Nudge-Based Interventions on Health Promotion Activity Among Very Old People: A Pragmatic, 2-Arm, Participant-Blinded Randomized Controlled Trial.

OBJECTIVES: Social distancing due to the coronavirus disease 2019 crisis can exacerbate inactivity in older adults. Novel approaches for older adults must be designed to improve their activity and maintain their health. This study examined the effect of nudge-based behavioral interventions on health-promoting activities in older adults in Japan. DESIGN: Two-arm, participant-blinded randomized controlled trial. SETTING AND PARTICIPANTS: Japanese continuing care retirement community residents (n = 99, median age 82 years, 73% women) INTERVENTION: Two-step nudge-based behavioral intervention promoting tablet usage. METHODS: We enrolled participants from an ongoing Internet of Things project in a retirement community in Japan. For the health promotion program, tablet computers were installed in a common area for participants to receive information about their health. The intervention group received a 1-time loss-emphasized nudge (first step), followed by asking questions about when they planned to use it again (second step). The control group used the tablet computers without being asked those questions. The main outcome was the participants' mean daily tablet activity every 4 weeks for the next 16 weeks. RESULTS: Ninety-nine individuals were randomly assigned to the intervention or control group. The rate ratios for tablet use were significantly higher in the intervention group in the second and third periods. The subgroup analysis showed that these effects were largely attributable to men. CONCLUSIONS AND IMPLICATIONS: Nudge-based interventions can be effective in promoting activities for older adults, especially older men. The finding of this study indicates a possible intervention to engage people who are socially isolated.

Experience of distance education for project-based learning in data science.

Data science plays an important role in many fields. Project-based learning is an effective teaching approach because students can learn data science practices based on real-world problems and real-world data. Because of a pandemic of COVID-19, we provided project-based learning as distance education (synchronic distance education). In this study, we explain how we developed and conducted it and provide survey results from students. The survey showed about 30% of the students found it difficult to communicate with each other and with teachers. However, it suggested that they could communicate to some extent even by remote group work. We found that, in remote communication, it is important to see the faces of all the students (and teachers) on the Zoom screen when they discuss using screen sharing. There remain some challenges such as timing to start talking and casual questions to teachers. Although some issues should be improved, distance education for project-based learning in data science can be implemented effectively. Supplementary Information: The online version contains supplementary material available at 10.1007/s42081-022-00154-2.

Experience of distance education for project-based learning in data science

Data science plays an important role in many fields. Project-based learning is an effective teaching approach because students can learn data science practices based on real-world problems and real-world data. Because of a pandemic of COVID-19, we provided project-based learning as distance education (synchronic distance education). In this study, we explain how we developed and conducted it and provide survey results from students. The survey showed about 30% of the students found it difficult to communicate with each other and with teachers. However, it suggested that they could communicate to some extent even by remote group work. We found that, in remote communication, it is important to see the faces of all the students (and teachers) on the Zoom screen when they discuss using screen sharing. There remain some challenges such as timing to start talking and casual questions to teachers. Although some issues should be improved, distance education for project-based learning in data science can be implemented effectively. Supplementary Information The online version contains supplementary material available at 10.1007/s42081-022-00154-2.