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Journal Description

The Journal of Medical Internet Research (JMIR), now in its 20th year, is the pioneer open access eHealth journal and is the flagship journal of JMIR Publications. It is the leading digital health journal globally in terms of quality/visibility (Impact Factor 2017: 4.671, ranked #1 out of 22 journals) and in terms of size (number of papers published). The journal focuses on emerging technologies, medical devices, apps, engineering, and informatics applications for patient education, prevention, population health and clinical care. As leading high-impact journal in its' disciplines (health informatics and health services research), it is selective, but it is now complemented by almost 30 specialty JMIR sister journals, which have a broader scope. Peer-review reports are portable across JMIR journals and papers can be transferred, so authors save time by not having to resubmit a paper to different journals. 

As open access journal, we are read by clinicians, allied health professionals, informal caregivers, and patients alike, and have (as all JMIR journals) a focus on readable and applied science reporting the design and evaluation of health innovations and emerging technologies. We publish original research, viewpoints, and reviews (both literature reviews and medical device/technology/app reviews).

We are also a leader in participatory and open science approaches, and offer the option to publish new submissions immediately as preprints, which receive DOIs for immediate citation (eg, in grant proposals), and for open peer-review purposes. We also invite patients to participate (eg, as peer-reviewers) and have patient representatives on editorial boards.

Be a widely cited leader in the digitial health revolution and submit your paper today!


Recent Articles:

  • Homepage of RAW Mindfulness Program. Source: Sadhbh Joyce / Placeit; Copyright: JMIR Publications; URL:; License: Creative Commons Attribution (CC-BY).

    Resilience@Work Mindfulness Program: Results From a Cluster Randomized Controlled Trial With First Responders


    Background: A growing body of research suggests that resilience training can play a pivotal role in creating mentally healthy workplaces, particularly with regard to protecting the long-term well-being of workers. Emerging research describes positive outcomes from various types of resilience training programs (RTPs) among different occupational groups. One specific group of workers that may benefit from this form of proactive resilience training is first responders. Given the nature of their work, first responders are frequently exposed to stressful circumstances and potentially traumatic events, which may impact their overall resilience and well-being over time. Objective: This study aimed to examine whether a mindfulness-based RTP (the Resilience@Work [RAW] Mindfulness Program) delivered via the internet can effectively enhance resilience among a group of high-risk workers. Methods: We conducted a cluster randomized controlled trial (RCT) comprising 24 Primary Fire and Rescue and Hazmat stations within New South Wales. Overall, 12 stations were assigned to the 6-session RAW Mindfulness Program and 12 stations were assigned to the control condition. A total of 143 active full-time firefighters enrolled in the study. Questionnaires were administered at baseline, immediately post training, and at 6-month follow-up. Measurements examined change in both adaptive and bounce-back resilience as well as several secondary outcomes examining resilience resources and acceptance and mindfulness skills. Results: Mixed-model repeated measures analysis found that the overall test of group-by-time interaction was significant (P=.008), with the intervention group increasing in adaptive resilience over time. However, no significant differences were found between the intervention group and the control group in terms of change in bounce-back resilience (P=.09). At 6-month follow-up, the group receiving the RAW intervention had an average increase in their resilience score of 1.3, equating to a moderate-to-large effect size compared with the control group of 0.73 (95% CI 0.38-1.06). Per-protocol analysis found that compared with the control group, the greatest improvements in adaptive resilience were observed among those who completed most of the RAW program, that is, 5 to 6 sessions (P=.002). Conclusions: The results of this RCT suggest that mindfulness-based resilience training delivered in an internet format can create improvements in adaptive resilience and related resources among high-risk workers, such as first responders. Despite a number of limitations, the results of this study suggest that the RAW Mindfulness Program is an effective, scalable, and practical means of delivering online resilience training in high-risk workplace settings. To the best of our knowledge, this is the first time a mindfulness-based RTP delivered entirely via the internet has been tested in the workplace. Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12615000574549; (Archived by WebCite at

  • Patient falling. Source: iStock; Copyright: Toa55; URL:; License: Licensed by the authors.

    Novel Approach to Inpatient Fall Risk Prediction and Its Cross-Site Validation Using Time-Variant Data


