Easy on the mind, easy on the wrongdoer? No evidence for perceptual fluency effects on moral wrongness ratings

Cognition 196 (2020) 104156

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Easy on the mind, easy on the wrongdoer? No evidence for perceptual fluency effects on moral wrongness ratings

T

Lena Nadarevica, , Meike Kroneisena,b ⁎

a b

Universität Mannheim, Germany Universität Koblenz-Landau, Germany

ARTICLE INFO

ABSTRACT

Keywords: Perceptual fluency Moral judgment Moral transgression Negative emotions

Processing fluency—the subjective ease of information processing—influences a variety of judgments (e.g., judgments of familiarity, liking, and truth). A study by Laham, Alter, and Goodwin (2009) suggests that this is also true for moral judgments. More specifically, the authors found that discrepant perceptual fluency mitigates moral wrongness ratings. In five studies (total N = 694), we tested the replicability of this finding for different kinds of scenarios (moral versus conventional transgressions) and different perceptual fluency manipulations. In Studies 1a and 1b we manipulated fluency by text background, in Studies 2a and 2b by font type, and in Study 3 by word spaces. Critically, none of the studies replicated Laham et al.'s discrepant fluency effect on moral wrongness ratings. In turn, we found that moral wrongness ratings were strongly affected by participants' emotional responses to the scenarios. Taken together, the findings of our five studies cast very strong doubt on perceptual fluency effects on moral judgments.

1. Introduction There are many different definitions of morality in the literature. For example, according to Rest (as cited by Krebs & Denton, 2005, p. 641) morality consists in “standards or guidelines that govern human cooperation—in particular how rights, duties, and benefits are [to be] allocated.” Another prominent definition of morality stems from Piaget (1932/1997, p. 13) who stated that “all morality consists in a system of rules, and the essence of all morality is to be sought for in the respect which the individual acquires for these rules.” Thus, both definitions describe morality as a set of social guidelines or rules. However, this does not mean that the reverse conclusion (i.e., all social rules are moral) holds as well. The social-cognitive domain theory (Nucci & Turiel, 1978; see Smetana, 2006, for a review) distinguishes between social-conventional rules and moral rules. Specifically, the theory proposes that social-conventional rules are based on principles of authority (e.g., show filial piety), tradition (e.g., marry before having a baby), and social norms (e.g., shake hands when you meet someone) and thus are alterable as well as context-dependent. By contrast, moral rules are characterized as objective, obligatory, as well as universally applicable rules which specifically refer to the principles of welfare (e.g., do not harm other people) and justice (e.g., treat others with respect and fairness). In the following work, we aimed at investigating whether judgments of conventional transgressions (i.e. violations of social norms) and ⁎

moral transgressions (i.e. harmful or unfair actions) are influenced by meta-cognitive feelings. In particular, we were interested in the effect of processing fluency—the subjective ease of information processing—on moral judgments. However, before elaborating on this research question in further detail, we will first give a brief, general overview on moral judgments. 1.1. Moral judgments One way to investigate moral judgments is to present participants with dilemmas that describe a conflict between different moral rules or principles, respectively. For example, when presented with the classical Heinz dilemma (Kohlberg, 1984), participants are asked to judge whether they think that Heinz should steal an overpriced medication in order to save his wife's life. Thus, the dilemma reflects the conflict between the obligation to save a life on the one hand and the obligation to respect the law on the other hand. According to a rationalist perspective, judgments on such moral dilemmas are the result of reasoning and reflection processes which are contingent on a person's stage of moral development (see Kohlberg, 1984; Piaget, 1932/1997). However, empirical evidence shows that moral judgments are also affected by context variables such as the personal relevance of the dilemma (Wark & Krebs, 1996), the audience (Carpendale & Krebs, 1992), and timepressure at the time of judgment (Suter & Hertwig, 2011). Moreover,

Corresponding author at: Department of Psychology, School of Social Sciences, University of Mannheim, D-68131 Mannheim, Germany. E-mail address: [email protected] (L. Nadarevic).

https://doi.org/10.1016/j.cognition.2019.104156 Received 21 November 2018; Received in revised form 2 December 2019; Accepted 9 December 2019 0010-0277/ © 2019 Elsevier B.V. All rights reserved.

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other studies highlight the role of affect and emotions on moral judgments (e.g., Haidt, Koller, & Dias, 1993; Rozin, Lowery, Imada, & Haidt, 1999; Schnall, Haidt, Clore, & Jordan, 2008; Strohminger, Lewis, & Meyer, 2011; Valdesolo & DeSteno, 2006). Taken together, the malleability of moral judgments by contextual variables and emotions challenges a purely rationalist model of moral judgments. Unlike rationalist models, the social intuitionist model (Haidt, 2001) proposes that moral judgments are determined by moral intuitions in the first place. Specifically, Haidt (2001, p. 818) defines moral intuition as “the sudden appearance in consciousness of a moral judgment, including an affective valence (good-bad, like-dislike), without any conscious awareness of having gone through steps of searching, weighing evidence, or inferring a conclusion.” For example, Haidt and colleagues (Haidt, Bjorklund, & Murphy, 2000; Haidt & Hersh, 2001) found that participants judged offensive but harmless behaviors as morally wrong even though they could not provide rational reasons for their judgment. The social intuitionist model thus assumes that moral judgments are based on people's gut feelings (e.g., emotions and affective experiences) and that verbalized arguments are merely retrospective justifications of people's moral intuitions.

