PhD, University of Cincinnati, 2021, Medicine: Industrial Hygiene (Environmental Health)

A large number of preventable deaths are attributable to air pollution each year. Ultrafine particles (UFPs, < 100 nm in diameter) are arguably more toxic than larger particles because of their ability to deposit into lung alveoli and translocate into circulation and secondary organs including the brain. Although the biological mechanisms responsible for UFP effects have been posited in toxicological literature, supporting epidemiological findings are inconsistent. Less literature exists for children, though they may be at an increased risk of exposure, representing a significant knowledge gap. Children inhale UFPs at greater deposition rates and incur greater pulmonary or neural structure and function damage due to UFPs. However, UFP exposure at an individual level is not accurately characterized by traditional measurement methods due to the spatial-temporal variability in UFP levels. Therefore, the objective of this dissertation was to employ personal sampling monitors among adolescents to describe short-term UFP exposure across individual time-activity patterns. We used these measurements to estimate the relationship of UFPs on both respiratory and mental health. The first chapter consisted of a literature review on current knowledge in the field, with a focus on pediatrics, while the second and third chapters were devoted to results obtained from the EcoMAPPE study. Results of the literature review revealed there is not sufficient evidence to support an association between UFPs and either respiratory or mental health outcomes. In the current study, adolescents measured personal UFP concentrations over one week (3 hours per day). Pulmonary function tests were conducted at a follow-up clinic visit and were interpreted as percent predicted values. In addition, personal spirometers were employed to collect various lung function values by participants throughout their sampling week. Participants reported respiratory symptoms through a mobile application. Fin (open full item for complete abstract)

Committee: Tiina Reponen Ph.D. (Committee Chair); Richard Brokamp Ph.D. (Committee Member); Patrick Ryan Ph.D. (Committee Member) Subjects: Environmental Health

MS, University of Cincinnati, 2019, Medicine: Industrial Hygiene (Environmental Health)

Immediately Dangerous to Life and Health (IDLH) values, developed by National Institute for Occupational Safety and Health (NIOSH), are 30-minute exposure values to protect workers from irreversible health effects, escape impairing effects, and death during an emergency. Developing an IDLH is a long process which is why there are approximately 135 IDLH values for the thousands of chemicals in commerce. The occupational community would benefit from developing additional IDLHs. Previous research has shown that a respiratory rate decrease of 50% (RD50) in animal studies has a good correlation with occupational exposure limits (OELs) (Alarie, 1981). This paper investigates extending the concept to escape impairing effects by using 30-minute Acute Exposure Guideline Levels (AEGLs) in a linear regression analysis with RD50 values. The 30-minute AEGL2 was used because the methodology, health effects, and duration are similar to IDLH values, thus are expected to comparable. The regression analysis of RD50 and AEGL2 was explored to determine if the values were correlated and if the resulting equation could be used in an algorithm along with the relationship between AEGL2 and IDLH to accurately predict an IDLH from a RD50 value. The regression analysis showed good correlation with a r2 of 0.74 for the RD50 and AEGL2 relationship and a r2 of 0.84 for the RD50 and IDLH relationship. The closeness of the correlations indicates that it may not be necessary to use the AEGL2 as a surrogate for the IDLH in a prediction algorithm for an IDLH. The next step is to validate the model with data separate from the data used to develop the model.

Committee: John Reichard PharmD Ph.D. (Committee Chair); Jurate Virkutyte Ph.D. (Committee Member) Subjects: Occupational Safety

