No description available.

Marriage and family research has its foundation in the positivist tradition, which dismisses the relevance of morality to the scientific enterprise. Yet morality is inherent in marriage and family studies—both in the topics studied and in methodology. In this conceptual research, positivist assumptions are explicated to show that positivist methodology relies on a stance of moral neutrality that turns out to be a hidden morality. This hidden morality requires that people be studied as other objects. The need for a methodology that has an explicit moral philosophy and that acknowledges that humans are not “things” is discussed. Levinas' relational philosophy of “being for the other” is shown to be one viable starting point for a methodology that takes the moral domain seriously. In contrast to methodologies that have their basis in positivism, this philosophy offers a coherent account of agency, a relational alternative to individualism, and an explicit moral stance intended to strengthen marriage and families. A method of evaluating research based on criteria of “being for the other” is outlined and used to evaluate three research articles to demonstrate how an explicit moral philosophy can strengthen the meaningfulness of empirical marriage and family research.

Alzheimer’s disease (AD) affects tens of millions of people worldwide. Its cause is unknown, with no cure, and disease-modifying treatment options have only recently become available. Emerging research has made a strong case for the involvement of immune cells, such as microglia and T cells, in modulating AD pathology. Newer technologies in RNA-sequencing have detailed specific phenotypic changes to microglia and T cells over the course of neurodegenerative disease. Some researchers have also used whole-genome sequencing to correlate genetic variants with changes in gene expression. However, no studies thus far have conducted this type of genotype-phenotype correlation in immune cells from aged individuals or AD patients. We have collected gene expression data from four sorted T cell subtypes in peripheral blood samples from 96 subjects in ROSMAP, a cohort of AD patients and age-matched controls. 78 of these subjects also have whole-genome sequencing data, which we used to detect genetic variants associated with changes in T cell gene expression. These are known as expression quantitative trait loci (eQTL). We found genes related to T cell cytotoxicity and immunosenescence in gene co-expression modules, among the eQTL, and in correlation with AD neuropathological traits or risk variants for several disease traits. We extended our findings related to disease association by calculating polygenic risk scores (PRSs) in our cohort from whole-genome sequencing data for 19 traits related to immune function and disease, including AD. Genes associated with the PRS for one or more disease traits often were in biological pathways related to downstream cytokine signaling, regulation of T cell receptor signaling, and T cell migration and trafficking. Overall, our findings indicate that the use of aged and AD patients in T cell genotype-phenotype correlation studies highlights genetic variants and differentially expressed genes that are not seen in studies using young, healthy individuals.

Organizations with multiple operating requirements require support functions to assist in execution of strategic goals. This effort, in turn, requires management of engineering activities in control of projects and in sustaining facilities. High level strategies include employing engineering support that consists of a project management function encompassing technical and managerial disciplines. The architecture/engineering, and construction office (AEC) is the subject of this research. Engineering and construction oriented organizations have experienced challenges to their abilities to learn and grow. This has potential detrimental implications for these organizations if support functions cannot keep pace with changing objectives and strategy. The competitive nature and low industry margins as well as uniqueness of projects as challenges facing engineering and construction. The differentiated nature of projects tasks also creates a need for temporary and dedicated modes of operation and thereby tends to promote highly dispersed management practices that do not dovetail very well with other organizational processes. Organizational learning is a means to enhance and support knowledge management for improving performance. The problem addressed through this research is the gap between desired and achieved individual and group learning by members of the AEC, and the members' abilities to distinguish between the need for adaptive learning or innovation. This research addresses learning by individuals and groups, and the strategies employed through an empirical study (survey). A conceptual model for organizational learning contributions by individuals and groups is presented and tested for confirmation of exploitive or explorative learning strategies for individuals, and directions composed of depth and breadth of learning. Strategies for groups are tested for internal or external search orientations and directions toward the single or multi-discipline unit. The survey is analyzed by method of principal components extraction and further interpreted to reveal factors that are correlated by Pearson product moment coefficients and tested for significance for potential relationships to factors for outcomes. Correlation across dependent variables prevented interpretation of the most significant factors for group learning strategies. However, results provide possible support for direction in supporting processes that promote networking among individuals and group structures that recognize the dual nature of knowledge - that required for technical competency and that required for success in the organization. Recommendations for practitioners include adjustments to knowledge acquisition direction, promoting external collaboration among firms, and provision of dual succession pathways through technical expertise or organizational processes for senior staff.

