This dissertation is organized in a traditional format while including three essays that address specific research questions. Essay 1 examined the relationship between physical activity and community engagement and their effect on mental well-being among older men and women. Data from National Health and Aging Trends Study (NHATS) from 2018 to 2020 were explored and the posited relationships were tested. This essay provides empirical support that older adults who are reasonably active and involved in the community have greater mental well-being than those who isolate themselves. Essay 2 provides insight into older adults' motivation to improve their physical activity through the use of a fitness tracker. The key finding from this study is that wearables, especially fitness trackers, can significantly facilitate increased physical activity. Essay 3 is a mixed-methods study to understand older adults' perception of the usefulness of fitness trackers and interaction with such devices. Findings suggest that to increase the adoption of fitness trackers among older adults, makers could improve the esthetics and quality of the wristband in addition to the battery life of the tracker.

Artificial intelligence (AI) and predictive modeling are tools used to diagnose a disease, determine how much a home is worth, estimate insurance risks, and detect fraud. AI and predictive modeling are so ubiquitous that they can be why one gets spam and why spam is automatically deleted. Information science integrates interdisciplinary elements of data-driven, behavioral, design, interpretive, and analytical research methodologies to design and understand interactions between digital media, information systems, and humans. This research focuses on the interaction between humans, AI, and predictive models. This research proposes a theoretical framework and a conceptual research model to understand the antecedents to reliance on AI and predictive modeling. The dissertation follows a traditional format that includes three studies. Study 1 employed a deductive quantitative research approach as a survey to model the relationship between trust in science and reliance on formal news sources. Study 2 employed a deductive quantitative research approach as a survey to understand the impact of framing questions and consider an alternative method of measuring society's reliance on science using predictive models. Study 3 employed a deductive quantitative research approach in the form of a survey to posit a new model based on the first two studies. This …

The purpose of this study was to collect design requirements from women engineers on artificial intelligence teammates such as Microsoft Teams, Slack, and Trello. A mixed methods research design was used for this study with an online survey and semi-structure interviews. The study results revealed design requirements from women engineers including solutions to sociotechnical issues that could arise from artificial intelligence teammates in the workplace. The results showed various ways women engineers collaborate in the workplace with and without artificial intelligence. Additionally, women engineers' attitude towards artificial intelligence was examined to identify if there was a correlation to self-efficacy. This research study fills a previous study gap that solicited design requirements from research scientists, by soliciting practitioners. Practitioners such as women engineers are underrepresented in the workplace, and they could benefit from an artificial intelligence teammate with their design requirements. Finally, this study contributes to the information science literature on collaborative information seeking, artificial intelligence design, and engineers' information seeking behaviors.

Research in scholarly communication is usually limited to the use and dissemination of scientific material by scholars. This excludes the transfer of knowledge from research producers to service providers. Some may argue the primary function of science is to investigate the conditions in the lab so everyday interactions with the environment are more effective and efficient. This is the underlying philosophy of the science of behavior analysis. Comprised of a basic science, an applied science and a philosophy the field of behavior analysis relies on research developments to inform effective practice. Guided by dissemination processes studied in information science, this investigation revealed the content layer in behavior analysis is primarily comprised of journal articles. Ninety four percent of the research artifacts cited in the current content layer are from journal articles. Other dissemination channels used to develop the behavior analytic content layer included scientific magazine articles, oral reports, dissertations and theses, and unpublished manuscripts. The information use environment for professionals in this field is very different than that of the scholars; most professionals do not have access to a university library. Therefore, the research producers are disseminating developments via communication channels some service providers cannot access. This investigation reveals the …

This study examines the background and qualifications of plaintiff and defense experts using the H-Index score as quantification of expert background and qualifications. The goal is to better understand the similarities and differences among the professionals offering paid expert witness testimony in mild traumatic brain injury (mTBI) civil litigation. In this quantitative study, descriptive statistics include the mean and standard deviation scores for the data to support examining measures of central tendency and variance, respectively. The study includes the use of logistic regression and the Wilcoxon signed-rank test, and their statistical assumptions were tested to determine whether they would be used or if it was more appropriate to use a non-parametric test. The study included two research questions: How do the qualifications of plaintiff and defense expert witnesses in mild traumatic brain injury civil litigation compare? and to what extent does a higher h-index correlate with a favorable litigation outcome in a mild traumatic brain injury case? The findings for the hypothesis tests associated with the research questions led to the acceptance of the null hypothesis in each test. There was a lack of asymptotic significance in Hypothesis 1 and a lack of significance in Hypothesis 2. The findings from …

