Master of Arts (MA), Bowling Green State University, 2022, Media and Communication

Scholarship on conspiracy theories, a relatively young domain of research, lacks a firm theoretical foundation. The existing literature on conspiracy theories includes numerous distinct theoretical perspectives explaining the antecedents of conspiracy beliefs. While some evidence exists to support each perspective, no single theory or model accounts for the range of variables and effects associated with belief in conspiracy theories. This thesis discusses the various ways conspiracy belief and conspiratorial thinking have been conceptualized, the variables they include, and the strengths and weaknesses of each approach. This study proposes that the Heuristic Systematic Model may serve as a means of understanding the effects associated with belief in conspiracy theories. To test this premise, 195 participants were recruited for an online study. Participants read a short story about a mysterious epidemic localized to a small town with no clear cause. Participants then rated the plausibility of two conflicting explanations for the events presented in the story, one conspiratorial and one non-conspiratorial. Anxiety and systematic thinking were manipulated to test their influence on the perceived plausibility of the two stories. Results suggest individuals processing information more heuristically were more likely to endorse a conspiratorial explanation for ambiguous events, whereas individuals processing information more systematically were less likely to endorse conspiratorial explanations. These results support the idea that conspiracy beliefs can be attributed to greater heuristic processing.

Committee: Frederick Busselle Ph.D (Committee Chair); Laura Stafford Ph.D (Committee Member); Yanqin Lu Ph.D (Committee Member) Subjects: Communication

PHD, Kent State University, 2024, College of Arts and Sciences / Department of Computer Science

Eye trackers are an important tool in cognitive science research. Advances in eye-tracking technology reduce the invasive nature of early forms of the equipment along with the costs to acquire the devices for research. As such, eye-tracking is becoming an essential device for research on software engineering and program comprehension. The main focus of this work is to study how developers read and understand source code in the context of various software engineering tasks (e.g., debugging, summarizing code, defect localization, etc.). However, eye-tracking devices create challenges for researchers. Eye tracking devices have inherent margins of error in sampling introduced by various factors, which introduces errors in data sampling during studies that cannot be controlled. As such, despite best efforts, eye-tracking data always needs some form of correction to help identify and remove invalid data or adjust the data as samples drift or become displaced over time by participant movements, fatigue, or other factors. The processes used to correct eye-tracking data are time-consuming and require trial and error to correct the data reasonably while mitigating the impact of the corrections. Additionally, eye-tracking infrastructure to support program comprehension studies with realistic stimuli in natural software development environments is limited. This dissertation addresses these limitations. Focusing on program comprehension-based studies using eye-tracking, SrcGaze, an algorithm to support the automatic correction of fixation gaze event data using source code stimulus, is presented. Compared to the state-of-the-art fixation correction methods, SrcGaze is capable of 73\% agreement with manually corrected fixation data. The algorithm also has a linear run time, making it the most computationally efficient approach; it can correct over 44,000 fixations in only 6 seconds. During this work, contributions are also made to iTrace, an infrastructure to support eye-tra (open full item for complete abstract)

Committee: Jonathan Maletic (Committee Chair); Jong-Hoon Kim (Committee Member); Qiang Guan (Committee Member); Michael Carl (Committee Member); Bonita Sharif (Committee Member); Jocelyn Folk (Committee Member); Michael Collard (Committee Member) Subjects: Computer Science

Doctor of Philosophy (PhD), Ohio University, 2023, Journalism (Communication)

