利益相关者对医疗保健中基于人工智能的计算机感知工具的信任标准:定性采访研究
Ansh Rai1, Meghan E Hurley1, John Herrington2
1Center for Medical Ethics and Health Policy, Baylor College of Medicine, Houston, United States.
Journal of medical Internet research
|December 12, 2025
概括
对于心理健康的计算机感知 (CP) 技术的信任不仅仅取决于性能. 诸如与信仰一致和专家认可等因素显著影响利益相关者的信任,突出潜在的偏见.
科学领域:
- 数字心理健康数字心理健康
- 人与计算机的交互
- 临床信息学 临床信息学
背景情况:
- 计算机感知 (CP) 技术分析被动传感数据以获得心理健康见解.
- 在医疗保健中成功实施CP取决于建立利益相关者的信任.
研究的目的:
- 调查青少年,护理人员,临床医生和开发人员对CP技术的信任因素.
- 确定CP工具在医疗保健环境中被认为值得信赖的条件.
主要方法:
- 进行了80次半结构面试,与各种各样的利益相关者群体 (青少年,护理人员,临床医生,开发人员) 进行了采访.
- 利用多阶段的,诱导性的主题内容分析来进行定性数据解释.
主要成果:
- 确定了五个信任的先决条件:认识体系对齐,可证明的严谨性,可解释性,对复杂性的敏感性和非替代性的角色.
- 认识论的对齐 (输出与信仰的一致性) 成为一个主导的,但潜在的偏见,信任因素.
- 通过认可观察到关系信任,但引发了对未经验证的错误应用信任的担忧.
结论:
- 对基于人工智能的CP技术的信任是由认知启发学,社会因素和认识论调整所塑造的,而不仅仅是技术性能.
- 建议对验证/监督和临床医师培训的机构框架,以减轻偏见并确保批判性评估.
- 重新校准对实际系统能力的信任对于在精神卫生保健中道德和有效的CP集成至关重要.
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