Pediatric Chronic Pain, Resilience and Psychiatric Comorbidity in Canada: A Retrospective, Comparative Analysis
Bibliographic record
Abstract
Objective Chronic pain compromises child and adolescent well-being and development. This study aimed to identify risk factors for chronic pain and exploration of how young people negotiate such risks and express resilience. We hypothesized children and youth with chronic pain would report greater prevalence of mental health disorders than the general population; and those demonstrating greater resilience would demonstrate less psychiatric comorbidity. Method A retrospective chart review was conducted for all patients (ages 7–17) attending the sole pediatric chronic pain clinic in Manitoba, from 2015 to 2019 (N = 116). Patients' demographic information and psychiatric illness burden were compared to provincial epidemiological data using Chi-Square tests. Pain sites, family history, psychiatric illness, psychosocial functioning, treatment history and treatment recommendations were explored. Results The sample was predominantly female (74%; N = 114). Sixty-eight percent of patients reported a family history of chronic pain. Thirty-seven percent of the patients (vs. 14.0% anticipated; N = 326 260) reported comorbid psychiatric disorder, X2 (1, N = 114) = 53.00, p < 0.001. Thirty-two percent reported diagnosis of mood and/or anxiety disorder (vs. 7.3%), X2 (1, N = 114) = 99.34, p < 0.001. Children and youth demonstrating resilience through engagement in more prosocial behaviors reported fewer psychiatric symptoms (rs = −0.292, N = 114, p = 0.002, Spearman's correlation). Conclusions Female sex, family history, and lower socioeconomic status were associated with chronic pain. Psychiatric conditions were more prevalent in chronic pain patients than in the general population. Approaching chronic pain from a mind-body perspective, while building on patients' strengths, is central to informing treatment.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".