A Subtype Perspective on Cognitive Trajectories in Healthy Aging.

Cognitive aging is a complex and dynamic process characterized by changes due to genetics and environmental factors, including lifestyle choices and environmental exposure, which contribute to the heterogeneity observed in cognitive outcomes. This heterogeneity is particularly pronounced among older adults, with some individuals maintaining stable cognitive function while others experience complex, non-linear changes, making it difficult to identify meaningful decline accurately. Current research methods range from population-level modeling to individual-specific assessments. In this work, we review these methodologies and propose that population subtyping should be considered as a viable alternative. This approach relies on early individual-specific detection methods that can lead to an improved understanding of changes in individual cognitive trajectories. The improved understanding of cognitive trajectories through population subtyping can lead to the identification of meaningful changes and the determination of timely, effective interventions. This approach can aid in informing policy decisions and in developing targeted interventions that promote cognitive health, ultimately contributing to a more personalized understanding of the aging process within society and reducing the burden on healthcare systems.

Examining the Feasibility, Acceptability, and Effectiveness of Remote Training on Community-Based Participatory Research: Single-Arm Pre-Post Pilot Study.

BACKGROUND: Over the past decade, a growing body of scientific evidence has demonstrated that community engagement in research leads to more relevant research, enhances the uptake of research findings, and improves clinical outcomes. Despite the increasing need for the integration of community engagement methodologies into the scientific inquiry, doctoral and master's level competencies in the field of psychiatry often lack dedicated training or coursework on community engagement methodologies. OBJECTIVE: A total of 13 service users, peer support specialists, caregivers of people with mental health challenges, and scientists (with specialties ranging from basic science to implementation science) aged 18 and older participated in remote training on community-based participatory research. Data were collected at baseline, 2 days, and 3 months. METHODS: A total of 13 service users, peer support specialists, caregivers of people with mental health challenges, and scientists (with specialties ranging from basic science to implementation science) aged 18 and older participated in remote training on community-based participatory research. Data were collected at baseline, 2 days, and 3 months. RESULTS: The pilot study demonstrated that a 3-month remote training on community-based participatory research ("Partnership Academy") was deemed feasible and acceptable by service users, peer support specialists, caregivers of people with mental health challenges, and scientists. Improvements were found in research engagement and the quality of partnership. A marked increase in distrust in the medical system was also found. Groups submitted 4 grant applications and published 1 peer-reviewed journal at a 3-month follow-up. CONCLUSIONS: This pre- and postpilot study demonstrated it is possible to train groups of service users, peer support specialists, caregivers of people with mental health challenges, and scientists in community-based participatory research. These findings provide preliminary evidence that a 3-month remote training on community-based participatory research ("Partnership Academy") is feasible, acceptable, and potentially associated with improvements in research engagement as well as the quality of partnership and output, such as manuscripts and grant applications.

Social Isolation, Physical Activity, and Subsequent Changes in Cognition Among Middle- and Older-Aged Adults: Results From the Canadian Longitudinal Study on Aging.

OBJECTIVE: The objectives of this study were to a) evaluate associations between social isolation and change in cognition over a 3-year period, and b) evaluate whether physical activity mediates the association between social isolation and cognition change. METHODS: Using baseline and follow-up 1 data from the Canadian Longitudinal Study on Aging, latent change score models, incorporating direct and indirect pathways, were constructed to estimate the indirect effect of social isolation on cognitive change through physical activity. Multigroup models were constructed based on age group (45-65 versus 65+ years) and sex to allow for varying estimates across age and sex. The final analytic sample included 51,338 participants. RESULTS: Indirect effects of social isolation on cognition through physical activity were evident in men and women 65+ years old for memory change ( = -0.005 [99.9% confidence interval = -0.007 to -0.002], p < .001 in both groups) and in male adults 65+ years old for executive function change ( = -0.01 [99.9% confidence interval = -0.02 to -0.006], p < .001). Statistically significant indirect effects were not observed for adults between 45 and 65 years old. CONCLUSIONS: Social isolation is associated with diminished physical activity, and in turn, diminished physical activity is associated with decline in memory in older women and men, with larger declines in executive function in older men. Public health initiatives to promote physical activity-perhaps incorporating social interaction-among older adults experiencing social isolation could be one way to mitigate the negative impact of social isolation on cognitive health.

