Support vector machines (SVMs) are a set of supervised learning methods that have recently been applied for structural damage detection due to their ability to form an accurate boundary from a small amount of training data. During training, they require data from the undamaged and damaged structure. The unavailability of data from the damaged structure is a major challenge in such methods due to the irreversibility of damage. Recent methods create data for the damaged structure from finite element models. In this thesis we propose a new method to derive the dataset representing the damage structure from the dataset measured on the undamaged structure without using a detailed structural finite element model. The basic idea is to reduce the values of a copy of the data from the undamaged structure to create the data representing the damaged structure. The performance of the method in the presence of measurement noise, ambient base excitation, wind loading is investigated. We find that SVMs can be used to detect small amounts of damage in the structure in the presence of noise. The ability of the method to detect damage at different locations in a structure and the effect of measurement location on the sensitivity of the method has been investigated. An online structural health monitoring method has also been proposed to use the SVM boundary, trained on data measured from the damaged structure, as an indicator of the structural health condition.

With the expansion of online communities, extant research in multiple disciplines has attempted to investigate its adoption and use among individuals. However, the biggest challenge encountered by managers of these communities is supplying knowledge, particularly, the willingness to share knowledge among the members. It is extremely important to maintain committed members in terms of active participation. Yet their level of participation might vary based on some social, behavioral and environmental factors that eventually affect their intentions on whether to participate actively or not, in fact some users choose to discontinue participating totally in the community. Cancers figure among the leading causes of morbidity and mortality worldwide, with approximately 14 million new cases and 8.2 million cancer related deaths in 2012. The number of new cases is expected to rise by about 70% over the next 2 decades. Among men, the 5 most common sites of cancer diagnosed in 2012 were lung, prostate, colorectal, stomach, and liver cancer. According to the world cancer report, among women the 5 most common sites diagnosed were breast, colorectal, lung, cervix, and stomach cancer. For this reason, there is an ever-increasing need to establish communities to offer empathic support to patients. Though peer support groups have been known to offer adequate support to patients with cancer and are considered to be an important complement to the formal health care system, however, practical barriers such as time, mobility and geography limit their use, this is where the online communities serve an advantage, as they have the potential to overcome barriers posed by regular offline communities. To achieve its objectives, this study mainly adopts the Social cognitive theory and two components of the social influence theory. According to the SCT, user behaviour is influenced by two factors: personal cognition and environment. Social influence model postulates that individual behaviour in a community can be affected by the social environment and three factors constitute this, they are compliance, identification and internalization. The study aims to provide insights on how and why patients diagnosed with cancer (and their relatives) seek social support using the Internet and social media. In particular, we seek to understand the motivation for joining these groups and the values derived from the community for the users both active and non-active.

Online Health Seeking (OHS) is widespread and widely studied, but its ideal fit in healthcare is still unclear. OHS is seemingly emblematic of patient self-interest and control and is an intuitive fit with the tenets of patient-centered care (PCC). Researchers have made only a few attempts to evidence or leverage this connection, focusing instead on describing the figures and typical characteristics of OHS. Finding, consuming and sharing online health and wellness information is one of the common online activities, and consumers are generally satisfied with their results despite using simple and error-prone search strategies. Physicians are interested in their patients' OHS, but for a variety of constraints including time, compensation and traditional roles in medicine, most patient OHS goes unshared with doctors. Healthcare facilitators, a relatively new class of health professional that works to bridge the gap between their client's health and personal life, may be an ideal partner for patients in OHS. In this dissertation I share my investigation of the OHS-PCC connection, presenting a case study of a type of healthcare facilitator that has embraced OHS. By studying OHS, I was also able to contribute to the collaborative information seeking (CIS) community. CIS theory and social search tools have pointed to social factors that can influence the entire process of information seeking. In this dissertation I argue that nearly any social search design can be seen as situated or embedded in a unique socio-environmental context. I suggest that social search tools can be used as probes to understand the environment, and that interactions with a search tool can illustrate phenomena far beyond direct search motivations and goals. I also hypothesize that social search field studies can produce changes in their environment, producing changes in user relationships outside of the experimental search system. My study of OHS is an opportunity to test these hypotheses by creating a collaborative search tool that seeks to use OHS as a tool to improve patient-provider relationships. In this dissertation I present the results of a series of field studies at a local clinic that centers on a unique form of health facilitator. Drawing on several formative investigations and related work I synthesize design guidelines for a collaborative OHS tool and describe Snack, a collaborative search tool for OHS customized to my field site. I also present results from Snack's field study and an analysis of email messages between advisors and clients at the clinic. My results show that these health facilitators embraced OHS as a tool to guide and connect with their clients, but fell from this practice after a change at their clinic. After analyzing these results I discuss what makes health facilitators good OHS partners and cover implications for future OHS-based interventions. I also report the positive connections I found between OHS and other quality of care indicators like patient-centered care and the Multidimensional Health Locus of Control. Finally, I consider social search's utility as a probe and intervention in light of my results.

