Prevalence of Mental Health Disorders Among Individuals Experiencing Homelessness
Notice bibliographique
Résumé
Importance: Several factors may place people with mental health disorders, including substance use disorders, at increased risk of experiencing homelessness and experiencing homelessness may also increase the risk of developing mental health disorders. Meta-analyses examining the prevalence of mental health disorders among people experiencing homelessness globally are lacking. Objective: To determine the current and lifetime prevalence of mental health disorders among people experiencing homelessness and identify associated factors. Data Sources: A systematic search of electronic databases (PubMed, MEDLINE, PsycInfo, Embase, Cochrane, CINAHL, and AMED) was conducted from inception to May 1, 2021. Study Selection: Studies investigating the prevalence of mental health disorders among people experiencing homelessness aged 18 years and older were included. Data Extraction and Synthesis: Data extraction was completed using standardized forms in Covidence. All extracted data were reviewed for accuracy by consensus between 2 independent reviewers. Random-effects meta-analysis was used to estimate the prevalence (with 95% CIs) of mental health disorders in people experiencing homelessness. Subgroup analyses were performed by sex, study year, age group, region, risk of bias, and measurement method. Meta-regression was conducted to examine the association between mental health disorders and age, risk of bias, and study year. Main Outcomes and Measures: Current and lifetime prevalence of mental health disorders among people experiencing homelessness. Results: A total of 7729 citations were retrieved, with 291 undergoing full-text review and 85 included in the final review (N = 48 414 participants, 11 154 [23%] female and 37 260 [77%] male). The current prevalence of mental health disorders among people experiencing homelessness was 67% (95% CI, 55-77), and the lifetime prevalence was 77% (95% CI, 61-88). Male individuals exhibited a significantly higher lifetime prevalence of mental health disorders (86%; 95% CI, 74-92) compared to female individuals (69%; 95% CI, 48-84). The prevalence of several specific disorders were estimated, including any substance use disorder (44%), antisocial personality disorder (26%), major depression (19%), schizophrenia (7%), and bipolar disorder (8%). Conclusions and Relevance: The findings demonstrate that most people experiencing homelessness have mental health disorders, with higher prevalences than those observed in general community samples. Specific interventions are needed to support the mental health needs of this population, including close coordination of mental health, social, and housing services and policies to support people experiencing homelessness with mental disorders.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,014 | 0,059 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,005 | 0,006 |
| Bibliométrie | 0,011 | 0,013 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 source (Gemma direct ou Codex distillé), 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 ».