The Role of Parkinson Nurses for Personalizing Care in Parkinson’s Disease: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Quality of life (QoL) of persons with Parkinson's disease (PD) is diminished by (non-)motor symptoms, that require personalized care. Parkinson Nurses (PN) may be pivotal promoting tailored care offerings. This systematic review and meta-analysis investigates PD care models and aims at furnishing current concepts of PN to offer personalized care. OBJECTIVE: The purpose of this study is to identify the various roles and functions that PN may hold for personalized PD care. METHODS: We performed a systematic literature review, utilizing: PubMed, Web of Science, The Cochrane Library, and PsycINFO. The review qualitatively evaluated articles, which described personalized care models involving PNs and was guided by the personalized care management model. A meta-analysis compared patient-reported QoL (quantified using the 39-item Parkinson's Disease Questionnaire) between personalized care interventions involving PN versus standard care with. RESULTS: Twenty-seven publications were identified, including six randomized, controlled trials ascertaining with health related QoL (n = 1830 PwPs). The qualitative evaluation revealed that PN contribute to all aspects of personalized care. The meta-analysis showed no improved QoL in personalized care models compared to standard care, thought a great heterogeneity among study design and interventions was outlined (Standardized Mean Difference = -0.8935; 95% Confidence Interval, -2.1177 to 0.3307; z = -1.43, p = 0.1526). CONCLUSION: PN fulfil important functions in personalized PD care. For the future, a clear role definition will be necessary to adjust training for PN across healthcare systems and care settings but especially to realize their full potential for PD care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.010 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".