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Community-dwelling people with Mild Cognitive Impairment self-reporting not to be meeting recommended physical activity levels participated in this study to (a) determine compliance of wearing (thigh-worn) accelerometers, (b) describe physical activity levels and sedentary behavior, and (c) determine the validity of the Physical Activity Scale for the Elderly (PASE) compared with activPAL accelerometers. A total of 79 people had valid accelerometer data (median [interquartile range]: age, 71 [54–75] years). Compliance was 86.81%. Participants were sedentary for 10.6 hr per day and engaged in a median of 9 min per day of moderate-intensity physical activity. Fair correlations were found between the PASE and total stepping time per day (r =.35, p <.01), total number of steps per day (r =.36, p <.01), and number of steps in stepping activities completed for ≤1 min (r =.42, p <.01). The PASE and Standing time (r =.04, p =.724) and PASE and Sitting time (r =.04, p =.699) had little to no relationship. The use of thigh-worn accelerometers for this population is achievable. People with Mild Cognitive Impairment have high levels of sedentary behavior and minimal engagement in moderate-intensity physical activity. The PASE has fair, positive criterion validity with activity-based outcomes measured by activPAL accelerometers but not with sedentary behavior, which is high for this population. [ABSTRACT FROM AUTHOR]

Most clinical information is encoded as free text, not accessible for quantitative analysis. This study presents an open-source pipeline using the local large language model (LLM) "Llama 2" to extract quantitative information from clinical text and evaluates its performance in identifying features of decompensated liver cirrhosis. The LLM identified five key clinical features in a zero- and one-shot manner from 500 patient medical histories in the MIMIC IV dataset. We compared LLMs of three sizes and various prompt engineering approaches, with predictions compared against ground truth from three blinded medical experts. Our pipeline achieved high accuracy, detecting liver cirrhosis with 100% sensitivity and 96% specificity. High sensitivities and specificities were also yielded for detecting ascites (95%, 95%), confusion (76%, 94%), abdominal pain (84%, 97%), and shortness of breath (87%, 97%) using the 70 billion parameter model, which outperformed smaller versions. Our study successfully demonstrates the capability of locally deployed LLMs to extract clinical information from free text with low hardware requirements. [ABSTRACT FROM AUTHOR]

Purpose: The current study used behavioral measures of discourse complexity and story recall accuracy in an expository discourse task to distinguish older adults testing within range of cognitive impairment according to a standardized cognitive screening tool in a sample of self-reported healthy older adults. Method: Seventy-three older adults who self-identified as healthy completed an expository discourse task and neuropsychological screener. Discourse data were used to classify participants testing within range of cognitive impairment using multiple machine learning algorithms and stability analysis for identifying reliably predictive features in an effort to maximize prediction accuracy. We hypothesized that a higher rate of pronoun use and lower scores on story recall would best classify older adults testing within range of cognitive impairment. Results: The highest classification accuracy exploited a single variable in a remarkably intuitive way: using 66% story recall as a cutoff for cognitive impairment. Forcing this decision tree model to use more features or increasing its complexity did not improve accuracy. Permutation testing confirmed that the 77% accuracy and 0.18 Brier skill score achieved by the model were statistically significant (p < .00001). Conclusions: These results suggest that expository discourse tasks that place demands on executive functions, such as working memory, can be used to identify aging adults who test within range of cognitive impairment. Accurate representation of story elements in working memory is critical for coherent discourse. Our simple yet highly accurate predictive model of expository discourse provides a promising assessment for easy identification of cognitive impairment in older adults. [ABSTRACT FROM AUTHOR]

Limited research has compared cognition of people with non-central nervous system metastatic cancer (NCM) vs. metastatic brain cancer (BM). This prospective cross-sectional study was comprised 37 healthy controls (HC), 40 NCM, and 61 BM completing 10 neuropsychological tests. The NCM performed below HCs on processing speed and executive functioning tasks, while the BM group demonstrated lower performance across tests. Tasks of processing speed, verbal fluency, and verbal memory differentiated the clinical groups (BM < NCM). Nearly 20% of the NCM group was impaired on at least three neuropsychological tests whereas approximately 40% of the BM group demonstrated the same level of impairment. [ABSTRACT FROM AUTHOR]

Purpose: Impairments of hearing and auditory processing (AP) have been indicated as risk factors for dementia, but it remains unclear if persons with clinically diagnosed mild cognitive impairment (MCI) show such impairments. The objective of these analyses was to compare AP between those with and without a clinical diagnosis of MCI using a battery of AP measures. Method: Data from 274 older adults from the Keys to Staying Sharp randomized clinical trial (NCT03528486) were analyzed. A battery of AP measures in which three domains (temporal processing, binaural processing, and degraded speech understanding) were addressed by six tests was administered. Analyses were registered at https://osf.io/nga4v. Results: Those with and without a clinical diagnosis of MCI differed significantly in age, p = .002; pure-tone hearing in the left ear, p = .007; sex, p = .015; and race, p < .001. These covariates were included in multivariate analysis of covariance, which indicated significant differences between persons with and without MCI on measures of binaural processing (ps ≤ .006), but not on measures of temporal processing or degraded speech (ps ≥ .093). Pure-tone hearing averages did not significantly differ among those with or without MCI after adjusting for age, sex, and race (ps ≥ .292). Conclusions: AP in the binaural domain is impaired in MCI, but peripheral hearing did not significantly differ between those with and without MCI. Poor performance on AP measures of binaural processing may reflect problems dividing attention and may be indicative of dementia risk. Results have clinical implications for early detection of and intervention for cognitive impairment. [ABSTRACT FROM AUTHOR]

Dementia represents a significant global health challenge, with early screening during the preclinical stage being crucial for effective management. Traditional diagnostic biomarkers for Alzheimer's Disease, the most common form of dementia, are limited by cost and invasiveness. Mild cognitive impairment (MCI), a precursor to dementia, is currently identified through neuropsychological tests like the Montreal Cognitive Assessment (MoCA), which are not suitable for large-scale screening. Eye-tracking technology, capturing and quantifying eye movements related to cognitive behavior, has emerged as a promising tool for cognitive assessment. Subtle changes in eye movements could serve as early indicators of MCI. However, the interpretation of eye-tracking data is challenging. This study introduced a dementia screening tool, VR Eye-tracking Cognitive Assessment (VECA), using eye-tracking technology, machine learning, and virtual reality (VR) to offer a non-invasive, efficient alternative capable of large-scale deployment. VECA was conducted with 201 participants from Shenzhen Baoan Chronic Hospital, utilizing eye-tracking data captured via VR headsets to predict MoCA scores and classify cognitive impairment across different educational backgrounds. The support vector regression model employed demonstrated a high correlation (0.9) with MoCA scores, significantly outperforming baseline models. Furthermore, it established optimal cut-off scores for identifying cognitive impairment with notable sensitivity (88.5%) and specificity (83%). This study underscores VECA's potential as a portable, efficient tool for early dementia screening, highlighting the benefits of integrating eye-tracking technology, machine learning, and VR in cognitive health assessments. [ABSTRACT FROM AUTHOR]

Background: Cognitive impairment and dementia are frequently under-recognized. Health system strategies anchored in primary care are essential to address gaps in timely, comprehensive diagnosis. The goal of this paper is to describe the adaptation of a tablet-based brain health assessment (TabCAT-BHA) intervention and the study protocol to test its effectiveness in improving the detection of cognitive impairment, including dementia. Methods: This mixed-methods, pragmatic, cluster randomized, hybrid effectiveness-implementation trial is being conducted in two 18-month waves with 26 Kaiser Permanente Southern California primary care clinics, with 13 serving as intervention clinics and 13 as usual care clinics. Patients 65 years and older with memory concerns (n ~ 180,000) receiving care at the 26 clinics will be included in the analyses. Primary care clinics are provided the following practice supports as part of the TabCAT-BHA intervention: brief education and training on neurocognitive disorders and study workflows; digital tools to assess cognitive function and support clinician decision making and documentation; and registered nurse support during the work-up and post-diagnosis periods for primary care providers, patients, and families. The intervention was adapted based on engagement with multiple levels of clinical and operational leaders in the healthcare system. Effectiveness outcomes include rates of cognitive impairment diagnosis in primary care and rates of completed standardized cognitive assessments and specialist referrals with incident diagnoses. Implementation outcomes include acceptability-appropriateness-feasibility, adoption, and fidelity. Results: We identified seven themes organized by system-, provider-, and patient-level domains that were used to adapt the TabCAT-BHA intervention. Accordingly, changes were made to the provider education, diagnostic work-up, and post-diagnostic support. Results will be reported in fall of 2027. Conclusions: Our engagement with multiple primary and specialty care clinical and operational leaders to adapt the TabCAT-BHA intervention to these primary care clinics has informed the protocol to evaluate the intervention's effectiveness for improving the detection of cognitive impairment, including dementia, in an integrated healthcare system. Trial Registation: Clinicaltrials.gov: NCT06090578 (registered 10/24/23). [ABSTRACT FROM AUTHOR]

The article revisits the meaning of cognitive impairment in older adults using the Aging, Demographics and Memory Study (ADAMS). Topics discussed include the methods used in the study, the performance of Mini-Mental State Examination (MMSE) as a screening tool for dementia, and the clinical implications of a low MMSE score.

