The Role of Technology Use in the Context of Social Isolation Among Immigrant Older Adults
Bibliographic record
Abstract
Technology has been integrated into every aspect of life for interpersonal support and connections and social isolation has become a hotspot topic for health promotion in nursing among various populations, but little attention has been paid to immigrant older adults using technology to overcome social isolation. The purpose of this narrative review is to comprehend the role of technology use in the context of social isolation, including the predisposing factors, encountered by immigrant older adults to support their psychosocial wellbeing. By studying relevant peer-reviewed articles published in professional databases from 2013 to 2024, 26 articles met the criteria and were accessed for this narrative review, despite an unexpected participant selection preference of older Asian immigrants living in a North American context among these eligible papers. It is discovered that technology use has improved the mental health of socially-isolated immigrant older adults. However, the benefits of technology use for these individuals are constrained by cultural and linguistic differences as well as educational backgrounds. Therefore, technology adaptation should be promoted in this population through a collaborative partnership with healthcare practitioners, educators, researchers and policymakers. There should be further exploration of the interrelationships between technology use and psychosocial support and continuous striving for the most suitable approach for social isolation prevention among immigrant 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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".