Impact of Time Spent in Front of Screens and Frequency of Risk Behaviours According to Type of Screen: A Cross Sectional Study in Teenagers — Oak Academic Publishing
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Impact of Time Spent in Front of Screens and Frequency of Risk Behaviours According to Type of Screen: A Cross Sectional Study in Teenagers
Department of General Practice, School of Medecine, University of Poitiers, Poitiers, France
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Department of General Practice, School of Medecine, University of Poitiers, Poitiers, France
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Department of Epidemiology & Biostatistics, School of Medecine, University of Poitiers, Poitiers, France
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Department of General Practice, School of Medecine, University of Poitiers, Poitiers, France
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Intersectoral Clinical Psychiatry Pierre Deniker, Academic Hospital Henri Laborit, Poitiers, France
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Department of General Practice, School of Medecine, University of Poitiers, Poitiers, France
1 Department of General Practice, School of Medecine, University of Poitiers, Poitiers, France
2 Department of General Practice, School of Medecine, University of Poitiers, Poitiers, France
3 Department of Epidemiology & Biostatistics, School of Medecine, University of Poitiers, Poitiers, France
4 Department of General Practice, School of Medecine, University of Poitiers, Poitiers, France
5 Intersectoral Clinical Psychiatry Pierre Deniker, Academic Hospital Henri Laborit, Poitiers, France
6 Department of General Practice, School of Medecine, University of Poitiers, Poitiers, France
The time spent in front of various technology screens during adolescence could be linked to risk behaviours. Our study, carried out in June 2012, was designed to show that this correlation differs not only depending on sex but also according to the type of screen being used. Method: A cross-sectional survey was conducted on 1235 schoolchildren, aged 15, from 90 different schools in the Poitou-Charentes region. The questions asked were based on the Health Behaviour in School-aged Children Survey. Questions on the amount of time spent daily either in front of a television, a computer, on video games and mobile phones were added on. Three sample subgroups were defined according to the frequency of six risk behaviours (smoking, drunkenness, cannabis consumption, early sexual intercourse, fights and suicide attempts). Results: Our total sample comprised 923 15-year-olds: 468 girls and 455 boys: 74.7% of the pupils were registered in the schools selected. The correlation between time spent in front of various technology screens and frequency of risk behaviours varied according to type of screen but not according to sex. Cellphone use resulted in the highest correlation amongst all teenagers: OR = 9.40 [6.1 - 14.4]. Amongst boys, no excess risk was found whilst watching the television, and there is only moderate risk when playing video games (OR = 2.11 [1.14 - 3.91]) or whilst using the computer to surf the internet (OR = 2.21 [1.13 - 4.34]). Amongst girls, risk grew when using the computer to surf the internet (OR = 3.31 [1.61 - 6.78]) and playing video games (OR = 5.84 [1.65 - 20.6]). Conclusion: These results suggest that questioning teenagers on screen use could represent an approach to risk behavior that would complement other screening tests.
American Academy of Pediatrics, Council on Communications and Media (2013). Children. Adolescents, and the Media. Pediatrics. http://pediatrics.aappublications.org/content/pediatrics/early/2013/10/24/peds.2013-2656.full.pdf
Bigot, R., Croutte, P., & Daudey, E. (2013). La diffusion des technologies de l’information et de la communication dans la société française (288 p.). Enquête Conditions de vie et Aspirations des Français. Credoc.
Binder, P., & Chabaud, F. (2004). Dépister les conduites suicidaires des adolescents. Conception d’un test et validation de son usage (I) et (II). La Revue du Praticien Médecine Générale, 18, 576-580.
Browne, K. D., & Hamilton-Giachritsis, C. (2005). The Influence of Violent Media on Children and Adolescents: A Public-Health Approach. The Lancet, 365, 702-710.
Busch, V., Manders, L. A., & de Leeuw, J. R. (2013). Screen Time Associated with Health Behaviors and Outcomes in Adolescents. American Journal of Health Behavior, 37, 819-830. https://doi.org/10.5993/AJHB.37.6.11
Carson, V., Pickett, W., & Janssen, I. (2011). Screen Time and Risk Behaviors in 10-to 16-Year-Old Canadian Youth. Preventive Medicine, 52, 99-103. https://doi.org/10.1016/j.ypmed.2010.07.005
Chan-Chee, C. (2011). Hospitalisations pour tentatives de suicide entre 2004 et 2007 en France métropolitaine. Analyse du PMSI-MCO. Bull Epidemiol Hebd, 47-48, 492-496.
