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Record W7126774280

Mind Flex : a high intensity exercise class with cognitive interventions for people

2025· other· en· W7126774280 on OpenAlexaboutno aff
Meg Weaver

Bibliographic record

VenueMOspace Institutional Repository (University of Missouri) · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsCognitionPsychological interventionCognitive trainingSocial cognitive theoryMontreal Cognitive AssessmentQuality of life (healthcare)FLEXClass (philosophy)
DOInot available

Abstract

fetched live from OpenAlex

Those with Parkinson's disease, a neurodegenerative condition, most often present with motor and non-motor symptoms. Occupational therapists treat individuals with Parkinson's to work on their physical well-being, cognition, independence in occupations, quality of life, and social participation. The purpose of this doctoral capstone experience was to design Mind Flex, an eight-week high intensity cycling exercise program with cognition interventions at the Parkinson's Exercise and Wellness Center. Seven participants were chosen for this project. The MoCA and a semi-structured questionnaires were used as primary outcome measures to evaluate general cognition before and after participants took part in the Mind Flex classes. The average MoCA pre-intervention score was 23/30 and the average MoCA post-intervention score was 22/30. All cognitive domain averages from the semi-structured questionnaire increased, indicating a higher confidence regarding completing cognitive tasks. The qualitative responses were analyzed for concurrent themes between fighters and the site mentor. The Mind Flex exercise plans were provided to the Parkinson's Exercise and Wellness Center for continued use and improvement of participants' symptoms because of Parkinson's Disease.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.126
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.015
GPT teacher head0.230
Teacher spread0.215 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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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