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To explain the ethnic paradox of mental health in aging, we evaluated whether Black and Latinx older adults experience (1) fewer depressive symptoms (DepSx), but more physical problems, and (2) greater psychological resilience as a result of life stressors than White older adults.DepSx, physical health, and recent stress were obtained biennially from 25,893 older adults (77% White, 15% Black, 9% Latinx) in the U.S. Health and Retirement Study, across 16 years. Psychological resilience, lifetime stress, and discrimination experiences were available for 13,655 individuals. We conducted mixed-effects and linear regression analyses.For Blacks and Latinxs, experiencing more-than-usual stress events was associated with less increase in DepSx compared to Whites, although on average Blacks and Latinxs experience more DepSx. Black adults showed worse physical health than White adults and weaker effects of stress on psychological resilience despite experiencing more stress of all types. Findings were mixed for Latinxs.Studying effects of time-varying stress on changes in health and multiple stressors on psychological resilience by race/ethnicity elucidates mechanisms for later-age health disparities.Cross-sectional evaluations of stress and psychological health in a clinical setting may provide incomplete appraisals of health risks for Black and Latinx older Americans.

In the general population, the construct of race is associated with disparities in cognitive aging. There are notable racial group disparities and inequities among people living with schizophrenia (PLWSz). Despite the salience of the construct of race in schizophrenia, there remains a knowledge gap about racial disparities in cognitive impairment among older adults in this vulnerable population. Our study uses mediation analysis to examine racial disparities in cognitive impairment among older adults with schizophrenia.We assess global cognition in PLWSz over age 55 with the Measurement and Treatment Research to Improve Cognition in Schizophrenia cognitive test battery in our "all-comer" sample (There was a Black/non-Black group racial disparity in global cognitive score (-2.8, 95% CI: -4.4, -1.3) after adjusting for confounding and interaction. This disparity was significantly mediated by years of education.There are notable racial disparities in cognitive impairment among older adults with schizophrenia; however, differences in cognitive scores between racial groups are mediated by level of education.Social determinants of health, particularly educational attainment, are important risk factors for cognitive impairment in PLWSz and should be considered by clinicians. Early screening and assessment of cognitive symptoms is essential to addressing health disparities/inequalities among older adults living with schizophrenia.Controlled Direct EffectsHIV: Human Immunodeficiency VirusMATRICS: Measurement and Treatment Research to Improve Cognition in SchizophreniaMCCB: MATRICS Consensus Cognitive BatteryMTE: Marginal Total EffectsNDE: Natural Direct EffectsPANSS: Positive and Negative Symptom ScalePLWSz: People with schizophrenia.

Purpose Many studies report about risk factors associated with adverse changes in mental health during the COVID-19 pandemic while few studies report about protective and buffering factors, especially in older adults. We present an observational study to assess protective and buffering factors against COVID-19 related adverse mental health changes in older adults. Methods 899 older adults (55 +) in the Netherlands were followed from 2018/19 to two pandemic time points (June–October 2020 and March–August 2021). Questionnaires included exposure to pandemic-related adversities (“COVID-19 exposure”), depressive and anxiety symptoms, loneliness, and pre-pandemic functioning. Linear regression analyses estimated main effects of COVID-19 exposure and protective factors on mental health changes; interaction effects were tested to identify buffering factors. Results Compared to pre-pandemic, anxiety symptoms, depression symptoms and loneliness increased. A higher score on the COVID-19 adversity index was associated with stronger negative mental health changes. Main effects: internet use and high mastery decreased depressive symptoms; a larger network decreased anxiety symptoms; female gender, larger network size and praying decreased loneliness. COVID-19 vaccination buffered against COVID-19 exposure-induced anxiety and loneliness, a partner buffered against COVID-19 exposure induced loneliness. Conclusion Exposure to COVID-19 adversity had a cumulative negative impact on mental health. Improving coping, finding meaning, stimulating existing religious and spiritual resources, network interventions and stimulating internet use may enable older adults to maintain mental health during events with large societal impact, yet these factors appear protective regardless of exposure to specific adversities. COVID-19 vaccination had a positive effect on mental health.

