Emotion regulation is generally thought of as the process of overriding one's initial emotional response to personally relevant events. One frequently investigated type of emotion regulation is cognitive reappraisal, which describes one's ability to cognitively alter the meaning of an event. Cognitive reappraisal is associated with better cognitive, social, and health outcomes compared to other emotion regulation strategies. The cognitive building blocks of cognitive reappraisal are related to executive cognitive control processes, which broadly describe one's ability to engage in non-automatic and goal-oriented behaviors. Crucially, executive control processes are also relevant in demanding cognitive tasks such as prospective memory since, similarly to cognitive reappraisal, they involve effortful and purpose driven efforts. However, cognitive reappraisal has thus far not been investigated regarding prospective memory performance despite findings that suggest that emotionally evocative stimuli improve prospective memory performance. The present study investigated whether cognitive reappraisal state and trait measures as well as other types of emotion regulation strategies are associated with prospective memory accuracy of negatively valenced prospective memory targets.

A total of 45 participants (69% women; M = 22.62 years, SD = 5.69 years) took part in this cross-sectional study. Cognitive reappraisal and prospective memory tasks were administered on the computer. A total of 106 pictures were shown in the prospective memory task, including 12 prospective memory hits. A 2-back paradigm was used as the effortful ongoing task. Dependent measures included accuracy of and reaction times to negative prospective memory hits. A total of 45 pictures were shown in the cognitive reappraisal task. Participants were asked to decrease their negative emotions when looking at previously normed negatively valenced pictures versus merely looking at them (Lang et al., 2001). Dependent measures in the cognitive reappraisal task included success of downregulating negative emotion after the DECREASE versus LOOK instruction. A mood manipulation check and a questionnaire asking about participants' reappraisal strategies was conducted. Trait based measures of emotion regulation included the Emotion Regulation Questionnaire and the Dysfunction of Emotion Regulation Scale.

Participants endorsed significantly higher negative mood after looking at negative versus neutral pictures, t(48) = 22.77, p , .05). Ratings further indicated that participants were able to significantly decrease how negative they felt when reappraising versus looking at negative pictures, t(44) = 12.82, p , .05. Regarding the relationship between prospective memory accuracy of negatively valanced prospective memory targets and cognitive reappraisal ability, no significant bivariate correlation was found (p > .05). However, a significant bivariate correlation was found between reaction times to negatively valenced prospective memory targets and cognitive reappraisal ability (rs = -.32, p = .03). No significant relationship was observed between prospective memory accuracy of or reaction times to negatively valenced prospective memory targets and trait based measures of emotion regulation (all ps > .05).

Hypotheses were partly supported. Higher state-based cognitive reappraisal abilities may be associated with lower cognitive costs when asked to remember negatively evocative pictures and/or higher overall cognitive capacity. The importance of assessing emotion regulation when utilizing emotionally evocative stimuli and their clinical significant is discussed.

Therapeutics targeting frontotemporal dementia (FTD) are entering clinical trials. There are challenges to conducting these studies, including the relative rarity of the disease. Remote assessment tools could increase access to clinical research and pave the way for decentralized clinical trials. We developed the ALLFTD Mobile App, a smartphone application that includes assessments of cognition, speech/language, and motor functioning. The objectives were to determine the feasibility and acceptability of collecting remote smartphone data in a multicenter FTD research study and evaluate the reliability and validity of the smartphone cognitive and motor measures.

A diagnostically mixed sample of 207 participants with FTD or from familial FTD kindreds (CDR®+NACC-FTLD=0 [n=91]; CDR®+NACC-FTLD=0.5 [n=39]; CDR®+NACC-FTLD>1 [n=39]; unknown [n=38]) were asked to remotely complete a battery of tests on their smartphones three times over two weeks. Measures included five executive functioning (EF) tests, an adaptive memory test, and participant experience surveys. A subset completed smartphone tests of balance at home (n=31) and a finger tapping test (FTT) in the clinic (n=11). We analyzed adherence (percentage of available measures that were completed) and user experience. We evaluated Spearman-Brown split-half reliability (100 iterations) using the first available assessment for each participant. We assessed test-retest reliability across all available assessments by estimating intraclass correlation coefficients (ICC). To investigate construct validity, we fit regression models testing the association of the smartphone measures with gold-standard neuropsychological outcomes (UDS3-EF composite [Staffaroni et al., 2021], CVLT3-Brief Form [CVLT3-BF] Immediate Recall, mechanical FTT), measures of disease severity (CDR®+NACC-FTLD Box Score & Progressive Supranuclear Palsy Rating Scale [PSPRS]), and regional gray matter volumes (cognitive tests only).

Participants completed 70% of tasks. Most reported that the instructions were understandable (93%), considered the time commitment acceptable (97%), and were willing to complete additional assessments (98%). Split-half reliability was excellent for the executive functioning (r’s=0.93-0.99) and good for the memory test (r=0.78). Test-retest reliabilities ranged from acceptable to excellent for cognitive tasks (ICC: 0.70-0.96) and were excellent for the balance (ICC=0.97) and good for FTT (ICC=0.89). Smartphone EF measures were strongly associated with the UDS3-EF composite (ß's=0.6-0.8, all p<.001), and the memory test was strongly correlated with total immediate recall on the CVLT3-BF (ß=0.7, p<.001). Smartphone FTT was associated with mechanical FTT (ß=0.9, p=.02), and greater acceleration on the balance test was associated with more motor features (ß=0.6, p=0.02). Worse performance on all cognitive tests was associated with greater disease severity (ß's=0.5-0.7, all p<.001). Poorer performance on the smartphone EF tasks was associated with smaller frontoparietal/subcortical volume (ß's=0.4-0.6, all p<.015) and worse memory scores with smaller hippocampal volume (ß=0.5, p<.001).

These results suggest remote digital data collection of cognitive and motor functioning in FTD research is feasible and acceptable. These findings also support the reliability and validity of unsupervised ALLFTD Mobile App cognitive tests and provide preliminary support for the motor measures, although further study in larger samples is required.

Probability bias—overestimation of the likelihood that feared social outcomes will occur—is a mechanism targeted for symptom reduction in cognitive behavioral therapy for social anxiety. Safety behaviors (i.e., the conscious and unconscious actions taken to reduce discomfort in feared social situations) are related to cognitive biases and can be manipulated to reduce probability bias. The purpose of this research was to test the hypothesis that scores from a newly developed computer task to measure probability bias, the Outcome Probability Task (OPT; Draheim & Anderson, 2022) would be associated with self-reported safety behaviors during a speech task.