    Background: Electronic medical records (EMRs) contain a considerable amount of information about patients. The rapid adoption of EMRs and the integration of nursing data into clinical repositories have made large quantities of clinical data available for both clinical practice and research. Objective: In this study, we aimed to investigate whether readily available longitudinal EMR data including nursing records could be utilized to compute the risk of inpatient falls and to assess their accuracy compared with existing fall risk assessment tools. Methods: We used 2 study cohorts from 2 tertiary hospitals, located near Seoul, South Korea, with different EMR systems. The modeling cohort included 14,307 admissions (122,179 hospital days), and the validation cohort comprised 21,172 admissions (175,592 hospital days) from each of 6 nursing units. A probabilistic Bayesian network model was used, and patient data were divided into windows with a length of 24 hours. In addition, data on existing fall risk assessment tools, nursing processes, Korean Patient Classification System groups, and medications and administration data were used as model parameters. Model evaluation metrics were averaged using 10-fold cross-validation. Results: The initial model showed an error rate of 11.7% and a spherical payoff of 0.91 with a c-statistic of 0.96, which represent far superior performance compared with that for the existing fall risk assessment tool (c-statistic=0.69). The cross-site validation revealed an error rate of 4.87% and a spherical payoff of 0.96 with a c-statistic of 0.99 compared with a c-statistic of 0.65 for the existing fall risk assessment tool. The calibration curves for the model displayed more reliable results than those for the fall risk assessment tools alone. In addition, nursing intervention data showed potential contributions to reducing the variance in the fall rate as did the risk factors of individual patients. Conclusions: A risk prediction model that considers longitudinal EMR data including nursing interventions can improve the ability to identify individual patients likely to fall.

  • Source: Freepik; Copyright: sirinarth; URL:; License: Licensed by JMIR.

    Cost-Effectiveness of Telemedicine in Remote Orthopedic Consultations: Randomized Controlled Trial


    Background: Telemedicine consultations using real-time videoconferencing has the potential to improve access and quality of care, avoid patient travels, and reduce health care costs. Objective: The aim of this study was to examine the cost-effectiveness of an orthopedic videoconferencing service between the University Hospital of North Norway and a regional medical center in a remote community located 148 km away. Methods: An economic evaluation based on a randomized controlled trial of 389 patients (559 consultations) referred to the hospital for an orthopedic outpatient consultation was conducted. The intervention group (199 patients) was randomized to receive video-assisted remote orthopedic consultations (302 consultations), while the control group (190 patients) received standard care in outpatient consultation at the hospital (257 consultations). A societal perspective was adopted for calculating costs. Health outcomes were measured as quality-adjusted life years (QALYs) gained. Resource use and health outcomes were collected alongside the trial at baseline and at 12 months follow-up using questionnaires, patient charts, and consultation records. These were valued using externally collected data on unit costs and QALY weights. An extended sensitivity analysis was conducted to address the robustness of the results. Results: This study showed that using videoconferencing for orthopedic consultations in the remote clinic costs less than standard outpatient consultations at the specialist hospital, as long as the total number of patient consultations exceeds 151 per year. For a total workload of 300 consultations per year, the annual cost savings amounted to €18,616. If costs were calculated from a health sector perspective, rather than a societal perspective, the number of consultations needed to break even was 183. Conclusions: This study showed that providing video-assisted orthopedic consultations to a remote clinic in Northern Norway, rather than having patients travel to the specialist hospital for consultations, is cost-effective from both a societal and health sector perspective. This conclusion holds as long as the activity exceeds 151 and 183 patient consultations per year, respectively. Trial Registration: NCT00616837; (Archived by WebCite at

  • Health Care and Cybersecurity: Bibliometric Analysis of the Literature


    Background: Over the past decade, clinical care has become globally dependent on information technology. The cybersecurity of health care information systems is now an essential component of safe, reliable, and effective health care delivery. Objective: The objective of this study was to provide an overview of the literature at the intersection of cybersecurity and health care delivery. Methods: A comprehensive search was conducted using PubMed and Web of Science for English-language peer-reviewed articles. We carried out chronological analysis, domain clustering analysis, and text analysis of the included articles to generate a high-level concept map composed of specific words and the connections between them. Results: Our final sample included 472 English-language journal articles. Our review results revealed that majority of the articles were focused on technology: Technology–focused articles made up more than half of all the clusters, whereas managerial articles accounted for only 32% of all clusters. This finding suggests that nontechnological variables (human–based and organizational aspects, strategy, and management) may be understudied. In addition, Software Development Security, Business Continuity, and Disaster Recovery Planning each accounted for 3% of the studied articles. Our results also showed that publications on Physical Security account for only 1% of the literature, and research in this area is lacking. Cyber vulnerabilities are not all digital; many physical threats contribute to breaches and potentially affect the physical safety of patients. Conclusions: Our results revealed an overall increase in research on cybersecurity and identified major gaps and opportunities for future work.

  • Source: Kadena Air Base (Tara A Williamson); Copyright: US Air Force; URL:; License: Public Domain (CC0).

