Table 3.
Problem gambling classification for students who reported gambling in the last 30 days by age and gender (N = 391)
| Classification: | Non-problem gambler | At-risk gambler | Problem gambler | p |
|---|---|---|---|---|
| Age | 0.074 | |||
| 12–13yrs (N = 64) | 37 (58%) | 20 (31%) | 7 (11%) | |
| 14yrs (N = 67) | 44 (66%) | 17 (25%) | 6 (9%) | |
| 15yrs (N = 77) | 29 (38%) | 32 (42%) | 16 (21%) | |
| 16yrs (N = 103) | 56 (54%) | 29 (28%) | 18 (18%) | |
| 17yrs (N = 80) | 34 (43%) | 33 (41%) | 13 (16%) | |
| Gender | < 0.001* | |||
| Males (N = 228) | 91 (40%) | 86 (38%) | 51 (22%) | |
| Females (N = 163) | 109 (67%) | 45 (28%) | 9 (6%) | |
| Total (N = 391) | 200 (51%) | 131 (34%) | 60 (15%) |
There were 17 students who could not be classified due to missing data on the DSM-IV-JR. Percentages are presented as row proportions for those who reported gambling in the last 30 days. Classification of problem gambling was based on Fisher (2000) and ACER 2011 scoring of the DSM-IV-[MR]-J with modified yes/no response options. *Indicates statistically significant differences (using p ≤ 0.023)