Digital Social Interaction in Older Adults During the COVID-19 Pandemic
Why this work is in the frame
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Bibliographic record
Abstract
Throughout the COVID-19 pandemic, older adults have been encouraged to stay indoors and isolated, leading to potential disruptions in their social activities and interpersonal relationships. This interview study ($N=24$) provides a close examination of older adults' communication technology adoption and usage in light of the pandemic. Our interviews revealed that the pandemic motivated many older adults to learn new technology and become more tech-savvy in an effort to stay connected with others. However, older adults also reported challenges related to the pandemic that were major impediments to technology adoption. These were: (1) lack of access to in-person technology support under physical distancing mandates, (2) lack of opportunities for online participation due to negative age stereotypes and assumptions, and (3) increased apprehension to seek help from family members and friends who were suffering from pandemic-related stresses. This study extends technology adoption literature and contributes an up-to-date examination of the "grey digital divide" (the gap between older adults who use technology and those who do not). Our findings demonstrate that despite the rapidly increasing number of tech-savvy seniors, a digital divide not only persists, but has been exacerbated by the transition to virtual-only offerings. We reveal the challenges and coping strategies of older adults who remain separated from technology and propose actionable solutions to increase digital access during the COVID-19 pandemic and beyond.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it