    Patient-Level Prediction of Cardio-Cerebrovascular Events in Hypertension Using Nationwide Claims Data


    Background: Prevention and management of chronic diseases are the main goals of national health maintenance programs. Previously widely used screening tools, such as Health Risk Appraisal, are restricted in their achievement this goal due to their limitations, such as static characteristics, accessibility, and generalizability. Hypertension is one of the most important chronic diseases requiring management via the nationwide health maintenance program, and health care providers should inform patients about their risks of a complication caused by hypertension. Objective: Our goal was to develop and compare machine learning models predicting high-risk vascular diseases for hypertensive patients so that they can manage their blood pressure based on their risk level. Methods: We used a 12-year longitudinal dataset of the nationwide sample cohort, which contains the data of 514,866 patients and allows tracking of patients’ medical history across all health care providers in Korea (N=51,920). To ensure the generalizability of our models, we conducted an external validation using another national sample cohort dataset, comprising one million different patients, published by the National Health Insurance Service. From each dataset, we obtained the data of 74,535 and 59,738 patients with essential hypertension and developed machine learning models for predicting cardiovascular and cerebrovascular events. Six machine learning models were developed and compared for evaluating performances based on validation metrics. Results: Machine learning algorithms enabled us to detect high-risk patients based on their medical history. The long short-term memory-based algorithm outperformed in the within test (F1-score=.772, external test F1-score=.613), and the random forest-based algorithm of risk prediction showed better performance over other machine learning algorithms concerning generalization (within test F1-score=.757, external test F1-score=.705). Concerning the number of features, in the within test, the long short-term memory-based algorithms outperformed regardless of the number of features. However, in the external test, the random forest-based algorithm was the best, irrespective of the number of features it encountered. Conclusions: We developed and compared machine learning models predicting high-risk vascular diseases in hypertensive patients so that they may manage their blood pressure based on their risk level. By relying on the prediction model, a government can predict high-risk patients at the nationwide level and establish health care policies in advance.

  • Viewing multiple digital data sets. Source: iStock by Getty; Copyright: YakobchukOlena; URL:; License: Licensed by the authors.

    A Framework for Analyzing and Measuring Usage and Engagement Data (AMUsED) in Digital Interventions: Viewpoint


    Trials of digital interventions can yield extensive, in-depth usage data, yet usage analyses tend to focus on broad descriptive summaries of how an intervention has been used by the whole sample. This paper proposes a novel framework to guide systematic, fine-grained usage analyses that better enables understanding of how an intervention works, when, and for whom. The framework comprises three stages to assist in the following: (1) familiarization with the intervention and its relationship to the captured data, (2) identification of meaningful measures of usage and specifying research questions to guide systematic analyses of usage data, and (3) preparation of datasheets and consideration of available analytical methods with which to examine the data. The framework can be applied to inform data capture during the development of a digital intervention and/or in the analysis of data after the completion of an evaluation trial. We will demonstrate how the framework shaped preparation and aided efficient data capture for a digital intervention to lower transmission of cold and flu viruses in the home, as well as how it informed a systematic, in-depth analysis of usage data collected from a separate digital intervention designed to promote self-management of colds and flu. The Analyzing and Measuring Usage and Engagement Data (AMUsED) framework guides systematic and efficient in-depth usage analyses that will support standardized reporting with transparent and replicable findings. These detailed findings may also enable examination of what constitutes effective engagement with particular interventions.

  • Source: Image created by the Authors; Copyright: The Authors; URL:; License: Creative Commons Attribution (CC-BY).

    Mitigation of Participant Loss to Follow-Up Using Facebook: All Our Families Longitudinal Pregnancy Cohort


    Background: Facebook, a popular social media site, allows users to communicate and exchange information. Social media sites can also be used as databases to search for individuals, including cohort participants. Retaining and tracking cohort participants are essential for the validity and generalizability of data in longitudinal research. Despite numerous strategies to minimize loss to follow-up, maintaining contact with participants is time-consuming and resource-intensive. Social media may provide alternative methods of contacting participants who consented to follow-up but could not be reached, and thus are potentially “lost to follow-up.” Objective: The aim of this study was to determine if Facebook was a feasible method for identifying and contacting participants of a longitudinal pregnancy cohort who were lost to follow-up and re-engaging them without selection bias. Methods: This study used data from the All Our Families cohort. Of the 2827 mother-child dyads within the cohort, 237 participants were lost to follow-up. Participants were considered lost to follow-up if they had agreed to participate in additional research, completed at least one of the perinatal questionnaires, did not complete the 5-year postpartum questionnaire, and could not be contacted after numerous attempts via phone, email, or mail. Participants were considered to be matched to a Facebook profile if 2 or more characteristics matched information previously collected. Participants were sent both a friend request and a personal message through the study’s Facebook page and were invited to verify their enrollment in the study. The authors deemed a friend request was necessary because of the reduced functionality of nonfriend direct messaging at the time. If the participant accepted the study’s friend request, then a personalized message was sent. Participants were considered reconnected if they accepted the friend request or responded to any messages. Participants were considered re-engaged if they provided up-to-date contact information. Results: Compared with the overall cohort, participants who were lost to follow-up (n=237) were younger (P=.003), nonmarried (P=.02), had lower household income (P<.001), less education (P<.001), and self-identified as being part of an ethnic minority (P=.02). Of the 237 participants considered lost to follow-up, 47.7% (113/237) participants were identified using Facebook. Among the 113 identified participants, 77.0% (87/113) were contacted, 32.7% (37/113) were reconnected, and 17.7% (20/113) were re-engaged. No significant differences were found between those identified on Facebook (n=113) and those who were not able to be identified (n=124). Conclusions: Facebook identified 47.6% (113/237) of participants who were considered lost to follow-up, and the social media site may be a practical tool for reconnecting with participants. The results from this study demonstrate that social networking sites, such as Facebook, could be included in the development of retention practices and can be implemented at any point in cohort follow-up.

