The Role of Internalizing and Externalizing Symptoms among Smokers and Physical Pain

The Role of Internalizing and Externalizing Symptoms among Smokers and Physical Pain

Presented at the 8th Annual BayesiaLab Conference on October 27, 2020.


The use of marijuana, tobacco, and opioid analgesics has long been associated with psychological distress and chronic pain. The aim of the study was to identify the effects of internalizing and externalizing psychological symptoms utilizing Bayesian Network models to gain a greater understanding of the interrelationships that may exist between pain, psychological and sociodemographic variables. This study included adults enrolled in Wave 4 (2016-2017) of the Population Assessment of Tobacco and Health (PATH) Study. The PATH Study is an ongoing, longitudinal cohort study of tobacco use and related health outcomes in the U.S. Participants with data on variables related to cigarette smoking, marijuana use, psychological distress from the Global Appraisal of Individual Needs Short Screener (GAIN-SS), opioid use, and pain levels (n=32,551) comprised the study sample. The GAIN-SS identifies individuals at risk for mental health or substance use disorders and has been used across the 4-point Likert scale asking about past year problems with internalized disorder, externalized disorder, substance use, and crime/violent behaviors (crime/violent behavior items were excluded from the PATH Wave 4 study). Established smoking status was defined as lifetime use of 100 cigarettes whereas non-established use was defined as not reaching the 100 cigarette lifetime use threshold. The analyses included population sample weights which accounted for missing data. We employed an augmented naïve Bayes (ABN; Bayesialab 9) supervised learning algorithm to identify the interrelationships between the use of pain medications, smoking status, pain intensity, alcohol and marijuana use, GAIN-SS factors, and select sociodemographic characteristics. The initial Augmented Naïve Bayes was cross-validated via the K-folds procedure, with K=10. The final ABN structure was learned and optimized via the minimum description length (MDL) scoring algorithm. The initial MDL score was 732,140.862, representing Entropy (H) = 23.0785 (Standard Deviation: 3.9705), and the final MDL score was 689,686.468, representing Entropy (H) = 21.7285 (Standard Deviation: 3.9812), with mean information compression of 5.7427%. Overall relationship analyses with pain indicated that the internalized behavior factor was the most important predictive variable among these participants suggesting that by knowing pain, we reduce our uncertainty regarding internalized behavior by 2.49% on average. Smoking status, opioid use, and marijuana use were also found to be associated with pain. The severity of internalized, externalized problems and substance use disorders along with current and former established cigarette smoking were associated with high levels of pain intensity, suggesting that self-reported pain is an important factor to consider in smoking cessation and substance abuse counseling programs.

Presentation Video

About the Presenters

Mahathi Vojjala, MPH
Doctoral Candidate, Department of Epidemiology, School of Global Public Health, New York University

Mahathi Vojjala is a third-year doctoral candidate in the Epidemiology track working with Dr. Raymond Niaura. She is a 2017 MPH graduate from New York University School of Global Public Health (GPH) with a concentration in Epidemiology. Prior to her MPH, Mahathi received a B.A. in religion and public health from Rutgers University. Mahathi’s previous research focused on youth smoking initiation and media advertising, dual and poly use of substances specifically marijuana and cigarettes among young adults, media portrayal of alcohol and tobacco in movie trailers and youth smoking rates, and more recently, use of oral analgesics combined with marijuana, alcohol, and cigarettes among people with chronic pain. Mahathi is primarily interested in assessing the benefits and risks of e-cigarettes by examining metabolic biomarker profiles of tobacco user groups using the Population Assessment of Tobacco and Health (PATH) Study.

Marcel de Dios, Ph.D.
Assistant Professor, Department of Psychological Health & Learning Sciences, College of Education, University of Houston

Dr. Marcel de Dios is a faculty member in the Department of Psychological, Health and Learning Sciences (PHLS) at the University of Houston. He received his Ph.D. in Counseling Psychology from the University of Miami in 2007. He completed his clinical psychology predoctoral internship at Denver Health and Medical Center and moved on to a two-year postdoctoral research fellowship in behavioral medicine at Brown University Medical School. During his post-doctoral fellowship, Marcel conducted research related to smoking cessation with HIV + Latino smokers. Upon the completion of his fellowship in 2009, Marcel became a faculty member in the Department of Psychiatry & Human Behavior at Brown University Medical School. As a faculty member, his work expanded to include other sub-populations of substance users including young adult marijuana users, Latino light smokers, methadone maintenance smokers, and emerging adults struggling with alcohol and marijuana use. In October of 2012, Marcel relocated to Houston Texas, and became a faculty member in the Department of Health Disparities Research at MD Anderson Cancer Center where he continued his work in the area of smoking cessation funded through an NIH K01 award. In 2017, Marcel joined the faculty of the Counseling Psychology Ph.D. Program at the University of Houston. He has continued his work in the areas of substance use including projects related to young adult marijuana and alcohol users, smokers, and opioid abusers.

Helen Sanchez
Doctoral Student, Counseling Psychology, College of Education, University of Houston

Helen Sanchez is a Counseling Psychology doctoral student at the University of Houston, working under the direction of Dr. Marcel de Dios. Prior to her doctoral studies, Helen completed research assistantships in the Health Behavior Research Group at Texas A&M University and the Prinsloo Neuromodulation Lab at MD Anderson Cancer Center. Currently, Helen is a graduate research assistant for the Psychology of Addiction Collaborative at the University of Houston, and her research interests broadly include substance use, health disparities among racial/ethnic minority populations, and health risk perception. Her current work focuses on the use of tobacco and other substances by South Asian Americans. Clinically, Helen works as a psychology intern with the Houston Fire Department, providing psychotherapy to first responders and their family members.

Raymond Niaura, Ph.D.
Interim Chair of the Department of Epidemiology and Professor of Social and Behavioral Sciences, School of Global Public Health, New York University

Dr. Raymond Niaura is a psychologist and an expert on tobacco dependence and treatment, as well as substance use. Dr. Niaura has a long history of extramural funding for research projects that have examined the biobehavioral mechanisms of tobacco dependence, including factors that influence adolescent and early adult tobacco and e-cigarette use trajectories. He has also conducted a number of clinical trials that have focused on pharmacological and behavioral interventions for tobacco cessation with an emphasis on disadvantaged and vulnerable subpopulations. Dr. Niaura’s work has been highly influential, and he has published over 400 peer-reviewed articles, commentaries, and book chapters, including the book The Tobacco Dependence Treatment Handbook: A Guide to Best Practices.

His work over several decades has been highly influential and cited and has significantly shaped public policy related to tobacco use and cessation

For North America

Bayesia USA

4235 Hillsboro Pike
Suite 300-688
Nashville, TN 37215, USA

+1 888-386-8383

Head Office

Bayesia S.A.S.

Parc Ceres, Batiment N 21
rue Ferdinand Buisson
53810 Change, France

For Asia/Pacific

Bayesia Singapore

1 Fusionopolis Place
#03-20 Galaxis
Singapore 138522

Copyright © 2024 Bayesia S.A.S., Bayesia USA, LLC, and Bayesia Singapore Pte. Ltd. All Rights Reserved.