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Summary of Findings We replicated the findings of Tversky and Kahneman (1988) where participants were more risk-averse for positively framed decisions and more risk-seeking for negatively framed decisions. Interruption made participants more risk-averse Frustration removed the effects of framing. Frustrated participants did not exhibit risk- seeking or risk-averse behavior. Implications of Our Findings Our scenarios involving situations more relevant to college students did not demonstrate any significant effects, contrary to Keller, Lipkus and Rimer’s (2003) and Nygren’s (1998) findings that framing effects are stronger when participants are highly emotionally involved. Future Research Further research on why the scenarios created for college students did not exhibit significant effects (for example, being related to the students’ lives may not be the same as being emotionally involved) should be conducted. Although it was not the focus of this experiment, performance on the math test should be examined before and after the interruption to look at the effect of the interruption on task performance. A 2x2x2 between-subjects ANOVA examined the effects of frustration (easy math test / hard math test), interruption (interrupted / not interrupted), and framing (positive / negative) on tendency to be risk-averse or risk-seeking. For the original Tversy and Kahneman (1988) scenario, we obtained significant results that were consistent with their original findings. T&K found 72% of participants were risk-averse (chose the sure-thing over the gamble) when the scenario was positively framed, and 22% were risk-averse when the scenario was negatively framed. We found 80.5% were risk-averse when the scenario was positively framed, and 28.6% were risk-averse when the scenario was negatively framed. We found a significant main effect for interruption, with participants who were interrupted being more risk-averse (61.5% choosing the sure-thing) than participants who were not interrupted (42.2% choosing the sure-thing). For the other three scenarios, we did not find any significant main effects or interactions. Our follow-up questions confirmed that the hard math test did, in fact, increase both anxiety and frustration in our participants. The mean test anxiety reported by participants who received the easy math test was 2.08 (sd=1.06). The mean test anxiety reported by participants who received the hard math test was 2.73 (sd=1.23). Anxiety was significantly higher for the participants who received the hard math test (t(109)=2.946, p=.004) The mean frustration reported by participants who received the easy math test was 1.72 (sd=.86). The mean frustration reported by participants who received the hard math test was 3.00 (sd=1.51). Frustration was significantly higher for the participants who received the hard math test (t(109)=5.59, p <.001) The Effects of Framing, Frustration, and Interruption on Risk-Seeking or Risk-Averse Decisions Introduction / Background The Effect of Framing on Decisions Framing is the cognitive heuristic in which people tend to reach conclusions based on the “framework” within which a situation was presented. Heuristics are “rules of thumb” that are used to make decisions quickly when incomplete information is available. Framing effects refer to the finding that subjects often respond differently to different descriptions of the same problem (Tversky & Kahneman, 1988; Frisch, 1993). Problems framed as having a negative outcome make participants more risk-seeking. When participants are risk-seeking, they are more likely to choose a gamble than a sure thing. Problems framed as having a positive outcome make participants more risk-averse. When participants are risk-averse, they are more likely to choose a sure thing than a gamble. Nygren (1998) suggested that there is a strong emotional component to framing effects and Keller, Lipkus and Rimer (2003) found that framing effects are stronger when the participant is emotionally involved. The Effect of Interruption on Decisions Distractions and interruptions can have a variety of negative effects on performance, including increases in errors (Forster & Lavie, 2008; McFarlane, 2002). Numerous factors relating to the interruption, task, and person mediate the effect (Xia & Sudharshan, 2002). In an experimental setting interruptions undermine performance on complex decision tasks but improve decision making on simple tasks (Seshadri & Shapira, 2001). This suggests that interruption will impact framing effects The Effect of Frustration on Decisions There is an increased focus on potential losses among those in a positive mood, as well as a reversed effect when the level of risk is low (Keller, Lipkus, & Rimer, 2003). The hedonic contingency theory suggests that people in a positive mood will be motivated to process uplifting messages and avoid depressing or negative information. The hedonic contingency framework also suggests that people in a positive mood are more sensitive to the mood-changing consequences of their actions than people in a negative or neutral mood. People in a positive mood prefer the gain-framed message to the loss-framed message but framing effects are weaker or insignificant when people are in a negative mood. We assumed that a frustrating math test would induce a negative mood. PURPOSE The purpose of the current study was to investigate the effects of frustration and interruption on framing effects for decisions made under uncertainty. Christopher Blake, Jessica Dudeck, LaShoya Harper, Suzanne Jones, Kayla Wymore Department of Psychology The objective of this study was to test the effects of framing, frustration, and interruption on decisions made under uncertainty. Results for the scenario from the original Tversky and Kahneman (1988) study were consistent with their original findings. There was a significant effect of interruption, and a significant framing x frustration interaction. Interruption made participants more risk-averse. Frustration removes the effects of positive and negative framing originally found by Tverksy and Kahneman. Scenarios created to be more relevant to students were not significant even though previous research suggests that emotional involvement makes framing effects stronger. AbstractAbstract