A study on the utilization of complementary and alternative medicine for elementary children
Bibliographic record
Abstract
Purpose : Recently, complementary and alternative medicine (CAM) has been increasingly used in children. Studies have shown that 34% of adults and 11% of children use CAM in the USA and Canada. The purpose of this study was to investigate the prevalence and patterns of CAM use in elementary children in Korea. Methods : From July to August 2007, parents of elementary children completed a questionnaire survey at Gwang-ju. In all, 794 questionnaires were analyzed. Results : Of the 794 respondents, 278 answered that their pupils (35%) had experienced CAM. The following types of CAM therapy were used: herbal medicine, 62.5% dietary supplements, 31.2% vitamins, 30.2% and acupuncture, 11.1%. CAM therapies were used for the following diseases: nutritional deficiency, 33.3% atopic dermatitis, 31.3% arthralgia, 31.3% allergic rhinitis, 28.8% obesity, 26.3% and asthma. The following were the motives to use CAM: prevention of diseases (33.5%), dissatisfaction with modern medicine (21.2%), and complementary therapy to modern medicine (20.5 %). People gained information about CAM through neighbors (65%) and mass media (21%). Moreover, 83 parents (30 %) were satisfied with CAM because of its effectiveness. Conclusion : Many parents have advocated the use of CAM in their children. However, most of them used CAM without any prescription or adequate knowledge. Further studies are required to determine the efficacy of CAM. (Korean J Pediatr
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".