Differential effects of the computer-tailored FATaintPHAT programme on dietary behaviours according to sociodemographic, cognitive and home environmental factors
Public Health Nutrition , Volume 17 - Issue 2 p. 431- 439
Abstract Objective To explore whether the effects on dietary behaviours of a computer-tailored intervention aimed to prevent excessive weight gain among adolescents, FATaintPHAT, were moderated by sociodemographic, cognitive and home environmental factors. Design A two-group cluster randomized trial. Potential moderation of the outcome measures (consumption of sugar-sweetened beverages, snacks, fruits and vegetables) was studied by gender, education level, ethnicity, awareness of risk behaviour, intention and home availability. Setting Twenty schools in the Netherlands. Subjects Students (n 883) aged 12-13 years. Results Of the twenty-four interactions tested, only three were significant. The intervention effect on sugar-sweetened beverages was moderated by level of education (P = 0·009); intervention effects were found only among academic preparatory students. The intervention effects on fruit and vegetable intake were moderated by awareness of fruit intake (P < 0·001) and home availability of vegetables (P = 0·007); an effect on fruit intake was found only among students who were aware of their low fruit intake at baseline and an effect on vegetable consumption was found only among students who reported that vegetables were always available at their home. Conclusions The effects of the intervention generally did not differ between sociodemographic subgroups. The moderation by home availability illustrates that the environment may influence the effects of educational interventions.
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|Public Health Nutrition|
|Organisation||Erasmus MC: University Medical Center Rotterdam|
Ezendam, N.P.M, Burg, J, Borsboom, G.J.J.M, van Empelen, P, & Oenema, A. (2014). Differential effects of the computer-tailored FATaintPHAT programme on dietary behaviours according to sociodemographic, cognitive and home environmental factors. Public Health Nutrition, 17(2), 431–439. doi:10.1017/S1368980012005344