Chinese hospital staff in anxiety and depression: Not only comfort patients but also should be comforted - A nationwide cross-sectional study.

BACKGROUND: Healthcare professionals are in short supply worldwide, especially in China, which can result in increased stress in the work environment and allostatic load for Chinese hospital staff. This study aimed to investigate the prevalence of anxiety and depressive symptoms and their relationship with total stress, allostatic overload, sleep quality, and episodic memory among Chinese hospital staff. METHOD: In this cross-sectional study, self-assessments including Generalized Anxiety Disorder 7-item (GAD-7), Patient Health Questionnaire-9 (PHQ-9), PsychoSocial Index (PSI), Pittsburgh Sleeping Quality Index (PSQI), and MemTrax test were used to evaluate participants' anxiety symptoms, depressive symptoms, total stress, allostatic load/overload, sleep quality, and episodic memory. RESULTS: A total of 9433 hospital staff from 304 cities participated. Anxiety prevalence was 21.0 % (95 % confidential interval (CI) 20.2 %, 21.8 %), while the prevalence of depressive symptoms was at 21.4 % (95 % CI 20.5 %, 22.2 %). 79.8 % (95 % CI 79.0 %, 80.6 %) of the hospital staff had allostatic overload. Poor sleep quality affected 50.4 % of participants, and 32.1 % experienced poor episodic memory. LIMITATIONS: This study utilized a convenience sampling approach, relying on an online survey as its data collection method. CONCLUSIONS: Hospital staff in China are facing a stressful environment with a high prevalence of anxiety and depressive symptoms, significant allostatic overload, poor sleep quality, and compromised episodic memory. It is imperative that local management and community structures enhance their support and care for these essential workers, enabling them to manage and withstand the stresses of their professional roles effectively.

Episodic memory assessment: effects of sex and age on performance and response time during a continuous recognition task.

Introduction: Continuous recognition tasks (CRTs) assess episodic memory (EM), the central functional disturbance in Alzheimer's disease and several related disorders. The online MemTrax computerized CRT provides a platform for screening and assessment that is engaging and can be repeated frequently. MemTrax presents complex visual stimuli, which require complex involvement of the lateral and medial temporal lobes and can be completed in less than 2 min. Results include number of correct recognitions (HITs), recognition failures (MISSes = 1-HITs), correct rejections (CRs), false alarms (FAs = 1-CRs), total correct (TC = HITs + CRs), and response times (RTs) for each HIT and FA. Prior analyses of MemTrax CRT data show no effects of sex but an effect of age on performance. The number of HITs corresponds to faster RT-HITs more closely than TC, and CRs do not relate to RT-HITs. RT-HITs show a typical skewed distribution, and cumulative RT-HITs fit a negative survival curve (RevEx). Thus, this study aimed to define precisely the effects of sex and age on HITS, CRs, RT-HITs, and the dynamics of RTs in an engaged population. Methods: MemTrax CRT online data on 18,255 individuals was analyzed for sex, age, and distributions of HITs, CRs, MISSes, FAs, TC, and relationships to both RT-HITs and RT-FAs. Results: HITs corresponded more closely to RT-HITs than did TC because CRs did not relate to RT-HITs. RT-FAs had a broader distribution than RT-HITs and were faster than RT-HITs in about half of the sample, slower in the other half. Performance metrics for men and women were the same. HITs declined with age as RT-HITs increased. CRs also decreased with age and RT-FAs increased, but with no correlation. The group over aged 50 years had RT-HITs distributions slower than under 50 years. For both age ranges, the RevEx model explained more than 99% of the variance in RT-HITs. Discussion: The dichotomy of HITs and CRs suggests opposing cognitive strategies: (1) less certainty about recognitions, in association with slower RT-HITs and lower HIT percentages suggests recognition difficulty, leading to more MISSes, and (2) decreased CRs (more FAs) but faster RTs to HITs and FAs, suggesting overly quick decisions leading to errors. MemTrax CRT performance provides an indication of EM (HITs and RT-HITs may relate to function of the temporal lobe), executive function (FAs may relate to function of the frontal lobe), processing speed (RTs), cognitive ability, and age-related changes. This CRT provides potential clinical screening utility for early Alzheimer's disease and other conditions affecting EM, other cognitive functions, and more accurate impairment assessment to track changes over time.

