Are patients’ goals in treatment associated with expected treatment outcomes? Findings from a mixed-methods study on outpatient pharmacological treatment for opioid use disorder
Bibliographic record
Abstract
OBJECTIVES: Existing methods of measuring effectiveness of pharmacological treatment for opioid use disorder (OUD) are highly variable. Therefore, understanding patients' treatment goals is an integral part of patient-centred care. Our objective is to explore whether patients' treatment goals align with a frequently used clinical outcome, opioid abstinence. DESIGN: Triangulation mixed-methods design. SETTING AND PARTICIPANTS: We collected prospective data from 2030 participants who were receiving methadone or buprenorphine-naloxone treatment for a diagnosis of OUD in order to meet study inclusion criteria. Participants were recruited from 45 centrally-managed outpatient opioid agonist therapy clinics in Ontario, Canada. At study entry, we asked, 'What are your goals in treatment?' and used NVivo software to identify common themes. PRIMARY OUTCOME MEASURE: Urine drug screens (UDS) were collected for 3 months post-study enrolment in order to identify abstinence versus ongoing opioid use (mean number of UDS over 3 months=12.6, SD=5.3). We used logistic regression to examine the association between treatment goals and opioid abstinence. RESULTS: Participants had a mean age of 39.2 years (SD=10.7), 44% were women and median duration in treatment was 2.6 years (IQR 5.2). Six overarching goals were identified from patient responses, including 'stop or taper off of treatment' (68%), 'stay or get clean' (37%) and 'live a normal life' (14%). Participants reporting the goal 'stay or get clean' had lower odds of abstinence at 3 months than those who did not report this goal (OR=0.73, 95% CI 0.59 to 0.91, p=0.005). Although the majority of patients wanted to taper off or stop medication, this goal was not associated with opioid abstinence, nor were any of their other goals. CONCLUSIONS: Patient goals in OUD treatment do not appear to be associated with programme measures of outcome (ie, abstinence from opioids). Future studies are needed to examine outcomes related to patient-reported treatment goals found in our study; pain management, employment, and stopping/tapering treatment should all be explored.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.088 | 0.160 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".