Part 1:
1. Choose a paper describing the development or validation of a measure of relevance in health disparities research (please give the full citation and/or upload the paper if that's possible).
Krieger N, Smith K, Naishadham D, Hartman C, Barbeau EM. Experiences of discrimination: validity and reliability of a self-report measure for population health research on racism and health. Soc Sci Med 2005 Oct;61(7):1576-96. Epub 2005 Apr 21.
2. What was the definition of the construct?
The authors developed an “Experiences of Discrimination” (EOD) measure that is obtained through a self-report questionnaire measuring exposure to racial discrimination.It was intended for use in large-scale studies as an index of racial discrimination and was based on an instrument previously used in the Coronary Artery Risk Development in Young Adults (CARDIA) study. The EOD questionnaire probes whether subjects had experienced discrimination in 9 situations (e.g. at school, getting hired, at work, etc) and the frequency of discrimination.
3. How did the authors provide evidence on the validity of the measure? Could you think of additional approaches to validating the measure?
The main study questionnaire was administered to African American, Latino, and white participants. A validation study was administered by having a subset of African American and Latino participants complete a re-test survey two to four weeks after the initial survey. Both surveys included the EOD questionnaire and several single-item questions related to worry about racial discrimination and global questions examining how often the participants felt members of their racial/ethnic group experienced discrimination. The validation survey also included questions from two other measures of discrimination, the Williams Major and Everyday measures.
The authors provided evidence of validity by comparing the EOD measure to the Williams Major and Everyday measures. In addition, they assessed the correlation between EOD measures and psychological distress and smoking, two health outcomes that have been correlated with experiences of racial discrimination. A previously validated instrument was used to measure psychological distress. Patients self-reported whether they had ever smoked at > 100 cigarettes. While these seem to be appropriate outcomes to choose, the authors could have chosen other health outcomes that have been associated with discrimination, such as depression, hypertension, and low birth weights.
The authors also created a validation structural equation model (SEM) to assess whether the measures of discrimination all tapped into the same underlying construct of self-reported racial discrimination. The model fit well with the data, as evidenced by a Comparative Fit Index (CFI) = 0.966 and Root Mean Square Error of Approximation (RMSEA) = 0.069
4. How did the authors provide evidence on the reliability of the measure? Could you think of additional approaches to evaluating the reliability of the measure?
The authors presented test-re-test reliability data for African American and Latino Participants combined (because the results were similar in these groups). Re-test data was obtained by having a cohort of study participants repeat the test two to four weeks after the initial survey. The test-re-test correlations for both 9-item and 7-item EOD scores (frequency and situation) were high (0.69 or higher). In contrast, single question measurements were less reliable and had low correlation with EOD scores. Cronbach’s alpha for the 9-item and 7-item EOD were > 0.74.
5. Describe the implications of a lack of measurement validity or reliability for future research applications.
Lack of reliability evidence would call into question the relevance of the EOD measure as an indicator of discrimination. Similarly, it’s important to assess whether EOD actually correlates with health outcomes that have been previously correlated with racial discrimination. Without this information, we have no way of saying whether or not EOD is a clinically useful measure of experiences of racial discrimination.
Part 2:
1. Find a paper describing a health disparity (please give the full citation or, even better, upload the paper so everyone else can look at it too)
Elli EF, Gonzalez-Heredia R, Patel N, Masrur M, Murphey M, Chen J, Sanchez-Johnsen L. Bariatric surgery outcomes in ethnic minorities. Surgery. 2016 Sep;160(3):805-12.
2. Summarize the construct and measurement of the dimension of disparity (e.g., racial inequalities?, SES inequalities?) and the outcome measured (e.g., self-rated health).
Self-reported race/ethnicity data were obtained from the EHR and were classified as white, Hispanic/Latino, African American/black, or other. The data were input into patient charts by administrative staff during hospital registration. The authors also conducted a final verification by examining additional locations in the medical record, where a patient's race and Hispanic/Latino background could be found.
The primary outcome was percent excess weight loss across and between racial groups at 6, 12, 24, and 36 months follow-up after sleeve gastrectomy or a Roux-en-Y gastric bypass.
3. What is the evidence for the validity and reliability of the measures?
The authors don’t specifically comment on the validity and reliability of their racial/ethnic classifications. The data is self-reported, though, and thus likely more reliable than the classifications of race/ethnicity in many retrospective studies that are assigned to patients by hospital personnel.
4. What is the reference category used for the disparity measure (ie, who is the comparison group)? Why does this reference category make sense (or not) for this research question?
The white group was used as the reference category. The use of white patients as the reference category isn’t inappropriate, but it is an example of the bias in medical research toward white patients as the baseline or norm against which other racial and ethnic groups are compared.
5. How is the disparity quantified or measured? Is this an absolute or relative measure or are both provided? Describe which type of measure you would prefer for this research area, or, if both, why.
The disparity measured is percent excess body weight (%EBW) lost after surgery. The authors used a linear mixed model analysis to account for the dependency between repeated measurements of %EBW over the study time period, and report the coefficient for black, Latino, and “others” in reference to white patients, which is a relative measure. It seems appropriate to use a relative measure in this situation.
Part 3:
Read someone else's response to part 1 above (identifying a construct) and comment, specifically noting whether you can see any additional implications of measurement quality for future research or whether you agree with those noted by your classmate
I agree with Toshali that it’s difficult to apply a one-dimensional model of attitudes within a community to other communities, as there may be many heterogeneous factors that go into a community’s attitudes toward smoke-free policies. I also noticed that the residents weren’t required to complete post-policy questionnaires, which could introduce an element of selection bias based on who chose to respond to the questionnaire.