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Surgery as a profession requires significant training to improve both clinical decision making and psychomotor proficiency. In the medical knowledge domain, tools have been developed, validated, and accepted for evaluation of surgeons' competencies. However, assessment of the psychomotor skills still relies on the Halstedian model of apprenticeship, wherein surgeons are

Surgery as a profession requires significant training to improve both clinical decision making and psychomotor proficiency. In the medical knowledge domain, tools have been developed, validated, and accepted for evaluation of surgeons' competencies. However, assessment of the psychomotor skills still relies on the Halstedian model of apprenticeship, wherein surgeons are observed during residency for judgment of their skills. Although the value of this method of skills assessment cannot be ignored, novel methodologies of objective skills assessment need to be designed, developed, and evaluated that augment the traditional approach. Several sensor-based systems have been developed to measure a user's skill quantitatively, but use of sensors could interfere with skill execution and thus limit the potential for evaluating real-life surgery. However, having a method to judge skills automatically in real-life conditions should be the ultimate goal, since only with such features that a system would be widely adopted. This research proposes a novel video-based approach for observing surgeons' hand and surgical tool movements in minimally invasive surgical training exercises as well as during laparoscopic surgery. Because our system does not require surgeons to wear special sensors, it has the distinct advantage over alternatives of offering skills assessment in both learning and real-life environments. The system automatically detects major skill-measuring features from surgical task videos using a computing system composed of a series of computer vision algorithms and provides on-screen real-time performance feedback for more efficient skill learning. Finally, the machine-learning approach is used to develop an observer-independent composite scoring model through objective and quantitative measurement of surgical skills. To increase effectiveness and usability of the developed system, it is integrated with a cloud-based tool, which automatically assesses surgical videos upload to the cloud.
ContributorsIslam, Gazi (Author) / Li, Baoxin (Thesis advisor) / Liang, Jianming (Thesis advisor) / Dinu, Valentin (Committee member) / Greenes, Robert (Committee member) / Smith, Marshall (Committee member) / Kahol, Kanav (Committee member) / Patel, Vimla L. (Committee member) / Arizona State University (Publisher)
Created2013
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Description
This dissertation investigates the condition of skeletal muscle insulin resistance using bioinformatics and computational biology approaches. Drawing from several studies and numerous data sources, I have attempted to uncover molecular mechanisms at multiple levels. From the detailed atomistic simulations of a single protein, to datamining approaches applied at the systems

This dissertation investigates the condition of skeletal muscle insulin resistance using bioinformatics and computational biology approaches. Drawing from several studies and numerous data sources, I have attempted to uncover molecular mechanisms at multiple levels. From the detailed atomistic simulations of a single protein, to datamining approaches applied at the systems biology level, I provide new targets to explore for the research community. Furthermore I present a new online web resource that unifies various bioinformatics databases to enable discovery of relevant features in 3D protein structures.
ContributorsMielke, Clinton (Author) / Mandarino, Lawrence (Committee member) / LaBaer, Joshua (Committee member) / Magee, D. Mitchell (Committee member) / Dinu, Valentin (Committee member) / Willis, Wayne (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The living world we inhabit and observe is extraordinarily complex. From the perspective of a person analyzing data about the living world, complexity is most commonly encountered in two forms: 1) in the sheer size of the datasets that must be analyzed and the physical number of mathematical computations necessary

The living world we inhabit and observe is extraordinarily complex. From the perspective of a person analyzing data about the living world, complexity is most commonly encountered in two forms: 1) in the sheer size of the datasets that must be analyzed and the physical number of mathematical computations necessary to obtain an answer and 2) in the underlying structure of the data, which does not conform to classical normal theory statistical assumptions and includes clustering and unobserved latent constructs. Until recently, the methods and tools necessary to effectively address the complexity of biomedical data were not ordinarily available. The utility of four methods--High Performance Computing, Monte Carlo Simulations, Multi-Level Modeling and Structural Equation Modeling--designed to help make sense of complex biomedical data are presented here.
ContributorsBrown, Justin Reed (Author) / Dinu, Valentin (Thesis advisor) / Johnson, William (Committee member) / Petitti, Diana (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Critical care environments are complex in nature. Fluctuating team dynamics and the plethora of technology and equipment create unforeseen demands on clinicians. Such environments become chaotic very quickly due to the chronic exposure to unpredictable clusters of events. In order to cope with this complexity, clinicians tend to develop ad-hoc

