The Temporal Relationship Between Faulty Gambling Cognitions and Gambling Severity in Young Adults
Bibliographic record
Abstract
Disordered gambling in young adults is hypothesized as being related to mistaken gambling-related cognitions. Few studies have examined the temporal order of this relationship using longitudinal data. The purpose of this study is to understand the directionality of the relationship between gambling cognitions and gambling severity in a longitudinal sample of young adults. Young adults (N = 578), initially aged 18-21 years, completed the Manitoba Longitudinal Survey of Young Adults at two time points approximately 2-3 years apart. Measures of beliefs about randomness related to gambling and gambling severity, as measured by the Problem Gambling Severity Index, were utilized. A cross-sectional relationship between gambling severity and gambling-related cognitions was observed with greater gambling severity being associated with increased endorsement of mistaken cognitions. Evidence for a bidirectional longitudinal relationship was observed with faulty gambling cognitions leading to later problematic gambling behaviors and vice versa when examining a total beliefs scale. When examining specific beliefs about randomness, initial gambling group membership predicted later endorsement of certain beliefs about randomness while initial belief ratings did not impact later gambling group membership. The results of this study suggest a bidirectional relationship between gambling severity and erroneous gambling-related cognitions. However, when examining specific beliefs about randomness, evidence was found for problem gambling behaviors leading to erroneous gambling beliefs. These findings suggest that prevention efforts targeting cognitions may not be as effective in impacting those not yet demonstrating disordered gambling behaviors.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".