Most multi‑problem young adults (18–27 years old) have been exposed to childhood maltreatment and/or have been involved in juvenile delinquency and, therefore, could have had Child Protection Service (CPS) interference during childhood. The extent to which their childhood problems persist and evolve into young adult‑ hood may differ substantially among cases. This might indicate heterogeneous profiles of CPS risk factors. These pro‑ files may identify combinations of closely interrelated childhood problems which may warrant specific approaches for problem recognition and intervention in clinical practice. The aim of this study was to retrospectively identify distinct statistical classes based on CPS data of multi‑problem young adults in The Netherlands and to explore whether these classes were related to current psychological dysfunctioning and delinquent behaviour. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
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Most multi‑problem young adults (18–27 years old) have been exposed to childhood maltreatment and/or have been involved in juvenile delinquency and, therefore, could have had Child Protection Service (CPS) interference during childhood. The extent to which their childhood problems persist and evolve into young adult‑ hood may differ substantially among cases. This might indicate heterogeneous profiles of CPS risk factors. These pro‑ files may identify combinations of closely interrelated childhood problems which may warrant specific approaches for problem recognition and intervention in clinical practice. The aim of this study was to retrospectively identify distinct statistical classes based on CPS data of multi‑problem young adults in The Netherlands and to explore whether these classes were related to current psychological dysfunctioning and delinquent behaviour. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
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Alliance has been shown to predict treatment outcome in family-involved treatment for youth problems in several studies.However, meta-analytic research on alliance in family-involved treatment is scarce, and to date, no meta-analytic study on the alliance–outcome association in this field has paid attention to moderating variables. We included 28 studies reporting on the alliance–outcome association in 21 independent study samples of families receiving family-involved treatment for youth problems (N= 2126 families,Mage youth ranging from 10.6 to 16.1). We performed three multilevel meta-analyses of theassociations between three types of alliance processes and treatment outcome, and of several moderator variables. The quality of the alliance was significantly associated with treatment outcome (r= .183,p< .001). Correlations were significantly stronger when alliance scores of different measurement moments were averaged or added, when families were help-seekingrather than receiving mandated care and when studies included younger children. The correlation between alliance improvement and treatment outcome just failed to reached significance (r= .281,p= .067), and no significant correlation was found between split alliances and treatment outcome (r= .106,p= .343). However, the number of included studies reporting onalliance change scores or split alliances was small. Our findings demonstrate that alliance plays a small but significant role in the effectiveness of family-involved treatment. Future research should focus on investigating the more complex systemic aspects of alliance to gain fuller understanding of the dynamic role of alliance in working with families
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