The purpose of this study was to investigate the disfluency characteristics of normal 33-39 month old children in order to determine the differential role of the SSI with young children. The following questions were answered: 1. What are the types and frequencies of disfluencies demonstrated by normal 33-39 month old children? 2. How do the scores of normal 33-39 month old children distribute on the Stuttering Severity Instrument?

Severe weather outbreaks are fairly common events that occur multiple times a year. Many studies have attempted to define and quantify these outbreaks, however, no work has been done to directly relate synoptic-scale processes to outbreak intensity using the N15 ranking index. It is believed that a statistically significantly strong relationship between outbreak severity and quantified synoptic-scale parameters exists and can be utilized to predict the severity of an upcoming outbreak using the N15 ranking index. Utilizing the NCEP-NCAR Reanalysis dataset, synoptic-scale variables were chosen and standardized into domains created from areal coverages. A series of tests were completed, including stepwise regression, principal component analysis, and a bootstrap cross-validation method to find the most significant variables and best domain size. The findings from this study suggest that synoptic-scale processes do not have a strong relationship to severe weather outbreak intensity and that future work would be necessary.

Low back pain (LBP) is the most prevalent work-related musculoskeletal disorder. Occupational risk factors have been studied for current ergonomic prevention strategies; however, other underlying mechanisms may exist since not all workers performing the same task develop the same severity. Previous research has identified personal and psychosocial risk factors that also contribute to LBP. Research quantifying the interactive effects of the various personal, psychosocial and occupational factors is limited, along with research on the effect of risk factor combinations on LBP severity. The objectives of this study were to: 1) study the various factors that are known to be involved in low back pain and analyze interactions, and 2) develop a model to predict low back pain and validate it. In order to address these objectives, 2 studies were conducted. The first study investigated the effects of various personal, genetic, occupational and psychosocial factors on two subjective LBP severity ratings: Oswestry Disability Index (ODI) and a Visual Analog Scale (VAS), and three physician-based ratings: MRI severity, canal stenosis and nerve impingement. Personal and psychosocial factors, in addition to occupational factors, were found to significantly affect the severity ratings. The second study involved building predictive models of LBP severity for each risk factor category as well as a combined risk factor model. Results showed that the combined risk factor models considering interaction effects both within and across risk factor categories were significantly better in predicting severity ratings than the individual models. However, validation conducted using 5 random samples showed inconsistent accuracies. Results obtained may help to develop a more reliable way to predict and, hence, prevent chronic LBP.

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The goal of this thesis is to determine the contributing factors affecting severe traffic crashes (severe: incapacitating and fatal - non-severe: no injury, possible injury, and non-incapacitating), and in particular those factors influencing crashes involving large vehicles (heavy trucks, truck tractors, RVs, and buses). Florida Department of Highway Safety and Motor Vehicles (DHSMV) crash reports of 2008 have been used. The data included 352 fatalities and 9,838 injuries due to large vehicle crashes. Using the crashes involving large vehicles, a model comparison between binary logit model and a Chi-squared Automatic Interaction Detection (CHAID) decision tree model is provided. There were 13 significant factors (i.e. crash type with respect to vehicle types, residency of driver, DUI, rural-urban, etc.) found significant in the logistic procedure while 7 factors found (i.e. posted speed limit, intersection, etc.) in the CHAID model. The model comparison results indicate that the logit analysis procedure is better in terms of prediction power. The following analysis is a modeling structure involving three binary logit models. The first model was conducted to estimate the crash severity of crashes that involved only personal vehicles (PV). Second model uses the crashes that involved large vehicles (LV) and passenger vehicles (PV). The final model estimated the severity level of crashes involving only large vehicles (LV). Significant differences with respect to various risk factors including driver, iii vehicle, environmental, road geometry and traffic characteristics were found to exist between those crash types and models. For example, driving under the influence of Alcohol (DUI) has positive effect on the severity of PV vs. PV and LV vs. PV while it has no effect on LV vs. LV. As a result, 4 of the variables found to be significant were similar in all three models (although often with quite different impact) and there were 11 variables that significantly influenced crash injury severity in PV vs. PV crashes, and 9 variables that significantly influenced crash injury severity in LV vs. PV crashes. Based on the significant variables, maximum posted speed, number of vehicles involved, and intersections are among the factors that have major impact on injury severity. These results could be used to identify potential countermeasures to reduce crash severity in general, and for LVs in particular. For example, restricting the speed limits and enforcing it for large vehicles could be a suggested countermeasure based on this study.

Roadway crashes related to vision obstruction due to fog/smoke (FS) conditions constitute a challenge for traffic engineers. Previous research efforts mostly concentrated on the snow and rain related crashes. Statistics show that Florida is among the top three states in terms of crashes due to vision obstruction by FS. This research culminated in a comprehensive study of fog and smoke related crashes in the state of Florida. The analysis took into account the crashes that occurred between 2003 and 2007 on Florida state roads. Spatial analysis and injury severity analysis have been conducted and significant results have been identified. The spatial analysis by GIS examines the locations of high trends of FS related crashes on state roads in the State of Florida. Statistical features of the GIS tool, which is used efficiently in traffic safety research, has been used to find the crash clusters for the particular types of crashes that occur due to vision obstruction by FS. Several segmentation processes have been used, and the best segmentation for this study was found to be dividing the state roads into 1 mile segments, keeping the roadway characteristics uniform. Taking into account the entire state road network, ten distinct clusters were found that can be clearly associated with these types of crashes. However, no clear pattern in terms of area was observed, as it was seen that the percentage of FS related crashes in rural and urban areas are close. The general characteristics of FS related crashes have been investigated in detail. For the comparison to clear visibility conditions, simple odds ratios (in terms of crash frequencies) have been introduced. The morning hours in the months of December to February are found to be the prevalent time for fog related crashes, while for the smoke related crashes the dangerous time was found to be morning to midday in the month of May. Compared to crashes under clear-visibility conditions, the fog crashes tend to result in more severe injuries and involve more vehicles. Head-on and rear-end crashes are the two most common crash types in terms of crash frequency and severe crashes. For the injury severity analysis, a random effect ordered logistic model was used. The model in brief illustrates that the head-on and rear-end crash types are the two most prevalent crash types in FS conditions. Moreover, these severe crashes mainly occurred at higher speeds. Also they mostly took place on undivided roads, roadways without any sidewalk and two-lane rural roads. Increase of average daily traffic decrease the severity of FS related crashes. Overall, this study provides the Florida Department of Transportation (FDOT) with specific information on where improvements could be made to have better safety conditions in terms of vision obstruction due to FS in the state roads of Florida. Also it suggests the times and seasons that the safety precautions must be taken or the FS warning systems to be installed, and the controlling roadway geometries that can be improved or modified to reduce injury severity of a crash due to FS related vision obstruction.

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Traumatic brain injury (TBI) history has been linked to damaged cognition and poorer quality of life. While this link has been established, there is not much known about this relationship in older adult populations experiencing normal cognitive decline. In the current study, mental status was predicted to moderate the relationship between TBI history and life satisfaction among older adults. Additionally, details of the injury - years since injury and time spent unconscious - were expected to play a role in this relationship. Per analyses, there was no relationship found between TBI history, mental status, and life satisfaction. Moreover, there was no link found between time since injury, time spent unconscious, mental status and life satisfaction. While insignificant, these results yield important findings. The results lend support to more positive long-term outcomes for those with a history of TBI than initially expected, especially if the TBI was mild and resulted in no loss of consciousness or a loss of consciousness less than 5 hours.

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