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Record W4311717261 · doi:10.7717/peerj.14469

Characteristics and usefulness of trunk muscle endurance tests on the Roman chair in healthy adults

2022· article· en· W4311717261 on OpenAlexaboutno aff
Maja Petrič, Lijana Zaletel‐Kragelj, Renata Vauhnik

Bibliographic record

VenuePeerJ · 2022
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
FundersJavna Agencija za Raziskovalno Dejavnost RS
KeywordsTrunkPhysical therapyMedicineBack musclesPhysical medicine and rehabilitationTest (biology)Low back pain

Abstract

fetched live from OpenAlex

Background Adequate trunk muscle endurance is considered to be an important indicator of good low back stability; therefore, its assessment is needed when determining an individual’s risk for back pain. Optimal tests to assess each trunk muscle group separately are difficult to find. The objective of this study was to verify if two groups of trunk muscle endurance tests (standard and alternative) show comparable results in terms of muscle endurance ratios, holding times and rated perceived effort to perform each test. Methods The study was designed as a quasi-experimental repeated-measures design. There was a single group of participants who took part in two different trunk muscle endurance testing. Sixty-eight healthy adult volunteers, aged 20–45 years (31.9 ± 7.2 years), without recent musculoskeletal injury or disorder participated in the study. All participants finished the study. Trunk muscle endurance tests as tested on the Roman chair (B tests) were compared with standard tests as suggested by McGill (A tests). Each group of tests consisted of an endurance test for trunk extensors, trunk flexors, and lateral trunk muscles for left and right side. The order of tests’ performances was randomly assigned to each participant, whereby a participant did perform A and B tests in the same order. In each test of A and B the holding time was recorded and a perceived effort in each test performance was also assessed by participants. Post testing performance the four ratios of trunk muscles endurance comparison were calculated for each group of tests to determine if there is a good or poor ratio between muscles. Results of each participant were compared for trunk muscle endurance ratio calculations, holding times and rated perceived effort for A and B tests. Results Results showed comparable trunk muscle endurance ratios in the three ratios observed, except for the flexors:extensors ratio (A FL:EX : 1.2 (IQR: 0.7–1.6) vs . B FL:EX : 0.6 (IQR: 0.3–0.8); p < 0.001). As compared to A tests, holding times were significantly longer in B tests for the extensors (A EX : 125.5 s (IQR: 104.8–182.8 s) vs . B EX : 284.0 s (IQR: 213.0–342.3 s); p < 0.001) and lateral trunk muscles (A L-LM : 61.0 s (IQR: 48.3–80.8 s) vs . B L-LM : 131.5 s (IQR: 95.5–158.5 s); A R-LM : 63.5 s (IQR: 45.8–77.3 s) vs . B R-LM : 113.0 s (IQR: 86.3–148.8 s); p < 0.001), both were also rated as slightly easier to perform in the extensors (A RPE-EX : 13 (IQR: 12.0–14.0) vs B RPE-EX : 11 (IQR: 10.0–13.0); p RPE-EX < 0.001) and lateral muscles testing (A RPE-LM : 14.0 (IQR: 12.3–15.8) vs . B RPE-LM : 13.0 (IQR: 12.0–15.0); p RPE-LM = 0.001). Conclusions A and B tests are comparable in three of four trunk muscle endurance ratios, while longer holding times and lower perceived effort to perform were observed in most of the B tests. The Roman chair tests could be used as an alternative to standard tests.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.330
Threshold uncertainty score0.182

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.016
GPT teacher head0.265
Teacher spread0.249 · 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.

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

Citations4
Published2022
Admission routes1
Has abstractyes

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