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Record W4409991159 · doi:10.1101/2025.04.28.25326452

Effects of a Remote Mental and Physical Practice Intervention on Freezing of Gait in People with Parkinson’s Disease: a Single-Blind Randomized Controlled Trial Protocol

2025· preprint· en· W4409991159 on OpenAlexaboutno aff
M.R. Pikel, Maria Elisa Pimentel Piemonte

Bibliographic record

VenuemedRxiv · 2025
Typepreprint
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsnot available
FundersFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsGaitPhysical medicine and rehabilitationProtocol (science)Parkinson's diseaseIntervention (counseling)Randomized controlled trialPhysical therapySingle blindPsychologyMedicineDiseasePsychiatryAlternative medicine

Abstract

fetched live from OpenAlex

Abstract Background Freezing of gait (FOG) is a common motor symptom in Parkinson’s disease (PD), increasing the risk of falls and reducing independence and quality of life. Effective management combines pharmacological treatment and, when necessary, surgical intervention with targeted strategies aimed at improving gait through compensatory brain networks. Mental Practice (MP), which consists of mentally rehearsing movements, has been studied as a possible strategy to facilitate gait through goal-directed motor control. However, there is limited evidence regarding its therapeutic effects on FOG. This study aims to compare the effects of a novel intervention combining MP based on Dynamic Neuro-Cognitive Imagery (DNI) and Physical Practice (PP) with a control intervention involving PP only, both delivered remotely on the severity of FOG episodes in individuals with PD. Methods A single-blind, controlled, and randomized trial is proposed. People with idiopathic PD who answered positively to the first question of New Freezing of Gait Questionnaire (NFOG-Q) will be randomly allocated into the Experimental Group (EG) and Control Group (CG). Both groups will undergo 10 remote intervention sessions lasting 45 - 60 minutes with identical volume and intensity, differing only in the MP components. The EG will perform sessions of MP combined with PP, while the CG will perform sessions of PP and stretching. They will be assessed before intervention (BI), after intervention (AI), and 30 days after the intervention, as a follow-up (FU). Primary outcomes included the time to complete the Rapid Turn Test, and the Percentage of time spent with FOG during the test (%FOG). Secondary outcomes included the NFOG-Q, the Movement Disorders Society – Unified Parkinson’s Disease Rating Scale (MDS-UPDRS), the Parkinson’s Disease Questionnaire-39 (PDQ-39), and the Telephone Montreal Cognitive Assessment (T-MoCA). A repeated measures ANOVA will be used for statistical analysis. Discussion The main hypothesis is that both interventions, which are similar in terms of volume, intensity, and progression of complexity, will positively affect the FOG severity. However, experimental intervention combining MP and PP is expected to produce better outcomes than the control intervention. If this hypothesis is confirmed, the study could significantly impact the treatment of people with PD by providing a low-cost and widely accessible option. Administrative information Note: The numbers in curly bracelets in this protocol refer to SPIRIT checklist item numbers. The order of the items has been modified to group similar items.

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)0.006
metaresearch head score (Gemma)0.005
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: Protocol · Consensus signal: Protocol
Teacher disagreement score0.022
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0100.004
Bibliometrics0.0020.001
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0220.003

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 head0.014
GPT teacher head0.317
Teacher spread0.303 · 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
GenreProtocol

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
Published2025
Admission routes1
Has abstractyes

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