Comparison of devices used to measure blood pressure, grip strength and lung function: A randomised cross-over study.

BACKGROUND: Blood pressure, grip strength and lung function are frequently assessed in longitudinal population studies, but the measurement devices used differ between studies and within studies over time. We aimed to compare measurements ascertained from different commonly used devices. METHODS: We used a randomised cross-over study. Participants were 118 men and women aged 45-74 years whose blood pressure, grip strength and lung function were assessed using two sphygmomanometers (Omron 705-CP and Omron HEM-907), four handheld dynamometers (Jamar Hydraulic, Jamar Plus+ Digital, Nottingham Electronic and Smedley) and two spirometers (Micro Medical Plus turbine and ndd Easy on-PC ultrasonic flow-sensor) with multiple measurements taken on each device. Mean differences between pairs of devices were estimated along with limits of agreement from Bland-Altman plots. Sensitivity analyses were carried out using alternative exclusion criteria and summary measures, and using multilevel models to estimate mean differences. RESULTS: The mean difference between sphygmomanometers was 3.9mmHg for systolic blood pressure (95% Confidence Interval (CI):2.5,5.2) and 1.4mmHg for diastolic blood pressure (95% CI:0.3,2.4), with the Omron HEM-907 measuring higher. For maximum grip strength, the mean difference when either one of the electronic dynamometers was compared with either the hydraulic or spring-gauge device was 4-5kg, with the electronic devices measuring higher. The differences were small when comparing the two electronic devices (difference = 0.3kg, 95% CI:-0.9,1.4), and when comparing the hydraulic and spring-gauge devices (difference = 0.2kg, 95% CI:-0.8,1.3). In all cases limits of agreement were wide. The mean difference in FEV1 between spirometers was close to zero (95% CI:-0.03,0.03), limits of agreement were reasonably narrow, but a difference of 0.47l was observed for FVC (95% CI:0.53,0.42), with the ndd Easy on-PC measuring higher. CONCLUSION: Our study highlights potentially important differences in measurement of key functions when different devices are used. These differences need to be considered when interpreting results from modelling intra-individual changes in function and when carrying out cross-study comparisons, and sensitivity analyses using correction factors may be helpful.

Worsened Ability to Engage in Social and Physical Activity During the COVID-19 Pandemic and Older Adults' Mental Health: Longitudinal Analysis From the Canadian Longitudinal Study on Aging.

Background and Objectives: Restrictions implemented to mitigate the transmission of coronavirus disease 2019 (COVID-19) affected older adults' ability to engage in social and physical activities. We examined mental health outcomes of older adults reporting worsened ability to be socially and physically active during the pandemic. Research Design and Methods: Using logistic regression, we examined the relationship between positive screen for depression (10-item Center for Epidemiological Studies-Depression Scale) or anxiety (7-item Generalized Anxiety Scale) at the end of 2020 and worsened ability to engage in social and physical activity during the first 6-9 months of the pandemic among older adults in Canada. Interactions between ability to participate in social and physical activity and social participation pre-COVID (2015-2018) and physical activity were also examined. We analyzed data collected before and during the COVID pandemic from the Canadian Longitudinal Study on Aging, a nationally representative longitudinal cohort: pre-pandemic (2015-2018), COVID-Baseline survey (April to May 2020), and COVID-Exit survey (September to December 2020). Results: Of the 24,108 participants who completed the COVID-Exit survey, 21.96% (n = 5,219) screened positively for depression and 5.04% (n = 1,132) for anxiety. Worsened ability to participate in social and physical activity was associated with depression (odds ratio [OR] = 1.85 [95% confidence interval {CI} 1.67-2.04]; OR = 2.46 [95% CI 2.25-2.69]), respectively, and anxiety (OR = 1.66 [95% CI 1.37-2.02] and OR = 1.96 [95% CI 1.68-2.30]). Fully adjusted interaction models identified a buffering effect of social participation and the ability to participate in physical activity on depression (χ2 [1] = 8.86, p = .003 for interaction term). Discussion and Implications: Older adults reporting worsened ability to participate in social and physical activities during the COVID-19 pandemic had poorer mental health outcomes than those whose ability remained the same or improved. These findings highlight the importance of fostering social and physical activity resources to mitigate the negative mental health impacts of future pandemics or other major life stressors that may affect the mental health of older adults.

