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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: Unsplash; Copyright: Brian McGowan; URL: https://unsplash.com/photos/GmKHxZZJcb4; License: Licensed by JMIR.

    Digital Media’s Role in the COVID-19 Pandemic

    Abstract:

    The severe acute respiratory syndrome coronavirus 2 outbreak has had a significant impact on global health, the economy, and society as a whole. Various measures are being taken to respond to the pandemic, with digital media playing a pivotal role, especially in the use of visual data to disseminate information, mobile health to coordinate medical resources, social media to promote public health campaigns, and digital tools to assist population management and disease tracing. However, digital media also faces some challenges like misinformation, lack of guidance, and information leakage. We encourage the increased use of digital media with a focus on improving trust, building social solidarity, reducing chaos, educating the public on prevention measures, and reducing the medical burden in facility-based sites.

  • Video-call in acute geriatric unit. Source: Image created by the authors; Copyright: The authors; URL: http://mhealth.jmir.org/2020/9/e21845/; License: Creative Commons Attribution (CC-BY).

    Communication Technology Preferences of Hospitalized and Institutionalized Frail Older Adults During COVID-19 Confinement: Cross-Sectional Survey Study

    Abstract:

    Background: Technological communication methods such as telephone calls and video calls can help prevent social isolation and loneliness in frail older adults during confinement. Objective: Our objectives were to determine which virtual communication method (ie, telephone call or video call) was preferred by confined older hospital patients and nursing home residents and the variables influencing this preference. Methods: The TOVID (Telephony Or Videophony for Isolated elDerly) study was a cross-sectional study that was designed to examine the preference between telephone calls and video calls among frail older adults who were either hospitalized in a geriatric acute care unit or institutionalized in a long-term care and nursing home during the COVID-19 confinement period. Results: A total of 132 older people were surveyed between March 25 and May 11, 2020 (mean age 88.2 years, SD 6.2); 79 (59.8%) were women. Patients hospitalized in the geriatric acute care unit were more able to establish communication independently than residents institutionalized in the long-term care and nursing home (P=.03) and were more satisfied with their communication experiences (P=.02). Overall, older people tended to favor telephone calls (73/132, 55.3%) over video calls (59/132, 44.7%); however, their satisfaction degree was similar regardless of the chosen method (P=.1), with no effect of age (P=.97) or gender (P=.2). In the geriatric acute care unit, the satisfaction degrees were similar for telephone calls (40/41, 98%) and video calls (33/38, 87%) in older patients (P=.10). Conversely, in the long-term care and nursing home, residents were more satisfied with the use of video calls to communicate with their relatives (14/15, 93%) versus the use of telephone calls (6/12, 50%; P=.02). Conclusions: Older people confined to health care settings were able to complete telephone calls more independently than video calls, and they tended to use telephone calls more often than video calls. The satisfaction degrees were similar with both modalities and even greater with video calls among long-term care and nursing home residents when they were given assistance to establish communication. Trial Registration: ClinicalTrials.gov NCT04333849: https://www.clinicaltrials.gov/ct2/show/NCT04333849.

  • Source: Freepik; Copyright: freepik; URL: https://www.freepik.com/free-photo/close-up-senior-playing-music-mobile_6108867.htm; License: Licensed by JMIR.

    Effect of Voluntary Participation on Mobile Health Care in Diabetes Management: Randomized Controlled Open-Label Trial

    Abstract:

    Background: The role of mobile health care (mHealth) in glycemic control has been investigated, but its impact on self-management skills and its psychological aspects have not been studied. Objective: We evaluated the efficacy of mHealth-based diabetes self-management education and the effect of voluntary participation on its effects. Methods: This study was a randomized controlled open-label trial conducted for 6 months at Kangbuk Samsung Hospital. Participants in the control group (n=31) maintained their previous diabetes management strategies. Participants in the intervention group (n=41) additionally received mHealth-based diabetes self-management education through a mobile app and regular individualized feedback from health care professionals. The primary outcome was change in glycated hemoglobin (HbA1c) level over 6 months between the 2 groups (intervention versus control) and within each group (at 6 months versus baseline). The secondary outcomes were changes in body mass index, blood pressure, lipid profile, and questionnaire scores (the Korean version of the Summary of Diabetes Self-Care Activities Questionnaire, an Audit of Diabetes Dependent Quality of Life, the Appraisal of Diabetes Scale, and Problem Areas in Diabetes) over 6 months between groups and within each group. Results: A total of 66 participants completed this study. HbA1c (P=.04), total cholesterol level (P=.04), and Problem Areas in Diabetes scores (P=.02) significantly decreased; total diet (P=.03) and self-monitoring of blood glucose level scores (P=.01), based on the Summary of Diabetes Self-Care Activities Questionnaire, markedly increased within the intervention group. These significant changes were observed in self-motivated participants who were recruited voluntarily via advertisements. Conclusions: mHealth-based diabetes self-management education was effective at improving glycemic control and diabetes self-management skills and lowering diabetes-related distress in voluntary participants. Trial Registration: ClinicalTrials.gov NCT03468283; http://clinicaltrials.gov/ct2/show/NCT03468283

  • Source: Pixabay; Copyright: Myriams-Fotos; URL: https://pixabay.com/photos/non-smoking-cigarette-box-cigarettes-2383236/; License: Licensed by JMIR.

    Implementing Facilitated Access to a Text Messaging, Smoking Cessation Intervention Among Swedish Patients Having Elective Surgery: Qualitative Study of...

    Abstract:

    Background: There is strong evidence that short-term smoking cessation before surgery can reduce postoperative morbidity. There are, however, several structural problems in health care systems concerning how to implement smoking cessation interventions in routine practice for preoperative patients. Objective: This study aimed to analyze the implementation of a text messaging, smoking cessation intervention targeting patients having elective surgery. Implementation of facilitated access (ie, referral from practitioners) and the perceived usefulness among patients were investigated. Elective surgery is defined as scheduled, nonacute surgery. Methods: A qualitative study was carried out at two medium-sized hospitals in the south of Sweden. The implementation of facilitated access was investigated during a 12-month period from April 2018 to April 2019. Facilitated access was conceptualized as specialists recommending the text messaging intervention to patients having elective surgery. Implementation was explored in terms of perceptions about the intervention and behaviors associated with implementation; that is, how patients used the intervention and how specialists behaved in facilitating usage among patients. Two focus groups with smoking cessation specialists and 10 individual interviews with patients were carried out. Qualitative content analysis was used to analyze the data. Results: Two main categories were identified from the focus group data with smoking cessation specialists: implementation approach and perceptions about the intervention. The first category, implementation approach, referred to how specialists adapted their efforts to situational factors and to the needs and preferences of patients, and how building of trust with patients was prioritized. The second category, perceptions about the intervention, showed that specialists thought the content and structure of the text messaging intervention felt familiar and worked well as a complement to current practice. Two categories were identified from the patient interview data: incorporating new means of support from health care and determinants of use. The first category referred to how patients adopted and incorporated the intervention into their smoking cessation journey. Patients were receptive, shared the text messages with friends and family, humanized the text messages, and used the messages as a complement to other strategies to quit smoking. The second category, determinants of use, referred to aspects that influenced how and when patients used the intervention and included the following: timing of the intervention and text messages, motivation to change, and perceptions of the mobile phone medium. Conclusions: Smoking cessation specialists adopted an active role in implementing the intervention by adapting their approach and fitting the intervention into existing routines. Patients showed strong motivation to change and openness to incorporate the intervention into their behavior change journey; however, the timing of the intervention and messages were important in optimizing the support. A text messaging, smoking cessation intervention can be a valuable and feasible way to reach smoking patients having elective surgery.

  • One Drop's fully-integrated diabetes digital therapeutics solution. Source: Image created by the authors; Copyright: The Authors; URL: http://mhealth.jmir.org/2020/9/e16745/; License: Creative Commons Attribution (CC-BY).

