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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 2018: 4.945, ranked #1 out of 26 journals in the medical informatics category) and in terms of size (number of papers published). The journal focuses on emerging technologies, medical devices, apps, engineering, and informatics applications for patient education, prevention, population health and clinical care. As a leading high-impact journal in its disciplines (health informatics and health services research), it is selective, but it is now complemented by almost 30 specialty JMIR sister journals, which have a broader scope. Peer-review reports are portable across JMIR journals and papers can be transferred, so authors save time by not having to resubmit a paper to different journals. 

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

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

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


Recent Articles:

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

    The Service of Research Analytics to Optimize Digital Health Evidence Generation: Multilevel Case Study


    Background: The widespread adoption of digital health interventions for chronic disease self-management has catalyzed a paradigm shift in the selection of methodologies used to evidence them. Recently, the application of digital health research analytics has emerged as an efficient approach to evaluate these data-rich interventions. However, there is a growing mismatch between the promising evidence base emerging from analytics mediated trials and the complexity of introducing these novel research methods into evaluative practice. Objective: This study aimed to generate transferable insights into the process of implementing research analytics to evaluate digital health interventions. We sought to answer the following two research questions: (1) how should the service of research analytics be designed to optimize digital health evidence generation? and (2) what are the challenges and opportunities to scale, spread, and sustain this service in evaluative practice? Methods: We conducted a qualitative multilevel embedded single case study of implementing research analytics in evaluative practice that comprised a review of the policy and regulatory climate in Ontario (macro level), a field study of introducing a digital health analytics platform into evaluative practice (meso level), and interviews with digital health innovators on their perceptions of analytics and evaluation (microlevel). Results: The practice of research analytics is an efficient and effective means of supporting digital health evidence generation. The introduction of a research analytics platform to evaluate effective engagement with digital health interventions into a busy research lab was ultimately accepted by research staff, became routinized in their evaluative practice, and optimized their existing mechanisms of log data analysis and interpretation. The capacity for research analytics to optimize digital health evaluations is highest when there is (1) a collaborative working relationship between research client and analytics service provider, (2) a data-driven research agenda, (3) a robust data infrastructure with clear documentation of analytic tags, (4) in-house software development expertise, and (5) a collective tolerance for methodological change. Conclusions: Scientific methods and practices that can facilitate the agile trials needed to iterate and improve digital health interventions warrant continued implementation. The service of research analytics may help to accelerate the pace of digital health evidence generation and build a data-rich research infrastructure that enables continuous learning and evaluation.

  • Source: iStock by Getty Images; Copyright: utah778; URL:; License: Licensed by the authors.

    Effects of Three Antecedents of Patient Compliance for Users of Peer-to-Peer Online Health Communities: Cross-Sectional Study


    Background: Over the past 50 years, patient noncompliance has appeared as a major public health concern and focus of a great deal of research because it endangers patient recovery and imposes a considerable financial burden on health care systems. Meanwhile, online health communities (OHCs) are becoming more common and are commonly used by individuals with health problems, and they may have a role in facilitating compliance. Despite this growing popularity, little is known about patient compliance predictors for OHCs’ users. Objective: This study aimed to investigate the extent to which participating in OHCs may trigger higher levels of compliance. It identified 3 interrelated predictors that may affect patient compliance: patient empowerment gained through peer-to-peer OHCs, satisfaction with the physician, and commitment to the physician. Methods: A Web-based survey tested the conceptual model and assessed the effects of patient empowerment gained through OHCs on patient satisfaction and commitment to the physician, as well as the effects of these 3 predictors on patient compliance with the proposed treatment. Members of peer-to-peer OHCs were asked to answer an online questionnaire. A convenience sample of 420 patients experiencing chronic illness and using peer-to-peer OHCs was surveyed in August 2018 in Québec, Canada. A path analysis using structural equation modeling tested the proposed relationships between the predictors and their respective paths on patient compliance. The mediation effects of these predictor variables on patient compliance were estimated with the PROCESS macro in SPSS. Results: The findings indicated that patient empowerment gained through OHCs was positively related to patient commitment to the physician (beta=.69; P<.001) and patient compliance with the proposed treatment (beta=.35; P<.001). Patient commitment also positively influenced patient compliance (beta=.74; P<.001). Patient empowerment did not exert a significant influence on patient satisfaction with the physician (beta=.02; P=.76), and satisfaction did not affect compliance (beta=−.07; P=.05); however, patient satisfaction was positively related to patient commitment to the physician (beta=.14; P<.01). The impact of empowerment on compliance was partially mediated by commitment to the physician (beta=.32; 95% CI 0.22-0.44) but not by satisfaction. Conclusions: This study highlights the importance of peer-to-peer OHCs for two main reasons. The primary reason is that patient empowerment gained through peer-to-peer OHCs both directly and indirectly enhances patient compliance with the proposed treatment. The underlying mechanisms of these effects were shown. Second, commitment to the physician was found to play a more critical role than satisfaction with the physician in determining patient-physician relationship quality. Overall, our findings support the assumption that health care stakeholders should encourage the use of peer-to-peer OHCs to favor patient empowerment and patient commitment to the physician to increase patient compliance with the proposed treatment.

