Attention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder characterized by persistent patterns of inattention, distractibility, hyperactivity, and impulsivity, which interfere with functioning or development (1). ADHD is associated with an elevated risk of other mental health disorders and adverse outcomes such as educational underachievement, employment difficulties, interpersonal relationship challenges, and potential involvement in criminal activities (2). These far-reaching impacts make accurate and reliable ADHD assessments critical for both clinical and research purposes. Diagnosing ADHD involves various methods, including clinical interviews, continuous performance tests, and behavioral rating scales. Best practices recommends triangulating information via a comprehensive diagnostic approach that synthesizes information from multiple sources, such as structured interviews, cognitive assessments, and behavioral rating scales (3, 4). However, in research contexts—particularly studies exploring new treatment approaches—behavioral rating scales are often the preferred outcome measure due to their cost-effectiveness, ease of administration, and accessibility (5–10). While this pragmatic choice is often driven by resource constraints that limit the feasibility of more comprehensive assessment procedures (11), it highlights a critical responsibility for researchers: ensuring the data collected through these scales accurately represent the genuine experiences of respondents. Selecting the appropriate scale is not just a matter of practicality—it is foundational to producing reliable, meaningful research outcomes. However, behavioral rating scales are not without their challenges. Their inherent subjectivity makes them vulnerable to feigned or exaggerated symptom reporting, which can compromise the validity of findings, and hinder scientific progress. To mitigate these risks, researchers need to remain vigilant about advancements in ADHD assessment methodologies, particularly the development of tools designed to detect invalid or exaggerated symptom presentations. These tools play a crucial role in distinguishing genuine cases from noncredible reports, ensuring that research findings are both reliable and meaningful. Without this level of scrutiny, studies risk being undermined by data that fail to accurately represent the true experiences of participants. In this opinion paper, we aim to provide researchers with an overview of the most widely used ADHD rating scales, focusing specifically on their capacity to detect malingering—’the intentional production of false or grossly exaggerated physical or psychological symptoms, motivated by external incentives (1). Additionally, we offer practical recommendations to guide researchers in selecting assessment tools that maximize diagnostic accuracy, enhancing the reliability and validity of their research. By addressing the challenges of malingering and invalid symptom reporting, we aim to contribute to the development of more robust ADHD evaluation strategies to allow the needed scientific progress.
Grandjean, M., & et al. (2025). Malingering in ADHD behavioral rating scales: recommendations for research contexts. Frontiers in Psychiatry. Published. https://doi.org/10.3389/fpsyt.2025.1532807 (Original work published 2025)