Public Perceptions around mHealth Applications during COVID-19 Pandemic: A Network and Sentiment Analysis of Tweets in Saudi Arabia

Survey on sentiment analysis: evolution of research methods and topics

Sentiment analysis, one of the research hotspots in the natural language processing field, has attracted the attention of researchers, and research papers on the field are increasingly published. Many literature reviews on sentiment analysis involving techniques, methods, and applications have been produced using different survey methodologies and tools, but there has not been a survey dedicated to the evolution of research methods and topics of sentiment analysis. There have also been few survey works leveraging keyword co-occurrence on sentiment analysis. Therefore, this study presents a survey of sentiment analysis focusing on the evolution of research methods and topics. It incorporates keyword co-occurrence analysis with a community detection algorithm. This survey not only compares and analyzes the connections between research methods and topics over the past two decades but also uncovers the hotspots and trends over time, thus providing guidance for researchers. Furthermore, this paper presents broad practical insights into the methods and topics of sentiment analysis, while also identifying technical directions, limitations, and future work.

Users' satisfaction levels about mHealth applications in post-Covid-19 times in Saudi Arabia

Purpose

This study aims to investigate the users’ satisfaction levels about mHealth applications and their intentions to use them in future (in post-Covid-19 times) in Saudi Arabia.

Methods

A cross-sectional survey design was adopted in this study. The mHealth App Usability Questionnaire (MAUQ)22 was used in this study. An online version of the survey was created using Google Surveys, and a link for the survey was generated. As the objective of this study is to assess the users’ satisfaction levels about mHealth applications and their intentions to use them in future (in post-Covid-19 times) in Saudi Arabia, all individuals who used or using mHealth applications will be included in this study. At the end of the survey time period, 318 responses were received.

Results

Items including ’easy to learn using the app’ (mean rating = 3.9), ’easy to find information on the application’(mean rating = 3.9), ’interface of the app’ (mean rating = 3.8) were rated to be highly effective by the participants.). However, ability to recover from mistakes while using the applications (mean rating = 2.9), inconsistency in navigation (mean rating = 2.9), and lack of all necessary functions (mean rating = 2.3) were few issues identified. No statistically significant difference of opinions was observed in relation to all sub-scales of usability factor.

Conclusion

Although the satisfaction levels are good with respect to mHealth applications, the sudden rise in the mHealth users can be partly linked to the several psychological issues such as anxiety and depression among people and also because of restricted access during the pandemic.

Strengthening the Trialability for the Intention to Use of mHealth Apps Amidst Pandemic: A Cross-Sectional Study

Recent advancements in mHealth apps and services have played a vital role in strengthening healthcare services and enabling their accessibility to marginalized people. With the alarming rise in COVID-19 infection rates around the world, there appears to be an urgent call to modernize traditional medical practices to combat the pandemic. This study aims to investigate the key factors influencing the trialability of mHealth apps/services and behavioral intention to adopt mobile health applications. The study also examines the moderating effects of self-discipline motivation, knowledge, and attitude on the relationship between trialability and behavioral intention to use. The deductive reasoning approach was followed in a positivism paradigm. The study used convenience sampling and collected responses from 280 Generation Y participants in Bangladesh. Partial least square-based structural equation modeling was employed. The results revealed that relative advantage (β = 0.229, p < 0.05), compatibility (β = 0.232, p < 0.05), complexity (β = −0.411, p < 0.05), and observability (β = 0.235, p < 0.05) of mHealth apps influence the trialability of mHealth apps and services among users. Trialability compatibility (β = 0.425, p < 0.05) of mHealth was positively related to the behavioral intention to use these mobile apps. The study found no moderating effects of attitude (β = 0.043, p > 0.05) or self-discipline motivation (β = −0.007, p > 0.05) on the hypothesized relationships. The empirical findings of this study may facilitate the development, design process, and implementation of mHealth applications with improved features that can lead to high user acceptance among Generation Y during future health crises.

The role of the COVID-19 pandemic in expediting digital health-care transformation: Saudi Arabia's experience

A comprehensive literature review of Research engines was conducted up to March 2022 to retrieve the articles. We considered all published data, press briefings, and announcements by the Ministry of Health of Saudi Arabia (MOH). The search included both sources in English and Arabic. Thus, this paper aims to give a comprehensive overview of the evolution and role of telemedicine and E-health represented in multiple informatics mobile applications during the COVID-19 pandemic in Saudi Arabia. As a component of its subjective drives, the MOH has launched and developed a total of 12 mobile applications from 2012 to 2019, three apps of which were developed during the COVID-19 pandemic. My health "Sehhaty" was the cornerstone of telemedicine services provided by the MOH in Saudi Arabia during the COVID-19 pandemic. Virtually booked physician appointments exceeded 3.8 million. Appointment "Mawid" app number of users sprinted from 4 million to 25 million users and the number of appointments booked in the same app went from 8 million to 100 million appointments in pre-COVID-19 compared to the post-COVID-19 period. Furthermore, the Health 937 hotline numbers grew to 24.6 million calls. The Health "Seha" app provided 2 million remote medical consultations with an almost 8-fold increase compared to pre-COVID-19 times.