IUPUI Campus Bulletin 2014-2016

This course provides an overview and foundation in the science and management of air quality, with a focus on health impacts and strategies to reduce these impacts. Course topics include the scientific technical aspects of air pollution through the study of the characteristics of the atmosphere and atmospheric pollutants, effects of meteorology on air pollution, urban air pollution, visibility, smog, acid deposition, stratospheric ozone depletion, global warming and indoor air pollution.

This course examines the extent and significance of toxic agents in the environment.  It covers risk assessment of potential adverse health effect resulting from human exposure to toxic environmental agents. It also provides a background for understanding mechanistic and biologic specific processes of environmental agents.

This course provides students with a focus on the policy-making process and the many variables that comprise the dynamic framework for environmental policy formulation.  The course explores the roles of politics, economics, science, health, values and ethics in setting policy through a consideration of key historical and contemporary issues.

This course provides students with a technical foundation in areas of solid and hazardous waste management that can be applied to the examination of policy options. Topics include characterization of the waste stream, regulations, health and environmental risks, liability issues, management techniques, and treatment and disposal options.

This course provides students with the knowledge and skills to establish or improve an environmental management system that is compatible with ISO (International Organization for Standardization) 14001, an international, voluntary standard that is emerging as a best-management practice for environment.

This course will examine the various hazards that cause food borne illness as well as the risk factors that are known to contribute to these diseases. Topics include etiological agents for common and emerging food borne diseases; basic concepts of food science and technology; food safety principles and practices that are recommended by the Food and Drug Administration's Food Code.  

This course provides a survey of technical and regulatory aspects of protecting the health and safety of workers. Topics include basic toxicology; skin, eye, and respiratory hazards; measuring hazardous atmospheres; ventilation systems; fire and explosion hazards; emergency response; occupational hearing loss; radiation; prevention of accidents; cumulative trauma; and personal protective equipment.

Using ArcGIS Desktop software, this course aims to familiarize students with applications of Geographic Information Systems (GIS) in the context of public health. Public Health cases will be used to explain and teach principles, methods, and techniques. Topics include creating layer packages in ArcMap, health data visualization, map design, health data downloading, geocoding tabular data, and spatial analysis and spatial joins. Downloading, processing and visualization of satellite data on environmental parameters that are traditionally determinants of public health will be covered at the end of the course. The course will provide practical experience to students through exercises and a final project.

This course is designed to expose the student to published material on a specific topic or technique in the field of Public Health.  The material to be studied will be determined primarily by the student under the direction of a faculty member with input from the student’s concentration advisor.  The student is expected to work closely with the faculty member to develop a strategy to identify the material to study, plan a time frame for completion of the study and to determine the nature of the study product.  Generally the product will be a summary and interpretation of the material studied in a literature review format.  The student and faculty member will complete a written agreement, which outlines the scope of work for the semester.  This agreement will also be signed by the concentration advisor.

Chemistry for Environmental Health Professionals provides a review of chemistry fundamentals and application of fundamentals to environmental health issues. Our focus is on the organic and inorganic chemistry of topics including hazardous materials and wastes; industrial processes, toxicology, and sustainability; water and water pollution and treatment; the atmosphere and air pollution; soil; and other related topics.

This class will give students a solid introduction to toxicology and the ways in which environmental exposures can contribute to human disease.  The course will also introduce the regulatory settings in which environmental toxicology is key.

Environmental Risk Assessment is the basis for making decisions related to ecology and human health. This course will examine the basic principles and methods of conducting ecological and human health risk assessments and how risk is managed and communicated to the public. Applications emphasizing real cases will be used to illustrate the interdisciplinary process and products of risk assessment, as well as the regulatory use of the information.

This course has a variable title and can be offered for variable credits. Similar to topics courses offered in other IUPUI programs, this course offers an introduction to a variety of public health topics and current issues will be covered in this course.

