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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: The Authors / Placeit; Copyright: JMIR Publications; URL: http://mhealth.jmir.org/2019/2/e11606; License: Creative Commons Attribution (CC-BY).

    The Current State of Mobile Phone Apps for Monitoring Heart Rate, Heart Rate Variability, and Atrial Fibrillation: Narrative Review

    Abstract:

    Background: Mobile phone apps capable of monitoring arrhythmias and heart rate (HR) are increasingly used for screening, diagnosis, and monitoring of HR and rhythm disorders such as atrial fibrillation (AF). These apps involve either the use of (1) photoplethysmographic recording or (2) a handheld external electrocardiographic recording device attached to the mobile phone or wristband. Objective: This review seeks to explore the current state of mobile phone apps in cardiac rhythmology while highlighting shortcomings for further research. Methods: We conducted a narrative review of the use of mobile phone devices by searching PubMed and EMBASE from their inception to October 2018. Potentially relevant papers were then compared against a checklist for relevance and reviewed independently for inclusion, with focus on 4 allocated topics of (1) mobile phone monitoring, (2) AF, (3) HR, and (4) HR variability (HRV). Results: The findings of this narrative review suggest that there is a role for mobile phone apps in the diagnosis, monitoring, and screening for arrhythmias and HR. Photoplethysmography and handheld electrocardiograph recorders are the 2 main techniques adopted in monitoring HR, HRV, and AF. Conclusions: A number of studies have demonstrated high accuracy of a number of different mobile devices for the detection of AF. However, further studies are warranted to validate their use for large scale AF screening.

  • Source: Pexels; Copyright: Helena Lopes; URL: https://www.pexels.com/photo/two-dinner-plates-on-square-brown-wooden-bar-table-693269/; License: Licensed by JMIR.

    Evaluating Mobile Health Apps for Customized Dietary Recording for Young Adults and Seniors: Randomized Controlled Trial

    Abstract:

    Background: The role of individual-tailored dietary recording in mobile phone health apps has become increasingly important in management of self-health care and population-based preventive service. The development of such mobile apps for user-centered designing is still challengeable and requires further scientific evidence. Objective: This study aims to conduct a randomized trial to assess the accuracy and time efficiency of two prototypes for dietary recoding utilization related to the input method of food intake. Methods: We first present an innovative combinatorial concept for dietary recording to account for dish variation. One prototype was a self-chosen tab app that featured choosing each food ingredient to synthesize an individual dish, whereas the other was an autonomous exhaustive list app that provided one selection from a comprehensive list of dish items. The concept included commercially available choices that allowed users to more accurately account for their individual food selection. The two mobile apps were compared in a head-to-head parallel randomized trial evaluation. Young adults (n=70, aged 18-29) and older adults (n=35, aged 55-73) were recruited and randomized into two groups for accuracy and response time evaluation based on 12 types of food items in use of the developed self-chosen tab and autonomous exhaustive list apps, respectively. Results: For the trials based on the self-chosen tab (53 participants) and autonomous exhaustive list groups (52 participants), the two prototypes were found to be highly accurate (>98%). The self-chosen tab app was found to be more efficient, requiring significantly less time for input of 11 of 12 items (P<.05). The self-chosen tab users occasionally neglected to select food attributes, an issue which did not occur in the autonomous exhaustive list group. Conclusions: Our study contributes through the scientific evaluation of the transformation step into prototype development to demonstrate that a self-chosen tab app has potentially better opportunity in effectiveness and efficiency. The combinatorial concept offers potential for dietary recording and planning which can account for high food item variability. Our findings on prototype development of diversified dietary recordings provide design consideration and user interaction for related further app development and improvement. Trial Registration: ISRCTN Registry ISRCTN86142301; http://www.isrctn.com/ ISRCTN86142301 (Archived by WebCite at http://www.webcitation.org/74YLEPYnS)

  • Health Coaching with mHealth. Source: The Authors; Copyright: The Authors; URL: http://mhealth.jmir.org/2019/1/e10988/; License: Licensed by JMIR.

    Evaluating Motivational Interviewing and Habit Formation to Enhance the Effect of Activity Trackers on Healthy Adults’ Activity Levels: Randomized...

    Abstract:

    Background: While widely used and endorsed, there is limited evidence supporting the benefits of activity trackers for increasing physical activity; these devices may be more effective when combined with additional strategies that promote sustained behavior change like motivational interviewing (MI) and habit development. Objective: This study aims to determine the utility of wearable activity trackers alone or in combination with these behavior change strategies for promoting improvements in active and sedentary behaviors. Methods: A sample of 91 adults (48/91 female, 53%) was randomized to receive a Fitbit Charge alone or in combination with MI and habit education for 12 weeks. Active and sedentary behaviors were assessed pre and post using research-grade activity monitors (ActiGraph and activPAL), and the development of habits surrounding the use of the trackers was assessed postintervention with the Self-Reported Habit Index. During the intervention, Fitbit wear time and activity levels were monitored with the activity trackers. Linear regression analyses were used to determine the influence of the trial on outcomes of physical activity and sedentary time. The influence of habits was examined using correlation coefficients relating habits of tracker use (wearing the tracker and checking data on the tracker and associated app) to Fitbit wear time and activity levels during the intervention and at follow-up. Results: Regression analyses revealed no significant differences by group in any of the primary outcomes (all P>.05). However, personal characteristics, including lower baseline activity levels (beta=–.49, P=.01) and lack of previous experience with pedometers (beta=–.23, P=.03) were predictive of greater improvements in moderate and vigorous physical activity. Furthermore, for individuals with higher activity levels at the baseline, MI and habit education were more effective for maintaining these activity levels when compared with receiving a Fitbit alone (eg, small increase of ~48 steps/day, d=0.01, vs large decrease of ~1830 steps/day, d=0.95). Finally, habit development was significantly related to steps/day during (r=.30, P=.004) and following the intervention (r=.27, P=.03). Conclusions: This study suggests that activity trackers may have beneficial effects on physical activity in healthy adults, but benefits vary based on individual factors. Furthermore, this study highlights the importance of habit development surrounding the wear and use of activity trackers and the associated software to promote increases in physical activity. Trial Registration: ClinicalTrials.gov NCT03837366; https://clinicaltrials.gov/ct2/show/NCT03837366

