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Beyond well-established difficulties with working memory in individuals with attention deficit hyperactivity disorder (ADHD), evidence is emerging that other memory processes may also be affected. We investigated, first, which memory processes show differences in adults and adolescents with ADHD in comparison to control participants, focusing on working and short-term memory, initial learning, interference, delayed and recognition memory. Second, we investigated whether ADHD severity, co-occurring depressive symptoms, IQ and physical fitness are associated with the memory performance in the individuals with ADHD.
We assessed 205 participants with ADHD (mean age 25.8 years, SD 7.99) and 50 control participants (mean age 21.1 years, SD 5.07) on cognitive tasks including the digit span forward (DSF) and backward (DSB), the Rey Auditory Verbal Learning Test (RAVLT), and the vocabulary and matrix reasoning subtests of the Wechsler Abbreviated Scale of Intelligence. Participants with ADHD were additionally assessed on ADHD severity, depression symptoms and cardiorespiratory fitness. A series of regressions were run, with sensitivity analyses performed when variables were skewed.
ADHD-control comparisons were significant for DSF, DSB, delayed and recognition memory, with people with ADHD performing less well than the control participants. The result for recognition memory was no longer significant in sensitivity analysis. Memory performance was not associated with greater ADHD or depression symptoms severity. IQ was positively associated with all memory variables except DSF. Cardiorespiratory fitness was negatively associated with the majority of RAVLT variables.
Individuals with ADHD showed difficulties with working memory, short-term memory and delayed memory, as well as a potential difficulty with recognition memory, despite preserved initial learning.
Exercise interventions in mental disorders have evidenced a mood-enhancing effect. However, the association between physical activity and affect in everyday life has not been investigated in adult individuals with ADHD, despite being important features of this disorder. As physical activity and affect are dynamic processes in nature, assessing those in everyday life with e-diaries and wearables, has become the gold standard. Thus, we used an mHealth approach to prospectively assess physical activity and affect processes in individuals with ADHD and controls aged 14–45 years. Participants wore accelerometers across a four-day period and reported their affect via e-diaries twelve times daily. We used multilevel models to identify the within-subject effects of physical activity on positive and negative affect. We split our sample into three groups: 1. individuals with ADHD who were predominantly inattentive (n = 48), 2. individuals with ADHD having a combined presentation (i.e., being inattentive and hyperactive; n = 95), and 3. controls (n = 42). Our analyses revealed a significant cross-level interaction (F(2, 135.072)=5.733, p = 0.004) of physical activity and group on positive affect. In details, all groups showed a positive association between physical activity and positive affect. Individuals with a combined presentation significantly showed the steepest slope of physical activity on positive affect (slope_inattentive=0.005, p<0.001; slope_combined=0.009, p<0.001; slope_controls=0.004, p = 0.008). Our analyses on negative affect revealed a negative association only in the individuals with a combined presentation (slope=-0.003; p = 0.001). Whether this specifically pronounced association in individuals being more hyperactive might be a mechanism reinforcing hyperactivity needs to be empirically clarified in future studies.
the benefits of physical activity (PA) and sleep for health, accurate and objective population-based surveillance is important. Monitor-based surveillance has potential, but the main challenge is the need for replicable outcomes from different monitors. This study investigated the agreement of movement behavior outcomes assessed with four research-grade activity monitors (i.e., Movisens Move4, ActiGraph GT3X+, GENEActiv, and Axivity AX3) in adults. Twenty-three participants wore four monitors on the non-dominant wrist simultaneously for seven days. Open-source software (GGIR) was used to estimate the daily time in sedentary, light, moderate-to-vigorous PA (MVPA), and sleep (movement behaviors). The prevalence of participants meeting the PA and sleep recommendations were calculated from each monitor’s data. Outcomes were deemed equivalent between monitors if the absolute standardized difference and its 95% confidence intervals (CI95%) fell within ± 0.2 standard deviations (SD) of the mean of the differences. The participants were mostly men (n = 14, 61%) and aged 36 (SD = 14) years. Pairwise confusion matrices showed that 83–87% of the daily time was equally classified into the movement categories by the different pairs of monitors. The between-monitor difference in MVPA ranged from 1 (CI95%: − 6, 7) to 8 (CI95%: 1, 15) min/day. Most of the PA and sleep metrics could be considered equivalent. The prevalence of participants meeting the PA and the sleep guidelines was 100% consistent across monitors (22 and 5 participants out of the 23, respectively). Our findings indicate that the various research-grade activity monitors investigated show high inter-instrument reliability with respect to sedentary, PA and sleep-related estimates when their raw data are processed in an identical manner. These findings may have important implications for advancement towards monitor-based PA and sleep surveillance systems.