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Journal Description

JMIR mHealth and uHealth (JMU, ISSN 2291-5222; Impact Factor 4.31) is a sister journal of JMIR, the leading eHealth journal. JMIR mHealth and uHealth is indexed in PubMed, PubMed Central, Scopus, MEDLINE and Science Citation Index Expanded (SCIE), and in June 2020 received an Impact Factor of 4.31, ranking the journal Q1 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: http://mhealth.jmir.org/2020/8/e19529/; License: Fair use/fair dealings.

    Mobile Fotonovelas Within a Text Message Outreach: An Innovative Tool to Build Health Literacy and Influence Behaviors in Response to the COVID-19 Pandemic

    Abstract:

    With all 50 US states reporting cases of coronavirus disease (COVID-19), people around the country are adapting and stepping up to the challenges of the pandemic; however, they are also frightened, anxious, and confused about what they can do to avoid exposure to the disease. Usual habits have been interrupted as a result of the crisis, and consumers are open to suggestions and strategies to help them change long-standing attitudes and behaviors. In response, a novel and innovative mobile communication capability was developed to present health messages in English and Spanish with links to fotonovelas (visual stories) that are accessible, easy to understand across literacy levels, and compelling to a diverse audience. While SMS text message outreach has been used to build health literacy and provide social support, few studies have explored the benefits of SMS text messaging combined with visual stories to influence health behaviors and build knowledge and self-efficacy. In particular, this approach can be used to provide vital information, resources, empathy, and support to the most vulnerable populations. This also allows providers and health plans to quickly reach out to their patients and members without any additional resource demands at a time when the health care system is severely overburdened.

  • Source: Freepik; Copyright: ijeab; URL: https://www.freepik.com/free-photo/doctor-checking-patient-arterial-blood-pressure_1211547.htm; License: Licensed by JMIR.

    Effects of a Novel Contextual Just-In-Time Mobile App Intervention (LowSalt4Life) on Sodium Intake in Adults With Hypertension: Pilot Randomized Controlled...

    Abstract:

    Background: High dietary sodium intake is a significant public health problem in the United States. High sodium consumption is associated with high blood pressure and high risk of cardiovascular disease. Objective: The aim of this study was to evaluate the effect of a just-in-time adaptive mobile app intervention, namely, LowSalt4Life, on reducing sodium intake in adults with hypertension. Methods: In this study, 50 participants aged ≥18 years who were under treatment for hypertension were randomized (1:1, stratified by gender) into 2 groups, namely, the App group (LowSalt4Life intervention) and the No App group (usual dietary advice) in a single-center, prospective, open-label randomized controlled trial for 8 weeks. The primary endpoint was the change in the 24-hour urinary sodium excretion estimated from spot urine by using the Kawasaki equation, which was analyzed using unpaired two-sided t tests. Secondary outcomes included the change in the sodium intake measured by the food frequency questionnaire (FFQ), the 24-hour urinary sodium excretion, blood pressure levels, and the self-reported confidence in following a low-sodium diet. Results: From baseline to week 8, there was a significant reduction in the Kawasaki-estimated 24-hour urinary sodium excretion calculated from spot urine in the App group compared to that in the No App group (–462 [SD 1220] mg vs 381 [SD 1460] mg, respectively; P=.03). The change in the 24-hour urinary sodium excretion was –637 (SD 1524) mg in the App group and –322 (SD 1485) mg in the No App group (P=.47). The changes in the estimated sodium intake as measured by 24-hour dietary recall and by FFQ in the App group were –1537 (SD 2693) mg and –1553 (SD 1764) mg while those in the No App group were –233 (SD 2150) mg and –515 (SD 1081) mg, respectively (P=.07 and P=.01, respectively). The systolic blood pressure change from baseline to week 8 in the App group was –7.5 mmHg while that in the No App group was –0.7 mmHg (P=.12), but the self-confidence in following a low-sodium diet was not significantly different between the 2 groups. Conclusions: This study shows that a contextual just-in-time mobile app intervention resulted in a greater reduction in the dietary sodium intake in adults with hypertension than that in the control group over a 8-week period, as measured by the estimated 24-hour urinary sodium excretion from spot urine and FFQ. The intervention group did not show a significant difference from the control group in the self-confidence in following a low sodium diet and in the 24-hour urinary sodium excretion or dietary intake of sodium as measured by the 24-hour dietary recall. A larger clinical trial is warranted to further elucidate the effects of the LowSalt4Life intervention on sodium intake and blood pressure levels in adults with hypertension. Trial Registration: ClinicalTrials.gov NCT03099343; https://clinicaltrials.gov/ct2/show/NCT03099343

  • Source: The Authors/Placeit; Copyright: The Authors/Placeit; URL: http://mhealth.jmir.org/2020/8/e17803/; License: Licensed by JMIR.