Importantly, the scenario was either printed in an easy to read font (fluent condition) or a difficult to read font (disfluent condition). The authors found that participants with siblings of the opposite-sex experienced more discomfort and shame in the disfluent font condition as compared to the fluent font condition. However, unlike Laham and colleagues, they did not find an effect of processing fluency on moral wrongness ratings. A potential explanation of this null-effect might be the lack of fluency discrepancy. That is, because fluency was manipulated between groups, participants did not experience a change of processing fluency. Finally, a recently published study (Spears, Fernández-Linsenbarth, Okan, Ruz, & González, 2018) examined whether perceptual fluency affects judgments about moral dilemmas that contrast a utilitarian choice (e.g., sacrificing someone in order to save a larger number of lives) with a deontological choice (e.g., not sacrificing anyone, although this means a greater loss of lives). Perceptual fluency was manipulated by presenting the first three dilemmas in an easy-to-read font and the last three in a difficult-to-read font, or vice versa. Spears et al. (2018) found that the disfluent font increased the acceptability of the utilitarian choice compared to the fluent font. Based on the dual-process theory of moral judgments (Greene, Sommerville, Nystrom, Darley, & Cohen, 2001) and the assumption that disfluency triggers analytic thinking (Alter, Oppenheimer, Epley, & Eyre, 2007), the authors reasoned that perceptual disfluency raises people's tendency to overcome their deontological, intuitive response in favor of a more rational, utilitarian response. However, there are studies that failed to support the assumed perceptual disfluency effect on analytic thinking (Meyer et al., 2015) or found it to be restricted to people of high cognitive ability (Thompson et al., 2013). Based on findings suggesting that “people are more likely to interpret the world abstractly when they experience cognitive disfluency” (Alter & Oppenheimer, 2008, p. 161), Spears et al. also offered an alternative interpretation of their findings. They reasoned that the presumably more abstract mental representation of disfluent dilemmas makes people focus less on the concrete action (e.g., sacrificing one life) and more on the desirable consequences of the action (e.g. saving several lives). But the authors did not test the proposed mechanisms. In view of the divergent findings between the outlined studies, the role of processing fluency in moral judgments is by no means clear. What complicates matters is that the three studies are not directly comparable. For instance, Spears et al. (2018) examined (dis)fluency effects on the acceptability of utilitarian choices, whereas the other two studies investigated such effects on moral wrongness ratings for conventional transgressions (e.g., offensive but harmless actions). Importantly, none of the studies investigated evaluations of clear moral transgressions (e.g., intentionally harmful or unfair actions). In fact, Laham et al. (2009) acknowledged this limitation and hypothesized that their findings should also generalize to moral transgressions. However, this prediction has never been tested empirically. Likewise, it is also unclear if the different findings of Laham et al. and Merritt and Monin (2011) relate to the different types of fluency manipulations (text-background contrast versus font type), or other procedural differences (e.g., fluency discrepancy or no such discrepancy). Based on the foundational study of Laham et al. (2009), our work aimed at providing clarification regarding the influence of processing fluency on moral judgments. Specifically, we conducted five studies that investigated three different perceptual fluency manipulations on moral wrongness ratings for moral transgressions (Studies 1a, 2a, and 3) and conventional transgressions (Studies 1b and 2b). The sample size of Laham et al. was set as the minimum sample size for our studies. Moreover, based on our final sample sizes, we conducted sensitivity analyses with G*Power (Faul, Erdfelder, Lang, & Buchner, 2007) for the critical fluency condition by scenario position interaction test. These analyses indicated that our least powerful interaction test (Study 2a,

1.2. Processing fluency and moral judgments One feeling that serves as an intuitive cue in many judgment domains is processing fluency—the feeling of ease with which information is processed (see Alter & Oppenheimer, 2009, for a review). For instance, processing fluency increases familiarity judgments (Whittlesea, 1993), preference judgments (Reber, Winkielman, & Schwarz, 1998), truth judgments (Reber & Schwarz, 1999), and judgments of learning (Undorf & Erdfelder, 2015). Hence, it is possible that processing fluency also influences moral intuitions and moral judgments, respectively. However, to our knowledge, there are currently only three studies that have investigated a possible link between processing fluency and moral judgments. In the following, we will describe these studies in further detail. Laham, Alter, and Goodwin (2009) handed participants a paperpencil questionnaire with six short scenarios, most of which described violations of social conventions (e.g., a brother and a sister kissing passionately). The participants' task was to provide moral wrongness ratings for the described behaviors. Three scenarios were printed per page in black ink. Importantly, one page had a white background so that the scenarios were easy to read (fluent condition), whereas the other page had a gray speckled background so that the scenarios were difficult to read (disfluent condition). The order of this background manipulation (fluent condition first vs. disfluent condition first) was manipulated between participants as was the position of three critical scenarios within the questionnaire (position 3 vs. position 4 vs. position 6). Importantly, all three critical scenarios described violations of social conventions. The result of Laham et al. revealed the following interaction effect of background manipulation and scenario position on moral wrongness ratings for the scenarios at interest: Page background only affected participants' ratings at position 4, i.e., the first rating after the background change. This finding suggests that discrepant fluency (e.g., Hansen, Dechêne, & Wänke, 2008; Whittlesea & Williams, 2001) rather than fluency per se affects moral judgments. Specifically, moral wrongness ratings were less harsh in case of discrepant fluency (i.e. after flipping from the speckled background to the white background) as compared to discrepant disfluency (i.e. after flipping from the white background to the speckled background). Laham et al. interpreted the direction of this fluency effect in light of a fluency-induced positive affect (Reber et al., 1998; Reber, Schwarz, & Winkielman, 2004). Merritt and Monin (2011) reported a study in which they presented participants the “sibling” scenario of Haidt (2001) that describes a brother and sister making love without any negative consequences.

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n = 106) was sensitive enough to detect an effect of f = 0.20 with a power of 0.95 (input parameters: α = 0.05, 1-ß = 0.95, ρ = 0.18).1 According to Cohen's (1988) conventions, this effect corresponds to a small to medium-sized effect. Thus, our sample sizes were sufficient to reliably detect smaller interaction effects than the one reported by Laham and colleagues (f = 0.25). For all studies we report all measures, conditions, and data exclusions. The materials and data of all studies are publicly available online at the Open Science Framework (https:// osf.io/cwf9s/).

scenarios were counterbalanced across the questionnaire positions of interest (i.e., positions 3, 4, and 6). Comparing moral judgments for these positions was crucial to test the effect of fluency discrepancy (rather than fluency per se) on moral judgments (positions 3 and 6: no fluency discrepancy; position 4: fluency discrepancy). Importantly, all critical scenarios in the current study described behaviors violating the justice principle and thus described true moral transgressions. In contrast, the filler scenarios, which were not of central interest, always appeared at the same questionnaire position (1 = “rag”; 2 = “innkeeper”; 5 = “cousins”) and described violations of moral or socialconventional rules, respectively. Participants read each scenario and provided a moral wrongness rating for the described behavior on a ten-point rating scale ranging from “not at all wrong” (1) to “absolutely wrong” (10). After completing moral judgments, participants answered some demographic questions. Moreover, the questionnaire asked participants which emotions had been elicited by the scenarios at position 3, position 4, and position 6. Response options were “anger”, “sadness”, “joy”, “disgust”, “fear”, “contempt”, “surprise”, and “no emotion”. Finally, participants were asked whether they had an idea what the study was about.

2. Study 1a Study 1a tested Laham et al.'s (2009) assumption, that discrepant perceptual fluency also affects judgments of true moral transgressions. For this reason, Study 1a was set up as a conceptual replication of Laham et al.'s study with critical scenarios describing moral instead of conventional transgressions. That is, the described behaviors violated principles of welfare or justice, respectively. Based on Laham et al.'s results, we predicted a fluency condition by scenario position interaction effect. More precisely, we predicted that discrepant fluency (i.e., a change from disfluent to fluent processing) mitigates moral wrongness ratings.

2.1.3. Design The experimental factors in Study 1a were the fluency condition (fluent contrast first vs. disfluent contrast first) and the position of the critical scenarios in the questionnaire (position 3 vs. position 4 vs. position 6). Thus, the design was a mixed design with fluency condition as the between-subjects factor and position as the within-subjects factor. Moreover, the scenario order, i.e., the assignment of the three scenarios wallet, e-mail, and resumé to the three critical positions was counterbalanced according to a Latin square.

2.1. Method 2.1.1. Participants Participants were recruited at the University of Koblenz-Landau and the University of Mannheim. One-hundred twenty-four participants completed the paper-pencil questionnaire. However, because foreignlanguage processing can alter moral judgments (e.g., Corey et al., 2017; Costa et al., 2014; Geipel, Hadjichristidis, & Surian, 2015), we restricted our data analyses to German native speakers only. The final sample thus consisted of n = 112 participants (33 male, 79 female), aged 18 to 47 years (M = 21.9, SD = 3.8), most of which were psychology students (86%).

