Overload From Anxiety: A Non-Motor Cause for Gait Impairments in Parkinson’s Disease
Bibliographic record
Abstract
Threatening situations lead to observable gait deficits in individuals with Parkinson's disease (PD) who suffer from high trait anxiety levels. The specific characteristics of gait that are affected appear to be similar to behaviors observed while walking during a dual-task (DT) condition. Yet, it remains unclear whether anxiety is similar to a cognitive load. If it were, then those with PD who have high trait anxiety might be expected to be more susceptible to DT interference during walking. Thus, the overall aim of this study was to evaluate whether trait anxiety influences gait during single-task (ST) and DT walking. Seventy participants (high-anxiety PD [HA-PD], N=26; low-anxiety PD [LA-PD], N=26; healthy control [HC], N=18) completed three ST and three DT walking trials on a data-collecting carpet. The secondary task consisted of digit monitoring while walking. Results showed that during both ST and DT gait, the HA-PD group demonstrated significant reductions in walking speed and step length, as well as increased step length variability and step time variability compared with healthy controls and the LA-PD group. Notably, ST walking in the HA-PD group resembled (i.e., it was not significantly different from) the gait behaviors seen during a DT in the LA-PD and HC groups. These results suggest that trait anxiety may consume processing resources and limit the ability to compensate for gait impairments in PD.
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 | 0.000 | 0.001 |
| 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".