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Rich and Easy to Deceive? The Influence of Money Priming on the Ability to Detect Deception

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Submitted:

10 May 2023

Posted:

12 May 2023

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Abstract
Based on recent popular money priming research results, which conclude that money 4 makes self-sufficient (e.g. less interest in other people), we assumed that people are less interested 5 in finding out whether others are lying or telling the truth. In a laboratory experiment, 163 students 6 (85 women, 78 men, MAge = 23.08, ranging from 18 to 36 years) were primed by actively handling 7 money (versus paper sheets). Afterwards, they classified 24 video statements as true or deceptive 8 (senders describing their most/least favorite movie), rated their classification confidence for each 9 decision and then answered control questions. Results revealed no influence of priming condition 10 on judgmental bias, classification accuracy, and classification confidence. Also the level of self-re-11 ported motivation to find out who lied or told the truth did not differ between conditions. Higher 12 motivation was correlated to higher classification confidence. Additionally, and in line with Rein-13 hard (2010) and Reinhard et al. (2011), higher classification accuracy correlated to a higher use of 14 verbal content cues for classification decisions. So, while we were able to replicate these findings, 15 our results contradict the assumption of a money prime influence on lie detection ability. Conclud-16 ing, our results make self-sufficiency in this context questionable and offer next steps for research.
Keywords: 
Subject: Social Sciences  -   Psychology

1. Introduction

“Money makes people self-sufficient”, a discussed assumption based on results of the pioneer research by Vohs and colleagues about the influence of a money prime on social orientation [1]. They define self-sufficiency “as an insulated state wherein people put forth effort to attain personal goals and prefer to be separate from others” [1] (p. 1). The results of nine experiments, that varied the type of the money prime and the type of the dependent variable, supported their assumption. They primed with descrambling tasks, reading an essay in front of a video camera, playing monopoly, having play money, imagination, looking at a screensaver or a poster. The dependent measures for self-sufficiency varied from persistence on the problem before asking for help (time), or volunteering for help (number of solutions), donating money, or sitting with someone (distance between the chairs), to preference for activities alone vs. together (survey) [2,3,4]. Another pro argument for self-sufficiency under priming with money follows the results by [5] on Chinese participants that let suggest an instrumentality orientation in social interactions (Experiment 1 and 2). In Experiment 1, the money prime manipulation was facilitated by a picture evaluation task, and the dependent variable was measured with a 20-item objectification scale (see also [6]). Objectification was significantly higher in the money prime condition than for the control group. In Experiment 2, a sentence-descrambling task was utilized as the money prime. After the money prime manipulation, a goal for the participants was set. They were instructed to complete a task that requires mathematics skills and logical thinking. Then participants red a profile of an anonymous student. Depending on the condition, that student was described as majoring in math, being a fan of math, and planning to become a financial analyst after graduation (instrumental) or as majoring in Chinese, loving to read and write, and planning to become a writer after graduation (non-instrumental). Next, the approach intention of the participants was measured by asking for to what extent they would choose the student as their work partner on the mathematical task, feel good about the student and make friends with the student. The measurement of the perceived instrumentality followed with two items, measuring how much the student could help on the task and how useful the student is. Under the money prime, approach intention was increased when the perceived instrumentality was high. The effect did not occur under high competence of achieving a goal self-employed (Experiment 3). In Experiment 3, participants got feedback about their Sudoku achievement (manipulation of the competence for achieving a goal self-employed by different benchmarks) and were asked to collaborate for a next Sudoku with an anonymous student described as being good in math. Therefore, under the money prime, people seem interested in others only when they need them to reach an own goal. In accordance, people also seem to be less distressed about social exclusion under the money prime [7], what refers to independence and self-sufficiency.
Beside the effect of the competence of achieving a goal self-employed on the outcomes of being primed with money, there also exists research regarding the feeling of socioeconomic status. [8] found that especially in the money prime condition, the feeling of a high economic status led to justifying the existing socioeconomic system (USA) more strongly (Study 1), and people believed more in the justness of its social outcomes (Study 2). In both studies, the authors used a word-descrambling task as money priming method and measured the socio economic status with the Mac Arthur Scale of subjective SES [9]. In Study 1, an 8-item System Justification Scale [10,11] was conducted as the dependent measure. In Study 2, the dependent variable was measured with the 20-item Belief in a Just World Scale [12]. So, money primed persons seem to be more trustful when a feeling of higher economic status is activated and therefore could rather fall for deception. In line with our reasoning, a new study also developed theoretical arguments that power (inducible by money) could be correlated to less deception detection [13]. To sum up, under the money prime, subjects show less interest in others, what others do, how they feel (self-sufficiency) and trust more; following, less interest whether others tell the truth or lie is assumable.

