Conversations in Times of Isolation: Exploring Rural-Dwelling Older Adults’ Experiences of Isolation and Loneliness during the COVID-19 Pandemic in Manitoba, Canada
Bibliographic record
Abstract
Older adults have been described as a vulnerable group in the current context of the COVID-19 pandemic. In Canada, where this study took place, older adults have been encouraged to self-isolate while the rest of the population has been cautioned against in-person contact with them. Prior to COVID-19, social isolation and loneliness among older adults was considered a serious public health concern. Using a series of semi-structured interviews with 26 community-dwelling older adults (65+) living in rural Manitoba, we explore older adults' experiences of isolation and loneliness in the initial stages of the pandemic between the months of May and July 2020. Participants identified a loss of autonomy, loss of activities and social spaces (e.g., having coffee or eating out, volunteering, and going to church), and lack of meaningful connection at home as factors influencing their sense of isolation and loneliness. Although these loses initially influenced participants' self-reported isolation and loneliness, the majority developed strategies to mitigate isolation and loneliness, such as drawing on past experiences of isolation, engaging in physically distanced visits, connecting remotely, and "keeping busy." Our findings call attention to the role of different environments and resources in supporting older adults social and emotional wellbeing, particularly as they adapt to changes in social contact over time.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| 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".