Evidence map›Paper›PMID 39362998›Full record

ArticleHealth care analysis : HCA : journal of health philosophy and policy2025

Exploring the Broader Benefits of Obesity Prevention Community-based Interventions From the Perspective of Multiple Stakeholders.

J Jacobs, M Nichols, N Ward, M Sultana, S Allender, V Brown

Abstract read
In one paragraph

Article in Health care analysis : HCA : journal of health philosophy and policy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

J JacobsGlobal Centre for Preventive Health and Nutrition (GLOBE), Institute for Health Transformation, Deakin University, Geelong, VIC, Australia. jane.jacobs@deakin.edu.au.ORCID http://orcid.org/0000-0002-3722-9672
M NicholsGlobal Centre for Preventive Health and Nutrition (GLOBE), Institute for Health Transformation, Deakin University, Geelong, VIC, Australia.
N WardDeakin Health Economics, Global Centre for Preventive Health and Nutrition (GLOBE), Institute for Health Transformation, Deakin University, Geelong, VIC, Australia.
M SultanaDeakin Health Economics, Global Centre for Preventive Health and Nutrition (GLOBE), Institute for Health Transformation, Deakin University, Geelong, VIC, Australia.
S AllenderGlobal Centre for Preventive Health and Nutrition (GLOBE), Institute for Health Transformation, Deakin University, Geelong, VIC, Australia.
V BrownDeakin Health Economics, Global Centre for Preventive Health and Nutrition (GLOBE), Institute for Health Transformation, Deakin University, Geelong, VIC, Australia.

Funding

Australian Medical Research Future Fund 2030589Australian Medical Research Future Fund RARUR 00072Deakin University Alfred Deakin Post-Doctoral FellowshipEuropean Union Horizon 2020 H2020-SFS-2016-2017National Health and Medical Research Council 1151572National Health and Medical Research Council 2002234National Health and Medical Research Council 2011209National Health and Medical Research Council 2015440National Health and Medical Research Council 2023737National Health and Medical Research Council 2024716National Health and Medical Research Council 2027736National Health and Medical Research Council GNT1162980National Health and Medical Research Council GNT2002234National Health and Medical Research Council GNT2006999C
6 · The paper itself

Abstract

Community-based interventions (CBIs) show promise as effective and cost-effective obesity prevention initiatives. CBIs are typically complex interventions, including multiple settings, strategies and stakeholders. Cost-effectiveness evidence, however, generally only considers a narrow range of costs and benefits associated with anthropometric outcomes. While it is recognised that the complexity of CBIs may result in broader non-health societal and community benefits, the identification, measurement, and quantification of these outcomes is limited. This study aimed to understand the perspectives of stakeholders on the broader benefits of CBIs and their measurement, as well as perceptions of CBI cost-effectiveness. Purposive sampling was used to recruit participants from three stakeholder groups (lead researchers, funders, and community stakeholders of CBIs). Online semi-structured interviews were conducted, taking a constructivist approach. Coding, theme development and analysis were based on published guidance for thematic analysis. Twenty-six stakeholders participated in the interviews (12 lead researchers; 7 funders; 6 community stakeholders). Six key themes emerged; (1) Impacts of CBIs (health impacts and broader impacts); (2) Broader benefits were important to stakeholders; (3) Measurement of benefits are challenging; (4) CBIs were considered cost-effective; (5) Framing CBIs for community engagement (6) Making equitable impacts and sustaining changes-successes and challenges. Across all stakeholders, broader benefits, particularly the establishment of networks and partnerships within communities, were seen as important outcomes of CBIs. Participants viewed the CBI approach to obesity prevention as cost-effective, however, there were challenges in measuring, quantifying and valuing broader benefits. Development of tools to measure and quantify broader benefits would allow for more comprehensive evaluation of the cost-effectiveness of CBIs for obesity prevention.

Indexed as

Community Health ServicesHealth PromotionObesityStakeholder ParticipationCost-Benefit AnalysisHumansInterviews as TopicQualitative ResearchBroader benefitsCommunity-based interventionsCost-effectivenessEconomic analysisObesity prevention

Identifiers

PMID39362998
PMCPMC12052814

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.