Reaching Out to Big Losers: How Different Types of Gamblers are Affected by a Brief Motivational Contact Initiated by the Gambling Provider
Bibliographic record
Abstract
Telephone and letter-based motivational interventions with high expenditure gamblers have significant short and long term positive effects on gambling and use of responsible gambling tools. This report examines how different subtypes of gamblers, based upon patterns of play, are differentially affected. A randomized controlled trial design with three conditions (n = 1003 in each): feedback intervention by letter, telephone or a no-contact control condition. Subtypes of gamblers were derived by latent class analyses (LCA) based upon gambling behavior pre intervention. The participants were customers of Norsk Tipping gambling platforms. 1003 statistical triplets from the top 0.5% of customers based upon annual expenditure, matched on sex, age, and net losses. Primary outcome measure was gambling theoretical loss (TL), derived from the Norsk Tipping customer database. The LCA identified six subtypes: High Casino, High Sport, High Lottery, High Video lottery terminal (VLT), Lottery/Mix and Bingo/Casino. There were almost no differences in change in TL between the six subtypes of gamblers receiving the letter or telefone interventions respectively. However, the choice of contact by letter or telephone did have different effects for the different gambling subtypes. Sending a letter seems like a cost effective alternative to telephone contact for the High Lottery type, but telephone contact performs better for High Casino, High Sport and High VLT customers. Responsible gambling interventions can be improved by subtyping of gamblers.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| 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 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".