  • Log2Lose. Source: iStock by Getty; Copyright: silverkblack; URL: https://www.istockphoto.com/ca/photo/two-cheerful-mixed-race-curly-girlfriends-shopping-online-with-tablet-computer-and-gm898378948-247885988; License: Licensed by the authors.

    Log2Lose: Development and Lessons Learned From a Mobile Technology Weight Loss Intervention

    Abstract:

    Background: Providing financial incentives has gained popularity as a strategy to promote weight loss, but questions remain about how best to utilize them. A promising mobile health strategy provides users with near-real-time financial incentives based on both the process of weight loss (behavioral modification) and actual weight loss. To maximize the impact of this strategy, a methodology is needed to close the gap between the desired behavior and the financial incentive. Leveraging mobile health tools—such as mobile phone apps, cellular body weight scales that transmit data to physicians and researchers, and text messaging for instructions and encouragement—has the potential to close this gap. Objective: This study aimed to describe the development of an innovative technology-based solution and lessons learned from a feasibility trial—Log2Lose—that encouraged individuals to lose weight by providing near-real-time financial incentives for weight loss and/or dietary self-monitoring. Methods: We recruited participants (N=96) with a body mass index greater than or equal to 30 kg/m2 for a 24-week weight loss trial. Participants received a behavioral intervention of biweekly, in-person group sessions and were instructed to log a minimum number of daily calories in MyFitnessPal and to step on the BodyTrace cellular scale at least twice per week. In a 2×2 design, participants were randomized into 4 groups to receive financial incentives for the following: (group 1) weekly weight loss and dietary self-monitoring, (group 2) dietary self-monitoring only, (group 3) weekly weight loss only, or (group 4) no financial incentives. Diet and weight data from the devices were obtained through application programming interfaces. Each week, we applied algorithms to participants’ data to determine whether they qualified for a monetary incentive (groups 1-3). A text message notified these participants of whether they met weight loss and/or self-monitoring requirements to earn an incentive and the amount they earned or would have earned. The money was uploaded to a debit card. Results: Our custom-engineered software platform analyzed data from multiple sources, collated and processed the data to send appropriate text messages automatically, and informed study staff of the appropriate incentives. We present lessons learned from the development of the software system and challenges encountered with technology, data transmission, and participants (eg, lost connections or delayed communication). Conclusions: With consistent and constant validation checks and a robust beta test run, the process of analyzing data and determining eligibility for weekly incentives can be mostly automated. We were able to accomplish this project within an academic health system, which required significant security and privacy safeguards. Our success demonstrates how this methodology of automated feedback loops can provide health interventions via mobile technology. Trial Registration: ClinicalTrials.gov NCT02691260; https://clinicaltrials.gov/ct2/show/NCT02691260

  • Source: Image created by the Authors; Copyright: The Authors; URL: http://mhealth.jmir.org/2019/2/e11644/; License: Creative Commons Attribution (CC-BY).

    The MomConnect Nurses and Midwives Support Platform (NurseConnect): A Qualitative Process Evaluation

    Abstract:

    Background: Over the past decade, mobile health has steadily increased in low-income and middle-income countries. However, few platforms have been able to sustainably scale up like the MomConnect program in South Africa. NurseConnect was created as a capacity building component of MomConnect, aimed at supporting nurses and midwives in maternal and child health. The National Department of Health has committed to expanding NurseConnect to all nurses across the country, and an evaluation of the current user experience was conducted to inform a successful scale up. Objective: This study aims to evaluate the perception and use of NurseConnect by nurses and midwives to produce feedback that can be used to optimize the user experience as the platform continues to scale up. Methods: We conducted focus group discussions and in-depth interviews with 110 nurses and midwives from 18 randomly selected health care facilities across South Africa. Questions focused on mobile phone use, access to medical information and their experience with NurseConnect registration, as well as the content and different platforms. Results: All participants had mobile phones and communication through calls and messaging was the main use in both personal and work settings. Of 110 participants, 108 (98.2%) had data-enabled phones, and the internet, Google, and apps (South African National Department of Health Guidelines, iTriage, Drugs.com) were commonly used, especially to find information in the work setting. Of 110 participants, 62 (56.4%) were registered NurseConnect users and liked the message content, especially listeriosis and motivational messages, which created behavioral change in some instances. The mobisite and helpdesk, however, were underutilized because of a lack of information surrounding these platforms. Some participants did not trust medical information from websites and had more confidence in apps, while others associated a “helpdesk” with a call-in service, not a messaging one. Many of the unregistered participants had not heard of NurseConnect, and some cited data and time constraints as barriers to both registration and uptake. Conclusions: Mobile and smartphone penetration was very high, and participants often used their phone to find medical information. The NurseConnect messages were well-liked by all registered participants; however, the mobisite and helpdesk were underutilized owing to a lack of information and training around these platforms. Enhanced marketing and training initiatives that optimize existing social networks, as well as the provision of data and Wi-Fi, should be explored to ensure that registration improves, and that users are active across all platforms.

