Assessing stress levels in older adults during cognitive and motor testing to advance earlier dementia screening
Bibliographic record
Abstract
Abstract Dementia is the second most feared diagnosis among adults, yet only a small percentage undergo cognitive testing for early signs during routine visits with primary care providers. It is possible that one reason for the low rate of routine screening may be patients’ resistance to testing, suggesting that anticipating or completing a cognitive assessment may induce stress in older adults. The primary purpose of this study was to determine the stress responses of older adults immediately prior to and during cognitive screening. This study also compared responses between a traditional (Montreal Cognitive Assessment, MoCA) and a novel (Brief Evaluation of Cognition and Daily Function, BEAN) assessment. Twenty-one unimpaired older adults were randomly assigned to either the MoCA or BEAN group and were initially blinded to their group assignment. Test-related stress was measured using subjective (STAI-6) and objective (salivary α-amylase and cortisol) methods at four time points: baseline, in anticipation of assessment type (immediately following unblinding), and then five and 30 minutes after test initiation. Contrary to our hypothesis, neither STAI-6 scores, α-amylase, nor cortisol values indicated test-related stress for either assessment relative to baseline, based on Bonferroni-adjusted repeated-measures ANOVAs. These results are important, as cognitive screening in both clinical care and clinical trials should have minimal stress responses. Future studies should explore test-related stress using continuous measures of stress response, such as electrodermal activity, particularly in patients with cognitive decline.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".