Promoting benzodiazepine cessation through an electronically-delivered patient self-management intervention (EMPOWER-ED): Randomized controlled trial protocol
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: Long-term benzodiazepine dependence carries significant health risks which might be reduced with low-cost patient self-management interventions. A booklet version of one such intervention (Eliminating Medications Through Patient Ownership of End Results; EMPOWER) proved effective in a Canadian clinical trial with older adults. Digitizing such an intervention for electronic delivery and tailoring it to different populations could expand its reach. Accordingly, this article describes the protocol for a randomized controlled trial to test the effectiveness of an electronically-delivered, direct-to-patient benzodiazepine cessation intervention tailored to U.S. military veterans. Methods: Design: Two-arm individually randomized controlled trial. Setting: US Veterans Health Administration primary care clinics. Participants: Primary care patients taking benzodiazepines for three or more months and having access to a smartphone, tablet or desktop computer. Intervention and comparator: Participants will be randomized to receive either the electronically-delivered EMPOWER (EMPOWER-ED) protocol or asked to continue to follow provider recommendations regarding their benzodiazepine use (treatment-as-usual). Measurements: The primary outcomes are complete benzodiazepine cessation and 25% dose reduction, assessed using administrative and self-report data, between baseline and six-month follow-up. Secondary outcomes are self-reported anxiety symptoms, sleep quality, and overall health and quality of life, measured at baseline and 6-month follow-up, and benzodiazepine cessation at 12-month follow-up. Comments: This randomized controlled trial will evaluate whether the accessibility and effectiveness of a promising intervention for benzodiazepine cessation can be improved through digitization and population tailoring.
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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 | 0.037 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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