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\"In spite of improved access to psychosocial interventions, many people with psychosis continue to experience persistent problems which act as significant barriers to their recovery. This book investigates risk and problem behaviours in psychosis including staff and service factors that can impede the delivery of effective care. Working with Problematic Behaviour in Psychosis provides a new approach for assessment formulation and intervention with such problem behaviours in a team context. Of particular interest will be: an outline of the SAFE (Shared Assessment, Formulation and Education) approach an integrative model for understanding risk and problematic behaviour shared risk assessment and management processes the use of CBT in day-to-day interactions with clients a set of formulation driven strategies for managing problematic behaviours case studies and vignettes providing guidance and highlighting the benefits of the approach. This book will have particular appeal to professionals working in residential care for those with complex mental health problems as well as those working in intensive community based services. It is also an excellent resource for those training in psychological therapies for complex mental health problems, risk assessment and management\"--Provided by publisher.

Nonlinguistic cognitive impairment has become an important issue for aphasic patients, but currently there are few neuropsychological cognitive assessment tests for it. To get more information on cognitive impairment of aphasic patients, this study aimed to develop a new cognitive assessment test battery for aphasic patients, the Non-language-based Cognitive Assessment (NLCA), and evaluate its utility in Chinese-speaking patients with aphasia. The NLCA consists of five nonverbal tests, which could assess five nonlinguistic cognitive domains such as visuospatial functions, attention test, memory, reasoning, and executive functions of aphasic patients. All tests are modified from the nonverbal items of the current existed tests with some changes to the characteristics of Chinese culture. The NLCA was tested in 157 participants (including 57 aphasic patients, 50 mild cognitive impairment (MCI) patients, and 50 normal controls), and was compared with other well-established relative neuropsychological tests on the reliability, validity, and utility. The NLCA was fully applicable in the MCI patients and the normal controls, almost working in the aphasic patients (57/62 patients, 91.9%). The NLCA scores were 66.70 ± 6.30, 48.67 ± 15.04, and 77.58 ± 2.56 for the MCI group, the aphasic group, and the control group, respectively , and a significant difference was found among three groups (F = 118.446, P < 0.001). The Cronbach's alpha of the NLCA as an index of internal consistency was 0.805, and the test-retest and interrater reliability was adequate (r=0.977 and r= 0.970, respectively). The correlations of the cognitive subtests and their validation instruments were between 0.540 and 0.670 (all P < 0.05). Spearman's correlation analysis indicated that the coefficient of internal consistency of each subtest itself was higher than other subtests. When choosing the Montreal Cognitive Assessment score of <26 as the diagnostic criteria of cognitive impairment, the area under the curve for all participants in the control and MCI groups was 0.942 (95% confidence interval: 0.895-0.989), and an optimal cutoff point of 75.00 seemed to provide the best balance between sensitivity and specificity. Age (r = -0.406, P < 0.001) was the main influence factor for the NLCA. The NLCA could efficiently differentiate the cognitive impairment patients from the normal controls and is a reliable and valid cognitive assessment test battery to specially find nonlinguistic cognitive function for aphasic patients.

The rising prevalence of dementia necessitates a scalable solution to cognitive screening. Paper-based cognitive screening examinations are well-validated but minimally scalable. If a digital cognitive screening examination could replicate paper-based screening, it may improve scalability while potentially maintaining the performance of these well-validated paper-based tests. Here, we evaluate the Rapid Online Cognitive Assessment (RoCA), a remote and self-administered digital cognitive screening examination. The objective of this study was to validate the ability of RoCA to reliably evaluate patient input, identify patients with cognitive impairment relative to the established tests, and evaluate its potential as a screening tool. RoCA uses a convolutional neural network to evaluate a patient's ability to perform common cognitive screening tasks: wireframe diagram copying and clock drawing tests. To evaluate RoCA, we compared its evaluations with those of established paper-based tests. This open-label study consists of 46 patients (age range 33-82 years) who were enrolled from neurology clinics. Patients completed the RoCA screening examination and either Addenbrooke's Cognitive Examination-3 (ACE-3, n=35) or Montreal Cognitive Assessment (MoCA, n=11). We evaluated 3 primary metrics of RoCA's performance: (1) ability to correctly evaluate patient inputs, (2) ability to identify patients with cognitive impairment compared to ACE-3 and MoCA, and (3) performance as a screening tool. RoCA classifies patients similarly to gold standard paper-based tests, with a receiver operating characteristic area under the curve of 0.81 (95% CI 0.67-0.91; P<.001). RoCA achieved sensitivity of 0.94 (95% CI 0.80-1.0; P<.001). This was robust to multiple control analyses. Approximately 83% (16/19) of the patient respondents reported RoCA as highly intuitive, with 95% (18/19) perceiving it as adding value to their care. RoCA may act as a simple and highly scalable digital cognitive screening examination. However, due to the limitations of this study, further work is required to evaluate the ability of RoCA to be generalizable across patient populations, assess its performance in an entirely remote manner, and analyze the effect of digital literacy.

