Funding source, trial outcome and reporting quality: are they related? Results of a pilot study
Bibliographic record
Abstract
BACKGROUND: There has been increasing concern regarding the potential effects of the commercialization of research. METHODS: In order to examine the relationships between funding source, trial outcome and reporting quality, recent issues of five peer-reviewed, high impact factor, general medical journals were hand-searched to identify a sample of 100 randomized controlled trials (20 trials/journal). Relevant data, including funding source (industry/not-for-profit/mixed/not reported) and statistical significance of primary outcome (favouring new treatment/favouring conventional treatment/neutral/unclear), were abstracted. Quality scores were assigned using the Jadad scale and the adequacy of allocation concealment. RESULTS: Sixty-six percent of trials received some industry funding. Trial outcome was not associated with funding source (p=.461). There was a preponderance of favourable statistical conclusions among published trials with 67% reporting results that favored a new treatment whereas 6% favoured the conventional treatment. Quality scores were not associated with funding source or trial outcome. CONCLUSIONS: It is not known whether the absence of significant associations between funding source, trial outcome and reporting quality reflects a true absence of an association or is an artefact of inadequate statistical power, reliance on voluntary disclosure of funding information, a focus on trials recently published in the top medical journals, or some combination thereof. Continued and expanded monitoring of potential conflicts is recommended, particularly in light of new guidelines for disclosure that have been endorsed by the ICMJE.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.038 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.005 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".