Trajectories of pain and anxiety in a longitudinal cohort of adolescent twins
Bibliographic record
Abstract
BACKGROUND: Adolescence is critical to intercept chronic/persistent pain and decipher its association with anxiety. We ascertained adolescent pain trajectories, their demographic and clinical correlates, the longitudinal association with opiate prescriptions at age 19, and the etiology of the covariation between adolescent pain problems and anxiety symptoms. METHODS: Longitudinal assessment of: 6 common pain problems at age 12, 13, 14, 15, and 17 years; 7 common anxiety symptoms at age 12, 13, and 14 years; opiates' prescriptions at age 19, in the Quebec Newborn Twin Study birth cohort of 667 twin pairs born between 1995-1998. RESULTS: : 5.45; CI: 2.67-11.11), the female sex (OR: 3.69; CI: 2.20-6.21), and lower socioeconomic status (OR: 0.87; CI: 0.77-0.98) were associated with the "frequent" compared to the "none-to-minimal" pain trajectory. Only the "frequent" pain trajectory predicted opioid prescriptions at age 19 (OR: 4.14; CI: 1.16-14.55). A twin bivariate latent growth curve model and a cross-lagged model showed that genetic factors and non-shared environmental factors common to both phenotypes influence the longitudinal association between anxiety and adolescent pain problems. CONCLUSIONS: The relatively common, adolescent "frequent pain" trajectory predicts early opioid prescriptions, and anxiety and adolescent pain share multiple etiological components. These data can inform diagnostic reasoning, clinical practice, and help reducing opioid prescriptions and abuse.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".