Relationship Between Balance Automaticity and Dual-Task Interference in Older Adults
Bibliographic record
Abstract
BACKGROUND: Age-related decline can impair older adults' ability to perform tasks involving a mix of motor and cognitive goals in a dual-task (DT) paradigm. The amount of DT interference effects has typically been associated with the availability of attentional resources and the degree of balance automaticity. Older adults with mild cognitive impairment may lack sufficient sensorimotor capacity for "automatic" regulation of posture under demanding balance conditions, resulting in larger DT interference effects due to increasing attentional control. RESEARCH QUESTION: Does the degree of automaticity affect balance stability in older adults with mild cognitive impairment during dual tasking, and does this relationship vary with the difficulty of the balance task? METHODS: Sixty-seven older adults, aged 60-80 years (23 mild cognitive impairmentss), were positioned barefoot on a single piezoelectric force plate in a double-support and tandem stance with eyes open. Each stance condition was tested as single task during performance of a mathematical counting task (i.e., DT). DT cost (DTC) scores of center-of-pressure sway velocity (DTCVcop) were calculated, and regression analyses were conducted to assess the unique contribution of baseline center-of-pressure sway entropy under single-task conditions to DTCVcop, with age, Montreal Cognitive Assessment scores, gender, and cognitive status included as covariates. RESULTS: Baseline sway entropy accounted for only 0.25%-4% of the variance in DTC of Vcop. Gender and cognitive status accounted for 12%-20% of the variance under double-support but not in tandem stance. SIGNIFICANCE: Our findings suggest that sway entropy has only minimal impact on DT interference while gender and cognitive status play a more substantial role, highlighting the importance of these factors in balance control of older adults.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".