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INTRODUCTION: Patients with Alzheimer's disease present with difficulty in lexical retrieval and reversal of the concreteness effect in nouns. Little is known about the phenomena before the onset of symptoms. We anticipate early linguistic signs in the speech of people who suffer from amnestic mild cognitive impairment (MCI). Here, we report the results of a corpus‐linguistic approach to the early detection of cognitive impairment. METHODS: One hundred forty‐eight English‐speaking Singaporeans provided natural speech data, on topics of their choice; 74 were diagnosed with single‐domain MCI (38 amnestic, 36 non‐amnestic), 74 cognitively healthy. The recordings yield 267,310 words, which are tagged for parts of speech. We calculate the per‐minute word counts and concreteness scores of all tagged words, nouns, and verbs in the dataset. RESULTS: Compared to controls, subjects with amnestic MCI produce fewer but more abstract nouns. Verbs are not affected. DISCUSSION: Slower retrieval of nouns and the reversal of the concreteness effect in nouns are manifested in natural speech and can be detected early through corpus‐based analysis. Highlights: Reversal of the concreteness effect is manifested in patients with Alzheimer's disease (AD) and semantic dementia.The paper reports a corpus‐based analysis of natural speech by people with amnestic and non‐amnestic mild cognitive impairment (MCI) and cognitively healthy controls.People with amnestic MCI produce fewer and more abstract nouns than people with non‐amnestic MCI and healthy controls. Verbs appear to be unaffected.The imageability problem can be detected in natural everyday speech by people with amnestic MCI, which carries a higher risk of conversion to AD. [ABSTRACT FROM AUTHOR]

Background: Cognitive frailty, defined as having both physical frailty and cognitive impairment that does not satisfy the criteria for Major Neurocognitive Disorder, represents an elevated risk for morbidity. Hence, it is crucial to mitigate such risks. Physical activity interventions have been found effective in protecting against physical frailty and cognitive deterioration. This pilot RCT examines if smartwatches and mobile phone applications can help to increase physical activity, thereby improving physical and cognitive outcomes. Methods: Older individuals (n = 60) aged 60 to 85 years old will have their physical activity tracked using a smartwatch. The subjects will be randomized into two arms: one group will receive daily notification prompts if they did not reach the recommended levels of PA; the control group will not receive prompts. Outcome variables of physical activity level, neurocognitive scores, and physical frailty scores will be measured at baseline, T1 (3 months), and T2 (6 months). Sleep quality, levels of motivation, anxiety, and depression will be controlled for in our analyses. We hypothesize that the intervention group will have higher levels of physical activity resulting in improved cognitive and physical outcomes at follow-up. This study was approved by the National University of Singapore's Institutional Review Board on 17 August 2020 (NUS-IRB Ref. No.: H-20-038). Discussion: Wearable sensors technology could prove useful by facilitating self-management in physical activity interventions. The findings of this study can justify the use of technology in physical activity as a preventive measure against cognitive frailty in older adults. This intervention also complements the rapidly rising use of technology, such as smartphones and wearable health devices, in our lives today. Registration details: This study has been retrospectively registered on clinicaltrials.gov on 5th January 2021 (NCT Identifier: NCT04692974), after the first participant was recruited. [ABSTRACT FROM AUTHOR]

We can study how fast our biological aging clocks tick by calculating the difference (i.e., age gaps) between machine learning estimations of biological age and chronological age. While this approach has been increasingly used to study various aspects of aging, few had applied this approach to study cognitive and physical age gaps; not much is known about the behavioral and neurocognitive factors associated with these age gaps. In the present study, we examined these age gaps in relation to behavioral phenotypes and mild cognitive impairment (MCI) among community-dwelling older adults. Participants (N = 822, Agemean = 67.6) were partitioned into equally-sized training and testing samples. Cognitive and physical age-prediction models were fitted using nine cognitive and eight physical fitness test scores, respectively, within the training samples, and subsequently used to estimate cognitive and physical age gaps for each subject in the testing sample. These age gaps were then compared among those with and without MCI and correlated with 17 behavioral phenotypes in the domains of lifestyle, well-being, and attitudes. Across 5000 random train-test split iterations, we showed that older cognitive age gaps were significantly associated with MCI (versus cognitively normal) and worse outcomes across several well-being and attitude-related measures. Both age gaps were also significantly correlated with each other. These results suggest accelerated cognitive and physical aging were linked to worse well-being and more negative attitudes about the self and others and reinforce the link between cognitive and physical aging. Importantly, we have also validated the use of cognitive age gaps in the diagnosis of MCI. [ABSTRACT FROM AUTHOR]