  • Source: Freepik; Copyright: jannoon028; URL:; License: Licensed by JMIR.

    Digital Education in Health Professions: The Need for Overarching Evidence Synthesis


    Synthesizing evidence from randomized controlled trials of digital health education poses some challenges. These include a lack of clear categorization of digital health education in the literature; constantly evolving concepts, pedagogies, or theories; and a multitude of methods, features, technologies, or delivery settings. The Digital Health Education Collaboration was established to evaluate the evidence on digital education in health professions; inform policymakers, educators, and students; and ultimately, change the way in which these professionals learn and are taught. The aim of this paper is to present the overarching methodology that we use to synthesize evidence across our digital health education reviews and to discuss challenges related to the process. For our research, we followed Cochrane recommendations for the conduct of systematic reviews; all reviews are reported according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidance. This included assembling experts in various digital health education fields; identifying gaps in the evidence base; formulating focused research questions, aims, and outcome measures; choosing appropriate search terms and databases; defining inclusion and exclusion criteria; running the searches jointly with librarians and information specialists; managing abstracts; retrieving full-text versions of papers; extracting and storing large datasets, critically appraising the quality of studies; analyzing data; discussing findings; drawing meaningful conclusions; and drafting research papers. The approach used for synthesizing evidence from digital health education trials is commonly regarded as the most rigorous benchmark for conducting systematic reviews. Although we acknowledge the presence of certain biases ingrained in the process, we have clearly highlighted and minimized those biases by strictly adhering to scientific rigor, methodological integrity, and standard operating procedures. This paper will be a valuable asset for researchers and methodologists undertaking systematic reviews in digital health education.

  • Source: CATCH at the University of Sheffield; Copyright: CATCH at the University of Sheffield; URL:; License: Creative Commons Attribution (CC-BY).

    Older Adults’ Perspectives on Using Digital Technology to Maintain Good Mental Health: Interactive Group Study


    Background: A growing number of apps to support good mental health and well-being are available on digital platforms. However, very few studies have examined older adults’ attitudes toward the use of these apps, despite increasing uptake of digital technologies by this demographic. Objective: This study sought to explore older adults’ perspectives on technology to support good mental health. Methods: A total of 15 older adults aged 50 years or older, in two groups, participated in sessions to explore the use of digital technologies to support mental health. Interactive activities were designed to capture participants’ immediate reactions to apps and websites designed to support mental health and to explore their experiences of using technology for these purposes in their own lives. Template analysis was used to analyze transcripts of the group discussions. Results: Older adults were motivated to turn to technology to improve mood through mechanisms of distraction, normalization, and facilitated expression of mental states, while aiming to reduce burden on others. Perceived barriers to use included fear of consequences and the impact of low mood on readiness to engage with technology, as well as a lack of prior knowledge applicable to digital technologies. Participants were aware of websites available to support mental health, but awareness alone did not motivate use. Conclusions: Older adults are motivated to use digital technologies to improve their mental health, but barriers remain that developers need to address for this population to access them.

  • MOTECH Ghana. Source: Grameen Foundation Ghana; Copyright: Grameen Foundation Ghana; URL:; License: Creative Commons Attribution (CC-BY).

    Mobile Technology for Community Health in Ghana: Is Maternal Messaging and Provider Use of Technology Cost-Effective in Improving Maternal and Child Health...


