Elsevier

Academic Pediatrics

Volume 9, Issue 5, September–October 2009, Pages 307-314
Academic Pediatrics

Media
Electronic Media Use and Adolescent Health and Well-Being: Cross-Sectional Community Study

https://doi.org/10.1016/j.acap.2009.04.003Get rights and content

Objective

To describe time adolescents spend using electronic media (television, computer, video games, and telephone); and to examine associations between self-reported health/well-being and daily time spent using electronic media overall and each type of electronic media.

Methods

Design–Cross-sectional data from the third (2005) wave of the Health of Young Victorians Study, an Australian school-based population study. Outcome Measures–Global health, health-related quality of life (HRQoL; KIDSCREEN), health status (Pediatric Quality of Life Inventory 4.0; PedsQL), depression/anxiety (Kessler-10), and behavior problems (Strengths and Difficulties Questionnaire). Exposure Measures–Duration of electronic media use averaged over 1 to 4 days recalled with the Multimedia Activity Recall for Children and Adolescents (MARCA) computerized time-use diary. Analysis–Linear and logistic regression; adjusted for demographic variables and body mass index z score.

Results

A total of 925 adolescents (mean ± standard deviation age, 16.1 ± 1.2 years) spent, on average, 3 hours 16 minutes per day using electronic media (television, 128 minutes per day; video games, 35; computers, 19; telephone, 13). High overall electronic media use was associated with poorer behavior, health status, and HRQoL. Associations with duration of specific media exposures were mixed; there was a favorable association between computer use (typing/Internet) and psychological distress, whereas high video game use was associated with poorer health status, HRQoL, global health, and depression/anxiety. Television and telephone durations were not associated with any outcome measure.

Conclusions

Despite television's associations with obesity, time spent in other forms of media use appear more strongly related to adolescent health and well-being. This study supports efforts to reduce high video game use and further exploration of the role of computers in health enhancement.

Section snippets

Design

Data were drawn from the third wave of the population-based longitudinal Health of Young Victorians Study, whose design has been reported elsewhere.20 Briefly, participants were selected for wave 1 in 1997 from across the state of Victoria, Australia, by means of a stratified 2-stage random sampling design based on school education sector (government, Catholic, or independent) and year level. The baseline response rate for prep (first school year) through third grade students was 83.2% (1943 of

Results

The sample comprised 925 adolescents (466 boys; mean ± SD age 16.1 ± 1.2 years), of whom 80 (8.7%) were in the first (most disadvantaged) SEIFA quartile, and of whom 239 (26.1%), 312 (34%), and 286 (31.2%) were in the second, third, and fourth (least disadvantaged) quartiles, respectively. The average PedsQL (health status) total mean score was 79.7 ± 10.8, the average SDQ (behavior) Total Difficulties score was 9.3 ± 5.0, and the mean KIDSCREEN (HRQoL) value was 47.5 ± 7.1. Although most participants

Discussion

This study confirmed high levels of electronic media use (averaging more than 3 hours per day), with television (just over 2 hours per day) followed by video games and computers, and the least time devoted to telephone use. High levels of video game use was associated with increased psychological distress and poorer physical and psychosocial well-being, HRQoL, and global health, while computer use was weakly associated with a lower risk of psychological distress. However, television was

Acknowledgments

We thank the students and parents/guardians who participated in each of the 3 waves of the Health of Young Victorians Study (HOYVS). We also thank the many schools that allowed us to visit to survey the students. We acknowledge the work of all the field workers who conducted the data collection, as well as the full HOYVS investigator team.

The third wave of the Health of Young Victorians Study was funded by Australian National Health and Medical Research Council (NHMRC; project grant 334303). Dr

References (36)

  • M. Stratton et al.

    The Young and the Restful—The Effects of Recreational Choices and Demographic Factors on Children's Participation in Sport

    Canberra, Australia: Australian Bureau of Statistics

    (2005)
  • S.G. Trost et al.

    Gender differences in physical activity and determinants of physical activity in rural fifth grade children

    J School Health

    (1996)
  • T. Gorely et al.

    Couch kids: correlates of television viewing among youth

    Int J Behav Med

    (2004)
  • A. Bandura

    Social Learning Theory

    (1977)
  • D. Bickham et al.

    Attention, comprehension, and the educational influences of television

  • R. Kraut et al.

    Internet paradox. A social technology that reduces social involvement and psychological well-being?

    Am Psychol

    (1998)
  • P. Sun et al.

    Internet accessibility and usage among urban adolescents in Southern California: implications for Web-based health research

    Cyberpsychol Behav

    (2005)
  • C.E. Sanders et al.

    The relationship of Internet use to depression and social isolation among adolescents

    Adolescence

    (2000)
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