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

Abstract

A series of mitigation efforts were implemented in response to the COVID-19 pandemic in Saudi Arabia, including the development of mobile health applications (mHealth apps) for the public. Assessing the acceptability of mHealth apps among the public is crucial. This study aimed to use Twitter to understand public perceptions around the use of six Saudi mHealth apps used during COVID-19: “Sehha”, “Mawid”, “Sehhaty”, “Tetamman”, “Tawakkalna”, and “Tabaud”. We used two methodological approaches: network and sentiment analysis. We retrieved Twitter data using specific mHealth apps-related keywords. After including relevant tweets, our final mHealth app networks consisted of a total of 4995 Twitter users and 8666 conversational relationships. The largest networks in size (i.e., the number of users) and volume (i.e., the conversational relationships) among all were “Tawakkalna” followed by “Tabaud”, and their conversations were led by diverse governmental accounts. In contrast, the four remaining mHealth networks were mainly led by the health sector and media. Our sentiment analysis approach included five classes and showed that most conversations were neutral, which included facts or information pieces and general inquires. For the automated sentiment classifier, we used Support Vector Machine with AraVec embeddings as it outperformed the other tested classifiers. The sentiment classifier showed an accuracy, precision, recall, and F1-score of 85%. Future studies can use social media and real-time analytics to improve mHealth apps’ services and user experience, especially during health crises.

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

“…As a component of its subjective drives, the Ministry of Health (MOH) launched and developed a total of 12 mobile applications between 2012 and 2019, three of which were developed within three months during the COVID-19 pandemic. These apps are Tawakkalna, My Health (Sehhaty), Tabaud, Rest Assured (Tataman), Health (SEHA), Appointment (Mawid), Qareebon, Anaat, Asafny, Eshar, and Wasfaty [ 6 ].…”

“…As a component of its subjective drives, the Saudi Ministry of Health (MOH) launched and developed a total of 12 mobile applications between 2012 and 2019, three of which were developed within three months during the COVID-19 pandemic. These apps are Tawakkalna, My Health (Sehhaty), Tabaud, Rest Assured (Tataman), Health (SEHA), Appointment (Mawid), Qareebon, Anaat, Asafny, Eshar, and Wasfaty [ 6 ], as illustrated in Table 1 and Table 2 . Sehhaty and Seha applications have the highest percentage of users among all apps; users exceeding 24 million users (68.5% of the population) [ 11 ].…”

“…The application targets giving protection and healthcare to citizens and residents who are self-isolating or in quarantine by enhancing their recovery procedures offering assistance in results, updating data of those who were in contact with confirmed cases, daily follow-up of the health status, epidemiological investigation, and communication with the health hotline number (937) [ 6 ].…”

Survey on sentiment analysis: evolution of research methods and topics

“…As the COVID-19 pandemic has unfolded, a large number of individuals, media and governments have been publishing news and opinions about the COVID-19 crisis on social media platforms. This has resulted in a lot of sentiment analysis studies focusing on COVID-19-related texts exploring the impact of the epidemic on people's lives (Sari and Ruldeviyani 2020;Wang, T. et al 2020a), physical health (Berkovic et al 2020;Binkheder et al 2021) and mental health (Yin et al 2020), and so on. Therefore, we can see many related keywords, such as "infodemiology," "healthcare," and "mental health."…”

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

“…In densely populated Bangladesh, where there are approximately 3.05 physicians per 10,000 people and 1.07 nurses per 10,000 people, non-therapeutic measures are out of control [ 13 , 14 ]. Thus, mHealth apps supported by smartphone and artificial intelligence technologies offer an alternative solution for healthcare to patients that ensure instantaneous and accessible medical services for contact tracing, health tracking, prescribing treatment, paperless medical documentation, monitoring, and health management for suspected COVID-19 patients [ 15 , 16 , 17 , 18 ]. mHealth apps are an innovative healthcare tool with the potential to enhance health communication among patients and clinicians and to improve patients’ health outcomes in a pandemic without physical movements [ 19 , 20 , 21 ].…”