Journal of Medical Internet Research

Recent attempts at clinical phenotyping for sepsis have shown promise in identifying groups of patients with distinct treatment responses. Nonetheless, the replicability and actionability of these phenotypes remain an issue because the patient trajectory is a function of both the patient’s physiological state and the interventions they receive.

Covidom was a telemonitoring solution for home monitoring of patients with mild to moderate COVID-19, deployed in March 2020 in the Greater Paris area in France to alleviate the burden on the health care system. The Covidom solution included a free mobile application with daily monitoring questionnaires and a regional control center to quickly handle patient alerts, including dispatching emergency medical services when necessary.

Artificial intelligence (AI) can improve the health and well-being of older adults and has the potential to assist and improve nursing care. In recent years, research in this area has been increasing. Therefore, it is necessary to understand the status of development and main research hotspots and identify the main contributors and their relationships in the application of AI in geriatric care via bibliometric analysis.

HIV incidence rates have increased in adolescent men who have sex with men (AMSM) and adolescent transgender women (ATGW). Thus, it is essential to promote access to HIV prevention, including pre-exposure prophylaxis (PrEP), among these groups. Moreover, using artificial intelligence and online social platforms to create demand and access to health care services are essential tools for adolescents and youth.

In November 2022, OpenAI publicly launched its large language model (LLM), ChatGPT, and reached the milestone of having over 100 million users in only 2 months. LLMs have been shown to be useful in a myriad of health care–related tasks and processes. In this paper, I argue that attention to, public access to, and debate about LLMs have initiated a wave of products and services using generative artificial intelligence (AI), which had previously found it hard to attract physicians. This paper describes what AI tools have become available since the beginning of the ChatGPT revolution and contemplates how it they might change physicians’ perceptions about this breakthrough technology.

The Depression Anxiety Stress Scale 21 (DASS-21) is a mental health screening tool with conflicting studies regarding its factor structure. No studies have yet attempted to develop a computer adaptive test (CAT) version of it.

Healthcare-associated infections have become a serious public health problem. Various types of information systems have begun to be applied in hospital infection prevention and control (IPC) practice. Clinicians are the key users of these systems, but few studies have assessed the use of infection prevention and control information systems (IPCISs) from their perspective.

Ecological momentary assessment (EMA) is increasingly used to evaluate behavioral health processes over extended time periods. The validity of EMA for providing representative, real-world data with high temporal precision is threatened to the extent that EMA compliance drops over time.

Artificial Intelligence (AI) represents a significant milestone in health care's digital transformation. However, traditional health care education and training often lack digital competencies. To promote safe and effective AI implementation, health care professionals must acquire basic knowledge of machine learning and neural networks, critical evaluation of data sets, integration within clinical workflows, bias control, and human-machine interaction in clinical settings. Additionally, they should understand the legal and ethical aspects of digital health care and the impact of AI adoption. Misconceptions and fears about AI systems could jeopardize its real-life implementation. However, there are multiple barriers to promoting electronic health literacy, including time constraints, overburdened curricula, and the shortage of capacitated professionals. To overcome these challenges, partnerships among developers, professional societies, and academia are essential. Integrating specialists from different backgrounds, including data specialists, lawyers, and social scientists, can significantly contribute to combating digital illiteracy and promoting safe AI implementation in health care.

 Therapeutic relational connection (TRC) in telehealth is a new concept that refers to the intentional use of relationship connection between health care providers and their patients as both parties work toward a therapeutic aim. It has been demonstrated that TRC positively affects patient-centered outcomes including adherence, self-management, and satisfaction with care. What is not known are best practices for establishing TRC during telehealth visits. The rapid emergence of telehealth during the COVID-19 pandemic has identified a number of challenges. These challenges include lack of human contact, distance creating mistrust, the inability to rely on nonverbal communication, and a sense of depersonalization. Training for health care providers in these interpersonal communication skills needed to establish TRC during telehealth visits is needed.

Resources are increasingly spent on artificial intelligence (AI) solutions for medical applications aiming to improve diagnosis, treatment, and prevention of diseases. While the need for transparency and reduction of bias in data and algorithm development has been addressed in past studies, little is known about the knowledge and perception of bias among AI developers.

Self-medication counseling in community pharmacies plays a crucial role in health care. Counseling advice should therefore be evidence-based. Web-based information and databases are commonly used as electronic information sources. EVInews is a self-medication–related information tool consisting of a database and monthly published newsletters for pharmacists. Little is known about the quality of pharmacists’ electronic information sources for evidence-based self-medication counseling.