Background: The need for cognitive testing is increasing with the aging population and the advent of new Alzheimer disease therapies. To respond to the increased demand, the XpressO was developed as a self‐administered digital cognitive prescreening tool that will help distinguish between populations of subjective and objective cognitive impairment according to the Montreal Cognitive Assessment (MoCA). Methods: This is a prospective validation study. XpressO is composed of tasks that assess memory and executive functions. It is validated compared to the digital MoCA as a gold standard. Out of 118 participants screened from the MoCA Clinic and a family practice clinic, 88 met inclusion criteria, two participants had missing data due to incomplete tasks, 86 participants were included in the analysis; the mean age was 70.34 years. A logistic regression model was built, and its accuracy was evaluated by the sensitivity, specificity, and Area Under the Curve (AUC) of the Receiver Operating Characteristic. Results: Analysis showed strong correlation between (1) XpressO memory tasks scores and the MoCA Memory Index Score (p‐values < 0.001), and between (2) XpressO sub‐test scores and MoCA total score (p‐values < 0.005). The AUC for predicting MoCA performance is 0.845. To classify individuals with normal and abnormal MoCA scores, two threshold values were introduced for the total XpressO scores: sensitivity of 91% at a cutoff of 72, specificity of 90% at a cutoff of 42, and an undetermined range in between. Conclusion: XpressO demonstrated high AUC, high sensitivity and specificity to predict cognitive performance compared to the digital MoCA. It may provide efficient cognitive prescreening by identifying individuals who would benefit from further clinical assessments, potentially reducing waiting times and high burden on healthcare clinics. [ABSTRACT FROM AUTHOR]

BACKGROUND: Postoperative delirium in patients receiving head and neck surgery is a pressing concern, affecting morbidity, mortality, and healthcare costs. With an aging population and about 65,000 new head and neck cancer diagnoses per year in the United States, surgery remains a primary treatment modality, regardless of age. OBJECTIVES: This article offers an educational overview of postoperative delirium management in patients receiving head and neck surgery, summarizing incidence, etiology, pathophysiology, diagnostic tests, treatment, complications, and risk factors. METHODS: A narrative literature review of articles published in the past 10 years was conducted to consolidate information on postoperative delirium in patients receiving head and neck surgery. FINDINGS: Postoperative delirium is characterized by acute, fluctuating cognitive dysfunction within 30 days after surgery, with incidence ranging from 11% to 26%. Pathophysiology is multifactorial, and pharmacologic options are limited because of side effects and varying effectiveness. Nonpharmacologic management focuses on addressing underlying causes and early mobilization. Reducing postoperative delirium risk necessitates interprofessional, systemwide collaboration. [ABSTRACT FROM AUTHOR]

Symptomatic HIV-associated neurocognitive disorder (HAND) is a complication of HIV (cognitive impairment, difficulties with everyday functioning). If detected early, interventions assist with optimizing care, avoiding rapid decline and enhancing coping. There remains inconsistency surrounding screening/diagnosis information within Australian healthcare professionals and community settings. A scoping review of academic literature, government policies and non-government organisations (NGOs) was conducted to map existing screening/diagnosis information using the guidelines of Joanna Briggs Institute. A literature search of EBSCOhost and Medline (dates: 2015–2021), the Australian government NGO web domains, Google and unpublished academic works was conducted (July 2021) and updated (December 2022) to identify Australian items (past 5 years). Seventeen items met the inclusion criteria. No government guidelines were identified. Various HIV-related organisations proposed different diagnostic guidelines. Most HAND research originated in Sydney. The most accessible information was from Dementia Australia, with some inaccuracies noted. There is scant Australian research/information on HAND screening/diagnosis. HAND translational research and screening/diagnosis standards are urgently needed to inform best practices. The Australian context is used to discuss international implications regarding higher-income countries with similar patterns/healthcare. [ABSTRACT FROM AUTHOR]

Objective: Early identification of cognitive impairment in older adults could reduce the burden of age-related disabilities. Gait parameters are associated with and predictive of cognitive decline. Although a variety of sensors and machine learning analysis methods have been used in cognitive studies, a deep optimized machine vision-based method for analyzing gait to identify cognitive decline is needed. Methods: This study used a walking footage dataset of 158 adults named West China Hospital Elderly Gait, which was labelled by performance on the Short Portable Mental Status Questionnaire. We proposed a novel recognition network, Deep Optimized GaitPart (DO-GaitPart), based on silhouette and skeleton gait images. Three improvements were applied: short-term temporal template generator (STTG) in the template generation stage to decrease computational cost and minimize loss of temporal information; depth-wise spatial feature extractor (DSFE) to extract both global and local fine-grained spatial features from gait images; and multi-scale temporal aggregation (MTA), a temporal modeling method based on attention mechanism, to improve the distinguishability of gait patterns. Results: An ablation test showed that each component of DO-GaitPart was essential. DO-GaitPart excels in backpack walking scene on CASIA-B dataset, outperforming comparison methods, which were GaitSet, GaitPart, MT3D, 3D Local, TransGait, CSTL, GLN, GaitGL and SMPLGait on Gait3D dataset. The proposed machine vision gait feature identification method achieved a receiver operating characteristic/area under the curve (ROCAUC) of 0.876 (0.852-0.900) on the cognitive state classification task. Conclusion: The proposed method performed well identifying cognitive decline from the gait video datasets, making it a prospective prototype tool in cognitive assessment. [ABSTRACT FROM AUTHOR]

Background: Vascular cognitive impairment (VCI) manifests in memory impairment, mental slowness, executive dysfunction, behavioral changes, and visuospatial abnormalities, significantly compromising the quality of daily life for patients and causing inconvenience to caregivers. Neuroimaging serves as a crucial approach to evaluating the extent, location, and type of vascular lesions in patients suspected of VCI. Nevertheless, there is still a lack of comprehensive bibliometric analysis to discern the research status and emerging trends concerning VCI neuroimaging. Objective: This study endeavors to explore the collaboration relationships of authors, countries, and institutions, as well as the research hotspots and frontiers of VCI neuroimaging by conducting a bibliometric analysis. Methods: We performed a comprehensive retrieval within the Core Collection of Web of Science, spanning from 2000 to 2023. After screening the included literature, CiteSpace and VOSviewer were utilized for a visualized analysis aimed at identifying the most prolific author, institution, and journal, as well as extracting valuable information from the analysis of references. Results: A total of 1,024 publications were included in this study, comprising 919 articles and 105 reviews. Through the analysis of keywords and references, the research hotspots involve the relationship between neuroimaging of cerebral small vessel disease (CSVD) and VCI, the diagnosis of VCI, and neuroimaging methods pertinent to VCI. Moreover, potential future research directions encompass CSVD, functional and structural connectivity, neuroimaging biomarkers, and lacunar stroke. Conclusion: The research in VCI neuroimaging is constantly developing, and we hope to provide insights and references for future studies by delving into the research hotspots and frontiers within this field. [ABSTRACT FROM AUTHOR]

The aging population in Canada has been increasing continuously throughout the past decades. Amongst this demographic, around 11% suffer from some form of cognitive decline. While diagnosis through traditional means (i.e., Magnetic Resonance Imagings (MRIs), positron emission tomography (PET) scans, cognitive assessments, etc.) has been successful at detecting this decline, there remains unexplored measures of cognitive health that could reduce stress and cost for the elderly population, including approaches for early detection and preventive methods. Such efforts could additionally contribute to reducing the pressure and stress on the Canadian healthcare system, as well as improve the quality of life of the elderly population. Previous evidence has demonstrated emotional facial expressions being altered in individuals with various cognitive conditions such as dementias, mild cognitive impairment, and geriatric depression. This review highlights the commonalities among these cognitive health conditions, and research behind the contactless assessment methods to monitor the health and cognitive well-being of the elderly population through emotion expression. The contactless detection approach covered by this review includes automated facial expression analysis (AFEA), electroencephalogram (EEG) technologies and heart rate variability (HRV). In conclusion, a discussion of the potentials of the existing technologies and future direction of a novel assessment design through fusion of AFEA, EEG and HRV measures to increase detection of cognitive decline in a contactless and remote manner will be presented. [ABSTRACT FROM AUTHOR]