  • Source: Freepik; Copyright: Freepik; URL: https://www.freepik.com/free-photo/man-typing-message-on-smartphone_1466868.htm; License: Licensed by JMIR.

    Can Brief, Daily Training Using a Mobile App Help Change Maladaptive Beliefs? Crossover Randomized Controlled Trial

    Abstract:

    Background: Obsessive-compulsive disorder (OCD) is a disabling condition with a wide variety of clinical presentations including contamination fears, fear of harm, and relationship-related obsessions. Cognitive behavioral models of OCD suggest that OC symptoms result from catastrophic misinterpretations of commonly occurring intrusive experiences and associated dysfunctional strategies used to manage them. OCD-related maladaptive beliefs including inflated responsibility, importance and control of thoughts, perfectionism, and intolerance for uncertainty increase the likelihood of such misinterpretations. Objective: Considering accumulating evidence suggesting that mobile health (mHealth) apps based on cognitive-behavioral principles may lead to significant reductions in psychopathological symptoms, we assessed the effectiveness of a novel cognitive training app (GGRO) designed to challenge OCD-related beliefs. Methods: A total of 97 students were randomized to groups undertaking immediate-use (iApp) or delayed use (dApp) of GGRO. All participants were requested to complete Web-based assessments, with questionnaires relating to maladaptive beliefs, mood, and OC symptoms at baseline (T1), 15 days from baseline (T2), and 30 days from baseline (T3). Participants in iApp group started using the app at baseline and continued using the app for 15 consecutive days. They were then requested to stop using the app until T3. Participants in the dApp group were requested to wait for 15 days and only then start using the app (crossover) for 15 consecutive days. Results: All participants used the app for a mean of 14.07 (SD 1.41) days with 2.94 levels per day. Consistent with previous findings, app use was associated with medium-large effect size reductions in both iApp (n=51) and dApp (n=46) groups. In the iApp group, all effects remained significant during the 15 days of follow-up. Analyses focusing on the first two assessment occasions revealed significant treatment × repeated measures interactions on maladaptive beliefs, several OC symptom measures, and self-esteem. Conclusions: This study provides further evidence for the efficacy of GGRO as a mobile-delivered training exercise that is useful for reducing OCD-related beliefs and symptoms. Trial Registration: ClinicalTrials.gov NCT03571464; https://clinicaltrials.gov/ct2/show/NCT03571464 (Archived by WebCite at http://www.webcitation.org/7675sYPsH)

  • Pain management apps (montage). Source: JMIR Publications / Placeit; Copyright: JMIR Publications; URL: http://mhealth.jmir.org/2019/2/e13080/; License: Creative Commons Attribution (CC-BY).

    Evaluation of Self-Management Support Functions in Apps for People With Persistent Pain: Systematic Review

    Abstract:

    Background: Smartphone apps are a potential mechanism for development of self-management skills in people with persistent pain. However, the inclusion of best-practice content items in available pain management apps fostering core self-management skills for self-management support is not known. Objective: The aim of the study was to evaluate the contents of smartphone apps providing information on pain management strategies for people with persistent pain facilitating self-management support and to appraise the app quality. Methods: A systematic search was performed in the New Zealand App Store and Google Play Store. Apps were included if they were designed for people with persistent pain, provided information on pain self-management strategies, and were available in English. App contents were evaluated using an a priori 14-item self-management support (SMS-14) checklist. App quality was assessed using the 23-item Mobile Apps Rating Scale. Results: Of the 939 apps screened, 19 apps met the inclusion criteria. Meditation and guided relaxation were the most frequently included self-management strategies. Overall, the included apps met a median of 4 (range 1-8) of the SMS-14 checklist. A total of 3 apps (Curable, PainScale-Pain Diary and Coach, and SuperBetter) met the largest number of items (8 out of 14) to foster self-management of pain. Self-monitoring of symptoms (n=11) and self-tailoring of strategies (n=9) were frequently featured functions, whereas a few apps had features facilitating social support and enabling communicating with clinicians. No apps provided information tailored to the cultural needs of the user. The app quality mean scores using Mobile Apps Rating Scale ranged from 2.7 to 4.5 (out of 5.0). Although use of 2 apps (Headspace and SuperBetter) has been shown to improve health outcomes, none of the included apps have been evaluated in people with persistent pain. Conclusions: Of the 3 apps (Curable, PainScale-Pain Diary and Coach, and SuperBetter) that met the largest number of items to support skills in self-management of pain, 2 apps (PainScale-Pain Diary and Coach and SuperBetter) were free, suggesting the potential for using apps as a scalable, wide-reaching intervention to complement face-to-face care. However, none provided culturally tailored information. Although 2 apps (Headspace and SuperBetter) were validated to show improved health outcomes, none were tested in people with persistent pain. Both users and clinicians should be aware of such limitations and make informed choices in using or recommending apps as a self-management tool. For better integration of apps in clinical practice, concerted efforts are required among app developers, clinicians, and people with persistent pain in developing apps and evaluating for clinical efficacy.