2.2. Results 2.2.1. Fluency and moral judgments Possible effects of the fluency condition, scenario position, and the scenario order on moral wrongness ratings were tested by means of a 2 (fluency condition: fluent contrast first vs. disfluent contrast first) × 3 (position: 3 vs. 4 vs. 6) × 3 (scenario order: 1 vs. 2 vs. 3) ANOVA. Unlike predicted, there was no fluency condition by position interaction effect, F < 1 (see Fig. 2A). Hence, the data of Study 1a did not replicate the findings of Laham et al. (2009). Moreover, there was no main effect of the fluency condition, F(1, 106) = 2.10, p = 0.150, ηp2 = 0.02, and no other main effect or interaction, Fs < 1. Likewise, moral wrongness ratings for the filler scenarios were also uninfluenced by the fluency manipulation, all ps > 0.05.3

2.1.2. Materials and procedure We presented participants with the following six scenarios most of which were adapted versions of scenarios used in previous studies on moral judgments (Haidt et al., 1993; Schnall, Benton, & Harvey, 2008): “wallet” (a man taking money of a found wallet), “resumé” (a woman adorning her resumé with false information), “e-mail” (a wife secretly checking her husband's e-mails), “rag” (a woman using her national flag as cleaning rag), “innkeeper” (an innkeeper throwing a bottle at two arguing guests), and “cousins” (a male cousin and his female cousin kissing passionately).2 In line with Laham et al. (2009), the six scenarios were presented in two blocks which were displayed on separate pages of a paper-pencil questionnaire. The scenarios, which were printed in black (font style: Times New Roman; point size 13), appeared on either a white background (see Fig. 1A) or gray-speckled background (granite fill effect, see Fig. 1B). Specifically, in the fluent first condition, scenarios 1 to 3 appeared on the white questionnaire page and scenarios 4 to 6 on a gray speckled page. This order was reversed (i.e., scenarios 1 to 3 on a gray speckled page and scenarios 4 to 6 on a white page) in the disfluent first condition. In order to prevent a suspicion of this background manipulation, we presented the gray speckled background as a copy error. The questionnaire contained three critical scenarios (“wallet”, “resumé”, and “e-mail”) and three filler scenarios (“rag”, “innkeeper”, and “cousins”). In line with Laham et al. (2009), the three critical

2.2.2. Fluency and emotions Based on the findings of Merritt and Monin (2011), we examined whether participants were more inclined to experience negative emotions for critical scenarios processed disfluently compared to fluently. To test this possibility, we coded participants' emotion judgments as “negative” vs. “non-negative”. When a participant indicated at least one negative emotion for a scenario (i.e., contempt, anger, disgust, fear, or sadness) their emotion judgment for this scenario was coded as negative. All other responses (joy, surprise, or no emotion) were coded as non-negative. Two participants had not provided emotion judgments and thus were excluded from the following analysis. We then compared the number of participants indicating at least one negative emotion between fluency conditions at position 3 (fluent: 66.7%; disfluent: 54.5%), position 4 (fluent: 74.5%; disfluent: 63.2%), and position 6 (fluent: 69.1%; disfluent: 71.9%). However, at none of the three critical

1 We estimated the true repeated measure-correlation ρ based on the mean of the observed repeated-measure correlations (i.e. correlations of moral judgments between critical scenario positions across our five studies). 2 For the scenarios' exact wording, see https://osf.io/749ru/.

3 Eight participants had correctly hypothesized that the study investigated text background effects on moral judgments. However, excluding these participants did not change the pattern and significance of the reported results.

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Fig. 1. Rag scenario in (A) fluent contrast and (B) disfluent contrast as illustration of the text-background manipulation.

Fig. 2. Mean moral wrongness ratings in (A) Study 1a and (B) Study1b as a function of fluency condition (fluent contrast first vs. disfluent contrast first) and position (3 vs. 4 vs. 6). White points/squares indicate fluent contrast; dark points/squares indicate disfluent contrast. Error bars represent standard error of the means.

positions, (dis)fluency significantly affected participants' propensity to report negative emotions, χ2s(1) ≤ 1.25, ps ≥ 0.263.

on moral judgments for offensive but harmless actions, which was reported by Laham and colleagues, does not apply to real moral transgressions. But why should evaluations of conventional transgressions be more susceptible to perceptual fluency effects than evaluations of moral transgressions? According to Cornwell and Higgins (2016) offensive but harmless actions are often intuitively judged as morally wrong whereas conscious reasoning leads to the insight that these actions do not violate any moral standards. Thus, for such offensive, conventional transgressions intuition-based and reasoning-based moral wrongness ratings should diverge. In contrast, for true moral transgressions, intuition and reasoning should have converging effects on moral wrongness ratings. As a consequence, evaluations of conventional transgressions might be more susceptible to contextual factors such as perceptual (dis)fluency than evaluations of moral transgressions. However, the null effect in Study 1a also leaves room for the following alternative interpretations. First, because the discrepant fluency effect reported by Laham et al. (2009) rests on a single study, it is unclear whether it represents a truly reliable effect. Thus, possibly, the effect does not replicate in a direct replication study with Laham et al.'s materials. Second, according to Oppenheimer (2006), people refrain from using fluency as a judgment cue and may even overcompensate (i.e., shift their judgment in the opposite direction), when an obvious source of the high/low processing fluency lies at hand. Because we presented the text-background manipulation as a copy error to prevent suspicion, participants might have discounted the (dis)fluency experience based on this rationale for the different text-backgrounds. Third, and finally, because Study 1a did not include a manipulation check for the fluency manipulation, we cannot guarantee that the fluency manipulation worked as intended.

2.2.3. Emotions and moral judgments We also explored the role of negative emotions on moral wrongness ratings with a linear mixed-model analysis. The analysis was run in R (R Development Core Team, 2008) with the package lme4 (Bates, Mächler, Bolker, & Walker, 2014). Degrees of freedom and p-values were calculated with the package lmerTest (Kuznetsova, Brockhoff, & Christensen, 2017). We first tested a baseline model that included the fixed factors fluency condition, scenario position and their interaction as well as random intercepts for participants and scenarios. In line with the ANOVA findings, moral judgments were not affected by condition, Fs(1, 110) ≤ 2.18, ps ≥ 0.143, position, F < 1, or their interaction, F < 1. In a second step, we added experienced emotions (negative vs. non-negative) as a further fixed factor. The extended model fitted the data significantly better than the baseline model as indicated by a likelihood-ratio test, χ2(1) = 72.02, p < 0.001. As before, there was no significant effect and no interaction of condition and position on moral wrongness ratings (all ps > 0.05). However, there was a significant emotion effect, F(1, 326.40) = 78.88, p < 0.001. Participants provided higher moral wrongness ratings when experiencing a negative emotion in response to a scenario (M = 8.26, SD = 1.56) than when not experiencing a negative emotion (M = 6.44, SD = 2.08). 2.3. Discussion In Study 1a, we did not find an effect of discrepant perceptual fluency on moral wrongness ratings. That is, we could not reproduce the findings of Laham et al. (2009), despite the same kind of (dis)fluency manipulation. This finding suggests that the discrepant fluency effect 4

