One of the main ways to find out about what a person thinks of their relationship is to simply ask them about it. As a result, relationship science tends to be heavily reliant on self-report measures. For example, to find out how much affection someone has experienced lately from their romantic partner, we might administer an item like, “Over the last week, my partner has been physically affectionate with me”, and have participants rate it from 1 = strongly disagree to 7 = strongly agree.

However, recent findings from our lab and others have called into question whether self-report relationship measures are properly capturing the constructs they are intended to capture. One major threat to the validity of these measures is a phenomenon called “sentiment override”: the tendency for people to project their global, gestalt relationship sentiments onto specific relationship measures they complete. If Rachel is asked how affectionate her partner Sanjay has been over the past week, we would ideally like her to recall her many recent interactions with Sanjay and think about how many hugs, kisses, etc. she received. However, she may instead think to herself, “I love Sanjay a lot. So, he’s probably been really affectionate lately.” This poses a problem for the field because it means that measures intended to capture specific constructs (e.g., physical affection) may actually capturing a more global construct (overall relationship quality).

At the Relationship Decisions Lab, we are very concerned about this problem and the threat that it poses to past and future relationship findings. As a result, much of the work being conducted in the lab right now is focused on basic measurement validation. What are we really capturing with the research measures that we use? Are there steps we can take to increase our confidence in those measures? How can we more confidently capture the constructs we are most interested in? These and similar questions are likely to be the main focus of the lab over the next several years.