TICS-M scores in an oldest-old normative cohort identified by computable phenotype.

Objective: To (1) examine the distribution of Telephone Interview for Cognitive Status modified (TICS-m) scores in oldest-old individuals (age 85 and above) identified as cognitively healthy by a previously validated electronic health records-based computable phenotype (CP) and (2) to compare different cutoff scores for cognitive impairment in this population. Method: CP identified 24,024 persons, 470 were contacted and 252 consented and completed the assessment. Associations of TICS-m score with age, sex, and educational categories (<10 years, 11-15 years, and >16 years) were examined. The number of participants perceived as impaired was studied with commonly used cutoff scores (27-31). Results: TICS-m score ranged from 18 to 44 with a mean of 32.6 (SD = 4.7) in older adults aged 85-99 years old. A linear regression model including (range-restricted) age, education, and sex, showed beta estimates comparable to previous findings. Different cutoff scores (27 to 31) generated slightly lower MCI and dementia prevalence rates of participants meeting the criteria for the impairments than studies of younger elderly using traditional recruitment methods. Conclusions: The use of validated computable phenotype to identify a normative cohort generated a normative distribution for the TICS-m consistent with prior findings from more effortful approaches to cohort identification and established expected TICS-m performance in the oldest-old population.

Evaluation of a Computable Phenotype for Successful Cognitive Aging.

Objective: To establish, apply, and evaluate a computable phenotype for the recruitment of individuals with successful cognitive aging. Participants and Methods: Interviews with 10 aging experts identified electronic health record (EHR)-available variables representing successful aging among individuals aged 85 years and older. On the basis of the identified variables, we developed a rule-based computable phenotype algorithm composed of 17 eligibility criteria. Starting September 1, 2019, we applied the computable phenotype algorithm to all living persons aged 85 years and older at the University of Florida Health, which identified 24,024 individuals. This sample was comprised of 13,841 (58%) women, 13,906 (58%) Whites, and 16,557 (69%) non-Hispanics. A priori permission to be contacted for research had been obtained for 11,898 individuals, of whom 470 responded to study announcements and 333 consented to evaluation. Then, we contacted those who consented to evaluate whether their cognitive and functional status clinically met out successful cognitive aging criteria of a modified Telephone Interview for Cognitive Status score of more than 27 and Geriatric Depression Scale of less than 6. The study was completed on December 31, 2022. Results: Of the 45% of living persons aged 85 years and older included in the University of Florida Health EHR database identified by the computable phenotype as successfully aged, approximately 4% of these responded to study announcements and 333 consented, of which 218 (65%) met successful cognitive aging criteria through direct evaluation. Conclusion: The study evaluated a computable phenotype algorithm for the recruitment of individuals for a successful aging study using large-scale EHRs. Our study provides proof of concept of using big data and informatics as aids for the recruitment of individuals for prospective cohort studies.

Early prediction of Alzheimer's disease and related dementias using real-world electronic health records.

INTRODUCTION: This study aims to explore machine learning (ML) methods for early prediction of Alzheimer's disease (AD) and related dementias (ADRD) using the real-world electronic health records (EHRs). METHODS: A total of 23,835 ADRD and 1,038,643 control patients were identified from the OneFlorida+ Research Consortium. Two ML methods were used to develop the prediction models. Both knowledge-driven and data-driven approaches were explored. Four computable phenotyping algorithms were tested. RESULTS: The gradient boosting tree (GBT) models trained with the data-driven approach achieved the best area under the curve (AUC) scores of 0.939, 0.906, 0.884, and 0.854 for early prediction of ADRD 0, 1, 3, or 5 years before diagnosis, respectively. A number of important clinical and sociodemographic factors were identified. DISCUSSION: We tested various settings and showed the predictive ability of using ML approaches for early prediction of ADRD with EHRs. The models can help identify high-risk individuals for early informed preventive or prognostic clinical decisions.

Burnt Out: Rate of Burnout in Neuropsychology Survey Respondents During the COVID-19 Pandemic, Brief Communication.

