Publishing Policies

Literature reviews, preferably systematic reviews and meta-analyses (authors are asked to follow the QUORUM checklist when submitting reviews), on the impact of digital health, mHealth, wearables, and apps for medicine on health outcomes and health policy.

Note that app and product reviews, where authors systematically searched app stores and review apps, are collected in the section Quality Evaluation and Descriptive Analysis/Reviews of Multiple Existing Mobile Apps. 

Related: 
Wearables and MHealth Reviews

Quality Evaluation and Descriptive Analysis/Reviews of Multiple Existing Mobile Apps

A commentary is published alongside other articles published in JMIR Publications journals. Commentaries are typically invited. Unsolicited commentaries may be considered at the discretion of the editor. They may or may not be peer-reviewed. Articles submitted as a commentary should offer thoughtful criticism of published work, drawing from evidence, expertise, and/or additional perspectives. 

Policy proposals should be based on a thorough review of the literature and stakeholder consultations, workshops or consensus building processes etc. If it is just the opinion of an individual (or small group of individuals), submit as viewpoint.

Opinion articles or perspectives papers which would not otherwise qualify as "original papers", because they do not have much original data, but would also not qualify as reviews, because they are based on personal experiences, workshop results, system descriptions etc.

A "how-to" paper on an important practical or research issue. We recommend contacting the editor to discuss the suitability of a topic before submitting it. Submission of slides or audio/video files as supplementary files is strongly recommended.

Infodemiology (Eysenbach 2002, Eysenbach 2006, Eysenbach 2009) has been defined as "the science of distribution and determinants of information in an electronic medium, specifically the Internet, or in a population, with the ultimate aim to inform public health and public policy. Infodemiology data can be collected and analyzed in near real time. Examples for infodemiology applications include: the analysis of queries from Internet search engines to predict disease outbreaks (eg. influenza); monitoring peoples' status updates on microblogs such as Twitter for syndromic surveillance; detecting and quantifying disparities in health information availability; identifying, defining, assessing and monitoring the "quality" of public health relevant publications on the Internet (eg. anti-vaccination sites, but also news articles or expert-curated outbreak reports); automated tools to measure information diffusion and knowledge translation, and tracking the effectiveness of health marketing campaigns e.g. by measuring how they resonate in social media or mass media outlets. Moreover, analyzing how people search and navigate the Internet for health-related information, as well as how they communicate and share this information, can provide valuable insights into health-related behavior of populations. " (Eysenbach 2009)

More recently, the World Health Organization (WHO) has declared an “infodemic” on top of the COVID-19 pandemic, and recognized the importance of infodemiology as a key method in fighting the infodemic. The seminal WHO papers on this topic were published in JMIR journals (e.g. Tangcharoensathien et al. 2020; Calleja et al. 2021).

See also related E-Collections: 

Infoveillance, Infodemiology and Digital Disease Surveillance  

Infoveillance and Social Listening

Pharmacovigilance

See also related Journals:

JMIR Infodemiology

JMIR Public Health & Surveillance 

Electronic (digital) ways of teaching and learning about health and medicine, primarily for professionals.

See also our dedicated journal JMIR Medical Education

We welcome high-impact original research, well-researched reviews, viewpoints and tutorials on emerging privacy and confidentiality issues in the age of personal health records, Google Health, Patient-Accessible Health Records, and Web-based behavior change interventions.

More articles on this topic can be found in the following journals:

JMIR Public Health & Surveillance

JMIR Infodemiology, including our cross-journal Ecollections on Infodemiolgy

Online Journal of Public Health Informatics

Long-term adherence to digital health interventions is one of the fundamental problems in digital health - how can we make digital health interventions engaging to prevent people/participants to cease use or drop out from studies? This research priority and paradigm was first posited by Eysenbach in the classic highly cited paper "The Law of Attrition", and is also known as "Eysenbach's Law".

See also:

• Augmented Reality (incl. Google Glass) Applications
• Usability of Virtual Reality Simulations
• Virtual Reality Interventions in Mental Health
• Virtual Reality and Augmented Reality in Medical Education
• Virtual Reality in Pediatrics
• Virtual Reality in Surgery Planning, Training, Education

Journal:

JMIR XR and Spatial Computing

eHealth Literacy (nowadays also sometimes referred to as "digtial health literacy" was introduced and defined as "the ability to seek, find, understand, and appraise health information from electronic sources and apply the knowledge gained to addressing or solving a health problem" by Camron Norman and colleagues in their seminal 2006 paper "eHealth Literacy: Essential Skills for Consumer Health in a Networked World". 

