Introduction. Social prescribing (SP) is an integrated care program aimed to improve individuals’ health and wellbeing. Understanding the influence of SP and determining best practices and processes are challenging due to variability in its delivery, implementation, and intervention characteristics between different studies and countries. This study aimed to identify the intervention characteristics, mechanisms, and outcomes associated with SP research and explore how these factors relate to the influence of SP on health and wellbeing, healthcare utilization, and care experiences. Method. A comprehensive search was conducted in twelve databases, Google Scholar, and reference lists of relevant studies published from January 2010 up to April 2023. Searches were limited to literature written in English or Dutch. We utilized ASReview, an open‐source machine learning tool, to conduct title and abstract screening. The methodological quality of the included studies was assessed using the Mixed Methods Appraisal Tool, and the risk of bias was evaluated using the Cochrane RoB2 and the ROBINS‐I. We coded all intervention characteristics, mechanisms, and relevant outcomes. Quantitative data were visually presented using Harvest Plots, and qualitative data were narratively summarized. Results and Discussion. In total, 49 papers were included, of which seven qualitative, seventeen quantitative, and 25 mixed method studies. The findings highlight the importance of social‐related mechanisms, including loneliness and social connectedness, in contributing to the observed positive influence of SP on mental health and wellbeing. The observed outcomes seem to be influenced by various characteristics, including gender, age, the presence of a link worker, and the use of behavior change techniques. However, we should be cautious when interpreting these results due to limitations in study designs, such as the lack of controlled trials and statistical considerations. Further rigorous research is needed to comprehensively understand the impact and potential benefits of SP.

Introduction: Behavior change techniques (BCTs) are considered as active components of implementation strategies, influencing determinants and, ultimately, implementation performance. In our previous Delphi study, experts formulated ‘implementation hypotheses’, detailing how specific combinations of BCTs and strategies (referred to as BCT-strategy combinations) might influence determinants and guideline implementation within youth care. For example, educational meetings providing instructions on guideline use were hypothesized to enhance practitioners' knowledge and, consequently, guideline implementation. However, these hypotheses have not been verified in practice yet. Method: We conducted a cross-sectional study involving practitioners and management professionals from youth (health)care organizations. Using questionnaires, we obtained data on the presence of BCT-strategy combinations and their perceived influence on determinants and implementation performance. Chi-squared tests and regression analyses were employed to determine the influence of specific BCT-strategy combinations on determinants and implementation performance. Results: Our analyses included data from 104 practitioners and 34 management professionals. Most of the management professionals indicated that the BCT-strategy combinations positively influenced or had the potential to influence their implementation performance. At the practitioner level, half of the combinations were perceived to have a positive influence on determinants and implementation performance. Furthermore, practitioners who reported the absence of BCT-strategy combinations were more skeptical about their potential influence on determinants and implementation performance. Conclusion: Several BCT-strategy combinations were perceived to improve or potentially improve implementation performance of both practitioners and management professionals. In the development and evaluation of implementation efforts, we advocate for clearly describing the implementation effort’s objective and using frameworks that detail the BCTs inducing behavior change, the strategy employed, and the processes driving the observed changes. Understanding these interconnected processes is important in designing targeted, evidence-based behavior change interventions. This understanding optimizes resource allocation and contributes to the overall success of implementation efforts in youth care.

This study examined social and physical environmental exposures, health, and healthcare utilization among children aged 0–12 in urban areas. A population-based cross-sectional design was used, incorporating general practitioners’ data (2018–2019, n = 14,547), and societal and environmental data. Latent class analysis identified three distinct classes based on child and family demographics: ‘Dutch-origin two-parent household’ (n = 7267), ‘households with diverse countries of origin’ (n = 4313), and ‘single-parent household’ (n = 2967). Binary and multinomial logistic regression examined associations with environmental factors and child health outcomes. Children from the Dutch-origin class most often had favorable family demographics, neighborhood conditions, and health outcomes. Children from the diverse countries of origin class most often faced adverse neighborhood conditions, had higher rates of physical or somatic health conditions, and higher healthcare costs. Children from the single-parent class more often had less favorable family demographics, a higher likelihood of mental health problems, more frequent general practitioner visits, and were often in contact with youth care. This study highlights how child and family demographics and social and neighborhood conditions impact child health and healthcare utilization. Future approaches should focus on strategies to build and strengthen family and community resilience and adopt family-centered, context-sensitive interventions.

