Quality of web‐based medical information on stable COPD: comparison of non‐commercial and commercial websites
Bibliographic record
Abstract
The Internet provides an easy and accessible way to deliver medical information about the management of various diseases, both to practitioners and to their patients. As there is no control over who posts information on the Web, there is a risk that the interests of the web producer may bias the quality of information. The quality of medical information on the management of chronic obstructive pulmonary disease (COPD) on the Internet was evaluated, comparing non-commercial and commercial websites. An internet search was conducted to locate relevant websites using a metasearch engine. The quality of websites was scored on a scale of 0-10, based on three items about the credibility of the site and seven items about the accuracy of the information provided by the site. Quality differences between commercial and non-commercial websites were explored. The search revealed 23 relevant websites (12 noncommercial and 11 commercial). The overall quality of non-commercial websites was better than that of commercial websites (median score 7 vs. 4, P = 0.01). Compared to commercial sites, non-commercial websites more often provided information about cessation of smoking (100% vs. 64%, P = 0.03), preventative influenza vaccinations (42% vs. 9%, P = 0.07) and use of long-term oxygen therapy (92% vs. 45%, P = 0.02). Among websites providing information on COPD, commercial sites were much more likely to be of poorer quality compared to sites of non-commercial organizations. In particular, commercial sites do not provide information about simple preventative treatments. There is a need to be vigilant about the quality of health information about COPD on the Internet.
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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.013 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".