"All old people are the same" is an unfortunate characterization of the perceived homogeneity in the older age group. This study attempts to debunk this myth in the context of the structural and functional brain. Within older relative to younger age groups, individuals are hypothesized to be more dissimilar to their similar-aged peers—thus demonstrating an age-related divergence. This study analyzed functional connectivity (FC) during multiple fMRI paradigms (2 rest + 5 tasks) and cortical thickness (CT) data from two lifespan datasets (Ntotal = 1161). On average, between-subject FC/CT correlations became weaker in the older age groups. Further analyses ruled out the possibility that more rapid age-related changes in older brains have increased the dissimilarity in these older age groups. Brain-wide analyses revealed significant effects of age-related divergence across most of the brain. Finally, CT similarity between a dyad significantly predicted their FC similarity across multiple fMRI task paradigms—demonstrating a close relationship between brain structure and function even at the between-dyad level. Contrary to the myth that "all old people are the same," these findings suggest young people are more similar to each other. This study presents major implications in the study of neural fingerprinting and brain-behavior associations. [ABSTRACT FROM AUTHOR]

Objective The Cambridge Neuropsychological Test Automated Battery (CANTAB) is widely used in research and clinical settings. However, little is known about the use of the CANTAB in the local aging context. This study aimed to develop normative data for various CANTAB measures in community-living older adults in Singapore. Normative data were built using the regression-based approach. A secondary aim was to examine the concurrent validity of CANTAB measures with their traditional neurocognitive test counterparts. Method A total of 210 older adults (Mage = 67.27 years, SD = 5.45) from an existing cohort study completed standard neurocognitive tests and a CANTAB battery. A total of 160 were normal aging, 46 diagnosed with Mild Cognitive Impairment (MCI), and one diagnosed with Dementia. Older adults with MCI and Dementia were not included in the calculation of norms but were included in other analyses. For the CANTAB battery, regression-based norms were generated for each CANTAB measure, with age, sex, and education included as covariates. Concurrent validity was examined by correlating the CANTAB measures with their traditional neurocognitive counterparts. Results As expected, performance across most CANTAB measures declined significantly with increasing age and decreasing education levels. There were no significant effects of sex on most CANTAB measures. Our study also showed that some CANTAB measures demonstrated good concurrent validity as they significantly correlated with their traditional neurocognitive test counterparts. Conclusions We have developed age, sex, and education-specific CANTAB norms for use in the local aging context. The advantages and challenges of using the CANTAB in the local aging context are discussed. [ABSTRACT FROM AUTHOR]

Background: Distrust, and more broadly, public perception of government's handling of a crisis, has been a widely studied topic within health crisis research and suggests that these perceptions are significantly associated with the behavior of its citizens. Purpose: To understand which aspects of the public's perception of government handling of the COVID-19 pandemic predicted engagement of protective behaviors among older adults, who are the most vulnerable to COVID-19. Methods: Participants were recruited from an ongoing biopsychosocial study on aging amongst community-dwelling older adults. There were two rounds of data collection, during the national lockdown and post-lockdown. The average length of follow-up was 5.88 months. N = 421 completed the first round of data collection and N = 318 subsequently completed the second round of questionnaires. Results: During the lockdown, perceptions that pandemic-related measures in place were sufficient, effective, timely, provided a sense of safety, important information was easily accessible, and government handling of the pandemic could be trusted, were found to significantly predict engagement in protective behaviors. During post-lockdown, only perceptions that measures in place were sufficient, provided a sense of safety, and important information was easily accessible, remained significant predictors. The perception that COVID-19 measures were clear and easy to understand now became a significant predictor. Conclusions: Public perceptions of government handling of the pandemic predicted engagement in protective behaviors but were less important during post-lockdown. To effectively engage older adults in protective behavior, our findings suggest for pandemic-related information to be accessible, introducing timely safety measures, and having easy-to-understand instructions for nuanced measures. [ABSTRACT FROM AUTHOR]

