Concordance of self-reported drug use and saliva drug tests in a sample of emergency department patients
Bibliographic record
Abstract
The purpose of this study was to assess the concordance of self-reports of cannabis, cocaine and amphetamines, and the utility of these, with a saliva point of collection drug test, the DrugWipe 5+, in an emergency department (ED) setting. METHODS: A random sample of people admitted to either of two emergency departments at hospitals in British Columbia, Canada were asked to participate in an interview on their substance use and provide a saliva test for detection of drugs. ANALYSES: Concordance of self-reports and drug tests were calculated. Prior DrugWipe 5+ sensitivity and specificity estimates were compared against a gold standard of mass spectrometry and chromatography (MS/GC). This was used as a basis to assess the truthfulness of self-reports for each drug. RESULTS: Of the 1584 patients approached 1190 agreed to participate, a response rate of 75.1%. For cannabis, among those who acknowledged use only 21.1% had a positive test and 2.1% of those who reported no use had a positive test. For cocaine and amphetamines respectively, 50.0% and 57.1% tested positive among those reporting use, while 2.1% and 1.3%, respectively reported no use and tested positive. Self-reports of cannabis and amphetamines use appear more truthful than self-reports of cocaine 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 | 0.003 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".