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Journal Description

JMIR mHealth and uHealth (JMU, ISSN 2291-5222; Impact Factor 4.301) is a sister journal of JMIR, the leading eHealth journal. JMIR mHealth and uHealth is indexed in PubMed, PubMed Central, Scopus, MEDLINE and Science Citation Index Expanded (SCIE), and in June 2019 received an Impact Factor of 4.301, which ranks the journal #2 (behind JMIR) in the medical informatics category indexed by the Science Citation Index Expanded (SCIE) by Thomson Reuters/Clarivate. 

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

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

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

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

 

Recent Articles:

  • Source: Image created by Authors; Copyright: The Authors; URL: http://mhealth.jmir.org/2020/1/e15663/; License: Creative Commons Attribution (CC-BY).
    Evaluation and Research Methodology...

    Jan 24, 2020

    Factors Related to User Ratings and User Downloads of Mobile Apps for Maternal and Infant Health: Cross-Sectional Study

    Authors List:

    Abstract:

    Background: Mobile health apps related to maternal and infant health (MIH) are prevalent and frequently used. Some of these apps are extremely popular and have been downloaded over 5 million times. However, the understanding of user behavior and user adoption of these apps based on consumer preferences for different app features and categories is limited. Objective: This study aimed to examine the relationship between MIH app characteristics and users’ perceived satisfaction and intent to use. Methods: The associations between app characteristics, ratings, and downloads were assessed in a sample of MIH apps designed to provide health education or decision-making support to pregnant women or parents and caregivers of infants. Multivariable linear regression was used to assess the relationship between app characteristics and user ratings, and ordinal logistic regression was used to assess the relationship between app characteristics and user downloads. Results: The analyses of user ratings and downloads included 421 and 213 apps, respectively. The average user rating was 3.79 out of 5. Compared with the Apple App Store, the Google Play Store was associated with high user ratings (beta=.33; P=.005). Apps with higher standardized user ratings (beta=.80; P<.001), in-app purchases (beta=1.12; P=.002), and in-app advertisements (beta=.64; P=.02) were more frequently downloaded. Having a health care organization developer as part of the development team was neither associated with user ratings (beta=−.20; P=.06) nor downloads (beta=−.14; P=.63). Conclusions: A majority of MIH apps are developed by non–health care organizations, which could raise concern about the accuracy and trustworthiness of in-app information. These findings could benefit app developers in designing better apps and could help inform marketing and development strategies. Further work is needed to evaluate the clinical accuracy of information provided within the apps.

  • Source: Unsplash.com; Copyright: Fred Moon; URL: https://unsplash.com/photos/KIuLg94a7mU; License: Licensed by JMIR.
    mHealth for Data Collection and Research

    Jan 24, 2020

    Spatiotemporal Analysis of Men Who Have Sex With Men in Mainland China: Social App Capture-Recapture Method

    Authors List:

    Abstract:

    Background: In China, the cases of newly diagnosed HIV/AIDS in men who have sex with men (MSM) have increased more than tenfold since 2006. However, the MSM population size, geographical distribution, and migration patterns are largely unknown. Objective: Our aim is to estimate the number, spatial distribution, and migration of MSM populations in mainland China using big data from social networking. Methods: We collected 85 days of data on online users of a social networking MSM app in mainland China. Daily online MSM users and their migration across the country were investigated during a holiday period and a nonholiday period. Using the capture-mark-recapture model, we designed an experiment consisting of two independent samples to estimate the total provincial MSM population. Results: The estimate of MSM in mainland China was 8,288,536 (95% CI 8,274,931-8,302,141), accounting for 1.732% (95% CI 1.729%-1.734%) of adult men aged 18 to 64 years. The average daily number of MSM social networking online across mainland China was 1,198,682 during the nonholiday period. The five provinces (including municipalities) with the highest average number of daily online MSM numbers were Guangdong (n=141,712), Jiangsu (n=90,710), Zhejiang (n=72,212), Shandong (n=68,065), and Beijing (n=66,057). The proportion of daily online MSM among adult men in different cities varied from 0.04% to 0.96%, with a mean of 0.20% (SD 0.14%). Three migrating centers—Guangdong, Beijing, and the Yangtze River Delta (Shanghai-Zhejiang-Jiangsu)—accounted for 57.23% of MSM migrants in the county. Conclusions: The percentage of MSM among adult men in mainland China is at the middle level compared with other Asia and Pacific countries. However, the number of MSM is very large, and the distribution is uneven. Both MSM distribution and migration are highly affected by socioeconomic status.

