Implementing Blended Care to Discontinue Benzodiazepine Receptor Agonist Use for Insomnia: Process Evaluation of a Pragmatic Cluster Randomized Controlled Trial
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.032 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".