Perceived Coercion and the Therapeutic Relationship: A Neglected Association?
Bibliographic record
Abstract
OBJECTIVE: Increasing patient autonomy and decreasing coercion are frequently cited goals in mental health care. Research suggests that the therapeutic relationship and patients' experiences of coercion may be associated. This study investigated the association between the therapeutic relationship and perceived coercion in psychiatric admissions. METHODS: Associations between perceived coercion and the therapeutic relationship and sociodemographic and clinical variables were examined by using data from structured interviews with 164 patients consecutively admitted to two psychiatric hospitals in Oxford, England. RESULTS: High levels of coercion were experienced by 48% of voluntarily and 89% of involuntarily admitted patients. A high perceived coercion score was significantly associated with involuntary admission and a poor rating of the therapeutic relationship. The therapeutic relationship confounded legal status as a predictor of perceived coercion. CONCLUSIONS: Similar factors may influence patients' experience of both coercion and the therapeutic relationship during psychiatric hospital admission. Hospitalization, even when voluntary, was viewed as more coercive when patients rated their relationship with the admitting clinician negatively. Interventions to improve the therapeutic relationship may reduce perceptions of coercion.
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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 | 0.002 | 0.023 |
| 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 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".