Use and perceived effectiveness of complementary health approaches in children
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Up to one-half of children may use complementary health approaches (CHA). However, current prevalence in North America, variables associated with CHA use and caregiver perceptions of effectiveness are unclear. We aimed to determine the self-reported use of CHA during the previous 12 months in paediatric patients, demographic variables associated with CHA use and perceptions around effectiveness of CHA. METHODS: A cross-sectional survey study of patients aged between 28 days and 18 years who presented to a large paediatric emergency department was conducted between December 2014 and July 2015. Univariate analysis and multivariate logistic regression were used to examine variables associated with CHA use. RESULTS: Of 475 potential participants, 412 (86.7%) responded to the questionnaire, of whom 369 (89.5%) had completed the entire survey. Of these, 61.7% (95% confidence interval [CI] 56.7% to 66.6%) reported using CHA for their child. The most used CHA products were vitamins and minerals (59.2%, 95% CI 52.4% to 65.7%). Among CHA practices, massage (50.0%, 95% CI 15.5% to 30.1%) was most common. Most CHA users perceived effectiveness of the therapy used. Parental education remained statistically significant (P=0.03) in multivariate logistic regression; the odds of CHA use among caregivers with university-level education were 1.65 times higher when compared with those without (95% CI 1.04% to 2.61%). CONCLUSIONS: CHA use is higher than previously reported in children. Given the high self-reported perceived effectiveness, paediatricians and family physicians should review CHA use with their patients in an open, non-judgmental manner, exploring both perceptions of safety and efficacy.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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, 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".