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Record W2128334959 · doi:10.1123/jab.29.6.670

Reliability of a Measure of Total Lumbar Spine Range of Motion in Individuals with Low Back Pain

2013· article· en· W2128334959 on OpenAlexafffund
Fadi Al Zoubi, Richard Preuss

Bibliographic record

VenueJournal of Applied Biomechanics · 2013
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsMcGill UniversityCentre for Interdisciplinary Research in Rehabilitation
FundersMcGill University
KeywordsLumbarGeneralizability theoryRange of motionMedicineLumbar spineLow back painOrthodonticsPhysical medicine and rehabilitationInclinometerMeasure (data warehouse)Lumbar vertebraePhysical therapyMathematicsComputer scienceGeodesyStatisticsSurgeryGeologyData mining

Abstract

fetched live from OpenAlex

Measuring lumbar spine range of motion (ROM) using multiple movements is impractical for clinical research, because finding statistically significant effects requires a large proportion of subjects to present with the same impairment. The purpose of this study was to develop a single measure representing the total available lumbar ROM. Twenty participants with low back pain performed three series of eight lumbar spine movements, in each of two sessions. For each series, an ellipse and a cubic spline were fit to the end-range positions, measured based on the position of the twelfth thoracic vertebra in the transverse plane of the sacrum. The area of each shape provides a measure of the total available ROM, whereas their center reflects the movements' symmetry. Using generalizability theory, the index of dependability for the area and anterior-posterior center position was found to be 0.90, but was slightly lower for the mediolateral center position. Slightly better values were achieved using the spline-fitting approach. Further analysis also indicated that excellent reliability, and acceptable minimal detectable change values, would be achieved with a single testing session. These data indicate that the proposed measure provides a reliable and easily interpretable measure of total lumbar spine ROM.

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)0.003
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.695
Threshold uncertainty score0.347

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.006
GPT teacher head0.222
Teacher spread0.216 · 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 designBench or experimental
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

Citations5
Published2013
Admission routes2
Has abstractyes

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