    Respiration Rate Estimation Based on Independent Component Analysis of Accelerometer Data: Pilot Single-Arm Intervention Study

    Authors List:

    Abstract:

    Background: As the mobile environment has developed recently, there have been studies on continuous respiration monitoring. However, it is not easy for general users to access the sensors typically used to measure respiration. There is also random noise caused by various environmental variables when respiration is measured using noncontact methods in a mobile environment. Objective: In this study, we aimed to estimate the respiration rate using an accelerometer sensor in a smartphone. Methods: First, data were acquired from an accelerometer sensor by a smartphone, which can easily be accessed by the general public. Second, an independent component was extracted to calibrate the three-axis accelerometer. Lastly, the respiration rate was estimated using quefrency selection reflecting the harmonic component because respiration has regular patterns. Results: From April 2018, we enrolled 30 male participants. When the independent component and quefrency selection were used to estimate the respiration rate, the correlation with respiration acquired from a chest belt was 0.7. The statistical results of the Wilcoxon signed-rank test were used to determine whether the differences in the respiration counts acquired from the chest belt and from the accelerometer sensor were significant. The P value of the difference in the respiration counts acquired from the two sensors was .27, which was not significant. This indicates that the number of respiration counts measured using the accelerometer sensor was not different from that measured using the chest belt. The Bland-Altman results indicated that the mean difference was 0.43, with less than one breath per minute, and that the respiration rate was at the 95% limits of agreement. Conclusions: There was no relevant difference in the respiration rate measured using a chest belt and that measured using an accelerometer sensor. The accelerometer sensor approach could solve the problems related to the inconvenience of chest belt attachment and the settings. It could be used to detect sleep apnea through constant respiration rate estimation in an internet-of-things environment.

  • Source: Image created by the authors; Copyright: The Authors; URL: http://mhealth.jmir.org/2020/8/e17709/; License: Creative Commons Attribution + Noncommercial + NoDerivatives (CC-BY-NC-ND).

    Influence of Personality on mHealth Use in Patients with Diabetes: Prospective Pilot Study

    Abstract:

    Background: Mobile technology for health (mHealth) interventions are increasingly being used to help improve self-management among patients with diabetes; however, these interventions have not been adopted by a large number of patients and often have high dropout rates. Patient personality characteristics may play a critical role in app adoption and active utilization, but few studies have focused on addressing this question. Objective: This study aims to address a gap in understanding of the relationship between personality traits and mHealth treatment for patients with diabetes. We tested the role of the five-factor model of personality traits (openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism) in mHealth adoption preference and active utilization. Methods: We developed an mHealth app (DiaSocial) aimed to encourage diabetes self-management. We recruited 98 patients with diabetes—each patient freely chose whether to receive the standard care or the mHealth app intervention. Patient demographic information and patient personality characteristics were assessed at baseline. App usage data were collected to measure user utilization of the app. Patient health outcomes were assessed with lab measures of glycated hemoglobin (HbA1c level). Logistic regression models and linear regression were employed to explore factors predicting the relationship between mHealth use (adoption and active utilization) and changes in health outcome. Results: Of 98 study participants, 46 (47%) downloaded and used the app. Relatively younger patients with diabetes were 9% more likely to try and use the app (P=.02, odds ratio [OR] 0.91, 95% CI 0.85-0.98) than older patients with diabetes were. Extraversion was negatively associated with adoption of the mHealth app (P=.04, OR 0.71, 95% CI 0.51-0.98), and openness to experience was positively associated with adoption of the app (P=.03, OR 1.73, 95% CI 1.07-2.80). Gender (P=.43, OR 0.66, 95% CI 0.23-1.88), education (senior: P=.99, OR 1.00, 95% CI 0.32-3.11; higher: P=.21, OR 2.51, 95% CI 0.59-10.66), and baseline HbA1c level (P=.36, OR 0.79, 95% CI 0.47-1.31) were not associated with app adoption. Among those who adopted the app, a low education level (senior versus primary P=.003; higher versus primary P=.03) and a high level of openness to experience (P=.048, OR 2.01, 95% CI 1.01-4.00) were associated with active app utilization. Active users showed a significantly greater decrease in HbA1c level than other users (ΔHbA1c=−0.64, P=.05). Conclusions: This is one of the first studies to investigate how different personality traits influence the adoption and active utilization of an mHealth app among patients with diabetes. The research findings suggest that personality is a factor that should be considered when trying to identify patients who would benefit the most from apps for diabetes management.

  • Source: Image created by the Authors; Copyright: The Authors; URL: https://mhealth.jmir.org/2020/8/e16862; License: Fair use/fair dealings.

    Using Natural Language Processing and Sentiment Analysis to Augment Traditional User-Centered Design: Development and Usability Study

    Abstract:

    Background: Sarcopenia, defined as the age-associated loss of muscle mass and strength, can be effectively mitigated through resistance-based physical activity. With compliance at approximately 40% for home-based exercise prescriptions, implementing a remote sensing system would help patients and clinicians to better understand treatment progress and increase compliance. The inclusion of end users in the development of mobile apps for remote-sensing systems can ensure that they are both user friendly and facilitate compliance. With advancements in natural language processing (NLP), there is potential for these methods to be used with data collected through the user-centered design process. Objective: This study aims to develop a mobile app for a novel device through a user-centered design process with both older adults and clinicians while exploring whether data collected through this process can be used in NLP and sentiment analysis Methods: Through a user-centered design process, we conducted semistructured interviews during the development of a geriatric-friendly Bluetooth-connected resistance exercise band app. We interviewed patients and clinicians at weeks 0, 5, and 10 of the app development. Each semistructured interview consisted of heuristic evaluations, cognitive walkthroughs, and observations. We used the Bing sentiment library for a sentiment analysis of interview transcripts and then applied NLP-based latent Dirichlet allocation (LDA) topic modeling to identify differences and similarities in patient and clinician participant interviews. Sentiment was defined as the sum of positive and negative words (each word with a +1 or −1 value). To assess utility, we used quantitative assessment questionnaires—System Usability Scale (SUS) and Usefulness, Satisfaction, and Ease of use (USE). Finally, we used multivariate linear models—adjusting for age, sex, subject group (clinician vs patient), and development—to explore the association between sentiment analysis and SUS and USE outcomes. Results: The mean age of the 22 participants was 68 (SD 14) years, and 17 (77%) were female. The overall mean SUS and USE scores were 66.4 (SD 13.6) and 41.3 (SD 15.2), respectively. Both patients and clinicians provided valuable insights into the needs of older adults when designing and building an app. The mean positive-negative sentiment per sentence was 0.19 (SD 0.21) and 0.47 (SD 0.21) for patient and clinician interviews, respectively. We found a positive association with positive sentiment in an interview and SUS score (ß=1.38; 95% CI 0.37 to 2.39; P=.01). There was no significant association between sentiment and the USE score. The LDA analysis found no overlap between patients and clinicians in the 8 identified topics. Conclusions: Involving patients and clinicians allowed us to design and build an app that is user friendly for older adults while supporting compliance. This is the first analysis using NLP and usability questionnaires in the quantification of user-centered design of technology for older adults.

  • Source: Unsplash; Copyright: Lily Banse; URL: https://unsplash.com/photos/iNsKPCS-Z5g; License: Licensed by JMIR.

    Complementing Human Behavior Assessment by Leveraging Personal Ubiquitous Devices and Social Links: An Evaluation of the Peer-Ceived Momentary Assessment Method

    Abstract:

    Background: Ecological momentary assessment (EMA) enables individuals to self-report their subjective momentary physical and emotional states. However, certain conditions, including routine observable behaviors (eg, moods, medication adherence) as well as behaviors that may suggest declines in physical or mental health (eg, memory losses, compulsive disorders) cannot be easily and reliably measured via self-reports. Objective: This study aims to examine a method complementary to EMA, denoted as peer-ceived momentary assessment (PeerMA), which enables the involvement of peers (eg, family members, friends) to report their perception of the individual’s subjective physical and emotional states. In this paper, we aim to report the feasibility results and identified human factors influencing the acceptance and reliability of the PeerMA Methods: We conducted two studies of 4 weeks each, collecting self-reports from 20 participants about their stress, fatigue, anxiety, and well-being, in addition to collecting peer-reported perceptions from 27 of their peers. Results: Preliminary results showed that some of the peers reported daily assessments for stress, fatigue, anxiety, and well-being statistically equal to those reported by the participant. We also showed how pairing assessments of participants and peers in time enables a qualitative and quantitative exploration of unique research questions not possible with EMA-only based assessments. We reported on the usability and implementation aspects based on the participants’ experience to guide the use of the PeerMA to complement the information obtained via self-reports for observable behaviors and physical and emotional states among healthy individuals. Conclusions: It is possible to leverage the PeerMA method as a complement to EMA to assess constructs that fall in the realm of observable behaviors and states in healthy individuals.

  • Source: freepik; Copyright: freepik; URL: https://www.freepik.com/free-photo/elder-man-sleeping-white-bed_4762493.htm#page=1&query=elderly%20person%20sleeping&position=0; License: Licensed by JMIR.

    Wearable Device Heart Rate and Activity Data in an Unsupervised Approach to Personalized Sleep Monitoring: Algorithm Validation

    Abstract:

    Background: The proliferation of wearable devices that collect activity and heart rate data has facilitated new ways to measure sleeping and waking durations unobtrusively and longitudinally. Most existing sleep/wake identification algorithms are based on activity only and are trained on expensive and laboriously annotated polysomnography (PSG). Heart rate can also be reflective of sleep/wake transitions, which has motivated its investigation herein in an unsupervised algorithm. Moreover, it is necessary to develop a personalized approach to deal with interindividual variance in sleep/wake patterns. Objective: We aimed to develop an unsupervised personalized sleep/wake identification algorithm using multifaceted data to explore the benefits of incorporating both heart rate and activity level in these types of algorithms and to compare this approach’s output with that of an existing commercial wearable device’s algorithms. Methods: In this study, a total of 14 community-dwelling older adults wore wearable devices (Fitbit Alta; Fitbit Inc) 24 hours a day and 7 days a week over period of 3 months during which their heart rate and activity data were collected. After preprocessing the data, a model was developed to distinguish sleep/wake states based on each individual’s data. We proposed the use of hidden Markov models and compared different modeling schemes. With the best model selected, sleep/wake patterns were characterized by estimated parameters in hidden Markov models, and sleep/wake states were identified. Results: When applying our proposed algorithm on a daily basis, we found there were significant differences in estimated parameters between weekday models and weekend models for some participants. Conclusions: Our unsupervised approach can be effectively implemented based on an individual’s multifaceted sleep-related data from a commercial wearable device. A personalized model is shown to be necessary given the interindividual variability in estimated parameters.

