Exploring the Access and Use of Social Technologies by Older Adults in Support of Their Mental Health During the COVID-19 Pandemic: A Rapid Review
Bibliographic record
Abstract
Abstract Coronavirus disease (COVID-19) lockdowns disproportionately affect older people where most suffer from social isolation and loneliness, which translate into higher rates of depression and anxiety. This study aimed to explore the accessibility, outcomes, and challenges of social technology use among community-dwelling older adults, older adults in long-term care, older adults with neurocognitive disorder, and older adults with pre-frailty and frailty, to help guide future research in this area. A rapid review was conducted, and articles were retrieved from four online databases, including Medline, AgeLine, EconLit and CINAHL, and grey literature from Google Scholar. Of the 131 articles retrieved, 24 were included in this review. The positive outcomes of social technology use include improved mental and physical health, reduced health disparities, and increased autonomy. Adverse outcomes include furthering the digital divide. More research surrounding the economic impacts of social technologies is warranted.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".