DiscussionDiscussion ResultsResults ReferencesReferences MethodMethod Participants received the scenario description and either choices A/B or choices C/D. Tversky & Kahneman (1988) Scenario: (Showed significant results) Imagine that the US is preparing for the outbreak of an unusual Asian disease, which is expected to kill 600 people. Two alternative programs to combat the disease have been proposed. Assume that the exact scientific estimates of the programs are as follows: If program A is adopted, 200 people will be saved. If program B is adopted, there is a 1/3 probability that 600 people will be saved, and 2/3 probability that no people will be saved. If program C is adopted 400 people will die. If program D is adopted there is a 1/3 probability that nobody will die, and 2/3 probability that 600 people will die Higher Involvement Scenarios: (None showed any significant results) Normally, 250 freshman at Missouri Western fail at least one of class. The University has two plans to help students succeed. Assume that the estimates for success are: If program A is adopted, 50 additional freshmen will pass all their classes If program B is adopted, there is a 25% chance that an additional 200 students will pass, and a 75% chance that no extra students will pass. If program C is adopted, 200 freshman will still fail at least one class If program D is adopted, there is a 25% chance that 50 students will still fail, and a 75% chance that there will be no change in the number of students who fail. Gas prices are $1.00 a gallon higher now than they were a year ago. The Energy Department has two plans to reduce the cost of gas. If program A is adopted, gas prices will go down $.50 a gallon. If program B is adopted, there is a 50% chance that gas prices will fall $1.00 a gallon and a 50% chance that they will stay the same. If program C is adopted, gas prices will still be $.50 a gallon higher than a year ago. If program D is adopted, there is a 50% chance that gas prices will be the same as a year ago, and a 50% chance that they will still be $1.00 a gallon higher. Your favorite team is expected to lose 9 games this season. The coaching staff has two plans they want to implement. If program A is adopted, your team will win an additional 3 games. If program B is adopted, your team has a 1/3 chance of winning all of their games and a 2/3 chance of not winning any additional games If program C is adopted, your team will lose 6 games. If program D is adopted, your team has a 1/3 chance of losing 0 games and a 2/3 chance of losing 9 games Decision Scenarios Participants The participants were 111 Undergraduate Students at Missouri Western State University in St. Joseph, Missouri. Materials Two versions (easy, hard) of a 50 question math test were used to either induce or not induce frustration in the participants. Four scenarios which had the participants make a decision where the outcome was either a sure thing, or where the outcome was uncertain. Two versions of each scenario were created where one version framed the outcome positively and the other version framed the outcome negatively. One scenario (regarding the outbreak of an Asian disease) was taken directly from Problem 5 in Tversky & Kahneman (1988). The other three scenarios were generated so that the choices were mathematically equivalent to each other, and the scenarios themselves were on topics that were relevant to college students. In order to track time remaining, a digital timer was displayed using digits that were approximately 10” tall. After finishing the study, participants completed a five question follow-up survey that asked about their levels of test anxiety, frustration, attention given to the decision task, effect of the wording of the scenarios, and effect of time pressure on their decisions. Procedure Each experimental session consisted of between two and 19 participants. Each session was randomly assigned to receive either the easy or hard math test and either the interrupted or non-interrupted condition. Within each session, participants randomly received either positively or negatively framed scenarios. The order of the scenarios was reversed for half of the participants. All participants were told that this was a study on math test anxiety. Participants were not allowed to use a calculator. Participants were told that they would have 7 minutes to complete tae task, and the remaining time was shown on a large digital timer. In the interrupted condition, another researcher would enter the room when the timer showed between 3:00 and 3:30 remaining. The researcher would ask if the study had already started, and the participants were told to stop working on the math test and were given the scenarios to complete. Participants were told they could resume the math test when the scenarios were finished. In the non-interrupted condition, participants were given the scenarios after seven minutes had elapsed. The final task that participants completed was a five item follow-up survey. Forster, S. & Lavie, N. (2008). Failures to ignore entirely irrelevant distracters: The role of load. Journal of Experimental Psychology: Applied, 14, 73-83. Frisch, D. (1993). Reasons for framing effects. Organizational Behavior and Human Decision Processes, 56, 399-429. Keller, P. A., Lipkus, I. M., & Rimer, B. (2003). Affect, framing, and persuasion. Journal of Marketing Research, 40, 54-64. McFarlane, D. C. (2002). Comparison of four primary methods for coordinating the interruption of people in human-computer interaction. Human-Computer Interaction, 17, 63-139. Nygren, T. E. (1998). Reacting to perceived high- and low-risk win-lose opportunities in a risky decision-making task: is it framing or affect or both? Motivation and Emotion, 22, 73-98. Seshadri, S. & Shapira Z. (2001). Managerial Allocation of time and effort: The effects of interruptions. Management Science, 47, 647-662. Tversky, A. & Kahneman, D. (1988). Rational choice and the framing of decisions. In Bell, D. E., Raiffa, H., & Tversky, A. (Eds) Decision making: Descriptive, normative, and prescriptive interactions. New York, NY, US: Cambridge University Press. Xia, L. & Sudharshan, D. (2002). Effects of interruptions on consumer online decision processes. Journal of Consumer Psychology, 12, 265- 280.
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