Appendix B (leaves 217-218), Appendix M (leaves 239-247) and Appendix O (leaves 253-259) in English and Amharic / The purpose of this research was to develop HIV testing Health Belief Scale (HTBS) that contains the constructs of Health Belief Model (HBM), and also to analyse HIV testing intention and behaviour among university students. The mixed method approach was used in phases. First, Literature review and in-depth interviews were conducted to develop item pool for HTBS, which was followed by content validity assessment by experts. In the second phase, a pilot survey was conducted on randomly selected 318 university students to refine the HTBS using item analysis and Exploratory Factor Analysis (EFA). Lastly, cross-sectional survey was conducted on representative sample of 612 students in order to further refine the HTBS using Confirmatory Factor Analysis (CFA) and also analyse predictors of HIV testing intention and behaviour. A total of 61 items was written for the HTBS and 23 of these were generated from the in-depth interviews. Content validity assessment by three experts indicated that the average content validity index (CVI) for the 61 items was 91.2% which was more than the recommended cut off point of 90%. The HTBS, after experts review, contained 64 items. EFA indicated that a five factor model which was roughly consistent with HBM was identified and 44 items were retained based on factor loading and reliability analysis. The Cronbach’s alpha for all the six constructs of HBM and HIV testing intention in the HTBS were >0,70. (susceptibility, benefit, self-efficacy and HIV testing intention) fitted the sample data based on chi-square test. However, all the seven constructs demonstrated RMSEA value of less than 0.08 and GFI value of >0.90 indicating acceptable fit. The final HTBS was reduced to 39 items based on factor loading and reliability assessment. All the constructs demonstrated a Cronbach’s alpha value >0.70 except for perceived susceptibility and cues to action. Analysis of multiple linear regression indicated that class year, perceived benefit, perceived self-efficacy and cues to action were significant predictors of HIV testing intention. However, only marital status and cues to action were significant predictors of recent history of HIV testing through analysis of binary logistic regression. / Health Studies / D.Litt. et Phil. (Health Studies)

Indiana University-Purdue University Indianapolis (IUPUI) / The objective of this research is to examine the development of the California alcohol outlets over time and the relationship between neighborhood characteristics and densities of the alcohol outlets. Two types of advanced analyses were done after the usual preliminary description of data. Firstly, fixed and random effects linear regression were used for the county panel data across time (1945-2010) with a dummy variable added to capture the change in law regarding limitations on alcohol outlets density. Secondly, a Bayesian spatio-temporal Poisson regression of the census tract panel data was conducted to capture recent availability of population characteristics affecting outlet density. The spatial Conditional Autoregressive model was embedded in the Poisson regression to detect spatial dependency of unexplained variance of alcohol outlet density. The results show that the alcohol outlets density reduced under the limitation law over time. However, it was no more effective in reducing the growth of alcohol outlets after the limitation was modified to be more restrictive. Poorer, higher vacancy rate and lower percentage of Black neighborhoods tend to have higher alcohol outlet density (numbers of alcohol outlets to population ratio) for both on-sale general and off-sale general. Other characteristics like percentage of Hispanics, percentage of Asians, percentage of younger population and median income of adjacency neighbors were associated with densities of on-sale general and off sale general alcohol outlets. Some regions like the San Francisco Bay area and the Greater Los Angeles area have more alcohol outlets than the predictions of neighborhood characteristics included in the model.