A Multi-Method Exploration of Older Adults’ Technology Use During the Pandemic in Two Canadian Provinces
Bibliographic record
Abstract
The pandemic caused a rapid shift to reliance on technology to meet basic daily needs related to both health and social interaction. As social isolation is known to be a major contributing factor to physiologic decline and psychological morbidity amongst older adults, we sought to study this shift, and conducted a multi-method study including; (1) a cross-sectional telephone survey and in-depth interviews with community dwelling older adults; and (2) interviews with community organizations supporting technology use for older adults. Quantitative data were analysed using descriptive, inferential statistics; qualitative data were analyzed using thematic analysis. Over 800 older adults completed surveys; 41 completed interviews. 26 community organizations shared their perceptions of supporting the rapid shift to virtual technology. Our results emphasize that social pressure plays a core role in adoption of new technology skills. These results are critical to appraise as reliance on digital technologies continues and look to support older adults.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.017 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".