Double-duty caregivers enduring COVID-19 pandemic to endemic: “It’s just wearing me down”
Bibliographic record
Abstract
The COVID-19 pandemic has considerably strained health care providers and family caregivers. Double-duty caregivers give unpaid care at home and are employed as care providers. This sequential mixed-method study, a survey followed by qualitative interviews, aimed to comprehensively understand the experiences of these Canadian double-duty caregivers amidst the pandemic and the transition to the endemic phase. The multi-section survey included standardized assessments such as the Double-duty Caregiver Scale and the State Anxiety Scale, along with demographic, employment-related, and care work questions. Data analysis employed descriptive and linear regression modeling statistics, and content analysis of the qualitative data. Out of the 415 respondents, the majority were female (92.5%) and married (77.3%), with 54.9% aged 35 to 54 years and 29.2% 55 to 64 years. 68.9% reported mental health decline over the past year, while 60.7% noted physical health deteriorated. 75.9% of participants self-rated their anxiety as moderate to high. The final regression model explained 36.8% of the variance in participants' anxiety levels. Factors contributing to lower anxiety included more personal supports, awareness of limits, younger age, and fewer weekly employment hours. Increased anxiety was linked to poorer self-rated health, and both perceptions and consequences of blurred boundaries. The eighteen interviewees highlighted the stress of managing additional work and home care during the pandemic. They highlighted the difficulty navigating systems and coordinating care. Double-duty caregivers form a significant portion of the healthcare workforce. Despite the spotlight on care and caregiving during the COVID-19 pandemic, the vital contributions and well-being of double-duty caregivers and family caregivers have remained unnoticed. Prioritizing their welfare is crucial for health systems as they make up the largest care workforce, particularly evident during the ongoing healthcare workforce shortage.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".