Study of Natural products Adverse Reactions (SONAR) in children seen in mental health clinics: a cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Paediatric mental health patients frequently use natural health products (NHP) in addition to prescription medications, but very little is known about adverse events and possible NHP-drug interactions. OBJECTIVE: To determine: (1) the prevalence of paediatric mental health patients taking prescription medications only, NHP only, both NHP and prescription medications concurrently or neither; (2) which prescription medications and NHP are most commonly used in paediatric mental health populations and (3) adverse events experienced in the last 30 days (serious and non-serious). DESIGN: Cross-sectional surveillance study. SETTING: Paediatric mental health clinics. POPULATION/INTERVENTION: On their first clinic visit, paediatric mental health patients were provided with a form inquiring about prescription drug use, NHP use and any undesirable event experienced in the last month. RESULTS: Of the 536 patients included in this study, 23% (n=120) reported taking only prescription medication(s), 21% (n=109) reported only NHP use, 21% (n=112) reported using both NHP and prescription drugs concurrently, and 36% (n=191) reported using neither. Overall, there were 23 adverse events reported; this represents 6.3%, 2.8%, 10.8% and 0.6% of each population, respectively. The majority of patients who experienced an adverse event reported taking more than one NHP or prescription drug. No serious adverse events were reported. CONCLUSION: Nearly half of the paediatric mental health patients in this study were taking NHPs alone or in addition to prescription medications. Active surveillance identified multiple adverse events associated with NHP and prescription drug use; none were serious. Healthcare professionals were encouraged to initiate conversations regarding NHP use.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | medium |
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".