Detecting cognitive impairments early after stroke is essential for appropriate referrals. Although recommended in stroke guidelines, early cognitive screening is not always implemented. We assessed whether the Montreal Cognitive Assessment (MoCA) adds diagnostic value compared to clinical observation alone. In addition, discharge destinations for stroke patients with and without cognitive deficits detected with the screening tool or the treatment team were explored. Forty-four stroke patients were screened with the MoCA during stroke unit admission. Their charts were studied for cognitive impairments reported by the stroke care team, who were blinded to screening scores. Proportions of detected cognitive deficits were compared between screening (score <26) and patient charts. Discharge destination distribution (home vs. rehabilitation) was explored. The proportion of cognitively impaired patients indicated by the MoCA (84%) and reported in patients' charts (25%) differed significantly (p < 0.001). The distribution of discharge destination did not suggest an association with the detection of cognitive deficits by the treatment team or the cognitive screening. The MoCA detects more cognitive deficits than clinical impression alone, emphasizing the importance of standard screening for cognitive impairments in acute stroke patients. Ultimately, systematic screening may enhance discharge planning and improve long-term outcomes. [ABSTRACT FROM AUTHOR]

Background: Mild cognitive deficits (MCD) emerge before the first episode of psychosis (FEP) and persist in the clinical high-risk (CHR) stage. This study aims to refine risk prediction by developing MCD models optimized for specific early psychosis stages and target populations. Methods: A comprehensive neuropsychological battery assessed 1059 individuals with FEP, 794 CHR, and 774 matched healthy controls (HCs). CHR subjects, followed up for 2 years, were categorized into converters (CHR-C) and non-converters (CHR-NC). The MATRICS Consensus Cognitive Battery standardized neurocognitive tests were employed. Results: Both the CHR and FEP groups exhibited significantly poorer performance compared to the HC group across all neurocognitive tests (all p < 0.001). The CHR-C group demonstrated poorer performance compared to the CHR-NC group on three sub-tests: visuospatial memory (p < 0.001), mazes (p = 0.005), and symbol coding (p = 0.023) tests. Upon adjusting for sex and age, the performance of the MCD model was excellent in differentiating FEP from HC, as evidenced by an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.895 (p < 0.001). However, when applied in the CHR group for predicting CHR-C (AUC = 0.581, p = 0.008), the performance was not satisfactory. To optimize the efficiency of psychotic risk assessment, three distinct MCD models were developed to distinguish FEP from HC, predict CHR-C from CHR-NC, and identify CHR from HC, achieving accuracies of 89.3%, 65.6%, and 80.2%, respectively. Conclusions: The MCD exhibits variations in domains, patterns, and weights across different stages of early psychosis and diverse target populations. Emphasizing precise risk assessment, our findings highlight the importance of tailored MCD models for different stages and risk levels. [ABSTRACT FROM AUTHOR]

Background: Understanding the development of cognitive impairment and its influencing factors in older adults is crucial for formulating early intervention strategies. Purpose: To identify the early dimensions of cognitive impairment and provide a comprehensive description of the trajectories of cognitive decline in older adults prior to death. Methods: Based on the data of 9883 older adults in the Chinese Longitudinal Healthy Longevity Survey from 2002 to 2018, a longitudinal item response theory (Longitudinal IRT) model including covariates was applied to estimate the following parameters. The items in which older adults encountered obstacles first had the least difficulty parameters (δ). The earlier the information curve of an item is lifted, the more information it provides in the early stages of cognitive impairment. Regression coefficient (β) represents the relative rate of cognitive decline. The cognitive impairment values estimated from the Longitudinal IRT were fitted to a mixed‐effects model to examine cognitive impairment trajectories. Results: 'Draw the figure on B Card' (δ = −0.816) was the most challenging item, followed by 'recalling 'clothes" (δ = 0.348) and 'recalling 'apples" (δ = 0.419), while 'name the 'pen" (δ = 4.402) was the simplest instruction for the old adults. The curves of the items in the recall dimension began to rise in the early stages of cognitive impairment. Cognitive impairment of older adults who were women (β = 0.061), elder (β = 0.111), smokers (β = 0.060), living in rural areas (β = 0.052), not participating in organised social activities (β = 0.092), suffering from hypertension (β = 0.022), hyperglycaemia (β = 0.035), dyslipidaemia (β = 0.314), low education levels (β = 0.128), manual labourers (β = 0.027), and eventual development of dementia (β = 0.212) exhibited a more accelerated progression. These individuals also had poorer cognitive trajectories. Conclusion: Recall is the earliest dimension of cognitive impairment. The subjects who were women, elder, smokers, living in rural areas, not participating in organised social activities, suffering from hypertension, hyperglycaemia, dyslipidaemia, low education, manual labourers, and eventually development of dementia, had a faster descending speed and poorer trajectories. [ABSTRACT FROM AUTHOR]

Introduction: The prevalence of cognitive impairment and dementia in the older population is increasing, and thereby, early detection of cognitive decline is essential for effective intervention. Methods: This study included 2,288 participants with normal cognitive function from the Ma'anshan Healthy Aging Cohort Study. Forty-two potential predictors, including demographic characteristics, chronic diseases, lifestyle factors, anthropometric indices, physical function, and baseline cognitive function, were selected based on clinical importance and previous research. The dataset was partitioned into training, validation, and test sets in a proportion of 60% for training, 20% for validation, and 20% for testing, respectively. Recursive feature elimination was used for feature selection, followed by six machine learning algorithms that were employed for model development. The performance of the models was evaluated using area under the curve (AUC), specificity, sensitivity, and accuracy. Moreover, SHapley Additive exPlanations (SHAP) was conducted to access the interpretability of the final selected model and to gain insights into the impact of features on the prediction outcomes. SHAP force plots were established to vividly show the application of the prediction model at the individual level. Results: The final predictive model based on the Naive Bayes algorithm achieved an AUC of 0.820 (95% CI, 0.773–0.887) on the test set, outperforming other algorithms. The top ten influential features in the model included baseline Mini-Mental State Examination (MMSE), education, self-reported economic status, collective or social activities, Pittsburgh sleep quality index (PSQI), body mass index, systolic blood pressure, diastolic blood pressure, instrumental activities of daily living, and age. The model demonstrated the potential to identify individuals at a higher risk of cognitive impairment within 3 years from older adults. Conclusion: The predictive model developed in this study contributes to the early detection of cognitive impairment in older adults by primary healthcare staff in community settings. [ABSTRACT FROM AUTHOR]

Background 10-year atherosclerotic cardiovascular disease (ASCVD) risk scores were useful for predicting large vessel disease, but the relationships between them and cerebral small vessel disease (CSVD) were unclear. Our study aimed to evaluate associations of 10-year ASCVD risk scores with CSVD and its magnetic resonance imaging (MRI) markers. Methods Community-dwelling residents from the PolyvasculaR Evaluation for Cognitive Impairment and vaScular Events study were included in this cross-sectional study. At baseline, we collected data related to the Framingham Risk Score (FRS), pooled cohort equation (PCE), prediction for ASCVD risk in China (China-PAR) and Systematic COronary Risk Evaluation model 2 (SCORE2), and classified participants into low, moderate and high groups. Participants underwent brain MRI scans. We evaluated white matter hyperintensity (WMH), lacunes, cerebral microbleeds (CMBs) and enlarged perivascular spaces in basal ganglia (BG-EPVS) according to criteria of Wardlaw and Rothwell, and calculated total CSVD score and modified total CSVD score. Results A total of 3063 participants were included, and 53.5% of them were female. A higher FRS was associated with higher total CSVD score (moderate vs. low: cOR 1.89, 95% CI 1.53–2.34; high vs. low: cOR 3.23, 95%CI 2.62–3.97), and the PCE, China-PAR or SCORE2 score was positively related to total CSVD score (P  < 0.05). Moreover, higher 10-year ASCVD scores were associated with higher odds of WMH (P  < 0.05), lacunes (P  < 0.05), CMBs (P  < 0.05) and BG-EPVS (P  < 0.05). Conclusions The 10-year ASCVD scores were positively associated with CSVD and its MRI markers. These scores provided a method of risk stratification in the population with CSVD. [ABSTRACT FROM AUTHOR]

