Clustering of health-compromising behavior and delinquency in adolescents and adults in the Dutch population

Nieuwenhuijzen, M. van; Junger, Marianne; Velderman, M. Klein; Wiefferink, Karin H.; Paulussen, Theo; Hox, Joop J.; Reijneveld, Sijmen A.

doi:10.1016/j.ypmed.2009.04.008

Cited by 115 publications

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“…There is ample evidence that adolescence is a period of increased risk behaviour (Burke et al, 1997;van Nieuwenhuijzen et al, 2009). Moreover, research suggests that those engaging in one type of risk behaviour often additionally do so in others, i.e.…”

Section: Introductionmentioning

confidence: 99%

“…In relation to adolescence, one explanation put forward is that teenagers combine sensation-seeking with a relative lack in impulse control (Peach & Gaultney, 2013;Steinberg et al, 2008;van Nieuwenhuijzen et al, 2009). Recent empirical evidence suggests that, similar to offline risk experiences, online risk experiences do often co-occur and are associated with similar characteristics (Hasebrink, Görzig, Haddon, Kalmus, & Livingstone, 2011).…”

Section: Introductionmentioning

confidence: 99%

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Adolescents’ experience of offline and online risks: Separate and joint propensities

Görzig

2016

Computers in Human Behavior

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Adolescence is a period of increased risk experience and ever more often these occur online.The current study aims to investigate whether adolescents' online and offline risk experiences are driven by the same general propensity to risks. Data from a representative study of N = 19,406 (50% girls) internet-using 11-16 year olds (M = 13.54, SD = 1.68) youth in Europe were subjected to the current analyses. Three confirmatory factor analyses were applied to measures of offline and online risk experiences (five each). A bi-factor model of a general risk factor and two specific factors of online and offline risks was shown to provide the best theoretical and empirical fit. All risk experiences loaded significantly on the general risk factor while additionally all offline risks loaded significantly on the offline risk factor.However, none of the online risks loaded significantly on the online risk factor. Online risks could not be explained by factors that go beyond a general propensity to experience risks suggesting that new technologies do not bring with them a new type of risk propensity driven by that environment. Interventions should target risk and protective factors that can account for adolescents' experiences across risk types (online and offline).

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adolescents’ experience of offline and online risks: Separate and joint propensities

Görzig

2016

Computers in Human Behavior

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“…Figure 1. World Health Organization model of the whole school approach, adapted from Wynn, Cahill, Holdsworth, Rowling, and Carson (2000) from Hendren, Birrell, Weissen, and Orley (1994) In addition, accumulating evidence shows many health behaviors in adolescents to cluster (De Bruijn & Van Den Putte, 2009;De Vries et al, 2008;Peters et al, 2009;Van Nieuwenhuijzen et al, 2009). Increasingly studies show such clustered behaviors to be most effectively tackled via interventions that address these behaviors simultaneously via a multi-behavioral approach instead of by single-behavior initiatives (Burke et al, 1997;Ottevaere et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Development and implementation of a tailored health promoting school in The Netherlands: Lessons learned

Busch¹,

Leeuw²,

Schrijvers³

2013

IJRSE

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This paper presents the lessons learned from the design and implementation of a whole school Health Promoting School (HPS) pilot on a high school in The Netherlands. This pilot aims to improve a range of health behaviours in adolescents via the Whole School Approach of Health Promoting Schools framework of the WHO-supported Schools for Health in Europe initiative (SHE). Eleven semi-structured interviews were held with key stakeholders in the intervention's design and implementation. Results showed that becoming a HPS should be considered a comprehensive curriculum change that requires significant organizational investments. By integrating the intervention instead of implementing it "as is" into school's existing infrastructure the additional burden to the curriculum was minimized; this was important for intervention relevance and it strengthens feelings of intervention ownership and motivation among teachers. Also, implementation should be led by a steering group of professionals from health sciences and education as well as parents, students and teachers from the school to combine knowledge on practical feasibility and evidence based practices. Teachers should be further educated to increase competence in their new role. Lastly, a central coordinator with proper personal competencies and power to get things done is necessary to steer these developments. Since not all schools are able to make the necessary investments, successfully becoming a HPS is not feasible for just any school at any point in time; it has to be considered a well-planned comprehensive system change. Schools with competing problems such as school violence or organizational struggles should postpone HPS developments.