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3. Study 1b

(scenario order: 1 vs. 2 vs. 3) ANOVA on moral judgments. As in Study 1a, there was no fluency condition by position interaction effect, F < 1 (see Fig. 2B). That is, even though we had used the fluency manipulation and the materials of Laham et al. (2009), we did not reproduce their discrepant fluency effect on moral judgments. There were no significant main effects of position, F < 1, condition, F(1, 111) = 1.99, p = 0.161, ηp2 = 0.02, and scenario order, F(2, 111) = 2.37, p = 0.098, ηp2 = 0.04. With the exception of a significant position by scenario order interaction effect, F(4, 222) = 27.08, p < 0.001, ηp2 = 0.33, there were no further interactions, Fs < 1. The position by scenario order interaction reflects strong differences in mean moral judgments between the three critical scenarios “kiss” (M = 6.56), “dog” (M = 7.63), and “deface” (M = 9.26). As a consequence, the pattern of moral judgments across critical positions varied markedly for the three scenario orders. However, importantly, this interaction was not further qualified by fluency condition. Moreover, moral wrongness ratings for the filler scenarios were also uninfluenced by the fluency manipulation, all ps > 0.05. Forty-seven participants (40.2%) had correctly hypothesized that the study investigated text background effects on moral judgments. In order to test a possible effect of fluency-discounting for these participants, we repeated the above ANOVA but this time included the factor “correct hypothesis” in the analysis. However, including this factor did not change the pattern and significance of results.

Study 1b was designed as direct replication of the Laham et al. (2009) study to check the reproducibility of its findings. That is, in Study 1b we not only used the design and background contrast manipulation of Laham et al. (2009), but also their scenarios. If the type of scenario matters, we should now be able to find a fluency discrepancy effect on moral judgments. Moreover, in line with the original study, we added a manipulation check to make sure that participants perceived the text on the gray-speckled background indeed as less legible than the text on the white background. Unlike Study 1a, we did not ask for participants emotions and did not provide a rationale for the background contrast manipulation in order to replicate Laham et al.'s study as closely as possible. 3.1. Method 3.1.1. Participants Participants were recruited at the University of Koblenz-Landau and the University of Mannheim. One-hundred twenty participants completed the questionnaire. As in Study 1a, we restricted data analyses to German native speakers only. Thus, the final sample comprised n = 117 participants (28 male, 88 female, one genderfluid), aged 18 to 39 years (M = 22.1, SD = 3.4), most of which were psychology students (65%).

3.2.2. Manipulation check In order to check whether the fluency manipulation had indeed worked as intended, we analyzed participants' ratings of text reading difficulty. That is, following Laham et al. (2009), we conducted a 2 (text-page: fluent vs. disfluent) × 2 (condition: fluent first vs. disfluent first) ANOVA on participants difficulty ratings. This analysis confirmed that the fluency manipulation had been successful, i.e. participants judged the text on the gray speckled background as significantly more difficult to read (M = 3.18, SD = 0.92) than the text on the white background (M = 1.07, SD = 0.31), F(1, 115) = 593.21, p < 0.001, ηp2 = 0.84. However, disfluent texts were still legible as indicated by their moderate reading difficulty ratings. It should also be emphasized that the text difficulty ratings were very close to the ones found by Laham et al. (disfluent: M = 3.29, SD = 1.04; fluent: M = 1.13, SD = 0.46). Moreover, as in the original study by Laham and colleagues, neither the condition main effect nor the condition by text interaction effect was significant, Fs(1, 115) ≤ 3.17, ps ≥ 0.078, ηp2s ≤ 0.03.

3.1.2. Materials, procedure, and design We presented participants with German translations of the six scenarios used by Laham et al. (2009): “kiss” (brother and sister kissing passionately), “dog” (a family eating its dead dog), “deface” (a man defacing a memorial), “punch” (a man punching another man in a bar), “flag” (a teacher burning her national flag in front of her class), and “hitler” (a man mocking sports fans with Hitler imitation.).4 The procedure was the same as in Study 1a, except for the following changes that were necessary for a direct replication of the Laham et al. study: The scenarios “kiss”, “dog”, and “deface” were counterbalanced across the critical positions 3, 4, and 6. Importantly, these critical scenarios described offensive but harmless behaviors. The remaining scenarios served as fillers that always appeared at the same position (1 = “punch”, 2 = “flag”, and 5 = “hitler”) and described violations of moral or social-conventional rules, respectively. All scenarios were printed in black (font style: Times New Roman; point size 12) and appeared on either a white or gray-speckled background (granite fill effect). Unlike in Study 1a, we did not present the gray-speckled background as a copy error. That is why we printed all questionnaires instead of copying them and did not provide any rationale for the different text backgrounds. Furthermore, no emotion judgments were queried. Instead, after providing moral judgments, participants rated the difficulty of reading the texts on the white versus gray-speckled background on a five-point rating scale (1 = "not at all difficult"; 5 = "very difficult"). The research design was the same as in Study 1a.

3.3. Discussion We again did not find an effect of discrepant perceptual fluency on moral judgments even though Study 1b was designed as exact replication of Laham et al.'s (2009) study. Taken together the findings of Study 1a and Study 1b raise doubts about a discrepant fluency effect on moral wrongness ratings for moral and conventional transgression. However, Studies 1a and 1b only investigated the effect of one specific perceptual fluency manipulation—a background contrast manipulation—on moral judgments. For this reason, we cannot generally rule out a perceptual fluency effect on moral wrongness ratings. Although the manipulation check in Study 1b confirmed that the gray speckled text background effectively reduced text legibility, the background contrast manipulation can be criticized for the following reason. People might perceive the white background as “clean” and the gray, speckled background as “dirty”. This is problematic because moral judgments can potentially be biased by perceptions of cleanliness/dirt (e.g., Schnall, Benton, & Harvey, 2008; Schnall, Haidt, et al., 2008; but see Johnson, Cheung, & Donnellan, 2014, for a failed replication). Moreover, people tend to associate brightness positively and darkness negatively (Meier, Robinson, & Clore, 2004; Sherman & Clore, 2009; Specker et al., 2018). Hence, it seems possible that the null effect

3.2. Results 3.2.1. Fluency and moral judgments In line with Study 1a, we conducted a 2 (fluency condition: fluent contrast first vs. disfluent contrast first) × 3 (position: 3 vs. 4 vs. 6) × 3 4 We thank Simon Laham for sending us the original scenarios. A bilingual German-English speaker translated the scenarios into German. The German scenarios were back-translated by the language processor DeepL (DeepL GmbH, 2017) and checked by another bilingual German-English speaker to make sure that the translations were true to the original scenarios. Please note that we had to change some country-specific details in the texts (names, places, nationalities) to make the scenarios suitable for a German sample. For the scenarios' exact wording, see https://osf.io/749ru/ Changes to the original scenarios are highlighted.

