A large and growing population of elderly Koreans with chronic conditions necessitates an increase in long-term care. This study is aimed at investigating the effects of occupational stress, work-centrality, self-efficacy, and job satisfaction on intent to leave among long-term care workers in Korea. We tested the hypothesized structural equation model predicting the intention to quit among long-term care workers in Korea. Survey data were collected from 532 long-term care workers in Seoul, Korea. Results showed that occupational stress was positively associated with intention to leave the job. The study also identified several possible mediators (self-efficacy, work-centrality, job satisfaction) in the relationship between stress and intent to quit. Evidence-based stress management interventions are suggested to help the workers better cope with stressors. Mentoring programs should also be considered for new workers.
The sensor network service has emerged as a new technical research area. The sensor network service provides useful functions to the user by sensing the condition of physical entities. One important issue that is rarely addressed by current studies on the sensor network service is that they only use sensor-derived data to achieve local service goals. However, once external users can discover globally deployed sensor networks, the information which is created by such networks will be more expansible to various novel services. Recently, few studies have addressed the importance of sensorderived data sharing, but they have not shown deep concern about ways to share sensor-derived data with external users. This paper proposes the sensor network registry for the sensor network registration and discovery. We explore the information that the sensor network registry should maintain in order to enable sensor network services to be shared, and also design the architecture of the system. We expect the sensor network registry will make sensor network technology more useful, just as a good Web search engine makes the Internet more useful.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.