Unique and Transdiagnostic Dimensions of Reward Functioning in Attention-Deficit/Hyperactivity Disorder and Alcohol Use Disorder Symptoms
Bibliographic record
Abstract
AIMS: Contemporary theories of attention-deficit/hyperactivity disorder (ADHD) and alcohol use disorder (AUD) emphasize core dysfunctions in reward-related processes and behaviors as pathognomonic characteristics. However, to date, it is unclear which domains of reward functioning are unique to ADHD versus AUD symptom dimensions, and which represent underlying shared correlates. METHODS: The current study employed secondary data analyses from a large community sample of emerging adults (N = 602; 57.3% female) and novel transdiagnostic modeling (i.e. bi-factor confirmatory factor analyses and structural equation modeling) of ADHD, AUD and shared symptom dimensions to identify unique and common reward-related dimensions: environmental suppressors, reward probability, hedonic capacity, proportionate substance-related reinforcement and delay discounting. RESULTS: The presence of environmental suppressors was the only reward-related construct that correlated with the underlying ADHD-AUD shared dimension. The AUD symptom dimension was uniquely associated with proportionate substance-related reinforcement, whereas the ADHD symptom dimension was uniquely associated with limited reward probability. No significant associations were found for delay discounting or hedonic capacity. CONCLUSIONS: These novel findings highlight specific aspects of reward-related functioning in ADHD, AUD and shared symptom dimensions. In so doing, this work meaningfully advances theoretical conceptualizations of these two commonly co-occurring presentations and suggests future directions for research on transdiagnostic correlates. Future longitudinal studies should include clinical samples with diagnoses of AUD and ADHD to further identify underlying correlates over time.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".