Reliability and Validity of the Global Pain Scalewith Chronic Pain Sufferers
Bibliographic record
Abstract
BACKGROUND: Many pain scales exist today; however, a comprehensive, easy-to-analyze test has yet to be available to evaluate a patient's pain and understand the sociocultural, cognitive, and affective factors contributing to a patient's overall pain experience. Many scales have attempted to create an all-encompassing pain assessment but remain incomplete in their assessment of pain and the contributing aspects of pain. OBJECTIVE: To present the Global Pain Scale (GPS) as an alternative to current pain assessments and evaluate the reliability and construct validity of the GPS. METHODS: Two hundred sixty-two undergraduates with chronic pain at a large midwestern university participated in this survey study. Participants reported in which of 14 specific body regions they have pain, the frequency of pain, and treatment history for their pain. Participants completed 4 scales--GPS, the West Haven Yale Scale (WHY), the Perceived Stress Scale (PSS), and the short form McGill (SF-MPQ)--in a randomized order. RESULTS: The GPS demonstrated high criterion validity and high construct validity (including both convergent and discriminant validity). The total GPS scale and each of the subscales were reliable. The total GPS score was significantly correlated with all other subscales, excluding those for which there is a theoretical reason for them to not be correlated with our participant population. LIMITATIONS: A sample of college students was used, thus decreasing the generalizability of these findings to patients approximating our sample. CONCLUSIONS: The GPS is a valid scale that is concise and easily interpreted. The GPS is a comprehensive assessment of pain evaluating pain, emotions, clinical outcomes, and daily activities. This may be a valuable tool for evaluation and treatment planning for interventional pain management physicians.
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".