A Preliminary Investigation of a Conceptual Model Describing the Associations Between Childhood Maltreatment and Alcohol Use Problems
Bibliographic record
Abstract
Background/Objectives: Childhood maltreatment has been linked to numerous adverse outcomes in adulthood, including problem substance use. However, not all individuals exposed to childhood maltreatment develop substance use problems, indicating the role of other factors in influencing this outcome. Past work suggests that adverse early life experiences, including childhood maltreatment, lead to neurobiological changes in frontolimbic functions that, in turn, result in altered stress and reward responses, heightened impulsivity, affect dysregulation, and, ultimately, increased risk for maladaptive behaviors such as substance use. The aim of this preliminary investigation using cross-sectional data was to test associations between these factors in the relationship between childhood maltreatment and alcohol use problems in a sample of emerging adults. Methods: Emerging adults (18–30 years old) who identified as regular drinkers (i.e., drinking at least 2–4 times in the past month) were recruited from a crowd-sourcing platform (Prolific) as well as community samples. Participants completed online standardized questionnaires assessing reward sensitivity and responsiveness, impulsivity, emotion regulation, and alcohol consequences. Results: Path analyses demonstrated good fit for the data (SRMR = 0.057, RMSEA = 0.096, 90% CI [0.055, 0.142], CFI = 0.957). Childhood maltreatment was associated with reward responsiveness (β = −0.026, Z = −4.222, p < 0.001) and emotion dysregulation (β = 0.669, Z = 9.633, p < 0.001), which in turn was associated with urgency and, subsequently, alcohol consequences (β = 0.758, Z = 7.870, p < 0.001). Conclusions: Although these findings are preliminary, the current study is one of the first to test a comprehensive model addressing the relationship between childhood maltreatment and alcohol use problems. The findings have the potential to inform treatment strategies that target motivation and goal-directed action for reducing and managing consequences associated with childhood maltreatment. Future research should test the model using longitudinal data to address the limitations of a cross-sectional study and assess temporal associations between constructs.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".