Development and validation of Image Stimuli for Emotion Elicitation (ISEE): A novel affective pictorial system with test-retest repeatability. (March 2018)

• Record Type: Journal Article
• Authors: Kim, Hanjoo; Lu, Xin; Costa, Michael; Kandemir, Baris; Adams, Reginald B.; Li, Jia; Wang, James Z.; Newman, Michelle G.
• Is Part Of: Psychiatry research. Volume 261(2018)
• Page Start: 414
• Page End: 420
• Publication Date: 2018-03
• Subjects: Emotion elicitation -- Pictorial stimuli -- Emotional dimensions -- Test-retest analysis -- Repeatability -- Reliability -- Agreement -- Pearson correlation analysis -- Bland-Altman analysis; Psychiatry -- Periodicals; Psychiatry -- periodicals; Psychiatrie -- Périodiques; 616.89
• DOI: 10.1016/j.psychres.2017.12.068
• Languages: English
• ISSNs: 0165-1781

Abstract

Abstract: The aim of this study was to develop a novel set of pictorial stimuli for emotion elicitation. The Image Stimuli for Emotion Elicitation (ISEE), are the first set of stimuli for which there was an unbiased initial selection method and with images specifically selected for high retest correlation coefficients and high agreement across time. In order to protect against a researcher's subjective bias in screening initial pictures, we crawled 10, 696 images from the biggest image hosting website (Flickr.com) based on a computational selection method. In the initial screening study, participants rated stimuli twice for emotion elicitation across a 1-week interval and 1620 images were selected based on the number of ratings of participants and retest reliability of each picture. Using this set of stimuli, a second phase of the study was conducted, again having participants rate images twice with a 1-week interval, in which we found a total of 158 unique images that elicited various levels of emotionality with both good reliability and good agreement over time. The newly developed pictorial stimuli set is expected to facilitate cumulative science on human emotions. Highlights: We developed a novel set of pictorial stimuli which have good repeatability. We applied computational selection methods to protect against a subjective bias. Each of two studies consisted of two consecutive experiments with 1-week interval. For data analysis, we conducted correlation analysis and agreement test. A total of 158 unique images were validated for repeatability.