Adaptive patterns of stress responsivity: a preliminary investigation

Abstract

The adaptive calibration model (ACM) is an evolutionary-developmental theory of individual differences in stress responsivity. In this article, we tested some key predictions of the ACM in a middle childhood sample (N = 256). Measures of autonomic nervous system activity across the sympathetic and parasympathetic branches validated the 4-pattern taxonomy of the ACM via finite mixture modeling. Moreover, the 4 patterns of responsivity showed the predicted associations with family stress levels but no association with measures of ecological stress. Our hypotheses concerning sex differences in responsivity were only partly confirmed. This preliminary study provides initial support for the key predictions of the ACM and highlights some of the methodological challenges that will need to be considered in future research on this topic.

Figure 1

The adaptive calibration model (ACM) of individual differences in development of stress responsivity. At a very general level, a nonlinear relation exists between exposures to environmental stress and support during development and optimal levels of stress responsivity. Although this nonlinear relation is specified for the stress response system (see Table 1), it may apply to other neurobiological systems as well. The figure does not imply that all components of the system will show identical responsivity profiles or that they will activate at the same time or over the same time course. Male/female symbols indicate sex-typical patterns of responsivity, but substantial within-sex differences in responsivity are expected as well. Roman numerals indicate the four prototypical responsivity patterns in the ACM. From “The Adaptive Calibration Model of Stress Responsivity,” by M. Del Giudice, B. J. Ellis, and E. A. Shirtcliff, 2010, Neuroscience & Biobehavioral Reviews, 35, p. 1577. Copyright 2010 by Elsevier.

Figure 2

Depiction of the finite mixture model. RSA–B = respiratory sinus arrhythmia at baseline; RSA–R = respiratory sinus arrhythmia reactivity; SCL–B = skin conductance level at baseline; SCL–R = skin conductance level reactivity.

Figure 3

Prediction of physiological indicators of the four latent classes (z scores). Roman numerals indicate the four prototypical responsivity patterns in the adaptive calibration model. SCL–R = skin conductance level reactivity; SCL–B = skin conductance level at baseline; RSA–B = respiratory sinus arrhythmia at baseline; RSA–R = respiratory sinus arrhythmia reactivity. Roman numerals indicate the four prototypical responsivity patterns in the adaptive calibration model.

Figure 4

Mean levels of environmental stress/support in the four latent classes. Roman numerals indicate the four prototypical responsivity patterns in the adaptive calibration model.

Figure 5

Probability of class membership as predicted by (a) family warmth/predictability and (b) negative family relationships. Probabilities are relative to the Buffered class (a probability of 0.5 indicates that membership in the two classes has the same likelihood).