Evidence map›Paper›PMID 42359144›Full record

ArticleFrontiers in public health2026

Survey-calibrated agent-based modeling of peer targeting for promoting physical activity among adolescents.

Weixuan Long, Binbing Zheng, Zhihan Wu, Hongsheng Qian, Yu Zou, Jingwang Tan, Yilei Wang

Abstract read
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Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Weixuan LongDepartment of Sport Science, College of Education, Zhejiang University, Hangzhou, Zhejiang, China.
Binbing ZhengDepartment of Sport Science, College of Education, Zhejiang University, Hangzhou, Zhejiang, China.
Zhihan WuCollege of Physical Education, Shanghai University of Sport, Shanghai, China.
Hongsheng QianCollege of Physical Education, Wuhan Sports University, Wuhan, Hubei, China.
Yu ZouDepartment of Sport Science, College of Education, Zhejiang University, Hangzhou, Zhejiang, China.
Jingwang TanCollege of Physical Education, Shanghai University, Shanghai, China.
Yilei WangDepartment of Sports, Hangzhou Medical College, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: This study aims to compare the effectiveness of various centrality-based peer-targeting strategies in promoting physical activity (PA) among adolescents and identify practical principles for school-based social network interventions. Study design: A modeling study combining cross-sectional survey data with an agent-based model (ABM) analysis. Methods: Questionnaire data from 1,692 middle-school students were used to parameterize PA distributions, friendship ties, and co-activity probabilities. Maximum-entropy class networks were generated, and a peer-influence diffusion process inspired by the Susceptible-Infected-Recovered (SIR) framework was implemented. Four targeting strategies including random, degree-, betweenness-, and closeness-centrality were evaluated based on diffusion speed and changes in the proportions of low-, moderate-, and high-PA students. Results: Centrality-based strategies generally accelerated PA diffusion relative to random targeting, although differences among centrality rules were small. Closeness-centrality showed a more concentrated diffusion pattern, but no single rule consistently dominated across all outcomes. Specific advantages varied by outcome: degree-centrality tended to strengthen already active clusters, while betweenness-centrality showed limited advantage in improving PA composition. Across all strategies, over 60% of adolescents who remained low active had below-average friendship degrees, indicating persistent structural disadvantages. Conclusion: Centrality-based peer-targeting strategies offer advantages over random allocation in school-based PA interventions. However, their effects on PA composition were limited, and socially peripheral adolescents remained difficult to engage through peer influence alone. No single centrality rule should be interpreted as universally optimal. These findings suggest that network-informed peer targeting should be combined with low-threshold, teacher- or coach-supported opportunities to improve inclusiveness and overall effectiveness.

Indexed as

ExerciseHealth PromotionPeer GroupAdolescentCross-Sectional StudiesFemaleHumansMaleSchoolsSurveys and Questionnairesadolescentagent-based modelcentrality-based peer targetingphysical activitysocial network intervention

Identifiers

PMID42359144
PMCPMC13292596

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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.