Why do people self-report an aversion to words like “moist”? The present studies represent an initial scientific exploration into the phenomenon of word aversion by investigating its prevalence and cause. Results of five experiments indicate that about 10–20% of the population is averse to the word “moist.” This population often speculates that phonological properties of the word are the cause of their displeasure. However, data from the current studies point to semantic features of the word–namely, associations with disgusting bodily functions–as a more prominent source of peoples’ unpleasant experience. “Moist,” for averse participants, was notable for its valence and personal use, rather than imagery or arousal–a finding that was confirmed by an experiment designed to induce an aversion to the word. Analyses of individual difference measures suggest that word aversion is more prevalent among younger, more educated, and more neurotic people, and is more commonly reported by females than males.

Copyright: © 2016 Paul H. Thibodeau. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Of note, these studies yielded large and complex data sets. The present paper focuses on the specific research questions outlined above and elaborated on below. However, the data have been made available through the Open Science Framework (osf.io/3jwd4) and may provide a foundation for investigating a number of other important research questions.

In addition, in Experiment 5, participants were asked to make a moral judgment about the acceptability of incest between siblings [ 23 ]. This scenario has several properties in common with word aversion: both seem to tap into an intuitive, emotionally driven, sense of disgust that people do not seem to describe accurately. The tendency to misattribute the cause of a moral judgment has been coined “moral dumbfounding” [ 24 ]. The results of the current experiments suggest an analogous “aversion dumbfounding”: moist-aversion is grounded in semantic associations, although moist-averse participants often point to phonological features of the word as the perceived source of their reaction. Along with highlighting parallels between these psychological phenomena, this measure allows for further investigation of the origin of word aversion. If people are averse to “moist” because the word has sexual connotations, one would expect moist-averse participants to find consensual incest between siblings less acceptable.

In each experiment, we asked people to speculate directly on why they found “moist” aversive (if they did), or why they thought other people find the word aversive (if they didn’t). We compare this explicit speculation to the more implicit measures in order to test whether participants’ meta-linguistic awareness aligns with their actual behavior. We also collected several individual difference measures (e.g., of disgust, the Big Five personality dimensions, and demographic variables) to help identify factors of individuals that predict who is likely to experience word aversion.

Along with investigating differences between people who did and did not report an aversion to moist, we included a contextual manipulation in these experiments. Sometimes “moist” was preceded by items that were designed to prime a sexual or culinary sense of the word (e.g., “pussy” or “cake”); other times it was preceded by unrelated negative or positive words to control for valence (e.g., “retarded” or “paradise”). We expected that priming a positive, culinary, sense of “moist” would make the word seem less aversive and that priming a sexual connotation of the word would make it seem more aversive. We use the results of the context manipulation as a reference point for characterizing the subjective experience of word aversion (e.g., are differences between moist-averse and non-averse participants similar in magnitude to expected differences that result from a context manipulation?).

Experiments 4 and 5 were designed to induce an aversion to “moist” among participants in the sample and thereby test whether an aversion to “moist” is transmitted socially or through a process of conscious deliberation (or both) [ 20 ]. People may report an aversion to “moist” because they are conforming to a social norm and/or because, after careful thought, it seems to have phonological properties or semantic associations that make it unpleasant (e.g., as a participant in Experiment 2 explained: “I’m not sure I did [think “moist” was aversive] until other people pointed out that they did. Then it started to bother me as well.”).

Because Experiment 1 relied on explicit judgments, which may not accurately track underlying psychological processes, more implicit measures of word aversion were used in Experiments 2 and 3: a free association and surprise recall task, respectively. If participants really do find the word “moist” aversive, then responses in a free association task may help to reveal why [ 21 ]. People who find “moist” aversive may be more likely to generate a lexical associate related to disgust–especially if the semantic connotation of “moist” is responsible for the aversion. Moist-averse participants should also be more likely to recall having rated the word in a surprise recall task if it has a stronger emotional valence for them [ 22 ].

