P.022 Cross-cultural experiences and expectations from caregivers of people living with Parkinson’s Disease: a comprehensive review
Bibliographic record
Abstract
Background: Care partners of people with Parkinson’s disease (PD) must continually cope with various stressors due to changes resulting from the disease process, including assisting and supporting with their medical, emotional, and social needs. Caregivers’ expectations, preferences, and experiences on PD management are a cornerstone to guarantee a comprehensive treatment of the disease and may be influenced or determined by cultural backgrounds. Methods: Comprehensive literature review to investigate the roles, experiences, and needs of caregivers of PwPD across cultures. We critically reviewed and analyzed the all published studies that examined the impact of cultural diversity on caregiving in PD. Results: Among some significant results, we found profound differences in caregivers’ experiences and perceptions between U.S, Mexican, and Latin-American, Asian, African and Indian caregivers. There are clear negative reinforced effects between caregiver status, education, health, labor participation and income-generating capacity, and social protection combined with the age and gender differences. Canadian information was not available. Conclusions: There is still a gap in the literature with a need for social and health services to understand the cultural factors that impact caregiver burden in PD to facilitate wellbeing and support from health and social services to better aid those in the caregiver role.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".