Childhood Mental Disorders and Subsequent Adverse Outcomes in Early Adulthood: A Population-Based Longitudinal Study
Bibliographic record
Abstract
IntroductionThe relationship between childhood/adolescent mental disorders and adult outcomes has been studied using surveys and clinical samples. These studies are prone to selection, recall and self-reporting biases. No previous studies have used population-based administrative databases linking individual-level data that could address these biases and further elucidate this relationship. Objectives and ApproachUsing de-identified administrative databases housed at the Manitoba Centre for Health Policy, we aimed to determine whether people diagnosed with mental disorders in childhood/adolescence, compared to those without, were at higher risk of early adverse adult outcomes. We created a birth cohort of 60,838 residents of Manitoba, Canada, born from fiscal years 1980/81 to 1984/85 and followed them to the end of study period in 2014/15. Through a scrambled health identifier, health, education, social services and justice system data were linked at an individual level. Survival analysis was used to test for differences controlling for key childhood covariates. ResultsWe found that 16.5% of the cohort had a diagnosed mental disorder at some point in their childhood/adolescence. Having a diagnosed mental disorder in childhood/adolescence increased the risk of being diagnosed with the same disorder in early adulthood (at age 30 to 34 years old). It also increased the risk of suicidal death (hazard ratio (HR): 2.41), suicide attempts (HR: 3.05), public housing use (HR: 1.44), income assistance use (HR: 2.07), criminal accusation (HR:1.53), and criminal victimization (HR:1.54) in adulthood. Similarly, but to a greater extent, suicide attempts in adolescence increased the risk of suicidal death (HR: 3.65), suicide attempts (HR: 5.68), public housing use (HR: 1.64), income assistance use (HR: 1.68), criminal accusation (HR: 2.18), or criminal victimization (HR: 2.43) in adulthood. Conclusion/ImplicationsYoung people’s mental health has significant influence on their health and well-being trajectories into adulthood. This knowledge could directly inform policy and practice to provide better population-based mental health promotion, prevention and early interventions for children/adolescents with mental disorders and subsequently prevent adverse adult outcomes in the future.
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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 | 0.003 |
| 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) | 0.001 | 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".