Impact of COVID‐19 on carers of people with dementia in the community: Findings from the British IDEAL cohort
Bibliographic record
Abstract
OBJECTIVE: Unpaid carers for people with dementia play a crucial role in society. Emerging evidence suggests the COVID-19 pandemic has negatively impacted on carers. This study sought to explore the impact of the COVID-19 pandemic on carers for community-dwelling people with dementia and compare responses with pre-pandemic data. METHODS: Data were collected between September 2020 and April 2021 in England and Wales. Carers were identified from the Improving the experience of Dementia and Enhancing Active Life (IDEAL) cohort and data were collected either through the telephone, video conferencing, or an online questionnaire. Responses from 242 carers were compared against benchmark data from the IDEAL cohort collected pre-pandemic. Analyses were conducted for the full sample of carers and spousal/partner carers only. RESULTS: In total 48.8% of carers thought their healthcare needs were negatively affected during the pandemic. Compared with pre-pandemic data carers were more lonely and experienced less life satisfaction. There was little impact on carers' experience of caregiving, although carers felt trapped in their caregiving role. Carers were more optimistic and had higher social contact with relatives. There were changes in the methods carers used for contacting relatives and friends. Most carers coped very or fairly well during the pandemic. There was little difference in the experiences of spousal/partner carers and the full sample. CONCLUSIONS: After a long period of providing care under pandemic conditions carers require additional support. This support needs to be focused on alleviating feelings of loneliness and increasing life satisfaction. Services need to consider how to improve access to health care, particularly resuming face-to-face appointments.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".