Geographic distribution and prevalence of complex health and social needs in British Columbia, Canada
Notice bibliographique
Résumé
Background The overlapping challenges of providing care for people with mental illness, substance dependence, homelessness, and involvement with the justice system are becoming increasingly problematic in jurisdictions throughout the world. Individuals with complex presentations including health and socio-legal needs have been overwhelmingly identified in urban settings where the majority of interventional research has also taken place. However, little is known about the geographic distribution of individuals with similarly complex needs over a large population base that includes urban, rural and remote settings. The goal of this study was to empirically measure the prevalence and geographic distribution of people who experience complex co-occurring disorders (CCD) in a Canadian Province to provide a basis for planning and delivery of indicated services and supports. Methods Linked administrative data were examined spanning health, income assistance, and criminal convictions within a population of approximately 3.7 million adults and over a five-year period. Inclusion criteria were: diagnosed substance use and mental disorders; psychiatric hospitalization; criminal conviction; and income assistance. Geographic distribution was examined by calculating the prevalence per 100,000 adults examined at four geographic levels of increasing size. Results 2,202 individuals (1.2% of the population) met our inclusion criteria for CCD. In addition to having concurrent substance use and mental disorders, participants had high rates of hospitalization (8.2 admissions), criminal convictions (8.6 sentences) and social assistance payments (>$36,000) within five years. There was wide variability in the geographic distribution of people with CCD. Conclusions People with CCD are not restricted to areas with large populations or to urban settings. While higher absolute numbers of CCD individuals were identified in regions with higher overall populations, the highest rates of CCD were observed in relatively remote locations. Empirically-supported services for those with CCD (e.g., specialized courts, assertive community treatment) are needed in urban areas, but these services must also be adapted for those non-urban settings where the prevalence of CCD is greatest. Key messages Individuals with complex, co-occurring disorders are likely to present in diverse regions. Effective models of inter-agency collaboration used in urban settings are also required in less populated environments.
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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,004 | 0,008 |
| Études des sciences et des technologies | 0,005 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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 ».