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Journal Description

The Journal of Medical Internet Research (JMIR), now in its 21st 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 2018: 4.945, ranked #1 out of 26 journals in the medical informatics category) 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 a 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 an open access journal, we are read by clinicians, allied health professionals, informal caregivers, and patients alike, and have (as with 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.

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Recent Articles:

  • PHD questionnaire in the Pollen App. Source: Image created by the Authors; Copyright: Katharina Bastl; URL: http://www.jmir.org/2020/2/e16767/; License: Creative Commons Attribution (CC-BY).

    Translating the Burden of Pollen Allergy Into Numbers Using Electronically Generated Symptom Data From the Patient’s Hayfever Diary in Austria and Germany:...

    Abstract:

    Background: Pollen allergies affect a significant proportion of the population globally. At present, Web-based tools such as pollen diaries and mobile apps allow for easy and fast documentation of allergic symptoms via the internet. Objective: This study aimed to characterize the users of the Patient’s Hayfever Diary (PHD), a Web-based platform and mobile app, to apply different symptom score calculations for comparison, and to evaluate the contribution of organs and medications to the total score for the first time. Methods: The PHD users were filtered with regard to their location in Austria and Germany, significant positive correlation to the respective pollen type (birch/grass), and at least 15 entries in the respective season. Furthermore, 4 different symptom score calculation methods were applied to the datasets from 2009 until 2018, of which 2 were raw symptom scores and 2 were symptom load index (normalized) calculations. Pearson correlation coefficients were calculated pairwise for these 4 symptom score calculations. Results: Users were mostly male and belonged to the age groups of 21 to 40 years or >40 years. User numbers have increased in the last 5 years, especially when mobile apps were made available. The Pearson correlation coefficients showed a significant linear relationship above 0.9 among the 4 symptom score datasets and thus indicated no significant difference between the different methods of symptom score calculation. The nose contributed the most to the symptom score and determined about 40% of the score. Conclusions: The exact method of calculation of the symptom score is not critical. All computation methods show the same behavior (increase/decrease during the season). Therefore, the symptom load index is a useful computation method in all fields exploring pollen allergy, and Web-based diaries are a globally applicable tool to monitor the effect of pollen on human health via electronically generated symptom data.

  • Source: Unsplash; Copyright: Hannah Olinger; URL: https://unsplash.com/photos/8eSrC43qdro; License: Licensed by JMIR.

    Evaluating the Effect of Daily Diary Instructional Phrases on Respondents’ Recall Time Frames: Survey Experiment

    Abstract:

    Background: Daily diaries are extensively used for examining participants’ daily experience in behavioral and medical science. However, little attention is paid to whether participants recall their experiences within the time frames prescribed by the task. Objective: This study aimed to describe survey respondents’ self-reported recall time frames and to evaluate the impact of different daily diary items on respondents’ reported affective states. Methods: In this study, 577 participants completed a mood survey with one of the following 4 time frame instructions: (1) today, (2) since waking up today, (3) during the last 24 hours, or (4) in the last day. They were also asked to indicate the periods they considered when answering these items and to recall the instructional phrases associated with the items. Results: Almost all participants in the today (141/146, 96.6%) and since waking up today (136/145, 93.8%) conditions reported using periods consistent with our expectations, whereas a lower proportion was observed in the during the last 24 hours (100/145, 69.0%) condition. A diverse range of responses was observed in the in the last day condition. Furthermore, the instructions influenced the levels of some self-reported affects, although exploratory analyses were not able to identify the mechanism underlying this finding. Conclusions: Overall, these results indicate that today and since waking up today are the most effective instructional phrases for inquiring about daily experience and that investigators should use caution when using the other 2 instructional phrases. Trial Registration:

  • Source: iStock by Getty Images; Copyright: metamorworks; URL: https://www.istockphoto.com/de/foto/ki-und-finanztechnologie-gm851956240-139994769; License: Licensed by the authors.

    The Economic Impact of Artificial Intelligence in Health Care: Systematic Review

    Abstract:

    Background: Positive economic impact is a key decision factor in making the case for or against investing in an artificial intelligence (AI) solution in the health care industry. It is most relevant for the care provider and insurer as well as for the pharmaceutical and medical technology sectors. Although the broad economic impact of digital health solutions in general has been assessed many times in literature and the benefit for patients and society has also been analyzed, the specific economic impact of AI in health care has been addressed only sporadically. Objective: This study aimed to systematically review and summarize the cost-effectiveness studies dedicated to AI in health care and to assess whether they meet the established quality criteria. Methods: In a first step, the quality criteria for economic impact studies were defined based on the established and adapted criteria schemes for cost impact assessments. In a second step, a systematic literature review based on qualitative and quantitative inclusion and exclusion criteria was conducted to identify relevant publications for an in-depth analysis of the economic impact assessment. In a final step, the quality of the identified economic impact studies was evaluated based on the defined quality criteria for cost-effectiveness studies. Results: Very few publications have thoroughly addressed the economic impact assessment, and the economic assessment quality of the reviewed publications on AI shows severe methodological deficits. Only 6 out of 66 publications could be included in the second step of the analysis based on the inclusion criteria. Out of these 6 studies, none comprised a methodologically complete cost impact analysis. There are two areas for improvement in future studies. First, the initial investment and operational costs for the AI infrastructure and service need to be included. Second, alternatives to achieve similar impact must be evaluated to provide a comprehensive comparison. Conclusions: This systematic literature analysis proved that the existing impact assessments show methodological deficits and that upcoming evaluations require more comprehensive economic analyses to enable economic decisions for or against implementing AI technology in health care.

