Chronic pain in adolescence and internalizing mental health disorders
Bibliographic record
Abstract
Chronic pain in childhood and adolescence has been shown to heighten the risk for depressive and anxiety disorders in specific samples in adulthood; however, little is known about the association between a wider variety of chronic pains and internalizing mental health disorders. Using nationally representative data, the objectives of this study were to establish prevalence rates of internalizing mental health disorders (anxiety and depressive disorders) among cohorts with or without adolescent chronic pain, and to examine whether chronic pain in adolescence is associated with lifetime history of internalizing mental health disorders reported in adulthood. Data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) was used (N = 14,790). Individuals who had chronic pain in adolescence subsequently reported higher rates of lifetime anxiety disorders (21.1% vs 12.4%) and depressive disorders (24.5% vs 14.1%) in adulthood as compared with individuals without a history of adolescent chronic pain. Multivariate logistic regression confirmed that chronic pain in adolescence was associated with an increased likelihood of lifetime history of anxiety disorders (odds ratio: 1.33; 95% confidence interval: 1.09-1.63, P = 0.005) and depressive disorders (odds ratio: 1.38; confidence interval: 1.16-1.64, P < 0.001) reported in adulthood. Future research is needed to examine neurobiological and psychological mechanisms underlying these comorbidities.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".