Master of Social Work, The Ohio State University, 2018, Social Work

Purpose: As record keeping and administrative technology provides for innovation and improvements in many sectors, the field of mental health lags in adopting health information technology (HIT) (Perron, 2010). This leads to care gaps, potential inefficiencies, and unnecessary cost (Puskar, Aubrecht, Beamer, & Carozza, 2004). The objective of the study is to describe the prevalence of HIT use among mental health organizations and identify characteristics that are associated with HIT use. The results have implications for organizational leaders and policy makers responsible for technology decision making in the mental health field. Methods: Secondary data was drawn from the 2014 National Mental Health Services Survey (NMHSS) conducted by Substance Abuse and Mental Health Services Administration (SAMHSA). The NMHSS measured whether organizations use computers, paper or both for 14 internal, external, and potentially external processes. Descriptive analysis was used to define the prevalence of HIT adoption, and regression analyses were used to examine organizational features (ownership, facility type, number served, licensing, and funding/payment types) related to HIT adoption. Results: Respondents reported low levels of overall HIT adoption, with internal processes having higher rates of adoption than external and either internal or external processes. Organizations with private, for profit ownership or public ownership, large numbers served, and residential care facility adopted HIT to a greater degree than other organizations. Implications: There is a need for strategic planning, regulation, and resources originating from entities that have influence over the entire field of mental health, not just particular organizations. Simply doing the same thing that has been done in other sectors, such as healthcare, would not be a successful endeavor for mental health. Resources, supports, and mandates should be put in place to boost HIT adoption. Special c (open full item for complete abstract)

Committee: Alicia Bunger PhD (Advisor); Njeri Kagotho PhD (Committee Member) Subjects: Information Technology; Mental Health; Social Work

PHD, Kent State University, 2018, College of Education, Health and Human Services / School of Lifespan Development and Educational Sciences

The purpose of this quantitative study was to determine whether a data driven profile of incoming youth can predict pro-social behavior, institutional misconduct, and length of stay during their term of incarceration at a juvenile rehabilitation facility. The analysis used data of 65 juvenile participants obtained during their intake process at a regional, juvenile rehabilitation facility, as well as the youths' performance during their commitment. Independent variables include age, sex, and race. Along with the demographic information, continuous data results from the Massachusetts Youth Screening Instrument—Version 2 (MAYSI-2) and How I Think Questionnaire (HIT) were part of the statistical pool utilized by the analysis. Dependent variables consisted of points for pro-social behavior, disciplinary write-ups for misconduct, and length of stay. Multiple regression and correlational analyses were applied to the data yielding varying degrees of correlations and statistically significant predictors of pro-social behavior, misconduct, and length of stay. The results of the study found that minorities had higher pro-social and misconduct rates than white youth. In addition, the MAYSI-2 angry-irritable and traumatic experiences, along with race, were predictive of institutional misconduct. Furthermore, correlations were evident between HIT scores and misconduct rates, as well as HIT and MAYSI-2 scores, suggesting some similarities in assessment qualities between the two measures. Juvenile correctional facilities can apply these findings by proactively implementing intervention strategies and services focusing on incoming youth exhibiting risk factors leading to negative behavior patterns. For example, anger management training would be beneficial for those exhibiting elevated scores on the angry-irritable subscale.

Committee: Pamela Luft (Committee Co-Chair); Brian Barber (Committee Co-Chair) Subjects: Special Education

Master of Science (MS), Ohio University, 2014, Exercise Physiology-Research (Health Sciences and Professions)

The purpose of this study was to determine the acute and residual effects of high intensity interval training on a cycle ergometer on fasting glucose and insulin and postprandial glycemic and insulinemic responses; a secondary purpose was to determine the effects of the exercise training on body composition and aerobic fitness. The exercise sessions consisted of six 20-second sprints on a cycle ergometer performed against a resistance equivalent to 7.5% of subjects' body weight; each sprint was separated by 4 minutes of active recovery. Exercise sessions were performed 2 to 4 days apart. A meal challenge was performed prior to the first exercise session, during which time a baseline blood sample was obtained, a standardized mixed meal was provided, and subsequent blood sampling occurred over a 3-hour period. This was repeated 48-72 hours after the final exercise session, and again 5-7 days later. In conclusion, in this group of apparently healthy, but sedentary men, six sessions of high intensity interval training on a cycle ergometer was not sufficient to improve fasting or postprandial glycemia or insulinemia but was sufficient to elicit an improvement in body fat percentage and cycling performance.

Committee: Michael Kushnick (Advisor); Michael Clevidence (Committee Member); Rika Tanda (Committee Member) Subjects: Alternative Medicine; Health Sciences; Kinesiology; Physiology; Sports Medicine

Doctor of Philosophy, The Ohio State University, 2013, Public Policy and Management

This work examines the issue of take-up of social assistance in the context of a case study of a foreclosure-mitigation program in Ohio known as Restoring Stability. The successful implementation of public assistance programs depends on a wide variety of factors, which have been the subject of much speculation, research, and debate within the field of Public Affairs. The important role of take-up in programmatic success has been relatively overlooked in the literature to date. The main contribution of this research is that take-up is not conceived of as a one-time, dichotomous choice on the part of potential beneficiaries as to whether to participate in an assistance program or not, but rather it is an iterated series of choices and actions on the part of eligible individuals and program administrators. Building on the work of Heckman and Smith (2004), it is argued here that a simple measure of the take-up rate which captures only the percentage of the total eligible population who participate in the program does not convey any information about the specific barriers to participation and, thus, is of little assistance to public administrators tasked with maximizing take-up. Instead, it is useful to decompose the take-up process into its component stages: eligibility, awareness, application, acceptance, and enrollment. This work examines several of the barriers to participation that appear at these stages and, unlike most work on the subject, assumes that administrative decisions and program design play an important role in establishing such barriers. Awareness of programs is not exogenously determined but, as least partially, is the result of program outreach and marketing efforts. As such, lessons can be taken from the for-profit marketing literature. Similarly, the application stage is not as straightforward is it is often assumed, and potential beneficiaries can face real costs in deciding whether or not to apply for program assistance. Finally, program admi (open full item for complete abstract)