  • Source: Image created by the Authors; Copyright: Just Eekhof; URL:; License: Creative Commons Attribution + NoDerivatives (CC-BY-ND).

    Patients’ Use of the Internet to Find Reliable Medical Information About Minor Ailments: Vignette-Based Experimental Study


    Background: Little is known about the exact process of how patients search for medical information on the internet and what they retrieve. There is especially a paucity of literature on browsing for information on minor ailments, a term used for harmless diseases that are very common in the general population and thus have a significant impact on health care. Objective: This vignette-based experimental study aimed to explore what kind of Web-based search strategies are applied and how search strategies, demographic characteristics, and the quality of the visited websites relate to finding the right diagnosis. Additional goals were to describe how searching on the Web influences one’s perception of the severity of the potential diagnosis and whether or not the participants would discuss the information they found on the internet with their doctors. Methods: Out of 1372 survey participants, 355 were randomly sampled, and 155 of them were recruited and assigned to one of four clinical scenarios. Each search term they used was classified as one of three search strategies: (1) hypothesis testing, (2) narrowing within the general hypothesis area, and (3) symptom exploration. The quality of the websites used was determined by using the DISCERN instrument. To compare the diagnostic accuracy of the participants before and after the internet search, a McNemar test was used. Chi-square tests were used to describe which factors are related to the chosen search strategy. A multivariate binary logistic regression model was constructed to predict which factors are related to finding a sound diagnosis after searching the internet for health information. Results: Most participants (65.8%, 102/155) used the symptom exploration strategy. However, this depends on the assigned scenario (P<.001) and the self-estimated severity score of the symptoms before the internet search (P=.001). A significant relation was found between choosing an accurate diagnosis and age (odds ratio [OR] 0.94, 95% CI 0.90 to 0.98) and the clinical scenario, as well as the use of high-quality websites (OR 7.49, 95% CI 1.85 to 30.26). Browsing the internet did not lead to a statistically significant change in participants’ beliefs about the severity of the condition (McNemar test, P=.85). Most participants (65%) shared their retrieved information with their physician and most of them (75%) received a positive response. Conclusions: Our findings suggest that most patients use a symptom-based approach; however, if patients expect the potential diagnosis to be severe, they tend to use a hypothesis verification strategy more often and are therefore prone to certain forms of bias. In addition, self-diagnosing accuracy is related to younger age, the symptom scenario, and the use of high-quality websites. We should find ways to guide patients toward search strategies and websites that may more likely lead to accurate decision making.

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

    A Revised Model of Trust in Internet-Based Health Information and Advice: Cross-Sectional Questionnaire Study


