Moderate burden amongst caregivers posthip arthroscopy linked to younger caregiver age and task load: A cross‐sectional survey study
Bibliographic record
Abstract
PURPOSE: To evaluate the burden experienced by primary informal caregivers of patients who have undergone hip arthroscopy and to identify factors that predict increased caregiver burden. METHODS: A cross-sectional study was conducted at a single academic hospital centre, enroling caregivers of patients who underwent hip arthroscopy between November 2018 and November 2023. Caregiver burden was assessed using the Caregiver Burden Inventory (CBI) survey. Multivariable linear regression models were used to identify predictors of caregiver burden, with the global CBI score serving as the primary outcome measure. Secondarily, open-ended survey questions were analyzed qualitatively to elucidate specific challenges and facilitators of caregiving, as reported by the caregivers themselves. RESULTS: The study involved 99 eligible caregivers (mean [standard deviation] age; 47 [11] years), 58% were female, and 85% were relatives of the patient. The median global CBI score was 13.0 (interquartile range: 8.0-22.4), indicating a moderate burden. Regression analyses demonstrated that younger caregiver age and a higher number of caregiving tasks were significant predictors of increased global burden. Additionally, nonweightbearing status of patients, female gender of caregivers and working full-time statistically significantly increased specific dimensions of caregiver burden. CONCLUSION: This study highlights the meaningful burden faced by caregivers of patients undergoing hip arthroscopy, despite its minimally invasive nature and outpatient setting. Identified risk factors such as younger caregiver age, female gender of the caregiver, nonweight-bearing status and increased caregiving tasks suggest targeted areas for intervention. The qualitative analysis revealed that caregivers struggle with time management and physical and emotional strain, yet better communication and practical support from healthcare teams could help to alleviate these challenges. LEVEL OF EVIDENCE: Level IV, prognostic study.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".