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Psychosocial risk factors of problematic sedentary behaviour among Hungarian adolescents in 2010(1): Research Institute for drug studies and Program Evaluation, firstname.lastname@example.org (2):, ELTE PPK Institute of psychology, email@example.com(3): National institute of children’s health (ogyei), firstname.lastname@example.org Health Behaviour in School-aged Children, 2010. (1) FerencMárványkövi, (2) JózsefRácz, (3) ÁgnesNémeth
Introduction • Problematic sedentary behaviour: excessive TV viewing, playing video and computer games, Internet use (chatting, surfing) (Salmon et al., 2008; Must and Tybor, 2005) • Excessive: 2 hrs + a day (American Academy of Paediatrics, 2001) • Increasing screentime worldwide (WHO, 2012) • Related problems - Physical health problems: risk factor for obesity and related cardiovascular and metabolic abnormalities (Mark and Janssen, 2008; DeMattia et al., 2007). - Social health problems: disengagement from social activities and peers (Richards et al, 2010 Brown & Witherspoon, 2003). - Mental health problems: depression, anxiety, body self-image issues (Ussher et al, 2007; Brodersen et al, 2005). • Correlation of physical activity, obesity and problematic sedentary behaviour more extensively explored (Fuller et al, 2012; Kuntsche et al, 2006) • Why psychosocial background? Key-role in tackling obesity problems (Luttikhuis, et al, 2009; Wilfley et al, 2007)
Hungary: facts, trends • 2002-2010: slightly increasing screen time among school-aged children including 11th graders but still below EU average (Aszmann et al, 2003; Németh et al, 2007, 2011) • Latest wave in 2010: small amount of physical activity, great amount of screen time (Németh et al, 2011) • Problematic sedentary behaviour as predictor of decreasedsubjective psychological well-being (Németh et al, 2010)
Objectives 1 To investigate the multidimensional correlates of basic socio-demographic, socio-economic, psychosocial factors AND problematic sedentary behaviour among Hungarian adolescents (11th graders) based on the 2010 wave of HBSC study 2 To explore a useful psychosocial explanatory model for adolescent problematic sedentary behaviour
METHODS 1 • Sample and sampling method • Representative sample of Hungarian 11th graders (2,315 - 1,171 boys, 1,144 girls, mean age: 17,7, SD=0,73) • Sampling protocol used (Currie et al, 2012) • Research tool: Health Behaviour in School-Aged Children study: young people's well-being, health behaviours and their social context • Data procession and statistical analysis: SPSS 13.0, PearsonChi-square-tests, ANOVAs, binary logistic regression
METHODS 2 Dependent variables (problematic sedentary behaviour) 1 Volume of TV, DVD and VRC watching during weekdays (max1 hour, 2 hours or more) 2 Volume of playing computer games (ECGP) during weekdays (max1 hour, 2 hours or more) 3 Volume of TV and ECGP during weekdays (doing both for more than 2 hours, doing less of any) Independent variables (determinants) 1 Socio-demography: gender, age, family structure, siblings, type of school, type of settlement, region 2 Socio-economy: father’s SES, mother’s SES (5 categories, both based on employment status and education), family affluence (4 categories, based on owing a computer, car, an own bedroom, family holidays in the past 12 months) 3 School domain: perceived school performance (4 categories), attachment to school (4 categories), classmate support (3 variables added: 13 –item scale), general perception of teachers (4 variables added: 17-item scale) 4 Family domain: parental monitoring (5 variables added:17-item scale), perceived attachment to parents (3 variables added, 9-item scale), communication with parents and best friend (4-item scale) 5 Peer domain: number of friends (4 categories), num of weekday afternoons with friends (6 categories), num of evenings with friends (8 categories), electronic media contact (EMC) (weekly, 5 categories), Social Self-Esteem (5 variables added: 16-item scale) 6 Sensation seeking (Brief Sensation Seeking Scale - HOYLE et al., 2002; URBÁN, 2009) (10 variables added, 33-item scale) 7 Subjective well-being: Child Depression Scale (Kovács, 1985; Rózsa et al., 1999) (3 categories), Adolescent self-esteem (Rosenberg, 1965) (10 variables added, 30-item scale)
Problematic sedentary behaviour: breakdown by gender TV, video, VCR (%) Chi-square=6,44; df=1; P < 0.05 Chi-square=199,03; df=1; P < 0.00
Determinants of excessive TV, DVD and VCR viewing * p < 0,05 ** p < 0,01 *** p < 0,001 Total variance explained: 12,1% (Nagelkerke R Square)
Determinants of ECGP * p < 0,05 ** p < 0,01 *** p < 0,001 Total variance explained: 24,1% (Nagelkerke R Square)
Determinants of excessive TV viewing and ECGP * p < 0,05 ** p < 0,01 *** p < 0,001 Total variance explained: 14,0% (Nagelkerke R Square) Main gender-related differences in determinants
Discussion and conclusion 1 • Results consistent with earlier research regarding determinants 1 Heavy TV viewing: lower parental socioeconomic status (Rey-López et al, 2011;Fairclough et al, 2011), weaker school performance (Krosnick et al, 2010; Gentile and Walsh, 2002), single-parent families (Gorely et al, 2009; Gentile et al, 2002), lack of classmate support (Kuntsche et al, 2008) 2 ECGP: adolescent males (Iannotti et al., 2009; Mark et al., 2006), weaker school performance (Gentile et al, 2002; Chiu, Lee, and Huang, 2004), higher level of depression (Niemz, Griffiths, and Banyard, 2005; Whang, Lee, Chang, 2003), lower sensation seeking (Roberts, Foehr and Rideout, 2005), more EMC (van den Eijnden, 2008) • Results inconsistent with earlier research: low attachment to peers and heavy TV viewing and excessive ECGP (Richards et al, 2010; Lee and Chae, 2007) vs. HBSC 2010: higher attachment to peers, more ECGP (if more EMC and evenings out is interpreted as higher attachment): more EMC, more computer use (van den Eijnden, 2008)? • Low sensation seekers socialize less (Sheldon, 2012), low sensation seekers play more computer? (Extensive literature on the correlation of sensation seeking and media CONTENT (Bagdasarov et al, 2010): high sensation seeking – violent, exciting games)
Discussion and conclusion 2 • Too much screen time • Less psychosocial influence at this age • Importance of school and peer domains – less parental influence at this age • No clinical intervention is necessarily needed for excessive media users • Gender-related differences (males - peer domain, females - school domain, depression; total variance explained) • Peer influences should not necessarily be limited • Prevention strategies should take into account differences in type of media use and gender when tackling excessive media use
Limitations • Comparison with similar research was difficult (age, variables) • Great deal of communication and time spent with peers = Higher attachment?
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