数据科学教育为居民,研究人员和学生在精神病学和心理学:程序开发和评估研究研究
Hayoung K Donnelly1,2, David Mandell1, Sy Hwang2
1Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.
JMIR medical education
|January 16, 2026
概括
一个虚拟研讨会显著提高了心理健康学员对人工智能 (AI) 和自然语言处理 (NLP) 进行自杀预防研究的信心. 参与者在数据分析和编码方面表现出更好的技能,提高了他们的研究能力.
科学领域:
- 行为健康科学 行为健康科学
- 精神病学中的数据科学
- 计算心理学 计算心理学
背景情况:
- 人工智能 (AI) 在行为健康中的采用正在增长,但心理健康专业人员缺乏足够的培训.
- 对临床医生来说,人工智能教育对于实施人工智能工具,与数据科学家合作以及发展跨学科研究技能至关重要.
- 人工智能培训的缺乏阻碍了先进分析在临床实践和研究中的整合.
研究的目的:
- 为精神病学和心理学学员开发,实施和评估关于人工智能在自杀预防研究中的应用的虚拟研讨会.
- 为训练员提供自然语言处理 (NLP) 和用于心理健康数据分析的Python编码的基础知识.
- 评估研讨会对实习生对数据科学自杀预防的信心和技能的影响.
主要方法:
- 进行了为期3小时的虚拟研讨会,涵盖NLP概念 (数据表征,标准化,概念提取) 和使用Azure Databricks上的Jupyter笔记本使用Python编码.
- 处理了电子健康记录首席投诉,以证明现实世界NLP应用在分析人口统计学中与自杀有关的遭遇.
- 使用了柯克帕特里克计划评估模型,通过研讨会前后的信心调查和开放式反来评估参与者的反应 (一级) 和学习成果 (二级).
主要成果:
- 10名精神病学和心理学学员参加了这次研讨会,他们认为这次研讨会很有帮助 (平均值为3.17/4).
- 在NLP知识 (P=.002) 和编码能力 (P=.01) 中观察到信心显著增加.
- 研讨会后的信心分数在NLP知识和编码技能方面都大幅上升.
结论:
- 量身定制的数据科学研讨会有效地提高了学员在应用NLP进行自杀预防研究方面的信心和技能.
- 未来的研讨会将纳入高级主题,如大型语言模型,主题分析和各种数据集.
- 进一步的研究将探讨这项培训对参与者的临床实践和研究成果的影响.
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