Speaker
Description
The Activation-Decision-Construction-Action-Theory (ADCAT), offers a promising avenue for refining malingering detection. ADCAT is a cognitive model for high-stakes deception that employs a cost-benefit formula to elucidate the cognitive, motivational, and social mechanisms underlying the decision to lie or tell the truth. Building upon existing research, the present study aims to explore the application of the ADCAT cost-benefit analysis across different malingering scenarios, recording both initial and final decisions after the ADCAT Decision protocol application. Results reveal dynamic shifts in participant responses, with increased feigning observed in some scenarios from initial to final decisions, while others exhibit reversals from feigning to honesty. Significant differences in ADCAT scores suggest feigners weigh honesty's advantages but prioritize feigning for benefits. Conversely, honest individuals recognize honesty's disadvantages but prioritize avoiding feigning risks, despite potential benefits. This underscores the ADCAT protocol's capacity for a cost-benefit evaluation, extending beyond binary choice. Furthermore, Discriminant Function Analyses demonstrate robust predictive power for final decisions, with EVHonesty, EVMalingering, and MMalingering significantly contributing to decision outcomes. These findings advance our understanding of decision-making in malingering, emphasizing situational variability and multifaceted motivations.
