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

Psychiatrists Can Help Train Police in Crisis Response

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

Notice bibliographique

RevuePsychiatric News · 2018
Typearticle
Langueen
DomainePsychology
ThématiquePsychiatric care and mental health services
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCrisis interventionMental healthMental illnessLaw enforcementIntervention (counseling)Quarter (Canadian coin)PsychologyPsychiatryNursingCriminologyPolitical scienceMedicineLawHistory

Résumé

récupéré en direct d'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

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,017
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: aucune
Score de désaccord entre enseignants0,426
Score d'incertitude au seuil0,818

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,017
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,001
Études des sciences et des technologies0,0040,001
Communication savante0,0030,006
Science ouverte0,0010,007
Intégrité de la recherche0,0060,007
Charge utile insuffisante (le modèle a refusé de juger)0,4260,245

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,021
Tête enseignante GPT0,363
Écart entre enseignants0,341 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2018
Routes d'admission1
Résumé présentoui

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