About the Author
My name is Adriana Rochelle, and I am a graduate student pursuing a Master of Public Health (MPH) in Population and Health Sciences at the University of Michigan with a focus in Health Behavior and Health Equity. I have a background in health communications, project management, and research. My experience working with the California Teachers Study (CTS) has been a valuable opportunity to strengthen my skills in data analysis, statistics, and using patient-reported health measures.
My Research Project
For my Applied Experience (APEx) project, I worked with the CTS to examine the relationship between demographic factors and health outcomes. Demographic factors are characteristics like a person's age, race, income, and education level. To evaluate health outcomes, I used Patient-Reported Outcomes Measurement Information System (PROMIS) measures. PROMIS is a set of measures that evaluate physical, mental, and social health. The National Institutes of Health (NIH) developed PROMIS as a tool that could be used to assess patient-reported health status across different populations.
The goal of my research was to explore whether CTS participants’ PROMIS responses varied based on their demographic and lifestyle characteristics. To do this, I looked at theta scores for six PROMIS measures:
● Fatigue
● Pain Interference
● Anxiety
● Depression
● Ability to Participate in Social Roles
● Cognitive Function
Theta scores capture how each participant's score relates to an average US population. Theta scores typically range from -4 to 4, where 0 is the mean. For example, if a participant had a fatigue theta score of 1, that means their fatigue is one standard deviation higher than the average US population.
My project evaluated whether CTS participants’ PROMIS theta scores were associated with five different demographic factors: age, race, marital status, retirement status, and income. In other words, do participants with different demographic factors score differently on PROMIS?
What I Found
In the CTS, PROMIS scores were associated with key demographic factors. Older participants generally reported lower levels of anxiety and depression but higher levels of fatigue and pain interference. I also found that retired participants had higher cognitive function scores compared to those still working. Additionally, income was associated with mental health outcomes: higher-income participants reported lower anxiety and depression scores. The results also showed that participants with high education levels reported more positive health outcomes overall.
Future Goals
Future research should focus on further exploring how demographic and lifestyle factors interact to shape health outcomes. These studies could also include diverse populations to provide a more comprehensive understanding of health disparities. Additionally, tracking PROMIS measures over time—instead of a single survey point—would allow researchers to investigate changes over the life course. This would offer valuable insights into how demographic factors may be associated with well-being at different life stages.