Patients' perspectives on feedback interventions to support adherence to long-term medication: a systematic review with thematic synthesis of qualitative evidence
Notice bibliographique
Résumé
Abstract Background Medication optimisation is a global issue with up to 50% of people not taking medicines as prescribed. Numerous interventions have been developed to address this, many of them including feedback on behaviour and outcomes. Understanding patients’ views on such interventions is essential for successful adoption and use. Purpose The purpose of this systematic review is to: (1) Understand patients’ perspectives and experiences of medication adherence feedback interventions and (2) Identify barriers and facilitators which influence their implementation within practice. Methods CINAHL, MEDLINE, EMBASE, PubMED, PsycINFO and Google Scholar were systematically searched to identify relevant studies. The inclusion criteria included; studies with qualitative or mixed method designs describing patients’ perspectives on medication adherence feedback interventions, primary studies with adult participants on long-term medications and studies involving interventions suitable for self-management in primary or community care. Quality assessment was completed using the Mixed Methods Appraisal Tool. The review was reported using the PRISMA and conducted using ENTREQ guidelines. Data were extracted and analysed using thematic synthesis (NVivo 20). Findings were presented narratively. Results From the 1,031 records screened, ten studies were included. Five studies were conducted in the United States, two in the United Kingdom, and one in the Netherlands, Canada, and Tanzania, respectively. Medication adherence interventions included the use of therapeutic drug monitoring methods and digital adherence technologies such as mHealth and eHealth for people living with asthma, HIV, coronary heart disease, hypertension, and type 2 diabetes. Patients found interventions acceptable if they were simple to use, allowed control over data sharing options, incorporated audio visual cues, and provided emotional and motivational support. Building trust between patients and healthcare providers and the resulting benefit of shared decision-making were also considered key factors for intervention success. However, developing interventions without user input was identified as a potential barrier to intervention implementation. Patients expressed an overall desire to have interventions tailored to meet their personal needs and preferences, highlighting the importance of placing user needs at the centre of intervention development. Conclusion Placing user needs at the centre of adherence intervention development is crucial for successful implementation. Further research which facilitates user involvement in co-designing interventions to compliment patients’ characteristics and preferences would be key for intervention implementation.
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 | 0,007 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,004 | 0,004 |
| 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 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 ».