Increasing Chance-Based Uncertainty Reduces Heavy Drinkers' Cognitive Reactance to Web-Based Personalized Normative Feedback

Abstract

Objective: Despite its prominence in the health communication literature, psychological reactance has rarely been considered as a factor that may undermine web-based Personalized Normative Feedback (PNF) alcohol interventions for college students. This study built on recent gamification work to examine how chance-based uncertainty, a popular game mechanic associated with motivation and attention in digital games for learning, might be leveraged to reduce the psychological reactance experienced by heavy drinking students receiving alcohol PNF, thereby leading to larger reductions in their alcohol consumption.

Method: Psychological reactance, perceptions of norms, and drinking behaviors were assessed during a 3-week period following random assignment of binge drinking students (N = 141, 51% female) into one of four web-based PNF conditions. These conditions asked the same questions about drinking and delivered identical PNF on alcohol use but differed in whether animated slot-machine spinners appeared to select participants' question and feedback topics as well as the number of additional topics (beyond alcohol) on which questions were asked and PNF was delivered.

Results: All conditions similarly reduced drinking norms but differed in the degree to which they aroused cognitive reactance and reduced drinking. Relative to a no-spinner alcohol-only condition, increasing chance-based uncertainty by giving question and feedback topics the appearance of being selected by gamelike spinners substantially reduced cognitive reactance, which, in turn, reduced drinking 20 days later. Overall, participants experienced the least cognitive reactance when spinners first selected three question topics and later selected two of these topics to deliver feedback on.

Conclusions: Findings suggest that introducing chance-based uncertainty through gamelike spinners, asking questions about multiple topics, and delivering feedback on additional topics unrelated to alcohol together work to reduce the degree to which the task feels like an alcohol intervention overtly aimed at reducing consumption, thereby making the alcohol PNF more effective among heavy drinking students.

Figure 1

Flow diagram for participants incentivized by partial human subject pool or judicial sanction credit. No differences in retention were observed between student groups. C = Condition.

Figure 2

Bootstrap Mediation model with study condition specified as a multi-categorical predictor. All paths controlled for Time 1 alcohol consumption, participants’ sex, class year, and group (human subject pool or judicial). The parenthesized coefficients onY paths indicate the total effect on alcohol consumption associated with each spinner condition relative to the no spinner control condition (C0). Above these, the nonparenthesized Y coefficients represent the direct effect of the study condition on alcohol consumption after accounting for the significant indirect effect (detailed in Table 4) from spinner condition to alcohol consumption via cognitive reactance. PNF = personalized normative feedback; ns = not significant. *p < .05; **p < .01; ***p < .001.