1.1. Deception Detection in Everyday Life

In general, humans tend to have a low ability to detect deception. Overall, we are slightly above chance level in the accuracy of judgments about veracity of true or invented statements [14,15,16]. Further, based on meta-analysis results by [14], people seem to be more accurate in identifying the truth as non-deceptive than lies as deceptive (Truth Bias). Research showed that neither education, sex, age, nor confidence are significantly related to accuracy of truth and lie classification [17]. Nevertheless, using verbal cues in contrast to nonverbal cues for the classification decision as true or lied can enhance the accuracy rate [14]. In line with this, [18] tested the theoretical assumption that high task involvement (Experiment 1) and high cognitive capacity increase the use of verbal (therefore content) information in credibility judgments (Experiment 2 and 3). Based on research findings regarding what kind of verbal and nonverbal cues people use to evaluate the credibility of a statement [19,20,21,22,23,24,25], the authors manipulated four versions of a short film about a social interaction between two persons (same film in Experiment 1 and 2, another version in Experiment 3). One person was able to be seen, the other person just could be heard. Four versions were created: Deceptive verbal and deceptive nonverbal vs. deceptive verbal and truthful nonverbal vs. truthful verbal and truthful nonverbal vs. truthful verbal and deceptive verbal behavior. Participants were assigned to one of these conditions. Beforehand, in Experiment 1, task involvement was manipulated by the information on how important the participation was for science (high vs. not, between-subjects). In the high-involvement condition, participants differentiated between the deceptive and non-deceptive cues for their credibility judgment (higher credibility for non-deceptive cues and lower for deceptive cues), while in the low-involvement condition, there was no differentiation. In Experiment 2 and 3, the authors manipulated cognitive load by assigning the participants either to a distracting task (high cognitive load) or no task (low cognitive load) before watching the videos. In both experiments, while nonverbal cues were used under high cognitive load, the verbal cues were only used by individuals with low cognitive load, and so higher cognitive capacity. Moreover, in Experiment 3, the authors additionally asked for reasons for the credibility judgments; their analysis yielded results in line with the assumption that participants in the low cognitive load condition used mainly verbal cues.
Accordingly, in following studies, the authors further confirmed that the use of verbal cues was correlated to higher lie detection accuracy [26,27]. To summarize, using verbal cues (that automatically focus on the content compared to nonverbal cues) predicts better deception detection accuracy. People use these verbal cues more often when they are highly involved in the detection task and expend their cognition. When people are less interested in others (self-sufficient), they should show less task involvement and so, according to dual process theories, use effortless ways (nonverbal behavior) to arrive at a judgment [28,29]. Combining these arguments, we hypothesized that the money prime decreases classification accuracy of truths and lies concerning other peoples’ statements.

2. Materials and Methods

2.1. Participants

A total of 163 students from the University of Mannheim participated in the study. A bar of chocolate and the possibility to win a game console were offered as incentives. The age of the participants ranged from 18 to 36 years (MAge = 23.09, SDAge = 4.14); two participants did not report their age. 85 women (52.15%) and 78 men (47.85%) participated.

