Chronic disease and use of online health information and online health services
Bibliographic record
Abstract
This study examines the factors associated with computer use for the self-management of health among individuals diagnosed with chronic diseases (CD) in Israel. We distinguish between: (1) access to online health information, and (2) use of online health services (OHS). A geographic representative sample comprising 2008 individuals was contacted. 1406 individuals (67.6%) reported using the computer for health concerns. Four conditions – heart, cancer, diabetes and hypertension – were identified (N = 225). Using a series of logit regression models it is shown that CD increases access to online health information (OHI) but its effect of use of OHS is specific to: (1) type of CD, i.e., heart condition, and (2) type of provided service, i.e., medical updates. These results indicate that while computer use increases the odds for higher empowerment this may not necessarily lead to higher use of OHS provided by the healthcare provider among individuals diagnosed with CD decreasing the likelihood for better self-management. Implications for health policy are discussed.
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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 | 0.001 | 0.000 |
| 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 | 0.005 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".