The Montreal Cognitive Assessment (MoCA) is a rapid screening battery, also including subtests to assess frontal functions such as set-shifting, abstraction and cognitive flexibility. MoCA seems to be useful to identify non-amnestic mild cognitive impairment (MCI) and subcortical dementia; it has high sensitivity and specificity in distinguishing MCI from mild Alzheimer’s Disease. Previous studies revealed that certain items of MoCA may be culturally biased and highlighted the need for population-based norms for the MoCA. The aim of present study was to collect normative values in a sample of Italian healthy subjects. Four hundred and fifteen Italian healthy subjects (252 women and 163 men) of different ages (age range 21–95 years) and educational level (from primary to university) underwent MoCA and Mini Mental State Examination (MMSE). Multiple linear regression analysis revealed that age and education significantly influenced performance on MoCA. No significant effect of gender was found. From the derived linear equation, a correction grid for MoCA raw scores was built. Inferential cut-off score, estimated using a non-parametric technique, is 15.5 and equivalent scores were computed. Correlation analysis showed a significant but weak correlation between MoCA adjusted scores with MMSE adjusted scores ( r  = 0.43, p  < 0.001). The present study provided normative data for the MoCA in an Italian population useful for both clinical and research purposes.

The US population over the age of 65 is expected to double by the year 2050. Concordantly, the incidence of dementia is projected to increase. The subclinical stage of dementia begins years before signs and symptoms appear. Early detection of cognitive impairment and/or cognitive decline may allow for interventions to slow its progression. Furthermore, early detection may allow for implementation of care plans that may affect the quality of life of those affected and their caregivers. We sought to determine the accuracy and validity of BrainCheck Memory as a diagnostic aid for age-related cognitive impairment, as compared against physician diagnosis and other commonly used neurocognitive screening tests, including the Saint Louis University Mental Status (SLUMS) exam, the Mini-Mental State Examination (MMSE), and the Montreal Cognitive Assessment (MoCA). We tested 583 volunteers over the age of 49 from various community centers and living facilities in Houston, Texas. The volunteers were divided into five cohorts: a normative population and four comparison groups for the SLUMS exam, the MMSE, the MoCA, and physician diagnosis. Each comparison group completed their respective assessment and BrainCheck Memory. A total of 398 subjects were included in the normative population. A total of 84 participants were in the SLUMS exam cohort, 51 in the MMSE cohort, 35 in the MoCA cohort, and 18 in the physician cohort. BrainCheck Memory assessments were significantly correlated to the SLUMS exam, with coefficients ranging from .5 to .7. Correlation coefficients for the MMSE and BrainCheck and the MoCA and BrainCheck were also significant. Of the 18 subjects evaluated by a physician, 9 (50%) were healthy, 6 (33%) were moderately impaired, and 3 (17%) were severely impaired. A significant difference was found between the severely and moderately impaired subjects and the healthy subjects (P=.02). We derived a BrainCheck Memory composite score that showed stronger correlations with the standard assessments as compared to the individual BrainCheck assessments. Receiver operating characteristic (ROC) curve analysis of this composite score found a sensitivity of 81% and a specificity of 94%. BrainCheck Memory provides a sensitive and specific metric for age-related cognitive impairment in older adults, with the advantages of a mobile, digital, and easy-to-use test. ClinicalTrials.gov NCT03608722; https://clinicaltrials.gov/ct2/show/NCT03608722 (Archived by WebCite at http://www.webcitation.org/76JLoYUGf).

The rising prevalence of mild cognitive impairment (MCI) and dementia, combined with persistent underdiagnosis, is driving an increased need for scalable cognitive assessment tools. Digital cognitive assessments (DCAs) offer a promising solution by addressing longstanding barriers to routine cognitive testing and diagnosis. However, variations in performance and intended use have created confusion about their clinical applications and utility. The Global CEO Initiative on Alzheimer's Disease convened a DCA Workgroup to define the preferred characteristics of DCAs to meet the needs of patients, health care providers, and regulators for three clinical contexts: (1) initial detection of cognitive impairment, (2) diagnostic support for MCI and dementia, and (3) characterization of cognitive profiles to support identifying etiology. In the near term, ensuring that DCAs meet or exceed the performance of non‐digital tools is a priority. DCAs must be validated in the intended use population with well‐characterized study samples and inclusive designs.