Critical care environments are complex in nature. Fluctuating team dynamics and the plethora of technology and equipment create unforeseen demands on clinicians. Such environments become chaotic very quickly due to the chronic exposure to unpredictable clusters of events. In order to cope with this complexity, clinicians tend to develop ad-hoc adaptations to function in an effective manner. It is these adaptations or "deviations" from expected behaviors that provide insight into the processes that shape the overall behavior of the complex system. The research described in this manuscript examines the cognitive basis of clinicians' adaptive mechanisms and presents a methodology for studying the same. Examining interactions in complex systems is difficult due to the disassociation between the nature of the environment and the tools available to analyze underlying processes. In this work, the use of a mixed methodology framework to study trauma critical care, a complex environment, is presented. The hybrid framework supplements existing methods of data collection (qualitative observations) with quantitative methods (use of electronic tags) to capture activities in the complex system. Quantitative models of activities (using Hidden Markov Modeling) and theoretical models of deviations were developed to support this mixed methodology framework. The quantitative activity models developed were tested with a set of fifteen simulated activities that represent workflow in trauma care. A mean recognition rate of 87.5% was obtained in automatically recognizing activities. Theoretical models, on the other hand, were developed using field observations of 30 trauma cases. The analysis of the classification schema (with substantial inter-rater reliability) and 161 deviations identified shows that expertise and role played by the clinician in the trauma team influences the nature of deviations made (p<0.01). The results shows that while expert clinicians deviate to innovate, deviations of novices often result in errors. Experts' flexibility and adaptiveness allow their deviations to generate innovative ideas, in particular when dynamic adjustments are required in complex situations. The findings suggest that while adherence to protocols and standards is important for novice practitioners to reduce medical errors and ensure patient safety, there is strong need for training novices in coping with complex situations as well.
ContributorsVankipuram, Mithra (Author) / Greenes, Robert A (Thesis advisor) / Patel, Vimla L. (Thesis advisor) / Petitti, Diana B. (Committee member) / Dinu, Valentin (Committee member) / Smith, Marshall L. (Committee member) / Arizona State University (Publisher)
Created2012
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Description
This work involved the analysis of a public health system, and the design, development and deployment of enterprise informatics architecture, and sustainable community methods to address problems with the current public health system. Specifically, assessment of the Nationally Notifiable Disease Surveillance System (NNDSS) was instrumental in forming the design of

This work involved the analysis of a public health system, and the design, development and deployment of enterprise informatics architecture, and sustainable community methods to address problems with the current public health system. Specifically, assessment of the Nationally Notifiable Disease Surveillance System (NNDSS) was instrumental in forming the design of the current implementation at the Southern Nevada Health District (SNHD). The result of the system deployment at SNHD was considered as a basis for projecting the practical application and benefits of an enterprise architecture. This approach has resulted in a sustainable platform to enhance the practice of public health by improving the quality and timeliness of data, effectiveness of an investigation, and reporting across the continuum.
ContributorsKriseman, Jeffrey Michael (Author) / Dinu, Valentin (Thesis advisor) / Greenes, Robert (Committee member) / Johnson, William (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Immunosignaturing is a technology that allows the humoral immune response to be observed through the binding of antibodies to random sequence peptides. The immunosignaturing microarray is based on complex mixtures of antibodies binding to arrays of random sequence peptides in a multiplexed fashion. There are computational and statistical challenges to

Immunosignaturing is a technology that allows the humoral immune response to be observed through the binding of antibodies to random sequence peptides. The immunosignaturing microarray is based on complex mixtures of antibodies binding to arrays of random sequence peptides in a multiplexed fashion. There are computational and statistical challenges to the analysis of immunosignaturing data. The overall aim of my dissertation is to develop novel computational and statistical methods for immunosignaturing data to access its potential for diagnostics and drug discovery. Firstly, I discovered that a classification algorithm Naive Bayes which leverages the biological independence of the probes on our array in such a way as to gather more information outperforms other classification algorithms due to speed and accuracy. Secondly, using this classifier, I then tested the specificity and sensitivity of immunosignaturing platform for its ability to resolve four different diseases (pancreatic cancer, pancreatitis, type 2 diabetes and panIN) that target the same organ (pancreas). These diseases were separated with >90% specificity from controls and from each other. Thirdly, I observed that the immunosignature of type 2 diabetes and cardiovascular complications are unique, consistent, and reproducible and can be separated by 100% accuracy from controls. But when these two complications arise in the same person, the resultant immunosignature is quite different in that of individuals with only one disease. I developed a method to trace back from informative random peptides in disease signatures to the potential antigen(s). Hence, I built a decipher system to trace random peptides in type 1 diabetes immunosignature to known antigens. Immunosignaturing, unlike the ELISA, has the ability to not only detect the presence of response but also absence of response during a disease. I observed, not only higher but also lower peptides intensities can be mapped to antigens in type 1 diabetes. To study immunosignaturing potential for population diagnostics, I studied effect of age, gender and geographical location on immunosignaturing data. For its potential to be a health monitoring technology, I proposed a single metric Coefficient of Variation that has shown potential to change significantly when a person enters a disease state.
ContributorsKukreja, Muskan (Author) / Johnston, Stephen Albert (Thesis advisor) / Stafford, Phillip (Committee member) / Dinu, Valentin (Committee member) / Arizona State University (Publisher)
Created2012
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Description

Expectation for college attendance in the United States continues to rise as more jobs require degrees. This study aims to determine how parental expectations affect high school students in their decision to attend college. By examining parental expectations that were placed on current college students prior to and during the

Expectation for college attendance in the United States continues to rise as more jobs require degrees. This study aims to determine how parental expectations affect high school students in their decision to attend college. By examining parental expectations that were placed on current college students prior to and during the application period, we can determine the positive and negative outcomes of these expectations as well as the atmosphere they are creating. To test the hypothesis, an online survey was distributed to current ASU and Barrett, Honors College students regarding their experience with college applications and their parents' influence on their collegiate attendance. A qualitative analysis of the data was conducted in tandem with an analysis of several case studies to determine the results. These data show that parental expectations are having a significant impact on the enrollment of high school students in college programs. With parents placing these expectations on their children, collegiate enrollment will continue to increase. Further studies will be necessary to determine the specific influences these expectations are placing on students.

