Abstract
Conflict adaptation can be measured by the “congruency sequence effect”, denoting the reduction of congruency effects after incongruent trials (where response conflict occurs) relative to congruent trials (without response conflict). Recently, it has been reported that conflict adaptation is larger in negative mood than in positive mood (van Steenbergen et al., Psychological Science 21:1629–1634, 2010). We conducted two experiments further investigating this important finding. Two different interference paradigms were applied to measure conflict adaptation: Experiment 1 was a Flanker task, Experiment 2 was a Stroop-like task. To get as pure a measure of conflict adaptation as possible, we minimized the influence of trial-to-trial priming effects by excluding all kinds of stimulus repetitions. Mood states were induced by presenting film clips with emotional content prior to the interference task. Three mood states were manipulated between subjects: amused, anxious, and sad. Across both interference paradigms, we consistently found conflict adaptation in negative, but not in positive mood. Taken together with van Steenbergen et al. (Psychological Science 21:1629–1634, 2010) findings, the results suggest that the negative-mood-triggered increase in conflict adaptation is a general phenomenon that occurs independently of the particular mood-induction procedure and interference paradigm involved.
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Notes
The questionnaire data were also analyzed in 3 × 3 ANOVAs with Group (amused, anxious, sad) and time point (before mood induction, after mood induction, after RT experiment) as independent variables. For the STAI state scale, the ANOVA yielded a significant interaction, F(4,114) = 6.73, p < 0.01, as well as a main effect of time point, F(2,114) = 17.62, p < 0.01, and no effect of mood group, F < 1. A preplanned contrast comparing the time points “before mood induction” and “after mood induction” revealed a significant interaction, F(2,57) = 10.34, p < 0.01. The respective ANOVA on the PANAS negative affect scale also yielded a significant interaction, F(4,114) = 3.37, p = 0.01, as well as a main effect of time point, F(2,114) = 8.88, p < 0.01, and no main effect of mood group, F < 1. The preplanned contrast comparing the time points “before mood induction” and “after mood induction” revealed a significant interaction, F(2,57) = 5.02, p = 0.01. As to the PANAS positive affect scale, there was also a significant interaction, F(4,114) = 3.06, p = 0.02, a main effect of time point, F(2,114) = 7.63, p < 0.01, and no effect of mood group, F < 1. The preplanned contrast comparing the time points “before mood induction” and “after mood induction” did not reveal a significant interaction, F(2,57) = 1.45, p = 0.24.
For the STAI state scale, the 3 × 3 ANOVA yielded a significant interaction, F(4,114) = 7.11, p < 0.01, as well as a main effect of time point, F(2,114) = 22.62, p < 0.01, and no effect of mood group, F < 1. A preplanned contrast comparing the time points “before mood induction” and “after mood induction” revealed a significant interaction, F(2,57) = 9.53, p < 0.01. The respective ANOVA on the PANAS negative affect scale did not yield a significant interaction, F(4,114) = 1.61, p = 0.18; there was a main effect of time point, F(2,114) = 14.40, p < 0.01, and no main effect of mood group, F < 1. The preplanned contrast comparing the time points “before mood induction” and “after mood induction” did not reveal a significant interaction with mood group, F(2,57) = 1.53, p = 0.23. As to the PANAS positive affect scale, the 3 × 3 interaction was not significant, F(4,114) = 1.79, p = 0.14; there was a main effect of time point, F(2,114) = 4.68, p = 0.01, and no effect of mood group, F < 1. The preplanned contrast comparing the time points “before mood induction” and “after mood induction” revealed a significant interaction, F(2,57) = 5.36, p < 0.01.
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We would like to thank Manuela Valencia Piedrahita for help with data collection.
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Schuch, S., Koch, I. Mood states influence cognitive control: the case of conflict adaptation. Psychological Research 79, 759–772 (2015). https://doi.org/10.1007/s00426-014-0602-4
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DOI: https://doi.org/10.1007/s00426-014-0602-4