Christiansen, E., & Jensen, B. F. (2007). Risk of Repetition of Suicide Attempt, Suicide or All Deaths after an Episode of Attempted Suicide: A Register-Based Survival Analysis. Australian & New Zealand Journal of Psychiatry, 41, 257-265. https://doi.org/10.1080/00048670601172749
Crowne, D., & Marlowe D. (1960). A New Scale of Social Desirability Independent of Psychopathology. Journal of Consulting Psychology, 24, 349-354. https://doi.org/10.1037/h0047358
Currie, C., Griebler, R., Inchley, J., Theunissen, A., Molcho, M., Samdal, O., & Dür, W. (2010). Health Behaviour in School-Aged Children (HBSC) Study Protocol: Background, Methodology and Mandatory Items for the 2009/10 Survey. Edinburgh: CAHRU & Vienna: LBIHPR. http://www.hbsc.org
Dalbudak, E. et al. (2013). Relationship of Internet Addiction Severity with Depression, Anxiety, and Alexithymia, Temperament and Character in University Students. Cyberpsychology, Behavior, and Social Networking, 16, 272-278. https://doi.org/10.1089/cyber.2012.0390
Eaton, D. K. et al. (2012). Youth Risk Behavior Surveillance—United States, 2011. Morbidity and Mortality Weekly Report, 61, 1-162. http://www.cdc.gov/mmwr/preview/mmwrhtml/ss6104a1.htm
Fitzpatrick, C., Burkhalter, R., & Asbridge, M. (2019). Adolescent Media Use and Its Association to Wellbeing in a Canadian National Sample. Preventive Medicine Reports, 14, Article ID: 100867. https://doi.org/10.1016/j.pmedr.2019.100867
Fu, K. W., Chan, W. S., Wong, P. W., & Yip, P. S. (2010). Internet Addiction: Prevalence, Discriminant Validity and Correlates among Adolescents in Hong Kong. The British Journal of Psychiatry, 196, 486-492. https://doi.org/10.1192/bjp.bp.109.075002
Grøntved, A. et al. (2015). Prospective Study of Screen Time in Adolescence and Depression Symptoms in Young Adulthood. Preventive Medicine, 81, 108-113. https://doi.org/10.1016/j.ypmed.2015.08.009
Ha, J. H., Chin, B., Park, D. H., Ryu, S. H., & Yu, J. (2008). Characteristics of Excessive Cellular Phone Use in Korean Adolescents. CyberPsychology & Behavior, 11, 783-784. https://doi.org/10.1089/cpb.2008.0096
Holtz, P., & Appel, M. (2011). Internet Use and Video Gaming Predict Problem Behavior in Early Adolescence. Journal of Adolescence, 34, 49-58. https://doi.org/10.1016/j.adolescence.2010.02.004
INSEE (2012). Evolution et structure de la population, RP exploitations complémentaires. Institut National de la Statistique et des Etudes Economiques (France). http://www.insee.fr/fr/themes/tableau_local.asp?ref_id=POP&millesime=2012&typgeo=REG&search=54
Jago, R. et al. (2014). Cross-Sectional Associations between the Screen-Time of Parents and Young Children: Differences by Parent and Child Gender and Day of the Week. International Journal of Behavioral Nutrition and Physical Activity, 11, 54. https://doi.org/10.1186/1479-5868-11-54
Jin, B., & Park, N. (2013). Mobile Voice Communication and Loneliness: Cell Phone Use and the Social Skills Deficit Hypothesis. New Media & Society, 15, 1094-1111. https://doi.org/10.1177/1461444812466715
Jousselme, C., Cosquer, M., & Hasssler, C. (2015). Portraits d’adolescents: Enquête épidémiologique multicentrique en milieu scolaire en 2013 (182 p.). Paris: INSERM.
Kang, M. J., & Lee, M. S. (2014). The Association of Depression and Suicidal Behaviors with Smartphone Use among Korean Adolescents. Korean Journal of Health Education and Promotion, 31, 147-158. https://doi.org/10.14367/kjhep.2014.31.5.147
Kim, K. et al. (2006). Internet Addiction in Korean Adolescents and Its Relation to Depression and Suicidal Ideation: A Questionnaire Survey. International Journal of Nursing Studies, 43, 185-192. https://doi.org/10.1016/j.ijnurstu.2005.02.005
Kokkevi, A., Rotsika, V., Arapaki, A., & Richardson, C. (2012). Adolescents’ Self-Reported Suicide Attempts, Self-Harm Thoughts and Their Correlates across 17 European Countries. Journal of Child Psychology and Psychiatry, 53, 381-389. https://doi.org/10.1111/j.1469-7610.2011.02457.x
Leather, N. C. (2009). Risk-Taking Behaviour in Adolescence: A Literature Review. Journal of Child Health Care, 13, 295-304. https://doi.org/10.1177/1367493509337443
Lenhart, A. (2012). Pew Internet & American Life Project-Teens, Smartphones & Texting. Washington DC: Pew Research Center. http://www.pewinternet.org/files/old-
Lenhart, A., Hitlin, P., & Madden, M. (2005). Pew Internet & American Life Project-Teens and Technology. Washington DC: Pew Research Center.
