HYPERTENSIVES USERS OF HEALTH WEB PORTALS: WHO ARE THEY? PROTOCOL AND PRELIMINARY RESULTS
Bibliographic record
Abstract
Objective: In Canada, 1 in 4 adults has hypertension. Many of them, concerned about their health, often turn to Internet to seek information. In order to meet this information need, the Quebec Society of Vascular Sciences has created a web portal. The information presented has been developed by profesionals but formulated as to be understand easily by lay people. However, literature still offer little to no data on the characteristics of users of these health portals. The purpose of the study is to characterize hypertensives who use health web portals. Design and method: This descriptive cross-sectional study is part of an ongoing multicenter project. This current study includes 250 participants with vascular disorders and aims to characterize all users of a health web portal. In the course of this sub-study, only individuals with a diagnosis of hypertension (n > 125) are included for analysis. Results: A validated and tested self-administered electronic questionnaire was developed with the Technology Acceptance Model 3 and will be presented in the communication. This questionnaire also explores personal characteristics, motivation and digital competence. The protocol and the preliminary results describing the characteristics of individuals with hypertension who use a health web portal, including motivations for use and digital competence will also be included. Conclusions: The results will help guide arterial hypertension societies in the development of health information Web portals.
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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 | 0.032 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.039 | 0.010 |
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".