Experiences with legally mandated treatment in patients with schizophrenia: A systematic review of qualitative studies
Bibliographic record
Abstract
BACKGROUND: Patients with severe mental illness, including schizophrenia, may be legally mandated to undergo psychiatric treatment. Patients' experiences in these situations are not well characterized. This systematic review of qualitative studies aims to describe the experiences of patients with schizophrenia and related disorders who have undergone legally mandated treatment. METHODS: Four bibliographic databases were searched: CINAHL Plus (1981-2019), EMBASE (1947-2019), MEDLINE (1946-2019), and PsycINFO (1806-2019). These databases were searched for keywords, text words, and medical subject headings related to schizophrenia, legally mandated treatment and patient experience. The reference lists of included studies and systematic reviews were also investigated. The identified titles and abstracts were reviewed for study inclusion. A thematic analysis was completed for the synthesis of positive and negative aspects of legally mandated treatment. RESULTS: A total of 4,008 citations were identified. Eighteen studies were included in the final synthesis. For the thematic analysis, results were collated under two broad themes; positive patient experiences and negative patient experiences. Patients were satisfied when their autonomy was respected, and dissatisfied when it was not. Patients often retrospectively recognized that their treatment was beneficial. Furthermore, negative aspects of the treatment included deficits in communication and a lack of information. CONCLUSIONS: Intervention research has historically focused on clinical outcomes and the quantitative aspects of treatment. Thus, this study provides insight into the qualitative aspects of patients' experiences with legally mandated treatment. Recognizing these opinions and experiences can lead to better attitudes toward treatment for patients with schizophrenia and related psychiatric illnesses.
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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 | 0.052 | 0.120 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.016 | 0.017 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".