Surfing for Back Pain Patients
Bibliographic record
Abstract
STUDY DESIGN: A prospective, systematic review of web sites related to back pain. OBJECTIVE: To assess the nature and quality of back pain-related information on the World Wide Web during a 2-year period. SUMMARY OF BACKGROUND DATA: The Internet has become a rich source of medical information. Limited knowledge is available, however, about the quality of online resources. Although previous systematic reviews on medical-related web sites found problems in varying degrees with the credibility of information, no such review was conducted to assess the back pain-related sites. METHODS: A search of web sites was conducted in November 1996 using five search engines (AltaVista, Infoseek, Lycos, Yahoo, and Magellan) and two key terms ("back pain" and "back problems"). A sample of sites was evaluated by two independent reviewers. Each site was described by the type and nature of the sponsor, target audience, and content. Overall quality was assessed in terms of evidence-based information available. RESULTS: Seventy-four web sites were reviewed in 1996, and nine of them (12.2%) were identified as high-quality sites. Advertising was the focus of 80.8% of the sites. Eleven sites (14.9%) were found to be discontinued 1 year later, and 20 (27.0%) were not accessible by the reviewers at the 2-year follow-up evaluation. Of the remaining 54 sites, 44.4% were produced by for-profit companies, and most sites targeted people with back pain (63.0%). Only seven out of the nine high-quality sites held their ratings at the 2-year follow-up evaluation. CONCLUSION: Most back pain-related web sites can be classified as advertising. The quality varied considerably, resulting in difficulties for patients to find useful information in this field. The increasing number of people seeking medical information on the Web creates a need for more high quality sites. Further, systematic review of web sites should be encouraged to monitor the accuracy of Internet publication.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".