Case study of A Pilot Online Treatment Service for Problem Gambling
Bibliographic record
Abstract
Objective: Most people with gambling-related problems do not seek treatment. Possible barriers to seeking treatment include stigma, travel distance, and competing obligations (e.g., childcare). Online group therapy may help reduce some of these barriers. Method: The current paper presents a small case study to assess the feasibility of an 8-week online group therapy program. This program called Skills for Change Online was designed as an introduction to treatment using a cognitive behavior therapy approach. It includes teaching coping skills, mindfulness, dealing with erroneous beliefs and emotions. Sixteen people consented to participate in the study, three were included in the group, but only two participants completed the treatment. The group was evaluated using a longitudinal case study design (pre-test, post-test, with a 1-year follow-up). In addition, 8 waitlist controls completed the follow-up up survey. Measures included the Problem Gambling Screening Index (PGSI), Mindfulness Attention Awareness Scale (MAAS), Random Events Knowledge Test (REKT), Perceived Social Support (PSS), Kessler Psychological Distress Scale (K6), and Quality of Life (QLI). Results: Both participants reported increases in their MAAS (d =.56), and REKT scores (d =1.06), and decreases in problem gambling, and gambling craving (d =-0.30) after treatment. In addition, both participants had clinically significant decreases in PGSI scores dropping from a severe problem gambling to a moderate level of gambling problems. These positive outcomes were sustained according to a 12-month follow-up survey. Participants provided feedback during treatment, that the treatment services were helpful but also discussed technological challenges involved in online group therapy. A group of participants who were not included in the treatment showed less overall improvement in gambling, mindfulness based on the MAAS and knowledge of random chance based on the REKT. Conclusion: The results are encouraging. However, the sample is very small and there is a need for further research with larger samples and randomized controlled designs. The difficulties of running on-line groups are discussed.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".