Missing Information: Using Automatic Attitudes to Resolve Inconsistencies in Close Relationships Research
By Lindsey Hicks
When romantic partners get married, they usually do so with expectations of love, happiness and companionship for years to come. Very few, if any, have visions of future conflict, dissatisfaction, or dissolution. Yet, many couples do experience significant declines in satisfaction (Meltzer, McNulty, Jackson & Karney, 2014b) and approximately 40% to 45% of marriages in the U.S. end in divorce (Kreider & Ellis, 2011). Although there are several important theories that provide a framework from which to understand these declines, such as interdependence theory, evolutionary theory, and attachment theory, our understanding of the mechanisms that can transform happy partners into bitter enemies remains incomplete.
In their recent article, McNulty and Olson (2015) suggest that incorporating dual process perspectives into the major theoretical perspectives of close relationships may fill some of these gaps. Dual process models emphasize that attitudes predict behavior in two ways—automatically and via controlled processes. In the absence of motivation to behave otherwise, people tend to automatically act in ways that reflect their “gut-level” attitudes. However, given sufficient motivation and ability, people are able to engage in controlled processes that guide their behavior, sometimes in ways unaligned with their gut-level attitudes.
Consider someone who strongly dislikes a colleague. Given such a negative attitude, this person’s automatic inclination will likely be to engage in more negative behaviors directed at the colleague (e.g., avoiding the colleague, bad mouthing the colleague, even being rude to the colleague). But people realize such confrontation can cause problems in the workplace and is at least uncomfortable. Given such motivations to behave more positively, this person may engage in various controlled processes to overcome the influence of this negative attitude—i.e., he or she may try to be nice to the colleague. Of course, these controlled processes require self-regulatory resources, so people must also have the ability to deliberately override their automatic attitudes if they are to successfully monitor their behavior. When stressed, tired, overworked, or distracted, our friend may revert to more negative behaviors, revealing his or her gut-level attitudes towards the colleague.
McNulty and Olson (2015) outline how similar processes can unfold in a relationship. Obviously, people who have very positive gut-level attitudes toward their partners should behave positively, but given sufficient motivation, even people with more negative gut-level attitudes will behave positively. And some people do have more negative gut level attitudes toward their partners. Imagine such a couple participating in a research study on marital satisfaction. Due to problems they are experiencing in their relationship, both spouses likely feel some negativity toward each other. However, due to numerous motivations (i.e., desire to see the relationship in a positive light, social pressure, embarrassment, beliefs that things will improve, etc.) both of them may override these negative feelings when reporting their satisfaction. But, is it crucial to note people can only engage in such controlled processes as long as they also have (a) control over the behavior in question and (b) sufficient cognitive resources. Therefore, any negative gut-level attitude will emerge (a) on behaviors over which people have little control and (b) at times when people do not have the resources necessary to behave otherwise. Indeed, consistent with the idea that partners will at times engage in automatic behaviors and face circumstances during which they are cognitively taxed, research indicates that initial gut-level attitudes predicted relationship satisfaction over the first four years of marriage (McNulty, Olson. Meltzer, & Shaffer, 2013).
Of course, in order to incorporate dual-process models into research on relationships, researchers must first assess gut-level attitudes. So far, most relationships research has measured attitudes explicitly by simply asking people how they feel about their relationships. As suggested in the preceding paragraph, explicit reports require deliberate cognitive processing, so any attitude captured by explicit reports are likely to reflect individual motivations, ideals, and biases. Therefore, capturing gut-level attitudes requires measuring them implicitly, in ways that people are unable to monitor. Fazio and colleagues (Fazio, Jackson, Dunton & Williams, 1995) evaluative priming procedure and Greenwald, Nosek and Banaji’s (2003) Implicit Attitude Test are two popular methods.
