Online health communities (OHCs) have been increasingly popular among patients with chronic or life-threatening illnesses for the exchange of social support. Contemporary research of OHCs relies on methods and tools to handle analytics of massive user-generated content at scale to complement traditional qualitative analysis. In this thesis, we aim at advancing the area of research by providing computational tools and methods which facilitate automated content analysis, and by presenting applications of these tools to investigating member characteristics and behaviors. We first provide a framework of conceptualization to systematically describe problems, challenges, and existing solutions for OHCs from a social support standpoint, to bridge the knowledge gap between health psychology and informatics. With this framework in hand, we define the landscape of online social support, summarize current research progress of OHCs, and identify research questions to investigate for this thesis. We then build a series of computational tools for analyzing OHC content, relying on techniques of machine learning and natural language processing. Leveraging domain-specific features, our tools are tailored to handle content analysis tasks on OHC text effectively. Equipped with computational tools, we demonstrate how characteristics of OHC members can be identified at scale in an automated fashion. In particular, we build up multi-dimensional descriptions for patient members, consisting of what topics they focus on, what sentiment they express, and what treatments they discuss and adopt. Patterns of how these member characteristics change through time are also investigated longitudinally. Finally, relying on computational analytics, members' behaviors of engagement such as debate and dropping-out are identified and characterized. Studies presented in this thesis discover static and longitudinal patterns of member characteristics and engagement, which are potential research hypotheses to be explored by health psychologists and clinical researchers. The thesis also contributes to the informatics community by making computational tools, lexicons, and annotated corpora available to facilitate future research.

As the development of medical treatments and the increase in longevity of human life interface with the rising cost of medical care, the issue of quality of life appears to be coming to the forefront in understanding how health care decisions will best be realized for patients. Ethical questions relating to matters such as cost-effective economics, physician-assisted suicide, and quantity of life versus quality of life make the construct of quality of life even more important to ascertain.Quality of life can be an elusive construct to define as well as a difficult one to measure; however, recent literature has shown promising trends. Many quality-of-life measures have been developed in recent years. Initially these measures focused on life satisfaction in general. Then instruments for healthrelated concerns were developed. In the last decade such measures have become more specific as several have emerged to identify the quality-of-life experience regarding a particular illness, such as cancer. The current step is the development of measures for specific populations in oncology. Another trend is the move from objective to subjective measures of assessment. A third trend is movement toward a multidimensional perspective, with the latest addition being the inclusion of a spiritual domain.This project explored the unique experience of cancer patients with recurrent or metastatic disease by utilizing qualitative methodology to describe common themes which emerged from the data. Focus group sessions centered around defining quality of life and discussing the factors that diminish or enhance a meaningful quality of life. A unique contribution of this study was the involvement of the participants as co-researchers in the analysis of the data. Thirteen central themes were identified: control, attitude, humor, death, gratitude, faith, fear, pain, social comparison, social support, financial concerns, information and knowledge, and the focus group experience. The findings confirmed the recent trends in quality-of-life research--multidimensionality, subjectivity, and the uniqueness of a specific cancer population, those with recurrent or metastatic disease. With this elicitative data, future research could include the development of a quality-of-life instrument for this population of oncology patients with more advanced cancer. / Department of Counseling Psychology and Guidance Services

Indiana University-Purdue University Indianapolis (IUPUI) / The presence of a chronic pain condition can have a profound impact on one’s self-concept. Some individuals may have had to make major lifestyle changes. As a result, some people may start to define themselves in terms of their pain, such that their self-schema and pain-schemas become intertwined in a process termed schema-enmeshment. It is thought that schema-enmeshment is related to psychological distress making it a prime target for intervention. Little research has been conducted on interventions to reduce schema-enmeshment. Acceptance-based interventions may be especially appropriate in reducing schema-enmeshment or the connection between self and illness symptoms as these interventions tend to emphasize learning to live with pain and other symptoms and to work toward important life goals rather than continually fighting against the condition and allowing it to control their life. This study is a randomized trial comparing Acceptance and Commitment Therapy (ACT) to education about pain management in a sample of women with Fibromyalgia Syndrome (FMS). The primary aim of this study was to assess the efficacy of ACT in reducing schema-enmeshment between self and pain, as well as enmeshment between self and other symptoms and FMS as a whole. In addition, this study also explored the role of pain acceptance, specifically activity engagement as a mediator of the relationship between treatment group membership and changes in schema-enmeshment. The data was analyzed as an intent-to-treat analysis using the “last measure carried forward” method. Results indicated that the ACT group reported statistically significant differences in self schema-enmeshment with FMS, fatigue, and cognitive symptoms, but not with pain, following the intervention, compared to the educational control group. In each of these cases, the ACT group experienced greater reductions in schema-enmeshment compared to the education group. Interestingly, no statistically significant differences were observed for schema-enmeshment with pain. Statistically significant group differences were also observed for acceptance of pain following the intervention. Finally, a mediational model in which changes in activity engagement (a form of pain acceptance) served as the mediator of the relationship between treatment group and changes in schema-enmeshment with FMS was tested. The model was tested using a bootstrapping method, and results revealed a trend toward a significant indirect effect of changes in activity engagement leading to changes in schema-enmeshment with FMS. Taken together, the results of this study indicate that ACT may be a promising intervention for targeting maladaptive beliefs about the self in relation to illness, especially schema-enmeshment of self with illness and illness symptoms. Additionally, there is evidence that ACT may target key constructs such as activity engagement, which may be related to other cognitive and behavioral changes. Future directions for research and clinical practice related to ACT as an intervention for FMS are discussed in depth.