Hypertension, brain training and cognition in the healthy adults aged over 50 years: An online longitudinal study
Bibliographic record
Abstract
Abstract Background There have been no studies that investigate if cognitive tasks that have been proven to delay the progress of cognitive decline confound the relationship between Hypertension (HT) and cognitive function. We aimed to investigate whether brain training has a modifying effect on the relationship between HT and cognitive decline. Method Participants were from Platform for Research Online to Investigate Cognition and Genetics in Ageing (PROTECT), a longitudinal online study which collected information on demographic, medical and cognitive function annually, who underwent brain training intervention (BT) delivered online throughout the year; participants could choose to undertake it as many times as they wanted or not at all. Digit span, Paired associates, Self‐ordered search and verbal reasoning tests were used to test cognitive functions. Regression models was done to assess influence of hypertension and BT on cognition at follow up and whether the frequency of BT had a modifying effect on the relationship between hypertension and cognitive function from baseline to one year. Results 5726 participants over the age of 50 participated in BT with mean age 61.9 (±7.05) and 77% women. 1448 (25%) participants with HT had lower scores on all the 4 cognitive measures after adjusting for BT and potential confounders, although only the association with Digit Span test was significant (beta=‐0.031 p=0.03). After testing for interactions, there was an association of HT with verbal reasoning score change for those with BT (beta=‐0.097, p=0.048). There was also an interaction between BT frequency (higher number of attempts) and HT for paired associate learning (interaction beta=‐0.118, p=0.008), whereby frequency of BT was associated with positive change (improvement) only in individuals without HT (beta=0.121, p<0.001), whereas no association was observed in individuals with HT (p>0.05). Conclusions HT was associated with lower cognition and also seems to modify the association of BT with cognition. There was improvement of all 4 cognition with increasing number of BT attempts irrespective of HT status, and improvement in Paired Associate scores over one year for participants without HT, implying a potential beneficial role for BT. However, this needs to be validated in larger and longitudinal studies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".