Purpose: Health literacy and obesity are major global issues. Vulnerable populations, such as those with low health literacy, have the highest rates of obesity. Native Hawaiian and other Pacific Islander (NHOPI) nations have the highest prevalence of obesity in the world. This study describes the relationship between health literacy and demographic variables in a sample of NHOPI caregiving adults. Methods: We conducted a correlational study of 364 NHOPI adults. Each was a caregiver of at least one NHOPI child. Data were collected at grocery stores and a preschool in two Hawaiian Islands (n=209) and at NHOPI events in Utah (n=155). Our questionnaire included demographics, the Newest Vital Sign, and questions about caregivers' food-serving and activity promotion. Results: 45% of the sample had limited health literacy. There was no significant difference between participants' health literacy in Hawaii and Utah. Other demographic variables (gender, age, income, BMI, and education) had a significant relationship with health literacy. Conclusions: Many NHOPIs have limited health literacy. This is concerning as limited health literacy can reduce an adults' ability to use health-related materials including nutrition facts labels.Implications for Practice: Health care providers should not assume NHOPIs understand nutrition facts labels. Instruction on nutrition facts labels should be available in schools and communities. Future research should examine effective interventions for this population.

Spirometry is the most important tool in diagnosing pulmonary disease and is the most frequently performed pulmonary function test. Respiratory disease is also one of the greatest causes for morbidity and mortality on the Hopi Nation, but no specific reference equations exist for this unique population. The purpose of this study was to determine if population reference equations were necessary for these children and, if needed, to create new age and race-specific pulmonary nomograms for Hopi children. Two hundred and ninety-two healthy children, ages 4-13 years, attending Hopi Nation elementary schools in Arizona, were asked to perform spirometry for a full battery of pulmonary volumes and capacities of which the following were analyzed: forced vital capacity (FVC), forced expiratory volume in 1 sec (FEV1), FEV1 % (FEV1/FVC), FEF25-75% and peak expiratory flow rate (PEFR). Spirometric data from Navajo children living in the same geographical region as the Hopi children were compared as well as spirometric data from common reference values used for other ethnic groups in the USA. Spirometry tests from 165 girls and 127 boys met American Thoracic Society quality control standards. We found that the natural log of height, body mass and age were significant predictors of FEV1, FVC, and FEF25-75% in the gender-specific models and that lung function values all increased with height and age as expected. The predictions using the equations derived for Navajo, Caucasian, Mexican-American, African-American youth were significantly different (P ≤ 0.05) from the predictions derived from the Hopi equations for all of the variables across both genders, with the exceptions of Hopi versus Navajo FEV1/FVC in the males and Hopi versus Caucasians FEF25-75% in the females. Thus it would appear for this population important to have specific formulae to provide more accurate reference values.

Spirometry is the most important tool in diagnosing pulmonary disease and is the most frequently performed pulmonary function test. Since respiratory disease is the single greatest cause for morbidity and mortality on the Navajo Nation, the purpose of this study was to create newage and race-specific pulmonary nomograms for Navajo children. Five hundred fifty-eight healthy children, ages 6-14 years, attending Navajo Nation elementary schools in Arizona, were asked to perform spirometry to develop population-specific and tribe-specific nomograms for forced vitalcapacity (FVC), forced expiratory volume in 1 sec (FEV1), and FEV1 Ratio (FEV1/FVC). Spirometry tests from 284 girls and 274 boys met American Thoracic Society quality control standards. Lung function values, except for FEV1/FVC, all increased with height. The lower limit of the normal range for FEV1/FVC was 80%. The spirometry reference equations from the healthyboys and girls were developed. Height and the natural log of height were significant predictors of FEV1, FVC, and FEF25-75% in the gender-specific models. The resulting population-specific spirometry reference equations should be used when testing Navajo children ages 6-14 years. However, the use of the NHANES III spirometry reference equations for Caucasian children may not result in significant misclassification in clinical settings providing that a maximal effort is given by the Navajo child being tested.

