Date of Award

May 2017

Degree Type


Degree Name

Doctor of Philosophy (PhD)


Social Sciences


Kevin G. Crowston

Second Advisor

Padmal Vitharana

Subject Categories

Social and Behavioral Sciences



The exponential growth of the Internet in the past two decades has been accompanied by an increased interest by Internet users in communicating among each other electronically about all sorts of topics, including health-related issues. This increased interest in peer-to-peer communication for health topics raised lots of questions about the potential harmful effects of these communications on those participants who might take some health-related action without consulting with a doctor first. This potential problem has motivated the researcher to investigate how people with certain health conditions use health information that they obtain from online support groups.

Even though the understanding of how information is sought, retrieved, and ultimately used is a very important topic within information behavior research, information use is an area that has seen less study. For this reason, the researcher decided to investigate information use within online consumer health support groups using a content analytical approach. The study had two specific objectives: (a) to describe what some of the cognitive, affective, and behavioral actions that consumers indicate they had taken based on information shared within some of the online support groups to which they belong; and (b) to determine if the uses given to information follow any pattern among different chronic conditions being studied with relation to the type of questions asked, the type of reply messages, and the health-related content of the messages.

Methodologically, the study used computer-mediated discourse analysis to guide collection of trace data that came from archives of selected online discussion boards related to the three chronic conditions chosen for the study. For data to be part of the study, the presence of interactions with indications of usefulness was necessary. Then, through content analysis, the data was coded using several classification schemas found in the literature, some of them in their original form, others adapted to fit this research purpose. These schemas looked into the types of questions asked, the functions of the reply messages, the type of medical content of the posted messages, and the type of use given to the information. Once all the data was processed, the researcher looked for patterns among the different variables and across the different gender-based chronic conditions.

Results of the analysis show that the message characteristics of content type, function of reply messages, and question types, have a significant relationship with the types of conditions. Message characteristics also show a significant relationship with the cognitive, affective, and behavioral information uses. Discussions of the results as well as some alternatives for future research are presented.

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Open Access