Cashless gambling and the pain of paying: effects of monetary format on slot machine gambling

Figures & data

Figure 1. The pain of paying hypothesis. As the pain of paying increases, risky behavior should decrease. (A) Hypothesis 1 predicts increased gambling when participants receive the money to gamble as a voucher, compared to cash. (B) Hypothesis 2 predicts decreased gambling when participants earn money to gamble, compared to a cash windfall. Image source for $5 bills: Bank of Canada.

Figure 2. Trial structure for the trial-level analysis. Spin initiation latency and next bet size (in red) were analyzed as a function of the current state of the machine at *, after the outcome.

Table 1. Demographic and session-level variables.

Expt 1a:	Cash	Voucher
Demographic variables
N	30	31
Age	48 (21–79)	44 (20–71)	W = 384.5, r = 0.07, p = .58
Gender	12 male, 18 female	18 male, 13 female	χ2(1) = 1.33, p = .25
PGSI	1 (0–6)	1 (0–4)	W = 424.5, r = 0.09, p = .55
Slot spend per month ($)	45 (0.5–500)	30 (1.6–400)	W = 490.5, r = 0.05, p = .72
Session-level variables
Mean bet size (cents)	30.53 (1.41–102.23)	30.46 (1.83–102.23)	W = 502, r = .10, p = .45
Total bet (session) ($)	52.75 (1.00–270.60)	54.37 (0.73–151.50)	W 436, r = .026, p = .84
Final balance ($)	26.24 (0–156.78)	14.50 (0–51.38)	W = 569.5, r = .23, p = .077
Total bet by 5 minutes ($)	17.00 (0.61–44.70)	14.56 (0.45–63.80)	W = 461, r = 0.020, p = .88
Expt 1 b:	Windfall	Earned
Demographic variables
N	28	20
Age	42 (19 − 81)	53.5 (19–54)	W = 249, r = .066, p = .66
Gender	11 male, 16 female, 1 other	8 male, 12 female	χ2(2) = .732, p = .69
PGSI	2 (0–6)	1.5 (0 − 6)	W = 331.5, r = .16, p = .28
Slot spend per month ($)*	50 (0–1000)	100 (2–500)	W = 257.5, r = .07, p = .64
Session-level variables
Mean bet size (cents)	40.00 (4.89–117.66)	40.00 (3.52–188)	W = 258.5, r = .037, p = .80
Total bet (session) ($)	49.13 (4.39–208.69)	47.76(9.79–166.17)	W = 242, r = .016, p = .92
Final balance ($)	27.37 (0–100.35)	30.00 (0–104.83)	W = 236, r = .035, p = .82
Total bet by 5 minutes ($)	18.40 (1.45–47.27)	12.56 (1.27–47.00)	W = 285, r = .12, p = .42

Continuous data violated the assumption of normality, so summary statistics are median and range, and Wilcoxon rank-sum tests were used to test for group differences. Three participants in experiment 1a and one participant in experiment 1 b did not provide their age, and so are excluded from the age analysis. For the session-level variables, we excluded participants who had accidentally cashed out (two participants in experiment 1 b) and participants who chose to stop gambling prior to the light flashing (one participant from each experiment). PGSI: problem gambling severity index; $: Canadian dollar.

Figure 3. Observed and predicted data for the spin initiation latency models. Observed data shown using Tukey boxplots. Spin initiation latency as a function of machine balance in experiment 1a (A) and experiment 1 b (B). Spin initiation latency as a function of loss streak length in experiment 1a (C) and experiment 1 b (D). Spin initiation latency as a function of the size of a win in experiment 1a (E) and experiment 1 b (F).

Table 2. Predictors of interest in the models of spin initiation latency.

	Beta	95% CI	p Value
After a loss
Exp1a: Cash vs credit
Log loss streak (CASH)	−0.056	−0.072, −0.039	<.001
Log loss streak * group	0.043	0.019, 0.068	<.001
Log loss streak (CREDIT)	−0.012	−0.031, 0.0062	.19
Machine balance ($)(CASH)	0.00013	−0.00021, 0.0018	.9
Machine balance ($)* group	0.0018	−0.00075, 0.0044	.165
Exp1b: Windfall vs earned
Log loss streak (WINDFALL)	−0.020	−0.037, −0.0020	<.05
Log loss streak * group	−0.0055	−0.032, 0.021	.676
Machine balance ($)(WINDFALL)	−0.0031	−0.0046, −0.0015	<.001
Machine balance ($)* group	0.0072	0.0049, 0.0096	<.001
Machine balance ($)(EARNED)	0.0041	0.0023, 0.0059	<.001
After a win
Exp1a: Cash vs credit
Log win size	0.10	0.074, 0.13	<.001
Log win size * group	0.0072	−0.030, 0.044	.699
Exp1b: Windfall vs earned
Log win size(WINDFALL)	0.16	0.13, 0.18	<.001
Log win size * group	−0.094	−0.13, −0.058	<.001
Log win size(EARNED)	0.062	0.036, 0.089	<.001

Subscript text indicates in which group the effect is measured in (group 0). For predictors that are significantly modulated by group (p < .05), the model was repeated with the group order reversed, to measure the effect in group 1. Bold text indicates significant predictors. CI: confidence interval. See supplemental materials for full models, including regressors of no-interest.

Figure 4. Observed and predicted data for the next bet size models. Observed data shown using Tukey boxplots. Probability of the next bet being higher than the participants median bet as a function of machine balance in experiment 1a (A) and experiment 1 b (B). Probability of the next bet being higher than the participants median bet as a function of loss streak length in experiment 1a (C) and experiment 1 b (D). Probability of the next bet being higher than the participants median bet as a function of the size of a win in experiment 1a (E) and experiment 1 b (F).

Table 3. Predictors of interest in the next bet models.

	OR	95% CI	p value
After a loss
Exp1a: Cash vs credit
Log loss streak(CASH)	0.92	0.90, 0.94	<.001
Log loss streak* group	1.06	0.94, 1.19	.326
Machine balance ($)(CASH)	1.04	1.03, 1.05	<.001
Machine balance ($) * group	1.00	0.98, 1.01	.504
Exp1b: Windfall vs earned
Log loss streak (WINDFALL)	0.95	0.86, 1.05	.319
Log loss streak* group	1.07	0.92, 1.25	.373
Machine balance ($) (WINDFALL)	1.00	0.99, 1.01	.836
Machine balance ($) * group	1.00	0.98, 1.00	.788
After a win
Exp1a: Cash vs credit
Log win size(CASH)	1.70	1.36, 2.12	<.001
Log win size * group	0.88	0.64, 1.21	.430
Exp1b: Windfall vs earned
Log win size(WINDFALL)	1.26	1.03, 1.54	<.05
Log win size * group	1.01	0.74, 1.38	.928

Subscript text indicates in which group the effect is measured in (group 0). CI: confidence interval; OR: odds ratio. See supplemental materials for full models, including regressors of no-interest.