  • during physical education lesson. Source: Authors; Copyright: The Authors; URL: http://mhealth.jmir.org/2020/8/e17699/; License: Creative Commons Attribution (CC-BY).

    Using Smart Bracelets to Assess Heart Rate Among Students During Physical Education Lessons: Feasibility, Reliability, and Validity Study

    Abstract:

    Background: An increasing number of wrist-worn wearables are being examined in the context of health care. However, studies of their use during physical education (PE) lessons remain scarce. Objective: We aim to examine the reliability and validity of the Fizzo Smart Bracelet (Fizzo) in measuring heart rate (HR) in the laboratory and during PE lessons. Methods: In Study 1, 11 healthy subjects (median age 22.0 years, IQR 3.75 years) twice completed a test that involved running on a treadmill at 6 km/h for 12 minutes and 12 km/h for 5 minutes. During the test, participants wore two Fizzo devices, one each on their left and right wrists, to measure their HR. At the same time, the Polar Team2 Pro (Polar), which is worn on the chest, was used as the standard. In Study 2, we went to 10 schools and measured the HR of 24 students (median age 14.0 years, IQR 2.0 years) during PE lessons. During the PE lessons, each student wore a Polar device on their chest and a Fizzo on their right wrist to measure HR data. At the end of the PE lessons, the students and their teachers completed a questionnaire where they assessed the feasibility of Fizzo. The measurements taken by the left wrist Fizzo and the right wrist Fizzo were compared to estimate reliability, while the Fizzo measurements were compared to the Polar measurements to estimate validity. To measure reliability, intraclass correlation coefficients (ICC), mean difference (MD), standard error of measurement (SEM), and mean absolute percentage errors (MAPE) were used. To measure validity, ICC, limits of agreement (LOA), and MAPE were calculated and Bland-Altman plots were constructed. Percentage values were used to estimate the feasibility of Fizzo. Results: The Fizzo showed excellent reliability and validity in the laboratory and moderate validity in a PE lesson setting. In Study 1, reliability was excellent (ICC>0.97; MD<0.7; SEM<0.56; MAPE<1.45%). The validity as determined by comparing the left wrist Fizzo and right wrist Fizzo was excellent (ICC>0.98; MAPE<1.85%). Bland-Altman plots showed a strong correlation between left wrist Fizzo measurements (bias=0.48, LOA=–3.94 to 4.89 beats per minute) and right wrist Fizzo measurements (bias=0.56, LOA=–4.60 to 5.72 beats per minute). In Study 2, the validity of the Fizzo was lower compared to that found in Study 1 but still moderate (ICC>0.70; MAPE<9.0%). The Fizzo showed broader LOA in the Bland-Altman plots during the PE lessons (bias=–2.60, LOA=–38.89 to 33.69 beats per minute). Most participants considered the Fizzo very comfortable and easy to put on. All teachers thought the Fizzo was helpful. Conclusions: When participants ran on a treadmill in the laboratory, both left and right wrist Fizzo measurements were accurate. The validity of the Fizzo was lower in PE lessons but still reached a moderate level. The Fizzo is feasible for use during PE lessons.

  • Source: Image created by the Authors; Copyright: The Authors; URL: https://mhealth.jmir.org/2020/8/e17193; License: Creative Commons Attribution (CC-BY).

    Evaluating a Theoretically Informed and Cocreated Mobile Health Educational Intervention for First-Time Hearing Aid Users: Qualitative Interview Study

    Abstract:

    Background: Adults living with hearing loss have highly variable knowledge of hearing aids, resulting in suboptimal use or nonuse. This issue can be addressed by the provision of high-quality educational resources. Objective: This study aims to assess the everyday experiences of first-time hearing aid users when using a newly developed, theoretically informed cocreated mobile health (mHealth) educational intervention called m2Hear. This intervention aims to deliver greater opportunities for individualization and interactivity compared with our previously developed multimedia intervention, C2Hear. Methods: A total of 16 first-time hearing aid users trialed m2Hear for a period of 10-weeks in their everyday lives, after which individual semistructured interviews were completed. The data were analyzed using an established deductive thematic analysis procedure underpinned by the Capability, Opportunity, Motivation-Behavior model. The model stipulates that to engage in a target behavior, an individual must have physical and psychological capability, physical and social opportunity, and automatic and reflective motivation. Results: Capability—m2Hear was viewed as a concise and comprehensive resource, suitable for a range of digital literacy skills. It was stated that m2Hear could be conveniently reused to provide useful reminders that facilitate knowledge of hearing aids and communication. Opportunity—m2Hear was simple and straightforward to use, enabling greater individualization and independence. The availability of m2Hear via mobile technologies also improved accessibility. Motivation—m2Hear provided greater support and reassurance, improving confidence and empowering users to self-manage their hearing loss. Conclusions: Overall, this qualitative study suggests that m2Hear supports first-time hearing aid users to successfully self-manage their hearing loss postfitting. Furthermore, this study demonstrates the utility of employing a combined theoretical and ecologically valid approach in the development of mHealth educational resources to meet the individual self-management needs of adults living with hearing loss. Trial Registration: ClinicalTrials.gov NCT03136718; https://clinicaltrials.gov/ct2/show/NCT03136718

  • Source: Image created by the Authors; Copyright: The Authors; URL: http://mhealth.jmir.org/2020/8/e19380/; License: Creative Commons Attribution + Noncommercial (CC-BY-NC).

