Integrating Mobile Fitness Trackers Into the Practice of Medicine

Supervised and Individualized Lifestyle Medicine Therapy of a Patient after Myocardial Infarction—Case Study

Background: In the rehabilitation of patients with cardiovascular disease (CVD) and after myocardial infarction (MI), lifestyle modifications—exercise and nutritional therapy, smoking cessation, stress management—are essential and have a major, long-term impact on the overall health of patients. Methods: After MI and acute primary care, a lifestyle medicine team (medical doctors, dietitian, exercise physiologist) supervised the therapy of a 40 year-old male patient for 12 months. The program included assessments, regular medical controls, personalized diet, and exercise therapy monitored by a heart rate watch. Results: Gradual and continuous weight loss, major reduction in medication and significant improvement in fitness level, blood glucose level, and cardiac function were measured after the program. Due to these positive changes, the patient’s overall health improved to an even better level than before his MI. Conclusion: The results of this program highlight the benefits and importance of the personalized therapy and the lifestyle medicine team approach in the rehabilitation of CVD patients. Individualized and supervised lifestyle therapy should be part of the primary hospital care of CVD patients lead by medical doctors and supported by other health care providers.

The Role of Individualized Exercise Prescription in Obesity Management-Case Study

Introduction: Obesity, or adiposity-based chronic disease (ABCD), is one of the most common health risk factors nowadays. Regular exercise—part of complex lifestyle medicine program—is effective treatment for obesity but is still underestimated. Monitoring andindividualization by an exercise professional is needed to define the accurate dose effect. Materials and Methods: The 30-week lifestyle change program of a 65-year-old male patient (body mass index (BMI) 43.8 kg/m²) was followed by a medical doctor, exercise physiologist, and nutritionist. Over regular controls and blood tests, each training activity was measured with a heart rate monitor watch, and a diet diary was written. Results: Bodyweight decreased by 24.1 kg (18.4%) and BMI to 35.8 kg/m². Decreased resting heart rate (from 72 bpm to 63 bpm), diastolic blood pressure (from 72 mmHg to 67 mmHg), and increased systolic blood pressure (from 126 mmHg to 135 mmHg) were reported, besides the reduction in antihypertensive and antidiabetic medicines. Blood test results and fitness level improved, and daily steps and time spent training increased. Conclusions: Lifestyle medicine with professional support is an effective and long-term treatment for ABCD. Individualized exercise and nutritional therapy are essential, and wearable technology with telemedicine consultation also has an important role.

Future Mobile Device Usage, Requirements, and Expectations of Physicians in German University Hospitals: Web-Based Survey

Background

The use of mobile devices in hospital care constantly increases. However, smartphones and tablets have not yet widely become official working equipment in medical care. Meanwhile, the parallel use of private and official devices in hospitals is common. Medical staff use smartphones and tablets in a growing number of ways. This mixture of devices and how they can be used is a challenge to persons in charge of defining strategies and rules for the usage of mobile devices in hospital care.

Objective

Therefore, we aimed to examine the status quo of physicians’ mobile device usage and concrete requirements and their future expectations of how mobile devices can be used.

Methods

We performed a web-based survey among physicians in 8 German university hospitals from June to October 2019. The online survey was forwarded by hospital management personnel to physicians from all departments involved in patient care at the local sites.

Results

A total of 303 physicians from almost all medical fields and work experience levels completed the web-based survey. The majority regarded a tablet (211/303, 69.6%) and a smartphone (177/303, 58.4%) as the ideal devices for their operational area. In practice, physicians are still predominantly using desktop computers during their worktime (mean percentage of worktime spent on a desktop computer: 56.8%; smartphone: 12.8%; tablet: 3.6%). Today, physicians use mobile devices for basic tasks such as oral (171/303, 56.4%) and written (118/303, 38.9%) communication and to look up dosages, diagnoses, and guidelines (194/303, 64.0%). Respondents are also willing to use mobile devices for more advanced applications such as an early warning system (224/303, 73.9%) and mobile electronic health records (211/303, 69.6%). We found a significant association between the technical affinity and the preference of device in medical care (χs2=53.84, P<.001) showing that with increasing self-reported technical affinity, the preference for smartphones and tablets increases compared to desktop computers.

Conclusions

Physicians in German university hospitals have a high technical affinity and positive attitude toward the widespread implementation of mobile devices in clinical care. They are willing to use official mobile devices in clinical practice for basic and advanced mobile health uses. Thus, the reason for the low usage is not a lack of willingness of the potential users. Challenges that hinder the wider adoption of mobile devices might be regulatory, financial and organizational issues, and missing interoperability standards of clinical information systems, but also a shortage of areas of application in which workflows are adapted for (small) mobile devices.

