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Government Direct-to-Consumer Education to Reduce Prescription Opioid Use

2024· article· en· W4399123011 on OpenAlexafffundabout
Justin P. Turner, Alex S. Halme, Patrícia Caetano, Aili Langford, Cara Tannenbaum

Bibliographic record

VenueJAMA Network Open · 2024
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsCanadian Agency for Drugs and Technologies in HealthUniversité de MontréalCentre Intégré de Santé et Services Sociaux de la GaspésieInstitut Universitaire de Gériatrie de Montréal
FundersCanadian Institutes of Health Research
KeywordsMedicineMedical prescriptionDiscontinuationRandomized controlled trialOpioidPharmacyIntervention (counseling)Family medicinePsychiatryInternal medicineNursing

Abstract

fetched live from OpenAlex

Importance: Direct-to-consumer education reduces chronic sedative use. The effectiveness of this approach for prescription opioids among patients with chronic noncancer pain remains untested. Objectives: To evaluate the effectiveness of a government-led educational information brochure mailed to community-dwelling, long-term opioid consumers to reduce prescription opioid use compared with usual care. Design, Setting, and Participants: This cluster randomized clinical trial was conducted from July 2018 to January 2019 in Manitoba, Canada. All adults with long-term opioid prescriptions were enrolled (n = 4225). Participants were identified via the Manitoba Drug Program Information Network. Individuals receiving palliative care or with a diagnosis of cancer or dementia were excluded. Data were analyzed from July 2019 to March 2020. Intervention: Participants were clustered according to their primary care clinic and randomized to the intervention (a codesigned direct-to-consumer educational brochure sent by mail) or usual care (comparator group). Main Outcomes and Measures: The main outcome was discontinuation of opioid prescriptions at the participant level after 6 months, ascertained by pharmacy drug claims. Secondary outcomes included dose reduction (in morphine milligram equivalents [MME]) and/or therapeutic switch. Reduction in opioid use was assessed using generalized estimating equations to account for clustering, with prespecified subgroup analyses by age and sex. Analysis was intention to treat. Results: Of 4206 participants, 2409 (57.3%) were male; mean (SD) age was 60.0 (14.4) years. Mean (SD) baseline opioid use was comparable between groups (intervention, 157.7 [179.7] MME/d; control, 153.4 [181.8] MME/d). After 6 months, 235 of 2136 participants (11.0%) in 127 clusters in the intervention group no longer filled opioid prescriptions compared with 228 of 2070 (11.0%) in 124 clusters in the comparator group (difference, 0.0%; 95% CI, -1.9% to 1.9%). More participants in the intervention group than in the control group reduced their dose (1410 [66.0%] vs 1307 [63.1%]; difference, 2.8% [95% CI, 0.0%-5.7%]). Receipt of the brochure led to greater dose reductions for participants who were male (difference, 3.9%; 95% CI, 0.1%-7.7%), aged 18 to 64 years (difference, 3.7%; 95% CI, 0.2%-7.2%), or living in urban areas (difference, 5.9%; 95% CI, 1.9%-9.9%) compared with usual care. Conclusions and Relevance: In this cluster randomized clinical trial, no significant difference in the prevalence of opioid cessation was observed after 6 months between the intervention and usual care groups; however, the intervention resulted in more adults reducing their opioid dose compared with usual care. Trial Registration: ClinicalTrials.gov Identifier: NCT03400384.

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.

How this classification was reachedexpand

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.254
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.023
GPT teacher head0.312
Teacher spread0.290 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2024
Admission routes3
Has abstractyes

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