Committee: Robert Greenbaum (Committee Chair); Stephanie Moulton (Committee Member); Jason Seligman (Committee Member); Holly Holtzen (Committee Member) Subjects: Public Administration; Public Policy

Master of Science, The Ohio State University, 2012, Statistics

Much health policy research has examined strategies to increase health provider quality and efficiency, and to improve patient outcomes. The American Recovery and Reinvestment Act (ARRA) and the Patient Protection and Affordable Care Act (PPACA) promote the adoption of electronic health records (EHR) as a mechanism of medical costs control and quality improvement meant to complement the national expansion of health care (Steinbrook, 2009). Given the EHR initiatives, Ohio Medicaid is pursuing the examination of Ohio-based EHR adoption and expansion. As an enticement for greater degrees of EHR adoption, Ohio is implementing the Medicaid Provider Incentive Program (MPIP) to assist practices having financial difficulties adopting EHR. To determine Ohio's EHR take up, in the fall of 2010 the Ohio Department of Job and Family Services and The Ohio Colleges of Medicine Government Resource Center administered the Electronic Health Records Survey to determine the use and implementation of EHR. The goal of this thesis is to improve the estimate of EHR take up rates by medical practitioners in Ohio. Those qualifying for incentives are medical practitioners, primary care physicians, medical specialists, dentists, nurse practitioners, and nurse midwives with a Medicaid patient volume above 30%, and pediatricians with a Medicaid patient volume above 20%. Two estimation techniques were employed to estimate Ohio's EHR take up rate: (1) a weighted stratified sampling estimator, which was the technique originally used, and (2) a new technique using a small area estimation estimator. To estimate the number of practitioners in Ohio eligible for thee MPIP, we will examine and compare the results of these two procedures.

Committee: Elizabeth Stasny Phd (Advisor); Eloise Kaizar Phd (Committee Member) Subjects: Statistics

Master of Science, The Ohio State University, 2011, Computer Science and Engineering

Modern compilers of self-optimizing computing systems require the values of hardware parameters such as the capacity of cache and number of entries in translation lookaside buffer (TLB). Additional information such as the cache block size and page size along with the Hit Time and Miss Penalty of these hardware entities are needed to apply static and dynamic compiler optimization techniques. Currently, no tool or approach is robust enough to provide accurate information regarding the underlying hardware. They fail when encoutering multiple levels of cache and TLB present in current generation of processors. In this Thesis, we describe a staggered and robust approach to first detecting the hardware entities and their sizes and then disambiguating between the entities by deducing their block sizes. We describe the novel algorithms for measurement of the hardware parameters and the mathematical intuition behind the disambiguation. Experimental evaluations of this technique on traditional workstations, laptops and servers show that our approach produces more accurate and complete results than existing tools.

Committee: Dr. Ponnusamy Sadayappan Phd (Advisor); Dr. Atanas Rountev Phd (Committee Member) Subjects: Computer Engineering; Computer Science

Master of Computer Science, Miami University, 2010, Computer Science and Systems Analysis

Spaced seeds have proved to be invaluable in BLAST-like homology searches of large genomic sequences. But the problem of evaluating spaced seeds for this purpose is computational challenging, while the problem of finding optimal multi-seed sets is known to be NP-hard. In this thesis, we first explored the unpublished details and implemented the dynamic programming algorithm of the Li et al. PatternHunter group to address the problem of evaluating a multiple spaced seed set, and implemented our own version of this algorithm. We then developed a genetic algorithm to address the problem of optimal multi-seed set selection and found that our solutions superior to the greedy algorithm. Finally we implemented two additional tools with the goal of applying our results to the problem of transposable element identification.

Committee: John Karro PhD (Advisor); Alton Sanders PhD (Committee Member); James Kiper PhD (Committee Member) Subjects: Bioinformatics; Computer Science

PHD, Kent State University, 2012, College of Education, Health and Human Services / School of Lifespan Development and Educational Sciences

This study determined and recommended empirically-based criteria for performing person matching as a psychometric scoring methodology to predict specialty selection for a profession. This study compared the predictive hit rates of standard scoring and three calculations of person matching based upon ex post facto data collected on 5,143 medical students who had taken an interest inventory and had entered their medical residency. The results suggested the following conclusions to the five hypotheses. First, the inclusion of all 150 raw item scores when person matching produced more accurate hit rates than when using the 18 scale scores. Person matching on the item level appears to be more accurate than person matching on the factor or scale level. Second, using the top 20 person matches produced the highest hit rates as compared to the top match and top 5 and 10 singular matches. Third, standard scoring outperformed person matching for the top match. However, the 150 items and the 30 items were able to outperform standard scoring when looking beyond the top match to offer medical students several medical specialties to research for further consideration. Fourth, gender differences were less pronounced for person matching than standard scoring. Fifth, the predictive hit rates were slightly higher when combining standard scoring and person matching psychometric scoring methodologies to person match based upon only 30 items on the inventory. In conclusion, person matching is worthy of considerable research attention in interest inventories as the benefits to women and a quickly-changing, global workforce could be immense.

Committee: Mark Savickas Ph.D (Committee Chair); Jason McGlothlin Ph.D. (Committee Member); Cynthia Symons D.Ed. (Committee Member) Subjects: Academic Guidance Counseling; Educational Tests and Measurements; Psychological Tests