The study examined the effects of emotional appeals, message sources, and social endorsement on message elaboration, social media engagement, and other persuasive outcomes. The study employed a 2 (emotion appeals: guilt and hope) x 2 (message sources: influencers and organizations) x 2 (social endorsement: high and low likes) between-subjects design. From the perspective of a dual-processing theory (i.e., heuristic-systematic model), the study tested how systematic cues (i.e., emotional appeals) and heuristic cues (i.e., message sources, and social endorsement) influenced the persuasive effects of a campaign message. 350 participants were recruited for an online experiment through a panel service company. Each participant was exposed to a nonprofit organization's Facebook message encouraging blood donations. The results showed that hope appeals produced higher message elaboration than guilt appeals, but guilt appeals had higher comment intentions and greater donation intentions than hope appeals. Also, influencers produced greater like and comment intentions, higher self-efficacy, and better attitudes than organizations. Moreover, high likes had higher message elaboration than low likes. Furthermore, influencers produced greater social media engagement than organizations in hope appeals with high likes. Theoretical and practical implications were discussed.

Committee: Jatin Srivastava (Committee Chair) Subjects: Communication; Mass Communications; Public Health

Doctor of Philosophy, The Ohio State University, 2022, Communication

Across the world and fueled by climate change, natural disasters are increasing in their geographic distribution and intensity. Theoretically guided message design can inform people about their disaster risk and persuade them to change their attitudes and behavioral intentions regarding preparedness. The purpose of this study was to use theory, including framing and the heuristic-systematic model, to inform message design to persuade people about hurricane preparedness. Specific message features under investigation included language framing, temporal framing, and the use of decision aids. The results suggest that using easier language to communicate about hurricanes and preparedness increased people's perceptions of their ability to process the information at hand, which increased systematic processing and led to persuasive outcomes. Further, results related to decision aids indicate that decision aid selection can serve as a behavioral outcome of systematic information processing and also amplify persuasive effects. Temporal framing did not increase motivation to process information, systematic processing, or persuasive outcomes. Overall, results suggest that easy language and use of decision aids are effective message features to facilitate persuasion about hurricane preparedness. More generally, using theory to inform message design can help researchers and practitioners optimize persuasive messaging.

Committee: Hillary Shulman (Advisor); Graham Dixon (Committee Member); Shelly Hovick (Committee Member); Kelly Garrett (Committee Member) Subjects: Communication

Doctor of Philosophy (PhD), Ohio University, 2021, Journalism (Communication)

Spread of mis- and dis-information has emerged as one of the most concerning threat to democratic processes in the United States. Who is to blame for such a rise in the spread of mis- and dis-information is yet to be decided, however, this study aimed to explore how such forms of information is consumed and believed by the audiences. This research expands on our understanding of how ideological cues work to promote mis/disinformation consumption along with other factors like, political opinion leaders, cognitive dissonance and personal ideology. Furthermore, the study explores the two-step selective evaluation process, which an information consumer goes through before making any decision on the information. The decision is then further rationalized in post-decisional effects. A survey experiment was conducted on 429 respondents who showed that any information content will be palatable to them if those information carries ideologically confirming cues. Moreover, the study used opinion leader as manipulation to test cognitive dissonance, consonance, and resonance against the personal ideology of the respondents to further divulge into the process of mis/disinformation consumption. A deductive thematic analysis of audience responses gives a direction to the decision-making process when faced with congruent or incongruent information.

Committee: Victoria LaPoe (Advisor) Subjects: Cognitive Psychology; Communication; Journalism; Mass Communications; Mass Media; Political Science

Master of Science, The Ohio State University, 2021, Mechanical Engineering

The EcoCAR Mobility Challenge is a four-year design cycle which tasks teams with designing a hybrid Chevrolet Blazer that serves the commuter market by efficiently providing a Mobility-as-a-Service. In Year 1 of the competition the OSU EcoCAR team selected a series-parallel hybrid architecture and defined vehicle performance goals to be achieved at the end of the development cycle. In Year 2, the stock GM Blazer was modified and hybrid propulsion components – a downsized 2.0L engine, P0 motor and P4 motor – were integrated and rear powertrain modifications were made. A full vehicle model, driver model, and HIL test harness for the EcoCAR hybrid vehicle was set up and the development of a Hybrid Supervisory Controller (HSC) was started. Components were bench tested after integration into the vehicle. In Year 3, the various algorithms necessary to achieve baseline functionality of the EcoCAR vehicle were developed and tested. A V-systems engineering process was followed to design control strategies from defined system requirements and constraints. Engine torque control was achieved by manipulating ACC (Adaptive Cruise Control) CAN messages through an Engine Control Module gateway. A simple REM torque assist strategy and a series charging algorithm utilizing the BAS were developed and implemented in the vehicle. The vehicle completed 200+ miles of VIL testing at the Transportation Research Center (TRC), maintaining SoC between 30-80% and meeting acceleration requests in performance mode. Methods to improve fuel economy with an energy management strategy has also been discussed for refining the HSC in Year 4.

