Abstract
Some researchers argue that the modified Stroop task (MST) can be employed to rule out feigning. According to these authors, modified Stroop interference effects are beyond conscious control and therefore indicative of genuine psychopathology. We examined this assumption using a within-subject design. In the first session, students (N = 22) responded honestly, while in the second session they were asked to read a vignette about test anxiety and then fake this condition. During both sessions, we administered an MST consisting of neutral, anxiety-related, and test anxiety-related words. Participants also completed the Self-Report Symptom Inventory (SRSI; Merten et al., 2016) that focuses on over-reporting of pseudosymptoms. Our feigning instructions were successful in that students succeeded in generating the typical MST effect by providing longer response latencies on anxiety related (r = 0.43) and test anxiety-related (r = 0.31) words, compared with neutral words. Furthermore, students endorsed significantly more pseudosymptoms on the SRSI (r = 0.62) in the feigning session than in the honest control condition. We conclude that the MST effect is not immune to feigning tendencies, while the SRSI provides promising results that require future research.
Original language | English |
---|---|
Article number | 1195 |
Journal | Frontiers in Psychology |
Volume | 9 |
DOIs | |
Publication status | Published - 11 Jul 2018 |
Fingerprint
Dive into the research topics of 'The modified stroop task is susceptible to feigning: stroop performance and symptom over-endorsement in feigned test anxiety'. Together they form a unique fingerprint.Datasets
-
Data availability statement for 'The modified stroop task is susceptible to feigning: stroop performance and symptom over-endorsement in feigned test anxiety'.
Boskovic, I. (Creator), Biermans, A. J. (Creator), Merten, T. (Creator), Jelicic, M. (Creator), Hope, L. (Creator) & Merckelbach, H. (Creator), Frontiers Media S. A., 11 Jul 2018
DOI: https://doi.org/10.3389/fpsyg.2018.01195
Dataset