    User Perception of a Smartphone App to Promote Physical Activity Through Active Transportation: Inductive Qualitative Content Analysis Within the Smart City...

    Abstract:

    Background: Physical inactivity is globally recognized as a major risk factor for morbidity, particularly the incidence of noncommunicable diseases. Increasing physical activity (PA) is therefore a public health priority. Engaging in active transportation (AT) is a viable approach for promoting daily PA levels. Mobile health interventions enable the promotion of AT to a larger population. The Smart City Active Mobile Phone Intervention (SCAMPI) study was a randomized controlled trial designed to evaluate the ability of a behavior change program delivered via a smartphone app to motivate participants to increase their PA by engaging in AT. Objective: This qualitative study aims to examine the acceptance and user experience of the app promoting AT that was used in the SCAMPI trial (the TRavelVU Plus app). Methods: A total of 17 residents of Stockholm County (13 women; age range 25-61 years) who completed the 3-month app-based behavioral change program (delivered through the TRavelVU Plus app) in the SCAMPI randomized controlled trial during 2018 agreed to participate in a semistructured telephone-based interview. These participants were well representative of the whole intervention group (n=127) in terms of baseline characteristics such as age, sex, and area of residence. The interviews were audiorecorded, transcribed verbatim, and analyzed using an inductive qualitative content analysis. Results: The content analysis revealed 2 themes and 4 subcategories. The first theme, “main motivators: monitoring and messages,” highlighted that monitoring AT and being able to set weekly goals using the app were the primary motivators reported by study participants. The second theme, “acceptable but modifiable,” reflects that the app was well accepted and effectively encouraged many participants to use more AT. Nevertheless, there were functions in the app that require modification. For example, while the semiautomated travel tracking feature was appreciated, participants found it time-consuming and unreliable at times. Conclusions: This study contributes novel insight into adults’ experiences of using a mobile app to promote the use of AT. The results showed that the app was well accepted and that self-monitoring and goal setting were the main motivators to engage in more AT. The semiautomated tracking of AT was appreciated; however, it was also reported to be energy- and time-consuming when it failed to work. Thus, this feature should be improved going forward. Trial Registration: ClinicalTrials.gov NCT03086837; https://clinicaltrials.gov/ct2/show/NCT03086837

  • Source: The Authors/Placeit; Copyright: The Authors/Placeit; URL: https://mhealth.jmir.org/2020/8/e15156; License: Licensed by JMIR.

    Rams Have Heart, a Mobile App Tracking Activity and Fruit and Vegetable Consumption to Support the Cardiovascular Health of College Students: Development and...

    Abstract:

    Background: With the increasing use of mobile devices to access the internet and as the main computing system of apps, there is a growing market for mobile health apps to provide self-care advice. Their effectiveness with regard to diet and fitness tracking, for example, needs to be examined. The majority of American adults fail to meet daily recommendations for healthy behavior. Testing user engagement with an app in a controlled environment can provide insight into what is effective and not effective in an app focused on improving diet and exercise. Objective: We developed Rams Have Heart, a mobile app, to support a cardiovascular disease (CVD) intervention course. The app tracks healthy behaviors, including fruit and vegetable consumption and physical activity, throughout the day. This paper aimed to present its functionality and evaluated adherence among the African American college student population. Methods: We developed the app using the Personal Health Informatics and Intervention Toolkit, a software framework. Rams Have Heart integrates self-reported health screening with health education, diary tracking, and user feedback modules to acquire data and assess progress. The parent study, conducted at a historically black college and university-designated institution in southeastern United States, consisted of a semester-long intervention administered as an academic course in the fall, for 3 consecutive years. Changes were made after the cohort 1 pilot study, so results only include cohorts 2 and 3, comprising a total of 115 students (n=55 intervention participants and n=54 control participants) aged from 17 to 24 years. Data collected over the study period were transferred using the secure Hypertext Transfer Protocol Secure protocol and stored in a secure Structured Query Language server database accessible only to authorized persons. SAS software was used to analyze the overall app usage and the specific results collected. Results: Of the 55 students in the intervention group, 27 (49%) students in cohort 2 and 25 (45%) in cohort 3 used the Rams Have Heart app at least once. Over the course of the fall semester, app participation dropped off gradually until exam week when most students no longer participated. The average fruit and vegetable intake increased slightly, and activity levels decreased over the study period. Conclusions: Rams Have Heart was developed to allow daily tracking of fruit and vegetable intake and physical activity to support a CVD risk intervention for a student demographic susceptible to obesity, heart disease, and type 2 diabetes. We conducted an analysis of app usage, function, and user results. Although a mobile app provides privacy and flexibility for user participation in a research study, Rams Have Heart did not improve compliance or user outcomes. Health-oriented research studies relying on apps in support of user goals need further evaluation.

  • Source: Pexels; Copyright: PhotoMIX Company; URL: https://www.pexels.com/photo/person-holding-silver-iphone-7-887751/; License: Licensed by JMIR.