2.2. Design and Conditions

We tested our hypothesis with a 2 (Prime: Money vs. Paper) x 2 (Message type: Truth vs. Lie) Mixed-Methods-Design in a laboratory experiment, with prime and set of the messages as between-subject factors and message type as within-subject factor. In reference to [17], we included the variables gender and classification confidence to our analysis and according to [30] also the control variable set of the messages.
A sensitivity power analysis (G*Power; [30]) for the given sample size of N = 163 (Manova: Repeated measures, between factors; correlation between repeated measures of r = .039, α = .05) showed that a minimum effect size of Cohen’s d = 0.32 could be detected with a power of 80%.

2.3. Procedure and Stimuli

As first, we thanked for the participation and instructed the participants that the study investigates the ability to recognize deception and truth. An informed consent followed. Afterwards, participants were randomized to one of two priming conditions (between-subjects, Money vs. Paper). For the money prime, we used the method of actively handling money due to it yielding the largest money priming effects (see meta-analysis by [31]). Participants were instructed to assess the value of the banknotes that were presented filled in a jar. For two times, they were instructed to grab into the jar and touch the banknotes. After the first time, they wrote down the estimated value. After the second time, they wrote down the estimated number of bank notes. For the control group (paper prime condition), instead of money (banknotes), participants were now presented a jar filled with paper sheets, same procedure. Here, in the first task, participants were instructed to estimate the weight of the paper sheets (by touching it). The next step of the experiment followed on the monitor (see Appendix A). After the task, participants were asked for demographics.

2.4.1. Stimulus Material

Due to us wanting to present a scenario that is basic for social interactions without offering an instrumentality [5], we used videos about a personal statement regarding an individual attitude as stimulus material. The material was taken from a study by [26] (Experiment 3): 36 female and 36 male students from the University of Mannheim were filmed, so that the head and upper body was to be seen, while for about one minute describing a movie they liked or disliked. In the truth condition, they actually liked or disliked the described movie. In the lie condition they stated to like (or dislike) the described movie when they actually disliked (or liked) it. All participants were instructed to make a statement as truthful as possible. They could receive an extra reward of five Euros if the interviewer (blind to the experimental conditions) believed that they indeed liked or disliked the movie. In accordance to [26], we created three sets with 24 messages (see also [30]). Each set contained 12 truthful and 12 deceptive messages (balanced valence of senders’ attitudes and gender, no difference in video length across conditions).

2.4.2. Deception Detection Task

Participants were instructed that out of 24 videos of students that talk about films that they like and that they do not like, they have to evaluate who is telling the truth and who is lying. The videos were shown one after another. After each video, participants gave their judgment if the report was true or lied. As a control variable according to [17], they then rated via a percentage scale (from 0% = not at all sure to 100% = completely sure) their decision confidence on the next page. Next, we measured how motivated the participants were in finding out who was telling the truth and who was lying with four items (Cronbach’s α = .72; “It was important to me not to judge people who tell the truth as liars”, “It was important to me not to overlook people who are lying.”, “It was important to me to properly assess people who tell the truth”, “It was important to me to recognize liars as such”) which were assessed on a 7-point scale (from 1 = does not apply at all to 7 = applies exactly). Parallel to [26,27], we also asked, if participants used more verbal or nonverbal behavior for their classification decision as true or deceptive with two items (Cronbach’s α = .85; “I based my judgment more on …” “In watching the messages, I tended to pay more attention to …”; scale from 1 = nonverbal behaviour to 7 = verbal content). As last, demographic data was collected.

3. Results

3.1. Judgmental Bias

Overall, participants judged 52.30% (SD = 11.53%) of the video-statements as true. This differed with a small effect size from 50%, t(162) = 2.55, p = .012, 95% CI [0.52, 4.08], dCohen = 0.20, resulting in a truth bias. An one-way ANOVA with priming condition (Money vs. Paper) as independent variable and number of truth judgments as dependent variable revealed no effect of prime condition, F(2, 161) = 1.88, p = .172, ηp2 = .01, 95% CIpaper prime [-6.03, 1.09] (see also Table 1). So, the participants’ classification decision regarding the messages as true or deceptive did not depend on the priming condition. An additional univariate analysis of variance revealed no main effect of gender of the judges on judgmental bias. Further, no interaction with the priming condition was found, and also no interaction between set of the messages and priming condition (see Appendix B).

