JMIR Formative Research

Breast cancer is the world’s most prevalent cancer. Although the 5-year survival rate for breast cancer in the United States is 91%, the stress and uncertainty of survivorship can often lead to symptoms of depression and anxiety. With nearly half of breast cancer survivors living with stress and symptoms of depression and anxiety, there are a significant number of unmet supportive care needs. New and potentially scalable approaches to meeting these supportive care needs are warranted.

Older adults might not use computers due to psychological barriers, environmental barriers such as not owning a computer or lack of Internet access, and health-related barriers such as difficulties with fine motor skills, low cognitive function, or low vision. Given the health benefits of Internet use among older adults, inadequate use of the Internet is an urgent public health issue in many countries.

As technology continues to shape the landscape of health research, the utilization of online surveys for collecting sexual health information among adolescents and young adults (AYAs) has become increasingly prevalent. However, this shift towards digital platforms brings forth a new set of challenges, particularly the infiltration of automated bots that can compromise data integrity and the reliability of survey results.

Systematic reviews and meta-analyses are important to evidence-based medicine, but the information retrieval and literature screening procedures are burdensome tasks. Rapid Medical Evidence Synthesis (RMES; Deloitte Tohmatsu Risk Advisory LLC) is a software designed to support information retrieval, literature screening, and data extraction for evidence-based medicine.

Recent advancements in virtual reality (VR) and biofeedback (BF) technologies have opened new avenues for breathing training. Breathing training has been suggested as an effective means for mental disorders, but it is difficult to master the technique at the beginning. VR-BF technologies address the problem of breathing, and visualizing breathing may facilitate the learning of breathing training. This study explores the integration of VR and BF to enhance user engagement in self-help breathing training, which is a multifaceted approach encompassing mindful breathing, guided breathing, and breath counting techniques.

Digitalization has profoundly transformed healthcare delivery, especially within primary healthcare, as a crucial avenue for providing accessible, cost-effective care. While eHealth services are frequently highlighted for improving healthcare availability and promoting equality, it is essential to recognize that digitalization can inadvertently exclude individuals who lack the prerequisites to utilize eHealth services, i.e., those with low eHealth literacy. Previous research has identified lower eHealth literacy among older individuals, those with lower educational levels, and those who use the Internet less frequently. However, in a Swedish context, only a few studies have investigated eHealth literacy.

The landscape of substance use behavior among young adults has observed rapid changes over time. Intensive longitudinal designs are ideal for examining and intervening in substance use behavior in real time but rely on high participant compliance in the study protocol, representing a significant challenge for researchers.

This paper discusses the implementation of the Whole Communities-Whole Health (WCWH) initiative, which is a community-based, longitudinal cohort study. WCWH seeks to better understand the impact of location on family health and child development while also providing support for families participating in the study. Implementing a longitudinal study that is both comprehensive in the data it is collecting and inclusive in the population it is representing is what makes WCWH extremely challenging. This paper highlights the learning process the initiative has gone through to identify effective strategies for implementing this type of research study and work toward building a new model for community-engaged research. Through iterative testing following the Plan-Do-Study-Act model, three main strategies for implementation were identified. These strategies are (1) creating a data collection schedule that balances participant burden and maintains temporality across data types; (2) facilitating multiple opportunities for qualitative and quantitative input from faculty, families, and nonparticipant community members; and (3) establishing an open-door policy for data analysis and interpretation. This paper serves as a guide and provides resources for other researchers wanting to implement a multidisciplinary and community-based cohort study.

While deep learning classifiers have shown remarkable results in detecting chest X-ray (CXR) pathologies, their adoption in clinical settings is often hampered by the lack of transparency. To bridge this gap, this study introduces the neural prototype tree (NPT), an interpretable image classifier that combines the diagnostic capability of deep learning models and the interpretability of the decision tree for CXR pathology detection.

Social media platforms have become home to numerous alternative health groups where people share health information and scientifically unproven treatments. Individuals share not only health information but also health misinformation in alternative health groups on social media. Yet, little research has been carried out to understand members of these groups. This study aims to better understand various characteristics of members in alternative health groups and the association between membership and attitudes toward vaccination and COVID-19 and influenza vaccination–related behaviors.

Smartphone-based technology has been used to enhance the delivery of health care services to the public in numerous countries.

With the increasing integration of Artificial Intelligence (AI) into various aspects of daily life, there is a growing interest among designers and practitioners in incorporating AI into their fields. In healthcare domains like art therapy, AI is also becoming a subject of exploration. However, the use of AI in art therapy is still undergoing investigation, with its benefits and challenges being actively explored.