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Journal Description

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

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

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

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


Recent Articles:

  • A blended cognitive behavioral therapy (CBT) session. Source: Image created by the Authors; Copyright: The Authors; URL:; License: Licensed by JMIR.

    Web-Based Cognitive Behavioral Therapy Blended With Face-to-Face Sessions for Major Depression: Randomized Controlled Trial


    Background: Meta-analyses of several randomized controlled trials have shown that cognitive behavioral therapy (CBT) has comparable efficacy to antidepressant medication, but therapist availability and cost-effectiveness is a problem. Objective: This study aimed to evaluate the effectiveness of Web-based CBT blended with face-to-face sessions that reduce therapist time in patients with major depression who were unresponsive to antidepressant medications. Methods: A 12-week, assessor-masked, parallel-group, waiting- list controlled, randomized trial was conducted at 3 medical institutions in Tokyo. Outpatients aged 20-65 years with a primary diagnosis of major depression who were taking ≥1 antidepressant medications at an adequate dose for ≥6 weeks and had a 17-item GRID-Hamilton Depression Rating Scale (HAMD) score of ≥14 were randomly assigned (1:1) to blended CBT or waiting-list groups using a computer allocation system, stratified by the study site with the minimization method, to balance age and baseline GRID-HAMD score. The CBT intervention was given in a combined format, comprising a Web-based program and 12 45-minute face-to-face sessions. Thus, across 12 weeks, a participant could receive up to 540 minutes of contact with a therapist, which is approximately two-thirds of the therapist contact time provided in the conventional CBT protocol, which typically provides 16 50-minute sessions. The primary outcome was the alleviation of depressive symptoms, as measured by a change in the total GRID-HAMD score from baseline (at randomization) to posttreatment (at 12 weeks). Moreover, in an exploratory analysis, we investigated whether the expected positive effects of the intervention were sustained during follow-up, 3 months after the posttreatment assessment. Analyses were performed on an intention-to-treat basis, and the primary outcome was analyzed using a mixed-effects model for repeated measures. Results: We randomized 40 participants to either blended CBT (n=20) or waiting-list (n=20) groups. All patients completed the 12-week treatment protocol and were included in the intention-to-treat analyses. Participants in the blended CBT group had significantly alleviated depressive symptoms at week 12, as shown by greater least squares mean changes in the GRID-HAMD score, than those in the waiting list group (−8.9 points vs −3.0 points; mean between-group difference=−5.95; 95% CI −9.53 to −2.37; P<.001). The follow-up effects within the blended CBT group, as measured by the GRID-HAMD score, were sustained at the 3-month follow-up (week 24) and posttreatment (week 12): posttreatment, 9.4 (SD 5.2), versus follow-up, 7.2 (SD 5.7); P=.009. Conclusions: Although our findings warrant confirmation in larger and longer term studies with active controls, these suggest that a combined form of CBT is effective in reducing depressive symptoms in patients with major depression who are unresponsive to antidepressant medications. Trial Registration: University Hospital Medical Information Network Clinical Trials Registry: UMIN000009242; (Archived by WebCite at http://www.webcitation. org/729VkpyYL)

  • Robotic services for older adults. Source: Image created by the Authors; Copyright: Filippo Cavallo; URL:; License: Creative Commons Attribution (CC-BY).

    Robotic Services Acceptance in Smart Environments With Older Adults: User Satisfaction and Acceptability Study


    Background: In Europe, the population of older people is increasing rapidly. Many older people prefer to remain in their homes but living alone could be a risk for their safety. In this context, robotics and other emerging technologies are increasingly proposed as potential solutions to this societal concern. However, one-third of all assistive technologies are abandoned within one year of use because the end users do not accept them. Objective: The aim of this study is to investigate the acceptance of the Robot-Era system, which provides robotic services to permit older people to remain in their homes. Methods: Six robotic services were tested by 35 older users. The experiments were conducted in three different environments: private home, condominium, and outdoor sites. The appearance questionnaire was developed to collect the users’ first impressions about the Robot-Era system, whereas the acceptance was evaluated through a questionnaire developed ad hoc for Robot-Era. Results: A total of 45 older users were recruited. The people were grouped in two samples of 35 participants, according to their availability. Participants had a positive impression of Robot-Era robots, as reflected by the mean score of 73.04 (SD 11.80) for DORO’s (domestic robot) appearance, 76.85 (SD 12.01) for CORO (condominium robot), and 75.93 (SD 11.67) for ORO (outdoor robot). Men gave ORO’s appearance an overall score higher than women (P=.02). Moreover, participants younger than 75 years understood more readily the functionalities of Robot-Era robots compared to older people (P=.007 for DORO, P=.001 for CORO, and P=.046 for ORO). For the ad hoc questionnaire, the mean overall score was higher than 80 out of 100 points for all Robot-Era services. Older persons with a high educational level gave Robot-Era services a higher score than those with a low level of education (shopping: P=.04; garbage: P=.047; reminding: P=.04; indoor walking support: P=.006; outdoor walking support: P=.03). A higher score was given by male older adults for shopping (P=.02), indoor walking support (P=.02), and outdoor walking support (P=.03). Conclusions: Based on the feedback given by the end users, the Robot-Era system has the potential to be developed as a socially acceptable and believable provider of robotic services to facilitate older people to live independently in their homes.

  • Source: Flickr; Copyright: mista stagga lee; URL:; License: Creative Commons Attribution (CC-BY).

