Personalizing Sensor-Controlled Digital Gaming to Self-Management Needs of Older Adults with Heart Failure: A Qualitative Study

Objectives: In older persons with heart failure (HF), an inability to self-manage their disease condition can result in poor health outcomes and quality of life. With the rise in smartphone use and digital game playing among older adults, digital tools such as sensor-controlled digital games (SCDGs) can offer accessible health-promoting tools that are enjoyable and easy to use. However, designing SCDGs that are compelling and aligned with their life values and self-management needs can be challenging. This article describes a qualitative study with older adults with HF who were recruited from a cardiac rehabilitation laboratory in central Texas to identify their perceptions and expectations regarding a SCDG for HF self-management. Materials and Methods: A low-fidelity prototype that demonstrated the features of a SCDG was used to obtain the participants' perceptions about the value of SCDGs for HF self-management with respect to content, customization, flexibility, and usability through qualitative interviews. Results: We interviewed 15 patients with HF (53% women; age range, 53-90 years; 60% white). The concept of SCDGs for HF self-management was highly acceptable (80%). Participants provided suggestions for game characters, progress in the game, and game notifications and incentives. Perceived benefits included helping users track their behaviors and establish routines, become informed on strategies to manage HF, and empower themselves to take charge of their health. Conclusions: The study's findings will guide personalization of SCDG development to motivate patient engagement in HF self-management behaviors.

The potential of digital phenotyping to advance the contributions of mobile health to self-management science

Digital phenotyping consists of moment-by-moment quantification of behavioral data from individual people, typically collected passively from smartphones and other sensors. Within the evolving context of precision health, digital phenotyping can advance the use of mobile health -based self-management tools and interventions by enabling more accurate prediction for prevention and treatment, facilitating supportive strategies, and informing the development of features to motivate self-management behaviors within real-world conditions. This represents an advancement in self-management science: with digital phenotyping, nurse scientists have opportunities to tailor interventions with increased precision. In this paper, we discuss the emergence of digital phenotyping, the historical background of ecological momentary assessment, and the current state of the science of digital phenotyping, with implications for research design, computational requirements, and ethical considerations in self-management science, as well as limitations.