JMIR Publications

[This corrects the article DOI: 10.2196/70450.].

Bipolar disorder (BD) impacts over 40 million people around the world, often manifesting in early adulthood and substantially impacting the quality of life and functioning of individuals. Although early interventions are associated with a better prognosis, the early detection of BD is challenging given the high degree of similarity with other psychiatric conditions, including major depressive disorder, which corroborates the high rates of misdiagnosis. Further, BD has a chronic, relapsing course, and the majority of patients will go on to experience mood relapses despite pharmacological treatment. Digital technologies present promising results to augment early detection of symptoms and enhance BD treatment. In this editorial, we will discuss current findings on the use of digital technologies in the field of BD, while debating the challenges associated with their implementation in clinical practice and the future directions.

Plan P - A Publishers’ Offer to Institutions and Funders to Transform to Open Science Plan P (http://planp.science) is JMIR Publication’s collaborative proposal for truly open scholarly communications and a framework for academic institutions and funders to facilitate a transformation towards Open Science. Plan P supports a “preprint first” publication model (PRC: Preprint - Review - Curate) by creating a platform for rapid AI-supported peer-review of preprints, editorial prospecting of preprints, and publication of curated peer-reviewed preprints in the overlay journal series JMIRx or - via a “manuscript marketplace” - in any other journal. Hashtag communities are peer-review communities, which include traditional journals but can also be other communities around a certain topical interest, can be targeted by preprint authors by using hashtags in their abstract and are being credited in published preprints. Plan P is also a business model that distributes the costs for peer-review and publication between institutions and funders. Encouragement of Registered Reports is another aspect of Plan P. Finally, Plan P creates research assessment metrics for institutions that go beyond citation-based approaches, measuring adherence to open science best practices. The ultimate goal of this endeavor is to develop the easiest path for authors to create transparent work by cataloging their entire research effort - from methodology to preliminary results and on to publication - as well as creating an environment for librarians where the needs of their budgets and institution do not conflict with their Open Science goals. Join Dr Gunther Eysenbach, founder and CEO of JMIR, as he presents this exciting plan to accelerate the move to Open Science. We would be thrilled to present to the FORCE2021 audience, given their interest in disruptive technologies and appreciation of the need for more open and equitable publishing solutions.

UNSTRUCTURED In this issue of the <i>Journal of Medical Internet Research</i>, the World Health Organization (WHO) is presenting a framework for managing the coronavirus disease (COVID-19) infodemic. Infodemiology is now acknowledged by public health organizations and the WHO as an important emerging scientific field and critical area of practice during a pandemic. From the perspective of being the first “infodemiolgist” who originally coined the term almost two decades ago, I am positing four pillars of infodemic management: (1) information monitoring (infoveillance); (2) building eHealth Literacy and science literacy capacity; (3) encouraging knowledge refinement and quality improvement processes such as fact checking and peer-review; and (4) accurate and timely knowledge translation, minimizing distorting factors such as political or commercial influences. In the current COVID-19 pandemic, the United Nations has advocated that facts and science should be promoted and that these constitute the antidote to the current infodemic. This is in stark contrast to the realities of infodemic mismanagement and misguided upstream filtering, where social media platforms such as Twitter have advertising policies that sideline science organizations and science publishers, treating peer-reviewed science as “inappropriate content.”