Research into the adoption and use of user-centered and sociotechnical design principles is needed to improve usability, perceived usefulness, and, ultimately, adoption of the technology. Proliferation and efficacy of interventions involving mobile applications will benefit from a holistic approach that takes into account patients' expectations and providers' needs.

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Many educational institutions have implemented ubiquitous or required laptop, notebook, or tablet personal computing programs for their students. Yet, limited evidence exists to validate integration and acceptance of the technology among student populations. This research examines student acceptance of mobile computing devices using a modification of the "Unified Theory of Acceptance and Use of Technology" (UTAUT) recently developed by leading researchers in the technology acceptance field. The objective of the study is to identify the variance of selected acceptance elements that contribute to the overall behavioral intent to use Tablet PCs (TPC). These outcomes are then used as a means to forecast, explain, and improve integration of the technology in the higher education context. The research also contributes to UTAUT's theoretical validity and empirical applicability and to the management of information technology (IT) based initiatives in education.Technology has a ubiquitous presence in educational institutions across the United States. Higher education has been particularly aggressive in acquiring mobile technology, some institutions even adopting computing initiatives that require every student to own their own computing device. Hundreds of higher education 79

Background The coronavirus disease (COVID-19) pandemic is considered to be the most daunting public health challenge in decades. With no effective treatments and with time needed to develop a vaccine, alternative approaches are being used to control this pandemic. Objective The objective of this paper was to identify topics, opinions, and recommendations about the COVID-19 pandemic discussed by medical professionals on the Twitter social medial platform. Methods Using a mixed methods approach blending the capabilities of social media analytics and qualitative analysis, we analyzed COVID-19–related tweets posted by medical professionals and examined their content. We used qualitative analysis to explore the collected data to identify relevant tweets and uncover important concepts about the pandemic using qualitative coding. Unsupervised and supervised machine learning techniques and text analysis were used to identify topics and opinions. Results Data were collected from 119 medical professionals on Twitter about the coronavirus pandemic. A total of 10,096 English tweets were collected from the identified medical professionals between December 1, 2019 and April 1, 2020. We identified eight topics, namely actions and recommendations, fighting misinformation, information and knowledge, the health care system, symptoms and illness, immunity, testing, and infection and transmission. The tweets mainly focused on needed actions and recommendations (2827/10,096, 28%) to control the pandemic. Many tweets warned about misleading information (2019/10,096, 20%) that could lead to infection of more people with the virus. Other tweets discussed general knowledge and information (911/10,096, 9%) about the virus as well as concerns about the health care systems and workers (909/10,096, 9%). The remaining tweets discussed information about symptoms associated with COVID-19 (810/10,096, 8%), immunity (707/10,096, 7%), testing (605/10,096, 6%), and virus infection and transmission (503/10,096, 5%). Conclusions Our findings indicate that Twitter and social media platforms can help identify important and useful knowledge shared by medical professionals during a pandemic.

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