Lyme disease prevention: A content analysis of Canadian patient group and government websites
Bibliographic record
Abstract
The quality of information presented on health-related websites-in terms of comprehensiveness, accuracy and consistency-is a public health concern. To date, the consistency of information across Canadian websites devoted to Lyme disease (LD) prevention has not been evaluated. The first aim of this study was to describe the contents and recommendations of LD prevention websites provided by two types of Canadian organizations: government (n = 3) and patient groups (n = 3). A second objective was to analyse the level of convergence among these websites in terms of their prevention-related content. Initial coding of the content resulted in information segments grouped into 114 subthemes related to nine overarching themes: tick habitat suitability, risk period, transmission, personal protection, peridomestic environmental management, tick identification and removal, early symptoms, testing and diagnosis and preventive treatment. Comparative content analyses were performed both within and between the content of websites of the two organization types. The themes most frequently addressed by both organization types were personal protection (20% of the prevention-related content in patient group websites and 22% of the prevention-related content in government websites), transmission (12% and 16%, respectively) and tick identification and removal (19% and 15%, respectively). Government websites' information was generally convergent with that of patient group websites (four highly convergent themes, three moderately convergent and two divergent). Nevertheless, of particular concern were divergent messages and inaccurate information found on 11 subthemes out of 103. Examples included other possible modes of transmission and the ineffectiveness of DEET insect repellent. These results suggest the need for public health and health communications research on the issue of the quality of LD prevention information found on the Internet.
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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 | 0.007 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".