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Record W2954747898

Pain as a barrier to physical activity in severe obesity and the alter-g anti-gravity treadmill as a potential therapeutic tool

2018· dissertation· en· W2954747898 on OpenAlexaboutno aff
Hunter W Turnipseed

Bibliographic record

VenueThinkTech (Texas Tech University) · 2018
Typedissertation
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsnot available
Fundersnot available
KeywordsPhysical activityMedicineObesityTreadmillPhysical therapyPsychologyPhysical medicine and rehabilitationInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Obesity is highly prevalent, and more than 36.5% of American adults have obesity. Common barriers to physical activity in people with obesity are pain and low enjoyment, and both may contribute to low levels of activity. The use of the Alter-G Anti-Gravity Treadmill as a therapeutic tool to overcome these barriers is a new area explored in this study. Specific aims explored in this study were to determine if: Aim 1 - pain was associated with physical functioning in obesity, Aim 2 - exercise barriers were reduced by using the unweighting function of the Alter-G Anti-Gravity Treadmill, and Aim 3 - energy expenditure of moderate intensity exercise sessions with self-selected duration was similar in weighted and unweighted groups. 
\nHealthy adults (20- 55 years) with obesity (≥30 BMI) were recruited for this study. Participants were randomized into two groups with the control group exercising at 100% body weight and the experimental group using the unweighting function with self-selection of body weight. This project was an analysis of baseline data from a longer randomized trial of a 12 week walking program. Measurements taken during the baseline visit include physical functioning test (6-minute walk test and Timed Up and Go) and questionnaires (Short-Form McGill Pain Assessment, Physical Activity Enjoyment Scale (PACES), and History of Joint Pain). After baseline measurements, energy expenditure during exercise sessions (calculated by the Alter-G`s Stride Smart system), Physical Activity Enjoyment Scale (after experiencing the Alter-G Anti-Gravity Treadmill for three workouts), and Subjective Pain during exercise sessions (provided by the Alter-G`s Stride Smart system) were measured. 
\nThere were sixteen (9 female, 7 male) participants (age M = 33.06, SD =10.99, weight (kg) M = 107.51, SD = 13.30, BMI (kg/m²) M = 37.94, SD = 5.20) that participated in the study. They were randomized into two groups (control n = 10, experimental n = 6). There was no detectable association between pain and physical functioning. Subjective pain was not statistically different between the two groups (p = .156), and change in PACES scores were not statistically different between groups (p = .947). However the experimental group did have a statistically significant increase in PACES scores from the baseline measurement (M = 82.40, SD = 14.63) to the measurement taking after the 3rd visit (M =92.40, SD = 10.71) (p = .043). There was no difference in energy expenditure between groups. The exercise sessions were broken down into average speed, incline, and duration. The average speed (p = .280) and incline (p = .758) was not statistically different between groups, but the duration was significantly higher in the experimental (M = 45.64, SD = 2.43) group compared to the control (M = 37.52, SD = 1.81) group, (p = .020). This study demonstrated that a walking protocol using the unweighting feature of Alter-G Anti-Gravity Treadmill was associated with a significant increase in PACES score, and that using the unweighting feature of the Alter-G Anti-Gravity Treadmill can cause the duration during exercise be higher, leading to similar energy expenditure compared to exercising at 100% body weight.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.723
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.249
Teacher spread0.242 · 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 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
Published2018
Admission routes1
Has abstractyes

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