  • Source: Placeit / The Authors; Copyright: The Authors; URL: http://mhealth.jmir.org/2020/1/e14082/; License: Creative Commons Attribution (CC-BY).
    Quality Evaluation and Descriptive...

    Jan 24, 2020

    Use of Evidence-Based Best Practices and Behavior Change Techniques in Breast Cancer Apps: Systematic Analysis

    Authors List:

    Abstract:

    Background: Theoretically designed mobile health (mHealth) breast cancer interventions are essential for achieving positive behavior change. In the case of breast cancer, they can improve the health outcomes of millions of women by increasing prevention and care efforts. However, little is known about the theoretical underpinnings of breast cancer apps available to the general public. Objective: Given that theories may strengthen mHealth interventions, this study aimed to identify breast cancer apps designed to support behavior change, to assess the extent to which they address content along the cancer care continuum and contain behavior change techniques, and to assess the degree to which star rating is related to theory-based design. Methods: Using a criteria-based screening process, we searched 2 major app stores for breast cancer apps designed to promote behavior change. Apps were coded for content along the cancer care continuum and analyzed for behavior change techniques. The Mann-Whitney U test was used to examine the relationship between star ratings and the use of behavior change techniques in apps with star ratings compared to those without ratings. Results: The search resulted in a total of 302 apps, of which 133 were identified as containing breast cancer content. Only 9.9% (30/302) of apps supported behavior change and were further analyzed. These apps were disproportionally focused on behaviors to enhance early detection, whereas only a few apps supported care management, treatment, and posttreatment behaviors. Regarding theories, 63% (19/30) of apps customized content to users, 70% (21/30) established a health-behavior link, and 80% (24/30) provided behavior change instructions. Of the 30 apps, 15 (50%) prompted intention formation whereas less than half of the apps included goal setting (9/30, 30%) and goal reviewing (7/30, 23%). Most apps did not provide information on peer behavior (7/30, 23%) or allow for social comparison (6/30, 20%). None of the apps mobilized social norms. Only half of the apps (15/30, 50%) were user rated. The results of the Mann-Whitney U test showed that apps with star ratings contained significantly more behavior change techniques (median 6.00) than apps without ratings. The analysis of behavior change techniques used in apps revealed their shortcomings in the use of goal setting and social influence features. Conclusions: Our findings indicate that commercially available breast cancer apps have not yet fully realized their potential to promote behavior change, with only a minority of apps focusing on behavior change, and even fewer including theoretical design to support behavior change along the cancer care continuum. These shortcomings are likely limiting the effectiveness of apps and their ability to improve public health. More attention needs to be paid to the involvement of professionals in app development and adherence to theories and best practices in app design to support individuals along the cancer care continuum.

  • Source: Image created by the Authors; Copyright: The Authors; URL: http://mhealth.jmir.org/2020/1/e17055/; License: Creative Commons Attribution (CC-BY).
    mHealth in a Clinical Setting

    Jan 23, 2020

    Benefits of Mobile Apps for Cancer Pain Management: Systematic Review

    Authors List:

    Abstract:

    Background: Pain ratings reported by patients with cancer continue to increase, and numerous computer and phone apps for managing cancer-related pain have been developed recently; however, whether these apps effectively alleviate patients’ pain remains unknown. Objective: This study aimed to comprehensively evaluate the role of mobile apps in the management of cancer pain. Methods: Literature on the use of apps for cancer pain management and interventions, published before August 2019, was retrieved from the following databases: MEDLINE, Embase, Cochrane, CINAHL, Scopus, and PsycINFO. The effects of apps on cancer pain were evaluated using RevMan5.3 software, and the rates of adverse drug reactions were analyzed using the R Statistical Software Package 3.5.3. Results: A total of 13 studies were selected for the analysis: 5 randomized controlled trials (RCTs), 4 before-after studies, 2 single-arm trials, 1 prospective cohort study, and 1 prospective descriptive study. The 5 RCTs reported data for 487 patients (240 patients in the intervention group and 247 patients in the control group), and the remaining studies reported data for 428 patients. We conducted a meta-analysis of the RCTs. According to the meta-analysis, apps can significantly reduce pain scores (mean difference [MD]=–0.50, 95% CI –0.94 to –0.07, I2=62%, P=.02). We then used apps that have an instant messaging module for subgroup analysis; these apps significantly reduced patients’ pain scores (MD=–0.67, 95% CI –1.06 to –0.28, I2=57%, P<.01). Patients using apps without an instant messaging module did not see a reduction in the pain score (MD=0.30, 95% CI –1.31 to 1.92, I2=70%, P=.71). Overall, patients were highly satisfied with using apps. Other outcomes, such as pain catastrophizing or quality of life, demonstrated greater improvement in patients using apps with instant messaging modules compared with patients not using an app. Conclusions: The use of apps with instant messaging modules is associated with reduced pain scores in patients with cancer-related pain, and patient acceptance of these apps is high. Apps without instant messaging modules are associated with relatively higher pain scores. The presence of an instant messaging module may be a key factor affecting the effect of an app on cancer pain.

