Regression Analysis of the Relationship Among the Level of Pain and Dysfunction and Psychosocial Factors in Patients With Chronic Back Pain
Bibliographic record
Abstract
Background: Chronic back pain shows a high correlation with lumbar disability, physical disability for daily activities, and psychosocial factors, such as depression. Object: The purpose of this study was to examine the correlation of the level of pain and disability with psychosocial factors, which are potential disturbance variables, in patients with chronic lumbar pain. Method: The sample included 258 patients, who had complained of chronic lumbar pain for more than three months. The Quadruple Visual Analogue Scale was used to measure the level of pain, and a Korean version of Oswestry Disability Index was used to measure the level of disability. Psychosocial factors were measured using the Tampa scale for Kinesiophobia-11, Fear Avoidance Beliefs Questionnaire, and Pain Self-Efficacy Questionnaire. The collected data was analyzed using PASW 18.0, and an independent samples t-test was used to examine frequency, percentage, mean, and standard deviation of sociodemographic characteristics and major variables. Pearson's correlation coefficient was used to investigate the correlation between the level of pain and disability and psychosocial factors. Stepwise multiple regression analysis was done to determine the level of pain and psychosocial factors of functional disorder. The significance level was set at . Result: There is a strong correlation between the level of pain and functional disorder and psychosocial factors in patients with chronic lumbar pain. The study also revealed that as the levels of pain and fear avoidance increase, pain self-efficacy decreases. Conclusion: The results suggest that negative perceptions towards pain, limitations of physical movement, and severe fear avoidance directly affect the decrease in pain self-efficacy. Therefore, it is recommended to test pain self-efficacy when measuring the level of pain and disability in patients with chronic low back pain.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".