“Don’t Judge a Book by Its Cover”: A Qualitative Study of Methadone Patients’ Experiences of Stigma
Bibliographic record
Abstract
INTRODUCTION: Despite its efficacy and widespread use, methadone maintenance treatment (MMT) continues to be widely stigmatized. Reducing the stigma surrounding MMT will help improve the accessibility, retention, and treatment outcomes in MMT. METHODS: Semi-structured interviews were conducted with 18 adults undergoing MMT. Thematic content analysis was used to identify overarching themes. RESULTS: In total, 78% of participants reported having experienced stigma surrounding MMT. Common stereotypes associated with MMT patients included the following: methadone as a way to get high, incompetence, untrustworthiness, lack of willpower, and heroin junkies. Participants reported that stigma resulted in lower self-esteem; relationship conflicts; reluctance to initiate, access, or continue MMT; and distrust toward the health care system. Public awareness campaigns, education of health care workers, family therapy, and community meetings were cited as potential stigma-reduction strategies. DISCUSSION AND CONCLUSION: Stigma is a widespread and serious issue that adversely affects MMT patients' quality of life and treatment. More efforts are needed to combat MMT-related stigma.
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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 | 0.014 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.011 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".