Five experiments were designed to address specific questions about word aversion. In the first, participants were asked to judge words along a variety of dimensions. Some of the words had similar semantic properties to “moist” (e.g., “damp” and “wet”); some of the words came from lexical categories that commonly elicit disgust (e.g., words that are used in a sexual context like “horny” and “fuck”; and words related to bodily excrement like “phlegm” and “vomit”); others had similar phonological properties to “moist” (e.g., “hoist” and “foist”). If people are averse to “moist” for semantic reasons, they should also find semantically related words and/or words related to disgust unpleasant. If people are averse to “moist” for phonological reasons, they should also find words like “foist” and “hoist” unpleasant.

A third possibility is that the semantic neighborhood of aversive words makes them unpleasant. “Moist” may have become contaminated, a symbol and elicitor of disgust, by virtue of its association with sex or bodily function [ 14 ] (e.g., another participant in Experiment 1 said: “it reminds people of sex and vaginas”). On this view, it may be possible to identify a cluster of words in the lexicon as aversive. Such a finding would contribute to a growing literature on the processing of highly valenced and arousing words [ 15 – 19 ] and speak to current debates on the role of culture in the psychology of disgust [ 20 ].

A second possibility, also related to phonology, is that words like “moist” are aversive because speaking them engages facial muscles that correspond to expressions of disgust: a facial feedback hypothesis [ 9 – 10 ]. For instance, one set of studies found that people disliked words with vowels that require speakers to constrict their zygomatic muscles (e.g., as in the German diphthong /yːr/ in für)–possibly because such constriction reduces blood flow through the cavernous sinus and raises cerebral temperature [ 11 – 12 ]. The facial feedback hypothesis is controversial, however, and investigations of word aversion may help to shed light on this theory and other embodied views of language and emotion (e.g., [ 13 ]).

Of particular interest is this last question, for which four hypotheses have been proposed. One possibility is that the phonology of certain words is inherently unpleasant. This is an explanation that people with an aversion to the word “moist” sometimes provide: for instance, one participant (from Experiment 1), speculating on their aversion, drew attention to “the ‘oy’ sound juxtaposed to ‘ss’ and ‘tt’. It’s not a word that sounds pleasant. Neither does hoist or foist.” Cognitive scientists have historically viewed sounds in a language as arbitrary with no inherent meaning [ 3 ]. However, some have argued that sound symbolism is a natural byproduct of enculturation in a language [ 4 ] and cross-cultural studies have found some evidence of sound symbolism beyond onomatopoeia [ 5 – 8 ].

The current paper addresses foundational questions related to word aversion, focusing on “moist” as a case study since it appears to garner the strongest feelings of aversion among the American public: 1) Approximately what proportion of the population reports an aversion to words like “moist”? 2) Are there individual difference variables that predict who is likely to experience word aversion? 3) Is aversiveness a dimension of words that can be measured reliably? And 4) What makes a word aversive in the first place?

Many people report that they find words like “moist,” “crevice,” “slacks,” and “luggage” acutely aversive. For instance, People Magazine [ 1 ] recently coined “moist” the “most cringeworthy word” in American English and invited their “sexiest men alive” to try to make it sound “hot.” One writer, in response, described the video as “…pure sadism. It’s torture, it’s rude, and it’s awful…” and claimed that the only way to overcome the experience was to “go Oedipal and gouge your eyes out” [ 2 ]. Indeed, readers who find the word “moist” aversive may experience some unpleasantness in reading this paper.