    Background: The internet continues to offer new forms of support for health decision making. Government, charity, and commercial websites increasingly offer a platform for shared personal health experiences, and these are just some of the opportunities that have arisen in a largely unregulated arena. Understanding how people trust and act on this information has always been an important issue and remains so, particularly as the design practices of health websites continue to evolve and raise further concerns regarding their trustworthiness. Objective: The aim of this study was to identify the key factors influencing US and UK citizens’ trust and intention to act on advice found on health websites and to understand the role of patient experiences. Methods: A total of 1123 users took part in an online survey (625 from the United States and 498 from the United Kingdom). They were asked to recall their previous visit to a health website. The online survey consisted of an updated general Web trust questionnaire to account for personal experiences plus questions assessing key factors associated with trust in health websites (information corroboration and coping perception) and intention to act. We performed principal component analysis (PCA), then explored the relationship between the factor structure and outcomes by testing the fit to the sampled data using structural equation modeling (SEM). We also explored the model fit across US and UK populations. Results: PCA of the general Web trust questionnaire revealed 4 trust factors: (1) personal experiences, (2) credibility and impartiality, (3) privacy, and (4) familiarity. In the final SEM model, trust was found to have a significant direct effect on intention to act (beta=.59; P<.001), and of the trust factors, only credibility and impartiality had a significant direct effect on trust (beta=.79; P<.001). The impact of personal experiences on trust was mediated through information corroboration (beta=.06; P=.04). Variables specific to electronic health (eHealth; information corroboration and coping) were found to substantially improve the model fit, and differences in information corroboration were found between US and UK samples. The final model accounting for all factors achieved a good fit (goodness-of-fit index [0.95], adjusted goodness-of-fit index [0.93], root mean square error of approximation [0.50], and comparative fit index [0.98]) and explained 65% of the variance in trust and 41% of the variance in intention to act. Conclusions: Credibility and impartiality continue to be key predictors of trust in eHealth websites. Websites with patient experiences can positively influence trust but only if users first corroborate the information through other sources. The need for corroboration was weaker in the United Kingdom, where website familiarity reduced the need to check information elsewhere. These findings are discussed in relation to existing trust models, patient experiences, and health literacy.

  • Source: Pixabay; Copyright: Jan Alexander; URL:; License: Licensed by the authors.

    Unlocking the Power of Artificial Intelligence and Big Data in Medicine

    Authors List:


    unstructured: Data-driven science and its corollaries in machine learning and the wider field of artificial intelligence have the potential to drive important changes in medicine. However, medicine is not a science like any other: It is deeply and tightly bound, with a large and wide network of legal, ethical, regulatory, economical, and societal dependencies. As a consequence, the scientific and technological progresses in handling information and its further processing and cross-linking for decision support and predictive systems must be accompanied by parallel changes in the global environment, with numerous stakeholders, including citizen and society. What can be seen at the first glance as a barrier and mechanism slowing down the progression of data science must, however, be considered an important asset. Only global adoption can transform the potential of big data and artificial intelligence into an effective breakthroughs in handling health and medicine. This requires science and society, scientists and citizens, to progress together.

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

    The Last Mile: Where Artificial Intelligence Meets Reality

    Authors List:


    Although much effort is focused on improving the technical performance of artificial intelligence, there are compelling reasons to focus more on the implementation of this technology class to solve real-world applications. In this “last mile” of implementation lie many complex challenges that may make technically high-performing systems perform poorly. Instead of viewing artificial intelligence development as a linear one of algorithm development through to eventual deployment, there are strong reasons to take a more agile approach, iteratively developing and testing artificial intelligence within the context in which it finally will be used.

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

    Validation of an Independent Web-Based Tool for Measuring Visual Acuity and Refractive Error (the Manifest versus Online Refractive Evaluation Trial):...


    Background: Digital tools provide a unique opportunity to increase access to eye care. We developed a Web-based test that measures visual acuity and both spherical and cylindrical refractive errors. This test is Conformité Européenne marked and available on the Easee website. The purpose of this study was to compare the efficacy of this Web-based tool with traditional subjective manifest refraction in a prospective open-label noninferiority clinical trial. Objective: The aim of this study was to evaluate the outcome of a Web-based refraction compared with a manifest refraction (golden standard). Methods: Healthy volunteers from 18 to 40 years of age, with a refraction error between –6 and +4 diopter (D), were eligible. Each participant performed the Web-based test, and the reference test was performed by an optometrist. An absolute difference in refractive error of <0.5 D was considered noninferior. Reliability was assessed by using an intraclass correlation coefficient (ICC). Both uncorrected and corrected visual acuity were measured. Results: A total of 200 eyes in 100 healthy volunteers were examined. The Web-based assessment of refractive error had excellent correlation with the reference test (ICC=0.92) and was considered noninferior to the reference test. Uncorrected visual acuity was similar with the Web-based test and the reference test (P=.21). Visual acuity was significantly improved using the prescription obtained by using the Web-based tool (P<.01). The Web-based test provided the best results in participants with mild myopia (ie, <3 D), with a mean difference of 0.02 (SD 0.49) D (P=.48) and yielding a corrected visual acuity of >1.0 in 90% (n=77) of participants. Conclusions: Our results indicate that Web-based eye testing is a valid and safe method for measuring visual acuity and refractive error in healthy eyes, particularly for mild myopia. This tool can be used for screening purposes, and it is an easily accessible alternative to the subjective manifest refraction test. Clinical Trial: NCT03313921;

  • Sleeping pills lying on night table and woman trying to sleep. Source: Shutterstock; Copyright:; URL:; License: Licensed by the authors.

