JMIR Public Health and Surveillance

A growing body of research supports the efficacy of text messaging programs to help tobacco users quit, but texting as a strategy for recruiting tobacco users into other evidence-based cessation services, such as quitline coaching, is less well understood. Texting to offer treatment could increase use of cessation resources, an important consideration for health systems trying to improve their quality metric performance on tobacco assessment and counseling.

Vitamin D and weight status are key determinants for neurodevelopmental outcomes in children. However, their independent and interactive associations with neurodevelopmental outcomes represent a critical yet insufficiently explored issue in pediatric health.

In today’s unstable funding climate, alternative research funding mechanisms are essential. Investigators are facing novel barriers to acquiring funding for their research. Early-stage investigators, in particular those who are beginning their careers in research, are especially vulnerable to these funding disruptions. Currently, finding alternative funding is especially relevant for scientists studying historically and intentionally excluded communities, such as lesbian, gay, bisexual, transgender, queer, or other sexual and/or gender expansive (LGBTQ+) populations, as many investigators have had their LGBTQ+ grants revoked by the Trump administration. Crowdfunding for research studies is a potential funding avenue that has grown in popularity, with more than US $12 million raised since 2012. This Viewpoint highlights crowdfunding as a potential funding model for LGBTQ+ cancer research, specifically to support the collection of preliminary data for predoctoral students and early-stage investigators. We describe the benefits and challenges of using crowdfunding as the sole funding mechanism for a mixed methods observational study among LGBTQ+ survivors of cancer. Despite challenges, crowdfunding can fund rigorous research on health disparities, notably in historically and intentionally excluded communities.

Diverse survey methodologies are essential to ensure equitable representation in public health research, particularly among minority populations. This study evaluates demographic differences among Vietnamese Americans who completed paper versus electronic surveys while administering the National Institutes of Health Community Engagement Alliance Common Survey 2, which focused on COVID-19–related topics.

Social determinants of health continue to drive persistent disparities in perioperative care. Our team has previously demonstrated racial and socioeconomic disparities in perioperative processes, notably in the administration of antiemetic prophylaxis, in several large perioperative registries. Given how neighborhoods are socially segregated in the United States, we examined geospatial clustering of perioperative antiemetic disparities.

Artificial intelligence (AI) is rapidly reshaping the landscape of health care, from clinical diagnostics and disease surveillance to the prediction of individual health risks. Yet, its immense promise will only materialize if the tools we deploy work for everyone. Algorithms trained on incomplete or biased datasets risk embedding historical health disparities and can replicate patterns of uneven data representation, thereby limiting accuracy and generalizability across population groups. Addressing algorithmic bias should be treated as a core health quality standard, comparable in importance to safety and efficacy evaluations, to ensure consistent performance across all segments of the population. This paper aims to frame algorithmic bias in health-related AI as a quality, safety, and governance challenge for health systems rather than solely a technical problem for developers. It aims to inform policymakers, regulators, health system leaders, and developers by translating existing scientific evidence and regulatory guidance into operational governance considerations, with particular attention to the realities of low- and middle-income settings in the region of the Americas. This paper synthesizes existing knowledge and institutional experience into a practical, regionally grounded policy perspective. To operationalize this perspective, this paper first outlines the main forms of algorithmic bias relevant to health systems—including representation, measurement, aggregation, and deployment biases—and illustrates how each can emerge across the AI lifecycle. It then situates these technical challenges within the broader digital health context, where structural, commercial, and social dynamics may amplify inequities. This paper discusses the implications of biased data for emerging areas such as precision medicine before proposing a governance-oriented framework for bias mitigation that spans design, validation, deployment, and postmarket monitoring. It concludes with priority governance actions for policymakers, regulators, and health system leaders to embed fairness as a measurable component of health system performance.

The growing use of artificial intelligence (AI) chatbots for seeking health-related information is concerning, as they were not originally developed for delivering medical guidance. The quality of AI chatbots’ responses relies heavily on their training data and is often limited in medical contexts due to their lack of specific training data in medical literature. Findings on the quality of AI chatbot responses related to health are mixed. Some studies showed the quality surpassed physicians’ responses, while others revealed occasional major errors and low readability. This study addresses a critical gap by examining the performance of various AI chatbots in a complex, misinformation-rich environment.

As communication technology advances and the digital divide grows, a deeper understanding of the influence of different information sources on vaccine uptake by generation can inform targeted public health intervention in times of future crisis. While the COVID-19 pandemic highlighted the role of media sources on the decision to receive vaccines, no studies have focused on the impact of type and number of information sources in a population-based sample in California.

Despite major biomedical advances in HIV testing, prevention, and treatment, annual HIV transmissions in the United States remain above 30,000. Geographic access to pre-exposure prophylaxis (PrEP) is critical to HIV prevention efforts, particularly in regions with high HIV burdens, such as metro-Atlanta. Community-based organizations (CBOs) play a central role in delivering culturally competent prevention services, yet many rely on federal funding that is increasingly unstable. Understanding the potential impact of CBO closures on geographic access to PrEP is essential for anticipating inequities and informing policy.

In France, reluctance toward hepatitis B vaccination remains high, despite the availability of a safe and effective vaccine to prevent this infection. To boost vaccination coverage, it is therefore essential to identify the factors that are likely to encourage a more favorable opinion of this vaccine. Health literacy (HL) is one such factor. It refers to the individual ability to access, understand, critically appraise, and apply health information to make informed decisions about health issues for oneself and for others.

People living with HIV are at increased risk for developing cancer, a leading cause of death in this population. The management of cancer in people living with HIV is particularly challenging, necessitating specialized, interdisciplinary care. However, insights into cancer care provision for people living with HIV in Germany remain scarce.

This cross-sectional analysis of more than 19 million e-commerce orders from Sweden and Norway indicates that nicotine pouches have overtaken traditional snus in market share in both countries, reinforcing the potential of nicotine pouches as a harm reduction tool.