Li, B., Friston, K. J., Liu, J., Liu, Y., Zhang, G., Cao, F., Su, L., Yao, S., Lu, H., & Hu, D. (2014). Impaired Frontal-Basal Ganglia Connectivity in Adolescents with Internet Addiction. Scientific Reports, 4, 5027. https://doi.org/10.1038/srep05027
Maras, D. et al. (2015). Screen Time Is Associated with Depression and Anxiety in Canadian Youth. Preventive Medicine, 73, 133-138. https://doi.org/10.1016/j.ypmed.2015.01.029
Ministère de l’éducation Nationale, de l’Enseignement supérieur et de la Recherche, Enfants & Internet. (2010). Baromètre 2009-2010. Un clic, déclic le Tour de France Des Etablissements Scolaires. http://eduscol.education.fr/numerique/textes/rapports/societe-numerique/culture-numerique/2010/calysto
Nieman, P. (2003). Canadian Pediatric Society Statement: Impact of Media on Children and Youth. Paediatrics & Child Health, 8, 301-306. https://doi.org/10.1093/pch/8.5.301
Niemz, K., Griffiths, M., & Banyard, P. (2005). Prevalence of Pathological Internet use among University Students and Correlations with Self-Esteem, the General Health Questionnaire (GHQ), and Disinhibition. CyberPsychology & Behavior, 8, 562-570. https://doi.org/10.1089/cpb.2005.8.562
Olson, C. K. (2004). Media Violence Research and Youth Violence Data: Why Do They Conflict? Academic Psychiatry, 28, 144-150. https://doi.org/10.1176/appi.ap.28.2.144
Pallanti, S., Bernardi, S., & Quercioli, L. (2006). The Shorter PROMIS Questionnaire and the Internet Addiction Scale in the Assessment of Multiple Addictions in a High-School Population: Prevalence and Related Disability. CNS Spectrums, 11, 966-974. https://doi.org/10.1017/S1092852900015157
Rey-López, J. P. et al. (2012). Reliability and Validity of a Screen Time-Based Sedentary Behaviour Questionnaire for Adolescents: The HELENA Study. European Journal of Public Health, 22, 373-377. https://doi.org/10.1093/eurpub/ckr040
Rice, E., Winetrobe, H., Holloway, I. W., Montoya, J., Plant, A., & Kordic, T. (2015). Cell Phone Internet access, Online Sexual Solicitation, Partner Seeking, and Sexual Risk Behavior among Adolescents. Archives of Sexual Behavior, 44, 755-763. https://doi.org/10.1007/s10508-014-0366-3
Richards, R., McGee, R., Williams, S. M., Welch, D., & Hancox, R. J. (2010). Adolescent Screen Time and Attachment to Parents and Peers. Archives of Pediatrics and Adolescent Medicine, 164, 258-262. https://doi.org/10.1001/archpediatrics.2009.280
Rideout, V. J., Roberts, D. F., & Foehr, U. G. (2010). Generation M2: Media in the Lives of 8-18-Year-Olds. http://kff.org/other/poll-finding/report-generation-m2-media-in-the-lives/
Villani, S. (2001). Impact of Media on Children and Adolescents: A 10-Year Review of the Research. Journal of the American Academy of Child & Adolescent Psychiatry, 40, 392-401. https://doi.org/10.1097/00004583-200104000-00007
Whang, L. S., Lee S., & Chang, G. (2003). Internet over-Users’ Psychological Profiles: A Behavior Sampling Analysis on Internet Addiction. CyberPsychology & Behavior, 6, 143-150. https://doi.org/10.1089/109493103321640338
Widyanto, L., & McMurran, M. (2004). The Psychometric Properties of the Internet Addiction Test. CyberPsychology & Behavior, 7, 443-450. https://doi.org/10.1089/cpb.2004.7.443
Young, K. S. (1998). Internet Addiction: The Emergence of a New Clinical Disorder. CyberPsychology & Behavior, 1, 237-244. https://doi.org/10.1089/cpb.1998.1.237