    Improving Prediction of Risk of Hospital Admission in Chronic Obstructive Pulmonary Disease: Application of Machine Learning to Telemonitoring Data


    Background: Telemonitoring of symptoms and physiological signs has been suggested as a means of early detection of chronic obstructive pulmonary disease (COPD) exacerbations, with a view to instituting timely treatment. However, algorithms to identify exacerbations result in frequent false-positive results and increased workload. Machine learning, when applied to predictive modelling, can determine patterns of risk factors useful for improving prediction quality. Objective: Our objectives were to (1) establish whether machine learning techniques applied to telemonitoring datasets improve prediction of hospital admissions and decisions to start corticosteroids, and (2) determine whether the addition of weather data further improves such predictions. Methods: We used daily symptoms, physiological measures, and medication data, with baseline demography, COPD severity, quality of life, and hospital admissions from a pilot and large randomized controlled trial of telemonitoring in COPD. We linked weather data from the United Kingdom meteorological service. We used feature selection and extraction techniques for time series to construct up to 153 predictive patterns (features) from symptom, medication, and physiological measurements. We used the resulting variables to construct predictive models fitted to training sets of patients and compared them with common symptom-counting algorithms. Results: We had a mean 363 days of telemonitoring data from 135 patients. The two most practical traditional score-counting algorithms, restricted to cases with complete data, resulted in area under the receiver operating characteristic curve (AUC) estimates of 0.60 (95% CI 0.51-0.69) and 0.58 (95% CI 0.50-0.67) for predicting admissions based on a single day’s readings. However, in a real-world scenario allowing for missing data, with greater numbers of patient daily data and hospitalizations (N=57,150, N+=55, respectively), the performance of all the traditional algorithms fell, including those based on 2 days’ data. One of the most frequently used algorithms performed no better than chance. All considered machine learning models demonstrated significant improvements; the best machine learning algorithm based on 57,150 episodes resulted in an aggregated AUC of 0.74 (95% CI 0.67-0.80). Adding weather data measurements did not improve the predictive performance of the best model (AUC 0.74, 95% CI 0.69-0.79). To achieve an 80% true-positive rate (sensitivity), the traditional algorithms were associated with an 80% false-positive rate: our algorithm halved this rate to approximately 40% (specificity approximately 60%). The machine learning algorithm was moderately superior to the best symptom-counting algorithm (AUC 0.77, 95% CI 0.74-0.79 vs AUC 0.66, 95% CI 0.63-0.68) at predicting the need for corticosteroids. Conclusions: Early detection and management of COPD remains an important goal given its huge personal and economic costs. Machine learning approaches, which can be tailored to an individual’s baseline profile and can learn from experience of the individual patient, are superior to existing predictive algorithms and show promise in achieving this goal. Trial Registration: International Standard Randomized Controlled Trial Number ISRCTN96634935; (Archived by WebCite at

  • My UmcUtrecht patient portal (montage). Source: UMC Utrecht; Copyright: UMC Utrecht; URL:; License: Licensed by JMIR.

    Use and the Users of a Patient Portal: Cross-Sectional Study


    Background: Patient portals offer patients access to their medical information and tools to communicate with health care providers. It has been shown that patient portals have the potential to positively impact health outcomes and efficiency of health care. It is therefore important that health care organizations identify the patients who use or do not use the patient portal and explore the reasons in either case. The Unified Theory of Acceptance and Use of Technology (UTAUT) is a frequently used theory for explaining the use of information technology. It consists of the following constructs: performance expectancy, effort expectancy, social influence, facilitating conditions, and behavioral intention to use. Objective: This study aimed to explore the prevalence of patient portal use and the characteristics of patients who use or do not use a patient portal. The main constructs of UTAUT, together with demographics and disease- and care-related characteristics, have been measured to explore the predictive factors of portal use. Methods: A cross-sectional study was conducted in the outpatient departments for adult patients of a university hospital in the Netherlands. Following outcomes were included: self-reported portal use, characteristics of users such as demographics, disease- and care-related data, eHealth literacy (modified score), and scores of UTAUT constructs. Descriptive analyses and univariate and multivariate logistic regression were also conducted. Results: In the analysis, 439 adult patients were included. Furthermore, 32.1% (141/439) identified as being a user of the patient portal; 31.2% (137/439) indicated as nonusers, but being aware of the existence of the portal; and 36.6% (161/439) as being nonusers not aware of the existence of the portal. In the entire study population, the factors of being chronically ill (odds ratio, OR 1.62, 95% CI 1.04-2.52) and eHealth literacy (modified score; OR 1.12, 95% CI 1.07-1.18) best predicted portal use. In users and nonusers who were aware of the portal, UTAUT constructs were added to the multivariate logistic regression, with chronically ill and modified eHealth literacy sum score. Effort expectancy (OR 13.02, 95% CI 5.68-29.87) and performance expectancy (OR 2.84, 95% CI 1.65-4.90) are shown to significantly influence portal use in this group. Conclusions: Approximately one-third of the patients of a university hospital self-reported using the patient portal; most expressed satisfaction. At first sight, being chronically ill and higher scores on the modified eHealth literacy scale explained portal use. Adding UTAUT constructs to the model revealed that effort expectancy (ease of use and knowledge and skills related to portal use) and performance expectancy (perceived usefulness) influenced portal use. Interventions to improve awareness of the portal and eHealth literacy skills of patients and further integration of the patient portal in usual face-to-face care are needed to increase use and potential subsequent patient benefits.

