Randomized controlled trial of motivational interviewing for reducing injection risk behaviours among people who inject drugs
Bibliographic record
Abstract
AIM: We tested the efficacy of a brief intervention based on motivational interviewing (MI) to reduce high-risk injection behaviours over a 6-month period among people who inject drugs (PWID). DESIGN: A single-site two-group parallel randomized controlled trial comparing MI with a brief educational intervention (EI). SETTING: A study office located in downtown Montréal, Canada, close to the community-based harm reduction programmes where PWID were recruited. PARTICIPANTS: PWID who had shared drug injection equipment or shared drugs by backloading or frontloading in the month prior to recruitment were randomized to either the MI (112) or EI (109) groups. INTERVENTION: The MI aimed to (1) encourage PWID to voice their desires, needs and reasons to change behaviours; (2) boost motivation to change behaviours; and (3) when the person was ready, support the plan he or she chose to reduce injection risk behaviours. The EI consisted of an individual session about safe injection behaviours. MEASUREMENTS: The primary outcome was defined as having any of these risk behaviours at 6 months: having shared syringes, containers, filters or water to inject drugs in the previous month and backloading/frontloading; each behaviour was examined separately, as secondary outcomes. FINDINGS: The probability of reporting a risk injection behaviour decreased in both the MI and the EI groups. At 6-month follow-up, participants who reported any risk behaviours were 50% [odds ratio (OR) = 0.50; confidence interval (CI) = 0.13-0.87] less likely to be in the MI group than in the EI group as well as those who reported sharing containers (OR = 0.50; CI = 0.09-0.90). PWID who reported sharing equipment excluding syringes were 53% less likely to be in the MI group (OR = 0.47; CI = 0.11-0.84). CONCLUSIONS: A brief motivational interviewing intervention was more effective than a brief educational intervention in reducing some high risk injecting behaviours up in the subsequent 6 months.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".