The Fear of Pain Questionnaire – Short Form (FPQ-SF): Factorial validity and psychometric properties
Bibliographic record
Abstract
McNeil and Rainwater's Fear of Pain Questionnaire III (FPQ-III, 1998) is an empirically derived self-report inventory that assesses fear of three broad categories of pain: Severe, Minor, and Medical Pain. Previous exploratory and confirmatory factor analyses suggest that the original 3-factor model of the FPQ-III has a poor fit [Osman A, Breitenstein JL, Barrios FX, Gutierrez PM, Kopper BA. The Fear of Pain Questionnaire-III: further reliability and validity with nonclinical samples. J Behav Med 2002;25:155-73; Albaret MC, Sastre MTM, Cottensin A, Mullet E. The Fear of Pain Questionnaire: factor structure in samples of young, middle-aged and elderly European people. Eur J Pain 2004;8:273-81; Roelofs J, Peters ML, Deutz J, Spijker C, Vlaeyen JWS. The Fear of Pain Questionnaire (FPQ): further psychometric examination in a non-clinical sample. Pain 2005;116:339-46.]. The goals of this study were to empirically evaluate the previously proposed 3-factor models of the FPQ-III, identify and remove items that contribute to the factor instability of the FPQ-III, and evaluate potential alternative models based on a reduced item pool. A sample of 589 participants from the University of Regina and the University of Manitoba communities was randomly divided into two subsamples of approximately equal size. FPQ-III data from these subsamples were subjected to confirmatory factor analysis and an iterative combination of exploratory and confirmatory factor analyses. The initial confirmatory factor analysis revealed that none of the previous models had acceptable fit to the data. Following iterative factor analyses and item reductions, a 4-factor model with good fit to the data and invariance across gender was identified. This model comprised 20-items distributed on factors representing Severe, Minor, Injection, and Dental Pain. The total scale and subscale scores based on the 4-factor model had good internal consistency, and preliminary support for construct validity was obtained. Use of this short version of the measure--the FPQ-Short Form--is discussed and directions for future research outlined.
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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 | 0.015 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".