In psychometrics, a concern is that the assessment is fair for all students who take it. The fairness of an assessment can be evaluated in several ways, including the examination of differential item functioning (DIF). An item exhibits DIF if a subgroup has a lower probability of answering an item correctly than another subgroup after matching on academic achievement. Subgroups include race, spoken language, disability status, or sex. Under item response theory (IRT), a single score is given to each student since IRT assumes that an assessment is only measuring one construct. However, under cognitive diagnostic modeling (CDM), an assessment measures multiple specific constructs and classifies students as having mastered the construct or not. There are several methods to detect DIF under both types of models, but most methods cannot conduct explanatory modeling. Explanatory modeling consists of predicting item responses and latent traits using relevant observed or latent covariates. If an item exhibits DIF which disadvantages a subgroup, covariates can be modeled to explain the DIF and indicate either true or spurious differences. If an item exhibited statistically significant DIF which became nonsignificant after modeling explanatory variables, then the DIF would be explained and considered spurious. If the DIF remained significant after modeling explanatory variables, then there was stronger evidence that DIF was present and not spurious. When an item exhibits DIF, the validity of the inferences from the assessment is threatened and group comparisons become inappropriate. This study evaluated the presence of DIF on the Trends in International Math and Science Study (TIMSS) between students who speak English as a first language (EFL) and students who do not speak English as a first language (multilingual learners [ML]) in the USA. The 8th grade science data was analyzed from the year 2011 since science achievement remains understudied, the 8th grade is a critical turning point for K-12 students, and because 2011 was the most recent year that item content is available from this assessment. The item response theory with covariates (IRT-C) model was used as the explanatory IRT model, while the reparameterized deterministic-input, noisy "and" gate (RDINA) model was used as the explanatory CDM (E-CDM). All released items were analyzed for DIF by both models with language status as the key grouping variable. Items that exhibited significant DIF were further analyzed by including relevant covariates. Then, if items still exhibited DIF, their content was evaluated to determine why a group was disadvantaged. Several items exhibited significant DIF under both the IRT-C and E-CDM. Most disadvantaged ML students. Under the IRT-C, two items that exhibited DIF were explained by quantitative covariates. Two items that did not exhibit significant nonuniform DIF became significant after explanation. Whether or not a student repeated elementary school was the strongest explanatory covariate, while confidence in science explained the most items. Under the E-CDM, five items initially exhibited significant uniform DIF with one also exhibiting nonuniform DIF. After scale purification, two items exhibited significant uniform DIF, and one exhibited marginally significant DIF. After explanatory modeling, no items exhibited significant uniform DIF, and only one item exhibited marginally significant nonuniform DIF. Examining covariates, home educational resources explained the most with ten items and the strongest positive covariate. Repeated elementary school had the strongest absolute effect. Examining the item content of 14 items, most items had no causal explanation for the presence of DIF. In four items, a causal mechanism was identified and concluded to exhibit item bias. An item's cognitive domain had a relationship with DIF items, with 79% of items under the Knowing domain. Based on these results, DIF that disadvantaged ML students was present among several items on this science assessment. Both the IRT-C and E-CDM identified several items exhibiting DIF, quantitative covariates explained several items exhibiting DIF, and item bias was discovered in several items. Following up on this empirical study, a simulation study was performed to evaluate DIF detection power and Type I error rates of the Wald test and likelihood ratio (LR) test, and parameter recovery when ignoring subgroups, using the compensatory reparameterized unified model (C-RUM). Factors included sample size, DIF magnitude, DIF type, Q-matrix complexity, their interaction effects, and p-value adjustment. Evaluating DIF under the C-RUM, the DIF detection method had the