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Record W3014722547 · doi:10.1111/medu.14166

Simulation in psychiatry for medical doctors: A systematic review and meta‐analysis

2020· review· en· W3014722547 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMedical Education · 2020
Typereview
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsMcGill University
Fundersnot available
KeywordsContext (archaeology)Meta-analysisConfidence intervalMedicineRandomized controlled trialMEDLINEPsychological interventionStrictly standardized mean differenceMental healthFamily medicinePsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Abstract Context Most medical doctors are likely to work with patients experiencing mental health conditions. However, educational opportunities for medical doctors to achieve professional development in the field of psychiatry are often limited. Simulation training in psychiatry may be a useful tool to foster this development. Objectives The purpose of this study was to assess the effectiveness of simulation training in psychiatry for medical students, postgraduate trainees and medical doctors. Methods For this systematic review and meta‐analysis, we searched eight electronic databases and trial registries up to 31 August 2018. We manually searched key journals and the reference lists of selected studies. We included randomised and non‐randomised controlled studies and single group pre‐ and post‐test studies. Our main outcomes were based on Kirkpatrick levels. We included data only from randomised controlled trials (RCTs) using random‐effects models. Results From 46 571 studies identified, we selected 163 studies and combined 27 RCTs. Interventions included simulation by role‐play (n = 69), simulated patients (n = 72), virtual reality (n = 22), manikin (n = 5) and voice simulation (n = 2). Meta‐analysis found significant differences at immediate post‐tests for simulation compared with active and inactive control groups for attitudes (standardised mean difference [SMD] = 0.52, 95% confidence interval [CI] 0.31‐0.73 [ I 2 = 0.0%] and SMD = 0.28, 95% CI 0.04‐0.53 [ I 2 = 52.0%], respectively), skills (SMD = 1.37, 95% CI 0.56‐2.18 [ I 2 = 93.0%] and SMD = 1.49, 95% CI 0.39‐2.58 [ I 2 = 93.0%], respectively), knowledge (SMD = 1.22, 95% CI 0.57‐1.88 [ I 2 = 0.0%] and SMD = 0.72, 95% CI 0.14‐1.30 [ I 2 = 80.0%], respectively), and behaviours (SMD = 1.07, 95% CI 0.49‐1.65 [ I 2 = 68.0%] and SMD = 0.45, 95% CI 0.11‐0.79 [ I 2 = 41.0%], respectively). Significant differences in terms of patient benefit and doctors’ behaviours and skills were found at the 3‐month follow‐up. Conclusions Despite heterogeneity in methods and simulation interventions, our findings demonstrate the effectiveness of simulation training in psychiatry training.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.772
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.080
GPT teacher head0.501
Teacher spread0.421 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it