Geriatric Pain Measure Short Form: Development and Initial Evaluation
Bibliographic record
Abstract
OBJECTIVES: To develop and evaluate a short form of the 24-item Geriatric Pain Measure (GPM) for use in community-dwelling older adults. DESIGN: Derivation and validation of a 12-item version of the GPM in a European and an independent U.S. sample of community-dwelling older adults. SETTING: Three community-dwelling sites in London, United Kingdom; Hamburg, Germany; Solothurn, Switzerland; and two ambulatory geriatrics clinics in Los Angeles, California. PARTICIPANTS: European sample: 1,059 community-dwelling older persons from three sites (London, UK; Hamburg, Germany; Solothurn, Switzerland); validation sample: 50 persons from Los Angeles, California, ambulatory geriatric clinics. MEASUREMENTS: Multidimensional questionnaire including self-reported demographic and clinical information. RESULTS: Based on item-to-total scale correlations in the European sample, 11 of 24 GPM items were selected for inclusion in the short form. One additional item (pain-related sleep problems) was included based on clinical relevance. In the validation sample, the Cronbach alpha of GPM-12 was 0.92 (individual subscale range 0.77-0.92), and the Pearson correlation coefficient (r) between GPM-12 and the original GPM was 0.98. The correlation between the GPM-12 and the McGill Pain Questionnaire was 0.63 (P<.001), similar to the correlation between the original GPM and the McGill Pain Questionnaire (Pearson r=0.63; P<.001). Exploratory factor analysis indicated that the GPM-12 covers three subfactors (pain intensity, pain with ambulation, disengagement because of pain). CONCLUSION: The GPM-12 demonstrated good validity and reliability in these European and U.S. populations of older adults. Despite its brevity, the GPM-12 captures the multidimensional nature of pain in three subscales. The self-administered GPM-12 may be useful in the clinical assessment process and management of pain and in pain-related research in older persons.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".