    Background: Mobile technologies are emerging as tools to enhance health service delivery systems and empower clients to improve maternal, newborn, and child health. Limited evidence exists on the value for money of mobile health (mHealth) programs in low- and middle-income countries. Objective: This study aims to forecast the incremental cost-effectiveness of the Mobile Technology for Community Health (MOTECH) initiative at scale across 170 districts in Ghana. Methods: MOTECH’s “Client Data Application” allows frontline health workers to digitize service delivery information and track the care of patients. MOTECH’s other main component, the “Mobile Midwife,” sends automated educational voice messages to mobile phones of pregnant and postpartum women. We measured program costs and consequences of scaling up MOTECH over a 10-year analytic time horizon. Economic costs were estimated from informant interviews and financial records. Health effects were modeled using the Lives Saved Tool with data from an independent evaluation of changes in key services coverage observed in Gomoa West District. Incremental cost-effectiveness ratios were presented overall and for each year of implementation. Uncertainty analyses assessed the robustness of results to changes in key parameters. Results: MOTECH was scaled in clusters over a 3-year period to reach 78.7% (170/216) of Ghana’s districts. Sustaining the program would cost US $17,618 on average annually per district. Over 10 years, MOTECH could potentially save an estimated 59,906 lives at a total cost of US $32 million. The incremental cost per disability-adjusted life year averted ranged from US $174 in the first year to US $6.54 in the tenth year of implementation and US $20.94 (95% CI US $20.34-$21.55) over 10 years. Uncertainty analyses suggested that the incremental cost-effectiveness ratio was most sensitive to changes in health effects, followed by personnel time. Probabilistic sensitivity analyses suggested that MOTECH had a 100% probability of being cost-effective above a willingness-to-pay threshold of US $50. Conclusions: This is the first study to estimate the value for money of the supply- and demand-side of an mHealth initiative. The adoption of MOTECH to improve MNCH service delivery and uptake represents good value for money in Ghana and should be considered for expansion. Integration with other mHealth solutions, including e-Tracker, may provide opportunities to continue or combine beneficial components of MOTECH to achieve a greater impact on health.

  • Source: Freepik; Copyright: katemangostar; URL:; License: Licensed by the authors.

    Use of Learning Analytics Data in Health Care–Related Educational Disciplines: Systematic Review


    Background: While the application of learning analytics in tertiary education has received increasing attention in recent years, a much smaller number have explored its use in health care-related educational studies. Objective: This systematic review aims to examine the use of e-learning analytics data in health care studies with regards to how the analytics is reported and if there is a relationship between e-learning analytics and learning outcomes. Methods: We performed comprehensive searches of papers from 4 electronic databases (MEDLINE, EBSCOhost, Web of Science, and ERIC) to identify relevant papers. Qualitative studies were excluded from this review. Papers were screened by 2 independent reviewers. We selected qualified studies for further investigation. Results: A total of 537 papers were screened, and 19 papers were identified. With regards to analytics undertaken, 11 studies reported the number of connections and time spent on e-learning. Learning outcome measures were defined by summative final assessment marks or grades. In addition, significant statistical results of the relationships between e-learning usage and learning outcomes were reported in 12 of the identified papers. In general, students who engaged more in e-learning resources would get better academic attainments. However, 2 papers reported otherwise with better performing students consuming less e-learning videos. A total of 14 papers utilized satisfaction questionnaires for students, and all were positive in their attitude toward e-learning. Furthermore, 6 of 19 papers reported descriptive statistics only, with no statistical analysis. Conclusions: The nature of e-learning activities reported in this review was varied and not detailed well. In addition, there appeared to be inadequate reporting of learning analytics data observed in over half of the selected papers with regards to definitions and lack of detailed information of what the analytic was recording. Although learning analytics data capture is popular, a lack of detail is apparent with regards to the capturing of meaningful and comparable data. In particular, most analytics record access to a management system or particular e-learning materials, which may not necessarily detail meaningful learning time or interaction. Hence, learning analytics data should be designed to record the time spent on learning and focus on key learning activities. Finally, recommendations are made for future studies.

  • Source: Image created by the Authors; Copyright: The Authors; URL:; License: Creative Commons Attribution (CC-BY).

    Evaluation of Mothers’ Perceptions of a Technology-Based Supportive Educational Parenting Program (Part 2): Qualitative Study


    Background: Transitioning into parenthood can be stressful as parents struggle to cope with new parenting responsibilities. Although perinatal care in hospitals aims to improve parental outcomes, there is a general consensus that it is suboptimal and insufficient. Therefore, many studies have designed intervention methods to supplement support for parents during this stressful period. However, studies often focus on parental outcomes as indicators of their interventions’ success and effectiveness. Studies evaluating participants’ experiences and feedback are limited. Objective: This study aimed to examine the experiences and perceptions of participants who participated in a supportive education parenting program intervention study. Methods: A qualitative semistructured interview was conducted with 16 mothers (6 control and 10 intervention) from a randomized controlled trial. The supportive education parenting program received by the intervention group included 2 phone-based perinatal educational sessions, a phone-based educational session after childbirth, and a 1-month postpartum access to a mobile health app. The interviews were approximately 30- to 60-min long, audiotaped and transcribed verbatim, and analyzed using thematic analysis. Study findings were reported according to the Consolidated Criteria for Reporting Qualitative Research checklist. Results: The 3 main themes evaluating mothers’ experiences and perceptions were generated: (1) changed perspective toward parenthood, (2) journey from pregnancy to after birth, and (3) a way forward. Mothers from the intervention group mostly had good perinatal experiences with sufficient support received, which elevated their emotional well-being and increased parenting involvement. Mothers in the control group, although satisfied with the hospital care received, were more stressed and shared a need for professional advice and extra support. Apart from technical enhancements, mothers also requested extended social support during early pregnancy up to 1 year postpartum, taking into consideration Asian cultural practices. Conclusions: Mothers who received the intervention were overall satisfied with the support provided by the technology-based supportive educational parenting program. The success of the educational program in this study highlights the need to supplement standard care in hospitals with technology-based educational programs. Future research should include fathers’ perceptions to attain an in-depth understanding of overall participants’ experiences and needs in the future development of supportive and educational programs.

