Can Dual Task Walking Improve in Parkinson’s Disease After External Focus of Attention Exercise? A Single Blind Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: It may be possible to use attention-based exercise to decrease demands associated with walking in Parkinson's disease (PD), and thus improve dual task walking ability. For example, an external focus of attention (focusing on the effect of an action on the environment) may recruit automatic control processes degenerated in PD, whereas an internal focus (limb movement) may recruit conscious (nonautomatic) control processes. Thus, we aimed to investigate how externally and internally focused exercise influences dual task walking and symptom severity in PD. METHODS: Forty-seven participants with PD were randomized to either an Externally (n = 24) or Internally (n = 23) focused group and completed 33 one-hour attention-based exercise sessions over 11 weeks. In addition, 16 participants were part of a control group. Before, after, and 8 weeks following the program (pre/post/washout), gait patterns were measured during single and dual task walking (digit-monitoring task, ie, walking while counting numbers announced by an audio-track), and symptom severity (UPDRS-III) was assessed ON and OFF dopamine replacement. Pairwise comparisons (95% confidence intervals [CIs]) and repeated-measures analyses of variance were conducted. RESULTS: Pre to post: Dual task step time decreased in the external group (Δ = 0.02 seconds, CI 0.01-0.04). Dual task step length (Δ = 2.3 cm, CI 0.86-3.75) and velocity (Δ = 4.5 cm/s, CI 0.59-8.48) decreased (became worse) in the internal group. UPDRS-III scores (ON and OFF) decreased (improved) in only the External group. Pre to washout: Dual task step time ( P = .005) and percentage in double support ( P = .014) significantly decreased (improved) in both exercise groups, although only the internal group increased error on the secondary counting task (ie, more errors monitoring numbers). UPDRS-III scores in both exercise groups significantly decreased ( P = .001). CONCLUSIONS: Since dual task walking improvements were found immediately, and 8 weeks after the cessation of an externally focused exercise program, we conclude that externally focused exercise may improve on functioning of automatic control networks in PD. Internally focused exercise hindered dual tasking ability. Overall, externally focused exercise led to greater rehabilitation benefits in dual tasking and motor symptoms compared with internally focused exercise.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".