Utilization of these implicit tests may provide insight into a phenomenon that challenges theoretical perspectives on motivated reasoning: people frequently become unhappy with their relationships over time despite being highly motivated see their partners in a positive light (Fletcher & Kerr, 2010). Though this idea may initially seem counterintuitive, instances of contrasting motivations in relationships are not difficult to picture. Imagine two partners who meet and instantly know that they have found “the one.” Their whirlwind romance quickly develops into marriage and a new life together. Initially, they are happy with their situation, but as time passes and the novelty of their romance starts to fade, each person begins to discover negative attributes about their spouse that they didn’t notice before or perhaps that they chose to ignore. Over time, these attributes may ignite full-blown arguments in their relationship until both partners have rather negative attitudes about their spouses. However, one partner fears the economic ramifications and social stigma that accompanies divorce and the other worries about the impact a spilt may have on the couple’s children, so they each seek to override their negative attitudes and focus on the positive aspects of their relationship. Yet, as previously mentioned, each partner’s ability to override negative sentiments is unlikely to exist indefinitely. This will be particularly problematic for our couple as times of stress are inevitable over the course of a long-term relationship, times at which they may not have the cognitive resources necessary to override their negative attitudes. At such times, any negative attitudes will ultimately directly affect their behavior and ultimately explicit perceptions.
Incorporating dual process models into relationships research may also help resolve another puzzling observation: frequent sex does not seem to predict greater relationship satisfaction. Because frequent sex increases the odds of conception, evolutionary perspectives suggest that humans likely developed a preference for frequent sex with their partners. Given that relationship satisfaction may reflect the extent to which partners are meeting evolved desires (Meltzer, McNulty, Jackson & Karney, 2014a), couples who engage in sex more frequently should be more satisfied with their relationship. However, empirical evidence supporting this idea is sparse, and some studies have shown that there is no relationship between sexual frequency and relationship satisfaction (Loewentstein, Krishnamurti, Kopsic & McDonald, 2015; McNulty, Wenner & Fisher, 2014). Rather than conclude that sexual frequency does not influence relationship satisfaction, it may be beneficial to consider that all prior research on this topic has utilized only explicit reports of satisfaction. Given that such explicit reports involve controlled processing and thus likely reflect ideals, norms, and other beliefs, the association between sexual frequency and relationship satisfaction may be biased by people’s beliefs regarding the importance of sex for relationships. If so, employing implicit measures of satisfaction may allow researchers to bypass such beliefs to more effectively capture the implications of sex for relationship satisfaction. In fact, given many romantic preferences likely evolved before human’s significantly enhanced capacity for deliberative thinking, implicit measures may better capture the implications of numerous preferences for relationship satisfaction, which may explain why predicted sex differences are sometimes elusive when examined using explicit measures.
A final inconsistency that may be explained by implicit measures can be found in research on romantic attachment. According to attachment theory, attachment styles are stable, trait-like working models that are automatically activated and predict important relationship behaviors. However, a number of studies have found attachment style can fluctuate depending on various relationship factors and life events (Gillath & Shaver, 2007; Zhang & Labouvie-Vief, 2004). One explanation for such fluctuations may be that most research on adult attachment has relied primarily on explicit self-reports of attachment security, which may be influenced by contextual factors, such as motivation and the ability to override automatic responding. Using implicit measures may remove such noise and demonstrate more stability. In fact, recent research on implicit trust, a construct closely related to attachment security, demonstrated that individuals' implicit/ automatic trust (or distrust) in their partners only influenced their behavior when they lacked the ability to override their impulsive sentiments (Murray et al., 2013). This finding suggests attachment measured by explicit self-report may vary depending on partners' opportunity to regulate their automatic attitudes. This variation in explicit self-reports may account for the perceived fluctuation in attachment styles.
These few examples demonstrate the potential benefits of considering both explicit and implicit/ automatic attitudes in relationships research. Ultimately, complete understanding of relationships likely requires assessing gut-level attitudes, motivation, cognitive resources, and explicit responses and their associations both cross-sectionally and over time.
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Lindsey Hicks is a doctoral student in Social Psychology under the direction of Dr. Jim McNulty at Florida State University.