A systematic evaluation of websites offering information on chronic kidney disease.

In this study, we described the content and characteristics of 40 non-proprietary websites offering information about chronic kidney disease (CKD) and evaluated their information quality using the DISCERN scale and readability using Flesch Reading Ease and Flesch-Kincaid grade level. The areas in which the websites scored the lowest on the DISCERN scale were whether the website discussed knowledge gaps, presented balanced information, and was clear about the information source. Websites that rated higher quality on the DISCERN scale were more difficult to read. The quality and readability of many websites about CKD to be used as meaningful educational resources for patients who desire to learn more about CKD and treatment options remain inadequate.

Designing Decision-Support Technologies for Patient-Generated Data in Type 1 Diabetes.

People living with type 1 diabetes generate data as a byproduct of diabetes management. The development of decision support technologies can be enabled by harnessing these patient-generated data, but a major challenge is for these technologies to provide meaningful and highly personalized guidance to support individual patients' decision-making processes. In this paper, results from a year-long qualitative study were reported. Twenty-six people with type 1 diabetes were interviewed regarding the types of self-generated data they use for decision-making, their decision-making processes using self-generated data, and the difficulties they experience when attempting to use this data for decision-making. These patients' behaviors and difficulties point to new approaches to designing decision support technologies for personal use, including patient-centered and automated data entry, automated and individualized data analysis, and humanized output.

Leveraging Social Media to Promote Public Health Knowledge: Example of Cancer Awareness via Twitter.

BACKGROUND: As social media becomes increasingly popular online venues for engaging in communication about public health issues, it is important to understand how users promote knowledge and awareness about specific topics. OBJECTIVE: The aim of this study is to examine the frequency of discussion and differences by race and ethnicity of cancer-related topics among unique users via Twitter. METHODS: Tweets were collected from April 1, 2014 through January 21, 2015 using the Twitter public streaming Application Programming Interface (API) to collect 1% of public tweets. Twitter users were classified into racial and ethnic groups using a new text mining approach applied to English-only tweets. Each ethnic group was then analyzed for frequency in cancer-related terms within user timelines, investigated for changes over time and across groups, and measured for statistical significance. RESULTS: Observable usage patterns of the terms "cancer", "breast cancer", "prostate cancer", and "lung cancer" between Caucasian and African American groups were evident across the study period. We observed some variation in the frequency of term usage during months known to be labeled as cancer awareness months, particularly September, October, and November. Interestingly, we found that of the terms studied, "colorectal cancer" received the least Twitter attention. CONCLUSIONS: The findings of the study provide evidence that social media can serve as a very powerful and important tool in implementing and disseminating critical prevention, screening, and treatment messages to the community in real-time. The study also introduced and tested a new methodology of identifying race and ethnicity among users of the social media. Study findings highlight the potential benefits of social media as a tool in reducing racial and ethnic disparities.