Daily physical activity and alcohol use across the adult lifespan.

Objective: In contrast to proposals that physical activity (PA) can be a substitute for alcohol use, people who engage in greater overall PA generally consume more alcohol on average than less-active peers. Acknowledging that both PA and alcohol use vary considerably from day-to-day, this study evaluated whether established associations reflect daily behavioral coupling within-person, are an artifact of procedures that aggregate behavior over time, or both.

Methods: A life span sample of 150 adults (aged 19-89 years) completed three 21-day measurement bursts of a daily diary study.

Examining the Interplay of Processes Across Multiple Time-Scales: Illustration With the Intraindividual Study of Affect, Health, and Interpersonal Behavior (iSAHIB).

Human development is characterized by the complex interplay of processes that manifest at multiple levels of analysis and time-scales. We introduce the Intraindividual Study of Affect, Health and Interpersonal Behavior (iSAHIB) as a model for how multiple time-scale study designs facilitate more precise articulation of developmental theory. Combining age heterogeneity, longitudinal panel, daily diary, and experience sampling protocols, the study made use of smartphone and web-based technologies to obtain intensive longitudinal data from 150 persons age 18-89 years as they completed three 21-day measurement bursts ( = 426 bursts, = 8,557 days) wherein they provided reports on their social interactions ( = 64,112) as they went about their daily lives.

Behavioral Landscapes and Change in Behavioral Landscapes: A Multiple Time-Scale Density Distribution Approach.

In developmental arenas, it is well accepted that multiple observations are needed to obtain a robust characterization of individuals' behavioral tendencies across time and context. In this paper, we fuse core ideas from the study of lifespan development with intraindividual variability based approaches to personality and methods used to characterize the topography of geographic landscapes. We generalize the notion of density distributions into bivariate and multivariate space and draw parallels between the resulting behavioral landscapes and geographic landscapes.