Pain, Executive Functioning, and Affect in Patients With Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVES: Rheumatoid arthritis (RA) is a chronic inflammatory disease resulting in substantial pain. The physical and emotional effects of RA are well known, but little attention has been given to the potential cognitive effects of RA pain, although intact executive functioning in patients with chronic illness is crucial for the successful completion of many daily activities. We examined the relationship between pain and executive functioning in patients with RA, and also considered the influence of positive and negative affect in the relationship between pain and executive functioning. METHODS: A sample of 157 adults with RA completed measures of pain and positive and negative affect and were tested for working memory and selective attention using the Letter Number Sequencing subtest from the Wechsler Adult Intelligence Scale-Third Edition and the Stroop Color Word Test tests, respectively. RESULTS: Consistent with prior research, pain was inversely related to executive functioning, with higher pain levels associated with poorer performance on executive functioning tasks. This relationship was not moderated or mediated by negative affect; however, positive affect moderated the relationship between pain and executive functioning. For patients high in positive affect there was a significant inverse relationship between pain and executive functioning, whereas there was no such relationship for patients low in positive affect. DISCUSSION: These findings are discussed in the context of cognitive research on the effects of positive affect on executive functioning and functional neuroanatomical research suggesting neurocognitive mechanisms for such moderation.
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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 | 0.004 |
| 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 | 0.001 |
| 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".