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Record W3121510889 · doi:10.1186/s12891-021-03944-z

Development and validation of a shoulder-specific body-perception questionnaire in people with persistent shoulder pain

2021· article· en· W3121510889 on OpenAlexfundno aff
Tomohiko Nishigami, Akihisa Watanabe, Toshiki Maitani, Hayato Shigetoh, Akira Mibu, Benedict M. Wand, Mark J. Catley, Tasha R. Stanton, G. Lorimer Moseley

Bibliographic record

VenueBMC Musculoskeletal Disorders · 2021
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsRasch modelMedicinePhysical therapyTest (biology)Reliability (semiconductor)RehabilitationPerceptionSports medicinePsychometricsPhysical medicine and rehabilitationClinical psychologyPsychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

BACKGROUND: There is evidence that people with persistent shoulder pain exhibit findings consistent with the presence of sensorimotor dysfunction. Sensorimotor impairments can manifest in a variety of ways, and further developing our understanding of sensorimotor dysfunction in shoulder pain may improve current models of care. The Fremantle Back Awareness Questionnaire (FreBAQ) has been developed to assess disturbed body perception specific to the back. The purpose of the present study was to develop a shoulder-specific self-perception questionnaire and evaluate the questionnaire in people with persistent shoulder pain. METHODS: The Fremantle Shoulder Awareness Questionnaire (FreSHAQ-J) was developed by modifying the FreBAQ. One hundred and twelve consecutive people with persistent shoulder pain completed the FreSHAQ-J. Thirty participants completed the FreSHAQ-J again two-weeks later to assess test-retest reliability. Rasch analysis was used to assess the psychometric properties of the FreSHAQ-J. Associations between FreSHAQ-J total score and clinical status was explored using correlational analysis. RESULTS: The FreSHAQ-J has acceptable category order, unidimensionality, no misfitting items, and excellent test-retest reliability. The FreSHAQ-J was moderately correlated with disability and pain catastrophization. CONCLUSIONS: The FreSHAQ-J fits the Rasch measurement model well and is suitable for use with people with shoulder pain. Given the relationship between the FreSHAQ-J score and clinical status, change in body perception may be worth assessing when managing patients with shoulder pain.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.856

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.013
GPT teacher head0.265
Teacher spread0.252 · 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

Citations15
Published2021
Admission routes1
Has abstractyes

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