Risk Indicators of Depressive Symptomatology among Injection Drug Users and Increased HIV Risk Behaviour
Bibliographic record
Abstract
OBJECTIVES: In 2009, the annual incidence of positive human immunodeficiency virus (HIV) test reports for people in the Saskatoon Health Region (SHR) was 31.3 per 100,000, when the national average was only 9.3 per 100 000. The first objective was to determine the prevalence of depressive symptomatology among injection drug users (IDUs) in the SHR. The second objective was to determine the unadjusted and adjusted risk indicators associated with depressive symptomatology among IDUs. The third objective was to determine if depressive symptomatology was associated with HIV risk behaviours. METHODS: From September 2009 to April 2010, 603 current IDUs were surveyed with validated instruments; this sample represents 76.6% of known IDUs in the SHR. RESULTS: Among the respondents, 81.4% reported depressive symptomatology, whereas 57.7% reported more severe depressive symptomatology. After multivariate analysis, the 4 covariates that had an independent association with depressive symptomatology included sexual assault as an adult, sexual assault as a child, attending a residential school, and having an annual income of less than $10,000 Depressive symptomatology was initially associated with 7 HIV risk behaviours. After multivariate analysis, depressive symptomatology was associated with giving sex to get money, giving drugs to get sex, and with more frequently sharing injecting equipment. CONCLUSIONS: This study found that depressive symptomatology was strongly associated with injection drug 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".