The MemTrax memory test for detecting and assessing cognitive impairment in Parkinson's disease.

INTRODUCTION: A valid, reliable, accessible measurement for the early detection of cognitive decline in patients with Parkinson's disease (PD) is in urgent demand. The objective of the study is to assess the clinical utility of the MemTrax Memory Test in detecting cognitive impairment in patients with PD. METHODS: The MemTrax, a fast on-line cognitive screening tool based on continuous recognition task, and Montreal Cognitive Assessment (MoCA) were administered to 61 healthy controls (HC), 102 PD patients with normal cognition (PD-N), 74 PD patients with mild cognitive impairment (PD-MCI) and 52 PD patients with dementia (PD-D). The total percent correct (MTx- %C), average response time (MTx-RT), composite score (MTx-Cp) of MemTrax and the MoCA scores were comparatively analyzed. RESULTS: The MoCA scores were similar between HC and PD-N, however, MTx- %C and MTx-Cp were lower in PD-N than HC(p < 0.05). MTx- %C, MTx-Cp and the MoCA scores were significantly lower in PD-MCI versus PD-N and in PD-D versus PD-MCI (p ≤ 0.001), while MTx-RT was statistically longer in PD-D versus PD-MCI (p ≤ 0.001). For PD groups, the MemTrax performance correlated with the MoCA scores. To detect PD-MCI, the optimal MTx- %C and MTx-Cp cutoff were 75 % and 50.0, respectively. To detect PD-D, the optimal MTx- %C, MTx-RT and MTx-Cp cutoff were 69 %, 1.341s and 40.6, respectively. CONCLUSION: The MemTrax provides rapid, valid and reliable metrics for assessing cognition in PD patients which could be useful for identifying PD-MCI at early stage and monitoring cognitive function decline during the progression of disease.

Early Diagnosis of Mild Cognitive Impairment due to Alzheimer's Disease Using a Composite of MemTrax and Blood Biomarkers.

BACKGROUND: Accessible measurements for the early detection of mild cognitive impairment (MCI) due to Alzheimer's disease (AD) are urgently needed to address the increasing prevalence of AD. OBJECTIVE: To determine the benefits of a composite MemTrax Memory Test and AD-related blood biomarker assessment for the early detection of MCI-AD in non-specialty clinics. METHODS: The MemTrax Memory Test and Montreal Cognitive Assessment were administered to 99 healthy seniors with normal cognitive function and 101 patients with MCI-AD; clinical manifestation and peripheral blood samples were collected. We evaluated correlations between the MemTrax Memory Test and blood biomarkers using Spearman's rank correlation analyses and then built discrimination models using various machine learning approaches that combined the MemTrax Memory Test and blood biomarker results. The models' performances were assessed according to the areas under the receiver operating characteristic curve. RESULTS: The MemTrax Memory Test and Montreal Cognitive Assessment areas under the curve for differentiating patients with MCI-AD from the healthy controls were similar. The MemTrax Memory Test strongly correlated with phosphorylated tau 181 and amyloid-ß42/40. The area under the curve for the best composite MemTrax Memory Test and blood biomarker model was 0.975 (95% confidence interval: 0.950-0.999). CONCLUSION: Combining MemTrax Memory Test and blood biomarker results is a promising new technique for the early detection of MCI-AD.

Correctness and response time distributions in the MemTrax continuous recognition task: Analysis of strategies and a reverse-exponential model.

