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Journal Description

JMIR mHealth and uHealth (JMU, ISSN 2291-5222) is a sister journal of JMIR, the leading eHealth journal. JMIR mHealth and uHealth is indexed in PubMed, PubMed Central, Scopus, and Science Citation Index Expanded (SCIE), and in June 2018 received an Impact Factor of 4.541, which ranks the journal #2 (behind JMIR) out of 25 journals in the medical informatics category indexed by the Science Citation Index Expanded (SCIE) by Thomson Reuters/Clarivate

The journal focusses on health and biomedical applications in mobile and tablet computing, pervasive and ubiquitous computing, wearable computing and domotics.

JMIR mHealth and uHealth publishes since 2013 and was the first mhealth journal in Pubmed. It publishes even faster and has a broader scope with including papers which are more technical or more formative/developmental than what would be published in the Journal of Medical Internet Research

JMIR mHealth and uHealth features a rapid and thorough peer-review process, professional copyediting, professional production of PDF, XHTML, and XML proofs.

JMIR mHealth and uHealth adheres to the same quality standards as JMIR and all articles published here are also cross-listed in the Table of Contents of JMIR, the worlds' leading medical journal in health sciences / health services research and health informatics.


Recent Articles:

  • Source: Image created by the Authors; Copyright: The Authors; URL:; License: Licensed by JMIR.

    Validity Evaluation of the Fitbit Charge2 and the Garmin vivosmart HR+ in Free-Living Environments in an Older Adult Cohort


    Background: Few studies have investigated the validity of mainstream wrist-based activity trackers in healthy older adults in real life, as opposed to laboratory settings. Objective: This study explored the performance of two wrist-worn trackers (Fitbit Charge 2 and Garmin vivosmart HR+) in estimating steps, energy expenditure, moderate-to-vigorous physical activity (MVPA) levels, and sleep parameters (total sleep time [TST] and wake after sleep onset [WASO]) against gold-standard technologies in a cohort of healthy older adults in a free-living environment. Methods: Overall, 20 participants (>65 years) took part in the study. The devices were worn by the participants for 24 hours, and the results were compared against validated technology (ActiGraph and New-Lifestyles NL-2000i). Mean error, mean percentage error (MPE), mean absolute percentage error (MAPE), intraclass correlation (ICC), and Bland-Altman plots were computed for all the parameters considered. Results: For step counting, all trackers were highly correlated with one another (ICCs>0.89). Although the Fitbit tended to overcount steps (MPE=12.36%), the Garmin and ActiGraph undercounted (MPE 9.36% and 11.53%, respectively). The Garmin had poor ICC values when energy expenditure was compared against the criterion. The Fitbit had moderate-to-good ICCs in comparison to the other activity trackers, and showed the best results (MAPE=12.25%), although it underestimated calories burned. For MVPA levels estimation, the wristband trackers were highly correlated (ICC=0.96); however, they were moderately correlated against the criterion and they overestimated MVPA activity minutes. For the sleep parameters, the ICCs were poor for all cases, except when comparing the Fitbit with the criterion, which showed moderate agreement. The TST was slightly overestimated with the Fitbit, although it provided good results with an average MAPE equal to 10.13%. Conversely, WASO estimation was poorer and was overestimated by the Fitbit but underestimated by the Garmin. Again, the Fitbit was the most accurate, with an average MAPE of 49.7%. Conclusions: The tested well-known devices could be adopted to estimate steps, energy expenditure, and sleep duration with an acceptable level of accuracy in the population of interest, although clinicians should be cautious in considering other parameters for clinical and research purposes.

  • Source: Freepik; Copyright: nensuria; URL:; License: Licensed by JMIR.

    Feedback on Physical Activity Through a Wearable Device Connected to a Mobile Phone App in Patients With Metabolic Syndrome: Pilot Study


    Background: Little is known of the effect of wearable devices on metabolic impairments in clinical settings. We hypothesized that a wearable device that can monitor and provide feedback on physical activity may help resolve metabolic syndrome. Objective: This study aimed to examine the objective effects of the use of these devices on metabolic syndrome resolution. Methods: Patients diagnosed with metabolic syndrome were recruited. Participants were prescribed regular walking using a wearable device (Coffee WALKIE +Dv.3, GC Healthcare CI, Korea) on their wrist for 12 weeks. Participants received self-feedback on the amount of their exercise through an app on their mobile phone. The information on physical activities of the participants was uploaded automatically to a website. Thus, a trained nurse could provide individuals with feedback regarding the physical activity via telephone consultation on alternate weeks. Blood pressure (BP), body composition, fasting plasma glucose, and lipid profiles were recorded. The primary outcome was metabolic syndrome resolution. The secondary outcome was an improvement in the components of metabolic impairment. Results: Of the 53 participants recruited, 20 participants with a median age of 46 (range 36-50) years completed the trial. There was no significant difference in the amount of calorie expenditure at weeks 4, 8, and 12. After 12 weeks, metabolic syndrome was resolved in 9 of 20 participants (45%), and the mean number of metabolic impairment components per person decreased from 3.4 to 2.9. Particularly, the mean systolic and diastolic BP decreased from mean 136.6 (SD 18.5) mm Hg to mean 127.4 (SD 19.5) mm Hg and from mean 84.0 (SD 8.1) mm Hg to mean 77.4 (SD 14.4) mm Hg (both P=.02), respectively. Conclusions: This study found that a 12-week intervention via feedback, based on a wearable physical activity monitor, helped metabolic syndrome patients to be more engaged in regular walking and it improved impaired metabolic components, especially in BP. However, some practical challenges regarding patients’ adherence and sustained engagement were observed.

