Harm reduction and recovery services support (HRRSS) to mitigate the opioid overdose epidemic in a rural community
Notice bibliographique
Résumé
BACKGROUND: Rural areas in the United States (US) are ravaged by the opioid overdose epidemic. Oconee County, an entirely rural county in northwest South Carolina, is likewise severely affected. Lack of harm reduction and recovery resources (e.g., social capital) that could mitigate the worst outcomes may be exacerbating the problem. We aimed to identify demographic and other factors associated with support for harm reduction and recovery services in the community. METHODS: The Oconee County Opioid Response Taskforce conducted a 46-item survey targeting a general population between May and June in 2022, which was mainly distributed through social media networks. The survey included demographic factors and assessed attitudes and beliefs toward individuals with opioid use disorder (OUD) and medications for OUD, and support for harm reduction and recovery services, such as syringe services programs and safe consumption sites. We developed a Harm Reduction and Recovery Support Score (HRRSS), a composite score of nine items ranging from 0 to 9 to measure level of support for placement of naloxone in public places and harm reduction and recovery service sites. Primary statistical analysis using general linear regression models tested significance of differences in HRRSS between groups defined by item responses adjusting for demographic factors. RESULTS: There were 338 survey responses: 67.5% were females, 52.1% were 55 years old or older, 87.3% were Whites, 83.1% were non-Hispanic, 53.0% were employed, and 53.8% had household income greater than US$50,000. The overall HRRSS was relatively low at a mean of 4.1 (SD = 2.3). Younger and employed respondents had significantly greater HRRSS. Among nine significant factors associated with HRRSS after adjusting for demographic factors, agreement that OUD is a disease had the greatest adjusted mean difference in HRSSS (adjusted diff = 1.22, 95% CI=(0.64, 1.80), p < 0.001), followed by effectiveness of medications for OUD (adjusted diff = 1.11, 95%CI=(0.50, 1.71), p < 0.001). CONCLUSIONS: Low HRRSS indicates low levels of acceptance of harm reduction potentially impacting both intangible and tangible social capital as it relates to mitigation of the opioid overdose epidemic. Increasing community awareness of the disease model of OUD and the effectiveness of medications for OUD, especially among older and unemployed populations, could be a step toward improving community uptake of the harm reduction and recovery service resources critical to individual recovery efforts.
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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 | 0,000 | 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 | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».