资产:对世界卫生组织的社会隔离和孤独干预分类系统进行系统审查和发展。

IF 2.5 2区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
D L Surkalim, A Farzana, W Y Choo, S Hussein, P C Hébert, V Welch, E Tanjong Ghogomu, C Mikton
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引用次数: 0

摘要

背景:社会隔离和孤独(SIL)已成为与各种不良健康结果相关的关键人群健康问题,包括心血管疾病、中风、痴呆、抑郁和过早死亡。然而,缺乏旨在减少SIL的干预措施的标准分类阻碍了一致的比较、评估和知识积累,影响了基于证据的政策决策。为了解决这一差距,我们开发并实证评估了资产(获取、技能、社会参与、治疗和心理、系统)分类系统,这是一种对SIL干预进行分类的标准化方法。方法:我们进行了一项系统综述,以确定和评估用于SIL干预的现有分类系统。从成立到2023年9月,17个数据库被搜索,没有语言限制。纳入标准包括已建立和广泛使用的评价,具有明确的干预分类和对一般人群的广泛适用性。专家咨询补充了系统综述,提供了迭代反馈和文献检索中遗漏的其他相关文献,为资产分类框架的制定提供了信息。开发的ASSeTS系统由独立专家进行了清晰性、适用性和可靠性的经验测试,并使用Fleiss的kappa评估了评级者之间的一致性。结果:该综述确定了11项研究,涵盖了一系列SIL干预分类方法。在综合和专家反馈的基础上,资产系统被分为五个主要类别:获取、技能、社会参与、治疗和心理以及系统干预。经实证检验,评分者间信度适中(κ = 0.419),表明专家评分者的可用性是可以接受的。在治疗和心理干预等类别中发现了较高的一致性,而系统干预显示出较低的可靠性,这表明未来有改进的机会。结论:资产分类系统为SIL干预措施的分类提供了一个急需的标准化框架,促进了可比性、严格的评估、积累的知识和基于证据的政策决策。未来的工作应侧重于改进不太可靠的类别,验证不同背景下的资产,并将其纳入全球政策框架,以更有效地解决SIL对公共卫生的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ASSeTS: a systematic review and development of the World Health Organization's classification system for social isolation and loneliness interventions.

Background: Social isolation and loneliness (SIL) have emerged as critical population health concerns linked to various adverse health outcomes, including cardiovascular disease, stroke, dementia, depression, and premature mortality. However, the absence of a standard categorization for interventions aimed at reducing SIL has impeded consistent comparison, evaluation, and the accumulation of knowledge, affecting evidence-based policy decisions. To address this gap, we developed and empirically evaluated the ASSeTS (Access, Skills, Social engagement, Therapeutic and psychological, Systemic) classification system, a standardized approach for categorizing SIL interventions.

Methods: We conducted a systematic review to identify and evaluate existing classification systems used for SIL interventions. Seventeen databases were searched from inception to September 2023, with no language restrictions. Inclusion criteria encompassed established and widely used reviews with clear intervention categorizations and broad applicability to general population groups. Expert consultations supplemented the systematic review, providing iterative feedback and additional relevant literature missed from the literature search, to inform the development of the ASSeTS classification framework. The developed ASSeTS system was empirically tested by independent experts for clarity, applicability, and reliability, with inter-rater agreement assessed using Fleiss' kappa.

Results: The review identified 11 studies covering a range of SIL intervention categorization approaches. Based on synthesis and expert feedback, the ASSeTS system was structured into five main categories: Access, Skills, Social engagement, Therapeutic and psychological, and Systemic interventions. Empirical testing yielded moderate inter-rater reliability (κ = 0.419), indicating acceptable usability among expert raters. Higher agreement was found for categories such as therapeutic and psychological interventions, whereas systemic interventions showed lower reliability, suggesting opportunities for future refinement.

Conclusion: The ASSeTS classification system provides a much-needed standardized framework for categorizing SIL interventions, facilitating comparability, rigorous evaluation, cumulative knowledge, and evidence-based policy decisions. Future work should focus on refining less reliable categories, validating ASSeTS across various contexts, and integrating it into global policy frameworks to more effectively address the public health implications of SIL.

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来源期刊
Population Health Metrics
Population Health Metrics PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
6.50
自引率
0.00%
发文量
21
审稿时长
29 weeks
期刊介绍: Population Health Metrics aims to advance the science of population health assessment, and welcomes papers relating to concepts, methods, ethics, applications, and summary measures of population health. The journal provides a unique platform for population health researchers to share their findings with the global community. We seek research that addresses the communication of population health measures and policy implications to stakeholders; this includes papers related to burden estimation and risk assessment, and research addressing population health across the full range of development. Population Health Metrics covers a broad range of topics encompassing health state measurement and valuation, summary measures of population health, descriptive epidemiology at the population level, burden of disease and injury analysis, disease and risk factor modeling for populations, and comparative assessment of risks to health at the population level. The journal is also interested in how to use and communicate indicators of population health to reduce disease burden, and the approaches for translating from indicators of population health to health-advancing actions. As a cross-cutting topic of importance, we are particularly interested in inequalities in population health and their measurement.
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