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Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

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A new general medical journal for the 21st century, focusing on innovation in health and medical research.

Latest Submissions Open for Peer Review

A new feature on the JMIR website, open peer review articles, allows JMIR users to sign themselves up as peer reviewers for specific articles currently considered by the Journal (in addition to author- and editor-selected reviewers). The list below shows recently submitted articles where submitting authors have not opted-out of the open peer-review experiment and where the editor has not made a decision yet. (Note that this feature is for reviewing specific articles - if you just want to sign up as reviewer (and wait for the editor to contact you if articles match your interests), please sign up as reviewer using your profile).
To assign yourself to an article as reviewer, you must have a user account on this site (if you don't have one, register for a free account here) and be logged in (please verify that your email address in your profile is correct). Add yourself as a peer reviewer to any article by clicking the '+Peer-review Me!+' link under each article. Full instructions on how to complete your review will be sent to you via email shortly after. Do not sign up as peer-reviewer if you have any conflicts of interest (note that we will treat any attempts by authors to sign up as reviewer under a false identity as scientific misconduct and reserve the right to promptly reject the article and inform the host institution).
The standard turnaround time for reviews is currently 2 weeks, and the general aim is to give constructive feedback to the authors and/or to prevent publication of uninteresting or fatally flawed articles. Reviewers will be acknowledged by name if the article is published, but remain anonymous if the article is declined.
The abstracts on this page are unpublished studies - please do not cite them (yet). If you wish to cite them/wish to see them published, write your opinion in the form of a peer-review!

Tip: Include the RSS feed of the JMIR submissions on this page on your iGoogle homepage, blog, or desktop RSS reader to stay informed about current submissions!

JMIR Submissions under Open Peer Review

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Titles/Abstracts of Articles Currently Open for Review

Titles/Abstracts of Articles Currently Open for Review:

  • Interventions to digital addiction: An umbrella review of meta-analyses

    Date Submitted: Apr 12, 2024
    Open Peer Review Period: Apr 15, 2024 - Jun 10, 2024

    Background: Numerous studies have explored interventions to reduce digital addiction outcomes, but inconclusive evidence makes it difficult for decision-makers, managers, and clinicians to get familiar with all available literature and find appropriate interventions. Objective: To summarize and assess the certainty of evidence of interventions proposed to decrease the digital addiction from published systematic reviews. Methods: An umbrella review of published systematic reviews was undertaken. Included studies were systematic reviews and meta-analyses of quantitative primary studies assessing an intervention that aimed to reduce digital addiction. Results: studies assessing 21 associations were included in the umbrella review, of which 4 (80%) were high-quality systematic reviews. Weak evidence was observed in 19 associations, whereas null associations appeared in the rest 2 associations. These associations pertained to nine interventions (group counseling, intergrated internet addiction prevention program, psychosocial intervention, reality therapy, self-control training program, cognitive behavior therapy (CBT), interventions to reduce screen time in child and exercise) and ten outcomes (self-control, self-esteem, IGD symptoms, time spent gaming, IA scores, screen use time, interpersonal sensitivity longlines, anxiety and depression). CBT could reduce anxiety (0.939, 95% CI, 0.311 to 1.586), IGD symptoms (1.394, 95% CI, 0.664 to 2.214) and time spent gaming 1.259, 95% CI, 0.311 to 2.206) and IA scores (-2.097, 95% CI, -2.814 to -1.381). Group counseling had a large effect size on improving self-control (1.296, 95% CI, 0.269 to 2.322) and reduced internet addiction levels (-1.147, 95% CI, -1.836 to -0.997). Exercise intervention reduced IA scores (-2.322, 95% CI, -3.212 to -1.431) and depression (-1.421, 95% CI, -2.046 to -797) and interpersonal sensitivity (-1.433, 95% CI, -2.239 to -0.627). Conclusions: The evidence indicates that current interventions to reduce digital addiction are weak. Data from more and better-designed studies with larger sample sizes are needed to establish robust evidence.

  • Predictors of drop-out in a longitudinal survey of Amazon Mechanical Turk workers with low back pain

    Date Submitted: Mar 25, 2024
    Open Peer Review Period: Apr 1, 2024 - May 27, 2024

    Background: Online surveys of internet panels such as Amazon’s Mechanical Turk (MTurk) are common in health research. Non-response in longitudinal studies can limit inferences about change over time. Objective: We (1) describe the patterns of survey responses and non-response among MTurk members with back pain, (2) identify factors associated with survey response over time, (3) assess the impact of non-response on sample characteristics, and (4) assess how well inverse probability weighting can account for differences in sample composition. Methods: We surveyed MTurk adults who identified as having back pain. We report participation trends over three survey waves and use stepwise logistic regression to identify factors related to survey participation in successive waves. Results: A total of 1,678 adults participated in Wave 1. Of those, 983 (59%) participated in Wave 2 and 703 (42%) in Wave 3. Participants who did not drop out took less time to complete prior surveys (30 minutes vs. 35 minutes in Wave 1, p<0.005; 24 minutes vs. 26 minutes in Wave 2, p=0.019) and reported having fewer health conditions (6 vs. 7, p<0.005). In multivariate models, higher odds of participation were associated with less time to complete the baseline survey, older age, not being Hispanic, not having a bachelor’s degree, being divorced or never married, having less pain interference and intensity, and having more health conditions. Weighted analysis showed slight differences in sample demographics and conditions, and larger differences in pain assessments, particularly for those who responded to Wave 2. Conclusions: Longitudinal studies on MTurk have large, differential dropouts between waves. This study provided information about the types of individuals who are more likely to drop out over time which can help researchers prepare for future surveys.