Context: Colorectal cancer (CRC) surgical treatment delay (TD) has been associated with mortality and morbidity; however, disparities by TD profiles are unknown. Objectives: This study aimed to identify CRC patient profiles of surgical TD while accounting for differences in sociodemographic, health insurance, and geographic characteristics. Design: We used latent class analysis (LCA) on 2005-2015 Tennessee Cancer Registry data of CRC patients and observed indicators that included sex/gender, age at diagnosis, marital status (single/married/divorced/widowed), race (White/Black/other), health insurance type, and geographic residence (non-Appalachian/Appalachian). Setting: The state of Tennessee in the United States that included both Appalachian and non-Appalachian counties. Participants: Adult (18 years or older) CRC patients (N = 35 412) who were diagnosed and surgically treated for in situ (n = 1286) and malignant CRC (n = 34 126). Main Outcome Measure: The distal outcome of TD was categorized as 30 days or less and more than 30 days from diagnosis to surgical treatment. Results: Our LCA identified a 4-class solution and a 3-class solution for in situ and malignant profiles, respectively. The highest in situ CRC patient risk profile was female, White, aged 75 to 84 years, widowed, and used public health insurance when compared with respective profiles. The highest malignant CRC patient risk profile was male, Black, both single/never married and divorced/separated, resided in non-Appalachian county, and used public health insurance when compared with respective profiles. The highest risk profiles of in situ and malignant patients had a TD likelihood of 19.3% and 29.4%, respectively. Conclusions: While our findings are not meant for diagnostic purposes, we found that Blacks had lower TD with in situ CRC. The opposite was found in the malignant profiles where Blacks had the highest TD. Although TD is not a definitive marker of survival, we observed that non-Appalachian underserved/underrepresented groups were overrepresented in the highest TD profiles. The observed disparities could be indicative of intervenable risk.

There are common pitfalls and neglected areas when using clustering approaches to solve educational problems. A clustering algorithm is often used without the choice being justified. Few comparisons between a selected algorithm and a competing algorithm are presented, and results are presented without validation. Lastly, few studies fully utilize data provided in an educational environment to evaluate their findings. In response to these problems, this thesis describes a rigorous study comparing two clustering algorithms in the context of an educational digital library service, called the Instructional Architect. First, a detailed description of the chosen clustering algorithm, namely, latent class analysis (LCA), is presented. Second, three kinds of preprocessed data are separately applied to both the selected algorithm and a competing algorithm, namely, K-means algorithm. Third, a series of comprehensive evaluations on four aspects of each clustering result, i.e., intra-cluster and inter-cluster distances, Davies-Bouldin index, users' demographic profile, and cluster evolution, are conducted to compare the clustering results of LCA and K-means algorithms. Evaluation results show that LCA outperforms K-means in producing consistent clustering results at different settings, finding compact clusters, and finding connections between users' teaching experience and their effectiveness in using the IA. The implication, contributions, and limitation of this research are discussed.

<p><b>Objectives</b> The study will assess patterns of known individual, interpersonal, and community-level circumstances leading to suicide to understand how these factors can co-occur. These patterns will help focus on prevention strategies.</p><p><b>Methods</b> Data was collected from the Iowa Violent Death Reporting System, Census data from the American Community Survey, and 2010 rural-urban commuting area codes from the Economic Research Service. The study consisted of three steps. The first step latent class analysis was conducted on data from suicide deaths from Iowa in 2016-2018 to create classes of patterns of circumstances leading to suicide. The second step maximum probability assignment was used to assign the sample of 1,276 to the created latent classes. Finally, in the third step bivariate regressions were ran to understand the relationship between the created latent classes and the rurality variable (nonmetropolitan vs metropolitan).</p><p><b>Results </b>Five latent classes of distinct patterns of suicide factors emerged. Class 1 is physical health problems living in areas that are average on all community-level variables. This class 1 is seen to happen with higher odds in nonmetropolitan areas. Class 2 is interpersonal problems in areas where living alone is high. This class 2 happened with higher odds in nonmetropolitan areas. Class 3 is mental health problems or depressed mood with no legal problems in areas that had lower educational attainment. This class 3 did not indicate greater odds based on rurality. Class 4 is history of mental health treatment in well-off areas. This class 4 was seen to happen with higher odds in metropolitan areas. Class 5 is substance abuse problems in poorer areas. This class 5 did not indicate greater odds based on rurality. All the classes shared a common theme of experiencing mental health issues or being in a depressed mood.</p><p><b>Conclusions </b>Suicide is a complex concern that could be classified into several classes that have distinct patterns of suicide factors. These classes and patterns help with identifying what services and interventions are needed in certain communities. Overall, providing support in regards to mental health as well as intervening in childhood to support positive development may provide substantial mitigation to the odds of committing suicide. In investigating these patterns, future prevention and intervention effort can take into consideration these patterns to tailor to the individual and the environments where they live.</p>