Social media is considered a particularly conducive arena for hate speech. Counter speech, which is a "direct response that counters hate speech" is a remedy to address hate speech. Unlike content moderation, counter speech does not interfere with the principle of free and open public spaces for debate. This dissertation focuses on the (a) automatic detection and (b) analyses of the effectiveness of counter speech and its fine-grained strategies in user-generated web content. The first goal is to identify counter speech. We create a corpus with 6,846 instances through crowdsourcing. We specifically investigate the role of conversational context in the annotation and detection of counter speech. The second goal is to assess and predict conversational outcomes of counter speech. We propose a new metric to measure conversation incivility based on the number of uncivil and civil comments as well as the unique authors involved in the discourse. We then use the metric to evaluate the outcomes of replies to hate speech. The third goal is to establish a fine-grained taxonomy of counter speech. We present a theoretically grounded taxonomy that differentiates counter speech addressing the author of hate speech from addressing the content. We further compare the conversational outcomes of …

The research examines the relationship between cyber addiction (excessive use of the Internet, CA), information overload (IO), and assesses their impact on workplace productivity. A multi-methods approach is used employing the Internet Addiction Test (IAT) and a quantitative survey design to assess and test the stated hypothesis. The study used random sampling methods targeting 150 respondents from different information technology departments of various organizations. The study hypothesizes that CA and IO have a reciprocal association, which adversely affects workplace productivity and employee performance. From the findings, IAT scores increase with an associated possibility of reporting burnout, fatigue, and other components associated with CA and IO. Also, CA and IO were significantly correlated, as evaluated by the chi-square test, although the same approach did not yield significant associations between CA and perceived internet dependence. Other findings CA components, such as social media use, significantly associated with task postponement and burnout. As well, CA affected IO with substantial impacts on workplace productivity. The paper highlights managerial aspects that organizations should consider in optimizing the output of their staff. Recommendations include wellness programs, altering the leadership and management styles, and sensitizing the employees on the adverse effects caused by the two variables.

In this research the focus is on data-centric AI with a specific concentration on data quality evaluation and improvement for machine learning. We first present a practical framework for data quality evaluation and improvement, using a legal domain as a case study and build a corpus for legal argument mining. We first created an initial corpus with 4,937 instances that were manually labeled. We define five data quality evaluation dimensions: comprehensiveness, correctness, variety, class imbalance, and duplication, and conducted a quantitative evaluation on these dimensions for the legal dataset and two existing datasets in the medical domain for medical concept normalization. The first group of experiments showed that class imbalance and insufficient training data are the two major data quality issues that negatively impacted the quality of the system that was built on the legal corpus. The second group of experiments showed that the overlap between the test datasets and the training datasets, which we defined as "duplication," is the major data quality issue for the two medical corpora. We explore several widely used machine learning methods for data quality improvement. Compared to pseudo-labeling, co-training, and expectation-maximization (EM), generative adversarial network (GAN) is more effective for automated data augmentation, especially …

Indigenous communities around the world are losing their languages at accelerating rates to the effects of the climate crisis and global capitalism. To preserve samples of these languages facing endangerment and extinction, samples of language use (e.g., audio-video recordings, photographs, textual transcriptions, translations, and analyses) are created and stored in language archives: repositories intended to provide long-term preservation of and access to language materials. In recent years, archives of all kinds are considering their origins and audiences. With the emergence of the community paradigm of archiving framework, the roles of archivists, communities, and institutions are under re-examination. Language archives too are reflecting this trend, as it becomes more common for speakers of Indigenous languages (also known as language communities) to document and archive their own languages and histories. As the landscape of language archiving expands, we now see increased emphasis on the re-use of archival material, particularly to support language revitalization—efforts to increase and maintain the use of the language. There are calls for language documentation (and, by extension, language archiving) to prioritize revitalization efforts. This dissertation is a case study of one language archive collection: the Boro Language Resource in the Computational Resource for South Asian Languages (CoRSAL) archive. …

Accurately predicting the deck condition rating of a bridge is crucial for effective maintenance and repair planning. Despite significant research efforts to develop deterioration models, a nationwide model has not been developed. This study aims to identify an appropriate machine learning (ML) algorithm that can accurately predict the deck condition ratings of the nation's bridges. To achieve this, the study collected big bridge data (BBD), which includes NBI, traffic, climate, and hazard data gathered using geospatial information science (GIS) and remote sensing techniques. Two sets of data were collected: a BBD for a single year of 2020 and a historical BBD covering a five-year period from 2016 to 2020. Three ML algorithms, including random forest, eXtreme Gradient Boosting (XGBoost), and Artificial Neural Network (ANN), were trained using 319,404 and 1,246,261 bridge decks in the BBD and the historical BBD, respectively. Results showed that the use of historical BBD significantly improved the performance of the models compared to BBD. Additionally, random forest and XGBoost, trained using the historical BBD, demonstrated higher overall accuracies and average F1 scores than the ANN model. Specifically, the random forest and XGBoost models achieved overall accuracies of 83.4% and 79.4%, respectively, and average F1 scores of …

