Background: Alzheimer disease is incurable, but it is possible to intervene and slow down the progression of dementia during periods of mild cognitive impairment (MCI) through virtual reality (VR) technology. Objective: This study aimed to analyze the effects of VR interventions on older adults with MCI. The examined outcomes include cognitive abilities, mood, quality of life, and physical fitness, including general cognitive function, memory performance, attention and information processing speed, executive function, language proficiency, visuospatial abilities, depression, daily mobility of individuals, muscle performance, and gait and balance. Methods: A total of 4 web-based databases (Web of Science, PubMed, Embase, and Ovid) were searched up to December 30, 2023, for randomized controlled trials assessing the self-reported outcomes of VR-based technology on cognition, mood, quality of life, and physical fitness in older adults (aged ≥55 years) with MCI. Two reviewers independently screened the search results and reference lists of the identified papers and related reviews. Data on the intervention components and delivery and behavioral change techniques used were extracted. A meta-analysis, risk-of-bias sensitivity analysis, and subgroup analysis were performed where appropriate to explore potential moderators. The Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach was used to assess the quality of evidence. Results: This review analyzed 18 studies involving 722 older adults with MCI. VR was delivered through different immersion levels with VR cognitive training, VR physical training, or VR cognitive-motor dual-task training. VR interventions showed significant improvements in memory (standardized mean difference [SMD] 0.2, 95% CI 0.02-0.38), attention and information processing speed (SMD 0.25, 95% CI 0.06-0.45), and executive function (SMD 0.22, 95% CI 0.02-0.42). VR without therapist involvement improved memory as well as attention and information processing speed. VR cognitive training also resulted in significant improvements in attention and information processing speed in older adults with MCI (SMD 0.31, 95% CI 0.05-0.58). In addition, immersive VR had a significant impact on improving attention and information processing speed (SMD 0.25; 95% CI 0.01-0.50) and executive function (SMD 0.25; 95% CI 0.00-0.50). However, the effects of the intervention were very small in terms of general cognitive function, language proficiency, visuospatial abilities, depression, daily living ability, muscle performance, and gait and balance. Quality of evidence varied, with moderate ratings for certain cognitive functions and low ratings for others, based on the GRADE approach. Conclusions: VR interventions can improve memory, attention and information processing speed, and executive function in older adults with MCI. The quality of evidence is moderate to low, and further research is needed to confirm these findings and explore additional health-related outcomes.

Background: While community-level interventions for promoting active ageing have received increasing attention and there is a trend to leverage technology to support traditional physical or social interventions, little hands-on guidance exists for designing these integral interventions. This study aimed to examine the interventions reported in the literature guided by Community-Based Participatory Research (CBPR) principles. The goal is to extract insights that inform future practices in co-designing integral interventions for active ageing. Methods: The systematic review focused on community-level interventions promoting active ageing that integrated physical, social, and digital elements, i.e., integral interventions. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. The included interventions were analysed abductively based on the CBPR principles. Results: A total of 13 studies were included, and 24 design considerations were generated under eight categories. Further reflection identified the interrelated nature of these design considerations and pinpointed the gaps in current research. This study highlights the urgency and importance of sharing recruitment methods and resource allocation details, recording and reporting collaboration specifics, and disseminating findings to stakeholders beyond academia. Conclusions: This study offers valuable insights and practical guidance to researchers and practitioners developing community-level integral interventions for active ageing. The findings also serve as a starting point for accumulating knowledge and practice in co-designing integral interventions for active ageing at the community level. The next crucial phase involves evaluating these design considerations within real-world cases to assess their applicability and identify potential areas for improvement.

