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Record W4395109651 · doi:10.1016/j.jesf.2024.04.003

Effects of conventional versus virtual reality-simulated treadmill exercise on fatigue, cognitive function, and participant satisfaction in post-COVID-19 subjects. A randomized trial

2024· article· en· W4395109651 on OpenAlexaboutno aff
Ahmad Ahmad, Sara Ali Mohamed Awad Allah, Gehad Ali Abd Elhaseeb, Dalia Ezzat Elsharawy, Hend Salem Ahmed, Mona Ahmed Mohamed Abdelwahab

Bibliographic record

VenueJournal of Exercise Science & Fitness · 2024
Typearticle
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsnot available
Fundersnot available
KeywordsVirtual realityTreadmillCognitionAerobic exercisePhysical medicine and rehabilitationPhysical therapyPsychologyCoronavirus disease 2019 (COVID-19)Randomized controlled trialMedicineComputer scienceHuman–computer interactionPsychiatry

Abstract

fetched live from OpenAlex

Post-COVID-19 subjects typically experience symptoms of fatigue, cognitive impairment, and sleep difficulty, which can be relieved by conventional aerobic exercise. Virtual Reality (VR) technology to support conventional exercise has recently gained much attention. Therefore, this study aimed to assess the effects of traditional treadmill exercise compared to virtual reality-simulated treadmill exercise on fatigue, cognitive function, sleep quality, and participant satisfaction with the exercise program in post-COVID-19 subjects. This single-centered, randomized, parallel-group intervention study was conducted between December 2021 and March 2022. Sixteen of twenty post-COVID-19 subjects completed this study (n1 = 8, n2 = 8). Inclusion criteria were persistent dyspnea/fatigue, mild cognitive problems, and age from 30 – 60 years. Exclusion criteria were previous severe COVID-19 infection and ICU admission, concomitant respiratory or cardiovascular disease, and musculoskeletal or neurological disease. Eligible subjects were assigned randomly to two groups: a non-VR group that received traditional treadmill aerobic exercise only and a VR group that received treadmill exercise with non-immersive VR. Both groups received moderate-intensity exercise on a treadmill at [50 – 60 % (peak HR-resting HR) + resting HR] for 30 – 45 min, three times per week, and for four weeks. The outcome measures were the Chalder Fatigue Scale, Montreal Cognitive Assessment (MoCA) questionnaire, Pittsburgh Sleep Quality Index (PSQI), and participant satisfaction with the exercise program rated on a 5-point Likert scale. Both groups showed significant improvements in the Chalder Fatigue Scale, the MoCA questionnaire, and the PSQI scores after training compared to baseline (p < 0.05), without significant differences between them (p > 0.05). However, participant satisfaction with the exercise program was significantly higher in the VR group than in the non-VR group (p = 0.037). A moderate-intensity 4-week treadmill exercise program with and without non-immersive VR may improve fatigue, cognitive function, and sleep quality to the same extent in COVID-19 survivors. However, participant satisfaction with the exercise program could be greater after conventional treadmill training assisted by non-immersive VR than after conventional treadmill training alone in this cohort. Pan African Clinical Trials Registry, PACTR202311561948428, retrospectively registered.

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 score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.038
GPT teacher head0.362
Teacher spread0.325 · 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

Citations8
Published2024
Admission routes1
Has abstractyes

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