Maintenance Note

On Friday, August 31, 2018 at 12:00 pm Eastern Time, JMIR will be completing a server migration to improve site stability and user experience. We expect to be back online Friday, August 31, 2018 at 5:00 pm Eastern Time. Should any problems arise our technical team will be using the weekend to resolve them, and users will be able to access our site by Sunday, September 2, 2018 at 1:00pm Eastern Time.

Who will be affected?


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:

  • Source: Pixabay; Copyright: janeb13; URL:; License: Public Domain (CC0).

    A Web-Based Acceptance-Facilitating Intervention for Identifying Patients’ Acceptance, Uptake, and Adherence of Internet- and Mobile-Based Pain...


    Background: Internet- and mobile-based interventions are effective for the treatment of chronic pain. However, little is known about patients’ willingness to engage with these types of interventions and how the uptake of such interventions can be improved. Objective: The aim of this study was to identify people’s acceptance, uptake, and adherence (primary outcomes) with regard to an internet- and mobile-based intervention for chronic pain and the influence of an information video as an acceptance-facilitating intervention (AFI). Methods: In this randomized controlled trial with a parallel design, we invited 489 individuals with chronic pain to participate in a Web-based survey assessing the acceptance of internet- and mobile-based interventions with the offer to receive an unguided internet- and mobile-based intervention for chronic pain after completion. Two versions of the Web-based survey (with and without AFI) were randomly sent to two groups: one with AFI (n=245) and one without AFI (n=244). Participants who completed the Web-based survey with or without AFI entered the intervention group or the control group, respectively. In the survey, the individuals’ acceptance of pain interventions, measured with a 4-item scale (sum score ranging from 4 to 20), predictors of acceptance, sociodemographic and pain-related variables, and physical and emotional functioning were assessed. Uptake rates (log in to the intervention) and adherence (number of completed modules) to the intervention was assessed 4 months after intervention access. To examine which factors influence acceptance, uptake rate, and adherence in the internet- and mobile-based interventions, we conducted additional exploratory subgroup analyses. Results: In total, 57 (intervention group) and 58 (control group) participants in each group completed the survey and were included in the analyses. The groups did not differ with regard to acceptance, uptake rate, or adherence (P=.64, P=.56, P=.75, respectively). Most participants reported moderate (68/115, 59.1%) to high (36/115, 31.3%) acceptance, with 9.6% (11/115) showing low acceptance (intervention group: mean 13.91, SD 3.47; control group: mean 13.61, SD 3.50). Further, 67% (38/57, intervention group) and 62% (36/58, control group) had logged into the intervention. In both groups, an average of 1.04 (SD 1.51) and 1.14 (SD 1.90) modules were completed, respectively. Conclusions: The informational video was not effective with regard to acceptance, uptake rate, or adherence. Despite the high acceptance, the uptake rate was only moderate and adherence was remarkably low. This study shows that acceptance can be much higher in a sample participating in an internet- and mobile-based intervention efficacy trial than in the target population in routine health care settings. Thus, future research should focus not only on acceptance and uptake facilitating interventions but also on ways to influence adherence. Further research should be conducted within routine health care settings with more representative samples of the target population. Trial Registration: German Clinical Trial Registration DRKS00006183; ?navigationId=trial.HTML&TRIAL_ID=DRKS00006183 (Archived by WebCite at

  • Choosing between treatment types requires a decision as well as crossroads do. Source: Pixabay; Copyright: Pixource; URL:; License: Public Domain (CC0).

    Predicting Therapy Success and Costs for Personalized Treatment Recommendations Using Baseline Characteristics: Data-Driven Analysis


    Background: Different treatment alternatives exist for psychological disorders. Both clinical and cost effectiveness of treatment are crucial aspects for policy makers, therapists, and patients and thus play major roles for healthcare decision-making. At the start of an intervention, it is often not clear which specific individuals benefit most from a particular intervention alternative or how costs will be distributed on an individual patient level. Objective: This study aimed at predicting the individual outcome and costs for patients before the start of an internet-based intervention. Based on these predictions, individualized treatment recommendations can be provided. Thus, we expand the discussion of personalized treatment recommendation. Methods: Outcomes and costs were predicted based on baseline data of 350 patients from a two-arm randomized controlled trial that compared treatment as usual and blended therapy for depressive disorders. For this purpose, we evaluated various machine learning techniques, compared the predictive accuracy of these techniques, and revealed features that contributed most to the prediction performance. We then combined these predictions and utilized an incremental cost-effectiveness ratio in order to derive individual treatment recommendations before the start of treatment. Results: Predicting clinical outcomes and costs is a challenging task that comes with high uncertainty when only utilizing baseline information. However, we were able to generate predictions that were more accurate than a predefined reference measure in the shape of mean outcome and cost values. Questionnaires that include anxiety or depression items and questions regarding the mobility of individuals and their energy levels contributed to the prediction performance. We then described how patients can be individually allocated to the most appropriate treatment type. For an incremental cost-effectiveness threshold of 25,000 €/quality-adjusted life year, we demonstrated that our recommendations would have led to slightly worse outcomes (1.98%), but with decreased cost (5.42%). Conclusions: Our results indicate that it was feasible to provide personalized treatment recommendations at baseline and thus allocate patients to the most beneficial treatment type. This could potentially lead to improved decision-making, better outcomes for individuals, and reduced health care costs.

  • A patient and the physician discussing Internet health information. Source: Pxhere; Copyright:; URL:; License: Public Domain (CC0).

