You may remember some time back I wrote a post on interdependence that focused on two different perspectives: dyadic interdependence and network interdependence. Since then there has been a bit more work that blend these two perspectives. I think it’s important to break that down because it may help us get a better picture of the ways in which our friends and families influence our relationship’s quality and lifespan.
To sum up my last post, dyadic interdependence works like this:
Person A and person B have their own life sequences, and interdependence is the extent to which they interrupt (i.e., facilitate or interfere with) each other’s daily goals and scripts1. That’s all well and good, but it’s also worth noting that the way in which we understand interdependence as a couple might spread to the way in which we understand interdependence as a network.
Specifically, and as described in my last post, network interdependence really just describes characteristics of a network: its size, density, reachability, overlap, and clustering2. But as of late, researchers have come to understand that we can actually measure interdependence in networks the same way that we measure it in ccouples3. This is kind of a big deal because interdependence plays a HUGE role in the ways that scientists study relationships. Theories of relationships even describe that interfering and facilitating behaviors from a partner are closely linked to emotional reactions4. In this way, we can literally measure the extent to which a couple’s overlapping interchain sequences affects their relationship.
If we consider the network as a group of people with who we are interdependent, we can measure the influence that they have on our relationship(s) as well. And wouldn’t you know it, the extent to which we believe ourselves to be interdependent with our social network relates to our relationship quality5! Network interdependence and dyadic interdependence, when measured, are very closely related to each other, such that levels of network interdependence at one time affect levels of dyadic interdependence at another time, and vice-versa. Most interesting of all, our network interdependence influences our emotions in the same way that dyadic interdependence does, although not quite as much.
So, why is this important? Well, the common myth is that our relationships as happening in a vacuum. Our love life isn’t our network’s business, and our partner shouldn’t necessarily intrude on our “friend time.” In practice we know that this is not the case. Often, we have to juggle friendships alongside relationships. Sometimes our friends dislike our partner, and sometimes our partners get jealous of our friends. These perceptions are meaningful, as they interfere with and facilitate our everyday activities. If we turn back to our definition of interdependence, we have to admit that our partners are not the only people with whom we share these interdependent relationships. They’re all over the place – some more meaningful than others. Visually, we might not be looking at an interchain sequence of interdependence, but more like an interchain helix:
Here we still see person A and person B, but also persons C, D, E, and F. Notice how some of these paths are thicker than others. This is because it’s likely that a best friend’s (person C) interchain sequence interrupt’s ours more so than, for example, a second cousin (person E). Look messy? It should! Relationships are complicated. It’s important that we understand that there are more than just two people in a relationship, and that our actions not only mesh with our partner’s, but also with everyone surrounding us as a couple. The next question plaguing researchers is to figure out just which types of network members are the most important role-players in our relationship development. I’ve got a story for that one, but it’ll have to wait for another day.
1Berscheid, E. (1983). Emotion. In H. H. Kelley, E. Berscheid, A. Christensen, J. Harvey, T. L. Huston, G. Levinger, E. McClintock, L. A. Peplau, D. R. Peterson (Eds.), Close Relationships (pp. 110– 168). San Francisco: Freeman
2Surra, C. A. (1988). The influence of the interactive network on developing relationships. In R. M. Milardo’s (Ed.), Families and social networks (pp. 48–82). Newbury Park, CA: Sage.
3Stein, J. B. (2018). “The company you keep”: Developing a measurement model of network and partner interdependence. Journal of Communication Methods and Measurements, 13(1), 19-25 doi: 10.1080/19312458.2018.1487546
4Solomon, D. H., Knobloch, L. K., Theiss, J. A., & McLaren, R. M. (2016). Relational turbulence theory: Explaining variation in subjective experiences and communication within romantic relationships. Human Communication Research. 32(4), 469-503.
5Stein, J. B., & Davidson, M. J. (2019). Exploring the predictive and theoretical validity of network interference and facilitation. Southern Communication Journal, 84(5). 314-327. doi: 10.1080/1041794X.2019.1641835
Dr. James Stein – Articles | Website/CV
James’ primary area of research is the study of uncertainty and how it influences close relationships. So, what behaviors make us the most uncertain about our relationships? And, more importantly, how do those uncertainties affect our relationships? James also studies friends with benefits relationships in great detail, and how they differ from/overlap with more traditional close relationships.