Participants (N=90) included diverse students from a university in a southern, metropolitan area. Individuals reported an average age of 20.74 (SD=3.57) and self-identified as 'Woman’ (69%), 'Man’ (30%), 'Transgender’ (1%), or 'Non-binary/Agender’ (1%), and 'African American or Black’ (52%), 'Asian or Asian American’ (19%), 'White’ (16%), 'Multi-racial’ (7%), 'Hispanic or Latine’ (5%), or 'Middle Eastern’ (1%). Participants viewed social images and imagined themselves in the scenarios, then rated the likelihood that they would be negatively evaluated on a 0-100% scale (higher ratings indicate greater probability bias), gave a speech, and completed a standardized self-report measure of safety behaviors to rate how often they engaged in avoidant safety behaviors during the speech.

Results from a linear regression indicated that OPT scores (ß=.43) were positively associated with self-reported safety behaviors during a speech task, R2 = .19, F(1, 88) = 20.02, p < .001, 95% CI [0.170, 0.443].

Negatively biased expectations about fear-relevant social situations—measured by a digital imagery task, the OPT—may contribute to increased engagement in avoidant safety behaviors during a speech task among a convenience sample. Outcome probability bias has previously only been measured through self-report, and the OPT is a promising new measure to multi-modally assess this aspect of social cognition. This task could be used along with imaging techniques to better understand the functional brain activity involved in outcome probability bias. Future studies could explore how activity in the orbitofrontal cortex, which is associated with the anticipation of negative outcomes, relates to responses on the OPT. If there is a connection, this brain region could be an indicator of improvement following intervention, such as cognitive behavioral therapy, for probability biases involved in social anxiety.

This study examines the clinical validity of the NIH Toolbox Cognition Battery measures in patients with oncological diagnoses and tumor predisposition syndromes, including Neurofibromatosis, Type 1 (NF1).

Participants included 158 patients (61% male, 67% White) ages 3 to 25 years (M = 8.38, SD = 4.32) who underwent neuropsychological evaluation between 2019 and 2022. Patients with brain tumors (n = 50) and leukemias (n = 49) accounted for 2/3 of the sample. The remainder had solid tumors, lymphomas, or cancer predisposition syndrome. Forty-eight had a diagnosis of NF1. Performance-based measures of attention, executive functioning, and processing speed were administered as part of neuropsychological evaluations. Patients were administered between 1 to 4 NIH Toolbox Cognition measures, including Flanker Inhibitory Control and Attention Test (Flanker), Dimensional Change Card Sort Test (DCCS), Pattern Comparison Processing Speed Test (PCCS), and List Sorting Test. Parent-reported measures of attention and EF were also obtained. Z-scores were used to compare performance across measures that assessed equivalent constructs. The rates of weak performance (>1 SD below the mean) using Toolbox measures were compared to rates of weak performance on traditional neuropsychological measures (e.g., Digit Span), and rates of functional impairment (e.g., parent-reported concerns, ADHD diagnosis).

FSIQ, Coding, and NEPSY Inhibition correlated with all 4 Toolbox measures, while Digit Span correlated with List Sorting, DCCS, and Flanker. DCCS and PCCS correlated with verbal fluency measures. NF1 patients scored lower than non-NF1 patients on Flanker, F(1,126) = 13.01, p<.001 and DCCS, F(1,150) = 6.85, p = .01. Toolbox performance did not differ significantly by age group. Rates of identified weakness were relatively similar on Toolbox measures, some traditional measures, and parent-reported attention problems. In identifying those with and without weakness, the agreement between Flanker and other measures ranged from 52% (Auditory Attention) to 66% (Coding). Agreement between DCCS and traditional measures ranged from 47% (Letter Fluency) to 80% (Switching). For PCCS, concordance ranged from 45% (Semantic Fluency) to 69% (Switching). List Sorting had 80% agreement with Digit Span and Coding.

List Sorting had the highest agreement with parent-reported attention problems (76%), EF problems (72%), and ADHD diagnosis (79%). There was relatively high concurrence between DCCS and ADHD diagnosis (69%) and parent-reported attention problems (60%) and EF problems (65%) and between Flanker and ADHD diagnosis (67%). PCCS had less agreement with functional outcomes, ranging from 49% for EF problems to 58% for attention problems and ADHD diagnosis. In comparison, Digit Span had 64% agreement for EF problems, 70% for attention problems, and 73% for ADHD diagnosis.

The NIH Toolbox Cognition Battery can be used to identify neurocognitive weaknesses in pediatric oncology patients and provide clinically meaningful data. Evaluation of the Toolbox measures’ sensitivity to change over time is warranted, as monitoring the progression of cognitive late effects is particularly salient in cancer survivorship.

Intraindividual variability (IIV) is defined as fluctuations in an individual’s cognitive performance over time1. IIV has been identified as a marker of neurobiological disturbance making it a useful method for detecting changes in cognition among cognitively healthy individuals as well as those with prodromal syndromes2. IIV on laboratory-based computerized tasks has been linked with cognitive decline and conversion to mild cognitive impairment (MCI) and/or dementia (Haynes et al., 2017). Associations between IIV and AD risk factors including apolipoprotein (APOE) ε4 carrier status, neurodegeneration seen on brain imaging, and amyloid (Aß) Positron emission tomography (PET) scan status have also been observed1. Recent studies have demonstrated that evaluating IIV on smartphone-based digital cognitive assessments is feasible, has the capacity to differentiate between cognitively normal (CN) and MCI individuals, and may reduce barriers to cognitive assessment3. This study sought to evaluate whether such differences could be detected in CN participants with and without elevated AD risk.

Participants (n=57) were cognitively normal older adults who previously received an Aß PET scan through the Butler Hospital Memory and Aging Program. The sample consisted of primarily non-Hispanic (n=49, 86.0%), White (n=52, 91.2%), college-educated (M=16.65 years), females (n=39, 68.4%). The average age of the sample was 68 years old. Approximately 42% of the sample (n=24) received a positive PET scan result. Participants completed brief cognitive assessments (i.e., 3-4 minutes) three times per day for eight days (i.e., 24 sessions) using the Mobile Monitoring of Cognitive Change (M2C2) application, a mobile app-based cognitive testing platform developed as part of the National Institute of Aging’s Mobile Toolbox initiative (Sliwinski et al., 2018). Participants completed visual working memory, processing speed, and episodic memory tasks on the M2C2 platform. Intraindividual standard deviations (ISDs) across trials were computed for each person at each time point (Hultsch et al., 2000). Higher ISD values indicate more variability in performance. Linear mixed effects models were utilized to examine whether differences in IIV existed based on PET scan status while controlling for age, sex at birth, and years of education.

n interaction between PET status and time was observed on the processing speed task such that Aß- individuals were less variable over the eight assessment days compared to Aß + individuals (B= -5.79, SE=2.67, p=.04). No main or interaction effects were observed on the visual working memory task or episodic memory task.

