Barriers to Deprescribing Benzodiazepines in Older Adults in a Survey of European Physicians
Bibliographic record
Abstract
Importance: The use of benzodiazepine receptor agonists (BZRA) poses serious health risks to older adults. Although several guidelines recommend deprescribing, implementation in clinical practice remains limited. Objective: To identify physicians' barriers to and enablers of deprescribing BZRA in adults aged 65 years and older taking a BZRA for sleep problems; to determine factors associated with hospital physicians' intention to deprescribe BZRA and their self-reported routine BZRA deprescribing. Design, Setting, and Participants: This survey study included hospital physicians and general practitioners (GPs) working across 6 European Countries (Belgium, Greece, Norway, Poland, Spain, and Switzerland) between December 2022 and March 2023. Main Outcomes and Measures: Barriers identification via a 35-item questionnaire based upon the Theoretical Domains Framework (TDF). Responses were categorized as major barriers, moderate barriers, and enablers based on their mean scores. Multivariable logistic regressions were used to identify background characteristics and TDF-based domains associated with hospital physicians' intention to deprescribe and self-reported routine deprescribing. Results: Questionnaires from 240 hospital physicians and 96 GPs were analyzed. Most participants were women: 144 (61.0%) hospital physicians and 52 (54.2%) GPs. In terms of experience, the most common reported time in practice was less than 5 years for hospital physicians (76 [31.7%]) and between 10 and 14 years for GPs (35 [36.5%]). Most reported deprescribing BZRA routinely (135 hospital physicians [57.2%] and 66 GPs [72.5%]). Major barriers (and TDF domains) were similar for hospital physicians and GPs across the 6 countries. These barriers included: lack of training (skills), low self-efficacy (beliefs about capabilities), prioritization of other health issues (goals), frustration with the challenges of deprescribing (emotions), insufficient staff and time, absence of local policies (environmental context and resources), and reluctance from patients (social influence). Intention to deprescribe was significantly associated with country, occupation type, and 5 TDF domains: memory, attention, and decision process (odds ratio [OR], 1.70; 95% Ci, 1.22-2.40); social and/or professional role and identity (OR, 5.92; 95% CI, 3.28-11.07); beliefs about capabilities (OR, 2.35; 95% CI, 1.55-3.63); beliefs about consequences (OR, 3.00; 95% CI, 1.61-5.71); and reinforcement (OR, 1.49; 95% CI, 1.05-2.15). Routine deprescribing was significantly associated with 3 TDF domains: memory, attention, and decision processes; intentions; and emotions. Conclusion: In this theory-based survey study of physicians, physicians and general practitioners described numerous barriers to deprescribing BZRA in older adults. Our findings indicate that effective deprescribing efforts require approaches that address both reflective processes (eg, enhancing capability) and impulsive processes (eg, managing emotions).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".