SDH Research Methods Course

"Soulcatcher" by Martin Oliver

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Journal Critique Logistics and Guidelines

Homework Assignment 1

Homework Assignment 2

Homework Assignment 3

Homework Assignment 3 Example

Homework Assignment 4

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Social Determinants of Health Home Page

Epidemiology

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Biostatistics

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Electronic Reserves

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EPI 548/HSERV 548

Winter Quarter 2009

Social Determinants of Health:

Research Methods

Course Home Page - Course Outline

INSTRUCTORS

Nicholas L. Smith, PhD Shirley A. A. Beresford, PhD

Associate Professor Professor

Department of Epidemiology Department of Epidemiology

University of Washington University of Washington

nlsmith@u.washington.edu beresfrd@u.washington.edu

Office hours by appointment Office hours by appointment

COURSE SCHEDULE:

· Tuesdays 10:30 – 11:50 am Room SCC 308

· Thursdays 10:30 – 11:50 am Room SCC 308

COURSE WEBSITE:

http://courses.washington.edu/epi548/

COURSE DESCRIPTION:

This 3-unit course will explore study-design, measurement, and analytic issues applicable to research into the social determinants of health (SDH). This graduate-level lecture/seminar course is offered to students with a basic knowledge of epidemiologic and biostatistical principles. The course consists of 15 lectures/seminars and 5 journal-article critique sessions.

COURSE LEARNING OBJECTIVES:

At the end of the course, the student will be able to:

1. List at least 4 approaches to assessing causality and explain their strengths and weaknesses when applied to the SDH

2. Develop a conceptual model to accurately and parsimoniously reflects the core factors related to a social factors influence on health and that presents a testable pathway for a hypothesis

3. Distinguish between SDH research questions with 2 or more units of analysis (multi-level) and those with a single unit of analysis and compare and contrast the interpretation of the results

4. Identify the key features of traditional and non-traditional epidemiologic study designs to test hypotheses related to the SDH

5. Compare and contrast individual and group level measures of the same SDH construct, and describe the relationship between them

6. List, describe, and compare the common indicators of socioeconomic status

7. Describe the strengths and the inherit limitations of ecologic data and its analysis and list methods to decrease the likelihood of biased results

8. Apply the concept of multi-level analyses to space-dependent and time-dependent SDH data structures and describe their appropriate statistical models

9. Demonstrate competence interpreting statistical output for ecologic, multi-level, and longitudinal analytic approaches

10. Describe the application of network and structural equation models to SDH research

11. Critically review the published literature addressing the SDH and provide a methods-based critique of the scientific approach

12. Convey in writing the basic concepts and understandings of SDH research methods through 3-page critique of a journal article

PREREQUISITES:

Prerequisites include either EPI 511 or the 512/513 series and either the BIOST 511/512 series or the 517/518 series or instructors permission for those student who already have an epidemiology and biostatistics background.

COURSE MATERIALS:

Most of the readings are posted on the UW Health Sciences Library E-Reserves and can be found by searching “EPI548” or “HSERV548” under Course Number at the following site (UW NetId required) at:

https://eres.lib.washington.edu/

Class notes will be posted by 9:00 am on the day of the presentation. Notes and homework assignments can be found on the EPI/HSERV 548 course website at:

http://courses.washington.edu/epi548/

Username: student

Password: [See instructor]

Some of the additional readings come from 5 books, which have been placed on 2-hour holds in the Health Sciences Library for winter quarter. These books include the following:

Biostatistics: a Methodology for the Health Sciences. 2004 Gerald van Belle et al.

Neighborhoods and Health. 2003. Edited by Ichiro Kawachi, Lisa F. Berkman

Social Epidemiology. 2000. Edited by Lisa F. Berkman, Ichiro Kawachi

Methods in Social Epidemiology. 2006. Edited by J. Michael Oakes

Causal Inference. 1988. Edited by Kenneth Rothman.

GUEST LECTURERS:

Sebastien J. Haneuse, PhD

Group Health Center for Health Studies (haneuse.s@ghc.org)

Affiliate Assistant Professor, Department of Biostatistics

Brian G. Leroux, PhD

Associate Professor, Departments of Biostatistics and Dental Public Health Sciences (leroux@u.washington.edu)

Jerald R. Herting, PhD

Research Associate Professor, Departs of Sociology and Psychosocial & Community Health (herting@u.washington.edu)

Kenneth M. Rice, PhD

Assistant Professor, Departments of Biostatistics (kenrice@u.washington.edu)

Lianne Sheppard, PhD

Professor, Departments of Biostatistics and Environmental and Occupational Health Sciences (sheppard@u.washington.edu)

ASSESSMENT:

Students will be evaluated on 4 criteria for an overall course grade.

