This randomized controlled trial aimed to test the effectiveness of brief face-to-face patient education in increasing influenza vaccination rate among elderly in the community. Recruitment and intervention were conducted at two general outpatient clinics in Hong Kong. 529 eligible patients were randomly assigned to intervention or control group with 1:1 allocation ratio. Patients in the intervention group received 3-min one-on-one verbal education by medical students and a pamphlet regarding influenza vaccination. Neither verbal health education nor pamphlet was given to the control group. Intention-to-treat analysis showed significantly higher vaccination rate in the intervention group compared with the control group (33.6 versus 25.0%) and the adjusted relative risk was 1.34 (95% CI 1.04-1.72; P = 0.021). Hence, brief face-to-face patient education was effective in increasing influenza vaccine uptake rate of community-dwelling elderly patients. Participants who were undecided whether to receive vaccination seemed to demonstrate larger beneficial effect (RR = 7.84; 95% CI 1.06-57.76) compared with patients who were certain of either receiving (RR = 1.16; 95% CI 0.90-1.48) or not receiving (RR = 2.18; 95% CI 0.68-6.99) the vaccine. The study also revealed that patients' intention for vaccination may not translate into action, reasons for which should be explored in future research.
Many IoT technologies have been applied in the logistics industry in recent years, and they have had a substantial impact on many sectors such as shipping, air freight, warehousing, inventory, etc. Exploring technology opportunities and carrying out technological trend analysis are essential for IoT’s evolution, and there are many techniques or methods for doing so. In this paper, data analysis and text mining techniques, technology opportunity analysis (TOA) and technology-service evolution analysis (TSEA) have been applied to analyze and observe IoT technologies’ and services’ evolution. Academic journals, market reports, and patents have been collected and reviewed on the topic of IoT in the logistics field in this paper. Moreover, by using TOA, technology opportunities have been analyzed to explore IoT-related logistics services. The results of TOA, for example, show that cloud technology is essential to develop smart logistics services, and communication RFID technologies are key to developing information logistics services. Finally, TSEA enables the observation of IoT technology and logistics service evolution by combining unstructured and semi-structured data from text documents. Observing the results of TSEA, the evolution of IoT in logistics is identified, and the results of TSEA also confirm those of TOA using unstructured or semi-structured text data from documents only. The results of this paper are discussed and compared with those of some previous review studies. In summary, the results of this paper provide methodological guidelines on this topic for a comprehensive understanding of IoT-related logistics services.
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