Master of Public Health, The Ohio State University, 2018, Public Health

Influenza A virus is a zoonotic pathogen whose introduction to humans from animals could potentially cause a pandemic. Animal-linage influenza A viruses (IAVs) that infect humans are referred to as variant IAVs, which are designated with a `v' after the subtype. To better understand the epidemiology of IAV in exhibition swine and resulting H3N2v in humans, we performed a phylogenetic analysis using full genome sequences from 279 IAV isolates collected from exhibition swine in 5 states from 2013-2015 and 23 of the 25 H3N2v cases reported during those same years. Sixty-six fairs (23.7%) had at least one sample that was positive for IAV and 20 of those fairs (30.3%) had more than one IAV genotype circulating in the pigs. An overall 3-year prevalence of 9.7% (95% CI: 9.1-10.3) was observed. However, the prevalence of IAV in swine significantly decreased from 2014 to 2015 when the proportion of fairs with IAV infected pigs decreased from 30.14% (95% CI: 19.6-40.1) in 2014 to 13.5% (95% CI: 6.9-20.1) in 2015. We found 19 IAV genotypes infecting swine and 6 IAV genotypes in humans, with 5 genotypes in both host species. There was a positive correlation between the number of fairs at which a genotype was present among the pigs and the number of human cases of that same genotype. Additionally, we showed that H3N2v isolates clustered tightly with exhibition swine isolates that were prevalent in the same year. Our data indicate that there are multiple genotypes of swine-lineage IAV that can infect humans, and highly prevalent IAV genotypes during a given year are the strains most likely to infect humans.

Committee: Andrew Bowman DVM, MS, PhD (Advisor); Armando Hoet DVM, PhD (Committee Member); Gregory Habing DVM, PhD (Committee Member); Kurt Stevenson MD, MPH (Committee Member) Subjects: Animal Diseases; Animals; Public Health

Master of Science, The Ohio State University, 2016, Allied Medicine

Background: Development of critical thinking skills in higher education, especially in the allied health or medical fields, is well-documented as a crucial part of any undergraduate education. There is a need, in respiratory therapy education specifically, to create a resource(s) that develops critical thinking skills and application of knowledge skills in clinical settings. The purpose of this study is to determine if a student developed, online, respiratory disease management resource improves critical thinking skills in undergraduate respiratory therapy students. Methods: Utilizing previously established assignments to assess progress, 1st year respiratory therapy students at The Ohio State University developed their own online, respiratory disease management database in the form of a Wiki. The grades received by the 1st year respiratory therapy students were then compared to the grades received on the identical assignments by the 2nd year respiratory therapy students the previous year. 1st year student were then asked to complete a survey to gather their subjective feelings about the database creation and whether or not they perceived it as helpful in critical thinking skill development. Results: 39 students were enrolled in this study; 20 currently enrolled in their 2nd year and 19 currently enrolled in their 1st year. The study findings indicated, with a few exceptions, that 1st year students had higher scores on the specific assignments chosen to monitor critical thinking skill development. Four scores on early assignments were significantly higher for 2nd year students, but the final assignment showed a statistically significant improvement in scores by 1st year students. 73.7% 1st year students completed the survey at the end of the study. Survey respondents used the database occasionally to often when completing assignments geared towards assessing critical thinking and a majority of respondents (92%) perceived the creation of this resource as useful in a (open full item for complete abstract)

Committee: sarah varekojis (Advisor); georgianna sergakis (Committee Member); crystal dunlevy (Committee Member) Subjects: Health Education; Health Sciences

PhD, University of Cincinnati, 2016, Medicine: Biostatistics (Environmental Health)

Particulate matter (PM) has long been known to have a negative effect on public health. Epidemiological studies associating air pollution and other sources of PM often rely on land use modeling for exposure assessment. This approach relies on the association of characteristics of the surrounding land with PM concentrations. Land use regression (LUR) is the most commonly implemented land use model and has several drawbacks, including model instability due to correlated predictors and an inability to capture non-linear relationships and complex interactions. Here, I utilize the machine learning random forest model within a land use framework to generate a novel land use random forest (LURF) model. Using ambient air sampling data from the Cincinnati Childhood Allergy and Air Pollution (CCAAPS) study, I developed LURF and LUR models for eleven elemental components of particulate matter, including Al, Cu, Fe, K, Mn, Ni, Pb, S, Si, V, Zn. We show that LURF models utilized a higher number and more diverse selection of land use predictors than the LUR models. Furthermore, the LURF models were more accurate and precise predictors of all elemental PM concentrations, except for Fe, Mn, and Ni. To extend the usability of the LURF models, I utilized the recent application of the infinitesimal jackknife (IJ) to the random forest model in order to estimate the prediction variance. The IJ theorems were originally verified under the assumptions of traditional random forest framework, namely using CART trees and bootstrap resampling. Alternatives to the traditional random forest, such as subsampling instead of bootstrap resampling and conditional inference trees instead of CART trees have been shown to increase the accuracy of the random forest algorithm and eliminate its variable selection bias. Here, I conduct simulation experiments to show that the IJ performs well when using these random forest variations. Specifically, using the conditional inference tree instead of the C (open full item for complete abstract)