The COVID-19 lockdown has drastically limited social interactions and brought about a climate of fear and uncertainty. These circumstances not only increased affective symptoms and social isolation among community dwelling older adults but also alter the dynamics between them. Using network analyses, we study the changes in these dynamics before and during the lockdown. Community-dwelling older adults (N = 419) completed questionnaires assessing depression, anxiety, and social isolation, before the COVID-19 pandemic, as part of a cohort study, and during the lockdown period. The total scores of these questionnaires were compared across time. For the network analyses, partial correlation networks were constructed using items in the questionnaires as nodes, separately at both timepoints. Changes in edges, as well as nodal and bridge centrality were examined across time. Depression and anxiety symptoms, and social isolation had significantly increased during the lockdown. Significant changes were observed across time on several edges. Greater connectivity between the affective and social isolation nodes at lockdown was observed. Depression symptoms have become more tightly coupled across individuals, and so were the anxiety symptoms. Depression symptoms have also become slightly decoupled from those of anxiety. These changing network dynamics reflect the greater influence of social isolation on affective symptoms across individuals and an increased vulnerability to affective disorders. These findings provide novel perspectives and translational implications on the changing mental health context amidst a COVID-19 pandemic situation. [ABSTRACT FROM AUTHOR]

Previous research on older adults with superior cognitive abilities (super-cognition) has typically examined cognition using a single domain approach, which may not adequately capture the multidimensional nature of successful cognitive aging. Furthermore, the lifestyle factors associated with super-cognition have not been studied adequately. The current study examined the cognitive profiles and lifestyle factors associated with super-cognition. Community-dwelling older adults (N = 693) were administered neuropsychological tests and self-reported measures of lifestyle factors at midlife (retrospectively recalled). Then, using an a priori set of criteria, we classified them as super-cognition or normal. A latent class analysis was conducted to examine the different cognitive profiles of super-cognition, and both groups were compared on their lifestyle-related outcomes. A total of 64 and 263 participants met the criteria for super-cognition and normal participants respectively. A three-class solution best described super-cognition among our participants. Approximately half of them had superior immediate memory; two other smaller groups of participants with super-cognition had superior attention, language, and visuospatial abilities. Participants with super-cognition reported less participation in social activities and, frequently, working more than 9 hours/day and feeling stressed, at midlife. Super-cognition among the elderly is associated with having a busier, more socially-isolated and stressful midlife. [ABSTRACT FROM AUTHOR]

Objective: Findings from single-session online studies highlighted the potential of using anodal prefrontal transcranial direct current stimulation (tDCS) to enhance executive functions (EF) in the context of aging. However, tDCS must be executed as a multi-session offline intervention to ascertain its viability in this context. Relatedly, findings from multi-session studies remained inconclusive. To this end, we examined the effects of multi-session anodal prefrontal tDCS on EF in an intervention. Method: The intervention consisted of 15 sessions; in each, healthy older participants (Agemean = 66.7) received either 15 min of 1.5 mA tDCS (N completed = 35) or sham stimulation (N completed = 33) while performing EF training tasks. EF measures were assessed at baseline, post-intervention, and 1-month follow-up. Hierarchical linear models were used to examine the effect of tDCS on EF outcomes. Results: Both groups of participants did not differ significantly in side effect ratings and attendance. There were no significant tDCS-associated gains in any EF outcomes in the intervention. Conclusions: Multi-session prefrontal tDCS did not lead to any significant gains in EF in the current intervention. More research is needed to optimize the use of tDCS before it can be effectively used to enhance EF among older adults. [ABSTRACT FROM AUTHOR]