Committee: Shawn Midlam-Mohler (Advisor); Rizzoni Giorgio (Committee Member) Subjects: Automotive Engineering; Mechanical Engineering

Master of Science, The Ohio State University, 2019, Mechanical Engineering

The automotive industry is driving towards electrification. As the emission and fuel economy standards get more stringent, manufactures are electrifying their vehicle platforms by developing more hybrid electric vehicles. Although new technology boosts the fuel economy, it also brings new challenges. One of them is that customers often find discrepancies between the rated fuel economy number and the number they get during real world operation. Therefore, there is a need to investigate the issue and develop a new calibration process for optimizing the HEV fuel economy over both certification and real-world operation. In this research, a model-based calibration process is developed. The process uses meta-heuristic algorithms to optimize five look-up tables that are relevant to fuel economy of the HEV. Four different meta-heuristic algorithms, namely PSO, GA and two hybrids, are investigated and compared. It is found that PSO has reasonably good performance and can deliver its performance consistently under different conditions. Other algorithms may have better performance under certain scenarios, but they are sensitive to constraints in test problems and fail to get rational solutions in the real problem. The research also investigates methods to reduce number of parameters to optimize, the initialization of the optimization set and ways to generate representative drive cycles based on real-world driving data. The important thing is that these methods are not vehicle-specific and therefore can be migrated to calibration of other HEVs easily.

Committee: Giorgio Rizzoni (Advisor); Marcello Canova (Committee Member) Subjects: Mechanical Engineering

Master of Science (MS), Ohio University, 2019, Industrial and Systems Engineering (Engineering and Technology)

This thesis defines different variants of the cluster-picking order batching problem (OBP) and proposes several problem-solving techniques to solve the problems. The basic OBP is commonly referred to in the literature as the grouping of customer orders into batches in a manner that minimizes the total distance such that the batch capacity is not violated. This problem is of high importance in the warehousing industry since the majority of warehouse costs arise from order picking activities. The first variant involves solving the OBP for a single work interval, where all orders must be completed by the end of the interval's duration. The objectives addressed are minimizing the total distance traveled, aisle congestion and the total number of pickers. The second variant addresses the scenario in which customer orders are set to have distinct pick-by times, corresponding to different waves or work intervals, in addition to allowing some orders to be picked in earlier intervals to improve the efficiency of grouping. In this variant, the OBP is solved for multiple intervals in order to determine the order-to-batch and batch-to-interval assignments simultaneously such that the total distance, overall aisle congestion, maximum number of pickers needed, and the total number of batches are minimized, whilst taking into account the limit on the number of early orders. In addition, the assignment of multiple batches to pickers is also incorporated as an extension to variant 2. The s-shape routing strategy and single-block rectangular layouts with parallel aisles and are applied throughout the thesis. Moreover, the problem-solving techniques developed for the OBP variants in this thesis are greedy heuristic, differential evolution algorithm and mathematical models. The greedy heuristic primarily focuses on minimizing the total distance, whereas the differential evolution algorithm and mathematical models are able to address multiple objectives. The problem-solving techniques ar (open full item for complete abstract)

Committee: Gursel Suer PhD (Advisor); Dale Masel PhD (Committee Member); Tao Yuan PhD (Committee Member); Ana Rosado Feger PhD (Committee Member) Subjects: Engineering; Industrial Engineering; Operations Research

