JMIR Publications

JMIR mHealth and uHealth

Mobile and tablet apps, ubiquitous and pervasive computing, wearable computing and domotics for health.

JMIR's Thomson Reuter Impact Factor of 4.636 for 2016
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Journal Description

JMIR mHealth and uHealth (JMU, ISSN 2291-5222) is a spin-off journal of JMIR, the leading eHealth journal (Impact Factor 2016: 5.175). JMIR mHealth and uHealth is indexed in PubMed, PubMed Central, and Science Citation Index Expanded (SCIE), and in June 2017 received a stunning inaugural Impact Factor of 4.636

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: FreeDigitalPhotos.net; Copyright: patrisyu; URL: http://www.freedigitalphotos.net/images/selfie-photo-p381328; License: Licensed by the authors.

    Improving Adherence to Web-Based and Mobile Technologies for People With Psychosis: Systematic Review of New Potential Predictors of Adherence

    Abstract:

    Background: Despite the boom in new technologically based interventions for people with psychosis, recent studies suggest medium to low rates of adherence to these types of interventions. The benefits will be limited if only a minority of service users adhere and engage; if specific predictors of adherence can be identified then technologies can be adapted to increase the service user benefits. Objective: The study aimed to present a systematic review of rates of adherence, dropout, and approaches to analyzing adherence to newly developed mobile and Web-based interventions for people with psychosis. Specific predictors of adherence were also explored. Methods: Using keywords (Internet or online or Web-based or website or mobile) AND (bipolar disorder or manic depression or manic depressive illness or manic-depressive psychosis or psychosis or schizophr* or psychotic), the following databases were searched: OVID including MedLine, EMBASE and PsychInfo, Pubmed and Web of Science. The objectives and inclusion criteria for suitable studies were defined following PICOS (population: people with psychosis; intervention: mobile or Internet-based technology; comparison group: no comparison group specified; outcomes: measures of adherence; study design: randomized controlled trials (RCT), feasibility studies, and observational studies) criteria. In addition to measurement and analysis of adherence, two theoretically proposed predictors of adherence were examined: (1) level of support from a clinician or researcher throughout the study, and (2) level of service user involvement in the app or intervention development. We provide a narrative synthesis of the findings and followed the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines for reporting systematic reviews. Results: Of the 20 studies that reported a measure of adherence and a rate of dropout, 5 of these conducted statistical analyses to determine predictors of dropout, 6 analyzed the effects of specific adherence predictors (eg, symptom severity or type of technological interface) on the effects of the intervention, 4 administered poststudy feedback questionnaires to assess continued use of the intervention, and 2 studies evaluated the effects of different types of interventions on adherence. Overall, the percentage of participants adhering to interventions ranged from 28-100% with a mean of 83%. Adherence was greater in studies with higher levels of social support and service user involvement in the development of the intervention. Studies of shorter duration also had higher rates of adherence. Conclusions: Adherence to mobile and Web-based interventions was robust across most studies. Although 2 studies found specific predictors of nonadherence (male gender and younger age), most did not specifically analyze predictors. The duration of the study may be an important predictor of adherence. Future studies should consider reporting a universal measure of adherence and aim to conduct complex analyses on predictors of adherence such as level of social presence and service user involvement.

  • Woman using Health Buddies App (montage). Source: The Authors / Placeit.net; Copyright: JMIR Publications; URL: http://mhealth.jmir.org/2017/7/e98/; License: Creative Commons Attribution (CC-BY).

    The Health Buddies App as a Novel Tool to Improve Adherence and Knowledge in Atrial Fibrillation Patients: A Pilot Study

    Abstract:

    Background: Atrial fibrillation (AF) constitutes an important risk for stroke, especially in an ageing population. A new app (Health Buddies) was developed as a tool to improve adherence to non-vitamin K antagonist oral anticoagulants (NOACs) in an elderly AF population by providing a virtual contract with their grandchildren, spelling out daily challenges for both. Objective: The aim of this pilot study was to assess the feasibility and usability of the Health Buddies app in AF patients. Methods: Two workshops were conducted to steer app development and to test a first prototype. The feasibility of the finalized app was investigated by assessing the number of eligible AF patients (based on current prescription of NOACs, the presence of grandchildren between 5 and 15 years old, availability of a mobile phone, computer, or tablet), and the proportion of those who were willing to participate. Participants had to use the app for 3 months. The motivation of the patients to use the app was assessed based on the number of logins to the app. Their perception of its usefulness was examined by specific questionnaires. Additionally, the effects on knowledge level about AF and its treatment, and adherence to NOAC intake were investigated. Results: Out of 830 screened AF patients, 410 were taking NOACs and 114 were eligible for inclusion. However, only 3.7% (15/410) of the total NOAC population or 13.2% of the eligible patients (15/114) were willing to participate. The main reasons for not participating were no interest to participate in general or in the concept in particular (29/99, 29%), not feeling comfortable using technology (22/99, 22%), no interest by the grandchildren or their parents (20/99, 20%), or too busy a lifestyle (12/99, 12%). App use significantly decreased towards the end of the study period in both patients (P=.009) and grandchildren (P<.001). NOAC adherence showed a taking adherence and regimen adherence of 88.6% (SD 15.4) and 81.8% (SD 18.7), respectively. Knowledge level increased from 64.6% (SD 14.7) to 70.4% (SD 10.4) after 3 months (P=.09). The app scored positively on clarity, novelty, stimulation, and attractiveness as measured with the user experience questionnaire. Patients evaluated the educational aspect of this app as a capital gain. Conclusions: Only a small proportion of the current AF population seems eligible for the innovative Health Buddies app in its current form. Although the app was positively rated by its users, a large subset of patients was not willing to participate in this study or to use the app. Efforts have to be made to expand the target group in the future.

  • Using data mining techniques to analyze patterns of usage in Manage My Pain. Source: Image created by the authors; Copyright: The authors; URL: http://mhealth.jmir.org/2017/7/e96/; License: Creative Commons Attribution (CC-BY).

    Patterns of User Engagement With the Mobile App, Manage My Pain: Results of a Data Mining Investigation

    Abstract:

    Background: Pain is one of the most prevalent health-related concerns and is among the top 3 most common reasons for seeking medical help. Scientific publications of data collected from pain tracking and monitoring apps are important to help consumers and healthcare professionals select the right app for their use. Objective: The main objectives of this paper were to (1) discover user engagement patterns of the pain management app, Manage My Pain, using data mining methods; and (2) identify the association between several attributes characterizing individual users and their levels of engagement. Methods: User engagement was defined by 2 key features of the app: longevity (number of days between the first and last pain record) and number of records. Users were divided into 5 user engagement clusters employing the k-means clustering algorithm. Each cluster was characterized by 6 attributes: gender, age, number of pain conditions, number of medications, pain severity, and opioid use. Z tests and chi-square tests were used for analyzing categorical attributes. Effects of gender and cluster on numerical attributes were analyzed using 2-way analysis of variances (ANOVAs) followed up by pairwise comparisons using Tukey honest significant difference (HSD). Results: The clustering process produced 5 clusters representing different levels of user engagement. The proportion of males and females was significantly different in 4 of the 5 clusters (all P ≤.03). The proportion of males was higher than females in users with relatively high longevity. Mean ages of users in 2 clusters with high longevity were higher than users from other 3 clusters (all P <.001). Overall, males were significantly older than females (P <.001). Across clusters, females reported more pain conditions than males (all P <.001). Users from highly engaged clusters reported taking more medication than less engaged users (all P <.001). Females reported taking a greater number of medications than males (P =.04). In 4 of 5 clusters, the percentage of males taking an opioid was significantly greater (all P ≤.05) than that of females. The proportion of males with mild pain was significantly higher than that of females in 3 clusters (all P ≤.008). Conclusions: Although most users of the app reported being female, male users were more likely to be highly engaged in the app. Users in the most engaged clusters self-reported a higher number of pain conditions, a higher number of current medications, and a higher incidence of opioid usage. The high engagement by males in these clusters does not appear to be driven by pain severity which may, in part, be the case for females. Use of a mobile pain app may be relatively more attractive to highly-engaged males than highly-engaged females, and to those with relatively more complex chronic pain problems.

  • Screenshot of an article discussing an initiative to create smoking cessation apps for consumers in China. Source: Seattle Times; Copyright: Seattle Times Company; URL: http://www.seattletimes.com/seattle-news/health/seattle-visit-sparks-effort-to-snuff-chinas-smoking-habit-with-an-app/; License: Fair use/fair dealings.