The greater sage-grouse (Centrocercus urophasianus; sage-grouse) is a species of conservation concern in Utah and range-wide due to declines in populations and threats to sagebrush habitat on which they depend. To effectively conserve the species, detailed site-specific knowledge of ecology and distribution is needed. To expand knowledge of local populations within the West Box Elder Sage Grouse Management Area (SGMA) and gain insights into the effectiveness of vegetation treatments intended to benefit sagegrouse, I radio marked and tracked 123 (68 female, 55 male) sage-grouse and conducted sage-grouse pellet surveys on 19 conifer removal projects. Widespread habitat restoration measures designed to benefit sage-grouse have highlighted the need for prioritization tools to optimize placement of sage-grouse habitat projects. I generated seasonal habitat models to predict sage-grouse habitat use within the West Box Elder SGMA using a suite of vegetation and topographical predictors and known sage-grouse locations. Model fit was good with brood, early summer, late summer, lekking (early spring), and non-breeding models reporting an AUC of >0.90; nest and winter models reported an AUC of 0.87 and 0.85, respectively. A vegetation disturbance history was built for the study area from 1985 to 2013; however, the vegetation disturbances mapped were not a strong predictor of sage-grouse seasonal habitat-use. To evaluate effectiveness of conifer reduction treatments I used fecal pellet and in concert with radio-telemetry data. Increased sage-grouse use of conifer treatments was positively associated with sage-grouse presence in adjacent habitats (P = 0.018), percent shrub cover (P = 0.039), and mesic environments within 1000 m of treatments (P = 0.048). Sage-grouse use of conifer treatments was negatively associated with conifer canopy cover (P = 0.048) within 1000 m of treatments. To investigate sample bias related to individual bird behavior or capture trauma I monitored 204 radio-marked sage-grouse within the West Box Elder and Rich-Morgan- Summit SGMAs in Utah between January 2012 and March 2013. Sage-grouse that flushed one or more times prior to capture had higher brood (P = 0.014) and annual survival (P = 0.027) than those that did not. Sage-grouse that experienced more capture trauma had decreased annual survival probabilities (P = 0.04).

Idiopathic Pulmonary Fibrosis (IPF) is an interstitial lung disease with no known cause or cure. IPF has an incidence of 75/1,000,000 of the population, predominately in men over the age of 60. This relatively rare disease develops in a chronic and progressive way, ultimately leading to death within two to five years of diagnosis. Our use of translatable methodologies in the bleomycin mouse model of IPF led to the novel identification of the similarities between the average percent loss of lung function in previous human clinical trials to that of our mouse model data. There is no treatment for IPF outside of lung transplantation, therefore our goal is to develop a protein therapy to halt the progression of IPF. B6_BP_dslf is a small, 93.36 kDa minibinder protein with a nanomolar affinity to αvβ6, an integrin of therapeutic potential for IPF when inhibited by halting αvβ6/TGF-β signaling. Our hypothesis is that B6_BP_dslf will halt the progression of pulmonary fibrosis induced in a mouse model of IPF. To test this hypothesis, a de novo design method was used resulting in the B6_BP_dslf minibinder having high β unit selectivity and nanomolar affinity for αvβ6, and maintenance of its secondary structure after aerosolization. These attributes led to testing in the bleomycin mouse model for IPF as an inhaled therapy. We found that B6_BP_dslf inhalation by mice with induced pulmonary fibrosis had reduced pathogenesis through the quantification of biomarkers for αvβ6/TGF-β mediated fibrosis, lowered histopathological scores, and improved lung function. These positive results from standard biochemical analysis and clinically translatable methods show that BP_B6_dslf has clinical potential as an inhaled therapy for IPF. Additionally, we tested the use of lung function tests in an animal model of chronic obstructive pulmonary disease (COPD), using secondhand smoke exposure to induce the disease and to identify inflammatory pathways. We found that smoke exposure increased inflammatory signaling through receptors for advanced glycation end-products, and inhibition of these receptors using a novel therapy of semi-synthetic glycosaminoglycan ethers (SAGEs) reduced inflammation and improved lung function. Together, the data from two different lung disease models supports the use of lung function as a preclinical efficacy variable for experimental drugs. The combination of biochemical and functional assessments of B6_BP_dslf and SAGEs gives weight to their therapeutic potential.

