When the first smartphone was introduced a decade and a half ago, there was much excitement at its novelty and the new parameters of its function.

Over the years, smartphones have become slowly integrated into daily life, with users depending on apps for entertainment, navigation, commerce, and telemedicine. In 2023, the smartphone era has truly arrived, with a deeply established presence in modern society. 

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There are many legitimate concerns regarding the use of smartphones, including in matters relating to health (ie, whether excessive screen time brings more harm than benefit to children and whether excessive dependency on smartphones results in the blunting of cognitive function). However, due to their ubiquity, smartphones offer clinicians an unprecedented opportunity to collect comprehensive, detailed data on patient-reported outcomes. 

Real-World Data of Patients With Myasthenia Gravis 

In an innovative study published in Frontiers in Neurology, Steyaert and colleagues sought to assess the feasibility of collecting real-world data via a smartphone research platform. The goal was to understand the types of symptoms typically experienced by patients during myasthenia gravis (MG) exacerbations. 

The trial was highly decentralized, with recruits participating from across the United States. They must have a documented diagnosis of MG and associated ocular/bulbar symptoms and be 18 years of age or over. Since data collection required internet access, only participants with internet-enabled smartphones capable of hosting the study app were included. 

Selected participants were required to record data on a mobile app, where it was collected and stored securely. Among the data collected were demographic information, disease characteristics, frequency of exacerbations, the presence of comorbidities, and current medications. Participants were also invited to submit their personal feelings regarding disease control daily; patients were free to report “good/bad symptom days” and exacerbations when they occurred. 

The study enrolled 113 participants, with 82 completing the study. Researchers reported that patients who completed the study said a more severe MG phenotype, with 84% experiencing multiple exacerbations per year. The median baseline MG-Activities of Daily Living (MG-ADL) score was 14 during high symptom burden and 5 when symptom burden was low. The most commonly associated comorbidities were hypertension (n=26), depression (n=12), and type 2 diabetes (n=11). Approximately 63% of individuals were on active MG medication; 28% required treatment due to persistent disease. 

The researchers were also quick to highlight the benefits of using this novel data collection technique to achieve a snapshot of the lives of patients with MG. For example, researchers discovered that 73% of participants reported being “unsure” of their symptoms in 630 days. This demonstrates 2 points: first, symptoms of MG often fluctuate to the point that patients themselves are unsure of how they feel about disease control, and second, the use of smartphones allows for the detailed tracking of a patient’s lived experience in an effective way, akin to an online journal. 

Through the daily check-in feature on the study app, patients could report all the symptoms associated with exacerbations; among them were swallowing difficulties, impaired speech, and breathing difficulties. Because these symptoms were perceived by patients as being severe in nature, their presence often correlated with their determination of what constitutes the worsening of their clinical condition. 

“Overall, our study suggests that decentralized, smartphone-based methods to collect real-world data from MG patients are feasible and may provide enhanced visibility into the lived experience of MG patients,” the study authors concluded. 

Embracing New Technologies 

The fact that the study above managed to collect data in real time for an extended period of 3 months shows the value of incorporating new technologies in engaging with patients and study participants. By using smartphones as the medium for data collection, the researchers recruited participants from 37 US states. This stands in contrast to traditional data collection methods, such as in-person interviews and observation studies conducted in healthcare facilities. 

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The most significant sticking point to the use of smartphones and related technologies is the issue of data protection and confidentiality. Patients have a right to complete confidentiality during every healthcare encounter; however, this may be difficult to guarantee over smartphones, especially if the apps used are less sophisticated in nature and vulnerable to hacking. 

Nevertheless, clinicians (and nonclinicians) are embracing tech as a means to move past the more bureaucratic aspects of data collection. Another example of this is in an ongoing study conducted by Wang and colleagues published in JMIR Research Protocols. They sought to evaluate the effectiveness of using e-interventions to improve the mental health of students in a university. E-interventions were conducted via a mobile app called Minder. 

At the time of writing, this study is still ongoing, and results will be published shortly. However, it highlights how effective smartphones can be in terms of data collection, primarily if an individual seeks detailed data over a long period. The idea here is that smartphones can be used to collect day-to-day data, including acute health incidents, alerting clinicians should a patient’s condition deteriorate. 

As with any new technology adapted to meet healthcare needs, strong regulation must be in place to protect data, ensure confidentiality, and deter the improper sharing of personal information. Once this takes shape, clinicians and researchers can fully use this technology to benefit their patients and enrich their understanding of the patient experience. 


Steyaert S, Lootus M, Sarabu C, et al. A decentralized, prospective, observational study to collect real-world data from patients with myasthenia gravis using smartphonesFront Neurol. Published online August 1, 2023. doi:10.3389/fneur.2023.1144183

Wang AY, Vereschagin M, Richardson CG, et al. Evaluating the effectiveness of a codeveloped e-mental health intervention for university students: protocol for a randomized controlled trialJMIR Res Protoc. Published online August 30, 2023. doi:10.2196/49364