A realist evaluation of patients’ decisions to deprescribe in the EMPOWER trial
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Successful mechanisms for engaging patients in the deprescribing process remain unknown but may include: (1) triggering motivation to deprescribe by increasing patients' knowledge and concern about medications; (2) building capacity to taper by augmenting self-efficacy and (3) creating opportunities to discuss and receive support for deprescribing from a healthcare provider. We tested these mechanisms during theEliminating Medications through Patient Ownership of End Results (EMPOWER) () trial and investigated the contexts that led to positive and negative deprescribing outcomes. DESIGN: A realist evaluation using a sequential mixed methods approach, conducted alongside the EMPOWER randomised clinical trial. SETTING: Community, Quebec, Canada. PARTICIPANTS: 261 older chronic benzodiazepine consumers, who received the EMPOWER intervention and had complete 6-month follow-up data. INTERVENTION: Mailed deprescribing brochure on benzodiazepines. MEASUREMENTS: Motivation (intent to discuss deprescribing; change in knowledge test score; change in beliefs about the risk-benefits of benzodiazepines, measured with the Beliefs about Medicines Questionnaire), capacity (self-efficacy for tapering) and opportunity (support from a physician or pharmacist). RESULTS: The intervention triggered the motivation to deprescribe among 167 (n=64%) participants (mean age 74.6 years±6.3, 72% women), demonstrated by improved knowledge (risk difference, 58.50% (95% CI 46.98% to 67.44%)) and increased concern about taking benzodiazepines (risk difference, 67.67% (95% CI 57.36% to 74.91%)). Those who attempted to taper exhibited increased self-efficacy (risk difference, 56.90% (95% CI 45.41% to 65.77%)). Contexts where the deprescribing mechanisms failed included lack of support from a healthcare provider, a focus on short-term quality of life, intolerance to withdrawal symptoms and perceived poor health. CONCLUSION: Deprescribing mechanisms that target patient motivation and capacity to deprescribe yield successful outcomes in contexts where healthcare providers are supportive, and patients do not have internal competing desires to remain on drug therapy. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov: NCT01148186.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 it