Multidimensional approach to restraint minimization: The journey of a specialized mental health organization
Bibliographic record
Abstract
The executive-level witnessing and review of restraint events has been identified as a key strategy for restraint minimization. In the present study, we examined the changes in restraint practices at a tertiary-level mental health-care facility with implementation of an initiative, in which representatives from senior management, professional practice, peer support, and clinical ethics witnessed seclusion and restraint events, and rounded with clinical teams to discuss timely release and brainstorm prevention strategies. Interrupted time series analysis compared the change from pre-implementation (14 months prior) to postimplementation (35 months' following) in the number of incidents/month, total hours/month, and average hours/incident/month for each of seclusion and mechanical restraint. With implementation, there was a step decrease in average hours/seclusion (-28.3 hours/seclusion, P < 0.001) and total seclusion hours (-1264.5 hours, P = 0.002). The postimplementation rate of decrease of -0.9 hours/incident/month was different than the pre-implementation rate of increase of 0.7 hours/incident/month for mechanical restraint (P = 0.03). Pre-implementation, there was a rate of decrease of 6.1 incidents/month (P < 0.001) and 4.5 incidents/month (P = 0.001) for seclusion and mechanical restraint, respectively. Postimplementation, there was a rate of increase of 0.3 incidents/month and a rate of decrease of 0.05 incidents/month for seclusion and mechanical restraint, respectively, both of which were different than pre-implementation (seclusion: P < 0.001, mechanical restraint: P = 0.002). In conclusion, the total hours of seclusion and average hours per seclusion and per restraint incident were reduced, demonstrating the value of leadership witnessing and daily rounds in promoting restraint minimization in tertiary-level mental health care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.004 |
| 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".