Trajectories of resilience over 25 years of individuals who as adolescents consulted for substance misuse and a matched comparison group
Bibliographic record
Abstract
AIMS: To examine trajectories of resilience over 25 years among individuals who as adolescents received treatment for substance misuse, the clinical sample (CS) and a matched general population sample (GP). DESIGN: Comparison of the CS and GP over 25 years using Swedish national registers of health care and criminality. SETTING: A substance misuse clinic for adolescents in an urban area in Sweden. MEASUREMENTS: Resilience was defined as the absence of substance misuse, hospitalizations for physical illnesses related to substance misuse, hospitalization for mental illness and law-abiding behaviour from ages 21 to 45 years. PARTICIPANTS: The CS included 701 individuals who as adolescents had consulted a clinic for substance misuse. The GP included 731 individuals selected randomly from the Swedish population and matched for age, sex and birthplace. FINDINGS: A total of 52.4% of the GP and 24.4% of the CS achieved resilience in all domains through 25 years. Among the CS, another one-third initially displayed moderate levels of resilience that rose to high levels over time, one-quarter displayed decreasing levels of resilience over time, while 9.3% showed little but improving resilience and 8.8% showed no resilience. Levels of resilience were associated with the severity of substance misuse and delinquency in adolescence. CONCLUSIONS: Individuals who had presented substance misuse problems in adolescence were less likely to achieve resilience over the subsequent 25 years than was a matched general population sample, and among them, four distinct trajectories of resilience were identified. The severity and type of problems presented in adolescence distinguished the four trajectories.
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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 | 0.000 | 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 | 0.001 |
| 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".