification (separation based on variables) is a common method to address confounding in the analysis phase

Confounding

journals tend to publish studies with positive results or better-quality study designs

does not arise within a given single study but can be seen in a review and analysis of the literature, as in a meta-analysis

leads to overly optimistic results or inflated associations

Publication Bias

retained knowledge of the results of one study influences the interpretation of the second study, potentially leading to a more accurate reading or diagnosis

learning-curve phenomenon

Reader-Order Bias

study subjects are randomly allocated to receive one or other of the alternative treatments under study.

Methods include allocation concealment and blinding

Mitigating Biases #1:Randomization

Allows for consideration of time factors

i.e.: differences in patients who visit an emergency room in the morning versus those who visit during the night

Mitigating Biases #2:Consecutive recruitment

Information such as pertinent test results, demographic data, or disease status, which may affect an investigator's test interpretation or assessment of an outcome, is not available to the investigator

A double-blinded study refers to one in which both the investigator and study subject are blinded to group assignment

Mitigating Biases #3:Blinding

Good Intentions

Mitigating Biases #4: