Barriers and Facilitators of Psychosocial Treatment Participation for Youth With Depression and Anxiety: A Scoping Review
Bibliographic record
Abstract
Depression and anxiety are prevalent mental health challenges experienced by youth and young adults; however, existing psychosocial interventions are not sufficiently effective. A growing body of research has examined the multiple factors that impact psychosocial treatment participation for youth with anxiety and depression. This scoping review uses the Health Belief Model (HBM) as a guiding framework to synthesize and categorize the factors that limit treatment participation (i.e., barriers) and those that are associated with greater treatment participation (i.e., facilitators) for youth aged 12-25 presenting to outpatient services for mood and anxiety difficulties. Abstracts and titles were reviewed for 5483 studies with 21 studies fitting full inclusion criteria. Most of the extracted factors fell within established HBM domains, with factors related to perceived barriers and severity most frequently reported. Relatively understudied areas included cues to action, perceived susceptibility, and self-efficacy. Also identified were multiple factors that serve as both barriers and facilitators depending on the context. The factors not captured by the HBM were socio-demographic factors and factors related to mental health service structure. Overall, this review aims to inform development of refined assessment and treatment approaches for youth with anxiety and/or depression at risk for early treatment termination.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".