The aim of this study was to validate the reliability of the Chinese version of Addenbrooke's Cognitive Examination III (ACE-III) for detecting mild cognitive impairment. Furthermore, the present study compares the diagnostic accuracy of ACE-III with that of Montreal Cognitive Assessment (MoCA). One hundred and twenty patients with MCI and 136 healthy controls were included in the study. All patients were evaluated by the Chinese version of ACE-III, MoCA and MMSE. Subjects in the control group showed better performance in ACE-III total score and its subdomain scores than those in the MCI group. There was a significantly positive correlation between ACE-III total score and MoCA score. Meanwhile, there was also a significantly positive correlation between ACE-III total score and MMSE score. For ACE-III total score, a cut-off point of 85 yielded a sensitivity of 97.3% and a specificity of 90.7%. The AUC for ACE-III total score was 0.978. For MoCA, a cut-off point of 23 yielded a sensitivity of 86.5% and a specificity of 97.7%. The AUC for MoCA was 0.961. There were no significant differences in diagnostic accuracy between ACE-III and MoCA. The present findings support that both ACE-III and MoCA are useful for detecting MCI in early stages.

Sensitive and frequent digital remote memory assessments via mobile devices hold the promise to facilitate the detection of cognitive impairment and decline. However, in order to be successful at scale, cognitive tests need to be applicable in unsupervised settings and confounding factors need to be understood. This study explored the feasibility of completely unsupervised digital cognitive assessments using three novel memory tasks in a Citizen Science project across Germany. To that end, the study aimed to identify factors associated with stronger participant retention, to examine test-retest reliability and the extent of practice effects, as well as to investigate the influence of uncontrolled settings such as time of day, delay between sessions or screen size on memory performance. A total of 1,407 adults (aged 18–89) participated in the study for up to 12 weeks, completing weekly memory tasks in addition to short questionnaires regarding sleep duration, subjective cognitive complaints as well as cold symptoms. Participation across memory tasks was pseudorandomized such that individuals were assigned to one of three memory paradigms resulting in three otherwise identical sub-studies. One hundred thirty-eight participants contributed to two of the three paradigms. Critically, for each memory task 12 independent parallel test sets were used to minimize effects of repeated testing. First, we observed a mean participant retention time of 44 days, or 4 active test sessions, and 77.5% compliance to the study protocol in an unsupervised setting with no contact between participants and study personnel, payment or feedback. We identified subject-level factors that contributed to higher retention times. Second, we found minor practice effects associated with repeated cognitive testing, and reveal evidence for acceptable-to-good retest reliability of mobile testing. Third, we show that memory performance assessed through repeated digital assessments was strongly associated with age in all paradigms, and individuals with subjectively reported cognitive decline presented lower mnemonic discrimination accuracy compared to non-complaining participants. Finally, we identified design-related factors that need to be incorporated in future studies such as the time delay between test sessions. Our results demonstrate the feasibility of fully unsupervised digital remote memory assessments and identify critical factors to account for in future studies.

Hypoxic environments like those present at high altitudes may negatively affect brain function. Varying levels of hypoxia, whether acute or chronic, are previously shown to impair cognitive function in humans. Assessment and prevention of such cognitive impairment require detection of cognitive changes and impairment using specific cognitive function assessment tools. This paper summarizes the findings of previous research, outlines the methods for cognitive function assessment used at a high altitude, elaborates the need to develop standardized and systematic cognitive function assessment tools for high‐altitude hypoxia environments.

Background/Objectives: The growing incidence of cognitive impairment among older adults has a significant impact on individuals, family members, caregivers, and society. Current conventional cognitive assessment tools are faced with some limitations. Recent evidence suggests that automating cognitive assessment holds promise, potentially resulting in earlier diagnosis, timely intervention, improved patient outcomes, and higher chances of response to treatment. Despite the advantages of automated assessment and technological advancements, automated cognitive assessment has yet to gain widespread use, especially in low and lower middle-income countries. This review highlights the potential of automated cognitive assessment tools and presents an overview of existing tools. Methods: This review includes 87 studies carried out with non-neuroimaging data alongside their performance metrics. Results: The identified articles automated the cognitive assessment process and were grouped into five categories either based on the tools’ design or the data analysis approach. These categories include game-based, digital versions of conventional tools, original computerized tests and batteries, virtual reality/wearable sensors/smart home technologies, and artificial intelligence-based (AI-based) tools. These categories are further explained, and evaluation of their strengths and limitations is discussed to strengthen their adoption in clinical practice. Conclusions: The comparative metrics of both conventional and automated approaches of assessment suggest that the automated approach is a strong alternative to the conventional approach. Additionally, the results of the review show that the use of automated assessment tools is more prominent in countries ranked as high-income and upper middle-income countries. This trend merits further social and economic studies to understand the impact of this global reality.