Online health support groups are popular, being used by almost 2/3 of American adults. If these groups are effective, it is because of the conversations that are their ďactive ingredient.Ē The overall goals of the proposed research are to clarify how the conversational dynamics of online cancer support groups influence partici-pantsí health quality of life and to improve the operations of these groups.
Our first goal is to understand how conversations in online cancer support groups produce social support at the level of the conversational episode. Our research will examine the dynamics of peer-to-peer in-teraction that lead these groups to make available different amounts and types of social support. To achieve this goal, we will conduct longitudinal studies using tens of thousands of archived conversational exchanges in online cancer support groups. Our second goal is to understand the impact of online social support on (a) membersí commitment to the group, as indicated by their willingness to remain in it and contribute to it both as information recipients and information providers, and (b) their health quality of life, as indicated by their self-reported distress, depression, and experienced pain. Our studies of commitment will involve quantitative life history analyses of group members who do and do not become active consumers and/or sources of social support. Our studies of health quality of life will involve panel regression analyses predicting changes in health quality based on the social support that participants exchange. Our third goal is to develop a suite of automated content analysis tools (the Analystís Helper), using text mining and language processing technol-ogy, to facilitate fast and accurate coding of conversations in online support groups. Such tools are needed be-cause analyzing conversational exchanges in online groups is not practical with hand-coding of messages or dictionary-based automated content-analysis tools. The Analystís Helper will enable health researchers to ana-lyze large corpora of conversational interactions in novel ways (e.g., by identifying the types of support that people seek and receive) and will be the basis of interventions to improve support groups. Finally, our fourth goal is to use the Analystís Helper to identify helpful and harmful conversations in online support groups and then to develop interventions for improving the training of support-group facilitators and reducing problematic conversations between support-group members.
Health support groups can yield substantial benefits for their members, but the social processes responsible for these benefits need to be specified. The proposed research will utilize theoretically-driven studies to clarify the conversational dynamics underlying the effectiveness of online cancer support groups, will create state-of-the-art tools for analyzing interactions in such groups, and will build interventions for improving group effectiveness. Identifying how communication in online cancer support groups influences participantsí commitment and health quality of life will have both theoretical and applied payoffs. Moreover, creating tools for analyzing large corpora of conversational data will facilitate the work of researchers interested in conversational behavior in other kinds of online groups. Finally, the proposed research will clarify the determinants of fundamental group processes (e.g., member commitment) that are critical to the success of offline as well as online groups.
The proposed work is innovative in several important ways. First, it tests theoretically-interesting questions in the context of online groups that matter deeply to large numbers of people, both cancer victims and their loved ones. Second, it focuses on a critical, but neglected, mechanism underlying the effectiveness of online cancer support groups, namely conversational dynamics between group members. Third, it provides a sophisticated set of methodological tools (the Analystís Helper) for analyzing conversations in online groups and enhancing the effectiveness of these groups. And, fourth, it benefits from the expertise of experienced investigators from a range of disciplinary backgrounds, including social, clinical, and health psychology and computational linguistics.