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Enregistrement W4405904960 · doi:10.1108/jap-07-2024-0036

To protect and serve: a review of initiatives to support of police officers to better meet the needs of older adult

2024· review· en· W4405904960 sur OpenAlexaff
Kristina M. Kokorelias, Adam Christopher, Anna Grosse, Joshua Wyman, Samir K. Sinha

Notice bibliographique

RevueThe Journal of Adult Protection · 2024
Typereview
Langueen
DomaineSocial Sciences
ThématiqueElder Abuse and Neglect
Établissements canadiensWestern UniversitySinai Health SystemUniversity of TorontoToronto Rehabilitation Institute
Organismes subventionnairesnon disponible
Mots-clésSafeguardingBusinessPublic relationsCriminologyPsychologyPolitical scienceNursingMedicine

Résumé

récupéré en direct d'OpenAlex

Purpose Police officers increasingly respond to incidents involving aging-related issues, where older adults are vulnerable and require tailored approaches. This scoping review aims to map initiatives aimed at enhancing interactions between older adults and police and evaluates outcomes. Findings inform the development of a geriatrics-focused police training curriculum to support age-friendly policing. A literature search across major databases and grey literature yielded 20 relevant publications. Three main initiatives were identified: geriatrics-oriented training programs, specialized geriatric police units and geriatrics-oriented policing guidelines. These insights highlight effective strategies for improving police responses to aging-related challenges and guide future research and policy in this domain. Design/methodology/approach The study employed a scoping review methodology guided by the Joanna Briggs Institute Manual and PRISMA-ScR checklist. A comprehensive search strategy was developed and executed across multiple databases and grey literature sources. Screening and selection of relevant studies were conducted in duplicate, with data extraction focusing on key elements such as study objectives, design, interventions and outcomes. Thematic analysis was employed to synthesize findings from included studies, highlighting three principal initiatives: geriatrics-oriented training programs, specialized geriatric police units and geriatrics-oriented policing guidelines. This approach aimed to map existing evidence, inform the development of a geriatrics-focused training curriculum and identify best practices for age-friendly policing. Findings The scoping review identified 28 studies meeting inclusion criteria. Findings highlighted varied approaches to enhancing police interactions with older adults, emphasizing training as pivotal. Effective strategies included specialized units, tailored training programs and guidelines integrating geriatrics principles. Key outcomes encompassed improved officer knowledge, communication skills and attitudes toward older adults, fostering enhanced service delivery and community relations. Evidence underscored the importance of ongoing education and collaborative partnerships in optimizing policing responses to aging populations, advocating for sustainable, age-friendly policing practices. Research limitations/implications The review’s limitations stem from primarily English-language studies, potentially overlooking non-English literature. Variability in study designs and outcomes poses challenges to synthesizing findings comprehensively. Limited generalizability may result due to geographic and cultural differences in policing practices. Future research could benefit from longitudinal studies assessing long-term impacts and broader inclusion of diverse policing contexts and perspectives, enhancing applicability and depth of understanding in optimizing police interactions with older adults. Practical implications Practical implications include informing policy makers and law enforcement agencies about effective strategies to enhance interactions with older adults, emphasizing communication skills and de-escalation techniques. Training programs should integrate age-sensitive approaches to improve officers’ awareness and response to older adults’ needs and vulnerabilities. Implementing community engagement initiatives can foster trust and cooperation, contributing to safer and more supportive environments for older adults in policing interactions. These efforts can ultimately promote enhanced well-being and reduced conflicts between law enforcement and older adults. Social implications Social implications highlight the need for broader societal awareness and education regarding the challenges faced by older adults in interactions with law enforcement. Addressing ageism and promoting respectful treatment can enhance community trust and reduce misunderstandings. Improved interactions between older adults and law enforcement can foster a more inclusive and supportive society, ensuring that older adults feel valued and protected. This can contribute to overall social cohesion and a more equitable experience for older adults in their interactions with law enforcement agencies. Originality/value The originality of this study lies in its focus on the intersection of age-related issues and law enforcement interactions, a relatively underexplored area in both gerontology and criminal justice research. By examining the perceptions and experiences of older adults and law enforcement officers, it provides valuable insights into mitigating ageism and improving interactions. The study’s findings contribute to enhancing understanding of how to promote respectful and effective communication between these groups, thereby offering practical implications for policy and training initiatives aimed at fostering better relationships and outcomes for older adults in law enforcement encounters.

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)0,003
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: Autre devis · Signal consensuel: aucune
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,731
Score d'incertitude au seuil0,537

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0030,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,002
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
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 Opus0,044
Tête enseignante GPT0,374
Écart entre enseignants0,330 · 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'étudeAutre devis
Domainenon disponible
GenreSynthèse

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
Publié2024
Routes d'admission1
Résumé présentoui

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