  • Patient using oximeter. Source: Image created by the Authors; Copyright: The Authors; URL: http://www.jmir.org/2020/2/e16694/; License: Creative Commons Attribution (CC-BY).

    Physical Examinations via Video for Patients With Heart Failure: Qualitative Study Using Conversation Analysis

    Abstract:

    Background: Video consultations are increasingly seen as a possible replacement for face-to-face consultations. Direct physical examination of the patient is impossible; however, a limited examination may be undertaken via video (eg, using visual signals or asking a patient to press their lower legs and assess fluid retention). Little is currently known about what such video examinations involve. Objective: This study aimed to explore the opportunities and challenges of remote physical examination of patients with heart failure using video-mediated communication technology. Methods: We conducted a microanalysis of video examinations using conversation analysis (CA), an established approach for studying the details of communication and interaction. In all, seven video consultations (using FaceTime) between patients with heart failure and their community-based specialist nurses were video recorded with consent. We used CA to identify the challenges of remote physical examination over video and the verbal and nonverbal communication strategies used to address them. Results: Apart from a general visual overview, remote physical examination in patients with heart failure was restricted to assessing fluid retention (by the patient or relative feeling for leg edema), blood pressure with pulse rate and rhythm (using a self-inflating blood pressure monitor incorporating an irregular heartbeat indicator and put on by the patient or relative), and oxygen saturation (using a finger clip device). In all seven cases, one or more of these examinations were accomplished via video, generating accurate biometric data for assessment by the clinician. However, video examinations proved challenging for all involved. Participants (patients, clinicians, and, sometimes, relatives) needed to collaboratively negotiate three recurrent challenges: (1) adequate design of instructions to guide video examinations (with nurses required to explain tasks using lay language and to check instructions were followed), (2) accommodation of the patient’s desire for autonomy (on the part of nurses and relatives) in light of opportunities for involvement in their own physical assessment, and (3) doing the physical examination while simultaneously making it visible to the nurse (with patients and relatives needing adequate technological knowledge to operate a device and make the examination visible to the nurse as well as basic biomedical knowledge to follow nurses’ instructions). Nurses remained responsible for making a clinical judgment of the adequacy of the examination and the trustworthiness of the data. In sum, despite significant challenges, selected participants in heart failure consultations managed to successfully complete video examinations. Conclusions: Video examinations are possible in the context of heart failure services. However, they are limited, time consuming, and challenging for all involved. Guidance and training are needed to support rollout of this new service model, along with research to understand if the challenges identified are relevant to different patients and conditions and how they can be successfully negotiated.

  • Source: iStockphoto; Copyright: AndreyPopov; URL: https://www.istockphoto.com/photo/businessman-videoconferencing-with-doctor-on-laptop-gm1000963898-270620484?clarity=false; License: Licensed by the authors.

    Barriers and Facilitators That Influence Telemedicine-Based, Real-Time, Online Consultation at Patients’ Homes: Systematic Literature Review

    Abstract:

    Background: Health care providers are adopting information and communication technologies (ICTs) to enhance their services. Telemedicine is one of the services that rely heavily on ICTs to enable remote patients to communicate with health care professionals; in this case, the patient communicates with the health care professional for a follow-up or for a consultation about his or her health condition. This communication process is referred to as an e-consultation. In this paper, telemedicine services refer to health care services that use ICTs, which enable patients to share, transfer, and communicate data or information in real time (ie, synchronous) from their home with a care provider—normally a physician—at a clinical site. However, the use of e-consultation services can be positively or negatively influenced by external or internal factors. External factors refer to the environment surrounding the system as well as the system itself, while internal factors refer to user behavior and motivation. Objective: This review aims to investigate the barriers and the facilitators that influence the use of home consultation systems in the health care context. This review also aims to identify the effectiveness of Home Online Health Consultation (HOHC) systems in improving patients’ health as well as their satisfaction with the systems. Methods: We conducted a systematic literature review to search for articles—empirical studies—about online health consultation in four digital libraries: Scopus, Association for Computing Machinery, PubMed, and Web of Science. The database search yielded 2518 articles; after applying the inclusion and exclusion criteria, the number of included articles for the final review was 45. A qualitative content analysis was performed to identify barriers and facilitators to HOHC systems, their effectiveness, and patients’ satisfaction with them. Results: The systematic literature review identified several external and internal facilitators and barriers to HOHC systems that were used in the creation of a HOHC framework. The framework consists of four requirements; the framework also consists of 17 facilitators and eight barriers, which were further categorized as internal and external influencers on HOHC. Conclusions: Patients from different age groups and with different health conditions benefited from remote health services. HOHC via video conferencing was effective in delivering online treatment and was well-accepted by patients, as it simulated in-person, face-to-face consultation. Acceptance by patients increased as a result of online consultation facilitators that promoted effective and convenient remote treatment. However, some patients preferred face-to-face consultation and showed resistance to online consultation. Resistance to online consultation was influenced by some of the identified barriers. Overall, the framework identified the facilitators and barriers that positively and negatively influenced the uptake of HOHC systems, respectively.

