The effect of data aggregation on temporal stability of cardiovascular reactivity

Temporal stability of behaviorally evoked cardiovascular responses is important for theoretical (concept of activation) and practical (risk for cardiovascular diseases) reasons. As in test psychology, reliability of physiological responsivity depends on the degree of data aggregation across several measurements. This paper describes a statistical approach based on intra-class correlations. This approach is suited to define certain stability measures based on variance components representing different levels of data aggregation. An empirical investigation is presented comprised of 58 subjects, three physiological parameters (heart rate, systolic and diastolic blood pressure), two mental tasks, two sequences of the tasks within one session, and 2 days with an interval of 4 weeks between them. In addition to the finding that data aggregation can generally increase stability, the different sources of aggregation (across phases within a task, across tasks, and across task sequences) and their combinations are systematically compared with regard to their contribution to this enhancement. Finally, it will be shown how the approach can be utilized to explain aggregation effects for other psychophysiological research questions such as covariation, consistency, and ambulatory assessment of cardiovascular functioning.