Impact of alternative income assistance disbursement on substance use disorder treatment adherence among people who use drugs
Bibliographic record
Abstract
Background: The synchronized disbursement of income assistance payments is associated with increased drug-related harms and substance use disorder (SUD) treatment interruptions. Desynchronizing and splitting these payments can mitigate escalations in drug use, suggesting that downstream effects on SUD treatment may be impacted as well.Objectives: To understand the effect of desynchronizing and splitting income assistance payments on treatment patterns, including adherence to medications for opioid use disorder (MOUD).Methods: Data came from The Impact of Alternative Social Assistance on Drug Related Harm (TASA) study, conducted in Vancouver, Canada. This parallel arm, multi-group, randomized controlled trial assigned participants for six payment cycles to the synchronized monthly government schedule control or one of two intervention arms receiving payments desynchronized from the government schedule: a “staggered” group receiving monthly payments or a “split & staggered” group receiving semimonthly payments. Multivariable generalized estimating equations assessed the effect on overall SUD treatment adherence, MOUD adherence, and non-MOUD SUD treatment adherence.Results: Between October 2015 and January 2019, 194 participants were randomized and followed, including 89 (45.8%) women and 83 (42.8%) who self-identified as a person of color. In both intent-to-treat (ITT) and modified per-protocol (MPP) analyses, neither intervention arm was associated with decreased adherence to SUD treatment (ITT staggered arm adjusted odds ratio [AOR] 0.75, 95% confidence interval [CI] 0.36–1.55, split and staggered arm AOR 0.83, 95% CI 0.44–1.57; MPP staggered arm AOR 0.72, 95% CI 0.38–1.39, split and staggered arm AOR 0.89, 95% CI 0.54–1.46), including MOUD and non-MOUD.Conclusions: Alternative income assistance disbursement did not positively impact SUD treatment adherence, contrary to the hypothesis. Changing payment schedules also did not negatively impact SUD treatment adherence, suggesting that changes to payment delivery could be completed without impacting 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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".