  • Source: Pixabay; Copyright: Wokandapix; URL: https://pixabay.com/photos/feet-bed-sleep-sleeping-bedroom-3496746/; License: Licensed by JMIR.

    Four-Year Trends in Sleep Duration and Quality: A Longitudinal Study Using Data from a Commercially Available Sleep Tracker

    Abstract:

    Background: Population estimates of sleep duration and quality are inconsistent because they rely primarily on self-reported data. Passive and ubiquitous digital tracking and wearable devices may provide more accurate estimates of sleep duration and quality. Objective: This study aimed to identify trends in sleep duration and quality in New York City based on 2 million nights of data from users of a popular mobile sleep app. Methods: We examined sleep duration and quality using 2,161,067 nights of data captured from 2015 to 2018 by Sleep Cycle, a popular sleep-tracking app. In this analysis, we explored differences in sleep parameters based on demographic factors, including age and sex. We used graphical matrix representations of data (heat maps) and geospatial analyses to compare sleep duration (in hours) and sleep quality (based on time in bed, deep sleep time, sleep consistency, and number of times fully awake), considering potential effects of day of the week and seasonality. Results: Women represented 46.43% (1,003,421/2,161,067) of the sample, and men represented 53.57% (1,157,646/2,161,067) of individuals in the sample. The average age of the sample was 31.0 years (SD 10.6). The mean sleep duration of the total sample was 7.11 hours (SD 1.4). Women slept longer on average (mean 7.27 hours, SD 1.4) than men (mean 7 hours, SD 1.3; P<.001). Trend analysis indicated longer sleep duration and higher sleep quality among older individuals than among younger (P<.001). On average, sleep duration was longer on the weekend nights (mean 7.19 hours, SD 1.5) than on weeknights (mean 7.09 hours, SD 1.3; P<.001). Conclusions: Our study of data from a commercially available sleep tracker showed that women experienced longer sleep duration and higher sleep quality in nearly every age group than men, and a low proportion of young adults obtained the recommended sleep duration. Future research may compare sleep measures obtained via wearable sleep trackers with validated research-grade measures of sleep.

  • Source: Image created by the Authors; Copyright: The Authors; URL: http://www.jmir.org/2020/2/e14122/; License: Public Domain (CC0).

    Concordance Between Watson for Oncology and a Multidisciplinary Clinical Decision-Making Team for Gastric Cancer and the Prognostic Implications:...

    Abstract:

    Background: With the increasing number of cancer treatments, the emergence of multidisciplinary teams (MDTs) provides patients with personalized treatment options. In recent years, artificial intelligence (AI) has developed rapidly in the medical field. There has been a gradual tendency to replace traditional diagnosis and treatment with AI. IBM Watson for Oncology (WFO) has been proven to be useful for decision-making in breast cancer and lung cancer, but to date, research on gastric cancer is limited. Objective: This study compared the concordance of WFO with MDT and investigated the impact on patient prognosis. Methods: This study retrospectively analyzed eligible patients (N=235) with gastric cancer who were evaluated by an MDT, received corresponding recommended treatment, and underwent follow-up. Thereafter, physicians inputted the information of all patients into WFO manually, and the results were compared with the treatment programs recommended by the MDT. If the MDT treatment program was classified as “recommended” or “considered” by WFO, we considered the results concordant. All patients were divided into a concordant group and a nonconcordant group according to whether the WFO and MDT treatment programs were concordant. The prognoses of the two groups were analyzed. Results: The overall concordance of WFO and the MDT was 54.5% (128/235) in this study. The subgroup analysis found that concordance was less likely in patients with human epidermal growth factor receptor 2 (HER2)-positive tumors than in patients with HER2-negative tumors (P=.02). Age, Eastern Cooperative Oncology Group performance status, differentiation type, and clinical stage were not found to affect concordance. Among all patients, the survival time was significantly better in concordant patients than in nonconcordant patients (P<.001). Multivariate analysis revealed that concordance was an independent prognostic factor of overall survival in patients with gastric cancer (hazard ratio 0.312 [95% CI 0.187-0.521]). Conclusions: The treatment recommendations made by WFO and the MDT were mostly concordant in gastric cancer patients. If the WFO options are updated to include local treatment programs, the concordance will greatly improve. The HER2 status of patients with gastric cancer had a strong effect on the likelihood of concordance. Generally, survival was better in concordant patients than in nonconcordant patients.