    Relationship Between Internet Health Information and Patient Compliance Based on Trust: Empirical Study


    Background: The internet has become a major mean for acquiring health information; however, Web-based health information is of mixed quality and may markedly affect patients’ health-related behavior and decisions. According to the social information processing theory, patients’ trust in their physicians may potentially change due to patients’ health-information-seeking behavior. Therefore, it is important to identify the relationship between internet health information and patient compliance from the perspective of trust. Objective: The objective of our study was to investigate the effects of the quality and source of internet health information on patient compliance using an empirical study based on the social information processing theory and social exchange theory. Methods: A Web-based survey involving 336 valid participants was conducted in China. The study included independent variables (internet health information quality and source of information), 2 mediators (cognition-based trust [CBT] and affect-based trust [ABT]), 1 dependent variable (patient compliance), and 3 control variables (gender, age, and job). All variables were measured using multiple-item scales from previously validated instruments, and confirmative factor analysis as well as structural equation modeling was used to test hypotheses. Results: The questionnaire response rate was 77.16% (375/486), validity rate was 89.6% (336/375), and reliability and validity were acceptable. We found that the quality and source of internet health information affect patient compliance through the mediation of CBT and ABT. In addition, internet health information quality has a stronger influence on patient compliance than the source of information. However, CBT does not have any direct effect on patient compliance, but it directly affects ABT and then indirectly impacts patient compliance. Therefore, the effect of ABT seems stronger than that of CBT. We found an unexpected, nonsignificant relationship between the source of internet health information and ABT. Conclusions: From patients’ perspective, internet health information quality plays a stronger role than its source in impacting their trust in physicians and the consequent compliance with physicians. Therefore, patient compliance can be improved by strengthening the management of internet health information quality. The study findings also suggest that physicians should focus on obtaining health information from health websites, thereby expanding their understanding of patients’ Web-based health-information-seeking preferences, and enriching their knowledge structure to show their specialization and reliability in the communication with patients. In addition, the mutual demonstration of care and respect in the communication between physicians and patients is important in promoting patients’ ABT in their physicians.

  • Browsing ratings of a physician. Source: The Authors; Copyright: The Authors; URL:; License: Creative Commons Attribution (CC-BY).

    Developing Embedded Taxonomy and Mining Patients’ Interests From Web-Based Physician Reviews: Mixed-Methods Approach


    Background: Web-based physician reviews are invaluable gold mines that merit further investigation. Although many studies have explored the text information of physician reviews, very few have focused on developing a systematic topic taxonomy embedded in physician reviews. The first step toward mining physician reviews is to determine how the natural structure or dimensions is embedded in reviews. Therefore, it is relevant to develop the topic taxonomy rigorously and systematically. Objective: This study aims to develop a hierarchical topic taxonomy to uncover the latent structure of physician reviews and illustrate its application for mining patients’ interests based on the proposed taxonomy and algorithm. Methods: Data comprised 122,716 physician reviews, including reviews of 8501 doctors from a leading physician review website in China (, collected between 2007 and 2015. Mixed methods, including a literature review, data-driven-based topic discovery, and human annotation were used to develop the physician review topic taxonomy. Results: The identified taxonomy included 3 domains or high-level categories and 9 subtopics or low-level categories. The physician-related domain included the categories of medical ethics, medical competence, communication skills, medical advice, and prescriptions. The patient-related domain included the categories of the patient profile, symptoms, diagnosis, and pathogenesis. The system-related domain included the categories of financing and operation process. The F-measure of the proposed classification algorithm reached 0.816 on average. Symptoms (Cohen d=1.58, Δu=0.216, t=229.75, and P<.001) are more often mentioned by patients with acute diseases, whereas communication skills (Cohen d=−0.29, Δu=−0.038, t=−42.01, and P<.001), financing (Cohen d=−0.68, Δu=−0.098, t=−99.26, and P<.001), and diagnosis and pathogenesis (Cohen d=−0.55, Δu=−0.078, t=−80.09, and P<.001) are more often mentioned by patients with chronic diseases. Patients with mild diseases were more interested in medical ethics (Cohen d=0.25, Δu 0.039, t=8.33, and P<.001), operation process (Cohen d=0.57, Δu 0.060, t=18.75, and P<.001), patient profile (Cohen d=1.19, Δu 0.132, t=39.33, and P<.001), and symptoms (Cohen d=1.91, Δu=0.274, t=62.82, and P<.001). Meanwhile, patients with serious diseases were more interested in medical competence (Cohen d=−0.99, Δu=−0.165, t=−32.58, and P<.001), medical advice and prescription (Cohen d=−0.65, Δu=−0.082, t=−21.45, and P<.001), financing (Cohen d=−0.26, Δu=−0.018, t=−8.45, and P<.001), and diagnosis and pathogenesis (Cohen d=−1.55, Δu=−0.229, t=−50.93, and P<.001). Conclusions: This mixed-methods approach, integrating literature reviews, data-driven topic discovery, and human annotation, is an effective and rigorous way to develop a physician review topic taxonomy. The proposed algorithm based on Labeled-Latent Dirichlet Allocation can achieve impressive classification results for mining patients’ interests. Furthermore, the mining results reveal marked differences in patients’ interests across different disease types, socioeconomic development levels, and hospital levels.

  • Set-up of the intervention in the waiting room. Source: Image created by the Authors; Copyright: Titus Josef Brinker; URL:; License: Creative Commons Attribution (CC-BY).

