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Record W4280605620 · doi:10.52403/ijhsr.20220533

Study of Kinesiophobia in Patients with Shoulder Pain

2022· article· en· W4280605620 on OpenAlexaff
Sana Farheen Khan, Chavda Charul Harishbhai, Mosam Patel

Bibliographic record

VenueInternational Journal of Health Sciences and Research · 2022
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsCanadian Physiotherapy Association
Fundersnot available
KeywordsMedicinePhysical therapyPositive correlationCorrelationPain scorePhysical medicine and rehabilitationInternal medicineSurgery

Abstract

fetched live from OpenAlex

Background: Kinesiophobia has been established as an important factor among the patients with musculoskeletal pain. Thus the study aims to explore prevalence of kinesiophobia among patient with shoulder pain and also to find out the correlation between age and kinesiophobia and pain and kinesiophobia. Aims and Objectives: To find out the prevalence of kinesiophobia among the patients having shoulder pain. To find out correlation between kinesiophobia and age. To find out the correlation between pain and kinesiophobia Methodology: A study with 50 subjects of age group between 40 to70 patients suffering from acute, subacute and chronic shoulder pain were selected. Pain was measured using NPRS and subjects were assessed using the tampa scale of kinesiophobia in which the scores above 37 were considered to have positive kinesiophobia whereas the score below were considered negative. Result- Positive kinesiophobia was present in 40 patients out of 50 that is 80% .This study also shows positive correlation between age and kinesiophobia with significant p value and also positive correlation between pain and TSK score. Conclusion: The study concludes that positive kinesiophobia is strongly associated with majority of the older adult patient with acute, subacute and chronic shoulder pain. Also with increasing age patients developed more severe kinesiophobia. Patient associated with high intensity of pain have higher tampa score. Key words: kinesiophobia, shoulder pain, Tampa scale.

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)0.011
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 score0.011
Threshold uncertainty score0.370

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.065
GPT teacher head0.458
Teacher spread0.393 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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