Committee: Patrick Ryan Ph.D. (Committee Chair); Roman A. Jandarov PH.D. (Committee Member); Marepalli Rao Ph.D. (Committee Member) Subjects: Biostatistics

PHD, Kent State University, 2015, College of Arts and Sciences / Department of Psychological Sciences

Research has shown that the rate of depression in patients with COPD is higher than in other chronic diseases and that depression in this population negatively impacts self-care (Qian et al., 2013). Unfortunately, depression is poorly managed in COPD patients (Norwood & Balkissoon, 2005); thus necessitating the development of alternative ways to manage COPD in the home. Often the burden of COPD management falls on an informal caregiver, who is expected to provide instrumental support by assisting with activities of daily living (Gardiner et al., 2010). Unfortunately, many informal caregivers lack the mental and physical capacity necessary to perform these activities. The aim of this investigation was to identify whether mental and physical morbidity in the informal caregivers of depressed patients with COPD influenced healthcare utilization in this population. Participants for this study were 50 COPD patients and their caregivers who were recruited from the pulmonary physicians' practices, pulmonary function testing laboratories, and pulmonary rehabilitation programs associated with a single, multi-center health system. The patients were asked to complete an in-home interview that addressed questions related to symptomology, adherence, healthcare utilization, and depression. In addition, presence of anxiety, depression, and physical morbidity were addressed during the caregiver interview. A moderated mediation analysis was conducted using structural equation modeling. Results of the analysis showed that patient depression was related to increased self-report of symptoms related to shortness of breath, decreased willingness to adhere to health behaviors, and increased healthcare facility admissions. Unexpectedly, the presence of physical morbidities in the caregiver attenuated the positive relationship between patient depression and healthcare utilization, although this became non-significant after controlling for patient age and COPD severity. In conclusion, results (open full item for complete abstract)

Committee: Joel Hughes PhD (Advisor); John Gunstad PhD (Committee Member); John Updegraff PhD (Committee Member); Barbara Drew PhD (Committee Member); Wendy Umberger PhD (Committee Member) Subjects: Experimental Psychology; Health

Master of Science, The Ohio State University, 2009, Allied Medicine

Student learning is an important consideration in the development of course designs. By recognizing and holding a better understanding of student learning styles, educators are able to build a better framework for more efficient and desirable teaching methods. This study aimed to find a relationship between allied health students' classroom and clinical learning styles. Two Kolb Learning Style Inventories were administered to a total of 82 seniors in The School of Allied Health at The Ohio State University. This sample included students in the Athletic Training, Medical Dietetics, Radiological Sciences, and Respiratory Therapy programs. The students were asked to fill out the first questionnaire in regards to their didactic classroom learning. The second survey was administered at least one week after the first and the students were asked to fill out this questionnaire in regards to their current clinical experience. The data collected from the questionnaires was then entered into the Statistical Package of the Social Sciences for analyses. Overall, in the didactic classroom setting, 24.2% (n=16) of the students were Divergers, 28.8% (n=19) were Accommodators, 19.7% (n=13) were Convergers and 27.3% (n=18) were Assimilators. In the clinical settings 27.8% (n=20) of the students were Divergers, 36.1% (n=26) were Accommodators, 23.6% (n=9) were Convergers and only 12.5% (n=9) were Assimilators. Learning style did not change for 66.7% (n=10) of Athletic Training Majors. Over half of the Medical Dietetics (53.8%,n=7), Radiological Sciences (72.7%, n=8) and Respiratory Therapy (52.9%, n=9) students' Learning Style did change with the switch of the setting from classroom to clinical. It was found in Cross tabulation that the Accommodating learner was least likely to change style with setting (75%, n=12) with the Diverger style next at 69.2%. The change of style that was least likely to occur was between the Converger and Diverger (n=2) and the Assimilator and Accommodator (open full item for complete abstract)