Doctor of Philosophy (PhD), Ohio University, 2019, Industrial and Systems Engineering (Engineering and Technology)

Control of costs and quality of patient care are both important concerns for healthcare systems. Improved management of supplies and instruments for operating rooms provides an opportunity to reduce costs while still maintaining the current level of patient care. Operating rooms are a main cost center within hospitals and previous research has shown that improved management of disposable supplies and sterile instruments, which are requested by surgeons through preference cards, provides an opportunity for significantly reducing surgical costs. Primarily, this means not opening or exposing items that aren't needed, which requires the items to be disposed or resterilized, even if they haven't been used. Additional improvements can be achieved by reducing duplication of instruments in inventory due to the variations in preference cards. In this research, various optimization models and solution methods are developed for managing surgical supplies and sterile instruments. The optimization models deal with the decision of configuring trays of instruments, as well as determining the quantity of surgical supplies to be stored in different locations in such a way that ensures: (1) surgeons' requirements are met, (2) inventory and reprocessing costs are minimized. The models also captures historical usage pattern of instruments and supplies and allow surgeons to make better decisions about the items included on the preference cards, and which items can be opened at the time of need as opposed to being opened before a procedure.

Committee: Dale Masel (Advisor); Gary Weckman (Committee Member); Ashley Metcalf (Committee Member); Kristin Schuller (Committee Member); Benjamin Sperry (Committee Member) Subjects: Health Care; Industrial Engineering; Operations Research

Doctor of Philosophy, The Ohio State University, 2018, Plant Pathology

More than 700 million tons of rice is produced on an annual basis constituting roughly twenty-percent of all calories consumed by humans. This fact illustrates how the study of protecting and improving rice yield is acutely important to a growing world population. Outbreaks of rice blast disease, caused by the fungus Magnaporthe oryzae, have led to major losses with this disease being the main limiting factor in rice production in many regions. The devastation caused by this disease has inspired the intense study of the molecular basis of the disease, including avirulence and virulence factors. By using the gene-for-gene model, many resistance (R)-genes have been identified, allowing breeders to craft rice cultivars that are resistant to many strains of the fungus. However, much is still unknown concerning the cognate avirulence (Avr) and virulence genes. This disparity is due to the lack of recognized sequence patterns of these genes. One goal of this study is to identify fungal genes that are related to M. oryzae virulence in hopes of better understanding the relationship between this hemibiotrophic pathogen and its host. M. oryzae strains KJ201 and CHNOS60-2-3 were utilized after demonstrating a difference in pathotype on the rice cultivar C101A51 Previous studies in the Mitchell lab have identified five candidate genes coding for punitive virulence factors by performing random insertion Agrobacterium tumefaciens-mediated transformation (rATMT), infection assays, and TAIL-PCR. These genes were cloned into the strain CHNOS60-2-3, which is naturally compatible with the C101A51 rice. By infecting C101A51 plants with the CHNOS60-2-3 transformants, and assessing disease, we were able to determine that homoaconitase MOLYS4 is involved in virulence for M. oryzae. Learning assessments dictate the environment of our classrooms. With an ever-increasing pace of life, it is becoming more important that instructors find meaningful and efficient ways to use di (open full item for complete abstract)

Committee: Thomas Mitchell PhD (Advisor); Jason Slot PhD (Committee Member); Robert Tabita PhD (Committee Member); Guo-Liang Wang PhD (Committee Member) Subjects: Plant Pathology

Doctor of Philosophy (Ph.D.), Bowling Green State University, 2018, Media and Communication

