“Picturing a Way Forward”: Strategies to Manage the Effects of COVID-19-Related Isolation on Long-Term Care Residents and Their Informal Caregivers
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Strategies to manage the coronavirus disease 2019 (COVID-19) pandemic included widespread use of physical distancing measures. These well-intended strategies adversely affected long-term care (LTC) residents' socialization and their caregiving arrangements, leading to exacerbation of social isolation and emotional distress for both residents and their caregivers. This study aimed to understand how these measures affected informal caregivers of people living in LTC homes in Ontario. Strategies to increase socialization and promote social connection during and post-COVID-19 were also explored. RESEARCH DESIGN AND METHODS: This qualitative study used descriptive and photovoice approaches. Of the 9 potential caregivers identified, 6 participated in the study and shared their experiences and photographic reflections in virtual focus group sessions. RESULTS: Findings highlighted the increased social isolation experienced by people living in LTC and their caregivers during COVID-19. Caregivers reported pronounced declines in residents' well-being and were frustrated by challenges connecting with their family members during quarantine. Attempts made by LTC homes to maintain social connections, such as window visits and video calls, did not fulfill the social needs of residents and their caregivers. DISCUSSION AND IMPLICATIONS: Findings underscore a need for better social support and resources for both LTC residents and their caregivers going forward to prevent further isolation and disengagement. Even in times of lockdown, LTC homes must implement policies, services, and programs that promote meaningful engagement for older adults and their families.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".