Finally, participants in all five studies were asked demographic (i.e., age, gender, educational background, and political ideology) and personality questions: a Ten Item Personality Inventory (TIPI), which is a brief measure of the Big Five personality traits [ 28 ]. Three measures of individual difference variables were presented to participants in Experiments 2–5 (but not to participants in Experiment 1): blirtatiousness, which measures the extent to which people respond to others quickly and effusively that has been shown to capture how physiologically aroused a person becomes in response to unpleasant stimuli [ 29 ]; a measure of disgust [ 30 ]; and a measure of religiosity [ 31 ]. The measure of religiosity was included in order to identify the source of a potential link between word aversion and disgust (e.g., a religiously-associated motivation for purity and cleanliness; [ 32 ]).

The free response question was coded by two independent raters who categorized the explanations into one of four mutually exclusive and exhaustive categories: those that identified 1) the sound alone; 2) the connotation alone; 3) both the sound and connotation; 4) or neither the sound nor the connotation. Inter-rater reliability was high for this coding scheme (Cohen’s Κ was between .7 and .85 in the five experiments); disagreements were resolved through discussion.

All participants were asked if they found “moist” aversive (yes or no) and to speculate either on “why you find it aversive?” or “why you think other people are averse to it?” (free response). In most experiments, these two questions were asked at the end of the survey; in Experiment 4, this question was asked at the beginning of the survey.

After rating the 64 words, participants were asked to “write all of the words that you can remember rating on the previous screens.” They were instructed to “do your best to recall the words from memory”; the survey prevented them from going back to previous pages.

The 64 words were divided into four blocks of 16 items. The order of most of the words varied randomly within their respective blocks; the orders of the blocks were fixed; blocks were presented on separate pages; words from the six categories identified in Experiment 1 (e.g., words related to sex and bodily function) were evenly distributed across blocks. However, the word “moist” was fixed to position 38 (the sixth word in the third block)–a position for which one would expect a low rate of recall [ 27 ]. The same three words (murderer, gold, shithead) always initiated the third block and were followed by two words that were either positive or negative and either related or unrelated to “moist” (i.e., the same words used to induce a context effect in Experiment 1).

The 36 additional words were carefully selected so as not to induce a semantic category effect for the word “moist” [ 26 ]. They included mostly positive unrelated (e.g., bride, fruit, happy) or negative unrelated words (e.g., anger, pain, war) taken from prior research [ 25 ].

Participants in Experiment 3 were asked to rate 64 words – 28 of the 29 items from the previous three experiments as well as 36 additional words (the word “buttfuck” was removed from the set in this experiment because of its similarity to “fuck”)–for their positive or negative connotation. Both sets of ratings were made on a five-point scale: from “Not at all positive” to “Very positive” or from “Not at all negative” to “Very negative.” The scales were carefully designed to focus participants’ attention on the positivity or negativity of the words: for instance, the low end of the positive scale was not anchored with the word “very negative” but instead by a negation of the word “positive.”

Two independent coders categorized responses to “moist” into five categories, which emerged from reading the range of responses given by participants: wet, yuck, sex, food, and other. Inter-rater reliability for this coding scheme was high (Cohen’s Κ = .835); disagreements were resolved through discussion.

In Experiment 2, participants were presented with the same set of 29 words in the same pseudo-random order as in Experiment 1 (with the same context manipulation induced by words that immediately preceded “moist”). However, instead of rating these words, participants were instructed to reply with the first word that came to mind.

In Experiment 5, participants who watched either video were asked a catch question (e.g., to identify an actor from the video). They were also asked whether the volume on their computer was on. People who responded incorrectly to a catch question or reported they did not hear the audio were excluded from analyses (n = 51; 8% excluded).

There were two differences between Experiment 1 and Experiment 5. First, in Experiment 5 the word “moist” was positioned at the end of the survey rather than toward the beginning (position 29 rather than 6). Second, the context manipulation in this experiment involved three between-subjects conditions: one third of participants were exposed to a video produced by People Magazine [ 1 ], in which some of “the sexiest men alive” spoke the word “moist”; one third of participants were exposed to a video of people using the word “moist” to describe the taste of cake; a final group was not shown a video. The second video (cake) was filmed by the researchers and was designed to be similar to the one made by People. Both videos included 5 actors who said the word “moist” in quick succession without elaboration (total time: ~30 seconds). Although the actors in the original video occasionally giggled or muttered “gross” or “yuck” quietly after saying “moist,” actors in the control video were instructed not to make such expressions. Instead, they were shown eating a piece of cake and then saying “moist.” Their utterance was often accompanied by a nod or an approving look toward the cake so that it was clear that “moist” was being used to describe a positive experience.

