Psychopathic Traits, Substance Use, and Motivation to Change: An Integrative Approach with Juvenile Offenders
Bibliographic record
Abstract
This study investigated the relationship between psychopathy and substance use (SU) and their interaction with motivation to change in predicting risk.Fifty-five adolescent offenders who admitted to using drugs or alcohol at least one time before their index offense were recruited from a south-eastern U.S. detention centre/court.Results indicated that psychopathy was related to a younger age of SU onset and increased severity of SU.However, this relationship appeared to be dependent on the self-report measure of psychopathy used.Psychopathy was only related to increased risk when motivation to change was low, even after controlling for the main effect of SU onset.These results offer initial support that psychopathy, SU, and motivation can be used as part of an integrative approach when working with juvenile offenders.However, more research is needed before such an approach can be used to inform long-term risk predictions or in planning specific treatment plans.PSYCHOPATHY, SUBSTANCE USE, AND MOTIVATION iii Dedication This thesis is dedicated to my mother for her outstanding support and love throughout my life.1. Have you ever ridden in a CAR driven by someone (including
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| 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".