Collaborative Help for Individualized Problems: Learning from the MythTV User Community and Diabetes Patient Support Groups.

As information technology increasingly becomes part of everyday life, new opportunities arise for aggregating people’s experiences and knowledge. Collaborative help can utilize collective experience and knowledge to benefit everyday problem solving activities. However, current help systems often limit their focus to common and active problems (e.g., Frequently Asked Questions), making it difficult for users to find answers to the problems that are uncommon and individualized. In my dissertation, I address how individualized problems can be better supported through collaborative help. My dissertation contributes to existing conversations around collaborative help, especially challenges in information reuse and contextualization. I further expand discussions around the role of temporal information during expertise sharing for finding solutions to individualized problems. In order to study this, I examined two research sites using an interpretivist approach (Strauss & Corbin, 1990): the MythTV user community and diabetes patient support groups. Because problems are often individualized for members of both communities, these sites serve as excellent places to examine the research problem. I discuss three key findings that are critical for understanding how individualized problems are solved in community-based collaborative help systems. First, operationalizing experiences is critical for sharing executable solutions and context. Operationalized experiences are not only about the objectification and easy transfer of tacit knowledge (Ambrosini & Bowman, 2002), but generate knowledge that can be directly re-used. Second, operationalization process inevitably fails to capture practices “simultaneously embedded in various processes” (Ackerman & Halverson, 2000) during maintenance activities, be it maintaining MythTV or diabetes. However, the breakdown of operationalization process helps each community member learn how to manage individualized situations as they occur. Lastly, operationalization process needs to take place within the larger context of sharing trajectories. By comparing, aligning, and collaging pieces of individual trajectories, community members collectively expand their knowledge about managing MythTV or diabetes over time. Through continual sharing of maintenance trajectories, members reduce uncertainty about the future, take preventative actions, and reflect on the past to revise their practices.Ph.D.InformationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/89774/1/jinah_1.pd

"This Girl is on Fire": Sensemaking in an Online Health Community for Vulvodynia

Online health communities (OHCs) allow people living with a shared diagnosis or medical condition to connect with peers for social support and advice. OHCs have been well studied in conditions like diabetes and cancer, but less is known about their role in enigmatic diseases with unknown or complex causal mechanisms. In this paper, we study one such condition: Vulvodynia, a chronic pain syndrome of the vulvar region. Through observations of and interviews with members of a vulvodynia Facebook group, we found that while the interaction types are broadly similar to those found in other OHCs, the women spent more time seeking basic information and building individualized management plans. They also encounter significant emotional and interpersonal challenges, which they discuss with each other. We use this study to extend the field's understanding of OHCs, and to propose implications for the design of self-tracking tools to support sensemaking in enigmatic conditions

Answers to Health Questions: Internet Search Results Versus Online Health Community Responses

Background: About 6 million people search for health information on the Internet each day in the United States. Both patients and caregivers search for information about prescribed courses of treatments, unanswered questions after a visit to their providers, or diet and exercise regimens. Past literature has indicated potential challenges around quality in health information available on the Internet. However, diverse information exists on the Internet—ranging from government-initiated webpages to personal blog pages. Yet we do not fully understand the strengths and weaknesses of different types of information available on the Internet. Objective: The objective of this research was to investigate the strengths and challenges of various types of health information available online and to suggest what information sources best fit various question types. Methods: We collected questions posted to and the responses they received from an online diabetes community and classified them according to Rothwell’s classification of question types (fact, policy, or value questions). We selected 60 questions (20 each of fact, policy, and value) and the replies the questions received from the community. We then searched for responses to the same questions using a search engine and recorded the Results: Community responses answered more questions than did search results overall. Search results were most effective in answering value questions and least effective in answering policy questions. Community responses answered questions across question types at an equivalent rate, but most answered policy questions and the least answered fact questions. Value questions were most answered by community responses, but some of these answers provided by the community were incorrect. Fact question search results were the most clinically valid. Conclusions: The Internet is a prevalent source of health information for people. The information quality people encounter online can have a large impact on them. We present what kinds of questions people ask online and the advantages and disadvantages of various information sources in getting answers to those questions. This study contributes to addressing people’s online health information needs

Answers to Health Questions: Internet Search Results Versus Online Health Community Responses

Background: About 6 million people search for health information on the Internet each day in the United States. Both patients and caregivers search for information about prescribed courses of treatments, unanswered questions after a visit to their providers, or diet and exercise regimens. Past literature has indicated potential challenges around quality in health information available on the Internet. However, diverse information exists on the Internet—ranging from government-initiated webpages to personal blog pages. Yet we do not fully understand the strengths and weaknesses of different types of information available on the Internet. Objective: The objective of this research was to investigate the strengths and challenges of various types of health information available online and to suggest what information sources best fit various question types. Methods: We collected questions posted to and the responses they received from an online diabetes community and classified them according to Rothwell’s classification of question types (fact, policy, or value questions). We selected 60 questions (20 each of fact, policy, and value) and the replies the questions received from the community. We then searched for responses to the same questions using a search engine and recorded the Results: Community responses answered more questions than did search results overall. Search results were most effective in answering value questions and least effective in answering policy questions. Community responses answered questions across question types at an equivalent rate, but most answered policy questions and the least answered fact questions. Value questions were most answered by community responses, but some of these answers provided by the community were incorrect. Fact question search results were the most clinically valid. Conclusions: The Internet is a prevalent source of health information for people. The information quality people encounter online can have a large impact on them. We present what kinds of questions people ask online and the advantages and disadvantages of various information sources in getting answers to those questions. This study contributes to addressing people’s online health information needs

