Although many theorists have speculated that chronic pain may be linked to some sort of central neuropsychological integration deficit, a review of the current literature reveals no empirical support for this theory. This study attempts to assess the severity, if any, of neuropsychological deficits in chronic pain subjects by using a neuropsychological screen developed at the University of North Texas. Also, presented are studies of correlations between the UNT Neuropsych-screen and the MMPI. the Dallas Pain Questionnaire (DPQ), the Dallas Pain Drawing CDPD), and time since injury in order to assess any possible relationships. The subjects in this study consist of 100 volunteers. Of these subjects, 74 were patients of the Spinal and Chronic Pain Center at Medical Arts Hospital in Dallas, Texas and represented the clinical population. The remaining 26 subjects were staff volunteers from the hospital . The results of the study indicate significant differences between chronic pain subjects and non-pain subjects across many areas of neuropsychological functioning, as well as other significant correlations among many of the variables. The implications of this study are elaborated upon, in the discussion section, in detail along with limitations and future research directions.

京都大学 / 0048 / 新制・課程博士 / 博士(社会健康医学) / 甲第22889号 / 社医博第113号 / 新制||社医||11(附属図書館) / 京都大学大学院医学研究科社会健康医学系専攻 / (主査)教授 川上 浩司, 教授 松田 文彦, 教授 中島 貴子 / 学位規則第4条第1項該当 / Doctor of Public Health / Kyoto University / DFAM

The purpose of this study was to validate the Spanish version of the Dallas Pain Questionnaire (DPQ). Not only does the DPQ offer the potential of statistical and clinical diagnostic value but also is easily interpretable across cultural lines. No such instrument has presently been validated for the Mexican-American population. A total of 81 Spanish speaking subjects participated in this study. Of these subjects, 56 were classified as chronic pain patients by nature of their medical diagnosis and duration of pain. The 25 normal subjects were family members of the chronic pain patients and members of the Northern New Mexico Hispanic community chosen at random. Hypothesis one predicted that reliability would be obtained on Spanish speaking populations based on test-retest with correlation coefficients of the items. The second hypothesis predicted that the Spanish DPQ would have content validity or consistent internal structure on those items that measure the trait or behavior of interest based upon factor analysis approaches and internal consistency measures. Hypothesis three predicted that the Spanish version of the DPQ would significantly correlate with the English version of the DPQ on all four factors. All four hypotheses were supported. The Spanish DPQ showed reliability over time based on test-retest. The statistics revealed an internally reliable test, alpha coefficient analysis and factor analysis. The validity was supported by significant correlations with the English DPQ and discrimination between chronic and nonchronic pain patients. While all four hypotheses were upheld, interpretation of the present findings should be moderated by recognition of the limitations of the studies. Future studies should test larger samples to improve confidence in the psychometric properties of the instrument. Still notable limitations of the questionnaire are that the Spanish DPQ is a form that is more accurately viewed as a global measure.

Sixty subjects divided equally among Anglo-Americans, Black Americans, and Hispanic Americans participated in the study. They were classified as chronic pain patients by medical diagnosis and duration of pain. They were drawing Workers' Compensation and were all blue-collar workers from the Dallas-Fort Worth area. Cognitive complexity is a measure of individuals' ability to construe their feelings, events of their lives, and their world in a meaningful manner. Cognitive complexity appeared to differ among the cultural groups as indicated by significantly different functionally independent construct scores. Anglo-Americans appeared to have a greater internal complexity than did Black Americans and Hispanic Americans.

