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Feasibility of Resistance Exercise Training in Gulf War Veterans with Widespread Pain

2019· article· en· W2953663873 on OpenAlexaboutno aff
Jacob V. Ninneman, Aaron J. Stegner, Patrick J. O’Connor, Jacob B. Lindheimer, Neda E. Almassi, Nicholas P. Gretzon, Ryan J. Dougherty, Kevin M. Crombie, Stephanie M. Van Riper, Dane B. Cook

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2019
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsResistance trainingTraining (meteorology)Gulf warResistance (ecology)Physical therapyMedicinePsychologyPhysical medicine and rehabilitationHistoryGeographyAncient historyBiology

Abstract

fetched live from OpenAlex

Roughly 25-33% of US Veterans of Operations Desert Shield or Desert Storm report a constellation of chronic symptoms including fatigue, confusion and widespread pain. Although exercise is routinely prescribed, and found to be efficacious, for many chronic pain conditions; Veterans’ reports of post-exertional exacerbation of symptoms complicates the question of whether exercise should be used as an adjunct treatment to standard care. PURPOSE: To determine the safety and efficacy of a resistance exercise training (RET) program in Gulf War Veterans (GV) with chronic widespread musculoskeletal pain (CMP). METHODS: Gulf Veterans suffering medically unexplained CMP lasting at least 3 months (N=50) were randomized to either 16 weeks of twice weekly RET or wait-list control (WLC). Training was supervised by exercise specialists and consisted of 10 exercises targeting major muscle groups. The program started at a very low intensity [25-35% of estimated 1-repetition maximum (1-RM)] and progressed in small (≤5%) increments. Thus, training was both individualized and standardized. Testing of 1-RM was completed at baseline and reevaluated at 16 weeks. The McGill Pain Questionnaire (MPQ) and Profile of Mood States (POMS) were completed at weeks 1, 6, 12 and 16. Exercisers not completing >50% of training were excluded from statistical analyses (n=4). Average 1-RM values were compared using dependent t-tests, and MPQ and POMS data were evaluated using repeated-measures ANOVAs. RESULTS: The final sample consisted of 22 GV in the RET group, with >90% adherence, and 20 WLC Veterans. No drop outs were due to negative complications with exercise. Following RET, participants on average lifted 67 kg/kg of body weight and significant (p<0.05) 1-RM increases were observed in all 8 lifts. Estimated 1-RM increased by at least 20% for 7 of 8 lifts. Mood scores significantly improved in both groups over the course of the trial with no significant difference between groups. No time or group effects (p>0.05) were observed in MPQ scores. CONCLUSIONS: RET significantly increased strength in GV with CMP. It resulted in no exacerbation of pain symptoms and did not increase mood disturbance. Resistance exercise appears safe and efficacious for Gulf Veterans with widespread pain. Supported by Dept. of Veterans Affairs grant: IO1-CX000383.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0020.000

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 head0.018
GPT teacher head0.292
Teacher spread0.274 · 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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