Psychophysiological insights and user perspectives: enhancing police de-escalation skills through full-body VR training
Bibliographic record
Abstract
In recent years, Virtual Reality (VR) has emerged as a promising tool for enhancing training responses in high-stress professions, notably among police officers. This study investigates the psychophysiological responses and subjective user experience of active police officers undergoing Mental Health Crisis Response (MHCR) training using an immersive full-body VR system. A total of 10 active police officers with Special Weapons and Tactics (SWAT) training participated in our controlled study. Officers independently took part in one VR training session lasting 7-12 min involving an avatar in crisis portrayed by an actor. Officers wore integrated cardiovascular and electrodermal activity measurement devices for physiological monitoring. VR user experience aspects such as induced symptoms or game mechanics were investigated upon completing the training, aiming to evaluate the officer's perceptions of the technology. We used the DePICT™ scale to evaluate the de-escalation skills of officers, coded by a research professional. Our findings revealed significant differences in heart rate and heart rate variability responses between baseline and VR scenario immersion, suggesting heightened stress regulation during the MHCR simulation using full-body VR. Arousal measurements also revealed measurable responses during the training in VR. Additionally, the user experience assessment indicated a positive reception to the VR training, with minimal VR-induced symptoms. A "Defensive-Dynamics-Dichotomy" was revealed highlighting dominant autonomic responses linked to defensive actions (e.g., officers who drew a weapon; those who kept their weapons holstered) and their respective implications for stress management and cognitive function. A unique constellation of de-escalation skills was revealed among officers who relied on weapons relative to those who did not, to resolve the scenario. The study highlighted the perceived utility of physiological monitoring technologies in enhancing police training outcomes. In conclusion, our research underscores the potential of VR as an effective tool for de-escalation training following MHCR simulated scenarios among active police officers, offering insights into its psychophysiological impact and user experience. The findings contribute to improving our understanding of the physiology associated with decision-making in police officers to draw a weapon, emphasizing the role of advanced simulation and physiological monitoring technology in developing evidence-based training programs for public safety.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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 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".