Severe mental illness (SMI), which includes schizophrenia, schizoaffective disorder and bipolar disorder, has profound health impacts, even in the elderly.

To evaluate relative risk of hospital admission and length of hospital stay for physical illness in elders with SMI.

To construct a population-based retrospective cohort observed from April 2007 to March 2016, data from a case registry with full but de-identified electronic health records were retrieved for patients of the South London and Maudsley NHS Foundation Trust, the single secondary mental healthcare service provider in south-east London. We compared participants with SMI aged >60 years old with the general population of the same age and residing in the same areas through data linkage by age-, sex- and fiscal-year-standardised admission ratios (SARs) for primary diagnoses at hospital discharge. Furthermore, we compared the duration of hospital stay with an age-, sex- and cause-of-admission-matched random group by linear regression for major causes of admission.

In total, records for 4175 older people with SMI were obtained, relating to 10 342 admission episodes, showing an overall SAR for all physical illnesses of 5.15 (95% CI: 5.05, 5.25). Among the top causes of admission, SARs ranged from 3.87 for circulatory system disorders (ICD-10 codes: I00–I99) to 6.99 for genitourinary system or urinary conditions (N00–N39). Specifically, the diagnostic group of ‘symptoms, signs and findings, not elsewhere classified’ (R00–R99) had an elevated SAR of 6.56 (95% CI: 6.22, 6.90). Elders with SMI also had significantly longer hospital stays than their counterparts in the general population, especially for digestive system illnesses (K00–K93), after adjusting for confounding.

Poorer overall physical health and specific patterns were identified in elders with SMI.

The acceptability of an electronic HH monitoring system (EHHMS) was evaluated among hospital staff members.

An electronic HH monitoring system was implemented in June 2020 at a large, academic medical center. An interdisciplinary team developed a cross-sectional survey to gather staff perceptions of the EHHMS.

The survey was conducted at a public, tertiary acute care hospital.

The survey included current employees and staff. 1,273 participants responded. The mean age was 44.9 years (SD = 13.5). Most of the samples were female (71%) and non-Hispanic white (83%).

A survey was conducted between June and July 2021. Responses were analyzed using Stata statistical software. Multiple logistic regression models were constructed to examine factors associated with negative perceptions of the EHHMS and its radiofrequency identification (RFID) badge. Supporting qualitative analyses were performed using Atlas.ti version 9.

Three-quarters (75%) of respondents reported neutral to negative perceptions of the EHHMS and its associated badge. Respondents reported limited influence on HH practices. Age, campus location, length of employment, job role, and opinion on data sharing were associated with negative perceptions of the EHHMS and RFID badge. Position in a direct patient care role was associated with negative perceptions of the RFID badge.

Perceptions of the EHHMS aligned with previous research. Identified associations provide opportunities for targeted education, outreach, and intervention to increase acceptability and uptake. Lack of acceptance is explained by poorly perceived ease of use and usefulness, as well as challenges in implementation.

Social connection is associated with better health, including reduced risk of dementia. Personality traits are also linked to cognitive outcomes; neuroticism is associated with increased risk of dementia. Personality traits and social connection are also associated with each other. Taken together, evidence suggests the potential impacts of neuroticism and social connection on cognitive outcomes may be linked. However, very few studies have simultaneously examined the relationships between personality, social connection and health.

We tested the association between neuroticism and cognitive measures while exploring the potential mediating roles of aspects of social connection (loneliness and social isolation).

We conducted a cross-sectional study with a secondary analysis of the Canadian Longitudinal Study on Aging (CLSA) Comprehensive Cohort, a sample of Canadians aged 45 to 85 years at baseline. We used only self-reported data collected at the first follow-up, between 2015 and 2018 (n= 27,765). We used structural equation modelling to assess the association between neuroticism (exposure) and six cognitive measures (Rey Auditory Verbal Learning Test immediate recall and delayed recall, Animal Fluency Test, Mental Alternation Test, Controlled Oral Word Association Test and Stroop Test interference ratio), with direct and indirect effects (through social isolation and loneliness). We included age, education and hearing in the models and stratified all analyses by sex, females (n= 14,133) and males (n=13,632).

We found positive, statistically significant associations between neuroticism and social isolation (p<0.05) and loneliness (p<0.05), for both males and females. We also found inverse, statistically significant associations between neuroticism and all cognitive measures (p<0.05), except the Stroop Test interference ratio. In these models, there was consistent evidence of indirect effects (through social isolation and loneliness) and, in some cases, evidence of direct effects. We found sex differences in the model results.

Our findings suggest that the association between neuroticism and cognitive outcomes may be mediated by aspects of social connection and differ by sex. Understanding if and how modifiable risk factors mediate the association between personality and cognitive outcomes would help develop and target intervention strategies that improve social connection and brain health.

Understanding the factors contributing to optimal cognitive function throughout the aging process is essential to better understand successful cognitive aging. Processing speed is an age sensitive cognitive domain that usually declines early in the aging process; however, this cognitive skill is essential for other cognitive tasks and everyday functioning. Evaluating brain network interactions in cognitively healthy older adults can help us understand how brain characteristics variations affect cognitive functioning. Functional connections among groups of brain areas give insight into the brain’s organization, and the cognitive effects of aging may relate to this large-scale organization. To follow-up on our prior work, we sought to replicate our findings regarding network segregation’s relationship with processing speed. In order to address possible influences of node location or network membership we replicated the analysis across 4 different node sets.

Data were acquired as part of a multi-center study of 85+ cognitively normal individuals, the McKnight Brain Aging Registry (MBAR). For this analysis, we included 146 community-dwelling, cognitively unimpaired older adults, ages 85-99, who had undergone structural and BOLD resting state MRI scans and a battery of neuropsychological tests. Exploratory factor analysis identified the processing speed factor of interest. We preprocessed BOLD scans using fmriprep, Ciftify, and XCPEngine algorithms. We used 4 different sets of connectivity-based parcellation: 1)MBAR data used to define nodes and Power (2011) atlas used to determine node network membership, 2) Younger adults data used to define nodes (Chan 2014) and Power (2011) atlas used to determine node network membership, 3) Older adults data from a different study (Han 2018) used to define nodes and Power (2011) atlas used to determine node network membership, and 4) MBAR data used to define nodes and MBAR data based community detection used to determine node network membership.

Segregation (balance of within-network and between-network connections) was measured within the association system and three wellcharacterized networks: Default Mode Network (DMN), Cingulo-Opercular Network (CON), and Fronto-Parietal Network (FPN). Correlation between processing speed and association system and networks was performed for all 4 node sets.

We replicated prior work and found the segregation of both the cortical association system, the segregation of FPN and DMN had a consistent relationship with processing speed across all node sets (association system range of correlations: r=.294 to .342, FPN: r=.254 to .272, DMN: r=.263 to .273). Additionally, compared to parcellations created with older adults, the parcellation created based on younger individuals showed attenuated and less robust findings as those with older adults (association system r=.263, FPN r=.255, DMN r=.263).

This study shows that network segregation of the oldest-old brain is closely linked with processing speed and this relationship is replicable across different node sets created with varied datasets. This work adds to the growing body of knowledge about age-related dedifferentiation by demonstrating replicability and consistency of the finding that as essential cognitive skill, processing speed, is associated with differentiated functional networks even in very old individuals experiencing successful cognitive aging.