Development of a complex community pharmacy intervention package using theory-based behaviour change techniques to improve older adults’ medication adherence
Notice bibliographique
Résumé
BACKGROUND: To improve the effectiveness of interventions targeting non-adherence in older adults, a systematic approach to intervention design is required. The content of complex interventions and design decisions are often poorly described in published reports which makes it difficult to explore why they are ineffective. This intervention development study reports on the design of a community pharmacy-based adherence intervention using 11 Behaviour Change Techniques (BCTs) which were identified from previous qualitative research with older patients using the Theoretical Domains Framework. METHODS: Using a group consensus approach, a five-step design process was employed. This focused on decisions regarding: (1) the overall delivery format, (2) formats for delivering each BCT; (3) methods for tailoring BCTs to individual patients; (4) intervention structure; and (5) materials to support intervention delivery. The APEASE (Affordability; Practicability; Effectiveness/cost-effectiveness; Acceptability; Side effects/safety; Equity) criteria guided the selection of BCT delivery formats. RESULTS: Formats for delivering the 11 BCTs were agreed upon, for example, a paper medicines diary was selected to deliver the BCT 'Self-monitoring of behaviour'. To help tailor the intervention, BCTs were categorised into 'Core' and 'Optional' BCTs. For example, 'Feedback on behaviour' and 'Action planning' were selected as 'Core' BCTs (delivered to all patients), whereas 'Prompts and cues' and 'Health consequences' were selected as 'Optional' BCTs. A paper-based adherence assessment tool was designed to guide intervention tailoring by mapping from identified adherence problems to BCTs. The intervention was designed for delivery over three appointments in the pharmacy including an adherence assessment at Appointment 1 and BCT delivery at Appointments 2 and 3. CONCLUSIONS: This paper details key decision-making processes involved in moving from a list of BCTs through to a complex intervention package which aims to improve older patients' medication adherence. A novel approach to tailoring the content of a complex adherence intervention using 'Core' and 'Optional' BCT categories is also presented. The intervention is now ready for testing in a feasibility study with community pharmacists and patients to refine the content. It is hoped that this detailed report of the intervention content/design process will allow others to better interpret the future findings of this work.
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 | 0,003 | 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 | 0,001 |
| 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 ».