Abstract
Objective:Typical evaluations of adult ADHD consist of behavior self-report rating scales, cognitive or intellectual functioning measures, and specific measures designed to measure attention. Boone (2009) suggested monitoring continuous effort is essential throughout psychological assessments. However, very few research studies have contributed to malingering literature on the ADHD population. Many studies have reported the adequate use of symptom validity tests, which assess effortful performance in ADHD evaluations (Jasinski et al., 2011; Sollman et al., 2010; Schneider et al., 2014). Because of the length of ADHD assessments, individuals are likely to become weary and tired, thus impacting their performance. This study investigates the eye movement strategies used by a clinical ADHD population, non-ADHD subjects, and malingering simulators when playing a common simple visual search task.Participants and Methods:A total of 153 college students participated in this study. To be placed in the ADHD group, a participant must endorse four or more symptoms on the ASRS (N = 37). To be placed in the non-ADHD, participants should have endorsed no ADHD symptoms (N = 43). Participants that did not meet the above criteria for ADHD and not-ADHD were placed in an Indeterminate group and were not included in the analysis. A total of 20 participants were instructed to fake symptoms related to ADHD during the session. A total of twelve Spot the Difference images were used as the visual picture stimuli. Sticky by Tobii Pro (2020) was used for the collection of eye-movement data was utilized. Sticky by Tobii Pro is an online self-service platform that combines online survey questions with an eye-tracking webcam, allowing participants to see images from their home computers.Results:Results indicated on the participants classified as Malingering had a significantly Visit Count (M = 17.16; SD= 4.99) compared to the ADHD(M = 12.53; SD= 43.92) and not-ADHD groups (M =11.51; SD=3.23). Results also indicated a statistically significant Area Under the Curve (AUC) = .784; SE = .067; p -.003; 95% CI = .652-.916. Optimal cutoffs suggest a Sensitivity of 50% with a False Positive Rate of 10%.Conclusions:Results indicated that eye-tracking technology could help differentiate simulator malingerers from non-malingerers with ADHD. Eye-tracking research’ relates to a patchwork of fields more diverse than the study of perceptual systems. Due to their close relation to attentional mechanisms, the study’s results can provide an insight into cognitive processes related to malingering performance.
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