  • Source: Image created by the Authors; Copyright: The Authors; URL: http://mhealth.jmir.org/2020/1/e15329/; License: Creative Commons Attribution (CC-BY).
    Evaluation and Research Methodology...

    Jan 22, 2020

    Quality Assurance of Health Wearables Data: Participatory Workshop on Barriers, Solutions, and Expectations

    Authors List:

    Abstract:

    Background: The ubiquity of health wearables and the consequent production of patient-generated health data (PGHD) are rapidly escalating. However, the utilization of PGHD in routine clinical practices is still low because of data quality issues. There is no agreed approach to PGHD quality assurance; therefore, realizing the promise of PGHD requires in-depth discussion among diverse stakeholders to identify the data quality assurance challenges they face and understand their needs for PGHD quality assurance. Objective: This paper reports findings from a workshop aimed to explore stakeholders’ data quality challenges, identify their needs and expectations, and offer practical solutions. Methods: A qualitative multi-stakeholder workshop was conducted as a half-day event on the campus of an Australian University located in a major health care precinct, namely the Melbourne Parkville Precinct. The 18 participants had experience of PGHD use in clinical care, including people who identified as health care consumers, clinical care providers, wearables suppliers, and health information specialists. Data collection was done by facilitators capturing written notes of the proceedings as attendees engaged in participatory design activities in written and oral formats, using a range of whole-group and small-group interactive methods. The collected data were analyzed thematically, using deductive and inductive coding. Results: The participants’ discussions revealed a range of technical, behavioral, operational, and organizational challenges surrounding PGHD, from the time when data are collected by patients to the time data are used by health care providers for clinical decision making. PGHD stakeholders found consensus on training and engagement needs, continuous collaboration among stakeholders, and development of technical and policy standards to assure PGHD quality. Conclusions: Assuring PGHD quality is a complex process that requires the contribution of all PGHD stakeholders. The variety and depth of inputs in our workshop highlighted the importance of co-designing guidance for PGHD quality guidance.

  • Source: Flickr; Copyright: Rob Tinworth; URL: https://www.flickr.com/photos/nyayahealth/8902606594; License: Creative Commons Attribution (CC-BY).
    Design and Formative Evaluation of...

    Jan 22, 2020

    Considerations for Improved Mobile Health Evaluation: Retrospective Qualitative Investigation

    Authors List:

    Abstract:

    Background: Mobile phone use and, consequently, mobile health (mHealth) interventions have seen an exponential increase in the last decade. There is an excess of 318,000 health-related apps available free of cost for consumers to download. However, many of these interventions are not evaluated and are lacking appropriate regulations. Randomized controlled trials are often considered the gold standard study design in determining the effectiveness of interventions, but recent literature has identified limitations in the methodology when used to evaluate mHealth. Objective: The objective of this study was to investigate the system developers’ experiences of evaluating mHealth interventions in the context of a developing country. Methods: We employed a qualitative exploratory approach, conducting semistructured interviews with multidisciplinary members of an mHealth project consortium. A conventional content analysis approach was used to allow codes and themes to be identified directly from the data. Results: The findings from this study identified the system developers’ perceptions of mHealth evaluation, providing an insight into the requirements of an effective mHealth evaluation. This study identified social and technical factors which should be taken into account when evaluating an mHealth intervention. Conclusions: Contextual issues represented one of the most recurrent challenges of mHealth evaluation in the context of a developing country, highlighting the importance of a mixed method evaluation. There is a myriad of social, technical, and regulatory variables, which may impact the effectiveness of an mHealth intervention. Failure to account for these variables in an evaluation may limit the ability of the intervention to achieve long-term implementation and scale.