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  • Trial Design, Feasibility, and Acceptability of an Intervention to Reduce Hypoglycemia Fear in Parents of Young Kids with Video-Based Telemedicine (REDCHIP)

    Date Submitted: Feb 15, 2019

    Open Peer Review Period: Feb 19, 2019 - Apr 16, 2019

    Background: Fear of hypoglycemia is common in parents of young children with type 1 diabetes (T1D) and problematically linked to maladaptive behaviors to avoid low blood glucose, parenting stress, and...

    Background: Fear of hypoglycemia is common in parents of young children with type 1 diabetes (T1D) and problematically linked to maladaptive behaviors to avoid low blood glucose, parenting stress, and burn-out. There are currently no interventions focused on reducing hypoglycemia fear in this population. Objective: To examine the feasibility and acceptability of a group-based telemedicine intervention to reduce fear of hypoglycemia in parents of young children with T1D. Methods: Forty-three families of a young child with T1D (1-6 years old; diagnosed with T1D for at least 6 months) enrolled in the study and 36 completed the Reducing Emotional Distress for Childhood Hypoglycemia in Parents (REDCHiP) intervention. We delivered a 10-session manualized cognitive behavioral intervention to reduce hypoglycemia fear using telemedicine (i.e., secure real-time videoconferencing). We assessed intervention feasibility with rates of attrition, intervention attendance, and fidelity to the treatment manual. Intervention completers answered a treatment satisfaction survey and a subset of completers (N=10) participated in qualitative interviews about intervention acceptability, facilitators, and challenges. Results: Total study attrition was 21%, including the long-term follow-up period (16% before or during the treatment phase of the study). On average, parents attended 94% of intervention sessions and average fidelity to the treatment manual was 89%. Intervention completers reported high satisfaction with the treatment groups (85% average satisfaction rating). Parents reported positive influencers of the REDCHiP intervention during qualitative interviews (i.e., knowledge, fear awareness, coping strategies, confidence, behavioral parenting strategies, and support). Parents did report some intervention challenges, including feeling fearful or overwhelmed, family stress, lack of trust, and difficulty connecting with other group members. Conclusions: The REDCHiP intervention demonstrated initial feasibility and acceptability. Next steps include determining the intervention’s impact on objective parent and child outcomes (e.g., glycemic control, parental fear of hypoglycemia, parental stress/distress). Clinical Trial: NICHD R21 HD081502

  • User Preferences Related to Multimedia Elements of a Mobile Application to Prevent Postpartum Diabetes: A Study with Focus Groups

    Date Submitted: Feb 15, 2019

    Open Peer Review Period: Feb 19, 2019 - Apr 16, 2019

    Background: Designing and implementing strategies using information technology to support programs that stimulate a healthy lifestyle in primary care plays an important role in the prevention of nonco...

    Background: Designing and implementing strategies using information technology to support programs that stimulate a healthy lifestyle in primary care plays an important role in the prevention of noncommunicable diseases. Objective: To understand user preferences related to the characteristics of an application that promotes and provides education on healthy habits in order to correctly design multimedia elements. Methods: Comprehensive qualitative study with an hermeneutical strategy, which gathered information using well-researched questions that were posed to focus groups consisting of 32 participants. These participants were asked for opinions related to multimedia elements to display educational messages about physical activity and healthy eating in a mobile application. Three analysis categories of multimedia elements: text, visual elements, and audio elements. Results: The majority of participants, 93.75%, are in the low socioeconomic stratum; 68.75% are in a civil union with their partner; 53.12% completed or failed to complete secondary school and 68.75% are housemakers. Based on the qualitative results, we found that mobile applications become mediating tools that support the adoption of actions that tend to improve lifestyles and increase knowledge about proper nutrition and physical activity. Message text used in mobile applications should promote the use of healthy habits and remind users of their benefits. Images and videos should be accompanied by text and audio to provide greater clarity regarding recommendations of healthy habits. Conclusions: Technology serves as a complement to health care, improving the accessibility and availability of timely care and enabling customized health self-management.

  • Pregnancy-related Information Seeking and Sharing in the Social Media Era: A Qualitative Study of Expectant Mothers in China

    Date Submitted: Feb 13, 2019

    Open Peer Review Period: Feb 19, 2019 - Apr 16, 2019

    Background: Social media has become the most popular communication tool used by Chinese citizens, including expectant mothers. An increasing number of women have adopted various forms of social media,...