Background: Electrophysiological biomarkers are being examined as potential diagnostic measures of cognitive impairment and its manifestations for psychiatric nurses' use in the care of Alzheimer's disease (AD). However, there is no integrative review describing the themes from the current research about electrophysiological biomarkers and the developing relationship among the themes. Characterizing this developing relationship is imperative for any possible integration of biomarkers into the care of AD by psychiatric nurses. Objective: The purpose of this integrative review is to identify themes from the current research about electrophysiological biomarkers of AD and the developing relationship among the themes, the conceivable relational premise for psychiatric nurses to integrate electrophysiological biomarkers into the screening, assessment, diagnosis, and treatment of AD for the care of persons with AD. Methods: A literature search was executed with PUBMED (accessing Medline and Elsevier) and CINAHL databases that focused on studies about electrophysiological biomarkers of AD from 2015 to 2022. Twenty-seven peer-reviewed studies met this review's inclusion criteria. Results: Five themes emerged: (1) assessing/screening, (2) assessment differential, (3) diagnosing, (4) diagnostic accuracy, and (5) treating. These themes related sequentially and linearly, establishing a developing relationship about the risk, the onset, and the progression of AD. Discussion: Electrophysiological biomarkers associated to cognitive impairment in AD, supporting the accepted understanding of the symptoms of AD. Changes in behavior and functioning were not examined, limiting the possible integration of electrophysiological biomarkers. Further investigations are warranted with an expansion of the clinical symptoms and diverse study populations. [ABSTRACT FROM AUTHOR]

Background and Objectives The number of older adults diagnosed with dementia is expected to more than double by mid-century. Monitoring older adults' cognitive functioning is essential for the early detection of dementia, which can increase treatment efficacy and slow the disease progression. Current approaches to detect preclinical dementia are expensive, invasive, and are not accessible to everyone. This study aimed to determine whether technology use patterns could be used as an indicator of cognitive change. Research Design and Methods Using 6 waves (2015–2020) from the National Health and Aging Trends Study, we examined within-person and between-person effects of stopping 4 types of technology use on 4 cognitive outcomes. Results Our analyses showed that stopping the use of the Internet, computers, and tablets, and sending texts and e-mails were related to cognitive decline. Discussion and Implications These results suggest that monitoring technology use patterns may be an innovative approach that is economical and efficient to identify individuals at risk of cognitive decline. [ABSTRACT FROM AUTHOR]

Background Cortical thickness (CT) alterations, mismatch negativity (MMN) reductions, and cognitive deficits are robust findings in first-episode psychosis (FEP). However, most studies focused on medicated patients, leaving gaps in our understanding of the interrelationships between CT, MMN, neurocognition, and psychosocial functioning in unmedicated FEP. This study aimed to employ multiple mediation analysis to investigate potential pathways among these variables in unmedicated drug-naïve FEP. Methods We enrolled 28 drug-naïve FEP and 34 age and sex-matched healthy controls. Clinical symptoms, neurocognition, psychosocial functioning, auditory duration MMN, and T1 structural magnetic resonance imaging data were collected. We measured CT in the superior temporal gyrus (STG), a primary MMN-generating region. Results We found a significant negative correlation between MMN amplitude and bilateral CT of STG (CT_STG) in FEP (left: r  = −.709, P  < .001; right: r  = −.612, P  = .008). Multiple mediation models revealed that a thinner left STG cortex affected functioning through both direct (24.66%) and indirect effects (75.34%). In contrast, the effects of the right CT_STG on functioning were mainly mediated through MMN and neurocognitive pathways. Conclusions Bilateral CT_STG showed significant association with MMN, and MMN plays a mediating role between CT and cognition. Both MMN alone and its interaction with cognition mediated the effects of structural alterations on psychosocial function. The decline in overall function in FEP may stem from decreased CT_STG, leading to subsequent MMN deficits and neurocognitive dysfunction. These findings underline the crucial role of MMN in elucidating how subtle structural alterations can impact neurocognition and psychosocial function in FEP. [ABSTRACT FROM AUTHOR]

The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) Effort Index (EI) may be unreliable at its standard recommended cutoff score when used with forensic psychiatric inpatient populations given high rates of genuine cognitive impairment. The present study sought to (a) examine the rate of invalid performance on the RBANS EI using the standard cutoff among incompetent to stand trial (IST) inpatients and (b) investigate the psychometric properties of the RBANS EI at various cutoff scores. This study was conducted using archival assessment data collected at a large forensic psychiatric hospital. Across the entire sample (N = 238, 79% male, Mage = 45 years, 24% primary Spanish-speaking), 79% were diagnosed with a schizophrenia spectrum disorder. Experiment 1 of the study (n = 165) contained IST patients who were classified as having a valid presentation. Experiment 2 contained a valid (n = 46) and invalid (n = 27) presentation group comprised of postadjudication and IST inpatients, respectively. In Experiment 1, over one third (36.4%) of the valid presentation sample scored above the standard recommended EI cutoff. In Experiment 2, applying the standard recommended cutoff score of >3 was associated with a false positive rate of over 20%. Obtaining <10% false positive errors was achieved at a cutoff score of >5. At this cutoff score, the estimated local base rate of invalid responding among IST patients was 28%. Clinical and forensic implications and recommendations for adopting this more conservative RBANS EI cutoff score are discussed. Public Significance Statement: The current research suggests that individuals with schizophrenia spectrum disorders who reside in forensic hospital settings are at risk for being falsely identified as putting forth invalid performance on the Repeatable Battery for the Assessment of Neuropsychological Status Effort Index when using the standard recommended cutoff score, which may be related to high rates of genuine cognitive impairment. As such, an alternative Repeatable Battery for the Assessment of Neuropsychological Status Effort Index cutoff score is recommended when assessing individuals in these and similar settings. [ABSTRACT FROM AUTHOR]

Accessible SummaryWhat is known on the subject?Functioning is one of the most affected areas in schizophrenia. Social, occupational and personal domains are affected, and these deficits are responsible for a major part of the disability associated with the disorder.There are several instruments to measure functioning, but the HoNOS provides a wide assessment of impairment in 12 areas of functioning.What does the paper add to existing knowledge?The Spanish version of the HoNOS shows good properties in terms of reliability and validity for use in schizophrenia patients.Although some authors divide the scale according to proposed underlying dimensions, in schizophrenia this division may not be appropriate.What are the implications for practice?A reliable and easy‐to‐use measure of impairment in different areas of functioning is useful for optimizing the treatment and rehabilitation of patients with schizophrenia. Introduction: The HoNOS scale was designed for the assessment of psychosocial impairment in various domains. While it is widely used in psychiatric settings, it has not been validated in Spanish for use in patients with schizophrenia. Aim: To examine the psychometric properties of the Spanish version of the HoNOS scale in a sample of schizophrenia patients. Method: A total of 194 individuals aged 18 to 65 with schizophrenia spectrum diagnoses were evaluated using the HoNOS. Illness severity and level of functioning were also assessed. Results: The HoNOS showed moderate internal consistency, good inter‐observer reliability and good test‐retest reliability. Factor analysis revealed an internal structure consisting of four factors, with item distribution differing from the theoretical dimensions proposed for the original scale. Discussion: The Spanish version of the HoNOS scale is a reliable and valid instrument for assessing psychosocial impairment in individuals diagnosed with schizophrenia spectrum disorders. However, further research is needed to determine its internal structure more accurately. Implications for Practice: The HoNOS scale provides researchers and clinicians with a valid measure of impairment in twelve different domains, which can facilitate and guide the treatment of schizophrenia patients. [ABSTRACT FROM AUTHOR]