    One Drop App With an Activity Tracker for Adults With Type 1 Diabetes: Randomized Controlled Trial

    Abstract:

    Background: In 2017, mobile app support for managing diabetes was available to 64% of the global population of adults with diabetes. One Drop’s digital therapeutics solution includes an evidence-based mobile app with global reach, a Bluetooth-connected glucometer, and in-app coaching from Certified Diabetes Educators. Among people with type 1 diabetes and an estimated hemoglobin A1c level≥7.5%, using One Drop for 3 months has been associated with an improved estimated hemoglobin A1c level of 22.2 mg/dL (–0.80%). However, the added value of integrated activity trackers is unknown. Objective: We conducted a pragmatic, remotely administered randomized controlled trial to evaluate One Drop with a new-to-market activity tracker against One Drop only on the 3-month hemoglobin A1c level of adults with type 1 diabetes. Methods: Social media advertisements and online newsletters were used to recruit adults (≥18 years old) diagnosed (≥1 year) with T1D, naïve to One Drop’s full solution and the activity tracker, with a laboratory hemoglobin A1c level≥7%. Participants (N=99) were randomized to receive One Drop and the activity tracker or One Drop only at the start of the study. The One Drop only group received the activity tracker at the end of the study. Multiple imputation, performed separately by group, was used to correct for missing data. Analysis of covariance models, controlling for baseline hemoglobin A1c, were used to evaluate 3-month hemoglobin A1c differences in intent-to-treat (ITT) and per protocol (PP) analyses. Results: The enrolled sample (N=95) had a mean age of 41 (SD 11) years, was 73% female, 88% White, diagnosed for a mean of 20 (SD 11) years, and had a mean hemoglobin A1c level of 8.4% (SD 1.2%); 11% of the participants did not complete follow up. Analysis of covariance assumptions were met for the ITT and PP models. In ITT analysis, participants in the One Drop and activity tracker condition had a significantly lower 3-month hemoglobin A1c level (mean 7.9%, SD 0.60%, 95% CI 7.8-8.2) than that of the participants in the One Drop only condition (mean 8.4%, SD 0.62%, 95% CI 8.2-8.5). In PP analysis, participants in the One Drop and activity tracker condition also had a significantly lower 3-month hemoglobin A1c level (mean 7.9%, SD 0.59%, 95% CI 7.7-8.1) than that of participants in the One Drop only condition (mean 8.2%, SD 0.58%, 95% CI 8.0-8.4). Conclusions: Participants exposed to One Drop and the activity tracker for the 3-month study period had a significantly lower 3-month hemoglobin A1c level compared to that of participants exposed to One Drop only during the same timeframe. One Drop and a tracker may work better together than alone in helping people with type 1 diabetes. Trial Registration: ClinicalTrials.gov NCT03459573; https://clinicaltrials.gov/ct2/show/NCT03459573.

  • Source: Image created by the Authors; Copyright: The Authors; URL: http://mhealth.jmir.org/2020/9/e19796/; License: Creative Commons Attribution (CC-BY).

    Mobile Health Apps on COVID-19 Launched in the Early Days of the Pandemic: Content Analysis and Review

    Abstract:

    Background: Mobile health (mHealth) app use is a major concern because of the possible dissemination of misinformation that could harm the users. Particularly, it can be difficult for health care professionals to recommend a suitable app for coronavirus disease (COVID-19) education and self-monitoring purposes. Objective: This study aims to analyze and evaluate the contents as well as features of COVID-19 mobile apps. The findings are instrumental in helping health care professionals to identify suitable mobile apps for COVID-19 self-monitoring and education. The results of the mobile apps’ assessment could potentially help mobile app developers improve or modify their existing mobile app designs to achieve optimal outcomes. Methods: The search for the mHealth apps available in the android-based Play Store and the iOS-based App Store was conducted between April 18 and May 5, 2020. The region of the App Store where we performed the search was the United States, and a virtual private network app was used to locate and access COVID-19 mobile apps from all countries on the Google Play Store. The inclusion criteria were apps that are related to COVID-19 with no restriction in language type. The basic features assessment criteria used for comparison were the requirement for free subscription, internet connection, education or advisory content, size of the app, ability to export data, and automated data entry. The functionality of the apps was assessed according to knowledge (information on COVID-19), tracing or mapping of COVID-19 cases, home monitoring surveillance, online consultation with a health authority, and official apps run by health authorities. Results: Of the 223 COVID-19–related mobile apps, only 30 (19.9%) found in the App Store and 28 (44.4%) in the Play Store matched the inclusion criteria. In the basic features assessment, most App Store (10/30, 33.3%) and Play Store (10/28, 35.7%) apps scored 4 out of 7 points. Meanwhile, the outcome of the functionality assessment for most App Store apps (13/30, 43.3%) was a score of 3 compared to android-based apps (10/28, 35.7%), which scored 2 (out of the maximum 5 points). Evaluation of the basic functions showed that 75.0% (n=36) of the 48 included mobile apps do not require a subscription, 56.3% (n=27) provide symptom advice, and 41.7% (n=20) have educational content. In terms of the specific functions, more than half of the included mobile apps are official mobile apps maintained by a health authority for COVID-19 information provision. Around 37.5% (n=18) and 31.3% (n=15) of the mobile apps have tracing or mapping and home monitoring surveillance functions, respectively, with only 17% (n=8) of the mobile apps equipped with an online consultation function. Conclusions: Most iOS-based apps incorporate infographic mapping of COVID-19 cases, while most android-based apps incorporate home monitoring surveillance features instead of providing focused educational content on COVID-19. It is important to evaluate the contents and features of COVID-19 mobile apps to guide users in choosing a suitable mobile app based on their requirements.

  • Wearable UV sensor. Source: Image created by the authors; Copyright: The Authors; URL: http://mhealth.jmir.org/2020/9/e21243/; License: Creative Commons Attribution + Noncommercial + NoDerivatives (CC-BY-NC-ND).

    Testing Wearable UV Sensors to Improve Sun Protection in Young Adults at an Outdoor Festival: Field Study

    Abstract:

    Background: Australia and New Zealand have the highest skin cancer incidence rates worldwide, and sun exposure is the main risk factor for developing skin cancer. Sun exposure during childhood and adolescence is a critical factor in developing skin cancer later in life. Objective: This study aims to test the effectiveness of wearable UV sensors to increase sun protection habits (SPH) and prevent sunburn in adolescents. Methods: During the weeklong school leavers outdoor festival (November 2019) at the Gold Coast, Australia, registered attendees aged 15-19 years were recruited into the field study. Participants were provided with a wearable UV sensor and free sunscreen. The primary outcome was sun exposure practices using the SPH index. Secondary outcomes were self-reported sunburns, sunscreen use, and satisfaction with the wearable UV sensor. Results: A total of 663 participants were enrolled in the study, and complete data were available for 188 participants (188/663, 28.4% response rate). Participants provided with a wearable UV sensor significantly improved their use of sunglasses (P=.004) and sunscreen use both on the face (P<.001) and on other parts of the body (P=.005). However, the use of long-sleeve shirts (P<.001) and the use of a hat (P<.001) decreased. During the study period, 31.4% (59/188) of the participants reported receiving one or more sunburns. Satisfaction with the wearable UV sensor was high, with 73.4% (138/188) of participants reporting the UV sensor was helpful to remind them to use sun protection. Conclusions: Devices that target health behaviors when outdoors, such as wearable UV sensors, may improve use of sunscreen and sunglasses in adolescents.

  • Source: Freepik; Copyright: jcomp; URL: https://www.freepik.com/free-photo/elderly-female-used-smartphone-patient-bed-hospital_7361537.htm#page=1&query=woman%20sick%20phone&position=13; License: Licensed by JMIR.

    Mobile Breast Cancer e-Support Program for Chinese Women With Breast Cancer Undergoing Chemotherapy (Part 3): Secondary Data Analysis

    Abstract:

