Dienst van SURF
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BACKGROUND: Most studies on multiple health risk behaviors among adolescents have cross-sectionally studied a limited number of health behaviors or determinants.PURPOSE: To examine the prevalence, longitudinal patterns and predictors of individual and multiple health risk behaviors among adolescents.METHODS: Eight health risk behaviors (no regular consumption of fruit, vegetables or breakfast, overweight or obesity, physical inactivity, smoking, alcohol use and cannabis use) were assessed in a prospective population study (second and third wave). Participants were assessed in three waves between ages 10 and 17 (2001-2008; n=2230). Multiple linear regression was used to assess the influence of gender, self-control, parental health risk behaviors, parental monitoring and socioeconomic factors on the number of health risk behaviors adjusted for preceding multiple health risk behaviors (analysis: 2013-2014).RESULTS: Rates of >5 health risk behaviors were high: 3.6% at age 13.5 and 10.2% at age 16. Smoking at age 13.5 was frequently associated with health risk behaviors at age 16. No regular consumption of fruit, vegetables and breakfast, overweight or obesity, physical inactivity and smoking predicted the co-occurrence of health risk behaviors at follow-up. Significant predictors of the development of multiple health risk behaviors were adolescents' levels of self-control, socioeconomic status and maternal smoking.CONCLUSIONS: Multiple health risk behaviors are common among adolescents. Individual and social factors predict changes in multiple health risk behaviors, showing that prevention targeting multiple risk behaviors is needed. Special attention should be paid to adolescents with low self-control and families with low socioeconomic status or a mother who smokes.
Background: The aims of this systematic review were to study the effectiveness of primary school-based physical activity, sedentary behavior and nutrition interventions with direct parental involvement on children’s BMI or BMI z-score, physical activity, sedentary behavior and nutrition behavior and categorize intervention components into targeted socio-cognitive determinants and environmental types using the Environmental Research framework for weight Gain prevention. Methods: In March 2018, a systematic search was conducted in four electronic literature databases. Articles written in English about effectiveness studies on school-based interventions with direct parental involvement targeting 4–12 year olds were included. Interventions with indirect parental involvement, interventions not targeting the school environment, and pilot studies were excluded. Study and intervention characteristics were extracted. Study quality and study effectiveness were assessed and effect sizes (Cohen’s d) were calculated for the outcome measures. Types of socio-cognitive factors and environmental types targeted were distinguished. Results: In total, 25 studies were included. Most studies on BMI or BMI z-score, physical activity and sedentary behavior found favorable results: 61.1%, 81.1% and 75%, respectively. Results regarding nutrition behavior were inconclusive. Methodological study quality varied. All interventions targeted multiple environmental types in the school and family environment. Five targeted socio-cognitive determinants (knowledge, awareness, attitude, self-efficacy and intrinsic motivation) of the children were identified. No consistent pattern was found between either type of environment targeted, number of type of environment targeted, or the child’s targeted socio-cognitive determinants and intervention effectiveness. Discussion: School-based interventions with direct parental involvement have the potential to improve children’s weight status, physical activity and sedentary behavior. Based on the results, it is recommended that school-based interventions with direct parental involvement target more than one EBRB, last at least one year, and focus particularly on the physical and social environment within both the school and the family environment
Parents who grew up without digital monitoring have a plethora of parental monitoring opportunities at their disposal. While they can engage in surveillance practices to safeguard their children, they also have to balance freedom against control. This research is based on in-depth interviews with eleven early adolescents and eleven parents to investigate everyday negotiations of parental monitoring. Parental monitoring is presented as a form of lateral surveillance because it entails parents engaging in surveillance practices to monitor their children. The results indicate that some parents are motivated to use digital monitoring tools to safeguard and guide their children, while others refrain from surveillance practices to prioritise freedom and trust. The most common forms of surveillance are location tracking and the monitoring of digital behaviour and screen time. Moreover, we provide unique insights into the use of student tracking systems as an impactful form of control. Early adolescents negotiate these parental monitoring practices, with responses ranging from acceptance to active forms of resistance. Some children also monitor their parents, showcasing a reciprocal form of lateral surveillance. In all families, monitoring practices are negotiated in open conversations that also foster digital resilience. This study shows that the concepts of parental monitoring and lateral surveillance fall short in grasping the reciprocal character of monitoring and the power dynamics in parent-child relations. We therefore propose that monitoring practices in families can best be understood as family surveillance, providing a novel concept to understand how surveillance is embedded in contemporary media practices among interconnected family members.
MULTIFILE