Publication Bias in Orthopaedic Research: An Analysis of Scientific Factors Associated with Publication in The Journal of Bone and Joint Surgery (American Volume)
Bibliographic record
Abstract
BACKGROUND: Positive outcomes are common in the orthopaedic literature, and there are many who believe it may be due to the preferential publication of studies with positive findings-a phenomenon known as publication bias. The purpose of this investigation was to determine whether positive findings rendered a manuscript submitted to The Journal of Bone and Joint Surgery (American Volume) more likely to be accepted for publication. METHODS: A total of 1181 manuscripts submitted to The Journal of Bone and Joint Surgery between January 1, 2004, and June 30, 2005, for publication as scientific articles were analyzed, with 855 meeting the inclusion criteria. The direction of the study findings (positive, neutral, or negative) was independently graded by three blinded reviewers. The final disposition (acceptance or rejection) was recorded, as was information on the scientific characteristics plausibly related to acceptance or rejection. Logistic regression was used to identify factors associated with acceptance for publication. RESULTS: The overall acceptance rate was 21.8% (186 of 855 studies). The study outcome was positive for 72.5% (620) of the manuscripts. The acceptance rate for the 235 manuscripts with nonpositive findings was 23.0% (fifty-four studies) compared with 21.3% (132) of the 620 studies with positive findings (crude odds ratio, 1.10 [95% confidence interval, 0.77 to 1.58]; p = 0.593). After controlling for all covariates, the adjusted odds ratio was 0.92 (95% confidence interval, 0.62 to 1.35; p = 0.652). In the multivariate analysis, the only factor significantly associated with acceptance for publication was level of evidence (p = 0.001). CONCLUSIONS: We found no evidence of publication bias in the review of manuscripts for publication by The Journal of Bone and Joint Surgery, as positive and nonpositive studies were accepted at similar rates. The dearth of nonpositive studies in the orthopaedic literature is of concern, and may be due largely to investigator-based factors. Orthopaedic researchers should submit negative and neutral studies for publication, confident that the likelihood of acceptance will not be influenced by the direction of study findings.
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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 | 0.197 | 0.485 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.008 |
| Bibliometrics | 0.015 | 0.018 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".