Water quality and management of water and wastewater are critical issues for the sustenance of every society and public health. A rational approach to deal with these issues requires understanding of basic principles about water and the surrounding ecosystem that both provides this resource and receives the waste from its use and misuse. This course is designed to teach public health students the fundamentals of water quality and treatment of water, wastewater and solid waste along with associated aspects of the water cycle, ecosystems, water resources and regulations. Although this is mostly a descriptive course with no lab component, few sessions will take place in a lab to reinforce some key concepts with lab experiments. 

P: A703  PBHL- A700 Environmental Health Continuous Enrollment in a one-credit course designed for MPH students who previously registered for A703 Environmental Health Concentration Project and are working on their Final Concentration Project until project grade has been assigned

Provides students the opportunity to synthesize and integrate knowledge acquired through coursework and the public health internship. Student projects will include components of environmental science analysis, research, and application

Statistical data analysis and study design is an art in practice. When and how to apply different statistical models and the interpretation of data analysis results is heavily driven by experience. This course is designed to develop students’ skills in study design, data analyses, and oral and written communication through multiple real-life projects.  The projects will cover designs and data analyses of observational studies and experimental studies. Practical issues in study design and data analysis include but are not limited to sample size and power estimation, interpretation of p-values, phase I to IV trial designs, case-control, case-cohort, retrospective/prospective study designs; ANOVA, ANCOVA, survival analysis, main effect/interaction, multiple comparisons, diagnostic tests, statistical modeling, and data analysis reporting, including both written and oral presentations.

The most important feature of the course is the intended training in the practice of biostatistics in collaborative environments. The course is part of the Biostatistics PhD curriculum. 

Course material will be covered by lectures and interactive exercises that include the instructors role playing as statistically naïve investigators. Knowledge gained will be reinforced by short homework assignments and projects that require presentations.

This is a standard course that prepares Biostatisticians for support of clinical trial projects. The course will cover fundamental aspects of the appropriate design and conduct of medical experiments involving human subjects (clinical research/trials) including ethics, design, sample size calculation, randomization, monitoring, data collection, analysis and reporting of the results.

B530 is a graduate level course designed for students in biostatistics, statistics, bioinformatics, and other related areas. The course covers a broad range of statistical methods used in many areas of bioinformatics research, including sequence alignment, genome sequencing and gene finding, gene expression microarray analysis, transcriptional regulation and sequence motif finding, comparative genomics, and proteomics. This course is designed to train student's skills in data analyses and communications through real life bioinformatics projects. The courses primary audiences include are graduate students in biostatistics, bioinformatics, and researchers from pharmaceutical industry.

P: STAT512 & STAT525   This course covers modern methods for the analysis of repeated measures, correlated outcomes and longitudinal data, including the unbalanced and incomplete data frequently encountered in biomedical research. Topics include an introduction to the analysis of correlated data, repeated measures analysis of variance (ANOVA), random-effects and growth-curve models, generalized linear models for correlated data, including generalized estimating equations (GEE), and generalized linear mixed models (GLMMs).

Class presentations and homework assignments will focus on data analysis in SAS using PROC GLM, PROC MIXED, PROC GENMOD, and PROC NLMIXED. Also, an introduction to fitting linear mixed models in R using fucntions lme() and gls() from the library(nlme) will be given.

P: One semester of undergraduate mathematics    This course introduces the basic principles and methods of data analysis in public health biostatistics.  Emphasis is placed on public health examples as they relate to concepts such as sampling, study design, descriptive statistics, probability, statistical distributions, estimation, hypothesis testing, chi-square tests, t-tests, analysis of variance, linear regression and correlation.  An introduction to SAS statistical software is now a part of this course.

Prerequisites: Students are assumed to have completed an undergraduate level statistics course and are familiar with the basic concepts of statistical inference. Students who are uncertain about their levels of preparation are encouraged to contact the instructors

Nonlinear mixed models are heavily utilized in drug development. Population pharmacokinetics/pharmacodynamics models are the most important applications. Because this topic has a heavy interdisciplinary flavor, it requires a mixed content that has pharmacology background, statistical theory, and computational implementations. The course’s primary audiences include graduate students in biostatistics, pharmacology, bioinformatics and researchers from pharmaceutical industry.