  • The SecondEars app. Source: Image created by the Authors; Copyright: The Authors; URL: https://mhealth.jmir.org/2020/1/e15593; License: Creative Commons Attribution (CC-BY).
    mHealth in a Clinical Setting

    Jan 21, 2020

    Testing Consultation Recordings in a Clinical Setting With the SecondEars Smartphone App: Mixed Methods Implementation Study

    Authors List:

    Abstract:

    Background: Health care systems are increasingly looking to mobile device technologies (mobile health) to improve patient experience and health outcomes. SecondEars is a smartphone app designed to allow patients to audio-record medical consultations to improve recall, understanding, and health care self-management. Novel health interventions such as SecondEars often fail to be implemented post pilot-testing owing to inadequate user experience (UX) assessment, a key component of a comprehensive implementation strategy. Objective: This study aimed to pilot the SecondEars app within an active clinical setting to identify factors necessary for optimal implementation. Objectives were to (1) investigate patient UX and acceptability, utility, and satisfaction with the SecondEars app, and (2) understand health professional perspectives on issues, solutions, and strategies for effective implementation of SecondEars. Methods: A mixed methods implementation study was employed. Patients were invited to test the app to record consultations with participating oncology health professionals. Follow-up interviews were conducted with all participating patients (or carers) and health professionals, regarding uptake and extent of app use. Responses to the Mobile App Rating Scale (MARS) were also collected. Interviews were analyzed using interpretive descriptive methodology; all quantitative data were analyzed descriptively. Results: A total of 24 patients used SecondEars to record consultations with 10 multidisciplinary health professionals. In all, 22 of these patients used SecondEars to listen to all or part of the recording, either alone or with family. All 100% of patient participants reported in the MARS that they would use SecondEars again and recommend it to others. A total of 3 themes were identified from the patient interviews relating to the UX of SecondEars: empowerment, facilitating support in cancer care, and usability. Further, 5 themes were identified from the health professional interviews relating to implementation of SecondEars: changing hospital culture, mitigating medico-legal concerns, improving patient care, communication, and practical implementation solutions. Conclusions: Data collected during pilot testing regarding recording use, UX, and health professional and patient perspectives will be important for designing an effective implementation strategy for SecondEars. Those testing the app found it useful and felt that it could facilitate the benefits of consultation recordings, along with providing patient empowerment and support. Potential issues regarding implementation were discussed, and solutions were generated. Clinical Trial: Australia and New Zealand Clinical Trials Registry ACTRN12618000730202; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=373915&isClinicalTrial=False

  • Weight loss program of mobile coaching intervention, which is integrated with local public healthcare center and a regional hospital’s anti-obesity clinic. Source: The Authors; Copyright: The Authors/Health Chosun; URL: http://mhealth.jmir.org/2020/1/e13273/; License: Licensed by JMIR.
    mHealth for Wellness, Behavior Change...

    Jan 21, 2020

    Effect of mHealth With Offline Antiobesity Treatment in a Community-Based Weight Management Program: Cross-Sectional Study

    Authors List:

    Abstract:

    Background: Weight loss interventions using mobile phone apps have recently shown promising results. Objective: This study aimed to analyze the short-term weight loss effect of a mobile coaching intervention when it is integrated with a local public health care center and a regional hospital’s antiobesity clinic as a multidisciplinary model. Methods: A total of 150 overweight or obese adults signed up to complete an 8-week antiobesity intervention program with human coaching through a mobile platform. Paired t tests and multiple linear regression analysis were used to identify the intervention factors related to weight change. Results: Among the 150 participants enrolled in this study, 112 completed the 8-week weight loss intervention. Weight (baseline: mean 77.5 kg, SD 12.9; after intervention: mean 74.8 kg, SD 12.6; mean difference −2.73 kg), body mass index, waist circumference, fat mass (baseline: mean 28.3 kg, SD 6.6; after intervention: mean 25.7 kg, SD 6.3; mean difference −2.65 kg), and fat percentage all showed a statistically significant decrease, and metabolic equivalent of task (MET) showed a statistically significant increase after intervention. In multiple linear regression analysis, age (beta=.07; P=.06), △MET (beta=−.0009; P=.10), number of articles read (beta=−.01; P=.04), and frequency of weight records (beta=−.05; P=.10; R2=0.4843) were identified as significant factors of weight change. Moreover, age (beta=.06; P=.03), sex (female; beta=1.16; P=.08), △MET (beta=−.0009; P<.001), and number of articles read (beta=−.02; P<.001; R2=0.3728) were identified as significant variables of fat mass change. Conclusions: The multidisciplinary approach, combining a mobile health (mHealth) care app by health care providers, was effective for short-term weight loss. Additional studies are needed to evaluate the efficacy of mHealth care apps in obesity treatment.

