bims-tyki2d 2026-05-17 papers

Issue of 2026–05–17
five papers selected by
Zoya Panahloo, UCB

J Genet Couns. 2026 Jun;35(3): e70220

Genetic counseling assistant-led education supports efficiency in rare disease care.

Laura Duncan, Jessa Bidwell, Kayla Troe, Corinne Berg, Emily Toering, Gabrielle Eversole, Alyssa Knudson, Kaitlin Sikkink Brown, Carolyn R Rohrer Vitek, Yan Li, Filippo Pinto E Vairo, Jennifer Kemppainen.

Genetic counseling assistants (GCAs) support genetic counselors (GCs) and genetics clinic workflows, but their potential roles in pretest genetic counseling for rare diseases have not been explored. A pilot within the Mayo Clinic Center for Individualized Medicine's Genetic Testing and Counseling Clinic (GTAC), which offers predefined tests for patients with rare disease, explored the impact of GCA pretest education on appointment time and patient questions. After training, GCAs met GTAC patients prior to the GC to provide scripted information on genetics concepts, the visit purpose, and the test including result types and disclosure plans. Data from the pilot and a control group were collected and analyzed using descriptive statistics and two-sided t-tests. Patient cohort characteristics did not differ between the two models. When a GCA provided pretest education, the GC spent an average of 11.2 minutes less with the patient during their session compared to visits completed solely by the GC (p < 0.0001). Total appointment time was not impacted by GCA education. Questions asked to GCAs were often not within GCA scope to answer (72.7%), and some patients asked repetitive questions to both the GC and GCA (63.2%). Reduction in GC time per patient could lead to increased accessibility by allowing additional patients to be seen in a day. Similar models may support GCA professional development while allowing GCs to remove repetitive education from their genetic counseling sessions, leading to less burnout and/or increased job satisfaction. Impact on administrative workflows, access, revenue, patient satisfaction and outcomes and GC/GCA satisfaction and benefits can continue to be explored when trialing models incorporating GCAs in pretest education roles.

Keywords: appointment time; genetic counseling assistant; genetic counselor; genetic testing; genetics services; intervention study; practice models; pretest; rare disease

DOI: https://doi.org/10.1002/jgc4.70220

PLOS Glob Public Health. 2026 ;6(5): e0006435

Rare diseases in children-Knowledge, experiences and challenges faced by pediatricians in Tanzania.

Mariam Noorani, Mohamedraza Ebrahim, Francis Furia.

Diagnosing and treating rare diseases in children is a major challenge for pediatricians globally. There is a lack of adequate knowledge of these conditions and diagnostic testing is not easily accessible, which frequently results in delays in care. The knowledge, experiences and challenges faced by pediatricians in Tanzania are not known. This study used a nationwide cross-sectional online survey to describe the knowledge of pediatricians in Tanzania on rare diseases, their experiences, and the challenges they face in treating these children. The survey tool was shared on the Pediatric Association of Tanzania WhatsApp group where most pediatricians are registered. 168 pediatricians completed the survey, giving a response rate of 52%. All of them had encountered a child with a presumed rare disease in their career, with 60% having seen one in the 6 months preceding the survey. The commonest presumed rare condition encountered was genetic/metabolic, and the most common difficulty (97%) encountered was lack of access to diagnostic testing. A third of respondents reported that rare diseases were taught in university and 60% felt unprepared to look after these children. Three quarter of respondents could not access to experts to advise them on management. Presumed rare diseases are commonly encountered by pediatricians in Tanzania, and there are challenges in diagnostic testing, gaps in training, lack of confidence in providing care and inability to access experts on rare disease management. To improve care of children with rare diseases, diagnostic testing should be made available, accessible and affordable. A review of medical training curricula should be done to incorporate rare disease education and skill development. Platforms and pathways to connect pediatricians with regional and global experts should be put in place to provide timely and appropriate care to children with rare diseases.

DOI: https://doi.org/10.1371/journal.pgph.0006435

JMIR Hum Factors. 2026 May 15. 13 e80230

Development, Implementation, and Preliminary Results of a Novel Social Network for Rare Disease Communities: Mixed Methods Study.

Lara Fendrich, Henriette Högl, Ralf Schmidt, David Bascom, Armin Berger, Max Lübbering, Gundula Ernst, Justus Schumacher, Sabrina Hölzer, Lorenz Grigull.