The most important feature of the course is the intended balance among pharmacology background, statistical theory and software implementation. At the end of this course, we expect that the students can understand the pharmacokinetic models, fit the nonlinear mixed model through the required software package, conduct the diagnosis of model fitting, perform hypothesis tests, and provide interpretation of the data. The course is part of the Biostatistics PhD curriculum.

The goal of this course is to introduce some advanced regres- sion techniques to students in the Biostatistics PhD program. The prerequisite in- cludes calculus, linear algebra, linear models, mixed models and generalized linear models.

This course will cover selected computational techniques useful in advanced statistical applications and statistical research. Topics to be covered include methods for solving linear equations, numerical optimization, numerical integration, Expectation-Maximization (EM) algorithm, Monte Carlo method, Bayesian methods, bootstrap methods and stochastic search algorithms.

Upon completion of the course, students are expected to understand the appropriate statistical computational approaches to discovery in data analysis, of statistical inference, and for development of statistical theory and methods.  Students are expected to implement research and computational ideas using R.

This is a standard course that prepares Biostatisticians for support of clinical trial projects. The course will cover fundamental aspects of the appropriate design and conduct of medical experiments involving human subjects (clinical research/trials) including ethics, design, sample size calculation, randomization, monitoring, data collection, analysis and reporting of the results.

There will be three homework projects assigned with about four weeks allowed for completion of each, plus two tests and a final exam. The relative weights of these in the final grade are given below.

P: Stat 528 & Stat 536  This course will discuss the counting process approach to the analysis of censored failure time data. From this prospective, we will revisit many of the standard statistical methods in survival analysis, including the Nelson-Aalen estimator of the cumulative hazard function, the Kaplan-Meier estimator of the survivor function, the weighted logrank statistics, the Cox proportional hazards regression model, and the accelerated failure time model. Counting process based martingale theory will be introduced to facilitate the derivation. Extension of Cox proportional hazards model will be introduced too.

This is an introductory statistical method course on generalized linear models and longitudinal data analysis for students in various public health disciplines. The course focuses on the basic concepts and implementation of four extensions to classical linear regression models: (1) generalized linear models (including logistic and log-linear regression); (2) mixed effects models; (3) generalized linear mixed models; and (4) population average models based on generalized estimating equations (GEE).  

Prerequisites: Bios S546 and familiarity with concepts and theory of statistical inference. Students who are uncertain about their level of preparation are encouraged to contact the instructor.

This course covers the theory of classical and modern approaches to the analysis of clustered data, repeated measures, and longitudinal data. Topics include random effects and growth curve models, generalized estimating equations, statistical analysis of repeated categorical outcomes, and estimation with missing data. The class also discusses computational issues including EM algorithm, quasi-likelihood methods and Bayesian methods for both traditional and new methodologies. The course is part of the Biostatistics Ph.D. curriculum

This course is designed to expose the student to published material on a specific topic or technique in the field of Public Health.  The material to be studied will be determined primarily by the student under the direction of a faculty member with input from the student’s concentration advisor.  The student is expected to work closely with the faculty member to develop a strategy to identify the material to study, plan a time frame for completion of the study and to determine the nature of the study product.  Generally the product will be a summary and interpretation of the material studied in a literature review format.  The student and faculty member will complete a written agreement, which outlines the scope of work for the semester.  This agreement will also be signed by the concentration advisor.

B651 is an introductory level biostatistics course designed for healthcare professionals. This course will cover the topics on data presentation techniques, describing data with numerical summary measures, probability and probability distributions, sampling distributions, statistical inferences from small and large samples, analysis of categorical data, analysis of variance, correlation and simple linear regression analysis.

