Background Various technological interventions have been proposed and studied to address the growing demand for care of residents in assisted living facilities, in which a preexisting shortage of professional caregivers has been exacerbated by the COVID-19 pandemic. Care robots are one such intervention with the potential to improve both the care of older adults and the work life of their professional caregivers. However, concerns about efficacy, ethics, and best practices in the applications of robotic technologies in care settings remain. Objective This scoping review aimed to examine the literature on robots used in assisted living facilities and identify gaps in the literature to guide future research. Methods On February 12, 2022, following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) protocol, we searched PubMed, CINAHL Plus with Full Text, PsycINFO, IEEE Xplore digital library, and ACM Digital Library using predetermined search terms. Publications were included if they were written in English and focused on the use of robotics in assisted living facilities. Publications were excluded if they did not provide peer-reviewed empirical data, focused on user needs, or developed an instrument to study human-robot interaction. The study findings were then summarized, coded, and analyzed using the Patterns, Advances, Gaps, Evidence for practice, and Research recommendations framework. Results The final sample included 73 publications from 69 unique studies on the use of robots in assisted living facilities. The findings of studies on older adults were mixed, with some studies suggesting positive impacts of robots, some expressing concerns about robots and barriers to their use, and others being inconclusive. Although many therapeutic benefits of care robots have been identified, methodological limitations have weakened the internal and external validity of the findings of these studies. Few studies (18/69, 26%) considered the context of care: most studies (48/69, 70%) collected data only on recipients of care, 15 studies collected data on staff, and 3 studies collected data on relatives or visitors. Theory-driven, longitudinal, and large sample size study designs were rare. Across the authors’ disciplines, a lack of consistency in methodological quality and reporting makes it difficult to synthesize and assess research on care robotics. Conclusions The findings of this study call for more systematic research on the feasibility and efficacy of robots in assisted living facilities. In particular, there is a dearth of research on how robots may change geriatric care and the work environment within assisted living facilities. To maximize the benefits and minimize the consequences for older adults and caregivers, future research will require interdisciplinary collaboration among health sciences, computer science, and engineering as well as agreement on methodological standards.
Research on work and occupations in the information field have largely focused on white‐collar jobs. Little is known about the information and technology experiences and behaviors of workers in blue‐collar jobs. This study examines the user experiences of current welding tools and welding training and asks how integration of information feedback through smart technology in welding tools can help welders do their jobs safer, easier, and faster. We conducted 14 in‐depth interviews with members of Longhorn Racing, a student organization that designs, builds, and tests race cars. Participants experienced frustrations with the dangerous and technical setup and the limited vision and information feedback from welding tools. Many argued that the integration of smart technology into welding tools could improve their experience. These innovations could lead to faster training and reduced attrition in the welding industry. Further, this research points to the urgent need for more research on blue‐collar workers in the information field.