Technology development in the sub-field of older adult care has always been on the back-burner compared to other healthcare areas. But with increasing life expectancy, this is poised to change. With the increasing older adult population, the current older adult care facilities and personnel are struggling to keep up with demand. Research conducted in the Netherlands [1] found 33,000 older adults were awaiting admission into a home for the elderly showing that demand far exceeds availability. This huge demand for older adult care has resulted in a decrease in the quality of care being provided. A recent study involving older adults aged 65 and above [2] compared the quality of care given to older adults in nursing homes in the UK and found it to be inadequate. While it is true that giant strides have been made in the field of personal health and fitness [3], we have to acknowledge that these technologies have not found widespread adoption in the elderly communities for a number of reasons which include lack of education, cognitive impediments, low-income and techno-phobia [4]. We believe that older adult care technologies should be approached from a different perspective in order to maximize outcomes. Inventions in the health care space are a moving target and a significant degree of technical aptitude and interest is required to keep up with these changes. My research work will be focused on developing a distributed system infrastructure that will enable large-scale monitoring of vital signals and early detection of emergency situations in nursing homes and assisted living communities. This new approach will increase automation in nursing homes leading to a reduction in running cost and an increase in capacity

Cancer is a leading cause of death globally, and early detection is crucial for better outcomes. This research aims to improve Region Of Interest (ROI) segmentation and feature extraction in medical image analysis using Radiomics techniques with 3D Slicer, Pyradiomics, and Python. Dimension reduction methods, including PCA, K-means, t-SNE, ISOMAP, and Hierarchical Clustering, were applied to highdimensional features to enhance interpretability and efficiency. The study assessed the ability of the reduced feature set to predict T-staging, an essential component of the TNM system for cancer diagnosis. Multinomial logistic regression models were developed and evaluated using MSE, AIC, BIC, and Deviance Test. The dataset consisted of CT and PET-CT DICOM images from 131 lung cancer patients. Results showed that PCA identified 14 features, Hierarchical Clustering 17, t-SNE 58, and ISOMAP 40, with texture-based features being the most critical. This study highlights the potential of integrating Radiomics and unsupervised learning techniques to enhance cancer prediction from medical images.

Yes / Objectives: To develop a logistic regression model to predict the risk of sepsis following emergency medical admission using the patient’s first, routinely collected, electronically recorded vital signs and blood test results and to validate this novel computer-aided risk of sepsis model, using data from another hospital. Design: Cross-sectional model development and external validation study reporting the C-statistic based on a validated optimized algorithm to identify sepsis and severe sepsis (including septic shock) from administrative hospital databases using International Classification of Diseases, 10th Edition, codes. Setting: Two acute hospitals (York Hospital - development data; Northern Lincolnshire and Goole Hospital - external validation data). Patients: Adult emergency medical admissions discharged over a 24-month period with vital signs and blood test results recorded at admission. Interventions: None. Main Results: The prevalence of sepsis and severe sepsis was lower in York Hospital (18.5% = 4,861/2,6247; 5.3% = 1,387/2,6247) than Northern Lincolnshire and Goole Hospital (25.1% = 7,773/30,996; 9.2% = 2,864/30,996). The mortality for sepsis (York Hospital: 14.5% = 704/4,861; Northern Lincolnshire and Goole Hospital: 11.6% = 899/7,773) was lower than the mortality for severe sepsis (York Hospital: 29.0% = 402/1,387; Northern Lincolnshire and Goole Hospital: 21.4% = 612/2,864). The C-statistic for computer-aided risk of sepsis in York Hospital (all sepsis 0.78; sepsis: 0.73; severe sepsis: 0.80) was similar in an external hospital setting (Northern Lincolnshire and Goole Hospital: all sepsis 0.79; sepsis: 0.70; severe sepsis: 0.81). A cutoff value of 0.2 gives reasonable performance. Conclusions: We have developed a novel, externally validated computer-aided risk of sepsis, with reasonably good performance for estimating the risk of sepsis for emergency medical admissions using the patient’s first, electronically recorded, vital signs and blood tests results. Since computer-aided risk of sepsis places no additional data collection burden on clinicians and is automated, it may now be carefully introduced and evaluated in hospitals with sufficient informatics infrastructure. / Health Foundation

