Exploring health related quality of life for women with breast cancer in Ireland and Québec, Canada throughout the COVID-19 pandemic
Bibliographic record
Abstract
The long-term consequences from the COVID-19 pandemic on breast cancer (BC) is highly unknown, however persisting unmet needs and psychosocial difficulties are likely. The objectives of this study were to evaluate the change in health-related quality of life (HR-QoL) from the pandemic to post-pandemic for women living with a diagnosis of BC and to assess the association between COVID-19 stressor impact and HR-QoL in Ireland and Québec, Canada. Women with a diagnosis of BC were initially enrolled in the cohort study. HR-QoL was assessed during the pandemic (2020-2021) and post-pandemic periods (2022). COVID-19 stressor impact was computed post-pandemic, and change in HR-QoL during and post-pandemic was compared between Ireland and Québec using independent t-tests. Multivariable analysis of covariance (ANCOVA) was used to evaluate the association between COVID-19 stressor impact and changes in HR-QoL, and compare it between Ireland and Québec. 405 participants were included from both settings (Ireland n = 267; Québec n = 138). The average HR-QoL improved from the COVID-19 pandemic to post-pandemic, and there were no differences between Ireland and Québec. Women with high COVID-19 stressor impact (18.9% of participants) had a significantly smaller improvement in their overall HR-QoL compared to those with low COVID-19 stressor impact, and this was evident in Ireland (p < 0.004) and Québec (p < 0.0001) but there were no significant differences between Ireland and Québec (interaction p-value > 0.05). Overall, HR-QoL for women with BC improved from pandemic to post-pandemic period. However, similarly in both settings, women who experienced higher levels of COVID-19-related stress had a slower recovery in HR-QoL. These results can guide decisions about health services and policies to adequately address the on-going effect of the pandemic and also prepare for future health crises.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".