B652 is an advanced biostatistics course designed for students with an interest in the health sciences. Students are expected to have completed at least one semester course of basic biostatistics. Knowledge of probability and probability distributions, concepts of estimation and hypothesis testing are assumed. Topics covered in this course include multiple linear regression, analysis of covariance, logistic regression, and survival analyses. Upon completion of the course, students are expected to understand the appropriate statistical models for various outcomes and be able to interpret results using statistical techniques covered in this course. Students are also expected to conduct simple analyses using SPSS on personal computers

P: B551 or B651 or One semester of graduate level Biostatistics

This course introduces the advanced principles and methods of data analysis in public health biostatistics.  Emphasis is placed on public health examples as they relate to concepts such as:  Multiple regression, analysis of variance and covariance, logistic regression, nonparametric statistics, survival analysis, epidemiology statistics, and repeated measures analysis.

This is a first course into two multivariate statistical procedures, the Analysis of Variance (ANOVA) and Regression with special focus in problems related to the Public Health sciences. This is an introductory course that will expose students to these methods, and consolidate their understanding of statistical inference (estimation and testing of statistical hypotheses) in the context of the two procedures. The course will be taught in two sessions, a lecture, where the relevant theory and methods will be presented, and a practicum or laboratory session, involving hands-on analysis of real-life problems using the SAS statistical software package.

This is a course into the application of experimental design to biomedical experiments, such as randomization, blocking, factorial designs and stratification. The course addresses both clinical and pre-clinical investigation as well as design of experiments to evaluate medical devices, which will likely be encountered by biomedical researchers. It is addressed to second-year graduate students in biostatistics or epidemiology with a solid understanding of analysis of variance, regression and working knowledge of survial analysis.The course will be taught in two sessions, a lecture, where the relevant theory and methods will be presented, and a practicum or laboratory session, involving hands-on analysis of real-life problems using the SAS statistical software package.

The statistical methods covered in this course focus on “time to event” data, where the event can be response to treatment, relapse of disease, or death.  Topics covered in this course include estimations of survival function and regression models for survival data. Specifically, this course covers the central functions of survival analysis: the hazard, survival, and cumulative hazard functions, nonparametric estimation of survival functions using life-table method and the Kaplan-Meier method, and comparison of survival distributions using the log-rank and other tests. In addition, we will discuss regression models for survival outcomes with emphasis on the Cox proportional hazards model. Alternative models such as the accelerated failure time model and use of parametric distributions (exponential, Weibull) will also be considered. Class material will include presentation of statistical methods for estimation and testing, along with current software (SAS) for implementing analyses of survival data. Applications to real data will be emphasized.

This course has a variable title and can be offered for variable credits. Similar to topics courses offered in other IUPUI programs, this course offers an introduction to a variety of public health topics and current issues will be covered in this course.

Nonlinear mixed models are heavily utilized in drug development. Population pharmacokinetics/pharmacodynamics models are the most important applications. Because this topic has a heavy interdisciplinary flavor, it requires a mixed content that has pharmacology background, statistical theory, and computational implementations. The course’s primary audiences include graduate students in biostatistics, pharmacology, bioinformatics and researchers from pharmaceutical industry.

The most important feature of the course is the intended balance among pharmacology background, statistical theory and software implementation. At the end of this course, we expect that the students can understand the pharmacokinetic models, fit the nonlinear mixed model through the required software package, conduct the diagnosis of model fitting, perform hypothesis tests, and provide interpretation of the data. The course is part of the Biostatistics PhD curriculum.

This course is designed to provide solid training in statistical theory used in genetic analyses.

Directed study and reports for students who wish to undertake individual reading and study on approved topics.

This course examines fundamental aspects of analyzing data generated by observational epidemiology studies.  The focus is on developing a solid understanding of contemporary analytical techniques to increase the validity of the study and control for possible confounding factors and biases. 

Students will learn each component of a successful proposal for research or community projects by a Federal or private agency.  Current funding opportunities from these agencies will be used as templates for preparation and review of proposals.  Skills needed to review proposals also will be taught.

This course will introduce the application of Informatics in the Public Health field. The course will include a brief review of core public health functions, describe the current policies defining the use of informatics in public health, and outline the history of the application of informatics principles in both public health and clinical health systems.

