The 3-year effects of a personality-targeted prevention program on general and specific dimensions of psychopathology
Bibliographic record
Abstract
This study aimed to examine the effect of a personality-targeted prevention program (Preventure) on trajectories of general and specific dimensions of psychopathology from early- to mid-adolescence. Australian adolescents (N = 2190) from 26 schools participated in a cluster randomized controlled substance use prevention trial. This study compared schools allocated to deliver Preventure (n = 13 schools; n = 466 students; Mage = 13.42 years), a personality-targeted selective intervention, with a control group (n = 7 schools; n = 235 students, Mage = 13.47 years). All participants were assessed for psychopathology symptoms at baseline, 6-, 12-, 24- and 36-months post-baseline. Outcomes were a general psychopathology factor and four specific factors: fear, distress, alcohol use/harms and conduct/inattention), extracted from a higher-order model. Participants who screened as ‘high-risk’ on at least one of four personality traits (negative thinking, anxiety sensitivity, impulsivity and sensation seeking) were included in intention-to-treat analyses. Intervention effects were examined using multi-level mixed models accounting for school-level clustering. Among high-risk adolescents, growth in general psychopathology was slower in the Preventure group compared to the control group (b = −0.07, p = 0.038) across the three years. After controlling for effects on general psychopathology, there were no significant, additional effects on the lower order factors. This study provides evidence for the effectiveness of a selective personality-targeted intervention in altering trajectories of general psychopathology during adolescence. This finding represents impacts on multiple symptom domains and highlights the potential for general psychopathology as an intervention target.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".