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Cognitive biases associated with medical decisions: a systematic review

Overview of attention for article published in BMC Medical Informatics and Decision Making, November 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#3 of 2,165)
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

news
7 news outlets
blogs
1 blog
policy
1 policy source
twitter
186 X users
facebook
3 Facebook pages
wikipedia
1 Wikipedia page

Citations

dimensions_citation
626 Dimensions

Readers on

mendeley
1029 Mendeley
citeulike
1 CiteULike
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Title
Cognitive biases associated with medical decisions: a systematic review
Published in
BMC Medical Informatics and Decision Making, November 2016
DOI 10.1186/s12911-016-0377-1
Pubmed ID
Authors

Gustavo Saposnik, Donald Redelmeier, Christian C. Ruff, Philippe N. Tobler

Abstract

Cognitive biases and personality traits (aversion to risk or ambiguity) may lead to diagnostic inaccuracies and medical errors resulting in mismanagement or inadequate utilization of resources. We conducted a systematic review with four objectives: 1) to identify the most common cognitive biases, 2) to evaluate the influence of cognitive biases on diagnostic accuracy or management errors, 3) to determine their impact on patient outcomes, and 4) to identify literature gaps. We searched MEDLINE and the Cochrane Library databases for relevant articles on cognitive biases from 1980 to May 2015. We included studies conducted in physicians that evaluated at least one cognitive factor using case-vignettes or real scenarios and reported an associated outcome written in English. Data quality was assessed by the Newcastle-Ottawa scale. Among 114 publications, 20 studies comprising 6810 physicians met the inclusion criteria. Nineteen cognitive biases were identified. All studies found at least one cognitive bias or personality trait to affect physicians. Overconfidence, lower tolerance to risk, the anchoring effect, and information and availability biases were associated with diagnostic inaccuracies in 36.5 to 77 % of case-scenarios. Five out of seven (71.4 %) studies showed an association between cognitive biases and therapeutic or management errors. Of two (10 %) studies evaluating the impact of cognitive biases or personality traits on patient outcomes, only one showed that higher tolerance to ambiguity was associated with increased medical complications (9.7 % vs 6.5 %; p = .004). Most studies (60 %) targeted cognitive biases in diagnostic tasks, fewer focused on treatment or management (35 %) and on prognosis (10 %). Literature gaps include potentially relevant biases (e.g. aggregate bias, feedback sanction, hindsight bias) not investigated in the included studies. Moreover, only five (25 %) studies used clinical guidelines as the framework to determine diagnostic or treatment errors. Most studies (n = 12, 60 %) were classified as low quality. Overconfidence, the anchoring effect, information and availability bias, and tolerance to risk may be associated with diagnostic inaccuracies or suboptimal management. More comprehensive studies are needed to determine the prevalence of cognitive biases and personality traits and their potential impact on physicians' decisions, medical errors, and patient outcomes.

X Demographics

X Demographics

The data shown below were collected from the profiles of 186 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1,029 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 <1%
United Kingdom 1 <1%
France 1 <1%
Unknown 1024 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 122 12%
Student > Bachelor 121 12%
Student > Ph. D. Student 110 11%
Researcher 98 10%
Other 80 8%
Other 245 24%
Unknown 253 25%
Readers by discipline Count As %
Medicine and Dentistry 328 32%
Psychology 105 10%
Nursing and Health Professions 73 7%
Social Sciences 44 4%
Computer Science 27 3%
Other 160 16%
Unknown 292 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 178. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 April 2024.
All research outputs
#231,492
of 25,820,938 outputs
Outputs from BMC Medical Informatics and Decision Making
#3
of 2,165 outputs
Outputs of similar age
#4,460
of 318,761 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#1
of 25 outputs
Altmetric has tracked 25,820,938 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,165 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 99% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 318,761 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.