Do Adverse Childhood Experiences Impact Adult Emotional Regulation and Interpersonal Functioning among Individuals Convicted of Sexual Offences? Implications for Assessment, Treatment, and Prevention
Bibliographic record
Abstract
Adverse childhood experiences (ACEs) are well-known risk factors for poor physical and mental health outcomes. The purpose of this study was to explore the relationship between ACEs and self-report measures of emotional regulation and interpersonal functioning among a sample of individuals provincially incarcerated for sexual offending. In total, 112 males participating in an in-custody sexual offender treatment program completed the study measures. Two-stage hierarchical linear regression was used to examine the association between cumulative ACE scores and each self-report measure. Individual ACE item impacts were also explored using two-stage hierarchical regression. Higher cumulative ACE scores were associated with greater emotional dysregulation and multiple indices of interpersonal dysfunction. Several ACE items were consistently associated with greater emotional and interpersonal difficulties. The findings have clinical implications for sexual offender assessment, treatment, and prevention. Specifically, the findings support a growing movement towards trauma-informed practice, incorporating attachment theory and intimacy-based interventions, and promoting empirically supported interventions for cultivating emotional self-regulation.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".