Our finding that Aß- individuals demonstrate less variability over time on a measure of processing speed is consistent with prior work. No associations were found between IIV in other cognitive domains and PET status. As noted by Allaire and Marsiske (2005), IIV is not a consistent phenomenon across different cognitive domains. Therefore, identifying which tests are the most sensitive to early change is crucial. Additional studies in larger, more diverse samples are needed prior to widespread clinical use for early detection of AD.

Unsupervised remote digital cognitive assessment makes frequent testing feasible and allows for measurement of learning across days on participants’ own devices. More rapid detection of diminished learning may provide a potentially valuable metric that is sensitive to cognitive change over short intervals. In this study we examine feasibility and predictive validity of a novel digital assessment that measures learning of the same material over 7 days in older adults.

The Boston Remote Assessment for Neurocognitive Health (BRANCH) (Papp et al., 2021) is a web-based assessment administered over 7 consecutive days repeating the same stimuli each day to capture multi-day-learning slopes. The assessment includes Face-Name (verbal-visual associative memory), Groceries-Prices (numeric-visual associative memory), and Digits-Signs (speeded processing of numeric-visual associations). Our sample consisted of200 cognitively unimpaired older adults enrolled in ongoing observational studies (mean age=74.5, 63% female, 87% Caucasian, mean education=16.6) who completed the tasks daily, at home, on their own digital devices. Participants had previously completed in-clinic paper-and-pencil tests to compute a Preclinical Alzheimer’s Cognitive Composite (PACC-5). Mixed-effects models controlling for age, sex, and education were used to observe the associations between PACC-5 scores and both initial performance and multi-day learning on the three BRANCH measures.

Adherence was high with 96% of participants completing all seven days of consecutive assessment; demographic factors were not associated with differences in adherence. Younger participants had higher Day 1 scores all three measures, and learning slopes on Digit-Sign. Female participants performed better on Face-Name (T=3.35, p<.001) and Groceries-Prices (T=2.00, p=0.04) on Day 1 but no sex differences were seen in learning slopes; there were no sex differences on Digit-Sign. Black participants had lower Day 1 scores on Face-Name (T=-3.34, p=0.003) and Digit Sign (T=3.44, p=0.002), but no racial differences were seen on learning slopes for any measure. Education was not associated with any measure. First day performance on Face-Name (B=0.39, p<.001), but not learning slope B=0.008, p=0.302) was associated with the PACC5. For Groceries-Prices, both Day 1 (B=0.27, p<.001) and learning slope (B=0.02, p=0.03) were associated with PACC-5. The Digit-Sign scores at Day 1 (B=0.31, p<.001) and learning slope (B=0.06, p<.001) were also both associated with PACC-5.

Seven days of remote, brief cognitive assessment was feasible in a sample of cognitively unimpaired older adults. Although various demographic factors were associated with initial performance on the tests, multi-day-learning slopes were largely unrelated to demographics, signaling the possibility of its utility in diverse samples. Both initial performance and learning scores on an associative memory and processing speed test were independently related to baseline cognition indicating that these tests’ initial performance and learning metrics are convergent but unique in their contributions. The findings signal the value of measuring differences in learning across days as a means towards sensitively identifying differences in cognitive function before signs of frank impairment are observed. Next steps will involve identifying the optimal way to model multi-day learning on these subtests to evaluate their potential associations with Alzheimer’s disease biomarkers.

Contextual memory, which refers to the ability to remember spatial or temporal circumstances related to an event, is affected early in Alzheimer’s Disease (AD). Computerized cognitive tasks have been suggested to be an ecological way to assess memory, but there are few studies that utilize these tools. Studying contextual memory via a computerized task in a Colombian kindred with autosomal dominant AD due to the Presenilin-1 (PSEN1) E280A mutation and a well-characterized disease progression may help us understand contextual memory changes in the preclinical AD stage. In this study we investigated whether a novel computerized task examining contextual memory can help identify those at increased risk for dementia.

A group of 31 non-carriers (mean age=38.97±6.11; mean education=11.45±4.34) and 15 cognitively unimpaired PSEN1E280A mutation carriers from the Colombia-Boston (COLBOS) Biomarker Study (mean age=35.67±5.50), mean education=10.60±3.83) performed the “MAPP Room Memory Task” on a computer. As part of this task, participants are asked to remember ten rooms and the specific location of a few objects for later recall. During the immediate recall phase, participants are asked to recognize the objects presented in each room (Immediate Object Recognition) and their location (Immediate Object Placement). During the subsequent delay phase of the task, participants are asked to select the correct room in which an object was first presented (Delayed Room Recognition) and place the objects previously seen in each room (Delayed Object Placement). We conducted Mann Whitney U tests to analyze differences between groups and Spearman Rho correlations to examine associations among the Room Memory Task performance, age, education, and Mini Mental State Examination (MMSE).

There were no differences in age or education between carriers and non-carriers (p>0.05, for both). Carriers had worse Delayed Room Recognition than non-carriers (Carriers mean score=0.893±0.18, non-carriers mean score=0.987±0.05; U=168.0, p=0.02), while there were no differences in the other task conditions (all p>0.05). In carriers, education was positively associated with Immediate Object Placement (rs=0.61, p=0.02), Delayed Object Placement (rs=0.76, p=0.001), and Delayed Room Recognition (rs=0.68, p=0.006). There were no significant associations between Room Memory Task conditions and age or MMSE scores in carriers. Further, no significant associations were observed between Room Memory Task performance, and age, education or MMSE scores in non-carriers.

Our preliminary findings show that the MAPP Room Memory Task, in particular the Delayed Room Recognition condition, may be helpful to discriminate those at increased risk of dementia. Future studies with larger samples using the Room Memory Task and AD-related biomarkers are needed to examine whether this task can be sensitive to early preclinical changes associated with AD and can potentially help track disease progression in those at risk.