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Fig. 3. Rag scenario in (A) fluent font and (B) disfluent font as illustration of the font type manipulation.

in Study 1a and Study 1b might be the result of antagonistic fluency discrepancy and cleanliness/brightness effects. That is, a change from a “clean” to a “dirty” page (or “bright” to “dark” page, respectively) could lead to harsher moral judgments (in line with the findings of Laham et al., 2009) whereas a change from a perceptual fluent to a perceptual disfluent text could possibly produce exactly the opposite effect. For this reason, it is important to investigate the effect of other perceptual fluency manipulations on moral judgment that do not confound fluency with the perceived cleanliness or brightness of the questionnaire page.

scenario order on moral wrongness ratings, Fs < 1. This time, however, we found a significant fluency condition by scenario position interaction effect, F(2, 200) = 3.87, p = 0.022, ηp2 = 0.04 (see Fig. 4A). This interaction had the exact opposite direction than the one reported by Laham et al. (2009). That is, scenarios presented at position 4 (i.e., the position after the fluency change) received higher moral wrongness ratings when presented in the fluent font (M = 8.05; SD = 1.98) as compared to the disfluent font (M = 7.20; SD = 2.38), t(104) = 2.03, p = 0.045, d = 0.39. In contrast, fluency differences did not have a significant effect on moral wrongness ratings at positions 3 and 6 (nor at any of the filler positions), all ps > 0.05.

4. Study 2a

4.2.2. Fluency and emotions As in Study 1a, we coded participants' emotion judgments as “negative” if participants named at least one negative emotion (contempt, anger, disgust, fear, or sadness). All other emotion judgments were coded as non-negative (joy, surprise, or no emotion). We then compared the number of participants indicating negative emotions between fluency conditions at position 3 (fluent: 63.3%; disfluent: 54.5%), position 4 (fluent: 65.5%; disfluent: 53.1%), and position 6 (fluent: 56.4%; disfluent: 66.7%). However, replicating Study 1a, fluency did not significantly affect participants' emotion judgments (negative vs. non-negative) at any of these critical positions χ2s(1) ≤ 1.18, ps ≥ 0.278.

Study 2a conceptually replicated Study 1a but manipulated perceptual fluency by different font types (Alter & Oppenheimer, 2008, 2009; Diemand-Yauman, Oppenheimer, & Vaughan, 2011; Merritt & Monin, 2011; Spears et al., 2018) instead of different background contrasts. We did so in order to avoid potential confounds when investigating perceptual fluency effects on moral judgments. 4.1. Method 4.1.1. Participants Participants were recruited at the University of Mannheim and a local high school. One-hundred eleven adult participants completed the paper-pencil questionnaire. As before, we restricted data analyses to German native speakers only. The final sample thus comprised n = 106 participants (29 male, 77 female), aged 18 to 44 years (M = 21.0, SD = 4.4), most of which were psychology students (98%).

4.2.3. Emotions and moral judgments In line with Study 1a, we additionally analyzed moral wrongness ratings with a linear mixed-model analysis. The baseline model included the fixed factors fluency condition, scenario position and their interaction as well as random intercepts for participants and scenarios. Replicating the ANOVA findings, the analysis did not display any main effects of condition and position on moral wrongness ratings, Fs < 1, but a significant condition by position interaction effect, F(2, 202.39) = 3.85, p = 0.023. We then added emotion judgments (negative vs. non-negative) as a further fixed factor to the model. The inclusion of this emotion factor significantly improved model fit, χ2(1) = 72.86, p < 0.001. At the same time the condition by position interaction was no longer statistically significant, F(2, 201.44) = 2.54, p = 0.082. However, there was a significant emotion effect, F(1, 299.63) = 81.04, p < 0.001, with higher moral wrongness ratings when participants experienced a negative emotion (M = 8.36, SD = 1.79) than when they did not experience such an emotion (M = 6.36, SD = 2.16).

4.1.2. Materials, procedure, and design The materials and research design were the same as in Study 1a. The procedure closely resembled Study 1a, except that we manipulated perceptual fluency by font type. More precisely, one block contained three scenarios printed in a fluent, easy to read font (Times New Roman, 12 point size, see Fig. 3A) whereas the other block contained three scenarios printed in a disfluent, difficult to read font (Haettenschweiler, 13 point size, see Fig. 3B).5 Participants were told that the questionnaire was part of a group project on moral judgments and had been designed by different students. We used this cover study to prevent participants from being suspicious of the different fonts in the questionnaire. 4.2. Results

4.3. Discussion

4.2.1. Fluency and moral judgments As in the previous studies, we conducted a 2 (fluency condition: fluent first vs. disfluent first) × 3 (position: 3 vs. 4 vs. 6) × 3 (scenario order: 1 vs. 2 vs. 3) ANOVA on moral wrongness ratings. Again, there were no main effects of fluency condition, scenario position, and

Study 2a investigated the effect of perceptual fluency on moral judgments by means of a font type manipulation. This time, our findings were diametrically opposed to the findings of Laham et al. (2009). That is, discrepant fluency in Study 2a did not mitigate but boost moral wrongness ratings. In the following, we will discuss potential explanations for this discrepant result. As noted in Section 2.3. the absence or reversal of a fluency effect might be the consequence of fluency (over)discounting. However, in

5 The font size of Haettenschweiler was increased to match the size of Times New Roman.

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Fig. 4. Mean moral wrongness ratings in (A) Study 2a and (B) Study 2b as a function of fluency condition (fluent font first vs. disfluent font first) and critical position (3 vs. 4 vs. 6). White points/squares indicate fluent font; dark points/squares indicate disfluent font. Error bars represent standard error of the means.

line with the original study of Laham et al. (2009), none of our participants indicated suspicion about the fluency manipulation. In addition, the results of our two previous studies did not differ depending on whether we provided a plausible reason for the fluency differences (Study 1a) or not (Study 1b). Hence, a fluency discounting effect on moral judgments seems very unlikely. In contrast, it seems much more plausible that the divergent findings relate to the different types of fluency manipulations (Laham et al.: background contrast; Study 2a: font type). For instance, because the background-contrast manipulation confounds perceptual fluency with the general appearance of the questionnaire pages (i.e., cleanliness, brightness) Laham et al.'s results might reflect a cleanliness or brightness effect on moral judgments whereas the font effect in Study 2a reflects a true fluency effect. However, we cannot completely rule out that other procedural differences between the studies account for the divergent results.

5.2. Results 5.2.1. Fluency and moral judgments We again conducted a 2 (fluency condition: fluent contrast first vs. disfluent contrast first) × 3 (position: 3 vs. 4 vs. 6) × 3 (scenario order: 1 vs. 2 vs. 3) ANOVA on moral judgments. In line with the Studies 1a and 1b, there was no fluency condition by position interaction effect, F < 1 (see Fig. 4B). That is, we again were not able to (conceptually) replicate the discrepant fluency effect on moral judgments found by Laham et al. (2009). The ANOVA also did not display any significant main effects of position, F < 1 and condition, F(1, 161) = 2.05, p = 0.154, ηp2 = 0.01. However, there was a main effect of scenario order on moral judgments, F(2, 161) = 4.31, p = 0.015, ηp2 = 0.05, and a position by scenario order interaction, F(3.85, 310.09) = 23.05, p < 0.001, ηp2 = 0.22.6 As in Study 1b, this position by scenario order interaction reflects strong differences in mean moral judgments between the three critical scenarios “kiss” (M = 7.19), “dog” (M = 7.81), and “deface” (M = 9.19). As a consequence, the pattern of moral judgments across critical positions varied markedly for the three scenario orders. However, importantly, this interaction was not further qualified by fluency condition and there were no further interactions, Fs < 1. Moreover, moral wrongness ratings for the filler scenarios were also uninfluenced by the fluency manipulation, all ps > 0.05.

