Treatment Outcomes and Predictors of Drop out for Problem Gamblers in South Australia: A Cohort Study
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVES: Recent prevalence studies in Australia, the USA and Canada have estimated 1-2% of the adult population meet the diagnostic criteria for problem or pathological gambling. The Statewide Gambling Therapy Service (SGTS) provides treatment for problem gamblers in key metropolitan and rural regions in South Australia. The aims of this study were two-fold: to analyse the short and mid-term outcomes following treatment provided by SGTS and to identify factors associated with treatment drop-out. METHOD: A cohort of treatment seeking problem gamblers was recruited through SGTS in 2008. Repeated outcome measures included problem gambling screening, gambling related cognitions and urge. Treatment drop-out was defined as participants attending three or less treatment sessions, whilst potential predictors of drop-out included perceived social support , anxiety and sensation-seeking traits. RESULTS: Of 127 problem gamblers who participated in the study, 69 (54%) were males with a mean age of 43.09 years (SD = 12.65 years) and with 65 (52%) reporting a duration of problem gambling greater than 5 years. Follow up time for 50% of participants was greater than 8.9 months and, overall, 41 (32%) participants were classified as treatment drop-outs. Results indicated significant improvement over time on all outcome measures except alcohol use for both treatment completers and drop-outs, although to a lesser extent for the treatment drop-out group. A significant predictor of treatment drop-out was sensation-seeking traits. CONCLUSION: These results will inform future treatment planning and service delivery, and guide research into problem gambling including aspects of treatment drop-out.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it