mHealth App Patient Testing and Review of Educational Materials Designed for Self-Management of Gout Patients: Descriptive Qualitative Studies

Abstract

BackgroundGout is a form of chronic arthritis caused by elevated serum uric acid (SUA) and culminates in painful gout attacks. Although effective uric acid-lowering therapies exist, adherence is low. This is partly due to the lack of support for patients to self-manage their disease. Mobile health apps have been used in the self-management of chronic conditions. However, not all are developed with patients, limiting their effectiveness.ObjectiveThe objective of our study was to collect feedback from gout patients to design an effective gout self-management app.MethodsTwo descriptive qualitative studies were conducted. In Study 1, researchers developed a short educational video and written materials about gout management, designed to be embedded into an app; 6 interviews and 1 focus group were held with gout patients to gather feedback on these materials. Usability testing in Study 2 involved additional gout patients using a pilot version of Healthy.me Gout, a gout self-management app, for 2 weeks. Following the trial, patients participated in an interview about their experiences using the app.ResultsPatients viewed the gout educational material positively, appreciating the combined use of video, text, and images. Patients were receptive to using a mobile app to self-manage their gout. Feedback about Healthy.me Gout was generally positive with patients reporting that the tracking and diary features were most useful. Patients also provided suggestions for improving the app and educational materials.ConclusionsThese studies involved patients in the development of a gout self-management app. Patients provided insight to improve the app’s presentation and usability and general lessons on useful features for chronic disease apps. Gout patients enjoyed tracking their SUA concentrations and gout attack triggers. These capabilities can be translated into self-management apps for chronic diseases that require monitoring of pathological values, medication adherence, or symptoms. Future health app design should integrate patient input and be developed iteratively to address concerns identified by patients.

Association Between User Engagement of a Mobile Health App for Gout and Improvements in Self-Care Behaviors: Randomized Controlled Trial

“…It is becoming increasingly clear in the mHealth literature that the design process needs to be user-centered in order to produce the best outcomes for patients [42-44]. Work in this area is currently underway by Nguyen and colleagues [45], who have recently developed a gout self-management app. User-centered design has been tested in apps for type 1 diabetes, heart health, and asthma and has shown favorable outcomes in the preliminary stages [44].…”

eHealth Delivery of Educational Content Using Selected Visual Methods to Improve Health Literacy on Lifestyle-Related Diseases: Literature Review

“…A total of 15 studies [ 27 - 29 , 31 , 32 , 35 - 39 , 41 - 44 , 48 ] aimed to manage a disease, including diabetes (n=6) [ 27 , 31 , 35 , 38 , 42 , 43 ] (1 study targeted type 1 diabetes [ 42 ] and the remainder targeted type 2 diabetes [ 27 , 31 , 35 , 43 , 47 ]), heart failure (n=3) [ 41 , 44 , 48 ], cardiovascular disease (n=2) [ 28 , 32 ], stroke (n=2) [ 36 , 37 ], gout (n=1) [ 29 ], chronic obstructive pulmonary disease (n=1) [ 38 ], and osteoarthritis of the knee (n=1) [ 39 ].…”

“…Studies used a number of measured values: body weight [ 27 , 29 , 30 , 33 , 41 , 44 , 48 ], waist circumference [ 27 , 30 ], blood pressure [ 27 , 44 ], oxygen usage [ 38 , 44 ], hemoglobin A 1c [ 27 , 38 , 42 ], serum uric acid [ 29 ], and knowledge about health conditions (eg, diabetes knowledge, self-efficacy score, cardiovascular health knowledge, smoking knowledge) [ 31 , 34 , 39 , 40 , 42 , 43 ]. Studies also investigated behavioral changes, smoking attitude [ 18 , 34 ], nutrition [ 33 , 35 , 38 , 40 ], physical activity [ 33 , 35 , 38 , 41 ], stress [ 33 ], medication [ 32 , 38 ], specific health behavior [ 27 ], and usability and acceptability of the intervention [ 30 , 36 ].…”

“…User satisfaction was evaluated for the intervention itself and for opinions on future development in 16 studies [ 18 , 30 - 32 , 34 - 37 , 39 , 41 , 42 , 44 - 48 ]. The 14 apps [ 18 , 28 - 32 , 34 , 37 , 39 , 41 , 42 , 44 , 45 , 48 ] receiving the highest satisfaction and appreciation ratings included those providing educational content (about diseases [ 30 - 32 , 34 , 39 , 41 , 48 ], through a diary program [ 29 , 42 ], and in game content [ 18 , 45 , 46 ]) using pictures, graphics [ 27 , 29 , 30 , 34 , 37 , 42 , 44 ], videos [ 18 , 27 - 31 , 33 - 37 , 39 , 41 - 45 , 47 ], icons, drawings, animations [ 47 ], and an avatar [ 48 ]. Only one app providing educational video [ 30 ] was considered unacceptable because the process of downloading and viewing the video was too difficult or took too much time.…”

“…The included studies are characterized in Multimedia Appendix 2. Of the 23 papers we explored, 13 [18,[27][28][29][30][31][32][33][34][35][36][37][38] were conducted in 2 stages, namely app development followed by intervention research. Two studies conducted randomized controlled trials (RCTs) [27,39], of which 1 [27] described the study protocol only.…”