Master of Science, The Ohio State University, 2023, Industrial and Systems Engineering

Introduction: Musculoskeletal disorders in the workforce are highly prevalent, especially in material handling operations. In addition to completing physically demanding work that is required in this domain, workers must also manage concurrent mental demands present in their tasks. Few studies have examined the effect of concurrent mental demands in occupationally-relevant tasks. This study attempted to fill this void by quantifying the effects of varying degrees of cognitive loads and task precision demands on a material handling task by examining these effects on the kinematics and muscle activity of the trunk and shoulders. Methods: Twelve subjects lifted and placed a 5 kg box on a rack at one of three destination heights (low, middle, high) while under a simultaneous cognitive load (no load, simple load, complex load) and/or precision constraint (low precision, high precision). Cognitive load consisted of time-based arithmetic questions where participants were tasked with determining the amount of time remaining from a given time to a target time (e.g., Get to 4:00 PM from 3:15 for simple load or get to 4:10 PM from 3:27 PM for complex load). The primary dependent measures were the angular velocities of the trunk and shoulders as well as muscle activity in the erector spinae, rectus abdominus, external oblique, latissimus dorsi, and anterior deltoid muscles. Results: Significant decreases in angular velocities for both higher cognitive load complexities and higher precision conditions were observed. Additionally, lower 90th percentile normalized muscle activity values were observed as complexity and precision increased. Cumulative muscle activity, however, increased with these increases in complexity and precision. Conclusions: This study examined the impact of varying levels of cognitive and precision conditions on muscle activity and kinematics of the trunk and shoulders. Results indicated that increased complexity and precision led to longer lift t (open full item for complete abstract)

Committee: Carolyn Sommerich (Committee Member); Steven Lavender (Advisor) Subjects: Behavioral Sciences; Biomechanics; Engineering; Health Sciences; Industrial Engineering; Kinesiology; Occupational Safety

Doctor of Philosophy (Ph.D.), Bowling Green State University, 2021, Psychology/Experimental

This dissertation explores the information processing mechanism of cognitive assimilation in short-story reading by manipulating the explanatory information and its presentation format. The primary purpose of this dissertation is to explain the lengthened reading time caused by cognitive complexity in the reading behavior found in Jacovina and Gerrig's study on how readers experience characters' decisions (Jacovina & Gerrig, 2010); furthermore, this dissertation intends to reveal how readers' mental models adjust to additional information related to a character's decisions and motivations and explore how different information presentation formats impact the participants' recognition memory. Three experiments were conducted to explain the phenomena unexplained in Jacovina and Gerrig's study of readers' participatory response to the story assimilation. Experiment 1 was a pilot study conducted to evaluate the decisions from three stories provided in the Jacovina and Gerrig study and examine whether the explanatory information in the textual and multi-media versions carried equal information. Experiment 2 was designed to test the Reconciliation Hypothesis by manipulating the congruency and explanatory status of additional information; stimuli used in Experiment 2 were the same from Jacovina and Gerrig's study except for the explanatory information. Explanatory information or non-explanatory information was introduced to stories based on the design before participants read the story outcome. The experiment results showed that providing the explanatory information for the character's decision would relieve participants from generating an explanation on the assimilation. Participants showed a shorter reading time when provided with explanatory information regarding the character's decision. Furthermore, recognition memory indicated that there was an improved effect on their memory in the recognition test for the explanatory information condition. The explanatory informatio (open full item for complete abstract)

Committee: Richard Anderson Ph.D. (Advisor); Umar Islambekov Ph.D. (Other); Dale Klopfer Ph.D. (Committee Member); Michael Zickar Ph.D. (Committee Member) Subjects: Psychology

MS, Kent State University, 2018, College of Arts and Sciences / Department of Computer Science

Posting on the internet, including weblogs or social media, is one of the ways individuals seek for an outlet to express themselves or mental health concerns. For many mental health issues such as psychosis, the timing of detection and treatment is critical; short and long-term outcomes are better when individuals begin treatment close to the onset of psychosis. While the internet offers a positive medium for short term therapy, it is not a face to face therapy session, wherein a trained professional is better able to deduce the root of the problem. Many clinicians are adopting electronic communication to strengthen their therapeutic alliance with their patients. The drawback of psychiatry is that it lacks objectified tests for mental illnesses that would otherwise be present in medicine. Current neuroscience has yet not found genetic markers that can characterize individual mental illnesses. A thought disorder (ThD) which is a widely found symptom in people suffering from schizophrenia, is diagnosed from the level of coherence when the flow of ideas is muddled without word associations. A system that can explore the use of speech analysis for aiding in psychiatric diagnosis is highly desirable and would help early detection and effective treatment results. This thesis introduces a framework – Prediction Onset Prediction System (POPS) - to predict the onset of psychosis based on written language habits. A scrape of a multitude of individual comments is analyzed using a trained psychosis prediction module that is able to predict if an individual is psychotic (based on the semantics) using natural language processing, machine learning techniques and a customized corpus with terms consist with psychotic language tendencies created using speech analysis techniques. The effectiveness of the corpus and its implication in psychosis detection is explored.

