通过交叉镜头的数字心理健康:叙述性审查
Rose Yesha1,2, Max C E Orezzoli3, Kimberly Sims4,5
1MedStar Health Research Institute, Columbia, MD 21044, USA.
Healthcare (Basel, Switzerland)
|January 28, 2026
概括
使用人工智能 (AI) 的数字心理健康应用程序 (DMHA) 可以改善护理,但风险偏差. 一个交叉框架突出了文化响应的策略,以确保对边缘化群体的精神卫生保健中公平的AI.
科学领域:
- 数字心理健康数字心理健康
- 医疗保健中的人工智能
- 卫生公平性健康公平性
背景情况:
- 面临边缘化的精神疾病患者经历了复杂的歧视和不充分的照顾.
- 数字心理健康应用 (DMHA) 利用人工智能和机器学习,但可能会延续偏见.
- DMHA中的算法偏差加剧了面临风险的边缘化群体的不平等.
研究的目的:
- 通过交叉框架分析数字心理健康的当前文献.
- 确定在精神卫生保健中为公平的人工智能提供文化响应策略.
- 解决边缘化个体所面临的不成比例的心理健康挑战.
主要方法:
- 叙事文学评论. 叙事文学评论. 叙事文学评论. 叙事文学评论.
- 应用一个交叉框架来分析数字心理健康.
- 评估人工智能培训模型及其对边缘化群体的代表性.
主要成果:
- 德马哈可以识别痛苦和弹性标记,但有算法偏差的风险.
- 边缘化的人群面临着文化上有能力的数字心理健康护理的重大障碍.
- 一个交叉的方法揭示了需要人工智能模型反映不同的生活经验.
结论:
- 公平的数字心理健康解决方案需要代表边缘化社区的AI培训数据.
- 文化响应策略对于减轻DMHA中偏见,伤害和排斥至关重要.
- 将生活经验纳入人工智能开发促进了公平,并改善了所有人的结果.
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