  • Exercise and mHealth. Source: Flickr; Copyright: Marco Verch; URL: http://www.flickr.com/photos/160866001@N07/44573043810; License: Creative Commons Attribution (CC-BY).

    Technology-Supported Self-Guided Nutrition and Physical Activity Interventions for Adults With Cancer: Systematic Review

    Abstract:

    Background: Nutrition and physical activity interventions are important components of cancer care. With an increasing demand for services, there is a need to consider flexible, easily accessible, and tailored models of care while maintaining optimal outcomes. Objective: This systematic review describes and appraises the efficacy of technology-supported self-guided nutrition and physical activity interventions for people with cancer. Methods: A systematic search of multiple databases from 1973 to July 2018 was conducted for randomized and nonrandomized trials investigating technology-supported self-guided nutrition and physical activity interventions. Risk of bias was assessed using the Cochrane Risk of Bias tool. Outcomes included behavioural, health-related, clinical, health service, or financial measures. Results: Sixteen randomized controlled trials representing 2684 participants were included. Most studies were web-based interventions (n=9) and had a 12-week follow-up duration (n=8). Seven studies assessed dietary behaviour, of which two reported a significant benefit on diet quality or fruit and vegetable intake. Fifteen studies measured physical activity behaviour, of which eight studies reported a significant improvement in muscle strength and moderate-to-vigorous physical activity. Four of the nine studies assessing the health-related quality of life (HRQoL) reported a significant improvement in global HRQoL or a domain subscale. A significant improvement in fatigue was found in four of six studies. Interpretation of findings was influenced by inadequate reporting of intervention description and compliance. Conclusions: This review identified short-term benefits of technology-supported self-guided interventions on the physical activity level and fatigue and some benefit on dietary behaviour and HRQoL in people with cancer. However, current literature demonstrates a lack of evidence for long-term benefit. Trial Registration: PROSPERO CRD42017080346; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=80346

  • Physical activity app (montage). Source: The Authors / Placeit; Copyright: JMIR Publications; URL: http://mhealth.jmir.org/2019/2/e11847/; License: Creative Commons Attribution (CC-BY).

    Efficacy and Effectiveness of Mobile Health Technologies for Facilitating Physical Activity in Adolescents: Scoping Review

    Abstract:

    Background: Increasing physical activity (PA) levels in adolescents aged 12 to 18 years is associated with prevention of unhealthy weight gain and improvement in cardiovascular fitness. The widespread availability of mobile health (mHealth) and wearable devices offers self-monitoring and motivational features for increasing PA levels and improving adherence to exercise programs. Objective: The aim of this scoping review was to identify the efficacy or effectiveness of mHealth intervention strategies for facilitating PA among adolescents aged 12 to 18 years. Methods: We conducted a systematic search for peer-reviewed studies published between 2008 and 2018 in the following electronic databases: PubMed, Google Scholar, PsychINFO, or SportDiscus. The search terms used included mHealth or “mobile health” or apps, “physical activity” or exercise, children or adolescents or teens or “young adults” or kids, and efficacy or effectiveness. Articles published outside of the date range (July 2008 to October 2018) and non-English articles were removed before abstract review. Three reviewers assessed all abstracts against the inclusion and exclusion criteria. Any uncertainties or differences in opinion were discussed as a group. The inclusion criteria were that the studies should (1) have an mHealth component, (2) target participants aged between 12 and 18 years, (3) have results on efficacy or effectiveness, and (4) assess PA-related outcomes. Reviews, abstracts only, protocols without results, and short message service text messaging–only interventions were excluded. We also extracted potentially relevant papers from reviews. At least 2 reviewers examined all full articles for fit with the criteria and extracted data for analysis. Data extracted from selected studies included study population, study type, components of PA intervention, and PA outcome results. Results: Overall, 126 articles were initially identified. Reviewers pulled 18 additional articles from excluded review papers. Only 18 articles were passed onto full review, and 16 were kept for analysis. The included studies differed in the sizes of the study populations (11-607 participants), locations of the study sites (7 countries), study setting, and study design. Overall, 5 mHealth intervention categories were identified: website, website+wearable, app, wearable+app, and website+wearable+app. The most common measures reported were subjective weekly PA (4/13) and objective daily moderate-to-vigorous PA (5/13) of the 19 different PA outcomes assessed. Furthermore, 5 of 13 studies with a control or comparison group showed a significant improvement in PA outcomes between the intervention group and the control or comparison group. Of those 5 studies, 3 permitted isolation of mHealth intervention components in the analysis. Conclusions: PA outcomes for adolescents improved over time through mHealth intervention use; however, the lack of consistency in chosen PA outcome measures, paucity of significant outcomes via between-group analyses, and the various study designs that prevent separating the effects of intervention components calls into question their true effect.

  • Source: Flickr; Copyright: Brad Flickinger; URL: https://www.flickr.com/photos/56155476@N08/6660064659/; License: Creative Commons Attribution (CC-BY).

