Stress Management Among Caregivers of Detained Youth: Protocol for Randomized Controlled Trial of the RAISE Web-Based mHealth App
Bibliographic record
Abstract
BACKGROUND: Detained adolescents exhibit high rates of behavioral health needs, yet few receive treatment during detention or community re-entry. Once adolescents are released into the community, caregivers must mobilize significant resources and overcome barriers to facilitate their treatment engagement. Parenting stress is often heightened during this forced separation and the re-entry transition. Parenting stress is associated with greater perceived barriers to treatment and, for adolescents who begin treatment, less therapeutic change and premature treatment dropout. Interventions designed to support caregivers of detained adolescents in managing their stress while navigating the juvenile legal system are urgently needed, and mobile health (mHealth) interventions offer promising, scalable approaches. RAISE (Reducing pArentIng StrEss) is a web-based application co-designed with caregivers of detained adolescents to reduce caregiver stress and promote postrelease adolescent behavioral health services use. OBJECTIVE: This study will evaluate the effectiveness of RAISE in reducing caregiver stress and promoting adolescent behavioral health services use following release from detention. METHODS: A randomized controlled trial with 60 caregivers of detained adolescents (ages 12-17 years) across the United States will be conducted. Caregivers will be recruited through passive and active techniques and randomized to receive RAISE (intervention) or an informational brochure (comparison). Self-assessment questionnaires will be completed at baseline and 3- and 6-month follow-up timepoints. The fully automated RAISE intervention includes an 8-week stress reduction intervention, self-monitoring and affirmational SMS text messaging, and resources related to navigating the juvenile legal system. Assessments include empirically validated measures of parenting stress, mindful parenting, parenting self-efficacy, adolescent services use, motivation for youth treatment, caregiver behavioral health, sociodemographics, and RAISE usability (intervention only). Caregivers will also participate in a semistructured qualitative exit interview at the 3-month (postintervention) timepoint. Descriptive statistics will examine recruitment, randomization, assessment, retention, and application usability. Independent samples t tests and chi-square analyses will determine whether randomization was successful based on multiple background variables; group differences will be accounted for in outcome analyses. Regression analyses will be used for outcome analyses, with an intent-to-treat design; analyses will include intervention group as a predictor and control for the baseline level of the outcome, application usage, and demographic characteristics. Potential moderators and mediators of intervention effects will be explored. RESULTS: We propose the enrollment of 60 caregivers by April 2025, final data collection by September 2025, and submission of main findings for publication in December 2025. CONCLUSIONS: This study will provide empirical evidence regarding the impact of an mHealth stress reduction intervention co-designed with caregivers of detained adolescents. Findings will be informative for legal systems regarding how best to support caregivers of detained adolescents and the impact of reducing caregiver stress on adolescents' linkage to behavioral health services following their release into the community. TRIAL REGISTRATION: ClinicalTrials.gov NCT05032742; https://clinicaltrials.gov/study/NCT05032742. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/67511.
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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 | 0.019 | 0.016 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.010 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.062 | 0.008 |
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".