Research Reporting Guidelines in Dentistry: A Survey of Editors
Bibliographic record
Abstract
The use of reporting guidelines has an important role in the development of health research, improving the quality and precision of the publications. This study evaluated how dental journals use reporting guidelines. All editors of dental journals registered on the 2013 Journal Citation Reports list (n=81) were invited to participate. The data were collected by a self-reported web-based questionnaire. Information about the profile of journal/editor and on the use of reporting guidelines by journals was gathered. Information/recommendations about the use of reporting guidelines were collected from the websites of all journals. Data were descriptively analyzed and frequencies were summarized. Thirty-four (42%) editors completed the questionnaire. Most journals are members of Committee on Publication Ethics (64.7%) and/or follow the International Committee of Medical Journal Editors recommendations (20.6%), while 26.5% are not members of any editorial group. Most editors are unfamiliar with the EQUATOR Network (55.9%), do not work full time (85.3%) and 88.2% have some income/payment. Most of them received educational training for this position (55.9%). The CONSORT Statement was endorsed by 61.8% of journals. Information from websites showed that 44.4% journals do not recommend any reporting guideline, 51.9% mention CONSORT Statement in the website and 28.4% only recommend the use of CONSORT Statement. There is clearly room for improving the use of reporting guidelines in dental journals. Broadening the understanding and the endorsement/adherence/implementation of reporting guidelines by journals may promote quality and transparence of published dental research.
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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 | 0.106 | 0.392 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".