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

Overview

Journal Front Public Health

Specialty Public Health

Date 2022 Apr 21

PMID 35444977

Authors

Shu Zhang

Tianyi Xiao

Jie He

Affiliations

Soon will be listed here.

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 ( = 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%, < 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, < 0.05), with a higher efficiency in girls than boys (average 3.68% vs. 2.99% per tick, < 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, < 0.05), while in boys, PageRank still had the greatest efficiency (3.21% per tick, < 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.

References

Gesell S, Tesdahl E, Ruchman E . The distribution of physical activity in an after-school friendship network. Pediatrics. 2012; 129(6):1064-71. PMC: 3362907. DOI: 10.1542/peds.2011-2567. View

Maximova K, McGrath J, Barnett T, OLoughlin J, Paradis G, Lambert M . Do you see what I see? Weight status misperception and exposure to obesity among children and adolescents. Int J Obes (Lond). 2008; 32(6):1008-15. PMC: 5760224. DOI: 10.1038/ijo.2008.15. View

Suh J, Jeon Y, Lee J, Song K, Choi H, Kwon A . Annual incidence and prevalence of obesity in childhood and young adulthood based on a 30-year longitudinal population-based cohort study in Korea: the Kangwha study. Ann Epidemiol. 2021; 62:1-6. DOI: 10.1016/j.annepidem.2021.05.002. View

Smith J, Morgan P, Plotnikoff R, Dally K, Salmon J, Okely A . Smart-phone obesity prevention trial for adolescent boys in low-income communities: the ATLAS RCT. Pediatrics. 2014; 134(3):e723-31. DOI: 10.1542/peds.2014-1012. View

Fu L, Sun L, Wu S, Yang Y, Li X, Wang Z . The Influence of Secular Trends in Body Height and Weight on the Prevalence of Overweight and Obesity among Chinese Children and Adolescents. Biomed Environ Sci. 2017; 29(12):849-857. DOI: 10.3967/bes2016.114. View

van Woudenberg T, Bevelander K, Burk W, Smit C, Buijs L, Buijzen M . A randomized controlled trial testing a social network intervention to promote physical activity among adolescents. BMC Public Health. 2018; 18(1):542. PMC: 5913789. DOI: 10.1186/s12889-018-5451-4. View

Auchincloss A, Diez Roux A . A new tool for epidemiology: the usefulness of dynamic-agent models in understanding place effects on health. Am J Epidemiol. 2008; 168(1):1-8. DOI: 10.1093/aje/kwn118. View

El-Sayed A, Scarborough P, Seemann L, Galea S . Social network analysis and agent-based modeling in social epidemiology. Epidemiol Perspect Innov. 2012; 9(1):1. PMC: 3395878. DOI: 10.1186/1742-5573-9-1. View

Fagot B . Peer relations and the development of competence in boys and girls. New Dir Child Dev. 1994; (65):53-65. DOI: 10.1002/cd.23219946506. View

10.

Zhang J, Seo D, Kolbe L, Lee A, Middlestadt S, Zhao W . Comparison of overweight, weight perception, and weight-related practices among high school students in three large Chinese cities and two large U.S. cities. J Adolesc Health. 2011; 48(4):366-72. DOI: 10.1016/j.jadohealth.2010.07.015. View

11.

Qiu N, He H, Qiao L, Ding Y, Ji S, Guo X . Sex differences in changes in BMI and blood pressure in Chinese school-aged children during the COVID-19 quarantine. Int J Obes (Lond). 2021; 45(9):2132-2136. PMC: 8178658. DOI: 10.1038/s41366-021-00871-w. View

12.

Shalizi C, Thomas A . Homophily and Contagion Are Generically Confounded in Observational Social Network Studies. Sociol Methods Res. 2012; 40(2):211-239. PMC: 3328971. DOI: 10.1177/0049124111404820. View

13.

Watts D, Strogatz S . Collective dynamics of 'small-world' networks. Nature. 1998; 393(6684):440-2. DOI: 10.1038/30918. View

14.

Matsushita Y, Yoshiike N, Kaneda F, Yoshita K, Takimoto H . Trends in childhood obesity in Japan over the last 25 years from the national nutrition survey. Obes Res. 2004; 12(2):205-14. DOI: 10.1038/oby.2004.27. View

15.

Valente T . Network interventions. Science. 2012; 337(6090):49-53. DOI: 10.1126/science.1217330. View

16.

Salvy S, Roemmich J, Bowker J, Romero N, Stadler P, Epstein L . Effect of peers and friends on youth physical activity and motivation to be physically active. J Pediatr Psychol. 2008; 34(2):217-25. PMC: 3202936. DOI: 10.1093/jpepsy/jsn071. View

17.

Rasberry C, Lee S, Robin L, Laris B, Russell L, Coyle K . The association between school-based physical activity, including physical education, and academic performance: a systematic review of the literature. Prev Med. 2011; 52 Suppl 1:S10-20. DOI: 10.1016/j.ypmed.2011.01.027. View

18.

Beheshti R, Jalalpour M, Glass T . Comparing methods of targeting obesity interventions in populations: An agent-based simulation. SSM Popul Health. 2018; 3:211-218. PMC: 5769018. DOI: 10.1016/j.ssmph.2017.01.006. View

19.

Keane E, Kearney P, Perry I, Kelleher C, Harrington J . Trends and prevalence of overweight and obesity in primary school aged children in the Republic of Ireland from 2002-2012: a systematic review. BMC Public Health. 2014; 14:974. PMC: 4197331. DOI: 10.1186/1471-2458-14-974. View

20.

Caine-Bish N, Scheule B . Gender differences in food preferences of school-aged children and adolescents. J Sch Health. 2009; 79(11):532-40. DOI: 10.1111/j.1746-1561.2009.00445.x. View