The random dyadic interdependence model: Modeling variability in physiological covariation within dyads

Area of Science:

• Psychology
• Physiology
• Biomedical Engineering

Background:

• Cognitive impairment significantly impacts family dynamics and physiological responses.
• Understanding physiological linkage in dyads is crucial for assessing health outcomes.
• Existing models may not fully capture the heterogeneity of physiological interdependence.

Purpose of the Study:

• To introduce a novel modeling strategy for capturing physiological linkage in dyads.
• To examine the heterogeneity of physiological interdependence in older parent-adult child dyads.
• To explore the association between family dynamics and physiological interdependence.

Main Methods:

• Utilized Dynamic Structural Equation Modeling (DSEM) framework.
• Analyzed repeated physiological measures (blood pressure, heart rate, respiration) from 102 parent-child dyads.
• Employed random covariance modeling to estimate interdependence patterns.

Main Results:

• Demonstrated substantial heterogeneity in dyadic physiological interdependence.
• Identified both positive and negative interdependence patterns across physiological measures.
• Found family cohesion and open expression linked to positive blood pressure interdependence.

Conclusions:

• The novel DSEM approach effectively captures variable physiological interdependence in dyads.
• Physiological interdependence is heterogeneous and can be positive or negative.
• Family cohesion may buffer negative physiological synchrony in parent-child dyads facing cognitive impairment.