Personality Traits Impact Alcohol Consumption through Subjective Time
Bibliographic record
Abstract
We aimed to investigate (1) bivariate associations between alcohol use, time perspective, temporal competency, and personality traits; (2) the extent to which different temporal scales predicted alcohol use in order to select constructs most related to alcohol use; and (3) the most related temporalities as mediators between personality traits and alcohol use. French ( n = 389) and Canadian ( n = 478) college students responded to questionnaires online. Analyses included (1) correlations between measures; (2) three multiple regressions in which different sets of temporalities (ZTPI, TCT-5D, a combination of scales) predicted alcohol use; (2) five multiple parallel mediator models, in which one big-5 trait was entered as a distal factor leading to alchol use through the parallel mediators of temporalities. Most temporal dimensions were correlated with alcohol use and a unique set of personality traits. The combination of temporal scales (past negative, present hedonist, anticipation, temporal rupture) predicted alcohol use better than any other instrument. All personality traits explained alcohol use through different sets of temporalities. Cases of indirect only and competitive mediation were observed. Personality traits explained alcohol consumption through the multiple parallel mediators of temporalities. In some cases (neuroticism, openness and agreeableness) temporalities had to be taken into account in order to observe an effect of personality on alcohol use which helps explain inconsistencies in the literature. Future work may benefit from taking into account combinations of temporal dimensions in order to best explain (drinking) behaviors, including but not limited to the Zimbardo Time Perspective Inventory.
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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) | 0.000 | 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) | 0.318 | 0.157 |
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; both teacher heads agree on what is shown here.
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".