Mediating Effect of Mutuality on Health-Related Quality of Life in Patients with Parkinson’s Disease
Bibliographic record
Abstract
The relationship quality, mutuality, has been identified as a protective factor in family care situations, but its role in mediating health-related quality of life (HRQoL) in patients having Parkinson's disease (PD) is not known. Data on patients' and partners' mutuality (MS), motor signs (UPDRS III), non-motor symptoms (NMSQuest), impaired cognition (IQCODE), dependency in activities of daily life (ADL), and HRQoL (PDQ8) were collected from 51 dyads. Structural equation model with manifest variables was applied to explore if the MS score mediated the effect of UPDRS III, NMSQuest, IQCODE, and dependency in ADL on PDQ8. The results suggest that increasing severity of motor and non-motor symptoms decreases patients' mutuality which leads to worse HRQoL. Partners' mutuality mediated the effect of impaired cognition which in turn decreased patients' mutuality. The findings enhance our understanding of how various symptoms may influence PD patients' HRQoL. This may help clinicians to personalize interventions to provide more effective interventions to improve the lives of patients with PD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".