  • Source: pixabay; Copyright: Willi Heidelbach; URL: https://pixabay.com/photos/font-lead-set-book-printing-705667/; License: Creative Commons Attribution (CC-BY).

    A Framework for Applying Natural Language Processing in Digital Health Interventions

    Abstract:

    Background: Digital health interventions (DHIs) are poised to reduce target symptoms in a scalable, affordable, and empirically supported way. DHIs that involve coaching or clinical support often collect text data from 2 sources: (1) open correspondence between users and the trained practitioners supporting them through a messaging system and (2) text data recorded during the intervention by users, such as diary entries. Natural language processing (NLP) offers methods for analyzing text, augmenting the understanding of intervention effects, and informing therapeutic decision making. Objective: This study aimed to present a technical framework that supports the automated analysis of both types of text data often present in DHIs. This framework generates text features and helps to build statistical models to predict target variables, including user engagement, symptom change, and therapeutic outcomes. Methods: We first discussed various NLP techniques and demonstrated how they are implemented in the presented framework. We then applied the framework in a case study of the Healthy Body Image Program, a Web-based intervention trial for eating disorders (EDs). A total of 372 participants who screened positive for an ED received a DHI aimed at reducing ED psychopathology (including binge eating and purging behaviors) and improving body image. These users generated 37,228 intervention text snippets and exchanged 4285 user-coach messages, which were analyzed using the proposed model. Results: We applied the framework to predict binge eating behavior, resulting in an area under the curve between 0.57 (when applied to new users) and 0.72 (when applied to new symptom reports of known users). In addition, initial evidence indicated that specific text features predicted the therapeutic outcome of reducing ED symptoms. Conclusions: The case study demonstrates the usefulness of a structured approach to text data analytics. NLP techniques improve the prediction of symptom changes in DHIs. We present a technical framework that can be easily applied in other clinical trials and clinical presentations and encourage other groups to apply the framework in similar contexts.

  • Source: freepik; Copyright: tirachardz; URL: https://www.freepik.com/free-photo/asian-senior-men-using-mobile-phone-home-asian-senior-chinese-male-search-information-about-how-good-health-internet-while-lying-bed-bedroom-home-morning-concept_5820713.htm#page=2&query=patient+in+bed&position=9; License: Licensed by JMIR.

    Effectiveness of eHealth Interventions in Improving Treatment Adherence for Adults With Obstructive Sleep Apnea: Meta-Analytic Review

    Abstract:

    Background: Poor adherence to continuous positive airway pressure (CPAP) treatment by adults with obstructive sleep apnea (OSA) is a common issue. Strategies delivered by means of information and communication technologies (ie, eHealth) can address treatment adherence through patient education, real-time monitoring of apnea symptoms and CPAP adherence in daily life, self-management, and early identification and subsequent intervention when device or treatment problems arise. However, the effectiveness of available eHealth technologies in improving CPAP adherence has not yet been systematically studied. Objective: This meta-analytic review was designed to investigate the effectiveness of a broad range of eHealth interventions in improving CPAP treatment adherence. Methods: We conducted a systematic literature search of the databases of Cochrane Library, PsycINFO, PubMed, and Embase to identify relevant randomized controlled trials in adult OSA populations. The risk of bias in included studies was examined using seven items of the Cochrane Collaboration risk-of-bias tool. The meta-analysis was conducted with comprehensive meta-analysis software that computed differences in mean postintervention adherence (MD), which was defined as the average number of nightly hours of CPAP use. Results: The meta-analysis ultimately included 18 studies (N=5429 adults with OSA) comprising 22 comparisons between experimental and control conditions. Postintervention data were assessed at 1 to 6 months after baseline, depending on the length of the experimental intervention. eHealth interventions increased the average nightly use of CPAP in hours as compared with care as usual (MD=0.54, 95% CI 0.29-0.79). Subgroup analyses did not reveal significant differences in effects between studies that used eHealth as an add-on or as a replacement to care as usual (P=.95), between studies that assessed stand-alone eHealth and blended strategies combining eHealth with face-to-face care (P=.23), or between studies of fully automated interventions and guided eHealth interventions (P=.83). Evidence for the long-term follow-up effectiveness of eHealth adherence interventions remains undecided owing to a scarcity of available studies and their mixed results. Conclusions: eHealth interventions for adults with OSA can improve adherence to CPAP in the initial months after the start of treatment, increasing the mean nightly duration of use by about half an hour. Uncertainty still exists regarding the timing, duration, intensity, and specific types of eHealth interventions that could be most effectively implemented by health care providers.

  • Source: ShutterStock; Copyright: Lordn; URL: https://www.shutterstock.com/image-photo/senior-woman-using-smartphone-home-after-1492696220?src=library; License: Licensed by the authors.