BACKGROUND Heart failure (HF) is the leading cause of hospitalization among older adults in the U.S. There are significant racial and geographic disparities in HF outcomes, with patients living in southern U.S. states suffering a mortality rate 69% higher than the national average. Self-management behaviors, particularly daily weight-monitoring and physical activity, are extremely important in improving HF outcomes, but patients typically have particularly low adherence to these behaviors. With the rise of digital technologies to improve health outcomes and motivate health behaviors, sensor-controlled digital games (SCDGs) are a promising approach. SCDGs, which leverage sensor-connected technologies, offer the benefits of being portable, scalable, and allowing for continuous observation and motivation of health behaviors in their real-world contexts. They are also increasingly popular among older adults and offer an immersive and accessible way to measure self-management behaviors and improve adherence. No SCDGs have been designed for older adults or evaluated to test their outcomes. OBJECTIVE This randomized clinical trial (RCT) assesses the efficacy of a sensor-controlled digital game in integrating HF participants’ behavioral data from weight scale and activity tracker sensors to activate game progress, rewards, and feedback and, ultimately, to improve adherence to important self-management behaviors. METHODS Two-hundred participants with HF, aged 45 or older, will be recruited and randomized into 2 groups: the SCDG-playing group (IG) and a sensor-only group (CG). Both groups will receive a weight scale, physical activity tracker, and accompanying app, while only the IG will play the SCDG. This design, thereby, assess the contributions of the game. All participants will complete a baseline survey as well as posttests at 6 and 12 weeks to assess the immediate effect of the intervention; they will also complete a 3rd posttest at 24 weeks to assess maintenance of behavioral changes. Efficacy and benefits will be assessed by measuring improvements in HF-related proximal outcomes (self-management behaviors of daily weight-monitoring and physical activity) and distal outcomes (HF hospitalization, QoL, functional status) between baseline to weeks 6, 12, and 24. The primary outcome measured will be days with weight-monitoring, for which this design provides at least 80% power to detect differences between the two groups. RESULTS Recruitment began in the fall of 2022, with the first patient enrolled in the study on November 7, 2022. Recruitment of the last participant is expected in Q1 of 2025. Publication of complete results and data from the study is expected in 2026. CONCLUSIONS This project will generate insight and guidance for scalable and easy-to-use digital gaming solutions to motivate persistent adherence to HF self-management behaviors and improve health outcomes among individuals with HF.
Background Heart failure (HF) is the leading cause of hospitalization among older adults in the United States. There are substantial racial and geographic disparities in HF outcomes, with patients living in southern US states having a mortality rate 69% higher than the national average. Self-management behaviors, particularly daily weight monitoring and physical activity, are extremely important in improving HF outcomes; however, patients typically have particularly low adherence to these behaviors. With the rise of digital technologies to improve health outcomes and motivate health behaviors, sensor-controlled digital games (SCDGs) have become a promising approach. SCDGs, which leverage sensor-connected technologies, offer the benefits of being portable and scalable and allowing for continuous observation and motivation of health behaviors in their real-world contexts. They are also becoming increasingly popular among older adults and offer an immersive and accessible way to measure self-management behaviors and improve adherence. No SCDGs have been designed for older adults or evaluated to test their outcomes. Objective This randomized clinical trial aims to assess the efficacy of a SCDG in integrating the behavioral data of participants with HF from weight scale and activity tracker sensors to activate game progress, rewards, and feedback and, ultimately, to improve adherence to important self-management behaviors. Methods A total of 200 participants with HF, aged ≥45 years, will be recruited and randomized into 2 groups: the SCDG playing group (intervention group) and sensor-only group (control group). Both groups will receive a weight scale, physical activity tracker, and accompanying app, whereas only the intervention group will play the SCDG. This design, thereby, assesses the contributions of the game. All participants will complete a baseline survey as well as posttests at 6 and 12 weeks to assess the immediate effect of the intervention. They will also complete a third posttest at 24 weeks to assess the maintenance of behavioral changes. Efficacy and benefits will be assessed by measuring improvements in HF-related proximal outcomes (self-management behaviors of daily weight monitoring and physical activity) and distal outcomes (HF hospitalization, quality of life, and functional status) between baseline and weeks 6, 12, and 24. The primary outcome measured will be days with weight monitoring, for which this design provides at least 80% power to detect differences between the 2 groups. Results Recruitment began in the fall of 2022, and the first patient was enrolled in the study on November 7, 2022. Recruitment of the last participant is expected in quarter 1 of 2025. Publication of complete results and data from this study is expected in 2026. Conclusions This project will generate insight and guidance for scalable and easy-to-use digital gaming solutions to motivate persistent adherence to HF self-management behaviors and improve health outcomes among individuals with HF. Trial Registration ClinicalTrials.gov NCT05056129; https://clinicaltrials.gov/ct2/show/NCT05056129 International Registered Report Identifier (IRRID) DERR1-10.2196/45801
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