  • Source: Immunization Action Coalition; Copyright: Centers for Disease Control and Prevention; URL:; License: Public Domain (CC0).

    Discordance Between Human Papillomavirus Twitter Images and Disparities in Human Papillomavirus Risk and Disease in the United States: Mixed-Methods Analysis


    Background: Racial and ethnic minorities are disproportionately affected by human papillomavirus (HPV)-related cancer, many of which could have been prevented with vaccination. Yet, the initiation and completion rates of HPV vaccination remain low among these populations. Given the importance of social media platforms for health communication, we examined US-based HPV images on Twitter. We explored inconsistencies between the demographics represented in HPV images and the populations that experience the greatest burden of HPV-related disease. Objective: The objective of our study was to observe whether HPV images on Twitter reflect the actual burden of disease by select demographics and determine to what extent Twitter accounts utilized images that reflect the burden of disease in their health communication messages. Methods: We identified 456 image tweets about HPV that contained faces posted by US users between November 11, 2014 and August 8, 2016. We identified images containing at least one human face and utilized Face++ software to automatically extract the gender, age, and race of each face. We manually annotated the source accounts of these tweets into 3 types as follows: government (38/298, 12.8%), organizations (161/298, 54.0%), and individual (99/298, 33.2%) and topics (news, health, and other) to examine how images varied by message source. Results: Findings reflected the racial demographics of the US population but not the disease burden (795/1219, 65.22% white faces; 140/1219, 11.48% black faces; 71/1219, 5.82% Asian faces; and 213/1219, 17.47% racially ambiguous faces). Gender disparities were evident in the image faces; 71.70% (874/1219) represented female faces, whereas only 27.89% (340/1219) represented male faces. Among the 11-26 years age group recommended to receive HPV vaccine, HPV images contained more female-only faces (214/616, 34.3%) than males (37/616, 6.0%); the remainder of images included both male and female faces (365/616, 59.3%). Gender and racial disparities were present across different image sources. Faces from government sources were more likely to depict females (n=44) compared with males (n=16). Of male faces, 80% (12/15) of youth and 100% (1/1) of adults were white. News organization sources depicted high proportions of white faces (28/38, 97% of female youth and 12/12, 100% of adult males). Face++ identified fewer faces compared with manual annotation because of limitations with detecting multiple, small, or blurry faces. Nonetheless, Face++ achieved a high degree of accuracy with respect to gender, race, and age compared with manual annotation. Conclusions: This study reveals critical differences between the demographics reflected in HPV images and the actual burden of disease. Racial minorities are less likely to appear in HPV images despite higher rates of HPV incidence. Health communication efforts need to represent populations at risk better if we seek to reduce disparities in HPV infection.

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

    Using Partially-Observed Facebook Networks to Develop a Peer-Based HIV Prevention Intervention: Case Study


    Background: This is a case study from an HIV prevention project among young black men who have sex with men. Individual-level prevention interventions have had limited success among young black men who have sex with men, a population that is disproportionately affected by HIV; peer network–based interventions are a promising alternative. Facebook is an attractive digital platform because it enables broad characterization of social networks. There are, however, several challenges in using Facebook data for peer interventions, including the large size of Facebook networks, difficulty in assessing appropriate methods to identify candidate peer change agents, boundary specification issues, and partial observation of social network data. Objective: This study aimed to explore methodological challenges in using social Facebook networks to design peer network–based interventions for HIV prevention and present techniques to overcome these challenges. Methods: Our sample included 298 uConnect study respondents who answered a bio-behavioral survey in person and whose Facebook friend lists were downloaded (2013-2014). The study participants had over 180,000 total Facebook friends who were not involved in the study (nonrespondents). We did not observe friendships between these nonrespondents. Given the large number of nonrespondents whose networks were partially observed, a relational boundary was specified to select nonrespondents who were well connected to the study respondents and who may be more likely to influence the health behaviors of young black men who have sex with men. A stochastic model-based imputation technique, derived from the exponential random graph models, was applied to simulate 100 networks where unobserved friendships between nonrespondents were imputed. To identify peer change agents, the eigenvector centrality and keyplayer positive algorithms were used; both algorithms are suitable for identifying individuals in key network positions for information diffusion. For both algorithms, we assessed the sensitivity of identified peer change agents to the imputation model, the stability of identified peer change agents across the imputed networks, and the effect of the boundary specification on the identification of peer change agents. Results: All respondents and 78.9% (183/232) of nonrespondents selected as peer change agents by eigenvector on the imputed networks were also selected as peer change agents on the observed networks. For keyplayer, the agreement was much lower; 42.7% (47/110) and 35.3% (110/312) of respondent and nonrespondent peer change agents, respectively, selected on the imputed networks were also selected on the observed network. Eigenvector also produced a stable set of peer change agents across the 100 imputed networks and was much less sensitive to the specified relational boundary. Conclusions: Although we do not have a gold standard indicating which algorithm produces the most optimal set of peer change agents, the lower sensitivity of eigenvector centrality to key assumptions leads us to conclude that it may be preferable. The methods we employed to address the challenges in using Facebook networks may prove timely, given the rapidly increasing interest in using online social networks to improve population health.

  • Source: Royal Air Force Lakenheath (Erin O’Shea); Copyright: US Air Force; URL:; License: Public Domain (CC0).