There is a need to identify scalable cognitive paradigms that are sensitive enough to relate to Alzheimer's disease biomarkers (amyloid and tau) in the preclinical stage. Here, we determine whether initial performance and practice effects on the memory-focused Computerized Cognitive Composite (C3) relate to demographic variables, amyloid status [abnormal (A+), normal (A-)], and regional tau in clinically unimpaired (CU) older adults.

We examined pre-randomization data from CU older adults screened for the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease (A4) study. We focused on participants who completed the C3 (n=3287), most of whom completed an alternate version of the C3 again approximately 51 days later (n=4141), as well as a subset of preclinical AD participants (i.e., A+ CU) who completed the C3 and tau PET imaging with [18]F-flortaucipir (initial C3: n=354; repeat C3: n=343). C3 initial performance and practice effects were examined in relation to amyloid status (A+, A-) and continuous regional tau burden.

Initial C3 performance was associated with amyloid status [B(SE) = -0.075 (0.021), p < 0.001] across all participants, as well as tau burden in the medial temporal lobe (MTL) [B (SE) = -0.728 (0.220), p = 0.001], inferior temporal (IT) cortex [B (SE) = -0.782 (0.264), p = 0.003], and inferior parietal (IP) cortex [B (SE) = -0.721 (0.281), p = 0.011] amongst preclinical AD individuals. Short-term practice effects were also associated with reduced tau burden in MTL [B (SE) = -0.471 (0.202), p = 0.020], IT [B (SE) = -0.640 (0.240), p = 0.008], and IP [B( SE) = - 0.584 (0.255), p = 0.023] amongst preclinical AD participants, but were not associated with amyloid status [B (SE) = -0.018 (0.020), p = 0.348]. Critically, these effects with tau were only detected when baseline performance was accounted for presumably due to opposing influence from both practice effects and regression to the mean effects.

This is the first study to show that performance on a brief cognitive battery administered in a multisite context is associated with both amyloid and tau among CU older adults. These findings suggest that computerized assessments may be a cost-effective and scalable approach for early detection efforts. Further, diminished practice effects on memory-based measures are associated with elevated tau burden in preclinical AD, suggesting that high-frequency cognitive testing collected over a short follow-up period may provide additional insights regarding early disease processes than single assessments.

Research has found that child molesters (both pedophilic and non-pedophilic) tend to have poorer executive functioning (EF), particularly inhibition, as compared to other types of criminal offenders (Eastvold, Suchy, Strassberg, & 2011; Suchy, Whittaker, Strassberg, & Eastvold, 2009). Poorer performance on measures of inhibition may have different mechanisms for pedophilic child molesters (PCM; i.e., those offenders who are sexually attracted only to children) than non-pedophilic child molesters (N-PCM; i.e., those offenders whose sexual attraction is not limited to children). Specifically, poor inhibition in PCM may be explained by slower processing speed (Suchy, et al., 2009; Suchy, Eastvold, Strassberg, & Franchow, 2014), whereas it may be explained by impulsive errors in N-PCM (Eastvold, Suchy, & Strassberg, 2011). Intraindividual variability (IIV) refers to transient, short-term fluctuations in performance (Nesselroade, 1991). IIV is sometimes interpreted as a measure of cognitive control, an aspect of EF that could impact performance speed and accuracy due to poorer focus.

Greater IIV also appreas to be associated with greater vulnerability to EF depletion after behavioral inhibition (DesRuisseaux, Suchy, & Franchow, 2021), which could represent a mechanism whereby vulnerability to EF depletion could be a precursor of offense. However, given that poor performance on measures of inhibition seem to have different underlying mechanisms for PCM and N-PCM, it is unclear whether both groups would exhibit greater IIV compared to non-sexual offenders.

Participants were PCM (n = 76, M age = 33.61(7.74), Range = 1947; 92.1% White, 2.6% Hispanic/Latino, 2.6% Native American, 1.3% Black, 1.3% Other), N-PCM (n = 52, M age = 30-88(6.37), Range = 2045; 73.1% White, 13.5% Hispanic/Latino, 7.7% Other, 3.8% Native American, 1.9% Black), and non-sexual offenders (n = 25, M age = 29.96(8.16), Range = 22-45; 80% White, 8% Hispanic/Latino, 8% Other, 8% Asian) recruited as part of two larger studies examining cognition in sex offenders. IIV was assessed using the Push-Turn-Tap-Tap (PTT) task, an experimental computerized measure of EF from which IIV can be calculated (DesRuisseaux et al., 2021).

Independent samples t-tests found that both PCM and N-PCM had greater IIV than nonsexual offenders (t(99) = 2.13, p = .04; t(75) = 2.23, p = .03, respectively). Even on their fastest responses, PCM had greater time elapsed between correct sequences (i.e., slower response style; t(126) = 2.23, p = .03) than N-PCM. There were no significant differences in error rates between any groups (p > .05).

These results suggest that IIV varies between sexual and non-sexual offenders but does not vary between PCM and N-PCM. This is consistent with prior research suggesting that both PCM and N-PCM have poorer EF than non-sexual offenders. Additionally, consistent with prior research, PCM had a slower response style than N-PCM and non-sexual offenders. Unlike prior research that has found significant differences in accuracy rates between PCM and N-PCM, the present results did not find a significant difference. Since IIV has been associated with increased likelihood of EF depletion (likely increasing risk of lapses), future research could examine whether CM with greater IIV have an increased likelihood of reoffending.

In recent years, rates of alcohol consumption and alcohol use disorder have steadily increased among adults age 60 and older. Large studies have demonstrated that moderate-to-heavy alcohol consumption (>7 drinks per week) is a risk factor for developing various types of dementias. The effects of alcohol-related problems on cognition are less clear, and are particularly understudied in older adults. Similarly, while there is an established link between worse cognition and financial exploitation vulnerability in older adults, no studies have examined relationships between alcohol-related problems and financial exploitation in this population. The current study therefore explores whether alcohol-related problems are associated with neuropsychological performance and financial exploitation vulnerability in a sample of older adults.

