Cognitive impairment in Parkinson's disease: impact on quality of life of carers
Bibliographic record
Abstract
BACKGROUND: The quality of life (QoL) of informal caregivers of people with Parkinson's disease (PD) (PwP) can be affected by the caring role. Because of cognitive symptoms and diminished activities of daily living, in addition to the management of motor symptoms, carers of PwP and cognitive impairment may experience increased levels of burden and poorer QoL compared with carers of PwP without cognitive impairment. This study aimed to investigate the impact of cognitive impairment in PD upon QoL of carers. METHODS: Approximately 36 months after diagnosis, 66 dyadic couples of PwP and carers completed assessments. PwP completed a schedule of neuropsychological assessments and QoL measures; carers of PwP completed demographic questionnaires and assessments of QoL. Factor scores of attention, memory/executive function and global cognition, as derived by principal component analysis, were used to evaluate cognitive domains. RESULTS: Hierarchical regression analysis found lower Montreal Cognitive Assessment was a significant independent predictor of poorer carer QoL, in addition to number of hours spent caregiving, carer depression and PD motor severity. Attentional deficits accounted for the largest proportion of variance of carer QoL. Carers of PwP and dementia (n = 9) had significantly poorer QoL scores compared with PwP and mild cognitive impairment (n = 18) or normal cognition (n = 39) carers (p < 0.01). CONCLUSIONS: Attentional deficits were the strongest predictor of carer QoL compared with other cognitive predictors. Carers for those with PD dementia reported the poorest QoL. Interventions such as respite or cognitive behavioural therapy to improve mood and self-efficacy in carers may improve carer QoL. © 2016 The Authors. International Journal of Geriatric Psychiatry published by John Wiley & Sons, Ltd.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".