About

Stephanie Lanza is the Director of The Edna Bennett Pierce Prevention Research Center and a Professor of Biobehavioral Health at Penn State. She holds a Ph.D. in Human Development and Family Studies, an M.A.S. in Applied Statistics, and an M.S. in Human Development and Family Studies from Penn State, as well as a B.S. in Mathematical Science and a B.A. in Psychology from the University of North Carolina at Chapel Hill. Her research primarily focuses on advancing finite mixture models, particularly latent class analysis, and applying new statistical models to reveal dynamic processes. She collaborates with researchers such as Bethany Bray, John Dziak, Megan Patrick, Runze Li, Michael Russell, and Sara Vasilenko to address research questions related to health behavior, age- and time-varying effects, and social data analytics.

Research topics

• Computer Science
• Management science
• Psychology
• Statistics
• Mathematics
• Engineering
• Data science

Selected publications

• Author’s response to: “The need to advance the measurement of exposure to digital content.”

  Nicotine & Tobacco Research · 2026-04-28

  article
  PublisherDOI

• Time‐Varying Effect Modeling to Address Novel Questions in Developmental Research

  2026-02-20

  other1st authorCorresponding

  Time-varying effect modeling (TVEM) is a statistical approach that enables researchers to estimate associations between variables as continuous functions of time, thus holding potential to address new questions in developmental science. First, we present a conceptual introduction to unique developmental questions that TVEM is well suited to address, such as questions about changes across development in the strength of associations between risk factors and problematic outcomes. We then summarize the key contributions of TVEM for developmental research. Second, we summarize technical details that are essential for applying TVEM to empirical research. Third, we present an empirical demonstration of how to apply TVEM to address developmental research questions. In this demonstration, we use TVEM to examine whether the strength of association between marijuana use and depressive symptoms varies across high school ages and identify specific ages at which this association differs for male and female adolescents. The syntax used to estimate these models and create figures showing relevant coefficient functions is included in an appendix. We conclude this chapter with a discussion of the demonstration, the application of TVEM to other time metrics (for example, to examine within-day processes by modeling intensive longitudinal data), and future directions for the application and development of TVEM in developmental research.

  PublisherDOI

• Daily motivation for and perceived accessibility of nondrug reward among people in long-term recovery from opioid use disorder

  Drug and Alcohol Dependence · 2026-04-08

  articleSenior author
  PublisherDOI

• A qualitative study investigating the role of humor in supporting recovery from addiction

  Journal of Substance Use and Addiction Treatment · 2025-11-24

  articleOpen accessSenior author
  PublisherOA PDFDOI

• A qualitative study investigating the role of humor in supporting recovery from addiction

  2025-02-04

  preprintSenior author

  IntroductionWhen adaptive aspects of humor are cultivated (i.e. humor to reframe negative events), humor can be supportive of mental health. Humor-based interventions improve mental health in several clinical populations, but there is minimal research on humor in people with addiction. The goal of our study was to examine if and how people in recovery from opioid addition use humor in their daily lives and whether humor is perceived as supportive of recovery.MethodsQualitative semi-structured interviews were conducted in one study visit with people in recovery from opioid addiction receiving methadone for treatment (n = 11). A reflexive thematic approach informed theme generation and coding; codes were developed both inductively and deductively informed by prior literature.ResultsHumor was central in nearly all participants’ lives and showed up in a variety of ways, providing nuance into the supportive role of humor in recovery. We identified the following themes: Dark Humor and Lived Experience, identifying humor used to make light of a difficult past; For Humor, Timing is Everything, demonstrating dynamic receptivity to humor; Good Vibrations or Distractions?, focusing on humor as pleasurable and serving as a distraction from stress; and Read the Room: Social Contexts Can Drive the Supportive Role of Humor, emphasizing that humor can facilitate social connections and useful conversations about addiction. ConclusionHumor was integral to participant’s lives, often because of (not despite) difficult lived experiences. Greater investigation is needed into how recovery identity may interplay with preference for substance use-related humor and the potential for humor to enhance mood and enable difficult conversations about addiction.

  PublisherDOI

• Constellations of Family Qualities and Links with Psychological and Behavioral Health in Adolescence and Young Adulthood

  Journal of Child and Family Studies · 2025-09-08

  articleOpen access

  Abstract Positive family qualities, including low parent pressure to control weight, high physical activity support, frequent family meals, family connectedness, healthy family functioning, and parental monitoring, may promote youth psychological and behavioral health. We aimed to identify naturally occurring patterns of family qualities during adolescence and examine links with body satisfaction, self-esteem, depressive symptoms, disordered eating, and substance use during adolescence and young adulthood. Our goal was to inform family-centered interventions to prevent adverse health outcomes impacting youth. Data were from a longitudinal study of 1568 youth (53% female; 20% Asian, 29% Black, 17% Latinx, 19% White), that spanned adolescence ( M age = 14.4 years) to young adulthood ( M age = 22.2 years). Results from latent class analysis indicated that 8% of families were thriving, with low probability of parent pressure to control weight and high probabilities of physical activity support, frequent family meals, family connectedness, healthy family functioning, and parental monitoring. Other classes were distinguished by weight-specific risk (23% of families), broad risk (34% of families), disengagement (18% of families), and high risk (16% of families). Youth in thriving families reported better psychological and behavioral health than their peers concurrently in adolescence and longitudinally in young adulthood; yet this pattern of family qualities was rare. Family-centered interventions that target parent pressure to control weight, physical activity support, family meals, family connectedness, family functioning, and parental monitoring may help prevent multiple psychological and behavioral health problems. Heterogeneity in family qualities suggests that family-centered interventions could be tailored based on family strengths.

