JMIR Cancer

Therapist-guided eHealth interventions have been shown to engage users more effectively and achieve better outcomes than self-guided interventions when addressing psychological symptoms. Building on this evidence, this viewpoint aimed to describe the adaptation of iConquerFear, a self-guided eHealth intervention targeting fear of cancer recurrence, into a therapist-guided version (TG-iConquerFear) tailored specifically for colorectal cancer survivors (CRCS). The goal was to optimize patient outcomes while minimizing the need for extensive resources. The adaptation process followed the Information System Research Framework, which facilitated a systematic integration of knowledge and iterative testing. Drawing on insights from the original iConquerFear development, as well as feedback from end-users, oncologists, and therapists, we began by identifying areas for improvement. These insights formed the foundation for the first design cycle. Initial internal testing revealed the need for several adjustments to enhance the intervention. While the core concept of iConquerFear remained unchanged, we made significant modifications to improve access by optimizing the platform for mobile devices, to support adherence by expanding the exercises, and to equip therapists with tools such as reflective questions and a monitoring control panel. External field testing with five CRCS provided further validation. Participants reported a high level of acceptability, and their feedback guided additional minor to consider incorporating in future versions. This study illustrates how a self-guided eHealth intervention can be successfully adapted into a therapist-guided format for fear of cancer recurrence, tailored to meet the needs of CRCS. The described approach serves as a valuable framework for integrating therapist guidance into similar interventions, ensuring their relevance and effectiveness for targeted populations.

Decision aids improve patient and clinician decision-making but are underused and often restricted to clinical settings.

Though telehealth has been a promising avenue for engaging cancer survivors with health care and lifestyle programming, older and rural-dwelling cancer survivors may have additional challenges to accessing digital devices and tools that have not yet been described. This study aims to utilize a robust, nationally representative sample collected in 2022 to provide an updated view of digital technology use and use of technology for health in this population.

Male breast cancer (MBC) is an uncommon disease. Few studies have discussed the prognosis of MBC due to its rarity.

Breast cancer is a major health concern in various countries. Routine mammography screening has been shown to reduce breast cancer mortality, and Japan has set national targets to improve screening participation and increase public attention. However, collecting nationwide data on public attention and activity is not easy. Google Trends can reveal changes in societal interest, yet there are no reports on the relationship between Internet search volume and nationwide participation rates in Japan.

Lack of information, awareness, and misconceptions about clinical trials are major barriers to cancer clinical trial participation. Digital and social media are dominant sources of health information and offer optimal opportunities to improve public medical awareness and education by providing accurate and trust-worthy sources of health information from reliable sources. Infotainment, material intended to both entertain and inform, is an effective strategy for engaging and educating audiences that can be easily disseminated using social media and may be a novel way to improve awareness of and recruitment in clinical trials.

Healthcare system-wide outcomes from routine treatment with erlotinib and gefitinib are incompletely understood.

While patient-reported outcome measures (PROMs) are regularly incorporated into phase III clinical trials, there has been little use of PROMs in early phase trials [1]. However, the patient perspective is a vital element of fully understanding dose-toxicity and selecting an optimal dose. This viewpoint paper reviews the rationale for, and practical approach to, collection of patient-reported outcomes (PRO) data in early-phase oncology drug development, and the rationale for electronic collection.

Older adults (>65 years) are disproportionately affected by cancer at a time when Canadians are surviving cancer in an unprecedented fashion. Contrary to persistent ageist assumptions, not only do the majority of older adult cancer survivors use digital health technologies (DHTs) regularly, such technologies also serve as important sources of health information. Although the transition of older adults to cancer survivorship is connected to the availability and provision of relevant and reliable information, little evidence exists as to how they use DHTs to supplement their understanding of their unique situation to manage, and make decisions about, their ongoing cancer related concerns.

Despite the known benefits of physical activity, cancer survivors remain insufficiently active. Prior trials have adopted digital health methods, though several have been pedometer-based and enrolled mainly female, non-Hispanic White, and more highly educated survivors of breast cancer.

Breast cancer is the most common malignant tumor and the fifth leading cause of cancer death worldwide, and it exerts a huge disease burden on China. Mammography is one of the most effective methods for breast cancer screening, especially for early breast cancer diagnosis. Douyin has gained popularity as a social media platform for sharing health information; however, the quality and reliability of mammography-related video content remains unexplored.

This Viewpoint proposes a robust framework for developing a medical chatbot dedicated to radiotherapy education, emphasizing accuracy, reliability, privacy, ethics, and future innovations. By analyzing existing research, the framework evaluates chatbot performance and identifies challenges such as content accuracy, bias, and system integration. The findings highlight opportunities for advancements in natural language processing, personalized learning, and immersive technologies. When designed with a focus on ethical standards and reliability, large language model–based chatbots could significantly impact radiotherapy education and health care delivery, positioning them as valuable tools for future developments in medical education globally.