Helicopter parenting has emerged as a prevalent phenomenon in families with adult children. Due to its developmentally inappropriate nature, helicopter parenting sometimes serves as a risk factor for children. In addition, culture and parents’ gender shape parenting and adult children’s outcomes. The purpose of the present study was to identify multidimensional constructs of helicopter parenting among college students and describe how latent classes of helicopter parenting of mothers and fathers are related to college students’ game and social media addictive behaviors in the United States and China. Using a three-step latent class approach, data from 1402 mother and young-adult child (MC) and 1225 father and young-adult child (FC) pairs in the United States and 527 MC and 426 FC pairs in China were analyzed. Four helicopter parenting latent classes (strong, strong but weak direct intervention, weak but strong academic management, and weak) were identified among MC and FC pairs in the United States, but three latent classes (strong, strong but weak direct intervention, and weak) were identified in China. In addition, college students whose parents were in the strong helicopter parenting class reported a higher level of game and social media addictive behaviors than those in weak and weak but strong academic management classes in the United States, but not in China. These findings indicate that helicopter parenting is multidimensional in nature in both American and Chinese families, but the impact of helicopter parenting on college students’ game and social media addictive behaviors differs between the two countries.

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PREFACE: The purpose of this Master’s thesis was to determine which attributes of an early intervention (EI) mental health service would encourage treatment initiation and sustained engagement. This research was motivated by the bourgeoning interest in patient-centered care, particularly the incorporation of patient preferences into service design and implementation. Additionally, the research was inspired by the use of marketing research methodology in healthcare. Two conjoint surveys were formulated with the purpose of asking two questions: what EI service attributes will increase the likelihood of someone (1) initiating contact with an EI service and attending their first appointment, and (2) remaining engaged in treatment. A literature search determined which attributes would be the most relevant and important for conceptualizing an EI service. These attributes were narrowed down with the help of focus groups, key informant interviews, the expertise of the authors, and in the case of the second survey, was also informed by the first survey’s results. Each attribute was assigned four levels and these multi-level attributes were formulated into the two aforementioned surveys that were completed by mental health patients, their families, and mental health professionals. Chapter 1 of this thesis contains a short overview of the research literature investigating the benefits of EI services, some of the reasons why many patients may not receive such services, and some potential strategies to enhance patients’ initial contact and ongoing engagement with such services. In particular, the central tenet of this thesis is that patient engagement with EI services will be enhanced if service design considers and incorporates the preferences of patients and their families with regard to the attributes that characterize the service and its delivery. This hypothesis is explored using discrete choice conjoint experimental (DCE) methods to identify important service attributes regarding patient initiation and engagement. Given that DCEs are the central methodology of this thesis, Chapter 1 also includes an introduction to these methods and their unique benefits. Each of these service attribute questions posed above is addressed in a separate survey and experiment. Therefore, the rationale, methods, results and conclusions of each experiment are described in separate chapters (Chapters 2 & 3). It should be noted that these two chapters are written in the form of stand-alone scientific reports, each of which is about to be submitted for publication to peer-reviewed journals. Finally, the thesis concludes with