Although digital equity is a recognized challenge in our K-12 school system, there is little research in using a holistic framework to investigate pre-conditions necessary for K-12 students to participate in digital learning and online processes. A conceptual framework of students' digital opportunity (SDO) is developed to represent the essential components of digital connectivity. The four key components are broadband internet availability, broadband usage, digital device ownership, and speed quality. A composite measure of SDO was created to quantitatively represent and measure the differences across 3,138 counties in the United States. Furthermore, spatial autocorrelation was applied to evaluate if the distribution of the SDO score is associated with geographical characteristics at the county level. The result showed the presence of significant county-level clusters with concentrations of high or low SDO scores. While the spatial analysis provided evidence of where the gaps in digital opportunities are located, there are underlying factors at the micro level that would need further investigation. This study suggests a collective approach between private and public entities to address the K-12 digital equity issue. The necessary conditions presented in the SDO model must be addressed first in order to bring change to K-12 students and schools in …

School librarians create an atmosphere where learners feel empowered. Moreover, school library programming should support diversity, equity, and inclusive learning opportunities to facilitate student success. Thus, school librarians are expected to model and advocate for equitable learning spaces while considering the universal design for learning approach to improving accessibility, utilization, and relevance for all library patrons. Although it has been established that school library standards support diversity, equity, and inclusion (DEI), more is needed to know about the impact of a crisis on school library programming and services. In addition, extensive research has not been conducted to determine school librarians' responsiveness and strategies to provide services for their school communities during disruptive times. This study examines school librarians' perceptions of the opportunities and challenges encountered while endeavoring to engage in DEI practices during crises.

The word diaspora is currently understood as the large scale voluntary movement of people, along with capital and goods due to the mechanisms of globalization. Adopting a diaspora, gender and leisure perspective, this dissertation looked at the information and document experiences of a particular fan community of women belonging to the Indian diaspora and the online spaces created and occupied by them (fan fiction blogs which can be viewed as book clubs). The study also looked at memory making and documenting of the same as a part of document experience, resulting in what can be termed as "serendipitous memory archives." The blogs hosting fan fiction and the mediated practices they support were viewed as documents for the study. The online spaces were conceptualized as small worlds and the theoretical framework used for the study consisted of a preliminary model of a small world (based on literature review and my understanding of the world under study), information experience as a concept as well as document experience models. The results show that social ties play a big role in the information and document experience, while memory making and documenting of the same are also seen to happen as part of the document …

This study explored issues related to the adoption and implementation of electronic health record (EHR) systems including building the awareness, knowledge, and experience of physicians toward cyber hygiene. This study used a qualitative research method to assess (a) the barriers to EHR systems adoption and implementation in Kuwait and (b) the level of awareness, knowledge and experiences related to cyber hygiene practices in Kuwait. The findings of the study supported the conceptual framework used to guide the research of the factors impacting the adoption and implementation of EHR systems in Kuwait as well as explore the level of awareness, knowledge, and experience of physicians about both EHR systems and cyber hygiene. The results from the systematic literature review analysis identified seven major barriers. These are financial barriers, time, difficulty of using technology, lack of support, negative attitude, legal and ethical (policies), and cultural barriers. The findings from the semistructured interviews supported the literature findings and provided more in-depth insights into the structural and social issues affecting the adoption and implementation of EHR systems. Given that Kuwait is a member of the Gulf Cooperation Countries (GCC), the results from the literature analysis showed that the problems in Kuwait are similar to …

When people access online health information, unfortunately, they have access to both clinically accurate and inaccurate information that they may then utilize to make informed personal health decisions. This research fills a gap in the literature of online health communities as they relate to chronic obstructive pulmonary disease (COPD). The conduct of this research required a multi-phased and multi-method approach, best presented in three distinct essays. In Essays 1 and 2, data gathering within two online health communities specific to COPD allowed this study to address three research questions: (1) what are the information needs of COPD patients that result in their participation in online health communities; (2) what are the information sources offered to the participants in these online communities; and (3) is the information obtained via those communities credible. Essay 1 harvested data from a moderated website hosted by a non-profit organization for patients with COPD and Essay 2 harvested data from a non-moderated Facebook group also serving this unique group. Data Miner, a Chrome extension designed to extract data, was used to collect data, key words and themes which brought an understanding of the health information needs of participants and identified what health information sources were preferred. …

