Psychosocial predictors of HIV testing behaviors among high risk heterosexuals

Though a lot of progress has been made in the treatment, prevention, and in increasing the knowledge and awareness of HIV/AIDS, the CDC reports that over 21% of the people infected with HIV are unaware of their HIV serostatus. Thirty-one percent of people infected with HIV are diagnosed late in the disease progression, often too late to prevent the transmission or the progression of HIV to AIDS. CDC has set a goal to increase by the year 2010, the number of people aware of the HIV serostatus by 5%. ^ This study examined the association between decision-making and risk-taking (assessed using the decision-making confidence and risk-taking scales of the Texas Christian University Self Rating Form) and HIV testing behaviors within a population of heterosexuals at risk for HIV infections living in Harris County, Texas (N=923). Data used in the study was obtained during the first cycle of the National HIV Behavioral Surveillance among heterosexuals at risk for HIV infection (NHBS-HET1), conducted from October, 2006 to June, 2007. Eighty percent of the study population reported testing for HIV at some point in their lives. The results showed that individuals who scored high (>3.3) on the decision-making confidence scale of the TCU/SRF were more likely to be tested for HIV when compared to those who scored low on the scale (OR= 2.02, 95% CI= 1.44–2.84), and that individuals who score low on the risk-taking scale of the TCU/SRF were more likely to have been tested for HIV when compared to those who scored high on the scale (OR= 1.65, 95% CI= 1.2–2.31). Several demographic factors were also assessed for their association with HIV testing behaviors. Only sex was found to be associated with HIV testing. ^ The findings suggest that risk-taking and decision-making are predictors of HIV testing behaviors such as prior HIV testing within heterosexuals living in high-risk areas of Houston, Texas, and that intervention designed to improve the risk-taking and decision-making attributes of this population might improve HIV testing within this population.^

Process and outcome evaluation of the hepatitis B perinatal vaccination program in Houston, Texas, 1991--1993

A retrospective cohort study was designed to evaluate the compliance of vaccination dose schedules and vaccination effectiveness at 12 months of age among a total of 226 high-risk infants born to HBsAg-positive pregnant women who participated in the HBV Perinatal Vaccination Program in Houston, Texas, 1991-1993.^ The seroprevalence of HBsAg-positivity was 0.5% among pregnant women who attended prenatal clinics in Houston, Texas, 1991-1993. The Asian women had the highest seroprevalence rate (5.9%), followed by black (1.9%), white (0.7%), and Hispanic women (0.3%). The seroprevalence of HBsAg increased with age (p =.02); the highest seroprevalence rate found among the $>$40 group (5.4%), followed by the 20-40 age group, and the $<$20 age. A steady increase was observed in the number of infants, from 45 in 1991, to 103 in 1993. The majority of these infants were black (58.0%), followed by Hispanic (28.8%), Asian (8.4%), and white infants (4.0%). Significant increases were observed from 1991 to 1993 in the number of infants who initiated vaccination (86.7% to 98.1%, p =.02) and in those infants who were post-tested at 12 months of age (24.4% to 44.7%, p =.04). During the same period an increase was also observed in the number of infants who completed the vaccination dose schedules (62.2% to 72.8%, p =.37). The compliance rates were not statistically significant regarding gender, race or ethnicity, health service area, medical referral source, and residential geographic areas. About 56.0% of the reasons cited for non-compliance among the 144 infants who neither completed the vaccination dose schedules nor received the 12-month post-test were "moved," and "no response/not at home." A total of 82 infants completed the vaccination dose schedules and were post-tested at 12 months of age for anti-HBs-positivity, and 96.3% of these infants seroconverted. A race-specific statistically significant seroconversion difference was found among infants who received all vaccination doses and were post-tested at 12 months of age (100% for the black and the white, 96.3% for the Hispanic, and 80.0% for the Asians infants, p =.05).^ From a public health perspective, the HBV Perinatal Vaccination Program improved during its first three years (1991-1993). It was effective in preventing perinatal HBV infection in almost 97.0% of infants who were vaccinated and post-tested. To increase the efficiency and efficacy of the program, the following recommendations are proposed: (1) Increase the vaccination compliance rate by educating and improving the tracking, communication and coordination channels with those individuals involved in the process and by increasing staff resources. (2) Reduce the post-test vaccination non-compliance by post-testing infants simultaneously with third vaccination dose at 6 months of age, and only post-test those infants who are anti-HBs-negative at 9-12 months of age. (Abstract shortened by UMI.) ^

