University of Minnesota
Social Determinants of Health: Methodological Opportunities
University of Minnesota

Social Determinants of Health: Methodological Opportunities

This course is part of Social Determinants of Health: Data to Action Specialization

Taught in English

Daniel J. Pesut, Ph.D., RN, FAAN
Karen A. Monsen, PhD, RN, FAMIA, FNAP, FAAN

Instructors: Daniel J. Pesut, Ph.D., RN, FAAN

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Course

Gain insight into a topic and learn the fundamentals

Beginner level
No prior experience required
17 hours (approximately)
Flexible schedule
Learn at your own pace

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Assessments

8 quizzes

Course

Gain insight into a topic and learn the fundamentals

Beginner level
No prior experience required
17 hours (approximately)
Flexible schedule
Learn at your own pace

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This course is part of the Social Determinants of Health: Data to Action Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 5 modules in this course

The purpose of this module is to examine community-based participatory research (CBPR) and evaluate its potential applications in data-to-action initiatives. Lesson one will define CBPR, as we discuss its origin and relation to collective impact. We will also review the goals, purpose, benefits and characteristics of CBPR as we compare it to traditional research methods. In lesson two, we will explore potential measurement strategies for analyzing CBPR outcomes and data-to-action interventions. We will also consider how CBPR success is measured and how data can be used to amplify community voices.

What's included

3 videos4 readings2 quizzes1 discussion prompt5 plugins

This module will introduce the principles of team science and examine how team science can be used to enhance data-to-action initiatives. In lesson one, we will define team science, as we discuss how it is related to collective impact and CBPR. We will also review recommendations made by the National Academies Committee on the Science of Team Science for improving team science effectiveness. Lesson two will focus on the opportunities and challenges for team science in communities, as we further discuss incorporating community perspectives into team science research. We will also evaluate how to measure team science outcomes, as we consider how team science can add perspective and voice to data.

What's included

2 videos4 readings2 quizzes1 discussion prompt3 plugins

This module will focus on the importance of community partnerships in collecting and analyzing community-level data that can be integrated into data-to-action initiatives. Lesson one will define key terms, and introduce the concept of whole-person health. We will also explore how community data can be used to advocate, influence and create policy to support health equity. In lesson two, we will examine the use of simplified plain language in the context of health literacy, as we discuss how to assess the usability of community-validated plain language terms. Lesson three will introduce the MyStrengths+MyHealth assessment, as we review the implications of collecting community-based social determinant of health data. Finally in lesson four, we will evaluate a community-level data exemplar, as we consider how to translate whole person health and community-level data into community-driven health initiatives.

What's included

5 videos8 readings2 quizzes1 discussion prompt

In this module, we will examine informatics as a potential methodology and resource to inform data-to-action initiatives. Lesson one will define key concepts including informatics, knowledge complexity, and knowledge management. Building on these concepts, we will investigate the levels of knowledge management proposed by Verna Allee. We will also consider the different perspectives on the proposed creation of a new social informatics specialty. Building on our understanding of knowledge management, in lesson two, we will explore knowledge representation structures. We will also analyze the use of publicly available population health records as contextual information to manage knowledge and data for action to reduce health disparities. In addition, we will evaluate knowledge representation structures of evidence-based social determinants of health interventions. Finally, we will explore some informatics applications including the Population Health Record and the WHO Health Equity Assessment Toolkit (HEAT).

What's included

2 videos4 readings2 quizzes1 discussion prompt3 plugins

This module will focus on analyzing, displaying and interpreting social determinants of health data, with a particular focus on comparing health outcomes by groups. Lesson one will provide an overview of ANOVA analysis and line graph visualization. In lesson two, we will learn how to conduct ANOVA analyses and create line graphs in R. Using the NHANES dataset, we will compare the mean Hgb a1c by education level. Using the Omaha System dataset, we will compare the mean change in status by number of problems. Finally, we will discuss how to interpret the results of our analysis as we visualize our findings using line graphs.

What's included

2 videos4 readings1 peer review1 discussion prompt1 ungraded lab3 plugins

Instructors

Daniel J. Pesut, Ph.D., RN, FAAN
University of Minnesota
7 Courses6,138 learners
Karen A. Monsen, PhD, RN, FAMIA, FNAP, FAAN
University of Minnesota
9 Courses45,023 learners

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