探索年轻成年人对喘药物管理的经验和信仰:试点定性研究比较人类和多个AI的主题分析
Ruth Ndarake Jeminiwa1, Caroline Popielaski2, Amber King1
1Department of Pharmacy Practice, Jefferson College of Pharmacy, Thomas Jefferson University, 901 Walnut Street, Philadelphia, PA, 19107, United States, 1 2159551159.
JMIR formative research
|August 15, 2025
概括
患有喘的年轻人需要全面的支持,以便更好地自我管理. 人工智能 (AI) 在分析定性数据以确定患者需求方面表现有前途,有助于开发有效的喘干预措施.
科学领域:
- 健康行为和自我管理
- 数字健康干预措施 数字健康干预措施
- 定性研究方法的方法论.
背景情况:
- 年轻成年人 (18-29岁) 对喘维持药物 (≤67%) 的坚持率低于最佳水平.
- 了解他们的独特需求对于有针对性的干预来改善喘自我管理至关重要.
- 人工智能 (AI) 可能有助于分析定性数据以识别模式,尽管支持文献有限.
研究的目的:
- 通过试点可行性研究,探索患有喘的年轻成年人的药物管理需求.
- 确定帮助患有喘的年轻人自我管理的最佳方法.
- 评估数字健康干预的实用性,并将人工智能驱动的专题分析与人类分析进行比较.
主要方法:
- 来自一个大都会大学的4名患有喘 (使用吸入性皮质类固醇) 的年轻成年人 (18-29岁) 的有目的采样.
- 通过电话会议进行半结构化采访,字面记录和转录.
- 采用了主题分析,将人类编码 (NVivo 14) 与人工智能平台 (Gemini,Copilot,ChatGPT) 进行比较.
主要成果:
- 人类分析确定了4个关键主题:临床医生支持,社会支持,数字自我管理支持和教育支持.
- 人工智能平台产生了类似的主题,尽管有不同的标签,但基本概念的重叠程度很高.
- 人工智能平台显示了主题分析的潜力,产生了与人类分析相似的结果.
结论:
- 需要采用整体方法来解决患有喘的年轻成年人的多方面的需求.
- 解决确定的需求可以改善药物坚持和健康结果,以健康信念模型为指导.
- 在仔细考虑的情况下,人工智能可以成为健康研究中定性数据分析的宝贵工具.
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