Sociodemographic Profiles and Clinical Outcomes for Clients on Methadone Maintenance Treatment in a Western Canadian Clinic: Implications for Practice
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: Clients on methadone maintenance treatment (MMT) have high attrition rates that are attributed to personal and system-related factors. To develop supportive interventions for these clients, it is imperative to understand social demographic characteristics and challenges that clients in the MMT program face. OBJECTIVES: This article aims to describe (a) the sociodemographic characteristics and clinical profiles of clients in a MMT program, (b) factors that impact their positive clinical outcomes, and (c) the study's implications for practice. METHODS: A retrospective review of 101 randomly selected electronic medical records representing one third of all the records were examined for sociodemographic characteristics, clinical profiles, and outcomes. Descriptive statistics were used to analyze these variables. Interviews with 18 healthcare providers focusing on their experiences of caring for clients in the MMT program were analyzed thematically. RESULTS: The average age of clients on MMT is 35.5 years. Clients had early exposure to alcohol and drugs, and at the time of enrollment to the program, they presented with complex healthcare needs, borne from chronic use, and exposure to adverse traumatic events. Personal and systemic factors impact clients' recovery. These include poverty, homelessness, and inadequate healthcare services. Understanding sociodemographic characteristics, clinical profiles, and clients' challenges is central to the development of supportive interventions that enhance retention to care and recovery.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it