What simple trick can you use to make a statistic seem more truthful?

We are more likely to believe something is true, if it is framed in a negative way.

Hilbig (2009) performed three experiments to find whether there was a link between framing and the perceived truth of a statistic.

The first experiment was conducted as an online-survey. After providing consent and demographic information, participants were shown statistical information from the crime domain and instructed to provide a truth rating. As information, the success rate of crimes from the category of rape and aggravated sexual coercion (denoted ‘rape’ in what follows) was presented. The actual success rate (85%) was used. Half of the participants were told that 85% of attempted instances of rape were successful (negative frame), while the other half were told that 15% were unsuccessful (positive frame). All participants were then asked to judge the truth of the stated information on a 4-point scale.

The mean rating of truth from the negative frame group was significantly higher than that of the positive frame group. The second experiment replicated these results.

Following the logic of Experiment 1, the information frame was again manipulated. Thirty eight participants (30 female, aged M = 17.3, SD = .50, recruited from a high school course of introductory psychology) were randomly assigned to two groups. These were shown the actual clearance rate of rape (70%), either framed positively (70% of cases cleared) or negatively (30% of cases not cleared) and asked to judge, again on a 4-point scale, the truth of the provided statement.

Again, participants rate the statistic as more likely if it emphasised the negative.

The principal logic of [the third experiment] was again to manipulate the frame of the information presented (between participants) while holding the actual validity constant. In contrast to the previous experiments, the information was not from the crime domain but from demographics. Specifically, participants were shown the probability of a marriage to be divorced within the first 10 years which is, in Germany, about 20% (Federal Statistical Office, n.d.). Participants were randomly assigned to one of two conditions: in the positive frame, they were informed that 80% of marriages lasted 10 years or longer whereas their counterparts in the negative frame were informed that 20% of marriages were divorced within the first 10 years. Like in the previous experiments, participants rated the truth of this statement on a 4-point scale. The experiment was run using simple 1-page questionnaires dispersed to a community sample of 33 participants.

This third experiment also clearly demonstrated negativity bias. The exact results of each study are shown in the graph below.

Fig. 1. Mean truth ratings (original scale ranging from 1 to 4) for the negative vs. positive framing conditions in each of the experiments. Error bars represent one standard error of the mean.

However, this effect is not confined to estimations of truth.

First, it has been argued that negative instances are often more informative (Peeters & Czapinski, 1990) – parallel to the higher informativeness of disconfirming evidence (Leyens & Yzerbyt, 1992). So, there could be a simple direct association between valence and (perceived) veracity.

 We also tend to dwell on the negative and discuss it with each other.

 Secondly, there is evidence for increased elaboration of negative instances which has been termed ‘informational negativity effect’ (e.g. Lewicka, 1997; see also Lewicka, Czapinski, & Peeters, 1992).

Negativity bias doesn’t operate in its own, but alongside many other effects.

Finally, there is a noteworthy body of literature which confirms that more elaboration, deeper processing, and high processing motivation can increase the persuasiveness of messages (e.g. Petty and Briñol, 2008 and Shiv et al., 2004). Similarly, though investigating the realm of wishful thinking rather than negativity bias, Bar-Hillel, Budescu, and Amar (2008) showed that the causal link ‘I focus on, therefore I believe in’ (p. 283) is well-supported. Also, elaboration can increase the perceived truth of past-events, even and especially when these never happened, which has been explained as an effect of constructive processing (Kealy, Kuiper, & Klein, 2006).

Does your mind completely accept new knowledge?

No. Our childish understanding of the world lurks in our minds, even after we have learnt scientifically correct theories that refute that understanding.

The theory of knowledge restructuring tells us that once we have learnt new knowledge, the old knowledge is entirely replaced.

A number of recent findings have challenged this idea, however, by showing that early modes of thought do sometimes reemerge later in life. Alzheimer’s patients, for instance, have been shown to endorse teleological explanations for natural phenomena that typically only children endorse

Shtulman and Valcarcel (2012)

Whilst studies have shown that a child’s understanding of biology stays into adulthood, Shtulmand and Valcercel demonstrated that this phenomenon occurs across all knowledge groups.

…we compare the speed and accuracy with which adults verify two types of statements: statements whose truth-value is known to remain constant across conceptual change (e.g., “The moon revolves around the Earth,” which is true on both naïve and scientific theories of astronomical phenomena) and syntactically analogous statements whose truth-value is known to reverse across that same change (e.g., “The Earth revolves around the sun,” which is true on a scientific theory but not a naïve theory).

They predicted that “if naïve theories survive the acquisition of a mutually incompatible scientific theory, then statements whose truth-value reverse across conceptual change should cause greater cognitive conflict than statements whose truth-value remain constant, resulting in slower and less accurate verifications for those statements”

In their study, participants were asked to answer 200 true or false questions. There were twenty questions in ten different categories of knowledge.

A quarter of the statements were true on both naïve and scientific theories of the domain (“steal is denser than foam”), a quarter were false on both naïve and scientific theories (“foam is denser than brick”), a quarter were true on naïve theories but false on scientific theories (“ice is denser than water”), and a quarter were true on scientific theories but false on naïve theories (“cold pennies are denser than hot pennies”).

Table 1. The five concepts covered in each domain.

Domain	Concept
Astronomy	Planet, star, solar system, lunar phase, season
Evolution	Common ancestry, phylogeny, variation, selection, adaptation
Fractions	Addition, division, conversion, ordering, infinite density
Genetics	Heritability, chromosome, dominance, expression, mutation
Germs	Contagion, contamination, infection, sterilization, microbe
Matter	Mass, weight, density, divisibility, atom
Mechanics	Force, velocity, acceleration, momentum, gravity
Physiology	Life, death, reproduction, metabolism, kinship
Thermodynamics	Heat, heat source, heat transfer, temperature, thermal expansion
Waves	Light, color, sound, propagation, reflection

The study found that questions that were inconsistent across the naïve and scientific theories in all knowledge areas listed above were not only answered slower than those that were consistent, but they were also answered incorrectly more often as well.

When students learn scientific theories that conflicts with earlier, naïve theories, what happens to the earlier theories? Our findings suggest that naïve theories are suppressed by scientific theories but not supplanted by them.