    Automatic Extraction of Mental Health Disorders From Domestic Violence Police Narratives: Text Mining Study


    Background: Vast numbers of domestic violence (DV) incidents are attended by the New South Wales Police Force each year in New South Wales and recorded as both structured quantitative data and unstructured free text in the WebCOPS (Web-based interface for the Computerised Operational Policing System) database regarding the details of the incident, the victim, and person of interest (POI). Although the structured data are used for reporting purposes, the free text remains untapped for DV reporting and surveillance purposes. Objective: In this paper, we explore whether text mining can automatically identify mental health disorders from this unstructured text. Methods: We used a training set of 200 DV recorded events to design a knowledge-driven approach based on lexical patterns in text suggesting mental health disorders for POIs and victims. Results: The precision returned from an evaluation set of 100 DV events was 97.5% and 87.1% for mental health disorders related to POIs and victims, respectively. After applying our approach to a large-scale corpus of almost a half million DV events, we identified 77,995 events (15.83%) that mentioned mental health disorders, with 76.96% (60,032/77,995) of those linked to POIs versus 16.47% (12,852/77,995) for the victims and 6.55% (5111/77,995) for both. Depression was the most common mental health disorder mentioned in both victims (22.30%, 3258) and POIs (18.73%, 8918), followed by alcohol abuse for POIs (12.24%, 5829) and various anxiety disorders (eg, panic disorder, generalized anxiety disorder) for victims (11.43%, 1671). Conclusions: The results suggest that text mining can automatically extract targeted information from police-recorded DV events to support further public health research into the nexus between mental health disorders and DV.

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

    Reach of Messages in a Dental Twitter Network: Cohort Study Examining User Popularity, Communication Pattern, and Network Structure


    Background: Increasing the reach of messages disseminated through Twitter promotes the success of Twitter-based health education campaigns. Objective: This study aimed to identify factors associated with reach in a dental Twitter network (1) initially and (2) sustainably at individual and network levels. Methods: We used instructors’ and students’ Twitter usernames from a Saudi dental school in 2016-2017 and applied Gephi (a social network analysis tool) and social media analytics to calculate user and network metrics. Content analysis was performed to identify users disseminating oral health information. The study outcomes were reach at baseline and sustainably over 1.5 years. The explanatory variables were indicators of popularity (number of followers, likes, tweets retweeted by others), communication pattern (number of tweets, retweets, replies, tweeting/ retweeting oral health information or not). Multiple logistic regression models were used to investigate associations. Results: Among dental users, 31.8% had reach at baseline and 62.9% at the end of the study, reaching a total of 749,923 and dropping to 37,169 users at the end. At an individual level, reach was associated with the number of followers (baseline: odds ratio, OR=1.003, 95% CI=1.001-1.005 and sustainability: OR=1.002, 95% CI=1.0001-1.003), likes (baseline: OR=1.001, 95% CI=1.0001-1.002 and sustainability: OR=1.0031, 95% CI=1.0003-1.002), and replies (baseline: OR=1.02, 95% CI=1.005-1.04 and sustainability: OR=1.02, 95% CI=1.004-1.03). At the network level, users with the least followers, tweets, retweets, and replies had the greatest reach. Conclusions: Reach was reduced by time. Factors increasing reach at the user level had different impact at the network level. More than one strategy is needed to maximize reach.

  • Source: Flickr / Adobe Stock; Copyright: JMIR Publications; URL:; License: Licensed by JMIR.

    Audio-/Videorecording Clinic Visits for Patient’s Personal Use in the United States: Cross-Sectional Survey


    Background: Few clinics in the United States routinely offer patients audio or video recordings of their clinic visits. While interest in this practice has increased, to date, there are no data on the prevalence of recording clinic visits in the United States. Objective: Our objectives were to (1) determine the prevalence of audiorecording clinic visits for patients’ personal use in the United States, (2) assess the attitudes of clinicians and public toward recording, and (3) identify whether policies exist to guide recording practices in 49 of the largest health systems in the United States. Methods: We administered 2 parallel cross-sectional surveys in July 2017 to the internet panels of US-based clinicians (SERMO Panel) and the US public (Qualtrics Panel). To ensure a diverse range of perspectives, we set quotas to capture clinicians from 8 specialties. Quotas were also applied to the public survey based on US census data (gender, race, ethnicity, and language other than English spoken at home) to approximate the US adult population. We contacted 49 of the largest health systems (by clinician number) in the United States by email and telephone to determine the existence, or absence, of policies to guide audiorecordings of clinic visits for patients’ personal use. Multiple logistic regression models were used to determine factors associated with recording. Results: In total, 456 clinicians and 524 public respondents completed the surveys. More than one-quarter of clinicians (129/456, 28.3%) reported that they had recorded a clinic visit for patients’ personal use, while 18.7% (98/524) of the public reported doing so, including 2.7% (14/524) who recorded visits without the clinician’s permission. Amongst clinicians who had not recorded a clinic visit, 49.5% (162/327) would be willing to do so in the future, while 66.0% (346/524) of the public would be willing to record in the future. Clinician specialty was associated with prior recording: specifically oncology (odds ratio [OR] 5.1, 95% CI 1.9-14.9; P=.002) and physical rehabilitation (OR 3.9, 95% CI 1.4-11.6; P=.01). Public respondents who were male (OR 2.11, 95% CI 1.26-3.61; P=.005), younger (OR 0.73 for a 10-year increase in age, 95% CI 0.60-0.89; P=.002), or spoke a language other than English at home (OR 1.99; 95% CI 1.09-3.59; P=.02) were more likely to have recorded a clinic visit. None of the large health systems we contacted reported a dedicated policy; however, 2 of the 49 health systems did report an existing policy that would cover the recording of clinic visits for patient use. The perceived benefits of recording included improved patient understanding and recall. Privacy and medicolegal concerns were raised. Conclusions: Policy guidance from health systems and further examination of the impact of recordings—positive or negative—on care delivery, clinician-related outcomes, and patients’ behavioral and health-related outcomes is urgently required.