  • The MySurgery app (montage). Source: The Authors / Placeit; Copyright: JMIR Publications; URL: https://mhealth.jmir.org/2020/1/e12859; License: Creative Commons Attribution (CC-BY).
    mHealth in a Clinical Setting

    Jan 20, 2020

    A Smartphone App Designed to Empower Patients to Contribute Toward Safer Surgical Care: Community-Based Evaluation Using a Participatory Approach

    Authors List:

    Abstract:

    Background: MySurgery is a smartphone app designed to increase patient and carer involvement in behaviors that contribute toward safety in surgical care. Objective: This study presents a pilot evaluation of MySurgery in which we evaluated surgical patients’ perceptions of the app in terms of its content, usability, and potential impacts on communication and safety. Methods: A participatory action research (PAR) approach was used to formulate a research steering group consisting of 5 public representatives and 4 researchers with equal decision-making input. Surgical patients were recruited from the community using multiple approaches, including Web based (eg, social media, recruitment websites, and charitable or voluntary organizations) and face to face (via community centers). Participants referred to MySurgery before, during, and after their surgery and provided feedback via an embedded questionnaire and using reflective notes. Results: A diverse mix of 42 patients took part with good representation from 2 “seldom heard” groups: those with a disability and those from a black, Asian, or minority ethnic group. Most were very supportive of MySurgery, particularly those with previous experience of surgery and those who felt comfortable to be involved in conversations and decisions around their care. The app showed particular potential to empower patients to become involved in their care conversations and safety-related behaviors. Perceptions did not differ according to age, ethnicity, or length of hospital stay. Suggestions for improving the app included how to make it more accessible to certain groups, for example, those with a disability. Conclusions: MySurgery is a novel technology-driven approach for empowering patients to play a role in improving surgical safety that seems feasible for use within the United Kingdom’s National Health Service. Adopting a PAR approach and the use of a diversity strategy considerably enhanced the research process in terms of gaining diverse participant recruitment and patient and public involvement. Further testing with stakeholder groups will follow.

  • The ReACT app for people with dementia. Source: Tomas Bertelsen; Copyright: Tomas Bertelsen / The Authors; URL: http://mhealth.jmir.org/2020/1/e14694/; License: Creative Commons Attribution (CC-BY).
    mHealth for Symptom and Disease...

    Jan 17, 2020

    A Tablet App Supporting Self-Management for People With Dementia: Explorative Study of Adoption and Use Patterns

    Authors List:

    Abstract:

    Background: Assistive technology (AT) is rapidly emerging within dementia care and support. One area of AT application is support of people with dementia in compensating for cognitive symptoms and thereby promoting their self-management. There is, however, little evidence for the applicability, usability, and effectiveness of AT for people with dementia, and there is a need to identify factors that can promote adoption. Objective: This study aimed to (1) evaluate the applicability and usability of an app, tailor-made for people with dementia; (2) explore factors affecting adoption; (3) explore the possible influence of caregiver involvement; and (4) contribute to process evaluation of the intervention. Methods: The ReACT (Rehabilitation in Alzheimer's disease using Cognitive support Technology) app was designed as a holistic solution to support memory and structure in daily living. Persons with dementia had access to a personal user account, and family caregivers were given a parallel login. Written and Web-based materials were provided to support self-applied implementation. A mixed methods design was applied to explore adoption and use patterns, including background and disease-related data, qualitative data from a survey, and log data. Adoption was defined as the use of the app over a period of ≥90 days. Results: Data from 112 participants and 98 caregivers were included. Shorter time from diagnosis (U=595; P=.046; r=0.19) and caregiver activating the app (P=.02) had a significant impact on the participant adoption status. Logistic regression analysis showed that if caregivers had activated the app, the participant was five times more likely to become an adopter (odds ratio 5.1, 95% CI 1.29-19.99; P=.02). However, the overall predictive power was low, and there was a wide variation in background and disease-related characteristics among adopters. The level of experience and skills in tablet use were not significantly different between adopters and nonadopters. Adopters generally rated the app high on usefulness, satisfaction, and ease of use (rated on the USEdem questionnaire). Their scores were significantly higher compared with nonadopters (U=5.5; P=.02; r=0.64). Analysis of use patterns showed that all functionalities of the app were used among adopters. Conclusions: For participants who became adopters, the ReACT app and the methods for self-applied implementation were applicable. However, the results were also in accordance with the well-known challenges of nonadoption and nonadherence to digital health interventions. The study provided insight into the importance of timely introduction and caregiver support for adoption of AT among people with dementia. It also underlined the high complexity of personal and contextual factors that influence adoption. These complex factors need to be considered when designing and implementing AT for people with dementia.

  • Source: Pxhere; Copyright: Pxhere; URL: https://pxhere.com/en/photo/88284; License: Public Domain (CC0).
    mHealth for Wellness, Behavior Change...

