Implementation Considerations for Family-Based Telehealth Interventions for Youth in Foster Care: Focus Group Study With Child Welfare System Professionals
Bibliographic record
Abstract
BACKGROUND: Between 2016 and 2020, over 600,000 youth were served annually by the foster care system. Despite approximately half of foster youth struggling with emotional or behavioral challenges, few receive much-needed services to address their mental health concerns. Family-based interventions are efficacious in addressing both youth and caregiver mental health needs; however, foster youth participation in these family-based interventions is limited by many barriers, including out-of-home placement far from their family of origin. Telehealth is a promising tool for mitigating barriers to access to treatment interventions for foster youth and their families. OBJECTIVE: This study aims to understand child welfare system professionals' perspectives on enabling factors and barriers to providing family-based interventions via telehealth to youth in out-of-county foster care placement. METHODS: This qualitative study derived themes from 3 semistructured focus groups with child welfare system professionals. Participants were asked to discuss how family-based interventions are delivered to foster youth and their caregivers in their jurisdictions, as well as to share their thoughts about how to use telehealth to improve access to family-based interventions for families with youth in out-of-home placement. Data were analyzed using constant comparative analysis and inductive thematic analysis, with the Behavioral Model for Vulnerable Populations as the theoretical framework. RESULTS: Participants were 19 child welfare system professionals (eg, social workers, residential treatment staff, and supervisors) who participated in 1 of the 3 focus groups (6-7/group). Most participants were women (n=13, 68%), White individuals (n=10, 53%), and social workers (n=8, 42%). On average, participants worked in the child welfare system for 16.6 (SD 8.3) years. Participants identified multilevel factors impacting family-based intervention delivery including environmental factors (eg, Medicare billing and presumptive transfer), predisposing characteristics (eg, psychological resources), enabling factors (eg, transportation and team-based youth-centered care), and need factors (eg, motivation to engage). Participants expressed optimism that telehealth could increase access to needed mental health care, diverse providers, and longevity of care while also expressing some concerns regarding telehealth access and literacy. CONCLUSIONS: Child welfare system professionals highlight the need to develop policies and telehealth interventions that are youth versus placement centered, include resources that limit barriers and bolster motivation for engagement, and follow a team-based care model. Findings from this study inform how telehealth can be used to increase access to and engagement with family-based interventions for youth in out-of-home placements and their caregivers of origin.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".