Louisa Ha, Advisor The present cross-cultural study applies the regulatory focus theory developed by Higgins and modifies the cultural dimensions proposed by Hofstede to explore and compare the relationships between cultural values and the focused strategic means college consumers use in China and the US. In total, 377 Chinese and 403 US college students participated in a survey to reveal the relations between variables of app download and their cultural values. In addition, for a deeper and insightful understanding of the app download behavior, the method of semi-structured interview was used to raise participants' and the researcher's consciousness of and critical reflections upon app download processes and experiences. The research results are five-fold: First, Chinese college students share similar scores of four cultural dimensions with the US college students, and there is no difference in indulgence between the two countries. Second, country is a more powerful variable than cultural dimensions in model testing in terms of differentiating consumers' regulatory focus. US consumers are more likely to be promotion focused and Chinese consumers are likely to be prevention focused. Third, promotion focused consumers are likely to seek both hedonic and utilitarian gratifications, and to heuristically process information. Fourth, US consumers and consumers who are seeking hedonic gratifications will download more apps of the same type. Finally, the interview data indicate that consumers consider many aspects when evaluating apps. The results of this study also reveal that social norm and perceived behavioral control are important factors affecting the decision-making process in terms of gratifications sought. Social norm also affects regulatory focus and heuristic processing. Future studies of mobile app adoption should include more variables such as application type (e.g., engagement level, free vs. pay, etc.) and other gratifications sought such as social and co (open full item for complete abstract)

Committee: Louisa Ha Dr. (Advisor); Patrick Pauken Dr. (Other); Lisa Hanasono Dr. (Committee Member); Kate Magsamen-Conrad Dr. (Committee Member) Subjects: Communication; Marketing; Mass Communications; Mass Media; Technical Communication; Technology

Doctor of Philosophy in Urban Studies and Public Affairs, Cleveland State University, 2017, Maxine Goodman Levin College of Urban Affairs

What is meant by "science" and whether it is an appropriate model for public administration has been a subject of debate since Woodrow Wilson called for a science of administration in 1887. This dissertation introduces another voice into that debate, the voice of a world-renowned physical chemist named Michael Polanyi. Polanyi's sharp criticism of positivism reinforces the arguments of those questioning the legitimacy of an administrative science, but instead of rejecting it, he constructed an alternative definition of science that recognizes the indeterminacy of reality, the personal nature of knowledge, and the centrality of "the logic of tacit knowing." Because all knowledge is tacit or rooted in tacit knowing, we can know more than we can tell, and tacit knowing becomes evident in the dynamic order of polycentric entities and in their reliance on tradition and the person, constrained by community, and morally responsible for discovery and practice.

Committee: Michael Spicer Ph.D. (Committee Chair); Helen Liggett Ph.D. (Committee Member); Walter Gulick Ph.D. (Committee Member) Subjects: Epistemology; Philosophy of Science; Public Administration

Master of Science (MS), Ohio University, 2017, Industrial and Systems Engineering (Engineering and Technology)

The main purpose of this thesis is to design a global supply chain network for a pharmaceutical company located in Puerto Rico, which manufactures blood sugar strips products. As a design aspect of supply chain, layered cellular manufacturing systems consist of dedicated, shared and remainder cells are considered. One of the main differences between classical cellular manufacturing systems and layered cellular manufacturing systems is, in layered cellular design, some cells may needed to be utilized by various parts of product families. Depending on the required demand and similarity in essential processes or manufacturing characteristics for each product family, products are grouped together and form a product family. If the product family assigned to one cell and just one product family utilizes that cell, the cell is a dedicated cell. Shared cells and remainder cells are employed by, two families and three or more families, respectively. In the first part of this study, a new heuristic layered-cellular manufacturing design approach is proposed and later in the second part, two mathematical models are proposed. The first one is with the objective of minimizing number of cells and cost of opening cells, and the second one is maximizing Net Present Value considering budget limitations for the whole manufacturing system. In the first step, the required number of cells are determined for a product family to meet an acceptable demand coverage (MADC) percentage. It is assumed that customer demand follows normal distribution with the established parameters mean (µ) and standard deviation (s). An attempt is made to increase the utilization of each cell by combining multiple families (thus creating shared and remainder cells) to increase the utilization of each cell as long as it is economically acceptable. As demand coverage increases, revenue also increases. However, this also increases operational costs. The expected profit is calculated based on the expected cell ut (open full item for complete abstract)

