Exploring Youth Gambling in Croatia - Guidelines for Creating Evidence Based Prevention Program
Bibliographic record
Abstract
The aim of this paper is to present key elements of the first evidence-based prevention of youth gambling in Croatia that is developing based on a large research study about youths’ gambling activities, prevalence of risk and problem gambling and correlates of problem gambling among high-school students. A sample of N=1.952 high-school students (47% of boys and 53% of girls) participated in the research from 4 biggest Croatian cities (Zagreb, Split, Osijek & Rijeka). This probability sample included students from different types of school programs and generations, and is representative for adolescents in urban areas. Age range is from 14 to 20 years of age (M=16.56, SD=1, 17). Results show that 83% of high-schools students gambled at least once in their lifetime, 19.0% play sport betting regularly and 6.2% play slot machines regularly. Male students more often play gambling games that are more risky for the development of problem gambling (e.g. sport betting, slot machines, casino, cards, virtual races etc.). Psychosocial consequences of gambling were measured with Canadian Problem Gambling Inventory (CAGI), developed by Wiebe, Tremblay, Wynne & Stinchfield (2010). This instruments measures global severity score on three levels as follows: (1) no problem, (2) low-to-moderate severity and (3) high severity. Our results reveal that 12% of high-school students show serious, high severity consequences due to their gambling activities, and 17% low-to-moderate severity. Boys are in greater risk of developing harmful psychosocial consequences of gambling as they also gamble more often. Our results also indicate that students who have more serious consequences due to their gambling activities have more friends that gamble, manifest other risky behavior with some elements of delinquent behavior, are more motivated by earning money and believe more often that they can predict and control the outcome of the game. They are also less responsible and worry less for other people, show more tendency for hedonism with less orientation for the future and achievement, and have generally less sense of control in their life. Even though in Croatia gambling is prohibited for minors (children under the age of 18), results clearly indicate their involvement in these activities and provide strong arguments for the development and implementation of preventive interventions. In this paper, with our major results, we shall also present developing activities of the first Croatian evidence-based prevention program of youth gambling in school setting that focuses on the most predictive factors for developing problem gambling syndromes.
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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 | 0.101 | 0.090 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.015 | 0.006 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".