Structural equation modeling reveals ADHD traits reduce decision-making quality in students, indicating issues with attention and delay discounting.
Research has associated attention-deficit/hyperactivity disorder (ADHD) with difficulties in executive functions, such as working memory, sustained attention, and inhibitory control, as well as with motivational alterations, including steep delay discounting. However, few studies have examined how these processes jointly contribute to ADHD-related decision-making within an integrative framework. To address this gap, the present study examined delay discounting and executive functions as predictors of decision-making performance under risk, with the aim of clarifying how suboptimal decision-making may be expressed in individuals with elevated ADHD traits. Sixty-three university students completed a behavioral battery assessing working memory, sustained attention, response inhibition, and decision-making on the Cambridge Gambling Task (CGT). Delay discounting was measured using the five-trial adjusting delay task, and ADHD traits were assessed with the Adult ADHD Self-Report Scale. Hypothesized relationships among these variables were examined using structural equation modeling (SEM). ADHD trait scores were negatively correlated with the CGT indices of decision-making quality and risk adjustment. Working memory errors were most strongly associated with poorer CGT performance, with sustained attention and response inhibition showing weaker associations. SEM indicated sequential indirect pathways linking steeper delay discounting to higher ADHD traits through reduced sustained attention, increased working-memory errors, and poorer CGT performance. The findings support a multi-pathway account of ADHD traits, suggesting that motivational (delay discounting) and executive (working memory, attention, inhibition) mechanisms jointly contribute to suboptimal decision-making under risk. This integrative framework advances understanding of the cognitive and motivational mechanisms underlying ADHD-related decision processes and may inform future assessment and intervention approaches.
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Ikegami et al. (2026) studied this question.
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