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Record W4289874694 · doi:10.5937/sanamed17-37885

Kinesthetic and visual imagery in young adults with chronic neck pain

2022· article· en· W4289874694 on OpenAlexaboutno aff
Özlem Özcan, Hayriye Kul Karaali

Bibliographic record

VenueSANAMED · 2022
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsMotor imageryKinesthetic learningMental imagePhysical medicine and rehabilitationPhysical therapyNeck painChronic painVisual analogue scaleMcGill Pain QuestionnaireMedicinePsychologyDevelopmental psychologyCognitionElectroencephalographyBrain–computer interfacePsychiatry

Abstract

fetched live from OpenAlex

Background: Young adults complain of neck pain almost every year. In recent years the ability of motor imagery (kinesthetic and visual imagery) in many musculoskeletal system problems other than neck pain in young adults has been investigated in the literature. The Cross-Sectional study aimed to question motor imagery ability in young adults with chronic neck pain. Methods: Two groups were included in the study: the chronic neck pain group (n = 83) and the control group (n = 91). Motor imagery ability of both groups was evaluated with Movement Imagery Questionnaire-3. Additionally, in the chronic neck pain group, pain was evaluated with the Short Form-McGill Pain Questionnaire, disability was evaluated with the Neck Disability Index, and kinesiophobia was evaluated with Tampa Scale for Kinesiophobia. Conclusions: Internal visual imagery and kinesthetic imagery were significantly different between chronic neck pain and control groups. There was a negative linear relationship between disability and internal visual imagery, external visual imagery, and kinesthetic imagery. Motor imagery ability is reduced in young adults with chronic neck pain. In addition, as the severity of disability increases, the motor imagery ability decreases. Therefore, it is considered appropriate to include a motor imagery training program when treating chronic neck pain in the future.

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 score0.206
Threshold uncertainty score0.255

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 head0.003
GPT teacher head0.236
Teacher spread0.232 · 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

Citations5
Published2022
Admission routes1
Has abstractyes

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