A qualitative examination of factors underlying transitions in problem gambling severity: Findings from the Leisure, Lifestyle, & Lifecycle Project
Bibliographic record
Abstract
Background: The current study sought to explore the narrative accounts of individuals who underwent changes in their problem gambling severity, and identify subjective factors underlying these transitions. Additionally, respondents’ perceived change in their gambling behavior was compared with a validated measure of problem gambling severity.Methods: Participants were recruited from The Leisure, Lifestyle, & Lifecycle Project (LLLP), a prospective cohort study based in Alberta, Canada. In-depth, semi-structured telephone interviews were conducted with a subset of participants identified as showing a significant increase or decrease in problem gambling severity between Wave 4 and 5 of the LLLP (n = 41). Principles of phenomenology and grounded theory were used to thematically code interviews.Results: About half of respondents increased in problem gambling severity between Wave 4 and 5 (n = 22), while 19 respondents decreased. For those who perceived this change (n = 13), the most common factors underlying increases in problem gambling severity were the same factors underlying decreases and included financial, social, and internal reasons. More than half of the sample (n = 28) perceived stability in, or a change in their gambling behavior that was incongruent with their problem gambling severity score. These respondents tended to endorse a greater degree of gambling fallacies, dissonant feelings, and mental health issues, compared to those who had accurately perceived their change.Conclusions: The findings suggest that many individuals may not accurately perceive transitions in their gambling. Gambling fallacies and dissonant feelings seem to underlie this discrepancy, highlighting the need for public health initiatives to focus on correcting these erroneous beliefs.
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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 | 0.012 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".