    A Face-Aging App for Smoking Cessation in a Waiting Room Setting: Pilot Study in an HIV Outpatient Clinic


    Background: There is strong evidence for the effectiveness of addressing tobacco use in health care settings. However, few smokers receive cessation advice when visiting a hospital. Implementing smoking cessation technology in outpatient waiting rooms could be an effective strategy for change, with the potential to expose almost all patients visiting a health care provider without preluding physician action needed. Objective: The objective of this study was to develop an intervention for smoking cessation that would make use of the time patients spend in a waiting room by passively exposing them to a face-aging, public morphing, tablet-based app, to pilot the intervention in a waiting room of an HIV outpatient clinic, and to measure the perceptions of this intervention among smoking and nonsmoking HIV patients. Methods: We developed a kiosk version of our 3-dimensional face-aging app Smokerface, which shows the user how their face would look with or without cigarette smoking 1 to 15 years in the future. We placed a tablet with the app running on a table in the middle of the waiting room of our HIV outpatient clinic, connected to a large monitor attached to the opposite wall. A researcher noted all the patients who were using the waiting room. If a patient did not initiate app use within 30 seconds of waiting time, the researcher encouraged him or her to do so. Those using the app were asked to complete a questionnaire. Results: During a 19-day period, 464 patients visited the waiting room, of whom 187 (40.3%) tried the app and 179 (38.6%) completed the questionnaire. Of those who completed the questionnaire, 139 of 176 (79.0%) were men and 84 of 179 (46.9%) were smokers. Of the smokers, 55 of 81 (68%) said the intervention motivated them to quit (men: 45, 68%; women: 10, 67%); 41 (51%) said that it motivated them to discuss quitting with their doctor (men: 32, 49%; women: 9, 60%); and 72 (91%) perceived the intervention as fun (men: 57, 90%; women: 15, 94%). Of the nonsmokers, 92 (98%) said that it motivated them never to take up smoking (men: 72, 99%; women: 20, 95%). Among all patients, 102 (22.0%) watched another patient try the app without trying it themselves; thus, a total of 289 (62.3%) of the 464 patients were exposed to the intervention (average waiting time 21 minutes). Conclusions: A face-aging app implemented in a waiting room provides a novel opportunity to motivate patients visiting a health care provider to quit smoking, to address quitting at their subsequent appointment and thereby encourage physician-delivered smoking cessation, or not to take up smoking.

  • Source: Ciran /; Copyright: The Authors; URL:; License: Licensed by JMIR.

    Effectiveness of Serious Gaming During the Multidisciplinary Rehabilitation of Patients With Complex Chronic Pain or Fatigue: Natural Quasi-Experiment


    Background: Current evidence for the effectiveness of specialist multidisciplinary programs for burdensome chronic pain and functional somatic syndromes drives the effort to improve approaches, strategies, and delivery modes. It remains unknown to what extent and in what respect serious gaming during the regular outpatient rehabilitation can contribute to health outcomes. Objective: The objectives of our study were to determine the effect of additional serious gaming on (1) physical and emotional functioning in general; (2) particular outcome domains; and (3) patient global impressions of change, general health, and functioning and to determine (4) the dependency of serious gaming effects on adherence. Methods: We conducted a naturalistic quasi-experiment using embedded qualitative methods. The intervention group patients received an additional guided (mindfulness-based) serious gaming intervention during weeks 9-12 of a 16-week rehabilitation program at 2 sites of a Dutch rehabilitation clinic. Simultaneously, 119 control group patients followed the same program without serious gaming at 2 similar sites of the same clinic. Data consisted of 10 semistructured patient interviews and routinely collected patient self-reported outcomes. First, multivariate linear mixed modeling was used to simultaneously estimate a group effect on the outcome change between weeks 8 and 16 in 4 primary outcomes: current pain intensity, fatigue, pain catastrophizing, and psychological distress. Second, similar univariate linear mixed models were used to estimate effects on particular (unstandardized) outcomes. Third, secondary outcomes (ie, global impression of change, general health, functioning, and treatment satisfaction) were compared between the groups using independent t tests. Finally, subgroups were established according to the levels of adherence using log data. Influences of observed confounding factors were considered throughout analyses. Results: Of 329 eligible patients, 156 intervention group and 119 control group patients (N=275) with mostly chronic back pain and concomitant psychosocial problems participated in this study. Of all, 119 patients played ≥75% of the game. First, the standardized means across the 4 primary outcomes showed a significantly more favorable degree of change during the second part of the treatment for the intervention group than for the control group (beta=−0.119, SE=0.046, P=.009). Second, the intervention group showed a greater outcome change in depressive mood (b=−2.748, SE=1.072, P=.011) but not in “insufficiency” or concentration problems. Third, no significant group effects on secondary outcomes were found. Fourth, adherence was generally high and invariant. Conclusions: The findings of this study suggest a very small favorable average effect on relevant health outcomes of additional serious gaming during multidisciplinary rehabilitation. The indication that serious gaming could be a relatively time-efficient component warrants further research into if, when, how, and for which patients serious gaming could be cost-effective in treatment and why. Trial Registration: Netherlands Trial Registry NTR6020; (Archived by WebCite at

  • Source: Vaping360 (; Copyright: Vaping360; URL:; License: Creative Commons Attribution + NoDerivatives (CC-BY-ND).

