ArticleGeroScience2026
Prediction of cognitive test scores: a comparison of brain structure, health, demographic, and cognitive data across adulthood.
Article in GeroScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Effect sizes for brain-based predictive models of cognition across the lifespan.Communications psychology · 2026Review
- Prediction of cognitive performance by demographics, sleep, and brain morphometry: machine learning findings from ENIGMA-Sleep Working Group.Research square · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
28 authors.
Funding
Abstract
Cognitive performance prediction may help identify early cognitive decline. However, the heterogeneity of research findings impedes the identification of key predictors. This study used 21,877 participants (25-74 years) from the German National Cohort (NAKO Gesundheitsstudie, NAKO) to systematically predict cognitive test scores based on brain structure, demographic, health-related, and cognitive data. Importantly, validation analyses were performed across study sites and external samples (1000BRAINS). Higher predictability was observed in the total sample compared to age-specific subgroups (10% difference in explained variance). Demographic (e.g. age) and cognitive data (e.g. memory) outperformed brain structure (e.g. grey matter volume) and health-related data (e.g. hypertension). Cognitive tests were differentially predictable, most evident between episodic memory and motor speed (R
Indexed as
Identifiers
42020918What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.