Intergenerational Effects on the Impacts of Technology Use in Later Life: Insights from an International, Multi-Site Study
Bibliographic record
Abstract
As the use of technology becomes further integrated into the daily lives of all persons, including older adults, it is important to investigate how the perceptions and use of technology intersect with intergenerational relationships. Based on the international multi-centered study Technology In Later Life (TILL), this paper emphasizes the perceptions of older adults and the interconnection between technology and intergenerational relationships are integral to social connectedness with others. Participants from rural and urban sites in Canada and the UK (n = 37) completed an online survey and attended a focus group. Descriptive and thematic analyses suggest that older adults are not technologically adverse and leverage intergenerational relationships with family and friends to adjust to new technologies and to remain connected to adult children and grandchildren, especially when there is high geographic separation between them. Participants referenced younger family members as having introduced them to, and having taught them how to use, technologies such as digital devices, computers, and social networking sites. The intergenerational support in the adoption of new technologies has important implications for helping older persons to remain independent and to age in place, in both age-friendly cities and in rural communities. The findings contribute to the growing literature in the fields of gerontology and gerontechnology on intergenerational influences and the impacts of technology use in later life and suggest the flexibility and willingness of older persons to adopt to new technologies as well as the value of intergenerational relationships for overcoming barriers to technology adoption.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| 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".