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Record W2159779800 · doi:10.3138/ptc.2011-33

Influence of Hamstring and Abdominal Muscle Activation on a Positive Ober's Test in People with Lumbopelvic Pain

2012· article· en· W2159779800 on OpenAlexvenueno aff
H. Rich Tenney, Kyndall L. Boyle, Aaron DeBord

Bibliographic record

VenuePhysiotherapy Canada · 2012
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
FundersMinisterul Cercetării, Inovării şi Digitalizării
KeywordsMedicineHamstringAbdominal musclesStraight leg raisePhysical therapyHamstring musclesPhysical medicine and rehabilitationIntervention (counseling)Range of motionSurgeryNursing

Abstract

fetched live from OpenAlex

PURPOSE: To assess the immediate effect of hamstring and abdominal activation on pain levels as measured by the Numeric Pain Scale (NPS) and hip range of motion as measured by Ober's Test in people with lumbopelvic pain. METHODS: Thirteen participants with lumbopelvic pain and positive Ober's Tests completed an exercise developed by the Postural Restoration Institute™ to recruit hamstrings and abdominal muscles. RESULTS: There was a significant increase in passive hip-adduction angles (p<0.01) and decrease in pain (p<0.01) immediately after the intervention. CONCLUSION: Specific exercises that activate hamstrings and abdominal muscles appear to immediately improve Ober's Test measurements and reduce pain as measured by the NPS in people with lumbo-pelvic pain. Hamstring/abdominal activation, rather than iliotibial band stretching, may be an effective intervention for addressing lumbopelvic pain and a positive Ober's Test.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.999
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0030.000

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 head0.003
GPT teacher head0.231
Teacher spread0.228 · 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

Citations10
Published2012
Admission routes1
Has abstractyes

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