Physical function estimates change in pain following <scp>IIPT</scp> among children with chronic pain
Bibliographic record
Abstract
INTRODUCTION: Chronic pain can negatively impact a child's quality of life. Pediatric Intensive Interdisciplinary Pain Treatment (IIPT) programs aim to improve overall functioning despite pain through various rehabilitative strategies. It is, however, unclear whether improved function corresponds to self-reported decrease in pain levels. Hence, the purpose of this study is to examine the relationship between changes in physical function and perceived pain among children with chronic pain who have undergone inpatient IIPT. MATERIALS AND METHODS: A secondary analysis of pre-existing databases of IIPT from two different inpatient acute rehabilitation programs was carried out. Children and adolescents (N = 309; age = 16.2 ± 2.6; 79% females) with chronic pain who attended on average 4-week inpatient IIPT from Nov 2011 to Jan 2023 were included. Participants completed pain intensity (Numerical Pain Rating Scale) and self-reported function measures (Lower Extremity Functional Scale [LEFS], Upper Extremity Functional Index [UEFI], Canadian Occupational Performance Measure [COPM]-Performance, and COPM-Satisfaction) at admission and discharge. RESULTS: Change in self-reported physical function was significantly associated with change in pain from admission to discharge. After covariate adjustment, self-reported physical function (per the LEFS, UEFI, COPM-Performance, and COPM-Satisfaction) explained 19.8%, 7.8%, 12.0%, and 8.6% of the variance in change in pain, respectively. These measures of self-reported physical function further distinguished between minimal (<30%) and moderate (≥30%) pain reduction. CONCLUSIONS: Self-reported functional gains during IIPT are associated with greater change in perceived pain. Moreover, measures of self-reported physical function can help identify children at risk of minimal pain reduction post-IIPT.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".