Committee: Kambiz Ghazinour (Advisor) Subjects: Computer Science; Health; Mental Health; Psychology; Sociology; Teaching; Technology

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

Aerobic exercise has benefits on both physical and mental health, including a reduction of stress. However, the differential effects of specific types of aerobic exercise are unclear. We compared the effects of two different types of aerobic exercise (high-intensity interval training; HIIT, and endurance training; ET) with an active control group (relaxation) on mood and cognition following a stressor. Participants were healthy undergraduates (aged 18-25). Physiological tests (e.g., heart rate; HR, and blood pressure; BP) were administered, followed by psychological tests of mood and cognition (e.g., Visual Analogue Scale; VAS, and Automated Neuropsychological Assessment Metrics; ANAM). Participants completed a negative mood-induction/stressor task (e.g. impromptu public speaking), and were then randomly assigned to complete one of three interventions (e.g. HIIT, ET, control). Physiological and psychological tests were then re-administered. We predict that the two forms of aerobic exercise (e.g. HIIT, ET) will have independent effects on mood and cognition, from the control and from each other. Our results will inform whether certain types of aerobic exercise (e.g. HIIT, ET) differentially impact mood and cognition and may promote the development of exercise-based interventions for stress-related emotional disorders (e.g. depression, anxiety, etc.).

Committee: Misty Hawkins PhD (Advisor); Joel Hughes PhD (Advisor); Shannon Ciesla PhD (Committee Member); Heidi Johnson M.Ed (Committee Member); Gianna Commito BFA (Committee Member) Subjects: Psychology

MDES, University of Cincinnati, 2012, Design, Architecture, Art and Planning: Design

People need to interact with many different products everyday to make sure all their needs are satisfied. A product should explain itself instead of forcing users to seek help from the product instructions or other people. A key role of design is to reduce user effort. However, identifying problems in the product-user interaction scenario is complicated and difficult. This thesis attempts to develop a design tool to help designers find the problems more efficiently so that they can improve the design of the user experience. This thesis is focused on user interactions, which are result-oriented, and the goal is to design a methodology to reduce the mental effort exerted by the user. In analyzing the anatomy of existing interaction and human perception models, it was determined that none focused specifically on the consideration of mental effort. This research and analysis led to the conclusion that a mental effort evaluation model would be of value to designers. MEE Model was developed and presented here, which examines where and how mental effort is exerted in an interaction process. The two major causes of mental effort exerted are interaction complexity and interaction difficulty. Complexity refers to the number of phases in a process, and difficulty refers to the mental effort exerted in completing a single step in the process. MEE Model is intended to help designers determine in more detail why complexity and difficulty happen, and how to avoid them by simplifying the user interaction. MEE Model is designed to allow designers to observe the users engaged in the interaction and then through interviewing the users, systematically evaluate the users' experience and use that data to improve that experience. In this way, they can locate and prioritize the problem areas, and then try to reduce the exertion of mental effort. As an example, this model is applied in the actual interaction design process to help find the problems and also give potential solutions about (open full item for complete abstract)

Committee: Peter Chamberlain MFA MPhil (Committee Chair); Dale Murray MA (Committee Member) Subjects: Design

Master of Science, The Ohio State University, 2011, Environment and Natural Resources

Weeds are one of the biggest financial, environmental, and social risks in organic farm operations. Experts acknowledge that inherent diversity and site specificity in organic farm systems deter standardization and diffusion of weed management knowledge and long term, preventive strategies. Our data, collected through in-depth, semi-structured interviews with weed scientists, USDA researchers, extension personnel, and 29 farmers in Ohio and Indiana suggests that in the absence of the chemical silver bullet, organic weed management must include a deeper understanding of human decision making systems and agroecosystems. Using the mental models approach, we created conceptual influence diagrams, or mental models, of weeds and weed management from both perspectives. The models provide a qualitative foundation to understand what organic farmers know about weed management, and, more importantly, how they use their knowledge, experience, risk perception, and emotion to process information and make weed management decisions. This research has both theoretical and practical implications for understanding why farmers, both conventional and organic, make decisions that are beneficial in the short term, but environmentally and economically damaging in the long term. Results show that outreach materials will be more successful if they help a farmer optimize their experiential/intuitive judgments alongside more analytical processing for efficient and successful long term weed management strategies. Such decisions will help to reduce the immense emotional, ecological, economic, and physical impacts of weeds.

Committee: Robyn Wilson PhD (Advisor); Doug Doohan PhD (Committee Member); Koontz Tom PhD (Committee Member); Hitzhusen Greg PhD (Committee Member) Subjects: Agriculture; Environmental Management; Psychology; Social Research; Sustainability