Using simulation to educate police about mental illness: A collaborative initiative
Bibliographic record
Abstract
Mental illness is a major public health concern in Canada and also globally. According to the World Health Organization, five of the top ten disabilities worldwide are mental health disorders. Within Canada, one in five individuals is living with mental illness each year. Currently, there are 6.7 million Canadians living with mental illness and over 1 million Canadian youth living with mental illness. Police are frequently the first responders to situations in the community involving people with mental illness, and police services are increasingly aware of the need to provide officers with additional training and strategies for effectively interacting with these citizens.This study examined the effectiveness of four online, interactive video-based simulations designed to educate police officers about mental illness and strategies for interacting with people with mental illness. The simulations were created through the efforts of a unique partnership involving a police service, a mental health facility and two postsecondary institutions. Frontline police officers from Ontario were divided into one of three groups (simulation, face to face, control). Using a pre- and post-test questionnaire, the groups were compared on their level of knowledge and understanding of mental illness. In addition, focus groups explored the impact of the simulations on officers’ level of confidence in engaging with individuals with mental illness and officers’ perceptions of the simulations’ ease of use and level of realism. The study’s findings determined that the simulations were just as effective as face-to-face learning, and the officers reported the simulations were easy to use and reflected real-life scenarios they had encountered on the job. As mental health continues to be a major public concern, not only in Canada but also globally, interactive simulations may provide an effective and affordable education resource not only for police officers but for other professionals seeking increased knowledge and skills in interacting with citizens with mental illness.Keywords: policing, mental illness, education, computer-based simulation
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".