An epidemiologic evaluation of a worksite based intervention

The healthcare industry spends billions on worker injury and employee turnover. Hospitals and healthcare settings have one of the highest rates of lost days due to injuries. The occupational hazards for healthcare workers can be classified into biological, chemical, ergonomic, physical, organizational, and psychosocial. Therefore, interventions addressing a range of occupational health risks are needed to prevent injuries and reduce turnover and reduce costs. ^ The Sacred Vocation Program (SVP) seeks to change the content of work, i.e., the meaningfulness of work, to improve work environments. The SVP intervenes at both the individual and organizational level. First the SVP attempts to connect healthcare workers with meaning from their work through a series of 5 self-discovery group sessions. In a sixth session the graduates take an oath recommitting them to do their work as a vocation. Once motivated to connect with meaning in their work, a representative employee group meets in a second set of five meetings. This representative group suggests organizational changes to create a culture that supports employees in their calling. The employees present their plan in the twelfth session to management beginning a new phase in the existing dialogue between employees and management. ^ The SVP was implemented in a large Dallas hospital (almost 1000 licensed beds). The Baylor University Medical Center (BUMC) Pastoral Care department invited front-line caregivers (primarily Patient Care Assistants, PCAs, or Patient Care Technicians, PCTs) to participate in the SVP. Participants completed SVP questionnaires at the beginning and following SVP implementation. Following implementation, employer records were collected on injury, absence and turnover to further evaluate the program's effectiveness on metrics that are meaningful to managers in assessing organizational performance. This provided an opportunity to perform an epidemiological evaluation of the intervention using the two sources of information: employee self-reports and employer administrative data. ^ The ability to evaluate the effectiveness of the SVP on program outcomes could be limited by the strength of the measures used. An ordinal CFA performed on baseline SVP questionnaire measurements examined the construct validity and reliability of the SVP scales. Scales whose item-factor structure was confirmed in ordinal CFA were evaluated for their psychometric properties (i.e., reliability, mean, ceiling and floor effects). CFA supported the construct validity of six of the proposed scales: blocks to spirituality, meaning at work, work satisfaction, affective commitment, collaborative communication, and MHI-5. Five of the six scales confirmed had acceptable measures of reliability (all but MHI-5 had α>0.7). All six scales had a high percentage (>30%) of the scores at the ceiling. These findings supported the use of these items in the evaluation of change although strong ceiling effects may hinder discerning change. ^ Next, the confirmed SVP scales were used to evaluate whether the intervention improved program constructs. To evaluate the SVP a one group pretest-posttest design compared participants’ self-reports before and after the intervention. It was hypothesized that measurements of reduced blocks to spirituality (α = 0.76), meaning at work (α = 0.86), collaborative communication (α = 0.67) and SVP job tasks (α = 0.97) would improve following SVP implementation. The SVP job tasks scale was included even though it was not included in the ordinal CFA analysis due to a limited sample and high inter-item correlation. Changes in scaled measurements were assessed using multilevel linear regression methods. All post-intervention measurements increased (increases <0.28 points) but only reduced blocks to spirituality was statistically significant (0.22 points on a scale from 1 to 7, p < 0.05) after adjustment for covariates. Intensity of the intervention (stratifying on high participation units) strengthened effects; but were not statistically significant. The findings provide preliminary support for the hypothesis that meaning in work can be improved and, importantly, lend greater credence to any observed improvements in the outcomes. (Abstract shortened by UMI.)^

Functional data analysis approaches for genotype-phenotype association studies from next-generation sequencing

Next-generation DNA sequencing platforms can effectively detect the entire spectrum of genomic variation and is emerging to be a major tool for systematic exploration of the universe of variants and interactions in the entire genome. However, the data produced by next-generation sequencing technologies will suffer from three basic problems: sequence errors, assembly errors, and missing data. Current statistical methods for genetic analysis are well suited for detecting the association of common variants, but are less suitable to rare variants. This raises great challenge for sequence-based genetic studies of complex diseases.^ This research dissertation utilized genome continuum model as a general principle, and stochastic calculus and functional data analysis as tools for developing novel and powerful statistical methods for next generation of association studies of both qualitative and quantitative traits in the context of sequencing data, which finally lead to shifting the paradigm of association analysis from the current locus-by-locus analysis to collectively analyzing genome regions.^ In this project, the functional principal component (FPC) methods coupled with high-dimensional data reduction techniques will be used to develop novel and powerful methods for testing the associations of the entire spectrum of genetic variation within a segment of genome or a gene regardless of whether the variants are common or rare.^ The classical quantitative genetics suffer from high type I error rates and low power for rare variants. To overcome these limitations for resequencing data, this project used functional linear models with scalar response to develop statistics for identifying quantitative trait loci (QTLs) for both common and rare variants. To illustrate their applications, the functional linear models were applied to five quantitative traits in Framingham heart studies. ^ This project proposed a novel concept of gene-gene co-association in which a gene or a genomic region is taken as a unit of association analysis and used stochastic calculus to develop a unified framework for testing the association of multiple genes or genomic regions for both common and rare alleles. The proposed methods were applied to gene-gene co-association analysis of psoriasis in two independent GWAS datasets which led to discovery of networks significantly associated with psoriasis.^