  PublisherOA PDFDOI

• Comparing subjective effects and intoxication on simultaneous alcohol and cannabis use occasions relative to alcohol‐ or cannabis‐only occasions

  Alcohol Clinical and Experimental Research · 2025-06-13

  articleOpen accessSenior author

  BACKGROUND: Simultaneous use of alcohol and cannabis-or use of both substances so effects overlap-is common among college-attending young adults and can heighten one's likelihood of experiencing substance-related harms in daily life. Limited ecological momentary assessment and daily diary work have examined the role of subjective intoxication and subjective effects when engaging in simultaneous relative to alcohol- or cannabis-only use, and studies have yielded mixed results. As such, subjective experiences serve as important internal cues for decision making; this study aimed to examine the level of subjective intoxication and effects across simultaneous, alcohol-only, and cannabis-only occasions. METHODS: Participants were 119 college students aged 18-25 who reported weekly simultaneous use at baseline. Participants enrolled in a 4-week ecological momentary assessment study with up to eight prompts per day collected on weekend days. RESULTS: Multilevel models revealed that relative to alcohol- and cannabis-only days, simultaneous use days were not significantly associated with subjective alcohol or cannabis intoxication, respectively. Peak levels of subjective alcohol effects were, however, significantly stronger during simultaneous use occasions relative to alcohol-only use occasions. Subjective cannabis effects were not significantly different between simultaneous and cannabis-only use days. CONCLUSIONS: Study findings suggest that "adding" cannabis to an alcohol use occasion may bolster subjective effects such as feeling clumsy, confused, and having difficulty concentrating. Findings also highlight that subjective effects, rather than degree of impairment/intoxication, more strongly differentiates alcohol and simultaneous use occasions, and may serve as a useful momentary intervention target in future work.

  PublisherOA PDFDOI

• A Latent Class Analysis of Health Characteristics Among Non-Drinking Middle-Aged and Older Adults

  Innovation in Aging · 2025-12-01

  articleOpen accessSenior author

  Abstract Despite documented health consequences of heavy alcohol consumption, there is ongoing debate around potential health benefits of low-to-moderate alcohol use. Better understanding variability in health characteristics among non-drinkers can inform discourse around the alcohol j-curve and underscore the diverse health profiles of adults who abstain in later life. The current study aimed to identify latent classes of non-drinkers based on subjective and objective health characteristics and examine person-level predictors of class membership. Participants were adults aged 50+ years in the Midlife in the United States study who did not report past-month alcohol use (N = 1,205; range=50-84 years). Dichotomous health indicators included any functional impairment, obesity, cardiometabolic risk factors (diabetes, high blood pressure, or stroke), chronic pain, chronic sleep problems, self-reported physical health (1=Fair/Poor; 2=Excellent/Very Good/Good), perceived health in comparison to others (1=Somewhat Worse/Much Worse, 2=Much Better/Somewhat Better/About the Same), chronic depression and/or anxiety, and self-reported mental health (1=Fair/Poor; 2=Excellent/Very Good/Good). Person-level predictors included age (1=Older Adult, 0=Middle-Aged), sex (1=Male, 0=Female), alcohol use history (1=Lifetime Abstainer, 0=Former Drinker), and education (1=College Degree or Higher, 0=Less Than College Degree). Five latent classes were identified: poor overall health (5.9%), poor physical and self-reported health but good mental health (17.9%), poor physical health but good self-reported and mental health (28.5%), good self-reported health but poor physical and mental health (9.8%), and good overall health (38.0%). Age, education, and biological sex, but not alcohol use history, predicted probability of class membership. Future research can explore how the underlying latent classes predict distal health outcomes.

  PublisherOA PDFDOI

• Innovative Methods Can Accelerate Advancements in Research on Alcohol and Other Drugs

  Journal of Studies on Alcohol and Drugs · 2025-10-22

  article1st authorCorresponding
  PublisherDOI

• Patterns of substance use on a given day in a national sample of U.S. young adults

  Addictive Behaviors · 2025-04-29 · 2 citations

  article
  PublisherDOI

Recent grants

• Center for Complex Data to Knowledge in Drug Abuse and HIV Behavioral Science

  NIH · $26.8M · 2015–2022

• NIH Grant R01CA168676

  NIH · $498k · 2016

• NIH Grant R03DA023032

  NIH · $126k · 2009

• NIH Grant P50DA010075

  NIH · $47.7M · 2016

• NIH Grant R01DA039854

  NIH · $676k · 2019

Frequent coauthors

• Ashley N. Linden‐Carmichael

  University of Oregon

  43 shared

• Sara A. Vasilenko

  Syracuse University

  24 shared

• Linda M. Collins

  New York University

  23 shared

• Constantino Lagoa

  19 shared

• Martha J. Cox

  18 shared

• John J. Dziak

  University of Illinois Chicago

  18 shared

• Samuel W. Stull

  Pennsylvania State University

  17 shared

• Joshua M. Smyth

  17 shared

Labs

• Social Data AnalyticsPI