The traditional definition of tourism has been transformed by significant advancements in communication and information technology. The concept of Metaverse, derived from the words "meta" (meaning beyond) and "verse" (meaning universe), has redefined how people experience travel. This innovative concept combines virtual reality, augmented reality, and artificial intelligence to create virtually augmented spaces. However, the tourism industry should clarify and narrow down the definition of Metaverse and its intriguing concept for its successful adoption in the future. Thus, it is crucial to define Metaverse tourism and understand how users will accept it in the near future. This study aims to comprehend the technology behind Metaverse tourism, review current research on the topic, and identify the critical factors related to experiential Metaverse tourism. The paper also examines how computer self-efficacy, novelty seeking, subjective norm, job relevance, perceived usefulness, perceived ease of use, and perceived enjoyment can influence expected user satisfaction and behavioral intention, given the context of situational motivation. The findings have significant implications for theory and management, addressing various questions related to users' perceptions, expectations, design considerations, stakeholder preparations, and performance assessment of metaverse technology in tourism applications.

Social media information behavior is increasingly critical, impacting not only individuals and groups but the beliefs, values, and direction of society and culture. The purpose of this study was to investigate how persistent observation by members of the online network influences social media users' information behavior, resulting in the phenomenon of social noise. Data analytics, including LDA, LSA, and clustering methodologies, were performed but could not provide information about the users' motivations. Using an ethnographic approach, participant observations and interviews were conducted with Facebook users as they interacted with informational posts, and the data collected was coded using a recursive method. Four key constructs of social noise were identified, and sub-codes were assigned within each construct as patterns emerged, providing insight into the different facets of social noise. Additionally, in most instances more than one of the four constructs were present, layering their influence on the information behavior. Based on these findings, social media users are not always interacting with information based on true personal beliefs or desires; instead, concerns surrounding their personal image, relationships with others, core beliefs, and online conflict are influencing their observable information behavior. The results of this exploratory study provide a basis to further develop …

Subject of information entity is one of the fundamental concepts in the field of information science. Subject of any document represents its intellectual potential -- 'aboutness' of the document. Traditionally, subject (along with title and author) is the one of three major ways to access information, so subject metadata plays a central role in this process and the role is constantly growing. Previous research concluded that the larger bibliographic database is, the richer subject vocabularies and classification schemes are needed to support information discovery. Further, a high proportion of information objects are unretrievable without subject headings in metadata records. This exploratory study provides the analysis of the subject metadata in MARC 21 bibliographic records created in 2020; and develops understanding of the level and patterns of 'aboutness' representation in the MARC 21 bibliographic records. Study also examines how these records apply the recent RDA and MARC21 guidelines and features intended to support functionality in a Linked Data environment. Methods of Social Network Analysis were applied along with content analysis, to answer research questions of this study. Suggestions for future research, implications for education, and practical recommendations for library metadata creation and management are discussed.

Cultural heritage institutions, including galleries, libraries, museums, and archives are increasingly digitizing physical items and collecting born-digital items and making these resources available on the Web. Metadata plays a vital role in the discovery and management of these collections. Existing frameworks to identify and address deficiencies in metadata rely heavily on count and data-value based metrics that are calculated over aggregations of descriptive metadata. There has been little research into the use of traditional network analysis to investigate the connections between metadata records based on shared data values in metadata fields such as subject or creator. This study introduces metadata record graphs as a mechanism to generate network-based statistics to support analysis of metadata. These graphs are constructed with the metadata records as the nodes and shared metadata field values as the edges in the network. By analyzing metadata record graphs with algorithms and tools common to the field of network analysis, metadata managers can develop a new understanding of their metadata that is often impossible to generate from count and data-value based statistics alone. This study tested application of metadata record graphs to analysis of metadata collections of increasing size, complexity, and interconnectedness in a series of three related …

