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Record W2890788050 · doi:10.1176/appi.pn.2018.9a2

Psychiatrists Can Help Train Police in Crisis Response

2018· article· en· W2890788050 on OpenAlexaboutno aff
Linda M. Richmond

Bibliographic record

VenuePsychiatric News · 2018
Typearticle
Languageen
FieldPsychology
TopicPsychiatric care and mental health services
Canadian institutionsnot available
Fundersnot available
KeywordsCrisis interventionMental healthMental illnessLaw enforcementIntervention (counseling)Quarter (Canadian coin)PsychologyPsychiatryNursingCriminologyPolitical scienceMedicineLawHistory

Abstract

fetched live from OpenAlex

Back to table of contents Previous article Next article Institute on Psychiatric ServicesFull AccessPsychiatrists Can Help Train Police in Crisis ResponseLinda M. RichmondLinda M. RichmondPublished Online:5 Sep 2018https://doi.org/10.1176/appi.pn.2018.9a2AbstractGetting involved in Crisis Intervention Team training (CIT) is an important way psychiatrists can help at-risk patients in their communities. Police departments across the United States are increasingly being called to serve as first responders for people experiencing mental health crises.Tragically, these encounters too often result in arrests, injury, or far worse. Of the 987 people shot to death by police officers in 2017, mental illness was known to have played a role in one quarter of these incidents, according to an ongoing national study by the Washington Post. Chandan Khandai, M.D., hopes that more police officers will get involved in Crisis Intervention Team training, also known as CIT."What training, if any, do police officers have in interactions with people experiencing mental illness?" asked Chandan Khandai, M.D., a consultation-liaison psychiatry fellow at the University of Washington School of Medicine. "Often they say 'I don't know what to do. I was never trained for this. I'm just trying to do my job.'" Khandai hopes that more police officers will receive Crisis Intervention Team training, also known as CIT, and that psychiatrists will assume a bigger role in shaping these programs. Khandai will be participating in the session "Law Enforcement-Mental Health Interactions and the Crisis Intervention Team (CIT) Model" at IPS: The Mental Health Services Conference, which is being held October 4 to 7 in Chicago."This is an easy, concrete way of helping our patient population by getting involved in this," he said. "The more partners we can develop outside of the traditional medical and mental health care setting, the better off our patients will be."Khandai, himself a native Chicagoan, attended CIT training this past May with the Chicago Police Department and was one of the first psychiatrists to attend the program. "It was quite an eye-opening experience," he said. "I never fully appreciated the difficulties that officers face when trying to handle mental health–related calls—not having a medical background, having incomplete information, having to balance doing what's best for the individual with keeping the community safe."Register Now!Advance registration rates are now in effect for IPS: The Mental Health Services Conference. Register online at psychiatry.org/IPS, where you will also find information about housing and the full scientific program.Research has demonstrated that CIT helps both officers and patients: it boosts police officers' knowledge of mental health issues and de-escalation techniques, raises referrals of people with mental illness to treatment venues, and lowers the likelihood of arrest and incarceration for individuals experiencing a crisis, he said.In Chicago, the training takes place in studios that are designed to look like houses or bars, and with individuals who have experienced mental illness acting out scenarios with police trainees. Both police officers and the "actors" benefit. "This allows them to reenact their bad experiences with police officers and get a better outcome," he said. The police officer who heads Chicago's CIT training will also be speaking at the session. ■"Law Enforcement–Mental Health Interactions and the Crisis Intervention Team (CIT) Model" will be held Thursday, October 4, 1 p.m. to 2:30 p.m. ISSUES NewArchived

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.002

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 head0.021
GPT teacher head0.363
Teacher spread0.341 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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