A patient-reported outcome (PRO) is a health outcome directly reported by the patient who experienced it. It stands in contrast to an outcome reported by someone else, such as a physician-reported outcome, a nurse-reported outcome, and so on. PRO methods, such as questionnaires, are used in clinical trials or other clinical settings, to help better understand a treatment's efficacy. The use of digitized PROs, or electronic patient-reported outcomes (ePROs), is on the rise in today's health research industry and a frequent focus of JMIR papers.

Artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals. Computer science defines AI research as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. More specifically, Kaplan and Haenlein define AI as “a system’s ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation”. Colloquially, the term "artificial intelligence" is applied when a machine mimics "cognitive" functions that humans associate with other human minds, such as "learning" and "problem solving" (Wikipedia).

This JMIR e-collection focuses on methods and approaches using artificial intelligence in health and medicine. 

For clinical decision making see Decision Support for Health Professionals and Clinical Information and Decision Making; for decision support for consumers see also Consumer & Patient Education and Shared-Decision Making.

For applications in medical education see also ChatGPT and Generative Language Models in Medical Education, 
Artificial Intelligence (AI) in Medical Education, Virtual Patients

See also JMIR e-collections on Robotics in Rehabilitation, Chatbots and Conversational Agents, Theme Issue 2022: Chatbots and COVID-19, Robots in Healthcare, Machine Learning, and Natural Language Processing 

Related Journal (preferred journal for machine-learning/AI applications that are not in clinical routine use): 
JMIR AI

Chatbots are Artificial Intelligence  programs (web-based or using smartphone app/messaging), which are increasingly used in particular for mental health applications (e.g. Depression and Mood Disorders), prevention and Behavior Change applications (such as Smoking Cessation or physical activity interventions). They are based on text-only exchanges between the client and an intelligent software which mimics a coach or therapist.

Related Themes/E-Collections:
ChatGPT and Generative Language Models in Medical Education 
Artificial Intelligence
Natural Language Processing

See also: Mobile Health in Psychiatry, mHealth for Wellness, Behavior Change and Prevention, Text-messaging (SMS)-Based Interventions. 

JMIR has a partnership with Infoway in which the APCs of Infoway-funded authors can be waived. For further information, please see KB article.

See also JMIR e-collections on Robotics in Rehabilitation, Chatbots and Conversational Agents, and Artificial Intelligence in Health.

Commentaries, opinion pieces, and original research related to Open Access to the research literature.

Blockchain technology and decentralized applications (DApps) have the potential to alleviate the traditionally high dependency on centralized, trusted parties for certification of information integrity and data ownership. These distributed ledger technologies (DLTs) mediate transactions and exchanges of digital assets in a decentralized and consensus-driven nature, which allows agreements (ie, smart contracts) to be directly made between interacting parties while guaranteeing their execution. Key properties of blockchain technology, including immutability, decentralization, distribution, replicated storage, and transparency, provide a unique position for this technology to serve as a potential infrastructure to address pressing issues in health care, such as incomplete records at point of care and difficult access to patients’ own health information. 

See also special 2019 theme issue on Blockchain and the call for papers.

Data science is a multi-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data. Data science is a similar concept as data mining and big data.

Related E-Collections:

Big Data

Machine Learning

Guidelines for Electronic Resources Reviews Revised December 2009 The purpose of the new electronic resources reviews section in the Journal of Medical Internet Research (JMIR) is to provide critical appraisals of electronic products and services that assist health care consumers and health professionals to select resources to manage or improve health. The focus is on consumer health informatics products, i.e. applications that have a direct interface to the consumer (although many of these products also have interfaces to health professionals, EMRs etc.). 

New methods, frameworks, collaborations to conduct science and clinical trials in the digital age and age of open data

Registered reports adhere to the highest ethical standards in research and require a protocol to be published (e.g. in JMIR Research Protocols), ideally before data collection. Publishing a protocol (Registered Report Stage 1, or RR1) prevents bias and JMIR's "acceptance in principle" policy for projects with published protocol facilitates publication of study results even if they are negative. 

This category/journal section/e-collection is for papers reporting the results (Registered Report Stage 2, or RR2). The IRRID in the abstract links back to the DOI of the protocol.

Precision medicine uses "big data" and data science to personalize diagnostic and therapeutic strategies for patients, based on their personal genetic and behavioral background. 

Related E-Collections:

Big Data

An evidence-based critical appraisal of a paper published in another journal. Could be used to point out key papers in other journals, or to discuss methodological flaws. See separate guidelines on how to write a CATCH-IT paper.Will usually be forwarded to the original author for a rebuttal.

This is an ecollection of papers submitted as a result of our standing Call for Papers to reanalyze trials using a Bayesian Method. Submissions are still accepted!

Letters to the Editor are exempt from Article Processing Fees. While this journal does publish "Research Letters" (short articles containing original data), JMIR also publishes letters responding to a previously published article. Short articles containing original data should be submitted as general article, not as a letter. A letter to the editor must cite and critique or substantially comment on a recent paper published in JMIR. The letter will be forwarded to the authors of the cited or critiqued article or other reviewers, and original authors will get a chance to respond. While some new data in a letter are allowed, a letter is NOT a short research report.