    Background: Many app-based interventions targeting women with breast cancer have been developed and tested for effectiveness. However, information regarding the evaluation of the usage of these interventions is scarce. A better understanding of usage data is important to determine how women use apps and how these interventions affect health outcomes. Objective: This study aimed to examine the usage duration and login frequency of an app-based intervention, the Breast Cancer e-Support (BCS) program, and to investigate the association between usage data and participants’ demographic and medical characteristics. Methods: This study is a secondary data analysis of a randomized controlled trial assessing the effectiveness of the BCS program. The BCS program contains four modules: Learning Forum, Discussion Forum, Ask-the-Expert Forum, and Your Story Forum. A total of 57 women in the intervention group accessed the BCS program during their 12-week chemotherapy. The app’s background system tracked the usage duration and login frequency for each forum and the entire BCS program. Results: The total usage duration per participant ranged from 0 to 9371 minutes, and the login frequency per participant ranged from 0 to 774 times. The Discussion Forum and the Learning Forum were the most frequently used modules. The general linear model showed that age, education, family monthly income, and employment were associated with BCS usage duration and/or login frequency. Age (F1,45=10.09, P=.003, B=115.34, 95% CI 42.22-188.47) and education level (F1,45=7.22, P=.01, B=1949.63, 95% CI 487.76-3411.50) were positively associated with the usage duration of the entire BCS program. Family monthly income was positively associated with the usage duration of the Learning Forum (F1,45=11.85, P=.001, B=1488.55, 95% CI 617.58-2359.51) and the login frequency of the entire BCS program (F1,45=4.47, P=.04, B=113.68, 95% CI 5.33-222.03). Employment was negatively associated with the usage duration of the Ask-the-expert Forum (F1,45=4.50, P=.04, B=–971.87, 95% CI –1894.66 to –49.07) and the Your Story Forum (F1,45=5.36, P=.03, B=–640.71, 95% CI –1198.30 to –83.11) and positively associated with the login frequency of the entire BCS program (F1,45=10.86, P=.002, B=192.88, 95% CI 75.01-310.74). No statistical differences were found between BCS usage data and cancer stage, BMI, comorbidity, types of surgery, or cycles of chemotherapy. Conclusions: Overall, this study found considerable variability in the usage of app-based interventions. When health care professionals incorporate app-based interventions into their routine care for women with breast cancer, the learning and discussion functions of apps should be strengthened to promote engagement. Additionally, characteristics of women with breast cancer, such as age, level of education, income, and employment status, should be taken in consideration to develop tailored apps that address their particular needs and therefore improve their engagement with the app. Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12616000639426; http://www.ANZCTR.org.au/ACTRN12616000639426.aspx

  • Source: Freepik; Copyright: pch.vector; URL: https://www.freepik.com/free-photo/focused-african-american-man-reading-shopping-list-smartphone_6628375.htm#page=1&query=grocery%20phone&position=1; License: Licensed by JMIR.

    Mobile Phone Apps for Food Allergies or Intolerances in App Stores: Systematic Search and Quality Assessment Using the Mobile App Rating Scale (MARS)

    Abstract:

    Background: Food allergies and intolerances are increasing worldwide, and mobile phone apps could be a promising tool for self-management of these issues. Objective: This study aimed to systemically search and assess food allergy or intolerance apps in app stores using the multidimensional Mobile App Rating Scale (MARS) to rate the objective and subjective quality and to identify critical points for future improvements. Methods: This systematic search identified apps through the keywords “food allergy,” “food intolerance,” and “allergens” in English, Spanish, and Italian in the Apple App Store (iOS) and Google Play Store (Android). The inclusion criteria were a user star rating of ≥3 (of 5 stars) to limit the selection to the most highly rated apps; ≥1000 reviews as an indicator of reliability; and the most recent update performed up to 2017. Then, the apps were divided according to their purpose (searching for allergen-free “food products,” “restaurants,” or recipes in “meal planners”) and evaluated on a scale of 1 to 5 points using the MARS in terms of (1) app classification category with a descriptive aim; (2) app subjective and objective quality categories comprised of engagement, functionality, esthetics, and information sections (Medline was searched for eligible apps to check whether they had been tested in trials); and (3) an optional app-specific section. Furthermore, the output and input features were evaluated. Differences between MARS sections and between app purposes and correlations among MARS sections, star ratings, and numbers of reviews were evaluated. Results: Of the 1376 apps identified, 14 were included: 12 related to food allergies and intolerances that detect 2-16 food allergens and 2 related only to gluten intolerance. The mean (SD) MARS scores (maximum 5 points) were 3.8 (SD 0.4) for objective quality, highlighting whether any app had been tested in trials; 3.5 (SD 0.6) for subjective quality; and 3.6 (SD 0.7) for the app-specific section. Therefore, a rating ≥3 points indicated overall acceptable quality. From the between-section comparison, engagement (mean 3.5, SD 0.6) obtained significantly lower scores than functionality (mean 4.1, SD 0.6), esthetics (mean 4, SD 0.5), and information (mean 3.8, SD 0.4). However, when the apps were compared by purpose, critical points were identified: meal planner apps showed significantly higher engagement (mean 4.1, SD 0.4) than food product (mean 3.0, SD 0.6; P=.05) and restaurant (mean 3.2, SD 0.3; P=.02) apps. Conclusions: In this systematic search of food allergy or intolerance apps, acceptable MARS quality was identified, although the engagement section for food product and restaurant purpose apps should be improved and the included apps should be tested in trials. The critical points identified in this systematic search can help improve the innovativeness and applicability of future food allergy and intolerance apps.

