The Co-occurrence of Pediatric Chronic Pain and Depression
Bibliographic record
Abstract
OBJECTIVES: Internalizing mental health issues co-occur with pediatric chronic pain at high rates and are linked to worse pain and functioning. Although the field has prioritized anxiety and posttraumatic stress disorder, little is known about co-occurring depression and chronic pain in youth, despite its high prevalence. The purpose of this narrative review was to examine the existing literature on the co-occurrence of pediatric chronic pain and depressive disorders and symptoms and propose a conceptual model of mutual maintenance to guide future research. METHODS: The literature from both fields of pediatric pain and developmental psychology were searched to review the evidence for the co-occurrence of pediatric chronic pain and depression. Conceptual models of co-occurring mental health issues and chronic pain, as well as child depression, were reviewed. From both literatures, we provide evidence for a number of proposed child, parent, and neurobiological factors that may serve to mutually maintain both conditions over time. On the basis of this evidence, we propose a conceptual model of mutual maintenance and highlight several areas for future research in this area. RESULTS: Evidence was found for the prevalence of depression in pediatric chronic pain as well as the co-occurrence of both conditions. The key mutually maintaining factors identified and proposed included neurobiological, intrapersonal (eg, cognitive biases, sleep disturbances, emotion regulation, and behavioral inactivation), and interpersonal (eg, parent mental health and pain, genes, and parenting) factors. DISCUSSION: Given the dearth of research on mutual maintenance in this area, this review and conceptual model could drive future research in this area. We argue for the development of tailored treatments for this unique population of youth to improve outcomes.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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 | 0.000 |
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".