设计用于长期的,基于应用程序的ADHD症状监测的新型自我评价仪器:混合方法开发和验证研究
Amanda Bäcker1, David Forsström1,2, Louise Hommerberg3
1Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, & Stockholm Health Care Services, Region Stockholm, Stockholm, Sweden.
Digital health
|September 26, 2024
概括
一个新的基于应用程序的工具,持续ADHD症状自我监测的mHealth尺度 (mCASS),有效地监测注意力缺陷多动症 (ADHD) 症状. 在临床医生和患者的投入下开发,它为持续的ADHD评估提供了有效和可靠的方法.
科学领域:
- 数字健康干预措施 数字健康干预措施
- 精神病学是一个精神病学.
- 神经发育障碍 神经发育障碍
背景情况:
- 常规的注意力缺陷多动症 (ADHD) 监测通常是有限的.
- 智能手机应用程序为持续的ADHD症状跟踪提供了一个可持续的解决方案.
- 利益相关者的偏好对于开发有效的移动健康工具至关重要.
研究的目的:
- 开发和验证一种基于应用程序的新型仪器,用于持续监测ADHD症状.
- 将临床医生和患者的观点纳入移动健康 (mHealth) 工具的设计.
- 评估基于应用程序的ADHD监测的心理测量特性和用户偏好.
主要方法:
- 混合方法方法涉及对13名临床医生进行定性采访.
- 连续ADHD症状自我监测 (mCASS) 的mHealth规模的代开发.
- 使用mCASS和成人多动症自我报告尺度-V1.1 (ASRS-V1.1) 对397名自我报告ADHD的个人进行了调查.
- 探索性因子分析,内部一致性和并发有效性分析.
主要成果:
- 临床医生强调内容的有效性,相关性和用户体验是关键因素.
- 12项的mCASS显示了四个因素:日常任务,生产力,休息/恢复和社交互动.
- mCASS显示了令人满意的并发有效性 (r=0.595) 和内部一致性 (α=0.826).
结论:
- mCASS是基于应用程序评估ADHD症状的有效工具,基于用户体验.
- 确定了开发针对ADHD患者的mHealth工具的关键考虑因素.
- 这项研究为未来在ADHD管理中的数字健康计划提供了宝贵的见解.
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