The effects of housing stability on service use among homeless adults with mental illness in a randomized controlled trial of housing first
Notice bibliographique
Résumé
BACKGROUND: Housing First is an effective intervention to stably house and alter service use patterns in a large proportion of homeless people with mental illness. However, it is unknown whether there are differences in the patterns of service use over time among those who do or do not become stably housed and what effect, if any, Housing First has on these differing service use patterns. This study explored changes in the service use of people with mental illness who received Housing First compared to standard care, and how patterns of use differed among people who did and did not become stably housed. METHODS: The study design was a multi-site randomized controlled trial of Housing First, a supported housing intervention. 2039 participants (Housing First: n = 1131; standard care: n = 908) were included in this study. Outcome variables include nine types of self-reported service use over 24 months. Linear mixed models examined what effects the intervention and housing stability had on service use. RESULTS: Participants who achieved housing stability, across the two groups, had decreased use of inpatient psychiatric hospitals and increased use of food banks. Within the Housing First group, unstably housed participants spent more time in prison over the study period. The Housing First and standard care groups both had decreased use of emergency departments and homeless shelters. CONCLUSIONS: The temporal service use changes that occurred as homeless people with mental illness became stably housed are similar for those receiving Housing First or standard care, with the exception of time in prison. Service use patterns, particularly with regard to psychiatric hospitalizations and time in prison, may signify persons who are at-risk of recurrent homelessness. Housing support teams should be alert to the impacts of stay-based services, such as hospitalizations and incarcerations, on housing stability and offer an increased level of support to tenants during critical periods, such as discharges. TRIAL REGISTRATION: ISRCTN. ISRCTN42520374 . Registered 18 August 2009.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,017 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,003 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».