Mid- and late-life lifestyle activities as main drivers of general and domain-specific cognitive reserve in individuals with Parkinson’s disease: cross-sectional and longitudinal evidence from the LANDSCAPE study
Bibliographic record
Abstract
BACKGROUND: Cognitive reserve (CR) is considered a protective factor for cognitive function and may explain interindividual differences of cognitive performance given similar levels of neurodegeneration, e.g., in Alzheimer´s disease. Recent evidence suggests that CR is also relevant in Parkinson's disease (PD). OBJECTIVE: We aimed to explore the role of life-stage specific CR for overall cognition and specific cognitive domains cross-sectionally and longitudinally in PD. METHODS: The cross-sectional analysis with data from the DEMPARK/LANDSCAPE study included 81 individuals without cognitive impairment (PD-N) and 87 individuals with mild cognitive impairment (PD-MCI). Longitudinal data covered 4 years with over 500 observations. CR was operationalized with the Lifetime of Experiences Questionnaire (LEQ), capturing the complexity of lifestyle activities across distinct life-stages. Cognition was assessed using a comprehensive neuropsychological test battery. RESULTS: ≤ 0.441) revealed that LEQ scores were positively related to cognitive performance independent of time. However, the decline in overall cognition and memory over time was slightly more pronounced with higher LEQ scores. CONCLUSIONS: This study emphasizes the association between complex lifestyle activities and cognition in PD. Data indicate that while CR might be related to a delay of cognitive decline, individuals with high CR may experience a more pronounced drop in overall cognition and memory. Future studies will have to replicate these findings, particularly regarding domain-specific effects and considering reverse causal mechanisms.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".