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Enregistrement W4226136641 · doi:10.22215/etd/2021-14909

A Reasonable Officer: Examining the Relationship between Stress, Training, and Performance in Use of Force Encounters

2021· dissertation· en· W4226136641 sur OpenAlexafffund
Simon Baldwin

Notice bibliographique

Revuenon disponible
Typedissertation
Langueen
DomaineHealth Professions
ThématiqueOccupational Health and Performance
Établissements canadiensCarleton University
Organismes subventionnairesSocial Sciences and Humanities Research Council of Canada
Mots-clésOfficerApplied psychologyPsychologyPerceptionStress (linguistics)Active dutyCognitionSocial psychologyService (business)Clinical psychologyMilitary personnelPolitical sciencePsychiatryBusiness

Résumé

récupéré en direct d'OpenAlex

High-stress police encounters can evoke psychological and physiological stress reactions in officers, which can result in cognitive and perceptual deficits, as well as inferior performance. These effects can be particularly detrimental during a critical incident, when officers are expected to demonstrate sound judgement and proficient performance. However, limited research exists that objectively measures stress reactivity experienced by police officers during active-duty or the degree of police performance that can reasonably be expected under the levels of stress observed in naturalistic use of force (UoF) encounters, based on the level of experience and training officers have received. This dissertation reports on two studies, one drawing on data from officers during activeduty and the other using an experimental scenario, to examine the relationship between stress, training, and performance in UoF encounters. Study 1 examined autonomic stress responses experienced by 64 police officers, during general duty calls for service and interactions with the public. Officer characteristics, including years of service and training profiles, were also examined to explore whether experience and training impacted cardiovascular reactivity. Study results highlight the sorts of risks that officers are routinely exposed to in the course of their duties, as well as the nature and frequency of the stress reactions experienced by officers. Results also showed that the phase of the call (e.g., encountering a subject) and incident factors (e.g., UoF) significantly increased stress reactivity. Study 2 assessed the performance of 122 officers during a realistic lethal force scenario to examine whether performance was affected by the officer's level of training, years of service, and stress reactivity. Results demonstrated that the scenario produced elevated heart rates, as well as iii A REASONABLE OFFICER perceptual and cognitive distortions, commensurate with those observed in naturalistic settings. The average performance rating from the scenario was 59%, with 27% of participants making at least one lethal force error. Elevated stress was a predictor of poorer performance and increased lethal force errors. Training and years of service had complex effects on both performance and lethal force errors. The results from these two studies provide important insights into the general relationship between stress, training, and performance in UoF encounters. The findings provide LEAs with an opportunity to critically reflect on current training practices and offer a roadmap for making evidence-based improvements to training. They also provide important evidence that may inform the reasonableness standard used in courts of law by painting a realistic picture of police performance under stress given the current training available to officers. Perhaps most importantly, the research identifies a need for a concerted effort to increase police training standards and ensure the necessary infrastructure is in place to achieve them.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,039
Score d'incertitude au seuil0,658

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,222
Tête enseignante GPT0,430
Écart entre enseignants0,208 · 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 tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

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
Publié2021
Routes d'admission2
Résumé présentoui

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