Neuroimaging and machine learning for studying the pathways from mild cognitive impairment to alzheimer's disease: a systematic review.

BACKGROUND: This systematic review synthesizes the most recent neuroimaging procedures and machine learning approaches for the prediction of conversion from mild cognitive impairment to Alzheimer's disease dementia. METHODS: We systematically searched PubMed, SCOPUS, and Web of Science databases following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) systematic review guidelines. RESULTS: Our search returned 2572 articles, 56 of which met the criteria for inclusion in the final selection. The multimodality framework and deep learning techniques showed potential for predicting the conversion of MCI to AD dementia. CONCLUSION: Findings of this systematic review identified that the possibility of using neuroimaging data processed by advanced learning algorithms is promising for the prediction of AD progression. We also provided a detailed description of the challenges that researchers are faced along with future research directions. The protocol has been registered in the International Prospective Register of Systematic Reviews- CRD42019133402 and published in the Systematic Reviews journal.

Predictors of the rate of cognitive decline in older adults using machine learning.

BACKGROUND: The longitudinal rates of cognitive decline among aging populations are heterogeneous. Few studies have investigated the possibility of implementing prognostic models to predict cognitive changes with the combination of categorical and continuous data from multiple domains. OBJECTIVE: Implement a multivariate robust model to predict longitudinal cognitive changes over 12 years among older adults and to identify the most significant predictors of cognitive changes using machine learning techniques. METHOD: In total, data of 2733 participants aged 50-85 years from the English Longitudinal Study of Ageing are included. Two categories of cognitive changes were determined including minor cognitive decliners (2361 participants, 86.4%) and major cognitive decliners (372 participants, 13.6%) over 12 years from wave 2 (2004-2005) to wave 8 (2016-2017). Machine learning methods were used to implement the predictive models and to identify the predictors of cognitive decline using 43 baseline features from seven domains including sociodemographic, social engagement, health, physical functioning, psychological, health-related behaviors, and baseline cognitive tests. RESULTS: The model predicted future major cognitive decliners from those with the minor cognitive decline with a relatively high performance. The overall AUC, sensitivity, and specificity of prediction were 72.84%, 78.23%, and 67.41%, respectively. Furthermore, the top 7 ranked features with an important role in predicting major vs minor cognitive decliners included age, employment status, socioeconomic status, self-rated memory changes, immediate word recall, the feeling of loneliness, and vigorous physical activity. In contrast, the five least important baseline features consisted of smoking, instrumental activities of daily living, eye disease, life satisfaction, and cardiovascular disease. CONCLUSION: The present study indicated the possibility of identifying individuals at high risk of future major cognitive decline as well as potential risk/protective factors of cognitive decline among older adults. The findings could assist in improving the effective interventions to delay cognitive decline among aging populations.

Contributors to mental health resilience in middle-aged and older adults: an analysis of the Canadian Longitudinal Study on Aging.

OBJECTIVES: Identifying the correlates of mental health resilience (MHR)-defined as the discrepancy between one's reported current mental health and one's predicted mental health based on their physical performance-may lead to strategies to alleviate the burden of poor mental health in aging adults. Socioeconomic factors, such as income and education, may promote MHR via modifiable factors, such as physical activity and social networks. DESIGN: A cross-sectional study was conducted. Multivariable generalized additive models characterized the associations between socioeconomic and modifiable factors with MHR. SETTING: Data were taken from the population-based Canadian Longitudinal Study on Aging (CLSA), which collected data at various data collection sites across Canada. PARTICIPANTS: Approximately 31,000 women and men between the ages of 45 and 85 years from the comprehensive cohort of the CLSA. MEASUREMENTS: Depressive symptoms were assessed by the Center for Epidemiological Studies Depression Scale. Physical performance was measured objectively using a composite of grip strength, sit-to-stand, and balance performance. Socioeconomic and modifiable factors were measured by self-report questionnaires. RESULTS: Household income, and to a lesser extent, education were associated with greater MHR. Individuals reporting more physical activity and larger social networks had greater MHR. Physical activity accounted for 6% (95% CI: 4 to 11%) and social network accounted for 16% (95% CI: 11 to 23%) of the association between household income and MHR. CONCLUSIONS: The burden of poor mental health in aging adults may be alleviated through targeted interventions involving physical activity and social connectedness for individuals with lower socioeconomic resources.

