Evidence for working memory deficits in chronic pain: A systematic review and meta-analysis
Bibliographic record
Abstract
People with chronic pain commonly report impaired cognitive function. However, to date, there has been no systematic evaluation of the body of literature concerning cognitive impairment and pain. Nor have modern meta-analytical methods been used to verify and clarify the extent to which cognition may be impaired. The objective of this study was to systematically evaluate and critically appraise the literature concerning working memory function in people with chronic pain. The study was conducted along Cochrane collaboration and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement guidelines. A sensitive search strategy was designed and conducted with the help of an expert librarian using 6 databases. Twenty-four observational studies evaluating behavioural and/or physiological outcomes in a chronic pain group and a control group met the inclusion criteria. All studies had a high risk of bias, owing primarily to lack of assessor blinding to outcome. High heterogeneity within the field was found with the inclusion of 24 papers using 21 different working memory tests encompassing 9 different working memory constructs and 9 different chronic pain populations. Notwithstanding high heterogeneity, pooled results from behavioural outcomes reflected a consistent, significant moderate effect in favour of better performance by healthy controls and, with the exception of one study, pooled results from physiological outcomes reflected no evidence for an effect. Future research would benefit from the use of clearly defined constructs of working memory, as well as standardised methods of testing.
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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 | 0.012 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.025 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".