Committee: Gursel Suer (Advisor); Tao Yuan (Committee Member); Diana Schwerha (Committee Member); Ashley Metcalf (Committee Member) Subjects: Industrial Engineering

Master of Science (MS), Ohio University, 2017, Industrial and Systems Engineering (Engineering and Technology)

Traditional facility location models used in industry are not adequate to decide facility locations for points of distribution in the context of post-disaster humanitarian logistics (PD-HL). They focus on facility placement and logistics costs, but deprivation costs, or cost of human suffering resulting for the deprivation of critical supplies are often omitted in objective function formulation. This thesis develops a mathematical model to determine facility location for points of distribution (PODs) and optimal delivery strategy for serving demand points. This model considers a combined set covering facility location and point-to-point inventory allocation model with the objective of minimizing social cost; including facility placement, logistics, and deprivation costs. The model is used to analyze the best facility location and delivery strategies in the context of natural disasters. This research highlights the importance of considering the temporal component of the system and resulting deprivation costs when making facility location decisions. This model contributes to the current research by integrating deprivation cost functions into the objective function of facility location decisions in PD-HL. It also allows for demand nodes to be served from multiple PODs. This is significant in conditions when one POD may not have the inventory to serve all demand points that it has been assigned. In practice, this model can help decision makers determine optimal facility locations for PODs as well as approximate the level of service that must be supplied at each demand point to reduce the suffering or survivors at each location. The model is solved using both a mixed integer nonlinear programming model (MINLP) and a heuristic approach developed to address some challenges that nonlinear solution presents.

Committee: Felipe Aros-Vera (Advisor) Subjects: Industrial Engineering

Master of Science (MS), Ohio University, 2017, Electrical Engineering & Computer Science (Engineering and Technology)

Understanding gene expression pattern is crucial in deciphering any observed biological phenotypes. Transcription factors (TF) are proteins that regulate genes by binding to a transcription factor binding site (TFBS) within the promoter region of a gene. Motif discovery is a computational approach that conventionally uses stochastic models, enumeration methods and many other techniques to report candidate motifs (TFBS). These methods generate similar motifs for a TF due to various reasons. Motif selection algorithms successfully identify a small set of motifs that address the specificity problem and coverage problem in motif discovery. However, these selected motifs do not always capture all the binding site preferences for a TF. This study verifies the hypothesis that motif discovery tools generate similar motifs for a transcription factor and once these variants (similar motifs) are identified, they can be used to form a super motif set, which may improve the accuracy of motif discovery. This study introduces the concept of Super motif set, a new model to accurately predict the binding sites for a TF. Two heuristic algorithms are introduced to identify Super motif sets, utilizing motif selection algorithms and a motif comparison tool. These super motif sets identified, capture the biological diversity in TFBS preferences of a TF. The algorithms are valuated on ChIP-seq data for 54 TF factor groups from the ENCODE project. Moreover, the proposed algorithms are used to optimize the motifs that are reported by motif selection algorithms and to report super motif sets in three case studies: Chagas disease, pollen specific HRGP genes in Arabidopsis thaliana and Shigellosis. On an average two motif variants are added to the selected motifs, which improve the accuracy of motif discovery.