A school community is often more than meets the eye. With more research highlighting the benefits of school-community partnerships, the notion of what constitutes community in an elementary school setting leaves much room to be further examined. In this study, community is considered through two lenses: a geographically-defined community and a sense of community defined by mutual sensibilities, goals, and practices (Weathers, 2011; Wenger, 1998). The purpose of this study was to understand faculty and staff perceptions of community in a challenged urban elementary school. A qualitative research methodology with a phenomenological approach was used in this case study. Participants included the faculty, staff, and the leadership team currently employed at an elementary school. Data collection methods included semi-structured interviews, participant conversations, observations, artifacts, and document analysis. These methods were used to capture the phenomenon and experiences of people working in and with the school. Three themes emerged from the data, describing who and what contribute to community in a challenged urban elementary school: (a) members of the community, (b) the prioritization of students at the school, and (c) the intractable problems that exist within the school, both on micro and macro levels. Based on these findings, the main conclusion was that teachers played the biggest role in prioritizing students, as they were the community members most immersed with students on a daily basis. Additional conclusions were: (a) the level of student need is high, (b) intractable problems challenge the development of community, and (c) principal and teacher turnover challenge the development of community. / Doctor of Philosophy / A school community is often more than meets the eye. With more research highlighting the benefits of school-community partnerships, the notion of what constitutes community in an elementary school setting leaves much room to be further examined. In this study, community is considered through two lenses: a geographically-defined community and a sense of community defined by mutual interests, goals, and practices. The purpose of this study was to understand faculty and staff perceptions of community in a challenged urban elementary school. I conducted my research at an elementary school in the Southeastern part of the United States. I focused on the faculty, staff, and the leadership team at the elementary school. I interviewed faculty and staff, had conversations, observed within the school, took photos, and examined documents that helped me better understand the school and its community. In my findings, I described who and what contribute to community: (a) members of the community, (b) the prioritization of students at the school, and (c) the intractable problems that exist within the school. The main conclusion in this study was that teachers played the biggest role in prioritizing students, as they were the community members most immersed with students on a daily basis. Additional conclusions were: (a) the level of student need is high, (b) intractable problems challenge the development of community, and (c) principal and teacher turnover challenge the development of community.

<div>Mixture modeling is a classical unsupervised learning method with applications to clustering and density estimation. This dissertation studies two challenges in modeling data with mixture models. The first part addresses problems that arise when modeling observations lying on constrained spaces, such as the boundaries of a city or a landmass. It is often desirable to model such data through the use of mixture models, especially nonparametric mixture models. Specifying the component distributions and evaluating normalization constants raise modeling and computational challenges. In particular, the likelihood forms an intractable quantity, and Bayesian inference over the parameters of these models results in posterior distributions that are doubly-intractable. We address this problem via a model based on rejection sampling and an algorithm based on data augmentation. Our approach is to specify such models as restrictions of standard, unconstrained distributions to the constraint set, with measurements from the model simulated by a rejection sampling algorithm. Posterior inference proceeds by Markov chain Monte Carlo, first imputing the rejected samples given mixture parameters and then resampling parameters given all samples. We study two modeling approaches: mixtures of truncated Gaussians and truncated mixtures of Gaussians, along with Markov chain Monte Carlo sampling algorithms for both. We also discuss variations of the models, as well as approximations to improve mixing, reduce computational cost, and lower variance.</div><div><br></div><div>The second part of this dissertation explores the application of mixture models to estimate contamination rates in matched tumor and normal samples. Bulk sequencing of tumor samples are prone to contaminations from normal cells, which lead to difficulties and inaccuracies in determining the mutational landscape of the cancer genome. In such instances, a matched normal sample from the same patient can be used to act as a control for germline mutations. Probabilistic models are popularly used in this context due to their flexibility. We propose a hierarchical Bayesian model to denoise the contamination in such data and detect somatic mutations in tumor cell populations. We explore the use of a Dirichlet prior on the contamination level and extend this to a framework of Dirichlet processes. We discuss MCMC schemes to sample from the joint posterior distribution and evaluate its performance on both synthetic experiments and publicly available data.</div>

In this dissertation, we have proposed two new algorithms for statistical inference for models with intractable normalizing constants: the Monte Carlo Metropolis-Hastings algorithm and the Bayesian Stochastic Approximation Monte Carlo algorithm. The MCMH algorithm is a Monte Carlo version of the Metropolis-Hastings algorithm. At each iteration, it replaces the unknown normalizing constant ratio by a Monte Carlo estimate. Although the algorithm violates the detailed balance condition, it still converges, as shown in the paper, to the desired target distribution under mild conditions. The BSAMC algorithm works by simulating from a sequence of approximated distributions using the SAMC algorithm. A strong law of large numbers has been established for BSAMC estimators under mild conditions. One significant advantage of our algorithms over the auxiliary variable MCMC methods is that they avoid the requirement for perfect samples, and thus it can be applied to many models for which perfect sampling is not available or very expensive. In addition, although the normalizing constant approximation is also involved in BSAMC, BSAMC can perform very robustly to initial guesses of parameters due to the powerful ability of SAMC in sample space exploration. BSAMC has also provided a general framework for approximated Bayesian inference for the models for which the likelihood function is intractable: sampling from a sequence of approximated distributions with their average converging to the target distribution. With these two illustrated algorithms, we have demonstrated how the SAMCMC method can be applied to estimate the parameters of ERGMs, which is one of the typical examples of statistical models with intractable normalizing constants. We showed that the resulting estimate is consistent, asymptotically normal and asymptotically efficient. Compared to the MCMLE and SSA methods, a significant advantage of SAMCMC is that it overcomes the model degeneracy problem. The strength of SAMCMC comes from its varying truncation mechanism, which enables SAMCMC to avoid the model degeneracy problem through re-initialization. MCMLE and SSA do not possess the re-initialization mechanism, and tend to converge to a solution near the starting point, so they often fail for the models which suffer from the model degeneracy problem.

