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.

Background: Self-medication (SM) among women during pregnancy poses a critical risk to maternal health, and SM is still commonly practiced in Saudi Arabia. Therefore, this study aims to assess the factors, attitudes, and prevalence of SM among pregnant women in the Ministry of Health (MOH) First Health Cluster. Methods: A cross-sectional design was used among 400 pregnant women who received care at primary, secondary, and tertiary healthcare levels. A structured tool was adopted and modified based on the literature review, expert and focus group interviews, and the experiences of the target participants. The dependent variables included history of illness, access to healthcare services, medication usage, and perception of SM, while the independent variables included socioeconomic status. Statistical Package for the Social Sciences (SPSS), Version 25 was used for analysis. Results: The prevalence of SM was 36.5%. Cough syrup and antipyretics were the most commonly used medications, while hair problems and weight loss were the most frequently reported reasons for SM. The primary sources of information guiding SM behavior were prior prescriptions and previous experience. Education level, occupation, age, number of pregnancies, and miscarriage history were all significantly associated with SM (p < 0.05). Conclusions: SM was found to be frequent among pregnant women in the First Health Cluster, highlighting the need for educational interventions and regulatory measures to reduce unsafe practices and improve maternal health.