Suchergebnisse

To reduce the spread of COVID-19, governments initiated lockdowns, limiting mobility and social interaction of populations. Lockdown is linked to health issues, yet the full impact on health remains unknown, particularly in more vulnerable groups. This study examined impact on frailty and outcomes in high and low COVID-19 risk older adults. We examined health-related behaviours and support resources participants used during lockdown(s). Lockdown impacts in two countries were compared across four time points to examine impacts of different rules. We recruited 70 participants (aged >70 years) in England and Spain. Participants were allocated to higher or lower COVID-19-risk groups based on UK NHS guidelines. They completed assessments for frailty, quality-of-life, loneliness, exercise frequency and social interaction, coping resources and perception of age-friendliness of their environment. The four assessments took place over a 7-month period. Frailty was highest at Time 1 (most severe lockdown restrictions) and significantly higher in the Spanish group. It was lower at Time 3 (lowest restrictions), but did not continue to reduce for the English participants. Perceptions of the age friendliness of the environment matched these changes. Coping resources did not mitigate changes in frailty and outcomes over time, but more frequent physical activity predicted more reduction in frailty. Lockdown had a negative impact on frailty, increasing risk of adverse events for older people, but recovery once lockdowns are eased is evidenced. Further research is required to consider longer term impacts and methods to mitigate effects of lockdown on health.

Deep neural networks (DNNs) have emerged as a state‐of‐the‐art tool in very different research fields due to its adaptive power to the decision space since they do not presuppose any linear relationship between data. Some of the main disadvantages of these trending models are that the choice of the network underlying architecture profoundly influences the performance of the model and that the architecture design requires prior knowledge of the field of study. The use of questionnaires is hugely extended in social/behavioral sciences. The main contribution of this work is to automate the process of a DNN architecture design by using an agglomerative hierarchical algorithm that mimics the conceptual structure of such surveys. Although the train had regression purposes, it is easily convertible to deal with classification tasks. Our proposed methodology will be tested with a database containing socio‐demographic data and the responses to five psychometric Likert scales related to the prediction of happiness. These scales have been already used to design a DNN architecture based on the subdimension of the scales. We show that our new network configurations outperform the previous existing DNN architectures.

Cognitive frailty (CF) is a topic of growing interest with implications for the study of preventive interventions in aging. Nevertheless, little research has been done to assess the influence of psychosocial variables on the risk of CF. Our objectives were to estimate the prevalence of CF in a Spanish sample and to explore the influence of psychosocial variables in this prevalence. Physical frailty and cognitive, functional, psychosocial, and socio-demographic aspects were assessed in a sample of 285 participants over 60 years. Univariate and multivariate logistic regression models were carried out. A prevalence of 21.8% (95% CI 17.4–26.9) was established when both frail and pre-frail conditions were included, and a prevalence of 3.2% (95% CI 1.7–5.9) if only frail individuals were considered. Age, educational level, profession and psychological well-being variables significantly predicted CF. Frailty and pre-frailty are high-prevalence health conditions in older adults influenced by socio-demographic, socio-educative and affective factors ; This research was funded by through FEDER founds by the Spanish Directorate General of Scientific and Technical Research (Project Ref. PSI2014–55316-C3–1-R); and by the Galician Government (Consellería de Cultura, Educación e Ordenación Universitaria; axudas para a consolidación e estruturación de unidades de investigación competitivas do Sistema Universitario de Galicia; GI-1807-USC: Ref. ED431–2017/27) ; SI

Background Dual tasking, or the ability to executing two tasks simultaneously, has been used in recent research to predict cognitive impairments, physical frailty, and has been linked with cognitive frailty in old adults. Aim This study aimed to determine age-related variables can predict dual-task (DT) performance in the older population. Methods A total of 258 healthy community-dwelling participants + 60 years were assessed in relation to their functional capacity, health, well-being, social support and years of education. Performance of a cognitive (Fluency) task and a cognitive– motor (Tracking) task was recorded under single and DT conditions. Multiple linear regression analysis was carried out for each dependent variable, in separate models including cognitive, functional and psychosocial variables. Results Performance in Fluency in DT conditions was predicted by cognitive variables, whereas performance in Tracking DT conditions was predicted by positive interaction, health status, age and motor variables. Discussion The findings suggest that a wide range of cognitive, psychological, social, physical and functional variables influence cognitive and motor performance in aging. Conclusion DT methodology is sensitive to different age-related changes and could be related to frailty conditions in aging ; Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This research was funded by through FEDER founds by the Spanish Directorate General of Scientific and Technical Research (Project Ref. PSI2014–55316-C3–1-R); and by the Galician Government (Consellería de Cultura, Educación e Ordenación Universitaria; axudas para a consolidación e estruturación de unidades de investigación competitivas do Sistema Universitario de Galicia; GI-1807-USC: Ref. ED431–2017/27) ; SI