Journal of Medical Internet Research

Abstract Advances in digital health have dramatically changed how patients engage with their health. Rather than relying solely on periodic clinical visits, patients now have access to smartphones, patient portals, wearable devices, and mobile apps that provide support for day-to-day self-care decisions. This commentary discusses the findings of Longhini et al’s systematic review and meta-analysi…

Abstract Background Chronic heart failure (CHF) significantly impairs physical function and quality of life. Although exercise-based cardiac rehabilitation represents a primary therapeutic strategy, participation rates remain low due to logistical barriers. Digital health technologies (DHTs) offer a promising alternative to deliver home-based interventions. However, evidence regarding their speci…

Abstract Background Telecommunications fraud causes financial and psychological harm, yet how individuals who experienced fraud retrospectively describe progression from initial trust to emotional escalation and reduced behavioral control remains unclear. Objective This study aimed to develop a stage-based psychological framework for telecommunications fraud and examine whether person-level cross…

Abstract Lock and colleagues showed promising effects for asynchronous virtual training in family-based treatment for anorexia nervosa paired with expert case-based consultation to promote fidelity. In this commentary, we present two promising directions by which to extend these early findings: (1) using AI to scale fidelity monitoring and prevent clinician drift over time; (2) broadening the rea…

Abstract Background Internet addiction (IA) has been consistently associated with adverse mental health outcomes, but less is known about whether adolescents with IA seek mental health support, and whether associations between help-seeking and mental health problems differ across pathways. Objective This study aimed to describe mental health help-seeking patterns across internet use and IA status…

Abstract Background Online social support, the interaction among individuals in which one helps another during difficult situations through online platforms such as online forums or social media, has proliferated as a vital tool for personal mental health care. Despite the growing usage and importance of online social support, prior studies have mainly focused on either understanding the characte…

Background: The use of social media in cancer research, patient support, and information sharing has been well documented. Objective: Using retinoblastoma as a model, we use the information provided from Twitter (subsequently rebranded X) to understand patients' treatment-seeking behavior and barriers, as well as investigate its application in research and epidemiology for rare diseases. Methods:…

Background: Chronic diseases account for nearly three-quarters of global deaths and demand continuous, personalized long-term management; yet traditional care models often fall short in delivering such sustained support. Large language models, with advanced conversational and analytical capabilities, present promising opportunities to address the problem by offering scalable, interactive support.…

Background: Patients with cancer undergoing long-term or vesicant chemotherapy frequently require peripherally inserted central catheters (PICCs). Due to the nature of ambulatory treatment administration, self-PICC management is essential for the continuation and completion of the planned treatment. Large language models offer potential for continuous patient support, but hallucinations and insuf…

Background: Chronic medical illnesses coexist with mental health challenges, negatively impacting quality of life and well-being. Compassion-based interventions have shown promise for individuals with chronic conditions, yet accessibility barriers limit their implementation. Internet-delivered formats may address these limitations while maintaining effectiveness. To our knowledge, no fully self-g…

Background: Lifestyle modification delivered through digital self-management is central to metabolic dysfunction-associated steatotic liver disease (MASLD) care, yet long-term engagement remains the threshold beyond which clinical benefit is realized. Understanding attrition requires examining both retention (dropout) and adherence (usage quality), which are often evaluated in isolation. Existing…

BACKGROUND: Overactive bladder (OAB) is a prevalent condition that substantially impairs quality of life (QoL); however, the real-world utility of standard behavioral and pharmacological therapies is often limited by poor long-term adherence. Digital interventions have emerged as a promising strategy to provide accessible and personalized support, but their overall efficacy compared with conventi…

Background: Electronic early warning/track-and-trigger systems (EW/TTS) are crucial for patient monitoring, detecting clinical deterioration (CD), and activating rapid response teams. Understanding the current level of automation in EW/TTS is essential. Objective: This study aimed to provide a comprehensive overview and critical assessment of electronic EW/TTS, including automated features, algor…

Unlabelled: Obesity in children and adolescents is rising in China and globally, with health consequences that are already evident during childhood. This Viewpoint represents the authors' interpretation of current evidence and policy experience, using China as an illustrative case for a wider international challenge. We argue that social media should be considered a modifiable obesogenic environm…

Background: Perioperative information asymmetry regarding intensive care unit (ICU) care remains a critical unmet clinical need. Traditional preoperative visits focus primarily on surgical risks but provide insufficient education about postoperative ICU stays, leading to widespread cognitive biases and anxiety among patients' family members. Virtual reality (VR) technology offers immersive, stand…

Background: Adverse drug events (ADEs) pose significant public health challenges and economic burdens. While substantial ADE information is documented in unstructured clinical notes, its extraction remains difficult due to semantic complexity. Large language models (LLMs) offer promising text comprehension capabilities but are often hindered by domain-specific hallucinations. Objective: This stud…

Background: Health care systems generate vast amounts of unstructured text, such as clinical notes, which capture nuanced patient experiences, clinical reasoning, and subtle indicators of health status. While health system research has traditionally relied upon structured data, natural language processing (NLP) enables the extraction of this rich textual information. Leveraging NLP could improve …

Background: AI is increasingly being integrated into health care, making it important to understand stakeholder preferences for AI-enabled technologies. Although discrete choice experiments (DCEs) are widely used to elicit preferences, evidence on preference attributes, willingness to pay (WTP), and reporting quality in AI-related DCEs has not been systematically synthesized. Objective: This syst…

Background: Multimodal large language models (MLLMs) have emerging potential for interpreting medical images and text, but their performance in orthopedic imaging tasks and the influence of prompt configuration remain insufficiently studied. Objective: This study aimed to evaluate the performance of commercial and open-source MLLMs for diagnosing and staging osteonecrosis of the femoral head (ONF…

Background: Vestibular disorders are common, burdensome, and frequently misdiagnosed, particularly in nonspecialist settings where history-taking is often incomplete or inconsistently structured. Digital health tools that standardize symptom elicitation could improve diagnostic triage, but most existing systems rely on static questionnaires or rule-based logic. Large language models (LLMs) offer …