    Adverse Events Due to Insomnia Drugs Reported in a Regulatory Database and Online Patient Reviews: Comparative Study


    Background: Patient online drug reviews are a resource for other patients seeking information about the practical benefits and drawbacks of drug therapies. Patient reviews may also serve as a source of postmarketing safety data that are more user-friendly than regulatory databases. However, the reliability of online reviews has been questioned, because they do not undergo professional review and lack means of verification. Objective: We evaluated online reviews of hypnotic medications, because they are commonly used and their therapeutic efficacy is particularly amenable to patient self-evaluation. Our primary objective was to compare the types and frequencies of adverse events reported to the Food and Drug Administration Adverse Event Reporting System (FAERS) with analogous information in patient reviews on the consumer health website The secondary objectives were to describe patient reports of efficacy and adverse events and assess the influence of medication cost, effectiveness, and adverse events on user ratings of hypnotic medications. Methods: Patient ratings and narratives were retrieved from 1407 reviews on between February 2007 and March 2018 for eszopiclone, ramelteon, suvorexant, zaleplon, and zolpidem. Reviews were coded to preferred terms in the Medical Dictionary for Regulatory Activities. These reviews were compared to 5916 cases in the FAERS database from January 2015 to September 2017. Results: Similar adverse events were reported to both and FAERS. Both resources identified a lack of efficacy as a common complaint for all five drugs. Both resources revealed that amnesia commonly occurs with eszopiclone, zaleplon, and zolpidem, while nightmares commonly occur with suvorexant. Compared to FAERS, online reviews of zolpidem reported a much higher frequency of amnesia and partial sleep activities. User ratings were highest for zolpidem and lowest for suvorexant. Statistical analyses showed that patient ratings are influenced by considerations of efficacy and adverse events, while drug cost is unimportant. Conclusions: For hypnotic medications, online patient reviews and FAERS emphasized similar adverse events. Online reviewers rated drugs based on perception of efficacy and adverse events. We conclude that online patient reviews of hypnotics are a valid source that can supplement traditional adverse event reporting systems.

  • Personalized Conversational Agents. Source: The Authors / Stocksnap; Copyright: The Authors / Lukas; URL:; License: Creative Commons Attribution (CC-BY).

    The Personalization of Conversational Agents in Health Care: Systematic Review


    Background: The personalization of conversational agents with natural language user interfaces is seeing increasing use in health care applications, shaping the content, structure, or purpose of the dialogue between humans and conversational agents. Objective: The goal of this systematic review was to understand the ways in which personalization has been used with conversational agents in health care and characterize the methods of its implementation. Methods: We searched on PubMed, Embase, CINAHL, PsycInfo, and ACM Digital Library using a predefined search strategy. The studies were included if they: (1) were primary research studies that focused on consumers, caregivers, or health care professionals; (2) involved a conversational agent with an unconstrained natural language interface; (3) tested the system with human subjects; and (4) implemented personalization features. Results: The search found 1958 publications. After abstract and full-text screening, 13 studies were included in the review. Common examples of personalized content included feedback, daily health reports, alerts, warnings, and recommendations. The personalization features were implemented without a theoretical framework of customization and with limited evaluation of its impact. While conversational agents with personalization features were reported to improve user satisfaction, user engagement and dialogue quality, the role of personalization in improving health outcomes was not assessed directly. Conclusions: Most of the studies in our review implemented the personalization features without theoretical or evidence-based support for them and did not leverage the recent developments in other domains of personalization. Future research could incorporate personalization as a distinct design factor with a more careful consideration of its impact on health outcomes and its implications on patient safety, privacy, and decision-making.

  • Source: Unsplash; Copyright: Brooke Cagle; URL:; License: Licensed by JMIR.

    Electronic Screening for Alcohol Use and Brief Intervention by Email for University Students: Reanalysis of Findings From a Randomized Controlled Trial Using...

