Mood As Cumulative Expectation Mismatch: A Test of Theory Based on Data from Non-verbal Cognitive Bias Tests

Frontiers in Psychology
Camille M C RaoultLorenz Gygax

Abstract

Affective states are known to influence behavior and cognitive processes. To assess mood (moderately long-term affective states), the cognitive judgment bias test was developed and has been widely used in various animal species. However, little is known about how mood changes, how mood can be experimentally manipulated, and how mood then feeds back into cognitive judgment. A recent theory argues that mood reflects the cumulative impact of differences between obtained outcomes and expectations. Here expectations refer to an established context. Situations in which an established context fails to match an outcome are then perceived as mismatches of expectation and outcome. We take advantage of the large number of studies published on non-verbal cognitive bias tests in recent years (95 studies with a total of 162 independent tests) to test whether cumulative mismatch could indeed have led to the observed mood changes. Based on a criteria list, we assessed whether mismatch had occurred with the experimental procedure used to induce mood (mood induction mismatch), or in the context of the non-verbal cognitive bias procedure (testing mismatch). For the mood induction mismatch, we scored the mismatch between the subjects' potential ex...Continue Reading

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Citations

Jun 13, 2019·Proceedings. Biological Sciences·Chloé LaubuFrançois-Xavier Dechaume-Moncharmont
Jun 30, 2018·Animals : an Open Access Journal From MDPI·Isabella L K Clegg
Sep 4, 2018·Frontiers in Veterinary Science·Emily V BushbyLisa M Collins
May 28, 2019·Scientific Reports·Camille M C Raoult, Lorenz Gygax
Feb 6, 2020·Journal of Animal Science·Ľubor KošťálKatarína Pichová
Jan 29, 2020·Neuroscience and Biobehavioral Reviews·Michael Mendl, Elizabeth S Paul
Nov 4, 2021·Journal of Applied Animal Welfare Science : JAAWS·Christian ManteuffelElisa Wirthgen
Nov 28, 2021·Scientific Reports·Louise KremerCornelis G van Reenen

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