This course is designed to expose the student to published material on a specific topic or technique in the field of Public Health.  The material to be studied will be determined primarily by the student under the direction of a faculty member with input from the student’s concentration advisor.  The student is expected to work closely with the faculty member to develop a strategy to identify the material to study, plan a time frame for completion of the study and to determine the nature of the study product.  Generally the product will be a summary and interpretation of the material studied in a literature review format.  The student and faculty member will complete a written agreement, which outlines the scope of work for the semester.  This agreement will also be signed by the concentration advisor.

This course will focus on the recognized value of Public Health Surveillance as well as the development and utility of Surveillance Systems.  Included are the historical development of surveillance systems, data sources, informatics of surveillance, data management, and evaluation of surveillance systems.  In addition, descriptive epidemiology techniques, identification of outbreaks and community needs.  Trend analysis based on the data collected from the surveillance system will be covered, along with related ethical and legal issues.  The course discusses how surveillance is conducted in low to middle income countries and the future of public health surveillance. 

This course has a variable title and can be offered for variable credits. Similar to topics courses offered in other IUPUI programs, this course offers an introduction to a variety of public health topics and current issues will be covered in this course.

This course provides an intensive focus on the formative phases of health survey research. Topics covered will include sampling methodologies, questionnaire development, testing, revision and administration, interviewing, coding procedures, as well as topical discussions related to research ethics and real world challenges of research. Active learning will be emphasized through several field based exercises, as well as a research proposal based on students’ own research interests.

This course examines fundamental aspects of designing and implementing observational epidemiology studies.  The focus is on developing strategies to increase the validity of the study results by using techniques to control for possible confounding factors and biases.  Topics include sampling methods, sensitivity, data weighting, standardization, selection of cases and controls, matching, data collection and project management.

P: E517  This course presents fundamental concepts and methods in molecular and genetic epidemiology, and explains different study designs commonly used in genetic epidemiology to identify the genetic basis of common, complex disease. Students will learn about available common molecular and genetic measures, various elements of study design, including definition of study population, phenotype definition, and choice of analytic methods. We will briefly discuss linkage analysis and then focus on association tests. Additional topics will be discussed including interactions with environmental factors, ethnical issues and genetic testing.

This course introduces the conceptual and practical tools needed for population-based genetic association studies among unrelated subjects. Lectures and selected readings present key issues (such as linkage disequilibrium, "tagging SNPs," haplotypes, population stratification and epistasis) and appropriate statistical methods. Students will be required to present selected papers in class. Students will gain hands-on experience with a range of analytic tools and software packages as part of a class project which gives them the opportunity to design and analyze an association study. This project will require students to work on real-world problems such as marker selection, potential multiple comparisons issues due to multiple markers and multiple outcomes, and missing data.

Courses offered under this course number would include PhD courses on topics expected to be offered only once, such as those taught by visiting faculty, and those that are newly developed and have not yet been assigned a specific course number. The course will focus on a specific topic or technique related to the field of Public Health.  The material to be studied will be determined by the instructor with input from the PhD faculty. 

This course is designed to expose a PhD student to published material on a specific topic or technique related to their field of study in Epidemiology.  The material to be studied will be determined primarily by the PhD student under the direction of a faculty member with input from the student’s concentration advisor.  The PhD student is expected to work closely with the faculty member to develop a strategy to identify the material to study, plan a time frame for completion of the study and to determine the nature of the study product.  Generally the product will be a summary and interpretation of the material studied in a literature review format.  The PhD student and faculty member will complete a written agreement, which outlines the scope of work for the semester.  The concentration advisor will also sign this agreement

This course is designed to allow PhD students the opportunity to explore research questions by collecting data or using existing data related to their field of study in Epidemiology.  The study topic will be determined primarily by the PhD student under the direction of a faculty member with input from the student’s concentration advisor.  The PhD student is expected to work closely with the faculty member to develop the study protocol, obtain IRB approval if necessary, obtain the data and collect the planned data analysis.  The time frame for completion and the nature of the study product will be determined by the PhD student, faculty member and advisor.  Generally the product will be a manuscript for submission to an appropriate journal. The PhD student and faculty member will complete a written agreement, which outlines the scope of work for the semester.  The concentration advisor will also sign this agreement.