Background: Cognitive impairment associated with schizophrenia (CIAS) represents a distinct, persistent, and core group of schizophrenia symptoms. Cognitive symptoms have been shown to have an impact on quality of life. There are several published CIAS measures, but none based on direct patient self-report. It is important to capture the patient's perspective to supplement performancebased outcome measures of cognition to provide a complete picture of the patient's experience. This paper describes additional validation work on the Patient-Reported Experience of Cognitive Impairment in Schizophrenia (PRECIS) instrument. Methods: Data from two large, international, pharmaceutical clinical trials in medically and psychiatrically stable English-speaking patients with schizophrenia and 88 healthy controls were analyzed. An exploratory factor analysis (EFA) was conducted in one trial (n = 215), using the original 35-item PRECIS. The factor structure suggested by EFA was further evaluated using item response theory (IRT; Samejima's graded response model), and tested using confirmatory factor analysis (CFA). Both EFA and CFA results were tested in a second trial with similar inclusion/exclusion characteristics (n = 410). Additional statistical properties were evaluated in healthy controls. Results: EFA suggested that the best solution after item reduction suggested a factor structure of 6 factors based on 26 items (memory, communication, self-control, executive function, attention, sharpness of thought), supporting a total score, with an additional 2-item bother score (28 items in all). IRT analysis indicated the items were well-ordered within each domain. The CFA demonstrated excellent model fit, accounting for 69% of the variance. The statistical properties of the 28-item version of the PRECIS were confirmed in the second trial. Evidence for internal consistency and test-retest reliability was robust. Known-groups validity was supported by comparison of healthy controls with patients with schizophrenia. Correlations indicated moderate associations between PRECIS and functioning instruments like the Schizophrenia Cognition Rating Scale (SCoRS), but weak correlations with performance-based outcomes like MATRICS Consensus Cognitive Battery (MCCB). Discussion: Using two clinical trial samples, we identified a robust factor structure for the PRECIS and were able to replicate it in the second sample. Evaluation of the meaningful score difference (MSD) should be repeated in future studies, as these samples did not show enough change for it to be evaluated. Conclusions: This analysis provides strong evidence for the reliability and validity of the PRECIS, a 28-item, patient-reported instrument to assess cognitive impairment associated with schizophrenia. The correlation with functioning and the weak correlation with performance on cognitive tasks suggests that patient reports of cognitive impairment measure a unique aspect of patient experience. [ABSTRACT FROM AUTHOR]

Background and Objectives Proxy respondents are an important tool in survey research, especially among people with cognitive impairment. However, proxy respondents may be unable to accurately answer subjective survey instruments for cognitively impaired persons. This study investigates the mediating effect of proxy status on the relationship between cognitive impairment and subjectively rated health. Research Design and Methods Respondents from the 2018 wave of the Health and Retirement Study (N  = 17,146) were included, and the Baron and Kenny method assessed the potential mediating role of having a proxy on subjectively rated health. Subjectively rated health and proxy status were dichotomously coded, and relationships between cognitive impairment, proxy status, and subjectively rated health were assessed using logistic regression. Results Findings indicate that cognitive impairment is inversely associated with subjectively rated health, and it is directly associated with having a proxy. They also indicate that having a proxy is inversely related to subjectively rated health. When including proxy status and cognitive impairment in the same model, cognitive impairment no longer predicted subjectively rated health. This indicates that proxy status perfectly mediated the relationship between cognitive impairment and subjectively rated health. Discussion and Implications Measuring the experiences of people with cognitive impairment is challenging in survey research due to the limiting features of cognitive impairment. Although having a proxy respondent helps address attrition-related measurement challenges in survey research, findings indicate that proxies report worse subjectively rated health for people with cognitive impairment compared to individuals with comparable levels of cognitive impairment without a proxy. Future research may benefit from exploring optimal proxy-respondent characteristics. [ABSTRACT FROM AUTHOR]

Background: Individuals experiencing subjective cognitive decline (SCD) are at an increased risk of developing mild cognitive impairment and dementia. Early identification of SCD and neurodegenerative diseases using biomarkers may help clinical decision-making and improve prognosis. However, few cross-sectional and longitudinal studies have explored plasma biomarkers in individuals with SCD using immunomagnetic reduction. Objective: To identify plasma biomarkers for SCD. Methods: Fifty-two participants [38 with SCD, 14 healthy controls (HCs)] underwent baseline assessments, including measurements of plasma Aß42, Aß40, t-tau, p-tau, and a-synuclein using immunomagnetic reduction (IMR) assays, cognitive tests and the Mini-Mental State Examination (MMSE). Following initial cross-sectional analysis, 39 individuals (29 with SCD, 10 HCs) entered a longitudinal phase for reassessment of these biomarkers and the MMSE. Biomarker outcomes across different individual categories were primarily assessed using the area under the receiver operating characteristic (ROC) curve. The SCD subgroup with an MMSE decline over one point was compared to those without such a decline. Results: Higher baseline plasma Aß1-42 levels significantly discriminated participants with SCD from HCs, with an acceptable area under the ROC curve (AUC) of 67.5% [95% confidence interval (CI), 52.7-80.0%]. However, follow-up and changes in MMSE and IMR data did not significantly differ between the SCD and HC groups (p > 0.05). Furthermore, lower baseline plasma Aß1-42 levels were able to discriminate SCD subgroups with and without cognitive decline with a satisfied performance (AUC, 75.0%; 95% CI, 55.6-89.1%). At last, the changes in t-tau and Aß42 × t-tau could differentiate between the two SCD subgroups (p < 0.05). Conclusion: Baseline plasma Aß42 may help identify people with SCD and predict SCD progression. The role of plasma Aß42 levels as well as their upward trends from baseline in cases of SCD that progress to mild cognitive impairment and Alzheimer's disease require further investigation. [ABSTRACT FROM AUTHOR]

Neurodegenerative disorders such as Alzheimer's disease (AD) represent an increasingly significant public health concern. As clinical diagnosis faces challenges, biomarkers are becoming increasingly important in research, trials, and patient assessments. While biomarkers like amyloid‐β peptide, tau proteins, CSF levels (Aβ, tau, and p‐tau), and neuroimaging techniques are commonly used in AD diagnosis, they are often limited and invasive in monitoring and diagnosis. For this reason, blood‐based biomarkers are the optimal choice for detecting neurodegeneration in brain diseases due to their noninvasiveness, affordability, reliability, and consistency. This literature review focuses on plasma neurofilament light (NfL) and CSF NfL as blood‐based biomarkers used in recent AD diagnosis. The findings revealed that the core CSF biomarkers of neurodegeneration (T‐tau, P‐tau, and Aβ42), CSF NFL, and plasma T‐tau were strongly associated with Alzheimer's disease, and the core biomarkers were strongly associated with mild cognitive impairment due to Alzheimer's disease. Elevated levels of plasma and cerebrospinal fluid NfL were linked to decreased [18F]FDG uptake in corresponding brain areas. In participants with Aβ positivity (Aβ+), NfL correlated with reduced metabolism in regions susceptible to Alzheimer's disease. In addition, CSF NfL levels correlate with brain atrophy and predict cognitive changes, while plasma total tau does not. Plasma P‐tau, especially in combination with Aβ42/Aβ40, is promising for symptomatic AD stages. Though not AD‐exclusive, blood NfL holds promise for neurodegeneration detection and assessing treatment efficacy. Given the consistent levels of T‐tau, P‐tau, Aβ42, and NFL in CSF, their incorporation into both clinical practice and research is highly recommended. [ABSTRACT FROM AUTHOR]

Disabled older adults exhibited a higher risk for cognitive impairment. Early identification is crucial in alleviating the disease burden. This study aims to develop and validate a prediction model for identifying cognitive impairment among disabled older adults. A total of 2138, 501, and 746 participants were included in the development set and two external validation sets. Logistic regression, support vector machine, random forest, and XGBoost were introduced to develop the prediction model. A nomogram was further established to demonstrate the prediction model directly and vividly. Logistic regression exhibited better predictive performance on the test set with an area under the curve of 0.875. It maintained a high level of precision (0.808), specification (0.788), sensitivity (0.770), and F1-score (0.788) compared with the machine learning models. We further simplified and established a nomogram based on the logistic regression, comprising five variables: age, daily living activities, instrumental activity of daily living, hearing impairment, and visual impairment. The areas under the curve of the nomogram were 0.871, 0.825, and 0.863 in the internal and two external validation sets, respectively. This nomogram effectively identifies the risk of cognitive impairment in disabled older adults. [ABSTRACT FROM AUTHOR]

Background and objectives People with parkinsonism who are older, living in a care home, with frailty, multimorbidity or impaired capacity to consent are under-represented in research, limiting its generalisability. We aimed to evaluate more inclusive recruitment strategies. Methods From one UK centre, we invited people with parkinsonism to participate in a cross-sectional study. Postal invitations were followed by telephone reminders and additional support to facilitate participation. Personal consultees provided information on the views regarding research participation of adults with impaired capacity. These approaches were evaluated: (i) using external data from the Parkinson's Real World Impact assesSMent (PRISM) study and Clinical Practice Research Datalink (CPRD), a sample of all cases in UK primary care, and (ii) comparing those recruited with or without intensive engagement. Results We approached 1,032 eligible patients, of whom 542 (53%) consented and 477 (46%) returned questionnaires. The gender ratio in PRIME-UK (65% male) closely matched CPRD (61% male), unlike in the PRISM sample (46%). Mean age of PRIME participants was 75.9 (SD 8.5) years, compared to 75.3 (9.5) and 65.4 (8.9) years for CPRD and PRISM, respectively. More intensive engagement enhanced recruitment of women (13.3%; 95% CI 3.8, 22.9%; P  = 0.005), care home residents (6.2%; 1.1, 11.2%; P  = 0.004), patients diagnosed with atypical parkinsonism (13.7%; 5.4, 19.9%; P  < 0.001), and those with a higher frailty score (mean score 0.2, 0.1, 0.2; P  < 0.001). Conclusions These recruitment strategies resulted in a less biased and more representative sample, with greater inclusion of older people with more complex parkinsonism. [ABSTRACT FROM AUTHOR]

