Executive Function: Application in the Rehabilitation of Chronic Pain
Bibliographic record
Abstract
Executive function (EF) is a control mechanism of human cognition that provides the capability to select actions in relation to internal goals organized by the prefrontal cortex (PFC). The PFC is essential for the temporal integration of sensory information in the sequencing of optimum motor behavior to achieve an internal goal. The temporal integration of sensory information also explains why the PFC has an additional role in the central modulation of pain. Pain modulation and motor function are altered in chronic pain, and this alteration can contribute to the reduced physical activity. EF is the driver of conscious control of thought and action that is critical to rehabilitation in chronic pain. However, EF is impaired in chronic pain. Rehabilitation practitioners typically use activity modification, exercise, and movement to enhance function in patients with chronic pain; exercise has beneficial effects on EF. However, impairments in EF can be barriers to adherence to exercise, activity, and lifestyle modifications required to optimize rehabilitation. Greater awareness of EF can enhance rehabilitation. This narrative review explores current theories of EF structure and function, how impairment of EF can be assessed in a clinical context, and its implications for rehabilitation in chronic pain.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".