    Jan 15, 2020

    Mobile Health Technology Interventions for Suicide Prevention: Systematic Review

    Authors List:

    Abstract:

    Background: Digital interventions are proposed as one way by which effective treatments for self-harm and suicidal ideation may be improved and their scalability enhanced. Mobile devices offer a potentially powerful medium to deliver evidence-based interventions with greater specificity to the individual when the intervention is needed. The recent proliferation of publicly available mobile apps designed for suicide prevention underlines the need for robust evidence to promote safe practice. Objective: This review aimed to examine the effectiveness of currently available mobile health (mHealth) technology tools in reducing suicide-specific outcomes. Methods: The following databases were searched: Cochrane Central Register of Controlled Trials (The Cochrane Library), MEDLINE, EMBASE, PsycINFO, and relevant sources of gray literature. All published and unpublished randomized controlled trials (RCTs), pseudo-RCTs, and pre-post observational studies that evaluated the effectiveness of mHealth technology in suicide prevention delivered via mobile computing and communication technology were included. Studies were included if they measured at least one suicide outcome variable (ie, suicidal ideation, suicidal intent, nonsuicidal self-injurious behavior, and suicidal behavior). A total of 2 review authors independently extracted data and assessed study suitability, in accordance with the Cochrane Collaboration Risk of Bias Tool, on July 31, 2018. Owing to the heterogeneity of outcomes found across studies, results were not amenable for pooled synthesis, and a meta-analysis was not performed. A narrative synthesis of the available research is presented here. Results: A total of 7 studies met criteria for inclusion . Four published articles that reported on the effectiveness of the following mobile phone apps were included: iBobbly, Virtual Hope Box, BlueIce, and Therapeutic Evaluative Conditioning. Results demonstrated some positive impacts for individuals at elevated risk of suicide or self-harm, including reductions in depression, psychological distress, and self-harm and increases in coping self-efficacy. None of the apps evaluated demonstrated the ability to significantly decrease suicidal ideation compared with a control condition. In addition, 3 unpublished and recently completed trials also met criteria for inclusion in the review. Conclusions: Further research is needed to evaluate the efficacy of stand-alone mHealth technology–based interventions in suicide prevention. The small number of studies reported in this review tentatively indicate that such tools may have a positive impact on suicide-specific outcomes. Future mHealth intervention evaluations would benefit from addressing the following 3 main methodological limitations : (1) heterogeneity of outcomes: a lack of standardized measurement of suicide outcomes across studies; (2) ecological validity: the tendency to exclude potential participants because of the elevated suicide risk may reduce generalizability within clinical settings; and (3) app regulation and definition: the lack of a standardized classification system for mHealth intervention type points to the need for better definition of the scope of such technologies to promote safe practice.

  • Taxi driver walking away from taxis in an airport holding yard. Source: Image created by the Authors; Copyright: The Authors; URL: https://mhealth.jmir.org/2020/1/e13133; License: Creative Commons Attribution (CC-BY).
    mHealth for Wellness, Behavior Change...

    Jan 15, 2020

    A Mobile Phone App to Improve the Mental Health of Taxi Drivers: Single-Arm Feasibility Trial

    Authors List:

    Abstract:

    Background: Psychological distress among taxi drivers is 5 times higher than that in the general population, and more than half of all drivers have experienced 3 or more potentially traumatic events in their lifetime. Nevertheless, help-seeking for mental health problems in this male-dominated, predominately immigrant workforce is low. Mobile technologies have the potential to increase mental health awareness, teach self-help skills, and encourage help-seeking in this hard-to-reach population. Objective: This study aimed to assess the feasibility, acceptability, and potential efficacy of Driving to Health, a mobile phone–friendly mental health website app designed for people working as taxi drivers. Methods: Drivers (n=46) were recruited from the Melbourne Airport Taxi Holding Yard to participate in a single-arm trial. Self-reported, paper-based assessments were completed at baseline and at 1 month. Feasibility was measured by completion rates, representativeness of study participants, and levels of use. Acceptability was assessed by measuring users’ perception of the quality of the app and anticipated levels of future use. The efficacy of Driving to Health to increase awareness, self-help behaviors, and intentions to seek help was assessed using the user version of the Mobile App Rating Scale (uMARS) and the General Help-Seeking Questionnaire (GHSQ). Psychological symptoms were measured using the short form of the Depression, Anxiety, and Stress Scale (DASS-21). Data were analyzed using complete case analysis. Results: In total, 42 participants comprising drivers from 10 different countries of origin, and 14 different languages, completed pre- and poststudy measures (42/46, 91% completion rate). Just under half (45%) of all users used the app more than once with an average visit of 4 min 8 seconds. Responding to the uMARS, 62% (26/42) of the participants said that they would recommend the app to many people. Nearly all (40/42, 95%) participants said that Driving to Health increased awareness of their own mental health; 86% (36/42) said that it increased their mental health knowledge; and 76% (32/42) said that it increased their self-help behaviors. Increases in help-seeking intentions on the GHSQ were not significant, and increases on all 3 scales of DASS-21 were not reliable or meaningful. Conclusions: This study suggests that Driving to Health is an acceptable and feasible electronic health intervention for a hard-to-reach population. Our findings also suggest that Driving to Health results in increases in mental health awareness, behaviors, and willingness to seek help.