This section lists all substantive corrections, additions or changes made to articles and reviews subsequent to their first publication in the journal. Corrigenda are usually submitted by the corresponding author of the original article, or the section editor. Published papers are considered "final", thus JMIR makes corrections to published papers only in exceptional circumstances. Note that while we do not charge to correct errata that are the responsibility of the publisher, we charge a $190 fee for discretionary corrigenda and addenda (please submit a correction under that section, if it is the authors' responsibility/decision to correct or add information to a already published article).

For corrigenda that are discretionary and a result of author-oversight (e.g., corrections in the affiliation etc.) we charge a $190 processing fee to make changes in the original paper and publish an erratum. Please submit a correction statement (text similar to http://www.jmir.org/2015/3/e76/) at http://www.jmir.org/author/submit/1 under the section "Discretionary Corrigenda".

The Journal of Medical Internet Research is inviting submissions for a special issue of the journal dedicated to Covid-19 research. 

All papers will be fast tracked and shared with the World Health Organization (WHO) immediately on submission. Please submit field reports, surveillance reports, technologies, apps, protocols and reports on isolation, suppression, treatment protocols, vaccinations, models, case studies, policy recommendations, rapid reviews, telework/telemedicine reports. etc.

See also: 

• Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports - see JMIR Public Health & Surveillance COVID-19 Theme Issue Call for Papers.

• JMIR Theme Issue: Covid-19 Special Issue (Articles submitted in response to the J Med Internet Res Call for Papers)

• JMH Theme Issue COVID-19 and Mental Health: Impact and Interventions (JMIR Mental Health)

• JPP Theme Issue: Digital Approaches for Pediatric Healthcare Delivery during the Coronavirus (Covid-19) Pandemic (see JMIR Pediatrics & Parenting Call for Papers)

Voice assistants are a subset of artificial intelligence powered chatbots/conversatinal agents that can understand natural human voice and which can respond with an artificial voice.

Examples for voice assistants are Amazon Alexa. Google Assistant. Microsoft Cortana. Samsung Bixby. Apple Siri. IBM Watson. 

See also: 

Artificial Intelligence [Section Id: 797]Chatbots and Conversational Agents [Section Id: 763]

Symptom checkers (SCs) are tools developed to provide clinical decision support to laypersons.
See also/Related: Consumer & Patient Education and Shared-Decision Making

Papers sponsored by or related to projects from DiMe, which is a nonprofit professional society dedicated to advancing digital medicine to optimize health.

Research Letters present new, early, or preliminary research findings. The text should use standard research headings of Introduction, Methods, Results, and Discussion and should be no longer than 750 words, with a maximum of 10 references and 2 tables or figures. The APF for Research Letters accepted after peer review is lower than the standard APF.

Theme issue (e-collection) related to role of health information technologies (HIT) in promoting and protecting reproductive health decisions. The original Call for Papers on Reproductive Informatics: Implications for Women's Health and Informed Choice is here.

Contributions of telehealth, virtual consulting or other health care innovations to the net zero agenda; development and implementation of medical or health care programs to support increased environmental sustainability; projects and initiatives to combat or respond to climate change

See also: 
Environmental Health

See also:

JMIR Medical Education: Theme Issue: ChatGPT and Generative Language Models in Medical Education

JMIR Nursing - Artificial Intelligence (AI) and ChatGPT in Nursing

JMIR Human Factors - Theme Issue on Artificial Intelligence (AI) and Human Factors—Towards Successful Application of AI in Health Care

JMIR Cardio - Generative and Multimodal Artificial Intelligence (AI) in Digital Cardiovascular Medicine

JMIR Mental Health - Theme Issue on “Responsible Design, Integration, and Use of Generative AI in Mental Health

JMIR Aging - Using AI Tools to Improve Health and Health Care for Older Adults

Asian/Pacific Island Nursing Journal - API Health and Nursing Care

JMIR Publications, the pioneering publisher of open access research dedicated to digital health, is proud to celebrate its 25th anniversary. Over the past quarter-century, we have witnessed an incredible transformation in the field of digital health. To commemorate this significant milestone, we invite authors to contribute to a theme issue that reflects on the evolution and impact of digital health technologies, interventions, methods, and policy issues over the last 25 years.

Call for Papers

Related issue:

Theme issue 2019: 20th Anniversary Issue

Articles in this section are written by journalists. They are not peer-reviewed but adhere to journalistic standards. We invite freelance journalists to pitch us original ideas.

For more information, refer to Call for Papers: Theme Issue: The Emergence of Medical Futures Studies