Abstract
In the areas of prevention and health promotion, there is a large number of measures for children and adolescents. One way of facilitating evidence-based action for those involved in these taks is by making available online evidence registers with customised, effectiveness-tested measures. The Green List Prevention is such a register and offers an overview of evidence-based programmes in Germany, currently with a focus on psychosocial health. The aims of this study were (a) to analyse the characteristics of the available and evaluated programmes on the psychosocial health of children and adolescents, (b) to identify priorities and underrepresented areas of the Green List Prevention and (c) to optimise the search functions of the register. The characteristic features were recorded on the basis of the existing upper categories of the register entries which were differentiated into subcategories in an inductive procedure by at least two persons. In addition, deductive categories were added for relevant aspects concerning content and implementation. The upper and lower categories formed were operationalized with characteristic values. All entries were analyzed by using a data sheet and were descriptively evaluated. The 102 programmes listed (as of 2/2024) addressed not only the primary target group of children and youth, but also secondary target groups (mainly teachers and guardians). Social and life skills programmes as well as trainings for guardians represented a focus. Behavioral prevention programmes on the topics of violence (including bullying) (63.7%), addiction (46.1%) and/or mental health (35.3%) were frequently represented, whereas nutrition and/or physical activity (4.9%) were hardly represented. Most of the programmes (88.2%) could be assigned to the eligibility criteria of the statutory health insurers (§20a SGB V). Potentials digital implementation forms and further implementation aspects were identified. The Green List Prevention bundles a large number of different measures and that there is potential for expansion. Processing knowledge about effective measures in a user-friendly manner can be optimised through expanded search functions, so that resource-conserving, evidence-based action can be facilitated.
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