    Content Analysis of Smartphone Apps for Smoking Cessation in China: Empirical Study

    Abstract:

    Background: With 360 million smokers, China consumes more cigarettes than any other country in the world. Given that 620 million Chinese own smartphones, smartphone apps for smoking cessation are increasingly used in China to help smokers quit. Objective: This study analyzed and evaluated the contents of all smoking cessation apps (iOS and Android) available in China, applying the China Clinical Smoking Cessation Guideline (CCSCG; identical to the US Clinical Practice Guideline for Treating Tobacco Use and Dependence) as a framework for analysis. Methods: We conducted a content analysis of Chinese Android and iOS smoking cessation apps (N=64) designed to assist users in quitting smoking. Each app was independently coded by two raters for its approach to smoking cessation and adherence to the CCSCG. We also recorded the features of smoking cessation apps (eg, release date, size, frequency of downloads, user ratings, type, quality scores by raters, and designers). Linear regression was used to test predictors of popularity and user-rated quality. Results: Chinese smoking cessation apps have low levels of adherence to guidelines, with an average score of 11.1 for Android and 14.6 for iOS apps on a scale of 0 to 46. There was no significant association between popularity, user rating, and the characteristics of apps. However, there was a positive relationship between popularity, user rating, and adherence score. Conclusions: Chinese apps for smoking cessation have low levels of adherence to standard clinical practice guidelines. New apps need be developed and existing apps be revised following evidence-based principles in China.

  • Diet-related smartphone apps. Source: Pixabay; Copyright: skeeze; URL: https://pixabay.com/en/croissant-baked-fresh-breakfast-2346528/; License: Public Domain (CC0).

    Controlling Your “App”etite: How Diet and Nutrition-Related Mobile Apps Lead to Behavior Change

    Abstract:

    Background: In recent years, obesity has become a serious public health crisis in the United States. Although the problem of obesity is being addressed through a variety of strategies, the use of mobile apps is a relatively new development that could prove useful in helping people to develop healthy dietary habits. Though such apps might lead to health behavior change, especially when relevant behavior change theory constructs are integrated into them, the mechanisms by which these apps facilitate behavior change are largely unknown. Objective: The purpose of this study was to identify which behavior change mechanisms are associated with the use of diet- and nutrition-related health apps and whether the use of diet- and nutrition-related apps is associated with health behavior change. Methods: A cross-sectional survey was administered to a total of 217 participants. Participants responded to questions on demographics, use of diet and nutrition apps in the past 6 months, engagement and likability of apps, and changes in the participant’s dietary behaviors. Regression analysis was used to identify factors associated with reported changes in theory and separately for reported changes in actual behavior, after controlling for potential confounding variables. Results: The majority of study participants agreed or strongly agreed with statements regarding app use increasing their motivation to eat a healthy diet, improving their self-efficacy, and increasing their desire to set and achieve health diet goals. Additionally, majority of participants strongly agreed that using diet/nutrition apps led to changes in their behavior, namely increases in actual goal setting to eat a healthy diet (58.5%, 127/217), increases in their frequency of eating healthy foods (57.6%, 125/217), and increases in their consistency of eating healthy foods (54.4%, 118/217). Participants also responded favorably to questions related to engagement and likability of diet/nutrition apps. A number of predictors were also positively associated with diet-related behavior change. Theory (P<.001), app engagement (P<.001), app use (P<.003), and education (P<.010) were all positively associated with behavior change. Conclusions: Study findings indicate that the use of diet/nutrition apps is associated with diet-related behavior change. Hence, diet- and nutrition-related apps that focus on improving motivation, desire, self-efficacy, attitudes, knowledge, and goal setting may be particularly useful. As the number of diet- and nutrition-related apps continues to grow, developers should consider integrating appropriate theoretical constructs for health behavior change into the newly developed mobile apps.

  • Young woman with mobile phone. Source: Pixabay; Copyright: Free-Photos; URL: https://pixabay.com/en/sunglasses-relax-texting-summer-1149212/; License: Public Domain (CC0).

    Mobile Health Technology Using a Wearable Sensorband for Female College Students With Problem Drinking: An Acceptability and Feasibility Study

    Abstract:

    Background: An increasing number of mobile app interventions have been developed for problem drinking among college students; however, few studies have examined the integration of a mobile app with continuous physiological monitoring and alerting of affective states related to drinking behaviors. Objective: The aim of this paper was to evaluate the acceptability and feasibility of Mind the Moment (MtM), a theoretically based intervention for female college students with problem drinking that combines brief, in-person counseling with ecological momentary intervention (EMI) on a mobile app integrated with a wearable sensorband. Methods: We recruited 10 non-treatment seeking, female undergraduates from a university health clinic who scored a 3 or higher on the Alcohol Use Disorders Identification Test–Consumption (AUDIT-C) to participate in this pilot study. Study activities involved an in-person baseline intake and 1 follow-up assessment, 2 in-person alcohol brief intervention counseling sessions, and use of MtM technology components (sensorband and EMI on a mobile app) for approximately 3-4 weeks. The intervention used motivational interviewing (MI) and cognitive behavioral therapy (CBT) strategies for reducing risks associated with drinking. We used both qualitative and quantitative assessments to measure acceptability of the intervention and feasibility of delivery. Use patterns of the sensorband and mobile app were also collected. Results: Quantitative and qualitative data indicated high levels of acceptability for the MtM intervention. Altogether, participants made reports on the app on 26.7% (78/292) the days the technology was available to them and completed a total of 325 reports with wide variation between participants. Qualitative findings indicated that sensorband-elicited alerts promoted an increase in awareness of thoughts, feelings, and behaviors related to current environmental stressors and drinking behaviors in theoretically meaningful ways. Specific challenges related to functionality and form of the sensorband were identified. Conclusions: Delivering intervention material “just-in-time,” at the moment participants need to use behavioral strategies has great potential to individualize behavioral interventions for reducing problem drinking and other health behaviors. These findings provide initial evidence for the promise of wearable sensors for increasing potency of theoretically grounded mobile health interventions and point to directions for future research and uptake of these technologies.

  • Source: Image created by the authors; Copyright: The authors; URL: http://mhealth.jmir.org/2017/7/e92/; License: Creative Commons Attribution (CC-BY).

    A Bit of Fit: Minimalist Intervention in Adolescents Based on a Physical Activity Tracker

    Abstract:

    Background: Only 5% of Canadian youth meet the recommended 60 minutes of moderate to vigorous physical activity (MVPA) per day, with leisure time being increasingly allocated to technology usage. Direct-to-consumer mHealth devices that promote physical activity, such as wrist-worn physical activity trackers, have features with potential appeal to youth. Objective: The primary purpose of this study was to determine whether a minimalist physical activity tracker-based intervention would lead to an increase in physical activity in young adolescents. A secondary aim of this study was to assess change in physical activity across a 7-week intervention, as measured by the tracker. Methods: Using a quasi-experimental crossover design, two groups of 23 young adolescents (aged 13-14 years) were randomly assigned to immediate intervention or delayed intervention. The intervention consisted of wearing a Fitbit-Charge-HR physical activity tracker over a 7-week period. Actical accelerometers were used to measure participants’ levels of MVPA before and at the end of intervention periods for each group. Covariates such as age, sex, stage of change for physical activity behavior, and goal commitment were also measured. Results: There was an increase in physical activity over the course of the study period, though it was not related to overall physical activity tracker use. An intervention response did, however, occur in a subset of participants. Specifically, exposure to the physical activity tracker was associated with an average daily increase in MVPA by more than 15 minutes (P=.01) among participants who reported being in the action and maintenance stages of behavior change in relation to participation in physical activity. Participants in the precontemplation, contemplation, and preparation stages of behavior change had no change in their level of MVPA (P=.81). Conclusions: These results suggest that physical activity trackers may elicit improved physical activity related behavior in young adolescents demonstrating a readiness to be active. Future studies should seek to investigate if integrating physical activity trackers as part of more intensive interventions leads to greater increases in physical activity across different levels of stages of behavior change and if these changes can be sustained over longer periods of time.

  • ViSi Mobile system (left) and HealthPatch (right). Source: Figure 1 from http://mhealth.jmir.org/2017/7/e91; Copyright: the authors; License: Creative Commons Attribution (CC-BY).

    Continuous Monitoring of Vital Signs Using Wearable Devices on the General Ward: Pilot Study

    Abstract:

    Background: Measurement of vital signs in hospitalized patients is necessary to assess the clinical situation of the patient. Early warning scores (EWS), such as the modified early warning score (MEWS), are generally calculated 3 times a day, but these may not capture early deterioration. A delay in diagnosing deterioration is associated with increased mortality. Continuous monitoring with wearable devices might detect clinical deterioration at an earlier stage, which allows clinicians to take corrective actions. Objective: In this pilot study, the feasibility of continuous monitoring using the ViSi Mobile (VM; Sotera Wireless) and HealthPatch (HP; Vital Connect) was tested, and the experiences of patients and nurses were collected. Methods: In this feasibility study, 20 patients at the internal medicine and surgical ward were monitored with VM and HP simultaneously for 2 to 3 days. Technical problems were analyzed. Vital sign measurements by nurses were taken as reference and compared with vital signs measured by both devices. Patient and nurse experiences were obtained by semistructured interviews. Results: In total, 86 out of 120 MEWS measurements were used for the analysis. Vital sign measurements by VM and HP were generally consistent with nurse measurements. In 15% (N=13) and 27% (N=23) of the VM and HP cases respectively, clinically relevant differences in MEWS were found based on inconsistent respiratory rate registrations. Connection failure was recognized as a predominant VM artifact (70%). Over 50% of all HP artifacts had an unknown cause, were self-limiting, and never took longer than 1 hour. The majority of patients, relatives, and nurses were positive about VM and HP. Conclusions: Both VM and HP are promising for continuously monitoring vital signs in hospitalized patients, if the frequency and duration of artifacts are reduced. The devices were well received and comfortable for most patients.

  • Girl using a smartphone. Source: Pixabay; Copyright: Jan Vašek; URL: https://pixabay.com/en/smartphone-phone-call-message-2212963/; License: Public Domain (CC0).

    Use of and Beliefs About Mobile Phone Apps for Diabetes Self-Management: Surveys of People in a Hospital Diabetes Clinic and Diabetes Health Professionals in...

    Abstract:

    Background: People with diabetes mellitus (DM) are using mobile phone apps to support self-management. The numerous apps available to assist with diabetes management have a variety of functions. Some functions, like insulin dose calculators, have significant potential for harm. Objectives: The study aimed to establish (1) whether people with DM in Wellington, New Zealand, use apps for DM self-management and evaluate desirable features of apps and (2) whether health professionals (HPs) in New Zealand treating people with DM recommend apps to patients, the features HPs regard as important, and their confidence with recommending apps. Methods: A survey of patients seen at a hospital diabetes clinic over 12 months (N=539) assessed current app use and desirable features. A second survey of HPs attending a diabetes conference (n=286) assessed their confidence with app recommendations and perceived usefulness. Results: Of the 189 responders (35.0% response rate) to the patient survey, 19.6% (37/189) had used a diabetes app. App users were younger and in comparison to other forms of diabetes mellitus, users prominently had type 1 DM. The most favored feature of the app users was a glucose diary (87%, 32/37), and an insulin calculator was the most desirable function for a future app (46%, 17/37). In non-app users, the most desirable feature for a future app was a glucose diary (64.4%, 98/152). Of the 115 responders (40.2% response rate) to the HPs survey, 60.1% (68/113) had recommended a diabetes app. Diaries for blood glucose levels and carbohydrate counting were considered the most useful app features and the features HPs felt most confident to recommend. HPs were least confident in recommending insulin calculation apps. Conclusions: The use of apps to record blood glucose was the most favored function in apps used by people with diabetes, with interest in insulin dose calculating function. HPs do not feel confident in recommending insulin dose calculators. There is an urgent need for an app assessment process to give confidence in the quality and safety of diabetes management apps to people with diabetes (potential app users) and HPs (potential app prescribers).

  • Parents engagement on infant feeding apps. Source: Flickr; Copyright: Quinn Dombrowski; URL: https://www.flickr.com/photos/quinnanya/3286068884; License: Creative Commons Attribution + Noncommercial + ShareAlike (CC-BY-NC-SA).

    Assessing User Engagement of an mHealth Intervention: Development and Implementation of the Growing Healthy App Engagement Index

    Abstract:

    Background: Childhood obesity is an ongoing problem in developed countries that needs targeted prevention in the youngest age groups. Children in socioeconomically disadvantaged families are most at risk. Mobile health (mHealth) interventions offer a potential route to target these families because of its relatively low cost and high reach. The Growing healthy program was developed to provide evidence-based information on infant feeding from birth to 9 months via app or website. Understanding user engagement with these media is vital to developing successful interventions. Engagement is a complex, multifactorial concept that needs to move beyond simple metrics. Objective: The aim of our study was to describe the development of an engagement index (EI) to monitor participant interaction with the Growing healthy app. The index included a number of subindices and cut-points to categorize engagement. Methods: The Growing program was a feasibility study in which 300 mother-infant dyads were provided with an app which included 3 push notifications that was sent each week. Growing healthy participants completed surveys at 3 time points: baseline (T1) (infant age ≤3 months), infant aged 6 months (T2), and infant aged 9 months (T3). In addition, app usage data were captured from the app. The EI was adapted from the Web Analytics Demystified visitor EI. Our EI included 5 subindices: (1) click depth, (2) loyalty, (3) interaction, (4) recency, and (5) feedback. The overall EI summarized the subindices from date of registration through to 39 weeks (9 months) from the infant’s date of birth. Basic descriptive data analysis was performed on the metrics and components of the EI as well as the final EI score. Group comparisons used t tests, analysis of variance (ANOVA), Mann-Whitney, Kruskal-Wallis, and Spearman correlation tests as appropriate. Consideration of independent variables associated with the EI score were modeled using linear regression models. Results: The overall EI mean score was 30.0% (SD 11.5%) with a range of 1.8% - 57.6%. The cut-points used for high engagement were scores greater than 37.1% and for poor engagement were scores less than 21.1%. Significant explanatory variables of the EI score included: parity (P=.005), system type including “app only” users or “both” app and email users (P<.001), recruitment method (P=.02), and baby age at recruitment (P=.005). Conclusions: The EI provided a comprehensive understanding of participant behavior with the app over the 9-month period of the Growing healthy program. The use of the EI in this study demonstrates that rich and useful data can be collected and used to inform assessments of the strengths and weaknesses of the app and in turn inform future interventions.

  • Source: Pixabay; Copyright: fancycrave1; URL: https://pixabay.com/en/smart-watch-apple-technology-style-821557/; License: Public Domain (CC0).

    Mobile Device Accuracy for Step Counting Across Age Groups

    Abstract:

    Background: Only one in five American meets the physical activity recommendations of the Department of Health and Human Services. The proliferation of wearable devices and smartphones for physical activity tracking has led to an increasing number of interventions designed to facilitate regular physical activity, in particular to address the obesity epidemic, but also for cardiovascular disease patients, cancer survivors, and older adults. However, the inconsistent findings pertaining to the accuracy of wearable devices for step counting needs to be addressed, as well as factors known to affect gait (and thus potentially impact accuracy) such as age, body mass index (BMI), or leading arm. Objective: We aim to assess the accuracy of recent mobile devices for counting steps, across three different age groups. Methods: We recruited 60 participants in three age groups: 18-39 years, 40-64 years, and 65-84 years, who completed two separate 1000 step walks on a treadmill at a self-selected speed between 2 and 3 miles per hour. We tested two smartphones attached on each side of the waist, and five wrist-based devices worn on both wrists (2 devices on one wrist and 3 devices on the other), as well as the Actigraph wGT3X-BT, and swapped sides between each walk. All devices were swapped dominant-to-nondominant side and vice-versa between the two 1000 step walks. The number of steps was recorded with a tally counter. Age, sex, height, weight, and dominant hand were self-reported by each participant. Results: Among the 60 participants, 36 were female (60%) and 54 were right-handed (90%). Median age was 53 years (min=19, max=83), median BMI was 24.1 (min=18.4, max=39.6). There was no significant difference in left- and right-hand step counts by device. Our analyses show that the Fitbit Surge significantly undercounted steps across all age groups. Samsung Gear S2 significantly undercounted steps only for participants among the 40-64 year age group. Finally, the Nexus 6P significantly undercounted steps for the group ranging from 65-84 years. Conclusions: Our analysis shows that apart from the Fitbit Surge, most of the recent mobile devices we tested do not overcount or undercount steps in the 18-39-year-old age group, however some devices undercount steps in older age groups. This finding suggests that accuracy in step counting may be an issue with some popular wearable devices, and that age may be a factor in undercounting. These results are particularly important for clinical interventions using such devices and other activity trackers, in particular to balance energy requirements with energy expenditure in the context of a weight loss intervention program.

  • Source: Flickr; Copyright: iphonedigital; URL: https://www.flickr.com/photos/iphonedigital/24432058895; License: Creative Commons Attribution + ShareAlike (CC-BY-SA).

