Tabassum Presenting Research at the American Public Health Association Conference

Author: Mufazzela Tabassum | Major: Public Health | Semester: Fall 2023

This research investigates social media discussions on emerging tobacco access laws, with a specific focus on the proposed California date-of-birth bill. The bill aims to ban sales of tobacco products to individuals born after 2006. By analyzing social media conversations, the study aims to identify enforcement challenges and public sentiments towards the policy, with the goal of providing valuable insights for policymakers to improve tobacco access policies and address potential loopholes.

My previous research project examined the evolving landscape of the tobacco industry by taking a deeper look into the diversity of e-cigarette devices available today. Through that experience I learned a lot on how policies and federal regulations play a role in combatting the alarming increase in the use of tobacco and nicotine products among our nation’s youth. Several policies have been enacted to take preventative measures. One notable policy is the tobacco 21 law, which has raised the age of purchase of tobacco and nicotine products from 18 to 21. Policies such as these play a significant role in shaping better public health outcomes. So, for this project, I decided to look specifically into the proposed California date-of-birth bill. This bill aims to ban sales of tobacco products to all individuals born on or after the year 2006. My goal was to proactively identify the enforcement challenges that may arise with implementing this regulation. Additionally, I aimed to qualitatively identify the public’s overall sentiment towards this policy.

My mentor, Dr. Page Dobbs, has secured an NIH grant for research initiatives focused on nicotine and tobacco product regulation. In collaboration with the University’s College of Engineering’s data science faculty and students, our team began a project centered around the analysis of Reddit data related to the proposed California date-of-birth bill. Utilizing their expertise, researchers in Dr. Khoa Luu’s data science lab successfully scraped Reddit data relevant to the discussion of the bill. Following this, we systematically transferred the data to Excel and created a comprehensive codebook to facilitate the coding process.

Working under the guidance of my mentor and alongside a PhD student in the lab, I, along with another undergraduate research assistant, undertook the task of coding a subset of the Reddit data each week. During the coding process, our primary focus was on discerning whether the public’s attitude toward the proposed policy was positive, negative, neutral, or a combination of these sentiments. Our coding agreeability was subsequently calculated each week using Cohen’s kappa to ensure that we had a reliable approach to measuring and assessing individual attitudes. However, attaining our desired level of coding agreeableness proved challenging. Week after week, we invested considerable time in long discussions, aiming to align our perspectives and clarify reasons behind specific codes. However, I found this process rewarding because it revealed the uniqueness of human interpretation. It demonstrated that qualitative data, by nature, carries a subjective component that adds richness and depth to our understanding.