Multisensory, Multi-Tasking Performance of Older Adults With and Without Subjective Cognitive Decline
Bibliographic record
Abstract
As the population ages, it is increasingly important to detect non-normative cognitive declines as early as possible. Measures of combined sensory-motor-cognitive functioning may be early markers for identifying individuals who are at increased risk of developing dementia. Further, older adults experiencing subjective cognitive decline (SCD) may have elevated risk of dementia compared to those without SCD. Tasks involving complex, multisensory interactions reflective of everyday challenges may be particularly sensitive to subjectively perceived, pre-clinical declines. In the current study, older adults with and without SCD were asked to simultaneously perform a standing balance task and a listening task under increasingly challenging sensory/cognitive/motor conditions using a dual-task paradigm in a realistic, immersive virtual environment. It was hypothesized that, compared to older adults without SCD, those with SCD would exhibit greater decrements in postural control and listening response accuracy as sensory/motor/cognitive loads increased. However, counter to predictions, older adults with SCD demonstrated greater reductions in postural sway under more challenging dual-task conditions than those without SCD. Across both groups, poorer postural task performance was associated with poorer cognitive function and speech-in-noise thresholds measured with standard baseline tests. Poorer listening task performance was associated with poorer global cognitive function, poorer mobility, and poorer speech-in-noise detection. Overall, the results provide additional support for the growing evidence demonstrating associations between sensory, motor, and cognitive functioning and contribute to an evolving consideration of how best to categorize and characterize SCD in a way that guides strategies for screening, assessment, and intervention.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".