Dorien Bangma

FDM IN NEURODEGENERATIVE DISEASES | 67 16. The subscale ‘money usage’ of the Numerical Activities of Daily Living (NADL; Semenza et al., 2014) can be used to evaluate financial capacity as a function of (basic) mathematical abilities. The NADL assesses basic aspects of mathematical abilities and their impact on daily life, including the use of money. A score can be calculated based on the number of reasonably estimated prices (e.g., estimating the price of a car), with higher scores indicating better financial mathematical capacity. The subscale ‘money usage’ of the NADL is used in one study included in this review (i.e., Benavides-Varela et al., 2015). 17. The subscale ‘money-related skills’ of the Structured Assessment of Independent Living Skills (SAILS; Mahurin et al., 1991) evaluates FDM as part of a larger instrument that can be used to directly evaluate everyday activities. The subscale ‘money-related skills’ consists of five money-related activities, including counting money, making change, understanding a monthly utility bill, writing a check and understanding a checkbook. A total score, based on all five activities, can be calculated for the subscale with higher scores indicating better money-related skills. The subscale ‘money-related skills’ of the SAILS is used in one study included in this review (i.e., Mahurin et al., 1991). 18. The subscale ‘finances’ of the University of California, San Diego (UCSD) performance-based skills assessment (Patterson et al., 2001) assesses financial skills using two tasks, i.e., (1) counting coins and making change and (2) make out a check. A total score can be calculated based on the number of correct elements achieved on both tasks. Higher scores indicate better financial skills. The subscale ‘finances’ of the UCSD performance based skills assessment is used in two studies included in this review (i.e., Pirogovsky et al., 2014, 2013). 19. The subscale ‘money management’ of the University of Miami computer-based functional assessment battery (UMCFAB; Czaja et al., 2017) evaluates money management abilities using a computer-based replication of an Automatic Teller Machine (ATM). The performance-based ATM requires individuals to perform money related actions, such as checking the balance in their savings account, transferring money or withdrawing cash from their savings account. Different scores can be calculated, i.e., ‘total correct answers’, ‘total incorrect answers’, ‘task completion time’ and ‘an efficiency/rate score based on total correct answers divided by task completion time’. The subscale ‘money management’ of the UMCFAB is used in one study included in this review (i.e., Czaja et al., 2017). Study analysis Content analysis. A content analysis approach was applied to the included studies. The results were organized and extracted in table format for each disorder separately displaying demographics and disease characteristics of the included samples. In addition, primary outcome measures and the most important results of each paper relevant for the research questions at hand are described (Table 4.2). Some studies describe the use of participants from the same study cohort, i.e., from the Cognitive Observations in Seniors Study ( COINS ; Clark et al., 2014; Gerstenecker et al., 2016, 2018, 2019; Gerstenecker, Hoagey, et al., 2017; Niccolai et al., 2017)