From numerical to empathy: the dual impact of psychological contracts in doctor-patient communication

To investigate how the presence or absence of psychological contracts and different formats of probabilistic data representation influence healthcare professionals' pain empathy and probability estimation bias in simulated doctor-patient communication contexts. We included 60 healthcare profess...

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Bibliographic Details
Published in:Frontiers in psychiatry Vol. 16; p. 1530932
Main Authors: Wang, Xinru, Chen, Yating, Yu, Yi, Jiang, Huan, Song, Jinyan, Liang, Weixian, Zhou, Qiang, Ying, Liang
Format: Journal Article
Language:English
Published: Switzerland Frontiers Media S.A 2025
Subjects:
doctor-patient relationship
empathy
pain
probability estimation bias
psychological contracts
empathy
pain
doctor-patient relationship
psychological contracts
probability estimation bias
ISSN:1664-0640, 1664-0640
Online Access:Get full text
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Summary:To investigate how the presence or absence of psychological contracts and different formats of probabilistic data representation influence healthcare professionals' pain empathy and probability estimation bias in simulated doctor-patient communication contexts. We included 60 healthcare professionals with the same mathematical ability and divided them into two groups to complete the probability estimation bias task of decision events and the classification task of pain non-pain pictures with and without psychological contracts. The data are analyzed by generalized estimation equation (Gee). The fulfillment of psychological contracts significantly affects the level of empathy for pain[0.3(95% CI 0.1, 0.4), 0.001], and the probability bias of decision events with an impact of [19.2 (95% CI 8.5, 29.8), 0.001] in small probability events and [-21.2 (95% CI -41.7, -0.5), <0.05] in large probability events. The establishment of psychological contract reduced the difference between the different data representation forms, significantly improved the pain empathy of the healthcare professionals, and reduced the probability estimation bias of risk decision events.
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ISSN:1664-0640
1664-0640
DOI:10.3389/fpsyt.2025.1530932