Participants were a community sample of cognitively unimpaired adults over the age of 50 (N = 55, Age M(SD) = 69.1(6.2), 74.5% female, Years of education M(SD) = 16.8(2.3)). Interested individuals were excluded if they reported current or past substance use disorders. Participants completed a laboratory visit that included a neuropsychological assessment. Measures included the NIH Cognition toolbox, CVLT-II, Digit Span, Trails A/B, Benson Complex Figure Recall, and Verbal Fluency: Phonemic and Semantic, from the Alzheimer’s Disease Centers’ Uniform Data Set (UDS) version 3. Participants completed the CAGE Alcohol Abuse Screening Tool and the Short Michigan Alcohol Screener Test - Geriatric Version (SMAST) to assess alcohol-related problems. Both measures are used as clinical screening tools to measure likelihood of a substance use disorder and produce a summary score (0-4 for CAGE, 010 for SMAST) tabulating symptoms of alcohol-related problems. Participants also completed the Perceived Financial Vulnerability Scale (PFVS) to assess financial exploitation vulnerability. As a significant number of participants reported no drinking and therefore no alcohol-related problems, negative binomial regressions were used to test associations between neuropsychological measures, financial exploitation vulnerability, and alcohol-related problems.

After covarying for age and sex, SMAST was negatively associated with NIH toolbox total cognition (B(SE) = -.14(.07), p<.05) and marginally negatively associated with fluid cognition (B(SE) = -.07(.04), p=.06). Neither SMAST nor CAGE scores were significantly associated with performance on any other neuropsychological test (ps = .13-.99). SMAST was positively associated with financial exploitation vulnerability (B(SE) = .31(.16), p = .05); this effect remained significant after covarying for NIH total composite score in a secondary analysis.

In a community sample of cognitively unimpaired, low-drinking adults over the age of 50, more alcohol-related problems were associated with worse NIH toolbox cognition scores. Similarly, more alcohol-related problems were associated with greater financial exploitation vulnerability, and this relationship was not driven by worse cognition. These results suggest that even low amounts of drinking and alcohol-related problems may be associated with cognition and financial exploitation vulnerability in cognitively unimpaired older adults. This study also corroborates the use of the SMAST over the CAGE in older adult populations that may be more sensitive to cognitive changes.

In December 2019, the first reports came from China about cases of pneumonia caused by a previously unknown coronavirus, SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2), responsible for a disease called COVID-19. Since then, the pandemic has spread worldwide, affecting people’s physical and mental health and as well as quality of life. Currently, many people are experiencing the health consequences of contracting COVID-19, also due to the impact this disease has on the central nervous system. As a result, in addition to well-known ailments, such as headaches, chronic fatigue or smell and taste disorders, COVID-19 survivors may develop neuropsychological problems such as executive-attentional deficits. However, the specificity of these executive-attentional problems has not been determined. Thus, the purpose of this study was to learn if survivors of COVID-19 may present with more generalized or rather specific dysfunction(s) of the anterior attentional-executive system.

The study group consisted of 37 individuals who underwent COVID-19 (age M=44, education M=17). The comparison group consisted of 25 matched controls tested before the COVID-19 pandemia. The experimental procedures included (1) a clinical interview, (2) an assessment of selected cognitive functions (3) and attentionalexecutive functioning, which was assessed using the ROtman-Baycrest Battery to Investigate Attention (ROBBIA); a battery was designed to measure three attentional processes (i.e., energizing, task setting, and monitoring). Overall, four reaction time (RT) subtests from ROBBIA were administered: (1) Simple RT, (2) Choice RT, (3), Prepare RT, and (4) Concentrate. For each subtest, the instruction was to press an appropriate button on a response pad as quickly as possible when a target stimulus (one of the following capital letters: A, B, C, or D) is detected, but also (in Choice RT, Prepare RT and Concentrate) to make as few errors as possible.

Overall, the analyses revealed that individuals who survived COVID-19 exhibited a different effect of the warning stimulus compared to controls. Specifically, COVID19 survivors presented an increase in reaction time from 1s warning condition to 3s warning condition being significantly greater than the control group’s increase (p < .05). Also, only in the COVID-19 group, reaction time in the Concentrate task tended to be longer (p = 0.01). No group differences in monitoring (e.g., number of errors) or task setting emerged.

The patients’ problems appear analogous to those observed in other chronic somatic diseases, likely due to the impact of COVID-19 on the frontal lobe’s medial regions. However, due to a small sample size, future neuroimaging research, including computerized studies of attentional-execution networks, is needed to confirm that COVID-19 may predominantly affect the energization system that contributes to these patient’s cognitive slowing and defective ability to sustain attention.

The dynamic transitions towards and away from digitizing mental health care services have put immense pressure on neuropsychology to develop a more technologically advanced approach to patient care. Consistent with this, neuropsychologists are faced with an increasing burden to rapidly learn novel techniques of administering digital and/or remote cognitive measures, which may not be sufficiently standardized and/or psychometrically validated.

The Hybrid Neuropsychology model, which aims to provide a framework for the integration of digital tools in neuropsychological assessment, has been incorporated routinely in our clinical practice, and among diverse clinical populations in inpatient and outpatient settings.

This talk aims to 1) provide a brief background on Hybrid Neuropsychology; 2) discuss preliminary findings from our ongoing studies implementing this approach in clinical populations; and 3) offer key insights gleaned from methodological, analytical, and practical perspectives.

Future work towards building a more integrative method of data collection and storage based on extant preliminary data will also be discussed.

The COVID-19 pandemic created barriers to healthcare that necessitated changes in services to meet needs of individuals. With these changes, technological advances in computerized cognitive testing became critical. As researchers and clinicians accelerated adaptation of computerized testing formats, considerations for development and interpretation of such tools have proved imperative. One such computerized tool, RC21X, utilizes performance measurement software comprising 15 modules to evaluate an individual’s processing speed, memory, executive functions, and neuromotor coordination. Although initial data has revealed strong psychometric properties (Saganis et al., 2020), a need to explore various attributes of this web-based tool has emerged. The current study examined impact of dominant handedness on an RC21X neuromotor task.

The sample consisted of 602 participants: 553 (91.86%) were right-hand dominant and 49 (8.14%) were left-hand dominant. Of participants who identified their sex, 81.2% were male, 18.3% were female; 0.5% chose not to identify. Age ranged from 7-95 years (M = 41.21, SD = 18.81). This study focused on the RC21X Eye-Hand Coordination subtest. Using a Fitts’ Law paradigm, the module provided instruction for participants to alternately press the “A” and “L” keys on a keyboard as quickly and accurately as possible using only one upper extremity (UE) at a time (tested separately for right then left UE). We computed a one-way between groups multivariate analysis of variance (MANOVA) to investigate handedness differences on task performance. Dependent variables were individuals’ performances on right- and left-UE tasks; the independent variable was dominant handedness. We conducted preliminary assumption testing with no serious violations noted. We also separated the sample by dominant handedness to compare right versus left-hand performance using paired samples t-tests within each group. There were no significant differences between the two groups on either age or sex.

