Reaching out to big losers: Exploring intervention effects using individualized follow-up.
Bibliographic record
Abstract
OBJECTIVE: Previous research suggests that a brief duty-of-care telephone call to high expenditure customers was associated with lower gambling over the subsequent year. The current aim was to assess effects on individual trajectories rather than overall group effects reported previously. The objective was to identify different patterns of individual change over the follow-up year and explore differential responses of subgroups of individuals. METHOD: A matched pair design contrasting the outcome for telephone intervention with a no-intervention control condition. Five hundred and ninety-six statistical pairs randomly drawn from the top 0.5% of customers based upon annual expenditure at Norsk Tipping, Norway. Primary outcome measure was gambling theoretical loss (TL), derived from the Norsk Tipping gambling data warehouse. Player trajectories across time were identified using growth mixture modeling to assess differential intervention effects on homogenous subgroups of individuals. RESULTS: Relatively low, medium, and high TL subgroups were identified. The telephone intervention was associated with greater reductions than the control condition for all three subgroups but showed the strongest effect for the subgroup with the highest TL. The intervention was most effective for casino and sport gamblers, male, young, and middle-aged. CONCLUSIONS: A brief duty of care telephone contact with high expenditure customers showed sustained effects over 12 months, in particular for individuals showing the highest level of TL. Examining trajectories using advanced statistical models identified customer characteristics most strongly associated with reduced TL. These findings can guide prevention strategies with evidence-based knowledge about differential effects. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.001 |
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 teacher head, 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".