Journal of Medical Internet Research

Virtual reality (VR) devices are increasingly used in health care settings. The use among patients has the potential to unintentionally transmit pathogens between patients and hospital staff. No standard operating procedure for disinfection exists to ensure safe use between patients.

Drug-induced long-QT syndrome (diLQTS) is a major concern among patients who are hospitalized, for whom prediction models capable of identifying individualized risk could be useful to guide monitoring. We have previously demonstrated the feasibility of machine learning to predict the risk of diLQTS, in which deep learning models provided superior accuracy for risk prediction, although these models were limited by a lack of interpretability.

There is no recognized gold standard method for estimating the number of individuals with substance use disorders (SUDs) seeking help within a given geographical area. This presents a challenge to policy makers in the effective deployment of resources for the treatment of SUDs. Internet search queries related to help seeking for SUDs using Google Trends may represent a low-cost, real-time, and data-driven infoveillance tool to address this shortfall in information.

Interest in critical care–related artificial intelligence (AI) research is growing rapidly. However, the literature is still lacking in comprehensive bibliometric studies that measure and analyze scientific publications globally.

The US Food and Drug Administration (FDA) recently restricted characterizing flavors in tobacco products. As a result, ice hybrid–flavored e-cigarettes, which combine a cooling flavor with fruit or other flavors (eg, banana ice), emerged on the market. Like menthol, ice-flavored e-cigarettes produce a cooling sensory experience. It is unclear if ice hybrid–flavored e-cigarettes should be considered characterizing flavors or menthol, limiting regulatory action. Monitoring the public’s conversations about ice-flavored e-cigarettes on Twitter may help inform the tobacco control community about these products and contribute to the US FDA policy targets in the future.

Previous studies have demonstrated telemedicine (TM) to be an effective tool to complement rheumatology care and address workforce shortage. With the outbreak of the SARS-CoV-2 pandemic, TM experienced a massive upswing. However, in rheumatology care, the use of TM stagnated again shortly thereafter. Consequently, the factors associated with physicians’ willingness to use TM (TM willingness) and actual use of TM (TM use) need to be thoroughly investigated.

Mindfulness has emerged as a promising approach toward improving mental health. Interest in mindfulness mobile app services has also increased in recent years. Understanding the determinants of mindfulness behavior is essential to predict people’s utilization of mindfulness mobile apps and beneficial for developing and implementing relevant intervention strategies. Nevertheless, little has been done to determine the predictors of mindfulness behavior.

HIV self-testing is preferred by many Chinese people for its convenience and confidentiality. However, most studies on HIV self-testing (HIVST) uptake in China overfocused on men who have sex with men and overrelied on obtrusive methods such as surveys and interviews to collect data.

Despite Catalonia being an advanced region in terms of digital health adoption, the “Forum for Professional Dialogue” identified the need to improve information and communication technology (ICT) competences as one of the present and future challenges for health care professionals (HPs).

Worldwide, mental well-being is a critical issue for public health, especially among medical staff; it affects professionalism, efficiency, quality of care delivery, and overall quality of life. Nevertheless, assessing mental well-being is a complex problem.

Despite the prevalence of parent health information seeking on the internet and its impact on parenting behavior, there is a paucity of research on parents of young children (ages 3 to 8 years). Given the importance of this developmental period, exploring how family socioeconomic indicators linked to the digital divide and health inequities affect parent proxy- and self-seeking is critical to further understanding variability in health information seeking and associated outcomes.

Much research is being carried out using publicly available Twitter data in the field of public health, but the types of research questions that these data are being used to answer and the extent to which these projects require ethical oversight are not clear.