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Concealed avoidance testing: response strategies of instructed malingerers during forced choice testing: new measures and criteria to detect concealed knowledge and feigned cognitive deficits

Student thesis: Doctoral Thesis

The Forced Choice Test (FCT) can be used to detect malingered loss of memory for a specific event or malingered cognitive deficits. This test consists out of binary multiple choice questions. The idea is that genuine impairment will force examinees to guess, resulting in test scores that fall within chance performance. In contrast, malingerers are expected to select incorrect answers purposefully, leading to test scores below chance performance (i.e. underperformance). Four empirical studies were conducted on the FCT with two aims in mind. First, to develop a better theoretical understanding of malingerers’ response strategies in the FCT. Second, to increase the detection accuracy of the FCT and optimize the decision making process for single case decision.
In Chapter 2 we address the lack of a theoretical foundation for malingerers’ behaviour by proposing a model that defines three distinct response strategies. With an empirical experiment we demonstrate that the proposed model fits the data well and conclude that that malingerers’ choice of response strategy can be influenced by the examiner. Furthermore, our model suggests that the traditionally used underperformance criterion is only sensitive to one of the three subgroups and that this group is actually a minority within the malingerer population. Based on these results we propose two pathways to improve the detection accuracy of the FCT.
First, detection accuracy can be improved by promoting the prevalence of response strategies the underperformance criterion detects well. In Chapter 3 we attempt to do that by introducing cognitive load to the FCT paradigm. However, instead of affecting malingerers’ strategy selected, cognitive load affected the quality of their chosen strategies. Although unexpected, these findings provide another angle to influence the detection rate of the FCT. Nonetheless, further disambiguation is required.
Second, detection accuracy can be improved by adding new criteria to the FCT that are sensitive to the remaining subgroups. In Chapters 4 and 5 we investigate the effectives of the ‘runs test’ and a within test response bias. Both criteria proved effective in detecting a subgroup that manages to avoid the underperformance criterion and the usefulness of a two-step classification procedure is discussed.
Finally, this thesis end with a reflection on the validity of our model based on the aggregated data from all previous chapters and a discussion about the decision making process. This is followed by a reflection on experimental limitations as well as recommendations for practical application
Original languageEnglish
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Award dateNov 2018

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