    Feasibility of an Electronic Health Tool to Promote Physical Activity in Primary Care: Pilot Cluster Randomized Controlled Trial

    Abstract:

    Background: Physical inactivity is associated with increased health risks. Primary care providers (PCPs) are well positioned to support increased physical activity (PA) levels through screening and provision of PA prescriptions. However, PCP counseling on PA is not common. Objective: This study aimed to assess the feasibility of implementing an electronic health (eHealth) tool to support PA counseling by PCPs and estimate intervention effectiveness on patients’ PA levels. Methods: A pragmatic pilot study was conducted using a stepped wedge cluster randomized trial design. The study was conducted at a single primary care clinic, with 4 pre-existing PCP teams. Adult patients who had a periodic health review (PHR) scheduled during the study period were invited to participate. The eHealth tool involved an electronic survey sent to participants before their PHR via an email or a tablet; data were used to automatically produce tailored resources and a PA prescription in the electronic medical record of participants in the intervention arm. Participants assigned to the control arm received usual care from their PCP. Feasibility was assessed by the proportion of completed surveys and patient-reported acceptability and fidelity measures. The primary effectiveness outcome was patient-reported PA at 4 months post-PHR, measured as metabolic equivalent of task (MET) minutes per week. Secondary outcomes assessed determinants of PA, including self-efficacy and intention to change based on the Health Action Process Approach behavior change theory. Results: A total of 1028 patients receiving care from 34 PCPs were invited to participate and 530 (51.55%) consented (intervention [n=296] and control [n=234]). Of the participants who completed a process evaluation, almost half (88/178, 49.4%) stated they received a PA prescription, with only 42 receiving the full intervention including tailored resources from their PCP. A cluster-level linear regression analysis yielded a non–statistically significant positive difference in MET-minutes reported per week at follow-up between intervention and control conditions (mean difference 1027; 95% CI −155 to 2209; P=.09). No statistically significant differences were observed for secondary outcomes. Conclusions: Our results suggest that it is feasible to build an eHealth tool that screens and provides tailored resources for PA in a primary care setting but suboptimal intervention fidelity suggests greater work must be done to address PCP barriers to resource distribution. Participant responses to the primary effectiveness outcome (MET-minutes) were highly variable, reflecting a need for more robust measures of PA in future trials to address limitations in patient-reported data. Trial Registration: ClinicalTrials.gov NCT03181295; https://clinicaltrials.gov/ct2/show/NCT03181295

  • Source: Image created by the Authors; Copyright: Emre Sezgin; URL: https://www.jmir.org/2020/2/e14202; License: Licensed by JMIR.

    Capturing At-Home Health and Care Information for Children With Medical Complexity Using Voice Interactive Technologies: Multi-Stakeholder Viewpoint

    Abstract:

    Digital health tools and technologies are transforming health care and making significant impacts on how health and care information are collected, used, and shared to achieve best outcomes. As most of the efforts are still focused on clinical settings, the wealth of health information generated outside of clinical settings is not being fully tapped. This is especially true for children with medical complexity (CMC) and their families, as they frequently spend significant hours providing hands-on medical care within the home setting and coordinating activities among multiple providers and other caregivers. In this paper, a multidisciplinary team of stakeholders discusses the value of health information generated at home, how technology can enhance care coordination, and challenges of technology adoption from a patient-centered perspective. Voice interactive technology has been identified to have the potential to transform care coordination for CMC. This paper shares opinions on the promises, limitations, recommended approaches, and challenges of adopting voice technology in health care, especially for the targeted patient population of CMC.

  • Source: Flickr; Copyright: Erik (HASH) Hersman; URL: https://www.flickr.com/photos/whiteafrican/2911951329/in/photolist-5rjvFp-sF9g6J-nev36D-QrS8nJ-68Kb6q-5PfBj3-bzmzib-y7ZPcJ-BzjXH-Xs5ia1-9av9Ro-d1XcgY-5caQS-cKsCHw-46uZse-roGzet-pr5B5s-5aKhSH-5PigdF-5riH2H-rpG3Vx-dgitYo-5w45bQ-jBZyWX-qEu1d6-68pYES-5LHZqj-7; License: Creative Commons Attribution (CC-BY).

    Use of Digital Technology to Enhance Tuberculosis Control: Scoping Review

    Abstract:

    Background: Tuberculosis (TB) is the leading cause of death from a single infectious agent, with around 1.5 million deaths reported in 2018, and is a major contributor to suffering worldwide, with an estimated 10 million new cases every year. In the context of the World Health Organization’s End TB strategy and the quest for digital innovations, there is a need to understand what is happening around the world regarding research into the use of digital technology for better TB care and control. Objective: The purpose of this scoping review was to summarize the state of research on the use of digital technology to enhance TB care and control. This study provides an overview of publications covering this subject and answers 3 main questions: (1) to what extent has the issue been addressed in the scientific literature between January 2016 and March 2019, (2) which countries have been investing in research in this field, and (3) what digital technologies were used? Methods: A Web-based search was conducted on PubMed and Web of Science. Studies that describe the use of digital technology with specific reference to keywords such as TB, digital health, eHealth, and mHealth were included. Data from selected studies were synthesized into 4 functions using narrative and graphical methods. Such digital health interventions were categorized based on 2 classifications, one by function and the other by targeted user. Results: A total of 145 relevant studies were identified out of the 1005 published between January 2016 and March 2019. Overall, 72.4% (105/145) of the research focused on patient care and 20.7% (30/145) on surveillance and monitoring. Other programmatic functions 4.8% (7/145) and electronic learning 2.1% (3/145) were less frequently studied. Most digital health technologies used for patient care included primarily diagnostic 59.4% (63/106) and treatment adherence tools 40.6% (43/106). On the basis of the second type of classification, 107 studies targeted health care providers (107/145, 73.8%), 20 studies targeted clients (20/145, 13.8%), 17 dealt with data services (17/145, 11.7%), and 1 study was on the health system or resource management. The first authors’ affiliations were mainly from 3 countries: the United States (30/145 studies, 20.7%), China (20/145 studies, 13.8%), and India (17/145 studies, 11.7%). The researchers from the United States conducted their research both domestically and abroad, whereas researchers from China and India conducted all studies domestically. Conclusions: The majority of research conducted between January 2016 and March 2019 on digital interventions for TB focused on diagnostic tools and treatment adherence technologies, such as video-observed therapy and SMS. Only a few studies addressed interventions for data services and health system or resource management.

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    Date Submitted: Feb 14, 2020

    Open Peer Review Period: Feb 14, 2020 - Apr 10, 2020

    Background: Chronic stress is increasing in prevalence and it is associated with several physical and mental disorders. Assessment of chronic stress is mostly performed by administrating questionnaire...

    Background: Chronic stress is increasing in prevalence and it is associated with several physical and mental disorders. Assessment of chronic stress is mostly performed by administrating questionnaires. Despite being convenient and valid tools, questionnaires do not inform on the detrimental effects of chronic stress on physiological functioning, which could be relevant for better characterization of stress and for tailoring stress management. Continuous measurement of vital signs in daily life and chronic stress detection algorithms could serve to this purpose. To this aim, it is paramount to model the effects of chronic stress on human physiology and include other cofounders, such as demographics, enabling to enrich population wide approach with individual variations. Objective: The main objectives of this study are to investigate the effect of chronic stress on the heart rate (HR) over time and test a possible modulation effect by gender and age in a healthy cohort. Methods: Chronic stress was assessed with the Perceived Stress Scale (PSS) inquiring on the degree to which situations in one’s life are appraised as stressful during the last month. Hourly heart rate (HR) was measured as the average HR derived from an electrocardiogram (ECG) signal, continuously measured over five days using a wearable health patch device. Models are compared including a trigonometric fit over time with four harmonics, gender, age, the PSS score and whether it was a workday or weekend-day as predictors. Results: As main effects, gender, the hour of the day and the four harmonics over time had a significant effect on the HR. Two three-way interaction effects were found. The interaction of age, whether it is a work- or weekend day and the circadian harmonic over time was significantly correlated to the HR (χ22 = 7.13, P = .028) as well as the interaction of gender, PSS score and the circadian harmonic over time (χ22 = 7.59, P = .023). Conclusions: The results of this study indicate that both baseline HR and daily fluctuations of HR are individual and time-dependent, and that although chronic stress does not relate to the average HR of an individual, it does influence the HR circadian pattern. This correlation of chronic stress with the HR over time is gender specific and possibly related to the evolution-based energy utilization strategies, as suggested in related literature studies. More research , including daily cortisol, longer recordings and wider population, should be done to confirm this interpretation. This would enable the development of more complete and personalized models of chronic stress.

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    Open Peer Review Period: Feb 14, 2020 - Feb 25, 2020

    Background: Computer-aided Diagnosis (CAD) may be an easy tool for radiologists to use on breast lesions in ultrasonography(US). Previous studies demonstrated that CAD can help to reduce the incidence...