The study of intractable conflicts has risen in recent years particularly with the work of Daniel Bar-Tal’s work on the ethos of conflict. The ethos of conflict is an original psychological concept that captures the collective societal mindset of cultures locked in intractable conflicts and examines the various factors that keep groups in conflict or help them towards peace. The Israeli-Palestinian conflict is arguably the most researched, publicized, and discussed intractable conflict in history. The purpose of this paper is to first examine the foundation of that intractable conflict through the lens of Bar-Tal’s theory and apply it once more how it has changed in the modern day. Particularly, this paper focuses on how the change in power structure in the Israeli-Palestinian conflict has prioritized the different elements of the ethos of conflict differently for both sides. In the beginning of the conflict, both groups held equitable power that caused them to have similar manifestations of the ethos of conflict. Working with the foundation of Bar-Tal’s theory, this paper provides an analysis of how Israel’s rise to power in the conflict influences different prioritizations of the ethos of conflict for both parties.

An important challenge facing humanity today is to determine how to resolve intractable conflicts. Intractable conflicts are intensely violent conflicts that are difficult to resolve and last at least one generation. The purpose of this study was to explore the themes leaders used in resolving intractable conflicts by writing peace agreements, which achieved at least a ninety percent implementation rating by the Kroc Institute for International Peace Studies at the University of Notre Dame. The research questions focused on the distribution of societal themes defined by Bar-Tal as present within societies experiencing an intractable conflict. This study used a multicase study approach and a directed content analysis of the narratives, chosen because the study began with an existing concept as a guide for determining initial codes. A categorization matrix was developed based on the existing concept and expanded to include one new category not initially included. The texts were coded by hand and the data were interpreted to reveal the findings, which show that the distribution of themes within narratives of the peace accords contained themes supported by Bar-Tal's research as being functional in transitioning a society out of conflict and absent themes found as being dysfunctional in helping societies make this transition. Second, interpretation of the findings confirmed that knowledge found in transformational leadership literature extends knowledge of narratives of peace accords. A new model of peacemaking emerged from these findings entitled the peace accords transformational leadership model. If leaders understood how to craft narratives of peace, then positive social change would result from a quicker end to violent conflicts and lasting peace for the societies suffering within them.

Classical approaches to conflict resolution assume that inducing conflict parties to analyse conflict constellations precipitates that the disputants recognise mutually shared needs or interests. Partially in critical reaction towards this assumption, a more recently emerging approach envisages setting up a communicative framework within which the conflict parties are supposed to harmonise their conceptualisations of the conflict. This dissertation, in contrast, argues that work within the frameworks of these classes of approaches is impolitic as long as war-related hostilities stay intact, since conflict parties which see the existence of the adversary as the core of the problem are unlikely to engage in a process of open communication or open analysis, so that trustbuilding is a sine qua non. Practice experiences of local NGOs in the former Yugoslavia suggest that the following activities can be conducive to trustbuilding: 1) supporting exchanges on personalising information, so that the internal heterogeneity of the opponent's group is rendered visible; 2) bringing intergroup iii commonalities to the foreground, either through cooperation on shared aspirations, or by unearthing interpersonal overlaps e.g. common feelings, values, and war-related experiences; 3) undermining the imagination of the own side's moral superiority by fostering the recognition of crimes and suffering inflicted by the own side. For those cultural and religious differences which persist after basic trustbuilding, a contingency approach is proposed: 1) Fostering the exploration of commonalities and differences; 2) If disagreements remain despite a better basic understanding, tolerance of these difference can be based on a better understanding of the values' background, and on an acceptance of differing beliefs as equal in valence; 3) Supporting the discovery of joint values to raise awareness for options of cohabitation with differences; disagreements which cannot be solved might be continued within an accepted communicative framework based on these shared values.