COMPARISON OF THE ORGANIZATIONAL STRUCTURES AND EFFECTIVENESS OF THE INVESTOR-OWNED AND VOLUNTARY MULTIHOSPITAL SECTORS

Objectives. The central objective of this study was to systematically examine the internal structure of multihospital systems, determining the management principles used and the performance levels achieved in medical care and administrative areas.^ The Universe. The study universe consisted of short-term general American hospitals owned and operated by multihospital corporations. Corporations compared were the investor-owned (for-profit) and the voluntary multihospital systems. The individual hospital was the unit of analysis for the study.^ Theoretical Considerations. The contingency theory, using selected aspects of the classical and human relations schools of thought, seemed well suited to describe multihospital organization and was used in this research.^ The Study Hypotheses. The main null hypotheses generated were that there are no significant differences between the voluntary and the investor-owned multihospital sectors in their (1) hospital structures and (2) patient care and administrative performance levels.^ The Sample. A stratified random sample of 212 hospitals owned by multihospital systems was selected to equally represent the two study sectors. Of the sampled hospitals approached, 90.1% responded.^ The Analysis. Sixteen scales were constructed in conjunction with 16 structural variables developed from the major questions and sub-items of the questionnaire. This was followed by analysis of an additional 7 structural and 24 effectiveness (performance) measures, using frequency distributions. Finally, summary statistics and statistical testing for each variable and sub-items were completed and recorded in 38 tables.^ Study Findings. While it has been argued that there are great differences between the two sectors, this study found that with a few exceptions the null hypotheses of no difference in organizational and operational characteristics of non-profit and for-profit hospitals was accepted. However, there were several significant differences found in the structural variables: functional specialization, and autonomy were significantly higher in the voluntary sector. Only centralization was significantly different in the investor owned. Among the effectiveness measures, occupancy rate, cost of data processing, total manhours worked, F.T.E. ratios, and personnel per occupied bed were significantly higher in the voluntary sector. The findings indicated that both voluntary and for-profit systems were converging toward a common hierarchical corporate management approach. Factors of size and management style may be better descriptors to characterize a specific multihospital group than its profit or nonprofit status. (Abstract shortened with permission of author.) ^

Knowledge, Attitudes, and Utilization of BRCA Testing Among Obstetricians and Gynecologists

Hereditary breast and ovarian cancer (HBOC) is an inherited cancer syndrome that is associated with mutations in the BRCA1 and BRCA2 genes. Carriers of BRCA mutations, both men and women, are at an increased risk for developing certain cancers. Carriers are most notably at an increased risk to develop breast and ovarian cancers; however an increased risk for prostate cancer, melanoma, and pancreatic cancers has also been associated with these mutations. In 2009 the American Congress of Obstetricians and Gynecologists (ACOG) released a practice bulletin stating that evaluating a patient’s risk for HBOC should be a routine part of obstetric and gynecologic practice. A survey was created and completed by 83 obstetricians and gynecologists in the greater Houston, TX area. The survey consisted of four sections designed to capture demographic information, attitudes towards HBOC and BRCA testing, utilization of BRCA testing, and the overall knowledge of respondents with regards to HBOC and BRCA testing. This study found that the majority of participants indicated that they felt that obstetricians and gynecologists should have the primary responsibility of identifying patients who may be at increased risk of carrying a BRCA mutation. Moreover, this study found that the majority of participants indicated that they felt comfortable or very comfortable in identifying patients at an increased risk of carrying a BRCA mutation. However, only about a quarter of participants indicated that they order BRCA genetic testing one to two times per month or more. Lastly, this study demonstrates that the overall knowledge of HBOC and BRCA testing among this population of obstetricians and gynecologists is poor. The results of this study stress the need for more education regarding HBOC, genetic testing, and strategies for identifying patients that may be at risk for having a mutation in a BRCA gene. Furthermore, it reiterates the importance of raising awareness to current practice guidelines and recommendations that can assist obstetricians and gynecologist to better identify and manage patients that may be at an increased risk of having HBOC.

A review of the Malaria Chemoprophylaxis Compliance Program at ExxonMobil Corporation

ExxonMobil, a Fortune 500 oil and gas corporation, has a global workforce with employees assigned to projects in areas at risk for infectious diseases, particularly malaria. As such, the corporation has put in place a program to protect the health of workers and ensure their safety in malaria endemic zones. This program is called the Malaria Control Program (MCP). One component of this program is the more specific Malaria Chemoprophylaxis Compliance Program (MCCP), in which employees enroll following consent to random drug testing for compliance with the company's chemoprophylaxis requirements. Each year, data is gathered on the number of employees working in these locations and are selected randomly and tested for chemoprophylaxis compliance. The selection strives to test each eligible worker once per year. Test results that come back positive for the chemoprophylaxis drug are considered "detects" and tests that are negative for the drug and therefore show the worker is non-compliant at risk for severe malaria infection are considered "non-detect". ^ The current practice report used aggregate data to calculate statistics on test results to reflect compliance among both employees and contractors in various malaria-endemic areas. This aggregate, non-individualized data has been compiled and reflects the effectiveness and reach of ExxonMobil's Malaria Chemoprophylaxis Compliance Program. In order to assess compliance, information on the number of non-detect test results was compared to the number of tests completed per year. The data shows that over time, non-detect results have declined in both employee and contractor populations, and vary somewhat by location due to size and scope of the MCCP implemented in-country. Although the data indicate a positive trend for the corporation, some recommendations have been made for future implementation of the program.^

