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Information Distortion in Physicians’ Diagnostic Judgments

Author

Listed:
  • Olga Kostopoulou
  • J. Edward Russo
  • Greg Keenan
  • Brendan C. Delaney
  • Abdel Douiri

Abstract

Background: Information distortion suggests that people change the evaluation of new information to support an emerging belief. The present study was designed to measure the extent to which physicians distort incoming medical information to support an emerging diagnosis. Design: Data were collected via an anonymous questionnaire. The experimental group (102 physicians) read 3 patient scenarios, each with 2 competing diagnoses. Physicians first read information that favored 1 of the 2 diagnoses (the “steer†). They then rated a series of neutral cues that favored neither diagnosis. At each cue presentation, respondents rated the extent to which cues favored either diagnosis and updated the strength of their diagnostic belief. After the neutral cues in the third scenario, respondents rated cues that opposed the initial steer. A control group (36 physicians) rated all the cues in random order and not within scenarios, thus providing unbiased baseline ratings for calculating distortion in the experimental group. Results: Distortion was statistically significant ( P

Suggested Citation

  • Olga Kostopoulou & J. Edward Russo & Greg Keenan & Brendan C. Delaney & Abdel Douiri, 2012. "Information Distortion in Physicians’ Diagnostic Judgments," Medical Decision Making, , vol. 32(6), pages 831-839, November.
    • Handle: RePEc:sae:medema:v:32:y:2012:i:6:p:831-839
    DOI: 10.1177/0272989X12447241
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    References listed on IDEAS

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    1. J. Edward Russo & Margaret G. Meloy & T. Jeffrey Wilks, 2000. "Predecisional Distortion of Information by Auditors and Salespersons," Management Science, INFORMS, vol. 46(1), pages 13-27, January.
    2. repec:cup:judgdm:v:4:y:2009:i:5:p:408-418 is not listed on IDEAS
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    1. J. Edward Russo, 2020. "A cognitive science perspective on historical narratives and future scenarios: Commentary on Schoemaker 2020," Futures & Foresight Science, John Wiley & Sons, vol. 2(3-4), September.
    2. Joseph Edward Russo, 2021. "Hidden dangers in complex computational structures: A commentary on Lustick and Tetlock 2021," Futures & Foresight Science, John Wiley & Sons, vol. 3(2), June.

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