  • Source: Image created by the Authors; Copyright: The Authors; URL:; License: Creative Commons Attribution (CC-BY).

    Understanding the Use of Smartphone Apps for Health Information Among Pregnant Chinese Women: Mixed Methods Study


    Background: Hospital-based health promotion resources to assist pregnant women in adopting a healthy lifestyle and optimizing gestational weight gain are important, but with limited effects. Increasingly, women are using mobile apps to access health information during the antenatal period. Objective: The aims of the study were to investigate app-usage by Chinese women during pregnancy and to gain a better understanding of their views and attitudes toward apps containing health information. Methods: A mixed methods study design was applied. Study participants were recruited from 2 maternity hospitals in Shanghai, China, between March and July 2018. A self-administered Web-based survey was conducted with 535 pregnant Chinese women on their sources of health information and reasons for using apps during pregnancy. A total of 4 semistructured focus groups were also conducted with the pregnant women (n=28). Results: The use of pregnancy-related apps and the internet was common among the respondents. Almost half of the women had used pregnancy-related apps. Specifically, the use of apps for health information declined as pregnancy progressed from 70% (35/50) in the first trimester to 41.3% (143/346) in the third trimester. The main reason for using an app was to monitor fetal development (436/535, 81.5%), followed by learning about nutrition and recording diet in pregnancy (140/535, 26.2%). The women found that the apps were useful and convenient and can support lifestyle modifications during pregnancy. However, some apps also contained misinformation or incorrect information that could cause anxiety as reported by the participants. Many women expressed the need for developing an app containing evidence-based, well-informed, and tailored health information to support them during pregnancy. Conclusions: The study suggests that apps were widely used by many Chinese women during pregnancy to monitor fetal development, to obtain diet and physical activity information, and to track their body changes. The women highly appreciated the evidence-based information, expert opinions, and tailored advice available on apps. Smartphone apps have the potential to deliver health information for pregnant women.

  • Source: Shutterstock Inc; Copyright: Samuel Borges Photography; URL:; License: Licensed by the authors.

    A Medication Adherence App for Children With Sickle Cell Disease: Qualitative Study


    Background: Young people with sickle cell disease (SCD) often demonstrate low medication adherence and low motivation for effectively self-managing their condition. The growing sophistication of mobile phones and their popularity among young people render them a promising platform for increasing medication adherence. However, so far, few apps targeting SCD have been developed from research with the target population and underpinned with theory and evidence. Objective: The aim of this study was to develop a theory-and-evidence-based medication adherence app to support children and adolescents with SCD. Methods: The Behavior Change Wheel (BCW), a theoretically based intervention development framework, along with a review of the literature, 10 interviews with children and adolescents with SCD aged between 12 and 18 years, and consultation with experts informed app development. Thematic analysis of interviews provided relevant theoretical and evidence-based components to underpin the design and development of the app. Results: Findings suggested that some patients had lapses in memory for taking their medication (capability); variation in beliefs toward the effectiveness of medication and confidence in self-managing their condition (motivation); a limited time to take medication; and barriers and enablers within the changing context of social support during the transition into adulthood (opportunity). Steps were taken to select the appropriate behavioral change components (involving behavior change techniques [BCTs] such as information on antecedents, prompts/cues; self-monitoring of the behavior; and social support) and translate them into app features designed to overcome these barriers to medication adherence. Conclusions: Patients with SCD have complex barriers to medication adherence necessitating the need for comprehensive models of behavior change to analyze the problem. Children and adolescents require an app that goes beyond simple medication reminders and takes into account the patient’s beliefs, emotions, and environmental barriers to medication adherence.

  • Apple Watch user records ECG and checks for atrial fibrillation. Source: Image created by the Authors; Copyright: The Authors; URL:; License: Creative Commons Attribution (CC-BY).

