Communicating behavioral genetics: Charting the limits of the genetic interpolation effect

Background

The field of behavioral genetics works at improving scientific understanding of human and animal social behaviors by investigating whether these behaviors are partly influenced by genetic predispositions. The causal framework that commonly underlies behavior genetics takes the form of a chain reaction, linking genes, at one end, to neural processes, mental abilities and temperament, personality traits, world views, attitudes, and behaviors^1,2. Survey research and focus groups suggest that the public generally adheres to a belief system that is consistent with this causal framework^3–5. Indeed, on average, people attribute a great role to genetics in explaining biological differences (i.e., eye color, height), a moderate influence for talents and social orientation (i.e., intelligence, sexual orientation), and a weak influence for complex social behavior (i.e., having debts, preferring Apple to Microsoft)⁶. However, the media sometimes presents research findings in a way that sharply contrasts with both the public understanding of genetics and actual research conclusions. Indeed, when paying attention to the language science reporters choose to describe research findings, it is often unclear whether the influence of genetics is deterministic, prominent, moderate, or marginal^7,8.

Many academics have expressed concern over the risk that the oversimplification of genetic causation in the mass media could lead the public to misinterpret research findings^9–11. Recent empirical works in the field of science communication have offered initial support for this concern. It is not uncommon to see a news story reporting on the results of a scientific study suggesting that genetics can influence complex social behavior or orientation X. Experimental studies have tested how people react to this kind of news⁶. Two findings arise from this research. First, there is evidence of a persuasion effect: people exposed to this information increase the influence they attribute to genetics in explaining the characteristic X described in the article. However, the results also show that disseminating behavioral genetics leads some members of the public to infer greater genetic causation for other complex social traits, which were not the focus of the study presented. This side-effect has been called the genetic interpolation effect.

It is presumed that people infer greater genetic causation for other traits because they update their belief system about the overall role that genetics plays in defining social traits. The psychological mechanism at play here is likely the anchoring and adjustment heuristic^12,13. This heuristic is a cognitive shortcut people often use in their everyday life to cope with uncertainty. Many individuals, even expert geneticists, would feel ambivalent if they had to assess the overall influence genetics has on a social orientation or a social behavior. Arguably, reading a news article presenting research findings from behavior genetics can offer a valuable piece of information to complete this task. Some people may react to behavior genetics by thinking to themselves that "if genetics is strong enough to have a significant influence on this complex social trait, then its general influence on other social traits must be stronger than I had imagined," thus causing them to infer greater genetic influence for other complex characteristics not mentioned in the news article content.

The purpose of this study is threefold. First, the main goal is to test if the persuasion effect (H1) and the genetic interpolation effect (H2) also emerge following exposure to a softer treatment. Addressing this issue is necessary to better capture what kind of message can trigger the genetic interpolation effect. While previous studies exposed participants to real news articles, here subjects are exposed to one paragraph claiming that genes can influence a complex social behavior: voting or abstaining at elections. Second, the experiment was designed to test whether clarifying that a particular gene involved in causing this behavior only has a marginal effect and can moderate the size of the persuasion effect (H3). If this was found to be the case, one could expect it to result in much weaker belief updating for other non-related traits, thus contributing to moderating the size of the genetic interpolation effect as well (H4). Finally, this study was also designed to test a counter-hypothesis, an alternative explanation for the genetic interpolation effect. This alternative explanation posits that, instead of resulting from belief updating, the genetic interpolation effect is due to the simple fact that thinking about genetics shortly before reporting beliefs makes the genetic argument more accessible to participants’ minds (H5). If this was the case, being reminded that genetics can influence various physical traits – a “placebo” message – would suffice to move participants’ average response.

Methods

This study was conducted as part of the Short Study Program of Time-Sharing Experiments in the Social Sciences. A web survey was fielded by the firm Government for Knowledge during the month of August 2013. A sample of 2080 respondents was recruited from a pre-existing panel, with a response rate of 62.6% (AAPOR RR3; see Data availability). No participants were excluded from this study. Participants were randomly assigned to one of four experimental conditions without knowing it. Table 1 reports the stimulus for each experimental condition. Table 2 reports a randomization check.

Following treatment exposure, subjects were asked how much they believe genetics (as opposed to the environment) impacts on three features: “turning out to vote,” “intelligence,” and “natural hairstyle (curly or straight).” Items were presented in random order. Table 3 shows the eleven-point response scale. We report all measures and manipulations.

