Modified Team-based Learning (TBL) as a tool in Problem-based learning (PBL); Observations and Lessons from Year One

Both TBL and PBL attempt to maximally engage the learner and both are designed to encourage interactive teaching / learning. PBL is student centered. TBL, in contrast, is typically instructor centered. The PBL Executive Committee of the UTHSC-Houston Medical School, in an attempt to capture the pedagogical advantages of PBL and of TBL, implemented a unique PBL experience into the ICE/PBL course during the final block of PBL instruction in year 2. PBL cases provided the content knowledge for focused learning. The subsequent, related TBL exercises fostered integration / critical thinking about each of these cases. [See PDF for complete abstract]

Nonlinear tests for genetic studies of complex disease

Linkage and association studies are major analytical tools to search for susceptibility genes for complex diseases. With the availability of large collection of single nucleotide polymorphisms (SNPs) and the rapid progresses for high throughput genotyping technologies, together with the ambitious goals of the International HapMap Project, genetic markers covering the whole genome will be available for genome-wide linkage and association studies. In order not to inflate the type I error rate in performing genome-wide linkage and association studies, multiple adjustment for the significant level for each independent linkage and/or association test is required, and this has led to the suggestion of genome-wide significant cut-off as low as 5 × 10 −7. Almost no linkage and/or association study can meet such a stringent threshold by the standard statistical methods. Developing new statistics with high power is urgently needed to tackle this problem. This dissertation proposes and explores a class of novel test statistics that can be used in both population-based and family-based genetic data by employing a completely new strategy, which uses nonlinear transformation of the sample means to construct test statistics for linkage and association studies. Extensive simulation studies are used to illustrate the properties of the nonlinear test statistics. Power calculations are performed using both analytical and empirical methods. Finally, real data sets are analyzed with the nonlinear test statistics. Results show that the nonlinear test statistics have correct type I error rates, and most of the studied nonlinear test statistics have higher power than the standard chi-square test. This dissertation introduces a new idea to design novel test statistics with high power and might open new ways to mapping susceptibility genes for complex diseases. ^

Encouraging adolescents toward mental health careers via website biographies.

This project designed, developed, implemented and is currently evaluating the effectiveness of an interactive, multi-media website designed to encourage adolescents to consider careers in mental health. This Web-based learning environment features biographies of mental health scientists. Evaluation is conducted in a systematic, structured way using cognitive achievement, usability (ease of use), and affective scales (e.g., fun to use) as outcome measures

Development of a standard sign-out procedure for clinicians in a pediatric intensive care unit

Background: Poor communication among health care providers is cited as the most common cause of sentinel events involving patients. Sign-out of patient data at the change of clinician shifts is a component of communication that is especially vulnerable to errors. Sign-outs are particularly extensive and complex in intensive care units (ICUs). There is a paucity of validated tools to assess ICU sign-outs. ^ Objective: To design a valid and reliable survey tool to assess the perceptions of Pediatric ICU (PICU) clinicians about sign-out. ^ Design: Cross-sectional, web-based survey ^ Setting: Academic hospital, 31-bed PICU ^ Subjects: Attending faculty, fellows, nurse practitioners and physician assistants. ^ Interventions: A survey was designed with input from a focus group and administered to PICU clinicians. Test-retest reliability, internal consistency and validity of the survey tool were assessed. ^ Measurements and Main Results: Forty-eight PICU clinicians agreed to participate. We had 42(88%) and 40(83%) responses in the test and retest phases. The mean scores for the ten survey items ranged from 2.79 to 3.67 on a five point Likert scale with no significant test-retest difference and a Pearson correlation between pre and post answers of 0.65. The survey item scores showed internal consistency with a Cronbach's Alpha of 0.85. Exploratory factor analysis revealed three constructs: efficacy of sign-out process, recipient satisfaction and content applicability. Seventy eight % clinicians affirmed the need for improvement of the sign-out process and 83% confirmed the need for face- to-face verbal sign-out. A system-based sign-out format was favored by fellows and advanced level practitioners while attendings preferred a problem-based format (p=0.003). ^ Conclusions: We developed a valid and reliable survey to assess clinician perceptions about the ICU sign-out process. These results can be used to design a verbal template to improve and standardize the sign-out process.^

A hybrid method in combining treatment effects from matched and unmatched studies

In the biomedical studies, the general data structures have been the matched (paired) and unmatched designs. Recently, many researchers are interested in Meta-Analysis to obtain a better understanding from several clinical data of a medical treatment. The hybrid design, which is combined two data structures, may create the fundamental question for statistical methods and the challenges for statistical inferences. The applied methods are depending on the underlying distribution. If the outcomes are normally distributed, we would use the classic paired and two independent sample T-tests on the matched and unmatched cases. If not, we can apply Wilcoxon signed rank and rank sum test on each case. ^ To assess an overall treatment effect on a hybrid design, we can apply the inverse variance weight method used in Meta-Analysis. On the nonparametric case, we can use a test statistic which is combined on two Wilcoxon test statistics. However, these two test statistics are not in same scale. We propose the Hybrid Test Statistic based on the Hodges-Lehmann estimates of the treatment effects, which are medians in the same scale.^ To compare the proposed method, we use the classic meta-analysis T-test statistic on the combined the estimates of the treatment effects from two T-test statistics. Theoretically, the efficiency of two unbiased estimators of a parameter is the ratio of their variances. With the concept of Asymptotic Relative Efficiency (ARE) developed by Pitman, we show ARE of the hybrid test statistic relative to classic meta-analysis T-test statistic using the Hodges-Lemann estimators associated with two test statistics.^ From several simulation studies, we calculate the empirical type I error rate and power of the test statistics. The proposed statistic would provide effective tool to evaluate and understand the treatment effect in various public health studies as well as clinical trials.^