Problem gambling, risk behaviours, and mental health in adolescence: A person oriented study
Bibliographic record
Abstract
Adolescent gambling is becoming a public health problem. While comorbidities with other externalizing behaviours have been ascertained, few studies focus on adolescents with a multi-problem behaviour pattern, i.e., alcohol and tobacco use, in addition to antisocial behaviour, which includes problem gambling. The purpose of this study was to identify adolescents with multi-problem behaviours, i.e., alcohol abuse, daily smoking, antisocial behaviour, and problem gambling and to investigate the differences in relation to gender. Unlike most studies on this topic, we adopted a person-oriented approach to identify groups of adolescent boys and girls who reported multi-problem risk behaviours, i.e., alcohol abuse, daily smoking, antisocial behaviour, and problem gambling. Moreover, we explored to what extent these adolescents exhibited mental health problems, i.e., depressive, psychosomatic, and ADHD symptoms, as well as sleep problems. The sample consisted of 1,526 adolescents from two age cohorts, 15- to 16-year-olds (n = 711, 47%) and 17- to 18-year-olds (n = 815, 53%). Latent Variable Mixture Modeling (LVMM) revealed one group with low rates of all risk behaviours and three groups with multi-problem behaviours. Among the latter three groups, two reported problem gambling and had higher levels of mental health problems. These results suggest that gambling can be added to the constellation of risk behaviours in adolescence and might be more associated with mental health problems than other externalizing behaviours.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".