JMIR Publications

JMIR Challenges


Journal Description

Seeking innovators and organizations seeking solutions and trying to stimulate innovation: Do you have a problem or question for the worlds' leading health innovators? For example, are you looking for software wireframes, blueprints, behavior change architectures, workflows, ideas or feedback from experts in the field, or do you need a piece of software development or software architecture outsourced? Or do you have an open dataset or big data resource and looking for experts to analyze the data? Do you want to sponsor a monetary or non-monetary prize/award for compelling solutions for a pressing public health problem? Is your research or development stuck because you need input from a broader community?  JMIR has a network of over 60.000 potential problem-solvers and idea generators: eHealth researchers and health experts, e-patients, leaders and innovators, including the top scientists in the fields of informatics, behavioral sciences, mental health, serious games, mHealth, ubiquitous computing, human factors, bioinformatics and biotechnology (sign up here). JMIR Challenges is a new platform connecting "solution-seekers" (sponsors) (companies, or other researchers) with "solution-providers" (entrants) (innovators, researchers, developers in the ehealth space).

Solution seekers submit a competition document (template here) specifying what they are looking for, the prize/award, and the detailed rules of the competition including evaluation process and criteria. After an internal review, JMIR Challenges will publish the competition document (the solution seeker can remain anonymous, if requested).

In response to the competition document, solution-providers will start submitting their solutions (documents e.g. with a description of their ideas or wireframes, multimedia files, software code) to the JMIR Challenges platform. Solution seekers can review the submissions and/or subject them to additional peer-review through their judges, selection panel or external reviewers (JMIR can help finding reviewers). At the end of the process, the solution-seeker will select winning submissions.

The solution seeker or solution provider may decide to publish the entries on the challenges platform or not (JMIR Challenges may eventually be PubMed-indexed).

JMIR is the administrator of the competition and will make sure that the prize money will be distributed as per the competition rules. 

Examples for possible competitions / challenges are:

  • $100,000 Challenge to find a solution for ...
  • $1,000 Prize for the best actual or potential use case of device XY (e.g. Google Glass) in health care
  • $5,000 Award to develop a questionnaire or method to measure adoption of XY
  • $10,000 Challenge develop wireframes and an algorithm for an app for XY patients
  • $5,000 Challenge to develop a research protocol to evaluate XY
  • $10,000 Challenge for an open source code for an mhealth app that does XY
  • ... to develop behavior change text messages for XY
  • ... to review and synthesize the literature on XY
  • ... to develop strategies to improve the use of / adherence to XY
  • ... to evaluate the usability of XY
  • ... to analyze the dataset Z and find an algorithm to predict a certain variable
  • ... to find new patterns and regularities in big dataset Z
  • ... to provide ideas for how to analyze dataset Z
  • ... to hacking challenge: see if individuals in an anonymized dataset Z can be re-identified (or proof proper de-identification)
  • ... to find a solution for public health problem XY
  • X Award for the most influential ...
  • X Prize for the most compelling ....
  • $1,000 JMIR Challenge for the best 3D Printdesign for a health care device or educational model (this is an actual forthcoming competition, monitor JMIR Challenges for the competition announcement)
  • $1,000 JMIR Patient Award for the best 3D Printdesign from an MRI scan showing a diseased organ (this is an actual forthcoming competition, monitor JMIR Challenges for the competition announcement)

For a template for a competition document and submission guidelines see Author Guidelines.




Recent Articles:

  • Screenshot from

    Partners Connected Health Innovation Challenge (CHIC)


    Partners Connected Health develops and validates technology-based solutions aimed at facilitating collaborative care, self-management, and improved quality. From ideation to implementation, our team envisions and builds innovations that facilitate collaborative care, self-management, and improved quality. Current solutions often do not meet their goals of promoting self-care due to limited integration into the clinical workflow, and low sustainability of patient, provider, and caregiver engagement. The Partners Connected Health core mission is to define the future of technology-enabled care delivery by integrating real-world patient and provider perspectives with user-centered design principles to create clear paths toward innovation. This year, we are launching the Partners Connected Health innovation challenge (CHIC), a competition geared toward finding innovative, technology-based solutions that enable care (preventive care and chronic disease management) outside of the clinic.