Intra-dialytic hypotension (IDH) is the most common complication in haemodialysis (HD) treatment and has been linked with increased mortality in HD patients. Despite various approaches towards understanding the underlying physiological mechanisms giving rise to IDH, the causes of IDH are poorly understood. Heart Rate Variability (HRV) has previously been suggested as a predictive measure of IDH. In contrast to conventional spectral HRV measures in which the frequency bands are defined by fixed limits, a new spectral measure of HRV is introduced in which the breathing rate is used to identify and measure the physiologically-relevant peaks of the frequency spectrum. The ratio of peaks leading up to the IDH event was assessed as a possible measure for IDH prediction. Changes in the proposed measure correlate well with the magnitude of abrupt changes in blood pressure in patients with autonomic dysfunction, but there is no such correlation in patients without autonomic dysfunction. At present, routine clinical vital sign monitoring beyond simple weight and blood pressure measurements at the start and end of each session has not established itself in clinical practice. To investigate the benefits of continuous vital sign monitoring in HD patients with regard to detecting and predicting IDH, different population-based and patient-specific models of normality were devised and tested on data from an observational study at the Oxford Renal Unit in which vital signs were recorded during HD sessions. Patient-specific models of normality performed better in distinguishing between IDH and non-IDH data, primarily due to the wide range of vital sign data included as part of the training data in the population-based models. Further, a patient-specific data fusion model was constructed using Parzen windows to estimate a probability density function from the training data consisting of vital signs from IDH-free sessions. Although the model was constructed using four vital sign inputs, novelty detection was found to be primarily driven by blood pressure decreases.

This doctoral thesis focuses on the modification of ACC to include actual driver workload in the context of automatic headway change. ACC is a driver assistance system that automatically maintains a preliminary defined speed and permits a driver to perform manual headway changes. As drivers show worse (brake) reaction times under high workload situations, the system increases headway accordingly. Driver workload is estimated based on physiological data. Here, we investigate the possibilities of such a system, assuming that physiological sensors can be implemented in future vehicles. The thesis consists of three parts: In the first part, the theoretical background is described and a suitable theoretical model is developed; in the second part, experiments are described, and in the last part, results are discussed. Altogether four experiments support this thesis: 1. The first experiment investigates the foundational relationships between physiology, brake reaction time and workload level. The study employs a simulator setting and results show that physiological data, such as heart rate and skin conductance, permit the identification of different workload levels. These findings validate the results of other studies showing that workload leads to an increase in reaction time. These results could only be validated between the extremes “no-workload” and “high workload” situations. 2. The second experiment simulates an ideal workload-adaptive cruise control (WACC) system. In a simulator setting, system acceptance and awareness are studied, with a view toward future implementation in a real car. The results show better acceptance of WACC in comparison with ACC when subjects receive additional information about the new system. This is because subjects do not perceive changes in distance under high workload conditions. 