    Understanding Users’ Vaping Experiences from Social Media: Initial Study Using Sentiment Opinion Summarization Techniques


    Background: E-liquid is one of the main components in electronic nicotine delivery systems (ENDS). ENDS review comments could serve as an early warning on use patterns and even function to serve as an indicator of problems or adverse events pertaining to the use of specific e-liquids—much like types of responses tracked by the Food and Drug Administration (FDA) regarding medications. Objective: This study aimed to understand users’ “vaping” experience using sentiment opinion summarization techniques, which can help characterize how consumers think about specific e-liquids and their characteristics (eg, flavor, throat hit, and vapor production). Methods: We collected e-liquid reviews on JuiceDB from June 27, 2013 to December 31, 2017 using its public application programming interface. The dataset contains 27,070 reviews for 8058 e-liquid products. Each review is accompanied by an overall rating and a set of 4 aspect ratings of an e-liquid, each on a scale of 1-5: flavor accuracy, throat hit, value, and cloud production. An iterative dichotomiser 3 (ID3)-based influential aspect analysis model was adopted to learn the key elements that impact e-liquid use. Then, fine-grained sentiment analysis was employed to mine opinions on various aspects of vaping experience related to e-liquids. Results: We found that flavor accuracy and value were the two most important aspects that affected users’ sentiments toward e-liquids. Of reviews in JuiceDB, 67.83% (18,362/27,070) were positive, while 12.67% (3430/27,070) were negative. This indicates that users generally hold positive attitudes toward e-liquids. Among the 9 flavors, fruity and sweet were the two most popular. Great and sweet tastes, reasonable value, and strong throat hit made users satisfied with fruity and sweet flavors, whereas “strange” tastes made users dislike those flavors. Meanwhile, users complained about some e-liquids’ steep or expensive prices, bad quality, and harsh throat hit. There were 2342 fruity e-liquids and 2049 sweet e-liquids. There were 55.81% (1307/2342) and 59.83% (1226/2049) positive sentiments and 13.62% (319/2342) and 12.88% (264/2049) negative sentiments toward fruity e-liquids and sweet e-liquids, respectively. Great flavors and good vapors contributed to positive reviews of fruity and sweet products. However, bad tastes such as “sour” or “bitter” resulted in negative reviews. These findings can help businesses and policy makers to further improve product quality and formulate effective policy. Conclusions: This study provides an effective mechanism for analyzing users’ ENDS vaping experience based on sentiment opinion summarization techniques. Sentiment opinions on aspect and products can be found using our method, which is of great importance to monitor e-liquid products and improve work efficiency.

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

    Information and Communication Technologies Interest, Access, and Use: Cross-Sectional Survey of a Community Sample of Urban, Predominantly Black Women


    Background: Information and communication technologies (ICT) offer the potential for delivering health care interventions to low socioeconomic populations who often face barriers in accessing health care. However, most studies on ICT for health education and interventions have been conducted in clinical settings. Objective: The aim of this study was to examine access to and use of mobile phones and computers, as well as interest in, using ICT for receipt of behavioral health information among a community sample of urban, predominately black, women with low socioeconomic status. Methods: Participants (N=220) were recruited from hair salons and social service centers and completed audio-computer assisted self-interviews. Results: The majority of the participants (212/220, 96.3%) reported use of a cell phone at least weekly, of which 89.1% (189/212) used smartphones and 62.3% (137/220) reported computer use at least weekly. Of the women included in the study, 51.9% (107/206) reported using a cell phone and 39.4% (74/188) reported using a computer to access health and/or safety information at least weekly. Approximately half of the women expressed an interest in receiving information about stress management (51%-56%) or alcohol and health (45%-46%) via ICT. Smartphone ownership was associated with younger age (odds ratio [OR] 0.92, 95% CI 0.87-0.97) and employment (OR 5.12, 95% CI 1.05-24.95). Accessing health and safety information weekly by phone was associated with younger age (OR 0.96, 95% CI 0.94-0.99) and inversely associated with higher income (OR 0.42, 95% CI 0.20-0.92). Conclusions: Our findings suggest that ICT use, particularly smartphone use, is pervasive among predominantly black women with low socioeconomic status in urban, nonclinical settings. These results show that ICT is a promising modality for delivering health information to this population. Further exploration of the acceptability, feasibility, and effectiveness of using ICT to disseminate behavioral health education and intervention is warranted.

  • Source:; Copyright: Intel Free Press; URL:; License: Creative Commons Attribution (CC-BY).

    Social Media Use in Interventions for Diabetes: Rapid Evidence-Based Review


    Background: Health authorities recommend educating diabetic patients and their families and initiating measures aimed at improving self-management, promoting a positive behavior change, and reducing the risk of complications. Social media could provide valid channel to intervene in and deliver diabetes education. However, it is not well known whether the use of these channels in such interventions can help improve the patients’ outcomes. Objective: The objective of our study was to review and describe the current existing evidence on the use of social media in interventions targeting people affected with diabetes. Methods: A search was conducted across 4 databases (PubMed, Scopus, EMBASE, and Cochrane Library).The quality of the evidence of the included primary studies was graded according to the Grading of Recommendations Assessment, Development and Evaluation criteria, and the risk of bias of systematic reviews was assessed by drawing on AMSTAR (A MeaSurement Tool to Assess systematic Reviews) guidelines. The outcomes reported by these studies were extracted and analyzed. Results: We included 20 moderate- and high-quality studies in the review: 17 primary studies and 3 systematic reviews. Of the 16 publications evaluating the effect on glycated hemoglobin (HbA1c) of the interventions using social media, 13 reported significant reductions in HbA1c values. The 5 studies that measured satisfaction with the interventions using social media found positive effects. We found mixed evidence regarding the effect of interventions using social media on health-related quality of life (2 publications found positive effects and 3 found no differences) and on diabetes knowledge or empowerment (2 studies reported improvements and 2 reported no significant changes). Conclusions: There is very little good-quality evidence on the use of social media in interventions aimed at helping people with diabetes. However, the use of these channels is mostly linked to benefits on patients’ outcomes. Public health institutions, clinicians, and other stakeholders who aim at improving the knowledge of diabetic patients could consider the use of social media in their interventions.