  • Source: Pexels; Copyright: Ketut Subiyanto; URL: https://www.pexels.com/photo/crop-sportswoman-checking-information-on-tracker-4426515/; License: Licensed by JMIR.

    Accuracy of Sedentary Behavior–Triggered Ecological Momentary Assessment for Collecting Contextual Information: Development and Feasibility Study

    Abstract:

    Background: Sedentary behavior has received much attention in the scientific community over the past decade. There is growing evidence that sedentary behavior is negatively associated with physical and mental health. However, an in-depth understanding of the social and environmental context of sedentary behavior is missing. Information about sedentary behavior, such as how everyday sedentary behavior occurs throughout the day (eg, number and length of sedentary bouts), where, when, and with whom it takes place, and what people are doing while being sedentary, is useful to inform the development of interventions aimed at reducing sedentary time. However, examining everyday sedentary behavior requires specific methods. Objective: The purpose of this paper is (1) to introduce sedentary behavior–triggered Ecological Momentary Assessment (EMA) as a methodological advancement in the field of sedentary behavior research and (2) to examine the accuracy of sedentary behavior–triggered EMA in 3 different studies in healthy adults. Moreover, we compare the accuracy of sedentary behavior–triggered EMA to simulations of random-trigger designs. Methods: Sedentary behavior–triggered EMA comprises a continuous assessment of sedentary behavior via accelerometers and repeated contextual assessments via electronic diaries (ie, an application on a smartphone). More specifically, the accelerometer analyzes and transfers data regarding body position (a sitting or lying position, or an upright position) via Bluetooth Low Energy (BLE) to a smartphone in real time and triggers the deployment of questionnaires. Each time a participant spends a specified time (eg, 20 minutes) in a sedentary position, the e-diary triggers contextual assessments. To test the accuracy of this method, we calculated a percentage score for all triggered prompts in relation to the total number of bouts that could trigger a prompt. Results: Based on the accelerometer recordings, 29.3% (5062/17278) of all sedentary bouts were classified as moderate-to-long (20-40 minutes) and long bouts (≥ 41 minutes). On average, the accuracy by participant was 82.77% (3339/4034; SD 21.01%, range 71.00-88.22%) on the study level. Compared to simulations of random prompts (every 120 minutes), the number of triggered prompts was up to 47.9% (n=704) higher through the sedentary behavior–triggered EMA approach. Nearly 40% (799/2001) of all prolonged sedentary bouts (≥ 20 minutes) occurred during work, and in 57% (1140/2001) of all bouts, the participants were not alone. Conclusions: Sedentary behavior–triggered EMA is an accurate method for collecting contextual information on sedentary behavior in daily life. Given the growing interest in sedentary behavior research, this sophisticated approach offers a real advancement as it can be used to collect social and environmental contextual information or to unravel dynamic associations. Furthermore, it can be modified to develop sedentary behavior–triggered mHealth interventions.

  • Source: Unsplash; Copyright: Yunmai; URL: https://unsplash.com/photos/5jctAMjz21A; License: Licensed by JMIR.

    Data Imputation and Body Weight Variability Calculation Using Linear and Nonlinear Methods in Data Collected From Digital Smart Scales: Simulation and...

