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Network interventions on physical activity in an afterschool program: An agent-based social network study

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  • Zhang, J.
  • Shoham, D.A.
  • Tesdahl, E.
  • Gesell, S.B.

Abstract

Objectives: We studied simulated interventions that leveraged social networks to increase physical activity in children. Methods: We studied a real-world social network of 81 children (average age = 7.96 years) who lived in low socioeconomic status neighborhoods, and attended public schools and 1 of 2 structured afterschool programs. The sample was ethnically diverse, and 44%were overweight or obese. We used social network analysis and agent-based modeling simulations to test whether implementing a network intervention would increase children's physical activity. We tested 3 intervention strategies. Results: The intervention that targeted opinion leaders was effective in increasing the average level of physical activity across the entire network. However, the intervention that targeted the most sedentary children was the best at increasing their physical activity levels. Conclusions: Which network intervention to implement depends on whether the goal is to shift the entire distribution of physical activity or to influence those most adversely affected by low physical activity. Agentbased modeling could be an important complement to traditional project planning tools, analogous to sample size and power analyses, to help researchers design more effective interventions for increasing children's physical activity.

Suggested Citation

  • Zhang, J. & Shoham, D.A. & Tesdahl, E. & Gesell, S.B., 2015. "Network interventions on physical activity in an afterschool program: An agent-based social network study," American Journal of Public Health, American Public Health Association, vol. 105, pages 236-243.
  • Handle: RePEc:aph:ajpbhl:10.2105/ajph.2014.302277_6
    DOI: 10.2105/AJPH.2014.302277
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    Cited by:

    1. Nematullah Hayba & Yumeng Shi & Margaret Allman-Farinelli, 2021. "Enabling Better Physical Activity and Screen Time Behaviours for Adolescents from Middle Eastern Backgrounds: Semi-Structured Interviews with Parents," IJERPH, MDPI, vol. 18(23), pages 1-20, December.
    2. Sabina B. Gesell & Shari L. Barkin & Edward H. Ip & Santiago J. Saldana & Evan C. Sommer & Thomas W. Valente & Kayla de la Haye, 2021. "Leveraging Emergent Social Networks to Reduce Sedentary Behavior in Low-Income Parents With Preschool-Aged Children," SAGE Open, , vol. 11(3), pages 21582440211, July.
    3. Linna Luo & Bowen Pang & Jian Chen & Yan Li & Xiaolei Xie, 2019. "Assessing the Impact of Lifestyle Interventions on Diabetes Prevention in China: A Modeling Approach," IJERPH, MDPI, vol. 16(10), pages 1-12, May.
    4. Sabina B. Gesell & Kayla de la Haye & Evan C. Sommer & Santiago J. Saldana & Shari L. Barkin & Edward H. Ip, 2020. "Identifying Social Network Conditions that Facilitate Sedentary Behavior Change: The Benefit of Being a “Bridge” in a Group-based Intervention," IJERPH, MDPI, vol. 17(12), pages 1-13, June.
    5. Thomas J. Lampoltshammer & Heidrun Maurer & Nike Pulda & Peter Klimek & Jan Hurt & Ursula Rosenbichler, 2023. "Challenges toward Evidence-Based Policymaking Using Agent-Based Modeling for Federal Sports Grants: A Self-Reflection from a Transdisciplinary Project," Sustainability, MDPI, vol. 15(4), pages 1-34, February.

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