Until 2011, social psychologists were able to believe that they were actually doing science. They conducted studies, often rigorous experiments with random assignment, analyzed the data and reported results only when they achieved statistical significance, p < .05. This is how they were trained to do science and most of them believed that this is how science works.
However, in 2011 an article by a well-respected social psychologists changed all this. Daryl Bem published an article that showed time-reversed causal processes. Seemingly, people were able to feel the future (Bem, 2011). This article shock the foundations of social psychology because most social psychologists did not believe in paranormal phenomena. Yet, Bem presented evidence for his crazy claim in 8 out of 9 studies. The only study that did not work was with supraliminal stimuli. The other studies used subliminal stimuli, suggesting that only our unconscious self can feel the future.
Over the past decade it has become apparent that Bem and other social psychologists had misused significance testing. They only paid attention to significant results, p < .05, and ignored non-significant results, p > .05. Selective publishing of significant results means that statistical results no longer distinguished between true and false findings. Everything was significant, even time-reversed implicit priming.
Some areas of social psychology have been hit particularly hard by replication failures. Most prominently, implicit priming research has been called out as a poster child of doubt about social psychological results by Nobel Laureate Kahneman. The basic idea of implicit priming is that stimuli outside of participants’ awareness can influence their behavior. Many implicit priming studies have failed to replicate.
Ten years later, we can examine how social psychologists have responded to the growing evidence that many classic findings were obtained with questionable practices (not reporting the failures) and cannot be replicated. Unfortunately, the response is consistent with psychodynamic theories of ego-defense mechanisms and social psychologists’ own theories of motivated reasoning. For the most part, social psychologists have simply ignored the replication failures in the 2010s and continue to treat old articles as if they provide scientific insights into human behavior. For example, Bargh – a leading figure in the implicit priming world – wrote a whole book about implicit priming that does not mention replication failures and presents questionable research as if they were well-established facts (Schimmack, 2017).
Given the questionable status of implicit priming research, it is not surprising that concerns are also growing about measures that were designed to reflect individual differences in implicit cognitions (Schimmack, 2019). The measures often have low reliability (when you test yourself you get different results each time) and show low convergent validity (one measure of your unconscious feelings towards your spouse doesn’t correlate with another measure of your unconscious feelings towards your spouse). It is therefore suspicious, when researchers consistently find results with these measures because measurement error should make it difficult to get significant results all the time.
Implicit Love
In an article from 2019 (i.e., when the replication crisis in social psychology has been well-established), Hicks and McNulty make the following claims about implicit love; that is feelings that are not reflected in self-reports of affection or marital satisfaction.
Their title is based on a classic article by Bargh and Chartrand.
Readers are not informed that the big claims made by Bargh twenty years ago have failed to be supported by empirical evidence. Especially the claim that stimuli often influence behavior without awareness lacks any credible evidence. It is therefore sad to say that social psychologists have moved on from self-deception (they thought they were doing science, but they did not) to other-deception (spreading false information knowing that credible doubts have been raised about this research). Just like it is time to reclaim humility and honesty in American political life, it is important to demand humility and honesty from American social psychologists, who are dominating social psychology.
The empirical question is whether research on implicit love has produced robust and credible results. One advantage for relationship researchers is that a lot of this research was published after Bem (2011). Thus, researchers could have improved their research practices. This could result in two outcomes. Either relationship researchers reported their results more honestly and did report non-significant results when they emerged, or they increased sample sizes to ensure that small effect sizes could produce statistically significant results.
Hicks and McNulty’s (2019) narrative review makes the following claims about implicit love.
1. The frequency of various sexual behaviors was prospectively associated with automatic partner evaluations assessed with an implicit measure but not with self-reported relationship satisfaction. (Hicks, McNulty, Meltzer, & Olson, 2016).
2. Participants with less responsive partners who felt less connected to their partners during conflict-of-interest situations had more negative automatic partner attitudes at a subsequent assessment but not more negative subjective evaluations (Murray, Holmes, & Pinkus, 2010).
