Changes in acute substance use patterns following traumatic event exposure in a marginalized population : an exploratory study
Bibliographic record
Abstract
The current study addressed the acute relationship between substance use and traumatic events in a marginalized population where substance dependence is ubiquitous, and trauma is an assumed part of life. A sample of participants living in Single Room Occupancy hotels on Vancouver’s Downtown Eastside were included (n = 274). A repeated measures analysis of variance was used to compare the number of days using substances from a month with a recorded traumatic event to the month following with no traumatic event. Substance classes were separated and analyzed separately (methamphetamine, cocaine, opioids, cannabis, and alcohol). The number of days used in the month prior to the trauma was utilized as a controlling covariate. Analyses revealed that, in the month following a traumatic event, there was an increase in number of days using methamphetamines (p = 0.002). In addition, a decrease in the number of days using alcohol was found in the month after a traumatic event (p < 0.001). The results have implications for harm-reduction strategies and addiction treatment for counsellors working with individuals residing on the Downtown Eastside. As this area of the trauma-substance use relationship has never been investigated, the findings offer new lines of opportunities for future research.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".