URBANA, IL (Chambana Today) – A groundbreaking study from the University of Illinois Urbana-Champaign is reshaping how researchers understand the evolution of romantic relationships over time. By applying a modern statistical approach known as Group-Based Trajectory Modeling (GBTM), researchers aim to test and refine widely accepted relationship theories with greater precision.
“Understanding how relationships change influences not just couples, but individual well-being and family functioning more broadly,” said lead author Jeremy Kanter, an associate professor in the Department of Human Development and Family Studies at Illinois. “If we can strengthen the theoretical foundation of relationship science, we can more effectively support interventions for couples.”
Traditionally, relationship research has relied on theories that attempt to explain why some couples thrive while others falter. But many of these models were developed before the arrival of advanced data-analysis tools like GBTM, which groups individuals with similar patterns of change in their relationships over time. This technique allows for a deeper exploration of how satisfaction, conflict, and other relationship dynamics evolve.
In the newly published paper in the Journal of Family Theory & Review, Kanter and co-authors Christine M. Proulx, Amy J. Rauer, and H. Cailyn Ratliff analyze five major relationship theories: enduring dynamics, emergent distress, gradual disillusionment, vulnerability-stress-adaptation, and relational turbulence.
Each theory offers a different view of how romantic satisfaction changes. For instance, enduring dynamics suggests early patterns persist throughout the relationship, while emergent distress points to the buildup of conflict over time. Gradual disillusionment warns of high initial satisfaction giving way to disappointment. Meanwhile, vulnerability-stress-adaptation emphasizes how life stress and individual traits shape relationship paths, and relational turbulence focuses on the disruption couples face during major life transitions.
“Each theory implies a different point of intervention — whether that’s during dating, early marriage, or periods of transition,” Kanter explained.
The researchers argue that using GBTM allows for stronger, testable hypotheses grounded in these theories, and for identifying which models best align with real-life relationship trajectories. For example, GBTM can reveal if relationship satisfaction tends to remain stable, decline uniformly, or follow more complex non-linear patterns.
Kanter also emphasized the importance of incorporating dyadic patterns — understanding how one partner’s emotional or behavioral changes influence the other — to build a fuller picture of relational dynamics.
“Incorporating these modern methods can show us not just if a theory holds up, but how it might need to evolve,” he said. “Some models may need revising, or even integration with others, to better reflect today’s understanding of relationships.”