There was one difference between the designs of Experiment 1 and Experiment 4. Whereas in Experiment 1 participants were asked to rate the 29 target words before they identified as categorically moist-averse (or not), this judgment was made at the beginning of the study in Experiment 4.

The words were presented in pseudo-random order. In Experiments 1 and 4, three words, which were designed to anchor participants’ ratings of aversiveness, initiated the survey (murderer, gold, and shithead). These items were followed by two words from one of four categories that were expected to influence the sense of “moist” that participants brought to mind: 1) related and positively valenced (cake, delicious), 2) related and negatively valenced (fuck, pussy), 3) unrelated and positively valenced (paradise, heaven), and 4) unrelated and negatively valenced (nigger, retarded). Words from the two semantically related conditions were designed to prime a sexual or culinary sense of “moist”; the unrelated negative and positive conditions served as a control to the general manipulation of valence. “Moist” was fixed to the sixth position of the questionnaire. The remaining words were presented in random order with one final exception: the word “love” was always the final item that participants’ rated. It was fixed to this position so that participants’ would end the survey having considered a positive item.

One of the 29 target words was “moist”; the remaining 28 words came from 6 lexical categories, including: 1) five words that were semantically related to “moist” (damp, dank, muggy, sticky, wet); 2) three words that had similar phonological properties to “moist” (foist, hoist, rejoiced); 3) three negatively valenced words relating to bodily function (phlegm, puke, vomit); 4) four words relating to sex (buttfuck, fuck, horny, pussy); 5) four unrelated negative and taboo words (murderer, nigger, retarded, shithead); and 6) nine positively valenced words (brave, cake, delicious, gold, heaven, love, paradise, sunset, sweet).

Ratings were made on 101-point scales that ranged from -50 to 50; for clarity of presentation these ratings have been shifted up by 50 units so that reported means have positive values between 0 and 100. The rating scales and 15 of the filler words were taken from prior work on taboo and emotionally valenced words [ 25 ].

In Experiments 1, 4, and 5 participants rated 29 words along six target dimensions that have previously been studied in relation to taboo and emotionally valenced words [ 25 ]: personal use, familiarity, aversiveness, valence, arousal, and imagery (see Table 3 ). Of note, Janschewitz’s [ 25 ] questions about the tabooness and offensiveness of words were replaced with a single question about the aversiveness of words in the present studies. This change was made because neither tabooness nor offensiveness seemed to capture the dimension along which words like “moist” are distinctive.

In most experiments, participants were asked whether they identified as categorically averse to “moist” at the end of the study. However, in Experiment 4, participants were asked to identify as categorically moist-averse at the beginning–to investigate how the ratings task might influence whether people identified as a categorically “moist” averse (and vice versa).

The materials and design for the five experiments were similar. The specific tasks that participants completed in each experiment and the order in which they completed them are shown in Table 2 ; methodological details for each experiment are presented in detail below. In Experiments 1, 4, and 5, participants rated a set of 29 target words along six dimensions. In Experiment 2, participants were exposed to these same words and replied with the first word that came to mind in a free association task. In Experiment 3, participants rated a larger set of words along one of two dimensions (positive or negative connotation); then they were presented with a surprise recall task.

These five experiments are a nearly exhaustive set of exploratory studies on this topic from our lab. One additional study was conducted (similar to Experiment 3) and is described in the S1 Text . A coding error in this version of the experiment prevented collection of critical information about participants in this sample.

