Impact of COVID‐19 on family care partners of persons with dementia in long‐term care settings in Canada: Not a ‘one‐size‐fits‐all’ story
Bibliographic record
Abstract
Abstract Background COVID‐19 has been devastating for older adults, particularly residents in long‐term care/retirement (LTC) homes. In an effort to curb the transmission of COVID‐19, public health measures have been put in place in many LTC homes, including mask wearing, physical distancing, and visitor restrictions. As the pandemic passes the one‐year mark, we are starting to understand the profound impacts of COVID‐19 and the corresponding public health measures on persons living with dementia (PLWD) and their family care partners (CPs). This research is part of a larger study exploring the impact of COVID‐19 on the wellbeing and social connections of PLWD and CPs. In this presentation, findings from qualitative interviews conducted with CPs of PLWD in LTC homes are shared. Methods The overall study used an intrinsic case study design, involving survey and interview data. Following completion of a survey, participants were invited to participate in an in‐depth qualitative interview. Interviews were conducted by phone or online, transcribed verbatim, and analyzed using thematic analysis. Results Eighteen CPs were interviewed. The impact of visitor restrictions varied between LTC homes and changed over the course of the pandemic, which was extremely challenging for CPs. At homes with visitor restrictions, the inability to visit family members with dementia was described as stressful, unfair, and frustrating. CPs stressed the importance of being able to visit their relatives, and ensuring their family members had regular social interaction to support their physical, social and emotional wellbeing. Even when CPs could visit, masks and physical distancing made communication with some PLWD challenging. Visitor policies also influenced perceptions of care. Some CPs felt that the needs of their family members with dementia were being met by the home, while others weren’t sure because CPs weren’t in the homes to assist staff and provide support to their family members with dementia. Conclusion While COVID‐19 and the pandemic restrictions have been difficult for all CPs of persons with dementia in LTC, for some it has been agonizing. Understanding these varied experiences can help inform the development of individually‐tailored resources to better support the wellbeing of CPs.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.036 | 0.010 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".