A Cross Sectional Analysis of Physical Activity Engagement in Adults with Mild Cognitive Impairment
Bibliographic record
Abstract
Abstract Background To address the paucity of literature regarding the relationship between mild cognitive impairment and physical activity engagement, this study aimed to understand the relative contribution of cognitive, demographic, physical and psychological variables related to physical activity engagement in individuals with mild cognitive impairment. Method This was a descriptive, cross – sectional study of secondary data from 62 participants with MCI (mean age 70.53, SD = 6.34), 53.2% female, median MoCA 23 (IQR: 20, 24)) from the NeuroExercise study, a 12 – month PA intervention on the outcome of cognitive function. The independent variable of interest was global cognitive function. Age, gender, years of education, number of medications, handgrip strength, depression, and quality of life were treated as covariates. The dependent variable was PA engagement in minutes per week, using the LAPAQ physical activity questionnaire and the Actigraph triaxial accelerometer device. Results Hierarchical regression analyses showed no significant effect of cognitive function on physical activity engagement after controlling for the effects of covariates. Physical activity engagement was low relative to global physical activity guidelines ((M = 111.38, SD = 94.29) Actigraph ( t (51) = -2.95, p < .005) and the LAPAQ (M = 51.71, SD = 22.80), t (61) = -33.94, p = < .001)). A Bland- Altman measure of agreement demonstrated that objective and subjective measures of physical activity were not equivalent. Conclusions This sample of adults with MCI were not sufficiently physically active. Further, there was substantial variability between objective and subjective measures of physical activity engagement. Objective measurement of PA data may be more reliable for adults with mild cognitive impairment.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".