Implementing Blended Care to Discontinue Benzodiazepine Receptor Agonist Use for Insomnia: Process Evaluation of a Pragmatic Cluster Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: Long-term use of benzodiazepine receptor agonists (BZRAs) remains common despite European guidelines advising that these drugs be used in the lowest possible dose and for the shortest possible duration. Half of all BZRAs are prescribed in family practice. This creates a window of opportunity for discontinuation in primary care. Therefore, the effectiveness of blended care for the discontinuation of long-term BZRA use in adult primary care patients with chronic insomnia disorder was tested in a multicenter, pragmatic, and cluster randomized controlled superiority trial in Belgium. In the literature, information on implementing blended care in a primary care setting is scarce. OBJECTIVE: The study aimed to contribute to a framework for the successful implementation of blended care in a primary care setting by increasing our understanding of this complex intervention through an evaluation of e-tool use and views and ideas of participants in a BZRA discontinuation trial. METHODS: Based on a theoretical framework, this study evaluated the processes of recruitment, delivery, and response using 4 components: a survey on recruitment (n=76), semistructured in-depth interviews with patients (n=18), web-based asynchronous focus groups with general practitioners (GPs; n=19), and usage data of the web-based tool. Quantitative data were analyzed descriptively, and qualitative data were analyzed thematically. RESULTS: For recruitment, the most common barriers were refusal by the patient and the lack of digital literacy, while facilitators were starting the conversation and the curiosity of patients. The delivery of the intervention to the patients was diverse, ranging from GPs who never informed the patient about their access to the e-tool to GPs consulting the e-tool in between consultations to have discussion points when the patient visited. Concerning response, patients' and GPs' narratives also showed much variety. For some GPs, daily practice changed because they received more positive reactions than expected and felt empowered to talk more often about BZRA discontinuation. Conversely, some GPs reported no changes in practice or among patients. In general, patients found follow-up by an expert to be the most important component in blended care, whereas GPs deemed the intrinsic motivation of patients to be the key element of success. An important barrier to implementation by the GP was time. CONCLUSIONS: Overall, the participants who had used the e-tool were positive about its structure and content. Nevertheless, many patients desired a more tailored application with feedback from an expert and personal tapering schedules. Strict pragmatic implementation of blended care seems to only reach GPs with an interest in digitalization. Although not superior to usual care, blended care could be a complementary tool that allows tailoring the discontinuation process to the personal style of the GP and the needs of the patient. TRIAL REGISTRATION: ClinicalTrials.gov NCT03937180; https://clinicaltrials.gov/ct2/show/NCT03937180.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,032 | 0,040 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,005 | 0,006 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,003 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,001 |
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 source (Gemma direct ou Codex distillé), 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 ».