Introduction: There is an increased acceptance and demand for online and mobile health (mHealth) interventions to support physical and mental health problems. However, the uptake and engagement of these interventions is relatively low and the evidence base for these interventions requires continual updating in line with technological advances. A systematic review was conducted, focusing on anxiety and depression, to explore the existing evidence base of both physical health and mental health mobile applications. The first research paper explores the acceptability of mHealth interventions for both mental health and physical health problems. The final research paper explores use and strategies when searching for mental health information online. Additionally, perceived quality, sentiment and barriers to online health information was explored. Methods: Studies were identified by searching for articles published between January 2008 and January 2016. Databases included: PsycINFO, MEDLINE, CINAHL PLUS and the Cochrane Central Register of Controlled Trials for 2016. In the research articles, 218 people completed an online survey in January 2016 exploring, online health seeking for mental health and physical health problems, and acceptability of mHealth interventions. Sentiment of online health resources was explored by extracting 432 individual tweets from Twitter. Results: The systematic review revealed twenty-seven studies for inclusion; 10 with a physical health focus and 17 with a mental health focus. Targeted depression applications have the superior evidence base; however, no firm conclusions can be made regarding interventions that targeted physical health, or those measuring anxiety. The first research paper found that face-to-face therapy would more likely meet expectations for treatment of both physical and mental health problems compared to mHealth interventions. Computerised interventions were more likely to meet expectations than mobile applications. Expectations of treatment were higher for the treatment of mental health problems than physical health problems. The second research paper found that a large proportion of the public use the internet to search for information on mental health, with half citing it as their primary source for mental health information. The online survey found that the quality of mental health information available on the internet was rated favourably, compared to mobile applications. Overall, the sentiment towards specific online mental health resources was generally positive. Conclusions: Research into online and mHealth interventions has developed considerably in recent years in line with advances in technology. These interventions have the potential to be an effective treatment of common mental health problems. The systematic review highlighted that depression applications are more established and effective than applications targeting anxiety. The first research paper suggests that mHealth interventions fall short of public expectations for treatment of health problems. The final research paper reflects that the perceived quality of online mental health information is rated favourably. However, many barriers still limit uptake. Future research could focus on continually developing and evaluating evidence based online and mHealth interventions and the outcome of this study suggests that incorporating them more widely into existing care systems, alongside face to face interventions could increase the public’s confidence in these interventions.

Finding health information online continues to help patients understand new symptoms. However, incomplete information or advice that errs on the site of caution can cause distress or anxiety and prompt visits to a doctor. Cyberchondria, a new phenomenon, is defined as excessive compulsive searching for health information online that leads to distress and increase utilization of healthcare services. Grounded theory guided the conception of a mixed method study to investigate cyberchondria and symptom appraisal within Emergency Departments. A questionnaire and interviews were used to collect data from patients visiting a local Emergency Room. Results showed 63.3% of respondents looked up their symptoms online before their visit, and exhibited higher levels of cyberchondria and health anxiety than those who did not (p .001, p .004), and that health information consulted online can impact the decision to seek out immediate care. Strategies are needed to improve and promote quality online sources to benefit both seekers and services.

