e-VITA study protocol: EU-Japan virtual coach for smart aging.

Aim: The aim of this study is to report a trial protocol for assessing the improvement of older adults' well-being, promoting active and healthy aging, and reducing the risks of social exclusion, using a virtual coach. Background: Increased longevity brings with it reduced autonomy and independence, and it is therefore necessary to act with preventive measures that can promote active and healthy aging. With the development of technology, new tools have appeared, including virtual coaches, which can enable people to lead a healthy lifestyle by identifying individual needs and goals and providing personalized recommendations and advice. However, it is important that these coaches take into consideration the inter-individual and cross-cultural differences of each person. Design: A randomized controlled trial is proposed. Methods: This study will recruit 240 healthy subjects aged 65 years and older. Participants will be assigned to an experimental group that will receive the e-VITA system or to the control group that will receive an information booklet only. The primary outcome measure is the person's quality of life (QoL). Data will be collected at baseline, 3 months after the trial, and at the end of the trial, after 6 months. Discussion: This study will evaluate the effectiveness of the e-VITA system, consisting of a virtual coach, several sensors for monitoring, a smartphone for use at home, and a booklet, in improving the older person's quality of life. The increased perceived well-being will also be linked to improvements in other areas of the person's life, psychological and cognitive status, the area of sociality, nutrition, and eHealth literacy.

Technology-Enabled Senior Living: A Preliminary Report on Stakeholder Perspectives.

BACKGROUND: The integration of stakeholders is crucial in developing smart living technologies to support the autonomy of elderly populations. Despite the clear benefits of these technologies, there remains a significant gap in comprehensive research. METHODS: This study presents the viewpoints of 19 stakeholders from Europe and Japan, focusing on the sustainability of smart living solutions for Active and Healthy Ageing (AHA). Data were gathered through qualitative semi-structured interviews and analysed using a Framework Analysis approach. RESULTS: Analysis of the interviews revealed six key sustainability categories: addressing the unmet needs of older adults, functionalities of the smart living coach, integration within organizations, identified barriers, financial considerations, and the social role of the smart living coach. CONCLUSIONS: This research underscores the importance of evaluating user needs through the involvement of various stakeholders, including the elderly, their caregivers, professionals, technicians, service providers, and government bodies. Collaborative efforts are essential to generate new evidence demonstrating the value of smart living solutions in facilitating Active and Healthy Ageing.

Intrinsic Capacity and Active and Healthy Aging Domains Supported by Personalized Digital Coaching: Survey Study Among Geriatricians in Europe and Japan on eHealth Opportunities for Older Adults.

BACKGROUND: The worldwide aging trend requires conceptually new prevention, care, and innovative living solutions to support human-based care using smart technology, and this concerns the whole world. Enabling access to active and healthy aging through personalized digital coaching services like physical activity coaching, cognitive training, emotional well-being, and social connection for older adults in real life could offer valuable advantages to both individuals and societies. A starting point might be the analysis of the perspectives of different professionals (eg, geriatricians) on such technologies. The perspectives of experts in the sector may allow the individualization of areas of improvement of clinical interventions, supporting the positive perspective pointed out by the intrinsic capacity framework. OBJECTIVE: The overall aim of this study was to explore the cross-national perspectives and experiences of different professionals in the field of intrinsic capacity, and how it can be supported by eHealth interventions. To our knowledge, this is the first study to explore geriatric care providers' perspectives about technology-based interventions to support intrinsic capacity. METHODS: A survey involving 20 geriatricians or clinical experts in the fields of intrinsic capacity and active and healthy aging was conducted in Italy, France, Germany, and Japan between August and September 2021. RESULTS: The qualitative findings pointed out relevant domains for eHealth interventions and provided examples for successful practices that support subjective well-being under the intrinsic capacity framework (the benefits offered by personalized interventions, especially by promoting health literacy but avoiding intrusiveness). Moreover, eHealth interventions could be used as a bridge that facilitates and enables social engagement; an instrument that facilitates communication between doctors and patients; and a tool to enrich the monitoring actions of medical staff. CONCLUSIONS: There is an unexplored and significant role for such geriatric perspectives to help the development process and evaluate the evidence-based results on the effectiveness of technologies for older people. This is possible only when clinicians collaborate with data scientists, engineers, and developers in order to match the complex daily needs of older adults.