Demographic characteristics of the five samples are shown in Table 1 . Participants were not permitted to complete related experiments (e.g., if a participant in Experiment 5 had participated in Experiment 1, their data from Experiment 5 was excluded from analysis). The sample size in Experiment 1 was set to include 100 participants per condition because of the exploratory nature of the work. Sample sizes for Experiments 2–4 were set to be consistent with that of Experiment 1 (100 per condition); the sample size for Experiment 5 was larger (200 per condition) because more attrition was expected.

Participants in all five experiments were recruited through Amazon’s Mechanical Turk using the same inclusion criteria: participants had to be at least 18 years of age, live in the US, and have a good performance rating (>90% approval rating). Participants were told in advance that they would encounter words that could be upsetting, although no specific words were identified explicitly in the description of the task.

The experiments reported here were done in accordance with the Declaration of Helsinki. Additionally, they followed the ethical requirements of the Oberlin College Institutional Review Board and complied with ethics guidelines set forth by the IRB recommendations; the Oberlin College Institutional Review Board reviewed and approved the protocol for studies presented here. Participants were informed that their data would be treated anonymously and that they could terminate the experiment at any time without providing any reason. We received informed consent from all participants before they participated in an experiment. The first page of the study described the potential risks and benefits of participation. Upon agreeing to these conditions, participants clicked a radio button as an indication of their consent; they were then provided with additional instructions and the experimental materials.

Results

The results section is organized around specific research questions. The first subsection describes three results that help characterize the phenomenon of word aversion, showing that it can be quite visceral. The second subsection quantifies the prevalence of moist-aversion and identifies characteristics of individuals who report experiencing the phenomenon. The remaining subsections seek to uncover the cause of word aversion by investigating whether people who identify as moist-averse are also relatively sensitive to words that have similar semantic or phonological properties to “moist” and by comparing the lexical profile of “moist” to the profile of disgusting and taboo words.

What is word aversion? Ratings data from Experiment 1, free response data from Experiment 2, and recall data from Experiment 3 help to characterize the subjective experience of word aversion. For instance, in Experiment 1, people who reported an aversion to “moist” tended to rate the word as 24.06 units higher on a 101-point scale of aversiveness. This between-group difference is comparable to the difference in aversivness, in ratings from the full sample of participants, between “nigger” and “phlegm” (23.2 units; two words that were judged to be above the midpoint of the aversiveness scale) as well as to the difference between “fuck” and “delicious” (25.8; two words that were judged to be below the midpoint of the aversiveness scale). The context manipulation in this experiment further helps to interpret what it means to be averse to a word. In Experiment 1, the word “moist” was preceded by two words that were either semantically related or not and either negatively or positively valenced. Participants’ rating of the aversiveness of “moist” differed as a function of this manipulation, F[3, 396] = 2.666, p = .048, η2 = .020. People found “moist” more aversive when it followed unrelated positive words (M = 36.812, 95%CI: [31.304, 42.320]) or sexual words (M = 36.188, 95%CI: [30.360, 42.016]) and less aversive when it followed food primes (M = 31.520, 95%CI: [26.032, 37.008]) or unrelated negative words (M = 26.969, 95%CI: [21.591, 32.348]). The largest difference between conditions was 9.84 units, which was the result of a contrast effect between the unrelated negative and unrelated positive conditions [33], and is small compared to the difference between moist-averse and non-averse participants (Cohen’s d = .355 compared to .854). Free response data from Experiment 2 revealed that word aversion can be acute. In this experiment, participants were asked to write the first word that came to mind in response to each word in the set. Responses to “moist” were coded into one of five mutually exclusive categories–wet, yuck, sex, food, and other–and a chi-square test of independence revealed a significant difference in the kinds of words that averse and non-averse participants gave in response, χ2[df = 4, N = 370] = 50.200, p < .001, V = .737 (a similar result was obtained from an analysis in which the other category was removed, χ2[df = 3, N = 357] = 50.400, p < .001, V = .639; [34]). Moist-averse participants were noteworthy for their tendency to respond with a word like “yuck” or “eww”, χ2[df = 1, N = 370] = 44.648, p < .001, V = .347; they were marginally less likely to reply with a synonym for “moist” like “wet,” χ2[df = 1, N = 370] = 3.201, p = .074 (see Fig 1). PPT PowerPoint slide

