Effect of increased physical activity on cognitive function in individuals with mild cognitive impairment: A pilot study
Bibliographic record
Abstract
Abstract Background Studies suggest physical activity reduces risk of dementia and aerobic exercise improves global cognitive function in people with Mild Cognitive Impairment (MCI). Commercial wearable activity trackers tested in neurological studies have shown excellent reliability with older adults and are valid measures of daily step count. The primary objective of this pilot study was to determine if increased physical activity improved cognitive function in individuals with MCI. The secondary objective was to evaluate the feasibility of the use of an activity tracker with individuals with MCI. Method This pilot was a one‐group pretest‐posttest study and included 16 community‐dwelling older adults diagnosed with MCI who met inclusion and exclusion criteria. Participants were patients of the memory clinic in Sacramento, CA during 2018‐2019. One wrist wearable activity tracker was issued to each participant, along with a free downloadable software application to pair the tracker with a device. Daily step count was measured by an activity tracker. Change in cognitive function was measured with a pretest and posttest using the Montreal Cognitive Assessment (MoCA). Timed Up and Go (TUG) assessed risk for fall as an exclusion criteria and to measure any change in physical fitness. Participants were encouraged to increase their physical activity for 12 weeks. The primary investigator contacted the participants every 2 weeks to check their progress. Result Increased step count was positively correlated with an improvement in cognitive function (p‐value of 0.04) with a moderate effect size (r = 0.55). The group of participants showing MoCA score improvement had a higher average daily step count than those that did not show score improvement at a confidence level of 90% (p‐value of 0.09). Conclusion 5,500 steps or more per day is recommended to help improve cognitive function in individuals with MCI. It is feasible for individuals with MCI to wear an activity tracker reliably. The results of this pilot suggest the need for a randomized controlled trial with a larger sample. Further study is also recommended to identify covariates, such as activity intensity or history of regular exercise that predict improvement in cognitive function after a 12‐week intervention.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".