THE RELATIONSHIP BETWEEN SEDENTARY BEHAVIOR AND COGNITIVE DOMAINS AMONG PEOPLE LIVING WITH DEMENTIA
Bibliographic record
Abstract
Abstract Greater sedentary behavior negatively impacts cognition among older adults without dementia; however, the relationship between sedentary behavior and cognitive domains among people living with dementia (PWD) is unclear. Our aim was to explore the association between sedentary behavior and cognitive domains in PWD in residential care facilities. The testing took place at one nursing home (n=15/23), one memory care unit (n=4/23), and one assisted living facility (n=4/23). Participants completed a battery of cognitive tests (global cognition: Montreal Cognitive Assessment; executive function: Trail Making test, Digit Span Backwards Test; perception and orientation: Benton Judgment of Line Orientation Test; language: Boston Naming Test; learning and memory: Rey Auditory Verbal Learning Test; complex attention: Digit Symbol Substitution Test). We used the Morse Fall Scale to measure fall risk. Participants wore an actigraphy monitor on their wrist over seven days to measure sedentary behavior. Most participants were male (74%), white (87%), and had unspecified dementia (48%). Participants were sedentary for 8.0±2.7 hours/day. The regression model for sedentary behavior was significant (R2=0.82, F(10, 12)=5.39, RMSE=92.47, p< 0.05). Greater sedentary behavior was associated with poorer language function (β=-0.82, p=0.02), poorer learning and memory (β=-0.82, p=0.002), and greater fall risk (β=-0.43, p=0.03). Sedentary behavior was not associated with the other cognitive domains. Greater sedentary behavior may indicate a decline in language function, learning and memory, and increase fall risk in PWD. Sedentary behavior should be considered in routine assessments, as it may play an important role in monitoring cognitive decline in PWD in residential care facilities.
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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 | 0.000 |
| 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 | 0.001 |
| 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".