    Authors List:


    Background: Almost a decade ago, Sweden became the first country to implement a national system enabling student health care centers across all universities to routinely administer (via email) an electronic alcohol screening and brief intervention to their students. The Alcohol email assessment and feedback study dismantling effectiveness for university students (AMADEUS-1) trial aimed to assess the effect of the student health care centers’ routine practices by exploiting the lack of any standard timing for the email invitation and by masking trial participation from students. The original analyses adopted the conventional null hypothesis framework, and the results were consistently in the expected direction. However, since for some tests the P values did not pass the conventional .05 threshold, some of the analyses were necessarily inconclusive. Objective: The outcomes of the AMADEUS-1 trial were derived from the first 3 items of the Alcohol Use Disorders Identification Test (AUDIT-C). The aim of this paper was to reanalyze the two primary outcomes of the AMADEUS-1 trial (AUDIT-C scores and prevalence of risky drinking), using the same models used in the original publication but applying a Bayesian inference framework and interpretation. Methods: The same regression models used in the original analysis were employed in this reanalysis (linear and logistic regression). Model parameters were given uniform priors. Markov chain Monte Carlo was used for Bayesian inference, and posterior probabilities were calculated for prespecified thresholds of interest. Results: Where the null hypothesis tests showed inconclusive results, the Bayesian analysis showed that offering an intervention at baseline was preferable compared to offering nothing. At follow-up, the probability of a lower AUDIT-C score among those who had been offered an intervention at baseline was greater than 95%, as was the case when comparing the prevalence of risky drinking. Conclusions: The Bayesian analysis allows for a more consistent perspective of the data collected in the trial, since dichotomization of evidence is not looked for at some arbitrary threshold. Results are presented that represent the data collected in the trial rather than trying to make conclusions about the existence of a population effect. Thus, policy makers can think about the value of keeping the national system without having to navigate the treacherous landscape of statistical significance. Clinical Trial: ISRCTN Registry ISRCTN28328154;

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

    A New Mental Health Mobile App for Well-Being and Stress Reduction in Working Women: Randomized Controlled Trial


    Background: Although the availability and use of mobile mental health apps has grown exponentially in recent years, little data are available regarding their efficacy. Objective: This study aimed to evaluate the effectiveness of an app developed to promote stress management and well-being among working women compared with a control app. Methods: Female employees at a private hospital were invited to participate in the study via mailing lists and intranet ads. A total of 653 individuals self-enrolled through the website. Eligible participants were randomized between control (n=240) and intervention (n=250) groups. The well-being mobile app provides an 8-week program with 4 classes per week (including a brief theoretical portion and a 15-min guided practice). The active control app also provided 4 assessments per week that encouraged participants to self-observe how they were feeling for 20 min. We also used the app to conduct Web-based questionnaires (10-item Perceived Stress Scale and 5-item World Health Organization Well-Being Index) and ask specific questions to assess subjective levels of stress and well-being at baseline (t1), midintervention (t4=4 weeks after t1) and postintervention (t8=8 weeks after t1). Both apps were fully automated without any human involvement. Outcomes from the control and intervention conditions at the 3 time points were analyzed using a repeated measures analysis of variance. Results: Among the randomized participants (n=490), 185 participants were excluded at the 4-week follow-up and another 79 at the 8-week follow-up because of noncompliance with the experimental protocol. Participants who did not complete t4 and t8 assessments were equally distributed between groups (t4: control group=34.6% [83/240] and intervention group=40.8% [102/250]; P=.16; t8: control group=29.9% [47/157] and intervention group=21.6% [32/148]; P=.10). Both groups showed a significant increase in general well-being as a function of time (F2,426=5.27; P=.006), but only the intervention group presented a significant increase in work-related well-being (F2,426=8.92; P<.001), as well as a significant reduction in work-related and overall stress (F2,426=5.50; P=.004 and F2,426=8.59; P<.001, respectively). Conclusions: The well-being mobile app was effective in reducing employee stress and improving well-being. Clinical Trial: NCT02637414;

  • User-facing app implementing the Instil digital phenotyping platform to collect both passive and active sensor data. Source: Image created by the Authors; Copyright: The Authors; URL:; License: Creative Commons Attribution + Noncommercial + NoDerivatives (CC-BY-NC-ND).

