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This response article discusses opportunities to bridge social work and social innovation as a promising partnership to address the issues impacting vulnerable populations across the global context. It starts by revisiting the conceptualization of innovation in social work and continues by considering factors that contribute to the growing interest in social innovation and related concepts. This article concludes by discussing differences in social work and social innovation and how these differences can be turned into opportunities for a fruitful partnership that can push both fields forward.

As part of a larger ethnographic study, this article explored the ways lowincome Kurdish families negotiated child characteristics identified as determinants in child labor decisions. Of the 27 Kurdish mothers who participated in the larger study, 18 were included for the purpose of this article. Data for this article primarily relied on demographic surveys and indepth interviews. Mothers' accounts showed that children's age, birth order, gender, and school success/continuation were critical factors in the decision-making process for child labor. Older children were more likely to work. Birth order was moderated by children's educational prospects. Gender was more critical in determining appropriate workplaces for girls and not whether they could work. In contrast to the existing literature, findings of this study showed that the relationship between child labor and education was bidirectional. More specifically, while child labor affected education, children's school success/attendance also shaped child labor decisions. Mothers' accounts also pointed to the complex and dynamic family processes that took into account children's and families' unique circumstances. As a result, this article offered a deeper understanding of family processes behind child labor decisions, which in turn had important policy and practice implications.

*PRODUCTION: please update (final ToC below in ToC Long field) Introduction -- Understanding Child Behavioral Health within the Kenyan Context: Current Efforts in Policy, Research, and Practice -- Understanding Child Behavioral Health within the Ghanaian Context: Current Efforts in Policy, Research, and Practice -- Understanding Child Behavioral Health within the Ugandan Context: Current Efforts in Policy, Research, and Practice -- HIV/AIDS and Child Behavioral Health -- Non-Kin Support Networks and Child Behavioral Health in Sub-Saharan Africa -- Child Behavioral Health in Emergency Settings -- Working with Children Affected by Conflict and Displacement -- Scaling-up Child Behavioral Health Interventions -- Measuring Child Behavioral Health in SSA: Current Practice and Way Forward -- Making Child Behavioral Health a Policy Priority: Comparative Analysis of Policy Frameworks from Ghana, Uganda, and Kenya -- Training a new Cadre of Child Behavioral Health Scientists. Current Gaps and Promise -- Integrating Research and Practice: A Practitioners' Perspective -- Engaging with the US Government on Issues of Child Behavioral Health in SSA -- Conclusion.

AbstractChild labor remains a concern in sub‐Saharan Africa. Yet, evidence‐based preventive efforts are limited. We analyzed longitudinal data from Ghanaian adolescent girls in a pilot randomized clinical trial testing the preliminary impact of a combination intervention on family cohesion as a protective factor against child labor and school dropout. While there was no statistical difference between the control and intervention groups at 9 months, the results show that family cohesion scores improved significantly from baseline to 9 months for the ANZANSI intervention group. Qualitative results indicated improved family cohesion in the intervention group. Hence, future studies should further examine this promising social work intervention.

AbstractDuring adolescence, youth experience several physical, psychosocial, and cognitive changes. Self‐esteem and self‐concept are identified as protective factors for adolescents in high‐income countries, but studies are limited in sub‐Saharan Africa. We examined the associations of self‐esteem and self‐concept with life satisfaction and attitudes toward school using baseline data from 97 Ghanaian adolescent girls at risk of school dropout. Ordinary Least Squares regression models were fitted to examine the association between self‐esteem and self‐concept on school attitudes and life satisfaction. Self‐esteem was positively associated with life satisfaction. Self‐concept was associated with more positive attitudes toward school. Hence, self‐esteem and self‐concept may be critical protective factors in promoting adolescent girls' life satisfaction and positive attitudes toward school.

AbstractIntroductionAchieving optimal adherence to antiretroviral therapy (ART) among adolescents living with HIV (ALWHIV) is challenging, especially in low‐resource settings. To help accurately determine who is at risk of poor adherence, we developed and internally validated models comprising multi‐level factors that can help to predict the individualized risk of poor adherence among ALWHIV in a resource‐limited setting such as Uganda.MethodsWe used data from a sample of 637 ALWHIV in Uganda who participated in a longitudinal study, "Suubi+Adherence" (2012 to 2018). The model was developed using the Least Absolute Shrinkage and Selection Operator (LASSO) penalized regression to select the best subset of multi‐level predictors (individual, household, community or economic‐related factors) of poor adherence in one year's time using 10‐fold cross‐validation. Seventeen potential predictors included in the model were assessed at 36 months of follow‐up, whereas adherence was assessed at 48 months of follow‐up. Model performance was evaluated using discrimination and calibration measures.ResultsFor the model predicting poor adherence, five of the 17 predictors (adherence history, adherence self‐efficacy, family cohesion, child poverty and group assignment) were retained. Its ability to discriminate between individuals with and without poor adherence was acceptable; area under the curve (AUC) = 69.9; 95% CI: 62.7, 72.8. There was no evidence of possible areas of miscalibration (test statistic = 1.20; p = 0.273). The overall performance of the model was good.ConclusionsOur findings support prediction modelling as a useful tool that can be leveraged to improve outcomes across the HIV care continuum. Utilizing information from multiple sources, the risk prediction score tool applied here can be refined further with the ultimate goal of being used in a screening tool by practitioners working with ALWHIV. Specifically, the tool could help identify and provide early interventions to adolescents at the highest risk of poor adherence and/or viral non‐suppression. However, further fine‐tuning and external validation may be required before wide‐scale implementation.