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Relationships

The Top 5 Predictors of Relationship Quality

4. Your perception of your partner's satisfaction.

Key points

  • Researchers analyzed data from over 11,000 couples to identify which factors best predict relationship quality.
  • Perceived partner commitment, appreciation, sexual satisfaction, perceived partner satisfaction, and conflict were the top 5 predictors.
  • Partner reports of the relationship and individual differences such as demographics and personality added little additional knowledge.
  • Change in relationship quality over time was relatively unpredictable.
Lucky Business/Shutterstock
Source: Lucky Business/Shutterstock

How much a couple fights, how committed partners are to each other, how long they have been together—when it comes to understanding the quality of people’s romantic relationships, which factors actually matter? Close relationship researchers Samantha Joel and Paul Eastwick gathered datasets from their colleagues to try to answer this question. In all, they gathered 43 datasets with data from more than 11,000 couples. They used dozens of factors measured across datasets to predict relationship satisfaction and commitment concurrently, as well as changes in satisfaction and commitment over time. Here are three key takeaways from what they found:

1. The top 5 predictors of relationship quality. The number-one predictor of relationship satisfaction and commitment was people's perception of their partner's relationship commitment. This was followed by appreciation for their partner, sexual satisfaction, perceptions of their partner's relationship satisfaction, and reported conflict in their relationship. (You can see the full list in the paper.)

2. People’s self-reported feelings about their relationship mattered most. The researchers looked at a variety of different predictors. These included not only people’s self-reports about their relationship and their perceptions of their partner but also their partner’s reports about their relationship. They found that after accounting for people’s own reports about the relationship, their relationship quality was not strongly influenced by their partner’s reports. In other words, while perceiving a partner as committed is the strongest predictor of relationship quality, it is that perception that really matters—how committed one's partner reports actually feeling does not add much beyond one's own perception. Why does this matter? It tells us that how our partners feel about our relationships seems to impact how we feel only to the extent that we pick up on their feelings. If your partner is not highly committed to your relationship, but you believe them to be highly committed, it is that belief or perception that will guide how you feel.

People’s self-reports about their relationship also mattered much more than demographics or individual differences, such as how extraverted or depressed people were. The top individual difference predictors were life satisfaction, negative affect, depression, attachment avoidance, and attachment anxiety. Age ranked sixth, and other demographics such as gender and race were much lower. However, as with partner reports, these individual differences did not predict relationship quality beyond people’s reports about their relationship, suggesting that any effect demographics and individuals differences have on relationship quality happens by shaping how people actually feel about their relationships. For example, people who tend to experience more negative affect and depression may be less satisfied in their relationships primarily because they are less appreciative of their partners and perceive them as less committed.

3. Change in relationship quality is hard to predict. When looking at how people’s satisfaction and commitment changed over time, the researchers found a similar pattern of effects in terms of which factors mattered most, but these effects were weaker; most of the change in relationship quality was unpredictable. This could be due in part to the fact that they only had one follow-up measurement for each study, and it is harder to predict outcomes when you only have two timepoints. However, other research also points to the general difficulty of predicting life trajectories. So while this research lends some insight into what shapes how we feel about our relationships in the moment, it doesn’t tell us nearly as much about what predicts how we are going to feel weeks, months, and years down the line.

To me, the highlights from these findings are: (1) how important our perceptions of our partner’s feelings are in shaping our own feelings, though of course, the reverse is also true: How we feel can shape how we think our partner feels since we often project our own feelings on to them). And, (2) rather than the quality of our relationships being predetermined based on factors outside of our control, such as our age or early life experiences, many of the top predictors of relationship quality are factors we have some control over: appreciation for our partners, satisfaction with our sex lives, and conflict in our relationships. This research looks at naturalistic associations, not interventions or treatments, and there is always individual variability; these effects tell us what happens on average for a large group of people, so we can’t say that boosting appreciation will necessarily make you more satisfied. However, as a whole, this research provides insights into good places to start looking if we are interested in trying to increase relationship quality.

Facebook image: Lucky Business/Shutterstock

References

Joel, S., Eastwick, P. W., Allison, C. J., Arriaga, X. B., Baker, Z. G., Bar-Kalifa, E., ... & Wolf, S. (2020). Machine learning uncovers the most robust self-report predictors of relationship quality across 43 longitudinal couples studies. Proceedings of the National Academy of Sciences, 117(32), 19061-19071.

Salganik, M. J., Lundberg, I., Kindel, A. T., Ahearn, C. E., Al-Ghoneim, K., Almaatouq, A., ... & McLanahan, S. (2020). Measuring the predictability of life outcomes with a scientific mass collaboration. Proceedings of the National Academy of Sciences, 117(15), 8398-8403.

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