Exploring the experiences of clients receiving opioid use disorder treatment at a methadone clinic in Kenya: a qualitative study
Bibliographic record
Abstract
BACKGROUND: Assessing the experiences of individuals on methadone treatment is essential to help evaluate the treatment program's effectiveness. This study aimed to explore the experiences of patients receiving methadone treatment at a clinic in Nairobi, Kenya. METHOD: This study employed an exploratory qualitative study design. Through purposive sampling, participants were enrolled from individuals attending a methadone clinic for at least 2 years. Semi-structured individual interviews were used to collect data on substance use and experience before methadone treatment and experiences after starting methadone treatment, including benefits and challenges. Interviews were transcribed, and NVIVO 12 software was used to code the data using the preidentified analytical framework. Thematic analyses were utilized to identify cross-cutting themes between these two data sets. Seventeen participants were enrolled. RESULTS: Seventeen participants were enrolled comprising 70% males, with age range from 23 to 49 years and more than half had secondary education. The interview data analysis identified four themes, namely: (a) the impact of opioid use before starting treatment which included adverse effects on health, legal problems and family dysfunction; (b) learning about methadone treatment whereby the majority were referred from community linkage programs, family and friends; (c) experiences with care at the methadone treatment clinic which included benefits such as improved health, family reintegration and stigma reduction; and (d) barriers to optimal methadone treatment such as financial constraints. CONCLUSION: The findings of this study show that clients started methadone treatment due to the devastating impact of opioid use disorder on their lives. Methadone treatment allowed them to regain their lives from the adverse effects of opioid use disorder. Additionally, challenges such as financial constraints while accessing treatment were reported. These findings can help inform policies to improve the impact of methadone treatment.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".