Using a computer simulation of three slot machines to investigate a gambler’s preference among varying densities of near-miss alternatives
The present article describes a software program in Visual Basic .NET designed to simulate three slot machines on a computer screen. This software is described in detail regarding utility, downloading, and usage; and data are presented illustrating the software’s potential for researchers interested in gambling behavior. A simulation of multiple slot machines such as this enables researchers to evaluate players’ preferences across various machines. In the highlighted experiment, 18 recreational slot machine players played the software for extra course credit and a chance at cash prizes. All participants played a version of the simulation in which every 5th response on average was a win, whereas the remaining trials were a loss. However, on those loss trials, a varying distribution of almost wins or near misses (i.e., two winning symbols on the payoff line and the final winning symbol directly above or below the payoff line) were presented in percentages of 15, 30, or 45. While no preferences across the three options could be predicted on the basis of reinforcement history alone, deviations from equal choices across the games were noted and appeared to be the result of the presentations of near-miss losing trials. Implications for a greater understanding of pathological gambling are presented.
- Dixon, M. R., &Delaney, J. (2006). The impact of verbal behavior on gambling behavior. In P. M. Ghezzi, C. A. Lyons, M. R. Dixon, & G. R. Wilson (Eds.),Gambling: Behavior theory, research, and application (pp. 171–189). Reno, NV: Context Press.Google Scholar
- Dixon, M. R., &Moore, K. (2006). Native American gambling: The quest for the new white buffalo. In P. M. Ghezzi, C. A. Lyons, M. R. Dixon, & G. R. Wilson (Eds.),Gambling: Behavior theory, research, and application (pp. 231–247). Reno, NV: Context Press.Google Scholar
- Dixon, M. R., &Schreiber, J. E. (2004). Near-miss effects on response latencies and win estimations of slot machine players.Psychological Record,54, 335–348.Google Scholar
- Ghezzi, P. M., Lyons, C. A., &Dixon, M. R. (2000). Gambling in socioeconomic perspective. In W. K. Bickel & R. E. Vuchinich (Eds.),Reframing health behavior change with behavioral economics (pp. 313–338). Mahwah, NJ: Erlbaum.Google Scholar
- MacLin, O. H., Dixon, M. R., Robinson, A., &Daugherty, D. (2006). Writing a simple slot machine simulation program. In P. M. Ghezzi, C. A. Lyons, M. R. Dixon, & G. R. Wilson (Eds.),Gambling: Behavior theory, research, and application (pp. 127–154). Reno, NV: Context Press.Google Scholar