Self-help group (SHG) attendance and treatment outcomes among older adults in the US
Notice bibliographique
Résumé
Substance dependency is a global problem and significantly affects the geriatric population in the United States. This study aims to determine how self-help group (SHG) attendance affects substance use treatment outcomes among older adults in the US. This cross-sectional study used the 2020 discharge treatment episodes data set (TEDS-D)fromthe Substance Abuse and Mental Health Services Administration (SAMHSA). Multivariable logistic regression was used to evaluate the relationship between self-help group attendance and treatment outcomes among older adults. We included 3,424 older adults (19.2% female). The primary substance use was alcohol in more than two-thirds of the participants (67.9%), while heroin (17.1%), cocaine (5.8%), and other opiates/synthetics (3.3%) were the other common primary substance of abuse among other participants. In the multivariate logistic regression analysis, SHG attendance at discharge from treatment facility was significantly associated with reduced frequency of use of primary substance -FUPS (p-value = 0.013) and increased odds of treatment completion (p-value <0.001) but no significant association with arrests at discharge from treatment facility (p-value = 0.101). SHG attendance on admission into treatment facility was associated with reduced odds of treatment completion (p-value <0.001). Having a living arrangement at discharge was found to be associated with reduced FUPS (p-value <0.001) but with lower odds of treatment completion (p-value <0.001). Association of SHG attendance with positive treatment outcomes indicates the need to enhance access to this service in the geriatric population. • The primary substances used were alcohol, heroin, and cocaine in 45.8%, 18.2%, and 4.9% of participants. • Self-help group attendance at dischargefrom treatment facility was significantly associated with reduced frequency of use of primary substance and increased odds of treatment completion. • Having a living arrangement at discharge was found to be associated with lower odds of treatment completion among older adults. Substance use is a prevalent problem among older adults in the United States ( Lipari, 2018 ). According to the Substance Abuse and Mental Health Services Administration (SAMHSA), approximately 5.7 million older adults had a form of substance use disorder (SUD) in 2018, and this number is expected to increase to nearly 6.4 million by 2030 ( Lipari, 2018 ). SUD can have severe negative consequences on older adults' physical and mental health, leading to a higher risk of chronic illnesses, cognitive impairment, and social isolation ( Meier & Best, 2006 ).
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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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| 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 ».