    Using Twitter to Detect Psychological Characteristics of Self-Identified Persons With Autism Spectrum Disorder: A Feasibility Study

    Abstract:

    Background: More than 3.5 million Americans live with autism spectrum disorder (ASD). Major challenges persist in diagnosing ASD as no medical test exists to diagnose this disorder. Digital phenotyping holds promise to guide in the clinical diagnoses and screening of ASD. Objective: This study aims to explore the feasibility of using the Web-based social media platform Twitter to detect psychological and behavioral characteristics of self-identified persons with ASD. Methods: Data from Twitter were retrieved from 152 self-identified users with ASD and 182 randomly selected control users from March 22, 2012 to July 20, 2017. We conducted a between-group comparative textual analysis of tweets about repetitive and obsessive-compulsive behavioral characteristics typically associated with ASD. In addition, common emotional characteristics of persons with ASD, such as fear, paranoia, and anxiety, were examined between groups through textual analysis. Furthermore, we compared the timing of tweets between users with ASD and control users to identify patterns in communication. Results: Users with ASD posted a significantly higher frequency of tweets related to the specific repetitive behavior of counting compared with control users (P<.001). The textual analysis of obsessive-compulsive behavioral characteristics, such as fixate, excessive, and concern, were significantly higher among users with ASD compared with the control group (P<.001). In addition, emotional terms related to fear, paranoia, and anxiety were tweeted at a significantly higher rate among users with ASD compared with control users (P<.001). Users with ASD posted a smaller proportion of tweets during time intervals of 00:00-05:59 (P<.001), 06:00-11:59 (P<.001), and 18:00-23.59 (P<.001), as well as a greater proportion of tweets from 12:00 to 17:59 (P<.001) compared with control users. Conclusions: Social media may be a valuable resource for observing unique psychological characteristics of self-identified persons with ASD. Collecting and analyzing data from these digital platforms may afford opportunities to identify the characteristics of ASD and assist in the diagnosis or verification of ASD. This study highlights the feasibility of leveraging digital data for gaining new insights into various health conditions.

  • Source: Image created by the Authors; Copyright: Atinkut Alamirrew Zeleke; URL: http://mhealth.jmir.org/2019/2/e10995/; License: Creative Commons Attribution (CC-BY).

    Evaluation of Electronic and Paper-Pen Data Capturing Tools for Data Quality in a Public Health Survey in a Health and Demographic Surveillance Site,...

    Abstract:

    Background: Periodic demographic health surveillance and surveys are the main sources of health information in developing countries. Conducting a survey requires extensive use of paper-pen and manual work and lengthy processes to generate the required information. Despite the rise of popularity in using electronic data collection systems to alleviate the problems, sufficient evidence is not available to support the use of electronic data capture (EDC) tools in interviewer-administered data collection processes. Objective: This study aimed to compare data quality parameters in the data collected using mobile electronic and standard paper-based data capture tools in one of the health and demographic surveillance sites in northwest Ethiopia. Methods: A randomized controlled crossover health care information technology evaluation was conducted from May 10, 2016, to June 3, 2016, in a demographic and surveillance site. A total of 12 interviewers, as 2 individuals (one of them with a tablet computer and the other with a paper-based questionnaire) in 6 groups were assigned in the 6 towns of the surveillance premises. Data collectors switched the data collection method based on computer-generated random order. Data were cleaned using a MySQL program and transferred to SPSS (IBM SPSS Statistics for Windows, Version 24.0) and R statistical software (R version 3.4.3, the R Foundation for Statistical Computing Platform) for analysis. Descriptive and mixed ordinal logistic analyses were employed. The qualitative interview audio record from the system users was transcribed, coded, categorized, and linked to the International Organization for Standardization 9241-part 10 dialogue principles for system usability. The usability of this open data kit–based system was assessed using quantitative System Usability Scale (SUS) and matching of qualitative data with the isometric dialogue principles. Results: From the submitted 1246 complete records of questionnaires in each tool, 41.89% (522/1246) of the paper and pen data capture (PPDC) and 30.89% (385/1246) of the EDC tool questionnaires had one or more types of data quality errors. The overall error rates were 1.67% and 0.60% for PPDC and EDC, respectively. The chances of more errors on the PPDC tool were multiplied by 1.015 for each additional question in the interview compared with EDC. The SUS score of the data collectors was 85.6. In the qualitative data response mapping, EDC had more positive suitability of task responses with few error tolerance characteristics. Conclusions: EDC possessed significantly better data quality and efficiency compared with PPDC, explained with fewer errors, instant data submission, and easy handling. The EDC proved to be a usable data collection tool in the rural study setting. Implementation organization needs to consider consistent power source, decent internet connection, standby technical support, and security assurance for the mobile device users for planning full-fledged implementation and integration of the system in the surveillance site.

  • Source: Health.mil (Brannon Deugan); Copyright: US Navy; URL: https://health.mil/News/Articles/2018/10/04/Mammograms-recommended-for-early-detection-of-breast-cancer; License: Public Domain (CC0).

