Reporting on the prevalence of drug and alternative health product use for mental health reasons: results from a national population survey.
Bibliographic record
Abstract
BACKGROUND: Concomitant use of alternative health products with commonly prescribed medications has been associated with elevated risks of adverse effects. OBJECTIVE: The aim of this study was to determine the prevalence and determinants of the use of alternative health products and psychotropic drugs in the same year for mental health reasons and to examine this for specific psychiatric and physical conditions. METHODS: This study used data from the Canadian Community Health Survey: Mental Health and Well-Being cycle 1.2 carried out by Statistics Canada in 2002 on 36,984 Canadians. Multivariate analyses were carried out to identify determinants of health product use. RESULTS: Overall, 13% of Canadians reported the use of alternative health products. Among respondents with a psychiatric diagnosis, heart disease, high blood pressure and diabetes the rate was 20.0%, 12.0%, 12.6% and 9.4% respectively. Use of alternative health products and psychotropic drugs within the same year was reported by 21.3%. Determinants of alternative health product use included older age, female sex, higher education, and mental disorder, the use of cardiovascular drugs, consulting a health care provider for mental health reasons and reporting an unmet mental health need. People with diabetes were less likely to be users. CONCLUSIONS: Concomitant use of alternative health products and psychotropic drugs for mental health reasons are prevalent. This increases the risk for potential drug-herb interactions. Health professionals need to be aware of patient alternative health product use, especially in the presence of co-morbid mental and physical conditions. Public health campaigns aimed towards increasing awareness and education may incite discussions between health professionals and patients on the risks and benefits of these products.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".