JMIR Publications

ABSTRACT

Background:

Continuous positive airway pressure (CPAP) is the mainstay treatment for obstructive sleep apnea (OSA), but poor adherence to CPAP is a common problem. Current guidelines specify 4 hours of CPAP use per night as a cut-off point defining adequate treatment adherence. Yet, effective OSA treatment requires all-night CPAP use during the entire time spent in bed for optimally treating respiratory events and preventing adverse health effects associated with time spent without wearing CPAP. Sleep patterns can vary considerably from night to night and between individuals, making it necessary to measure CPAP adherence relative to time spent in bed. Weight loss is also an important goal for OSA patients. Tools are needed to address these clinical challenges in OSA.

Objective:

We aimed to develop an mHealth tool with weight loss and percent CPAP adherence tracking features for OSA patients.

Methods:

We used an iterative, user-centered process to design a new CPAP adherence tracking module that integrates with an existing weight loss app. A total of 37 OSA patients aged 25 to 65 years were recruited. In phase 1, patients with known OSA who were receiving CPAP treatment (n=7) tested the weight loss app to track nutrition, activity, and weight for 10 days. Participants completed a usability and acceptability survey. In phase 2, patients with known OSA who were receiving CPAP treatment (n=21) completed an online survey about their interpretations and preferences for wireframes displaying information from the CPAP tracking module. In phase 3, newly diagnosed OSA patients who were CPAP-naïve (n=9) were prescribed a CPAP machine (ResMed) and tested the app with integrated CPAP and weight loss tracking features for 3 to 4 weeks. Participants completed a usability survey and provided feedback on the app.

Results:

During phase 1, participants found the weight loss app mostly easy to use except for some difficulty searching for specific foods in the database. All found the connected devices (Fitbit activity tracker and Fitbit Aria scale) easy to use and helpful. During phase 2, participants correctly interpreted CPAP adherence success, expressed as % wear time relative to time in bed and preferred seeing clearly stated % goals. In phase 3, participants found the integrated app easy to use and requested push notifications as reminders to wear CPAP before bedtime and to sync Fitbit in the morning.

Conclusions:

We developed a customized mHealth tool that integrates a new CPAP adherence tracking module into an existing weight loss app with diet, activity, and weight tracking. Novel features are: addressing OSA-obesity comorbidity, expressing CPAP adherence goals and success as the percent wear time relative to time spent in bed and push notifications at meaningful times of day to foster adherence. Future research on the effectiveness of this tool in improving treatment adherence in OSA is warranted.