Acupuncture for substance abuse treatment in the downtown Eastside of Vancouver
Bibliographic record
Abstract
Eastside (DES) represents the poorest urban population in Canada. A prevalence rate of 30 % for HIV and 90 % for hepatitis C makes this a priority area for public-health interventions aimed at reducing the use of injected drugs. This study examined the util-ity of acupuncture treatment in reducing substance use in the marginalized, transient population. Acupuncture was offered on a voluntary, drop-in basis 5 days per week at two community agencies. During a 3-month period, the program generated 2,755 cli-ent visits. A reduction in overall use of substances (P =.01) was reported by subjects in addition to a decrease in intensity of withdrawal symptoms including “shakes, ” stomach cramps, hallucinations, “muddle-headedness, ” insomnia, muscle aches, nausea, sweating, heart palpitations, and feeling suicidal, P <.05. Acupuncture offered in the context of a community-based harm reduction model holds promise as an adjunct therapy for reduction of substance use.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".