This course provides students with an overview of fundamental concepts and methods of nutritional epidemiology and the current state of knowledge on well-studied associations between diet and chronic diseases. Emphasis will be placed on the design, implementation, analysis, and interpretation of nutritional epidemiologic studies

This course is designed to expose PhD students to a wide range of specific research topics and issues in Public Health.  The seminar topics will be chosen by the Director of the PhD program with input from other faculty members.  The PhD students are expected to attend each seminar session, read assigned material, and participate in the seminar discussions. The PhD students may be asked to present their research projects during the seminar to obtain feedback and recommendations from the faculty and other students.

This is a graduate level introductory pharmacoepidemiology course. Students will learn how principles of modern epidemiologic methods are used to evaluate the safety, effectiveness, and utilization patterns of medical products (drugs, vaccines, and medical devices) in human populations, with a focus on observational studies. Related topics, including therapeutic risk management, data sources and ethical principles will be discussed. Advanced methodology, such as that utilized to address confounding by indication and misclassification will be introduced.

An advanced graduate course that discusses the topics related to the epidemiology and prevention of cardiovascular diseases. The purpose is to give students an overview of the major cardiovascular diseases and their risk factors. To develop critical thinking skills related to the key issues that epidemiologists consider.

The dissertation will be written on an original topic of epidemiology research and presented as one of the final requirements for the PhD degree. The dissertation must be an original contribution to knowledge and of high scholarly merit. The candidate’s research must reveal critical ability and powers of imagination and synthesis. The dissertation is written under the supervision of the Dissertation Committee Chair with input from the other members of the Dissertation Committee. The data used by the student may involve analysis of primary or secondary data.

This course provides the knowledge and skills needed to understand the application of personnel and labor relations techniques to the health services sectors, with particular emphasis on human resources management, employees' benefit programs, and labor relations as applied to the health services delivery organization.

This web-based course is evidence-based and focused on health outcomes research in contemporary health care. The different types of health outcomes assessment tools and their application in determining patient health status, changes in health status, and the effectiveness of health care interventions will be addressed. The course will focus on generic and specific health related outcomes assessment tools, looking at such issues as disease specific outcomes and patient satisfaction.

This course explores management roles in health care. Application of strategic management theories, concepts and principles and an understanding of managerial roles in organizations are emphasized. Managerial process, management theories, leadership, organizational design, and strategic management are examined. 

The goal of this course is to introduce students to the theoretical and practical aspects of health impact assessment (HIA) as a methodological tool in public health.  HIA utilizes a variety of qualitative and quantitative methods and tools, designed to assess the potential health effects of a public policy, program, project, or initiative.  While HIA is still an emerging practice in the United States, in Europe, Canada, and other areas of the world, the assessment of the public health impact of public decisions have been performed regularly to support policy decisions and promote conditions required for optimal health.

During the first part of the semester, students will learn the necessary steps to conduct an HIA, review national and international case studies, and discuss how findings may or may not impact policy making.  During the second half of the course, students will work in teams with a local or state health department to examine the potential health impact of policy proposals in Indiana.

This course is designed to expose the student to published material on a specific topic or technique in the field of Public Health.  The material to be studied will be determined primarily by the student under the direction of a faculty member with input from the student’s concentration advisor.  The student is expected to work closely with the faculty member to develop a strategy to identify the material to study, plan a time frame for completion of the study and to determine the nature of the study product.  Generally the product will be a summary and interpretation of the material studied in a literature review format.  The student and faculty member will complete a written agreement, which outlines the scope of work for the semester.  This agreement will also be signed by the concentration advisor.

Cost-effectiveness analysis is widely used in evaluating the performance of public health programs and policies.  In this course, students will learn to frame the conceptual model, to collect and synthesize data regarding "cost" and "effectiveness", to perform a cost-effectiveness analysis, and to form recommendations based on the analysis.  Meta-analysis and various survey/interview techniques will be introduced as essential tools for data collection in cost-effectiveness analyses.  Learning will be facilitated by numerous examples of the application of this popular method. Health Policy and Management students have option of taking this course in place of H509.