    The Association Between App-Administered Depression Assessments and Suicidal Ideation in User Comments: Retrospective Observational Study

    Abstract:

    Background: Many people use apps to help understand and manage their depression symptoms. App-administered questionnaires for the symptoms of depression, such as the Patient Health Questionnaire-9, are easy to score and implement in an app, but may not be accompanied by essential resources and access needed to provide proper support and avoid potential harm. Objective: Our primary goal was to evaluate the differences in risks and helpfulness associated with using an app to self-diagnose depression, comparing assessment-only apps with multifeatured apps. We also investigated whether, what, and how additional app features may mitigate potential risks. Methods: In this retrospective observational study, we identified apps in the Google Play store that provided a depression assessment as a feature and had at least five user comments. We separated apps into two categories based on those having only a depression assessment versus those that offered additional supportive features. We conducted theoretical thematic analyses over the user reviews, with thematic coding indicating the helpfulness of the app, the presence of suicidal ideation, and how and why the apps were used. We compared the results across the two categories of apps and analyzed the differences using chi-square statistical tests. Results: We evaluated 6 apps; 3 provided only a depression assessment (assessment only), and 3 provided features in addition to self-assessment (multifeatured). User comments for assessment-only apps indicated significantly more suicidal ideation or self-harm (n=31, 9.4%) compared to comments for multifeatured apps (n=48, 2.3%; X21=43.88, P<.001). Users of multifeatured apps were over three times more likely than assessment-only app users to comment in favor of the app’s helpfulness, likely due to features like mood tracking, journaling, and informational resources (n=56, 17% vs n=1223, 59% respectively; X21=200.36, P<.001). The number of users under the age of 18 years was significantly higher among assessment-only app users (n=40, 12%) than multifeatured app users (n=9, 0.04%; X21=189.09, P<.001). Conclusions: Apps that diagnose depression by self-assessment without context or other supportive features are more likely to be used by those under 18 years of age and more likely to be associated with increased user distress and potential harm. Depression self-assessments in apps should be implemented with caution and accompanied by evidence-based capabilities that establish proper context, increase self-empowerment, and encourage users to seek clinical diagnostics and outside help. Trial Registration:

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    Date Submitted: Aug 8, 2020

    Open Peer Review Period: Aug 7, 2020 - Oct 2, 2020

    Background: Despite strong evidence of clinical benefit, cardiac rehabilitation (CR) programs are currently underutilized and smartphone-based CR strategies are thought to address this unmet need. How...

    Background: Despite strong evidence of clinical benefit, cardiac rehabilitation (CR) programs are currently underutilized and smartphone-based CR strategies are thought to address this unmet need. However, the previous applications have several limitations and there are scarce data regarding its usefulness and clinical benefit. The application for self-improvement (AnSim) trial is a multicenter, prospective randomized trial to explore the feasibility and efficacy of smartphone-based messaging application for patients who underwent percutaneous coronary intervention (PCI). Objective: The current study will focus on the development of a smartphone-based, patient-specific messaging application and detailed design of the trial. Methods: The AnSim application is developed by multidisciplinary team collaboration including cardiologists, psychiatrists, nurses, pharmacists, nutritionists, and rehabilitation doctor and therapists. First, the focus group interview was conducted and narratives of the patients were analyzed to identify their needs and preferences. Based on the results, health care experts and clinicians drafted messages into 5 categories: (1) general information regarding cardiovascular health and medications, (2) nutrition, (3) physical activity, (4) destressing, and (5) smoking cessation. In each category, 30 messages were developed according to three simplified steps of the transtheoretical model of behavioral change: (1) pre-contemplation, (2) contemplation and preparation, and (3) action and maintenance. After internal review and feedback from potential users, a bank of 450 messages and application were finally developed. Results: The focus interview was performed with 8 patients with recent PCI within 1 month and development of 450 messages were done. Positive feedback obtained from the potential users (n = 200) that Likert scale score was 3.95±SD and 3.91±SD for readability and usefulness, respectively. Based on the results, the several messages were refined. Furthermore, messages using various forms of multimedia such as exercise videos and dietary regimens, and connection for smoking cessation center were also developed as needed. Conclusions: A final bank of 450 smartphone-based, patient-specific messages were developed to support behavior change and decrease cardiovascular risk factors through 5 step iterative process. The detailed process of multidisciplinary collaboration in the course of the study provides a scientific basis for various medical professionals who are planning smartphone based clinical research and AnSim trial will demonstrate the feasibility and efficacy of a patient-specific messaging smartphone application in secondary prevention of coronary heart disease.

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    Date Submitted: Aug 3, 2020

    Open Peer Review Period: Aug 2, 2020 - Sep 27, 2020

    Background: Effective contact tracing is labor- and time-intensive during the coronavirus disease 2019 (COVID-19) pandemic, but essential in the absence of effective treatment and vaccines. Singapore...

