Perception of aging and changes in later life: Findings from ethnographic interviews with older adults
Bibliographic record
Abstract
Abstract Older adults’ understanding of aging and their perception of aging-related issues (e.g., health, social life) have fundamental impacts on their preparation for later life, and the quality of life during the aging process. This study intends to explore how older adults understand aging and aging-related issues through later life experiences during and after the COVID-19 pandemic. This study is based on 21 ethnographic interviews conducted by social work students who enrolled in a gerontology course in a western Canada university between 2022 and 2024. The participants of interviews are older adults aged 70 years and older. A thematic analysis was conducted to all 21 transcripts. Four main themes were identified, including 1) Older adults normalize the aging process through the changes of family/generation structure, a shift from a productive to a recreative social life, and the narrowed networking size; 2) Older adults adjust to the deterioration of physical health and functional capability using various strategies; 3) Older adults distinguish the perception of aging from the concept of oldness; and 4) The COVID-19 pandemic and recent developments (e.g., technology advancement) contribute to older adults’ challenges in navigating their later life. Findings suggest that older adults actively make changes to their different life aspects to enhance the quality of later life. It also reveals older adults’ understanding of aging process, particularly their acceptance of age but not oldness. This study further emphasizes the salience of aging-friendly society without barriers to enable healthy and active aging.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".