Current definitions of sustainability and sustainable development are problematic. They reinforce the dominant capitalist paradigm of economic growth as a goal—a system which has contributed in no uncertain terms to the current state of the planet—and they exclude animals as moral entities. We propose that sustainability is primarily an ethical issue which connects people, the planet on which we live, and the animals and other organisms which inhabit it. Our definition of sustainability states that in all decisions and actions on any scale, from the individual to the institutional, we should minimise our immediate and future negative impact on humans, other animals, and the planet, while simultaneously maximising our positive impacts on these domains. We take an interdisciplinary approach in discussing trade-offs between these three broad interests, providing a rationale for adopting this more inclusive definition at every level of society. Our definition calls for a normative shift in discussions around sustainability, one of which is more inclusive of the animals and other organisms with which we share the planet. We believe that the paper forms a strong and coherent foundation for policy and communication about sustainability going forward.

Active exergaming for improving cognitive function is a relatively novel concept as it has certain unique features that could prove advantageous in improving patient outcomes, particularly in patients with neurological disabilities. Hence, we have conducted this review to obtain a comprehensive estimate of effectiveness of active exergames for improving cognitive functioning in patients with neurological disabilities. Literature search was done in PubMed Central, SCOPUS, MEDLINE, and Cochrane Library, ScienceDirect, and Google Scholar until February 2022. We carried out a meta-analysis with a random-effects model and reported pooled standardized mean differences (SMDs) with 95% confidence intervals (CIs). In total, we analyzed 21 studies and half of them had a high risk of bias and were conducted in Korea and the United States. The pooled SMD for global cognition was 0.46 (95% CI: -0.01 to 0.94

Background In 2015, the Dutch government implemented a long-term care (LTC) reform primarily designed topromote older adults to age-in-place. Increased proportions of older adults living in the community might haveresulted in more and longer acute hospitalisations. The aims of this study were to evaluate whether the Dutch 2015LTC reform was associated with immediate and longitudinal increases in the monthly rate of acute clinicalhospitalisation and monthly average hospital length of stay (LOS) in adults aged 65 years or older.Methods In this interrupted time series analysis of national hospital data (2009–18), we evaluated the association ofthe Dutch 2015 LTC reform with the monthly rate of acute clinical hospitalisation and monthly average LOS for olderadults (aged ≥65 years). Patient-level episodic hospital data were provided by Dutch Hospital Data. Records wereincluded that were defined as an acute clinical hospital admission for which a medical specialist decided treatmentwas necessary within 24 h. The analysis controlled for population growth (Dutch population data was provided byStatistics Netherlands) and seasonality, and calculated adjusted incident rate ratios (IRR).Findings Before the 2015 LTC reform, the rate of acute monthly hospitalisation was increasing (IRR 1·002 [95% CI1·001–1·002]). A positive average reform effect was observed (1·116 [1·070–1·165]), accompanied by a negative changein trend (0·997 [0·996–0·998]) that resulted in a decreasing trend over the post-reform period (0·998 [0·998–0·999]).The pre-reform trend of LOS was decreasing (0·998 [0·997–0·998]), and the 2015 reform exhibited a positive changein trend (1·002 [1·002–1·003]) that resulted in a stabilisation of LOS in the post-reform period (0·999 [0·999–1·000]).Interpretation Our findings suggest that the increase in the rate of acute hospitalisation after the reformimplementation was temporary, whereas the increase in LOS post-reform appeared to last longer than expected.These results have the potential to inform policy makers about effects of ageing-in-place LTC strategies on health andcurative care.

Acute alcohol intoxication impairs cognitive and psychomotor abilities leading to various public health hazards such as road traffic accidents and alcohol-related violence. Intoxicated individuals are usually identified by measuring their blood alcohol concentration (BAC) using breathalysers that are expensive and labour-intensive. In this paper, we developed the Audio-based Deep Learning Algorithm to Identify Alcohol Inebriation (ADLAIA) that can instantly predict an individual's intoxication status based on a 12-second recording of their speech.ADLAIA was trained on a publicly available German Alcohol Language Corpus that comprises a total of 12,360 audio clips of inebriated and sober speakers (total of 162, aged 21-64, 47.7% female). ADLAIA's performance was determined by computing the unweighted average recall (UAR) and accuracy of inebriation prediction.ADLAIA was able to identify inebriated speakers-with BAC of 0.05% or higher-with an UAR of 68.09% and accuracy of 67.67%. ADLAIA had a higher performance (UAR of 75.7%) in identifying intoxicated speakers (BAC0.12%).Being able to identify intoxicated individuals solely based on their speech, ADLAIA could be integrated in mobile applications and used in environments (such as bars, sports stadiums) to get instantaneous results about inebriation status of individuals.