Socio-demographic, psychosocial and home-environmental attributes associated with adults' domestic screen time
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Updated: May 30, 2026

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
Published on: July 27, 2018
Delfien Van Dyck1, Greet Cardon, Benedicte Deforche
1Research Foundation Flanders (FWO), 1000 Brussels, Belgium. delfien.vandyck@ugent.be
Background:
Sedentary behaviors (involving prolonged sitting time) are associated with deleterious health consequences, independent of (lack of) physical activity. To inform interventions, correlates of prevalent sedentary behaviors need to be identified. We examined associations of socio-demographic, home-environmental and psychosocial factors with adults' TV viewing time and leisure-time Internet use; and whether psychosocial and environmental correlates differed according to gender, age and educational attainment.
Methods:
This cross-sectional study was conducted in Ghent, Belgium, between March and May 2010. Respondents to a mail-out survey (n = 419; 20-65 years; mean age 48.5 [12.1] years; 47.3% men) completed a questionnaire on sedentary behaviors and their potential socio-demographic, psychosocial and home environmental correlates. Statistical analyses were performed using multiple linear regression models.
Results:
The independent variables explained 31% of the variance in TV viewing time and 38% of the variance in leisure-time Internet use. Higher education, greater perceived pros of and confidence about reducing TV time were negatively associated with TV viewing time; older age, higher body mass index, larger TV set size and greater perceived cons of reducing TV time showed positive associations. Perceived pros of and confidence about reducing Internet use were negatively associated with leisure-time Internet use; higher education, number of computers in the home, positive family social norms about Internet use and perceived cons of reducing Internet use showed positive associations. None of the socio-demographic factors moderated these associations.
Conclusions:
Educational level, age, self-efficacy and pros/cons were the most important correlates identified in this study. If further cross-sectional and longitudinal research can confirm these findings, tailored interventions focusing on both psychosocial and environmental factors in specific population subgroups might be most effective to reduce domestic screen time.
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