Bibliographic record
Abstract
PURPOSE OF REVIEW: As prevalence rates of dietary supplement use are observed to be increasing in adolescents and the population in general, questions need to be asked about the efficacy, motivations, and consequences of such usage. Focusing mainly on individuals between the ages of 12 to 19 (adolescents) this review will highlight current prevalence rates, types of supplements being consumed, reasons for consumption, and concerns regarding physiological, psychological, knowledge transfer, and regulatory aspects of supplement use. RECENT FINDINGS: Studies have indicated the prevalence of dietary supplement usage by adolescents range from approximately 10% to as high as 74%. Some of the highest rates of usage appear in chronically ill adolescents. Multivitamin and mineral preparations are the most common supplements being consumed; however, many studies indicate that adolescents are using other substances like creatine, herbals, or protein supplements. Some of the most appealing supplements among this age group are those that enhance athletic performance or physical appearance. Recent literature suggests three key moderating factors for supplement use in adolescents: health status, gender, and level of physical activity involvement. SUMMARY: As the dietary supplement industry is now a multi-billion dollar industry, there is growing pressure, and a subsequent need for research to establish the efficacy and safety of these products particularly for adolescent users. The psychological and educational components of such use cannot be ignored as they play an equally important role in the health and safety of adolescents.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".