Recent developments in the field of machine learning andwearable sensor technology have led to a renewed interest in the efficient monitoring of cattle health conditions. Wearable inertial sensors are particularly suited for a noninvasive solution to assess cattle health by continuously providing their daily behavior information. However, current classification methods have limitations in terms of the lack of interpretability analysis of the resulting models for the combined behaviors. In this study, a data-driven assessment approach was proposed to classify and understand cattle health through behavior recognition and health classification algorithms. Data were collected through wearable sensors attached to the cattle's collar and leg, providing acceleration, angular velocity, and Euler angles. Random forest was used to implement behavior recognition and health classification of dairy cattle, which was incorporated with explainable artificial intelligence (XAI) for result interpretation. The behavior recognition model achieves high accuracy in distinguishing between behaviors. The health classification model exhibits a strong discriminative ability, and the receiver operating characteristic curve confirms its effectiveness in identifying cattle health status using behavior data. The results showcase the crucial role of XAI analysis in establishing a correlational description between the combined behavioral characteristics of cows and their health classification. This work not only enhances the credibility of the development model but also offers valuable guidance for the predictions of cattle health by motion and feeding behaviors.

Background and Objectives: Researchers from different fields are increasingly interested in incorporating technology into community-based interventions that promote active aging. Yet, there lacks a comprehensive understanding of technology roles, posing challenges for designers seeking to maximize the intended impacts of such interventions. This systematic review aims to fill the gap by examining existing community-based interventions that integrate digital technologies to promote active aging. Research Design and Methods: Thirteen studies were screened, with a total of 14 interventions examined, following the PRISMA Guideline. Results: The challenges in designing and operating community-based interventions, the roles of technology in the interventions, and the caveats of utilizing technology during the process were identified. The review emphasizes the importance of overcoming challenges in community-based interventions and leveraging technology to enhance the intended impacts. Discussion and Implications: The findings underscore the need to understand technology’s nuanced roles in community-based interventions for active aging. The article provides a starting point for accumulating knowledge and practice in utilizing technology to navigate the challenges and opportunities encountered in such interventions. It also sheds light on a notable gap: the lack of innovative and strategic approaches that harness digital interventions appropriately in community-based interventions. This emphasizes a crucial requirement for guidelines to assist designers, policymakers, and community staff in integrating technology appropriately into community-based interventions or implementing interventions that incorporate digital technologies at the community level.

Background: As smart speakers become more popular, there have been an increasing number of studies on how they may benefit older adults or how older adults perceive them. Despite the increasing ownership rates of smart speakers among older adults, studies that examine their integration and the long-term use in older adults’ daily practices are scarce. Objective: This study aims to uncover the integration of smart speakers into the daily practices of older adults over the long term, contributing to an in-depth understanding of maintained technology use among this demographic. Methods: To achieve these objectives, the study interviewed 20 older adults who had been using smart speakers for over 6 months. These semistructured interviews enabled participants to share their insights and experiences regarding the maintained use of smart speakers in the long term. Results: We identified 4 dimensions of the long-term use of smart speakers among older adults, including functional integration, spatial integration, cognitive integration, and semantic integration. For the functional integration of smart speakers, the study reported different types of use, including entertainment, information collection, medication reminders, companionship, environment modification, and emergency calls. For the spatial integration of smart speakers, the study showed older adults’ agency in defining, changing, and reshaping daily practices through the spatial organization of smart speakers. For the cognitive integration of smart speakers, the findings showed the cognitive processes involved in adapting to and incorporating smart speakers into daily habits and routines. For the semantic integration of smart speakers, the findings revealed that older adults’ enjoyable user experience and strong bonds with the device contributed to their acceptance of occasional functional errors. Finally, the study proposed several suggestions for designers and developers to better design smart speakers that promote maintainable use behaviors among older adults. Conclusions: On the basis of the findings, this study highlighted the importance of understanding how older adults use smart speakers and the practices through which they integrate them into their daily routines. The findings suggest that smart speakers can provide significant benefits for older adults, including increased convenience and improved quality of life. However, to promote maintainable use behaviors, designers and developers should consider more about the technology use contexts and the specific needs and preferences of older adults when designing these devices.