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Outdoor air pollution is a major contributor to adverse health effects of citizens, in particular those living in urban environments. Air quality monitoring networks are set up to measure air quality in different environments in compliance with national and European legislation. Generally, only a few fixed monitoring sites are located within a city and thus cannot represent air pollutant concentrations in urban areas accurately enough to allow for a detailed human exposure assessment. Other approaches to derive detailed urban air pollutant concentration estimates exist, such as dispersion models and land-use regression (LUR) models. Low-cost portable air quality monitors are also emerging, which have the potential to add value to existing monitoring networks by providing measurements at greater spatial resolution and also to provide individual-level exposure assessment. The aim of this thesis is to demonstrate how measurements and modelling in combination allow detailed investigations of the variability of air pollutants in space and time in urban area, and in turn improve on the current exposure assessment methods. Three types of low-cost portable monitors measuring NO2, O3 (Aeroqual monitors) and PM2.5 (microPEM monitor) were evaluated against their respective reference instruments. The Aeroqual O3 monitor showed very good correlation (r2 > 0.9) with the respective reference instruments, but biases in the slope and intercept coefficients indicated that calibration of Aeroqual O3 monitor was needed. The Aeroqual NO2 monitor was subject to cross-sensitivity from O3, which, as demonstrated, can be effectively corrected by making O3 and NO2 measurements in tandem. Correlation between the microPEM monitor and its reference instrument was poor (r2 < 0.1) when PM2.5 concentrations were low (< 10 μg m-3), but significantly improved (r2 > 0.69) during periods with elevated PM2.5 concentrations. Relative humidity was not found to affect the raw results of PM2.5 measurements in a consistent manner. All three types of monitors cannot be used as equivalent or indicative methods instead of reference methods in studies that require quantification of absolute pollutant concentrations. However, the generally good correlations with reference instruments reassure their application in studies of relative trends of air pollution. Concentrations of PM2.5, ultrafine particles (UFP) and black carbon (BC) were quantified using portable monitors through a combination of mobile and static measurements in the city of Edinburgh, UK. The spatial variability of UFP and BC was large, of similar magnitude and about 3 times higher than the spatial variability of PM2.5. Elevated concentrations of UFP and BC were observed along streets with high traffic volumes whereas PM2.5 showed less variation between streets and a footpath without road traffic. Both BC and UFP significantly correlated with traffic counts, while no significant correlation between PM2.5 and traffic counts was observed. The relationships between UFP, NO2 and inorganic components of PM2.5 were further investigated through long-term measurements at roadside, urban background and rural sites. UFP moderately correlated with NOx (NO2 + NO) and showed varying relationships with NOx depending on the particle size distribution. Principal component analysis and air-mass back trajectory analysis revealed that PM2.5 concentrations were dominated by long-range transport of secondary inorganic aerosols, whereas UFP were mainly related to varying local emissions and meteorological conditions. These findings imply the need for different policies for managing human exposure to these different particle components: control of much BC and UFP appears to be manageable at local scale by restricting traffic emissions; however, abatement of PM2.5 requires a more strategic approach, in cooperation with other regions and countries on emissions control to curb long-range transport of PM2.5 precursors. A dispersion model (ADMS-Urban) was used to simulate high resolution NO2 and O3 concentrations in Edinburgh. The effects of different emission and meteorological input datasets on the resulting modelled NO2 concentrations were investigated. The modelled NO2 and O3 concentrations using the optimal model setup were validated against reference instrument and diffusion tube measurements. Temporal variability of NO2 was predicted well at locations that were not heavily influenced by local effects, such as road junctions and bus stops. Temporal variability of O3 was predicted better than for NO2. Long-term spatial variability of NO2 was found to correlate well with diffusion tube measurements, while modelled spatial variability of O3 in ADMS-Urban compared poorly with diffusion tube measurements. However, it was found that the O3 diffusion tube measurements may be subject to some unidentified biases affecting their accuracy. Land-use regression (LUR) models are widely used to estimate exposure to air pollution in urban areas. An appropriately sized and designed monitoring network is an important component for the development of a robust LUR model. Concentrations of NO2 were simulated by ADMS-Urban at ‘virtual’ monitoring sites in 54 different network designs of varying numbers and types of site, using a 25 km2 area including much of the Edinburgh city area. Separate LUR models were developed for each network. These LUR models were then used to estimate ambient NO2 concentrations at all residential addresses, which were evaluated against the ADMS-Urban modelled concentration at these addresses. The improvement in predictive capability of the LUR models was insignificant above ~30 monitoring sites, although more sites tended to yield more precise LUR models. Monitoring networks containing sites located within highly populated areas better estimated NO2 concentrations across all residential locations. LUR models constructed from networks containing more roadside sites better characterised the high end of residential NO2 concentrations but had increased errors when considering the whole range of concentrations. No particular composition of monitoring network resulted in good estimation simultaneously across all residential NO2 concentration and of the highest NO2 levels implying a lack of spatial contrast in LUR-modelled pollution surface compared with the dispersion model. Finally, the results from the measurement and modelling studies presented in thesis are synthesised in the context of current exposure assessment studies. Low-cost air-quality monitors currently do not possess and are unlikely in the near future to provide the robustness and accuracy to replace the existing routine monitoring network. Development of the low-cost air-quality should be aiming at upgrading them as the indicative method as defined in the data quality objective in the EU directive. The monitoring sites used to build LUR models should capture well the population distribution in the study area as opposed to capturing the greatest pollution contrast. The traditional methods of evaluating LUR models are also ineffective in characterising the models’ capability at estimating pollutant concentration at residential address. Given that the dispersion models are also subject to the availability and uncertainties in the input data, future air quality model development should endeavour to incorporate both dispersion and land-use regression models, where the uncertainty in the input data can be reduced by using LUR models built on actual measurements, and the limitation in the statistical modelling can be replaced by adopting the deterministic approach used in the dispersion model.

