No abstract

Child welfare jurisdictions increasingly place foster children with kinship foster parents as a means of meeting their need for stability, family connection, and behavioral and emotional support. However, the lack of financial and educational assistance provided to kin by child welfare authorities often undermines these caregivers’ ability to provide effective and lasting care for the children in their homes. This study uses a mixed-methods approach to understand how formal training and licensure processes can aid kinship foster parents in facilitating positive outcomes for children and youth in the foster care system. Specifically, we investigated the barriers experienced by kinship foster parents while trying to access existing licensure-based training and supports, as well as the initial outcomes of a kin-tailored licensure training curriculum alternatingly administered in in-person and virtual delivery formats. Participants reported that incomplete or inaccurate communication about licensing processes, practical difficulties in attending training, irrelevant session content, and stringent licensing requirements acted as barriers to accessing these resources. However, participants in the kin-specific licensure training administered in this study reported high levels of learning related to key parenting competencies and increased awareness of kinship permanency supports, although these outcomes appeared to be less pronounced among those receiving the training in a virtual format. These findings suggest that researchers and policymakers should consider developing, implementing, and evaluating further initiatives to provide accessible and tailored supports to kinship foster parents as a means of improving outcomes for the children in their care.

Objective: Open-ended survey questions crucially contribute to researchers' understandings of respondents' experiences. However, analyzing open-ended responses using human coders is labor-intensive and prone to inconsistencies. Structural topic modeling (STM) is a text mining method that discover topics from textual data. We demonstrate the use of STM to analyze openended survey responses to understand how parents cope during COVID-19 lock-down in Singapore. Method: We administered online surveys to 199 parents in Singapore during the COVID-19 lock-down. To show a STM analysis, we demonstrated a workflow that includes steps in data preprocessing, model estimation, model selection, and model interpretation.Results: An 18-topic model best fitted the data based on model diagnostics and researchers' expertise. Prevalent coping methods described by respondents include "Spousal Support", "Routines/Schedules" and "Managing Expectations". Topic prevalence for some topics varies with respondents' levels of parenting stress and whether parents were fathers or mothers. Conclusion: STM offers an efficient, valid, and replicable way to analyze textual data such asopen-ended survey responses and case notes that can complement researchers' knowledge and skills. STM can be used as part of a multistage research process or to support other analyses such as clarifying quantitative findings and identifying preliminary themes from qualitative data.

No abstract

No abstract