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

    Differences in the Effect of Internet-Based Cognitive Behavioral Therapy for Improving Nonclinical Depressive Symptoms Among Workers by Time Preference:...


    Background: Previous randomized controlled trials (RCTs) have shown a significant intervention effect of internet-based computerized cognitive behavioral therapy (iCBT) on improving nonclinical depressive symptoms among healthy workers and community residents in a primary prevention setting. Time preference is one’s relative valuation for having a reward (eg, money) at present than at a later date. Time preference may affect the effectiveness of cognitive behavioral therapy. Objective: This RCT aimed to test the difference of intervention effect of an iCBT program on improving nonclinical depressive symptoms between two subgroups classified post-hoc on the basis of time preference among workers in Japan. Methods: All workers in one corporate group (approximate n=20,000) were recruited. Participants who fulfilled the inclusion criteria were randomly allocated to either intervention or control groups. Participants in the intervention group completed 6 weekly lessons and homework assignments within the iCBT program. The Beck Depression Inventory-II (BDI-II) and Kessler’s Psychological Distress Scale (K6) measures were obtained at baseline and 3-, 6-, and 12-month follow-ups. Two subgroups were defined by the median of time preference score at baseline. Results: Only few (835/20,000, 4.2%) workers completed the baseline survey. Of the 835 participants, 706 who fulfilled the inclusion criteria were randomly allocated to the intervention or control group. Participants who selected irrational time preference options were excluded (21 and 18 participants in the intervention and control groups, respectively). A three-way interaction (group [intervention/control] × time [baseline/follow-up] × time preference [higher/lower]) effect of iCBT was significant for BDI-II (t1147.42=2.33, P=.02) and K6 (t1254.04=2.51, P=.01) at the 3-month follow-up, with a greater effect of the iCBT in the group with higher time preference. No significant three-way interaction was found at the 6- and 12-month follow-ups. Conclusions: The effects of the iCBT were greater for the group with higher time preference at the shorter follow-up, but it was leveled off later. Workers with higher time preference may change their cognition or behavior more quickly, but these changes may not persist. Trial Registration: UMIN Clinical Trials Registry UMIN000014146; recptno=R000016466 (Archived by WebCite at

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

    Internet of Things Buttons for Real-Time Notifications in Hospital Operations: Proposal for Hospital Implementation


    Background: Hospital staff frequently performs the same process hundreds to thousands of times a day. Customizable Internet of Things buttons are small, wirelessly-enabled devices that trigger specific actions with the press of an integrated button and have the potential to automate some of these repetitive tasks. In addition, IoT buttons generate logs of triggered events that can be used for future process improvements. Although Internet of Things buttons have seen some success as consumer products, little has been reported on their application in hospital systems. Objective: We discuss potential hospital applications categorized by the intended user group (patient or hospital staff). In addition, we examine key technological considerations, including network connectivity, security, and button management systems. Methods: In order to meaningfully deploy Internet of Things buttons in a hospital system, we propose an implementation framework grounded in the Plan-Do-Study-Act method. Results: We plan to deploy Internet of Things buttons within our hospital system to deliver real-time notifications in public-facing tasks such as restroom cleanliness and critical supply restocking. We expect results from this pilot in the next year. Conclusions: Overall, Internet of Things buttons have significant promise; future rigorous evaluations are needed to determine the impact of Internet of Things buttons in real-world health care settings.

  • Source:; Copyright: StockSnap; URL:; License: Public Domain (CC0).

    Using Mobile Apps to Assess and Treat Depression in Hispanic and Latino Populations: Fully Remote Randomized Clinical Trial


    Background: Most people with mental health disorders fail to receive timely access to adequate care. US Hispanic/Latino individuals are particularly underrepresented in mental health care and are historically a very difficult population to recruit into clinical trials; however, they have increasing access to mobile technology, with over 75% owning a smartphone. This technology has the potential to overcome known barriers to accessing and utilizing traditional assessment and treatment approaches. Objective: This study aimed to compare recruitment and engagement in a fully remote trial of individuals with depression who either self-identify as Hispanic/Latino or not. A secondary aim was to assess treatment outcomes in these individuals using three different self-guided mobile apps: iPST (based on evidence-based therapeutic principles from problem-solving therapy, PST), Project Evolution (EVO; a cognitive training app based on cognitive neuroscience principles), and health tips (a health information app that served as an information control). Methods: We recruited Spanish and English speaking participants through social media platforms, internet-based advertisements, and traditional fliers in select locations in each state across the United States. Assessment and self-guided treatment was conducted on each participant's smartphone or tablet. We enrolled 389 Hispanic/Latino and 637 non-Hispanic/Latino adults with mild to moderate depression as determined by Patient Health Questionnaire-9 (PHQ-9) score≥5 or related functional impairment. Participants were first asked about their preferences among the three apps and then randomized to their top two choices. Outcomes were depressive symptom severity (measured using PHQ-9) and functional impairment (assessed with Sheehan Disability Scale), collected over 3 months. Engagement in the study was assessed based on the number of times participants completed active surveys. Results: We screened 4502 participants and enrolled 1040 participants from throughout the United States over 6 months, yielding a sample of 348 active users. Long-term engagement surfaced as a key issue among Hispanic/Latino participants, who dropped from the study 2 weeks earlier than their non-Hispanic/Latino counterparts (P<.02). No significant differences were observed for treatment outcomes between those identifying as Hispanic/Latino or not. Although depressive symptoms improved (beta=–2.66, P=.006) over the treatment course, outcomes did not vary by treatment app. Conclusions: Fully remote mobile-based studies can attract a diverse participant pool including people from traditionally underserved communities in mental health care and research (here, Hispanic/Latino individuals). However, keeping participants engaged in this type of “low-touch” research study remains challenging. Hispanic/Latino populations may be less willing to use mobile apps for assessing and managing depression. Future research endeavors should use a user-centered design to determine the role of mobile apps in the assessment and treatment of depression for this population, app features they would be interested in using, and strategies for long-term engagement. Trial Registration: NCT01808976; (Archived by WebCite at