3. The third experiment focuses on acceptance of the simulated system in on-road conditions. In this study, WACC is integrated in the car and is operated using a MATLAB model. The experiment shows that more subjects notice changes in distance in the on-road condition. In general WACC is preferred over ACC; it is especially these subjects who do not notice changes in distance, who value WACC more than ACC. With the aim of implementing an operational WACC that is capable of adjusting distance according to changes in physiological data, a workload algorithm is developed. 4. The fourth experiment validates the workload algorithm. Results of the algorithm are compared with recordings of the activated workload task and detection rate is calculated. The detection of workload periods was feasible in nearly every case and detection rate was favorable, especially if one considers lags due to design-related latency periods. The experiments presented here indicate that workload is detectable in physiological data and that it influences brake reaction time. Further, we provide evidence pointing to the technical possibility of implementing WACC as well as positive acceptance. The results have been published as an article and are part of this thesis. Also, some parts of the thesis are published as a book chapter (see footnotes). Another publication is in preparation, coauthored by diploma thesis students, who are supervised by the author (consult footnotes). This dissertation is composed, in part, of these publications. References to page numbers of the diploma theses are given to ensure correspondence. The author escorted the topic WACC from the beginning to the end. Sometimes students were involved and intensively supervised, from a thematic as well as a personnel guidance perspective. The author planned the whole project and executed studies and calculations. His psychology insights were not only limited to the discipline of psychology but were furthermore, with the help of students, interdisciplinarily expanded to the subject of informatics. Every study and every result which is presented within this work, was conducted or achieved by the author or (if students supported him) was discussed with the author in weekly discussions (and often several times a day). In these discussions the author provided new ideas and corrections if necessary. Apart from that, the author looked after the fulfillment of the central theme, implemented his psychological knowledge on a daily basis and provided his expertise to complement interdisciplinary point of views. He discussed the central theme as well as details with external partners like the MIT AgeLab as well as professors of the European Union from the adaption project (a project aimed at educating future researchers which includes involvement of highly important commercial and educational partners) and beyond. In this time he also visited conferences and accumulated knowledge which led to the successful achievements of the main objective and he was relevant in reaching the common goals of the adaption project. Furthermore he presented the results of the scientific work on a conference, workshops and in written publications. Within BMW Group Research and Technology, he identified important department- and project- partners and combined the knowledge to a result which benefits science and economy. / In dieser Dissertation wird eine Abwandlung des Active Cruise Control (ACC) untersucht, das zusätzlich die Belastung (Workload) des Fahrers als Parameter betrachtet, um den Abstand zum Vordermann automatisiert zu verändern. Bei diesem ACC handelt es sich um ein Fahrerassistenzsystem, das automatisiert die eingestellte Geschwindigkeit hält und eine manuelle (durch den Nutzer ausgelöste) Abstandsveränderung zum Vordermann ermöglicht. Da sich die Bremsreaktionszeit von Fahrern in hohen Belastungssituationen verschlechtert, soll das entwickelte Workload-adaptive Cruise Control (WACC) in Situationen hoher Belastung den Abstand zum Vordermann automatisiert erhöhen. Die Belastung des Fahrers soll durch physiologische Daten ermittelt werden. Die vorliegende Arbeit untersucht die Möglichkeit eines solchen Systems unter der Annahme, dass in Zukunft geeignete physiologische Sensoren ins Auto eingebaut werden können. Die Arbeit besteht aus drei Teilen: • Im ersten Teil wird der theoretische Hintergrund beschrieben und ein passendes theoretisches Modell entwickelt. • Im zweiten Teil werden die durchgeführten Experimente beschrieben. • Im dritten Teil werden die Ergebnisse diskutiert. Insgesamt wurden im Rahmen dieser Arbeit vier Experimente durchgeführt: Das erste Experiment beschäftigte sich