Gambling behaviours and treatment uptake among vulnerable populations during COVID-19 crisis
Bibliographic record
Abstract
This study aimed to explore changes in gambling behaviours and gambling disorder (GD) treatment uptake during the COVID-19 pandemic among those with a heightened vulnerability to gambling-related harm. This was a single-center, cross-sectional, retrospective case series study assessing gambling behaviours and GD counselling participation among a vulnerable population sector following the COVID-19 shutdown. The clinical records of clients at a community substance use disorder (SUD) treatment center were explored (N = 67). Eight clients (n = 8) had satisfied the objective criteria, and were qualified for data exploration and analysis of gambling activities and GD treatment participation following the COVID-19 shutdown. All clients in the study belonged to subgroups at an elevated risk for gambling-related harm, with a mean duration of gambling problems of 9.5 years. Following the COVID-19 shutdown, an increase in gambling activities was noted in five cases. Migration to online gambling was noted in three cases. In two cases, no change in gambling activities was noted, and a reduction of gambling activities was noted in one case. In seven cases, no screening for gambling problems prior to current SUD program was noted. None had a history of, nor were currently engaged in counselling for gambling problems. The COVID-19 crisis and associated increase in gambling participation, coupled with a diminutive gambling counselling uptake during the pandemic, present an opportunity to rethink current behavioural addictions service delivery model for those with an increased vulnerability to gambling-related harm. Further investigation of the changes in gambling participation, and a closer look at optimizing GD service delivery among vulnerable population sectors during the COVID-19 crisis is warranted.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".