Background: The implementation of youth care guidelines remains a complex process. Several evidence–based frameworks aid the identification and specification of implementation determinants and strategies. However, the influence of specific strategies on certain determinants remains unclear. Therefore, we need to clarify which active ingredients of strategies, known as behaviour change techniques (BCTs), elicit behaviour change and improve implementation outcomes. With this knowledge, we are able to formulate evidence–based implementation hypotheses. An implementation hypothesis details how determinants and in turn, implementation outcomes might be influenced by specific implementation strategies and their BCTs. We aimed to identify (1) determinants relevant to the implementation of youth care guidelines and (2) feasible and potentially effective implementation hypotheses. Methods: A four–round online modified Delphi study was conducted. In the first round, experts rated the implementation determinants based on their relevance. Next, experts formulated implementation hypotheses by connecting BCTs and implementation strategies to determinants and were asked to provide a rationale for their choices. In round three, the experts reconsidered and finalised their hypotheses based on an anonymous overview of all formulated hypotheses, including rationales. Finally, the experts rated the implementation hypotheses based on their potential effectiveness and feasibility. Results: Fourteen experts completed the first, second, and third rounds, with 11 completed the final round. Guideline promotion, mandatory education, presence of an implementation leader, poor management support, knowledge regarding guideline use, and a lack of communication skills were reported as most relevant determinants. In total, 46 hypotheses were formulated, ranging from 6 to 9 per determinant. For each determinant, we provide an overview of the implementation hypotheses that were most commonly deemed feasible and potentially effective. Conclusion: This study offers valuable insights into youth care guideline implementation by systematically identifying relevant determinants and formulating hypotheses based on expert input. Determinants related to engagement and to knowledge and skills were found to be relevant to youth care guideline implementation. This study offers a set of hypotheses that could help organisations, policymakers, and professionals guide the implementation process of youth care guidelines to ultimately improve implementation outcomes. The effectiveness of these hypotheses in practice remains to be assessed.

Introduction: The Context-sensitive Positive Health Questionnaire (CPHQ) was developed to measure broad health, grounded in Positive Health and the Capability Approach. Through co-creation with professionals from various domains and citizens, including those with lower socioeconomic position, the instrument was revised into a 28-item version. This study evaluates its psychometric properties. Methods: This longitudinal study used a stratified sample of Dutch adults to evaluate the psychometric properties of the revised 28-item CPHQ, including factorial and concurrent validity, reliability, and responsiveness. Factorial validity was assessed using Exploratory Factor Analysis, Item Response Theory, and Confirmatory Factor Analysis. Concurrent validity was examined via correlations with existing health and wellbeing measures. Subgroup comparisons were conducted to assess discriminative validity, using independent samples t-tests or ANOVA. Mixed models and Kappa were used to assess test-retest reliability across three timepoints, controlling for life events. Results: Factor analyses supported an eight-factor structure (mental relaxation, social acceptance, wellbeing, vitality, social support, financial resources, health literacy, mobility) explaining 59.2% of the variance, with good model fit. Internal consistency was acceptable, with composite reliability ranging from 0.59 (health literacy) to 0.90 (financial resources). Concurrent validity was supported by strong correlations with related constructs, particularly in wellbeing, vitality, and social support. Subgroup analyses confirmed hypothesized differences across gender, age, socioeconomic position, and life events, supporting the discriminative validity of the CPHQ2.0. The CPHQ2.0 showed good test-retest reliability (ICCs mostly >0.70), with the total score showing highest stability (ICC=0.88). Kappa values indicated moderate to substantial agreement across timepoints. Conclusion: The CPHQ2.0 is a valid and reliable tool for measuring broad, context-sensitive health, grounded in the Capability Approach and Positive Health concept. Developed with input from diverse stakeholders, it is suitable for use in research, policy, and to target and evaluate health promoting interventions. Future research should assess its sensitivity to detect changes over time following interventions, and explore applicability across settings and populations.

Background: The increase of adolescent multimorbidity in welfare states is a major concern for current and future population health. However, current health interventions remain insufficient. Syndemic research among adolescents in high-income countries could improve understanding of mechanisms contributing to social and health inequalities. This study explores the existence of clustered health conditions among adolescents aged 10–19 registered at general practices in two average Dutch cities: The Hague and Leiden. We examine which social and contextual factors are associated with these clustered health conditions and to what extent these clusters relate to healthcare use and costs. Methods: This cross-sectional study used general practitioner registration data on diagnoses from the Extramural Leiden University Medical Centrum Academic Network database to explore multimorbidity based on the 2-year prevalence of 20 health conditions among adolescents (n=10 841). Latent class analysis was applied to distinguish multimorbidity classes. Statistics Netherlands provided information on factors at the individual (eg, country of origin), family (eg, divorced parents) and household (eg, income) levels. Multinomial logistic regression analysis was applied to identify multimorbidity class differences in these social contextual factors, healthcare use and costs. Results: In 2018 and 2019, 25.7% (n=2781) of adolescents had at least two health conditions. We identified four classes characterised by a high probability of health conditions: ‘asthma-skin conditions’ (n=442), ‘skin conditions-pain’ (n=794), ‘externalising behavioural disorders and skin conditions’ (n=565) and ‘gastrointestinal conditions, internalising disorders and pain’ (n=980). Adolescents in classes characterised by externalising or internalising conditions combined with physical and somatic health conditions were most often linked to several more prominent adverse social contextual factors, such as early school dropout. Increased healthcare use and costs across all classes indicated a higher disease burden for adolescents with clustered health conditions compared with those with one or no health conditions. Conclusions: Disease clusters are prevalent in adolescents living in Dutch cities, driven by social contextual factors at the individual, household and parental levels, and show increased healthcare use and costs. Our results support the need for integrated preventative strategies focusing on multi-level aspects.