There was a statistically significant difference between right-hand dominant and left-hand dominant participants on the dependent variables, F (2, 599) = 8.84, p < .001, Wilks’ Lambda = .971. Mean scores indicated that right-hand dominant participants (M = 52.87, SD = 20.42) outperformed their left-hand dominant counterparts (M = 46.30, SD = 12.79) when using their right UE, though both groups performed similarly when using their left UE (right-hand dominant M = 48.55, SD = 17.81; left-hand dominant M = 49.70, SD = 14.13). These findings were present despite expected results from paired samples t-tests that revealed individuals performed best with their dominant hand.

Results revealed that handedness is necessary to consider in design and utilization of computerized neuropsychological tests. The large proportion of right-hand dominant individuals may have affected our results; however, our sample is representative of handedness distribution in the general population. Although our paired samples t-tests support validity of RC21X, continued investigation of computerized performance measurement tools is necessary. Future research must explore the possibility of an ordering effect (i.e., right-handed participants starting with their dominant UE, but left-handed participants starting with their nondominant UE) or due to construction of everyday items (e.g., computer keyboards) primarily for right-hand dominant people.

The Tower of London is commonly used to assess planning ability. Deficient outcomes may however have different causes: A participant may not have the ability to think a sufficient number of steps into the future, or may become, for example, impatient to evaluate different possible paths. Outcomes are thus not pure measures of the "planning" construct of primary interest, which may have contributed to findings of low reliability and low validity of these outcomes in the literature. The advent of computerized testing combined with computational modeling potentially allows to go beyond traditional outcomes such as "total number of moves" and "total time taken" and disentangle different processes that are of primary interest. The goal of the current study is to establish whether a model that consists of "planning ability" and "response inhibition" parameters can be used to describe Tower of London data.

We constructed an algorithm that produces Tower of London data, and a computational model that uses every single decision of a participant as input (e.g., whether a participant moves the red or the blue ball to the right peg in setting 15 when trying to get to setting 28). There are 210 unique decision situations that participants can encounter. Our algorithm and Bayesian hierarchical model uses two parameters for each participant as well as a guessing rule, that together determine the participant's decision at every step. The appropriateness of the model was evaluated in a simulation study, where the simulated distribution of data implied by this model is compared to the empirical distribution of total number of moves observed in real datasets. Data were simulated for 10 items with a sample size of 200 participants.

Our simulation study shows that with our model the empirical distribution of total number of moves is successfully replicated in the distribution of the simulated data.

Computational modeling provides a new window into Tower of London performance by identifying different processes. Modeling thus allows us to go beyond aspecific descriptions of planning ability. Furthermore, using the high-resolution data of computerized testing allows us to estimate these parameters reliably without requiring "big data", keeping participant burden low. This study will be followed up in three ways. First, predictions will be preregistered and tested for these new cognitive outcomes in several large oncological patient samples. Second, the model will be extended to include reaction times, to include an additional metric of cognitive computation. Third, the new cognitive process outcomes will be analyzed in conjunction with cognitive process outcomes on other tests to establish process communalities.

Frequent and remote cognitive assessment may improve sensitivity to subtle cognitive decline associated with preclinical Alzheimer’s disease (AD). The objective of this study was to evaluate the feasibility and acceptability of repeated remote memory assessment in late middle-aged and older adults.

We recruited participants from a longitudinal aging cohort to complete three medial temporal lobe-based memory paradigms (Object-In-Room Recall [ORR], Mnemonic Discrimination for Objects and Scenes [MDT-OS], Complex Scene Recognition [CSR]) using the neotiv application at repeated intervals over one year. We conducted initial telephone calls to perform screening, consent, and download instructions. Participants were assigned 24 remote sessions on a smartphone or tablet and were alerted via push notification when an assignment was ready to complete. Participants were randomly assigned to: (1) complete memory tests every other week or (2) complete memory tests for multiple days within one week every other month. Each remote session lasts approximately 10 minutes and includes one memory paradigm and brief usability/acceptability questionnaires followed by a delayed retrieval session 90 minutes later. Feasibility metrics examined included participation, retention, compliance, and usability/acceptability.

Of 150 participants recruited, 113 consented and were enrolled into the study (participation rate = 75%). Current retention rate is 75%, with 85/113 currently active (n=73) or completed (n=12). Of the 85 active or completed participants, the mean age is 68.7 (range = 4882), 64% are women, 70% used a smartphone (30% tablet), 84 are cognitively unimpaired and 1 has mild cognitive impairment. The primary threat to retention was participants consenting into the study but never registering in the app or completing their first scheduled assignment. After enrollment, 130 telephone calls were made by study staff to facilitate registration into the app or to remind participants to complete tasks. 74-80% of participants completed delayed retrieval tasks within 30 minutes of push notification, but average retrieval time was 125137 minutes post-learning trials. Regarding acceptability/usability, 94% agreed the application was easy to use, 56% enjoyed completing the mobile memory tests (36% felt neutral), 40% prefer remote mobile memory tests to standard in-person paper and pencil tests, and 50% understood the test instructions. 87% felt the frequency of tests assigned was “just right” (13% “too often”) and 90% felt the test length was “just right” (7% too short, 3% too long). Participants who completed all 24 sessions to date (n=12) all endorsed being “satisfied” or “very satisfied” with the platform and visit schedule, as well as recommended continued use of this type of cognitive testing.

Remote memory assessment using smartphones and tablets is feasible and acceptable for cognitively unimpaired late middle-aged and older adults. Follow-up by study staff was needed to ensure adequate retention. Comprehension of instructions and compliance with completing delayed retrieval tasks within the expected timeframe was lower than expected. These feedback will be incorporated into an updated version of the app to improve compliance and retention. Longitudinal data collection is ongoing and results will be updated with a larger sample. Results will be compared across frequency schedule groups.

