Referring Adolescent Primary Care Patients to Single-Session Interventions for Anxiety and Depression: Protocol for a Feasibility Study
Bibliographic record
Abstract
BACKGROUND: Despite the growing prevalence of depression and anxiety among adolescents, fewer than half access appropriate mental health care. Single-session interventions (SSIs) for depression and anxiety offered in primary care are a promising approach to bridging the treatment gap. OBJECTIVE: We aimed to implement a clinical workflow for primary care and behavioral health providers to refer patients aged 13 to 17 years with mild to moderate depression and anxiety symptoms to Project YES (Youth Empowerment and Support), an open-access SSI platform, in a large group medical practice with an integrated behavioral health department. METHODS: Pediatric primary care and integrated behavioral health providers will be educated on the benefits of Project YES for adolescent anxiety and depression and trained in a workflow integrated within the electronic health record system, Epic, to refer patients during well-child visits and pediatric behavioral health visits. Patients with mild to moderate internalizing symptoms based on the 17-item Pediatric Symptom Checklist or youth Pediatric Symptom Checklist will be invited to try an SSI through Project YES. We will examine provider uptake and perceptions of acceptability, feasibility, and appropriateness over time. RESULTS: The rollout will take place between November 2022 and May 2023, when outcomes will be evaluated. Data analysis and manuscript writing are anticipated to be completed during the summer of 2023. CONCLUSIONS: SSIs such as those available through Project YES have the potential to provide low-cost, evidence-based mental health treatment to adolescents with mild to moderate depression and anxiety. If deemed feasible and acceptable, providing SSIs in primary care settings could significantly improve access to mental health care without taxing pediatric primary care and behavioral health providers. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/45666.
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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 | 0.037 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.082 | 0.016 |
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".