CHARACTERIZATION OF THE COUNT RATE PERFORMANCE AND EVALUATION OF THE EFFECTS OF HIGH COUNT RATES ON MODERN GAMMA CAMERAS

CHARACTERIZATION OF THE COUNT RATE PERFORMANCE AND EVALUATION OF THE EFFECTS OF HIGH COUNT RATES ON MODERN GAMMA CAMERAS Michael Stephen Silosky, B.S. Supervisory Professor: S. Cheenu Kappadath, Ph.D. Evaluation of count rate performance (CRP) is an integral component of gamma camera quality assurance and measurement of system dead time (τ) is important for quantitative SPECT. The CRP of three modern gamma cameras was characterized using established methods (Decay and Dual Source) under a variety of experimental conditions. For the Decay method, input count rate was plotted against observed count rate and fit to the paralyzable detector model (PDM) to estimate τ (Rates method). A novel expression for observed counts as a function of measurement time interval was derived and the observed counts were fit to this expression to estimate τ (Counts method). Correlation and Bland-Altman analysis were performed to assess agreement in estimates of τ between methods. The dependencies of τ on energy window definition and incident energy spectrum were characterized. The Dual Source method was also used to estimate τ and its agreement with the Decay method under identical conditions and the effects of total activity and the ratio of source activities were investigated. Additionally, the effects of count rate on several performance metrics were evaluated. The CRP curves for each system agreed with the PDM at low count rates but deviated substantially at high count rates. Estimates of τ for the paralyzable portion of the CRP curves using the Rates and Counts methods were highly correlated (r=0.999) but with a small (~6%) difference. No significant difference was observed between the highly correlated estimates of τ using the Decay or Dual Source methods under identical experimental conditions (r=0.996). Estimates of τ increased as a power-law function with decreasing ratio of counts in the photopeak to the total counts and linearly with decreasing spectral effective energy. Dual Source method estimates of τ varied as a quadratic with the ratio of the single source to combined source activities and linearly with total activity used across a large range. Image uniformity, spatial resolution, and energy resolution degraded linearly with count rate and image distorting effects were observed. Guidelines for CRP testing and a possible method for the correction of count rate losses for clinical images have been proposed.

Evaluation of the Hosmer -Lemeshow global goodness -of-fit statistic for mixed variable logistic regression models

The performance of the Hosmer-Lemeshow global goodness-of-fit statistic for logistic regression models was explored in a wide variety of conditions not previously fully investigated. Computer simulations, each consisting of 500 regression models, were run to assess the statistic in 23 different situations. The items which varied among the situations included the number of observations used in each regression, the number of covariates, the degree of dependence among the covariates, the combinations of continuous and discrete variables, and the generation of the values of the dependent variable for model fit or lack of fit.^ The study found that the $\rm\ C$g* statistic was adequate in tests of significance for most situations. However, when testing data which deviate from a logistic model, the statistic has low power to detect such deviation. Although grouping of the estimated probabilities into quantiles from 8 to 30 was studied, the deciles of risk approach was generally sufficient. Subdividing the estimated probabilities into more than 10 quantiles when there are many covariates in the model is not necessary, despite theoretical reasons which suggest otherwise. Because it does not follow a X$\sp2$ distribution, the statistic is not recommended for use in models containing only categorical variables with a limited number of covariate patterns.^ The statistic performed adequately when there were at least 10 observations per quantile. Large numbers of observations per quantile did not lead to incorrect conclusions that the model did not fit the data when it actually did. However, the statistic failed to detect lack of fit when it existed and should be supplemented with further tests for the influence of individual observations. Careful examination of the parameter estimates is also essential since the statistic did not perform as desired when there was moderate to severe collinearity among covariates.^ Two methods studied for handling tied values of the estimated probabilities made only a slight difference in conclusions about model fit. Neither method split observations with identical probabilities into different quantiles. Approaches which create equal size groups by separating ties should be avoided. ^

A simulation study of the effects of small center enrollment in multi -center clinical trials

Multi-center clinical trials are very common in the development of new drugs and devices. One concern in such trials, is the effect of individual investigational sites enrolling small numbers of patients on the overall result. Can the presence of small centers cause an ineffective treatment to appear effective when treatment-by-center interaction is not statistically significant?^ In this research, simulations are used to study the effect that centers enrolling few patients may have on the analysis of clinical trial data. A multi-center clinical trial with 20 sites is simulated to investigate the effect of a new treatment in comparison to a placebo treatment. Twelve of these 20 investigational sites are considered small, each enrolling less than four patients per treatment group. Three clinical trials are simulated with sample sizes of 100, 170 and 300. The simulated data is generated with various characteristics, one in which treatment should be considered effective and another where treatment is not effective. Qualitative interactions are also produced within the small sites to further investigate the effect of small centers under various conditions.^ Standard analysis of variance methods and the "sometimes-pool" testing procedure are applied to the simulated data. One model investigates treatment and center effect and treatment-by-center interaction. Another model investigates treatment effect alone. These analyses are used to determine the power to detect treatment-by-center interactions, and the probability of type I error.^ We find it is difficult to detect treatment-by-center interactions when only a few investigational sites enrolling a limited number of patients participate in the interaction. However, we find no increased risk of type I error in these situations. In a pooled analysis, when the treatment is not effective, the probability of finding a significant treatment effect in the absence of significant treatment-by-center interaction is well within standard limits of type I error. ^