Differences in Personal Recovery Among Individuals with Severe Mental Disorders in Private and Supported Accommodations: An Exploratory Study
Bibliographic record
Abstract
People with severe mental disorders (SMD) face long-term functional impairments requiring integrated, community-based, recovery-oriented care. Italy provides two main housing models for people with SMD: private accommodation (PA) and supported accommodation (SA). This exploratory study investigated differences in recovery outcomes across these settings using the Mental Health Recovery Star (MHRS). A six-month longitudinal study was conducted within the South Verona Community Mental Health Service. Nineteen trained mental health professionals assessed 25 people with SMD (14 in PA, 11 in SA) at baseline (BL) and follow-up (FU) using standardized tools for recovery (MHRS), functioning, psychopathology, functional autonomy, and needs. Group comparisons and within-group changes were analyzed using paired and independent t-tests. At BL, people with SMD in PA showed better functioning (p = 0.040) and fewer needs than those in SA (p = 0.008). Recovery goals differed, with people with SMD in PA focusing on health and networks, while people with SMD in SA emphasized functioning. At FU, people with SMD in PA improved across all MHRS domains (p < 0.001), with significant reductions in symptom severity and unmet needs. People with SMD in SA showed targeted improvements in functioning, autonomy, and MHRS social networks (p < 0.001), with increases in met needs but non-significant changes in unmet needs. When comparing PA and SA at FU, the differences were relatively modest. Recovery is achievable in both housing settings, although outcomes differ. People with SMD in PA experienced broader improvements, while people with SMD in SA progressed in their prioritized areas, likely reflecting more complex initial needs. These findings underscore the value of aligning recovery-oriented care with the specific needs and contexts of different residential settings. Further research is needed to confirm and expand these results.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".