Weidan Cao

Cardiovascular disease is the leading cause of death in the United States (US). Despite the well-recognized efficacy of statins, statin discontinuation rates remain high. Statin intolerance is a major cause of statin discontinuation. To accurately diagnose statin intolerance, healthcare professionals must distinguish between statin-associated and non-statin-associated muscle symptoms, because many muscle symptoms can be unrelated to statin therapy. Patients’ feedback on muscle-related symptoms would help providers make decisions about statin treatment. Given the potential benefits and feasibility of existing apps for cardiovascular disease (CVD) management and the unmet need for an app specifically addressing statin intolerance management, the objectives of the study were 1) to describe the developmental process of a novel app designed for patients who are eligible for statin therapy to lower the risk of CVD; 2) to explore healthcare providers’ feedback of the app; and 3) to explore patients’ app usage experience.

Background: mHealth interventions can produce both intended and unintended effects. Examining these unintended effects helps to create a more complete and objective understanding of mHealth interventions and can reduce potential harm to participants. Existing studies on the unintended effects, which were published several years ago, tend to have either a general focus on health information technology or a specific focus on healthcare providers, thereby excluding other key stakeholders (e.g., patients, community health workers). Additionally, these studies did not systematically outline the causes of the unintended effects or strategies for their prevention. Objective: To address this gap, this systematic review, guided by the ecological framework, aims to systematically identify the unintended effects of mHealth interventions, create a typology for them, investigate the reasons for their occurrence, describe how they were detected, and propose ways to prevent or lessen them. Methods: Following the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines, a systematic review was performed to examine the unintended effects of health interventions that use mobile technology. Results: A total of 15 articles were included in the review. An ecological typology of mHealth Unintended Effects (mHUE) was developed, which includes 26 distinct effects (e.g., silencing and boomerang). The majority of these unintended effects (n = 20) occur at the individual level and span physical/behavioral (n = 7), psychological (n = 8), cognitive (n = 4), and financial (n = 1) domains. Three effects occur at the interpersonal level, and another three at the community/institutional level. Most of the identified effects (n = 22) were negative. Potential causes for these effects include the improper use of mHealth technology, poorly designed interventions, the application of unsuitable intervention mechanisms, or a misalignment between the untended outcomes and the socio-cultural context. Strategies and recommendations (e.g., considering the context such as cultural norms) were suggested to help prevent or reduce the unintended effects. Conclusions: The unintended effects detailed in the mHUE typology were heterogenous and context dependent. These effects can influence individuals across different domains, and also affect unintended people within the ecological system. As most of the unintended effects are negative, if they are not monitored, mHealth interventions designed to empower participants could paradoxically disempower them (e.g., decreasing self-efficacy for disease management, undermining patient control and engagement). The mHUE typology, together with the proposed recommendations and strategies, can be used as a guide to enhance the planning, design, implementation, and post-implementation evaluation on mHealth interventions. Future research should concentrate on understanding the specific mechanisms behind these unintended effects.

Background: Cardiotoxicity is a limitation of several cancer therapies and early recognition improves outcomes. Symptom-tracking mobile health (mHealth) apps are feasible and beneficial, but key elements for mHealth symptom-tracking to indicate early signs of cardiotoxicity are unknown. Objective: We explored considerations for the design of, and implementation into a large academic medical center, an mHealth symptom-tracking tool for early recognition of cardiotoxicity in patients with cancer after cancer therapy initiation. Methods: We conducted semistructured interviews of >50% of the providers (oncologists, cardio-oncologists, and radiation oncologists) who manage cancer treatment-related cardiotoxicity in the participating institution (n=11), and either interviews or co-design or both with 6 patients. Data were coded and analyzed using thematic analysis. Results: Providers indicated that there was no existing process to enable early recognition of cardiotoxicity and felt the app could reduce delays in diagnosis and lead to better patient outcomes. Signs and symptoms providers recommended for tracking included chest pain or tightness, shortness of breath, heart racing or palpitations, syncope, lightheadedness, edema, and excessive fatigue. Implementation barriers included determining who would receive symptom reports, ensuring all members of the patient’s care team (eg, oncologist, cardiologist, and primary care) were informed of the symptom reports and could collaborate on care plans, and how to best integrate the app data into the electronic health record. Patients (n=6, 100%) agreed that the app would be useful for enhanced symptom capture and education and indicated willingness to use it. Conclusions: Providers and patients agree that a patient-facing, cancer treatment-related cardiotoxicity symptom-tracking mHealth app would be beneficial. Additional studies evaluating the role of mHealth as a potential strategy for targeted early cardioprotective therapy initiation are needed.