Psychometric properties of the brief pain inventory modified for proxy report of pain interference in children with cerebral palsy with and without cognitive impairment
Bibliographic record
Abstract
Abstract Introduction: Cerebral palsy (CP) is the most common cause of physical disability in children and is often associated with secondary musculoskeletal pain. Cerebral palsy is a heterogeneous condition with wide variability in motor and cognitive capacities. Although pain scales exist, there remains a need for a validated chronic pain assessment tool with high clinical utility for use across such a heterogeneous patient population with and without cognitive impairment. Objectives: The purpose of this study was an initial assessment of several psychometric properties of the 12-item modified brief pain inventory (BPI) pain interference subscale as a proxy-report tool in a heterogeneous sample of children with CP with and without cognitive impairment. Methods: Participants (n = 167; 47% male; mean age = 9.1 years) had pain assessments completed through caregiver report in clinic before spasticity treatment (for a subgroup, the modified BPI was repeated after procedure). To measure concurrent validity, we obtained pain intensity ratings (Numeric Rating Scale of pain) and pain intensity, duration, and frequency scores (Dalhousie Pain Interview). Results: Modified BPI scores were internally consistent (Cronbach α = 0.96) and correlated significantly with Numeric Rating Scale intensity scores (rs = 0.67, P < 0.001), Dalhousie Pain Interview pain intensity (rs = 0.65, P < 0.001), pain frequency (rs = 0.56, P = 0.02), and pain duration scores (rs = 0.42, P = 0.006). Modified BPI scores also significantly decreased after spasticity treatment (pretest [scored 0–10; 3.27 ± 2.84], posttest [2.27 ± 2.68]; t (26) = 2.14, 95% confidence interval [0.04–1.95], P = 0.04). Conclusion: Overall, the modified BPI produced scores with strong internal consistency and that had concurrent validity as a proxy-report tool for children with CP.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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 | 0.000 | 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".