The negative symptoms of schizophrenia include impoverished speech, affective blunting, an inability to anticipate pleasure, asociality, and amotivation. Current effective treatment options are limited, which is a significant issue given their strong association to functional impairment. The primary aims of this thesis are to explore areas which may inform the design of clinical trials addressing these symptoms, build upon recent advances in negative symptom assessment, and further understand the impact of negative symptoms on outcomes. A meta-analysis examining the longitudinal course of negative symptoms demonstrated a consistent reduction in negative symptoms over the study period in all treatment conditions examined, including in studies which adopted different eligibility criteria to minimise the presence of secondary negative symptoms. A comparison of different eligibility criteria revealed that whilst these criteria reduce the association between negative and depressive symptoms, their association to positive symptoms remains largely unaffected, and can substantially reduce the proportion of available participants. Given existing negative symptom assessment tools have been identified as a significant barrier in the development of new treatments, a comparison of assessment methods was performed. Results revealed the Clinical Assessment Interview for Negative Symptoms to be a more sensitive instrument, and a better predictor of functional impairments, relative to the negative subscale of the Positive and Negative Syndrome Scale. Findings described here also demonstrate that the link between negative symptoms and subjective quality of life may be stronger than previously assumed, relating exclusively to experiential deficits. Finally, manic and positive symptoms, rather than negative symptoms, were found to be associated with inpatient treatment appraisal, an important factor in treatment outcomes. Overall, this thesis describes key findings which demonstrate the importance of the appropriate assessment of negative symptoms of schizophrenia, shine new light on symptom progression over time, and highlight a need to further refine clinical trial inclusion criteria.

As engineering work becomes more globalized, it is important to prepare students to succeed in a global engineering workforce. Prior research has explored different factors important to the design of global programs generally, but less is known about the experiences and learning outcomes of engineering students while abroad. Because this population has historically been underrepresented in global programs, few research-based practices have been identified to support the intentional design of global experiences for engineering students. This dissertation seeks to provide such insights through three studies that address the following components of global engineering program design: 1) the assessment of Global Engineering Competency (GEC) through use of a series of scenarios based in the Chinese context; 2) the relationship between program destination and students’ experiences and reported learning outcomes; and 3) the experiences that engineering students identify as most significant during their time abroad. I used a combination of quantitative, qualitative, and mixed research methods to explore students’ learning and experiences in global engineering programs. The results of these studies revealed that engineering students have a wide variety of learning outcomes and experiences as a result of global programs, that great care should be exercised in choosing and interpreting assessment methods for global programs, and that the design of global engineering programs should be informed by characteristics of both the student participants and the program destination. Overall, the results of this dissertation highlight the importance of intentionality when designing global engineering programs to better prepare students for success in a global work environment.

The present study investigated current anxiety assessment procedures used by practicing school psychologists, as well as the most common barriers they see to the assessment process. A statewide survey of practicing school psychologists was conducted. The participants included (n=111) licensed school psychologists employed in the state of Ohio, who were also members of the Ohio School Psychologists Association (OSPA) listserv or who attended the OSPA spring (2013) conference. Findings indicated the most frequently used assessment method was interviews, while the most frequently utilized measurement tool was the Behavior Assessment Scale for Children, 2nd edition (BASC-2). The most frequently reported barrier to using evidence-based assessment methods for anxiety in the schools was the lack of available time. Implications for assessing anxiety in school-age youth are discussed.

