揭示ChatGPT在总结质量深度采访方面的潜力
Mei Hui Adeline Kon1,2, Michelle Jessica Pereira2, Joseph Antonio De Castro Molina2
1National University of Ireland, Galway, Ireland.
Eye (London, England)
|November 5, 2024
概括
聊天GPT显著加快了定性数据分析,显示了与人类研究人员中等到良好的主题一致性. 这种人工智能工具在研究环境中提供了快速初步分析的潜力.
科学领域:
- 定性研究方法论的研究方法.
- 医疗保健研究中的人工智能
- 自然语言处理应用程序
背景情况:
- 定性研究往往耗时,阻碍实践者和决策者获得快速,可操作的见解.
- 数据收集,转录和分析是对定性研究资源密集性的关键贡献者.
- 像OpenAI的聊天生成预训练变压器 (ChatGPT) 这样的大型语言模型在协助数据分析方面表现有前途.
研究的目的:
- 将ChatGPT (版本3.5和4.0) 产生的主题与深入访谈数据的传统人类分析进行比较.
- 评估ChatGPT在定性数据分析中的效率和准确性.
- 评估人工智能工具在加速研究方面的潜力.
主要方法:
- 分析了社区眼科诊所一项患者体验评估研究的三个成绩单.
- 一位独立的研究人员进行了传统的主题分析.
- 不识别的成绩单被ChatGPT 3.5和4.0处理,并提供了特定的主题生成指令.
主要成果:
- 每个成绩单的ChatGPT分析时间平均为11.5分钟 (3.5) 和11.9分钟 (4.0),而人类分析时间为240分钟.
- 人类研究人员确定了六个关键主题:可访问性,患者意识,信任,期望,返回意愿和转介来源解释.
- 聊天GPT生成的主题与人类分析之间的一致性在66%至100%之间.
结论:
- 聊天GPT在定性数据分析中显著减少了时间.
- 像ChatGPT这样的AI工具提供了与人类分析的中等到良好的主题一致性,促进了快速的初步见解.
- 在定性研究中,对子题重组和最终解释仍然需要人类监督.
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