a General Discussion (Chapter 4), which attempts to frame the two studies, and this line of inquiry more generally, in the broader research literature and highlight their clinical and policy implications. It should also be noted that, given that there exists substantial conceptual overlap between the two experiments and the main issues described in both the General Introduction and General Discussion, the reader may encounter some repetition throughout the thesis. / Mental illness places a large burden on individuals and society-at-large, a problem that becomes much worse the longer it is left untreated. Early intervention (EI) can mitigate this burden; however, those experiencing emerging mental illnesses often do not seek help promptly. Patient-centered care, such as shared-decision making models of mental healthcare, may reduce barriers to treatment. A central tenet of patient-centered care is that patient engagement and service utilization increases when patient preferences are incorporated into clinical services. In the current thesis, discrete choice conjoint experiments (DCE) were used to elicit the preferences of patients and their families, as well as the hypothesized preferences of patients according to mental health professionals, in two surveys. The first survey aimed to identify the attributes of an EI service that would encourage people experiencing psychiatric symptoms to initiate contact with a service and attend their first appointment (Chapter 2). The second survey sought to determine which service attributes would encourage someone to remain engaged with mental health treatment (Chapter 3). Both surveys used Latent Class Analysis to segment the study populations into identifiable subgroups based on shared preferences, and Randomized First Choice simulations to predict which service delivery model each of these identified groups would most likely use. The results of these studies have several implications for current and future mental health services. Effective EI mental health services should include rapid access to services, a range of treatment options, and effective crisis response. Moreover, future DCE studies should focus on replicating these results using more heterogeneous samples and improving DCE methods. / Thesis / Master of Science (MSc)

This thesis examines family formation in Scotland, with a focus on having a first birth. I argue that fertility behaviour must be researched as part of a process of family formation across the life course and informed by the conceptual framework of the Theory of Planned Behaviour. Starting from geographical patterns in fertility rates, housing and partnership, I establish relationships between shared social attitudes, partnership, housing, and family formation behaviour. I use cross-sectional and panel data from the Scottish Social Attitude Survey, the Scottish Census, the Scottish Longitudinal Study and the British Household Panel Study. The methodological contribution lies in the use of a Latent Class Analysis to identify shared social attitudes groups, which are then incorporated in more generic models predicting fertility intentions and first birth outcomes. The findings indicate that social attitudes and norms are important for family formation. While the Second Demographic Transition Theory argued that social norms are being replaced by more independent choices, more recent fertility literature has called for more attention to social norms. The current thesis thus supports these recent calls by showing how social norms might be (indirectly) measured in quantitative research. A key focus is on relationships between housing and family formation, especially normative ideas of 'proper' family housing. I demonstrate that family housing is a significant predictor of first births, at least for women. The gendered nature of family formation is also demonstrated by the different indicators found to predict men's and women's fertility intentions and realisations. I conclude that improved understanding of fertility behaviour requires longitudinal research that goes beyond the usual fertility indicators such as partnership and recognises the importance of gender differences, housing, shared social attitudes, and, above all, the continuing relevance of social norms in the family formation process.

