Current Knowledge on the Evolution of Care Partner Burden, Needs, and Coping in Parkinson's Disease
Bibliographic record
Abstract
BACKGROUND: Care partners support people with Parkinson's disease through a long journey ranging from independence to dependence for many daily tasks. Longitudinal studies are important to understand the evolution of this process and predictors of future needs of care partners. METHODS: A scoping review was conducted, searching PubMed for longitudinal studies examining care partner burden, needs or coping in Parkinson's disease published through May 2020. RESULTS: Eight observational studies and 19 interventional studies met the eligibility criteria. Longitudinal observation ranged from 7 weeks to 10 years, involving between six and 8515 care partners. All studies addressed care partner burden, while two and three studies respectively addressed needs and coping. Only one study related burden to specific stages or duration of disease. Results from identified studies show that care partners in Parkinson's disease are at risk for increasing burden over time. Multiple predictors of future burden have been identified related to the person with Parkinson's disease, the care partner, or an intervention. No studies examined the evolution of needs and coping in caregiving in Parkinson's disease. CONCLUSION: The scarcity of longer term, observational research on the temporal evolution of burden and particularly needs and coping in caregiving for someone with PD is a main identified gap. Even within these observational studies, the impact of caregiving is not often reported. Longitudinal studies on these topics are needed to help understand their change over time and relation to each other, which can inform support planning for care partners.
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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 | 0.010 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".