    Acceptance of Mobile Health in Communities Underrepresented in Biomedical Research: Barriers and Ethical Considerations for Scientists

    Abstract:

    Background: The rapid expansion of direct-to-consumer wearable fitness products (eg, Flex 2, Fitbit) and research-grade sensors (eg, SenseCam, Microsoft Research; activPAL, PAL Technologies) coincides with new opportunities for biomedical and behavioral researchers. Underserved communities report among the highest rates of chronic disease and could benefit from mobile technologies designed to facilitate awareness of health behaviors. However, new and nuanced ethical issues are introduced with new technologies, which are challenging both institutional review boards (IRBs) and researchers alike. Given the potential benefits of such technologies, ethical and regulatory concerns must be carefully considered. Objective: Our aim was to understand potential barriers to using wearable sensors among members of Latino, Somali and Native Hawaiian Pacific Islander (NHPI) communities. These ethnic groups report high rates of disparate health conditions and could benefit from wearable technologies that translate the connection between physical activity and desired health outcomes. Moreover, these groups are traditionally under-represented in biomedical research. Methods: We independently conducted formative research with individuals from southern California, who identified as Latino, Somali, or Native Hawaiian Pacific Islander (NHPI). Data collection methods included survey (NHPI), interview (Latino), and focus group (Somali) with analysis focusing on cross-cutting themes. Results: The results pointed to gaps in informed consent, challenges to data management (ie, participant privacy, data confidentiality, and data sharing conventions), social implications (ie, unwanted attention), and legal risks (ie, potential deportation). Conclusions: Results shed light on concerns that may escalate the digital divide. Recommendations include suggestions for researchers and IRBs to collaborate with a goal of developing meaningful and ethical practices that are responsive to diverse research participants who can benefit from technology-enabled research methods. Trial Registration: ClinicalTrials.gov NCT02505165; https://clinicaltrials.gov/ct2/show/NCT02505165 (Archived by WebCite at http://www.Webcitation.org/6r9ZSUgoT)

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    Date Submitted: Jul 18, 2017

    Open Peer Review Period: Jul 18, 2017 - Sep 12, 2017

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    Open Peer Review Period: Jul 16, 2017 - Sep 10, 2017

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    Open Peer Review Period: Jul 14, 2017 - Sep 8, 2017

    Background: In the past, significant research has been directed towards predicting churn of customers, particularly in the telecoms industry. However, few works have addressed the equally important qu...

    Background: In the past, significant research has been directed towards predicting churn of customers, particularly in the telecoms industry. However, few works have addressed the equally important question of employee turnover in companies and none have been able to create a predictive model to manage retention Objective: To identify turnover risk factors of employees. Methods: Using a smartphone Happiness application that tracks Happiness, we applied search-engine like classification methods (such as Google page ranking algorithm) to rank employees by risk of turnover. We set a risk cut-off to cluster employees in two groups: the ones that turn over and the ones that stay in the company. Then we used the top discriminant traits of each group to identify risk factors. The data source is the employee interaction with a mobile app that is used to track happiness. Sample size: 4k employees. Time length: 2 years. Participating companies: 34. Results: We developed a turnover prediction model that identifies employees that turnover with Sensitivity 34% and Specificity 99.4%. Predictive value of the positive test is 80%. Predictive value of the negative test= 96%. Test set contained 116 churns, test set sample size 1944 employees. Risk factors related to app usage are identified. Conclusions: The top three risk factors related to employee churn are low number of likes received in the anonymous company forum (low employee comment likeability), infrequent company posts (disengaged company), lower happiness than the company average (low relative happiness). Other factors such as absolute individual happiness, or likes given to other's anonymous post (positivity and engagement of the employee) was not found to be correlated with turnover. Clinical Trial: Does not apply

  • Identifying Asbestos-Containing Materials in Homes: Design and Development of the ACM Check Mobile Phone App

    Date Submitted: Jul 12, 2017

    Open Peer Review Period: Jul 13, 2017 - Sep 7, 2017

    Background: Asbestos-containing materials (ACM) can still be found in many homes in Australia and other countries. ACMs present a health risk when they are damaged or disturbed, such as during do-it-y...

    Background: Asbestos-containing materials (ACM) can still be found in many homes in Australia and other countries. ACMs present a health risk when they are damaged or disturbed, such as during do-it-yourself home renovations. However, there remains a lack of knowledge and awareness amongst community members about asbestos identification and its safe management in residential settings. Objective: To describe the process of developing a mobile phone application (“app”), ACM Check, that incorporates a questionnaire designed to identify and assess asbestos-containing materials located in residential settings. Methods: A multidisciplinary team was involved in the formative development and creation of the mobile phone app. The formative development process included 6 steps: defining the scope of the app; comprehensive desktop review; drafting and revising the content, questionnaire, conditional branching rules and scoring algorithms; expert input; manual pre-testing of the questionnaire; and formulation of a final content document to be provided to the software development company. ACM Check was then constructed on the iOS platform for use in a validation study prior to being updated, replicated on Android, and released to the public. Results: The ACM Check app identifies potential ACMs, prioritises the materials based on their condition and likelihood of disturbance, and generates a summary report for each house assessed. Conclusions: ACM Check is an initiative to raise community members’ awareness of asbestos in the residential environment and also serves as a data collection tool for epidemiological research. It can potentially be modified for implementation in other countries or used as the basis for the assessment of other occupational or environmental hazards.