mit den grundlegenden Zusammenhängen zwischen Physiologie, Bremsreaktionszeit und Belastungslevel. Wie die Ergebnisse der im Simulator durchgeführten Studie zeigen, können mit physiologischen Daten wie Herzrate, Herzratenvariabilität und Hautleitfähigkeit unterschiedliche Workloadlevel identifiziert werden. Darüber hinaus wurden die Ergebnisse anderer Studien bestätigt, die belegen, dass Workload die Bremsreaktionszeit erhöht, wobei dies nur im Kontrast zwischen den Extrembereichen „kein Workload“ und „hoher Workload“ nachweisbar ist. Das zweite Experiment diente der Simulierung eines perfekten WACC. Im Simulator wurden Akzeptanz und Systemwahrnehmung getestet, um vor der Implementierung in ein Realfahrzeug weitere Erkenntnisse zu gewinnen. Im Vergleich zum ACC wurde das WACC von den Probanden besser akzeptiert, nachdem sie zusätzliche Informationen zum neuen System erhalten hatten. Der wesentliche Grund dafür ist, dass die Probanden ohne Informationen die Abstandsveränderung bei hohem Workload nicht realisieren. Das dritte Experiment fokussierte auf die Akzeptanz des simulierten Systems unter Realbedingungen. Das WACC wurde in das Auto integriert und durch ein MATLAB Modell gesteuert. Als Ergebnis zeigte sich, dass unter Realbedingungen mehr Probanden die Abstandsveränderung realisieren als im Simulator. Generell wird das WACC präferiert – vor allem jene Probanden, die die Abstandsveränderung nicht realisieren, bewerten das WACC besser als das ACC. Mit den in diesem Teilexperiment erhobenen Daten wurde ein Algorithmus zur Workloaderkennung entwickelt. Auf dieser Basis konnte im letzten Experiment ein Realsystem implementiert werden, das aufgrund physiologischer Daten den Abstand verändert. Das vierte Experiment beschäftigte sich mit der Validierung des Algorithmus zur Workloaderkennung. Die Ergebnisse des Algorithmus wurden mit der aufgezeichneten Aktivierung des Workloadtasks verglichen und eine Detektionsrate ermittelt. Die Detektion der Workloadperioden gelingt in fast allen Fällen und die Detektionsrate ist vielversprechend, gerade wenn man Verzögerungen berücksichtigt, die wegen der Latenzzeit körperlicher Reaktionen nicht verbesserungsfähig sind. In den vorliegenden Experimenten konnte gezeigt werden, dass Workload über die Physiologie messbar ist und sich auf die Bremsreaktionszeit auswirkt. Darüber hinaus wurde gezeigt, dass ein WACC technisch machbar ist und die Ergebnisse lassen außerdem auf eine hohe Akzeptanz schließen. Die Forschungsergebnisse wurden in einem Artikel publiziert, der auch in dieser Dissertation zu finden ist. Teile der vorliegenden Arbeit wurden außerdem als Buchkapitel veröffentlicht (siehe Fußnoten), eine weitere Publikation mit den vom Autor umfassend betreuten Diplomanden ist in Ausarbeitung. Um die Nachvollziehbarkeit zu gewährleisten, wurde auf die Seitenzahlen der entsprechenden Diplomarbeiten verwiesen. Als Autor dieser Dissertation habe ich das Thema WACC von Anfang bis Ende selbst erarbeitet bzw. wurden Studenten eingesetzt und angeleitet, wo es sinnvoll erschien. Neben der fachlichen wie personellen Führung der Studenten umfassten meine Aufgaben die Planung des Gesamtprojekts, das Durchführen der Studien und die Berechnung von Kennzahlen – sowohl in meinem eigenen psychologischen Fachgebiet als auch interdisziplinär mit Hilfe von Experten aus der Informatik. Jedes Ergebnis, das in dieser Arbeit präsentiert wird, wurde entweder von mir selbst erzielt oder – sofern ich dabei von Studenten unterstützt wurde – mit mir in wöchentlichen (oft auch mehrmals täglich stattfindenden Meetings) besprochen. Wichtig war mir als Autor, einen durchgängigen Weg zur Entwicklung eines WACC zu wahren, mein psychologisches Fachwissen täglich anzuwenden und in interdisziplinären Aufgaben und Diskussionen meine Perspektive einzubringen. Besonders wichtig war dabei die Diskussion des Gesamtprojekts und der Details mit externen Partnern wie dem MIT AgeLab oder Professoren aus der Europäischen Union im Rahmen des Adaptation Projekts (ein von der EU gefördertes Projekt zur Ausbildung von Forschern, unter Einbindung wirtschaftlich und wissenschaftlich hochrangiger Partner). Durch die Präsentation der Ergebnisse auf Konferenzen, in Workshops und Publikationen konnte ich einen Beitrag dazu leisten, um die Adaptation-Ziele zu erreichen. Innerhalb der BMW Group Forschung und Technik habe ich darauf geachtet, relevante Schnittstellen- und Projektpartner zu identifizieren und das erlangte Wissen zu einem Ergebnis zu verbinden, das Wissenschaft und Wirtschaft gleichermaßen nützt.