The Inclusion of Patients’ Reported Outcomes to Inform Treatment Effectiveness Measures in Opioid Use Disorder. A Systematic Review
Notice bibliographique
Résumé
Nitika Sanger,1,* Balpreet Panesar,2,* Michael Dennis,3 Tea Rosic,4 Myanca Rodrigues,4 Elizabeth Lovell,5 Shuling Yang,3 Mehreen Butt,6 Lehana Thabane,4,7 Zainab Samaan4,5 1Medical Science Graduate Program, McMaster University, Hamilton, Ontario, Canada; 2Neuroscience Graduate Program, McMaster University, Hamilton, Ontario, Canada; 3Michael G DeGroote School of Medicine, McMaster University, Hamilton, Ontario, Canada; 4Health Research Methodology Graduate Program, McMaster University, Hamilton, Ontario, Canada; 5Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, Ontario, Canada; 6Accelerated Nursing Program, McMaster University, Hamilton, Ontario, Canada; 7Centre for Evaluation of Medicines, Programs for Assessment of Technology in Health (PATH) Research Institute, McMaster University, Hamilton, Ontario, Canada*These authors contributed equally to this workCorrespondence: Zainab Samaan, Health Research Methodology Graduate Program, McMaster University, Department of Psychiatry and Behavioural Neurosciences, McMaster University, 1280 Main St. West, Hamilton, Ontario, Canada, Tel +1 905-522-1155 ext. 35448, Fax +1 905-381-5629, Email samaanz@mcmaster.caIntroduction: Patient centred care is needed now more than ever in the treatment of opioid use disorder. Trials, policy makers, and service providers have most often used treatment retention and opioid urine screens as measures of treatment effectiveness. However, patients receiving medication for opioid use disorder treatment (MOUD) may prioritise the use of different ways to assess treatment success.Objective: The aim of this review is to synthesize literature examining the self-reported goals patients would like to achieve in MOUD for opioid use disorder.Methods: We searched MEDLINE, EMBASE, PsycINFO, Cumulative Index to Nursing and Allied Health Literature, Web of Science, Cochrane Library, Cochrane Clinical Trials Registry, the National Institutes for Health Clinical Trials Registry, and the WHO International Clinical Trials Registry Platform from inception until April 30th, 2021. No restrictions were placed on language, age, or type of MOUD. A qualitative synthesis is presented given that a meta-analysis was not possible.Results: The search yielded a total of 21,082 records from which 8 met criteria for inclusion in the qualitative synthesis. We identified a total of 43 patient-reported treatment goals from the 8 studies. Twelve domains were created from the 43 goals reported. These domains cover a range of important areas for patients’ goals related to living a normal life, physical health, mental health, treatment, and substance use specific areas.Conclusion: This review highlights several patient goals that they would like to achieve during treatment for opioid use disorder that are not commonly considered as markers of treatment effectiveness. Goals related to health, living a normal life, and overall substance use concerns by patients should be taken into consideration by clinical trialists, researchers, policy makers, service providers, patients, and communities engaged in developing and tailoring treatment plans for opioid use disorder.Systematic Review Registration: PROSPERO CRD42018095553.Keywords: opioid use disorder, patient reported outcomes, patient-centred care, medication for opioid use disorder
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 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 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».