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Record W2610613993 · doi:10.1136/bmjopen-2017-015959

A realist evaluation of patients’ decisions to deprescribe in the EMPOWER trial

2017· article· en· W2610613993 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueBMJ Open · 2017
Typearticle
Languageen
FieldMedicine
TopicMedication Adherence and Compliance
Canadian institutionsUniversité de MontréalInstitut Universitaire de Gériatrie de Montréal
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health Research
KeywordsDeprescribingMedicineIntervention (counseling)Quality of life (healthcare)PharmacistRandomized controlled trialFocus groupHealth careClinical trialPolypharmacyFamily medicinePharmacyNursingIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.734
Threshold uncertainty score0.724

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.505
GPT teacher head0.560
Teacher spread0.055 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it