Background: Rare diseases affect approximately 20 million Europeans, presenting unique challenges such as delayed diagnoses, limited therapies, and significant personal and financial burden. While resilience-supporting factors such as peer support are available and artificial intelligence-based diagnostic tools are being developed further, there is a lack of a dedicated online social network connecting patients, caregivers, relatives, and experts. This study presents the development and preliminary findings of Unrare.me, a novel social network designed to provide a secure space for experts and individuals affected by rare and chronic diseases (diagnosed and undiagnosed).
Objective: This study aimed to design, develop, and evaluate a social networking platform tailored to the needs of different stakeholders of the rare disease community, facilitating interaction, knowledge exchange, and emotional support while prioritizing data security.
Methods: This multidisciplinary, multicenter initiative brought together patient groups, health care professionals, psychologists, and web design experts. A literature review assessed existing networking approaches in the rare disease community. Structured interviews and user journey mapping defined user needs and essential app features. Iterative prototyping and stakeholder discussions informed the final design, which was developed into a functional app launched in December 2023 on major platforms. A survey conducted four months post-launch evaluated user feedback. Data security was prioritized throughout development.
Results: A total of 270 users (approximately 1 in 7 users at the time) participated in the evaluation. Most of them (n=221, 81.9%) registered to connect with others in similar situations, whereas 56.7% (n=153) sought expert input and 44.4% (n=120) looked for disease-related information. The app received positive ratings for usability (mean 6.12, SD 1.03; out of 7), accessibility (mean 5.59, SD 1.22), and design (mean 5.84, SD 1.12), as well as overall impression (mean grade of 2.24, SD 0.90 on a scale from 1-6, with 1 being the best score). Data security was highly rated (mean 5.58, SD 1.15). The app's ontology was suitable for 77% (n=208) of the participants, enabling them to find their diagnosis, and 60.7% (n=164) of users found at least one match. Matching preferences centered on shared diagnosis (mean 82.5, SD 25.1 on a visual analog scale from 0 to 100), symptoms (mean 74.2, SD 25.8), and everyday experiences (mean 69.6, SD 29.5). Overall, users welcomed the opportunity to network with each other securely and highlighted areas for further improvement, such as enhanced matching features and group chat options.
Conclusions: Unrare.me has generated significant interest and engagement within the German rare disease community, serving as a valuable tool for peer support, knowledge sharing, and expert identification. Current challenges include optimizing user acquisition and refining matching algorithms. Planned features include group chats, expert interaction, and gamification elements. Unrare.me illustrates the potential of tailored digital solutions to address unmet needs in the rare disease community.

Keywords: AI; app; artificial intelligence; mutual support; rare disease; social network

DOI: https://doi.org/10.2196/80230

Patterns (N Y). 2026 May 08. 7(5): 101535

Centering the marginalized: AI-driven strategies for advancing health equity in rare disease care.

Chaoyu Lei, Ying Zuo, Claudia Abreu Lopes, Jaimee Stuart, Benjamin Xu, T Y Alvin Liu, Thomas Ploug, Zilong Wang, Kang Dang, Kai Jin, Haoxuan Yu, Heaven Yeshaneh Tatere, Fanyi Kong, Ning Zhang, Lufa Zhang, Huifang Zhou.

Rare diseases (RDs) affect 6%-8% of the global population but remain critically underserved. People living with an RD face misdiagnosis, limited treatment options, and inequitable access to specialized care. While artificial intelligence (AI) offers transformative potential in RD care, significant challenges remain. This perspective identifies five key dimensions to equitable AI application in RD care: data availability, algorithmic fairness, patient privacy, resource prioritization, and medical ethics. To address these barriers, strategies include enhancing data diversity through internationally harmonized repositories, leveraging synthetic data, and employing fairness-aware algorithms. Privacy-preserving methods safeguard sensitive genetic data while enabling collaborative research. Transparent resource-allocation frameworks and interdisciplinary governance ensure equitable distribution of AI-driven benefits, particularly in low- and middle-income countries. Ethical considerations, including patient-centered consent and dynamic risk assessments, are foundational to sustainable AI integration. By addressing these multidisciplinary challenges, AI can advance health equity, transforming RD care from fragmented and inequitable to inclusive and innovative. This paradigm shift aligns technological progress with the ethical imperative to ensure no patient is left behind in the promise of precision medicine.

Keywords: artificial intelligence; ethics; fairness; health equity; rare disease

DOI: https://doi.org/10.1016/j.patter.2026.101535