An Evidence-Based Evaluation of Health Information on Erectile Dysfunction From 10 Nationwide Daily Newspapers in Korea
Bibliographic record
Abstract
PURPOSE: A rapid growth in the socioeconomic status of Koreans has triggered an unprecedented explosion of health information for the general population. Despite its obvious benefits, this increase in information could also result in potentially harmful effects for both consumers and professionals who do not use it appropriately. Thus, this study was conducted to evaluate the quality and accuracy of health information on erectile dysfunction from 10 nationwide daily newspapers. MATERIALS AND METHODS: This study analyzed health information from 10 nationwide daily newspapers in Korea from January 2011 through December 2011. We reviewed the health information for quality by using evidence-based medicine tools and evaluated the accuracy of the information provided. Articles that simply summarized scientific congresses or journal articles and that did not include direct quotations were excluded, as were advertisements. RESULTS: A total of 47 articles were gathered. Among them, 27 (57.4%) contained inaccurate or misleading statements on the basis of an evidence-based medicine evaluation. These statements included using inappropriate surrogate outcomes as clinical endpoints (three cases, 6.4%), extrapolating nonhuman results to humans (two cases, 4.3%), exaggerating the significance of results (eight cases, 17.0%), and using incorrect words (14 cases, 29.8%). The rate of error was higher in the information from Korean sources than in that from international sources (22 cases vs. 5 cases). CONCLUSIONS: Approximately 57% of all articles on erectile dysfunction from 10 nationwide daily newspapers were found to contain inaccuracies.
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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 | 0.026 | 0.104 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.021 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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; 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".