Youth Perspectives on Restrictive Mental Health Placement: Unearthing a Counter Narrative
Bibliographic record
Abstract
Though research has focused on clinical characteristics and behavioral problems of youth in out-of-home mental health placement settings, few studies have examined how adolescents and emerging adults (Arnett, 2000) experience and make sense of treatment. In this study, semistructured interviews regarding the experience of mental health placement were conducted with 12 adolescent and emerging adult participants with emotional and behavioral challenges, between the ages of 16 and 23. The participants were previously placed in residential mental health treatment centers, facilities, and inpatient hospitals. At the time of the interviews, all participants were involved in youth-run forums across New York State, through which they engage in peer-support initiatives and advocacy efforts aimed at reforming the children’s mental health system. Miles and Huberman’s suggestions for qualitative data coding (1994) were used to analyze the narratives. The participants identified salient conflicts when describing their experiences in restrictive mental health settings and also described the negative psychosocial ramifications of these experiences, including stigma and alienation. The findings suggest that by eliciting critical youth perspectives on mental health placement, a “counternarrative” emerges (Bamberg, 2004; Solis, 2004), which challenges and complicates clinically oriented discourses on youth with emotional and behavioral challenges. Implications for mental health reform and directions for future research are discussed.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.012 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.005 |
| 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".