OBJECTIVE: Due to the COVID-19 pandemic, burnout among healthcare workers has significantly increased. This study evaluated rates of burnout in neuropsychologists one year into the COVID-19 pandemic. METHOD: A survey invitation was sent across five neuropsychology-related listservs in April 2021. Burnout was assessed with the Copenhagen Burnout Inventory (CBI; Kristensen, T. S., Borritz, M., Villadsen, E., & Christensen, K. B. (2005). The Copenhagen Burnout Inventory: A new tool for the assessment of burnout. Work & Stress, 19 (3), 192-207) and differences in Personal, Work, and Client burnout scores were evaluated across patient population and work setting. RESULTS: 57.3% and 51.5% of respondents (N = 130) endorsed moderate-to-high levels of personal and work-related burnout, respectively. In the Personal domain, respondents working with pediatric patients had higher mean scores and a higher proportion of respondents endorsed moderate-to-high levels of burnout. CONCLUSION: More than half of the survey respondents endorsed elevated levels of personal and work-related burnout. This is concerning as burnout is associated with personal challenges and diminished patient care. Potential organizational interventions are discussed.

African ancestry GWAS of dementia in a large military cohort identifies significant risk loci.

While genome wide association studies (GWASs) of Alzheimer's Disease (AD) in European (EUR) ancestry cohorts have identified approximately 83 potentially independent AD risk loci, progress in non-European populations has lagged. In this study, data from the Million Veteran Program (MVP), a biobank which includes genetic data from more than 650,000 US Veteran participants, was used to examine dementia genetics in an African descent (AFR) cohort. A GWAS of Alzheimer's disease and related dementias (ADRD), an expanded AD phenotype including dementias such as vascular and non-specific dementia that included 4012 cases and 18,435 controls age 60+ in AFR MVP participants was performed. A proxy dementia GWAS based on survey-reported parental AD or dementia (n = 4385 maternal cases, 2256 paternal cases, and 45,970 controls) was also performed. These two GWASs were meta-analyzed, and then subsequently compared and meta-analyzed with the results from a previous AFR AD GWAS from the Alzheimer's Disease Genetics Consortium (ADGC). A meta-analysis of common variants across the MVP ADRD and proxy GWASs yielded GWAS significant associations in the region of APOE (p = 2.48 × 10-101), in ROBO1 (rs11919682, p = 1.63 × 10-8), and RNA RP11-340A13.2 (rs148433063, p = 8.56 × 10-9). The MVP/ADGC meta-analysis yielded additional significant SNPs near known AD risk genes TREM2 (rs73427293, p = 2.95 × 10-9), CD2AP (rs7738720, p = 1.14 × 10-9), and ABCA7 (rs73505251, p = 3.26 × 10-10), although the peak variants observed in these genes differed from those previously reported in EUR and AFR cohorts. Of the genes in or near suggestive or genome-wide significant associated variants, nine (CDA, SH2D5, DCBLD1, EML6, GOPC, ABCA7, ROS1, TMCO4, and TREM2) were differentially expressed in the brains of AD cases and controls. This represents the largest AFR GWAS of AD and dementia, finding non-APOE GWAS-significant common SNPs associated with dementia. Increasing representation of AFR participants is an important priority in genetic studies and may lead to increased insight into AD pathophysiology and reduce health disparities.

Central Nervous System Manifestations of COVID-19: A Critical Review and Proposed Research Agenda.

OBJECTIVE: On March 11, 2020, the World Health Organization declared an outbreak of a new viral entity, coronavirus 2019 (COVID-19), to be a worldwide pandemic. The characteristics of this virus, as well as its short- and long-term implications, are not yet well understood. The objective of the current paper was to provide a critical review of the emerging literature on COVID-19 and its implications for neurological, neuropsychiatric, and cognitive functioning. METHOD: A critical review of recently published empirical research, case studies, and reviews pertaining to central nervous system (CNS) complications of COVID-19 was conducted by searching PubMed, PubMed Central, Google Scholar, and bioRxiv. RESULTS: After considering the available literature, areas thought to be most pertinent to clinical and research neuropsychologists, including CNS manifestations, neurologic symptoms/syndromes, neuroimaging, and potential long-term implications of COVID-19 infection, were reviewed. CONCLUSION: Once thought to be merely a respiratory virus, the scientific and medical communities have realized COVID-19 to have broader effects on renal, vascular, and neurological body systems. The question of cognitive deficits is not yet well studied, but neuropsychologists will undoubtedly play an important role in the years to come.

Examination of Early CNS Symptoms and Severe Coronavirus Disease 2019: A Multicenter Observational Case Series.