    Background: Computer-aided Diagnosis (CAD) may be an easy tool for radiologists to use on breast lesions in ultrasonography(US). Previous studies demonstrated that CAD can help to reduce the incidence of missed diagnosis for radiologists. However, the optimal method of diagnostic planes to assess tumor has not been mentioned. Objective: To explore the diagnostic performance of CAD in quadri-planes(QP) method on detecting breast cancer. Methods: We prospectively enroll 331 consecutive patients (age, mean[SD], 43.88[12.10] years; range, 17-70 years), 512 lesions (mean[SD], 1.85[1.19], range,0.26-9.5cm; 200 with malignant and 312 with benign), with breast mass as prominent symptom. Blindly to each other, one novice radiologist and one experienced radiologist are both assigned to read US images of lesions without CAD, according to the fifth edition of the American College of Radiology Breast Imaging Reporting and Data System lexicon and final assessment categories. The results of CAD were in dichotomized form: possibly benign and possibly malignant, and final assessments are composed by radiologist and CAD. We then compare the diagnostic performance of the readers in without-CAD mode, CAD in QP method, and readers combined with CAD in QP method. Results: The area under the receiver operating characteristic curve(AUC) of CAD in QP method is 0.90, based on the Youden index(0.68), the cutoff value of positive planes are greater or equal to 2.5, we choose two positive of four planes as threshold, the AUC of QP is significantly higher than CP method (0.84 vs 0.76;P<.001]). The AUC of the novice radiologist is significantly improved from .732(without-CAD) to 0.843 (in QP; P<.001). For the experienced reader, those are mildly improved from 0.845(without-CAD) to 0.87(in QP; P=.15). The consistency between experienced reader and novice reader in QP method is good (kappa value 0.63). The sensitivity, specificity, PPV, NPV, and accuracy of CAD in QP method are 87.50%, 81.41%, 75.11%, 91.04%, and 83.79%. Combining with CAD, sensitivity and NPV of the novice reader significantly improved from 60.0% to 79.0% (P=.004), 76.81% to 86.71%( P=.07), respectively, while, specificity, PPV and accuracy are mildly improved from 84.94% to 87.82%(P =.53), 71.86% to 80.61% (P =.13), and 75.20% to 84.38% (P =.12), respectively. For the experienced reader, sensitivity also improved significantly from 76.00% to 87% (P=.045), others with mildly changed without significance, specificity 92.95% down to 87.18%(P =.16), PPV 87.36% down to 81.31%( P =.25), NPV 85.80% up to 91%(P =.27), accuracy 86.33% to 87%(P =.84). Conclusions: The QP method for CAD has a better precision, with good consistency with the experienced radiologist, which can significantly improve the diagnostic performance of the novice radiologist, having an important application value in clinical diagnosis of breast cancer on ultrasonography. Clinical Trial: ChiCTR1800019649 (http://www.chictr.org.cn)

  • Delivering Perinatal Health Information via a Voice Interactive App: A Mixed Method Study

    Date Submitted: Feb 13, 2020

    Open Peer Review Period: Feb 13, 2020 - Apr 9, 2020

    Background: Perinatal healthcare is critically important to maternal infant health outcomes. The U.S. fares considerably worse than comparable countries for maternal and infant mortality rates. As suc...

    Background: Perinatal healthcare is critically important to maternal infant health outcomes. The U.S. fares considerably worse than comparable countries for maternal and infant mortality rates. As such, alternative models of care or engagement are warranted. Ubiquitous digital devices and increased utilization of digital health tools have the potential to extend the reach to women and infants in their everyday lives and make positive impacts to their health outcomes. As voice-enabled devices become more mainstream, research is prudent to establish evidence-based practice on how to best leverage voice interaction to promote maternal infant health. Objective: Our primary aim was to assess the feasibility and usability of voice technology in perinatal health education. A secondary aim was to explore perceptions and attitudes of pregnant women towards perinatal health content delivered through voice. Methods: The study was a mixed method design. Study activities included completing baseline surveys, using a voice interactive app for two-weeks, and participating in exit interviews. Through the intervention, SMILE, users were able listen to perinatal health content delivered through mini-podcasts and provide immediate verbal feedback. Descriptive analysis was performed on quantitative survey data. Podcast feedback was analyzed using sentiment and thematic analysis. Interview data was analyzed using thematic analysis. Results: 19 pregnant women (ranging 17-36 weeks pregnant) were consented. Themes identified as important for perinatal health information include: establishing routines, expected norms and realistic expectations, and providing key takeaways. Themes identified important for voice interaction include: customization and user preferences, privacy, family and friends, and context and convenience. Qualitative analysis suggested that perinatal health promotion content delivered by voice should be accurate, succinctly delivered, and highlight key takeaways. Perinatal health interventions with voice-interaction delivery should provide users with the ability to customize the intervention, but also provide opportunities to engage family members, particularly spouses. To leverage the convenience of voice technology, solution must consider user contexts (e.g. timing or ability to listen/talk versus non-voice interaction with the system) in designing intervention activities. Conclusions: Findings from this research inform future content, design, and delivery considerations of perinatal digital health interventions and contribute to an evolving domain of digital health intervention research using voice interactive technology. Clinical Trial: n/a

  • Validating CoRe in Multiple Sclerosis: A rapid electronic cognitive assessment measure

    Date Submitted: Feb 13, 2020

    Open Peer Review Period: Feb 13, 2020 - Apr 9, 2020

    Background: Incorporating cognitive testing into clinical practice is a challenge in MS, given the wide spectrum of both cognitive and physical impairments. Shortened paper and verbal assessments pred...

