Suppr超能文献

人口健康干预措施(深度)框架的开发与应用,用于对人口健康干预措施的能动需求进行分类。

Development and application of the Demands for Population Health Interventions (Depth) framework for categorising the agentic demands of population health interventions.

作者信息

Garrott Kate, Ogilvie David, Panter Jenna, Petticrew Mark, Sowden Amanda, Jones Catrin P, Foubister Campbell, Lawlor Emma R, Ikeda Erika, Patterson Richard, van Tulleken Dolly, Armstrong-Moore Roxanne, Vethanayakam Gokulan, Bo Lorna, White Martin, Adams Jean

机构信息

MRC Epidemiology Unit, University of Cambridge, Cambridge, UK.

Department of Public Health, Environments and Society, London School of Hygiene and Tropical Medicine, London, UK.

出版信息

BMC Glob Public Health. 2024 Mar 4;2(1):13. doi: 10.1186/s44263-024-00043-8.

Abstract

BACKGROUND

The 'agentic demand' of population health interventions (PHIs) refers to the capacity, resources and freedom to act that interventions demand of their recipients to benefit, which have a socio-economical pattern. Highly agentic interventions, e.g. information campaigns, rely on recipients noticing and responding to the intervention and thus might affect intervention effectiveness and equity. The absence of an adequate framework to classify agentic demands limits the fields' ability to systematically explore these associations.

METHODS

We systematically developed the Demands for Population Health Interventions (Depth) framework using an iterative approach: (1) developing the Depth framework by systematically identifying examples of PHIs aiming to promote healthier diets and physical activity, coding of intervention actors and actions and synthesising the data to develop the framework; (2) testing the Depth framework in online workshops with academic and policy experts and a quantitative reliability assessment. We applied the final framework in a proof-of-concept review, extracting studies from three existing equity-focused systematic reviews on framework category, overall effectiveness and differential socioeconomic effects and visualised the findings in harvest plots.

RESULTS

The Depth framework identifies three constructs influencing agentic demand: exposure - initial contact with intervention (two levels), mechanism of action - how the intervention enables or discourages behaviour (five levels) and engagement - recipient response (two levels). When combined, these constructs form a matrix of 20 possible classifications. In the proof-of-concept review, we classified all components of 31 interventions according to the Depth framework. Intervention components were concentrated in a small number of Depth classifications; Depth classification appeared to be related to intervention equity but not effectiveness.

CONCLUSIONS

This framework holds potential for future research, policy and practice, facilitating the design, selection and evaluation of interventions and evidence synthesis.

摘要

背景

人群健康干预措施(PHIs)的“能动需求”是指干预措施要求其接受者为获得益处而具备的行动能力、资源和自由,这些具有社会经济模式。高度能动的干预措施,如信息宣传活动,依赖于接受者注意到并对干预措施做出反应,因此可能会影响干预效果和公平性。缺乏一个适当的框架来对能动需求进行分类,限制了该领域系统探索这些关联的能力。

方法

我们采用迭代方法系统地开发了人群健康干预措施需求(深度)框架:(1)通过系统识别旨在促进更健康饮食和身体活动的PHIs示例、对干预行为主体和行动进行编码并综合数据来开发深度框架;(2)在与学术和政策专家的在线研讨会上测试深度框架,并进行定量可靠性评估。我们在概念验证综述中应用了最终框架,从三项现有的以公平为重点的系统综述中提取关于框架类别、总体效果和社会经济差异影响的研究,并在汇总图中直观呈现研究结果。

结果

深度框架确定了影响能动需求的三个结构:接触——与干预的初次接触(两个层次)、作用机制——干预如何促进或抑制行为(五个层次)和参与——接受者的反应(两个层次)。这些结构组合在一起时,形成了一个包含20种可能分类的矩阵。在概念验证综述中,我们根据深度框架对31项干预措施的所有组成部分进行了分类。干预措施的组成部分集中在少数几个深度分类中;深度分类似乎与干预公平性相关,但与效果无关。

结论

该框架在未来研究、政策和实践方面具有潜力,有助于干预措施的设计、选择和评估以及证据综合。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验