核心心理健康数据集 (CMHDS) 方法可行性论文
Kathryn Mary Abel1,2, Auden Edwardes1, Heidi Tranter3,2
1Centre for Women's Mental Health, The University of Manchester Faculty of Biology Medicine and Health, Manchester, England, UK.
BMJ health & care informatics
|December 12, 2025
概括
将核心心理健康数据集 (CMHDS) 嵌入到身体健康研究中是可行的和可以接受的. 在身体健康研究中例行收集心理健康数据可以最大限度地减少偏见,并增强对心身联系的理解.
科学领域:
- 综合医学是一个整体的医学.
- 数字健康数字健康
- 收集临床数据的收集.
背景情况:
- 精神和身体健康之间的联系是公认的,但潜在的机制和对治疗坚持的影响研究不足.
- 在身体健康研究中常规收集心理健康数据是有限的.
- 国家卫生和护理研究院 (NIHR) 资助了核心心理健康数据集 (CMHDS) 研究.
研究的目的:
- 评估将数字核心心理健康数据集 (CMHDS) 嵌入到身体健康研究中的可行性和可接受性.
- 探索在身体健康研究环境中的精神健康数据的例行收集.
主要方法:
- 建议将核心心理健康数据集 (CMHDS) 整合到两个身体健康试验中:囊性纤维化 (CF) 护理研究和索尔福德脏研究 (SKS).
- 研究人员联系了身体健康试验的首席调查员,以嵌入CMHDS工具.
- 收集了关于参与者协议和完成率的数据.
主要成果:
- 在CF和SKS试验中,CMHDS成功嵌入了CF和SKS试验.
- 在478名受邀参与者中,88%的人同意完成CMHDS,44%的人完成了它.
- 在SKS中,完成者年轻,功能高 (eGFR),来自较不贫困地区;在CF研究中没有发现显著差异.
结论:
- 将CMHDS嵌入身体健康研究中,以进行例行数据收集是可行的,研究人员和参与者认为这是可以接受的.
- 未来的研究应该经常嵌入CMHDS并鼓励完成以减少偏见.
- 建议在身体健康研究中优化心理健康共变量的使用.
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