Carie Cunningham, Tao Deng, Crystal Miller, Jessica Francis & Ran Duan (Michigan State University, USA)
Summary of the Project
Universities and colleges striving to be more sustainable are employing multiple strategies to reduce the 3.6 million tons of solid waste produced on college campuses in the United States (Saphire, 1998). One way campuses are combatting this problem is with communication to students, faculty, and staff through campaign posters promoting sustainable food practices. These posters are designed to be esthetically pleasing, but often do not have strategic placement or colors for efficient cognitive processing.
This work in progress uses Feature Integration Theory (FIT) to help explain why some parts of a campaign poster are remembered while others are not. Specifically, this paper examines the effects of arousal on the areas that capture attention in a poster.
RQ1: How does color affect the area of attention?
RQ2: How does arousal affect the area of attention?
RQ3: What are the interaction effects between color and arousal on the area of attention?
Feature Integration Theory (FIT) explains that for attention to be given to one specific stimulus or icon, there must first be basic visual processing. Treisman and Gelade (1980) explain that initial visual processes happen in parallel where certain features of a stimulus are registered early and automatically, the preattentive stage. The preattentive stage draws out the features of a stimulus to then later combine these features in detail to form the stimulus (Treisman & Gelade, 1980).
Winner Takes All (WTA) says that high contrast areas (areas of interest) can promote attention to a stimulus. The WTA effect is greatest when the desired area of interest (in this case the message) is in the highest contrast with the environment (the background of the poster) (Koch & Ullman, 1985). These “features of a stimulus” that attract attention to the area of interest come in many forms: “length, closure, size, curvature, density, number, hue, luminance, intersections, terminators, 3D depth, flicker, and lighting direction” (Healy & Enns, 2012, p. 3). These are characteristics that are employed to capture attention.
Motivational Variables. Attention can be magnified with the addition of motivational variables. In mass media, Wang et al. (2012) identified three basic message motivational variables: arousing content, positivity (appetitiveness) and negativity (aversiveness). Arousing content or arousal determines how intense the motivational systems will react and attend to a stimulus (Wang et al., 2012).
The study employed a 2×2 between-subjects factorial design to test the relationship of arousal (high vs. low) and color (red vs. blue) on participant’s identification of areas of interest. The independent variable in this study was level of arousal and color of the poster. The dependent variable was high contrast area. Other variables that were examined were recall, involvement, attitude, and demographics.
Pretest. The study’s stimuli were pretested into high and low perceived arousal using the miniMAM (Lang et al., 2011). Thirty students evaluated 15 posters in a controlled lab setting. Participants were asked to evaluate the emotional tone of each poster and to rate each poster on a 7-point scale for arousal, positivity, and negativity.
Main test. The six poster, as a result of the pretest, were modified into red and blue versions using image processing software. The color red contains different shades of red with one bright red (R255, G0, B0) as dominant color. Similarly, the color blue contains different shades of blue with bright blue (R0, G100, B255) dominates the posters. A total of 12 posters were produced for the four condition groups (high arousing/red, low arousing/red, high arousing/blue, and low arousing/blue).
147 student participants were recruited from a large Midwest university for the main test. Participants were randomly assigned to the four condition groups. Each group evaluated three posters. During the main test, participants were asked to click (up to ten times) the area in each poster that draws their attention (See Appendix A). Following the viewing of each poster, participants were asked to answer additional questions including demographics, recall, attitude, and involvement.
After a preliminary analysis, the color change (RQ1: How does color affect the area of attention?) was not statically significant between groups and thus, the groups were combined to form a high arousal group and a low arousal group. Specifically, the color differences between groups (high arousal) (n=72) and (low arousal) (n= 75) were not significant, despite the pretest, and thus, the groups were analyzed as either high arousal or low arousal.
A Chi-square analysis found that the difference in area of attention between the high and low arousal groups is statistically significant (X2 (2) = 4.28, p <.05), indicating arousal level has an effect on area of attention, thereby answering RQ2. Future analysis on the interaction effects of color and arousal will be ran to answer RQ3. To that end, multivariate analysis of variance (MANOVA) and mean comparison of in different arousal groups are needed.
Healey, C. G., & Enns, J. T. (2012). Attention and visual memory in visualization and computer graphics. Visualization and Computer Graphics, IEEE Transactions on, 18(7), 1170-1188.
Koch, C., & Ullman, S. (1985). Shifts in selective visual attention: Towards the underlying neural circuitry. Human Neurobiology, 4, 219–227.
Lang, A., Potter, R., Kurita, S., & Rubenking, B. (2011). MiniMAM: Validating a short version of the motivation activation measure. Communication Methods and Measures, 5(2), 146-162.
Saphire, D. (1998). Getting An “A” in Lunch: Smart Strategies to Reduce Waste in Campus Dining. INFORM. Retrieved December 2, 2014, from http://informinc.org/reportpdfs/wp/GettinganA.pdf
Treisman, A.M., & Gelade, G. (1980). A feature-integration theory of attention. Cognitive Psychology, 12(1), 97-136.
Wang, Z., & Lang, A. (2012). Reconceptualizing excitation transfer as motivational activation changes and a test of the television program context effects. Media Psychology, 15(1), 68-92.
Initial results showed color of the poster has no effect on people’s attention on specific areas on the poster. To fully answer RQ1, follow up analyses are needed to find out the effects of color on attention, especially under different arousal level. Although these results are preliminary, the data seems to suggest that arousal differences can lead to attention differences in the areas of interest. This may imply that some messages on sustainability posters are not completely processed due to their attentional areas being misplaced. In this case, low arousing images (more than high arousing images or high arousing information or low arousing information) seemed to be more attractive to the viewer. There are still many more analyses, the researchers would like to run MANOVA and mean comparisons between condition groups to answer RQ3. In addition, effects of possible moderators and mediators need to be studied.
This study only used sustainable food consumption posters and thus may not be generalizable to other types of visual messages. In future research, more accurate data can be collected through the use of an eye tracker, instead of a self-report survey. Where actual fixation on the areas of interest occurs, instead of the perceived, self-reported areas of interest.