Joshua Kirton and Dr. Timothy Smith, Dept. CPSE

This project was undertaken to evaluate how melioration explain behavior addiction more robustly than more conventional models such as maximization. Suboptimal behavior, including addiction, can be conceptualized as the consequence of a decision strategy called melioration that is utilized in choice situations in which the value of an alternative is affected by the rate of its availability (Hernstein & Vaughan 1980; Lowenstein & Elster, 1992). The higher the rate of availability of an alternative, the lower the overall value. Melioration can result in negative consequences that are not recognized by the individual until their cumulative negative effect becomes unavoidable (Bickel & Marsch, 2000; Elster and Skog, 1999; Rachlin, 2000). This negative effect may go unrecognized because individual decisions in the series of repeated choices are not perceived as adding much weight to the overall consequences. This failure to perceive the overall outcome has been referred to as the “primrose path to addiction” (Rachlin, 2000, p.74).

For this project research was completed to analyze whether human behavior more closely follows a pattern of melioration as explained above, or a maximizing strategy in which an individual will always choose the option that is more valuable overall. To maximize an individual must take into consideration a variety of factors and consider the long term and will choose the option that provides the most valuable outcome. In melioration they choose what they perceive as the most valuable when they make a decision.

A within-subjects design was used to determine whether an individual’s behavior would shift toward maximization and away from melioration within the experimental session. A traditional ABA design recorded initial melioration in the (baseline) followed by exposure to a visual cues exposing the internality (treatment). A final period resembled the first. All 76 participants completed Experiment 1. In this experiment, each participant completed a 20-minute session. For the combination cue, no additional instructions were given; all participants received the same instructions. Next, each participant was given a practice period of 1 minute. A 5-min baseline condition then began in the absence of visual cues. At the conclusion of that time, a 1-min break was taken, followed by a 5-min period in which the participant continued earning money and one of the three visual cue options was presented. Following that interval, another1-min break occurred. The final 5-min period was a return to the baseline condition in which money was earned but no cues were present. The program then indicated at the end if they qualified to participate in the other experiments.

Participants in Experiment 1 who responded in the second time period with at least 55% of their choices representing maximization were candidates for Experiment 2. Using a slightly higher criterion than chance responding (50%) was intended to include those participants who at least partially responded in a pattern representing maximization. The second criterion for inclusion in Experiment 2 was a return to a lower level of responding during the final time period. A return to a lower level of responding was defined as an overall drop of 25% of more maximization responses.

The second experiment assessed whether a fading procedure would aid individuals in maintaining maximizing choice allocation. The procedure was almost identical to that described in Experiment 1 and each participant was matched to the cue previously received. The only variation occurred in the second time period. After the second money earning portion of the experiment began, the visual cue was present for the first 10 trials. Once those 10 trials were finished, only the first 8 of the next 10 had the visual cue present. The next 10 trials consisted of a 6 and 4 split. A final 5-min money-earning period concluded the session.

Choice allocation that more closely approximated maximization in the second time period compared with the first would represent exposure to the internality and resultant behavior modification. Choices more similar to maximization in the third time period compared with the first would suggest that the fading procedure was a more successful than removing the cue and allowing the participant to maintain awareness of the internality in the absence of the cue.

Participants who responded with .75 or more of their choice allocation to the key representing maximization during the final time period of Experiment 1 qualified to be invited to participate in Experiment 3. This criterion was selected to identify those who established and maintained a strategy more consistent with maximization following the treatment condition. With a cutoff of .75, participants who used a strategy of balancing their choices equally between the choices would not be included, nor would those who selected the key representing maximization for a short time then returning to a melioration strategy overall.

Based on the selection criteria, eight participants qualified to complete Experiment 3. However, only one participant was actually invited to complete the experiment. The participant was an 18-yearold female freshman who received the graph cue.

Experiment 3 was similar in procedure to Experiments 1 and 2, but there were several notable differences. The experiment provided 900 seconds in which to earn money, with no breaks available during the session. The session began with a 1-min warm-up period in which no money was earned and in which the averaging window was set at 10 choices, meaning only the most recent 10 choices were used to calculate the delay for the next choice made. Following the warm-up, the averaging window for the session was re-sized based on responding within the window. The minimum possible size of the window was 10 choices and the maximum possible was 20 choices.

The experiments were used to determine if maximization can be increased when exposed to different cues that reveal the internality or the actual reward schedule present in a choice situation. We found that the more information that you have the more likely you are to respond in a way that maximizes reward over time rather than choosing the alternative that pays more now. This is particularly paramount in treatment of addiction. Knowing individuals who are able to see the results of their decisions are more likely to make the choice that pays off in the long run rather than persisting in the behavior that pays off immediately, we can begin to devise therapeutic ways to reveal the consequences of choices to those who are stuck in behavioral addictions.

Currently the paper to publish this research is being drafted. It is 40 pages in length which is too long. I am editing down to 20-25so that it can be submitted to a journal. My final edits should be done within the month, and then it will be passed to my mentor who will make his final touches before submitting it for publication. Our target journal is the Journal of Addiction Research and Theory.

References

• Bickel, W. K. & Marsch, L. A. (2000). The tyranny of small decisions: Origins, outcomes and proposed solutions. In W. K. Bickel & R. E. Vuchinich (Eds.), Reframing health behavior change with behavioral economics. New Jersey: Lawrence Erlbaum Associates.
• Elster, J. & Skog, O. (1999). Getting hooked. New York: Cambridge University Press.
• Hernstein, R. J. & Vaughn, Jr., W. (1980). Melioration and behavioral allocation. In: J.E.R. Standon (ed), Limits to Action: The allocation of individual behavior. New York: Academic Press
• Lowenstein, G., & Elster, J. (1992). Choice over time. New York: Russell Sage Foundation.
• Rachlin, H. (2000). The science of self-control. Cambridge: Harvard University Press.