Background: Dementia is a cognitive decline that leads to the progressive deterioration of an individual's ability to perform daily activities independently. As a result, a considerable amount of time and resources are spent on caretaking. Early detection of dementia can significantly reduce the effort and resources needed for caretaking. Aims: This research proposes an approach for assessing cognitive decline by analysing speech data, specifically focusing on speech relevance as a crucial indicator for memory recall. Methods & Procedures: This is a cross‐sectional, online, self‐administered. The proposed method used deep learning architecture based on transformers, with BERT (Bidirectional Encoder Representations from Transformers) and Sentence‐Transformer to derive encoded representations of speech transcripts. These representations provide contextually descriptive information that is used to analyse the relevance of sentences in their respective contexts. The encoded information is then compared using cosine similarity metrics to measure the relevance of uttered sequences of sentences. The study uses the Pitt Corpus Dementia dataset for experimentation, which consists of speech data from individuals with and without dementia. The accuracy of the proposed multi‐QA‐MPNet (Multi‐Query Maximum Inner Product Search Pretraining) model is compared with other pretrained transformer models of Sentence‐Transformer. Outcomes & Results: The results show that the proposed approach outperforms the other models in capturing context level information, particularly semantic memory. Additionally, the study explores the suitability of different similarity measures to evaluate the relevance of uttered sequences of sentences. The experimentation reveals that cosine similarity is the most appropriate measure for this task. Conclusions & Implications: This finding has significant implications for the early warning signs of dementia, as it suggests that cosine similarity metrics can effectively capture the semantic relevance of spoken language. The persistent cognitive decline over time acts as one of the indicators for prevalence of dementia. Additionally early dementia could be recognised by analysis on other modalities like speech and brain images. WHAT THIS PAPER ADDS: What is already known on this subject: It is already known that speech‐ and language‐based detection methods can be useful for dementia diagnosis, as language difficulties are often early signs of the disease. Additionally, deep learning algorithms have shown promise in detecting and diagnosing dementia through analysing large datasets, particularly in speech‐ and language‐based detection methods. However, further research is needed to validate the performance of these algorithms on larger and more diverse datasets and to address potential biases and limitations. What this paper adds to existing knowledge: This study presents a unique and effective approach for cognitive decline assessment through analysing speech data. The study provides valuable insights into the importance of context and semantic memory in accurately detecting the potential in dementia and demonstrates the applicability of deep learning models for this purpose. The findings of this study have important clinical implications and can inform future research and development in the field of dementia detection and care. What are the potential or actual clinical implications of this work?: The proposed approach for cognitive decline assessment using speech data and deep learning models has significant clinical implications. It has the potential to improve the accuracy and efficiency of dementia diagnosis, leading to earlier detection and more effective treatments, which can improve patient outcomes and quality of life. [ABSTRACT FROM AUTHOR]

Introduction: Early diagnosis of dementia is partly based on the evaluation of the basic (b-), instrumental (i-) and advanced (a-) activities of daily living (ADL). Adapting the item content of assessment tools to maintain relevance, understanding, and equivalence of the items and scales across other groups is pertinent. However, there are limited assessment tools developed on or adapted for use on the growing older Sub-Saharan African (SSA) migrant population in Europe. Focusing on the item content, we evaluated the relevance of the advanced activities of daily living (a-ADL) tool to the older SSA migrant population in Belgium. Method: Two focus group discussions were organized with participants from the SSA community in Gent, Belgium. Relevant, irrelevant, unclear, and new items were identified. The data was analyzed through the inductive method while consensus agreements were used to arrive at refined themes. Results: Out of the 49 items on the tool, both groups unanimously agreed that 15 items were relevant and 23 irrelevant. Thirteen new items were identified, whereas 15 items were considered unclear. Conclusion: Participants agreed the tool was relevant but should be adapted. Verification and validation of these results in a larger SSA older migrant population in Belgium is strongly recommended. [ABSTRACT FROM AUTHOR]

The worldwide incidence of cognitive impairment is escalating, yet no effective solutions for these afflictions have been discovered. Consequently, the importance of early identification and immediate intervention is heightened. Advanced eye movements--a form of voluntary eye movements that includes anti-saccades, memory-guided saccades, predictive saccades, pro-saccades and gap/overlap saccades, mediated by the cerebral cortex and subcortical pathways reflect cognitive levels and functions across different domains. In view of their objectivity, reproducibility, and non-invasive characteristics, advanced eye movement examination possesses significant prospective utility across a wide range of cognitive impairment. This paper extensively reviews various models associated with advanced eye movement examinations and their current applications in cognitive impairment such as Alzheimer's disease, Lewy body dementia and frontotemporal dementia. Advanced eye movement examination can serve as a biomarker for early screening diagnosis and research on cognitive impairment. In the future, combining advanced eye movement examination with neuropsychological scale assessment and other diagnostic methods may contribute to further early identification of these types of diseases. [ABSTRACT FROM AUTHOR]

Background: Vascular cognitive impairment (VCI) is a major cause of cognitive impairment in the elderly and a co-factor in the development and progression of most neurodegenerative diseases. With the continuing development of neuroimaging, multiple markers can be combined to provide richer biological information, but little is known about their diagnostic value in VCI. Methods: A total of 83 subjects participated in our study, including 32 patients with vascular cognitive impairment with no dementia (VCIND), 21 patients with vascular dementia (VD), and 30 normal controls (NC). We utilized resting-state quantitative electroencephalography (qEEG) power spectra, structural magnetic resonance imaging (sMRI) for feature screening, and combined them with support vector machines to predict VCI patients at different disease stages. Results: The classification performance of sMRI outperformed qEEG when distinguishing VD from NC (AUC of 0.90 vs. 0,82), and sMRI also outperformed qEEG when distinguishing VD from VCIND (AUC of 0.8 vs. 0,0.64), but both underperformed when distinguishing VCIND from NC (AUC of 0.58 vs. 0.56). In contrast, the joint model based on qEEG and sMRI features showed relatively good classification accuracy (AUC of 0.72) to discriminate VCIND from NC, higher than that of either qEEG or sMRI alone. Conclusion: Patients at varying stages of VCI exhibit diverse levels of brain structure and neurophysiological abnormalities. EEG serves as an affordable and convenient diagnostic means to differentiate between different VCI stages. A machine learning model that utilizes EEG and sMRI as composite markers is highly valuable in distinguishing diverse VCI stages and in individually tailoring the diagnosis. [ABSTRACT FROM AUTHOR]

Introduction: Assessing functional decline related to activities of daily living (ADLs) is deemed significant for the early diagnosis of dementia. As current assessment methods for ADLs often lack the ability to capture subtle changes, technology-based approaches are perceived as advantageous. Specifically, digital biomarkers are emerging, offering a promising avenue for research, as they allow unobtrusive and objective monitoring. Methods: A study was conducted with the involvement of 36 participants assigned to three known groups (Healthy Controls, participants with Subjective Cognitive Decline and participants with Mild Cognitive Impairment). Participants visited the CERTH-IT Smart Home, an environment that simulates a fully functional residence, and were asked to follow a protocol describing different ADL Tasks (namely Task 1 - Meal, Task 2 - Beverage and Task 3 - Snack Preparation). By utilizing data from fixed in-home sensors installed in the Smart Home, the identification of the performed Tasks and their derived features was explored through the developed CARL platform. Furthermore, differences between groups were investigated. Finally, overall feasibility and study satisfaction were evaluated. Results: The composition of the ADLs was attainable, and differentiation among the HC group compared to the SCD and the MCI groups considering the feature "Activity Duration" in Task 1 - Meal Preparation was possible, while no difference could be noted between the SCD and the MCI groups. Discussion: This ecologically valid study was determined as feasible, with participants expressing positive feedback. The findings additionally reinforce the interest and need to include people in preclinical stages of dementia in research to further evolve and develop clinically relevant digital biomarkers. [ABSTRACT FROM AUTHOR]