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  • Methodology used in Ecological Momentary Assessment (EMA) studies about sedentary behavior (SB) in children, adolescents and adults: a systematic review using the Checklist for Reporting EMA Studies (CREMAS)

    Date Submitted: Aug 17, 2018

    Open Peer Review Period: Aug 21, 2018 - Oct 16, 2018

    Background: The use of ecological momentary assessment (EMA) to measure sedentary behavior (SB) in children, adolescents and adults can increase understanding of the role of context of SB on health ou...

    Background: The use of ecological momentary assessment (EMA) to measure sedentary behavior (SB) in children, adolescents and adults can increase understanding of the role of context of SB on health outcomes. Objective: The aim of the present study was to systematically review the literature to describe EMA methodology used in studies on SB in youth and adults, verify how many studies adhere to the Methods aspect of the Checklist for Reporting EMA Studies (CREMAS), and detail measures used to assess SB and this associated context. Methods: A systematic literature review was conducted in the PUBMED, Scopus, Web of Science, PsycINFO, CINAHL, and SPORTDiscus databases, covering the entire period of existence of the databases until January 2018. Results: This review presented information about the characteristics and methodology used in 21 articles which utilized EMA to measure SB in youth and adults. There were more studies conducted among youth compared to adults, and studies of youth included more waves and more participants (n=696) than studies with adults (n=97). Most studies (85.7%) adhered to the Methods aspect of the CREMAS Checklist. The main criteria used to measure SB in EMA was self-report (81%) with only 19% measuring SB using objective methods (e.g., accelerometer). The main equipment to collect objective SB was the ActiGraph, and the cut-off point to define SB was <100 counts.min-1. Studies most commonly used a 15-minute window to compare EMA and accelerometer data. Conclusions: The majority of studies in this review met minimum CREMAS Checklist criteria for studies conducted with EMA. Most studies measured SB with EMA self-report (n=17; 81,0%), and a few studies also used objective methods (n=4; 19%). The standardization of the 15-minute window criteria to compare EMA and accelerometer data would lead to a comparison between these and new studies. New studies using EMA with mobile phones should be conducted as they can be considered a valid alternative for capturing information about the specific context of SB activities of young people and adults, in real time, or very close to it.

  • Evaluating information quality of revised patient education information on colonoscopy: It’s new but is it improved?

    Date Submitted: Aug 17, 2018

    Open Peer Review Period: Aug 21, 2018 - Oct 16, 2018

    Background: Previous research indicates that patients and their families have many questions about colonoscopy that are not fully answered by existing resources. We developed revised forms on colonosc...

    Background: Previous research indicates that patients and their families have many questions about colonoscopy that are not fully answered by existing resources. We developed revised forms on colonoscopy bowel preparation and on the procedure itself. Objective: Because the goal of the revised materials is to have improved information relative to currently available information, we were interested in how revised information compared to what’s currently available in terms of information quality and patient preference. Methods: In two studies, participants were asked to review one at a time the Revised and Current versions of Colonoscopy bowel preparation instructions and About Colonoscopy (order of administration was randomly counterbalanced). They were asked to rate each form along the following dimensions: amount, clarity, trustworthiness, readability/understandability, how new or familiar the information was, and reassurance. These ratings used 5-point Likert-type scales. Participants were also asked which form they preferred and four questions about why they preferred it. Results: The Study 1 and Study 2 samples were similar. Overall in Study 1, 62% preferred the Revised form, 28% preferred the Current form, and 7% were not sure. Overall in Study 2, 50.5% preferred the Revised form, 31% preferred the Current form, and 18% were not sure. Almost 75% of those in Study 1 who received the Revised form first, preferred it, compared to less than half of those who received it first in Study 2. In Study 1, 75% of those without previous colonoscopy experience preferred the Revised form, compared to more than half of those who had previously received a colonoscopy. The Study 1 regression analysis demonstrated that participants were more likely to prefer the Revised form if they had viewed it first and no previous experience with colonoscopy was also associated with higher preference for the Revised form. In Study 2, none of the six variables assessed were associated with preference for the Revised form. In comparing the two forms head-to-head, participants who preferred the Revised form in Study 1 rated it as clearer compared to those that preferred the Current form and their ratings of clarity. Finally, many participants who preferred the Revised form indicated in the open-ended questions that they liked it because it had more information than the Current form, and that it had good visuals. Conclusions: This study is one of the first to evaluate two different patient education resources in a head-to-head comparison using the same participants in a within-subjects design. This approach was useful in comparing revised educational information to resources already used in the area. Moving forward, this knowledge translation approach of a head-to-head comparison of two different information sources could be taken to develop and refine information sources on other health issues.

