Exploring the relationship between perceived personal well-being and clinical characteristics among youth who have accessed intensive mental health treatment
Bibliographic record
Abstract
High personal well-being has been found to be associated with many enduring benefits (Diener and Chan, 2011). However, researchers who have explored mental health disorders have often focused on pathology, and personal well-being has been overlooked. This study is part of a larger longitudinal, observational study on the psychosocial outcomes of children and youth who have accessed residential or intensive home-based treatment in five agencies in Ontario, Canada (Preyde et al., 2011). The purpose of this study was to explore the level of perceived personal well-being among a subsample of youth who accessed residential treatment (n=33) and intensive home based treatment (n=30). Youth completed a cross-sectional survey measuring personal well-being at 12-18 months post-discharge. Many youth reported high personal well-being. Demographic and clinical characteristics did not predict participants’ personal well-being scores, suggesting that no clear relationship exists between personal well-being and symptom severity and psychosocial functioning.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".