    Accuracy of mHealth Devices for Atrial Fibrillation Screening: Systematic Review


    Background: Mobile health (mHealth) devices can be used for the diagnosis of atrial fibrillation. Early diagnosis allows better treatment and prevention of secondary diseases like stroke. Although there are many different mHealth devices to screen for atrial fibrillation, their accuracy varies due to different technological approaches. Objective: We aimed to systematically review available studies that assessed the accuracy of mHealth devices in screening for atrial fibrillation. The goal of this review was to provide a comprehensive overview of available technologies, specific characteristics, and accuracy of all relevant studies. Methods: PubMed and Web of Science databases were searched from January 2014 until January 2019. Our systematic review was performed according to the Preferred Reporting Items for Systematic Review and Meta-Analyses. We restricted the search by year of publication, language, noninvasive methods, and focus on diagnosis of atrial fibrillation. Articles not including information about the accuracy of devices were excluded. Results: We found 467 relevant studies. After removing duplicates and excluding ineligible records, 22 studies were included. The accuracy of mHealth devices varied among different technologies, their application settings, and study populations. We described and summarized the eligible studies. Conclusions: Our systematic review identifies different technologies for screening for atrial fibrillation with mHealth devices. A specific technology’s suitability depends on the underlying form of atrial fibrillation to be diagnosed. With the suitable use of mHealth, early diagnosis and treatment of atrial fibrillation are possible. Successful application of mHealth technologies could contribute to significantly reducing the cost of illness of atrial fibrillation.

  • Source: Freepik; Copyright: freepik; URL:; License: Licensed by JMIR.

    Estimating Maximal Oxygen Uptake From Daily Activity Data Measured by a Watch-Type Fitness Tracker: Cross-Sectional Study


    Background: Cardiorespiratory fitness (CRF), an important index of physical fitness, is the ability to inhale and provide oxygen to the exercising muscle. However, despite its importance, the current gold standard for measuring CRF is impractical, requiring maximal exercise from the participants. Objective: This study aimed to develop a convenient and practical estimation model for CRF using data collected from daily life with a wristwatch-type device. Methods: A total of 191 subjects, aged 20 to 65 years, participated in this study. Maximal oxygen uptake (VO2 max), a standard measure of CRF, was measured with a maximal exercise test. Heart rate (HR) and physical activity data were collected using a commercial wristwatch-type fitness tracker (Fitbit; Fitbit Charge; Fitbit) for 3 consecutive days. Maximal activity energy expenditure (aEEmax) and slope between HR and physical activity were calculated using a linear regression. A VO2 max estimation model was built using multiple linear regression with data on age, sex, height, percent body fat, aEEmax, and the slope. The result was validated with 2 different cross-validation methods. Results: aEEmax showed a moderate correlation with VO2 max (r=0.50). The correlation coefficient for the multiple linear regression model was 0.81, and the SE of estimate (SEE) was 3.518 mL/kg/min. The regression model was cross-validated through the predicted residual error sum of square (PRESS). The PRESS correlation coefficient was 0.79, and the PRESS SEE was 3.667 mL/kg/min. The model was further validated by dividing it into different subgroups and calculating the constant error (CE) where a low CE showed that the model does not significantly overestimate or underestimate VO2 max. Conclusions: This study proposes a CRF estimation method using data collected by a wristwatch-type fitness tracker without any specific protocol for a wide range of the population.

  • Source: Image created by the Authors; Copyright: The Authors; URL:; License: Licensed by JMIR.

    Deep Learning Approaches to Detect Atrial Fibrillation Using Photoplethysmographic Signals: Algorithms Development Study


