Reporting the methods used in public health research and practice
Bibliographic record
Abstract
The methods section of a scientific article often receives the most scrutiny from journal editors, peer reviewers, and skeptical readers because it allows them to judge the validity of the results. The methods section also facilitates critical interpretation of study activities, explains how the study avoided or corrected for bias, details how the data support the answer to the study question, justifies generalizing the findings to other populations, and facilitates comparison with past or future studies. In 2006, the Enhancing the QUAlity and Transparency Of health Research (EQUATOR) Programme began collecting and disseminating guidelines for reporting health research studies. In addition, guidelines for reporting public health investigations not classified as research have also been developed. However, regardless of the type of study or scientific report, the methods section should describe certain core elements: the study design; how participants were selected; the study setting; the period of interest; the variables and their definitions used for analysis; the procedures or instruments used to measure exposures, outcomes, and their association; and the analyses. Specific requirements for each study type should be consulted during the project planning phase and again when writing begins. We present requirements for reporting methods for public health activities, including outbreak investigations, public health surveillance programs, prevention and intervention program evaluations, research, surveys, systematic reviews, and meta-analyses.
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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 | 0.862 | 0.727 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads 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".