- Bias is the systematic distortion of the estimated intervention effect away from the “truth”, caused by inadequacies in the design, conduct, or analysis of a trial
- cannot be reduced by sample size (which reduces the effects of chance/ random variation and improves the precision, but not the accuracy of a trial)
- Systematic bias makes a study inaccurate i.e. lacking internal validity
Bias can affect any stage of the clinical research process:
- in reading-up on the field
- in specifying and selecting the study sample
- in executing the experimental manoeuvre (or exposure)
- in measuring exposures and outcomes
- in analyzing the data
- in interpreting the analysis, and
- in publishing the results
Over 50 types of bias affecting clinical research have been described.
MAJOR TYPES OF BIAS
- Occurs when the selection of subjects into a sample or their allocation to a treatment group produces a sample that is not representative of the population, or treatment groups that are systematically different
- prevented by random selection and random allocation
- Occurs when observations in one group are not sought as diligently as in the other
- prevented by observer blinding
- Occurs when the observer is able to be subjective about the outcome
- prevented by observer blinding and outcome measure design
- Occurs when patients know which group they have been allocated to, which influences the way they report past history and symptoms
- ie. if patient knows the are in the placebo group they may exaggerate their ‘untreated’ symptoms
- prevented by patient blinding
- Occurs when patients who enroll in a trial may not represent those of the population as a whole
- ie. the obese patients who enroll in a weight loss medication trial may be more motivated than those in the general population
- prevention -> random sampling from population
- Occurs because negative studies less likely to be submitted and/or published than positive ones
- prevented by clinical trials registries and ensuring all well conducted studies are submitted and published (should be mandatory)
- in meta-analysis, the possibility of absent negative studies should be sought for by funnel plot analysis
Regression to the mean
- Occurs when random effects may cause a rare, extreme variation on a measurement
- if the measurement is repeated, the likelihood is that the measurement will be less extreme
- thus, if a treatment had been given after the first measurement, it would erroneously appear, on the basis of the second measurement, that it had had an effect
- prevented by having a control group
- Occurs when the process of studying and following up patients itself influences the outcome
- ie. chronic headache may improve in patients who are being studied and regularly followed up
- prevented by having a control group and masking the intention of study from patients and observers
References and Links
- CCC — Interpretative biases
- Sackett, D. L. (1979). Bias in analytic research. Journal of Chronic Diseases 32 (1–2): 51–63. PMID: 447779.
Chris is an Intensivist and ECMO specialist at the Alfred ICU in Melbourne. He is also the Innovation Lead for the Australian Centre for Health Innovation at Alfred Health, a Clinical Adjunct Associate Professor at Monash University, and the Chair of the Australian and New Zealand Intensive Care Society (ANZICS) Education Committee. He is a co-founder of the Australia and New Zealand Clinician Educator Network (ANZCEN) and is the Lead for the ANZCEN Clinician Educator Incubator programme. He is on the Board of Directors for the Intensive Care Foundation and is a First Part Examiner for the College of Intensive Care Medicine. He is an internationally recognised Clinician Educator with a passion for helping clinicians learn and for improving the clinical performance of individuals and collectives.
After finishing his medical degree at the University of Auckland, he continued post-graduate training in New Zealand as well as Australia’s Northern Territory, Perth and Melbourne. He has completed fellowship training in both intensive care medicine and emergency medicine, as well as post-graduate training in biochemistry, clinical toxicology, clinical epidemiology, and health professional education.
He is actively involved in in using translational simulation to improve patient care and the design of processes and systems at Alfred Health. He coordinates the Alfred ICU’s education and simulation programmes and runs the unit’s education website, INTENSIVE. He created the ‘Critically Ill Airway’ course and teaches on numerous courses around the world. He is one of the founders of the FOAM movement (Free Open-Access Medical education) and is co-creator of LITFL.com, the RAGE podcast, the Resuscitology course, and the SMACC conference.
His one great achievement is being the father of two amazing children.
On Twitter, he is @precordialthump.