Texas Tech University

Researchers Contribute to Broader Understanding of Committed Relationships

Glenys Young

August 24, 2020

Sylvia Niehuis and Alan Reifman were part of a recent international collaboration.

Relationships can be complicated – but they don't have to be.

Two faculty members in Texas Tech University's Department of Human Development and Family Studies (HDFS) recently contributed to international research seeking to better understand relationships.


Sylvia Niehuis, an associate professor, and husband Alan Reifman, a professor, were part of a landmark multi-university endeavor to determine the major contributing factors for satisfying and committed dating and marital relationships. The findings were published in the Proceedings of the National Academy of Sciences.

The study's lead investigators, Samantha Joel of the University of Western Ontario and Paul Eastwick of the University of California-Davis, reached out to fellow relationship researchers around the world to contribute their data, allowing them all to be analyzed together. However, the contributed data had to meet very specific criteria: studies must include both partners in each couple, rather than relying on one partner to report for both; studies must follow the couples longitudinally over time; and studies needed to assess a certain set of concepts pertaining to close relationships, for instance satisfaction and commitment.


Niehuis had two studies from her SMITTEN Research Lab that fit the bill: one on newlywed couples in Lubbock County and one on college dating couples.

"I began the newlywed study shortly after my arrival at Texas Tech in 2007," Niehuis said. "We have collected data from couples twice, once within six months of their wedding and again roughly two and-a-half years later. It was a large-scale study designed specifically to examine how premarital and early marital experiences impact subsequent marriage. The study combined both psychological and societal or cultural variables to examine the interplay between them.

"The dating study was more intensive, with couples completing surveys three times, each separated by one month. The focus was entirely on psychological aspects of early intimate relationships."

Assisted by Reifman and former doctoral student Rebecca Oldham, now a faculty member at Middle Tennessee State University, Niehuis prepared and submitted the data and accompanying documentation, according to the lead investigators' specifications. Ultimately, 43 usable datasets were submitted, including Niehuis' two.

"This is similar to a meta-analysis, but not exactly the same," Niehuis explained. "In a meta-analysis, the researcher has access only to published or unpublished research reports and averages together the final statistical results reported in each article. In our project, the data analysts not only had each study's final statistical results, but also all the original data from each participating couple – more than 11,000 couples in all from the 43 studies – so they could go into greater depth with the data than can be done in a typical meta-analysis."

Joel and Eastwick performed highly advanced analyses on the data using machine-learning techniques.

"The software looks for patterns in the data, just as email programs try to anticipate the next word you will write based on which words tend to follow each other," Niehuis said. "In our case, as an analogy, the program would look for patterns of how couples' reported behaviors such as social support, sexual satisfaction and conflict go together with couples' relationship satisfaction.

"The software was capable of detecting not only linear relations – for instance, does each one-unit rise in social support go along with a one-unit rise in relationship satisfaction? – but also nonlinear relations – do support and satisfaction move in tandem up to a point, at which extremely high levels of support start to become associated with lower satisfaction, perhaps because the recipient of the support feels a loss of independence?"

The researchers investigated more than 2,000 variables, including relationship-related variables such as sexual satisfaction, conflict and investment, and individual difference variables such as negative affect, attachment styles and stress. They found that relationship characteristics were the best predictors of satisfaction. The top five variables were perceived partner commitment, appreciation of one's partner, sexual satisfaction, perceived partner satisfaction and reduced conflict.

One major strength of this study is that samples came from the United States, Canada, New Zealand, Israel and several European countries, each in its own social context, so its findings can be more broadly applied.

"My newlywed study, for example, consisted mostly of Hispanic and white couples in a politically conservative region where many couples marry at a younger age than elsewhere in the U.S. and in some European nations," Niehuis said. "In fact, my sample had among the highest Hispanic representation of the collected studies. In addition, although some samples were made up of college students, others, such as my newlywed study, used data that either were or came close to being representative of the population from which they were drawn. Thus, some of the samples included low-income couples, minority couples, etc.

"By merging so many studies, the entire body of data likely represents a rich diversity of contexts, although the countries were predominantly Western and economically advanced. The wider the array of countries – and subcultures within each country – one can study, the more thoroughly the characteristics of the different geographical regions can balance each other out."

Niehuis emphasized that, while large-scaled collaborations are common in certain disciplines, they are newer and fewer in social sciences. She hopes such efforts will further a broader understanding of human relationships.

"Some scholars have made the analogy of a single study being like a brick and a collection of studies being like a building," she said. "By drawing from so many different sources of data and each study's particular findings, we can deliver a more powerful message regarding the overall conclusions we can draw."