  • The messages presented in electronic cigarette related social media promotions and discussions: A scoping review

    Date Submitted: Aug 16, 2018

    Open Peer Review Period: Aug 20, 2018 - Oct 15, 2018

    Background: There has been a rapid rise in the popularity of electronic cigarettes (e-cigarettes) over the last decade, with growth predicted to continue. The uptake of these devices has escalated des...

    Background: There has been a rapid rise in the popularity of electronic cigarettes (e-cigarettes) over the last decade, with growth predicted to continue. The uptake of these devices has escalated despite inconclusive evidence of their efficacy as a smoking cessation device and unknown long term health consequences. As tobacco smoking rates continue to drop or plateau in many well developed countries transnational tobacco companies have transitioned into the vaping industry and are now using social media to promote their products. Evidence suggests that e-cigarettes are being marketed on social media as a harm reduction alternative with retailers and manufactures utilising marketing techniques historically used by the tobacco industry. Objective: To identify and describe the messages presented in e-cigarette related social media (Twitter, YouTube, Instagram and Pinterest) promotions and discussions, and identify future directions for research, surveillance and regulation. Methods: Data sources included Medline, Scopus, ProQuest, Informit, Journal of Medical Internet Research and Google Scholar. Studies must have been published in English between 2007 and 2017, analyse content captured from e-cigarette related social media promotions or discussions, and report results for e-cigarettes separately to other forms of tobacco and nicotine delivery. Database searching ceased October 2017. Initial searching identified 536 studies. Two reviewers screened studies by title and abstract. One reviewer examined 71 full texts to determine eligibly and identified 25 studies for inclusion. This process was undertaken with the assistance of the online screening and data extraction tool - Covidence. The review was registered with The Joanna Briggs Institute Systematic Reviews database and followed the methodology for JBI Scoping Reviews. Results: Several key messages are being used to promote e-cigarettes including as a safer alternative to cigarettes, efficacy as a smoking cessation aid, and for use where smoking is prohibited. Other major marketing efforts aimed at capturing a larger market involve promotion of innovative flavouring and highlighting the public performance of vaping. Discussion and promotion of these devices appears to be predominantly occurring among everyday people and those with vested interests such as retailers and manufacturers. There is a noticeable silence from the public health and government sector in these discussions on social media. Conclusions: The social media landscape is being dominated by pro-vaping messages disseminated by the vaping industry and vaping proponents. The uncertainty surrounding e-cigarette regulation expressed within the public health field appears not to be reflected in ongoing social media dialogues, and highlights the need for public health professionals to interact with the public to actively influence social media conversations and create a more balanced discussion. With the vaping industry changing so rapidly real time monitoring and surveillance of how these devices are discussed, promoted, and reportedly used on social media is necessary in conjunction with evidence published in academic journals.

  • Time2bHealthy – an internet-based childhood obesity prevention program for parents of preschool-aged children: outcomes of a randomized controlled trial

    Date Submitted: Aug 16, 2018

    Open Peer Review Period: Aug 20, 2018 - Oct 15, 2018

    Background: E-Health obesity programs offer benefits to traditionally-delivered programs and have shown promise in improving obesity-related behaviors in children. Objective: To assess the efficacy of...

    Background: E-Health obesity programs offer benefits to traditionally-delivered programs and have shown promise in improving obesity-related behaviors in children. Objective: To assess the efficacy of a parent-focussed internet-based healthy lifestyle program for preschool-aged children, who are overweight or at risk of becoming overweight, on child BMI, obesity-related behaviors, parent modelling and parent self-efficacy. Methods: The Time2bHealthy randomized controlled trial was conducted in the Illawarra and surrounding areas of New South Wales and Melbourne, Victoria, Australia during 2016-2017. Participants were recruited both online and through more traditional means. Parent/carer and child (aged 2-5 years) dyads were randomized into an intervention or comparison group. Intervention participants received an 11-week internet-based healthy lifestyle program, which was underpinned by Social Cognitive Theory, followed by fortnightly emails for 3-months thereafter. Intervention participants were encouraged to access and contribute to a closed (secret) Facebook group to communicate with other participants and a dietitian. Comparison participants received email communication only. Child BMI was the primary outcome, which was objectively measured. Secondary outcomes included objectively-measured physical activity, parent- and objectively-measured sleep habits, and parent-reported dietary intake, screen-time, child feeding, parent modelling and parent self-efficacy. All data were collected at face-to-face appointments at baseline, 3- and 6-months by blinded data collectors. Randomization was conducted using a computerized random number generator post-baseline data collection. Results: Eighty-six dyads were recruited, with 42 randomized to the intervention group and 44 to the comparison group. 78 dyads attended the 3- and 6-month follow-ups, with 7 lost to follow-up and one withdrawing. Mean child age was 3.46 years and 91% were in the healthy weight range. Sixty-nine percent of participants completed at least 5 of the 6 modules. Intention-to-treat analyses found no significant outcomes for change in BMI between groups. Compared to children in the comparison group, those in the intervention group reduced frequency of discretionary food intake (estimate -0.360, 95% CI -2.272 to -0.447, P=0.00), and parents showed improvement in child feeding pressure to eat practices (-0.304, 95% CI 0.061 to -0.003, P=0.048) and nutrition self-efficacy (0.429, 95% CI 0.096 to 0.763, P=0.01). No significant time by group interaction was found for other outcomes. Conclusions: The trial demonstrated that a parent-focussed eHealth childhood obesity prevention program can provide support to improve dietary-related practices and self-efficacy but was not successful in reducing BMI. The target sample size was not achieved, which would have affected statistical power. Clinical Trial: Australian and New Zealand Clinical Trials Registry (12616000119493).

