Trajectories of medical service use among girls and boys with and without early-onset conduct problems
Bibliographic record
Abstract
Background: Children with conduct problems (CP) have been found to be heavy and costly medical service users in adulthood. However, there is little knowledge on how medical service use develops during childhood and adolescence among youth with and without childhood CP. Knowing whether differences in developmental trajectories of medical service use for specific types of problems (e.g., injuries) are predicted by childhood CP would help clinicians identify developmental periods during which they might intensify interventions for young people with CP in order to prevent later problems and associated increased service use. Methods: Participants were drawn from an ongoing longitudinal study of boys and girls with and without childhood CP as rated by parents and teachers. Medical service use was assessed using administrative data from a public single payer health plan. Latent growth modeling was used to estimate the mean trajectory of four types of medical visits (psychiatric, injury-related, preventative, total visits) across time and evaluate the effect of CP and other covariates. Results: Support the hypothesis that early CP predicts higher medical service use at nine years old, and that this difference persists in a chronic manner over time, even when controlling the effects of ADHD and family income. Girls had fewer medical visits for psychiatric reasons than boys at baseline, but this difference diminished over time. Conclusions: Clinicians should be aware that childhood CP already predicts increased medical service use in elementary school. Issues specific to different contexts in which injuries might occur and sex differences are discussed.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".