The broad topic for this course is health program evaluation. Topics we will cover during the semester include: evaluation standards and ethics; program theory; evaluation design; problems that arise in evaluation and how to address them; working with and communicating to stakeholders. A theme that will be addressed throughout the class is the intersection of program evaluation and politics, and we will be focusing specifically on the intersection between program evaluation and public policy at the end of the semester. We will also take some time at the end of the semester to discuss implementation science, a topic that is closely related to program evaluation. More often than not, evaluation is a complex process where researchers cannot implement strict controls in their designs. Therefore, my primary goal for this class is that you will gain an understanding of the issues affecting program evaluation in real-world contexts and how to address limitations that are imposed by factors that cannot be controlled for (e.g., resources, time, politics, ethical issues, logistics).

This 3 hour course is designed to expand students’ perspectives on global health care through the in-depth study of health care and health systems that are distinct from the U.S. health care system.  Students also will learn how health policy and management research apply the comparative method in the study of health systems and health policy.  Finally, students will explore health policy as a global challenge through a systematic discussion of international health policymaking and responses to health problems requiring global or regional nation-level cooperation.

PBHL- H700 Health Policy and Management Continuous Enrollment in a one-credit course designed for MPH students who previously registered for H705 Health Policy and Management Concentration Project and are working on their Final Concentration Project until project grade has been assigned.

This course introduces the range of methods and associated political and ethical issues related to comparative effectiveness research in health and medicine, with a particular focus on developing quantitative skills to the design, review and analysis of clinical trials (e.g. drugs, devices, clinical or behavioral strategies). Students will learn quantitative methodologies that can be utilized to synthesize a range of evidence regarding the benefits and harms of available choices for care, and will explore the potential and limitations of comparative effectiveness findings for policy and health care decision making.

This course is designed to expose a PhD student to published material on a specific topic or technique related to their field of study in Health Policy and Management.  The material to be studied will be determined primarily by the PhD student under the direction of a faculty member with input from the student’s concentration advisor.  The PhD student is expected to work closely with the faculty member to develop a strategy to identify the material to study, plan a time frame for completion of the study and to determine the nature of the study product.  Generally the product will be a summary and interpretation of the material studied in a literature review format.  The PhD student and faculty member will complete a written agreement, which outlines the scope of work for the semester.  The concentration advisor will also sign this agreement.

This course is designed to allow PhD students the opportunity to explore research questions by collecting data or using existing data related to their field of study in Health Policy and Management.  The study topic will be determined primarily by the PhD student under the direction of a faculty member with input from the student’s concentration advisor.  The PhD student is expected to work closely with the faculty member to develop the study protocol, obtain IRB approval if necessary, obtain the data and collect the planned data analysis.  The time frame for completion and the nature of the study product will be determined by the PhD student, faculty member and advisor.  Generally the product will be a manuscript for submission to an appropriate journal. The PhD student and faculty member will complete a written agreement, which outlines the scope of work for the semester.  The concentration advisor will also sign this agreement.

This course is designed to expose PhD students to a wide range of specific research topics and issues in Public Health.  The seminar topics will be chosen by the Director of the PhD program with input from other faculty members.  The PhD students are expected to attend each seminar session, read assigned material, and participate in the seminar discussions. The PhD students may be asked to present their research projects during the seminar to obtain feedback and recommendations from the faculty and other students.

This course is designed to expose a PhD student to published material on a specific topic or technique related to their field of study in Health Policy and Management.  The material to be studied will be determined primarily by the PhD student under the direction of a faculty member with input from the student’s concentration advisor.  The PhD student is expected to work closely with the faculty member to develop a strategy to identify the material to study, plan a time frame for completion of the study and to determine the nature of the study product.  Generally the product will be a summary and interpretation of the material studied in a literature review format.  The PhD student and faculty member will complete a written agreement, which outlines the scope of work for the semester.  The concentration advisor will also sign this agreement.

This course is designed to expose the student to different readings in public health.  The course will allow the student to apply skills learned in the public health core courses by collecting data and applying techniques.  The student will be required to read critically published papers and identify research topics.