The role of youth sports in public health

Study 1: Schools provide a range of opportunities for youth to be active, however, over the past decade, these opportunities have been declining. Sports teams are a promising venue to promote physical activity yet limited research has examined the gender an ethnic differences in sport participation. The purpose of this study is to examine trends in sport participation from 1991-2009 among US high school students. Secondly, we examined the association between gender and ethnicity with sports over time. This serial cross-sectional study used surveillance data from the Youth Risk Behavior Survey, a probability based sample weighted to represent gender and race/ethnic subpopulations of US high school students. The findings of this paper reveal persistent gender and ethnic disparities for sports participation among US youth. Since sports teams may provide a substantial source of physical activity, greater efforts should be undertaken to increase the participation of girls, especially minorities, in sports teams. ^ Study 2: Sports team participation is congruent with teaching and supporting healthy eating, yet limited research has examined the association between sports participation and dietary behaviors. This study aims to determine the association between youth sports participation and dietary behaviors among elementary-aged children. Significant dose-response associations were observed between number of sports teams and consumption of most fruits and vegetables. The likelihood of eating fruit for boys increased with the number of sports teams (1 team: OR=1.89; 3 teams: OR=3.44, p<0.001) and the likelihood of consuming green vegetables for girls was higher with the number of sports teams (1 team: OR=1.50; 3 teams: OR=2.39; p<0.001). For boys, the odds of consuming fruit-flavored drinks was higher ( p=0.019) and the odds of drinking soda was lower (p=0.018) with participation in increasing number of sports teams whereas for girls, sports participation was positively associated with diet soda consumption (p=0.006). ^ Study 3: Parents and peers have been shown to have a strong influence over the physical activity, dietary, and sedentary behaviors of youth. Youth sports teams have the potential to offer physical activity, displace sedentary behaviors, and promote a healthy diet. The purpose of this study is to assess how peer and parental support for physical activity and healthy eating, coupled with sport participation, is associated obesity related risk factors including diet and sedentary behaviors. A secondary analysis of data from the School Physical Activity and Nutrition study, a state-representative survey, was conducted. Eighth (n=3,931) and 11th (n=2,785) grade students were categorized into four groups based upon the level of peer and parental support derived from a three item scale and their participation in sports (sports/high support, sports/low support, no sports/high support, no sports/low support). Linear models were conducted to determine the difference in means between these groups for the following outcome variables: previous day fruit and vegetable intake, scores for an unhealthy and healthy food index, and hours spent watching television, playing video games, and working on a computer. Eighth graders had significantly greater levels of parental support for healthy eating and physical activity compared to 11th grade. Both 8 th and 11th graders in the sport/high support for healthy eating from peers and parents scored significantly higher on the healthy food index than other groups. Eighth and 11th graders in the sport/high support for physical activity from peers participated in fewer hours of sedentary behaviors than any other group (p ≤ 0.032). Although it is thought that sport participation may offer opportunities to support a healthy diet and displace sedentary time by offering providing physical activity, our study found that parental and peer support for activity and healthy eating may further attenuate this association. Parents and peer support should be an important target when developing strategies to improve healthy diets and reduce sedentary time among youth, especially in the context of youth sports. (Abstract shortened by UMI.)^

Regression with autocorrelated data: A study of time trend of global infant mortality rate

The infant mortality rate (IMR) is considered to be one of the most important indices of a country's well-being. Countries around the world and other health organizations like the World Health Organization are dedicating their resources, knowledge and energy to reduce the infant mortality rates. The well-known Millennium Development Goal 4 (MDG 4), whose aim is to archive a two thirds reduction of the under-five mortality rate between 1990 and 2015, is an example of the commitment. ^ In this study our goal is to model the trends of IMR between the 1950s to 2010s for selected countries. We would like to know how the IMR is changing overtime and how it differs across countries. ^ IMR data collected over time forms a time series. The repeated observations of IMR time series are not statistically independent. So in modeling the trend of IMR, it is necessary to account for these correlations. We proposed to use the generalized least squares method in general linear models setting to deal with the variance-covariance structure in our model. In order to estimate the variance-covariance matrix, we referred to the time-series models, especially the autoregressive and moving average models. Furthermore, we will compared results from general linear model with correlation structure to that from ordinary least squares method without taking into account the correlation structure to check how significantly the estimates change.^