Integrated collaborative care teams to enhance service delivery to youth with mental health and substance use challenges: protocol for a pragmatic randomised controlled trial
Bibliographic record
Abstract
INTRODUCTION: Among youth, the prevalence of mental health and addiction (MHA) disorders is roughly 20%, yet youth are challenged to access evidence-based services in a timely fashion. To address MHA system gaps, this study tests the benefits of an Integrated Collaborative Care Team (ICCT) model for youth with MHA challenges. A rapid, stepped-care approach geared to need in a youth-friendly environment is expected to result in better youth MHA outcomes. Moreover, the ICCT approach is expected to decrease service wait-times, be more youth-friendly and family-friendly, and be more cost-effective, providing substantial public health benefits. METHODS AND ANALYSIS: In partnership with four community agencies, four adolescent psychiatry hospital departments, youth and family members with lived experience of MHA service use, and other stakeholders, we have developed an innovative model of collaborative, community-based service provision involving rapid access to needs-based MHA services. A total of 500 youth presenting for hospital-based, outpatient psychiatric service will be randomised to ICCT services or hospital-based treatment as usual, following a pragmatic randomised controlled trial design. The primary outcome variable will be the youth's functioning, assessed at intake, 6 months and 12 months. Secondary outcomes will include clinical change, youth/family satisfaction and perception of care, empowerment, engagement and the incremental cost-effectiveness ratio (ICER). Intent-to-treat analyses will be used on repeated-measures data, along with cost-effectiveness and cost-utility analyses, to determine intervention effectiveness. ETHICS AND DISSEMINATION: Research Ethics Board approval has been received from the Centre for Addiction and Mental Health, as well as institutional ethical approval from participating community sites. This study will be conducted according to Good Clinical Practice guidelines. Participants will provide informed consent prior to study participation and data confidentiality will be ensured. A data safety monitoring panel will monitor the study. Results will be disseminated through community and peer-reviewed academic channels. TRIAL REGISTRATION NUMBER: Clinicaltrials.gov NCT02836080.
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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 | 0.063 | 0.056 |
| Meta-epidemiology (narrow) | 0.009 | 0.004 |
| Meta-epidemiology (broad) | 0.017 | 0.011 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.090 | 0.014 |
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".