Manhattan residents living near the World Trade Center may have been particularly vulnerable to posttraumatic stress disorder (PTSD) after the September 11, 2001 (9/11) terrorist attacks. In 2003-2004, the authors administered the PTSD Checklist to 11,037 adults who lived south of Canal Street in New York City on 9/11. The prevalence of probable PTSD was 12.6% and associated with older age, female gender, Hispanic ethnicity, low education and income, and divorce. Injury, witnessing horror, and dust cloud exposure on 9/11 increased risk for chronic PTSD. Postdisaster risk factors included evacuation and rescue and recovery work. The results indicate that PTSD is a continued health problem in the local community. The relationship between socioeconomic status and PTSD suggests services must target marginalized populations. Followup is necessary on the course and long-term consequences of PTSD.

Twitter is an online microblogging tool that disseminates more than 400 million messages per day, including vast amounts of health information. Twitter represents an important data source for the cancer prevention and control community. This paper introduces investigators in cancer research to the logistics of Twitter analysis. It explores methodological challenges in extracting and analyzing Twitter data, including characteristics and representativeness of data; data sources, access, and cost; sampling approaches; data management and cleaning; standardizing metrics; and analysis. We briefly describe the key issues and provide examples from the literature and our studies using Twitter data to understand public health issues. For investigators considering Twitter-based cancer research, we recommend assessing whether research questions can be answered appropriately using Twitter, choosing search terms carefully to optimize precision and recall, using respected vendors that can provide access to the full Twitter data stream if possible, standardizing metrics to account for growth in the Twitter population over time, considering crowdsourcing for analysis of Twitter content, and documenting and publishing all methodological decisions to further the evidence base.

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