Shannon C Montgomery1, Michael Donnelly2, Jennifer Badham2, Frank Kee2, Laura Dunne3, Ruth F Hunter4. 1. UKCRC Centre of Excellence for Public Health (Northern Ireland)/Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, Northern Ireland, UK. smontgomery18@qub.ac.uk. 2. UKCRC Centre of Excellence for Public Health (Northern Ireland)/Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, Northern Ireland, UK. 3. School of Social Sciences, Education and Social Work, Queen's University Belfast, Belfast, Northern Ireland, UK. 4. UKCRC Centre of Excellence for Public Health (Northern Ireland)/Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen's University Belfast, Belfast, Northern Ireland, UK. ruth.hunter@qub.ac.uk.
Abstract
BACKGROUND: There is a need for novel interventions to target inadequate levels of adolescent physical activity behavior. Previous research indicates that better understanding of the processes by which social networks influence physical activity behavior in adolescents may be useful to enhance intervention design. METHODS: This study used a multi-methods approach to aid our understanding about the role of social networks for adolescent physical activity behavior. The quantitative phase of data collection was analyzed using a three-step linear regression model using cross-sectional data from the WiSe study (n = 529 participants, 48.6% female, mean age 14.38 years (SD 0.32)). A demographically reflective sub-sample of schools were invited to take part in the qualitative phase, which involved focus group discussions. Thematic analysis was used to explore findings from the quantitative phase in greater depth, and identify other themes pertaining to the association between social networks and physical activity behavior. RESULTS: Males' physical activity behavior was predicted by their friend group (0.46, p = 0.007) whereas females' physical activity was predicted by their best friend (0.21, p = 0.03). The three main findings that were uncovered by the regression analysis were explored during the qualitative phase: 1) friends have similar physical activity behaviors; 2) friendship social networks may influence differently early adolescent male and female physical activity behavior; 3) popularity and sociability were not associated with physical activity behavior. Two additional themes emerged from the analysis of focus group data: 4) social norms and 5) external factors that may impact the relationship between adolescent physical activity behavior and social networks. CONCLUSIONS: The investigation of the interplay between the findings from each phase of the inquiry indicated that social networks influence in different ways and to different degrees the physical activity of adolescent males and females. In turn, these insights point to the need for a systematic tailoring process for the development and implementation of physical activity behavior interventions.
BACKGROUND: There is a need for novel interventions to target inadequate levels of adolescent physical activity behavior. Previous research indicates that better understanding of the processes by which social networks influence physical activity behavior in adolescents may be useful to enhance intervention design. METHODS: This study used a multi-methods approach to aid our understanding about the role of social networks for adolescent physical activity behavior. The quantitative phase of data collection was analyzed using a three-step linear regression model using cross-sectional data from the WiSe study (n = 529 participants, 48.6% female, mean age 14.38 years (SD 0.32)). A demographically reflective sub-sample of schools were invited to take part in the qualitative phase, which involved focus group discussions. Thematic analysis was used to explore findings from the quantitative phase in greater depth, and identify other themes pertaining to the association between social networks and physical activity behavior. RESULTS: Males' physical activity behavior was predicted by their friend group (0.46, p = 0.007) whereas females' physical activity was predicted by their best friend (0.21, p = 0.03). The three main findings that were uncovered by the regression analysis were explored during the qualitative phase: 1) friends have similar physical activity behaviors; 2) friendship social networks may influence differently early adolescent male and female physical activity behavior; 3) popularity and sociability were not associated with physical activity behavior. Two additional themes emerged from the analysis of focus group data: 4) social norms and 5) external factors that may impact the relationship between adolescent physical activity behavior and social networks. CONCLUSIONS: The investigation of the interplay between the findings from each phase of the inquiry indicated that social networks influence in different ways and to different degrees the physical activity of adolescent males and females. In turn, these insights point to the need for a systematic tailoring process for the development and implementation of physical activity behavior interventions.
Entities:
Keywords:
Adolescents; Multi-methods analysis; Physical activity; Social networks
Authors: Carolyn C Voorhees; David Murray; Greg Welk; Amanda Birnbaum; Kurt M Ribisl; Carolyn C Johnson; Karin Allor Pfeiffer; Brit Saksvig; Jared B Jobe Journal: Am J Health Behav Date: 2005 Mar-Apr
Authors: Shannon C Montgomery; Michael Donnelly; Prachi Bhatnagar; Angela Carlin; Frank Kee; Ruth F Hunter Journal: Prev Med Date: 2019-11-13 Impact factor: 4.018
Authors: Meg Bruening; Richard MacLehose; Marla E Eisenberg; Marilyn S Nanney; Mary Story; Dianne Neumark-Sztainer Journal: J Nutr Educ Behav Date: 2014-04-13 Impact factor: 3.045
Authors: Anthony D Okely; David R Lubans; Philip J Morgan; Wayne Cotton; Louisa Peralta; Judith Miller; Marijka Batterham; Xanne Janssen Journal: Int J Behav Nutr Phys Act Date: 2017-06-21 Impact factor: 6.457
Authors: Maïté Verloigne; Teatske Maria Altenburg; Mai Jeanette Maidy Chinapaw; Sebastien Chastin; Greet Cardon; Ilse De Bourdeaudhuij Journal: Int J Environ Res Public Health Date: 2017-08-01 Impact factor: 3.390