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The current dissertation provides an examination of health information technology (HIT) by analyzing big datasets. It contains two separate essays focused on: (1) the evolving intellectual structure of the healthcare informatics (HI) and healthcare IT (HIT) scholarly communities, and (2) the impact of social support exchange embedded in social interactions on health promotion outcomes associated with online health community use. Overall, this dissertation extends current theories by applying a unique combination of methods (natural language processing, machine learning, social network analysis, and structural equation modeling etc.) to the analyses of primary datasets. The goal of the first study is to obtain a full understanding of the underlying dynamics of the intellectual structures of HI and its sub-discipline HIT. Using multiple statistical methods including citation and co-citation analysis, social network analysis (SNA), and latent semantic analysis (LSA), this essay shows how HIT research has emerged in IS journals and distinguished itself from the larger HI context. The research themes, intellectual leadership, cohesion of these themes and networks of researchers, and journal presence revealed in our longitudinal intellectual structure analyses foretell how, in particular, these HI and HIT fields have evolved to date and also how they could evolve in the future. Our findings identify which research streams are central (versus peripheral) and which are cohesive (as opposed to disparate). Suggestions for vibrant areas of future research emerge from our analysis. The second part of the dissertation focuses on comprehensively understanding the effect of social support exchange in online health communities on individual members’ health promotion outcomes. This study examines the effectiveness of online consumer-to-consumer social support exchange on health promotion outcomes via analyses of big health data. Based on previous research, we propose a conceptual framework which integrates social capital theory and social support theory in the context of online health communities and test it through a quantitative field study and multiple analyses of a big online health community dataset. Specifically, natural language processing and machine learning techniques are utilized to automate content analysis of digital trace data. This research not only extends current theories of social support exchange in online health communities, but also sheds light on the design and management of such communities.

Today the amount of online medical information sources in Swedish is steadily increasing. The information is convenient and always at hand. People who turn to Google and other search engines are, however, not always knowledgeable about how to identify trustworthy information, or how search algorithms work. The main purpose of this study is to :ind out how Swedish students in the ages of 18-35 search for medical information online. One aspect of this is to gain a better understanding of how they navigate the internet, and how they prioritize and value different information sources. We also look at what sources they turn to for medical information and whether source credibility is crucial in their choices. Our study is based on an online survey at Umeå University. The survey was conducted among eight different study programs with students in the ages of 18-35. In total, we received 305 responses, of which 163 (53,4%) were women, 139 (45,6%) were men, and 1% de:ined as others. The main conclusion of this study is that the target group is most likely to turn to information sites provided by authorities. These sites are considered to be the most trustworthy. The study also showed that the target group was well aware of Sweden’s biggest online doctors, Kry in particular, and rated them as trustworthy as well. The target group would, however, not turn to these sites for medical information. We can also notice that the target group consider themselves to be critical of information online and good at evaluating source credibility.

Background. Lung cancer is the leading cause of cancer deaths worldwide. Low survival rates have been attributed to delays to diagnosis, and some patients report having symptoms for several months before presenting to health services. Strategies are needed to encourage timely help-seeking. The Web is increasingly used as a health information source. Aim. The aim of this thesis is to explore whether the Web plays a role in help-seeking behaviour of people with lung cancer prior to diagnosis, and how the Web can be utilised to encourage earlier presentation to health services for symptomatic people. Systematic review. To begin, I carried out a systematic review of the literature (N=34), which highlighted a scarcity of research on Web use for symptom appraisal among cancer populations. Mixed-methods study. I conducted a survey with recently diagnosed (6 months or less) lung cancer patients (N=113). Based on survey responses, I purposively selected a sub-sample of patients and their family/friends ("proxies") for semi-structured interviews (N=33). In the survey, 20.4% of participants reported they or proxies had researched their condition online before the diagnosis. Interview results suggest perceived impacts of online information on symptom appraisal, forming the decision to seek help, and on interactions with healthcare professionals. Intervention development and evaluation. Based on my findings, I developed a Web-based intervention. The intervention provides tailored information about lung cancer, and uses components based on the Theory of Planned Behaviour ("TPB-components") to encourage earlier help-seeking. This intervention was tested in an online feasibility study (N=130), and subsequently in an online randomised controlled trial (N=212) with a factorial design to test main and interaction effects of tailoring and TPB-components. The feasibility study and first trial helped identify methodological issues which were addressed in a second trial with a mixed factorial design. This trial (N=253) indicated that the self-reported likelihood of visiting a doctor increased significantly by 11.8% from before to after viewing study information (p < 0.001), but no effects of tailoring or TPB-components were found. When examining only those aged ≥50 years, who are at highest risk of lung cancer, those receiving tailored information reported an increase of 13.2% in likelihood of seeking help, compared to 3.2% in the untailored group (p=0.01). Participants aged 50+ receiving the TPB-component reported a larger increase (13.8%) than those who did not receive the TPB-component (5.2%), but this did not meet the significance criterion (p=0.054). Conclusions. According to patients' perceptions, the Web can impact on processes in the appraisal, help-seeking and diagnostic interval leading up to diagnosis. Presentation of information about symptoms and risk factors online can produce significant effects on self-reported likelihood of seeking help. These findings indicate that there is potential for the Web to be utlised in the endeavour to educate the public about symptoms and to promote earlier presentation to health services, but due to small effects and differential dropout in this study, further research is required.