Level – Advanced

Ethical Dilemmas in Community-Based Participatory Research: Recommendations for Institutional Review Boards

VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

Source: Journal of Urban Health

Type: PDF Document

Level: Advanced

Description: This articles assesses the function of IRBs in CBPR in protecting individuals with less emphasis on risk-reduction for communities.



Issue Brief: Collection of Race, Ethnicity, and Primary Language Data: Tools to Improve Quality of Care and Reduce Health Care Disparities (2005)

VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

Source: Health Research & Educational Trust

Type: Online Article

Level: Advanced

Description: This document summarizes the importance of using data to improve quality of care and reduce health care disparities.Author: Health Research & Educational Trust in partnership with AHA.



CBPR: Assessing a Community’s Health Status Using Readily Available Secondary Data (2007)

VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

Source: Center for Community Health Development School of Rural Public Health Texas A&M–HSC

Type: Electronic Power Point Presentation

Level: Advanced

Description: This presentation summarizes the results of analysis of secondary data to provide information on baseline health status of the Brazos Valley Region of Texas. Presenter: Jane Bolin



Finding Solutions to Challenges in CBPR Between Academic and Community Organizations (2006)

VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

Source: Journal of Interprofessional Care

Type: Electronic Paper

Level: Intermediate

Description: This article provides a case study of the challenges of community-academic partnerships and suggested solutions. Authors: Jan Shoultz, Mary Frances Oneha, Lois Magnussen, Mya Moe Hla, Zavi Brees-Saunders, Marissa Dela Cruz, Margaret Douglas.



Biostatistics for Medical Product Regulation

VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

Source: Johns Hopkins Bloomberg School of Public Health

Type: PowerPoint & Lecture Materials

Level: Introductory

Description: Provides a broad understanding of the application of biostatistics in a regulatory context. Reviews the relevant regulations and guidance documents. Includes topics such as basic study design, target population, comparison groups, and endpoints. Addresses analysis issues with emphasis on the regulatory aspects, including issues of missing data and informative censoring. Discusses safety monitoring, interim analysis and early termination of trials with a focus on regulatory implications.



Statistics for Psychosocial Research: Structural Models

VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

Source: Johns Hopkins Bloomberg School of Public Health

Type: PowerPoint / Lecture Materials

Level: Advanced

Description: Quantitative study on principles of path analysis, casual inference, measurement models, and other relevant topics to social sciences.



Decision Modeling Cost-Effectiveness

VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

Source: Tufts Clinical and Translational Science Institute

Type: Online Course

Level: Advanced

Description: “After completing this lecture, you will be able to:
Show how the probability of a diagnosis is affected by a test result, sensitivity, and specificity
Describe how evidence can be integrated using decision trees
Illustrate the concept of threshold probabilities and their implications
Discuss how sensitivity analyses are performed and what they mean
Explain how patient preferences (utilities or values) can be integrated into patient-centered choices using decision analysis
Identify different types of economic analyses in comparative effectiveness research
Explain how to calculate incremental cost-effectiveness
List how cost-effectiveness analysis is being used for technology assessment”



Personalized Medicine, Heterogeneity of Treatment Effect, and Implications for Comparative Effectiveness

VN:F [1.9.22_1171]
Rating: 0.0/5 (0 votes cast)

Source: Tufts Clinical and Translational Science Institute

Type: Online Course

Level: Advanced

Description: “After completing this lecture, you will be able to:
Identify the limitations of applying the overall results of clinical trials to individual patients
Discuss how summary results of individual trials might not even reflect the benefits of typical patients in the trial
Explain how subgroup analyses are prone both to false-positive and false-negative results
Illustrate approaches that might lead to more credible and actionable subgroup results
Express why multidimensional risk models may have advantages over conventional “one-variable-at-a-time” subgroup analysis
Determine some of the limitations of using genetic information as a basis for exploring heterogeneity of treatment effect”