    Background: Wearable devices have evolved as screening tools for atrial fibrillation (AF). A photoplethysmographic (PPG) AF detection algorithm was developed and applied to a convenient smartphone-based device with good accuracy. However, patients with paroxysmal AF frequently exhibit premature atrial complexes (PACs), which result in poor unmanned AF detection, mainly because of rule-based or handcrafted machine learning techniques that are limited in terms of diagnostic accuracy and reliability. Objective: This study aimed to develop deep learning (DL) classifiers using PPG data to detect AF from the sinus rhythm (SR) in the presence of PACs after successful cardioversion. Methods: We examined 75 patients with AF who underwent successful elective direct-current cardioversion (DCC). Electrocardiogram and pulse oximetry data over a 15-min period were obtained before and after DCC and labeled as AF or SR. A 1-dimensional convolutional neural network (1D-CNN) and recurrent neural network (RNN) were chosen as the 2 DL architectures. The PAC indicator estimated the burden of PACs on the PPG dataset. We defined a metric called the confidence level (CL) of AF or SR diagnosis and compared the CLs of true and false diagnoses. We also compared the diagnostic performance of 1D-CNN and RNN with previously developed AF detectors (support vector machine with root-mean-square of successive difference of RR intervals and Shannon entropy, autocorrelation, and ensemble by combining 2 previous methods) using 10 5-fold cross-validation processes. Results: Among the 14,298 training samples containing PPG data, 7157 samples were obtained during the post-DCC period. The PAC indicator estimated 29.79% (2132/7157) of post-DCC samples had PACs. The diagnostic accuracy of AF versus SR was 99.32% (70,925/71,410) versus 95.85% (68,602/71,570) in 1D-CNN and 98.27% (70,176/71,410) versus 96.04% (68,736/71,570) in RNN methods. The area under receiver operating characteristic curves of the 2 DL classifiers was 0.998 (95% CI 0.995-1.000) for 1D-CNN and 0.996 (95% CI 0.993-0.998) for RNN, which were significantly higher than other AF detectors (P<.001). If we assumed that the dataset could emulate a sufficient number of patients in training, both DL classifiers improved their diagnostic performances even further especially for the samples with a high burden of PACs. The average CLs for true versus false classification were 98.56% versus 78.75% for 1D-CNN and 98.37% versus 82.57% for RNN (P<.001 for all cases). Conclusions: New DL classifiers could detect AF using PPG monitoring signals with high diagnostic accuracy even with frequent PACs and could outperform previously developed AF detectors. Although diagnostic performance decreased as the burden of PACs increased, performance improved when samples from more patients were trained. Moreover, the reliability of the diagnosis could be indicated by the CL. Wearable devices sensing PPG signals with DL classifiers should be validated as tools to screen for AF.

  • Source: Pexels; Copyright: Rodolfo Quirós; URL:; License: Licensed by JMIR.

    Mobile Health Adoption in Mental Health: User Experience of a Mobile Health App for Patients With an Eating Disorder


    Background: Despite the worldwide growth in mobile health (mHealth) tools and the possible benefits for both patients and health care providers, the overall adoption levels of mHealth tools by health professionals remain relatively low. Objective: This study aimed (1) to investigate attitudes of health care providers and mHealth experts toward mHealth tools in the health context in general, and this study aimed (2) to test the acceptability and feasibility of a specific mHealth tool for patients with an eating disorder (ED), called TCApp, among patients and ED specialists. Methods: To this purpose, we conducted an explorative qualitative study with 4 in-depth group discussions with several groups of stakeholders: our first focus group was conducted with 11 experts on mHealth from the Catalan Association of Health Entities; the second focus group included 10 health care professionals from the Spanish College of Doctors of Barcelona; the third focus group involved 9 patients with an ED who had used the TCApp over a 12-week period, and the fourth and last focus group involved 8 ED specialists who had monitored such ED patients on the Web. Results: The focus groups showed that health care providers and mHealth experts reported barriers for mHealth adoption more often than facilitators, indicating that mHealth techniques are difficult to obtain and use. Most barriers were attributed to external factors relating to the human or organizational environment (ie, lack of time because of workload, lack of direct interest on a legislative or political level) rather than being attributed to internal factors relating to individual obstacles. The results of the mHealth intervention study indicate that the TCApp was considered as easy to use and useful, although patients and the ED specialists monitoring them on the Web reported different adoption problems, such as the inability to personalize the app, a lack of motivational and interactive components, or difficulties in adhering to the study protocol. Conclusions: In general, this paper indicates that both health professionals and patients foresee difficulties that need to be addressed before comprehensive adoption and usage of mHealth techniques can be effectively implemented. Such findings are in line with previous studies, suggesting that although they acknowledge their possible benefits and cost-effectiveness, health care providers are quite resistant and conservative about integrating mHealth technologies in their daily practice.

  • Source: Pxhere; Copyright: Pxhere; URL:; License: Public Domain (CC0).

    Factors Determining Patients’ Choice Between Mobile Health and Telemedicine: Predictive Analytics Assessment


    Background: The solution to the growing problem of rural residents lacking health care access may be found in the use of telemedicine and mobile health (mHealth). Using mHealth or telemedicine allows patients from rural or remote areas to have better access to health care. Objective: The objective of this study was to understand factors influencing the choice of communication medium for receiving care, through the analysis of mHealth versus telemedicine encounters with a virtual urgent clinic. Methods: We conducted a postdeployment evaluation of a new virtual health care service, Virtual Urgent Clinic, which uses mHealth and telemedicine modalities to provide patient care. We used a multinomial logistic model to test the significance and predictive power of a set of features in determining patients’ preferred method of telecare encounters—a nominal outcome variable of two levels (mHealth and telemedicine). Results: Postdeployment, 1403 encounters were recorded, of which 1228 (87.53%) were completed with mHealth and 175 (12.47%) were telemedicine encounters. Patients’ sex (P=.004) and setting (P<.001) were the most predictive determinants of their preferred method of telecare delivery, with significantly small P values of less than .01. Pearson chi-square test returned a strong indication of dependency between chief concern and encounter mediums, with an extremely small P<.001. Of the 169 mHealth patients who responded to the survey, 154 (91.1%) were satisfied by their encounter, compared with 31 of 35 (89%) telemedicine patients. Conclusions: We studied factors influencing patients’ choice of communication medium, either mHealth or telemedicine, for a virtual care clinic. Sex and geographic location, as well as their chief concern, were strong predictors of patients’ choice of communication medium for their urgent care needs. This study suggests providing the option of mHealth or telemedicine to patients, and suggesting which medium would be a better fit for the patient based on their characteristics.