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

    Mindfulness-Based Resilience Training in the Workplace: Pilot Study of the Internet-Based Resilience@Work (RAW) Mindfulness Program


    Background: The impact of mental illness on society is far reaching and has been identified as the leading cause of sickness absence and work disability in most developed countries. By developing evidence-based solutions that are practical, affordable, and accessible, there is potential to deliver substantial economic benefits while improving the lives of individual workers. Academic and industry groups are now responding to this public health issue. A key focus is on developing practical solutions that enhance the mental health and psychological resilience of workers. A growing body of research suggests resilience training may play a pivotal role in the realm of public health and prevention, particularly with regards to protecting the long-term well-being of workers. Objective: Our aim is to examine whether a mindfulness-based resilience-training program delivered via the internet is feasible and engaging to a group of high-risk workers. Additionally, we aim to measure the effect of the Resilience@Work Resilience@Work Mindfulness program on measures of resilience and related skills. Methods: The current pilot study recruited 29 full-time firefighters. Participants were enrolled in the 6-session internet-based resilience-training program and were administered questionnaires prior to training and directly after the program ended. Measurements examined program feasibility, psychological resilience, experiential avoidance, and thought entanglement. Results: Participants reported greater levels of resilience after Resilience@Work training compared to baseline, with a mean increase in their overall resilience score of 1.5 (95% CI -0.25 to 3.18, t14=1.84, P=.09). Compared to baseline, participants also reported lower levels of psychological inflexibility and experiential avoidance following training, with a mean decrease of -1.8 (95% CI -3.78 to 0.20, t13=-1.94, P=.07). With regards to cognitive fusion (thought entanglement), paired-samples t tests revealed a trend towards reduction in mean scores post training (P=.12). Conclusions: This pilot study of the Resilience@Work program suggests that a mindfulness-based resilience program delivered via the Internet is feasible in a high-risk workplace setting. In addition, the firefighters using the program showed a trend toward increased resilience and psychological flexibility. Despite a number of limitations, the results of this pilot study provide some valuable insights into what form of resilience training may be viable in occupational settings particularly among those considered high risk, such as emergency workers. To the best of our knowledge, this is the first time a mindfulness-based resilience-training program delivered wholly via the internet has been tested in the workplace.

  • Young person using the Mental Health eClinic. Source: The Authors; Copyright: The Authors; URL:; License: Creative Commons Attribution (CC-BY).

    Using New and Innovative Technologies to Assess Clinical Stage in Early Intervention Youth Mental Health Services: Evaluation Study


    Background: Globally there is increasing recognition that new strategies are required to reduce disability due to common mental health problems. As 75% of mental health and substance use disorders emerge during the teenage or early adulthood years, these strategies need to be readily accessible to young people. When considering how to provide such services at scale, new and innovative technologies show promise in augmenting traditional clinic-based services. Objective: The aim of this study was to test new and innovative technologies to assess clinical stage in early intervention youth mental health services using a prototypic online system known as the Mental Health eClinic (MHeC). Methods: The online assessment within the MHeC was compared directly against traditional clinician assessment within 2 Sydney-based youth-specific mental health services (headspace Camperdown and headspace Campbelltown). A total of 204 young people were recruited to the study. Eligible participants completed both face-to-face and online assessments, which were randomly allocated and counterbalanced at a 1-to-3 ratio. These assessments were (1) a traditional 45- to 60-minute headspace face-to-face assessment performed by a Youth Access Clinician and (2) an approximate 60-minute online assessment (including a self-report Web-based survey, immediate dashboard of results, and a video visit with a clinician). All assessments were completed within a 2-week timeframe from initial presentation. Results: Of the 72 participants who completed the study, 71% (51/72) were female and the mean age was 20.4 years (aged 16 to 25 years); 68% (49/72) of participants were recruited from headspace Camperdown and the remaining 32% (23/72) from headspace Campbelltown. Interrater agreement of participants’ stage, as determined after face-to-face assessment or online assessment, demonstrated fair agreement (kappa=.39, P<.001) with concordance in 68% of cases (49/72). Among the discordant cases, those who were allocated to a higher stage by online raters were more likely to report a past history of mental health disorders (P=.001), previous suicide planning (P=.002), and current cannabis misuse (P=.03) compared to those allocated to a lower stage. Conclusions: The MHeC presents a new and innovative method for determining key clinical service parameters. It has the potential to be adapted to varied settings in which young people are connected with traditional clinical services and assist in providing the right care at the right time.

  • Source: Flickr (Bob Nichols); Copyright: US Department of Agriculture; URL:; License: Creative Commons Attribution (CC-BY).

