P156 HYPERTENSIVES USERS OF A HEALTH WEB PORTAL
Bibliographic record
Abstract
Background and objective: In Canada, approximately 1 in 4 adults live with high blood pressure. These people, concerned about their health, often turn to health information Web portals. To meet this need for information, Quebec Society of Vascular Sciences (QSVS) du Québec has created a web portal (www.yourvascularhealth.ca). However, limited data is available to describe the characteristics and motivations of hypertensive users of these websites. Method In this multicenter study, participants had to be ≥18 years old, hypertensive and able to use digital tools. They were approached by collaborating physicians (n=30) during routine consultations. An anonymous, validated electronic questionnaire assessed socio-demographic variables, digital competence, and motivations for using a health website. Adapted Technology Acceptance Model III was used as a framework. Results: Forty-three participants were recruited mean age of 70.3 ± 10.5 years, 67% male, 33% had achieved a university level of education. For health behaviors, less than 30% attained the 150 weekly minutes of exercise promoted in Canada while a less than half (44%) say that they eat according to DASH guidelines. The vast majority don’t smoke (67%) and drink less than once a month (86%). Preliminary analysis show that most participants (84%) use search engine. When questioned (on a Likert scale 1 to 7) about the portal, they perceived it was useful (6.0 ± 1.1), easy to use (5.4 ± 1.2) and expressed the intention of using the portal again (5.7 ± 1.5). When motivation was assessed; autonomous motivation was highest (5.83 ± 0.99) followed by amotivation (3.83 ± 1.35) and controlled motivation (3.13 ± 1.39). Conclusion: Patients with hypertension are consulting websites to obtain more information and this even later in life. It is our responsibility to provide websites that are designed for this population and scientifically based. This study will contribute to a better characterization of health website users and may guide the development and dissemination of health websites.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.036 | 0.004 |
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".