Feasibility and Acceptability of a Family-Based Telehealth Intervention for Families Impacted by the Child Welfare System: Formative Mixed Methods Evaluation
Bibliographic record
Abstract
BACKGROUND: Despite elevated rates of trauma exposure, substance misuse, mental health problems, and suicide, systems-impacted teens and their caregivers have limited access to empirically supported behavioral health services. Family-based interventions are the most effective for improving mental health, education, substance use, and delinquency outcomes, yet the familial and placement disruption that occurs during child welfare involvement can interfere with the delivery of family-based interventions. OBJECTIVE: To address this gap in access to services, we adapted an in-person, empirically supported, family-based affect management intervention using a trauma-informed lens to be delivered via telehealth to families impacted by the child welfare system (Family Telehealth Project). We describe the intervention adaptation process and an open trial to evaluate its feasibility, acceptability, and impact. METHODS: Adaptations to the in-person, family-based affect management intervention were conducted iteratively with input from youth, caregivers, and systems partners. Through focus groups and collaborative meetings with systems partners, a caregiver-only version of the intervention was also developed. An open trial of the intervention was conducted to assess family perspectives of its acceptability and feasibility and inform further refinements prior to a larger-scale evaluation. Participants included English-speaking families involved in the child welfare system in the past 12 months with teens (aged 12-18 years). Caregivers were eligible to participate either individually (caregivers of origin, kinship caregivers, or foster parents; n=7) or with their teen (caregiver of origin only; n=6 dyads). Participants completed session feedback forms and surveys at pretreatment, posttreatment, and 3-month posttreatment time points. Qualitative exit interviews were conducted with a subset of participants (12/19, 63%) to further understand their experiences with the intervention. RESULTS: Session attendance was high, and both caregivers and teens reported high acceptability of clinicians and sessions on feedback forms. Families were comfortable with video technology, with very few (<5%) sessions having reported technology problems. Thematic analysis of exit interview transcripts indicated that families used effective communication and affect management skills taught during the intervention. Regarding challenges and barriers, some caregiver-only participants expressed a desire to have their teen also participate in the intervention. All interview participants reported that they would recommend the intervention to others and perceptions of the intervention were overwhelmingly positive. Quantitative surveys revealed differential responses to the intervention regarding affect management and communication. CONCLUSIONS: An open trial of the Family Telehealth Project, a skills-based telehealth intervention for families impacted by the child welfare system, suggests high levels of intervention feasibility and acceptability. Participants noted improvements in areas often hindered by the impacts of trauma and family separation: communication and affect management. Perceptions of the intervention were positive overall for both teens and caregivers. The Family Telehealth Project shows promise in addressing the gaps in behavioral health access for systems-impacted families. TRIAL REGISTRATION: ClinicalTrials.gov NCT04488523; https://clinicaltrials.gov/study/NCT04488523.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.053 | 0.050 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".