    Background: Effective contact tracing is labor- and time-intensive during the coronavirus disease 2019 (COVID-19) pandemic, but essential in the absence of effective treatment and vaccines. Singapore launched the first Bluetooth-based contact tracing app— “TraceTogether” in March 2020 to augment its contact tracing capabilities. Objective: This study aimed to compare the performance of the contact tracing app—“TraceTogether” with a wearable tag-based Real-Time Locating System and validate them against the Electronic Medical Records at the National Center for Infectious Disease (NCID), the national referral center for COVID-19 screening. Methods: All patients and physicians in NCID’s screening center were issued with RTLS tags for contact tracing. Eighteen physicians deployed to NCID’s screening center from May 10–19, 2020 activated the “TraceTogether” app on their smartphones during shifts and urged patients to whom they medically attended to use the app. We compared patient contacts identified by “TraceTogether” and tag-based RTLS within NCID’s vicinity during the physicians’ 10-day posting. We further validated both digital contact tracing tools by verifying the physician-patient contacts with the EMR of 156 patients who attended at NCID’s screening center over a 24-hr time frame within the study period. Results: RTLS had a high sensitivity of 95.3% in detecting all patient contacts identified either by the system or “TraceTogether” while “TraceTogether” had an overall sensitivity of 6.5%, performing significantly better on Android phones (Android: 9.7%, iPhone: 2.7%, P<.001). When validated against the EMR, RTLS tags had a sensitivity of 96.9% and specificity of 83.1% while “TraceTogether” detected only two patient contacts with physicians who did not attend to them. Conclusions: “TraceTogether” had a much lower sensitivity compared with tag-based RTLS in identifying patient contacts in a clinical setting. Although tag-based RTLS tags performed well for contact tracing in the clinical setting, implementation and technology enforcement would be challenging in the community compared with “TraceTogether”. Given the uncertainty on the adoption and capabilities contact tracing apps, policy makers should be cautioned against the over-reliance on an app for contact tracing. Nonetheless, leveraging on technology to augment conventional manual contact tracing was a necessary move for life to return to some normalcy over the long haul of COVID-19.

  • ReMindCare app for Early Psychosis: clinical outcomes of a real-world intervention.

    Date Submitted: Jul 29, 2020

    Open Peer Review Period: Jul 29, 2020 - Sep 23, 2020

    Background: e-Health interventions are widely used in clinical trials and increasingly care setting as well; however, their efficacy in real-world contexts remains unknown. ReMindCare is a smartphone...

    Background: e-Health interventions are widely used in clinical trials and increasingly care setting as well; however, their efficacy in real-world contexts remains unknown. ReMindCare is a smartphone application that has been systematically implemented in a First Episode of Psychosis Program (FEPP) for patients with Early Psychosis (EP) since 2018. Objective: The objective of this study is to assess the efficacy of ReMindCare after 19 months of use in the clinic and varying use by individual patients Methods: The integration of ReMindCare app into the FEPP started on October 2018. Patients with EP self-selected to the app (RC group) or treatment as usual (TAU). The outcome variables considered were: adherence to the intervention, number of relapses, hospital admissions, and visits to urgent care units. Data from 90 patients with EP was analyzed: 59 on the RC group and 31 on the TAU group. Mean age of the sample was 32.8 (SD=9.4), 72.5% (66/90) were males, 91.2% (83/90) were Caucasian and 81.3% (74/90) were single. Results: Significant differences between RC and TAU groups were found in number of relapses, hospitalizations, and visits to urgent care units, with each showing benefits for the app. Only 20.3% (12/59) of patients from the RC Group had a relapse while 58% (18/31) of TAU patients had one or more relapses (X2= 13.7, p=0.001). Moreover, RC patients had less visits to urgent care units (X2= 7.4, p=0.006) and less hospitalizations than TAU patients (X2= 4.6, p=0.032). Mean of days using the app was 352.2 (SD=191.2; min/max: 18-594) and mean of engagement was 84.5 (16.04). Conclusions: To our knowledge this is the first e-Health intervention that has preliminary proven its benefits on the real-world treatment of patients with EP.

  • Reducing Cancer Caregiver Burden: A User-Centered Design Approach for an mHealth App

    Date Submitted: Jul 20, 2020

    Open Peer Review Period: Jul 20, 2020 - Sep 14, 2020

    Background: Informal caregivers are essential partners in the delivery of complex cancer care services at home, and about 25% of those caring for cancer patients spend more than 40 hours a week provid...

    Background: Informal caregivers are essential partners in the delivery of complex cancer care services at home, and about 25% of those caring for cancer patients spend more than 40 hours a week providing services. Caregivers frequently suffer psychological, behavioral and physiological effects that can not only affect the patients’ mental and physical health, but also impair the caregivers’ health. Objective: In this paper, we describe a user-centered design approach to build an mHealth smartphone app to provide support and resources to informal caregivers (carepartners) while enabling them to remotely monitor the cancer survivor’s health for unanticipated adverse events, thereby reducing burden for clinical staff. Methods: An iterative information gathering process was conducted that included a) key-informant interviews with 138 stakeholders to assess health care value propositions and corresponding benefit modules; b) semi-structured interviews with clinicians (N=3), cancer patients (N=3) and carepartners (N=3) to identify needs and interests, and; c) a 28-day beta iOS user testing with feasibility and acceptability feedback from 8 carepartners in two geographically different academic cancer centers (Duke and Stanford). This study was registered on clinicaltrials.gov (NCT04018677). Results: The interviews conducted prior to developing the mHealth app prototype identified areas of consistency in responses between different stakeholder groups in terms of how the mobile app should work, as well as areas of difference. The Beta test of the prototype indicated satisfaction with the app’s usability. Carepartners preferred to focus primarily on the patient’s health and not their own, and regular surveys on the patient’s symptoms helped educate care partners and reduce their anxiety. Conclusions: This study describes the user-centered design process and demonstrates the feasibility and acceptability of TOGETHERCareTM, an iOS smartphone app for informal cancer carepartners. Larger studies, in various oncology populations, are needed to establish the efficacy of the app in reducing carepartner burden and to facilitate critical remote monitoring. Clinical Trial: clinicaltrials.gov (NCT04018677)

