We all know the statistics. Obesity rates are a global concern, and finding effective, scalable solutions is more critical than ever. Enter eHealth interventions – digital programs offering support and guidance right at your fingertips. But in the realm of traditional weight loss programs, group support often reigns supreme. So, the burning question is: does this group dynamic translate to the digital space, and can a little face-to-face interaction boost the effectiveness of an eHealth program?

A significant new study, "Dissemination and Implementation Approach to Increasing Access to Local Pre-Exposure Prophylaxis PrEP Resources With Black Cisgender Women: Intervention Study With Vlogs Shared on Social Media," has been published in the prestigious JMIR Public Health and Surveillance.

Have you ever typed a health question into Google? You're not alone! For years, search engines have been the go-to digital first stop for understanding symptoms, treatments, and diagnoses. But hold on to your stethoscopes, folks, because the landscape of online health information is shifting dramatically – and faster than you might think!

Can your smartphone habits really impact your mental well-being? It's a question that has sparked countless studies, with some sounding the alarm about negative effects and others suggesting minimal impact. But what if the answer isn't so black and white? A groundbreaking new study delves into the deeply personal relationship between our digital lives and our mental health, challenging the notion of a one-size-fits-all answer.

2025 is already off to a rapid start for digital mental health technology. One of the emerging themes for this year is regulation, which opens questions about how different governments plan to assess, regulate, and pay for digital mental health technology.

Scholarly and scientific publishing is constantly evolving, and most recently driven by major movements towards open science and also influenced by the widespread availability of technology, like generative artificial intelligence. Negative influencers such as misaligned academic incentives, “pay-to-publish” publishing models, paper mills and plagiarism, and other unethical behaviors and their consequences are on the rise. The evergreen challenge? Keeping research transparent, trustworthy, and just plain honest. Research integrity is super important, to say the very least – and it is HOT! 

The integration of artificial intelligence (AI) into the peer review process is a rapidly evolving landscape, offering the promise of streamlined efficiency and increased objectivity. However, this exciting development also highlights several ethical considerations that reviewers should thoughtfully address and navigate. Most importantly, if a reviewer is considering using generative AI to help them with performing a peer review, first check journal policy on whether this is permissible and, if so, then how.

Ethical considerations are paramount in eHealth and informatics research, particularly when dealing with human subjects. Peer reviewers play a crucial role in ensuring that research adheres to the highest ethical standards. Therefore, one of the main responsibilities of a reviewer is to carefully scrutinize studies and verify that they have conducted their human subjects research ethically. 

Inclusive language is more than just a matter of political correctness; it's essential for cultivating an academic environment where everyone feels valued, respected, and heard. In the realm of peer review, where critical feedback is exchanged, the choice of words carries significant weight. Let's delve deeper into how we can make our reviews more inclusive and unbiased.

Peer review is a cornerstone of scholarly publishing, acting as a way to support the publication of high-quality research and to maintain scientific integrity. During peer review, experts evaluate the work of their peers, providing invaluable feedback. Some examples of key feedback during peer reviews include: evaluations of the validity of the scientific question(s) and approach, methodological rigor, how the work contributes to scientific advancement, potential errors or missing relevant/milestone references in the field, and significance and originality of the research (or appropriateness of reproduction in reproducibility studies, if applicable).