Journal of Medical Internet Research

Health information consumers increasingly rely on question-and-answer (Q&A) communities to address their health concerns. However, the quality of questions posted significantly impacts the likelihood and relevance of received answers.

With the widespread adoption of digital health records, including electronic discharge summaries (eDS), it is important to assess their usability in order to understand whether they meet the needs of the end users. While there are established approaches for evaluating the usability of electronic health records, there is a lack of knowledge regarding suitable evaluation methods specifically for eDS.

Digital public health (DiPH) interventions may help us tackle substantial public health challenges and reach historically underserved populations, in addition to presenting valuable opportunities to improve and complement existing services. However, DiPH interventions are often triggered through technological advancements and opportunities rather than public health needs. To develop and evaluate interventions designed to serve public health needs, a comprehensive framework is needed that systematically covers all aspects with relevance for public health. This includes considering the complexity of the technology, the context in which the technology is supposed to operate, its implementation, and its effects on public health, including ethical, legal, and social aspects.

Wikipedia is the largest free online encyclopedia and the seventh most visited website worldwide, containing >45,000 freely accessible English-language medical articles accessed nearly 1.6 billion times annually. Concerns have been expressed about the balance of content related to biological sex on Wikipedia.

The prevalence of type 1 diabetes (T1D) is increasing worldwide, with a much higher proportion of adult patients. However, achieving stable glycemic control is difficult in these patients.

Monitoring free-living physical activity (PA) through wearable devices enables the real-time assessment of activity features associated with health outcomes and provision of treatment recommendations and adjustments. The conclusions of studies on PA and health depend crucially on reliable statistical analyses of digital data. Data analytics, however, are challenging due to the various metrics adopted for measuring PA, different aims of studies, and complex temporal variations within variables. The application, interpretation, and appropriateness of these analytical tools have yet to be summarized.

Cognitive frailty refers to a clinical syndrome in which physical frailty and mild cognitive impairment coexist. Motor-cognitive training and virtual reality (VR) have been used to launch various therapeutic modalities to promote health in older people. The literature advocates that motor-cognitive training and VR are effective in promoting the cognitive and physical function of older people. However, the effects on older people with cognitive frailty are unclear.

Social media posts that portray vaping in positive social contexts shape people’s perceptions and serve to normalize vaping. Despite restrictions on depicting or promoting controlled substances, vape-related content is easily accessible on TikTok. There is a need to understand strategies used in promoting vaping on TikTok, especially among susceptible youth audiences.

Lifestyle modifications are a key part of type 2 diabetes mellitus treatment. Many patients find long-term self-management difficult, and mobile apps could be a solution. In 2010, in the United States, a mobile app was approved as an official medical device. Similar apps have entered the Japanese market but are yet to be classified as medical devices.

Internet gaming disorder among university students has become a great concern for university counsellors worldwide since the COVID-19 pandemic. The factors influencing the development of internet gaming disorder in students during the COVID-19 pandemic could be different from those before the pandemic.

Stroke is a leading cause of death and disability worldwide. Rapid and accurate diagnosis is crucial for minimizing brain damage and optimizing treatment plans.

Prompt engineering, focusing on crafting effective prompts to large language models (LLMs), has garnered attention for its capabilities at harnessing the potential of LLMs. This is even more crucial in the medical domain due to its specialized terminology and language technicity. Clinical natural language processing applications must navigate complex language and ensure privacy compliance. Prompt engineering offers a novel approach by designing tailored prompts to guide models in exploiting clinically relevant information from complex medical texts. Despite its promise, the efficacy of prompt engineering in the medical domain remains to be fully explored.