  • The mScreening text messaging intervention (montage). Source: The Authors / Placeit; Copyright: JMIR Publications; URL:; License: Creative Commons Attribution (CC-BY).

    Development of a Mobile Health Intervention to Promote Papanicolaou Tests and Human Papillomavirus Vaccination in an Underserved Immigrant Population: A...


    Background: Disparities in cervical cancer incidence and mortality signify the need for intervention efforts targeting Korean American immigrant women. Objective: The purpose of this study was to demonstrate how a culturally targeted and tailored mobile text messaging intervention, mobile screening (mScreening), was developed to promote the uptake of Papanicolaou tests and human papillomavirus vaccine among young Korean American immigrant women. Methods: Guided by the Fogg behavior model, the mScreening intervention was developed through a series of focus groups. Braun and Clarke’s thematic analysis was used to identify core themes. Results: Overall, 4 themes were identified: (1) tailored message content (ie, basic knowledge about cervical cancer), (2) an interactive and visual message format (ie, age-appropriate and friendly messages using emoticons), (3) brief message delivery formats to promote participant engagement, and (4) use of an incentive to motivate participation (ie, gift cards). Conclusions: This study demonstrated the processes of gathering culturally relevant information to develop a mobile phone text messaging intervention and incorporating the target population’s perspectives into the development of the intervention. The findings of the study could help guide future intervention development targeting different types of cancer screening in other underserved racial or ethnic groups.

  • Wearable finger pulse oximeter used in the study. Source: Image created by the Authors; Copyright: The Authors; URL:; License: Licensed by the authors.

    Wearable Finger Pulse Oximetry for Continuous Oxygen Saturation Measurements During Daily Home Routines of Patients With Chronic Obstructive Pulmonary...


    Background: Chronic obstructive pulmonary disease (COPD) patients can suffer from low blood oxygen concentrations. Peripheral blood oxygen saturation (SpO2), as assessed by pulse oximetry, is commonly measured during the day using a spot check, or continuously during one or two nights to estimate nocturnal desaturation. Sampling at this frequency may overlook natural fluctuations in SpO2. Objective: This study used wearable finger pulse oximeters to continuously measure SpO2 during daily home routines of COPD patients and assess natural SpO2 fluctuations. Methods: A total of 20 COPD patients wore a WristOx2 pulse oximeter for 1 week to collect continuous SpO2 measurements. A SenseWear Armband simultaneously collected actigraphy measurements to provide contextual information. SpO2 time series were preprocessed and data quality was assessed afterward. Mean SpO2, SpO2 SD, and cumulative time spent with SpO2 below 90% (CT90) were calculated for every (1) day, (2) day in rest, and (3) night to assess SpO2 fluctuations. Results: A high percentage of valid SpO2 data (daytime: 93.27%; nocturnal: 99.31%) could be obtained during a 7-day monitoring period, except during moderate-to-vigorous physical activity (MVPA) (67.86%). Mean nocturnal SpO2 (89.9%, SD 3.4) was lower than mean daytime SpO2 in rest (92.1%, SD 2.9; P<.001). On average, SpO2 in rest ranged over 10.8% (SD 4.4) within one day. Highly varying CT90 values between different nights led to 50% (10/20) of the included patients changing categories between desaturator and nondesaturator over the course of 1 week. Conclusions: Continuous SpO2 measurements with wearable finger pulse oximeters identified significant SpO2 fluctuations between and within multiple days and nights of patients with COPD. Continuous SpO2 measurements during daily home routines of patients with COPD generally had high amounts of valid data, except for motion artifacts during MVPA. The identified fluctuations can have implications for telemonitoring applications that are based on daily SpO2 spot checks. CT90 values can vary greatly from night to night in patients with a nocturnal mean SpO2 around 90%, indicating that these patients cannot be consistently categorized as desaturators or nondesaturators. We recommend using wearable sensors for continuous SpO2 measurements over longer time periods to determine the clinical relevance of the identified SpO2 fluctuations.

