Comparing the Psychological Effects of Manikin-Based and Augmented Reality–Based Simulation Training: Within-Subjects Crossover Study
Bibliographic record
Abstract
BACKGROUND: Patient simulators are an increasingly important part of medical training. They have been shown to be effective in teaching procedural skills, medical knowledge, and clinical decision-making. Recently, virtual and augmented reality simulators are being produced, but there is no research on whether these more realistic experiences cause problematic and greater stress responses as compared to standard manikin simulators. OBJECTIVE: The purpose of this research is to examine the psychological and physiological effects of augmented reality (AR) in medical simulation training as compared to traditional manikin simulations. METHODS: A within-subjects experimental design was used to assess the responses of medical students (N=89) as they completed simulated (using either manikin or AR) pediatric resuscitations. Baseline measures of psychological well-being, salivary cortisol, and galvanic skin response (GSR) were taken before the simulations began. Continuous GSR assessments throughout and after the simulations were captured along with follow-up measures of emotion and cortisol. Participants also wrote freely about their experience with each simulation, and narratives were coded for emotional word use. RESULTS: Of the total 86 medical students who participated, 37 (43%) were male and 49 (57%) were female, with a mean age of 25.2 (SD 2.09, range 22-30) years and 24.7 (SD 2.08, range 23-36) years, respectively. GSR was higher in the manikin group adjusted for day, sex, and medications taken by the participants (AR-manikin: -0.11, 95% CI -0.18 to -0.03; P=.009). The difference in negative affect between simulation types was not statistically significant (AR-manikin: 0.41, 95% CI -0.72 to 1.53; P=.48). There was no statistically significant difference between simulation types in self-reported stress (AR-manikin: 0.53, 95% CI -2.35 to 3.42; P=.71) or simulation stress (AR-manikin: -2.17, 95% CI -6.94 to 2.59; P=.37). The difference in percentage of positive emotion words used to describe the experience was not statistically significant between simulation types, which were adjusted for day of experiment, sex of the participants, and total number of words used (AR-manikin: -4.0, 95% CI -0.91 to 0.10; P=.12). There was no statistically significant difference between simulation types in terms of the percentage of negative emotion words used to describe the experience (AR-manikin: -0.33, 95% CI -1.12 to 0.46; P=.41), simulation sickness (AR-manikin: 0.17, 95% CI -0.29 to 0.62; P=.47), or salivary cortisol (AR-manikin: 0.04, 95% CI -0.05 to 0.13; P=.41). Finally, preexisting levels of posttraumatic stress disorder, perceived stress, and reported depression were not tied to physiological responses to AR. CONCLUSIONS: AR simulators elicited similar stress responses to currently used manikin-based simulators, and we did not find any evidence of AR simulators causing excessive stress to participants. Therefore, AR simulators are a promising tool to be used in medical training, which can provide more emotionally realistic scenarios without the risk of additional harm.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".