A critical issue in addressing medical conditions is measurement. Memory measurement is difficult, especially episodic memory, which is disrupted by many conditions. On-line computer testing can precisely measure and assess several memory functions. This study analyzed memory performances from a large group of anonymous, on-line participants using a continuous recognition task (CRT) implemented at https://memtrax.com. These analyses estimated ranges of acceptable performance and average response time (RT). For 344,165 presumed unique individuals completing the CRT a total of 602,272 times, data were stored on a server, including each correct response (HIT), Correct Rejection, and RT to the thousandth of a second. Responses were analyzed, distributions and relationships of these parameters were ascertained, and mean RTs were determined for each participant across the population. From 322,996 valid first tests, analysis of correctness showed that 63% of these tests achieved at least 45 correct (90%), 92% scored at or above 40 correct (80%), and 3% scored 35 correct (70%) or less. The distribution of RTs was skewed with 1% faster than 0.62 s, a median at 0.890 s, and 1% slower than 1.57 s. The RT distribution was best explained by a novel model, the reverse-exponential (RevEx) function. Increased RT speed was most closely associated with increased HIT accuracy. The MemTrax on-line memory test readily provides valid and reliable metrics for assessing individual episodic memory function that could have practical clinical utility for precise assessment of memory dysfunction in many conditions, including improvement or deterioration over time.

Episodic-Memory Performance in Machine Learning Modeling for Predicting Cognitive Health Status Classification.

BACKGROUND: Memory dysfunction is characteristic of aging and often attributed to Alzheimer's disease (AD). An easily administered tool for preliminary assessment of memory function and early AD detection would be integral in improving patient management. OBJECTIVE: Our primary aim was to utilize machine learning in determining initial viable models to serve as complementary instruments in demonstrating efficacy of the MemTrax online Continuous Recognition Tasks (M-CRT) test for episodic-memory screening and assessing cognitive impairment. METHODS: We used an existing dataset subset (n = 18,395) of demographic information, general health screening questions (addressing memory, sleep quality, medications, and medical conditions affecting thinking), and test results from a convenience sample of adults who took the M-CRT test. M-CRT performance and participant features were used as independent attributes: true positive/negative, percent responses/correct, response time, age, sex, and recent alcohol consumption. For predictive modeling, we used demographic information and test scores to predict binary classification of the health-related questions (yes/no) and general health status (healthy/unhealthy), based on the screening questions. RESULTS: ANOVA revealed significant differences among HealthQScore groups for response time true positive (p = 0.000) and true positive (p = 0.020), but none for true negative (p = 0.0551). Both % responses and % correct had significant differences (p = 0.026 and p = 0.037, respectively). Logistic regression was generally the top-performing learner with moderately robust prediction performance (AUC) for HealthQScore (0.648-0.680) and selected general health questions (0.713-0.769). CONCLUSION: Our novel application of supervised machine learning and predictive modeling helps to demonstrate and validate cross-sectional utility of MemTrax in assessing early-stage cognitive impairment and general screening for AD.

A Computerized Continuous-Recognition Task for Measurement of Episodic Memory.

Based on clinical observations of severe episodic memory (EM) impairment in dementia of Alzheimer's disease (AD), a brief, computerized EM test was developed for AD patient evaluation. A continuous recognition task (CRT) was chosen because of its extensive use in EM research. Initial experience with this computerized CRT (CCRT) showed patients were very engaged in the test, but AD patients had marked failure in recognizing repeated images. Subsequently, the test was administered to audiences, and then a two-minute online version was implemented (http://www.memtrax.com). The online CCRT shows 50 images, 25 unique and 25 repeats, which subjects respectively either try to remember or indicate recognition as quickly as possible. The pictures contain 5 sets of 5 images of scenes or objects (e.g., mountains, clothing, vehicles, etc.). A French company (HAPPYneuron, SAS) provided the test for 2 years, with these results. Of 18,477 individuals, who indicated sex and age 21-99 years and took the test for the first time, 18,007 individuals performed better than chance. In this group, age explained 1.5% of the variance in incorrect responses and 3.5% of recognition time variance, indicating considerable population variability. However, when averaging for specific year of age, age explained 58% of percent incorrect variance and 78% of recognition time variance, showing substantial population variability but a major age effect. There were no apparent sex effects. Further studies are indicated to determine the value of this CCRT as an AD screening test and validity as a measure of EM impairment in other clinical conditions.