The Mediating Role of Physical Function on the Self-Reported Pain and Cognitive Function Association
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: Studies that have investigated the relationship between pain intensity and interference and cognitive function have failed to fully consider the role physical function may play in this relationship. Therefore, the purpose of this study was to examine the mediating role of physical function in the relationship between self-reported pain intensity and interference and cognitive function in middle-to-older aged adults with knee pain. METHODS: Middle-to-older aged participants with knee pain (n = 202) completed the Graded Chronic Pain Scale to assess pain intensity and interference, the Short Performance Physical Battery to assess lower-extremity physical function, and the Montreal Cognitive Assessment to assess global cognitive function. Linear regression-based mediation analyses were used to assess associations between pain intensity and interference and cognitive function, with lower-extremity physical function as the mediator. RESULTS: The direct relationship between pain intensity and cognitive function was significant (β = -0.269, p < .001) and remained significant when physical function was included as a mediator (c'=-0.0854, p = .003). The direct relationship between pain interference and cognitive function was also significant (β = -0.149, p = .023) but was attenuated when physical function was included as a mediator (c'=-0.0100, p = .09). CONCLUSION: Physical function partially mediated the relationship between pain intensity and cognitive function and fully mediated the relationship between pain interference and cognitive function. Significance/Implications: Higher levels of pain intensity and interference may lead to worse cognitive function when physical function is also impaired. Improving physical function may improve cognitive function in those with 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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".