Understanding the impact of digital technology on the well-being of older immigrants and refugees: A scoping review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: The fast-paced development of digital technologies in the areas of social media, pet robots, smart homes, and artificial intelligence, among others, profoundly influence the daily lives of older adults. Digital technology can improve the well-being and quality of life of older adults, older immigrants and refugees who suffer migration-associated stress, loneliness, health and psychosocial challenges. Aims: The aim of this scoping review is to map out extant empirical literature that has examined the implication of digital technology among older refugees and immigrants. Methods: before the full-text review. The comprehensive database search yielded 4134 articles, of which 15 met the inclusion criteria. Results: The results of the review suggest that digital technology is essential to the well-being, quality of life of older immigrants and refugees, especially for maintaining and building new social support networks, navigating opportunities, coping with migration-induced stress through e-leisure, and staying connected to their culture. The literature also revealed poor utilisation of digital technologies amongst older immigrants and refugees, suggesting barriers to access. Conclusion: The study concluded by highlighting the need for more research and interventions that focus on multiple strategies, including education for increased access to and utilisation of digital technology to ensure that more older migrants can benefit from the advantages of digital technology in a safe way.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it