Similarities and differences in cognition as a function of sex: A longitudinal study of healthy control participants from the Parkinson Progression Markers Initiative
Bibliographic record
Abstract
Abstract Background As the global population of older adults continues to rise, there is an urgent need to understand the expected cognitive changes in healthy aging. Despite sex‐based differences in life expectancy and age‐related diseases such as Alzheimer’s disease, limited research has explicitly examined sex differences in aging. The objective of the current study was to answer three primary questions using longitudinal data for sample of healthy adults: 1) How does cognition change over time? 2) What are the sex differences in cognition? and 3) What are the sex differences in rates of cognitive change over time? Method Longitudinal data from the healthy control group of the Parkinson’s Progression Markers Initiative was used to examine cognitive changes in healthy adult males (n = 125, mean age = 61.61, SD = 10.97) and females (n = 68, mean age = 59.44, SD = 11.56). Participants underwent annual neuropsychological testing for up to five years. A series of 2‐level linear mixed models estimated within‐person change in cognition over time (i.e., level‐1) and between‐group differences in longitudinal change trajectories as predicted by sex (i.e., level 2). Each neuropsychological measure was modeled separately as a single outcome variable, for a total of seven models. Result Stability in neuropsychological scores was seen over five years. At baseline, males scored higher on the Benton Judgement of Line Orientation Test, while females scored higher on the Symbol Digit Modalities Test, the Semantic Fluency Test, and the Hopkins Verbal Learning Test‐Revised. Rates of cognitive change over time did not significantly differ by sex. Higher age and lower education at baseline predicted lower neuropsychological scores. Conclusion Stability in cognition was found across five years in a sample healthy control participants from a large multi‐site longitudinal study. Sex differences in cognition were found in several domains, including visuospatial ability, processing speed, verbal fluency, and verbal memory. However, rates of cognitive change over time did not significantly differ by sex. Higher age and lower education were predictive of lower cognitive functioning. Great intraindividual variability in cognitive trajectories was observed. Future research should continue to examine factors that predict individual trajectories of aging in healthy individuals.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".