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“…The latter type of clusters will be used in this study. The following clusters were found: a cluster of healthy eating and physical activity (Lippke et al, 2012), a cluster of smoking and alcohol abuse (Wiefferink et al, 2006), three separate clusters of, respectively, health-promoting behaviours, alcohol/sexual behaviour, and delinquent behaviours (Van Nieuwenhuijzen et al, 2009).The existence of health behaviour clusters has triggered some researchers to search for factors associated with these clusters (e.g. Brooks, Magnussen, Spencer, & Morgan, 2012;Prochaska, 2008).…”

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confidence: 99%

“…We disregarded the group of proximal factors, because these factors can be expected to have more behaviour-specific influences, while we focus on non-behaviour-specific influences. Furthermore, it is known that effective prevention strategies also include some distal and ultimate factors, while most studies focus on proximal factors (see Donath et al, 2012).The following three behaviour clusters found by Van Nieuwenhuijzen et al (2009) are used as outcomes: Health (including having breakfast, fruit consumption, non-smoking, hours of sleep and physical activity), Alcohol (including alcohol consumption and unsafe sexual behaviour) and Delinquency (including physical and verbal aggression, delinquent behaviour, drug abuse, and jumping traffic lights). The study aims to identify factors associated with several of these clusters and to assess whether their associations follow the pathways as hypothesised by the Theory of Triadic Influence.…”

mentioning

confidence: 99%

Targets for primary prevention: Cultural, social and intrapersonal factors associated with co-occurring health-related behaviours

Dusseldorp

Velderman

Paulussen

et al. 2014

Psychology & Health

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Objective: Multiple studies have identified clusters of co-occurring healthrelated behaviours. Little is known, however, about factors associated with such clusters. This study aims to identify these factors and to assess whether their effects are in accordance with the Theory of Triadic Influence (TTI). Design: A cross-sectional study using a representative sample (N = 3497) of the Dutch population aged 19-40. Main Outcome Measures: Our data concerned 18 health-related behaviours combined in three clusters (Health, Alcohol and Delinquency) and 30 non-behaviour-specific (i.e. ultimate or distal) cultural, social and intrapersonal factors. The three clusters were used as outcomes in regression analyses. Results: Descriptive Norms of Friends and Gender were associated with all three behaviour clusters. Furthermore, Having Parents who Smoke or Consume Alcohol was associated with, respectively, the Health and Alcohol clusters. Self-Control and past Parental Monitoring were associated with the Health and Delinquency clusters. Effect sizes were moderate to large (r 2 : 0.05 to 0.22). Conclusion: Factors with a moderate to large association with several behaviour clusters were identified. These factors were located within the social and intrapersonal stream of the TTI, not within the cultural stream.Keywords: multiple risk behaviour; theory of triadic influence; self-control; delinquency; descriptive norm; parental monitoring; determinant; cluster IntroductionDuring the past decade, health-related behaviours have frequently been shown to co-occur (e.g. Conry et al., 2011;Faeh, Viswanathan, Chiolero, Warren, & Bovet, 2006;Lippke, Nigg, & Maddock, 2012;Poortinga, 2007;Schuit, Van Loon, Tijhuis, & Ocke, 2002;Van Nieuwenhuijzen et al., 2009;Wiefferink, et al., 2006 investigated co-occurrence of health behaviours in several ways. Some studies looked at joint prevalences, i.e. the prevalence of combinations of risk behaviours (e.g. Faeh et al., 2006;Poortinga, 2007;Schuit et al., 2002). Some studies identified clusters of persons who show the same behaviours (e.g. Conry et al., 2011). Other studies identified clusters (also called factors) of behaviours closely associated with each other. The latter type of clusters will be used in this study. The following clusters were found: a cluster of healthy eating and physical activity (Lippke et al., 2012), a cluster of smoking and alcohol abuse (Wiefferink et al., 2006), three separate clusters of, respectively, health-promoting behaviours, alcohol/sexual behaviour, and delinquent behaviours (Van Nieuwenhuijzen et al., 2009).The existence of health behaviour clusters has triggered some researchers to search for factors associated with these clusters (e.g. Brooks, Magnussen, Spencer, & Morgan, 2012;Prochaska, 2008). If such factors exist, then there would be support for the development of more integrated approaches to promoting healthier lifestyles. In the words of Prochaska (2008) 'Multiple Health Behaviour Research represents the future of preventive medicine' (p. 281). Some stud...

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Clustering of health-compromising behavior and delinquency in adolescents and adults in the Dutch population

Cited by 115 publications

References 58 publications

Adolescents’ experience of offline and online risks: Separate and joint propensities

Adolescents’ experience of offline and online risks: Separate and joint propensities

Development and implementation of a tailored health promoting school in The Netherlands: Lessons learned

Targets for primary prevention: Cultural, social and intrapersonal factors associated with co-occurring health-related behaviours

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