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larger image TIFF original image Download: Fig 1. Lexical Associates. Proportions of lexical associates from moist-averse and non-averse participants by category. Error bars denote 95% confidence intervals. Asterisk indicates a statistically significant difference at the p < .001 level. https://doi.org/10.1371/journal.pone.0153686.g001 Finally, Experiment 3 revealed an influence of word aversion on memory. In this experiment, participants rated a set of 64 words and were then presented with a surprise recall task. The word “moist” was rated in the third of four blocks (fixed to position 38 of 64), yet was recalled by a surprisingly large number of participants (50.7%, 95%CI: [.470, .544])–especially those who reported an aversion to the word (61.2%, 95%CI: [.536, .695] compared to 47.9%, 95%CI: [.438, .521]), χ2[1, N = 688] = 7.264, p = .007, V = .103 (see Table 4). PPT PowerPoint slide

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larger image TIFF original image Download: Table 4. Most and Least Frequently Recalled Words. https://doi.org/10.1371/journal.pone.0153686.t004 Together data from these three experiments help to characterize what it means to be averse to a particular word. The phenomenon is characterized by a visceral response to the aversive word, which can be seen directly in subjective ratings of word aversiveness, and in the responses of participants in a free association task. In addition, people with an aversion to “moist” were significantly more likely to remember and report having encountered the word in a surprise recall task.

How common is word aversion and who experiences it? In Experiments 1–5, 20.5% (n = 82, 95%CI: [.168, .247]), 15.1% (n = 57, 95%CI: [.168, .247]), 18.9% (n = 108, 95%CI: [.168, .247]), 13.2% (n = 49, 95%CI: [.168, .247]), and 20.2% of participants (n = 139, 95%CI: [.168, .247]) reported a categorical aversion to the word “moist.” At least three methodological factors influenced this judgment: 1) when participants were asked the question, 2) whether the experiment involved a rating task, and 3) the dimensions along which ratings were made. First, participants were less likely to report an aversion to “moist” when they were asked to identify as categorically averse at the beginning of the study, before having rated the target items (Experiment 4) compared to the end, after they had rated the target items (Experiment 1), χ2[df = 1, N = 777] = 7.433, p = .006, V = .098. Second, participants were less likely to report an aversion to “moist” when they had engaged in a free response (Experiment 2) rather than a rating task (Experiment 1), χ2[df = 1, N = 770] = 6.664, p = .010, V = .093. Third, participants were more likely to find “moist” aversive after having rated it (and other target items) for a positive (24.9%, 95%CI: [.206, .298]), rather than a negative (15.7%, 95%CI: [.122, .198]), connotation (Experiment 3): χ2[df = 1, N = 688] = 8.572, p = .003, V = .112. These results suggest that the rating task itself (indeed, nuances of the rating task) may have contributed to participants’ judgment about their own aversion to “moist,” and that word aversion may result, at least in part, from an explicit consideration of a word’s lexical properties. Further, for many people, a negative connotation of “moist” may be particularly salient or difficult to suppress, leading to a contrast effect when rating words for a positive connotation [33], as people were most likely to report a categorical aversion to “moist” after rating the word for a positive connotation (in Experiment 3). To investigate who is likely to experience word aversion we analyzed demographic and personality variables. Table 5 shows the proportion of moist-averse participants by demographic and personality variable. PPT PowerPoint slide