    Research-Tested Mobile Apps for Breast Cancer Care: Systematic Review

    Abstract:

    Background: The use of mobile health (mHealth) apps in clinical settings is increasing widely. mHealth has been used to promote prevention, improve early detection, manage care, and support survivors and chronic patients. However, data on the efficacy and utility of mHealth apps are limited. Objective: The main objective of this review was to provide an overview of the available research-tested interventions using mHealth apps and their impact on breast cancer care. Methods: A systematic search of Medline, PsycINFO, Embase, and Scopus was performed to identify relevant studies. From the selected studies, the following information was extracted: authors, publication date, study objectives, study population, study design, interventions’ features, outcome measures, and results. Results: We identified 29 empirical studies that described a health care intervention using an mHealth app in breast cancer care. Of these, 7 studies were about the use of an mHealth application in an intervention for breast cancer prevention and early detection, 12 targeted care management, and 10 focused on breast cancer survivors. Conclusions: Our results indicate consistent and promising findings of interventions using mHealth apps that target care management in breast cancer. Among the categories of mHealth apps focusing on survivorship, mHealth-based interventions showed a positive effect by promoting weight loss, improving the quality of life, and decreasing stress. There is conflicting and less conclusive data on the effect of mHealth apps on psychological dimensions. We advocate further investigation to confirm and strengthen these findings. No consistent evidence for the impact of interventions using mHealth apps in breast cancer prevention and early detection was identified due to the limited number of studies identified by our search. Future research should continue to explore the impact of mHealth apps on breast cancer care to build on these initial recommendations.

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  • eDiary of maternal care in the context of a home-visiting intervention for adolescent mothers in an urban deprived area of São Paulo, Brazil: a randomized controlled trial

    Date Submitted: Feb 12, 2019

    Open Peer Review Period: Feb 15, 2019 - Apr 12, 2019

    Background: Pregnancy during adolescence is a prevalent condition in low and middle-income countries (LMIC) associated with various adverse outcomes. However, testing early childhood development inter...

    Background: Pregnancy during adolescence is a prevalent condition in low and middle-income countries (LMIC) associated with various adverse outcomes. However, testing early childhood development interventions in LMIC can be challenging due to limited resources. The use of ambulatory assessment (AA) delivered via smartphone can be an alternative data collection method ideal to measure outcomes in an environment with adverse conditions. Objective: Our study had two objectives. First, to investigate the adequacy of an eDiary protocol to measure daily maternal care experience of participants. Second, to test the efficacy of a nurse home visiting intervention on child maternal care and parental well-being. Methods: We conducted a randomized controlled trial to test the efficacy of Primeiros Laços, a nurse home visiting program for adolescent mothers living in an urban deprived area of São Paulo, Brazil. One hundred and sixty-nine pregnant youth were assessed for eligibility criteria and 80 youth were included and randomized to intervention (n=40), and control group (care as usual, n=40). Primeiros Laços is a home visiting intervention delivered by trained nurses tailored to first-time pregnant adolescents and their children, starting during the first 16 weeks of pregnancy to the child’s 24 months. Participants were assessed by blind interviewers at 8-16 weeks of pregnancy (baseline), 30 weeks of pregnancy, 3, 6, and 12 months of child’s age. At 18 months participants were assessed regarding maternal care and parental well-being using a 7 consecutive days electronic daily diary (eDiary). The smartphone app was programmed to notify participants every day at 9:00 p.m. over a period of seven days. Results: We were able to contact 57 (71.3%) participants (29 intervention, 28 control) at 18 months of the child’s age. Forty-eight (84.2%) participants responded at least one day of the eDiary protocol. Our analyses showed the effect of the intervention on parental well-being (B=0.32, P=.015) and mother telling a story or singing to the child (OR=2.33, P=.012). Conclusions: eDiary was accepted by adolescent mothers living in an urban deprived area as a method of assessment. Our findings showed the efficacy of Primeiros Laços on improving maternal child care and parental well-being. Primeiros Laços is a promising intervention to promote maternal child care and well-being among low income adolescent mothers. Future studies can implement AA in LMIC via smartphones to measure mother and child behaviors. More frequent assessments should be implemented to further enhance temporal and ecological validity, and also to increase the scope of measured behaviors. Clinical Trial: Trial registration at clinicaltrial.gov: NCT02807818.

  • Predictors of Success Using a mHealth Intervention in Adults with Prediabetes: Results of a Pilot Study

    Date Submitted: Feb 14, 2019

    Open Peer Review Period: Feb 15, 2019 - Feb 22, 2019

    Background: About one-third of American adults have prediabetes and are at increased risk of type 2 diabetes. Mobile health (mHealth) technologies provide a scalable approach to diabetes prevention by...

    Background: About one-third of American adults have prediabetes and are at increased risk of type 2 diabetes. Mobile health (mHealth) technologies provide a scalable approach to diabetes prevention by encouraging physical activity (PA), weight loss, and adherence to a healthy diet in large numbers of patients. Objective: To identify factors associated with improvements in PA and glycated hemoglobin (A1c) measures among prediabetic adults who received a mobile intervention program (smartphone app in combination with a digital body weight scale) in a previously completed pilot study. Methods: We conducted a post hoc analysis of a 3-month prospective, single-arm, observational study using the Sweetch™ mHealth intervention among adults with prediabetes. Change in A1C was calculated as the difference between the 3-month and baseline A1C measurements and was categorized as decrease vs. no decrease. PA was evaluated using the total minutes and metabolic equivalent of task (MET)-hours per week. Change in MET-hours/week was categorized as increase vs. no increase. Age, sex, race, education, employment status, area deprivation, smartphone usage attitudes, and PA stage of change were compared between groups by outcomes of change in A1C and change in MET-hour/week. Results: A total of 37 adults received the final Sweetch mobile intervention and were included in the analysis. 62% were female and 81% were white, with average age of 57 years. The median [IQR] baseline A1C was 6.0% [5.8, 6.2]. A1C measure at 3-month was decreased in 24 (65%) participants when compared to baseline A1C. There was an inverse association between average MET-hours per week and change in A1C. Among participants whose A1C decreased vs. did not decrease, the MET-hours per week in last 2 weeks of study was 18.7 (8.4) and 15.0 (7.1), respectively (P=0.19), and the change in MET-hours per week was 2.1 (7.1) and 4.1(6.1), respectively (P=0.41). There were otherwise no statistically significant differences in participant factors by A1C and PA outcomes. Conclusions: In this small pilot study, Sweetch mHealth intervention achieved comparable A1C response prediabetic adults with different individual, sociodemographic and anthropometric characteristics. Clinical Trial: ClincialTrials.gov NCT02896010; https://clinicaltrials.gov/ct2/show/NCT02896010 (Archived by WebCite at http://www.webcitation.org/6xJYxrgse)

