The present study evaluates the Youth Initiated Mentoring (YIM) approach in which families and youth care professionals collaborate with an informal mentor, who is someone adolescents (aged twelve to twenty-three) nominate from their own social network. The informal mentor can be a relative, neighbour or friend, who is a confidant and spokesman for the youth and a co-operation partner for parents and professionals. This approach fits with the international tendency in social work to make use of the strengths of families’ social networks and to stimulate client participation. The current study examined through case-file analysis of 200 adolescents (YIM group n ¼ 96, residential comparison group n ¼ 104) whether the YIM approach would be a promising alternative for out-of-home placement of youth with complex needs. A total of 83 per cent of the juveniles in the YIM group were able to nominate a mentor after an average of thirty-three days. Ninety per cent of the adolescents in the YIM group received ambulatory treatment as an alternative for indicated out-of-homeplacement, while their problems were largely comparable with those of juveniles in Dutch semi-secure residential care. Results suggest that the involvement of important non-parental adults may help to prevent out-of-home placement of adolescents with complex needs.
MULTIFILE
Knowledge of how professional youth work might prevent individual and social problems in socially vulnerable youngsters is poorly developed. This article presents a conceptual framework that clarifies the implicit methodical process used by professional youth workers and focuses on what stakeholders regard as the potential of professional youth work as a preventive service. A qualitative research synthesis approach was used to combine the findings of six practice-based studies conducted in six European countries. This synthesis revealed that professional youth workers employ a multi-methodic approach in their prevention efforts, strengthening the social skills and self-mastery of youngsters, reinforcing their social network, enhancing their civic participation and helping them find additional social or health services. Twelve methodic principles were identified as contributing to achieving these prevention efforts, shedding light on the process taking place between youngsters and youth workers. This conceptual framework provides essential information for future evaluation research.
DOCUMENT
When it comes to hard to solve problems, the significance of situational knowledge construction and network coordination must not be underrated. Professional deliberation is directed toward understanding, acting and analysis. We need smart and flexible ways to direct systems information from practice to network reflection, and to guide results from network consultation to practice. This article presents a case study proposal, as follow-up to a recent dissertation about online simulation gaming for youth care network exchange (Van Haaster, 2014).
DOCUMENT
Youth care is under increasing pressure, with rising demand, longer waiting lists, and growing staff shortages. In the Netherlands, one in seven children and adolescents is currently receiving youth care. At the same time, professionals face high workloads, burnout risks, and significant administrative burdens. This combination threatens both the accessibility and quality of care, leading to escalating problems for young people and families. Artificial intelligence (AI) offers promising opportunities to relieve these pressures by supporting professionals in their daily work. However, many AI initiatives in youth care fail to move beyond pilot stages, due to barriers such as lack of user acceptance, ethical concerns, limited professional ownership, and insufficient integration into daily practice. Empirical research on how AI can be responsibly and sustainably embedded in youth care is still scarce. This PD project aims to develop practice-based insights and strategies that strengthen the acceptance and long-term adoption of AI in youth care, in ways that support professional practice and contribute to appropriate care. The focus lies not on the technology itself, but on how professionals can work with AI within complex, high-pressure contexts. The research follows a cyclical, participatory approach, combining three complementary implementation frameworks: the Implementation Guide (Kaptein), the CFIR model (Damschroder), and the NASSS-CAT framework (Greenhalgh). Three case studies serve as core learning environments: (1) a speech-to-text AI tool to support clinical documentation, (2) Microsoft Copilot 365 for organization-wide adoption in support teams, and (3) an AI chatbot for parents in high-conflict divorces. Throughout the project, professionals, clients, ethical experts, and organizational stakeholders collaborate to explore the practical, ethical, and organizational conditions under which AI can responsibly strengthen youth care services.
