ÌÇÐÄvlog

This survey study assesses the utility of crowdsourcing via web search advertisements to create a representative dermatology image dataset.

This cross-sectional study examines the content and quality of information about urinary tract infections and asymptomatic bacteriuria on publicly available websites.

This cross-sectional study examines the frequency of medical board discipline of US physicians for spreading medical misinformation relative to discipline for other offenses.

This Special Communication reviews current research on the association of social media use with suicide risk among youth and outlines obstacles toward studying this topic.

This randomized clinical trial investigates whether an online text editing tool is effective in helping health information providers simplify written health information according to health literacy and plain language guidelines.

This cross-sectional study examines whether synthetic nicotine e-cigarette brands implemented Food and Drug Administration health warning requirements and evaluates the association between health warnings and user engagement on Instagram.

This cross-sectional study examines whether there is an association between adolescents and young adults’ preferred and actual sources of contraceptive information and reporting sufficient contraceptive information.

This qualitative study used an artificial intelligence (AI) large language model and social media to investigate challenges encountered by transgender individuals during breast and gynecological cancer care.

This cross-sectional study examines changes in children’s exposure to food-related television advertising after changes in the voluntary industry self-regulatory Children’s Food and Beverage Advertising Initiative standards.

This cross-sectional study examines the prevalence and factors associated with exposure to tobacco products advertised, marketed, or promoted on television or streaming platforms among US adults.

This cross-sectional study compares the race and ethnicity and gender of images of physicians generated by artificial intelligence (AI) with US physician demographic characteristics.