Opioid consumption frequency and its associations with potential life problems during opioid agonist treatment in individuals with prescription-type opioid use disorder: exploratory results from the OPTIMA Study
Bibliographic record
Abstract
BACKGROUND: Traditional treatment approaches for prescription-type opioid use disorder (POUD), centered on abstinence, have limitations and hinder the development of interventions that meet the needs of people with POUD. Reduction in use without complete abstinence presents a promising avenue for intervention enhancement, but supporting data is scarce regarding its translation into positive patient outcomes. This study explores whether reducing opioid use frequency (OUF) during opioid agonist treatment correlates with reduced potential life problems in individuals with POUD, including those using fentanyl. METHODS: This study is an exploratory analysis of the OPTIMA trial, a pragmatic, open-label, randomized controlled study comparing the effectiveness of flexible take-home dosing of buprenorphine/naloxone and supervised methadone in reducing opioid use amongst individuals with POUD. OUF was assessed every two weeks for 24 weeks after treatment initiation using the Timeline Followback. Potential life problems were evaluated at baseline and study completion using the Addiction Severity Index Self-Report. The 114 participants who completed both baseline and end-of-study questionnaires were included. A repeated-measures generalized linear mixed model (GLMM) was used to evaluate the influence of OUF on potential life problems. RESULTS: Reducing OUF was significantly associated with fewer problems related to medical status (p = 0.049), psychiatric status (p = 0.019), and alcohol problem severity (p = 0.001). The interaction was non-significant for employment (p = 0.264), family status (p = 0.352) and legal status (p = 0.050). Life improvements emerged with ≤ 21 days of opioid use per 28-day period. CONCLUSION: Findings underscore the significance of harm reduction goals focusing on opioid use reduction, which translated in improvements across many life domains. TRIAL REGISTRATION: Study was registered with ClinicalTrials.gov (NCT03033732) prior to participant enrollment.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".