Awareness of Sources of Peer-Reviewed Research Evidence on the Internet
Bibliographic record
Abstract
CONTEXT: Peer-reviewed research evidence that was once available only to clinicians is now posted on the Internet and accessible to everyone, but levels of awareness of this evidence among patients and clinicians is not known. METHODS: Cross-sectional survey, conducted from July 1998 through January 2000, of cancer patients (n = 1998), their family physicians (n = 871), and all oncologists (n = 30) and oncology nurses (n = 44) at the Hamilton Regional Cancer Centre, Hamilton, Ontario. Comparisons made between and within groups to examine use of the Internet by patients and clinicians to find health information, and their awareness of organizations using Internet-based resources to promote evidence-based decision making. RESULTS: Response rates were 72%, 44%, 97%, and 84% for patients, family physicians, oncologists, and nurses, respectively; 47% of patients, 64% of family physicians, 100% of oncologists, and 72% of nurses reported that they used the Internet. Few patients were aware of the existence of the Cochrane Collaboration (1%), MEDLINE (13%), or the Program in Evidence-Based Care of Cancer Care Ontario (3%). Oncologists had the highest reported levels of awareness of the sources of evidence on the Internet. Most family physicians had not heard of any of the sources. CONCLUSIONS: The awareness of evidence sources on the Internet varies between patients and clinicians and across groups of clinicians, and some of the most rigorously developed sources of information are still unknown.
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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 | 0.035 | 0.272 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".