AI-Augmented Clearinghouse to Facilitate Evidence-Based Decision-Making and Social Spending: a Conceptual Framework.

IF 2.5 2区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Prevention Science Pub Date : 2026-10-01 Epub Date: 2025-10-11 DOI:10.1007/s11121-025-01848-1
Pamela R Buckley, Diana Fishbein, Neil J Wollman
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引用次数: 0

Abstract

Social spending refers to public or private funds aimed at helping vulnerable groups. Evidence-based decision-making supports social spending by applying existing evidence to inform funding and involves integrating relevant information from various sources, such as experimental studies and community feedback. Online clearinghouses support evidence-based decision-making by synthesizing evidence on what works, though manually updating literature is incomplete. In addition, passively summarizing evaluations is insufficient for end-users to implement preventive solutions that achieve population impacts. A responsive platform and a dissemination plan are needed to encourage the uptake of equitable and culturally relevant preventive interventions grounded in transparency and rigorous evidence of effectiveness. A two-part conceptual framework is proposed for a clearinghouse platform that integrates stepwise, interactive, AI-driven capabilities safeguarded by human touchpoints. First, clearinghouses should adopt a "living" review to automatically update evaluations-an approach embraced globally by organizations such as the World Health Organization, Cochrane Collaboration, and the U.N.'s Pan American Health Organization. The second component involves adding a chatbot to support assessment and implementation guidance and make recommendations on (1) the provision of all evidence-based preventive interventions (EBPIs) and their key activities, (2) EBPIs shown to achieve equitably distributed outcomes, (3) culturally relevant EBPIs that align with the values and needs of a target population, (4) implementation support, such as materials, training, and fidelity measures, and (5) delivery costs. The resulting platform will ethically expedite the translational process of identifying and scaling EBPIs, leading to a more complete, comprehensive, and accessible body of evidence on effective preventive strategies.

人工智能增强信息交换中心促进基于证据的决策和社会支出:一个概念框架。
社会支出是指旨在帮助弱势群体的公共或私人资金。以证据为基础的决策支持社会支出,方法是运用现有证据为供资提供信息,并整合来自各种来源的相关信息,如实验研究和社区反馈。在线信息交换所通过综合有效的证据来支持基于证据的决策,尽管手工更新文献是不完整的。此外,被动地总结评价不足以使最终用户执行对人口产生影响的预防性解决办法。需要一个反应迅速的平台和传播计划,以鼓励采取基于透明度和严格有效性证据的公平和与文化相关的预防性干预措施。提出了一个由两部分组成的概念框架,用于票据交换所平台,该平台集成了由人类接触点保护的逐步、交互式、人工智能驱动的功能。首先,信息交换中心应该采用“实时”审查来自动更新评估——世界卫生组织、Cochrane协作组织和联合国等全球组织都采用了这种方法泛美卫生组织。第二个组成部分包括添加一个聊天机器人来支持评估和实施指导,并就以下方面提出建议:(1)提供所有基于证据的预防干预措施(ebpi)及其关键活动,(2)显示可实现公平分配结果的ebpi,(3)与目标人群的价值观和需求保持一致的文化相关的ebpi,(4)实施支持,如材料,培训和保真度措施,以及(5)交付成本。由此产生的平台将在伦理上加快识别和扩展ebpi的转化过程,从而形成更完整、全面和可获取的有效预防策略证据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Prevention Science
Prevention Science PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
6.50
自引率
11.40%
发文量
128
期刊介绍: Prevention Science is the official publication of the Society for Prevention Research. The Journal serves as an interdisciplinary forum designed to disseminate new developments in the theory, research and practice of prevention. Prevention sciences encompassing etiology, epidemiology and intervention are represented through peer-reviewed original research articles on a variety of health and social problems, including but not limited to substance abuse, mental health, HIV/AIDS, violence, accidents, teenage pregnancy, suicide, delinquency, STD''s, obesity, diet/nutrition, exercise, and chronic illness. The journal also publishes literature reviews, theoretical articles, meta-analyses, systematic reviews, brief reports, replication studies, and papers concerning new developments in methodology.
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