Cognitive reappraisal is a frequently researched emotion regulation strategy. It broadly describes one's ability to alter or reinterpret the meaning of personally relevant events. Cognitive reappraisal is robustly associated with lower self-reported negative affect, lower physiological arousal, and higher positive affect, which is the reason why it is a key component of many psychotherapeutic interventions. However, little research to date has investigated different types of cognitive reappraisal tactics and their association with cognitive reappraisal success. Given that there are an arguably indefinite number of ways to reappraise personally relevant events, it would be clinically informative to identify those tactics that are associated with the greatest decline in negative emotionality. The current study investigated whether one's predominant use of a specific reappraisal strategy is associated with divergent cognitive reappraisal success.

A total of 42 participants (67% women; M = 23.33 years, SD = 6.05 years) took part in this cross-sectional study. Cognitive reappraisal was administered via a computerized task modeled after McRae et al. (2012). A total of 45 previously normed pictures were shown in the cognitive reappraisal task (Lang et al., 2001). Participants were asked to either decrease how they felt or look at negatively evocative images. The dependent measure was success of downregulating negative emotion after the “decrease” versus “look” instruction (i.e., cognitive reappraisal success). A mood manipulation check, a questionnaire asking about participants' reappraisal strategies, and frequency of each reappraisal tactic was conducted after the task was completed to ensure that participants implemented the task as intended. Reappraisal tactics were rated by 3 independent raters individually according to a previously established rating tactic coding system (McRae et al., 2012). An analysis of variance was conducted comparing reappraisal success across groups of the reappraisal tactic most frequently used for each participant. Additionally, total number of reappraisal strategies used was included as a covariate.

Participants endorsed significantly higher negative mood after looking at negative versus neutral pictures, t(41) = 22.70, p < .05). Ratings further indicated that participants were able to significantly decrease how negative they felt when reappraising versus looking at negative pictures, t(41) = 11.95, p < .05. On average, participants' most frequently used reappraisal tactic was used 50.54% (SD = 16.32) of the time. Descriptive statistics on frequency of reappraisal tactics across participants is shown. Regarding the analysis of variance of divergent reappraisal success based on tactic, no significant relationship was found (p > .05). The inclusion of number of reappraisal strategies per participant did not impact the results (p > .05).

The present study did not show a significant difference between reappraisal tactics regarding their cognitive reappraisal success. This replicates past findings and indicates that type of reappraisal tactic used may be not as impactful as using cognitive reappraisal in some fashion. However, reappraisal tactics were not distributed equally across participants. Future studies should include larger samples to attain adequate sample sizes for each reappraisal tactic. Furthermore, participants should be instructed to use a specific reappraisal tactic alongside their self-selected reappraisal preferences to gain insight into the relative success of different reappraisal tactics. Clinical relevance of present findings is discussed.

The Stricker Learning Span (SLS) is a computer-adaptive word list memory test specifically designed for remote assessment and self-administration on a web-based multi-device platform (Mayo Test Drive). Given recent evidence suggesting the prominence of learning impairment in preclinical Alzheimer’s disease (AD), the SLS places greater emphasis on learning than delayed memory compared to traditional word list memory tests (see Stricker et al., Neuropsychology in press for review and test details). The primary study aim was to establish criterion validity of the SLS by comparing the ability of the remotely-administered SLS and inperson administered Rey Auditory Verbal Learning Test (AVLT) to differentiate biomarkerdefined groups in cognitively unimpaired (CU) individuals on the Alzheimer’s continuum.

Mayo Clinic Study of Aging CU participants (N=319; mean age=71, SD=11; mean education=16, SD=2; 47% female) completed a brief remote cognitive assessment (∼0.5 months from in-person visit). Brain amyloid and brain tau PET scans were available within 3 years. Overlapping groups were formed for 1) those on the Alzheimer’s disease (AD) continuum (A+, n=110) or not (A-, n=209), and for 2) those with biological AD (A+T+, n=43) vs no evidence of AD pathology (A-T-, n=181). Primary neuropsychological outcome variables were sum of trials for both the SLS and AVLT. Secondary outcome variables examined comparability of learning (1-5 total) and delay performances. Linear model ANOVAs were used to investigate biomarker subgroup differences and Hedge’s G effect sizes were derived, with and without adjusting for demographic variables (age, education, sex).

Both SLS and AVLT performances were worse in the biomarker positive relative to biomarker negative groups (unadjusted p’s<.05). Because biomarker positive groups were significantly older than biomarker negative groups, group differences were attenuated after adjusting for demographic variables, but SLS remained significant for A+ vs A- and for A+T+ vs A-T- comparisons (adjusted p’s<.05) and AVLT approached significance (p’s .05-.10). The effect sizes for the SLS were slightly better (qualitatively, no statistical comparison) for separating biomarker-defined CU groups in comparison to AVLT. For A+ vs A- and A+T+ vs A-T- comparisons, unadjusted effect sizes for SLS were -0.53 and -0.81 and for AVLT were -0.47 and -0.61, respectively; adjusted effect sizes for SLS were -0.25 and -0.42 and for AVLT were -0.19 and -0.26, respectively. In secondary analyses, learning and delay variables were similar in terms of ability to separate biomarker groups. For example, unadjusted effect sizes for SLS learning (-.80) was similar to SLS delay (.76), and AVLT learning (-.58) was similar to AVLT 30-minute delay (-.55) for the A+T+ vs AT- comparison.

Remotely administered SLS performed similarly to the in-person-administered AVLT in its ability to separate biomarker-defined groups in CU individuals, providing evidence of criterion validity. The SLS showed significantly worse performance in A+ and A+T+ groups (relative to A- and A-T-groups) in this CU sample after demographic adjustment, suggesting potential sensitivity to detecting transitional cognitive decline in preclinical AD. Measures emphasizing learning should be given equal consideration as measures of delayed memory in AD-focused studies, particularly in the preclinical phase.

Stroke results in various cognitive and motor impairments. The most frequent cognitive problem is spatial and non-spatial attention, typically caused by unilateral brain lesion. Attention is typically assessed with several different paper-and-pencil tests, which have long been criticized for their lack of theoretical basis, their limited ecological validity to deficits experienced in daily life, and their lack of measurement sensitivity (Appelros et al., 2004; Azouvi, 2017). Here, our global aim was to develop an innovative integrative serious game in an immersive environment. The REASmash, combines the evaluation of spatial attention, non-spatial attention, and motor performance. We present the spatial and non-spatial cognitive attention evaluation results.

