Do “central sensitization” questionnaires reflect measures of nociceptive sensitization or psychological constructs? A systematic review and meta-analyses
Bibliographic record
Abstract
ABSTRACT: Central sensitization (CS) is defined as an increased nociceptive responsiveness due to sensitization of neurons in the central nervous system, usually the result of prolonged nociceptive input or a disease state associated with noxious inputs (eg, polyarthritis). The concept of CS has recently been adopted in clinical assessments of chronic pain, but its diagnosis in humans may now include a wide range of hypervigilant responses. The purpose of this review is to ascertain whether self-report questionnaires linked with CS are associated with enhanced nociceptive responses or whether they measure sensitivity in a broader sense (ie, emotional responses). According to our published, PROSPERO-registered review protocol (CRD42021208731), a predefined search of studies that involve the Central Sensitization Inventory (CSI) or Pain Sensitivity Questionnaire (PSQ), correlated with either nociceptive sensory tests or emotional hypervigilance was conducted on MEDLINE, PsycINFO, and Web of Science. Correlations between the CSI or PSQ with our primary outcomes were extracted and meta-analysed. A review of 66 studies totalling 13,284 participants found that the CSI (but not the PSQ) strongly correlated with psychological constructs: depression, anxiety, stress, pain catastrophising, sleep, and kinesiophobia. The CSI and PSQ showed weak or no correlations with experimental measures of nociceptive sensitivity: pain thresholds, temporal summation, or conditioned pain modulation. The PSQ did, however, correlate strongly with phasic heat and tonic cold pain tests. The studies reviewed did not provide sufficient evidence that self-report measures reflect a canonical understanding of CS. The CSI more closely reflects psychological hypervigilance than increased responsiveness of nociceptive neurons.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".