No Impairment of Executive Function, Psychomotor Speed, and Decision-Making Under Risk in Chronic Lower Back Pain Patients
Bibliographic record
Abstract
Clinical studies suggest that cognitive functions are impaired in chronic pain patients. However, there is no obvious common pattern between studies. The aim of our study was (1) to evaluate how executive function, psychomotor speed and decision-making under risk are altered in chronic lower back pain patients and (2) to answer the question if impaired decision-making is due to cognitive dysfunction or other reasons, such as impaired reward processing. We examined 27 patients aged 49 to 69 with chronic lower back pain (CLBP >6 months, with a mean of 91 months, SD = 160) and 30 healthy volunteers, matched for age, sex, and education. Pain was evaluated by Visual Analogue Scale, Pakula Pain Questionnaire (Lithuanian analogue of McGill Pain Questionnaire), and Fibromyalgia Tender Points Examination. A battery of neuropsychological tests were used to measure cognitive performance. CLBP patients did not score significantly worse in any examined neuropsychological tests. Neither pain duration, nor subjective pain scores correlated with any of the cognitive domains. Psychomotor speed was the only domain that correlated inversely with the number of affective pain descriptors. Since Game of Dice Task was performed in an Eastern European population for the first time, an unexpected finding was observed: CG seemed to favor risky decisions. Our results indicate that there is no statistically significant difference in executive functions, psychomotor speed and decision-making under risk between CLBP patients and healthy older adults. A risky decision-making pattern found in Lithuanian population underscores the importance of cultural context when examining executive function.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".