3.2. Classifcation Accuracy

The overall classification accuracy of 55.78% (SD = 10.72%) differed with a medium effect size from chance level (50%), t(162) = 6.88, p < .001 , 95% CI [4.12, 7.44], dCohen = 0.54. True statements were classified more accurate (M = 58.08%, SD = 53.48%) with a small effect size than false statements (M = 53.48%, SD = 17.97%), F(1, 162) = 6.49, p = .012, ηp2 = .04. To test our hypothesis, a 2 (Prime: Money vs. Paper) x 2 (Message type: Truth vs. Lie deceptive) mixed-design ANOVA with classification accuracy (in %) as the dependent variable was run. Against our hypothesis, analysis revealed no effect of priming condition, F(2, 161) = 0.10, p = .758, ηp2 = .00, 95% CIpaper prime [-2.81, 3.85], so the money prime did not decrease classification accuracy compared to the paper prime (see also Table 1). An additional univariate analysis of variance revealed no significant main effect of gender of the judges and no significant interaction with priming condition, further no significant interaction between set of the messages and priming condition (see Appendix B).

3.3. Classification Confidence

Overall classification confidence was M = 70.23% (SD = 12.43%). Confidence ratings regarding true statements (M = 70.80%, SD = 13.10%) did not differ to confidence ratings regarding false statements (M = 69.67%, SD = 13.15%), F(1, 162) = 2.96, p = .087, ηp2 = .02. A 2 (Prime: Money vs. Paper) x 2 (Message type: Truth vs. Lie) mixed-design ANOVA with classification confidence (in %) as the dependent variable was run. No effect of priming condition on classification confidence was found, F(1, 162) = 0.28, p = .595, ηp2 = .00, 95% CIpaper prime [-4.90, 2.82] (see also Table 1). An additional univariate analysis of variance revealed no main effect of gender of the judges and no interaction with priming condition, and further no interaction between set of the messages and priming condition (see Appendix B).

3.4. Self-Reported Task Motivation

In an univariate ANOVA with priming condition as independent variable and self-reported motivation as the dependent variable, there was no main effect of money prime, F(2, 161) = 0.37, p = .546, ηp2 = .00, 95% CIpaper prime [4.80, 5.31]. Against our assumption, participants in the money prime condition did not report less motivation (M = 5.05, SD = 1.18) compared to participants in the paper prime condition (M = 4.94, SD = 1.15). Further, neither the judgmental bias, r = .03, p = .715, nor classification accuracy, r = .07, p = .367 was correlated to motivation. However, higher classification confidence was correlated to higher self-reported motivation to correctly classify the statements as true or lied, r = .21, p = .007.

3.5. Self-Reported Use of Verbal Content Versus Nonverbal Information

In an univariate ANOVA with prime condition as independent variable and self-reported use of nonverbal versus verbal content information as the dependent variable, no main effect of money prime was found, F(2, 161) = 1.78, p = .184, ηp2 = .01, 95% CIpaper prime [-0.15, 0.75]. In contrast to our assumption, participants in the money prime condition did not report significantly less use of verbal content information (M = 3.53, SD = 1.38) than did participants in the paper prime condition (M = 4.04, SD = 1.51). Judgmental bias was not correlated to verbal content use, r = .01, p = .907. In line with the findings of [26] and [27], classification accuracy was correlated low with self-reported use of verbal content versus nonverbal information, r = .16, p = .039. Higher classification accuracy was low correlated to more self-reported use of verbal content. The negative correlation between classification confidence and verbal content use was only small, r = -.10, p = .196.