The closing decades of the 20th century have witnessed a large increase in the numbers of young people remaining in education post-16 rather than entering the labour market. Concurrently, overall educational attainment in General Certificate of Secondary Education (GCSE) qualifications in England and Wales has steadily increased since their introduction in 1988. The 1990s represent a key period of change in these trends. Some sociologists argue that processes of detraditionalisation have occurred whereby previous indicators of social inequality, such as social class, are less relevant to the transitions of young people from school to work. Sociologists from other traditions argue that inequalities persist in the stratification of educational attainment by the family backgrounds of young people but that these factors have changed during this period. This thesis is an investigation of the influence of family background factors upon GCSE attainment during the 1990s. This includes extensive statistical analysis of measures of parental occupation, parental education and family structure with gender, ethnicity, school type and housing tenure type within the Youth Cohort Study of England and Wales. These analyses include over 100,000 respondents in 6 cohorts of school leavers with the harmonisation of data from cohort 6 (1992) to the Youth Cohort Time Series for England, Wales and Scotland 1984-2002 (Croxford, Ianelli and Shapira 2007). By adding the 1992 data to existing 1990s cohorts, the statistical models fitted apply to the complete set of 1990s cohorts and are therefore able to provide insight for the whole of this period. Strong differentials by parental occupation persist throughout the 1990s and do not diminish despite the overall context of rising attainment. This relationship remains net of the other factors listed, irrespective of the measure of parental occupation or the GCSE attainment outcome measure used. This builds upon and supports previous work conducted using the Youth Cohort Study and suggests that stratification in educational attainment remains a significant factor. Gender and ethnicity remain further sources of persistent stratification in GCSE attainment. Following a discussion of the weighting system and features of the Youth Cohort Study as a dataset, a thorough investigation of missing data is included, with the results of multiply imputed datasets used to examine the potential for missing data to bias estimates. This includes a critique of these approaches in the context of survey data analysis. The findings from this investigation suggest the importance of survey data collection methods, the limitations of post-survey bias correction methods and provide a thorough investigation of the data. The analysis then develops and expands previous work by investigating variation in GCSE attainment by subjects studied, through Latent Class Analysis of YCS cohort 6 (1992). Of the four groups identified in the model, a clear division is noted between those middle-attaining groups with respect to attainment in Science and Mathematics. GCSE attainment in combinations of subjects studied is stratified particularly with respect to gender and ethnicity. This research offers new insight into the role of family background factors in GCSE attainment by subject combination.

This study was part of a larger multi-informant longitudinal study with a sample of 319 children (52% male, 48% female) ages 4-12 (mean= 7 years 9 months) whose parents had recently filed for divorce. Three annual waves of data from four informants were used for analysis: child self-report, mother, teacher, and observer report. The purpose of the study was to add to the understanding of multi-informant research and children’s psycho-social well-being. The first goal was to determine the consensus of children’s psycho-social well-being scores within informant across time, within child across informant, and between children over time. The second goal was to determine factors that contribute to the levels of consensus, such as, child gender, child age, child ethnicity, and length of parents’ separation, maternal baseline depressive symptoms score, and timing of the teacher questionnaire. The third goal was to determine if children could be classified into meaningful psycho-social well-being groups. Lastly, a visual diagnostic tool, the “patchwork”, was created using a random sample of eight prototypical cases of group membership based on predicted probabilities. This tool displayed the four informants scores, and child and informant characteristics. A single measure of child psycho-social well-being was created for each informant to compare rater consensus in hierarchical linear modeling. Latent class analysis was used to determine groupings. The HLM results indicate that 53% of the variance is within informants across time, 31% is within child across raters, and only 16% is between child over time. As expected, results showed more consensus of informants’ scores among girls than boys, the greatest consensus for children in middle childhood over other age groups, among Non-Hispanic White children compared to other ethnicities, and among spring reports than fall reports from teachers. Maternal baseline depressive symptoms score was significantly related to level of consensus of reporters, with greatest consensus when mother’s baseline depressive symptoms scores are at the mean (15.47). Mother’s scores of children’s psycho-social well-being decrease from highest scores of when baseline depressive symptoms score is 0, decreasing -.02 with each point increase in baseline depressive symptoms score. The results of the latent class analysis show two latent classes with maternal baseline depressive symptoms as a covariate best fit the data, one class with psycho-social well-being scores above the mean (N=258), and one with scores below the mean (N=61). Baseline data alone sufficiently models these groups and is chosen for parsimony over latent transition analysis. In sum, this study demonstrated benefits of multi-method multi-informant research, while acknowledging the strengths and biases that influence informant consensus of children’s psycho-social well being / text