Committee: Jill Clutter PhD (Advisor); Laura Harris PhD (Committee Member); Georgianna Sergakis PhD (Committee Member) Subjects: Adult Education; Behaviorial Sciences; Continuing Education; Education; Educational Evaluation; Educational Psychology; Educational Theory; Health; Health Care; Health Education; Higher Education; Sports Medicine; Teacher Education; Teaching

PHD, Kent State University, 2010, College of Education, Health and Human Services / School of Foundations, Leadership and Administration

The purpose of this study was to evaluate the efficacy of admission standards that have been used for undergraduate allied health and nursing programs. Five professions met the initial criteria including the awarding of a 2- or 4-year degree, a national board examination administered upon program completion, and published research covering entrance standards. The professions are: dental hygiene, medical technology, registered nursing, radiologic technology, and respiratory therapy. Random-format meta-analysis was used to evaluate 28 years of research gathered from both published and unpublished documents. Length of time used for data collection was defined by published research using outcome parameters, including national board examinations. Forty-eight studies resulted in 230 comparable effect size variables. Twenty-one predictors were identified in the research and were measured against 4 criterion variables. ACT English, entrance grade point average, and biology were statistically significant predictors for all 5 professions. While no predictors had a shared variance across all professions, 8 predictors resulted in shared variance when moderators were considered. These included: ACT English, math, science, and social science; chemistry; entrance grade point average; SAT verbal; and a specialized test, the AHPAT. Each of these measures used board scores as the criterion measure. Moderators included the length of time used to gather data, year of study or publication, whether the study was published, and the profession. Profession had the largest effect on the statistical significance of the predictors. Two- and 4-year programs were identified as subgroups. Considering the moderator, profession, only 2 predictors were affected by the subgroups: entrance grade point average in Medical Technology and ACT science in Registered Nursing.

Committee: Mark Kretovics PhD (Committee Chair); Susan Iverson EdD (Committee Member); Frederick Law PhD (Committee Member); Alicia Crowe PhD (Other) Subjects: Higher Education

Doctor of Philosophy (Ph.D.), Bowling Green State University, 2011, Psychology/Clinical

Research has generally shown that worry leads to a decrease in respiratory sinus arrhythmia (RSA) and cardiac vagal activity. Low vagal activity has been associated with a variety of physical ailments, including cardiovascular disease. However, research has also revealed inconsistencies in the relationship between worry and RSA, and the assessment of possible moderating relationships is lacking. The present study investigated the relationships among trait and induced worry on RSA, as well as a number of health behavior moderators, in a sample of undergraduate students. One hundred-fifteen participants completed a pretest measure of worry along with a number of protective health behavior measures. While having their heart rate measured (RSA), participants engaged in a 10-minute baseline condition, a 5-minute worry condition, a 5-minute control condition, and a 10-minute recovery condition. Consistent with predictions, high trait worriers who reported higher levels of physical activity displayed significantly higher levels of RSA, relative to high trait worriers who also reported lower levels of physical activity. Moreover, the same effect was not found for low trait worriers. Possible cardiovascular health implications, as well as implications for effects of physical activity on worry from an afferent perspective, are discussed.

Committee: William O'Brien Ph.D. (Advisor); Robert Carels Ph.D. (Committee Member); Casey Cromwell Ph.D. (Committee Member); William Morrison Ed.D. (Committee Member) Subjects: Health Sciences; Physiological Psychology; Psychobiology; Psychology