4. Discussion

In this study, we hypothesized that people are less accurate in their classification accuracy of video-messages as true or deceptive under a money prime compared to a neutral prime (paper). While the participants’ overall accuracy (of 55.78%) was a medium effect sized better than chance (see also [14]), our results did not support our hypothesis; the classification accuracy did not depend on the priming condition. We found a small effect that true statements were classified accurately more often than lied statements, which might be caused by a small judgmental bias. In line with the meta-analysis results by [17], classification accuracy was also not influenced by the control variable gender (just as judgmental bias and classification confidence). The overall classification confidence was 70.23%.
We investigated our research question in a laboratory experimental study with the money priming method that recently offered the highest self-sufficiency effects, actively handling money [32]. Furthermore, we presented 24 stimuli to each person (3 sets), [30] showed that with a minimum of 20 stimuli, the classification accuracy measurement becomes valid. Respectively, we found no interaction between set of the messages and priming condition, for neither the judgmental bias, the classification accuracy, nor the classification confidence. While our method was appropriate, we did not find an effect regarding our assumption.

4.1. Limitations

One could argue that the money prime manipulation did not work, no manipulation check was assessed. Nevertheless, also without a manipulation check, we could have found effects if they actually existed; in the research of the pioneer paper by [1], no manipulation checks are reported as well. Also the available research papers listed in the meta-analysis by [32], with the priming method actively handling money, did not check for an effective manipulation. Moreover, the results of our control questions revealed that priming with money did not lead to less motivation and less use of (the more valid) verbal content information. So, the assumed lower interest in detecting lies of others about a personal theme caused by a money prime was not displayed in the results of our control questions. One could argue, due to this, no priming effect on classification accuracy was shown. However, these findings implicate that the priming had no effect: In the theoretical background, we just assumed lower ratings in the control questions when the money prime actually influences classification accuracy. Otherwise, deception detection would mean a separate paradigm with which it is not possible to display “self-sufficiency” which can be found with other dependent measures. Based on people showing low deception detection ability in general [14,15,16] and our sensitivity analysis presuming an effect size of minimum Cohen’s d = 0.32, it is possible that the effect actually exists but was too small to be found with our sample size of 163 participants. Nevertheless, the results of our control questions showed an increased classification accuracy by more use of verbal content cues than nonverbal cues for participants’ classification decision. Further, high motivation in finding out who was telling the truth and who was lying led to an increase in classification confidence, both independently from the priming condition.
An indirect argument for the nonexistence of an effect of money priming on deception detection are the results by [13] that exposed an increase in deception detection under power (asymmetric control over valued resources in social relationships, see [33]). Money implicates having power, being independent from others and, as explained before, seems to let people interact with others only when it is needed to instrumentalize them for reaching an own goal [5]. However, [13] found in their experiments that having power over others enhanced the accuracy of one’s veracity assessment. In line, we did not find a decrease of classification accuracy by money priming in the recent study. In accordance and in contrast to the findings by [5] (Experiment 3), [34] revealed that enhancing self-affirmation (by writing an essay explaining why the participant’s core value is personally important) weakened the influence of money priming on self-sufficiency regarding different dependent measures; such as donating more money under high self-affirmation, being more likely to request help, choosing more leisure experiences to be shared with others (versus individually focused ones) and feeling distressed after social exclusion (Cyberball; [35]).
Recent research by [36] suggested that the consequences effected by priming with money depended on the constitution of the bank note, in detail if it is an unused new one versus used one. A new banknote enhanced feelings of empathy regarding co-workers (Study 2) and decreased self-serving behavior compared to a used one and a general money priming (without information of the newness, Study 3). Further, priming with new money led to perceived stronger norms of social conscientiousness and higher helping intentions (Study 4). The authors conclude, priming with new money induces peoples’ warmth (prosocial behavior). These findings, the meta-analysis by [31] and the results of the present study display the assumption that money priming makes self-sufficient as quiet questionable.