    Clinical Decision Support Systems for Drug Allergy Checking: Systematic Review


    Background: Worldwide, the burden of allergies—in particular, drug allergies—is growing. In the process of prescribing, dispensing, or administering a drug, a medication error may occur and can have adverse consequences; for example, a drug may be given to a patient with a documented allergy to that particular drug. Computerized physician order entry (CPOE) systems with built-in clinical decision support systems (CDSS) have the potential to prevent such medication errors and adverse events. Objective: The aim of this review is to provide a comprehensive overview regarding all aspects of CDSS for drug allergy, including documenting, coding, rule bases, alerts and alert fatigue, and outcome evaluation. Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed as much as possible and searches were conducted in 5 databases using CPOE, CDSS, alerts, and allergic or allergy as keywords. Bias could not be evaluated according to PRISMA guidelines due to the heterogeneity of study types included in the review. Results: Of the 3160 articles considered, 60 met the inclusion criteria. A further 9 articles were added based on expert opinion, resulting in a total of 69 articles. An interrater agreement of 90.9% with a reliability Κ=.787 (95% CI 0.686-0.888) was reached. Large heterogeneity across study objectives, study designs, study populations, and reported results was found. Several key findings were identified. Evidence of the usefulness of clinical decision support for drug allergies has been documented. Nevertheless, there are some important problems associated with their use. Accurate and structured documenting of information on drug allergies in electronic health records (EHRs) is difficult, as it is often not clear to healthcare providers how and where to document drug allergies. Besides the underreporting of drug allergies, outdated or inaccurate drug allergy information in EHRs poses an important problem. Research on the use of coding terminologies for documenting drug allergies is sparse. There is no generally accepted standard terminology for structured documentation of allergy information. The final key finding is the consistently reported low specificity of drug allergy alerts. Current systems have high alert override rates of up to 90%, leading to alert fatigue. Important challenges remain for increasing the specificity of drug allergy alerts. We found only one study specifically reporting outcomes related to CDSS for drug allergies. It showed that adverse drug events resulting from overridden drug allergy alerts do not occur frequently. Conclusions: Accurate and comprehensive recording of drug allergies is required for good use of CDSS for drug allergy screening. We found considerable variation in the way drug allergy are recorded in EHRs. It remains difficult to reduce drug allergy alert overload while maintaining patient safety as the highest priority. Future research should focus on improving alert specificity, thereby reducing override rates and alert fatigue. Also, the effect on patient outcomes and cost-effectiveness should be evaluated.

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  • The Use of Social Networking Sites in Mental Health Interventions for Young People: A Systematic Review

    Date Submitted: Sep 19, 2018

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

    Background: The onset of mental health problems peaks between adolescence and young adulthood, however young people face barriers to treatment and are often reluctant to seek professional help. Many a...

    Background: The onset of mental health problems peaks between adolescence and young adulthood, however young people face barriers to treatment and are often reluctant to seek professional help. Many are instead seeking support and information regarding their mental health online, especially via social networking sites (SNSs), so there is a promising opportunity to use SNSs to deliver or integrate with youth-focused online mental health interventions. Previous reviews have evaluated the effectiveness of SNSs for specific disorders in young people, however none to date have covered the breadth of SNS-based youth mental health interventions available across all mental health issues. Objective: The aim of this review was to systematically identify available evidence regarding the use of SNS-based interventions to support the mental health of young people, in order to evaluate their effectiveness, suitability and safety, and identify gaps and opportunities for future research. Methods: The PubMed and PsycInfo databases were searched using Medical Subject Headings (MeSH) terms and exploded keywords and phrases. Retrieved abstracts (n=974) were double screened, yielding 235 articles for screening at the full-text level. Of these, nine articles met the review inclusion criteria. Given the small number of studies, their exploratory nature and the variety of outcome measures used, a quantitative meta-analysis was not possible. Results: The nine articles (quantitative studies, qualitative studies and descriptions of the iterative design process) covered five separate interventions. Two interventions used purpose-built platforms based on the Moderated Online Social Therapy (MOST) model, two used Facebook, and one evaluated a purpose-built mobile app. The two MOST interventions targeted specific mental health issues (depression and psychosis), while the others focused on improving mental health literacy, social support and general wellbeing. Only three quantitative studies were identified, and all used a pre-post design (without a control group) to establish ‘proof of concept’. Of the outcome variables assessed, there were significant improvements in mental health knowledge and number of depressive symptoms, but no improvement in anxiety or psychosis symptoms. Acceptability of and engagement with the SNS platforms was generally high, as were perceptions of usefulness and safety, with no adverse incidents reported. Moderation by clinical experts was identified as a key component of the more successful interventions. When offered a choice, users showed a preference for mobile apps over web-based interfaces. Conclusions: The evidence reviewed suggests young people find SNS-based interventions highly usable, engaging and supportive. However, future studies need to address the current lack of high-quality evidence for their efficacy in reducing mental health symptoms. Given that young people are already turning to SNSs to engage in knowledge-seeking and peer-to-peer support, SNS-based youth mental health interventions provide an opportunity to address some of the barriers young people face in accessing qualified mental health support and information.

  • Correlation study of ADHD clinical features: Toward data fusion of EEG and activity sensors

    Date Submitted: Sep 14, 2018

    Open Peer Review Period: Sep 20, 2018 - Nov 15, 2018

    Background: Attention deficit hyperactivity disorder is a neurobehavioral disease that makes children who suffer from it display behaviors of inattention, hyperactivity or impulsivity, thus affecting...

