Cognitive Function, Consent for Participation, and Compliance With Wearable Device Protocols in Older Adults
Bibliographic record
Abstract
Background: Population-based studies of older adults increasingly use wearable devices to measure activity and sleep. Whether cognitive impairment reduces consent and compliance has not been assessed. Methods: In the context of a nationally representative cohort of community-dwelling adults aged 62-90, individuals were invited to participate in a sleep and activity substudy that required wearing a wrist actigraph for 72 consecutive hours. Cognitive function in the parent study was assessed with the survey adaptation of the Montreal Cognitive Assessment, and individuals were categorized as normal, mild cognitive impairment, or dementia. Participants were asked to press an event marker on the actigraph when they started trying to fall asleep and when they awoke each day. Logistic and negative binomial regressions were used to link cognitive status to nonconsent, returning usable data, wearing the actigraph three full days, ever taking the device off-wrist during the 3-day study period, and pushing the event markers, controlling for demographics. Results: Cognitive status was not associated with nonconsent, returning usable data, off-wrist, or missing days. However, individuals classified with dementia were more likely to miss bedtime and wake-up event markers. Individuals classified as mild cognitive impairment were more likely to miss wake-up event markers. Conclusions: Impaired cognition does not seem to be a barrier to compliance with simply wearing a device but may affect compliance with additional action such as pressing event markers.
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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 | 0.014 | 0.061 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".