Interprofessional simulation training for community mental health teams: Findings from a mixed methods study
Bibliographic record
Abstract
Community mental health teams (CMHTs) in England face mounting service pressures due to an increased focus on out-of-hospital care. Interprofessional working is essential to providing good mental healthcare in community settings. Simulation training is underused in mental health, despite strong support for its improvement of clinical skills, confidence, teamwork, and interprofessional collaboration in other healthcare settings. This study aims to evaluate the impact of simulation training on community mental health professionals. An interprofessional simulation training course on assessment and team working skills for community mental health professionals was developed and delivered at a time of service reorganisation in South London services, including changes to job roles and responsibilities. In total, 57 course participants completed a survey that measured perceptions of knowledge and confidence, as well as a general view of the course. Eight participants took part in further semi-structured interviews 2-3 months after the course to provide perceptions about this experience's subsequent impact. There were statistically significant increases in knowledge and confidence scores with large effect sizes. Thematic analyses of open-text survey and interview data identified emergent themes of interprofessional understanding; attitudes in clinical practice; staff well-being; the value of reflection; opportunity for feedback; and fidelity to clinical practice. Simulation training can improve confidence and knowledge in core skills and team working for CMHTs. Participants reported benefits to key areas of community mental healthcare, such as interprofessional collaboration, reflective practice, and staff well-being. Findings represented individual and team learning, as well as subsequent changes to clinical practice, and were related back to the interactive and reflective nature of the simulation. Implications are highlighted concerning the use of interprofessional simulation training in mental health, particularly relating to staff well-being, attitudes, and interprofessional working.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".