Determinants of Health-Related Quality of Life of Opiate Users at Entry to Low-Threshold Methadone Programs
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to conduct an exploratory analysis of factors associated with poor health-related quality of life (HRQOL) among opiate users at entry to low-threshold methadone treatment. METHODS: The SF-36 questionnaire was administered to 145 opiate users at enrollment into low-threshold methadone maintenance programs. ANOVA and correlational analyses were performed to investigate the determinants of poor physical and mental composite summary scales (PCS and MCS) of the SF-36 among opiate users. Stepwise regression methods were also employed to fit PCS and MCS multivariate models. RESULTS: Age, employment status, chronic medical conditions, hospitalization, emotional abuse, sexual abuse and age at first injection episode were significantly associated with PCS. Mental health problems, sexual abuse, physical abuse, the use of sedatives, the use of cocaine, the number of days of cocaine use, sedative use and multiple substance use in the past month were significantly associated with MCS. The variances in the MCS and PCS were not readily explained by any one factor. CONCLUSION: The multiplicity of factors influencing HRQOL of opiate users suggests the need for a range of services within the context of a methadone program, addressing primary medical care needs as well as treatment for both mental health problems and abuse issues.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".