To determine if early CNS symptoms are associated with severe coronavirus disease 2019. DESIGN: A retrospective, observational case series study design. SETTING: Electronic health records were reviewed for patients from five healthcare systems across the state of Florida, United States. PATIENTS: A clinical sample (n = 36,615) of patients with confirmed diagnosis of coronavirus disease 2019 were included. Twelve percent (n = 4,417) of the sample developed severe coronavirus disease 2019, defined as requiring critical care, mechanical ventilation, or diagnosis of acute respiratory distress syndrome, sepsis, or severe inflammatory response syndrome. INTERVENTIONS: None. MEASUREMENT AND MAIN RESULTS: We reviewed the electronic health record for diagnosis of early CNS symptoms (encephalopathy, headache, ageusia, anosmia, dizziness, acute cerebrovascular disease) between 14 days before the diagnosis of coronavirus disease 2019 and 8 days after the diagnosis of coronavirus disease 2019, or before the date of severe coronavirus disease 2019 diagnosis, whichever came first. Hierarchal logistic regression models were used to examine the odds of developing severe coronavirus disease 2019 based on diagnosis of early CNS symptoms. Severe coronavirus disease 2019 patients were significantly more likely to have early CNS symptoms (32.8%) compared with nonsevere patients (6.11%; χ2[1] = 3,266.08, p < 0.0001, φ = 0.29). After adjusting for demographic variables and pertinent comorbidities, early CNS symptoms were significantly associated with severe coronavirus disease 2019 (odds ratio = 3.21). Diagnosis of encephalopathy (odds ratio = 14.38) was associated with greater odds of severe coronavirus disease 2019; whereas diagnosis of anosmia (odds ratio = 0.45), ageusia (odds ratio = 0.46), and headache (odds ratio = 0.63) were associated with reduced odds of severe coronavirus disease 2019. CONCLUSIONS: Early CNS symptoms, and specifically encephalopathy, are differentially associated with risk of severe coronavirus disease 2019 and may serve as an early marker for differences in clinical disease course. Therapies for early coronavirus disease 2019 are scarce, and further identification of subgroups at risk may help to advance understanding of the severity trajectories and enable focused treatment.

Initial changes in neuropsychologists clinical practice during the COVID-19 pandemic: A survey study.

Objective: In light of the COVID-19 pandemic, a majority of clinicians have had to quickly and dramatically alter their clinical practices. Two surveys were administered on 3/26/2020 and 3/30/2020, respectively, to document immediate changes and challenges in clinical practice.Method: Two surveys were administered between 3/26/2020 and 3/30/2020, via SurveyMonkey and Google Forms, asking clinicians questions pertaining to practice issues during the early stages of the COVID-19 pandemic. Quantitative responses from the second survey were stratified by clinical setting (Medical Hospital vs. Private Practice) prior to analysis. Qualitative, free-response items were coded by the authors to better understand immediate changes in practice and other concerns.Results: 266 neuropsychologists completed Survey 1 and 230 completed Survey 2. Results suggest that practices immediately moved towards remote service provision. A meaningful proportion of clinicians and their staff were immediately affected economically by the pandemic, with clinicians in private practice differentially affected. Furthermore, a small but significant minority of respondents faced ethical dilemmas related to service provision and expressed concerns with initial communication from their employment organizations. Respondents requested clear best-practice guidelines from neuropsychological practice organizations.Conclusions: It is clear that field of neuropsychology has drastically shifted clinical practices in response to COVID-19 and is likely to continue to evolve. While these responses were collected in the early stages of stay-at-home orders, policy changes continue to occur and it is paramount that practice organizations consider the initial challenges expressed by clinicians when formulating practice recommendations and evaluating the clinical utility of telehealth services.

Validity of teleneuropsychology for older adults in response to COVID-19: A systematic and critical review.

