Dorien Bangma

FDM IN ADULTS WITH ADHD | 175 (when applying the conservative p-value of p £ .01). There is thus no strong evidence that comorbid disorders, including substance dependency, account for the group differences between adults with ADHD and healthy controls found on objective measures of FDM. A second limitation of the present study is that researchers were not blind to the diagnosis of participants, which might have led to an observer bias. However, the use of a protocolary and objective approach for both the assessment and scoring probably minimized this effect. Third, although all healthy controls indicated to not have ADHD, no clinical evaluation of ADHD has been performed in these participants. Self-report questionnaires for current and retrospective symptoms of ADHD were used to give additional support to the diagnostic status of the participants, however, due to underreporting of symptoms (Sibley et al., 2019) and the under-diagnosis of adult ADHD (Ginsberg et al., 2014) it is conceivable that adults with ADHD are included in the healthy control group. Fourth, adults with ADHD were off medication during assessment and it is, therefore, unclear what the effect of stimulants will be on their performances on measures of FDM. Not only the stimulant itself, but also the onset of medication use and other treatments (e.g., cognitive behavioral therapy or coaching) might have an influence on FDM. The influence of treatment use should, therefore, be explored in future research on FDM and adults with ADHD. Fifth, other confounding factors should be considered in more detail in future research. For example, childhood socioeconomic status and parental education level may be of influence on one’s personal financial situation and the ability to make financial decisions. Also, the motivation of participants should be evaluated. Especially in adults with ADHD, less optimal decision-making seems to be related to experienced boredom while making a decision (Matthies et al., 2012). Boredom may play a role in the assessment of relatively simple aspects of FDM (e.g., financial competence or capacity). Furthermore, the personal financial situation of participants was evaluated using self-report measures and only approximate indications of income, free money to spend, and amount of social security were asked. These questions rely on a good insight of one’s own personal financial situation, which may not always be sufficient in adults with ADHD as well as in healthy controls. Finally, it has to be pointed out that the ecological validity of the FDM test battery needs further investigation in order to determine to what extent these impaired test performances translate into problems of daily life. Nevertheless, the current study is the first to explore FDM in adults with ADHD by using self-report as well as standardized objective FDM tests and by including a sample of adults with a broad age range as well as including males and females with ADHD alike. Adults with ADHD were found to have difficulties with several aspects of FDM, i.e., evaluating financial problems (i.e., financial decision-making capacity), understanding bank statements/protocols (i.e., financial competence), financial decisions with implications for the future and impulsive buying. Furthermore, adults with ADHD more often used an avoidant and a spontaneous decision-making style when making financial decisions than healthy controls. When applying a more clinical approach, 34.2% of adults with ADHD are classified as impaired on at least one aspect of FDM compared to 19.6% of healthy controls, with a large number of adults with ADHD showing impairment in financial competence (i.e., 26.7% of adults with ADHD have an impaired performance on the FCAI compared to 2.0% of healthy controls). These difficulties