Novel Measurement of Personality Dynamics Using Intensive Longitudinal Design (1.5 CEs)

Abstract

Examining the Construct Validity of Interpersonal Sensitivities Using Intensive Longitudinal Experience Sampling Presentation Abstract: The present study investigated the effect of interpersonal sensitivity, how bothered an individual is by the behavior of another, on the perception of another’s behavior according to the dimensions of agency, ranging from dominance to submission, and communion, ranging from friendliness to unfriendliness. Specifically, the present study explored the associations between interpersonal sensitivities and the average level, variability, and instability of perceived agentic and communal behavior. Finally, the present study investigated the impact of interpersonal sensitivities on perceptual bias, tendency to simultaneously perceive similar levels of dominant and friendly behaviors in others. Data for the current analyses were drawn from the Intraindividual Study of Affect, Health, and Interpersonal Behavior (iSAHIB), a multiple timescale study including 150 participants who completed a series of three 21-day “measurement bursts” spaced at about 4.5 month intervals (t = 426 bursts, t = 8,557 days). Prior to the first burst, participants completed demographic questionnaires and a measure of interpersonal sensitivity. During each measurement burst, participants reported on social interactions as the interactions occurred in real time (t = 64,112). Chloe Bliton | Pennsylvania State University Examining the Trans-Theoretical Personality Model in Daily Life Michael Roche, PhD | Penn State - Altoona Using Machine Learning and Personality Traits to Understand the Predictability of Day-to-Day Affective Dynamics Nicholas Jacobson, PhD | Dartmouth College Inferring Maladaptive Personality Traits from Passive Sensing Data Whitney Ringwald, M.S.WM.S.WM.S.WM.S.WM.S.WM.S.WM.S.WM.S.WM.S.W., M.S. | University of Pittsburgh Understanding dynamic characteristics of personality requires methodology capable of measuring patterns of behavior, affect, and cognitions over time and across situations. Intensive longitudinal designs have been used to model the unfolding of these processes in daily life. This symposium brings together several novel approaches within the intensive longitudinal framework for measuring aspects of personality. First, Chloe Bliton examines perception and personality through the lens of interpersonal theory, using data from multiple time scales. Social interactions were reported on over the course of three, 21-day measurement bursts spaced at 4.5 month intervals, and were used to investigate the effect of interpersonal sensitivity on the average level, variability, and bias in perception of another’s behavior. Next, Michael Roche introduces a new instrument for capturing broad domains of personality functioning at the daily level. Multi-level confirmatory factor analyses were used to examine its internal structural validity, and a person-specific application of the instrument is presented. Leveraging a different technique of person-specific modeling, Nicholas Jacobson applies machine learning to predict the strength of autoregressive and cross-regressive dynamics of day-to-day affective changes from traitbased personality data. Finally, Whitney Ringwald shows how passive-sensing data, which unobtrusively collects nearly continuous streams of information using smartphone technology, can provide insight into daily behaviors relevant to personality function and dysfunction. These talks highlight advances in personality measurement and point to exciting opportunities for future research.

Chair

Whitney Ringwald | University of Pittsburgh 

Goals & Objectives

1. Apply intensive longitudinal design methods to the assessment of personality. 
2. Identify the benefits of using intensive longitudinal designs, machine learning, and passive-sensing for studying personality.