Objective: Due to the recent COVID-19 pandemic, the field of neuropsychology must rapidly evolve to incorporate assessments delivered via telehealth, or teleneuropsychology (TNP). Given the increasing demand to deliver services electronically due to public health concerns, it is important to review available TNP validity studies. This systematic review builds upon the work of Brearly and colleagues' (2017) meta-analysis and provides an updated review of the literature, with special emphasis on test-level validity data.Method: Using similar methodology as Brearly and colleagues (2017) three internet databases (PubMed, EBSCOhost, PsycINFO) were searched for relevant articles published since 2016. Studies with older adults (aged 65+) who underwent face-to-face and TNP assessments in a counterbalanced cross-over design were included. After review, 10 articles were retained. Combined with nine articles from Brearly's analysis, a total of 19 studies were included in the systematic review.Results: Retained studies included samples from 5 different countries, various ethnic/cultural backgrounds, and diverse diagnostic populations. Test-level analysis suggests there are cognitive screeners (MMSE, MoCA), language tests (BNT, Letter Fluency), attention/working memory tasks (Digit Span Total), and memory tests (HVLT-R) with strong support for TNP validity. Other measures are promising but lack sufficient support at this time. Few TNP studies have done in-home assessments and most studies rely on a PC or laptop.Conclusions: Overall, there appears to be good support for TNP assessments in older adults. Challenges to TNP in the current climate are discussed. Finally, a provisional outline of viable TNP procedures used in our clinic is provided.

Erroneous conclusions: The impact of failing to identify invalid symptom presentation when conducting adult attention-deficit/hyperactivity disorder (ADHD) research.

Invalid symptom report during assessment confounds the differential diagnosis process. This study examined differences in neuropsychological functioning between individuals diagnosed with attention-deficit/hyperactivity disorder (ADHD) and depression and/or anxiety disorders before and after participants meeting diagnostic criteria for malingered neurocognitive dysfunction were excluded. One hundred sixty-one adult patients undergoing ADHD assessment [M age 27.98 (8.35)] were evaluated and assigned to one of two groups based on medical records, a clinical interview, and self-report measures (depression/anxiety disorder n = 85; ADHD and depression/anxiety disorders n = 76). When all patients were considered, individuals with comorbid ADHD and depression/anxiety symptoms performed more poorly on 10 of 18 neuropsychological measures compared with those with only a depression/anxiety disorder (Cohen's d ranged from .32 to .72). In contrast, there was no evidence that the cumulative effect of ADHD and depression/anxiety resulted in diminished cognitive performance after excluding 54 patients with invalid symptom presentation. Additionally, the magnitude of association between self-report of ADHD symptoms and performance on neuropsychological test measures decreased dramatically. Thus, it is imperative that researchers administer performance and symptom validity measures to identify invalid symptom presentation when conducting large-scale studies. The failure to do so may result in inaccurate conclusions regarding the neurocognitive functioning of patients with ADHD and comorbid conditions. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Physiological Synchronization and Subjective Workload in a Competitive Emergency Response Task.

Human dyads and larger teams tend to acquire synchronized movements and autonomic arousal levels while working together or simply socializing. The synchronization of arousal patterns is of theoretical interest for group dynamics because they may add predictive value to the dynamics of group cohesion and team performance. This study examined the four-way relationship among experimental conditions: team size, task difficulty, time pressure (between-subjects) and subsequent experimental sessions (within-subjects). Previously, we have shown these conditions affect subjective ratings of workload that come from individual and group-level sources, synchronization of arousal, and team performance. In an experiment involving an emergency response (ER) simulation, 360 undergraduates, who were wearing electrodermal sensors, were organized into 44 teams of various sizes. Workload was experimentally varied by team size (three, four, seven or eight members), number of opponents (one or two), and time pressure; the latter was introduced sooner or later across two experimental sessions. Results showed that the experimental conditions affected synchronization levels, either at the beginning of a session or in the middle; synchronization and experimental conditions were not directly related to team performance. Subjective group workload ratings of the coordination demand of the task correlated with synchronization at the beginning of a session while team satisfaction was correlated with greater synchrony at the end of a session. The competitive nature of the ER task, as compared to strictly cooperative tasks, could be responsible for the complexity of these empirical relationships.

Cusp catastrophe models for cognitive workload and fatigue in teams.

The use of two cusp catastrophe models has been effective for untangling the effects of cognitive workload, fatigue, and other complications on the performance of individuals. This study is the first to use the two models to separate workload and fatigue effects on team performance. In an experiment involving an emergency response simulation, 360 undergraduates were organized into 44 teams. Workload was varied by team size, number of opponents, and time pressure. The cusp models for workload and fatigue were more accurate for describing trends in team performance criteria compared to linear alternatives. Individual differences in elasticity-rigidity were less important than subjective workload and experimental conditions as control variables. Fluid intelligence within the team was an important compensatory ability in the fatigue model. Results further supported the nonlinear paradigm for the assessment of cognitive workload and fatigue and demonstrated its effectiveness for understanding team phenomena.

Autonomic Synchronization, Team Coordination, Participation, and Performance.

