Table 1.
Participant socio-demographic and gambling characteristics (n = 363)
| Frequency | Percentagea | |
|---|---|---|
| Gender | ||
| Male | 185 | 51.0% |
| Female | 178 | 49.0% |
| Geographic location | ||
| New South Wales | 217 | 59.8% |
| Victoria | 146 | 40.2% |
| Age | ||
| 18–29 | 99 | 27.3% |
| 30–45 | 89 | 24.5% |
| 46–60 | 90 | 24.8% |
| 60 + | 85 | 23.4% |
| Country of birth | ||
| Australia | 290 | 79.9% |
| United Kingdom | 16 | 4.4% |
| India | 14 | 3.9% |
| China | 10 | 2.8% |
| Other | 33 | 9.1% |
| Education | ||
| Secondary school education | 114 | 31.4% |
| Trades-based education | 105 | 28.9% |
| Tertiary education | 144 | 39.7% |
| Employment status | ||
| Working full-time | 165 | 45.5% |
| Working part-time / casually | 67 | 18.5% |
| Retired | 60 | 16.5% |
| Homemaker | 22 | 6.1% |
| Unemployed but looking for work | 20 | 5.5% |
| Full-time student | 14 | 3.9% |
| Other | 15 | 4.1% |
| Income per week | ||
| Over $3000 | 39 | 10.7% |
| $2500—$2999 | 39 | 10.7% |
| $2000—$2499 | 51 | 14.0% |
| $1500—$1999 | 65 | 17.9% |
| $1000—$1499 | 82 | 22.6% |
| $500—$999 | 59 | 16.3% |
| $499 or less | 27 | 7.4% |
| No income | 1 | 0.3% |
| Gambling products used in a typical monthb | ||
| Electronic gambling machines | 268 | 73.8% |
| Lotteries | 231 | 63.6% |
| Sports betting | 185 | 51.0% |
| Scratch cards / scratchies | 166 | 45.6% |
| Horse betting | 128 | 35.2% |
| Casino games | 70 | 19.2% |
| Number of gambling products used in a typical month | ||
| 1 | 54 | 14.9% |
| 2 | 91 | 25.1% |
| 3 | 120 | 33.1% |
| 4 + | 98 | 27.0% |
aTotals may not add up to 100% due to rounding
bParticipants could select multiple responses