Aim: This study aimed to examine the relationships between levels of competence and impaired physical and cognitive functions in older adults. Methods: We used a data set of the Integrated Longitudinal Studies on Aging in Japan for 2017 including 5475 community-dwelling older adults. Levels of competence were assessed using the Japan Science and Technology Agency Index of Competence (JST-IC). Grip strength (low grip strength: <28 kg for men and <18 kg for women) and gait speed (slow gait speed: <1.0 m/s for both sexes) were evaluated as physical function measurements, and the Mini-Mental State Examination (cognitive decline: <24 on the Mini-Mental State Examination) was used to assess cognitive function. Results: The JST-IC had areas under the curve estimated from receiver operating characteristic analysis ranging from 0.65 to 0.73 for detecting low function as assessed by these tests. Restricted cubic spline curves showed that the shape of the association between the JST-IC and impaired function depended on sex and the test used. The comparison between perfect and imperfect JST-IC scores showed significant differences in the prevalence of low grip strength in both sexes, slow gait speed in women, and cognitive decline in men. Conclusions: It may be insufficient to identify those with impaired physical or cognitive function using the JST-IC. The shape of the association with the JST-IC varies across their measurements. Our findings can help interpret JST-IC scores in the context of low physical and cognitive functions. [ABSTRACT FROM AUTHOR]

Previous studies have suggested that individuals with Parkinson's disease (PD) have difficulty retrieving verbs and nouns. Among the factors that have been proposed to contribute to this verb retrieval difficulty is the semantic properties of the verbs. The aim of this study was to investigate the verb and noun naming abilities in Greek speaking individuals with PD. Furthermore, the effect of semantic complexity on verb retrieval ability was explored. Specifically, two verb categories were investigated mainly, instrumental verbs as semantically heavy and non-instrumental verbs that are considered semantically light verbs. Participants were 24 non-demented individuals with PD matched for age and education with 15 healthy control participants. Word retrieval abilities for nouns and verbs were evaluated using the Greek Object and Action Test (GOAT), a picture-based assessment of single word retrieval. The results revealed that participants with PD performed significantly worse on naming verbs and nouns compared to healthy controls. Specifically, the PD group had a greater difficulty in retrieving verbs compared to nouns. In addition, a positive effect of instrumentality on verb retrieval abilities was observed. The results of this study suggest that semantic complexity may play a critical role in verb retrieval abilities in PD. Furthermore, verbs related to upper limb movement with the inclusion of instrumental verbs may have a facilitatory effect on lexical retrieval. This finding emphasizes the need for the inclusion of the evaluation of different verb categories for naming during the initial clinical assessment of cognitive-linguistic abilities of patients with PD. [ABSTRACT FROM AUTHOR]

Objectives: We previously analysed the preparedness to deliver a disease-modifying Alzheimer's treatment in the United Kingdom and predicted substantial wait times. This study updates the prediction for the National Health Service (NHS) in England, using an improved model and newer data. Methods: We reviewed published data on capacity for diagnosis of cognitive impairment combined with expert input and constructed a model for wait times to access from 2023 to 2043. The model tracks patients from initial evaluation in primary care, cognitive testing by a dementia specialist, confirmatory biomarker testing with positron emission tomography (PET) scans or examination of cerebrospinal fluid and infusion delivery. Capacity for specialist visits and PET scans are assumed to be capacity constrained, and cerebrospinal fluid testing and infusion delivery to be scalable. Results: Capacity constraints were projected to result in substantial wait times: patients referred to specialists based on a brief cognitive test, which is the current standard of care, would expect an overall initial wait times of 56 months in 2023, increasing to 129 months in 2029 and then falling slowly to around 100 months. Use of a blood test for the confirmation of Alzheimer's pathology as an additional triage step, would reduce wait times to around 17 to 25 months. Discussion: The NHS England lacks capacity to provide timely access to a disease-modifying treatment, which is estimated to result in significant wait times and potentially avoidable disease progression. Better diagnostic tools at initial evaluation may reduce delays. [ABSTRACT FROM AUTHOR]

As the percentage of older adults aged 65 and over continues to rise dramatically in the United States and globally, psychology must develop ways to meet the behavioral health needs of this age group. The psychology workforce devoted to working with older adults is insufficient, and one consequence of this deficit is the underidentification of behavioral health symptoms in this age group, often closing the door for further intervention. Older adults with mild-moderate symptoms and who reside in rural and/or underresourced areas are least likely to seek help for behavioral health concerns, and, when they do, it is most often requested from their primary care provider who may not recognize symptoms as indicative of a behavioral health concern. Psychologists in training participated in a clinical experience to improve their competence in providing services to older adults. This training and community engagement experience focused on the identification of mild-moderate behavioral health symptoms within a rural, community-dwelling older adult population over a 6-year span. Students provided behavioral health screenings, psychoeducation, feedback, and referral to assessment/treatment services for older adults during regional health and wellness events. Screening results revealed high rates of anxiety, mild neurocognitive disorder, and depressive symptomology in our sample (n = 658) of older adults, providing evidence for routine and systematic screening and early detection of behavioral health symptoms in the older adult age group. Impacts on readiness to work with older adults by those who completed this clinical training experience are discussed. [ABSTRACT FROM AUTHOR]

Considering various factors that influence the accuracy of the Subjective Visual Vertical (SVV) and Subjective Postural Vertical (SPV), standardization of assessment methods is needed. This retrospective study examined the contribution of Head-on-Body (HOB) position, starting roll position (SRP) and visuospatial neglect (VSN) to SVV and SPV constant errors (i.e. deviation from true vertical). Also, the contribution of HOB position and VSN presence to SVV and SPV variability (i.e. intra-individual consistency between trials) was assessed. First-ever unilateral hemispheric stroke survivors (<85 years; <100 days post-stroke) were assessed with three HOB positions (neutral, contralesional, and ipsilesional) and seven starting positions (20°Contralesional to 20° ipsilesional) of the laser bar and tilt chair. Linear mixed models were selected to evaluate the contribution of HOB, SRP, and VSN to SVV/SPV constant errors and variability. Thirty-four subjects (24 VSN-/10 VSN+) were assessed. A tilted HOB position led to significantly higher constant errors for the SVV and SPV (the latter only in the VSN- group), and an increased SVV variability. SRP only significantly contributed to the SVV constant errors and only in the VSN- group. Furthermore, the presence of VSN resulted in a significantly higher SVV and SPV variability. HOB position and the presence of SRP and VSN are important factors to consider during SVV and SPV measurements. Assessment with a neutral HOB position leads to more accurate results. HOB position and SRP influence the results of SVV and SPV differently in individuals with and without VSN, which highlights the relevance of VSN assessment. [ABSTRACT FROM AUTHOR]

Purpose: To systematically review the prevalence of motoric cognitive risk syndrome (MCR) among community-dwelling older adults and provide evidence-based support for policymakers planning health and social care policies. Method: Web of Science, PubMed, and Cochrane Library databases were searched for cross-sectional, prospective cohort, or population-based longitudinal studies of community-dwelling older adults aged ≥60 years with MCR from inception of the database through December 18, 2021. Results: Seventeen studies were included. Pooled prevalence of MCR was found to be 10% (95% confidence interval [8%, 12%], I2 = 98.4%). Results of a subgroup analysis revealed a combined prevalence of MCR of 8.2% in males and 9.2% in females. Pooled prevalence of MCR was 9.7% in Asia and 10.2% in other regions. Conclusion: Prevalence of MCR in community-dwelling older adults is high. Our research may improve the epidemiological understanding of MCR, draw attention to older adults with MCR, and thus promote research of MCR and the formulation of relevant public health policies. With early identification and intervention of MCR, cognitive function can be improved, and the onset of dementia can be delayed or prevented. [Journal of Gerontological Nursing, 50(4), 16–24.] [ABSTRACT FROM AUTHOR]

Aging shows biologically complex features with high individual variability, which reflects the exposure to several stimuli and the adaptation to them. Among them, metabolic changes are well observed as consequences or possible causes of aging. Calorie restriction extends organismal life span in experimental models. Several metabolites; for example, resveratrol or nicotinamide mononucleotide, are reported to mimic calorie restriction effects in vivo. Metabolomic research would be useful to evaluate metabolites as biomarkers in aging‐relevant events and to identify metabolic regulation of aging. We recently developed the metabolomic approach for whole blood analysis, which functions as strong tool for this purpose. We review the update findings in aging‐relevant metabolites detected by this method. Geriatr Gerontol Int 2024; 24: 44–48. [ABSTRACT FROM AUTHOR]

