Hierarchical Linear Modeling for Analysis of Ecological Momentary Assessment Data in Physical Medicine and Rehabilitation Research.

Ecological momentary assessment (EMA) methods collect real-time data in real-world environments, which allow physical medicine and rehabilitation researchers to examine objective outcome data and reduces bias from retrospective recall. The statistical analysis of EMA data is directly related to the research question and the temporal design of the study. Hierarchical linear modeling, which accounts for multiple observations from the same participant, is a particularly useful approach to analyzing EMA data. The objective of this paper was to introduce the process of conducting hierarchical linear modeling analyses with EMA data. This is accomplished using exemplars from recent physical medicine and rehabilitation literature.

Using virtual reality to explore self-regulation in high-risk settings.

Virtual reality (VR) models allow investigators to explore high-risk situations carefully in the laboratory using physiological assessment strategies and controlled conditions not available in field settings. This article introduces the use of a virtual experience to examine the influence of self-regulatory skills training on female participants' reactions to a high-risk encounter with an aggressive male. Sixty-three female participants were recruited for the study. Demographic data indicated that 54% of the participants were not currently in a relationship, 36.5% were in a committed relationship, and 9.5% were occasionally dating. After obtaining informed consent, participants were assigned randomly to either a diaphragmatic breathing training condition or an attention control condition. Results indicated that both groups rated the virtual environment as equally realistic; the aggressive advances of the male were also perceived as equally real across the two experimental groups. Physiological data indicated that there were no differences between the groups on respiration or cardiovascular measures during baseline or during the VR task. After the VR experience, however, the participants in the breathing training condition had lower respiration rates and higher heart rate variability measures than those in the control condition. The results suggest that VR platforms provide a realistic and challenging environment to examine how self-regulation procedures may influence behavioral outcomes. Real-time dynamic engagement in a virtual setting affords investigators with an opportunity to evaluate the utility of self-regulatory skills training for improving safety in situations where there are uncertain and risky outcomes.