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Active CONTINUING GRANT National Science Foundation (US)

CAREER: Patterns of Dynamic Change in Relationship Quality Over Time

$5.57M USD

Funder National Science Foundation (US)
Recipient Organization Regents of the University of Michigan - Ann Arbor
Country United States
Start Date Jul 01, 2025
End Date Jun 30, 2030
Duration 1,825 days
Number of Grantees 1
Roles Principal Investigator
Data Source National Science Foundation (US)
Grant ID 2440913
Grant Description

Romantic relationships play a critical role in human happiness and well-being, yet predicting their success or failure has long puzzled scientists. This difficulty may come from not having enough detailed information about daily relationship experiences. With modern technology, like smartphones, people now track many parts of their daily lives, such as diet, exercise, and mood.

This project uses similar technology to better understand romantic relationships by observing how they change day by day. It applies techniques like those used to forecast the weather or stock market trends to identify relationship patterns. These patterns help scientists learn about the different ways that relationships ebb and flow in daily life and predict which relationships are likely to last and which may not.

This project seeks to transform the basic scientific understanding of romantic relationship quality. It uses innovative intensive longitudinal methods with large, heterogeneous samples of individuals and couples in romantic relationship to (1) examine dynamic patterns of change in relationship quality over time and (2) identify whether some relationship patterns are more adaptive than others.

For instance, patterns involving quick recovery from negative experiences might be more adaptive than those involving slow recovery. Tracking day-to-day relationship changes over long periods allows for discovery of common patterns that emerge before a relationship ends, improving predictions of relationship outcomes. In addition, examining how partners change with, view, and affect each other adds an important dyadic component to prediction models, filling a key gap in our scientific knowledge.

The development and sharing of innovative statistical methods for analyzing dynamic social processes provides valuable resources for the scientific community. Broad dissemination of study findings, including through an interactive website, ensures that the findings are shared broadly. Ultimately, this project expands our knowledge of relationship science by encouraging us to view relationships in a novel way - as potentially meaningful dynamic patterns of change which informs future research and interventions aimed at promoting healthy, lasting relationships.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

All Grantees

Regents of the University of Michigan - Ann Arbor

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