The present study utilized a person-centered approach to examine the different profiles of problem sleepers in a community sample of elderly. In addition, this study also explores how demographic and psychiatric variables may be related to these different profiles of sleep problems. A total of 515 participants (Mean age = 67 years, SD = 5) were administered self-report measures of sleep problems, depression and anxiety. Among them, 230 who reported significant problems in any of five selected sleep components were entered into a latent class analysis. The remaining 285 participants were assigned to a comparison control group. The profiles of ‘inadequate sleep', ‘disturbed sleep’, ‘trouble falling asleep’ and ‘multiple problems’ were identified. The ‘multiple problems’ group had significantly higher levels of depression and anxiety relative to the control group. Regression analyses indicated that these different profiles had contributed to a significant increase in variance explained in anxiety but not depression levels, on top of the severity of sleep problems and demographic variables. Although sleep problems occur among the elderly with considerable heterogeneity, they can generally be classified into four different profiles. Furthermore, the inclusion of sleep problem profiles can significantly enhance the prediction of anxiety symptoms. [ABSTRACT FROM AUTHOR]

Prior literature has suggested that cognitive flexibility is implicated in the feeling of hopelessness. However, studies on the nature of their relationship have been scarce. This study posits a moderation hypothesis on the relationship between cognitive flexibility and hopelessness. A total of 78 elderly participants (Mage = 70, SD = 6.1) were administered a self-report measure of hopelessness across two time points approximately 10 months apart and a measure of cognitive flexibility. We hypothesized that baseline hopelessness scores would moderate the relationship between cognitive flexibility and hopelessness scores 10 months later. Specifically, among the high baseline hopelessness group, we predicted that cognitively flexible participants would report lower hopelessness scores 10 months later. However, for the low baseline hopelessness group, cognitive flexibility would be unrelated to hopelessness scores 10 months later. The results of a bootstrapped moderation analysis controlling for age, sex, education, and general cognitive status supported our moderation hypothesis and predictions. These findings reveal the complex nature of the relationship between cognitive flexibility and hopelessness. The implications of these findings in the wider clinical context were discussed. [ABSTRACT FROM AUTHOR]

Geriatric depression and anxiety disorders often manifest as neuropsychiatric symptoms among those with mild cognitive impairment. Both tend to co-occur, and overlap in symptomology and etiology. Such commonalities are likely to be reflected in the brain as common neural correlates. Using connectome-based predictive modeling (CPM), we examined the functional and structural connectomes predicting depression and anxiety symptoms, and subsequently the overlap and cross-syndrome generalization of the connectomes associated with either disorder. Ninety-one older adults completed self-reported measures of depression and anxiety, and underwent diffusion tensor imaging and resting-state functional magnetic resonance imaging. Functional connectivity (FC) and structural connectivity (SC) matrices were derived from these scans and, in various combinations, entered into CPM models to predict either type of symptoms. Leave-one-out cross-validation was performed. Predictive accuracy was assessed via the correlation between predicted and observed scores (ρ predicted-observed). While FC or SC features alone significantly predicted either type of symptoms, these symptoms were best predicted by models that consisted of both FC and SC features (depression: ρ predicted-observed = 0.497; anxiety: ρ predicted-observed = 0.455). The features common to depression and anxiety were identified and entered into another model which was similarly accurate in predicting either type of symptoms. Moreover, cross-syndrome generalization was observed— the depression-associated features significantly predicted anxiety symptoms (ρ predicted-observed = 0.403) and vice-versa (ρ predicted-observed = 0.378). These FC and SC features are complementary biomarkers of geriatric depression and anxiety symptoms. Both types of symptoms are largely underpinned by common patterns of altered FC and SC, alluding to the transdiagnostic neurobiological susceptibility in both disorders. • Connectome-based predictive models were modified to include multimodal features. • Depression and anxiety symptoms were best predicted by multimodal features. • Both types of symptoms were significantly predicted by their overlapping features. • Depression model predicted anxiety scores and vice versa. [ABSTRACT FROM AUTHOR]