Match!
Stephanie T. Lanza
Pennsylvania State University
Developmental psychologyPsychologyLatent class modelMedicineSocial psychology
178Publications
32H-index
6,043Citations
What is this?
Publications 185
Newest
#1David E. Conroy (PSU: Pennsylvania State University)H-Index: 36
#2Chih-Hsiang Yang (USC: University of South Carolina)H-Index: 5
Last. Constantino Lagoa (PSU: Pennsylvania State University)H-Index: 18
view all 5 authors...
BACKGROUND: Mobile technology has increased the reach of health behavior interventions but raised new challenges in assessing the fidelity of treatment receipt. Fidelity can be compromised if participant fatigue or burden reduces engagement, leading to missed or delayed treatments for just-in-time interventions. OBJECTIVE: This study aimed to investigate the temporal dynamics of text message receipt confirmations. METHODS: Community-dwelling adults (N=10) were sent five text messages daily for 4...
Source
#1Tianchen QianH-Index: 3
#2Michael A. RussellH-Index: 34
Last. Susan A. MurphyH-Index: 42
view all 7 authors...
Although there is much excitement surrounding the use of mobile and wearable technology for the purposes of delivering interventions as people go through their day-to-day lives, data analysis methods for constructing and optimizing digital interventions lag behind. Here, we elucidate data analysis methods for primary and secondary analyses of micro-randomized trials (MRTs), an experimental design to optimize digital just-in-time adaptive interventions. We provide a definition of causal "excursio...
#1John J Dziak (PSU: Pennsylvania State University)H-Index: 11
#2Donna L. Coffman (PSU: Pennsylvania State University)H-Index: 19
Last. Runze Li (PSU: Pennsylvania State University)H-Index: 42
view all 5 authors...
Choosing a model with too few parameters can involve making unrealistically simple assumptions and lead to high bias, poor prediction, and missed opportunities for insight. Such models are not flexible enough to describe the sample or the population well. A model with too many parameters can fit the observed data very well, but be too closely tailored to it. Such models may generalize poorly. Penalizedlikelihood information criteria, such as Akaike’s Information Criterion (AIC), the Bayesian Inf...
139 CitationsSource
#1Hio Wa MakH-Index: 2
#2Michael A. RussellH-Index: 34
Last. Gregory M. FoscoH-Index: 16
view all 5 authors...
Antisocial peer behavior and low parental knowledge of adolescents' activities are key interpersonal risk factors for adolescent substance use. However, how the magnitude of associations between these risk factors and substance use may vary across adolescence remains less well understood. The present study examined the age-varying associations of parental knowledge and antisocial peer behavior with adolescents' substance use (i.e., cigarette use, drunkenness, and marijuana use) using time-varyin...
Source
Simultaneous alcohol and marijuana (SAM) use is prevalent among young adult drinkers and associated with increased risk for harms. Less understood about SAM use is whether increased risk is incurred on SAM use occasions relative to occasions in which individuals used only 1 substance. From a sample of young adult SAM users, we compared occasions in which individuals simultaneously used alcohol and marijuana so that the effects overlapped ("SAM days"), occasions involving only alcohol ("alcohol d...
3 CitationsSource
Affect regulation models state that affect both motivates and reinforces alcohol use. We aimed to examine whether affect levels and rates of change differed across drinking versus nondrinking days in a manner consistent with affect regulation models. Four hundred four regularly drinking adults, aged 18-70 years, completed ecological momentary assessments over 3 weeks. Participants provided positive affect (PA; enthusiastic, excited, happy) and negative affect (NA; distressed, sad) reports during...
Source
Prevalence of heavy alcohol use remain high, and daily marijuana use is at an all-time high in young adults. As perceptions of drug effects may guide risky decision making, understanding subjective feelings for alcohol and marijuana use is critical. Existing laboratory-based and diary metrics (0-100 rating of "how drunk/high do you feel?") may be problematic in differentiating levels of subjective effects. Measures incorporating contemporary language may better capture subjective feelings in exp...
Source
#1Korkut BekirogluH-Index: 2
#2Michael A. Russell (PSU: Pennsylvania State University)H-Index: 34
Last. Candice L. Odgers (Duke University)H-Index: 33
view all 7 authors...
Source
#1Bethany C. BrayH-Index: 16
#2John J DziakH-Index: 11
Last. Stephanie T. LanzaH-Index: 32
view all 3 authors...
Abstract Introduction Although much of the work on risky alcohol use behaviors, such as heavy drinking, focuses on adolescence and young adulthood, these behaviors are associated with negative health consequences across all ages. Existing studies on age trends have focused on a single alcohol use behavior across many ages, using methods such as time-varying effect modeling, or a single age period with many behaviors, using methods such as latent class analysis. This study integrates aspects of b...
Source
#1Bharathi J. Zvara (UNC: University of North Carolina at Chapel Hill)H-Index: 6
#2Roger Mills-Koonce (UNCG: University of North Carolina at Greensboro)H-Index: 7
Last. Patricia Garrett-PetersH-Index: 14
view all 14 authors...
Children’s representational models of self and relationship quality with caregivers in the context of intimate partner violence (IPV) were investigated using family drawings created by children in ...
Source
12345678910