    Intelligent Sensing to Inform and Learn (InSTIL): A Scalable and Governance-Aware Platform for Universal, Smartphone-Based Digital Phenotyping for Research...


    unstructured: In this viewpoint we describe the architecture of, and design rationale for, a new software platform designed to support the conduct of digital phenotyping research studies. These studies seek to collect passive and active sensor signals from participants' smartphones for the purposes of modelling and predicting health outcomes, with a specific focus on mental health. We also highlight features of the current research landscape that recommend the coordinated development of such platforms, including the significant technical and resource costs of development, and we identify specific considerations relevant to the design of platforms for digital phenotyping. In addition, we describe trade-offs relating to data quality and completeness versus the experience for patients and public users who consent to their devices being used to collect data. We summarize distinctive features of the resulting platform, InSTIL (Intelligent Sensing to Inform and Learn), which includes universal (ie, cross-platform) support for both iOS and Android devices and privacy-preserving mechanisms which, by default, collect only anonymized participant data. We conclude with a discussion of recommendations for future work arising from learning during the development of the platform. The development of the InSTIL platform is a key step towards our research vision of a population-scale, international, digital phenotyping bank. With suitable adoption, the platform will aggregate signals from large numbers of participants and large numbers of research studies to support modelling and machine learning analyses focused on the prediction of mental illness onset and disease trajectories.

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  • Communicating Uncertainty from Limitations in Quality of Evidence to the Public in Written Consumer Health Information: a Parallel-group, Web-based Randomized Controlled Trial

    Date Submitted: Nov 8, 2019

    Open Peer Review Period: Nov 8, 2019 - Jan 3, 2020

    Background: Uncertainty is integral to evidence-informed decision making and is of particular importance for preference-sensitive decisions. Communicating uncertainty to patients and the public has lo...

    Background: Uncertainty is integral to evidence-informed decision making and is of particular importance for preference-sensitive decisions. Communicating uncertainty to patients and the public has long been identified as a goal in the informed and shared decision-making movement. Despite this, there is little quantitative research on how uncertainty in health information is perceived by readers. Objective: The aim of this study was to examine the impact of different uncertainty descriptions regarding the evidence for a treatment effect in a written research summary for the public. Methods: We developed 8 versions of a research summary on a fictitious tinnitus drug with varying degrees (Q1), sources (Q2) and magnitudes of uncertainty (Q3). We recruited 2099 members of the German public from a web-based research panel. Of these, 1727 fulfilled the inclusion criteria and were randomly presented with one of these research summaries. Randomization was conducted by a centralized computer using a random number generator. Web-based recruitment and data collection were fully automated. Participants were not aware of the purpose of the study and alternative presentations. We measured the following outcomes: perception of the treatment effectiveness (primary); certainty in the judgement of treatment effectiveness; perception of the body of evidence; text quality; intended decision. Outcomes were self-assessed. Results: We did not find a global effect for Q1 and Q2 (p=.25 and p=.73), but for Q3 (p=.048). Pairwise comparisons showed a weaker perception of the treatment effectiveness for the research summary with 3 sources of uncertainty compared to a version with 2 sources of uncertainty (p=.037). Specifically, 9% less participants perceived the tinnitus drug as possibly beneficial, while 8% more considered it to be of unclear benefit in the group with 3 sources of uncertainty. There was no difference compared to a version with 1 source of uncertainty (p=.31), however. We did not find any meaningful differences between the research summaries for the secondary outcomes. Conclusions: Communicating even a large magnitude of uncertainty for a treatment effect had little impact on perceived effectiveness. Efforts to improve public understanding of research are needed to improve understanding of evidence based health information. Clinical Trial: German Clinical Trials Register DRKS00015911,

  • Development of an innovative Real World Evidence registry for the Herpes Simplex Virus: a case study

    Date Submitted: Nov 6, 2019

    Open Peer Review Period: Nov 6, 2019 - Nov 13, 2019

    Background: Infection with the Herpes Simplex Virus is common but is not well understood and stigmatised. Whilst a considerable number of people experience mild to severe physical symptoms after infec...

    Background: Infection with the Herpes Simplex Virus is common but is not well understood and stigmatised. Whilst a considerable number of people experience mild to severe physical symptoms after infection, only one sub-effective drug is available for treatment. A registry collecting real world data reported by people with the Herpes Simplex Virus could help them manage their condition, facilitate research into a vaccine, better treatment, and the impact of herpes on other conditions. Objective: This paper reports on the development a registry to collect real world data reported by people with the Herpes Simplex Virus. Methods: A case study design was selected to support a systematic means of observing the subject of investigation. The case study followed seven stages: plan, design, prepare, collect, analyse, create and share. We carried out semi-structured interviews with experts, thematically analysed the findings and built use cases. These will be used to generate detailed models of how a real world evidence registry might look, feel, and operate for different users. Results: We found the following key themes in the interviews: 1) stigma and anonymity; 2) selection bias; 3) understanding treatment and outcome gaps; 4) lifestyle factors; 5) individualised vs population-level; and 6) severe complications of herpes simplex virus. We developed use cases for different types of patients, members of the public, researchers and clinicians for a herpes simplex virus registry. Conclusions: This case study showed insights for the development of an appropriate registry to collect real world data reported by people with the Herpes Simplex Virus. Further research is needed on developing and testing the registry with different users and evaluate its feasibility and effectiveness of collecting data to support symptom management, and the development of vaccines and better treatment.