ContributorsJohnson, Benjamin Howard (Co-author) / Scheller, Sara (Co-author) / Kappes, Janelle (Thesis director) / Fairbanks, Elizabeth (Committee member) / Department of Psychology (Contributor) / School of Social Transformation (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

The purpose of this project was to research the expression of Autism Spectrum Disorder in children and create a children’s book that can help the peers of individuals with a diagnosis to understand what the disorder entails and potentially gain a new sense of empathy for peers of all levels

The purpose of this project was to research the expression of Autism Spectrum Disorder in children and create a children’s book that can help the peers of individuals with a diagnosis to understand what the disorder entails and potentially gain a new sense of empathy for peers of all levels of physical and mental abilities. The research component includes interviews with individuals deemed knowledgeable about ASD, including occupational therapists, behavioral analysts, and parents, as well as a literature review of research studies on the expression of Autism in children. This written portion of the project may also serve as a manual for individuals who have little to no knowledge of ASD, as it dives deeper into the content of the book and research, while remaining easily understandable and clear to those without any prior knowledge or experience with ASD. It could prove especially useful for those in professions that come into contact with individuals with Autism, but do not necessarily require psychology courses or training as a prerequisite for the role, such as teachers and some health professionals.

ContributorsSigna, Hope (Author) / Nelson, Elizabeth (Thesis director) / Spinrad, Tracy (Committee member) / Department of Psychology (Contributor) / Sanford School of Social and Family Dynamics (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

Due to the Covid-19 pandemic, healthcare professionals including occupational therapy practitioners (OTPs) were required to transition to working utilizing an online-service delivery model called telehealth. The use of telehealth for occupational therapy (OT) sessions was limited prior to the pandemic, and this shift required OTPs to provide services in ways

Due to the Covid-19 pandemic, healthcare professionals including occupational therapy practitioners (OTPs) were required to transition to working utilizing an online-service delivery model called telehealth. The use of telehealth for occupational therapy (OT) sessions was limited prior to the pandemic, and this shift required OTPs to provide services in ways many had never experienced. The purpose of this study was to identify how the transition to telehealth impacted OTPs and their ability to provide proper care to the pediatric population via telehealth. The final analytic sample included 32 female OTPs who worked with the pediatric population. Results from qualitative and quantitative analyses showed that OTPs had positive feelings toward using telehealth and that the telehealth modality had a moderate impact on their job performance. The areas that pediatric OTPs want to be addressed included technology and internet issues, lack of parent involvement, decreased quality of care, inaccessibility of materials, decreased attention span and increased distractions, and lack of general knowledge about telehealth among clients, parents, and professionals. Despite these drawbacks, a positive theme emerged that the telehealth model is good for current circumstances. The results show telehealth is a positive experience for OTPs and allows OT to be more accessible to their clients. Implications for increasing education for healthcare professionals, clients, and parents/guardians to make telehealth accessible to clients on a large scale are discussed.

ContributorsMulvaney, Kaitlin Marie (Author) / Bryce, Crystal (Thesis director) / Seeley, Bridget (Committee member) / Sanford School of Social and Family Dynamics (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

The present study explored the relationship between desired purchasing behavior and individual differences using two nationally-representative, longitudinal samples of the U.S. population early in the COVID-19 pandemic. Past research has shown that individual differences provide information about how one might respond to threat. Therefore, we predicted changes in desired purchasing

The present study explored the relationship between desired purchasing behavior and individual differences using two nationally-representative, longitudinal samples of the U.S. population early in the COVID-19 pandemic. Past research has shown that individual differences provide information about how one might respond to threat. Therefore, we predicted changes in desired purchasing behavior across different sociodemographic variables that might reflect those differences. Specifically, we investigated hypotheses related to political orientation, age, sexual orientation, socioeconomic status, and whether or not the participant had children. We measured participants’ reported desired purchasing behavior across eleven categories of goods and investigated the connection between specific demographic variables and desired purchasing behavior. We found that conservatives desired to purchase more basic protection goods (guns/ammunition, cash, gas) and that older people desired to purchase more cleaning supplies and toiletries. These findings illustrate possible explanations for purchasing behavior during the COVID-19 pandemic and reveal directions for marketing designed to influence purchasing behavior.

ContributorsZeider, Justyn (Author) / Varnum, Michael (Thesis director) / Neuberg, Steven (Committee member) / Department of Psychology (Contributor) / School of International Letters and Cultures (Contributor) / School of Social Transformation (Contributor) / Sandra Day O'Connor College of Law (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05