Conduct problems and depressive symptoms in association with problem gambling and gaming: A systematic review
Bibliographic record
Abstract
BACKGROUND AND AIMS: Behavioral addictions such as gambling and gaming disorder are significant public health issues that are of increasing importance to policy makers and health care providers. Problem gambling and gaming behaviors have been identified as being associated with externalizing and internalizing problems, with theoretical models suggesting that both conduct problems and depressive symptoms may be significant risk factors in the development of problem gambling and gaming. As such, the purpose of this systematic review is to provide an overview of research identifying the relationship between conduct problems, depressive symptoms and problem gambling and gaming among adolescents and young adults. METHODS: Systematic literature searches in accordance with PRISMA guidelines found 71 eligible studies that met the inclusion criteria, 47 for problem gambling, 23 for problem gaming and one for both problem behaviors. RESULTS: Based on cross-sectional evidence, both problem gambling and gaming are consistently concurrently associated with conduct problems and depressive symptoms. Longitudinal evidence appears to be clearer for conduct problems as a risk factor for problem gambling, and depressive symptoms as a risk factor for problem gaming. However, both risk factors appear to increase the risk for these problem behaviors. DISCUSSION AND CONCLUSIONS: Results from the literature review suggest that problem gambling and gaming are associated with the presence of conduct problems and depressive symptoms, with the potential of sharing common etiological factors. Additional research is necessary to confirm these longitudinal relationships with an emphasis on investigating the interaction of both early conduct problems and depressive symptoms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".