Economic and objective burden of caregiving on informal caregivers of patients with systemic vasculitis
Bibliographic record
Abstract
INTRODUCTION: Systemic vasculitis (SV) is associated with substantial economic impact to patients and the healthcare system but little is known about the burden of SV on informal caregivers. We evaluated the objective caregiving burden experienced by informal caregivers of patients with SV. METHODS: We surveyed adult patients and their informal caregivers on the physical, emotional, social and economic impacts of SV. We asked patients about the extent to which they felt they were a burden to their identified caregivers. Caregivers reported the direct and indirect economic impact of SV, including employment disturbance, income loss and relative time investment of caregiving for their care recipient's SV. We used the Inventory of Caregiving Activities Questionnaire to compute the objective caregiving burden. RESULTS: We analysed data from 68 SV patient-caregiver dyads. Patients reported moderate levels of subjective burden to their caregivers. Over one-quarter of caregivers reported ever having lost some income owing to caregiving for SV. Caregivers reported spending a median of 19 weekly hours on various caregiving tasks, including a median 17 weekly hours on household activities. DISCUSSION: Given the extended hours that caregivers spend caring for their care recipient, intervention targets should aim to reduce caregiver burnout in the SV population. Future research should examine the relationship between the objective burden of caregiving for SV and the overall physical health, mental health and quality of life of caregivers.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".