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Feigned ADHD Results

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  • Pages: 3
  • Word count: 594
  • Category: Adhd Child

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The main aim of this study was to address the lack of research evidence on the validity of CAARS in the detection of feigned ADHD. Accordingly, the practical contribution of the present research is that it provides much needed empirical data on the CII Index which was specially developed to detect non-credible responding and showed reasonable sensitivity and an excellent specificity in the initial validation (Suhr et al., 2011a).

In our first hypothesis, we predicted that instructed malingerers would score higher than genuine ADHD patients and control participants on CII (suspect score 21 or higher). We performed the appropriate test to know whether there were significant differences among these conditions and the results are shown in Table 3. The Kruskal-Wallis test is based on a single factor entered into the analysis; therefore η² equals ηp² as no other variable accounts for variance in the dependent variable. The effect size of group differences was medium and it showed that 38% of the change in the dependent variable can be accounted for by the independent variable (see Table 2). The difference between Instructed malingerers and genuine ADHD patients showed a significant difference only when Bonferroni adjustment was not used (see Table 3). Moreover, there was a significant difference between Instructed simulators and Control group with or without the adjustment. However, 44% of instructed simulators scored in a range that indicated non-credible responding, therefore, the hypothesis was not supported. This is in line with the results of the study by Fuermaier et al. (2016) where CII was unable to distinguish between people with genuine symptoms with sufficient accuracy.

Next, we tested our second hypothesis which claims that the majority of instructed malingerers would score in a believable range of ADHD on INC, Inattention, and Hyperactivity/Impulsivity Scale. On INC, 84% of instructed simulators scored in a believable range of ADHD. On Inattention, 55 % of instructed simulators scored in a believable range and 61% of them scored in a believable range on Hyperactivity/Impulsivity Scale (Table 2). This seems to support the claim of Musso & Gouvier (2014) that the initial CAARS (Conners et al., 1999) containing only the Inconsistency Index has poor sensitivity to detect feigners.

The current study has several limitations that should be addressed to guide future research. Namely the motive to feign ADHD in an experimental setting is not representative of real-life situations in clinical practice (Rogers, Harrell, & Liff, 1993). Therefore, another research design such as known-groups comparisons might be more appropriate. This design may also implement groups of individuals with differing severities of ADHD condition as 35% of genuine ADHD patients (N=40) were also indicated as feigners on CII. This could be attributed to a significantly smaller ADHD group. Therefore, it can be investigated whether the severity of ADHD has an impact on the possibility of symptom exaggeration in genuine ADHD patients.

Concluded on the basis of the presented literature review and the results obtained from the current study, there is an urgent need for more testing and development of measures that are specifically designed for the identification of feigned ADHD. Recently developed ADHD Symptom Infrequency Scale (ASIS) by Courrégé et al. (2019) shows promising results. This novel tool, designed to detect rarely endorsed symptoms of ADHD in genuine patients, demonstrated higher sensitivity than available ADHD rating scales with similar specificity. However, one limitation of the study was that the participants were notably older than typical university students where ADHD assessment is more frequent (Courrégé et al., 2019). Future research could focus on further validation of this scale including a sample of individuals of traditional college age.

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