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We report a study of peer support in online health communities for pregnancy care along three gestational stages (trimesters) to investigate how pregnant women seek and receive peer support during different stages of pregnancy. Using Babycenter.com as our research setting, we found that pregnant women sought peer support due to constrained access to healthcare providers, dissatisfaction with healthcare services/medical advice, limited offline social support, and unavailability of information in other venues. While the particular topics of concern typifying each trimester were distinct, pregnant women consistently sought advice, informal and formal knowledge, reassurance, and emotional support from peers during each stage of pregnancy. BabyCenter.com peers provided support by leveraging their own experiential knowledge and passing along clinical expertise acquired during the course of their own healthcare. We discuss design implications for health services and IT systems that meet pregnant women's temporal and multi-faceted needs during prenatal care.

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Recently, diseases like H1N1 influenza, Ebola, and Zika virus have created severe crises, requiring public resources and personal behavior adaptation. Crisis Informatics literature examines interconnections of people, organizations, and IT during crisis events. However, how people use technology to cope with disease crises (outbreaks, epidemics, and pandemics) remains understudied. We investigate how individuals used social media in response to the outbreak of Zika, focusing on travel-related decisions. We found that extreme uncertainty and ambiguity characterized the Zika virus crisis. To cope, people turned to social media for information gathering and social learning geared towards personal risk assessment and modifying decisions when dealing with partial and conflicting information about Zika. In particular, individuals sought local information and used socially informed logical reasoning to deduce the risk at a specific locale. We conclude with implications for designing information systems to support individual risk assessment and decision-making when faced with uncertainty and ambiguity during public health crises.