Envisioning a safety paradigm in inpatient mental health settings: Moving beyond zero-risk approaches
Bibliographic record
Abstract
A zero-risk paradigm currently dominates the organization and delivery of mental health care within inpatient settings, giving rise to a proliferation of risk management strategies that are ineffective and produce harms. Drawing on Foucault’s confinement and grounded in a comprehensive analysis of the extant literature, we identify three central processes that constitute this paradigm, including: risk is situated within the patient; eliminating risk is a foundational aim; and mental health professionals lead decision-making. Responding to the zero-risk paradigm, this paper proposes a novel safety paradigm comprised of four intersecting components, undertaken collectively by mental health professionals to guide practice: i) holding risk, ii) building capacity, iii) prioritizing relationships, and iv) re-envisioning environments. Foundationally underlying these commitments is direct action toward reducing coercive practices and structures, such as chemical and physical restraints, seclusion, and door locking. Mental health professionals are encouraged to challenge the zero-risk paradigm and its resultant risk management approaches, and embrace a safety paradigm to meaningfully re-orient care toward enhancing patients’ safety and well-being during and following hospitalization.
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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 | 0.038 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.012 | 0.066 |
| Scholarly communication | 0.019 | 0.021 |
| Open science | 0.004 | 0.022 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.002 | 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".