  • How is my Child’s Asthma?”: Digital Phenotype and Actionable Insights for Pediatric Asthma

    Date Submitted: Aug 20, 2018

    Open Peer Review Period: Aug 20, 2018 - Aug 29, 2018

    Background: Asthma is a multifactorial chronic disease that severely affects a child’s daily activity and quality of life. Pediatric asthma causes reduced playtime, disturbed sleep, and missed schoo...

    Background: Asthma is a multifactorial chronic disease that severely affects a child’s daily activity and quality of life. Pediatric asthma causes reduced playtime, disturbed sleep, and missed school days -- impacting a child’s long-term academic and physical growth. In this paper, we discuss the use of the kHealth system for continuous and comprehensive monitoring of child’s symptoms, activity, sleep pattern, environmental triggers, and compliance. The kHealth system helps in deriving actionable insights to help manage asthma both at personal and at the cohort level. Specifically, the two of scores introduced here are also the basis of ongoing work on addressing personalized asthma care, and to answer questions such as: how can I help my child better adhere to care instructions and reduce future exacerbation? Objective: In traditional asthma management protocol, a child meets with a clinician infrequently, say once in 3 to 6 months. The child provides information about his/her recent asthma condition by answering a set of questions to assess asthma control which may include the validated Asthma Control Test questionnaire. The elicited information may be inadequate for precise diagnosis of the cause for the timely determination of asthma control and compliance and for assessing the effectiveness of the treatment plan. The continuous monitoring and improved tracking of child’s symptoms, activities, sleep, treatment adherence, and the environmental conditions allow more precise determination of asthma triggers, and reliable assessment of medication compliance and its effectiveness. Methods: The kHealth system comprises of kHealth kit, kHealth cloud, and kHealth dashboard. Digital Phenotype Score and Controller Compliance Score are defined to summarize the child’s condition from the data collected using the kHealth kit to provide better actionable insights. Digital Phenotype Score formalizes the asthma control level using data about symptoms, rescue medication usage, activity level, and sleep pattern. The Compliance Score captures how well the child is complying with the treatment protocol. We monitored and analyzed data for 95 children, each recruited for a 1 or 3-month long study. Results: At cohort level, we found 36.6% of the children’s asthma was Very Poorly Controlled, 25.6% was Not Well Controlled, and 37.8% was Well Controlled. Among the Very Poorly Controlled children (n=30), we found 30% were Highly Compliant towards their controller medication intake suggesting their re-evaluation for change in medication/dosage, while 50% were Poorly Compliant and candidates for more timely intervention to improve compliance to mitigate their situation. Conclusions: We observed that a patient’s Digital Phenotype Score and Controller Compliance Score computed based on continuous digital monitoring provides clinician a more timely and detailed evidence of patient’s asthma-related condition compared to the Asthma Control Test scores taken infrequently during clinic visits.

  • Profiles of health information seeking and the current digital divide within a California population-based sample

    Date Submitted: Aug 14, 2018

    Open Peer Review Period: Aug 19, 2018 - Oct 14, 2018

    Background: Internet use for health information is important given the rise of eHealth integrating technology into healthcare. Despite perceived widespread use of the Internet, a persistent “digital...

    Background: Internet use for health information is important given the rise of eHealth integrating technology into healthcare. Despite perceived widespread use of the Internet, a persistent “digital divide” exists in which many individuals have ready access to the Internet and others do not. To date, most published reports have compared characteristics of Internet users seeking health information vs. non-users. However, there is little understanding of the differences between Internet users seeking health information online and users who do not. Understanding these differences could enable targeted outreach for health interventions and promotion of eHealth technologies. Objective: This study aims to assess population-level characteristics associated with types of Internet use, particularly for seeking online health information. Methods: The 2015-2016 California Health Interview Survey (CHIS) datasets were used for this study. Internet use was classified as: those who have never used the Internet (Never use), those who have ever used the Internet but not to search for health information in the last 12-months (Use not for health), and those who have ever used the Internet and have used it to search for health information in the last 12-months (Use for health). Weighted multinomial logistic regression was used to assess sociodemographic and health characteristics associated with types of Internet use. Findings are reported as odds ratios (OR) with 95% confidence intervals (CI). Results: Among 42,087 participants (weighted sample of 29,236,426), 19% reported Never Use of the Internet, 27.9% reported Use not for health, and 53.1% reported Use for health. Compared to Never Use, Use for health individuals were more likely to be younger (OR: 0.1 [CI: 0.1, 0.2] for ≥60 years vs <60 years), female (OR: 1.6 [CI: 1.3, 1.9] compared to males), non-Hispanic White (OR: 0.54 [CI: 0.4, 0.7] and OR: 0.2 [CI: 0.2, 0.4] for Latinos and African Americans, respectively), and have a higher socioeconomic status (400%+ Federal Poverty Guidelines OR: 1.3 [CI: 1.4, 2.4]). Overall, characteristics for the Use not for health and Use for health groups were similar, except for those with lower levels of education and respondents not having visited a physician in the last year. For these two characteristics Use not for health were more similar to Never Use. Conclusions: Findings indicate that a digital divide characterized by sociodemographic and health information exists across three types of users. Results reflect previous studies about the divide specifically with regards to disparities in use and access related to age, race/ ethnicity, and socioeconomic status. Disparities in health seeking online may reflect existing disparities in healthcare access extending into a new era of health technology. Findings support the need for interventions to target Internet access and health literacy among Never Use and Use not for health groups.