    Abstract:

    Background: Body weight variability (BWV) is common in the general population and may act as a risk factor for obesity or diseases. The correct identification of these patterns may have prognostic or predictive value in clinical and research settings. With advancements in technology allowing for the frequent collection of body weight data from electronic smart scales, new opportunities to analyze and identify patterns in body weight data are available. Objective: This study aims to compare multiple methods of data imputation and BWV calculation using linear and nonlinear approaches Methods: In total, 50 participants from an ongoing weight loss maintenance study (the NoHoW study) were selected to develop the procedure. We addressed the following aspects of data analysis: cleaning, imputation, detrending, and calculation of total and local BWV. To test imputation, missing data were simulated at random and using real patterns of missingness. A total of 10 imputation strategies were tested. Next, BWV was calculated using linear and nonlinear approaches, and the effects of missing data and data imputation on these estimates were investigated. Results: Body weight imputation using structural modeling with Kalman smoothing or an exponentially weighted moving average provided the best agreement with observed values (root mean square error range 0.62%-0.64%). Imputation performance decreased with missingness and was similar between random and nonrandom simulations. Errors in BWV estimations from missing simulated data sets were low (2%-7% with 80% missing data or a mean of 67, SD 40.1 available body weights) compared with that of imputation strategies where errors were significantly greater, varying by imputation method. Conclusions: The decision to impute body weight data depends on the purpose of the analysis. Directions for the best performing imputation methods are provided. For the purpose of estimating BWV, data imputation should not be conducted. Linear and nonlinear methods of estimating BWV provide reasonably accurate estimates under high proportions (80%) of missing data.

  • Source: Image created by the authors; Copyright: The Authors; URL: http://mhealth.jmir.org/2020/9/e17083/; License: Creative Commons Attribution (CC-BY).

    Identification of Type 2 Diabetes Management Mobile App Features and Engagement Strategies: Modified Delphi Approach

    Abstract:

    Background: Diabetes is a significant public health issue. Saudi Arabia has the highest prevalence of type 2 diabetes mellitus (T2DM) in the Arab world. Currently, it affects 31.6% of the general population, and the prevalence of T2DM is predicted to rise to 45.36% by 2030. Mobile health (mHealth) offers improved and cost-effective care to people with T2DM. However, the efficiency of engagement strategies and features of this technology need to be reviewed and standardized according to stakeholder and expert perspectives. Objective: The main objective of this study was to identify the most agreed-upon features for T2DM self-management mobile apps; the secondary objective was to identify the most agreed-upon strategies that prompt users to use these apps. Methods: In this study, a 4-round modified Delphi method was applied by experts in the domain of diabetes care. Results: In total, 11 experts with a mean age of 47.09 years (SD 11.70) consented to participate in the study. Overall, 36 app features were generated. The group of experts displayed weak agreement in their ranking of intervention components (Kendall W=0.275; P<.001). The top 5 features included insulin dose adjustment according to carbohydrate counting and blood glucose readings (5.36), alerting a caregiver of abnormal or critical readings (6.09), nutrition education (12.45), contacts for guidance if required (12.64), and offering patient-specific education tailored to the user’s goals, needs, and blood glucose readings (12.90). In total, 21 engagement strategies were generated. Overall, the experts showed a moderate degree of consensus in their strategy rankings (Kendall W=0.454; P<.001). The top 5 engagement strategies included a user-friendly design (educational and age-appropriate design; 2.82), a free app (3.73), allowing the user to communicate or send information/data to a health care provider (HCP; 5.36), HCPs prescribing the mobile app in the clinic and asking about patients’ app use compliance during clinical visits (6.91), and flexibility and customization (7.91). Conclusions: This is the first study in the region consisting of a local panel of experts from the diabetes field gathering together. We used an iterative process to combine the experts’ opinions into a group consensus. The results of this study could thus be useful for health app developers and HCPs and inform future decision making on the topic.

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    Date Submitted: Sep 15, 2020

    Open Peer Review Period: Sep 15, 2020 - Nov 10, 2020

    Background: Rapid penetration and demonstrated efficacy of mobile applications suggested the feasibility of using mobile technologies to manage supportive care needs among patients with cancer. The ef...

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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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