Stability and change of psychopathology symptoms among youth with chronic physical illness: A latent transition analysis
Bibliographic record
Abstract
BackgroundThis study examined whether youth transition between different mental health symptom profiles over time, and what factors predict these transitions. Understanding the stability and change in psychopathology helps discern whether certain behaviours are temporary or signs of persistent problems.MethodsData were drawn from a longitudinal study of 263 youth (ages 2-16) with chronic physical illness and their parents, assessed at baseline (T1), six months (T2), 12 months (T3), and 24 months (T4). Parents reported on youth psychopathology using the Emotional Behavioural Scales (EBS). Latent profile analysis identified psychopathology profiles, and latent transition analysis quantified the probability that youth remained or moved between groups over time.ResultsFour profiles were identified: low psychopathology (LP), primarily internalizing (PI), primarily externalizing (PE), and high psychopathology (HP). Homotypic continuity (i.e., remaining in the same profile over time) was lower for the PI, PE, and HP subgroups. Youth in the PI subgroup were more likely to transition to the LP, while those in HP showed greater stability, with many remaining in the high-symptom groups. Child age, parent psychopathology, and parent education significantly predicted profile transitions.ConclusionsMost youth showed changes in their mental health over time, but a small proportion with HP (<5%) had more persistent problems. Results demonstrate the need for early identification and intervention for youth at risk of chronic mental health difficulties.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".