Do trait anticipatory processing, self-focused attention, and post-event processing explain the relationship between social anxiety and negative drinking motives in undergraduates?
Bibliographic record
Abstract
Despite an established relationship between social anxiety (SA) and negative reinforcement drinking motives (NRDMs), relatively little is known about the factors that explain this relationship. This study explored whether three processes implicated in cognitive models of SA (anticipatory processing, self-focused attention, and post-event processing) mediated the relationship between SA and NRDMs in undergraduates. Participants (N = 180) completed self-report measures of social interaction and evaluation anxiety, anticipatory and post-event processing, self-focused attention, drinking motives, and depression. Analyses were conducted using parallel multiple-mediation analyses, which employed bootstrapping tests of significance. Most notably, results showed that the relationships between interaction/evaluation anxiety and drinking to cope with anxiety were explained by trait tendency to experience anticipatory processing and self-focused attention. The relationship between interaction anxiety and drinking to cope with depression was also explained by a tendency to engage in self-focused attention. Conversely, evaluation anxiety directly predicted drinking to cope with depression, while both interaction and evaluation anxiety directly predicted drinking to conform to peers. Overall, these findings further elucidate these relationships by suggesting that anticipatory processing and self-focused attention, but not post-event processing, explain the relationship between SA and drinking to cope with negative affect. Alternatively, these cognitive processes do not appear relevant to SA and conformity-motivated drinking.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".