5. Study 2b In Study 2b, we again manipulated perceptual fluency by font type, but this time we kept all other procedural details similar to Laham et al.'s study (and Study 1b, respectively). We only switched the questionnaire format from paper pencil to web-based. This allowed us to compare the processing times for the two different font types in addition to their rated legibility.

5.2.2. Manipulation checks In order to check whether the font type manipulation had worked as intended, we analyzed participants' ratings of text reading difficulty by means of a 2 (text: fluent vs. disfluent) × 2 (condition: fluent first vs. disfluent first) ANOVA on participants difficulty ratings. This analysis confirmed that the font type manipulation had been successful, i.e. participants judged the text in Haettenschweiler font as significantly more difficult to read (M = 2.63, SD = 1.31) than the text in Times New Roman font (M = 1.57, SD = 0.95), F(1, 165) = 89.55, p < 0.001, ηp2 = 0.35. There was no effect of condition on the difficulty ratings, F(1, 165) = 1.16, p = 0.283, ηp2 = 0.01, but there was a small but statistically significant condition by text fluency interaction effect, F(1, 165) = 3.96, p = 0.048, ηp2 = 0.02. Participants in the fluent first condition indicated larger differences in reading difficulty between the two font types (fluent: M = 1.54, SD = 0.93; disfluent: M = 2.82, SD = 1.31) than participants in the disfluent first condition (fluent: M = 1.61, SD = 0.98; disfluent M = 2.45, SD = 1.30). In addition to the participants' difficulty ratings, we also analyzed participants' processing times. We therefore conducted a 2

5.1. Method 5.1.1. Participants Participants were recruited via mailing lists at the University of Koblenz-Landau. One-hundred seventy-eight participants completed the web-based study. As before, we restricted our data analyses to German native speakers only. The final sample thus comprised n = 167 participants (47 male, 120 female), aged 18 to 59 years (M = 24.7, SD = 6.4), most of which were students of various disciplines (92%). 5.1.2. Materials, procedure, and design The German translations of the original scenarios of Laham et al. (2009) served as stimulus material (see Study 1b). Moreover, the procedure resembled the original study of Laham and colleagues (and Study 1b, respectively) except for the following changes: First, as in Study 2a, we manipulated perceptual fluency by font type (fluent font: Times New Roman; disfluent font: Haettenschweiler). Second, the study was implemented as a web-based study. The design was the same as in all preceding studies.

6 Due to a violation of the sphericity assumption, degrees of freedom for the position by scenario order interaction are Greenhouse-Geisser corrected.

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(questionnaire-page: fluent vs. disfluent) × 2 (condition: fluent page first vs. disfluent page first) ANOVA, with the page processing time (in s) as the dependent variable. However, processing times were unaffected by the two factors and their interaction, all Fs < 1. In sum, even though participants experienced the text in Haettenschweiler font as more difficult to read than the text in Times New Roman font, actual processing times did not differ significantly between the two font types (Haettenschweiler page: M = 65.3 s; Times New Roman page: M = 63.2 s).

would maximize the chances of finding an effect of discrepant fluency on moral wrongness ratings by increasing the unexpectedness of the fluency change. We also replaced the categorical emotion judgments by emotion ratings in order to determine the strength of negative emotions rather than their presence or absence, respectively. Moreover, based on findings suggesting that fluency leads to more concrete mental representations than disfluency (Alter & Oppenheimer, 2008) and based on the notion that concrete representations are characterized by high “imaginability” (Gong & Medin, 2012), we also included an imageability rating for each scenario. We hypothesized that possible perceptual fluency effects on moral wrongness ratings might be mediated by imaginability. More precisely, we predicted a positive relationship between imaginability and moral wrongness ratings, because it seems plausible that a very concrete representation of a scenario intensifies the perceived severity of the described transgression (e.g., Gong & Medin, 2012; but see Eyal, Liberman, & Trope, 2008). Finally, we increased the sample size in Study 3 to further enhance the sensitivity of our statistical tests.

5.3. Discussion In Study 2b we once more did not find a discrepant fluency effect on moral judgments. To summarize, three of our studies had revealed a null-result (Studies 1a, 1b, and 2b) and only one (Study 2a) had demonstrated a perceptual fluency effect on moral wrongness ratings. However, the effect was diametrically opposed to the one of Laham et al. (2009) and vanished, when taking participants emotions (negative vs. non-negative) into account. Our present findings therefore strongly challenge a perceptual fluency effect on moral judgments. But before jumping to conclusions, we tested another, stronger perceptual fluency manipulation on moral judgments in Study 3. Moreover, Study 3 further explored the role of negative emotions on moral wrongness ratings.

6.1. Method 6.1.1. Participants Participants were recruited at the University of Koblenz-Landau and the University of Mannheim. Two hundred and five participants completed the questionnaire. We restricted data analyses to participants who had a) indicated German as their native language and b) had provided moral judgments for the two critical scenarios. The final sample thus comprised n = 192 participants (26 male, 165 female, 1 diverse), aged 18 to 44 years (M = 21.1, SD = 3.2), most of which were psychology students (87%).

6. Study 3 In the previous studies, we had used a background contrast manipulation (Studies 1a and 1b) and a font type manipulation (Studies 2a and 2b), respectively, to investigate perceptual (dis)fluency effects on moral judgments. Both fluency manipulations demonstrably affect participants' perceived processing ease as indicated by our manipulation checks as well as by previous studies (Galak & Nelson, 2011; Halin, Marsh, Haga, Holmgren, & Sörqvist, 2014; Laham et al., 2009). However, there is no evidence that these manipulations also reliably influence factual processing speed. For instance, in Study 2b, we did not find significant differences in processing times between the questionnaire page displaying the scenario texts in Times New Roman and the page with the texts in Haettenschweiler. Similarly, Halin et al. (2014) reported that even though their participants experienced a text in Times New Roman as easier to read than a text in Haettenschweiler, reading speed was actually faster for the latter font. Thus, possibly, we did not find a reliable fluency effect on moral judgments, because the contrast and font type manipulations had only affected subjective but not objective processing ease. For this reason, Study 3 applied a perceptual fluency manipulation that demonstrably reduces the speed of information processing. Specifically, in the disfluent condition, we eliminated all blank spaces—a manipulation that has been shown to reduce processing speed by about 50% (Epelboim, Booth, Ashkenazy, Taleghani, & Steinman, 1997; Rayner, Fischer, & Pollatsek, 1998). We also implemented the following procedural changes: Unlike in the previous studies, the change in processing fluency did not take place until the sixth (i.e. final) scenario. We expected that this modification

