使用人工智能的对话评估与抑郁症尺度一样临床有用,用户更喜欢使用它
Rachel L Weisenburger1, Michael C Mullarkey2, Jocelyn Labrada2
1Department of Psychology and Institute for Mental Health Research, The University of Texas at Austin, United States of America.
Journal of affective disorders
|January 30, 2024
概括
人工智能 (AI) 准确地预测了机器人管理的采访中从口头反应中预测抑郁症的严重程度. 这种人工智能心理健康查工具没有偏见,性能与自我报告措施相当.
科学领域:
- 心理健康 心理健康
- 人工智能的人工智能
- 数字健康数字健康
背景情况:
- 抑郁症是一种广泛的慢性疾病,由于查机会有限,往往无法诊断.
- 分析口语反应的人工智能 (AI) 模型为高效和可访问的抑郁症查提供了潜在的解决方案.
研究的目的:
- 通过使用多样化的样本在机器人管理的采访中验证先前训练的AI模型.
- 评估人工智能模型对与年龄,性别,种族和种族相关的算法偏见的评估.
主要方法:
- 成年人 (N=393) 通过Aiberry应用完成了机器人管理的面试和抑郁症自我报告.
- 一个人工智能模型从采访回复中预测了抑郁症得分.
- 临床医生审查了AI预测和自我报告之间的差异.
主要成果:
- 在AI预测和自我报告得分 (r=0.73) 之间发现了强大的并发有效性.
- 在90%的病例中,人工智能预测与自我报告或临床判断一致.
- 在人口群体 (年龄,性别,种族,种族) 中没有观察到差异化的模型性能.
结论:
- 人工智能模型通过远程口语响应准确预测抑郁症的严重程度.
- 人工智能显示出作为心理健康查工具的前景,与自我报告措施相提并论.
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