Latent Profile Analysis of Heavy Episodic Drinking in Emerging Adults: A Reinforcer Pathology Approach
Bibliographic record
Abstract
BACKGROUND: Heavy episodic drinking (HED) is a major public health problem among emerging adults (individuals 18 to 25), but with considerable heterogeneity in concurrent substance use and psychopathology. The current study used latent profile analysis (LPA) to detect discrete subgroups of HED based on alcohol, other drug severity, and concurrent psychopathology. A reinforcer pathology approach was used to understand motivational differences among the latent subgroups. METHODS: Participants were 2 samples of emerging adults reporting regular HED, 1 Canadian (n = 730) and 1 American (n = 602). Indicators for the LPA were validated dimensional self-report assessments of alcohol severity, cannabis severity, other drug severity, nicotine dependence, depression, anxiety, posttraumatic stress disorder, and attention-deficit/hyperactivity disorder. Reinforcer pathology indicators were measures of alcohol demand, proportionate substance-related reinforcement, and discounting of future rewards. RESULTS: The LPA yielded parallel 3-class solutions in both samples. The largest subgroup was characterized by comparatively low substance severity and psychopathology (Low overall severity). The second largest subgroup was characterized by comparatively high alcohol and other drug severity (excluding tobacco) and high levels of psychopathology (Heavy alcohol & high psychiatric severity). The third subgroup exhibited high alcohol, smoking and intermediate levels of other substance use and psychopathology (Heavy alcohol, smoking, & intermediate psychiatric severity). The Heavy alcohol & high psychiatric severity and Heavy alcohol, smoking, & intermediate psychiatric severity subgroups exhibited significantly higher alcohol demand, greater proportionate substance-related reinforcement, and steeper delay discounting. CONCLUSIONS: Parallel latent subgroups of emerging adults engaging in HED were present in both samples, and the high-risk subgroups were significantly differentiated by the reinforcer pathology indicators. These latent profiles may ultimately inform heterogeneity in the longitudinal course of HED in emerging adults.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".