Background: Gesture imitation, a simple tool for assessing visuospatial/visuoconstructive functions, is reportedly useful for screening and diagnosing dementia. However, gesture imitation performance in healthy older adults is largely unknown, as are the factors associated with lower performance. To address these unknowns, we examined the gesture imitation performance of a large number of community‐dwelling older adults aged ≥65 years in Arao City, Kumamoto Prefecture (southern Japan). Methods: The examiner presented the participants with eight gesture patterns and considered it a success if they could imitate them within 10 s. The success rate of each gesture imitation was calculated for three diagnostic groups: cognitively normal (CN) (n = 1184), mild cognitive impairment (MCI) (n = 237), and dementia (n = 47). Next, we reorganised the original gesture imitation battery by combining six selected gestures with the following scoring method: if the participants successfully imitated the gestures, immediately or within 5 s, two points were assigned. If they succeeded within 5–10 s, one point was assigned. The sensitivity and specificity of the battery were investigated to detect the dementia and MCI groups. Factors associated with gesture imitation battery scores were examined. Results: Except one complex gesture, the success rate of imitation in the CN group was high, approximately 90%. The sensitivity and specificity of the gesture imitation battery for discriminating between the dementia and CN groups and between the MCI and CN groups were 70%/88%, and 45%/75%, respectively. Ageing, male sex, and a diagnosis of dementia or MCI were associated with lower scores on the gesture imitation battery. Conclusion: Gesture imitation tasks alone may not be sufficient to detect MCI. However, by combining gestures with set time limits, gesture imitation tasks can be a low‐burden and effective method for detecting dementia, even in community medicine, such as during health check‐ups. [ABSTRACT FROM AUTHOR]

Background: The Mini‐Mental State Examination (MMSE) is the most widely used standardised screener for impairments across a range of cognitive domains. However, the degree to which its domains (orientation, registration, attention, recall, language, and visuospatial) capture cognitive functioning measured using standardised neuropsychological tests is unclear. Method: A longitudinal research design with four biannual assessments over a 6‐year period was used with an initial sample of 1037 older adults (aged above 70 years). Participants completed MMSE and neuropsychological tests at each assessment. Network analysis was utilised to investigate unique associations among the MMSE and its domains and neuropsychological test performance at each time point. Results: The total MMSE and two of its domains, language and recall, were associated with neuropsychological memory performance. The MMSE orientation, registration and visuospatial domains did not have any unique associations with neuropsychological performance. No stable internal interconnections between MMSE domains were found over time. The association of total MMSE as well as its recall domain with neuropsychological memory performance remained very similar over the 6‐year period. Conclusions: The present study adds evidence to the validity of the MMSE and supports the clinical usage of the MMSE, whereby the total score is used for screening patients with or without cognitive impairments, with repeated administration to monitor cognitive changes over time, to inform intervention. However, the tool is not able to diagnose the cases for changes in specific cognitive domains and as such, should not replace a complete neuropsychological assessment. [ABSTRACT FROM AUTHOR]

Background: Caregivers of persons with cognitive decline (PWCD) are at increased risk of poor sleep quantity and quality. It is unclear whether this is due to factors in the caregiver versus in the PWCD. Methods: This secondary data analysis using Aging, Demographics, and Memory Study data from the Health Retirement Study examined factors contributing to reduced sleep/rest among spouses and caregivers of older adults with varying levels of cognitive decline (cognitively normal (CN), cognitive impairment but not dementia (CIND), or dementia). Results: In our preliminary analysis, among N = 218 spouses (not necessarily caregivers) (mean age (SD) = 73.77 (7.30); 70.64% female) of older adults with varying levels of cognitive decline, regression revealed that frequency of sleep complaints was lowest among spouses with CN partners, second highest with CIND partners, and highest with dementia‐partners, X2 = 26.810, P = 0.002. Primary aim: among n = 136 caregivers of PWCD (mean age (SD) = 59.27 (13.97); 74.26% female; 22.79% spouses), we analyzed whether caregiver reduced sleep/rest was predicted by PWCD factors (i.e., frequent nighttime waking, dementia severity) and/or caregiver factors (i.e., depression symptoms, caregiver role overload). Regression revealed that caregiver depression symptoms (d = 0.62) and role overload (d = 0.88), but not PWCD factors, were associated with reduced caregiver sleep/rest after adjusting for demographic factors, caregiving frequency, and shared‐dwelling status (overall model: X2 = 31.876, P = 0.002). Exploratory analyses revealed that a caregiver was 7.901 times more likely (95% CI: 0.99–63.15) to endorse experiencing reduced sleep/rest if back‐up care was not available (P = 0.023). Conclusion: Findings highlight that the frequency of reported sleep problems among spouses increases in a stepwise fashion when partners have dementia versus CIND versus CN. The results also emphasise that caregiver mental health and burden are strongly associated with caregiver sleep disturbances and thus may be targets of intervention for caregiver sleep problems. [ABSTRACT FROM AUTHOR]

Background: Recently, the Ultra‐Brief Confusion Assessment Method (UB‐CAM), designed to help physicians and nurses to recognize delirium, showed high, but imperfect, accuracy compared with Research Reference Standard Delirium Assessments (RRSDAs). The aim of this study is to identify factors associated with disagreement between clinicians' app‐based UB‐CAM assessments and RRSDAs. Methods: This is a secondary analysis of a prospective diagnostic test study. The study was conducted at two hospitals and included 527 inpatients (≥70 years old) and 289 clinicians (53 physicians, 236 nurses). Trained research associates performed RRSDAs and determined delirium presence using the CAM. Clinicians administered the UB‐CAM using an iPad app. Disagreement factors considered were clinician, patient, and delirium characteristics. We report odds ratios and 95% confidence intervals. Results: One thousand seven hundred and ninety‐five clinician UB‐CAM assessments paired with RRSDAs were administered. The prevalence of delirium was 17%. The rate of disagreement between clinician UB‐CAM assessments and RRSDAs was 12%. Significant factors associated with disagreement between clinician UB‐CAM assessments and RRSDAs (OR [95% CI]) included: presence of dementia (2.7 [1.8–4.1]), patient education high school or less (1.9 [1.3–2.9]), psychomotor retardation (2.5 [1.4–4.2]), and the presence of mild delirium or subsyndromal delirium (5.5 [3.5–8.7]). Significant risk factors for false negatives were patient age less than 80 (2.2 [1.1–4.3]) and mild delirium (3.5 [1.6–7.4]). Significant risk factors for false positives were presence of dementia (4.0 [2.3–7.0]), subsyndromal delirium (5.1 [2.9–9.1]), and patient education high school or less (2.0 [1.2–3.6]). Clinician characteristics were not significantly associated with disagreement. Conclusions: The strongest factors associated with disagreement between clinician UB‐CAM screens and RRSDAs were the presence of dementia and subsyndromal delirium as risk factors for false positives, and mild delirium and younger age as a risk factor for false negatives. These disagreement factors contrast with previous studies of risk factors for incorrect clinician delirium screening, and better align screening results with patient outcomes. [ABSTRACT FROM AUTHOR]

Workplace violence in ambulatory care is less controlled than in inpatient settings due to a variety of factors, including location, patient population, volume of visits, hours of operation, physical environment, and availability of resources. Personal knowledge, skills, and ability, as well as data and organizational resources, are needed to mitigate events. Continued research, publication of evidence-based practice, and advocacy for laws protecting health care workers in ambulatory care are necessary. The development of workplace violence risk assessments, violence screening questions, and national nursing quality indicators are needed to help move the prevention needle in ambulatory care settings. [ABSTRACT FROM AUTHOR]

To identify the prevalence of anxiety symptoms using a variety of instruments in an Australian memory clinic sample. This is an exploratory cross-sectional study using a purposive consecutive series sample of 163 individuals and their carers who attended a Brisbane, Australia, memory clinic in 2012–2015. Descriptive statistics and correlation analyses were performed to explore different approaches to measuring anxiety in the sample, using clinician-rated, self-report and carer-report measures. The mean age of participants was 78 years, nearly 53% were females. Over 70% of participants with mild cognitive impairment (MCI) and dementia (n = 163) experienced mild to moderate anxiety per a clinician-rated measure (HAM-A), which moderately correlated with carer-report anxiety (IQAD; rs =.59, p <.001). Only weak correlations of these measures with self-report anxiety (GAI) were detected. Mild to moderate anxiety symptoms were frequent in memory clinic attendees diagnosed with MCI or dementia using the HAM-A, suggesting experiences of subclinical anxiety symptoms. Self- as well as carer-report screening tools should be used in memory clinics in addition to routinely administered neuropsychiatric assessments to support early identification of anxiety symptoms and mapping of available post-diagnostic care pathways for people diagnosed with cognitive impairment. [ABSTRACT FROM AUTHOR]