Childhood reading problems and cognitive ageing across mid to later life
Bibliographic record
Abstract
BACKGROUND: Little research has investigated long-term associations of childhood reading with cognitive ageing. The aim of this study was to test longitudinal associations between childhood reading problems and cognitive function from mid-adulthood (age 43) to early old age (age 69), and whether associations were mediated by education. METHODS: Data were from the MRC National Survey of Health and Development, a prospective population-based birth cohort. Reading problems were measured at age 11 using a reading test. Verbal memory and processing speed were measured at ages 43, 53, 60-64 and 69 and Addenbrooke's Cognitive Examination (ACE) was administered at age 69. Linear mixed models and path analyses were used to test: (1) associations between reading problems and verbal memory and processing speed trajectories; (2) associations between reading problems and ACE-III scores; (3) whether associations were mediated by education. RESULTS: Reading problems were associated with poorer verbal memory at intercept but not rate of decline (N=1726), and were not associated with processing speed intercept or decline (N=1730). There were higher rates of scores below ACE-III clinical thresholds (<82 and <88) in people with reading problems compared with those without. Reading problems were associated with poorer total ACE-III scores and all domain scores at age 69 (N=1699). Associations were partly mediated by education. CONCLUSION: Reading problems in childhood were associated with poorer cognitive function in early old age, and associations were partly mediated by education.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".