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  • Using digitally augmented objects to reduce sedentary behavior in office workers: design and development of the WorkMyWay intervention

    Date Submitted: Jan 21, 2020

    Open Peer Review Period: Jan 21, 2020 - Jan 28, 2020

    Background: Sedentary behavior (SB) is associated with various adverse health outcomes. The prevalence of prolonged sitting at work among office workers makes a case for SB interventions to target thi...

    Background: Sedentary behavior (SB) is associated with various adverse health outcomes. The prevalence of prolonged sitting at work among office workers makes a case for SB interventions to target this setting and population. Everyday mundane objects augmented with embedded microelectronics and ubiquitous computing represent a novel mode of intervention delivery enabled by the Internet of Things (IoT). However, there is a lack of documentation of how these IoT-enabled interventions are developed and what research underpins the design, which hinders the replicability of research. Objective: This paper documents the development of an IoT-enabled SB intervention targeting office workers, and details the resultant intervention, including its content, theoretical underpinnings, delivery plan and technology, and planned assessment of adherence and fidelity based on technology-captured data. Methods: The process was guided by the Behavior Change Wheel (BCW), a systematic framework for theory-informed and evidence-based development of behavior change interventions, complemented by the human-centered design (HCD) approach. The design was shaped by findings from a diary-probed interview study and a stakeholder design workshop, along with a series of literature review, secondary analyses and interdisciplinary collaborations. Results: The resultant intervention, WorkMyWay, targets a reduction in office workers’ prolonged stationary behaviors at work and an increase in regular ambulatory breaks. It draws on 16 Behavior Change Techniques to address behavioural determinants in 11 theoretical domains. The intervention contents are underpinned by theories including the dual process model, goal setting theory, implementation intention, and modern habit theory. The delivery system, also called WorkMyWay, is composed of a wearable activity tracker, a reminder device attached to digitally augment a vessel, and a companion Android App connected to both devices over Bluetooth connection. The planned delivery consists of a 2-week baseline assessment, a 30-min face-to-face action planning session, and 6-week self-directed use of the WorkMyWay system. Conclusions: Combining the BCW with HCD resulted in an IoT-enabled behavior change intervention that is informed by theories and balanced with stakeholder requirements. The intervention mapping table that specifies links between individual intervention components and the hypothesized mechanisms through which they can influence the target behavior will serve as the basis for theory-based evaluation. The next step is to assess the feasibility of WorkMyWay prior to testing efficacy in a full-scale trial.

  • Health system stakeholders’ perspective on the role of mHealth and its adoption in the Swiss health system: a qualitative study.

    Date Submitted: Dec 17, 2019

    Open Peer Review Period: Dec 20, 2019 - Feb 20, 2020

    Background: Digital Health solutions have a great potential to transform healthcare towards better clinical outcome and improved processes and access, amongst other benefits. Yet, adoption of mHealth...

