Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Apr 4:10:861743.
doi: 10.3389/fpubh.2022.861743. eCollection 2022.

The Influence of a School Social Network Intervention on Adolescent's Health Behaviors: A Gender-Specific Agent-Based Model

Shu Zhang  1 , Tianyi Xiao  1 , Jie He  1   2
Affiliations

The Influence of a School Social Network Intervention on Adolescent's Health Behaviors: A Gender-Specific Agent-Based Model

Shu Zhang et al. Front Public Health. .

Abstract

Introduction: Adolescence is a crucial stage for health behavior development, which is associated with health in adulthood. School closures caused by the coronavirus disease 2019 (COVID-19) pandemic have exposed adolescents to an increased risk of obesity due to a lack of physical activity. Although social network interventions provide an effective approach for promoting health-related behavior, current practices neglect gender differences in adolescent behavioral patterns and emotional preferences. The aim of this study was to examine the effectiveness of centrality-based methods integrated with of gender contexts in a social network intervention to improve adolescent's health behavior.

Methods: We developed an agent-based model (ABM) that supports the small-world characteristics of adolescent social networks. Health-related data for junior middle school students (n = 234, 48% girls) were collected in November 2018, 2019 and 2020 in Tianjin, China. We simulated multiple network-based interventions with different criteria for influential agents (i.e., betweenness centrality, closeness centrality, eigenvector centrality, and PageRank) and a random condition. The rules for generating peer influence and accelerating behavioral changes were based on the diffusion of innovations theory, with gender specifications.

Results: After the school closures, there was a significant increase in the prevalence of overweight and obesity among adolescents, with a greater increase in girls than in boys (+8.85% vs. +1.65%, p < 0.001). Simulations showed that centrality-based network interventions were more effective than the random condition (average 6.17% per tick vs. 5.22% per tick, p < 0.05), with a higher efficiency in girls than boys (average 3.68% vs. 2.99% per tick, p < 0.05). PageRank outperformed other centrality conditions at the population level (6.37% per tick, p < 0.05). In girls, betweenness centrality was the best method (3.85% per tick, p < 0.05), while in boys, PageRank still had the greatest efficiency (3.21% per tick, p < 0.05).

Conclusions: We found evidence for gender differences in the negative impact of COVID-19-related school closures and the potential for centrality-based social network interventions to affect adolescent health behavior. Therefore, we emphasize the importance of gender-specific targeting strategies to further promote health-related school programs in the post-pandemic era.

Keywords: agent-based model (ABM); centrality measurement; gender differences; obesity; peer influence; small-world networks.

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
The building process of the Watts–Strogatz small-world model with gender contexts.
Figure 2
Figure 2
Intervention outcomes of the random and four centrality-based conditions.
Figure 3
Figure 3
Gender differences under four centrality-based interventions.
See this image and copyright information in PMC

Similar articles

See all similar articles

References

    1. Rasberry CN, Lee SM, Robin L, Laris B, Russell LA, Coyle KK, et al. . The association between school-based physical activity, including physical education, and academic performance: a systematic review of the literature. Prev Med. (2011) 52:S10–20. 10.1016/j.ypmed.2011.01.027 - DOI - PubMed
    1. Institute of Medicine (US) . Committee on Physical Activity and Physical Education in the School Environment. Educating the student body: Taking Physical Activity And Physical Education To School. National Academies Press; (2013). Available online at: https://www.nap.edu/catalog/18314/educating-the-student-body-taking-phys... (accessed March 17, 2022). - PubMed
    1. Okely AD, Kontsevaya A, Ng J, Abdeta C. 2020 WHO guidelines on physical activity and sedentary behavior. Sport Med Health Sci. (2021) 3:115–18. 10.1016/j.smhs.2021.05.001 - DOI - PMC - PubMed
    1. Hallal PC, Andersen LB, Bull FC, Guthold R, Haskell W, Ekelund U. Global physical activity levels: surveillance progress, pitfalls, and prospects. Lancet. (2012) 380:247–57. 10.1016/S0140-6736(12)60646-1 - DOI - PubMed
    1. Liu Y, Tang Y, Cao ZB, Chen PJ, Zhang JL, Zhu Z, et al. . Results from Shanghai's (China) 2016 report card on physical activity for children and youth. J Phys Act Health. (2016) 13:124–8. 10.1123/jpah.2016-0362 - DOI - PubMed

Publication types