A framework for secondary cognitive and motor tasks in dual-task gait testing in people with mild cognitive impairment
Bibliographic record
Abstract
BACKGROUND: Cognition is a key factor in the regulation of normal walking and dual-task gait assessment is an accepted method to evaluate the relationship. The objective of this study was to create a framework for task complexity of concurrent motor and cognitive tasks with gait in people with mild cognitive impairment (MCI). METHODS: Community-dwelling people with MCI (n = 41, mean age = 76.20 ± 7.65 years) and cognitively normal controls (n = 41, mean age = 72.10 ± 3.80 years) participated in this study. Gait velocity was collected using an instrumented walkway under one single task and six combined tasks of motor and cognitive activities. The cognitive cost was the difference between the single gait task and each of the concurrent motor and cognitive challenges. A repeated two-way measure ANOVA assessed the effect of cognitive group and walking test condition for each gait task test. RESULTS: Gait velocity was significantly slower in the MCI group under all tasks. For both groups, the concurrent motor task of carrying a glass of water conferred a challenge not different from the cognitive task of counting backwards by ones. Performance of the complex cognitive task of serial seven subtractions reduced gait velocity in both groups, but produced a greater change in the MCI group (31.8%). CONCLUSIONS: Not all concurrent tasks challenge cognition-motor interaction equivalently. This study has created a framework of task difficulty which allows for the translation of dual-task test conditions to future research and clinical practice to ensure the accuracy of assessing patient deficits and risk.
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 | 0.015 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".