患者对精神科服务中基于机器学习的临床决策支持系统的使用信任：一项随机调查实验。

Patient trust in the use of machine learning-based clinical decision support systems in psychiatric services: A randomized survey experiment.

机构信息

Department of Affective Disorders, Aarhus University Hospital - Psychiatry, Aarhus, Denmark.

Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.

出版信息

Eur Psychiatry. 2024 Oct 25;67(1):e72. doi: 10.1192/j.eurpsy.2024.1790.

DOI:10.1192/j.eurpsy.2024.1790

PMID:39450771

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11730065/

Abstract

BACKGROUND

Clinical 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.

METHODS

We 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.

RESULTS

Out 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%], = 0.0096) and the blank control arm (mean increase in trust: 4% [1%; 8%], = 0.015). Similarly, the intervention reduced distrust in ML-based CDSS when compared to the active control (mean decrease in distrust: -3%[-1%; -5%], = 0.021) and the blank control arm (mean decrease in distrust: -4% [-1%; -8%], = 0.022). No statistically significant differences were observed between the active and the blank control arms.

CONCLUSIONS

Receiving basic information on ML-based CDSS in hospital psychiatry may increase patient trust in such systems.

摘要

背景

基于机器学习 (ML) 模型的临床决策支持系统 (CDSS) 在精神病学领域中逐渐兴起。如果患者不信任该技术，其实施可能会破坏医患关系。因此，本研究旨在探讨提供有关基于 ML 的 CDSS 的基本信息是否会增加患者对其的信任。

方法

我们在丹麦中部地区的精神科服务中进行了一项在线随机调查实验。参与患者被随机分为三组：干预组 = 接受关于基于 ML 模型的临床决策支持的信息；主动对照组 = 接受关于标准临床决策过程的信息；空白对照组 = 不提供任何信息。参与者对实验并不知情。随后，参与者被问及对基于 ML 的 CDSS 的信任和不信任的不同方面。通过比较分配组之间的信任和不信任评分来评估干预的效果。

结果

在 5800 名受邀者中，有 992 人完成了调查实验。与主动对照组相比，干预组增加了对基于 ML 的 CDSS 的信任（信任平均增加：5% [95% CI：1%；9%]， = 0.0096），也增加了对空白对照组的信任（信任平均增加：4% [1%；8%]， = 0.015）。同样，与主动对照组相比，干预组减少了对基于 ML 的 CDSS 的不信任（不信任平均减少：-3%[-1%；-5%]， = 0.021），也减少了对空白对照组的不信任（不信任平均减少：-4% [-1%；-8%]， = 0.022）。主动对照组和空白对照组之间没有观察到统计学上的显著差异。