6.1.2. Material and procedure The materials and the procedure were the same as in Studies 1a and 2a except for the following changes: Each moral scenario was presented on a separate questionnaire page. The first four scenarios were filler scenarios (1 = “rag”, 2 = “innkeeper”, 3 = “cousins”, 4 = “resumé”). Critical scenarios (“wallet” and “e-mail”) were presented at positions 5 and 6. The order of these critical scenarios was counterbalanced between participants (wallet first vs. e-mail first). Perceptual fluency was manipulated by means of blank spaces, i.e., the scenario texts and instructions were either displayed with blank spaces (Fig. 5A) or without blank spaces (see Fig. 5B). Specifically, in the fluent first condition, scenarios 1 to 5 were easy to read because they appeared with normal word spacing (i.e. with blank spaces between words) whereas scenario 6 was difficult to read because words were not separated by blank spaces. In addition to omitting the word spaces, all words that were not at the beginning of the sentence were written in lower case to make word discrimination more difficult. The order of the word spaces manipulation reversed in the disfluent first condition (i.e., scenarios 1 to 5 appeared without spaces and scenario 6 with spaces). We told participants that the questionnaire examined effects of text readability on different kinds of judgments. After reading a moral

Fig. 5. Rag scenario with (A) fluent spacing and (B) disfluent spacing as illustration of the word spaces manipulation. 8

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scenario, participants provided a moral wrongness rating for the described behavior (1 = “not at all wrong” to 10 = “absolutely wrong”). Subsequently, they indicated whether the scenario had elicited negative emotions. More precisely, following Geipel et al. (2015), participants rated how angry, sad, disgusted, contemptuous, and worried they felt about the described behavior (1 = “not at all” to 5 = “very strong”). Finally, participants rated their capability to imagine the described scenario (1 = “not at all” to 10 = “very good”).

ANOVA. This analysis showed that negative emotions were neither influenced by the fluency condition, nor by scenario position, nor by their interaction, Fs(1, 190) ≤ 3.09, ps ≥ 0.080, ηp2s ≤ 0.02. That is, fluency did not affect participants' negative emotion scores for the critical scenarios at position 5 (fluent: M = 2.53; disfluent: M = 2.31) and position 6 (fluent: M = 2.51; disfluent: M = 2.55). This finding is in line with the results of Studies 1a and 2a. 6.2.3. Emotions and moral judgments In line with Studies 1a and 2a, we also conducted a linear mixedmodel analysis on moral judgments. We first tested a baseline model that included the fixed factors fluency condition, scenario position, and their interaction as well as random intercepts for participants and scenarios. The results were in accordance with the ANOVA findings. Moral wrongness ratings differed significantly between the critical scenario positions, F(1, 189.03) = 5.01, p = 0.026, but this effect was not qualified by condition as there was no position by condition interaction, F < 1. Moreover, there was also no main effect of condition, F < 1. We then added participants' negative emotion scores and their imaginability ratings as further fixed factors to the model. This extended model fitted the data significantly better than the baseline model, χ2(2) = 164.27, p < 0.001. At the same time the position main effect was no longer statistically significant, F(1, 176.15) = 3.48, p = 0.064. However, replicating the results of Studies 1a and 2a, there was a significant emotion effect, F(1, 343.33) = 208.32, p < 0.001. The more negative participants' emotions in response to a moral scenario, the more morally wrong they judged the described transgression. The model did not display any other significant effects on moral judgments (ps > 0.05).

6.1.3. Design The experimental factors in Study 3 were the fluency condition (fluent first vs. disfluent first), the position of the critical scenarios in the questionnaire (position 5 vs. position 6), and the scenario order of the two critical scenarios (wallet first vs. e-mail first). Thus, the design was a mixed design with position as the only within-subjects factor. 6.2. Results 6.2.1. Fluency and moral judgments We analyzed moral wrongness ratings with a 2 (fluency condition: fluent first vs. disfluent first) × 2 (position: 5 vs. 6) × 2 (scenario order: e-mail first vs. wallet first) ANOVA. The analysis revealed a significant main effect of position, F(1, 188) = 5.20, p = 0.024, ηp2 = 0.03. Participants were stricter in their moral wrongness ratings for the scenario presented at position 6 (M = 7.66, SD = 2.03), i.e., the position at which the processing fluency changed, compared to position 5 (M = 7.23, SD = 2.00), at which the processing fluency was the same as in the previously presented scenarios. However, this main effect was neither qualified by the fluency condition, F < 1 (see Fig. 6), nor by the scenario order, F(1, 188) = 1.54, p = 0.216, ηp2 = 0.01. There were also no further significant main effects and interactions, Fs(1, 188) ≤ 3.27, ps ≥ 0.072, ηp2s ≤ 0.02. Hence, as in Studies 1a, 1b, and 2b, we did not find an interaction between processing fluency and position. Furthermore, moral wrongness ratings for the filler scenarios were also uninfluenced by the fluency manipulation, all ps > 0.05.

6.3. Discussion Although we had implemented several procedural changes to maximize the chances of finding a fluency discrepancy effect on moral judgments, we again failed to find such an effect. More precisely, discrepant fluent processing neither decreased moral wrongness ratings (as found by Laham et al., 2009), nor selectively increased moral wrongness ratings (as observed in Study 2a). In contrast, moral wrongness ratings slightly increased from position 5 to position 6, irrespectively of the fluency condition. This position effect, however, disappeared when taking participants' negative emotions into account. To sum up, in Study 3 we again did not find a perceptual fluency effect on moral judgments. In contrast, we replicated the effect of negative emotions on moral wrongness ratings. This was the case even though we had replaced the categorical emotion judgment of Studies 1a and 2a by emotion ratings. Imageability ratings, in turn, were unrelated to moral judgments.

6.2.2. Fluency and emotions Because ratings on the different negative emotion scales (anger, sadness, disgust, contempt, and worry) were highly correlated (Cronbach's alpha = 0.86), we calculated a negative emotion score by averaging the emotion ratings across the scales (see Geipel et al., 2015). We then submitted this negative emotion score to a 2 (fluency condition: fluent first vs. disfluent first) × 2 (scenario position: 5 vs. 6)

7. General discussion The goal of this work was to investigate perceptual fluency effects on moral judgments. Based on the study of Laham et al. (2009), which had found that discrepant fluency mitigates moral wrongness ratings for violations of social conventions (e.g., a family eating its dead dog), we tested the replicability and generalizability of this effect. That is, we assessed the effect with the original scenarios describing conventional transgressions and with scenarios describing moral transgressions. Moreover, we tested three different perceptual fluency manipulations. Studies 1a and 1b used the background contrast manipulation of Laham et al., but did not find any background contrast effects on moral wrongness ratings—neither for scenarios describing moral transgressions (Study 1a) nor for the scenarios of Laham and colleagues describing conventional transgressions (Study 1b). In Study 2a we manipulated perceptual fluency by font type and found that discrepant fluency increased moral wrongness ratings. However, this fluency effect—which was exactly opposed to the effect found by Laham and

Fig. 6. Mean moral wrongness ratings in Study 3 as a function of fluency condition (fluent spacing first vs. disfluent spacing first) and position (5 vs. 6). White points/squares indicate fluent spacing; dark points/squares indicate disfluent spacing. Error bars represent standard error of the means. 9