  • App photo feature users can take a snapshot of their food items before eating and select correct matches among a list of suggested items [33]. The calories and nutrients for the items are then displayed. Source: Figure 1 from; Copyright: the authors; License: Creative Commons Attribution (CC-BY).

    Weight Loss Following Use of a Smartphone Food Photo Feature: Retrospective Cohort Study


    Background: Tracking of dietary intake is key to enhancing weight loss. Mobile apps may be useful for tracking food intake and can provide feedback about calories and nutritional value. Recent technological developments have enabled image recognition to identify foods and track food intake. Objective: We aimed to determine the effectiveness of using photography as a feature of a smartphone weight loss app to track food intake in adults who were overweight or obese. Methods: We analyzed data from individuals (age, 18-65 years; body mass index≥25 kg/m2; ≥4 days of logged food intake; and ≥2 weigh-ins) who used a mobile-based weight loss app. In a retrospective study, we compared those who used the photo feature (n=9871) and those who did not use the feature (n=113,916). Linear regression analyses were used to assess use of the photo feature in relation to percent weight loss. Results: Weight loss was greater in the group using the photo feature (Δ=0.14%; 95% CI 0.06-0.22; P<.001). The photo feature group used the weight loss app for a longer duration (+3.5 days; 95% CI 2.61-4.37; P<.001) and logged their food intake on more days (+6.1 days; 95% CI 5.40-6.77; P<.001) than the nonusers. Mediation analysis showed that the weight loss effect was absent when controlling for either duration or number of logged days in the program. Conclusions: This study was the first to examine the effect of a food photo feature to track food intake on weight loss in a free-living setting. Use of photo recognition was associated with greater weight loss, which was mediated by the duration of app use and number of logged days in the program.

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  • Development and Use of a Mobile Texting App ‘Heptalk’ for Patient Engagement in Viral Hepatitis B Care

    Date Submitted: Jun 19, 2019

    Open Peer Review Period: Jun 19, 2019 - Jun 27, 2019

    Background: Chronic hepatitis B virus (HBV) infection is a major cause of liver-related morbidity and mortality among Asian Americans in the U.S. population. Despite the available resources, a majorit...

    Background: Chronic hepatitis B virus (HBV) infection is a major cause of liver-related morbidity and mortality among Asian Americans in the U.S. population. Despite the available resources, a majority of HBV infected individuals are not able to access adequate health care owing to numerous barriers. Objective: This study was designed to assess the efficacy of a newly developed mobile texting app ‘heptalk’ to overcome these barriers and to help engage HBV infected and non-immune individuals to health access. Methods: A mobile texting app heptalk was employed for a two-way communication between patients and patient navigators (PNs). A total of 82 Korean-American participants who were either HBV infected or non-immune to HBV were enrolled for the study. After informed consent was obtained, both the frequency and themes of the texting messages were evaluated. The effects of these communications on the linkage to care (LTC) at the end of the six-month intervention period were analyzed and discussed. Results: On average, PNs sent and received 14 and 8 messages per participant, respectively, during the six-month period. The themes of the messages were similar with respect to the following four categories: finding providers, scheduling appointments with providers, health education, and financial issues. Of 82 participants, a total of 78 were linked to care within six months, a 95 % linkage rate. Conclusions: A mobile texting app heptalk may be employed as an effective and strategic tool to facilitate communicative interaction between patients and PNs or healthcare providers (HCPs), thereby improving patient engagement and healthcare access.

  • Are modern activity trackers useful for monitoring exercise behavior in chronic cardiac patients: a validation study.

    Date Submitted: Jun 15, 2019

    Open Peer Review Period: Jun 18, 2019 - Aug 13, 2019

    Background: Improving physical activity (PA) is a core component of secondary prevention and cardiac (tele)rehabilitation. Commercially available activity trackers are frequently used to monitor and p...