Committee: Frank Drews (Advisor); Lonnie Welch (Committee Chair); Jundong Liu (Committee Member); Erin Murphy (Committee Member) Subjects: Bioinformatics; Biology; Biomedical Research; Computer Engineering; Computer Science; Genetics; Molecular Biology

Doctor of Philosophy, Miami University, 2017, English

As American colleges and universities continue to enroll increasing numbers of international students, blatant acts of neo-racism aimed at these students have become more prevalent. Institutions must consider how their representations of international students rhetorically create the “international student” identity and how they can revise their rhetoric to purposefully combat neo-racism and promote inclusivity. In Revising the Rhetoric, I outline a layered methodological approach that utilizes a theoretical framework of critical race theory, whiteness studies, and postcolonial studies; a methodology of institutional critique; and the methods of postmodern mapping and actor network theory. This approach highlights issues of race and culture and emphasizes the importance of specific institutional contexts. For this reason, my project seeks to describe and analyze the rhetoric created by the objects, texts, spaces, and people that make up the network of the Office of International Student Affairs' International Student Orientation. As the first face-to-face interaction between international students and members of The University, the international student identity that it creates has a strong impact on how welcome international students feel at the institution. I trace the rhetoric of the orientation through observations of the orientation events, interviews with stakeholders, and archival documents. I show how this rhetoric has changed over time as it has been affected by outside forces, including politics, government regulations, state funding, and institutional demands. While the rhetoric has changed, there is an underlying practicality that has defined the orientation since its inception and contributes to problematic representations. I offer a heuristic tailored to the specific context of the orientation that makes the rhetoric of practicality visible and can help guide OISA's future rhetorical revisions. Although my project focuses on a single event on one (open full item for complete abstract)

Committee: Michele Simmons (Committee Chair); Jason Palmeri (Committee Member); LuMing Mao (Committee Member); Linh Dich (Committee Member); C. Lee Harrington (Committee Member) Subjects: Higher Education; Minority and Ethnic Groups; Rhetoric; School Administration

Master of Science, University of Akron, 2017, Applied Mathematics

Combinatorial methods have proved to be useful in generating relaxations of polytopes in various areas of mathematical programming. In this work, we propose a discrete-integer linear programming model for a recent version of the Phylogeny Estimation Problem (PEP), known as the Balanced Minimal Evolution Method (BME). We begin by examining an object known as the Balanced Minimal Evolution Polytope and several classes of geometric constraints that result in its relaxation. We use this information to develop the linear program and propose two Branch and Bound algorithms to solve the model. The second algorithm takes advantage of a heuristic known as a large neighborhood search. We provide experimental results for both algorithms, using perfect and noisy data, as well as suggestions for further improvement.

Committee: Stefan Forcey Dr. (Advisor); Malena Espanol Dr. (Committee Member); Patrick Wilber Dr. (Committee Member) Subjects: Applied Mathematics; Biology

Master of Arts (MA), Bowling Green State University, 2017, Psychology

Decision-makers neglect prior probabilities, or base-rates, when faced with problems of Bayesian inference (e.g. Bar-Hillel, 1980; Kahneman & Tversky, 1972, 1973; Nisbett and Borgida 1975). Judgments are instead made via the representativeness heuristic, in which a probability judgment is made by how representative its most salient features are (Kahneman & Tversky, 1972). Research has shown that base-rate neglect can be lessened by making individual subsets amenable to overall superset extraction (e.g. Gigerenzer & Hoffrage, 1995; Evans et al. 2000; Evans et al. 2002; Tversky & Kahneman, 1983). In addition to nested sets, psychological distance should change the weight afforded to base-rate information. Construal Level Theory (Trope & Liberman, 2010) proposes that psychological distances—a removal from the subjective and egocentric self—result in differential information use. When we are proximal to an event we focus on its concrete aspects, and distance from an event increases our focus on its abstract aspects. Indeed, previous research has shown that being psychologically distant from an event increases the use of abstract and aggregate information (Burgoon, Henderson, & Wakslak, 2013; Ledgerwood, Wakslak, & Wang, 2010), although these results have been contradicted (Braga, Ferreira, & Sherman, 2015). Over two experiments I test the idea that psychological distance increases base-rate use. In Experiment 1 I attempt to partially replicate previous research that indicates temporal psychological distance increases the use of the representativeness heuristic (Braga et al., 2015); that is, actually increases base-rate neglect. In Experiment 2 I tested this effect in problems of Bayesian inference, using the standard mammography (Eddy, 1982) and lawyers and engineers (Kahneman & Tversky, 1973) problems. My results provide preliminary, converging evidence that both social and temporal psychological distances increase the use of base-rate information.