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larger image TIFF original image Download: Table 5. Demographics of Word Aversion. https://doi.org/10.1371/journal.pone.0153686.t005 To conduct statistical tests on the relationship between these individual difference measures and word aversion, we aggregated data across the four experiments that included all of the individual difference measures (Experiments 2–5, excluding those who declined to respond to any of these measures; N = 1,873 analyzed). We conducted separate tests of the relationships between the individual difference measures and moist-aversion, which revealed differences by gender, age, blirtatiousness, disgust toward bodily function, and neuroticism (see Table 5). Due to the covariation between these measures, a logistic regression model with predictors for age, gender, sub-components of the disgust scale (e.g., disgust related to bodily function and disgust related to sex), religiosity, and the Big Five personality dimensions (openness, conscientiousness, extraversion, agreeableness, and neuroticism) was also fit to the data. To find the best fitting model, we utilized a stepwise model selection algorithm from the MASS library in R [35]. This algorithm takes a maximally parameterized model and tests alternatives that include subsets of predictor variables by comparing AIC values (by both pairing down from the maximally parameterized one and working up from the minimally parameterized one) in order to find the best fit for the data [36]. Table 6 shows the results of the best fitting model (AIC = 1602.8; AIC for the maximally parameterized model = 1615.2; AIC for a model without predictors = 1728.5), which suggests that the prototypical moist-averse person is a young, neurotic, female who is well-educated and somewhat disgusted by bodily function. This model is largely consistent with the results shown in Table 5, although the logistic regression model omitted the measure of blirtatiousness (which was significantly related to each of the variables that were included in the final model) and included participants’ educational background. PPT PowerPoint slide

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larger image TIFF original image Download: Table 6. Predicting Word Aversion by Individual Differences. https://doi.org/10.1371/journal.pone.0153686.t006 The relationships between gender, age, and neuroticism to word aversion is consistent with prior work on disgust (e.g., [37–38]). Females, younger individuals, and people who express more neuroticism tend to be more sensitive to disgust. The influence of education seems more uniquely related to the phenomenon of word aversion. The relationship between word aversion and disgust for bodily function, and not disgust for sex, suggests possible support for a specific semantic relatedness hypothesis–that aversion to “moist” may be grounded in associations to effluvia [39]. We tested for converging evidence for the hypothesis that word aversion is related to (specific) semantic associations of “moist” in the sections below by, for instance, investigating whether moist-averse participants were sensitive to the cluster of words related to bodily function (e.g., phlegm, puke, vomit), the cluster of words related to sex (e.g., fuck, horny, pussy), and to words with similar phonological properties to “moist” (e.g., foist, hoist, rejoiced).

Did people who found “moist” aversive also condemn incest? The results so far suggest that “moist” is aversive because of its semantic connotation and may be grounded in a disgust elicited by bodily function. However, in Experiment 4, moist-averse participants also rated sexual words as more aversive, suggesting that feelings of disgust associated with sex may also contribute to word aversion. To further explore the relationship between word-aversion and disgust, we asked participants in Experiment 5 to make a moral judgment about the acceptability of incest between siblings [23]. If moist-aversion is related to sex, one would expect moist-averse participants to find consensual incest to be less morally acceptable. An independent samples t-test revealed no difference between groups, t[570] = .941, p = .347, a result that, in concert with the ratings data and the analysis of individual measures, suggests that moist-aversion is more strongly related to a non-sexual aspect of disgust (i.e., to bodily function).