    Background: Social media has become the most popular communication tool used by Chinese citizens, including expectant mothers. An increasing number of women have adopted various forms of social media, such as interactive websites, instant messaging, and software applications (apps), to solve problems experienced during pregnancy. Although the use of the Internet by pregnant women has been studied extensively worldwide, limited exist that explore the changing social media usage in China where the one-child policy ended in 2015. Objective: This study intends to a) identify major patterns in pregnancy-related information seeking, b) present the status quos of information sharing on social media applications for pregnancy-related information, and c) reveal the impact derived from social media usage among expectant mothers. Methods: A qualitative approach was employed to examine the social media usage and its consequences by pregnant women. 20 conceiving women during various stages of pregnancy were interviewed from 1st July – 25th August 2017. Data collected was subjected to a grounded theory analysis. Results: 80% (n=16) of participants were in their 20s (M=28.5, S.D.=4.3). More than 90% of the participants had used social media for pregnancy-related purposes. Most of the pregnant women were ‘lurkers’ i.e. viewing, but not participating, and they preferred not to engage in random conversations on social media. However, they were active in private talks via social media. Meanwhile, the most frequently discussed concern was the do’s and don’ts during pregnancy, and subconsciously avoiding bad news on social media. In terms of patterns in user behavior, they tended to cross-reference multiple sources on social media for accuracy, and credibility, with relation to healthcare provision. Most of the participants reported a positive impact on informed decision making and mental stability. Conclusions: It is indisputable that social media has played an increasingly important role in supporting expectant women in China. Their trust of social media-based pregnancy-related sources were varied, and highly dependent on the authoritativeness of the providers as well as their understanding of prenatal care. As pregnancy, in Chinese culture, has a ‘vulnerable’ stigma attached, it makes pregnant women only active within closed groups. Future prenatal care delivery should utilize the unique seeking and sharing behavior patterns to maximize the positive benefit of pregnant women in China, as well as reducing the inequality of social media-based services caused by digital divide.

  • The Effectiveness of an App-Based Nurse-Moderated Program for New Mothers With Depression and Parenting Problems (eMums Plus): A Pragmatic Randomised Controlled Trial.

    Date Submitted: Feb 13, 2019

    Open Peer Review Period: Feb 19, 2019 - Apr 16, 2019

    Background: Background: Postnatal depression adversely affects mothers and infants. There is evidence that caregiving difficulties associated with depressive symptoms also adversely affect later child...

    Background: Background: Postnatal depression adversely affects mothers and infants. There is evidence that caregiving difficulties associated with depressive symptoms also adversely affect later childhood development. In many countries, resources available to support mothers experiencing depressive symptoms during the postnatal period are limited. Cost-effective online group-based nurse-led interventions delivered by mobile phone ‘apps’ have the potential to help address this problem by providing large numbers of mothers with access to professional and peer support during the postnatal period. Objective: Objective: The aim of this study was to test the effectiveness of a 4-month online group-based nurse-led intervention delivered when infants were 2-6 months as compared to standard care outcomes. Methods: Methods: The study was a block randomised control trial. Mothers were recruited at the time they were contacted for the postnatal health check offered to all mothers in South Australia. Those who agreed to participate were randomly assigned to the intervention or standard care. The overall response rate was 63% (N=133/210). Primary outcomes were level of maternal depressive symptoms assessed with the Edinburgh Postnatal Depression Scale (EPDS); and quality of maternal caregiving assessed using the Parenting Stress Index (PSI competence and attachment subscales), the Parenting Sense of Competence Scale, and the Nursing Child Assessment Satellite Training Scale. Assessments were completed at baseline (mean child age=4.9 weeks, SD=1.4) and again when infants were aged 8, and 12 months. Results: Results: Outcomes were evaluated using linear generalized estimating equations adjusting for post-randomization group differences in demographic characteristics and the outcome score at baseline. There were no significant differences in the intervention and standard care groups in scores on the PSI competence subscale (P=.69) nor the Parenting Sense of Competence Scale (P=.11). While the group by time interaction suggested there were differences over time between the EPDS and PSI attachment subscales scores in the intervention and standard care groups (P=.001 and P=.04 respectively), these arose largely because the intervention group had stable scores over time while the standard care group showed some improvements between baseline to 12 months. Mothers engaged well with the intervention with 60% of mothers logging-in once per week during the first 11 weeks of the intervention. The majority of mothers also rated the intervention as helpful and user-friendly. Conclusions: Conclusions: Mothers reported that the intervention was helpful and the app was described as easy to use. As such, it appears that support for mothers during the postnatal period, provided using mobile phone technology, has the potential to be an important addition to existing services. Possible explanations for the lack of differences in outcomes for the two groups in this study are the failure of many mothers to use key components of the intervention and residual differences between the intervention and standard care groups post-randomization. Clinical Trial: Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN 12616001732471

  • Perception and Sentiments about Electronic Cigarette on the Social Media: A Systematic Review

    Date Submitted: Feb 14, 2019

    Open Peer Review Period: Feb 19, 2019 - Apr 16, 2019

    Background: Electronic cigarettes (e-cigarettes) have been widely promoted on the internet, and subsequently, social media platforms have been used as an important informative medium by the users. Lik...

