使用计算机辅助替代传统主题分析来识别严重抑郁症的未满足需求:与精神病医生的定性访谈研究
Michelle A Worthington1,2, Richard H Christie1, Aaron J Masino1,3
1AiCure, New York, NY, United States.
JMIR formative research
|March 1, 2024
概括
混合定性分析方法提供了一种更快的方法,可以更快地找到数字健康工具的未满足临床需求. 这种方法有助于开发实用的工具来改善患者的健康结果.
科学领域:
- 数字健康数字健康
- 定性研究是指质量研究.
- 临床需要评估评估.
背景情况:
- 开发临床相关的数字健康工具需要了解利益相关者的需求.
- 传统的定性数据分析是耗时且资源密集的.
- 需要一种时间效率高的方法来确定数字工具开发中的目标需求.
研究的目的:
- 开发一种可访问,简单和时间效率高的替代品来替代传统的定性数据主题分析.
- 从精神病学家采访中确定关键主题,用于开发针对未满足临床需求的数字工具.
主要方法:
- 进行了10次半结构化访谈,与美国精神病医生进行了治疗主要抑郁症.
- 使用混合分析方法,将计算机辅助文本分析与演分析相结合.
- 识别了词汇频率,内容类别和与护理管理中未满足需求相关的主题.
主要成果:
- 确定了临床医生在重大抑郁症治疗中感兴趣的关键领域.
- 根据确定的需求,揭示了数字工具开发的潜在目标.
结论:
- 一种混合方法 (计算机辅助 + 演) 对于识别数字工具开发的未满足需求而言是时间高效的.
- 这种方法有助于创建实用的数字工具,以改善患者的健康结果.
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