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Impact Of A Remotely Instructed Bodyweight Interval Training Program For Adults With Obesity

2024· article· en· W4402662119 on OpenAlexaff
Gabriella F. Bellissimo, Alyssa R. Bailly, Quint Berkemeier, Jonathan Specht, J. Maclean Smith, Jeremy B. Ducharme, Shandy Simpson, Matthew Stork, Jonathan P. Little, Len Kravitz, Christine M. Mermier, Flávio de Castro Magalhães, Ann L. Gibson, Fabiano T. Amorim

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsInterval trainingTraining (meteorology)Interval (graph theory)ObesityMedicinePsychologyGerontologyPhysical therapyMathematicsGeographyInternal medicineMeteorology

Abstract

fetched live from OpenAlex

Bodyweight interval training (BW-IT) may be feasible for enhancing aerobic capacity and muscular strength. BW-IT delivered remotely may especially appeal to those who wish to refrain from public exercise or have limited access to fitness facilities/equipment. PURPOSE: To determine the impact of a 6-week BW-IT program hosted via YouTube on cardiorespiratory fitness (CRF), muscular strength, and physical activity enjoyment (PACES) in adults with obesity. METHODS: Fourteen inactive but otherwise healthy adults with obesity (30.7 ± 10.3 yrs.,35.5 ± 5.4 kg/m2) participated in a 6-week BW-IT program that progressed bi-weekly from a work-to-rest ratio of 1:3 to 1:1. Using pre-recorded videos, participants performed BW-IT (2 sets of high knees, squat jumps, scissor jacks, jumping lunges, and burpees for as many repetitions as possible interspersed with active recovery walking in place) 3x/week. The videos showcased modified (reduced range of motion/elimination of plyometric phase) and advanced versions of each exercise. Baseline and post-intervention testing were identical and included peak oxygen consumption (V̇O2peak) through individualized treadmill protocols, dominant leg isometric muscular strength (isokinetic dynamometer), and waist circumference (WC) taken at the superior border of the iliac crest. Enjoyment was assessed after the first and final week of the program. Pre- and post-BW-IT variables were assessed using student’s paired t-test (α < .05). RESULTS: Thirteen subjects completed all 18 sessions (100% compliance), but 1 completed 14 sessions (78% compliance). Increases in muscular strength (~10%, +0.2 ± 0.2 Nm/kg, p = 0.02) and V̇O2peak (~5%, +0.1 ± 0.2 L/min, p = 0.02) occurred. WC decreased (-2.2 ± 2.4 cm, p = 0.03). PACES scores were higher after week 1 (102.8 ± 16.5) compared to week 6 (92.9 ± 16.9) of BW-IT, p = 0.003. CONCLUSION: In previously inactive adults with obesity, remotely delivered bodyweight interval training elicited significant improvements in CRF, lower extremity muscular strength, and WC. Future studies may benefit from manipulating the selection of calisthenics and protocol progression to determine interventions that improve physiological health and maintain or enhance physical activity enjoyment. NMRG ($3000)/Grammarly, Inc. was used for grammatical checks

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.016
GPT teacher head0.313
Teacher spread0.297 · 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 designObservational
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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