  • Usability and Usefulness Study of a Mobile Health App for Promoting Breastfeeding in Thailand

    Date Submitted: Jul 13, 2017

    Open Peer Review Period: Jul 13, 2017 - Sep 7, 2017

    Background: Breastfeeding is proven to have lasting health benefits for both mothers and infants, however, exclusive breastfeeding rate up to 6 months remains below 20% in Thailand. Although the numbe...

    Background: Breastfeeding is proven to have lasting health benefits for both mothers and infants, however, exclusive breastfeeding rate up to 6 months remains below 20% in Thailand. Although the number of research and commercial apps for breastfeeding women is significantly growing, they are country-specific and restricted to English-speaking users. There exists a major knowledge gap on how mobile health apps could support breastfeeding in Thailand. To address these gaps, MoomMae is developed with the intention to support Thai women in breastfeeding outside of their homes and in keeping their feeding records. Objective: To evaluate the usability and usefulness of MoomMae, a smartphone app designed to support breastfeeding women. Methods: A total of 21 breastfeeding women with at least one Android phone or tablet were recruited via convenience and snowball sampling. Each participant was requested to attend a pre-use interview and given the app to use for 4 weeks. Following this period, a post-use interview was conducted to examine the usability and usefulness of the app. Both sessions were held individually and audio-recorded for qualitative analysis. Results: The mean scores of usability and usefulness from the post-use survey were 4.33 (SD 0.87; range 1-5) and 4.60 (SD 0.74; range 2-5). Our qualitative analysis revealed a total of 137 feedbacks: 71 related to usability and 66 associated with usefulness. A further sentimental analysis showed that comments on usability were generally negative (59 negative, 11 positive, and 1 neutral) and comments on usefulness were relatively positive (56 positives, 9 negative, and 1 neutral). We discovered 26 unique design issues and proposed recommendations for future improvement. Conclusions: Our usability and usefulness assessment of MoomMae demonstrated that MoomMae is easy to use and offer great potential to be a useful self-management tool for breastfeeding mothers in Thailand. The qualitative analysis suggested that the app is supportive of breastfeeding on demand, but the flow and inputs of the app should be redesigned to be more intuitive. For future implementations, the most desirable feature is a pump-reminding notification system.

  • Feasibility of a Smart Phone Application Supporting Recovery from Addiction in China

    Date Submitted: Jul 10, 2017

    Open Peer Review Period: Jul 11, 2017 - Sep 5, 2017

    Background: Mobile health technologies have been shown to improve self-management of chronic diseases. However, there is limited research investigating its feasibility in supporting recovery from subs...

    Background: Mobile health technologies have been shown to improve self-management of chronic diseases. However, there is limited research investigating its feasibility in supporting recovery from substance use disorders (SUDs) in China. Objective: Mobile health technologies have been shown to improve self-management of chronic diseases. However, there is limited research investigating its feasibility in supporting recovery from substance use disorders (SUDs) in China. Methods: A total of 75 participants with SUDs in Shanghai were recruited to participate in the pilot study lasting 4 weeks, with 50 participants randomly assigned to the experimental group and 25 participants to the control group. The experimental group used m-health based ecological momentary assessment (EMA) technology to assess their daily drug use in natural environments, while the control group only received 2 short health messages each day from the app. Urine test and life experience timeline (LET) assessment were conducted at each week and a post-intervention survey was conducted for both groups. The correspondence between EMA and LET data were investigated. Results: The mean age of our participants was 41.6 years, and 70.7% were male. During 4 weeks of observation, 690 daily EMA survey data were recorded with the response rate being 49.3%. The percent agreement of drug use between EMA and LET was 66.7%, 79.2%, 72.4%, and 85.8% for each of the 4 weeks, and the correspondence between EMA and urine test was 51.2%, 65.1%, 61.9%, 71.5%. Post-intervention survey indicated that participants (45.7%) preferred to use face-to-face interview rather than m-health app. Conclusions: This study demonstrated a good concordance between EMA data and LET, but the acceptance of m-health among SUDs in China was not optimistic. Much more efforts are needed to improve its acceptance in China.

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