A longitudinal examination of the interpersonal fear avoidance model of pain: the role of intolerance of uncertainty
Bibliographic record
Abstract
Youth with chronic pain and their parents face uncertainty regarding their diagnosis, treatment, and prognosis. Given the uncertain nature of chronic pain and high comorbidity of anxiety among youth, intolerance of uncertainty (IU) may be critical to the experience of pediatric chronic pain. This study longitudinally examined major tenets of the Interpersonal Fear Avoidance Model of Pain and included parent and youth IU as key factors in the model. Participants included 152 youth with chronic pain (Mage = 14.23 years; 72% female) and their parents (93% female). At baseline, parents and youth reported on their IU and catastrophic thinking about youth pain; youth reported on their fear of pain, pain intensity, and pain interference; and parents reported on their protective responses to child pain. Youth reported on their pain interference 3 months later. Cross-lagged panel models, controlling for baseline pain interference, showed that greater parent IU predicted greater parent pain catastrophizing, which, in turn, predicted greater parent protectiveness, greater youth fear of pain, and subsequently greater youth 3-month pain interference. Youth IU had a significant indirect effect on 3-month pain interference through youth pain catastrophizing and fear of pain. The results suggest that parent and youth IU contribute to increases in youth pain interference over time through increased pain catastrophizing, parent protectiveness, and youth fear of pain. Thus, parent and youth IU play important roles as risk factors in the maintenance of pediatric chronic pain over time and may be important targets for intervention.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".