4.2. Future Research

At first, in further research, manipulation checks should be accessed. According to [5], a possible manipulation check for a primed mindset could be the participants’ indication of their positivity toward words related to the prime, here money, compared to neutral words. Investigations on the information processing level depending on money priming seem to be essential as well. If a money prime makes self-sufficient (therefore being less interested in others, and based on dual-process theories [28,29], one could argue that these participants show lower motivation and so a lower level of attention regarding various social measures. To find out how the process level functions, distraction and time pressure are variables that could be manipulated, counterbalanced in both priming conditions.
Also a different operationalization for being primed with money when wanting to answer if money makes self-sufficient than actively holding it (and estimating its value) could be something to focus on in further research. For example, the influence of the present socio-economic status and how satisfied the participants are with it on lie detection ability could reveal other effects than those found in the current study. Another variable that might offer some new insights is emotional intelligence. [37] showed in their research that high scoring emotionally intelligent people rather figured out mismatches between facial expression (nonverbal behavior) and verbal content information of the lying or the truth telling senders. Nevertheless, a good liar could even control facial expressions or body movements. As explained in the introduction, nonverbal cues seem not connected to a better classification accuracy [26,27]. In line, while [38] found that emotional intelligence leads to a higher use of nonverbal cues, deception detection was not heightened; emotional intelligence rather seems to lead to an overestimation of the own lie detection ability [39]. [40] concluded that the aspect “perception of emotion” of emotional intelligence supported the deception detection. Moreover, based on findings by [41] that indicate a money priming effect on increased lying and cheating, further research not only regarding deception detection ability but also the actual lying behavior seems to be plausible.

Supplementary Materials

The following supporting information can be downloaded at: https://osf.io/zbu8f, Appendix A, Appendix B.

Author Contributions

Research idea und theoretical hypotheses: Main contribution by the second author and additional contribution by the first author. Development of material and data collection: Full contribution by the second author. Data analysis: First and second author made equal contribution. Discussion: Main contribution by the first author and additional contribution by the second author.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in full accordance with the Ethical Guidelines of the German Association of Psychologists (DGPs) and the American Psychological Association (APA). Moreover, by the time the data were acquired it was also not customary at University of Mannheim, nor at most other German universities, to seek ethics approval for simple studies on lie detection ability. Therefore, ethical approval was not required for this study in accordance with the national and institutional guidelines. The study exclusively makes use of anonymous questionnaires. No identifying information was obtained from participants. Every participant had to read (and agree to) an informed consent. They were thereby explicitly informed that all data are treated confidentially and that they may withdraw from the study at any time without giving explanation. Contact information of the researchers was available from the beginning of the study until the end.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data is available on demand, https://osf.io/sa9w7/.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

A.1. Instruction Money Prime Condition (Presented on a Printed Paper Sheet)

Task 1:
In the following we would like to ask you to do an estimation task. The experimenter will show you a jar filled with bank notes.
Please estimate the value of the bank notes.
Studies show that the ability to estimate improves when the goods to be estimated can be touched. Therefore, please reach into the glass to touch the bank notes.
Now please go to the experimenter and reach into the jar.
Write down the estimated value of the bank notes:
Task 2:
Please estimate the number of bank notes.
Please reach into the glass again to enable a more accurate estimate.
Now please go to the experimenter and reach into the jar.
Write down the estimated number of bank notes:
WHEN YOU ARE FINISHED, PLEASE CONTACT THE EXPERIMENTER SO THEY CAN ASSIGN YOU TO A PC!

A.2 Instruction Paper Prime Condition (Presented on a Printed Paper Sheet)

Task 1:
In the following we would like to ask you to do an estimation task. The experimenter will show you a jar filled with paper sheets.
Please estimate the weight of the paper sheets.
Studies show that the ability to estimate improves when the goods to be estimated can be touched. So, to give you a more accurate estimate, you are allowed to put your hands inside the jar.
Now please go to the experimenter and reach into the jar.
Write down the estimated weight of the paper sheets:
Task 2:
Please estimate the number of the paper sheets.
To give you a more accurate guess, you may put your hand in the jar again.
Now please go to the experimenter and reach into the jar.
Write down the estimated number of leaves:
WHEN YOU ARE FINISHED, PLEASE CONTACT THE EXPERIMENTER SO THEY CAN ASSIGN YOU TO A PC!

