OBJECTIVES: This paper discusses RISAPI of our original work in the field, which shows how probabilistic planning and system theory algorithms in workplace robotic systems that work with people can allow for that reasoning using a security robot system. The problem is a general way as an incomplete knowledge 2-player game.
RESULTS: In this general framework, the various hypotheses and these contribute to thrilling and complex robot behavior through real-time interaction, which transforms actual human subjects into a spectrum of production systems, robots, and care facilities.
CONCLUSION: The models of the internal human situation, in which robots can be designed efficiently, are limited, and achieve optimal computational intractability in large, high-dimensional spaces. To achieve this, versatile, lightweight portrayals of the human inner state and modern algorithms offer great hope for reasoning.
Patients and methods: A focus group discussion was conducted with 12 community pharmacists. Participants were recruited using snowball sampling. Audio-recordings were transcribed verbatim, and analyzed using a thematic approach.
Results: Three themes were apparent: 1) suggestions for app design and content, 2) perceived benefits of the app, and 3) potential challenges related to the app. Participants believed the app would be able to facilitate and improve communication, and hence relationship, between pharmacists and the DHoH. Potential challenges of the app were highlighted, such as the need for manpower to manage the app, and its cost to this group of economically disadvantaged people. There were also concerns about privacy and security.
Conclusions: This study allowed community pharmacists, one of the end-users of the app, to provide feedback on the contents and design of the app, which would allow them to provide pharmaceutical care services to patients who are DHoH, and better serve them. Potential benefits and challenges of the app were also identified. Undoubtedly, through the mHealth app, community pharmacists will be better equipped to serve and communicate with the DHoH, and this will hopefully translate to improved health outcomes in these patients.
OBJECTIVES: This study aims to identify the determinants associated with Twitter use in psychiatric consultations and to assess the level of satisfaction in using the microblogging platform. In addition, the level of e-health literacy is also assessed among users.
METHODS: The target population included Twitter users seeking psychiatric consultation. A leading psychiatrist's twitter account with 4.5 million followers was selected and consent obtained. A validated Patient Satisfaction Questionnaire was adopted to assess the level of satisfaction in Twitter use and e-health literacy. The questionnaire was tagged to the chosen Twitter account and reminders were sent until the sample size was reached. Data was analysed using SPSS version 22.0. The analysis included descriptive statistics tabulation, multi-response analysis, and cross-tabulation for satisfaction variables and the chi-square test was used to measure association between different variables.
RESULTS: The study obtained 155 completed response sheets, of which 52 were Twitter users seeking psychiatric advice while the rest sought general health advice. Most of the study participants were females (71.6 %). Women, single status and income range between 4000-9000 Saudi riyal were found to be significantly associated with Twitter use for psychiatric consultation. Generally, most of the participants were satisfied with Twitter in seeking psychiatric consultation that reduced financial disbursement. Furthermore, concerns were expressed regarding the waiting period, word limitations and issues of privacy. The e-health literacy was higher among the participants.
CONCLUSION: Psychiatric consultations via Twitter is more popular among women. By addressing privacy issues and reducing response time, Twitter may be used as a major platform to deliver mental health services to the population.
AIMS: This study aimed to explore the postgraduate students' perspective on using Twitter as a learning resource.
SUBJECTS AND METHODS: This qualitative study was conducted as part of a postgraduate program at a university in the United Kingdom. A focus group discussion and five in-depth interviews were conducted after receiving the informed consent. The qualitative data were analyzed by R package for Qualitative Data Analysis software.
ANALYSIS USED: Deductive content analysis was used in this study.
RESULTS: Qualitative analysis revealed four salient themes, which were (1) background knowledge about Twitter, (2) factors influencing the usage of Twitter, (3) master's students' experiences on using Twitter for education, and (4) potential of using Twitter in the postgraduate study. The students preferred to use Twitter for sharing links and appreciated the benefit on immediate dissemination of information. Meanwhile, privacy concern, unfamiliarity, and hesitation to participate in discussion discouraged the students from using Twitter as a learning platform.
CONCLUSIONS: Using social media platforms in education could be challenging for both the learners and the educators. Our study revealed that Twitter was mainly used for social communication among postgraduate students however most could see a benefit of using Twitter for their learning if they received adequate guidance on how to use the platform. The multiple barriers to using Twitter were mainly related to unfamiliarity which should be addressed early in the learning process.
Methods: A community-based participatory research method was utilized. Two focus group discussions (FGDs) were conducted in Malaysian sign language (BIM) with a total of 10 DHH individuals. Respondents were recruited using purposive sampling. Video-recordings were transcribed and analyzed using a thematic approach.
Results: Two themes emerged: (I) challenges and scepticism of the healthcare system; and (II) features of the mHealth app. Respondents expressed fears and concerns about accessing healthcare services, and stressed on the need for sign language interpreters. There were also concerns about data privacy and security. With regard to app features, the majority preferred videos instead of text to convey information about their disease and medication, due to their lower literacy levels.
Conclusions: For an mHealth app to be effective, app designers must ensure the app is individualised according to the cultural and linguistic diversity of the target audience. Pharmacists should also educate patients on the potential benefits of the app in terms of assisting patients with their medicine-taking.