Pain Catastrophizing, Pain Self-Efficacy, and Kinesiophobia Effects on Outcomes After Upper Extremity Fracture
Bibliographic record
Abstract
Objective: The aim of our study was to investigate the effects of pain-related psychosocial factors such as pain catastrophizing, pain self-efficacy, and kinesiophobia on pain, disability, and quality of life after upper extremity fracture. Methods: This single-center cross-sectional study included 90 individuals with upper extremity fracture between March and August 2021, with a mean age of 45.00 ± 12.63 years. Data were collected with the Demographic Information Form, Quick Disabilities of the Arm, Shoulder, and Hand Questionnaire (QuickDASH), Tampa Kinesiophobia Scale (TKS), Short Form McGill Pain Questionnaire (SF-MPQ), Short Form-12 (SF-12) Quality of Life Questionnaire, Pain Self-Efficacy Questionnaire (PESQ), and Pain Catastrophizing Scale (PCS). Multivariate regression analysis was used to examine the effects of psychosocial factors on outcomes. Results: Pain catastrophizing, of pain and quality of life; pain self-efficacy, of disability and quality of life; and kinesiophobia, of all outcomes were found to be significant predictors (P < .001). Higher pain catastrophizing scores predicted increased pain and decreased quality of life (SF-MPQ, R2 = 0.446; SF-12, R2 = −0.616) higher pain self-efficacy scores predicted increased disability and quality of life (QuickDASH, R2 = −0.662 SF-12, R2 = 0.376), and higher kinesiophobia scores predicted increased pain, extent of disability, and quality of life (SF-MPQ, R2 = 0.276; QuickDASH, R2 = − 0.391; SF-12, R2 = −0.229). Conclusion: The findings of the study support an approach with a biopsychosocial perspective that explains the possible contributions of ineffective coping strategies such as kinesiophobia and pain catastrophizing on pain intensity and extent of disability after upper extremity fractures. Cite this article as: Şimşek D, Kaya Ciddi P. Pain catastrophizing, pain self-efficacy, and kinesiophobia effects on outcomes after upper extremity fracture. Arch Health Sci Res. 2023;10(1):17-21.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".