Perceived social support according to the type and number of addictions
Bibliographic record
Abstract
BACKGROUND: Addiction is very closely related to social determinants. It can be an outcome of the excessive consumption pushed by society and be protected against by society's many positive dimensions. The main objectives of the present paper are to examine whether perceived social support (PSS) - the perceived availability of others to provide us assistance when needed - varies (a) according to different types of addiction (i.e., gambling, gaming, alcohol, cannabis, and nicotine), and (b) according to the presence of multiple addictions. METHODS: A sample of 5654 male emerging adults (mean age = 21.34 years old) completed a questionnaire that included a scale for measuring PSS and several screening tools used to identify addictive behaviors like gambling, gaming, and the consumption of alcohol, cannabis, or nicotine. RESULTS: Compared to a non-addicted control group and to peers with alcohol, cannabis or nicotine disorder, male emerging adults with gambling or gaming addiction reported the lowest levels of PSS. Moreover, these findings showed that PSS decreased among male emerging adults with multiple addictions. CONCLUSION: Our results suggest that young men with gambling and gaming disorders may be at a greater risk of social isolation and loneliness and, thus, of experiencing deteriorations in their physical and mental health.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".