The synchronization of autonomic arousal levels within dyads and larger teams has become a potentially important variable in the explanation of team performance and group processes. Synchronization research with groups of three or more members has been challenging because of limited means for quantifying relationships that are more extensive than dyads. This article presents an empirical investigation of group performance and participation using a new synchronization coefficient that is grounded in nonlinear dynamical systems theory. We introduce the concept of a driver, a person with whom the group tends to synchronize the most, and an empath, a person who is most synchronized with other team members. Fifty-five undergraduate research participants, who were organized into 11 groups of three or four participants, played six emergency response simulations against an opponent while generating electrodermal data. Results showed that greater physiological synchronization resulted from better team performance and greater par-ticipation levels. Synchronization was higher for groups of four team members compared to three. Synchronization was also observed between the opponent and team members. Further opportunities for using the synchronization coefficient in group process research are discussed.

Turn Taking, Team Synchronization, and Non-stationarity in Physiological Time Series.

This study investigated the stationarity of electrodermal time series collected in situations where turn taking in human interactions are involved. In this context, the stationarity of the time series is the extent to which a simple model can be used to fit the entire time series. The experiment involved seven participants in an emergency response simulation against one opponent. They generated 48 time series across six simulations, which were split and re-spliced to separate the team's turns and the opponent's turns. Significant differences in R2 coefficients were found for both linear and nonlinear statistical models between experimental conditions, but the difference only amounted to 3% of the accuracy of those models relative to the original data. It was thus concluded that the impact of turn taking on stationarity was a small effect at most. A comparison of synchronization coefficients for the team data, which rely on the collective accuracy of the individual time series models, indicated stronger synchronization during periods when the team was watching the opponent's actions compared to when they took their own turns. It was thus concluded, furthermore, that the common focus of attention prevailed against any non-stationarity that was introduced by turn taking.

Performance and Participation Dynamics in an Emergency Response Simulation.

This study examined relationships between participation and performance within a team and performance transfer effects between opponents in an Emergency Response (ER) simulation. Classical organizational theories have emphasized the importance of group participation for organizational performance, but there have been few or no attempts to investigate participation-performance relationships in short-interval time series. The experimental task was a Stag Hunt game, as defined in game theory; performance trends would be affected by levels of participation, which in turn should be affected by recent performance experiences that modulate the players' self-efficacy for the task. Participants were 62 undergraduates who were organized into 11 teams of 3 or 4 members playing an ER board game against one attacker. Time series analyses were conducted through nonlinear regression with exponential structural equations and by linear analyses for comparison. Results showed that performance time series of one opponent did not affect the other for teams of this size. Teams showed higher levels of adaptability compared to attackers, as evidenced by higher Lyapunov exponents. Performance affected group participation levels more so than the other way around. There appeared to be emergent group dynamics occurring between two experimental sessions that moderated the validity of the core linear and nonlinear models. Emergent group properties are one of several possible directions for further investigation within this experimental paradigm. Nonlinear models were more accurate than linear models after correcting for correlated residuals.

Physiological Synchronization in Emergency Response Teams: Subjective Workload, Drivers and Empaths.

Behavioral and physiological synchronization have important implications for work teams with regard to workload management, coordinated behavior and overall functioning. This study extended previous work on the nonlinear statistical structure of GSR series in dyads to larger teams and included subjective ratings of workload and contributions to problem solving. Eleven teams of 3 or 4 people played a series of six emergency response (ER) games against a single opponent. Seven of the groups worked under a time pressure instruction at the beginning of the first game. The other four groups were not given that instruction until the beginning of the fourth game. The optimal lag length for the teams, which appeared to be phase-locked, was substantially shorter than that obtained previously for loosely-coupled dyads. There was a complex nonlinear effect from the time pressure manipulation on the autocorrelation over time that reflected workload and fatigue dynamics that were operating. The R2 values for linear and nonlinear statistical models differed by less than .01. The average amount of influence from one ER team member to another was 4.5-4.7% of the variance in GSR readings. ER team members were classified as drivers and empaths, based on the autocorrelations and transfer influences to and from other players in the GSR time series. Empaths were rated by their peers as making more types of positive contributions to the problem solving discussions than others, and drivers received the lowest ratings. Larger Lyapunov exponents that were calculated from the GSR time series were positively correlated with individuals' ratings of subjective workload and were negatively correlated with leadership indicators. Several directions for further research are outlined.