Provider Perspectives on Integrating Sensor-Captured Patient-Generated Data in Mental Health Care

The increasing ubiquity of health sensing technology holds promise to enable patients and health care providers to make more informed decisions based on continuously-captured data. The use of sensor-captured patient-generated data (sPGD) has been gaining greater prominence in the assessment of physical health, but we have little understanding of the role that sPGD can play in mental health. To better understand the use of sPGD in mental health, we interviewed care providers in an intensive treatment program (ITP) for veterans with post-traumatic stress disorder. In this program, patients were given Fitbits for their own voluntary use. Providers identified a number of potential benefits from patients' Fitbit use, such as patient empowerment and opportunities to reinforce therapeutic progress through collaborative data review and interpretation. However, despite the promise of sensor data as offering an "objective" view into patients' health behavior and symptoms, the relationships between sPGD and therapeutic progress are often ambiguous. Given substantial subjectivity involved in interpreting data from commercial wearables in the context of mental health treatment, providers emphasized potential risks to their patients and were uncertain how to adjust their practice to effectively guide collaborative use of the FitBit and its sPGD. We discuss the implications of these findings for designing systems to leverage sPGD in mental health care.

Behavior Change Techniques Incorporated in Fitness Trackers: Content Analysis

Background

The use of fitness trackers as tools of self-management to promote physical activity is increasing. However, the content of fitness trackers remains unexplored.

Objective

The aim of this study was to use the Behavior Change Technique Taxonomy v1 (BCTTv1) to examine if swim-proof fitness trackers below Aus $150 (US$ 105) incorporate behavior change techniques (BCTs) that relate to self-management strategies to increase physical activity and reduce sedentary behavior and to determine if content of the fitness trackers correspond to physical activity guidelines.

Methods

A total of two raters used the BCTTv1 to code 6 fitness trackers that met the inclusion criteria. The inclusion criteria were the ability to track activity, be swim proof, be compatible with Android and Apple operating systems, and cost below Aus $150.

Results

All fitness trackers contained BCTs known to promote physical activity, with the most frequently used BCTs overlapping with self-management strategies, including goal setting, self-monitoring, and feedback on behavior. Fitbit Flex 2 (Fitbit Inc) contained the most BCTs at 20. Huawei Band 2 Pro (Huawei Technologies) and Misfit Shine 2 (Fossil Group) contained the least BCTs at 11.

Conclusions

Fitness trackers contain evidence-based BCTs that overlap with self-management strategies, which have been shown to increase physical activity and reduce sedentary behavior. Fitness trackers offer the prospect for physical activity interventions that are cost-effective and easily accessed by a wide population.

Health App Use Among US Mobile Phone Owners: A National Survey

BACKGROUND

Mobile phone health apps may now seem to be ubiquitous, yet much remains unknown with regard to their usage. Information is limited with regard to important metrics, including the percentage of the population that uses health apps, reasons for adoption/nonadoption, and reasons for noncontinuance of use.

OBJECTIVE

The purpose of this study was to examine health app use among mobile phone owners in the United States.

METHODS

We conducted a cross-sectional survey of 1604 mobile phone users throughout the United States. The 36-item survey assessed sociodemographic characteristics, history of and reasons for health app use/nonuse, perceived effectiveness of health apps, reasons for stopping use, and general health status.

RESULTS

A little over half (934/1604, 58.23%) of mobile phone users had downloaded a health-related mobile app. Fitness and nutrition were the most common categories of health apps used, with most respondents using them at least daily. Common reasons for not having downloaded apps were lack of interest, cost, and concern about apps collecting their data. Individuals more likely to use health apps tended to be younger, have higher incomes, be more educated, be Latino/Hispanic, and have a body mass index (BMI) in the obese range (all P<.05). Cost was a significant concern among respondents, with a large proportion indicating that they would not pay anything for a health app. Interestingly, among those who had downloaded health apps, trust in their accuracy and data safety was quite high, and most felt that the apps had improved their health. About half of the respondents (427/934, 45.7%) had stopped using some health apps, primarily due to high data entry burden, loss of interest, and hidden costs.

CONCLUSIONS

These findings suggest that while many individuals use health apps, a substantial proportion of the population does not, and that even among those who use health apps, many stop using them. These data suggest that app developers need to better address consumer concerns, such as cost and high data entry burden, and that clinical trials are necessary to test the efficacy of health apps to broaden their appeal and adoption.