Service use Decision-Making among Youth Accessing Integrated Youth Services: Applying the Unified Theory of Behavior.
Bibliographic record
Abstract
OBJECTIVE: With the development of 75% of mental health disorders before age 25, it is alarming that service use among youth is so low. Little theoretically driven research has explored the decision-making process youth make when accessing services. This study utilized a decision-making framework, the Unified Theory of Behavior (UTB), to understand service use among youth attending Foundry, a network of integrated youth services centres designed to support the health and wellbeing of youth. METHODS: Forty-one participants were recruited from one Foundry centre in an urban community in Canada. Semi-structured interviews with participants aged 15 - 24 explored the relationship between UTB constructs and service use. Youth and parent advisory teams were engaged in the research process. Analysts used content analysis methodology to develop a taxonomy of the top categories for each construct. RESULTS: Categories with the most salient and rich content were reported for each construct. The impact of emotions on service use was most commonly discussed in relation to the framework. The UTB constructs 'self-efficacy' and 'knowledge' were found to be interrelated. Differences in UTB categories emerged by symptom severity. Findings pointed towards a dynamic nature of service use, whereby service use experiences, may lead youth to consider future decisions surrounding service use within Foundry. CONCLUSIONS: This study contributes to a new understanding of integrated youth services utilization. The results can help shape the development of interventions to increase service access and retention, in addition to informing the design of systems of care that are accessible to all.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".