Committee: Richard Anderson (Advisor); Scott Highhouse (Committee Member); Yiwei Chen (Committee Member) Subjects: Psychology

Master of Education (MEd), Bowling Green State University, 2017, Human Movement, Sport and Leisure Studies /Sport Administration

In the face of uncertainty, human judgment and decision-making often tends to deviate from the realm of rationality. Gambler's fallacy and its opposite, hot outcome, are two such departures from laws of probability involving random streak of events. However, the adaptive thinking approach to decision-making proposes that any irrational heuristic or illogical belief can be fully adaptive as long as it fulfills the requirements of the decision task. During penalty shootouts in association football, goalkeepers face a series of multiple penalty kicks which are independent draws from a random process, and they need to anticipate the likely kick directions with limited time, insufficient information and computational capacity. The objective of this current study was to observe the goalkeepers in real-world competitive settings and examine whether they use gambler's fallacy and hot outcome as predictive strategies to decide on their dive directions during penalty shootouts following streaks of correct and incorrect predictions in the same direction. Another goal was to investigate from the adaptive thinking perspective whether such strategies lead to more correct predictions by the goalkeepers. Penalty shootout data were collected from the elite soccer tournaments over the course of last 25 years (1992 - 2016) and after applying appropriate exclusion criterions, 405 penalty kicks were considered for the final analysis. Binomial tests revealed that following progressively longer streaks of correct predictions in the same direction, goalkeepers became increasingly more likely to dive in the opposite direction for the subsequent kick than would be expected by chance, a behavior consistent with gambler's fallacy. However, neither gambler's fallacy nor hot outcome type patterns were observed when analyzing dives of goalkeepers following streaks of incorrect predictions in a particular direction. On the other hand, results of the Fisher's exact tests confirmed that both the fal (open full item for complete abstract)

Committee: David Tobar PhD (Advisor); Adrian Turner PhD (Committee Member); Matt Laurent PhD (Committee Member) Subjects: Behavioral Psychology; Behavioral Sciences; Cognitive Psychology; Kinesiology; Sports Management

Master of Arts, The Ohio State University, 2016, Psychology

Recent research has demonstrated that acetaminophen reduces affective reactivity. Because affect is a critical determinant of risk perception and risk-taking, this drug taken by 23% of Americans each week could potentially impact these important judgments and decisions. To test this hypothesis, we examined the effects of acetaminophen on well-validated risk perception and risk-taking tasks. In Study 1 (N = 142) and Study 2 (N = 189), we demonstrated that acute doses of acetaminophen increase risk-taking behavior. This increase in risk-taking emerged on post-loss trials, not on the first trial, suggesting acetaminophen may be affecting how individuals respond to experiences of loss. However, acetaminophen did not affect self-reports of reactivity to loss events, motivation to avoid loss, focus on gains or losses, or perceived probability of a loss. In Study 2, but not Study 1, we also found evidence that acetaminophen reduced the negative correlation between perceived risk and benefit in some risk perception domains, suggesting less reliance on the “affect heuristic.” To examine the neurochemical mechanism underlying this effect, Study 3 tested whether the increase in risk-taking extends to the non-steroidal anti-inflammatory drug ibuprofen. We did not find an effect of ibuprofen on risk-taking overall, but did see a significant increase in risk-taking among those who reported higher recent illness and who received ibuprofen. Taken together, the results suggest acetaminophen, an over-the-counter drug, can impact critically important risk judgment and risk-taking behavior.

Committee: Baldwin Way (Advisor); Jennifer Crocker (Committee Member); Ellen Peters (Committee Member) Subjects: Social Psychology