Care partner needs in Parkinson's disease: A systematic review of qualitative and quantitative data
Bibliographic record
Abstract
BackgroundCare for persons with Parkinson's disease (PD) is to a great extent carried out by care partners. It is important to understand their needs to ease their burden and help with their important role.ObjectiveTo present (1) what is known about needs in caregiving for someone with PD from both qualitative and quantitative papers; and (2) to identify research gaps in the existing literature to guide future research.MethodsA systematic search was conducted, searching PubMed, CINAHL, PsychINFO, and MEDLINE for both qualitative and quantitative studies examining care partner needs in Parkinson's disease published from the start of the databases up to 13 November 2024. The best-fit framework synthesis method was employed for qualitative data extraction and analysis. The Critical Appraisal Skills Programme (CASP) and the Newcastle-Ottawa Scale (NOS) were used for quality assessment of studies.ResultsForty-eight qualitative studies, ten quantitative studies, and three mixed methods studies met the eligibility criteria. All studies were of observational, cross-sectional design. A total of nine themes (the need for information, the need to be heard, PD healthcare, emotional support, daily living, financial support, skills, care partner physical well-being, and respite care) were identified from qualitative data and all quantitative data could fit this framework. Quantitative data on the frequency of needs and when they arise over the course of PD were scarce. Only one quantitative study made use of a validated measurement instrument to measure care partner needs, the Family Needs Questionnaire.ConclusionsCare partner needs in PD are wide-ranging. A significant gap identified is the absence of quantitative data to determine the prevalence, timing, and factor contributing to the needs revealed by the qualitative research.
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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 | 0.085 | 0.205 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.025 | 0.026 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".