Eighteen first stroke individuals and 40 age-match healthy controls were assessed on the REASmash. They were instructed to find a target mole presented amongst distractor moles. The stimulus array consisted of a grid of 6 columns and 4 rows of molehills, from which the target and 11, 17 and 23 distractors moles could randomly appear, in two search conditions (single feature condition and saliency condition). Responses were made with the ipsilesional hand for individuals with stroke and with the dominant hand for the healthy controls. Participants were evaluated also with two standardized clinical tests of attention; the hearts cancellation task of the Oxford Cognitive Screen, and the visual scanning subtest of the Test for Attentional Performance.

Validation results showed significant and strong correlations between the REASmash and the two reference tests, with the REASmash showing high sensitivity and specificity (i.e., the correct identification of the post-stroke vs. control individuals). The REASmash also showed significant and strong test/re-test reliability. We additionally evaluated user experience using the UEQ, and the results showed excellent attractiveness and novelty, and good stimulation and efficiency.

In conclusion, the REASmash is a novel immersive virtual environment serious game that is valid, sensitive, and usable. It provides a new diagnosis measure spatial and non-spatial attention impairment.

While there exist numerous validated neuropsychological tests and batteries to measure cognitive and behavioral capacities, the vast majority of these are time intensive and difficult to administer and score outside of the clinic. Moreover, many existing assessments may have limited ecological validity in some contexts (e.g., military operations). Therefore, we have been developing a novel approach to administering neuropsychological assessment using a virtual reality (VR) “game” that will collect simultaneously acquired multidimensional data that is synthesized by machine learning algorithms to identify neurocognitive strengths and weaknesses in a fraction of the time of typical assessment approaches. For our initial pilot project, we developed a preliminary VR task that involved a brief game-like military “shoot/no-shoot” task that collected data on hits, false alarms, discriminability, and response times under a context-dependent rule set. This prototype task will eventually be expanded to include a significantly more complex set of tasks with greater cognitive demands, sensor feeds, and response variables that could be modified to fit many other contexts. The objective of this project was to construct a rudimentary pilot version and demonstrate whether it could predict outcomes on standard neuropsychological assessments.

To demonstrate proof-of-concept, we collected data from 20 healthy participants from the general population (11 male; age=24.8, SD=7.8) with high average intelligence (IQ = 112, SD=10.7). All participants completed the Wechsler Abbreviated Scale of Intelligence-II (WASI-II), and several neuropsychological tests including the ImPACT, the Attention and Executive Function modules of the Neuropsychological Assessment Battery (NAB), and the VR task. Initially, we used a prior dataset from 359 participants (n=191 mild traumatic brain injury; n=120healthy control; n=48 sleep deprived) to serve as a training sample for machine learning models. Based on these outcomes, we applied machine learning, as well as standard multiple regression approaches to predict neuropsychological outcomes in the 20 test participants.

In this limited study, the machine learning approach did not converge on a meaningful prediction due to the instability of the small sample. However, standard multiple linear regression using stepwise entry/deletion of the VR task variables significantly predicted neuropsychological performance. The VR task predicted WASI-II vocabulary (R=.457, p=.043), NAB Attention Index (R=.787, p=.001), and NAB Executive Function Index (R=.715, p=.002). Interestingly, these performances were generally as good or better than the predictions resulting from the ImPACT, a commercially available neuropsychological test battery, which correlated with WASI-II vocabulary (R=.557, p=.011), NAB Attention Index (R=.574, p=.008), and NAB Executive Function Index (R=.619, p=.004).

Our pilot VR task was able to predict performances on standard neuropsychological assessment measures at a level comparable to that of a commercially available computerized assessment battery, providing preliminary evidence of concurrent validity. Ongoing work is expanding this rudimentary task into one involving greater complexity and nuance. As multivariate data integration models are incorporated into the tasks and extraction features, future work will collect data on much larger samples of individuals to develop and refine the machine learning models. With additional work this approach may provide an important advance in neuropsychological assessment methods.

Mobile, valid, and engaging cognitive assessments are essential for detecting and tracking change in research participants and patients at risk for Alzheimer’s Disease and Related Dementias (ADRDs). The mobile cognitive app performance platform (mCAPP) includes memory and executive functioning tasks to remotely detect cognitive changes associated with aging and preclinical Alzheimer’s disease. This study assesses participants’ comfort and subjective experiences with mCAPP as the potential utility and advantage of mobile app-based assessments for remote monitoring among older adults will depend upon usability and adoptability of such technology.

The mCAPP includes three gamified tasks: (1) a memory task involving learning and matching hidden card pairs (“Concentration”) (2) a stroop-like task (“Brick Drop”), and (3) a digit-symbol coding-like task (“Space Imposters”). Participants included 37 older adults (60% female; age=72±4.4; years of education=17±2.5; 67% White) with normal cognition enrolled in the Penn ADRC cohort. Participants completed one baseline session of mCAPP in-person, followed by two weeks of at-home use with eight scheduled sessions. Information on prior experience with mobile technology and games was collected, and usability of mCAPP was measured at baseline and after 2-weeks of use with the IBM Computer Usability Satisfaction Questionnaire and the mHeath App Usability Questionnaire (MAUQ) respectively. Feedback on perceived difficulty, enjoyment, and likelihood to play mCAPP games again on their own was collected.

Participants completed on average 11±4.9 sessions over 2 weeks, with each session lasting 11.5±2.5 minutes. 59% of participants reported using their mobile device to play games (“mobile game players”). Performance on mCAPP tasks was slower at baseline for non-players, with trend-level differences on higher-load blocks of Space Imposters (p=.057 and .059). No differences in game performance were seen between groups after playing 8 sessions at-home. There were no differences in usability of mCAPP between groups, with average usability 8.2±1.5 (IBM, 0-9 scale) at T1 and 6.2±0.8 (MAUQ, 1-7 scale) after completion of two weeks of at-home use (TLast). Reported enjoyment was moderate to high for both groups at baseline and increased over time. Likelihood to play Concentration and Brick Drop again trended lower among nonplayers at T1 (p=.061 and .054), but not at TLast. Further, change in likelihood to play mCAPP from T1 to TLast was positive among non-players, with change for Concentration significantly higher for non-players than for players (p=.037).

Participants were willing and able to complete at-home cognitive testing and most completed more than the assigned sessions. While participants who do not play games on their own mobile device were slower on some tasks at baseline, these differences dissipated with further play at-home. Usability and enjoyment of mCAPP games were high regardless of mobile game-playing status, and non-players demonstrated increased willingness to play mCAPP games again at the end of participation compared to baseline. This pilot study shows preliminary feasibility and adoptability of mobile app-based assessment regardless of prior experience with mobile games.