    Background: Attention deficit hyperactivity disorder is a neurobehavioral disease that makes children who suffer from it display behaviors of inattention, hyperactivity or impulsivity, thus affecting their ability to learn and establish proper family and social relationships. Various tools are currently used by child and adolescent psychiatric clinics to diagnose, evaluate, and collect information and data that then allows professional physicians to assess if patients need further treatment, following a thorough and careful clinical diagnosis process. Objective: The scientific advancements in the domain of brainwaves, e.g. electroencephalography, have been perfecting, both portable and wearable equipment have gradually been developed with the hope of determining relevant indicators of brainwave parameters in ADHD children. Methods: The sample size consists of a total of 63 subjects, 40 males and 9 females in the experimental group; while 5 males and 9 females in the control group. The brainwave sensor and wristwatch sensor were used in the experimental process, which was divided into three stages: pre_test, in_test, and post_test, with a testing interval of 20 minutes each. We use t-test and correlation analysis to investigate indicators of the disorder children. Results: The results show the disorder is significant negative correlation with brainwaves (p<0.05), the higher the concentration of brainwave activity, the less likely that the disorder is present; while, it is significant positive correlation with the activity amounts (p<0.01), the higher the amount of activity, the greater the probability that the patient will have the disorder. Two groups achieved significant differences in the independent t-test (p<0.05), indicating that the amount of activity detected by the wristwatch sensor is capable of identifying the disorder. Finally, the amount of mean activity only in in_test stage is significant differences from pre_test and post_test stages. Conclusions: The results show that when the subjects are stimulated under restricted conditions, the disorder subjects will present with different amount of activity over the unrestricted condition due to patients’ inability to exercise control over their own concentration. Further studies are required in the future to determine whether the wristwatch sensor can be used to detect the amount of activity and help physicians diagnose the disorder in order to develop more objective, rapid auxiliary diagnostic tools.

  • My Whiplash Navigator, an interactive website for whiplash: Process evaluation of design and implementation

    Date Submitted: Sep 16, 2018

    Open Peer Review Period: Sep 20, 2018 - Nov 15, 2018

    Background: Whiplash is a world-wide health and economic burden. Contributing to this burden is poor guideline adherence and lack of identifying and addressing modifiable risk factors. Online tools th...

    Background: Whiplash is a world-wide health and economic burden. Contributing to this burden is poor guideline adherence and lack of identifying and addressing modifiable risk factors. Online tools that facilitate clinical pathways of care are a novel solution to improve management. Objective: To develop, implement and evaluate an online tool to support whiplash management following a robust framework. Methods: We followed the first three processes of a research translation framework including idea generation, feasibility and efficacy. Development of the website involved stakeholder consultations to discuss content, design, features and functionality. Implementation strategies included classroom education, educational meetings, educational outreach, reminders and direct phone contact. Surveys and focus group discussions were conducted amongst primary and specialist health care professionals (HCPs) and people with whiplash to assess feasibility. Outcomes evaluated were; website metrics, acceptability and self-rated improvements in knowledge amongst HCPs and website logs of treatment decisions (e.g. shared-care, specialist care, referred care) made by specialist HCPs. Results: The development process delivered an interactive, user-friendly and acceptable website, My Whiplash Navigator, tailored to the needs of people with whiplash and HCPs. The content and features of the website were identified following consultative meetings between researchers and industry partners and further informed by results of surveys and focus group discussions amongst people with whiplash and HCPs. 320 registrations were recorded from June 2016-March 2018, including 260 HCPs (175 student, 65 primary, 20 specialist HCPs) and 60 people with whiplash. Most effective implementation strategies were classroom teaching for students (81% uptake) and educational meetings for primary HCPs (43% uptake). Popular pages visited were those containing information about advice and exercises and risk assessment. All HCPs agreed that their knowledge regarding risk management (81.4%) and providing appropriate exercises (87.6%) improved. Specialists’ most common decision was ‘shared care’, improving their management decisions from a previous cohort. Areas to improve were navigation and access to outcome measures. Conclusions: A robust development process resulted in an innovative, interactive, user-friendly website, the “My Whiplash Navigator”. Implementation with HCPs was best achieved through classroom education and educational meetings. Evaluation of the website showed improved knowledge and practice to be more consistent with a risk-based clinical care pathway for whiplash. The positive results provide sufficient evidence to scale implementation nationally and involving other target markets.

  • Do millions of prayers increase one’s longevity? A cohort study of the impact of intercessory prayers on the mortality of Roman Catholic bishops

    Date Submitted: Sep 14, 2018

    Open Peer Review Period: Sep 19, 2018 - Nov 14, 2018

    Background: There have been mixed results of the studies checking whether prayers do actually extend the life duration of the people prayed for. Most studies on the topic included a small number of pr...

    Background: There have been mixed results of the studies checking whether prayers do actually extend the life duration of the people prayed for. Most studies on the topic included a small number of prayers and most of them focused on people already struggling with a medical condition. Intercessory prayer’s influence on health is of scholarly interest, yet it is unclear if its effect may be dependent on the number of prayers for a named individual received per annum. Objective: We sought to examine if there is a noticeable increased longevity effect of intercessory prayer for a named individual’s well-being, if he receives a very high number of prayers per annum for an extended period. Methods: We retrieved and conducted a statistical analysis of the data about the length of life for 857 Roman Catholic bishops, 500 Catholic priests, and 3038 male academics from the US, France, Italy, Poland, Brazil, and Mexico. We obtained information for these individuals who died between 1988 and 2018 from Wikidata, and conducted an observational cohort study. Bishops were chosen for the study, as they receive millions of individual prayers for well being, according to conservative estimates. Results: There was a main effect for occupation F(2, 4391) = 4.07, p = .017, ηp 2 = .002, with pairwise comparisons indicating significant differences between the mean life duration of bishops (M=30489) and of priests (M=29894), but none between the academic teachers (M=30147) and either of the other groups. A comparison analysis between bishops from the largest and the smallest dioceses showed no significant difference t(67.31)=1.61, p = .11. Our main outcome measure is covariance of the mean length of life in each of the categories: bishops, priests, academic teachers, controlled for nationality. Conclusions: The first analysis proved that bishops live longer than priests, but due to a marginal effect size this result should be treated with caution. No difference was found between the mean length of life of bishops from the largest and the smallest dioceses. We found no difference between bishops and male academics. These results show that the impact of intercessory prayers on longevity is not observable.

