Van Dyck et al. BMC Public Health 2011, 11:668 http://www.biomedcentral.com/1471-2458/11/668 connection) available for use in their home. In addition, participants were asked about the size of their largest TV set. To obtain this information, five pictures of different TVs (screen diagonals ranging from 39 cm to 139 cm) were shown and participants were asked to indicate which TV resembled their own TV the most. Psychosocial variables All questions on psychosocial variables, except for social norm from family and friends, were derived from a validated questionnaire developed by Norman and collea- gues [26] in the context of the PACE (Physician-based Assessment and Counseling for Exercise) study. This ques- tionnaire has been mainly used in adolescent research, but since no specific psychosocial questionnaires have been developed for use in adults yet, it was used as a basis for the present adult study. Pros and cons of reducing screen time, self-efficacy about reducing screen time, and social norm from family and friends were included. The ques- tions to assess social norm from family and friends were based on previously validated questions to measure social norms towards physical activity [27,28]. The wording of the original physical activity-related questions was changed to reflect social norm towards the targeted SBs. Table 1 shows the contents of the different questions. Computation of the relevant scales was based on the scoring protocol used in the PACE study [26]. Factor analyses confirmed the applicability of the original scoring protocol [26] to the present data. Internal consistency of the scales was moder- ate-to-good, with Cronbach Alpha values ranging from 0.50 to 0.78 (Table 1). All psychosocial correlates were rated on a five-point (one to five) Likert scale. For pros and cons of reducing screen time and social norm from family and friends, the response options ranged from ‘strongly disagree’ to ‘strongly agree’, while for self-efficacy about reducing screen time, the descriptors for the options ranged from ‘I think this is very difficult’ to ‘I do not think this is difficult at all’. Data Analysis All analyses were run using SPSS 16.0 for Windows. Multiple linear regression analyses were executed to inves- tigate associations of socio-demographic, psychosocial and home-environmental factors with the outcome measures. Dependent variables were min/week of TV viewing time and min/week of leisure-time Internet use. Because both dependent variables were positively skewed, logarithmic transformations were applied to improve normality [29]. Independent variables included gender, age, education, employment status and BMI (socio-demographic vari- ables), number of TVs/computers and size of largest TV set (home-environmental variables) and the following psychosocial variables: pros and cons of reducing TV viewing/Internet use (sum scores), self-efficacy about reducing TV viewing/Internet use (sum scores) and social Page 3 of 10 norm from family and friends. To investigate whether the associations of the psychosocial and home-environmental factors with TV viewing time/leisure-time Internet use dif- fered by gender, age and education, moderated multiple regression analyses were executed. To test for these poten- tial moderating effects, the cross-product terms of gender/ age/education with the different psychosocial and home- environmental factors were entered in a hierarchical multiple regression (block 2) after the main effects of the socio-demographic, home-environmental and psychosocial factors (block 1). To check the moderating effect of each factor, three regression models were constructed, one model for each potential moderator (gender/age/educa- tion) and its cross-products with the psychosocial and home-environmental factors. To avoid high correlations between the main effects and the interaction terms and reduce the effects of multicollinearity, centered variables (raw minus mean data) were used [30]. For all analyses, statistical significance was set at 0.05. Results Sample characteristics Socio-demographic characteristics and mean scores for the home-environmental factors, psychosocial factors (sum scores and item level) and SB are shown in Table 1. Bivariate correlations of the home-environmental and psychosocial items with TV viewing time and leisure- time Internet use are presented in Table 2. The total sample consisted of 198 men (47.3%) and 221 women (52.7%). Mean age was 48.50 (12.10 years), mean BMI was 24.61 (3.90) kg/m2. Of all participants, 56.7% had a college/university degree, 70.6% was employed and 80.3% reported having a white-collar job. Compared with Belgian census data [31], the sample was more likely to be highly-educated and employed. Mean TV viewing time was 128.40 (76.74) min/day and the participants used Internet during leisure-time for on average 43.57 (46.57) min/day. Table 3 gives information on the amount of TV viewing time and Internet use according to gender, age and education. No significant correlation was found between TV viewing time and leisure-time Internet use (r = 0.029, p = 0.56). Associations of socio-demographic, home-environmental and psychosocial variables with TV viewing time (Table 4) The regression analyses showed that 39% of the variance in TV viewing time was explained by the independent variables. Regarding the socio-demographic factors, age (p < 0.001) and BMI (p = 0.030) were positively associated with TV viewing time, while educational level had a nega- tive association (p = 0.001). Size of the largest TV set was the only home-environmental factor that was positively associated with TV viewing time (p = 0.012). For the psy- chosocial variables, perceiving more cons was associated