  • Who is tracking health on mobile devices: A Behavioral Logfile Analysis in Hong Kong

    Date Submitted: Feb 11, 2019

    Open Peer Review Period: Feb 12, 2019 - Feb 20, 2019

    Background: Health apps on mobile devices provide an unprecedented opportunity for ordinary people to develop social connections revolving around health issues. With increasing penetration of mobile d...

    Background: Health apps on mobile devices provide an unprecedented opportunity for ordinary people to develop social connections revolving around health issues. With increasing penetration of mobile devices and well-recorded behavioral data on such devices, it is desirable to employ digital traces on mobile devices, rather than self-reported measures, to capture the behavioral patterns underlying the use of mobile health apps in a more direct and valid way. Objective: The objectives of our study were to (1) assess the demographic predictors of the adoption of mobile health apps; (2) investigate the temporal pattern underlying the use of mobile health apps; (3) explore the impacts of demographic variables, temporal features, and app types on the use of mobile health apps. Methods: Log data of mobile devices was collected from a representative panel of about 2,500 users in Hong Kong. Users’ health app activities records were analyzed. We firstly conducted a binary logistic model to assess demographics predictors of user’s adoption status. Then we utilized a multi-level negative binomial regression to examine the impact of temporal pattern, app type, and user’s demographic characteristics on health app usage time. Results: It is found that 27.5% of mobile device users in Hong Kong adopt at least one type of health apps. Adopters of mobile health apps tend to be female and better educated. However, demographic characteristics do not showcase the predictive powers on the use of mobile health apps, except for the gender effect (B female vs male= -0.18, SE = 0.066, p<0.01). The use of mobile health apps demonstrates a significant temporal pattern, which is found to be moderately active during daytime and intensifying at weekends and night. Such temporal patterns in mobile health apps use are moderated by individuals’ demographic characteristics. Conclusions: Our findings suggest the importance of temporal patterns in understanding user’s mobile health app activities. Mobile health app developers should consider more about the demographic differences in temporal patterns when they develop the apps. Besides, our research also contribute to the promotion of mobile health apps by emphasizing the differences of usage needs for various groups of people.

  • Feasibility and Acceptability of a mHealth System to Self-track Antihypertensive Medication Adherence and Deliver SMS text message feedback on Adherence Patterns in Adults with Chronic Kidney Disease

    Date Submitted: Feb 10, 2019

    Open Peer Review Period: Feb 11, 2019 - Feb 18, 2019

    Background: Medication nonadherence occurs in as many as 50% of people yet studies for detecting nonadherence and delivering real-time interventions to improve adherence are lacking. mHealth technolog...

    Background: Medication nonadherence occurs in as many as 50% of people yet studies for detecting nonadherence and delivering real-time interventions to improve adherence are lacking. mHealth technologies show promise to support medication adherence. Commercially available off the shelf technology shows promise for developing interventions using existing technologies that are readily accessible and easy to use. Objective: The purpose of this study was to evaluate the feasibility and acceptability of using a mHealth system using commercially available off the shelf technology to self-track medication adherence and deliver near real-time short message service (SMS) text message feedback about medication adherence patterns. The mHealth system consists of a commercially available smart button device to self-track medication-taking, a companion smart phone app, a computer algorithm used to determine adherence to a prescribed medication and deliver a standard or tailored SMS text messages based on the timing of medication taking. Standard text messages provided participant feedback indicating that the smartphone app registered the button press, whereas tailored text messages provided feedback to reinforce habit formation based on the timing that medications were taken. Methods: A convenience sample of 5 adults with chronic kidney disease prescribed antihypertensive medication participated in a 52-day longitudinal study. The study was conducted in three phases with a standard text message sent in phases 1 (study day 1 – 14) and 3 (study day 15 - 45) and tailored text messages sent during phase 2 (study days 46 - 52) in response to participant self-tracking of medication taking using the mHealth system. Medication adherence was measured using two different methods: (1) the smart button used to self-track medication taking as part of the mHealth system, and (2) electronic medication monitoring caps. Concordance between these two methods was evaluated using the percentage of measurements made on the same day and occurring within +/- 5 minutes of one another. Acceptability was evaluated using qualitative feedback from participants. Results: Five patients with chronic kidney disease stages 1-4 were enrolled in the study with the majority being men (60%), white (80%) and Hispanic/Latino (40%) of middle age (52.6 years; SD = 22.49; range 20- 70). The mHealth system was successfully initiated in the clinic setting for all enrolled participants. Of the expected 260 data points, 36.5% (n=95) were recorded with the smart button and 76.2% (n=198) with electronic monitoring. Concordant events (n=94) occurred 47.4% of the time and 58.5% occurred within +/- 5 minutes of one another. Participant comments suggested text messages were encouraging, and two participants thought messages that helped remind people who had a problem remembering to take medications would be a better approach. Conclusions: It was feasible to recruit participants in the clinic setting for a mHealth study and our system was successfully initiated for all enrolled participants in the clinic. The smart button is an innovative way to self-report measurement of adherence data including date and timing of medication taking not previously available from measures that rely on recall of adherence data. Although the selected smart button had poor concordance with electronic monitoring caps, participants were willing to use it to self-track medication adherence and found the mHealth system acceptable to use in most cases. The mHealth system has potential to provides real-time actionable information about medication taking, despite some noted limitations in the selected technologies.