BACKGROUND: The healthcare industry relies on hospitals to employ competent individuals providing care to patients in many different specialties. There is a lack of research available that effectively describes the current state of Respiratory Therapy department orientation. The purposes of this study were to describe how respiratory therapy department managers have structured their new employee orientations programs to verify competency (using the competencies from the AARC’s 2015 and Beyond) and describe how these programs were designed to meet the JC standards. METHODS: This study was executed through the use of survey research methodology and used the list serves for the national Management and Education Section Memberships of the AARC to distribute the survey invitation email, which totaled 2,907 members. A request was made in the email for the recipient to forward the survey to the individual in the department who is responsible for new employee orientation. Thirty-seven of the sixty-nine competencies outlined in the 2015 & Beyond initiative were selected. The JC standards originated from the Human Resources section of the 2010 Hospital Accreditation Program Standards. RESULTS: From 449 respondents who accessed the online survey, 333 met the inclusion criteria. Fifty-five percent of respondents described their hospital type as a community hospital, 30.1% as Academic/Teaching, 4.0% as Children’s, and under the other option respondents listed types of hospitals as: LTACHs, specialty, and cardiology. Forty-two percent of respondents described their hospital location as urban, 30.6% as suburban, and 26.9% rural. Two hundred twenty-six (77%) respondents indicated newly hired staff therapists receive individualized orientation programs based on their needs or passed experience. Individuals responsible for conducting newly hired staff therapist orientation reported that additional training had been completed in order to be qualified to assure new staff competency. Of the AARC 2015 and Beyond competencies, 36 of the selected 37 were most frequently assessed with the observation of performing task (check-off) option. Only 8 out of 37 competencies were not assessed by greater than 25% of respondents. The JC topics for assessment used mixed methods, most commonly computer based learning, lecture, and handouts. All JC topics in the survey were covered by greater than 95% of respondents except for early warning signs of a changing patient condition. Significant differences were found between competency assurance for both location and hospital type for several competencies. Probationary periods of 60-90 days were frequently reported as a timeframe where new employees were expected demonstrate competency prior to termination. CONCLUSION: RT departments are qualified and excelling in assessing competency for new staff therapists and should continue to incorporate advanced skills for the 2015 & Beyond initiative. Methods used to assess competency should incorporate those beyond traditional tests and check-offs. Departments should consider the use of simulators due to the added benefits of learning retention, critical thinking, and teamwork skills.

Spring dead spot (SDS) is one of the most severe diseases of bermudagrass in Australia, New Zealand, and in the United States where bermudagrass goes into winter dormancy. Several key factors have hampered research on SDS in the past and are likely due to the lack of complete knowledge about the etiology and epidemiology of SDS, lack of knowledge for optimal fungicide efficacy, and the erratic distribution of SDS in the field, which contributes to experimental error. The objectives of this research were to optimize application methods, application timings, and fungicide efficacy, to evaluate rating methods for analysis of SDS incidence, and to identify the causal organism for SDS of bermudagrass in North Carolina. Between 2002 and 2004, we evaluated the efficacy of five application methods, twelve application timings, and four fungicides. No significant differences were detected among application methods; however application in higher volumes of water tended to provide better control. No significant differences were noted among applications timings when compared to the untreated control, but multiple applications starting in August or September tended to provide better control than single or late season applications. Spring applications had no significant effect on SDS incidence or recovery rate. Of the fungicides that were evaluated in this project, fenarimol and propiconazole were most effective, providing from 44 to 89% and 42 to 54% control, respectively. In the spring of 2003, comparison of three different assessment methods for SDS were evaluated: digital photography (DP), visual estimation (VE), and the point-intersect method (PI). Results of this study indicate that DP is more effective than VE for assessment of SDS incidence. Digital photography consistently produced higher r2 values and lower CV, MSD, and MSE values than VE. Reductions in experimental error translated directly to differences in mean separations used to compare disease incidence in response to fungicide treatments. Digital photography was not consistently more accurate or precise than PI. In total, two-hundred twenty-one isolates of Ophiosphaerella were collected between 2003 and 2004. Of the isolates collected, Ophiosphaerella korrae (186 of 221) was the predominant organism isolated from SDS symptomatic bermudagrass. Ophiosphaerella herpotricha (22 of 221) was detected at low levels in the Charlotte, Raleigh, and Wilmington regions, whereas O. narmari was never detected at all in this study.