在精神科服务中接收有关基于机器学习的临床决策支持系统的信息增加了员工对这些系统的信任:随机调查实验
Erik Perfalk1,2, Martin Bernstorff1,2, Andreas Aalkjær Danielsen1,2
1Department of Affective Disorders, Aarhus University Hospital - Psychiatry, Aarhus, Denmark.
Acta psychiatrica Scandinavica
|February 11, 2025
概括
提供关于基于机器学习 (ML) 的临床决策支持系统的信息,增加了医疗保健工作人员的信任. 这项研究表明,对机器学习系统的培训提高了员工对这些新兴精神病学工具的信心.
科学领域:
- 精神病学是一个精神病学.
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 机器学习 (ML) 模型越来越多地用于精神病学中的临床决策支持系统 (CDSS).
- 医疗保健工作人员的信任对于成功实施这些基于ML的CDSS至关重要.
- 本研究调查了提供基于ML的CDSS信息对员工信任的影响.
研究的目的:
- 为了确定是否教育医疗保健工作人员关于基于ML的CDSS提高了他们对这些系统的信任.
- 评估信息提供对信任和不信任水平的影响.
主要方法:
- 对精神病医疗保健工作人员进行了一项随机调查实验.
- 参与者被分配到三个组:干预 (ML信息),主动控制 (标准过程信息) 或空白控制 (没有信息).
- 两组之间的信任和不信任得分使用对对比进行对比.
主要成果:
- 与活体和空白对照组相比,干预组显示出明显增强的信任和减少的不信任.
- 干预组与活跃对照组的信任增加了5%,不信任减少了4%.
- 统计学意义在所有比较中保持不变 (p < 0.05).
结论:
- 提供基于ML的CDSS的基本信息可以有效地提高医疗保健工作人员对医院精神病学中的这些系统的信任.
- 这一发现支持了改善在精神卫生保健机构采用人工智能驱动工具的战略.
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