IN-PERSON AND TECHNOLOGY-BASED SOCIAL INTERACTION IN OLDER ADULTS DURING THE COVID-19 PANDEMIC 2022
Bibliographic record
Abstract
Abstract Social support is an important factor in the health and well-being of older adults. Early COVID-19 lockdowns disrupted in-person social interactions but presumably increased technology-based social connection. This work examines social interactions during Spring of 2022 in older Arkansans with widely available vaccines and waning lockdowns to investigate current in-person and online social interactions. During Spring 2022, 603 older Arkansans (65+) (86.5% White, non-Hispanic, 65.9% women) completed the 20 question self-report automated survey (text or phone). Results indicated 27.6% continued to curtail in-person interactions significantly; however, 63% engaged in in-person social interactions outside their home more than once a week. Video chatting pre-pandemic was prevalent (40% video chatting multiple times a week); still, 20.6% never did. 22.8% reported increased video chatting during the pandemic, but surprisingly, 37.3% reported a decline. 70% felt socially connected during online interactions. Only 78% reported being satisfied with their social connection compared to 93% pre-pandemic. These findings suggest that while many have re-established in-person social interactions, around one-quarter of participants continue to curtail in-person interaction and report social connection dissatisfaction. Social technology alternatives were increased by about one quarter of participants and were reported to lead to feelings of social connection when used, and yet a decline in this usage was reported across 40% of these participants during the pandemic. These data support access to technology-based social interactions through expansion and improvement of older adult friendly virtual platforms and internet access which could help improve quality and quantity of social connection and reduce social isolation.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".