    Background: Digital Health solutions have a great potential to transform healthcare towards better clinical outcome and improved processes and access, amongst other benefits. Yet, adoption of mHealth solutions, i.e. for patient monitoring, has been rather slow in Switzerland. The reasons are complex and a better understanding is needed to leverage the full potential of mHealth. Objective: This study aims at deepening the understanding of the role of mHealth and factors driving or restraining its adoption in the Swiss health system and providing feasible recommendations for action. Methods: We conducted a qualitative survey using a maximum variation sample of a heterogenous group of stakeholders (N=50) in the Swiss healthcare system with a profound knowledge of digital and mobile health and medical device reimbursement. A semi-structured interview guide including open- and closed-ended questions was used to address questions around mHealth relevance and influence on the health system, the relevance of selected determinants for mHealth adoption as well as important influencing factors. Results: Overall, respondents thought that mHealth will have a beneficial impact on the Swiss health system but that its adoption would evolve slowly. We derived 23 key opportunities regarding patient and patient pathway, treatment of disease, and diseases and health conditions. A high consistency in answers among respondents was observed for ‘treatment of disease’. Providers of healthcare services mentioned a relatively wide range of topics. Stakeholders’ attitudes towards mHealth adoption along the relevance of 23 pre-selected determinants was relatively consistent. However, we obtained diverging attitudes regarding the influence of general trends, enablers and restraints in Switzerland. We derived 26 key themes influencing mHealth adoption. Relevant trends: ‘changing needs and expectations of patients’, ‘a rising need for efficient healthcare delivery’, ‘growing interest in improved outpatient care’, and ‘emerging technologies and progressing digitization’. Important enablers: ‘growing demand for new financing schemes and incentive concepts’, ‘rising demand for comprehensive information on and stronger body of evidence for mHealth use cases’, and ‘increasing need for easy to use alternate care approaches’. Challenging restraints: ‘rigidness of thinking and siloed actions of health system actors’, ‘complexity to change existing regulations and structures’, ‘little understanding of mHealth use and the role of clinicians’, and ‘risk of further polarization of the population’. Conclusions: This study provides a comprehensive look at mHealth in the Swiss health system. It becomes apparent that strong governance is inevitable to foster a sustainable data strategy and to reconcile the different interests of stakeholders. The use of mHealth will add value but not necessarily reduce the burden on the system caused by emerging societal needs and changing disease prevalence. Health system actors need orientation and sensitization in terms of digitization. This study contributes to present additional ways to promote mHealth adoption in Switzerland.

  • Towards earlier diagnosis in rheumatology using combined eHealth tools: The JPAST Project

    Date Submitted: Dec 17, 2019

    Open Peer Review Period: Dec 17, 2019 - Feb 11, 2020

    Outcomes of patients with inflammatory rheumatic diseases have significantly improved over the last three decades, mainly due to therapeutic innovations, more timely treatment and a recognition of the...

    Outcomes of patients with inflammatory rheumatic diseases have significantly improved over the last three decades, mainly due to therapeutic innovations, more timely treatment and a recognition of the need to monitor response to treatment and to titrate treatments accordingly. A major challenge for all stakeholders remains diagnostic delay. The combination of eHealth, serologic and genetic markers holds greats promise to improve the current management of patients with inflammatory rheumatic diseases by speeding up access to appropriate care. The Joint Pain Assessment Scoring Tool (JPAST) project, funded by the European Union (EU) European Institute of Innovation and Technology (EIT) Health program is a unique European project aiming to enable and accelerate personalized precision medicine for early treatment in rheumatology, ultimately also enabling prevention. The aim of the project is to facilitate this while at the same time reducing cost for society and patients.

  • Barriers to and facilitators of the prescription of mHealth apps in Australian general practice: a qualitative study

    Date Submitted: Dec 12, 2019

    Open Peer Review Period: Dec 12, 2019 - Feb 6, 2020

    Background: The ubiquity of smartphones and health apps make them a potential self-management tool for patients that could be prescribed by medical professionals. However, little is known about how Au...

    Background: The ubiquity of smartphones and health apps make them a potential self-management tool for patients that could be prescribed by medical professionals. However, little is known about how Australian general practitioners (GPs) and their patients view the possibility of health app prescription. Objective: To determine barriers and facilitators to prescribing mHealth apps in Australian general practice from the perspective of GPs and patients. Methods: Semi-structured interviews were conducted in Australian general practice settings. GPs and patients were purposively sampled. Interviews were audio-recorded and transcribed. Transcripts were coded and analysed thematically by two researchers. Results: Twenty GPs and 15 adult patients were interviewed. From the GPs’ perspective barriers to prescribing apps were: a generational difference in the digital propensity for GPs and patients; lack of knowledge of prescribable apps and trustworthy sources to access them; the time commitment required of GPs and patients to learn and use the apps; and concerns about privacy, safety, and trustworthiness of health apps. Facilitators from GPs’ perspectives were trustworthy sources to access prescribable apps and information, and younger generation and widespread smartphone ownership. From patients’ perspective, the main barriers for older patients and the usability of the apps. Patients were not concerned about privacy and data safety issues regarding health app use. The facilitators for patients were the ubiquity of smartphones and apps especially for the younger generation, and recommendation of apps by doctors. Evidence of effectiveness was identified as an independent theme from both GPs’ and patients’ perspective. Conclusions: mHealth app prescription appears to be feasible in general practice. The barriers and facilitators identified from the GPs and patients’ perspectives overlapped, though privacy was of less concern to patients. Involvement of health professionals and patients is vital for successful integration of effective, evidence-based mHealth apps with clinical practice.

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