Identifying Patterns of Alcohol Use and Obesity‐Related Factors Among Emerging Adults: A Behavioral Economic Analysis
Bibliographic record
Abstract
Background Although heavy alcohol consumption and maladaptive eating behaviors have been shown to co‐occur among college students, less is known about the co‐occurrence of these behaviors in a more diverse community‐dwelling, emerging adult sample. The purpose of this study was to: (i) identify classes of emerging adults by their reported alcohol consumption patterns, food addiction symptoms, and body mass index; and (ii) determine whether these classes differed on indices of behavioral economic reinforcer pathology (e.g., environmental reward deprivation, impulsivity, alcohol demand). Method Emerging adult participants were recruited as part of a study on risky alcohol use ( n = 602; 47% white, 41.5% Black; mean age = 22.63, SD = 1.03). Participants completed questionnaires on alcohol and food‐related risk factors and underwent anthropometric assessment. Results Latent profile analysis suggested a four‐profile solution: a moderate alcohol severity, overweight profile (Profile 1; n = 424, 70.4%), a moderate alcohol severity, moderate food addiction + obese profile (Profile 2; n = 93, 15.4%), a high alcohol severity, high food addiction + obese profile (Profile 3; n = 44, 7.3%), and a high alcohol severity, overweight profile (Profile 4; n = 41, 6.8%). Individuals in Profile 1 reported significantly lower levels of environmental reward deprivation than either Profile 2 or 3, and participants in Profile 3 reported significantly higher environmental reward deprivation than those in Profile 4 ( p < 0.001). Profile 4 demonstrated significantly higher alcohol demand intensity and O max and lower demand elasticity than Profile 1, Profile 2, or Profile 3. Profile 4 also demonstrated significantly greater proportionate substance‐related reinforcement than Profile 1 ( p < 0.001) and Profile 2 ( p = 0.004). Conclusion Maladaptive eating patterns and alcohol consumption may share common risk factors for reinforcer pathology including environmental reward deprivation, impulsivity, and elevated alcohol demand.
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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 | 0.000 |
| 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".