Development and validation of the perceived approval of Risky Drinking Inventory in undergraduate students.
Bibliographic record
Abstract
OBJECTIVE: Undergraduates frequently engage in risky drinking (i.e., drinking alcohol in ways that may result in problems). The reasoned action approach identifies injunctive norms (i.e., perceptions that others approve of risky drinking) as central in predicting engagement in risky drinking. However, research linking injunctive norms and risky drinking is equivocal, possibly because of extensive variability in the operationalization of injunctive norms across studies. This study describes the development and validation of the Perceived Approval of Risky Drinking Inventory (PARDI), designed according to best practice guidelines in questionnaire development. METHOD: = 875). RESULTS: Exploratory and confirmatory factor analyses supported a 20-item four-factor solution (Heavy Drinking, Drinking-Related Problems, Coping-Related Drinking, and Sexual-Risk Taking) across the three assessed referent groups (friends, parents, and typical students), all of which present satisfactory estimates of scale score and composite reliability. The results also provided preliminary support for the convergent validity of scores obtained on the PARDI, as demonstrated through correlations with other measures of perceived norms, alcohol use, alcohol-related problems, and coping-motivated drinking. Finally, the results supported the generalizability of the PARDI factor structure by demonstrating its measurement invariance across gender and drinking status (i.e., alcohol use and problems). CONCLUSIONS: The PARDI represents a reliable, valid, yet nuanced measure of injunctive norms that can be used to support further theory development and intervention. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".