A Prospective Study of Mental Health in Relation to Online Gambling One-year Later in a Large Cohort of Adolescents in Canada
Bibliographic record
Abstract
PURPOSE: Concerns have increased about online gambling among adolescents. Poor mental health may place adolescents at increased risk of engagement in online gambling, however, longitudinal evidence is limited. The purpose of this study was to examine how mental health relates to engagement in online gambling one-year later in a large cohort of adolescents. METHODS: We used 2-year prospective survey data from 26,818 students in Grades 9 to 11 (secondary III-IV in Quebec) attending 121 secondary schools in four Canadian provinces (Alberta, British Columbia, Ontario, and Quebec) who participated in the COMPASS study during the 2017/18, 2018/19, and/or 2019/20 school years. Generalized linear mixed models were used to examine the likelihood of online gambling one-year later by baseline mental health outcomes (depressive symptoms, anxiety symptoms, psychosocial well-being, emotional dysregulation), controlling for student sex, grade, race, weekly spending money, and baseline online gambling. RESULTS: Online gambling in the past 30-days was reported by 2.1%, 2.3%, and 2.5% of students in study years 2017/18, 2018/19, and 2019/20, respectively. In the combined model, students reporting high depressive symptoms were significantly more likely to report online gambling one-year later (OR = 1.58, 95%CI = 1.19, 2.09) relative to those reporting low symptoms, controlling for baseline online gambling, the other mental health measures, and sociodemographic characteristics. CONCLUSION: This study provides prospective evidence that high depressive symptoms may place adolescents at an elevated risk of future engagement in online gambling. It may be worthwhile targeting students with high depressive symptoms in preventative efforts.
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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) | 0.001 | 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 | 0.000 |
| 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".