  • Adopting patient portals in hospitals: a qualitative study

    Date Submitted: Nov 5, 2019

    Open Peer Review Period: Nov 5, 2019 - Dec 31, 2019

    Background: Theoretical models help to explain or predict the adoption of eHealth technology and illustrate the complexity of the adoption process. Various models provide insights into general factors...

    Background: Theoretical models help to explain or predict the adoption of eHealth technology and illustrate the complexity of the adoption process. Various models provide insights into general factors that influence the use of eHealth technology. However, they do not give hospitals much actionable knowledge on how to facilitate the adoption process. Objective: Our study aims to provide insights into patient portal adoption processes among patients and hospital staff (including healthcare professionals, managers and administrative clerks). Studying the experiences and views of stakeholders answers this question: How can hospitals encourage patients and healthcare professionals to adopt a patient portal? Methods: 22 semi-structured (group) interviews (N=69) in 12 hospitals and four focus groups with members of (semi)national organizations and patient portal suppliers (N=53). Results: The effort hospitals put into adopting patient portals can be split into three themes. First, informing patients and healthcare professionals about the portal. The communication strategy has four objectives: 1) knowing about the portal, 2) knowing how it works, 3) encouraging visits to the portal and 4) knowing where to get support. Second, embedding the patient portal in the daily routine of healthcare professionals and management with three forms of support: 1) hospital policy, 2) management by numbers, and 3) a structured implementation strategy that includes all staff of one department. This embedding requires changing work processes and routines. Third, adjusting the portal to meet patients’ needs in the effort to optimize user-friendliness in two ways: 1) using patient feedback, and 2) focusing on optimizing the portal for patients with special needs (e.g. low literacy,, low digital skills). Interestingly,hospitals are reluctant to involve patients in the continuous development of patient portals, because they have experienced that nothing can be done with the feedback received (e.g. technologically impossible or too expensive). Conclusions: Asking stakeholders what they have learned from their attempts to stimulate patient portal use in hospitals elicited rich insights into the adoption process. This practical knowledge helps to translate the relatively abstract success factors one finds in scientific adoption models to the everyday pragmatics of eHealth projects in hospitals.

  • Bringing Home Cognitive Assessment: Initial Validation of Unsupervised Web-based Cognitive Testing on the Cambridge Neuropsychological Test Automated Battery (CANTAB) using a within-subjects counterbalanced design

    Date Submitted: Oct 29, 2019

    Open Peer Review Period: Oct 29, 2019 - Dec 24, 2019

    Background: Computerised assessments already confer advantages for deriving accurate and reliable measures of cognitive function, including test standardisation, accuracy of response recordings and au...

    Background: Computerised assessments already confer advantages for deriving accurate and reliable measures of cognitive function, including test standardisation, accuracy of response recordings and automated scoring. Web-based cognitive assessment could improve accessibility and flexibility of research and clinical assessment, widen participation and promote research recruitment whilst simultaneously reducing costs. However, differences between lab-based and unsupervised cognitive assessment may influence task performance. Validation is required to establish reliability, equivalency and agreement with respect to gold-standard lab-based assessments. Objective: The current study validates an unsupervised web-based version of the Cambridge Neuropsychological Test Automated Battery (CANTAB) against a typical in-person lab-based assessment, using a within-subjects counterbalanced design. The study tests: 1) reliability, the correlation between measurements across participants, 2) equivalence, the extent to which test results in different settings produce similar, or by contrast, different overall results, and 3) agreement, by quantifying acceptable limits to bias and differences between the different measurement environments. Methods: Fifty-one healthy adults (32 women, 19 men; mean age 37 years) completed two testing sessions on average one week apart. Assessments included equivalent tests of emotion recognition (Emotion Recognition Task: ERT), visual recognition (Pattern Recognition Memory: PRM), episodic memory (Paired Associate Learning: PAL), working memory and spatial planning (Spatial Working Memory: SWM; One-Touch Stockings of Cambridge: OTS), and sustained attention (Rapid Visual Information Processing: RVP). Participants were randomly allocated to one of two groups, either assessed in-person first (n=33) or using web-based assessment first (n=18). Performance measures (errors, correct trials, response sensitivity), and median reaction times were extracted. Analyses included intra-class correlations (ICC) to examine reliability, linear mixed models and Bayesian paired samples t-tests to test for equivalence, and Bland Altman plots to examine agreement. Results: Intra-class correlation coefficients ranged from 0.23-0.67, with high correlations in three performance measures (from PAL, SWM and RVP tasks, ≥0.60). High intra-class correlations were also seen for reaction time measures from two tasks (PRM and ERT tasks, ≥0.60). However, reaction times were slower during web-based assessments, which undermined both equivalence and agreement for reaction time measures. Performance measures did not differ between assessment modalities, and generally showed satisfactory agreement. Conclusions: Our results support the use of CANTAB performance measures (errors, correct trials, response sensitivity) in unsupervised web-based assessments. Reaction times are not as easily translatable from in-person to web-based testing, likely due to variation in home computer hardware. Results underline the importance of examining more than one index to ascertain validity, since high correlations can be present in the context of consistent, systematic differences which are a product of differences between measurement environments. Further work is now needed validate web-based assessments in clinical populations, and in larger samples to improve sensitivity for detecting subtler differences between test settings.

