Development and Initial Evaluation of the Patterns of Activity Measure—Pain Short Form
Bibliographic record
Abstract
OBJECTIVES: There has been growing interest in examining pain-related activity patterns and their relationships to psychosocial functioning. The Patterns of Activity Measure-Pain (POAM-P) is frequently used to measure 3 pain-related activity patterns: avoidance, overdoing, and pacing. Although the POAM-P possesses excellent psychometric properties, its length may limit its utility where multiple measures of functioning are required or the time available for assessment is limited. The present studies describe the development and evaluation of a short-form version of this measure. MATERIALS AND METHODS: In Study 1, 775 individuals with ongoing pain completed the original POAM-P at the start of a treatment program. Item analyses were conducted to construct a short-form of the POAM-P. In Study 2, a separate sample of 171 individuals completed the original and short-form of the POAM-P, and measures of psychosocial functioning. Correlations between the short-form and original, and between the short-form and measures of psychosocial functioning were examined to evaluate the reliability and validity of the short-form. RESULTS: The 3 scales of the short-form were found to have excellent internal consistency and correlated well with corresponding scales on the original POAM-P. Correlations between scales on the short-form and measures of psychosocial functioning supported the construct validity of the measure. DISCUSSION: The short-form of the POAM-P possesses good psychometric properties and correlates well with the long-form of the measure. It appears to be a promising addition to existing measures of pain-related activity. It may be useful as an addition to questionnaire batteries that comprehensively assess the psychosocial functioning of individuals with ongoing pain.
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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 | 0.010 | 0.018 |
| 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) | 0.002 | 0.001 |
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".