Table 5.

Past-month monetary gambling by type and past-month skin gambling predicting problem gambling

Variables	Advertisements Sample Problem Gambling NG/NPG vs AR/PG1 (ref = NG/NPG)					Qualtrics Sample Problem Gambling NG/NP vs AR/PG1 (ref = NG/NPG)
	B	SE	Wald's χ 2	P	Odds ratio	B	SE	Wald's χ 2	P	Odds ratio
Monetary gambling
Poker machines	3.553	0.726	23.952	<0.001***	34.935	1.443	0.485	8.846	0.003**	4.234
Horse/greyhound racing	-0.110	1.216	0.008	0.928	1.116	0.600	0.464	1.670	0.196	1.822
Scratchies, lottery, lotto, pools	2.536	0.599	17.950	<0.001***	12.634	0.830	0.284	8.553	0.003**	2.293
Keno	2.740	1.358	4.072	0.044*	15.479	0.281	0.507	0.308	0.579	1.325
Bingo	3.653	0.848	18.610	<0.001***	38.708	0.549	0.386	2.029	0.154	1.732
Poker	0.870	1.606	0.294	0.588	2.114	1.717	0.681	6.361	0.012*	5.568
Casino table games3	-	-	-	-		-0.529	0.740	0.510	0.475	0.589
Sporting events	-1.208	1.043	1.341	0.247	0.299	0.663	0.480	1.913	0.167	1.942
Esports	1.665	0.669	6.192	0.013*	5.285	-0.188	0.433	0.189	0.664	0.829
Fantasy sports	2.990	0.661	20.450	<0.001***	19.891	0.764	0.501	2.323	0.127	2.146
Informal private betting	2.782	0.500	30.989	<0.001***	16.154	0.777	0.307	6.430	0.011*	2.175
Skin gambling	2.730	0.476	32.84	<0.001***	15.333	2.202	0.237	86.218	<0.001***	9.047
Constant	-4.580	0.459	99.776	<0.001***	0.010	-2.590	0.156	274.633	<0.001***	0.075

*P < 0.05; **P < 0.01; ***P < 0.001.

1. Two problem gambling categories: NG/NPG = Non-Gamblers plus Non-Problem-Gamblers; AR/PG = At-risk gamblers plus PG = Problem Gamblers.

2. Omnibus test of final model: advertisement sample (Block: Likelihood χ ² = 37.049; df = 1; P < 0.001***; Model: Likelihood Ratio χ ² = 987.395; df = 11; P < 0.001***); Qualtrics sample (Block: Likelihood χ ² = 11.083; df = 1; P = 0.001**; Model: Likelihood Ratio χ ² = 288.518; df = 12; P = 0.001**).

3. Sample size for the casino table games category was too small for this analysis.