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colleagues—vanished when controlling for participants' negative emotions. Moreover, the fluency effect did not replicate in Study 2b, which used the same font type manipulation but different scenarios (conventional instead of moral transgressions). Finally, in Study 3, we varied perceptual fluency by means of a blank space manipulation. Even though leaving out blank spaces demonstrably reduces processing speed, we again failed to find an effect of discrepant fluency on moral wrongness ratings. In summary, none of our five studies reproduced Laham et al.'s finding that perceptual fluency mitigates moral wrongness ratings. Taken together, our results cast very strong doubt on the existence of perceptual fluency effects on moral judgments. Similar to moral judgments, emotion judgments were also not influenced by discrepant perceptual (dis)fluency. More precisely, we did not find empirical support for the assumption that discrepant (dis)fluency affects participants' negative emotional responses to the described moral transgressions. At first glance, this finding seems to be at odds with studies demonstrating that processing fluency is hedonically marked (see Winkielman, Schwarz, Fazendeiro, & Reber, 2003, for a review). However, unlike our work, these studies have examined effects of perceptual fluency on positive instead of negative affect.7 Thus possibly, there are strong valence asymmetries in fluency effects on affective experiences. Moreover, fluency effects on affective experiences have typically been investigated with simple, neutral stimuli such as geometrical shapes or line drawings (Reber et al., 1998). In contrast, the scenarios used in our studies were much more complex and meaningful. In fact, Winkielman et al. (2003) presumed that “when the stimuli are more meaningful, the impact of the fluency signal may be attenuated” (p. 209). In addition, it should be noted that moral and conventional transgressions are inherently negative. Hence, the feeling of processing (dis)fluency might have been too subtle in comparison to the strong emotional reactions evoked by the scenarios. Unlike fluency, negative emotions reliably affected moral judgments. In Studies 1a and 2a, participants provided higher moral wrongness ratings when they reported a negative emotion in response to the described scenario. In Study 3, the indicated strength of negative emotions predicted moral wrongness ratings. These results are in line with the social intuitionist model of Haidt (2001), which proposes that moral judgments are strongly linked to people's gut feelings (e.g., emotions and affective experiences). However, please note that because we did not experimentally manipulate emotions, we cannot draw any conclusions about the causal relationship between emotions and moral judgments. We would also like to point out the following limitations of our work. In the five studies presented, we only investigated perceptual fluency effects on moral judgments. Thus, we cannot generalize our results to other types of fluency. For this reason, future studies might examine whether moral wrongness ratings are moderated by conceptual fluency—the ease with which the meaning of information is processed. According to Alter and Oppenheimer (2009) perceptual and conceptual fluency have the same judgmental consequences. However, in some studies perceptual and conceptual fluency manipulations produced different results (e.g., Garcia-Marques, Silva, & Mello, 2016; Silva, Garcia-Marques, & Mello, 2016). Thus, we cannot rule out that unlike perceptual fluency, conceptual fluency affects moral wrongness ratings. Additionally, it is unclear whether processing fluency (perceptual or conceptual) influences moral judgments other than moral wrongness ratings. For example, as outlined in the introduction section, Spears et al. (2018) found a perceptual (dis)fluency effect on judgments of moral dilemma choices. Specifically, acceptability ratings for utilitarian moral choices were higher when the dilemmas were presented in a perceptual disfluent font as compared to a fluent font. Based on the methodological differences between our studies and the one of Spears 7

and colleagues, we cannot draw any inferences about perceptual (dis) fluency effects on moral dilemma choices. But we would like to point out that—similar to Laham et al.'s (2009) findings—the results of Spears et al. rest on a single study. Furthermore, their sample size is relatively small (n = 51) and the presumed mediation of the (dis)fluency effect by analytic thinking is not without controversy (see Meyer et al., 2015). For these reasons, the findings of Spears and colleagues should be interpreted with caution until their reproducibility has been verified in direct and conceptual replication studies. In sum, our results suggest that unlike other types of judgments, judgments of moral and conventional transgressions are insusceptible to perceptual (dis)fluency. Moreover, although we cannot completely rule out that there are conditions under which processing fluency influences certain types of moral judgments (e.g. acceptability ratings of utilitarian choices), our findings give reason to assume that if anything, fluency plays a negligible role in moral judgments. In contrast, we found negative emotions to be a reliable and strong predictor of moral judgments. We therefore conclude that studies that investigate determinants of moral judgments should necessarily take participants' emotional responses into account. Author contribution statement Lena Nadarevic: Conceptualization, Formal analysis, Investigation, Writing – Original draft, Visualization, Supervision, Project administration. Meike Kroneisen: Conceptualization, Investigation, Writing – Review & Editing, Supervision. Funding This work was supported by a University of Mannheim autonomy grant. Acknowledgements We thank the following people for their help with questionnaire preparation and data collection: Anja Römer (Study 2a), Nicole Oelke (Study 2b), and Julian Quevedo (Study 3). References Alter, A. L., & Oppenheimer, D. M. (2008). Effects of fluency on psychological distance and mental construal (or why New York is a large city, but New York is a civilized jungle). Psychological Science, 19(2), 161–167. https://doi.org/10.1111/j.1467-9280. 2008.02062.x. Alter, A. L., & Oppenheimer, D. M. (2009). Uniting the tribes of fluency to form a metacognitive nation. Personality and Social Psychology Review, 13(3), 219–235. https:// doi.org/10.1177/1088868309341564. Alter, A. L., Oppenheimer, D. M., Epley, N., & Eyre, R. N. (2007). Overcoming intuition: Metacognitive difficulty activates analytic reasoning. Journal of Experimental Psychology: General, 136(4), 569–576. https://doi.org/10.1037/0096-3445.136.4. 569. Bates, D., Mächler, M., Bolker, B., & Walker, S. (2014). Fitting linear mixed-effects models using lme4. https://arxiv.org/abs/1406.5823. Carpendale, J. L. M., & Krebs, D. L. (1992). Situational variation in moral judgment: In a stage or on a stage? Journal of Youth and Adolescence, 21(2), 203–224. https://doi. org/10.1007/BF01537337. Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Hillsdale, N.J: L. Erlbaum Associates. Corey, J. D., Hayakawa, S., Foucart, A., Aparici, M., Botella, J., Costa, A., & Keysar, B. (2017). Our moral choices are foreign to us. Journal of Experimental Psychology: Learning Memory and Cognition, 43(7), 1109–1128. https://doi.org/10.1037/ xlm0000356. Cornwell, J. F. M., & Higgins, E. T. (2016). Eager feelings and vigilant reasons: Regulatory focus differences in judging moral wrongs. Journal of Experimental Psychology: General, 145(3), 338–355. https://doi.org/10.1037/xge0000136. Costa, A., Foucart, A., Hayakawa, S., Aparici, M., Apesteguia, J., Haefner, J., & Keysar, B. (2014). Your morals depend on language. PLoS One, 9, e94842. https://doi.org/10. 1371/journal.pone.0094842. R Development Core Team (2008). R: A language and environment for statistical computing [Computer software]. http://www.R-project.org. DeepL GmbH (2017). DeepL [Computer software]. https://www.deepl.com/translator.

We would like to thank an anonymous reviewer who pointed this out. 10

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