In our lead up to #ICA25, we are providing information about papers that received Top Paper awards from the Communication Science and Biology (CSaB) Interest Group. Each paper received exceptionally high scores from reviewers. These papers reflect outstanding scholarship in CSaB. Today’s Top Paper features Ma, Haworth, & Hu paper: “Effects of Narrative versus Non-Narrative Pictorial Warning Labels on Visual Attention and Alcohol-Related Cancer Risk Perceptions: An Eye-Tracking Study”. Be sure to check out the paper at #ICA25.
In a few short sentences, what is your study about?
We conducted an online, webcam-based eye-tracking experiment with moderate and heavy drinkers. Participants viewed either three narrative pictorial warning labels (PWLs) or three non-narrative PWLs, presented one at a time. Narrative PWLs included photos of cancer patients and non-narrative PWLs had images of diseased organs. Both warning types included the same text warning statement. Across both conditions, participants paid more attention to the image than to the text. They also spent more time viewing the narrative PWLs compared to the non-narrative ones; however, their risk perceptions did not differ between warning types.
How did you come up with the idea for this line of research?
The first author, Dr. Ma, has always been interested in narrative persuasion research and wanted to explore whether the persuasive advantage of narratives might be extended to still images. Because a major mechanism through which narratives exert persuasive influence is by engaging attention, she wanted to examine whether narrative PWLs better attract attention than non-narrative graphic PWLs.
Anything else you would like to add?
This was our first time using Sticky by Tobii, a webcam-based eye-tracking platform. We enjoyed many benefits it brings, particularly the ability to collect data remotely without requiring in-person sessions. However, we also encountered several challenges related to its technological limitations. I’d be happy to share more about our experience if anyone is interested in using it.
We also wanted to acknowledge that this project was funded by NIH (7R03CA273391-02). This work would not have been made possible without their support.
Tell us more about the team!
The team consists of a communication scientist (Dr. Ma), an eye-tracking expert (Dr. Haworth), and a statistician (Dr. Hu). Dr. Ma met and started working with Drs. Haworth and Hu at her previous institution, Oakland University.