1) Participation in class discussion throughout course (20% of final grade)

2) Journal article critique (20% of final grade): Five journal-article critique sessions are part of the regular course schedule. These discussion sessions are led by the students. Students will be assigned to 2 of the 5 sessions at the beginning of the course so that each of the 5 sessions will have from 4-6 students assigned to it. Students are graded on their contribution to the 2 sessions. Working together, each group will have to create 3-5 discussion questions for the class that are distributed to the class a week before the discussion. On the day of the discussion, a primary discussant and a secondary discussant will be selected at random from the group and will lead the discussion for the class. Others from the group are expected to contribute to the discussion. More details about leading a journal article critiques can be found in the “SDHRM journal critique logistics and guidelines.doc” document found on the course web site.

a) Questions for class discussion (5% of final grade): each group is to meet and develop 3-5 discussion questions for each article. Questions are distributed to the class approximately 1 week before the discussion.

b) Knowledge of the article (15% of final grade): based on contributions to the discussion and on answers to questions from the class instructor.

3) Homework assignments (30% of final grade)

a) Creation of conceptual model (7.5%)

b) Choosing between studies designs (7.5%)

c) Interpretation of ecologic data analysis and multi-level data analysis output (10%)

d) Interpretation of longitudinal analysis output (5%)

4) Final: Journal article critique (30% of final grade): A journal article will be distributed on the last day of class and all students will be required to provide a written critique of the paper’s methods that address the following points: conceptual model, study design, measurements, analytic approach, and conclusion.

CRITERIA FOR GRADES:

Range	Percent of Class	Quality of Performance
3.9 - 4.0 (A)	Graduate: 20%	Superior performance in all aspects of the course with work exemplifying the highest quality. Unquestionably prepared for subsequent courses in field.
3.5 - 3.8 (A-)	Graduate: 50%	Superior performance in most aspects of the course; high quality work in the remainder. Unquestionably prepared for subsequent courses in field.
3.2 - 3.4 (B+)	Graduate: 25%	High quality performance in all or most aspects of the course. Very good chance of success in subsequent courses in field.
2.9 - 3.1 (B)	Graduate: _5%	High quality performance in some of the course; satisfactory performance in the remainder. Good chance of success in subsequent courses in field.
2.5 - 2.8 (B-)	Graduate: _0%	Satisfactory performance in the course. Evidence of sufficient learning to succeed in subsequent courses in field.
2.2 - 2.4 (C+)	Graduate: _0%	Satisfactory performance in most of the course, with the remainder being somewhat substandard. Evidence of sufficient learning to succeed in subsequent courses in field with effort.
2.1 and below (C and below)	Graduate: _0%	Evidence of some to minimal learning. Marginal to very low chance of success in subsequent courses in field.

DISTRIBUTION AND DUE DATES FOR HOMEWORK AND FINAL:

Thursday, Jan 8: Distributed homework assignment #1

Monday, Jan 12: Receive homework assignment #1 by 17h00

Thursday, Jan 22: Distributed homework assignment #2

Thursday, Jan 29: Collect homework assignment #2

Tuesday, Feb 17: Distributed homework assignment #3

Tuesday, Feb 24: Collect homework assignment #3

Thursday, Feb 26: Distributed homework assignment #4

Thursday, Mar 5: Collect homework assignment #4

Thursday, Mar 12: Distribute final journal article for critique

Tuesday, Mar 17: Final journal critique due by 9h00

ABBREVIATED COURSE OUTLINE:

Session

Session Description

Lecturers

Tue, Jan 6

Introduction and Overview

Shirley A. A. Beresford, PhD & Nicholas L. Smith, PhD

Thu, Jan 8

Causality and Conceptual Models

NLS

Tue, Jan 13

Major Conceptual Models in SDH Research

NLS & student-led discussion

Thu, Jan 15

Journal Article Critique #1:

Conceptual Models

None (student-led discussion)

Tue, Jan 20

Study Design Issues (part 1)

NLS

Thu, Jan 22

Study Design Issues (part 2)

NLS

Tue, Jan 27

Measurement Issues

SAAB

Thu, Jan 29

Social Status and Health Disparities

SAAB

Tue, Feb 3

Analytic Issues (part 1):

Ecologic Data

Sebastien J. Haneuse, PhD & NLS

#10

Thu, Feb 5

Journal Article Critique #2:

Study Design and Measurements

None (student-led discussion)

#11

Tue, Feb 10

Analytic Issues (part 2):

Analyzing Multi-level Data

Kenneth M. Rice, PhD & NLS

#12

Thu, Feb 12

Analytic Issues (part 3):

Confounding and Effect Modification with Multi-level Data

Lianne Sheppard, PhD & NLS

#13

Tue, Feb 17

Analytic Issues (part 4)

Network Analysis and Multi-level Review

SAAB & NLS

#14

Thu, Feb 19

Journal Article Critique #3:

Multilevel

None (student-led discussion)

#15

Tue, Feb 24

Analytic Issues (part 5)

Longitudinal Data

Brian G. Leroux, PhD

#16

Thu, Feb 26

Analytic Issues (part 6):

Geography & Neighborhood and Longitudinal Data Review

SAAB & NLS

#17

Tue, Mar 3

Analytic Issues (part 7):

Structural Equation Models

Jerald R. Herting, PhD

#18

Thu, Mar 5

Journal Article Critique #4:

Longitudinal

None (student-led discussion)

#19

Tue, Mar 10

Translation of Research Findings

NLS

#20

Thu, Mar 12

Journal Article Critique #5:

General Overview

None (student-led discussion)

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Last Updated:
02/20/2007

Contact the instructor at 287-2784: or by e-mail nlsmith@u.washington.edu