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Record W4416285441 · doi:10.5327/cbn241607

The effectiveness of dual task training when combined with exercise on cognition in individuals with Parkinson’s disease: a randomized clinical trial

2024· article· W4416285441 on OpenAlexaboutno aff
Rogério José de Souza, Alessandra Cattaneo Estrada Melanda, GUILHERME VIEIRA SILVA, Andressa Letícia Miri, Patrícia Gonçalves Broto, Victor Hugo Kenzo Ishii, Ana Raquel Rodrigues Lindquist, Suellen Marinho Andrade, Suhaila Mahmoud Smaili

Bibliographic record

VenueArquivos de Neuro-Psiquiatria · 2024
Typearticle
Language
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsStroop effectCognitionCognitive trainingTranscranial direct-current stimulationTreadmillRandomized controlled trialTask (project management)Elementary cognitive taskDorsolateral prefrontal cortex

Abstract

fetched live from OpenAlex

Background: Cognitive decline is among the most frequent non-motor symptoms of Parkinson’s disease (PD). This decline affects daily activities, gait, postural control, and the ability to perform dual tasks (DT). Managing PD, especially its non-motor symptoms, is challenging, leading to a growing interest in studies investigating the effectiveness of various treatment protocols, whether isolated or combined. Objective: To verify the effectiveness of dual task training when combined with walking on a treadmill as well as anodal transcranial direct current stimulation (tDCS) on cognition in individuals with PD. Methods: This study is a randomized, controlled, blinded clinical trial involving 36 individuals with mild to moderate PD without cognitive decline. Participants were divided into two groups: 1) the Experimental Group (EG): underwent dual task training + walking on a treadmill + anodal tDCS and 2) the Control Group (CG): underwent walking on a treadmill + anodal tDCS. There were 12 intervention sessions, that were conducted three times a week. The dual task training protocol consisted of three levels, with six tasks per level, progressively increasing in complexity, and was applied for 18 minutes while walking on a treadmill. The current was applied to the left dorsolateral prefrontal cortex at an intensity level of 2mA, while walking on a treadmill. A cognitive assessment was conducted using the Montreal Cognitive Assessment (MoCA), the Trail Making Test, and the Stroop Test. Evaluations were performed three times at different points: pre-intervention, post-intervention, and after a 4-week follow-up period. Repeated measures ANOVA was used to compare the groups based on intervention, time, and group-time interaction. The study was approved by the Ethics Committee (CAAE: 30668420.7.0000.5188) and registered at Clinical Trials (NCT04581590). Results: There was a significant improvement in cognition in the EG (time effect) between pre- and post-intervention, and between pre-intervention and follow-up in the delayed recall domain and the total MoCA score. Additionally, there was improvement from pre-intervention to follow-up in the Stroop Test performance. For the CG, there was improvement between pre- and post-intervention in the Stroop Test performance, and between pre-intervention and follow-up in the delayed recall domain of the MoCA. No differences were observed between groups or in the time vs. group interaction. Conclusion: The addition of dual task training to a combined walking on a treadmill and anodal tDCS protocol was not effective in improving cognition in individuals with PD. Cognition is a complex construct, and more studies are needed to advance this investigation and seek an optimal protocol based on the type, number of sessions, frequency, duration, and intensity of the intervention to aid clinical decision-making.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.003
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.045
GPT teacher head0.321
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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