Supportive social relationships and adolescent health risk behavior among secondary school students in El Salvador

An increasing number of studies suggest that supportive social relationships in the family and school may exert a protective effect against a number of youth health risk behaviors. This study examines the association between perceived parental social support and perceived social cohesion at school with selected youth risk behavior outcomes (physical fighting, victimization, suicidal ideation, substance use, and sexual intercourse) among 930 female and male public secondary school students studying in the central region of El Salvador. The study questionnaire comprised closed-ended items of parent/school relationships and risk behaviors based on the United States Center for Disease Control and Prevention's Youth Risk Behavior Survey. In regression analyses, female students who perceived low parental social support were significantly more likely to report engaging in all risk behaviors examined, and female students with perceptions of low school social cohesion were more likely to report suicidal ideation, binge drinking, and drug use. Perceptions of parental social support and school social cohesion held fewer but still significant associations across risk behaviors for male students. Male students who reported low parental social support were significantly more likely to report suicidal ideation, drug use and physical fighting, while male students with low perceived school social cohesion were more likely to report physical fighting but less likely to report binge drinking. This study lends support to the importance of supportive social relationships for understanding youth risk behavior and suggests that supportive families and schools may operate differently for female and male students living in El Salvador.Adolescents Risk behavior Social relationships Gender El Salvador Parental support

HIV Education for Young People: Intervention Effectiveness, Programme Development, and Future Research

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Implementation mapping: Using intervention mapping to develop implementation strategies

Background: The ultimate impact of a health innovation depends not only on its effectiveness but also on its reach in the population and the extent to which it is implemented with high levels of completeness and fidelity. Implementation science has emerged as the potential solution to the failure to translate evidence from research into effective practice and policy evident in many fields. Implementation scientists have developed many frameworks, theories and models, which describe implementation determinants, processes, or outcomes; yet, there is little guidance about how these can inform the development or selection of implementation strategies (methods or techniques used to improve adoption, implementation, sustainment, and scale-up of interventions) (1, 2). To move the implementation science field forward and to provide a practical tool to apply the knowledge in this field, we describe a systematic process for planning or selecting implementation strategies: Implementation Mapping. Methods: Implementation Mapping is based on Intervention Mapping (a six-step protocol that guides the design of multi-level health promotion interventions and implementation strategies) and expands on Intervention Mapping step 5. It includes insights from both the implementation science field and Intervention Mapping. Implementation Mapping involves five tasks: (1) conduct an implementation needs assessment and identify program adopters and implementers; (2) state adoption and implementation outcomes and performance objectives, identify determinants, and create matrices of change objectives; (3) choose theoretical methods (mechanisms of change) and select or design implementation strategies; (4) produce implementation protocols and materials; and (5) evaluate implementation outcomes. The tasks are iterative with the planner circling back to previous steps throughout this process to ensure all adopters and implementers, outcomes, determinants, and objectives are addressed. Discussion: Implementation Mapping provides a systematic process for developing strategies to improve the adoption, implementation, and maintenance of evidence-based interventions in real-world settings

A taxonomy of behaviour change methods: An Intervention Mapping approach

In this paper, we introduce the Intervention Mapping (IM) taxonomy of behaviour change methods and its potential to be developed into a coding taxonomy. That is, although IM and its taxonomy of behaviour change methods are not in fact new, because IM was originally developed as a tool for intervention development, this potential was not immediately apparent. Second, in explaining the IM taxonomy and defining the relevant constructs, we call attention to the existence of parameters for effectiveness of methods, and explicate the related distinction between theory-based methods and practical applications and the probability that poor translation of methods may lead to erroneous conclusions as to method-effectiveness. Third, we recommend a minimal set of intervention characteristics that may be reported when intervention descriptions and evaluations are published. Specifying these characteristics can greatly enhance the quality of our meta-analyses and other literature syntheses. In conclusion, the dynamics of behaviour change are such that any taxonomy of methods of behaviour change needs to acknowledge the importance of, and provide instruments for dealing with, three conditions for effectiveness for behaviour change methods. For a behaviour change method to be effective: (1) it must target a determinant that predicts behaviour; (2) it must be able to change that determinant; (3) it must be translated into a practical application in a way that preserves the parameters for effectiveness and fits with the target population, culture, and context. Thus, taxonomies of methods of behaviour change must distinguish the specific determinants that are targeted, practical, specific applications, and the theory-based methods they embody. In addition, taxonomies should acknowledge that the lists of behaviour change methods will be used by, and should be used by, intervention developers. Ideally, the taxonomy should be readily usable for this goal; but alternatively, it should be clear how the information in the taxonomy can be used in practice. The IM taxonomy satisfies these requirements, and it would be beneficial if other taxonomies would be extended to also meet these needs