Sociodemographic characteristics of patients with children in a methadone maintenance program: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Ever-increasing numbers of opioid use disorder (OUD) in Canada has created the recent opioid crisis. One common treatment for OUD is methadone maintenance treatment (MMT). Various factors, including being a parent which entails specific stressors, may increase susceptibility to negative treatment outcomes. This study aims to investigate differences between OUD patients with and without children in socio-demographic and clinical outcomes. METHODS: Data for this study are part of a larger program. All participants are 18+ years old with OUD, provided consent, and receiving MMT. We performed a multivariable logistic regression to examine the differences between participants' parental status, sociodemographic variables, and clinical parameters including MMT outcomes. We performed subgroup analyses on individuals with children younger than 18. RESULTS: A total of 1099 participants were included, with 64% having children. Participants with children were older (OR 1.06, 95% CI 1.04, 1.08), more likely to be female (OR 2.39, 95% CI 1.75, 3.27), living with a partner (OR 1.75, 95% CI 1.27, 2.41), first exposed to opioids through a prescription (OR 1.517, 95% CI 1.13, 2.04) and had lower levels of education (OR 1.86, 95% CI 1.20, 2.87). There was no significant difference in illicit opioid use patterns between groups. Same results held true in the subgroup analyses based on the age of the children except for participant age. CONCLUSION: Our results demonstrate social and demographic differences between parents and non-parents receiving MMT. These differences highlight the need to understand necessary additional support for parents such as child support and other necessary therapies.
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How this classification was reachedexpand
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) | 0.000 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".