Internet use and life satisfaction among Chinese older adults: the mediating effects of social interaction.

Internet use has been suggested to have a crucial effect on older adults' quality of life; however, few studies have investigated the underlying mechanisms in the relationship between internet use and life satisfaction among older adults. Employing multiple linear regression models and mediation analysis with 2019 Chinese Social Survey (CSS) data, this study analyzed the associations between the internet use and life satisfaction of Chinese older adults. Additionally, it explored the mediating role of social interaction, including online and offline social interactions. The results showed that internet use was positively associated with older adults' life satisfaction, and offline social interaction significantly mediated internet use. Our findings indicate that internet use could improve older adults' quality of life by promoting offline social interaction. Therefore, the government, communities, and families should create conditions for older adults to integrate into online society and participate in offline social interaction.

The Intersection of Business Innovation and Scientific Exploration to Address Early Mortality in People With Serious Mental Illness.

This Viewpoint describes how open innovation has been used by communities to support individual and community health and discusses how scientists and clinicians could apply this idea- and resource-sharing strategy to generate breakthrough advances that may extend the life span of people with serious mental illness (SMI).

Guidelines to Establish an Equitable Mobile Health Ecosystem.

Mobile health (mHealth)-that is, use of mobile devices, such as mobile phones, monitoring devices, personal digital assistants, and other wireless devices, in medical care-is a promising approach to the provision of support services. mHealth may aid in facilitating monitoring of mental health conditions, offering peer support, providing psychoeducation (i.e., information about mental health conditions), and delivering evidence-based practices. However, some groups may fail to benefit from mHealth despite a high need for mental health services, including people from racially and ethnically disadvantaged groups, rural residents, individuals who are socioeconomically disadvantaged, and people with disabilities. A well-designed mHealth ecosystem that considers multiple elements of design, development, and implementation can afford disadvantaged populations the opportunity to address inequities and facilitate access to and uptake of mHealth. This article proposes inclusion of the following principles and standards in the development of an mHealth ecosystem of equity: use a human-centered design, reduce bias in machine-learning analytical techniques, promote inclusivity via mHealth design features, facilitate informed decision making in technology selection, embrace adaptive technology, promote digital literacy through mHealth by teaching patients how to use the technology, and facilitate access to mHealth to improve health outcomes.

Multimorbidity, COVID-19 and Mental Health: Canadian Longitudinal Study on Aging (CLSA) Longitudinal Analyses.

OBJECTIVES: This paper examines the longitudinal effects of the COVID-19 pandemic on older adults (65+) with multimorbidity on levels of depression, anxiety, and perceived global impact on their lives. METHODS: Baseline (2011-2015) and Follow-up 1 (2015-2018) data from the Canadian Longitudinal Study on Aging (CLSA), and the Baseline and Exit waves of the CLSA COVID-19 study (April-December, 2020) (n = 18,099). Multimorbidity was measured using: a) an additive scale of chronic conditions; and b) six chronic disease clusters. Linear Mixed Models were employed to test hypotheses. RESULTS: Number of chronic conditions pre-pandemic was associated with pandemic levels of depression (estimate = 0.40, 95% CI: [0.37,0.44]); anxiety (estimate = 0.20, 95% CI: [0.18, 0.23]); and perceived negative impact of the pandemic (OR = 1.04, 95% CI: [1.02, 1.06]). The associations between multimorbidity and anxiety decreased during the period of the COVID-19 surveys (estimate = -0.02, 95% CI: [-0.05, -0.01]); whereas the multimorbidity association with perceived impact increased (OR = 1.03, 95% CI: [1.01, 1.05]). CONCLUSIONS: This study demonstrates that pre-pandemic multimorbidity conditions are associated with worsening mental health. CLINICAL IMPLICATIONS: Clinicians treating mental health of older adults need to consider the joint effects of multimorbidity conditions and pandemic experiences to tailor counseling and other treatment protocols.

