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Enregistrement W2283395735 · doi:10.1111/jpm.12287

Housing outcomes and predictors of success: the role of hospitalization in street outreach

2016· article· en· W2283395735 sur OpenAlexaffabout
Bernadette Lettner, Richard Doan, A. W. Miettinen

Notice bibliographique

RevueJournal of Psychiatric and Mental Health Nursing · 2016
Typearticle
Langueen
DomaineHealth Professions
ThématiqueHomelessness and Social Issues
Établissements canadiensUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésOutreachMedicineIntervention (counseling)Mental healthMultidisciplinary approachMental illnessNursingPsychiatryHousing FirstSubstance abuseSociology

Résumé

récupéré en direct d'OpenAlex

ACCESSIBLE SUMMARY: What is known on the subject? Outreach services are often successful in engaging and housing street homeless individuals. People experiencing homelessness have greatly increased rates of mental illness and substance abuse. What this paper adds to existing knowledge? Given the relative lack of research involving street homeless individuals, this retrospective chart review examined factors associated with successful housing by a multidisciplinary street outreach team, including the use of hospitalization as an intervention within a housing first framework. The majority of clients were successfully housed by the end of outreach team involvement. An admission to hospital was strongly associated with successful housing for those with a psychotic disorder. What are the implications for practice? Multidisciplinary outreach teams, specifically those with psychiatric and nursing support, successfully work with and house people experiencing street homelessness and psychosis. Mental health nurses embedded in the community are an essential link between inpatient and outpatient care for highly vulnerable street homeless individuals. Introduction Housing-first strategies have helped establish housing as a human right. However, endemic homelessness persists. Multidisciplinary outreach teams that include nursing, social and psychiatric services allow for integrative strategies to engage and support clients on their housing trajectory. The following retrospective review focused on the identification of demographic, clinical, and service characteristics that predicted the obtainment of housing, and explored the role of psychiatric hospitalization as an intervention, not an outcome measure, in contrast to previous studies. These have rarely focused on street homelessness. METHOD: A retrospective chart review of 85 homeless, primarily rough-sleeping, clients was conducted to determine housing outcomes and the factors associated with obtaining housing through care provided by a psychiatric street outreach team in Toronto, Canada. Demographics, homelessness duration, diagnosis, hospitalization and housing status were tracked during team involvement. RESULTS: Overall, 46% (36/79) were housed during the study term. Securing housing at the end of treatment/data collection was significantly enhanced by hospitalization (OR = 9.04, 95% CI [2.43, 33.59]). It was significantly diminished by psychosis (OR = 0.22, 95% CI [0.05, 0.95]) and prior homelessness >36 months (OR = 0.10, 95% CI [0.02, 0.50]). Twenty-three of 31 (74%) hospitalized clients with psychosis were subsequently housed, compared to 4 of 30 (13%) not hospitalized (Fisher's exact, P < .001). DISCUSSION: Multidisciplinary street outreach teams successfully house long-standing homeless clients (>12 months without a permanent address) with serious mental illness and/or substance abuse. Hospitalization can be utilized as a complimentary intervention, particularly for those with psychosis, in the continuum of housing first initiatives, and can contribute to securing housing for those with persistent psychotic disorders. Implications for nursing practice Community mental health nurses are uniquely positioned to translate care between hospital and community settings, ensuring timely assessment, intervention and treatment of clients who are historically difficult to engage.

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)0,000
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 enseignants0,091
Score d'incertitude au seuil0,181

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
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 Opus0,014
Tête enseignante GPT0,381
Écart entre enseignants0,367 · 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

Citations17
Publié2016
Routes d'admission2
Résumé présentoui

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