Journal of Medical Internet Research

Nationally, COVID-19 spurred the uptake of telehealth to facilitate patients’ access to medical care, especially among individuals living in geographically isolated areas. Despite the potential benefits of telehealth to address health care access barriers and enhance health outcomes, there are still disparities in the accessibility and utilization of telehealth services. Hence, identifying facilitators and barriers to telehealth should be prioritized to ensure that disparities are mitigated rather than exacerbated.

Accurate measurement of food and nutrient intake is crucial for nutrition research, dietary surveillance, and disease management, but traditional methods such as 24-hour dietary recalls, food diaries, and food frequency questionnaires are often prone to recall error and social desirability bias, limiting their reliability. With the advancement of artificial intelligence (AI), there is potential to overcome these limitations through automated, objective, and scalable dietary assessment techniques. However, the effectiveness and challenges of AI applications in this domain remain inadequately explored.

To address geographic barriers to specialty care access for services such as cardiology, the Veterans Health Administration (VA) has implemented a novel, regionalized telehealth care hub. The Clinical Resource Hub (CRH) model extends care, including cardiology services, to individuals in low-access communities across the region. Little is known, however, about the reach of such programs.

Psychoeducation is a recommended first-line intervention for transition-aged autistic youth, but it has not been previously evaluated in an internet-delivered format. SCOPE (Spectrum Computerized Psychoeducation) is an 8-week individual, internet-delivered, therapist-supported psychoeducative intervention.

Digital health interventions have gained prominence in recent years, offering innovative solutions to improve health care delivery and patient outcomes. Researchers are increasingly using qualitative approaches to explore patient experiences of using digital health interventions. Yet, the qualitative methods used in these studies can vary widely, and some methods are frequently misapplied. We highlight the methods we find most fit for purpose to explore user experiences of digital tools and propose 5 questions for researchers to use to help them select a qualitative method that best suits their research aims.

The COVID-19 pandemic prompted social distancing policies and caused misinformation that hindered in-person HIV screening for high-risk groups. Social media platforms provide additional options for voluntary counseling and testing (VCT) for HIV, overcoming these limitations. However, there is a lack of data on HIV testing recruitment through social media platforms and its outcomes during the pandemic.

Online wellness influencers (individuals dispensing unregulated health and wellness advice over social media) may have incentives to oppose traditional medical authorities. Their messaging may decrease the overall effectiveness of public health campaigns during global health crises like the COVID-19 pandemic.

Detecting early dropout from digital interventions is crucial for developing strategies to enhance user retention and improve health-related behavioral outcomes. Bricker and colleagues proposed a single metric that accurately predicted early dropout from 4 digital tobacco cessation interventions based on log-in data in the initial week after registration. Generalization of this method to additional interventions and modalities would strengthen confidence in the approach and facilitate additional research drawing on it to increase user retention.

Growth hormone deficiency (GHD) and idiopathic short stature (ISS) are the major etiologies of short stature in children. For the diagnosis of GHD and ISS, meticulous evaluations are required, including growth hormone provocation tests, which are invasive and burdensome for children. Additionally, sella magnetic resonance imaging (MRI) is necessary for assessing etiologies of GHD, which cannot evaluate hormonal secretion. Recently, radiomics has emerged as a revolutionary technique that uses mathematical algorithms to extract various features for the quantitative analysis of medical images.

The widespread adoption of information and communication technologies (ICTs) further deepens disparities in resource access, particularly among the aging population. However, the relationship between these factors and their resulting impact on cognitive abilities remains uncertain.

Many patients do not receive a comprehensive medication reconciliation, mostly owing to limited resources. We hence need an approach to identify those patients at the emergency department (ED) who are at increased risk for clinically relevant discrepancies.

To cope with the enormous burdens placed on health care systems around the world, from the strains and stresses caused by longer life expectancy to the large-scale emergency relief actions required by pandemics like COVID-19, many health care companies have been using artificial intelligence (AI) to adapt their services. Nevertheless, conceptual insights into how AI has been transforming the health care sector are still few and far between. This study aims to provide an overarching structure with which to classify the various real-world phenomena. A clear and comprehensive taxonomy will provide consensus on AI-based health care service offerings and sharpen the view of their adoption in the health care sector.