  • Mobile-technology induced information dissemination on reversible contraceptives and reproductive health: Lessons from a controlled before-and-after study in rural India

    Date Submitted: Nov 1, 2018

    Open Peer Review Period: Feb 10, 2019 - Apr 7, 2019

    Background: Concern over the unavailability and non-use of reversible modern contraceptive methods in India has been expressed by researchers and activists since decades. New attempts to increase acce...

    Background: Concern over the unavailability and non-use of reversible modern contraceptive methods in India has been expressed by researchers and activists since decades. New attempts to increase access, availability and acceptance of reversible contraception instead of sole reliance on female sterilization need to be developed. mHealth initiatives may offer one way to serve the underprivileged populations in countries like India with challenges in sexual and reproductive health (SRH). Objective: To examine the impact of an mHealth intervention in enhancing knowledge, attitude and practice of reversible contraception in rural western India. Methods: A non-randomized controlled trial (before-and-after study in an intervention area and control area) in the Indian state of Maharashtra was implemented. The intervention was a project by a non-governmental organization (NGO) using a mobile SRH help line. A baseline survey and a follow-up survey were carried out in two public health centre (PHC) areas. The samples in both baseline and follow-up surveys were 405 respondents respectively. The effect of the intervention was estimated using logistic regression adjusted for gender by calculating robust standard errors to take into account clustering of individuals by the area (intervention or control). In each regression model, the effect of intervention was estimated by including a term for interaction between the intervention area and the period (before and after the intervention). The exponent of the regression coefficient of the interaction term corresponding to the period after the intervention along with the 95% confidence interval are reported here. This exponent corresponds to the odds. Calls received in the intervention were recorded and their topics analysed. Results: The current use of contraception (8 % increase in intervention area versus 21 % decrease in control area; 95% CI) and particularly the use of reversible contraception (18% increase in intervention area versus 2% increase in control area; 95% CI) have seen changes. Demand for wider SRH information beyond contraception was in high demand. Men and adolescents, in addition to married women, made use of the help line. Conclusions: A mobile help line that can be confidentially approached in the time most convenient to the client can help to provide necessary information and support to those who need reversible contraception or other confidential sexual health information. Services that integrate mHealth in a context-sensitive way to other face-to-face health care services add value to SRH services in rural India.

  • Pairing the Mobile Device with Student Health Coaches to Improve Blood Pressure Management

    Date Submitted: Feb 5, 2019

    Open Peer Review Period: Feb 8, 2019 - Apr 5, 2019

    Background: Hypertension is a significant problem in the United States, affecting 1 in 3 adults over the age of 18 and is associated with higher risk for cardiovascular disease and stroke. Prevalence...

    Background: Hypertension is a significant problem in the United States, affecting 1 in 3 adults over the age of 18 and is associated with higher risk for cardiovascular disease and stroke. Prevalence of hypertension is increased in medically underserved areas (MUAs). Mobile health technology, such as digital self-monitoring devices, has been shown to improve management of chronic health conditions, however, patients from MUAs have reduced access to these devices because of limited resources and low health literacy. Health coaches and peer training programs are a potentially cost-effective solution for the shortage of physicians available to manage hypertension in MUAs. Activating young people in a health coaching role is a promising strategy to improve community health. Objective: This pilot study aims to assess (1) the feasibility of training high school students as health technology coaches in MUAs (2) whether the addition of student health coaches to digital home monitoring improve the frequency of self-monitoring and overall blood pressure (BP) control. Methods: Fifteen high school students completed a 3-day health coaching training. Patients who had a documented diagnosis of hypertension were randomly assigned to 1 of 3 intervention arms. The “home monitor alone (HM)” group was provided a QardioArm cuff only to use at their convenience. The “student alone (S)” group was instructed to meet for 30 minutes once a week for 5 weeks with a health coach to create action plans for reducing BP. The “home monitor+student (HM+S)” group received both interventions. Results: Participants (n=27) were randomly assigned (9:9:9). All 15 students completed training, while 6/15 students (40%) completed all 5 meetings with their assigned patient. Barriers to feasibility included transportation and patient response drop-off at the end of the study. 92% of students rated their experience as “very good” or higher and 69% reported that this experience made them more likely to go into the medical field. There was a statistically significant difference in frequency of cuff use (HM+S vs HM groups, 37v17, p<0.01). The difference in baseline and final systolic BPs for HM+S, HM and S groups were -11 mmHg, -4 mmHg, and -8 mmHg, respectively. Though not a statistically significant difference between groups (p=0.89), the HM+S group demonstrated the largest reduction in systolic BP. Conclusions: This pilot demonstrated feasibility of pairing technology with young student coaches, though challenges existed. The HM+S group used their cuff more than HM group. Patients were more engaged in the HM+S group, which resulted in better BP control.

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