A Comparison of Two Pain Measures for Asian American Cancer Patients
Bibliographic record
Abstract
Although two of the most commonly used multidimensional pain scales are the McGill Pain Questionnaire-Short Form (MPQ-SF) and the Brief Pain Inventory-Short Form (BPI-SF), there has been little psychometric analysis of these tools used among ethnic minority populations. The purpose of this study was to evaluate and compare psychometric properties of these two pain scales among 119 Asian American cancer patients. The Cronbach's alpha coefficients of the MPQ-SF and the BPI-SF were high (alpha = .85-.97). The correlation coefficients of the item analyses were .12 to .88 for the MPQ-SF and .44 to .90 for the BPI-SF. Two factors were extracted for both instruments. Correlations between pain scores and the usage of pain medications were low for the MPQ-SF (r = .23-.33) and moderate for the BPI-SF (r = .40-.42). The results of this study indicated that, among Asian Americans, both the pain scales were internally consistent; some items in each instrument were redundant; and the BPI-SF is more valid than the MPQ-SF.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".