Results

Table 4 presents the results of the experiment. The first element worth noticing is that the mean genetic attribution for turnout in the control group is much higher than what one would intuitively expect, with a mean of 27.24 on a scale ranging from 0 to 100. We ran Welch t-tests to assess the impact of treatment exposure. The second column of Table 3 presents the results of comparisons between the group exposed to genopolitics (Group 2) and the control group (Group 1). The results for the turning out to vote item show evidence of a statistically significant, but substantially small persuasion effect, offering support for H1. However, although the average genetic attribution for intelligence in Group 1 is higher than in the control group, this difference is too small to reach statistical significance. Therefore, we must reject H2.

Results presented in the third column indicate that there is still a significant persuasion effect among the group exposed to the paragraph insisting on the marginal effect of a particular gene (Group 3). The fourth column presents the result of a difference in difference comparison, testing whether adding this word of caution about the marginal influence of a specific gene succeeds at moderating the persuasion effect. The results displayed in the first row of this column indicate no significant difference between the persuasion effects caused by these two paragraphs about genopolitics, thus leading us to reject H3. Considering that both H2 and H3 are rejected, it should be no surprise to find that the second row of the fourth column offers no support for H4 either. Finally, the fifth column of Table 3 suggests that, contrary to what H5 predicts, presenting a paragraph describing how genetics impacts on human physical traits is not sufficient to generate the genetic interpolation effect.

Noticeably, the results also present an unanticipated finding: compared to Group 1, Group 2 and Group 3 show lower average genetic attribution for natural hair style. The genetic interpolation hypothesis offers no explanation for this phenomenon, but something else may be at play here.

Survey satisficing occurs when respondents use strategies and cognitive shortcuts to offer a survey response without making all the efforts to ensure that the answer they give best corresponds to their opinion, their point of view or, as it is the case here, their belief¹⁴. Strength-lining is a form of satisficing that consists of picking the same answer repeatedly for different questions without differentiating between them¹⁵. A closer look at the response distribution offers reasons to believe that exposure to either of the two genopolitics treatment paragraphs demotivated some participants to offer honest answers. Indeed, in both of these groups, approximately 10% of respondents picked the same response option for our three question items; in comparison, the equivalent figures for the control group and the group exposed to the placebo treatment are 6.45% and 6.65% (pairwise differences are statistically significant at p<0.05). But crucially, most straightliners answered the middle option category (50% genetics and 50% environment) for all three questions.

Greater satisficing thus pulls the average genetic attribution response further toward the center of the scale. This unexpected finding may partly explain the surprising negative effect observed for the hair style response item. Admittedly though, it might as well partly account for the positive effect observed on the voting at election item, a positive effect that what would otherwise be assimilated to the persuasion effect.

Discussion

The main purpose of this study was to test whether exposure to a paragraph on behavior genetics can generate the genetic interpolation effect. The experimental evidence presented above offers no indication that this is the case. However, both paragraphs presenting behavior genetics findings were successful at moving reported beliefs about how much genetics impacts on the trait presented in the paragraph – here, voting at elections. Yet, a closer look at the response distribution suggests that we should not overemphasize this finding, for a part of it may be attributable to lower response quality. Furthermore, our results indicate that insisting on the small role of a particular gene fails at moderating this persuasion effect. Finally, the results suggest that making genetic causation more accessible to the mind using a placebo message does not suffice to produce the persuasion or the genetic interpolation effect.

Nevertheless, the key finding here is related to the fact that the genetic interpolation effect was not exhibited. One likely explanation for this relates to the small size of the persuasion effect, more or less 4 percentage points. For the sake of comparison, in previous experiments, participants exposed to a whole news article about genopolitics showed persuasion effects ranging between 10 and 15 percentage points⁶. With this in mind, it seems plausible to interpret this null finding as an indication that a short paragraph on behavior genetics is a treatment condition that is not strong enough to cause people to update their general belief framework about the influence of genetics.

Additional research is needed to clarify the reasons why neither the moderation hypothesis nor the counter-hypothesis were confirmed. Indeed, it remains unclear whether these hypotheses would be supported if subjects were exposed to a real, and presumably more credible, news article instead. In spite of its null finding, the present study will hopefully help orient future research investigating how people react to behavior genetics. Indeed, our results help to chart the limits of the genetic interpolation effect by showing that not every type of message about behavior genetics succeeds in triggering this side-effect.

Ethical approval

The study was approved by the Comité d’éthique de la recherche en arts et en sciences of the Université de Montréal.

Data availability

The dataset and the pollster report for this study are hosted on the Open Science Framework: DOI: 10.17605/OSF.IO/2UBP2¹⁶.