Monique Simons1, Emely de Vet2, Johannes Brug3, Jaap Seidell2, Mai J M Chinapaw4. 1. Department of Health Sciences and the EMGO Institute for Health and Care Research, Faculty of Earth and Life Sciences, VU University Amsterdam, The Netherlands; TNO, Expertise Centre Life Style, Leiden, The Netherlands; Body@Work, Research Center PA, Work and Health, TNO-VU/VUmc, VU University Medical Center, Amsterdam, The Netherlands. Electronic address: m.simons@vu.nl. 2. Department of Health Sciences and the EMGO Institute for Health and Care Research, Faculty of Earth and Life Sciences, VU University Amsterdam, The Netherlands. 3. Department of Epidemiology & Biostatistics and EMGO Institute for Health and Care Research, VU University Medical Center, The Netherlands. 4. Body@Work, Research Center PA, Work and Health, TNO-VU/VUmc, VU University Medical Center, Amsterdam, The Netherlands; Department of Public and Occupational Health and the EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands.
Abstract
OBJECTIVES: The aim of study was to determine prevalence and identify demographic correlates of active and non-active gaming among adolescents. DESIGN: Cross-sectional. METHODS: A survey, assessing game behavior and correlates, was conducted among adolescents (12-16 years, n = 373), recruited via schools. Multivariable logistic regression analyses were conducted to examine demographic correlates of active gaming (≥ 1 h per week) and non-active gaming (>7h per week). RESULTS: Of all participants (n=373), 3% reported to play exclusively active games, 40% active games and non-active games, 40% exclusively non-active games, and 17% not playing video games at all. Active gaming adolescents played active games on average on 1.5 (sd = 1.2) days per school week for 36 (sd = 32.9)min and 1 (sd = 0.54) day per weekend for 42 (sd = 36.5)min. Non-active gaming adolescents played on average on 3.3 (sd = 1.6) days per school week for 65 (sd = 46.0)min and 1.4 (sd = 0.65) days per weekend for 80 (sd = 50.8)min. Adolescents attending lower levels of education were more likely to play active games ≥ 1 h per week than adolescents attending higher educational levels. Boys and older adolescents were more likely to play non-active games >7h per week, than girls or younger adolescents. CONCLUSIONS: Many adolescents play active games, especially those following a lower educational level, but time spent in this activity is relatively low compared to non-active gaming. To be feasible as a public health strategy, active gaming interventions should achieve more time is spent on active gaming at the expense of non-active gaming.
OBJECTIVES: The aim of study was to determine prevalence and identify demographic correlates of active and non-active gaming among adolescents. DESIGN: Cross-sectional. METHODS: A survey, assessing game behavior and correlates, was conducted among adolescents (12-16 years, n = 373), recruited via schools. Multivariable logistic regression analyses were conducted to examine demographic correlates of active gaming (≥ 1 h per week) and non-active gaming (>7h per week). RESULTS: Of all participants (n=373), 3% reported to play exclusively active games, 40% active games and non-active games, 40% exclusively non-active games, and 17% not playing video games at all. Active gaming adolescents played active games on average on 1.5 (sd = 1.2) days per school week for 36 (sd = 32.9)min and 1 (sd = 0.54) day per weekend for 42 (sd = 36.5)min. Non-active gaming adolescents played on average on 3.3 (sd = 1.6) days per school week for 65 (sd = 46.0)min and 1.4 (sd = 0.65) days per weekend for 80 (sd = 50.8)min. Adolescents attending lower levels of education were more likely to play active games ≥ 1 h per week than adolescents attending higher educational levels. Boys and older adolescents were more likely to play non-active games >7h per week, than girls or younger adolescents. CONCLUSIONS: Many adolescents play active games, especially those following a lower educational level, but time spent in this activity is relatively low compared to non-active gaming. To be feasible as a public health strategy, active gaming interventions should achieve more time is spent on active gaming at the expense of non-active gaming.
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