Senior Tutor CEBM
University of Oxford
Carl Heneghan Professor of Evidence-Based Medicine & Director CEBM
University of Oxford
any. I volunteer for this task, would welcome collaboration, and
would appreciate receiving nominations and examples of
additional biases.
conclusions about treatment effects that
are systematically different from the truth.
“It thus seems that in situations when bias is
likely the size of such bias is unpredictable.”
Empirical evidence of bias in treatment effect estimates in controlled
trials with different interventions and outcomes: meta-epidemiological
study BMJ 2008; 336
Bias enters health studies at all stages and often influences the
magnitude and direction of results. To obtain the least biased
information, researchers must acknowledge the potential presence
of biases and take steps to avoid and minimise their effects.
Equally, in assessing the results of studies, we must be aware of
the different types of biases, their potential impact and how this
affects interpretation and use of evidence in health care decision
making.
The aim of our EBM for under 18s work is to:
1) To equip the next generation with the critical thinking skills to make
informed healthcare choices;
2) To emphasise opportunities to teach critical thinking using health claims,
opportunities that may be lost in the need to stress factual knowledge in such
topics.
Detection bias (5,027)
Ascertainment bias (3,528)
Perception bias (2,584)
bias, n. /bs/ A systematic distortion, due to a design problem, an interfering
factor, or a judgement, that can affect the conception, design, or conduct of a
study, or the collection, analysis, interpretation, presentation, or discussion of
outcome data, causing erroneous overestimation or underestimation of the
probable size of an effect or association [ancient Greek πικρσιος, crosswise,
esp. at right angles, via French biais]
@Catalogofbias
#catalogofbias
www.catalogofbias.org
Want to help?