DEBIASING MEDICAL JUDGMENTS AND DECISION-MAKING – A SYSTEMATIC REVIEW
Method(s): A systematic search of 14 electronic databases was complemented by hand search and resulted in 2143 abstracts eligible for screening. Of those, 55 articles reporting 67 relevant experiments tested the effectiveness of a debiasing strategy and thus met the predefined inclusion criteria. Two reviewers independently performed the screening procedure, data extraction, and quality appraisal using the QATSDD tool, whereby all inconsistencies were resolved through discussion.
Result(s): Of 55 reviewed articles, 58.2% (n=32) explicitly referred to “debiasing”. However, 25.0% (n=8) of these studies did not clarify the term’s meaning. Most experiments intended to debias optimism bias (n=24), followed by framing effects (n=10), and a biased statistical reasoning such as denominator neglect (n=13). Lay people, as opposed to health care professionals, were in 82.1% (n=55) of cases the target of debiasing efforts. Applying the categorization of Larrick (2004), the majority of studies employed a cognitive (n=30) or technological (n=21) debiasing strategy aiming at an alteration of participants’ way of thinking or the design of a more decision-friendly information environment, respectively. Methodological quality ranged from 31.0 to 92.9% (mean: 70.6%). The quality appraisal identified a lack of pilot-testing of experimental materials, insufficient reporting of sample size considerations, and the use of non-representative samples such as undergraduate students as main methodological limitations. Overall, 65.7% (n=44) of the debiasing strategies were found to be completely (n=27) or partially (n=17) successful.
Conclusion(s): In the past, debiasing was considered to be effortful and with only little prospects of success. Yet, the rise of novel technologies and the growing importance of informed decision-making and its accompanying tools such as decision aids seem to have sparked the new development of innovative debiasing strategies with a high success rate. Future debiasing studies could benefit from a stronger tie to the existing evidence-base and a consistent application of the underlying theoretical concepts including their terminology.
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