Adolescent pain: appraisal of the construct and trajectory prediction-by-symptom between age 12 and 17 years in a Canadian twin birth cohort
Bibliographic record
Abstract
ABSTRACT: Adolescent pain is common and continues into adulthood, leading to negative long-term outcomes including substance-related morbidity: an empirical definition of its construct may inform the early detection of persistent pain trajectories. These secondary analyses of a classical twin study assessed whether headaches, back pains, abdominal pain, chest pains, stabbing/throbbing pain, and gastric pain/nausea, measured in 501 pairs across 5 waves between age 12 and 17 years, fit a unitary construct or constitute independent manifestations. We then assessed which symptoms were associated with a steady, "frequent pain" trajectory that is associated with risk for early opioid prescriptions. Item response theory results indicated that all 6 pain symptoms index a unitary construct. Binary logistic regressions identified "back pain" as the only symptom consistently associated with membership in the "frequent adolescent pain" trajectory (odds ratio: 1.66-3.38) at all 5 measurement waves. Receiver operating characteristic analyses computed the discriminating power of symptoms to determine participants' membership into the "frequent" trajectory: they yielded acceptable (0.7-0.8) to excellent (0.8-0.9) area under the curve values for all 6 symptoms. The highest area under the curve was attained by "back pain" at age 14 years (0.835); for multiple cut-off thresholds of symptom frequency, "back pain" showed good sensitivity/false alarm probability trade-offs, predominantly in the 13 to 15 years age range, to predict the "frequent pain" trajectory. These data support a unitary conceptualization and assessment of adolescent pain, which is advantageous for epidemiological, clinical, and translational purposes. Persistent back pain constitutes a sensitive indicator of a steady trajectory of adolescent pain.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".