  • Digital platforms for the self-management of noncommunicable disease: A systematic review

    Date Submitted: Oct 23, 2019

    Open Peer Review Period: Oct 23, 2019 - Dec 18, 2019

    Background: Digital interventions are effective for health behavior change as they enable the self-management of chronic, noncommunicable diseases (NCDs). However, they often fail to facilitate the sp...

    Background: Digital interventions are effective for health behavior change as they enable the self-management of chronic, noncommunicable diseases (NCDs). However, they often fail to facilitate the specific or current needs and preferences of the individual. A proposed alternative is a digital platform, which would host a suite of discrete, already existing digital health interventions. A platform architecture would allow users to explore a range of evidence-based solutions over time to optimize their self-management and health behavior change. For this review, a digital platform has been defined as: a web-based host for numerous discrete, evidence-based digital health interventions, which are effective in supporting NCD self-management. Offers tool for guidance towards the interventions that are most suited to the user’s needs and preferences. Objective: This review aims to identify digital platforms and examine their potential for supporting NCD self-management and health behavior change. Methods: A literature search was conducted in August 2018 using EBSCOhost, PubMed, Scopus, and No digital platforms were identified, so criteria were broadened to include platform-like digital health interventions. Eligible interventions offered several health behavior change features to optimize NCD self-management in an adult population and provided digitally-supported guidance for the user towards the features best suited to them. Data collected on interventions was guided by the CONSORT-EHEALTH checklist. Evaluation data were collected on effectiveness and process outcomes. Results: Six interventions were included for review. Targeted NCDs included cardiovascular diseases (n=2), diabetes (n=3), and chronic obstructive pulmonary disease (n=1). All six used behavior change theories and frameworks to guide conceptualization. Development approaches were similar, with five of six implementing user-centered, iterative processes to optimize intervention relevance. Physical activity was the most targeted health behavior, addressed in all six interventions. Self-report measures and existing medical records were the main sources of data collection during evaluation. Four of the six interventions assessed changes in behavior. Just one demonstrated significant improvements in overall physical activity compared to the control group at 3-months (+4297 MET-minutes/week, P=.02). Significant improvements in diabetes-specific self-care behavior were observed for two of the six interventions at 1-month and 9-months. Older age, female, and lower baseline self-efficacy were associated with greater changes in self-care. One of the six studies reported significant improvements in disease-related quality of life of users at 9-months compared to non-users of the intervention. Adherence was based on the number of follow-up respondents and ranged from 27% to 83% across the six interventions (mean 65 ± SD 25). Initial log-in rates were high (84% ± 17%) and an average of 4 log-ins per user per month (± SD 2.5) was recorded for half of the interventions. User satisfaction was high and platform-like interventions were considered useful, especially the personal relevance to the user and the authoritative nature of the evidence-based components. Conclusions: This review suggests that, with guidance and support, a digital platform could effectively address the individual needs of users to affect positive behavior change. Drawing several evidence-based interventions together has the potential to engage a diverse user group and optimize engagement with existing interventions. This review highlights the need for comprehensive user-centered development and iterative evaluation of a digital platform for NCD self-management. Clinical Trial: PROSPERO 2018 CRD 420 1810 2095