Citing this Article

Right click to copy or hit: ctrl+c (cmd+c on mac)

Latest Submissions Open for Peer-Review:

View All Open Peer Review Articles
  • User Participation and Engagement with the See Me Smoke-Free mHealth App: Results of a Prospective Feasibility Trial

    Date Submitted: Apr 21, 2017

    Open Peer Review Period: May 31, 2017 - Jul 14, 2017

    Background: The See Me Smoke-Free (SMSF) mobile health (mHealth) application (app) was developed to help women quit smoking by targeting concerns about body weight, body image, and self-efficacy throu...

    Background: The See Me Smoke-Free (SMSF) mobile health (mHealth) application (app) was developed to help women quit smoking by targeting concerns about body weight, body image, and self-efficacy through cognitive behavioral techniques and guided imagery audio files addressing smoking, diet, and physical activity. A feasibility trial found associations between SMSF usage and positive treatment outcomes. This paper reports a detailed exploration of program use among those who downloaded the app, and the relationship between program use and treatment outcomes. Objective: To determine whether: 1) participants were more likely to set quit dates, be current smokers, and report higher levels of smoking at baseline than non-participants; 2) participants opened the app and listened to audio files more frequently than non-participants; and 3) participants with more app usage had a higher likelihood of smoking abstinence at follow-up. Methods: The SMSF feasibility trial was a single arm, within-subjects, prospective cohort study with assessments at baseline, 30- and 90-days post-enrollment. The SMSF app was deployed on the Google Play store for download, and basic profile characteristics were obtained for all app installers. Additional variables were assessed for study participants. Participants were prompted to use the app daily during study participation. Crude differences in baseline characteristics between trial participants and non-participants were evaluated using t-tests (continuous variables) and Fisher’s exact tests (categorical variables). Exact Poisson tests were used to assess group-level differences in mean usage rates over the full study period, using aggregate Google Analytics data on participation and usage. Negative binomial regression models were used to estimate associations of app usage with participant baseline characteristics, after adjustment for putative confounders. Associations between app usage and smoking abstinence were assessed using separate logistic regression models for each outcome measure. Results: Participants (n=151) were more likely than non-participants (n=96) to report female gender (P < 0.02) and smoking in the 30 days prior to enrollment (P < 0.0001). Participants and non-participants opened the app and updated quit dates at the same average rate (Rate ratio (RR) 0.98; 95% CI: 0.92, 1.04; P = 0.43), but participants started audio files (RR 1.07; 95% CI: 1.00, 1.13; P < 0.04) and completed audio files (RR 1.11; 95% CI: 1.03, 1.18; P < 0.003) at significantly higher rates than non-participants. Higher app usage among participants was generally associated with increased smoking cessation, and most effect sizes suggested strong associations, though generally without statistical significance. Conclusions: The current study suggests potential efficacy of the SMSF app, as increased usage was generally associated with higher smoking abstinence. A planned randomized controlled trial will assess the SMSF app’s efficacy as an intervention tool to help women quit smoking. Clinical Trial: NCT02972515

  • Low- and No-Cost Strategies to Recruit Women to a Mobile Health Smoking Cessation Trial

    Date Submitted: Jan 19, 2017

    Open Peer Review Period: May 31, 2017 - Jul 14, 2017

    Background: Successful recruitment and retention of adequate numbers of participants to mobile health (mHealth) studies remains a challenge. Given that researchers must decide how to invest limited re...

    Background: Successful recruitment and retention of adequate numbers of participants to mobile health (mHealth) studies remains a challenge. Given that researchers must decide how to invest limited recruitment resources, it is important to identify the most effective recruitment strategies, defined as those that incur low costs relative to participant yield. Objective: The objective of this manuscript is to describe the development and implementation process for the recruitment phase of an mHealth intervention designed to increase smoking cessation among weight-concerned women smokers. These recruitment methods could be applicable across a range of mHealth studies. Methods: Study information was released to the media in multiple phases. First, local city and state media were contacted, followed by national women’s health media, and finally outlets in states with high smoking rates. Stories and mentions resulting from the press releases (earned media) were disseminated via existing department and new study-specific social media accounts. Strategic hashtags were used in Facebook and Twitter posts to connect with broader smoking cessation campaigns. Posts were also made to third-party Facebook smoking cessation communities and Internet classifieds sites. Results: Media coverage was documented across 75 publications and radio/television broadcasts, 35 of which were local, 39 national, and 1 international. Between March 30th and July 31st, 2015, 151 participants were successfully recruited to the study. Conclusions: Leveraging social media, and coordinating with university public affairs offices were effective and low-cost strategies to earn media coverage, and reach potential participants. Clinical Trial: Not Applicable