Sequential dependency for affective appraisal of food images

Autor: Alexander Toet, Abadi Gebre Mezgebe, Henriëtte L. de Kock, Youjin Kim, Zahra Abbasi, Victor Kallen, Anne-Marie Brouwer, Jan B. F. van Erp, Emily MacEachern, G. O. Olatunde, Erik Van der Burg, Tzong-Ru Lee, Muhammad Rizwan Tahir, Wilis Srisayekti, Merve Aslıhan Yürek, Rouja Nikolova, Bohdan L. Luhovyy, Shota Ushiama, Yingxuan Liu, Marise Kinnear, Dyah Kusbiantari, Daisuke Kaneko
Přispěvatelé: Brein en Cognitie (Psychologie, FMG), Brain and Cognition, Human Media Interaction
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Humanities and Social Sciences Communications, 8:228. Springer Nature
Humanities and Social Sciences Communications, 8(1):228. Springer
Humanities & Social Sciences Communications, Vol 8, Iss 1, Pp 1-11 (2021)
ISSN: 2662-9992
Popis: How we perceive the world is not solely determined by our experiences at a given moment in time, but also by what we have experienced in our immediate past. Here, we investigated whether such sequential effects influence the affective appraisal of food images. Participants from 16 different countries (N = 1278) watched a randomly presented sequence of 60 different food images and reported their affective appraisal of each image in terms of valence and arousal. For both measures, we conducted an inter-trial analysis, based on whether the rating on the preceding trial(s) was low or high. The analyses showed that valence and arousal ratings for a given food image are both assimilated towards the ratings on the previous trial (i.e., a positive serial dependence). For a given trial, the arousal rating depends on the arousal ratings up to three trials back. For valence, we observed a positive dependence for the immediately preceding trial only, while a negative (repulsive) dependence was present up to four trials back. These inter-trial effects were larger for males than for females, but independent of the participants’ BMI, age, and cultural background. The results of this exploratory study may be relevant for the design of websites of food delivery services and restaurant menus.
Databáze: OpenAIRE