    Background: Improving physical activity (PA) is a core component of secondary prevention and cardiac (tele)rehabilitation. Commercially available activity trackers are frequently used to monitor and promote PA in cardiac patients. However studies on the validity of these devices in cardiac patients are scarce. As cardiac patients are being advised and treated based on PA parameters measured by these devices, it is highly important to evaluate the accuracy of these parameters in this specific population. Objective: The aim of this study was to determine the accuracy and responsiveness of two wrist-worn activity trackers, Fitbit Charge 2 (FC2) and Mio Slice (MS), for the assessment of energy expenditure (EE) in cardiac patients. Methods: EE assessed by the activity trackers was compared with indirect calorimetry (Oxycon Mobile, (OM)) during a laboratory activity protocol. Two groups were assessed: patients with stable coronary artery disease (CAD) with preserved left ventricular ejection fraction (LVEF) and patients with heart failure with reduced ejection fraction (HFrEF). Results: 38 patients were included: 19 with CAD and 19 with HFrEF (LVEF 31.8±7.6 %). The CAD group showed no significant difference in total EE between FC2 and OM (47.5±112 kcal, p=.09), in contrast to a significant difference between MS and OM (88±108 kcal, p=.003). The HFrEF group showed significant differences in EE between FC2 and OM (38±57 kcal, p=.01), as well as between MS and OM (106±167 kcal, p=.02). Agreement of the activity trackers was low in both groups (CAD: ICC FC2=0.10, ICC MS=0.12; HFrEF: ICC FC2=0.42, ICC MS=0.11). The responsiveness of FC2 was poor, while MS was able to detect changes in cycling intensity only. Conclusions: Both activity trackers demonstrated low accuracy in estimating EE in cardiac patients, but importantly, also showed poor performance to detect within-patient changes in exercise intensity. These findings show that these commercially available activity trackers should not be used for interventions to improve exercise behavior in patients with CAD and HFrEF and highlight the need for population-specific devices and algorithms. Clinical Trial:, NCT03951740

  • Content and Feature Preferences for a Physical Activity App for Adults with Physical Disabilities: Focus Group Findings

    Date Submitted: Jun 13, 2019

    Open Peer Review Period: Jun 17, 2019 - Aug 12, 2019

    Background: Hundreds of thousands of mobile phone applications intended to improve health and fitness are available for download across platforms and operating systems; however few have been designed...

    Background: Hundreds of thousands of mobile phone applications intended to improve health and fitness are available for download across platforms and operating systems; however few have been designed with people with disabilities (PwD) in mind, ignoring a large population that may benefit from an effective tool to increase physical activity. Objective: This study represents the first phase in the development process of a fitness tracking app for PwD interested in nontraditional sport. The aim of this research was to explore user preferences for content, appearance, and operational features of a proposed physical activity app for PwD to inform the design of a mobile phone app for increasing physical activity. Methods: Four focus groups were conducted with 15 adults with physical disabilities who currently participate in non-traditional, non-Paralympic sport. Data collected from the focus group sessions centered on content, functionality, and appearance of apps currently used by participants as well as preferences for a future app. All sessions were audio recorded and transcribed verbatim. Thematic analysis of the data was undertaken. Results: Participants (mean age 35.7, SD 9.2, years) were mostly white (13/15, 87%), and all were currently participating in CrossFit and at least one other sport. Five main themes were identified. Themes included preferences for (1) workout-specific features that were tailored or searchable by disability, (2) user experience that was intuitive and accessible, (3) profile personalization options, (4) gamification features that allowed for competition with self and other users, and (5) social features that allowed increased interaction among users. Participants expressed a primary interest in having a fitness app that was designed for PwD such that the features present in other fitness tracking apps were relevant to them and their community of adaptive athletes. Conclusions: The results showed that features related to user experience, social engagement, and gamification are considered important to PwD. Features highlighted by participants as most desired, from a consumer perspective, were in line with research identifying attributes of quality apps that use behavior change techniques to influence positive physical activity behavior change. Such insights should inform the development of any fitness app designed to integrate users with disabilities as a primary user base.

  • Mobile apps in rheumatology: review and analysis using the Mobile App Rating Scale (MARS)

    Date Submitted: Jun 10, 2019

    Open Peer Review Period: Jun 13, 2019 - Aug 8, 2019

    Background: Chronic rheumatic diseases need long-term treatment and professional supervision. Mobile applications promise to improve the lives of patients as well as physicians. In routine practice, h...

    Background: Chronic rheumatic diseases need long-term treatment and professional supervision. Mobile applications promise to improve the lives of patients as well as physicians. In routine practice, however, rheumatology apps are largely unknown and little is known about their quality and safety. Objective: The aim of this study was to provide an overview of the mobile rheumatology applications currently available in the German app stores, to evaluate the app quality using the Mobile App Rating Scale (MARS) and to compile brief, ready-to-use descriptions for patients as well as rheumatologists. Methods: The German Google Play and Apple app stores were systematically searched to identify German rheumatology mobile applications applying to patients as well as physicians. MARS was used to independently assess app quality by a total of 8 physicians, 4 using Android and 4 using iOS smartphones. Apps were randomly assigned so that 4 apps were rated by all raters and the remaining apps were rated by two Android and two iOS users. Furthermore, brief app descriptions including app developers, app categories and features were compiled to inform potential users and developers. Results: In total, 128 and 63 apps were identified in the German Google Play and Apple app stores, respectively. After removing doublets and only including apps that were available in both stores, 28 apps remained. Sixteen apps met the inclusion criteria, which were: (1) German language; (2) availability in both app stores; (3) targeting patients or physicians as users; and (4) clearly including rheumatology or rheumatic diseases as subject matter. Exclusion criteria were: (1) congress apps and (2) company apps with advertisements. Nine apps addressed patients and 7 apps addressed physicians. No clinical studies to support the effectiveness and safety of these apps could be found. Pharmaceutical companies were the main developers of two apps. Rheuma-Auszeit was the only app mainly developed by a patient organisation. This app, had the highest overall MARS score (4.19/5). Three out of nine patient apps featured validated questionnaires. The median overall MARS score was 3.85/5, ranging from 2.81/5 to 4.19/5. One patient targeted app and one physician-targeted app had a MARS score >4/5. No significant gender or platform (iOS/Android) differences could be observed. The overall correlation between app store ratings and MARS scores was low and inconsistent between platforms. Conclusions: This is the first study, which systematically identified and evaluated mobile applications in rheumatology for patients, as well as physicians, available in German app stores. We found a lack of supporting clinical studies, use of validated questionnaires and involvement of academic developers. Overall app quality was very heterogeneous. To create high-quality apps a closer cooperation lead by patients and physicians is vital.

