PSYCHOSOCIAL RISK FACTORS OF PROBLEMATIC SEDENTARY BEHAVIOUR AMONG HUNGARIAN ADOLESCENTS IN 2010

(1): RESEARCH INSTITUTE FOR DRUG STUDIES AND PROGRAM EVALUATION, MARVANYKOVI@RIDS.HU (2):, ELTE PPK INSTITUTE OF PSYCHOLOGY, RACZ.JOZSEF@PPK.ELTE.HU(3): NATIONAL INSTITUTE OF CHILDREN’S HEALTH (OGYEI), NAGI@OGYEI.HU

(1) Ferenc Márványkövi, (2) József Rácz, (3) Ágnes Németh

Health Behaviour in School-aged Children, 2010.

Can’t help it…

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 screen time 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 decreased subjective 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, Pearson Chi-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, region2 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)

Heavy TV viewing and excessive computer game playing (ECGP)

Type of sedentary behaviour

%

TV, DVD and VCR (N=2,066)

0-1 hour 43

2 or more than 2 hours 57

Total 100

ECGP (N=2,033)

0-1 hour 73

2 or more than 2 hours 27

Total 100

Problematic sedentary behaviour: breakdown by

genderECGP (%)TV, video, VCR (%)

Chi-square=6,44; df=1; P < 0.05 Chi-square=199,03; df=1; P < 0.00

boys girls0

10

20

30

40

50

60

70

80

90

100

4146

5954

Series32 hrs or more

boys girls0

10

20

30

40

50

60

70

80

90

100

58

86

42

14

2 hrs or moreless than 1 hr

Determinants of excessive TV, DVD and VCR viewing

Determinants OR Level of significanc

eLiving in Central Trans-danubia (ref cat.: Central Hungary)

1,10 ,002**

Having a father with lower SES 1,33 ,009**

Weaker school performance (perceived)

0,73 ,003**

More frequent EMC with friends 1,26 ,000***

* p < 0,05 ** p < 0,01*** p < 0,001

Total variance explained: 12,1% (Nagelkerke R Square)

Determinants of ECGP

Determinants OR Level of significa

nceBeing a male 0,23 ,000***

Spending more evenings with friends

1,14 ,02*

More frequent EMC with friends 1,50 ,000***

Being more depressed (ref cat.: no depression)

1,31 ,02*

Lower level of sensation seeking

0,96 ,01*

* p < 0,05 ** p < 0,01*** p < 0,001

Total variance explained: 24,1% (Nagelkerke R Square)

Main gender-related differences regarding determinants

TV, DVD, VCR

Boys Girls

Living in a single-parent family Lower SES father

Living in Trans-danubia Lack of classmate support

More frequent EMC with friends Weaker school performance (perceived)

More frequent EMC with friends

14.3% (total variance explained) 21.6% (total variance explained)

ECGP

Boys Girls

Higher age Attending a 6th grader grammar school

More evenings spent with friends Weaker school performance (perceived)

More frequent EMC with friends More frequent EMC with friends

Lower level of sensation seeking Higher level of depression

17.2% (total variance explained) 21.7% (total variance explained)

Determinants of excessive TV viewing and ECGP

Determinants OR Level of significance

Being a male ,30 ,001**

Higher maternal monitoring

1,40 ,01*

Frequent EMC with friends

1,38 ,01*

Being slightly depressed

1,51 ,02** p < 0,05 ** p < 0,01*** p < 0,001

Total variance explained: 14,0% (Nagelkerke R Square)

Boys Girls

Higher maternal monitoring Weaker school performance (perceived)

Being slightly depressed

Main gender-related differences in determinants

Discussion and conclusion 1

Results consistent with earlier research regarding determinants1 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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