  • A Wearable Real-time Non-Contact Electrocardiogram System for Arrhythmia Detection and Classification

    Date Submitted: Jul 19, 2020

    Open Peer Review Period: Jul 19, 2020 - Sep 13, 2020

    Background: Driven by the increasing demand for potential patients to monitor their own heart health, wearable technology is increasingly helping people to better monitor their heart health status at...

    Background: Driven by the increasing demand for potential patients to monitor their own heart health, wearable technology is increasingly helping people to better monitor their heart health status at a medical level. Objective: The aim of this study was to develop a flexible and non-contact wearable electrocardiogram system, which can achieve real-time monitoring and primary diagnosis. Methods: A flexible electrocardiogram (ECG) acquisition device (wearable ECG) is designed based on flexible front-end circuit and textile capacitive electrodes, which are based on a conductive textile instead of rigid metal plates. The multi-domain feature space consists of time-domain features and frequency-domain statistical features, which can be used for classification via a back-propagation neural network (BPNN) and a support vector machine (SVM), both of which are optimized using a genetic algorithm. Results: The BPNN classifier exhibits good performance, with an accuracy of 98.33%, a sensitivity of 98.33%, a specificity of 99.63% and a positive predictive value of 97.85%. The SVM classifier achieves a higher classification accuracy of 98.89% and also performs better than the BPNN classifier in terms of the sensitivity, specificity and positive predictive value, achieving values of 98.89%, 99.81% and 98.89%, respectively. Conclusions: The experimental results reveal that there is a better classification effect of SVM when classifying normal heart rhythms and 8 types of arrhythmia. The proposed wearable ECG monitoring can aid in the primary diagnosis of certain heart diseases.

  • Smartphone applications and its role in foot and ankle surgery

    Date Submitted: Jul 19, 2020

    Open Peer Review Period: Jul 19, 2020 - Sep 13, 2020

    Background: The coronavirus disease 19 (COVID-19) pandemic has exposed inherent weaknesses in global healthcare systems. Conversely, it has encouraged innovation, research and collaboration. Digital t...

    Background: The coronavirus disease 19 (COVID-19) pandemic has exposed inherent weaknesses in global healthcare systems. Conversely, it has encouraged innovation, research and collaboration. Digital technology and AI has the ability to tackle these difficulties via the use of applications. However, the reliability and validity of unregulated medical applications must be questioned. The aim of this study was to review surgical foot and ankle themed applications and specifically assess the level of involvement from medical professionals in the design and content.The orthopaedic apps currently available have a variety of uses – they can be related to patient education, physician education, clinical evaluation, clinical treatment and surgical training. As of April 2020 there were 2.56 million apps available to download on Google Play, making it the largest app store on the market . Apple's app Store is the second-largest with approximately 1.85 million Apps available for iOS . Smartphone Apps provide platform for surgeons and software developers to collaborate and create novel tools to assist surgeons in practice and education. The purpose of this review is to identify and assess all smartphone apps related to the field of foot and ankle surgery. Objective: To summarize the most popular and useful foot and ankle apps. To provide an overview about app usage, customer satisfaction and availability. To provide recommendations to the foot and ankle community regarding medical profession involvement in the development of these apps. Methods: A team of reviewers searched the The App Store (iOS), Google Play (Android) and the BlackBerry App World (Blackberry) for foot and ankle themed applications. Due to Official shut down of blackberry World on 31st December 2019 and most of Blackberry devices since 2015 no longer used Blackberry 10operating system but used Android reviews were restricted to Android and iOS stores. The following search terms were used: bunions, ankle sprains, diabetic foot, foot and ankle deformities, pre-op templating, Patho-anatomy, post-operative rehab, gait, measurement of clinical angles of foot and ankle. A qualitative analysis of the data collected was performed. Data collected included target audience of the apps, patient and healthcare worker involvement and customer satisfaction reviews. The total number of applications and their availability in the UK were also noted Results: 35 individual foot and ankle themed applications were identified. 30 applications had customer satisfaction ratings, 11 applications were predominantly health-worker centric and 3 were patient centered. 23 applications had medical professional involvement in their development or content. Conclusions: Lack of involvement of medical professionals and scientific validation is of major concern hence there should be Industry code of conduct for a balance for ensuring patient safety while supporting innovation in development. The benefits of applications are offset by the lack of Foot and ankle specification. There is relatively little medical professional involvement in their design. Increased regulation is required to improve accountability of application content

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