3. Pairing the partner with positive affect from other sources (i.e., positive words and pleasant images) can increase the positivity of automatic partner attitudes relative to a control group.
4. The frequency of orgasm during sex was associated with automatic partner attitudes, whereas sexual frequency was associated only with deliberate reports of relationship satisfaction for participants who believed frequent sex was important for relationship health.
5. More positive automatic partner attitudes have been linked to perceiving fewer problems over time (McNulty, Olson, Meltzer, & Shaffer, 2013).
6. More positive automatic partner attitudes have been linked to self-reporting
fewer destructive behaviours (Murray et al., 2015).
7. More positive automatic partner attitudes have been linked to more cooperative relationship behaviors (LeBel & Campbell, 2013)
8. More positive automatic partner attitudes have been linked to displaying attitude-consistent nonverbal communication in conflict discussions (Faure et al., 2018).
9. More positive automatic partner attitudes were associated with a decreased likelihood of dissolution the following year, even after controlling for explicit relationship satisfaction (Lee, Rogge, & Reis, 2010).
10. Newlyweds’ implicit partner evaluations but not explicit satisfaction within the first few months of marriage were more predictive of their satisfaction 4 years later.
11. People with higher motivation to see their relationship in a positive light because of barriers to exiting their relationships (i.e., high levels of relationship investments and poor alternatives) demonstrated a weaker correspondence between their automatic attitudes and their relationship self-reports.
12. People with more negative automatic evaluations are less trusting of their partners when their working memory capacity is limited (Murray et al., 2011).
These claims are followed with the assurance that “these studies provide compelling evidence that automatic partner attitudes do have implications for relationship outcomes” (p. 256).
Should anybody who reads this article or similar claims in the popular media believe them? Have social psychologists improved their methods to produce more credible results over the past decade?
Fortunately, we can answer this question by examining the statistical evidence that was used to support these claims, using the z-curve method. First, all test statistics are converted into z-scores that represent the strength of evidence against the null-hypothesis (i.e., implicit love has no effect or does not exist) in each study. These z-scores are a function of the effect size and the amount of sampling error in a study (signal/noise ratio). Second, the z-scores are plotted as a histogram to show how many of the reported results provide weak or strong evidence against the null-hypothesis. The data are here for full transparency (Implicit.Love.xlsx).
The figure shows the z-curve for the 30 studies that reported usable test results. Most published z-scores are clustered just above the threshold value of 1.96 that corresponds to the .05 criterion to claim a discovery. This clustering is indicative of the use of selecting significant results from a much larger set of analyses that were run and produced non-significant results. The grey curve from z = 0 to 1.96 shows the predicted number of analyses that were not reported. The file drawer ratio implies that for every significant result there were 12 analyses with non-significant results.
Another way to look at the results is to compare the observed discovery rate with the expected discovery rate. The observed discovery rate is simply the percentage of studies that reported a significant result, which is 29 out of 30 or 97%. The estimated discovery rate is the average power of studies to produce a significant result. It is only 8%. This shows that social psychologists still continue to select only successes and do not report or interpret the failures. Moreover, in this small sample of studies, there is considerable uncertainty around the point estimates. The 95%confidence interval for the replication success probability includes 5%, which is not higher than chance. The complementary finding is that the maximum number of false positives is estimated to be 63%, but could be as high as 100%. In other words, the results make it impossible to conclude that even some of these studies produced a credible result.
In short, the entire research on implicit love is bullshit. Ten years ago, social psychologists had the excuse that they did not know better and misused statistics because they were trained the wrong way. This excuse is wearing thin in 2020. They know better, but they continue to report misleading results and write unscientific articles. In psychology, this is called other-deception, in everyday life it is called lying. Don’t trust social psychologists. Doing so is as stupid as believing Donald Trump when he claims that he won the election.