  • Assessing the Acceptability and Perceived Accuracy of Tailored Feedback and Computerized Adaptive Testing in Quality of Life Assessment

    Date Submitted: Sep 14, 2018

    Open Peer Review Period: Sep 19, 2018 - Nov 14, 2018

    Background: Quality of life (QoL) assessments, or patient-reported outcome measures (PROMs), are becoming increasingly important and can improve decision making, satisfaction, and outcomes of care. S...

    Background: Quality of life (QoL) assessments, or patient-reported outcome measures (PROMs), are becoming increasingly important and can improve decision making, satisfaction, and outcomes of care. Some physicians and patients find questionnaires too burdensome, which could be reduced by using computerized adaptive testing. Furthermore, questionnaire user experience might increase by making a questionnaire more interesting, for example by providing graphical and contextualized feedback. However, little is known about how shorter assessments and feedback impact user experience. Objective: We conducted a controlled experiment to assess the impact of tailored multimodal feedback and computerized adaptive testing on user experience in QoL assessment using validated PROMs. Methods: We recruited a representative sample from the general population in the United Kingdom using the Oxford Prolific academic web panel. Participants completed either a computer adaptive testing version of the World Health Organization Quality of Life assessment (WHOQOL-CAT) or the fixed-length WHOQOL-BREF. We randomly assigned participants to conditions in which they would receive either no feedback, graphical feedback only, or graphical and adaptive text feedback. Participants rated the assessment in terms of perceived acceptability, engagement, clarity, and accuracy. Results: We included 1386 participants in our analysis. Assessment experience was improved when graphical and tailored text feedback was provided together alongside PROMs (p<0.001, Δ=0.22). Providing graphical feedback alone was not associated with improvement in overall experience (p=0.006, Δ=0.10). Graphical and text feedback made the questionnaire more interesting and users were more likely to share the results with a physician or family member (p<0.001, Δ=0.17, and p<0.001, Δ=0.17, respectively). No difference was found in perceived accuracy of the graphical feedback scores of the WHOQOL-CAT and WHOQOL-BREF (p=0.05, Δ = 0.06). Computerized adaptive testing resulted in a 25% item reduction (SE<0.45) compared to the fixed-length assessment but did not result in an increased user experience (p=0.21). Conclusions: Using tailored text feedback to contextualize numeric scores maximized the acceptability of electronic QoL assessment. Improving user experience may increase response rates and reduce attrition in research and clinical use of PROMs. In this study, CAT administration was associated with a modest decrease in assessment length but did not improve user experience. Patient perceived accuracy of feedback was equivalent when comparing CAT with fixed-length assessment. Further research is warranted to explore the relationship between assessment length, feedback, and response burden in diverse populations.

  • A retrospective observational study of post-vaccination fever response in children collected via the mobile application Fever Coach

    Date Submitted: Sep 15, 2018

    Open Peer Review Period: Sep 19, 2018 - Nov 14, 2018

    Background: Post-vaccination fever (PVF) is a mild adverse event that is naturally reversible without complications, but is highly prevalent and, in some cases, accompanied by febrile convulsions. The...

    Background: Post-vaccination fever (PVF) is a mild adverse event that is naturally reversible without complications, but is highly prevalent and, in some cases, accompanied by febrile convulsions. These adverse effects may cause parents to delay or abandon vaccinating their children. Objective: The aim of this paper was to identify PVF patterns and the ability of antipyretics to affect changes in these patterns. Methods: We used the data collected by the parents of the feverish children in the mobile application named Fever Coach to identify the PVF patterns according to the vaccinations and the use of antipyretic drugs. We selected single vaccination records that contained 5 or more body temperature readings performed within 48 hours of vaccination and analyzed PVF onset, offset, duration, and maximum temperature. By observing PVF response to vaccination, we identified effects of antipyretic drugs on PVF onset, offset, and duration times; the extent of fever; and rate of decline. We also performed the logistic regression test to determine demographic variables (age, weight, and gender) to produce relatively high fevers (≥39 ° C). Results: The highest body temperature at which infants and young children received antipyretic drugs was 38 ° C (9.8% of the total data). The number of instances where this temperature threshold was reached was more than four times greater than the number reaching 37.9 ° C. Analyses showed no significant difference in onset time between antipyretic and non-antipyretic cases, but offset time and duration time were significantly shorter in non-antipyretic cases (P < .001). In non-antipyretic cases, offset times and duration times were, on average, 9.9 hours and 10.1 hours shorter, respectively than antipyretic cases. Body temperatures also decreased faster in non-antipyretic cases. Besides, we found that fevers associated with the influenza vaccine lasted relatively long, while fevers associated with the pneumococcus vaccine were relatively short-lived. Conclusions: These findings suggest that PVF has its own fever pattern that is dependent upon vaccine type and presence of antipyretic drugs, and post-vaccination temperature monitoring may ease fever phobia and reduce unnecessary use of antipyretics and medical care.