User Perceptions and Needs Analysis of a Virtual Coach for Active and Healthy Ageing-An International Qualitative Study.

Virtual coaching systems show great potential for meeting the challenges of demographic change. However, the proportion of older users in the field of digital technologies is far behind that of younger people. As part of the e-VITA project, semi-structured interviews were conducted in Japan, France, Italy and Germany with 58 people aged 65 and over, and the content was analyzed with the aim of obtaining information about how older adults organize their everyday lives, also with regard to the COVID-19 pandemic, how they deal with their health, what role digital technologies play in the lives of the interviewees and why they oppose progressive digitization. Second, the survey asked why the older adults oppose a virtual coach, which is to be developed in the e-VITA project to support older adults in healthy and active aging, and what barriers they see in a possible implementation. It was found that older respondents lead active, varied lives and that the COVID-19 pandemic contributed to the increased use of digital solutions. In addition, respondents were consciously addressing their own health. With regard to a virtual coach, barriers were seen primarily in the area of data security and sharing. It can be concluded from this that heterogeneity among older user groups should be taken into account when developing virtual coaches. In addition, aspects of data security and data protection should be presented in a clearly understandable and transparent manner.

Sex-Dependent Effects of the APOE ɛ4 Allele on Behavioral Traits and White Matter Structures in Young Adults.

The APOE ɛ4 allele is associated with a risk of Alzheimer's disease in the elderly, with the association being pronounced in females. Conversely, findings of the effects of the APOE ɛ4 allele in young adults are mixed. Here, we investigated the sex-genotype interaction effects of the APOE ɛ4 allele on cognitive functions as well as brain structures among 1258 young adults. After adjusting for multiple comparisons, there were significant effects of the interaction between sex and the number of APOE ɛ4 allele on some speed tasks (e.g., simple processing speed tasks and the reverse Stroop task) as well as on regional white matter volume (rWMV). The observed sex-genotype interaction conferred better cognitive performance and greater rWMV in the anterior frontal and precentral white matter areas in females having more APOE ɛ4 alleles and reduced rWMV in the same areas in male having more APOE ɛ4 alleles. These findings support the long-debated antagonistic pleiotropic effects of the APOE ɛ4 allele in females.

Author Correction: Nrf2 contributes to the weight gain of mice during space travel.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Nrf2 contributes to the weight gain of mice during space travel.

Space flight produces an extreme environment with unique stressors, but little is known about how our body responds to these stresses. While there are many intractable limitations for in-flight space research, some can be overcome by utilizing gene knockout-disease model mice. Here, we report how deletion of Nrf2, a master regulator of stress defense pathways, affects the health of mice transported for a stay in the International Space Station (ISS). After 31 days in the ISS, all flight mice returned safely to Earth. Transcriptome and metabolome analyses revealed that the stresses of space travel evoked ageing-like changes of plasma metabolites and activated the Nrf2 signaling pathway. Especially, Nrf2 was found to be important for maintaining homeostasis of white adipose tissues. This study opens approaches for future space research utilizing murine gene knockout-disease models, and provides insights into mitigating space-induced stresses that limit the further exploration of space by humans.

Impact of Cystic Fibrosis on Unaffected Siblings: A Systematic Review.

