Commercial funding of randomized controlled trials of weight-loss interventions using dietary supplements: A rapid review
Bibliographic record
Abstract
BACKGROUND: Nutrition research funded by commercial entities may be subject to bias. To date, no study has examined the prevalence of commercial funding in clinical trials of dietary supplements for weight loss. OBJECTIVE: To estimate the prevalence of commercial funding of randomized controlled trials (RCTs) of dietary supplement interventions for weight loss. METHODS: We conducted a rapid review of English-language RCTs published between 1 January 2023, testing dietary supplements for weight loss. Funding sources were extracted from full texts and categorized as industry, nonprofit, trade association, academic, government, or other. Commercial funders, trade associations, and nonprofits were further reviewed for ties to supplement sales. RESULTS: = 44) reported commercial funding, involving 64 unique funders and 118 instances of commercial involvement. More than half of funders sold dietary supplements or had affiliated companies that did, though some affiliations could not be verified due to limited transparency. No nonprofit funders had ties to supplement sales. CONCLUSIONS: The majority of RCTs evaluating dietary supplements for weight loss reported commercial funding. Further research is needed to assess whether such funding influences study findings.
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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 | Metaresearch Domain: Incentives · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
| gpt | MetaresearchMeta-epidemiology (narrow) Domain: Incentives · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
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 | 0.226 | 0.588 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.019 | 0.018 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".