    Background: Incorporating cognitive testing into clinical practice is a challenge in MS, given the wide spectrum of both cognitive and physical impairments. Shortened paper and verbal assessments predominate but still are not used routinely. Computer-based tests are becoming more widespread however changes in how a paper test is implemented can impact what exactly is being assessed in an individual. The Symbol Digit Modalities Test (SDMT) is one validated test that already has computer-based versions and forms part of the cognitive batteries used in MS. We developed a computer-based variant of this that has the potential to be deployed on multiple devices outside of the clinic environment. Objective: Develop, validate and deploy a computer-based SDMT variant, the Cognition Reaction (CoRe) test that can reliably replicate the characteristics of the paper-based SDMT. Methods: The CoRe test was validated as an alternative to the paper SDMT, with test-retest reliability, in a MS population from two NHS sites. Results: SDMT and CoRe test scores were correlated and consistent with one-month retest values. Results were normally distributed and demonstrated consistency (Pearson’s correlation coefficient r = 0.947, t = 15.60, df = 28, P < .001). Lower scores were seen in patients with higher age (P < .001) and some effect was seen with increasing disability (P < .002). There was no learning effect evident. A novel metric in CoRe was found; Question Answer Velocity could be calculated. This demonstrated a small increase in speed over the 90s duration of the test in MS and healthy controls. Conclusions: This study validates a computer-based SDMT that can be utilised in clinic with little or no technician support. It enables accurate recording of elements of cognition relevant in MS but offers additional metrics which may offer further value. Practical aspects of its implementation will enable its deployment on multiple devices.

  • Applying digital information delivery to convert habits of antibiotics use in primary care in Germany: Mixed-methods study

    Date Submitted: Feb 11, 2020

    Open Peer Review Period: Feb 11, 2020 - Apr 7, 2020

    Background: Antimicrobial resistance remains high on the global health agenda. In Germany, the national agenda supports various interventions to convert habits of antibiotics use. The CHANGE-3 study (...

    Background: Antimicrobial resistance remains high on the global health agenda. In Germany, the national agenda supports various interventions to convert habits of antibiotics use. The CHANGE-3 study (‘Converting Habits of Antibiotic Use for Respiratory Tract Infections in German Primary Care’, 2017-2020) applied digital information delivery using tablet computers in primary care practices, e-learning platforms for medical professionals and a website for the public to promote awareness and health literacy among primary care physicians, their teams and patients. Objective: Embedded in the process evaluation of the CHANGE-3 study, this present study aimed at evaluating the acceptance and uptake of digital devices for the delivery of health-related information to enhance awareness and change habits of antibiotics use in primary care in Germany. Methods: For this study, audio-recorded telephone interviews were conducted with physicians, non-physician health professionals and patients in the CHANGE-3 program. Pseudonymized verbatim transcripts were coded using thematic analysis. In-depth analysis was based on the inductive category ‘information provision via digital information tools’. Identified themes were related to main postulates of the Diffusion of Innovation Theory. In addition, data generated through a structured survey with physicians and non-physician health professionals in the program were analyzed descriptively. Results: Findings regarding acceptance and uptake of digital devices mirrored in three postulates of the Diffusion of Innovation Theory: innovation characteristics, communication channels and unanticipated consequences. Participants considered the provided digital educative solutions as supportive for promoting health literacy regarding a conversion of habits of antibiotics use. However, health care professionals also found it challenging to integrate these into existing routines in primary care and to align these with their professional values. Low technology affinity was a major barrier to the use of digital information in primary care as well. Patients welcomed the general idea of introducing health-related information in digital formats, but had concerns about device-related hygiene and their appropriateness for older patients. Conclusions: Patients and medical professionals in primary care are reluctant to use digital devices that aim to promote awareness and health literacy regarding a rational use of antibiotics. Using a Diffusion of Innovation approach can support assessment of existing barriers and provide information about setting-specific pre-conditions necessary for future tailoring of implementation strategies Clinical Trial: ISRCTN, ISRCTN15061174. Registered 13 July 2018 – Retrospectively registered http://www.isrctn.com/ISRCTN15061174

  • Smartphone remote monitoring app to follow-up colorectal cancer survivors: a requirement analysis

    Date Submitted: Feb 2, 2020

    Open Peer Review Period: Feb 10, 2020 - Apr 10, 2020

    Background: Colorectal survivors after discharge face multiple challenges and eHealth may potentially support them through providing tools such as smartphone apps. They have lots of capabilities to ex...

    Background: Colorectal survivors after discharge face multiple challenges and eHealth may potentially support them through providing tools such as smartphone apps. They have lots of capabilities to exchange information and could be used for remote monitoring of these patients. Objective: In this study, we addressed required features for apps designed to follow-up colorectal cancer patients. Methods: Features of related apps were extracted through the literature; the features were categorized and then they were modified. A questionnaire is designed containing the features listed and prioritized based on MoScoW technique and an open question for each category. The link of the questionnaire is shared among oncological surgeons and related clinical experts in the country. The answers were analyzed using CVR and the minimum feature set of a monitoring app to follow-up colorectal cancer patients were obtained. Results: The questionnaire contained ten sections evaluating nine categories of features. Eighteen experts filled the questionnaire. the minimum features of the app identified as: patient information registration, sign and symptoms monitoring, education, reminders, and patient evaluation (0.42<CVR<0.85). Features including physical activity, personalized advice, and social network did not get the minimum score (-0.11<CVR<0.39). Conclusions: The requirements set could be used for designing an app for the targeted population. Further research might address patient’s concerns on such an app also the extensibility of this features to other types of cancer.

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