OBJECTIVE: To conduct a systematic review of the evidence to determine the impact of cystic fibrosis (CF) on unaffected siblings. STUDY DESIGN: We searched MEDLINE (Ovid interface, from 1946); EMBASE (Ovid interface, from 1946); CINAHL (EBSCO interface); Academic Search Complete (EBSCO interface); Psych Info (EBSCO interface); ProQuest Theses' and Dissertation's (ProQuest); British Index of Nursing (ProQuest); Web of Science (ISI, Web of Knowledge portal); PubMed (PubMed NCBI); BASE (Bielefeld Academic Research Engine); Scopus; EThOS (e-theses online service); Open Grey; and Cochrane Library. Contents pages of the Journal of Cystic Fibrosis, June 2002-April 2017 were hand searched to identify further eligible studies. Reference lists of eligible articles and relevant review papers were screened. Inclusion criteria were full studies published after 1989 in English focusing on the impact of cystic fibrosis on unaffected siblings. RESULTS: In total, 13 papers, 4 PhD theses and 1 MSc thesis were included in the review. Four themes were identified; family functioning, psychosocial impact, knowledge of CF, and condition-specific differences. CONCLUSIONS: Most studies are old and may not accurately represent the impact of CF on unaffected siblings following changes to health care provision including newborn bloodspot screening and the advent of CF transmembrane regulator modulator therapies. Further work is needed directly with siblings rather than using mothers as proxies to determine effect of age, sex, and disease trajectory on unaffected siblings' experiences.

Mixtures of multivariate power exponential distributions.

An expanded family of mixtures of multivariate power exponential distributions is introduced. While fitting heavy-tails and skewness have received much attention in the model-based clustering literature recently, we investigate the use of a distribution that can deal with both varying tail-weight and peakedness of data. A family of parsimonious models is proposed using an eigen-decomposition of the scale matrix. A generalized expectation-maximization algorithm is presented that combines convex optimization via a minorization-maximization approach and optimization based on accelerated line search algorithms on the Stiefel manifold. Lastly, the utility of this family of models is illustrated using both toy and benchmark data.

Mixtures of Shifted AsymmetricLaplace Distributions.

A mixture of shifted asymmetric Laplace distributions is introduced and used for clustering and classification. A variant of the EM algorithm is developed for parameter estimation by exploiting the relationship with the generalized inverse Gaussian distribution. This approach is mathematically elegant and relatively computationally straightforward. Our novel mixture modelling approach is demonstrated on both simulated and real data to illustrate clustering and classification applications. In these analyses, our mixture of shifted asymmetric Laplace distributions performs favourably when compared to the popular Gaussian approach. This work, which marks an important step in the non-Gaussian model-based clustering and classification direction, concludes with discussion as well as suggestions for future work.

Model-based learning using a mixture of mixtures of Gaussian and uniform distributions.

We introduce a mixture model whereby each mixture component is itself a mixture of a multivariate Gaussian distribution and a multivariate uniform distribution. Although this model could be used for model-based clustering (model-based unsupervised learning) or model-based classification (model-based semi-supervised learning), we focus on the more general model-based classification framework. In this setting, we fit our mixture models to data where some of the observations have known group memberships and the goal is to predict the memberships of observations with unknown labels. We also present a density estimation example. A generalized expectation-maximization algorithm is used to estimate the parameters and thereby give classifications in this mixture of mixtures model. To simplify the model and the associated parameter estimation, we suggest holding some parameters fixed-this leads to the introduction of more parsimonious models. A simulation study is performed to illustrate how the model allows for bursts of probability and locally higher tails. Two further simulation studies illustrate how the model performs on data simulated from multivariate Gaussian distributions and on data from multivariate t-distributions. This novel approach is also applied to real data and the performance of our approach under the various restrictions is discussed.

Optimal two-stage reliability studies.

The intraclass correlation is often used to assess the reliability of a measurement system. There is a considerable literature devoted to optimizing the standard assessment plan in which a number of subjects are measured repeatedly. We propose a two-stage investigation, here called a leveraged plan (LP), where in Stage I, we measure a number of subjects once. Then in Stage II, we select a subset of subjects with extreme initial measurements for repeated measurement. For a fixed total number of measurements, we show that the optimal LP provides a more precise estimate of the intraclass correlation coefficient than does the optimal standard plan (SP). We provide a table for finding the optimal LP given the true intraclass correlation and a specified precision for the estimate. For a fixed total number of measurements N, a nearly optimal LP makes roughly N/2 measurements in Stage I and then selects roughly N/6 extreme subjects to re-measure thrice each in Stage II. We also compare optimal leveraged with optimal SPs when there is a limit on the number of times each subject can be re-measured.