人工智能在系统文献评论中的引入和采用:一个离散选择实验
Seye Abogunrin1, Bart P H Slob2, Marie Lane1
1F. Hoffmann-La Roche, Basel, Switzerland.
BMJ open
|October 15, 2025
概括
人工智能 (AI) 工具可以帮助系统文献审查 (SLR),但采用不仅仅取决于减少工作负载. 具有中度熟练程度需求和高灵敏度的用户友好型AI是评审者接受的关键.
科学领域:
- 健康研究方法的方法论.
- 在研究中的人工智能.
- 系统的文献评论 系统的文献评论
背景情况:
- 系统性文献审查 (SLR) 对于证据综合至关重要,但资源密集.
- 人工智能 (AI) 提供了简化SLR流程的潜力,特别是选.
- 了解SLR中AI工具的用户偏好对于有效实施至关重要.
研究的目的:
- 调查SLR专业人员对AI工具属性的偏好.
- 确定影响人工智能在SLR选中的权衡因素.
- 确定影响AI工具在系统审查中使用可能性的因素.
主要方法:
- 一个离散选择实验 (DCE) 涉及187名参与者,他们执行SLR.
- 参与者评估了具有不同属性的假设人工智能工具:选中的作用,所需的熟练程度,灵敏度,工作量减少和培训投资.
- 使用条件多项逻辑的统计分析,包括人口相互作用.
主要成果:
- 中级人工智能熟练程度和显著的工作量减少与人工智能工具采用有积极的相关性.
- 对人工智能工具的高水平要求降低了经验丰富的作者采用的可能性.
- 更多的SLR出版物的经验增加了人工智能采用的可能性.
结论:
- 仅仅减少工作量并不能保证SLR中采用AI;工具的可靠性和用户友好性至关重要.
- 人工智能工具更有可能被采用,这些工具协助而不是取代人类审稿人,具有适度的熟练要求和高灵敏度.
- 未来的SLR人工智能开发应该专注于平衡效率与用户需求和专业知识水平.
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