Bridging the digital divide: examining the use and access to e-health based technologies by millennials and older adults in Ontario, Canada
Bibliographic record
Abstract
The digital divide is the gap between demographics and regions that have access to information communication technologies and those who do not. The older adult generation may not be familiar with e-Health usage, compared to generations such as millennials. A convenience non-random descriptive comparative study was conducted; Information was collected based on demographics; health information collection, usage and distribution; E-health and e-health technology usage; and digital literacy levels. Millennials (n=31) were undergraduate students recruited at Ontario Tech University; Older adults (n=28) were recruited from senior centres in the Durham region. Data was examined using sex and age cohort, to identify any statistically significant differences. Results showed that older adults had a decreased understanding of E-health based technologies, digital literacy, and accessed the internet less. These preliminary findings suggest that there are noted challenges facing older Canadians in terms of utilization of e-health technologies, in comparison to younger Canadians in Ontario.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".