‘Make the Most of the Situation’. Older Adults’ Experiences during COVID-19: A Longitudinal, Qualitative Study
Bibliographic record
Abstract
The COVID-19 pandemic restrictions have been associated with increased social isolation and reduced participation in older adults. This longitudinal qualitative study drew on life course theory to analyse data from a series of four sequential semi-structured interviews conducted between May 2020–February 2021 with adults aged 65+ (n = 12) to explore older adults’ experiences adjusting to the COVID-19 pandemic. We identified three themes: (1) Struggling ‘You realize how much you lost’ describes how older adults lost freedoms, social connections and activities; (2) Adapting ‘whatever happens, happens, I’ll do my best’, revealing how older adults tried to maintain well-being, participation and connection; and (3) Appreciating ‘enjoy what you have’, exploring how older adults found pleasure and contentment. Engagement in meaningful activities and high-quality social interactions supported well-being during the COVID-19 pandemic for older adults. This finding highlights the need for policies and services to promote engagement during longstanding global crises.
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.
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 | 0.013 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".