People's Perceptions Toward Bias and Related Concepts in Large Language Models: A Systematic Review

Large language models (LLMs) have brought breakthroughs in tasks including translation, summarization, information retrieval, and language generation, gaining growing interest in the CHI community. Meanwhile, the literature shows researchers' controversial perceptions about the efficacy, ethics, and intellectual abilities of LLMs. However, we do not know how lay people perceive LLMs that are pervasive in everyday tools, specifically regarding their experience with LLMs around bias, stereotypes, social norms, or safety. In this study, we conducted a systematic review to understand what empirical insights papers have gathered about people's perceptions toward LLMs. From a total of 231 retrieved papers, we full-text reviewed 15 papers that recruited human evaluators to assess their experiences with LLMs. We report different biases and related concepts investigated by these studies, four broader LLM application areas, the evaluators' perceptions toward LLMs' performances including advantages, biases, and conflicting perceptions, factors influencing these perceptions, and concerns about LLM applications

The Impact of Automatic Pre-annotation in Clinical Note Data Element Extraction - the CLEAN Tool

Objective. Annotation is expensive but essential for clinical note review and clinical natural language processing (cNLP). However, the extent to which computer-generated pre-annotation is beneficial to human annotation is still an open question. Our study introduces CLEAN (CLinical note rEview and ANnotation), a pre-annotation-based cNLP annotation system to improve clinical note annotation of data elements, and comprehensively compares CLEAN with the widely-used annotation system Brat Rapid Annotation Tool (BRAT). Materials and Methods. CLEAN includes an ensemble pipeline (CLEAN-EP) with a newly developed annotation tool (CLEAN-AT). A domain expert and a novice user/annotator participated in a comparative usability test by tagging 87 data elements related to Congestive Heart Failure (CHF) and Kawasaki Disease (KD) cohorts in 84 public notes. Results. CLEAN achieved higher note-level F1-score (0.896) over BRAT (0.820), with significant difference in correctness (P-value < 0.001), and the mostly related factor being system/software (P-value < 0.001). No significant difference (P-value 0.188) in annotation time was observed between CLEAN (7.262 minutes/note) and BRAT (8.286 minutes/note). The difference was mostly associated with note length (P-value < 0.001) and system/software (P-value 0.013). The expert reported CLEAN to be useful/satisfactory, while the novice reported slight improvements. Discussion. CLEAN improves the correctness of annotation and increases usefulness/satisfaction with the same level of efficiency. Limitations include untested impact of pre-annotation correctness rate, small sample size, small user size, and restrictedly validated gold standard. Conclusion. CLEAN with pre-annotation can be beneficial for an expert to deal with complex annotation tasks involving numerous and diverse target data elements

The Relation between Birth Weight and Insulin Resistance in Korean Adolescents

Low birth weight is associated with insulin resistance and type 2 diabetes in adults. The fetal programming hypothesis has shown that insulin resistance and its associated metabolic disturbances result from a poor gestational environment, for which low birth weight is a surrogate. An at-home questionnaire survey was performed on 660 middle school students (12-15 years) in Seoul, Korea, and 152 cases were randomly selected based on their birth weight. Subjects were divided into three groups according to birth weight. We recorded their birth weight and measured their current anthropometric data, blood pressure, lipid profile, HOMA-IR, and HOMA-β, and compared these parameters among the groups. The relation of birth weight to physiological characteristics in adolescence was examined. Systolic blood pressure, lipid profiles, and fasting plasma glucose, HOMA-β were not significantly different among the groups, but diastolic blood pressure was lower in the third tertile. Insulin, C-peptide, and HOMA-IR were higher in the lower birth weight tertile. After adjustment for confounding factors, birth weight was inversely related to diastolic blood pressure, insulin, C-peptide, and HOMA-IR. We conclude that low birth weight may predict the risk of the insulin resistance and its progression over age, and that adequate gestational nutrition is therefore necessary to prevent low birth weight

Characteristics of Type 2 Diabetes in Terms of Insulin Resistance in Korea

The aim of this study was to assess the implications of insulin resistance on the clinical and biochemical profiles of Korean type 2 diabetic patients. 122 patients with type 2 diabetes underwent a short insulin tolerance test to assess insulin resistance. Subjects were classified in tertiles according to ISI (insulin sensitivity index), and the tertile I (the insulin-resistant group) and tertile III (the insulin-sensitive group) clinical and biochemical parameters were compared. Age, waist circumference (WC), systolic blood pressure (SBP), HbA1c, body fat content, and fasting plasma glucose were significantly higher in tertile I than tertile III (all p < 0.05). The frequency of hypertension and family history of cerebrovascular disease (CVD) were greater in tertile I than III (p < 0.05). To evaluate the factors affecting ISI, multiple regression was performed, and age, WC, SBP, HbA1c, and body fat content were found to be independently related to insulin resistance (p < 0.05). Old age, hypertension, central obesity, and poor glycemic control were identified as clinical parameters of insulin resistance in Korean type 2 diabetic patients

Attachment-Informed Design: Digital Interventions That Build Self-Worth, Relationships, and Community in Support of Mental Health

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/176786/1/2023_DIS_Attachment.pdfSEL