  • Examining Variations of Digital Behavior Change Techniques for Physical Activity Using an Adaptive Intervention Design

    Date Submitted: Jun 10, 2019

    Open Peer Review Period: Jun 13, 2019 - Aug 8, 2019

    Background: To foster physical activity behavior, technology often incorporates evidence-based behavior change techniques (BCTs). However, a gap exists on how to apply BCTs for optimal behavior change...

    Background: To foster physical activity behavior, technology often incorporates evidence-based behavior change techniques (BCTs). However, a gap exists on how to apply BCTs for optimal behavior change, and do so in time-varying adaptive interventions. Objective: This study evaluated BCT variations using an adaptive intervention design that randomly assigned participants to a different intervention version based on whether participants met a self-determined physical activity goal. Methods: The study contained three intervention versions (individual pursuit, community comparison, and team competition). Each version included variations of 4 BCTs (goal setting, action planning, feedback, and prompts & cues). The individual pursuit version was the control, while versions two and three received variations of the social competition/comparison BCT. BCTs were delivered via phone app, phone texts, and a Garmin vivofit 3™. Participants who did not increase physical activity in the first 21 days as compared to their baseline were re-randomized into a different intervention version, reassessed at 42 days, and re-randomized again if physical activity did not increase. Ecological momentary assessments were conducted for secondary measures of self-efficacy, barriers, expectations, motivation, mood, social support, and well-being. Results: A total 158 adults in central Florida with low to moderate levels of physical activity, were randomized into one of three intervention versions. Based on a subsample analysis of 87 participants, those who received the team competition intervention version first, followed by community comparison, and individual pursuit, saw the greatest increase in their overall physical activity as compared to other intervention orders. In addition, five distinct behavioral pattern subgroups were identified. We also predicted the likelihood of a participant being active or inactive 14 days into observation and with >80% precision. There was also evidence that app usage in the first 21 days of observation was positively associated with physical activity behavior at study conclusion. Conclusions: The way BCTs are designed and the sequence in which they are delivered can impact physical activity behavior. Additional work is needed on determinants of physical activity behavior, as well as longevity of BCT novelty and user engagement. Clinical Trial: N/A

  • Cardiology Handbook Application: A Pilot Study to Improve Medical Education

    Date Submitted: Jun 9, 2019

    Open Peer Review Period: Jun 12, 2019 - Aug 7, 2019

    Background: At most institutions, internal medicine residents struggle with balancing clinical duties and learning opportunities, particularly during busy cardiology ward rotations. To improve learni...

    Background: At most institutions, internal medicine residents struggle with balancing clinical duties and learning opportunities, particularly during busy cardiology ward rotations. To improve learning experiences for residents, the authors helped develop a cardiology handbook application (app) to supplement cardiology education. Objective: The aim of this study was to report the development, implementation, and preliminary impact of a cardiology reference app in graduate medical education. Methods: In June 2017, 122 residents at Indiana University were invited to download the digital handbook in the Krannert app. The Krannert app featured a total of thirteen chapters which were written by cardiology fellows and faculty at Indiana University. Residents were surveyed on their self-reported improvement in cardiology knowledge and in their satisfaction after using the handbook app. Residents were also surveyed regarding their preference for a digital handbook app versus a paper handbook. Results: Thirty-eight trainees (31%) participated in survey evaluations. Among all respondents, 82% of app users reported the app helped improve their cardiology knowledge base. The handbook app had an overall favorable response. Conclusions: The Krannert cardiology app shows promise in augmenting clinical education in cardiology with mobile learning. Future work includes adding new topics, updating the content, comparing the app to other learning modalities.