Exercise interventions for stress reduction in older adult populations: a systematic review of randomized controlled trials.

Background and Objectives: To assess which forms of supervised exercise are effective in reducing psychological stress in older adults. Research Design: Systematic Review. Methods: Four electronic databases (PubMed, Web of Science, PsycInfo, and SportDiscus) were searched in February of 2021. Randomised controlled trials (RCTs) investigating supervised exercise interventions for psychological stress reduction in adults aged 50 + were included in this review. Data on type, intensity, and duration of the intervention were also extracted. Results: 854 studies were identified by the search strategy. Twelve RCTs met inclusion criteria. Trials involving low-intensity qigong and trials combining aerobic and anaerobic or aerobic and nutrition/diet education demonstrated the strongest evidence for stress reduction. Discussion and Implications: Exercise may reduce stress in older adults. Suitable duration of programme ranges from 3 months to 1 year. Light to moderate activity is recommended for best results, with qigong being the most consistent and common exercise.

An analysis of dynamic, bidirectional associations between memory and verbal fluency with depressive symptoms in middle- and older-aged adults: A cohort study.

OBJECTIVES: This study compared two approaches to analyzing bidirectional associations between aspects of cognition-specifically, verbal memory and fluency-and depression using multi-wave longitudinal data. The cross-lagged panel model (CLPM) does not distinguish between- versus within-person variation, whereas the random-intercepts CLPM (RI-CLPM) partitions variation into a stable, trait-like component that varies across individuals and a wave-specific deviation that varies within individuals. METHODS: Observational study of 47,719 adults ages 45 to 95 from the Survey of Health, Ageing, and Retirement in Europe (mean age = 63 years, SD = 9 years at first assessment; 57 % female). Participants completed at least four of 8 biennial waves of data collection from 2004 and 2020. Depressive symptoms were assessed by the EURO-D. Cognition was assessed by animal fluency, and immediate and delayed word recall. Multi-group CLPMs and RI-CLPMs were fit on middle-aged (45-65 year) and older (65+ years) males and females. RESULTS: The estimates from the CLPMs indicated bidirectionality in the associations between cognition and depression, whereas the RI-CLPMs provided clearer evidence that changes in depression may produce subsequent changes in cognition, rather than vice versa. Prospective associations were small and consistent across age, sex and cognitive measure. LIMITATIONS: Measures of executive function-a domain of cognition affected by aging and related to mood-were not available. CONCLUSIONS: CLPMs and RI-CLPMs address conceptually distinct questions about how verbal memory and fluency may be dynamically related to depression, and therefore, produce different inferences from the same data about how these aspects of cognition and depression are related.

Digital interventions for depression and anxiety in older adults: a systematic review of randomised controlled trials.

One in five older adults experience symptoms of depression and anxiety. Digital mental health interventions are promising in their ability to provide researchers, mental health professionals, clinicians, and patients with personalised tools for assessing their behaviour and seeking consultation, treatment, and peer support. This systematic review looks at existing randomised controlled trial studies on digital mental health interventions for older adults. Four factors have been found that contributed to the success of digital mental health interventions: (1) ease of use; (2) opportunities for social interactions; (3) having human support; and (4) having the digital mental health interventions tailored to the participants' needs. The findings also resulted in methodological considerations for future randomised controlled trials on digital mental health interventions: (1) having a healthy control group and an intervention group with clinical diagnoses of mental illness; (2) collecting data on the support given throughout the duration of the interventions; (3) obtaining qualitative and quantitative data to measure the success of the interventions; and (4) conducting follow-up interviews and surveys up to 1 year post-intervention to determine the long-term outcomes. The factors that were identified in this systematic review can provide future digital mental health interventions researchers, health professionals, clinicians, and patients with the tools to design, develop, and use successful interventions for older users.

Multimorbidity resilience and COVID-19 pandemic self-reported impact and worry among older adults: a study based on the Canadian Longitudinal Study on Aging (CLSA).

