Types of questions TVEM can answer

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Presentation transcript:

Types of questions TVEM can answer Age (Developmental Time) Mean levels and associations are dynamic with age Example: Vasilenko & Lanza (2014) Journal of Adolescent Health How does salience of risk factors for having multiple sexual partners unfold with age? Rates of Multiple Partners by Age Male 95% CI Male Female 95% CI Female ADD associations example? Proportion of individuals having sex with multiple partners by age is significantly different for men and women in late 20s.

Types of questions TVEM can answer Effect on Craving: Baseline Dependence Time from Event: Associations among variables change as function of time from event Example: Lanza et al., (2014) Nicotine and Tobacco Research How do predictors relate to craving over 14 days post-quitting cigarettes? Treatment group shows significantly weaker association between dependence and craving during second week after quit.

Types of questions TVEM can answer Historical time (years) Levels, prevalence, and associations can change across years Example: Lanza et al, 2015, Journal of Adolescent Health Trends in substance use among U.S. high school seniors by race Black Youth White Youth Black and white youth demonstrate different patterns of substance use over historical time.

Types of questions TVEM can answer Timing/age of onset of event Outcomes may differ depending on when individuals first experienced an event Example: Lanza & Vasilenko, 2015, Addictive Behaviors Identify precise age ranges during which onset of regular smoking confers highest risk for adult nicotine dependence Male 95% CI Male Estimated Prevalence of Dependence Female 95% CI Female Males Age of Onset Individuals who started smoking earlier have higher prevalence of dependence; women have higher prevalence than men at age of onset between 10 and 20.

Types of questions TVEM can answer Non-time questions: “Time” is in the name, but any continuous variable can be used instead of time Essentially a nuanced way of examining a continuous moderator Example: Selya et al., 2015, Addictive Behaviors Examines how associations between smoking and mood change as a function of level of nicotine dependence Nicotine dependence serves as the “time” variable

Data Considerations Meaningful centering/alignment point Needs to be time from some meaningful zero Potentially problematic: EMA study assessing a “typical week”—no time anchor Coverage across the entire time span of interest Need to have all times/ages assessed near continuously Potentially problematic: Birth cohort study with data every 5 years The same measures at all waves of data collection Can be challenge in long-term longitudinal studies

Types of Data that can be used in TVEM Type 1. Cross-Sectional Type 2. Panel (repeated measures) Type 3. Intensive Longitudinal Data (ILD) Description of Data Data captured from population at one specific point in time Study that involves repeated observations of same variables at 2 or more time points (waves) MANY repeated observations of the same variables (typically >20) Participant Follow-up Participants not followed prospectively Participants only interviewed/assessed once Participants followed prospectively for two or more waves Participants followed prospectively for many assessments (not called waves) Example Paper Fish et al., 2018, Prevention Science Vasilenko 2017, Developmental Psychology Cook et al., 2017, Nicotine and Tobacco Research