This course has a variable title and can be offered for variable credits. Similar to topics courses offered in other IUPUI programs, this course offers an introduction to a variety of public health topics and current issues will be covered in this course.

This course examines fundamental research methods used in the field of public health.  The focus is on understanding how community and clinical data are collected in scientifically valid methods and how study results are fairly interpreted.  Students will learn how to critique published research to identify the strengths and limitations of the designs and approaches used, along with possible confounding factors and biases.  Topics include components of research studies, including: justification for a research project, development of research questions, research designs (qualitative, quantitative), selection of participants, sampling methods, project management, and data for analysis. Methods used to complete and interpret community-based needs assessments and program evaluation will be included.

This course will provide students with a systematic approach to program planning and evaluation of health programs.  Students will apply program planning, implementation and evaluation theory to develop an evidence-based health promotion program that addresses a public health issue of personal interest.

This course provides learning opportunities for public health graduate students to develop an understanding of culture and of how qualitative methods can be used to develop a sensitivity to and an understanding of cultural practices. Such cultural sensitivities and competencies are basic to effective program planning, implementation, service delivery, and program evaluation. This class will provide important knowledge and opportunities related to public health practice in a community setting comprised of a multicultural population with differing health beliefs, values, behaviors and health care needs. By the end of the semester, the student will be able to define and distinguish the concepts of culture and traditions, acculturation and enculturation, traditionalism and modernism and will be able to begin to identify how to build on cultural practices to develop interventions aimed at influencing health behaviors. Further, the student will have active experience in conducting qualitative research in a community setting, including skills in conducting windshield surveys, participant observations, key informant interviews, and focus groups.

This course will examine stress holistically, i.e. from a biological/physiological, psychological and sociological perspective.  You will learn how stress is manifested psychologically as well as in the systems of the body.  You will also examine stress from a community/population perspective. Finally, the effects of stress on the body will be examined through examples from its role as a cause of and contributor to major illnesses.

This course is designed to teach students how to coach individuals and groups attempting to improve their health behaviors. Theory, evidence-based practices, and different types of communication and interviewing styles will be explored through hands-on activities. Students will practice the learned techniques throughout the semester and will be able to apply these techniques upon completion of the course. Health educators, health educator trainers, health care providers, and others interested in guiding behavior change will benefit from this course.

This course is designed to expose the student to published material on a specific topic or technique in the field of Public Health.  The material to be studied will be determined primarily by the student under the direction of a faculty member with input from the student’s concentration advisor.  The student is expected to work closely with the faculty member to develop a strategy to identify the material to study, plan a time frame for completion of the study and to determine the nature of the study product.  Generally the product will be a summary and interpretation of the material studied in a literature review format.  The student and faculty member will complete a written agreement, which outlines the scope of work for the semester.  This agreement will also be signed by the concentration advisor.

This course has a variable title and can be offered for variable credits. Similar to topics courses offered in other IUPUI programs, this course offers an introduction to a variety of public health topics and current issues will be covered in this course.

This international service-learning course is designed for students who are interested in developing an in-depth understanding of the relationship between health and housing outside of the U.S. This course will provide students with an opportunity to learn and work with individuals, families and communities struggling to overcome poverty to improve well-being in Argentina through a collaborative project with Habitat for Humanity, International. This course combines didactic learning related to the social determinants of health with a short term international service experience with Habitat for Humanity that will not only explore the complex social and geopolitical factors associated with health and housing, but will provide firsthand experience in an international setting. The course will require travel to participate in a 8-10 day service learning experience within an Argentinian community where community development efforts are underway to improve the health and well being of communities impacted by poverty.

PBHL- S700 Social and Behavioral Health Science Continuous Enrollment in a one-credit course designed for MPH students who previously registered for B701 Biostatistics Concentration Project and are working on their Final Concentration Project until project grade has been assign.

This 1.0 credit seminar course will prepare advanced graduate students for the roles and responsibilities they may assume as faculty members.  Course content will include an overview of the higher education culture and faculty expectations for teaching, research and service.