Parental and peer influences on emerging adult problem gambling: Does exposure to problem gambling reduce stigmatizing perceptions and increase vulnerability?
Bibliographic record
Abstract
Research has identified 18 to 30 years olds as the biggest spenders on gambling activities, with significantly higher prevalence of gambling problems than other age groups. Identifying the factors that influence the development of gambling problems in young people is important for guiding prevention strategies. This study aimed to analyse how emerging adult problem gambling is influenced by the people around them. In particular, we explored whether perceived parental and peer problem gambling predicted emerging adult problem gambling, and whether reduced gambling self-stigma mediated these relationships. A community sample of 188 Australian gamblers aged 18 to 29 (M = 21.41, SD = 2.99) completed three versions of the Problem Gambling Severity Index (PGSI) and the Gambling Perception Scale. Results indicated that perceived parental and peer gambling were positively related to emerging adult problem gambling. While reduced gambling helping stigma was related to higher problem gambling, stigma did not mediate the links between significant others' gambling and emerging adult problem gambling. We conclude that social influences are important in the development of problem gambling for young people, and that older male emerging adults who have a gambling mother are at most risk of problem gambling.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".