Response inhibition, set shifting, and complex executive function in patients with chronic lower back pain
Bibliographic record
Abstract
OBJECTIVE: The aim of our study was to evaluate how response inhibition, set shifting, and complex executive function (represented by risky decision-making) are altered in chronic lower back pain patients. MATERIALS AND METHODS: A total of 29 patients with chronic lower back pain (CLBP >6 months) aged 49-69 years and 30 healthy volunteers matched for age, gender, and education were enrolled in a case-control study. The study was conducted in the Departments of Neurology and Neurosurgery of Panevėžys Regional Hospital, Lithuania. Pain was evaluated by the visual analog scale, Pakula Pain Questionnaire (Lithuanian analog of McGill Pain Questionnaire), and Fibromyalgia Tender Points Examination. A battery of neuropsychological tests used included Stroop Test Victoria version, Trail Making Test parts A and B, and Game of Dice Task (GDT). RESULTS: CLBP patients did not score significantly worse in any examined neuropsychological tests. Response Inhibition correlated inversely with number of tender points in CLBP patients. GDT performance showed no significant difference in net score (number of safe minus risky decisions). Unexpectedly, both groups favored risky decisions. CONCLUSIONS: We found no statistically significant difference in response inhibition, set shifting, or complex executive function between CLBP patients and healthy older adults. Moreover, a risky decision-making pattern found in the Lithuanian population may underscore the importance of cultural context when examining complex executive function. However, further studies are needed to prove this point.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".