    Background: Electronic cigarettes (e-cigarettes) have been widely promoted on the internet, and subsequently, social media platforms have been used as an important informative medium by the users. Likewise, reasons to initiate, switch to and from conventional smoking to e-cigarette smoking, and to like and dislike e-cigarette have been largely influenced by the belief and knowledge displayed on the social media. However, there is a gap in the knowledge on people’s perception, attitudes, and sentiments about e-cigarettes depicted on social media and the sources of information they exchange. Objective: To explore peoples’ perceptions about e-cigarette on the internet and social media whether they portray benefits or harmfulness of e-cigarette use, and to examine the kind of information that people share and obtain about the e-cigarette on social media. Methods: Searches in major electronic databases, including PubMed, CINAHL, EMBASE and Web of Science were conducted using search terms: “electronic cigarette,” “electronic vaporizer,” “electronic nicotine,” and “electronic nicotine delivery systems,” combined with “internet,” “social media,” and “internet use”. The studies were selected if they examined participants’ perception and sentiments of e-cigarettes on the internet forums or social media websites within the last 10 years (2007-2017). Results: Fifteen articles were included. Nine social media platforms: Twitter, Reddit, Instagram, online discussion boards such as JuiceDB, and forums (Vapor Talks, Hookah forum, Electronic cigarette forum, Vapors forum, GLOBALink) were identified in qualitative (n=5), quantitative (n=4), and mixed-methods (n=6) studies. Real-time snapshot and characteristics of sentiments, personal experience, and perceptions toward e-cigarettes on internet were identified. Common topics regarding e-cigarettes included positive and negative health effects and appeals reported by current users, potential risks, benefits, regulations associated with e-cigarettes, and attitudes toward them as smoking cessation aids. Conclusions: Although mixed perceptions among the social media users were depicted, there were more volume of pro e-cigarette tweets and threads than anti-use. This study significantly adds to our understanding of current trend in the popularity and attitude towards e-cigarettes among social media users. It also suggests that social media has the potential to screen, prevent, and disseminate health promotional information and prevention interventions for the public’s well-being. Future research should focus on the efficacy of health focus e-campaigns or link on social media that delivers appropriate information about the facts, harms and benefits of e-cigarette.

  • Developing a fuzzy expert system for determining the levels of students' eHealth literacy

    Date Submitted: Feb 15, 2019

    Open Peer Review Period: Feb 19, 2019 - Apr 16, 2019

    Background: The concept of eHealth literacy refers to the ability of a person to access electronic health information, evaluate the information and apply the resulting knowledge in order to address or...

    Background: The concept of eHealth literacy refers to the ability of a person to access electronic health information, evaluate the information and apply the resulting knowledge in order to address or solve a health problem. In a society with higher levels of e-health literacy, health and aid in health care can be promoted by using electronic health tools. The first step of promoting eHealth literacy is to assess the current situation of society and determine its health literacy level. Although there are different methods for determination of the level of eHealth literacy in the existing studies, there is no way to measure the level of e-health literacy more precisely and realistically due to its subjective concept. Objective: This research aims to develop and implement a fuzzy expert system to determine the level of eHealth literacy. The system must be able to identify the weakness of students' e-health literacy in order to tailor services and information to the needs of the target group. In addition, the system could be a help for responsible organizations such as the Ministry of Health or the university to suggest intervention programs for improving the students' eHealth literacy based on the results. Methods: In this paper, different ways of measuring the individual’s literacy level were extracted. Due to the experts’ opinion, the Digital Health Literacy Instrument was selected and used to develop a rule-based fuzzy expert system to determine the levels of eHealth literacy. The reliability and validity of the expert system were evaluated based on the experts’ judgment and by asking for the participation of 50 students of Mashhad University of Medical Sciences. In order to decrease the calculation time and make the system easier to use, the fuzzy expert system was modified based on rough set theory, which caused a reduction in the number of rules from 300 to 159. Results: The comparison between the two fuzzy expert systems indicated that no significant difference was detected and both systems were succeeded in around 90% of the cases. Conclusions: Determination of the levels of students’ electronic health literacy is a complex problem that includes uncertainty and inaccuracy. Due to the accuracy and agility of expert systems, it is recommended to use the fuzzy-rough expert system in order to overcome this problem.