Behavioral skills training for teaching safety skills to mental health service providers compared to training-as-usual: a pragmatic randomized control trial
Bibliographic record
Abstract
Abstract Background Violence in the healthcare workplace has been a global concern for over two decades, with a high prevalence of violence towards healthcare workers reported. Workplace violence has become a healthcare quality indicator and embedded in quality improvement initiatives of many healthcare organizations. The Centre for Addiction and Mental Health (CAMH), Canada’s largest mental health hospital, provides all clinical staff with mandated staff safety training for self-protection and team-control skills. These skills are to be used as a last resort when a patient is at imminent risk of harm to self or others. The purpose of this study is to compare the effectiveness of two training methods of this mandated staff safety training for workplace violence in a large psychiatric hospital setting. Methods Using a pragmatic randomized control trial design, this study compares two approaches to teaching safety skills CAMH’s training-as-usual (TAU) using the 3D approach (description, demonstration and doing) and behavioural skills training (BST), from the field of applied behaviour analysis, using instruction, modeling, practice and feedback loop. Staff were assessed on three outcome measures (competency, mastery and confidence), across three time points: before training (baseline), immediately after training (post-training) and one month later (follow-up). This study was registered with the ISRCTN registry on 06/09/2023 (ISRCTN18133140). Results With a sample size of 99 new staff, results indicate that BST was significantly better than TAU in improving observed performance of self-protection and team-control skills. Both methods were associated with improved skills and confidence. However, there was a decrease in skill performance levels at the one-month follow-up for both methods, with BST remaining higher than TAU scores across all three time points. The impact of training improved staff confidence in both training methods and remained high across all three time points. Conclusions The study findings suggest that BST is more effective than TAU in improving safety skills among healthcare workers. However, the retention of skills over time remains a concern, and therefore a single training session without on-the-job-feedback or booster sessions based on objective assessments of skill may not be sufficient. Further research is needed to confirm and expand upon these findings in different settings.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".