Appendix B

B.1. Supplementary Material, Additional Analysis

B.1.1. Judgmental Bias

No significant influence of the control variable gender on judgmental bias was found, F(1, 162) = 0.27, p = .603, ηp2 = .00, 95% CIfemale [-8.41, 8.21]. Gender and prime condition did not interact significantly, F(1, 162) = 1.27, p = .261, ηp2 = .01. Unexpectedly, analysis yielded a significant main effect for the control variable set of messages, F(2, 161) = 14.38, p < .001, ηp2 = .16 (set 1: M = 56.85%, SD = 11.55%; set 2: M = 45.41%, SD = 9.09%; set 3: M = 53.56%, SD = 10.71%), 95% CIset 1 [-9.95, 8.28], 95% CIset 2 [-12.49, 5.05]. However, there was no significant interaction between prime condition and set of messages on judgmental bias, F(1, 162) = 0.77, p = .465, ηp2 = .01. No significant three-way interaction was found, F(2, 161) = 0.70, p = .501, ηp2 = .01 (see also Table A).

B.1.2. Classification Accuracy

Further, the analysis yielded no significant effect for the control variable gender on classification accuracy, F(1, 162) = 3.48, p = .064, ηp2 = .02, 95% CIfemale [-4.38, 10.66].
Gender and prime condition did not interact significantly, F(1, 162) = 0.32, p = .570, ηp2 = .00. Unexpectedly, a significant main effect of the control variable set of statements on classification accuracy was shown, F(2, 161) = 21.87, p < .001, ηp2 = .23, 95% CIset 1 [-5.44, 11.05], 95% CIset 2 [7.83, 23.71]. We found no significant interaction between prime condition and set of messages on classification accuracy, F(2, 161) = 1.87, p = .158, ηp2 = .02. There was no significant three-way interaction, F(2, 161) = 1.21, p = .302, ηp2 = .02 (see also Table A).

B.1.3. Classification Confidence

Further, for the control variable gender, no significant effect on classification confidence was found, F(1, 162) = 0.32, p = .575, ηp2 = .00, 95% CIfemale [-12.78, 7.01]. Further, no significant interaction between gender and prime condition emerged, F(1, 162) = 0.59, p = .444, ηp2 = .00. There was also no significant effect for the control variable set of messages on classification confidence, F(2, 161) = 0.08, p = .926, ηp2 = .00, 95% CIset 1 [-12.64, 9.06], 95% CIset 2 [-15.51, 5.38]. In line, analysis further yielded no significant interaction between prime condition and set of messages on classification confidence, F(2, 161) = 1.81, p = .167, ηp2 = .02. No significant three-way interaction was found, F(2, 161) = 0.93, p = .396, ηp2 = .01 (see also Table A).
Variable Main effect
(gender) 		Interaction
(gender x prime)
F(1, 161) ηp2 F(1, 161) ηp2
Truth bias 2.40 .02 1.85 .01
Classification accuracy
Overall 0.37 .00 0.13 .00
True messages 3.48 .02 2.22 .01
Deceptive messages 0.38 .00 0.42 .00
Classification confidence
Overall 0.33 .00 0.20 .00
True messages 0.77 .01 0.00 .00
Deceptive messages 0.04 .00 0.75 .01

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Table 1. Means, standard deviations, and one-way analyses of variance for truth bias, classification accuracy, and classification confidence depending on treatment manipulation (bank notes vs. paper sheets).
Table 1. Means, standard deviations, and one-way analyses of variance for truth bias, classification accuracy, and classification confidence depending on treatment manipulation (bank notes vs. paper sheets).
Variable Money prime Paper prime F(1, 162) ηp2
M SD M SD
Truth bias 53.51% 10.56% 51.04% 12.39% 1.88 .01
Classification accuracy
Overall
55.52% 11.05% 56.04% 10.44% 1.00 .00
True messages
Deceptive messages		 59.04% 13.09% 57.08% 13.20% 0.90 .01
52.01% 17.20% 55.00% 18.73% 1.13 .01
Classification confidence
Overall
True messages
Deceptive messages		 70.74% 9.43% 69.70% 14.97% 0.28 .00
70.53% 10.32% 68.77% 15.57% 0.73 .00
70.96% 10.53% 70.63% 15.39% 0.03 .00
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