This dissertation examines the impact of trauma on information-seeking behaviors and decision-making processes. Essay 1 includes a qualitative analysis of the transcripts obtained from interviews with four military service members diagnosed with PTSD. The results showed that 75% of this small sample population exhibited addictive behavior that was presented in their information behaviors. All four members indicated that the excessive extent to which they seek information is related to the perceived importance of the information and their level of trust in the sources. Low trust in information sources increases the number of sources searched for validation in this population. Essay 2 involved the collection and analysis of survey data. The results of the stepwise backward regression show that two trauma variables (adult sexual assault, sudden fear) have a significant combined negative effect on decision-making in this population. The analysis and results of a different survey are presented in Essay 3. The stepwise logistic regression analysis results conducted on the summated scales developed showed a strong positive link between trust in scientific experts for scientific information and the dichotomous dependent variable trust in social media for news. The research conducted in this dissertation extends the understanding of how trauma affects people's …

This study's first goal is to investigate whether a 23-item multidimensional scale is a valid and reliable measure of benefits private club members perceive to be important. Seven theoretically plausible model structures are empirically tested: a unidimensional model, a two oblique first-order factors model, a four oblique first-order factors model, a two oblique second-order factors model, a bifactor model with two domain-specific factors, a bifactor model with four domain-specific factors, and two oblique bifactor models. The second goal is to examine the benefits members receive most often from their membership clubs. The multidimensional scale is based on four dimensions: member-to-employee relationship, member-to-member relationship, confidence, and reduced anxiety. Member-to-employee relationship and member-to-member relationship subscales are aligned with social benefits while confidence and reduced anxiety subscales are aligned with psychological benefits. The study participants (N = 114) were recruited through a commercial crowdsourcing platform, Prolific. The results of a Bayesian confirmatory factor analysis (BCFA) provided support for the two oblique bifactor models. Additionally, the social benefits and psychological benefits bifactor scales displayed acceptable reliability. A comparison of the means for each type of benefit revealed that no statistically significant differences existed between the general social benefits factor and the general psychological benefits …

Most training performance measurement tools rely heavily on quantitative metrics that do not consider factors impacting knowledge transfer and behavioral change such as social relationships and company culture. This study observed a training performance measurement tool for a major U.S.-based airline. Analysis of the measurement tool consists of: a pilot study providing a baseline for the current gaps in training performance measurement, a survey of flight attendants to understand how company cultural and social factors impact learning and knowledge transfer, and focus groups to provide an in-depth analysis of what the underlying company cultural and social factors are. Both quantitative and qualitative analysis were utilized to identify the impact of cultural factors and social relationships on performance measurement to provide in-depth understanding of the role of tacit knowledge transfer in the training environment. Results show that cultural factors such as empathy, coaching, and on-the-job training, negatively impact the accuracy of flight attendants' ability to measure learning and knowledge transfer. A second finding shows social factors, personality, and agreement, show a strong trend towards negatively affecting the ability to accurately measure learning and knowledge transfer. The proposed knowledge transfer measurement model was further modified to reflect the findings and the results …

In this study we explore the factors impacting physician patient interaction time and how these factors can be used to improve health knowledge transfer from physicians to patients. We also investigate how technology tools can be used to improve this interaction time. Physician patient interaction time is important because this is the time when both sides engage with each other, exchange information so that physicians understand their patients' health issues. Given the increasing health care costs and demand for physician time, over the years, this interaction time has been distracted due to many factors. It is important to explore these factors and provide some possible solutions, such as advanced knowledge management systems, such as knowledge portals. To identify the factors impacting this interaction time and the role of technology, we first identified the variables and then developed hypotheses. We used data from the surveys administered by the AHRQ and NCHS to test these hypotheses. We conducted correlation analyses to determine the factors that can be used to improve health knowledge transfer from physicians to patients and how technology tools can be used to improve physician patient interaction time. Our analyses indicate that the factors we identified to improve health knowledge …

The purpose of this study was to assess visual analytics technology acceptance and user experience among in vitro fertilization (IVF) consumers. The research aimed to show how visual analytics tools and technologies can be applied in the consumer space to enhance how users interpret healthcare success rate data. This exploratory user evaluation study utilized a quantitative dominant, mixed-methods approach with a convergent parallel design based on the data-validation variant. Survey data were collected from consumers who were currently seeking information about IVF treatment in the United States. The study findings indicated that the extended unified theory of acceptance and use of technology (UTAUT2) constructs of performance expectancy and hedonic motivation influenced consumer behavioral intention to use visual analytics technology, while effort expectancy did not. Further, the findings from the user experience and qualitative analyses indicated that there is strong support for consumer adoption of visual analytics technology for personal healthcare decision-making. These findings may help in the design and development of modern, interactive visualization tools that could be used to visualize public or private healthcare data for analysis by consumers. Stakeholders, including the US Centers for Disease Control and Prevention, the World Health Organization, and medical practitioners, may use the …