<p>Understanding factors that contribute to the disposal of unused opioid medication</p>
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Notice bibliographique
Résumé
PURPOSE: Drivers of excess controlled substance disposal behaviors are not well understood. A survey of patients who had received opioid-based medications was conducted to inform the design of future innovative drug take-back programs. METHODS: This was a cross-sectional survey study conducted in 152 participants who received treatment with an opioid within the previous 2 years and had possession of unused medication following either switching to a different opioid or discontinuation of pain. RESULTS: Approximately one-third of patients had disposed of their unused opioid medication. Education about the importance of and appropriate methods for drug disposal was associated with a significantly increased likelihood of patients disposing of unused medication, and it was observed that patients prescribed an immediate-release/short-acting opioid were twice as likely to keep their medication compared to those prescribed an extended-release/long-acting opioid. The most commonly reported methods for disposal were via drug return kiosks and flushing the medication down the toilet. Some of the most impactful drivers of unused opioid disposal were routine practice of disposing of all unused drugs and instruction from a health care provider, and the most common driver of keeping unused medication was the desire to have it on-hand should there be a need to treat pain in the future. Over 80 % of patients indicated that they would be more likely to use a drug take-back service if they were offered compensation or if the kiosk was in a location that they visited frequently, and approximately half of the patients indicated that they would be willing to request an initial partial fill of an opioid prescription to reduce the volume of unused medication. CONCLUSION: There is a clear need to increase patient awareness about the importance and methods of proper medication disposal, and a great opportunity for health care providers to increase patient education efforts. These study findings also highlight key areas for improvement in drug take-back programs that may promote and incentivize more patients to utilize the services.
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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 | 0,008 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 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 | 0,001 |
| 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 découle