Predictors of Spiritual Well-Being in Family Caregivers for Individuals with Parkinson's Disease
Bibliographic record
Abstract
Background: Parkinson's disease (PD) is a common neurodegenerative illness that causes disability through both motor and nonmotor symptoms. Family caregivers provide substantial care to persons living with PD, often at great personal cost. While spiritual well-being and spirituality have been suggested to promote resiliency in caregivers of persons living with cancer and dementia, this issue has not been explored in PD. Objective: The aim of this study was to identify predictors of spiritual well-being in PD patients' caregivers. Design: A cross-sectional analysis was performed. Our primary outcome measure, the Functional Assessment of Chronic Illness Therapy—Spiritual Well-Being (FACIT-Sp), was measured in caregivers alongside measures of patient quality of life, symptom burden, global function, grief, and spiritual well-being and caregiver mood, burden, and perceptions of patient quality of life. Univariate correlation and multiple regression were used to determine associations between predictor variables and caregiver FACIT-Sp. Setting/Subjects: PD patient/caregiver dyads were recruited through three academic medical centers in the United States and Canada and regional community support groups. Results: We recruited 183 dyads. Patient faith, symptom burden, health-related quality of life, depression, motor function, and grief were significant predictors of caregiver spiritual well-being. Predictive caregiver factors included caregiver depression and anxiety. These factors remained significant in combined models, suggesting that both patient and caregiver factors make independent contributions to caregiver spiritual well-being. Conclusions: The present study suggests that both patient and caregiver factors are associated with spiritual well-being in PD. Further study is needed to understand the causal relationship of these factors and whether interventions to support caregiver spiritual well-being improve outcomes for caregivers or patients. Clinicaltrials.gov registration NCT02533921.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".