largest effect on Type I error rates, with the Wald test recovering the nominal p-value much better than the LR test. In terms of power, DIF magnitude was the most important factor, followed by Q-matrix complexity. As DIF magnitude increased and Q-matrix complexity decreased, power rates increased. In terms of parameter recovery, the DIF type had the strongest effect, followed by Q-matrix complexity. Nonuniform DIF recovered the parameter more than uniform DIF, while fewer attributes measured by an item improved parameter recovery. Several factors affected DIF detection power and Type I error, including DIF detection method, DIF magnitude, and Q-matrix complexity. For parameter recovery, DIF type had an impact, along with Q-matrix complexity, and DIF magnitude. / Doctor of Philosophy / Academic assessments are a necessary tool to evaluate student educational progress in different subjects across school years. These are necessary to establish student proficiency within schools, districts, states, and countries. The results can be broken down to make various comparisons, including by race, ethnicity, gender, language status, schools, or any other demographic. Other comparisons can be made against a proficiency standard or passing rate. It is important and necessary to make comparisons between groups so that any disparities or achievement gaps can be identified and rectified. This study evaluated achievement gaps between multilingual learner (ML) students and English first language (EFL) students on individual items of an 8th-grade international science assessment. This subject and grade level are crucial for students preparing for college and starting their career development. Every test item was analyzed to determine if there was an achievement gap and if an item was biased against a group based on their first language. Several follow-up analyses were conducted on every item to ensure that the results were as accurate as possible and that there were no other plausible explanations. Several explanatory factors were evaluated, including student home educational resources, confidence in science, likes learning science, repeating elementary school, being bullied at school, and time spent on science homework. For items that had achievement gaps based on language, further analysis was conducted to ensure that the gaps were not due to other student characteristics. Based on that analysis, the item content was examined by myself and a content expert. This was done to evaluate if there were characteristics of the item that led to the language achievement gap. This allowed for the evaluation of whether an item was biased against either ML or EFL students. Fourteen items exhibited achievement gaps based on language status. Most items disadvantaged ML students, and the achievement gaps ranged from small to large. This initial analysis was followed up with more extensive analyses to rule out other potential causes of the achievement gaps. Repeated elementary school had the strongest relationship with these items, while confidence in science was related to the most items exhibiting achievement gaps. There were two items in which the language achievement gap was explained by a combination of factors, thus concluding that there was not any gap on the items. The remaining items still exhibited achievement gaps which led to analysis of the item content. On four items, the causes of the remaining achievement gaps were discovered. For the remaining items, there was no clear reason for the item bias and achievement gaps. This study was followed by a study to evaluate a new method of detecting achievement gaps. This was done by creating specific data so that the true values were known. The sample size, test item complexity, achievement gap size and direction, and gap detection method were evaluated. These conditions and their values were chosen to reflect realistic testing scenarios and provide a better understanding of the previous study's results. The results indicated that one achievement gap detection method had higher detection rates compared to the other detection method. This was true in all conditions. Additionally, achievement gaps were found more often when sample sizes and achievement gaps were larger, test items were less complex, and when one group was disadvantaged across all ability levels. When comparing the estimated and true statistics, there were large deviations when one group was disadvantaged at different proficiency levels. Also, when items were more complex, and sample sizes were smaller, the deviation between true and estimated statistics was larger than when items were simpler and sample sizes were larger.

