Substance Use in Young Swiss Men: The Interplay of Perceived Social Support and Dispositional Characteristics
Bibliographic record
Abstract
BACKGROUND: Social environment plays a central role in substance use behaviors. However, it is not clear whether its role varies as a function of individual dispositional characteristics. OBJECTIVES: To investigate the interaction between dispositional characteristics (i.e. sensation seeking, anxiety/neuroticism) and social environment (i.e. perceived social support [PSS]) in association with substance use. METHODS: A representative sample of 5,377 young Swiss males completed a questionnaire assessing substance use, sensation seeking, anxiety/neuroticism, and PSS from friends and from a significant other. RESULTS: Sensation seeking and anxiety/neuroticism were positively related to most substance use outcomes. PSS from friends was significantly and positively related to most alcohol and cannabis use outcomes, and significantly and negatively associated with the use of hard drugs. PSS from a significant other was significantly and negatively associated with most alcohol and cannabis use outcomes. The associations of sensation seeking with drinking volume, alcohol use disorder and the use of illicit drugs other than cannabis were stronger in individuals reporting high levels of PSS from friends than those with low levels. The associations of sensation seeking with risky single-occasion drinking and the use of hard drugs were weaker in participants reporting high levels of PSS from a significant other than in those with low levels. CONCLUSIONS: Sensation seeking and anxiety/neuroticism may constitute risk factors for substance use and misuse. PSS from friends may amplify the risk for alcohol and illicit drug use (other than cannabis) associated with high sensation seeking, whereas the PSS from a significant other may reduce it.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".