Journal of Medical Internet Research
The leading peer-reviewed journal for digital medicine and health and health care in the internet age.
Editor-in-Chief:
Gunther Eysenbach, MD, MPH, FACMI, Founding Editor and Publisher; Adjunct Professor, School of Health Information Science, University of Victoria, Canada
Impact Factor 5.8 CiteScore 14.4
Recent Articles

Information distortion in nursing records poses significant risks to patient safety and impedes the enhancement of care quality. The introduction of information technologies, such as decision support systems and predictive models, expands the possibilities for using health data but also complicates the landscape of information distortion. Only by identifying influencing factors about information distortion can care quality and patient safety be ensured.

Self-recording is an effective behavior change technology that has long been used in diverse health contexts. Recent technological advancements have broadened its applications. While previous studies have explored its role and benefits in enhancing self-awareness and informed decision-making, relatively little attention has been given to its potential to address the multidimensional nature of health with various health metrics.

Health coaching refers to the practice of health education and promotion to drive goal-directed behavioral changes and improve an individual’s well-being. Remote patient monitoring systems, which employ health coaching interventions, have been gaining interest and may aid in the management of patients with type 2 diabetes mellitus (T2DM).

An estimated 93% of adults in the United States access the internet, with up to 80% looking for health information. However, only 12% of US adults are proficient enough in health literacy to interpret health information and make informed health care decisions meaningfully. With the vast amount of health information available in multimedia formats on social media platforms such as YouTube and Facebook, there is an urgent need and a unique opportunity to design an automated approach to curate online health information using multiple criteria to meet the health literacy needs of a diverse population.

Ransomware attacks on health care provider information systems have the potential to impact patient mortality and morbidity, and event details are relayed publicly through news stories. Despite this, little research exists on how these events are depicted in the media and the subsequent impacts of these events.


The global demographic shift towards longer life expectancy and complex health needs is increasing the number of people with chronic diseases, placing pressure on health and care systems. With the digitalization of healthcare, digital Health Literacy (dHL), or the use of digital skills in health, is gaining importance. It involves navigating digital health information, using digital tools effectively, and making informed health decisions. Measuring dHL can help identify gaps and develop strategies to improve dHL and health, ensuring citizens equal opportunity to participate in a digital healthcare system. The European project “The Improving Digital Empowerment for Active and Healthy Living (IDEAHL)” with the objective to empower European Union citizens to use digital instruments to take a more active role in managing their health and well-being creates the base for this overview

Artificial intelligence (AI) has potential in promoting and supporting self-management in patients with chronic conditions. However, the development and application of current AI technologies to meet patients’ needs and improve their performance in chronic condition self-management tasks remain poorly understood. It is crucial to gather comprehensive information to guide the development and selection of effective AI solutions tailored for self-management in patients with chronic conditions.

Despite the increasing approval of antiamyloid antibodies for Alzheimer disease (AD), their clinical relevance and risk-benefit profile remain uncertain. The heterogeneity of AD and the limited availability of long-term clinical data make it difficult to establish a clear rationale for selecting one treatment over another.

An intelligence-enabled clinical decision support system (CDSS) is a computerized system that integrates medical knowledge, patient data, and clinical guidelines to assist health care providers make clinical decisions. Research studies have shown that CDSS utilization rates have not met expectations. Clinicians’ intentions and their attitudes determine the use and promotion of CDSS in clinical practice.

Due to its high incidence, prostate cancer (PC) imposes a burden on Western societies. Individualized treatment decision for nonmetastatic PC (eg, surgery, radiation, focal therapy, active surveillance, watchful waiting) is challenging. The range of options might make affected persons seek peer-to-peer counseling. Besides traditional face-to-face support groups (F2FGs), online support groups (OSGs) became important, especially during COVID-19.
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