Trial reportEuropean psychiatry : the journal of the Association of European Psychiatrists2024
Patient trust in the use of machine learning-based clinical decision support systems in psychiatric services: A randomized survey experiment.
Trial report in European psychiatry : the journal of the Association of European Psychiatrists, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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4 authors.
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Abstract
backgroundClinical decision support systems (CDSS) based on machine-learning (ML) models are emerging within psychiatry. If patients do not trust this technology, its implementation may disrupt the patient-clinician relationship. Therefore, the aim was to examine whether receiving basic information about ML-based CDSS increased trust in them.
methodsWe conducted an online randomized survey experiment in the Psychiatric Services of the Central Denmark Region. The participating patients were randomized into one of three arms: Intervention = information on clinical decision-making supported by an ML model; Active control = information on a standard clinical decision process, and Blank control = no information. The participants were unaware of the experiment. Subsequently, participants were asked about different aspects of trust and distrust regarding ML-based CDSS. The effect of the intervention was assessed by comparing scores of trust and distrust between the allocation arms.
resultsOut of 5800 invitees, 992 completed the survey experiment. The intervention increased trust in ML-based CDSS when compared to the active control (mean increase in trust: 5% [95% CI: 1%; 9%],
conclusionsReceiving basic information on ML-based CDSS in hospital psychiatry may increase patient trust in such systems.
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