Happy Intro Stats: Exploring Self-Care and Mental Health Inequities via Statistics

Co-created by Shu-Min and her students, Happy Intro Stats is an interactive course designed to help students understand inequities in mental health issues via statistics. We begin the course by examining mental health stigmas and practice self-care exercises to train our “happy muscles” together. We also discover the scientific evidence behind those self-care practices and explore existing racial disparities in mental health care systems, while learning about important statistical concepts and mastering our data analysis skills using R. This course is offered with minimum barriers – no prerequisites, no expectations on prior coding experience, and no costs for the textbook and software – and maximum support through student-centered designs and inclusive pedagogies.

Weekly Self-Care Practices & Mental Health Readings

• Weekly Self-Care Practices: 10-minute weekly self-care practices we tried through Fall 2022
• Required Readings for Mental Health Discussion (readings related to sample examples and activities shared below)

Sample Class Examples & R Activities

• R Activity 2 (Fall 2022): This R Activity covers basic Explanatory Data Analysis using a paper (see the reading list above) which explores the effects of gratitude journaling on student mental and physical health during the pandemic.
• R Activity 3 (Fall 2022): This R Activity focuses on one study (see the reading list above) that discusses a self-care practice (meditation), and includes a lot of comprehensive information about Regression.
• Class Example 5 (Fall 2022): This Class Example introduces how to use our “three-R inference approach” to create a bootstrap confidence interval for one proportion, using a study aimed to explore the influence of various mental health stigmas on students, with data retrieved from the Healthy Minds Network 2019 survey.
• R Activity 5 ( Fall 2022): This R Activity explains how to use our “three-R inference approach” to create a bootstrap confidence interval for one mean.
• Class Example 7 (Fall 2022): This Class Example explains how to use our “three-R inference approach” to conduct a randomization test for the different between two means.
• R Activity 9 (Fall 2022): This R Activity Example explains how to use our “three-R inference approach” to conduct a randomization test, as well as to construct a bootstrap confidence interval, for a regression coefficient. The data used are based on a study (see the reading list above) on medical and biomedical doctoral trainees in a big University which investigates if there is a discernible difference in mental health conditions and access amongst students of various communities.

Course Projects

• Group Project Guideline (Fall 2022)
  • Dataset 1 (2020BRFSS.csv): The Behavioral Risk Factor Surveillance System (BRFSS) 2020 dataset contains survey data collected from adults from the U.S. about their health-related risk behaviors, chronic health conditions, and use of preventative services.
  • Dataset 2 (student_mental_health.csv): This dataset came from a paper, titled “A Dataset of Students’ Mental Health and Help-Seeking Behaviors in a Multicultural Environment”, that investigated international and domestic students’ mental health and help-seeking behaviors in an international university in Japan.

More teaching materials will be shared here during Year 2023-2024……