What is the lexical profile of an aversive word? Two methods were used to assess the lexical profile of “moist.” In Experiment 3, half of participants rated words for their positive connotation while the other half rated words for their negative connotation. One potentially distinguishing feature of the word “moist” (as well as many other words cited as aversive) is that it has both strongly positive and strongly negative connotations (e.g., associations with cake and armpits). These distinct senses of “moist” may lead to a dissonant experience of the word that imparts the aversion (e.g., the word may simultaneously call to mind cake and armpits). Evidence for such a possibility would be found if “moist” was rated as having both strongly positive and strongly negative connotations. We found that, across the full set of items, ratings of positive and negative connotations were highly correlated, r[62] = -.863, p < .001. However, there was also a non-linear relationship between the positive and negative ratings of the target words. A regression model revealed significant linear, β = -6.852, SE = .316, p < .001, and quadratic, β = 3.158, SE = .316, p < .001, relationships between the positive and negative ratings of the words (adjusted-R2 = .900). According to a Kolmogorov-Smirnov Test, the two sets of ratings data were similarly distributed, D = .141, p = .552; however, as shown in Fig 4, the relationships between the positive and negative words differed as a function of how positive/negative the words were. The solid line in Fig 4 depicts this relationship as it was characterized by the regression model (i.e., with a combination of linear and quadratic functions). Words that were rated has having only a slightly negative connotation (roughly less than 2.5) showed a strong linear correlation between ratings of their positive and negative connotations, r[38] = -.903, p < .001; words that were rated has having a more negative connotation (greater than 2.5) were judged as having a fairly low positive connotation. The positive and negative connotation ratings for these words was weaker, r[22] = -.449, p = .028, and showed less variability along the positive dimension (s2 = .059 compared to s2 = .628, F[1, 62] = 89.050, p < .001, η2 = .590). The words “pussy” and “fuck” were notable exceptions to this pattern: possibly because these words can be used both pejoratively and to describe positive sexual experiences. PPT PowerPoint slide

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larger image TIFF original image Download: Fig 4. Positive and Negative Connotations. Relationship between ratings of the 64 words’ negative and positive connotations. The dotted line represents what would be expected if the ratings of the words’ negative connotations were perfectly anti-correlated with the words’ positive connotations. The solid line reflects predicted values from the regression line, which revealed linear and quadratic relationships between the ratings. Items that deviated from the general pattern and “moist” are identified with labels. https://doi.org/10.1371/journal.pone.0153686.g004 “Moist” was rated close to the midpoint of the positive (M = 1.915, 95%CI: [1.867, 1.962]; median for all words = 2.381) and negative scales (M = 2.546, 95%CI: [2.496, 2.596]; median for all words = 2.091). Unlike “pussy” and “fuck,” and contrary to our prediction, it was not rated as having both unusually strong positive and negative connotations. A second way in which we sought to characterize the lexical profile of aversive words was by quantifying “moist” along six target dimensions (Experiments 1, 4, and 5)–personal use, familiarity, aversiveness, valence, arousal, and imagery–a paradigm that has been used to study the lexical profile of taboo and emotionally valenced words [25]. In prior work, taboo and disgusting words were found to be associated with a negative valence and a large difference between, on the one hand, familiarity, and on the other hand, personal use and offensiveness: people were highly familiar with these words but did not use them and found them offensive. Neither taboo nor disgusting words were noteworthy for their imageability or arousal, relative to other positive and negative words. For participants who reported an aversion to “moist,” the pattern of ratings data for “moist” showed some similarity to this profile: “moist,” for averse participants, was notable for its aversiveness, valence, and personal use, rather than imagery or arousal. However, unlike what was found for taboo words, moist-averse participants also reported less familiarity for “moist” compared to non-averse participants (see Table 9 and Fig 5). One explanation for this difference is that averse participants may have a more negative sense of “moist” in mind when making this rating, thereby making the word seem less familiar. PPT PowerPoint slide

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larger image TIFF original image Download: Fig 5. Moist Ratings by Aversion. Ratings of “moist” along six dimensions grouped by participants who identified as moist-averse or non-averse. Error bars denote standard errors of the means. Asterisks indicate statistically significant differences at the p < .001 level. https://doi.org/10.1371/journal.pone.0153686.g005 PPT PowerPoint slide

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larger image TIFF original image Download: Table 9. Differences in Rated Dimensions of Moist. https://doi.org/10.1371/journal.pone.0153686.t009