BACKGROUND: The Coronavirus Disease-2019 (COVID-19) pandemic has created a spectrum of adversities that have affected older adults disproportionately. This paper examines older adults with multimorbidity using longitudinal data to ascertain why some of these vulnerable individuals coped with pandemic-induced risk and stressors better than others - termed multimorbidity resilience. We investigate pre-pandemic levels of functional, social and psychological forms of resilience among this sub-population of at-risk individuals on two outcomes - self-reported comprehensive pandemic impact and personal worry. METHODS: This study was conducted using Follow-up 1 data from the Canadian Longitudinal Study on Aging (CLSA), and the Baseline and Exit COVID-19 study, conducted between April and December in 2020. A final sub-group of 9211 older adults with two or more chronic health conditions were selected for analyses. Logistic regression and Generalized Linear Mixed Models were employed to test hypotheses between a multimorbidity resilience index and its three sub-indices measured using pre-pandemic Follow-up 1 data and the outcomes, including covariates. RESULTS: The multimorbidity resilience index was inversely associated with pandemic comprehensive impact at both COVID-19 Baseline wave (OR = 0.83, p < 0.001, 95% CI: [0.80,0.86]), and Exit wave (OR = 0.84, p < 0.001, 95% CI: [0.81,0.87]); and for personal worry at Exit (OR = 0.89, p < 0.001, 95% CI: [0.86,0.93]), in the final models with all covariates. The full index was also associated with comprehensive impact between the COVID waves (estimate = - 0.19, p < 0.001, 95% CI: [- 0.22, - 0.16]). Only the psychological resilience sub-index was inversely associated with comprehensive impact at both Baseline (OR = 0.89, p < 0.001, 95% CI: [0.87,0.91]) and Exit waves (OR = 0.89, p < 0.001, 95% CI: [0.87,0.91]), in the final model; and between these COVID waves (estimate = - 0.11, p < 0.001, 95% CI: [- 0.13, - 0.10]). The social resilience sub-index exhibited a weak positive association (OR = 1.04, p < 0.05, 95% CI: [1.01,1.07]) with personal worry, and the functional resilience measure was not associated with either outcome. CONCLUSIONS: The findings show that psychological resilience is most pronounced in protecting against pandemic comprehensive impact and personal worry. In addition, several covariates were also associated with the outcomes. The findings are discussed in terms of developing or retrofitting innovative approaches to proactive coping among multimorbid older adults during both pre-pandemic and peri-pandemic periods.

Help-Seeking Behaviors Among Older Adults: A Scoping Review.

Although older adults may experience health challenges requiring increased care, they often do not ask for help. This scoping review explores the factors associated with the help-seeking behaviors of older adults, and briefly discusses how minority ethnic populations can face additional challenges in help-seeking, due to factors such as language barriers and differing health beliefs. Guided by Arksey and O'Malley's scoping review framework and the Preferred Reporting Items for Systematic Reviews and Meta-AnalysesScoping Review guidelines, a systematic search of five databases was conducted. Using a qualitative meta-synthesis framework, emergent themes were identified. Data from 52 studies meeting inclusion criteria were organized into five themes: formal and informal supports, independence, symptom appraisal, accessibility and awareness, and language, alternative medicine and residency. Identifying how factors, including independence and symptom appraisal, relate to older adults' help-seeking behaviors may provide insights into how this population can be supported to seek help more effectively.

Overcoming Barriers for Older Adults to Maintain Virtual Community and Social Connections during the COVID-19 Pandemic.

OBJECTIVES: We describe the evaluation of remote training, an innovative use of technology to maintain older adults' virtual connection with their community and socialization, which were disrupted by the pandemic. Remote training was conducted via telephone using principles of cognitive rehabilitation and delivered by trained clinicians. METHODS: We thematically analyzed trainer reflection notes and interviews with older adult participants. RESULTS: The main facilitators were technology training with exposure, and the main barrier was fear of technology. CONCLUSIONS: We describe how telephone-based training grounded in principles of cognitive rehabilitation can be used to remotely train older adults to use new technology and to help them maintain their community-based connections and engage in socialization. CLINICAL IMPLICATIONS: Fear of technology during the pandemic can cause significant impairment in social functioning for older adults, at least when the only method for socialization is technology mediated such as during the COVID-19 pandemic. Empathically delivered remote training in an understanding manner can reduce fear and increase social and community connections in the era of physical distancing.