title: Genetics blogs as a public health tool: assessing credibility and influence.
abstract: The Internet is becoming an important source of information about genetics and holds promise for public health applications. However, the public has concerns about the credibility of online genetics information. We conducted a content analysis of genetics blogs (n = 94). Specifically, we assessed the prevalence of various genetics-related topics and perceived credibility indicators. The relationship between content indicators, credibility indicators, and blog influence, measured as links between blogs, was evaluated. Coverage of issues related to health or self-knowledge (31%) and life science (26%) was most common among genetics blogs. In terms of credibility indicators, most blogs disclosed authors' full names (81%) and biographical information (67%). Many blog authors reported having genetics (67%) or life science expertise (59%). However, only 7% of blogs were affiliated with educational or medical institutions. Overall, blogs that focused on ancestry, that had authors with life science expertise, and that posted more frequently tended to be more influential. Findings suggest that life scientists and those who blog frequently may figure more centrally in shaping the genetics information available to the public via blogs. There is room for institutions that are likely to be perceived as credible sources of genetics information to assume a greater presence through blogs.
authors.affiliation: Social and Behavioral Research Branch, National Human Genome Research Institute, Bethesda, MD 27599, USA. lkwagner@live.unc.edu
authors.forename: L
authors.initials: L
authors.lastname: Wagner
authors.forename: R
authors.initials: R
authors.lastname: Paquin
authors.forename: S
authors.initials: S
authors.lastname: Persky
mesh_terms: D057218:Blogging; D005823:Genetics; D015894:Genome, Human; D023281:Genomics / Q000379:methods*; D006801:Humans; D033181:Information Dissemination / Q000379:methods*; D020407:Internet; D015233:Models, Statistical; D011381:Programming Languages; D011634:Public Health; D015980:Public Health Practice; D011639:Public Opinion; D012044:Regression Analysis