Impact of the first wave of COVID‐19 on the health and psychosocial well‐being of Māori, Pacific Peoples and New Zealand Europeans living in aged residential care
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: To investigate the impact of New Zealand's (NZ) first wave of COVID-19, which included a nationwide lockdown, on the health and psychosocial well-being of Māori, Pacific Peoples and NZ Europeans in aged residential care (ARC). METHODS: interRAI assessments of Māori, Pacific Peoples and NZ Europeans (aged 60 years and older) completed between 21/3/2020 and 8/6/2020 were compared with assessments of the same ethnicities during the same period in the previous year (21/3/2019 to 8/6/2019). Physical, cognitive, psychosocial and service utilisation indicators were included in the bivariate analyses. RESULTS: A total of 538 Māori, 276 Pacific Peoples and 11,322 NZ Europeans had an interRAI assessment during the first wave of COVID-19, while there were 549 Māori, 248 Pacific Peoples and 12,367 NZ Europeans in the comparative period. Fewer Māori reported feeling lonely (7.8% vs. 4.5%, p = 0.021), but more NZ Europeans reported severe depressive symptoms (6.9% vs. 6.3%, p = 0.028) during COVID-19. Lower rates of hospitalisation were observed in Māori (7.4% vs. 10.9%, p = 0.046) and NZ Europeans (8.1% vs. 9.4%, p < 0.001) during COVID-19. CONCLUSIONS: We found a lower rate of loneliness in Māori but a higher rate of depression in NZ European ARC populations during the first wave of COVID-19. Further research, including qualitative studies with ARC staff, residents and families, and different ethnic communities, is needed to explain these ethnic group differences. Longer-term effects from the COVID-19 pandemic on ARC populations should also be investigated.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it