Chronic non-cancer pain (CNCP) is a complex phenomenon that affects multiple dimensions of daily life. Optimal therapies for managing CNCP must, then, demonstrate clinically important benefits that go beyond reductions in pain and adverse events. The Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials (IMMPACT) has recommended that clinical trialists who are evaluating treatments for chronic pain consider reporting treatment effects across nine patient-important outcome domains. This thesis begins with an investigation of the extent to which clinical trials evaluating the effects of opioids for CNCP report IMMPACT-recommended core outcome domains. Further, it explores optimal therapeutic strategies for specific CNCP conditions; specifically, it features a systematic review of randomized controlled trials of all pharmacological and non-pharmacological therapies for central post-stroke pain, as well as a plan for a network meta-analysis of all therapies for all chronic neuropathic pain syndromes. Chronic pain is also a common reason for disability, and this thesis concludes with a retrospective cohort study focused on identifying predictors of claim duration following acceptance for disability benefits among Canadian workers. / Thesis / Doctor of Philosophy (PhD)

Symptomatic spinal disorders affect a large proportion of the population and are associated with substantial morbidity, social burden, and economic impact. Spine surgery interventions can provide excellent results in carefully selected patients whose symptoms fail to improve with non-operative management, but an evidence-based approach is paramount to optimize outcomes and rigorous standards of health research methodology are critical to avoid misleading conclusions. This thesis aimed to investigate and apply modern innovations in health research methodology to the field of spine surgery. It consists of seven chapters divided between three sections: randomized controlled trials, observational studies, and systematic reviews and meta-analyses. By applying the findings of each chapter, clinicians, researchers, and other evidence users can advance the credibility of future research and enhance the care of patients with spinal disorders. / Thesis / Doctor of Philosophy (PhD)

Transcriptome studies disentangle functional mechanisms of gene expression regulation and may lend key insights into disease mechanisms. However, the cost of RNA-sequencing and types of tissues currently assayed pose major limitations to study expansion and disease-relevant discovery. This thesis develops methods for sampling noninvasive biospecimens for transcriptome studies, investigating their technical and biological characteristics, and assessing the feasibility of using noninvasive samples in transcriptomic and clinical applications. Chapter 1 explores the technical and biological features of four potential noninvasive sample types (buccal swabs, hair follicles, saliva, and urine cell pellets) in a pilot study of 19 individuals whereby four separate collections of each tissue were performed (i.e. 76 samples/tissue, 304 samples in total). From this data, consistency of library preparation, cell type content, replication of GTEx cis-eQTLs, and disease applications were assessed. In all, hair follicles and urine cell pellets were found to be most promising for future applications. Chapter 2 investigates the scaling potential of noninvasive sampling in SPIROMICS, a COPD clinical cohort. To do so, 140 hair follicle and 110 buccal swab samples were collected from seven different clinical sites. Consistency of sample quality was observed to be high for hair follicles, and hair cell type abundance estimates were consistent within SPIROMICS and compared to the 19 subject pilot study. Mapping of cis-eQTLs in hair revealed 339 associations not identified in any prior study. These cis-eQTLs show higher replication in GTEx tissues that share cell types with hair follicles, indicating hair follicles may indeed capture gene expression regulatory mechanisms found in more invasive tissue types of the body. This thesis suggests future use of noninvasive sampling will facilitate discovery by increasing sample sizes in more diverse populations and in tissues with greater cell type diversity and biological relatedness to disease mechanisms. Moreover, the nature of noninvasive sampling enables complex, longitudinal study designs with greater ability to capture context-dependent mechanisms of genetic regulation not currently able to be interrogated.

Workplace discrimination exists in the Swedish work environment. Minority groups (such as immigrants, persons from ethno-racial backgrounds different from the majority population, persons of non-normative sexual orientation, gender, or religious background) may experience discrimination or the fear of possible exposure to discrimination in the workplace. This presents an additional form of stress referred to as ‘minority stress’. Minority Stress is added stress to general stressors experienced by all people that is unique to minority groups. In the workplace, workplace discrimination is a psychosocial risk factor which could lead to minority stress. To address this risk, studies aimed at eliminating health and other disparities requires quality and methodologically sound research on racial/ethnic minorities, yet little guidelines are available. This thesis aims to bridge this gap and adopts ethno-racialization and participatory research frameworks to elicit the views and opinions of eight (8) ethno-racialized minorities in Sweden on how survey items investigating workplace discrimination in Sweden could be designed in a sensitive, non-stigmatizing manner that does not reinforce negative stereotypes. Study participants included five men and three women aged between 18 – 45 years old recruited through opportunistic, snowball sampling technique, with Swedish work experience between1 – 10 years, and working across academia, hospitality, communication, and health sectors. Participants responded to survey questionnaire and were interviewed on four key areas: Demographics; Ethno-racialization questions; Sample of various wordings on discrimination questions and Technology related questions regarding data collection, storage, and access.The result from this study show that “language” used in the wording of survey questions directed at ethno-racialized minorities is an important element if/how they respond and interpret questions. In this regard, using unclear and indirect language that is vague, ambiguous in survey questionnaire could lead to multiple interpretations and impact the validity of data collected. The study also found that ethno-racialized persons are not a homogenous group and as such, how they interpret and respond to survey questions indicate differences and reflect their individual preferences. The study concludes that survey items investigating workplace discrimination among ethno-racialized minorities should be designed using language that is direct and considers the varied opinions and perspectives of members of the group – that is, ethno-racialized minorities come from diverse backgrounds and their views are not homogenous.

No description available.