In our first study we sought to examine whether men’s dehumanization and objectification of women relates to their sexual aggression attitudes and interests above and beyond a range of previously established related factors. Specifically, we sought to assess (a) whether dehumanization and objectification of women in general correlate with men’s sexually aggressive attitudes and interests and (b) whether this relationship is maintained when controlling for specific individual differences.

Although our first study was largely exploratory, with no a priori predictions being made about the impact of specific control variables or differences in manifestations of dehumanization (e.g., human nature vs. human uniqueness), we sought to establish initial strong evidence for a direct link between dehumanization and objectification with sexually aggressive attitudes and interests in men. We did expect that there would be relationships between both dehumanization and objectification with all sexual aggression factors that would act as a foundation to experimental tests of causation.

Method

Participants

Our study was reviewed and approved by the institutional ethics board of a large United Kingdom university for compliance with standards for the ethical treatment of human participants prior to study recruitment. A total of 225 men were recruited through an online site, Prolific Academic, and were paid £1.50 (approx. $2). Thirteen failed to complete three or more scales, and 22 people began the study and failed to complete it, leaving a final sample of 190 men. All participants were British male adults who identified as heterosexual. Due to the sensitive nature of the topic, and in hopes of encouraging truthful responding by emphasizing anonymity, no further demographic data were gathered. Prior to full data collection, ten initial participants were run, and we noticed that due to a survey software issue, they were skipping or responding invalidly to a crucial measures, the Other Objectification Questionnaire (OOQ). Their data were not examined in relation to study hypotheses at this time, and the problem was corrected within the Qualtrics survey mechanics platform prior to continuing data collection. Thus, these ten participants’ data were excluded on the OOQ only; they were retained on all other measures.

Procedure and Measures

Participants completed the study online. Following informed consent, all participants completed the Other Objectification Questionnaire (Noll and Fredrickson 1998) and the Human Nature and Human Uniqueness scales (Bastian et al. 2012). They all also completed three dependent variable measures relevant to sexual aggression: the Likelihood to Sexually Harass Scale (LSH; Pryor 1987), the Attraction to Sexual Aggression Scale’s rape proclivity items (ASAI; Malamuth 1989), and the Attitudes toward Rape Victims Scale (ARVS; Ward 1988). To reduce fatigue, the control measures were split such that they were each completed by half the sample based on random assignment. The specific scales included for the two subsamples were chosen such that an equal number of items would be completed by each group. One half (102 men; reduced to 96) completed the Ambivalent Sexism Inventory (ASI; Glick and Fiske 1996), the Masculinity Contingency Scale’s (MCS) threat scale (Burkley et al. 2016), and four Conformity to Masculine Norms Inventory subscales (i.e., risk taking, violence, power over women, and playboy; Parent and Moradi 2011). The other half (101 men; reduced to 94) completed the Short Dark Triad (SD3) scales for narcissism and psychopathy (Jones and Paulhus 2014); the Multidimensional Inventory of Development, Sex, and Aggression’s (MIDSA) sexual sadism subscales (Knight and Cerce 1999); and the physical aggression scale (Wrench 2002). The scale descriptions that follow conform to the order of presentation: dehumanization and objectification measures, then sexual aggression attitudes and beliefs measures, and lastly control measures.

Objectification

The Self-Objectification Questionnaire (SOQ; Noll and Fredrickson 1998) is commonly used in objectification research. Strelan and Hargreaves (2005) modified the SOQ to measure the objectification of others, referring to this as the Other Objectification Questionnaire (OOQ). Employing the latter approach, we asked participants to rank the relative importance of appearance and competence attributes on their evaluation of the bodies of women. This scale has been used similarly with success in past research (Kozak et al. 2009; Loughnan et al. 2015). The scale consists of a total of ten items: five appearance-based (i.e., sex appeal, physical attractiveness, weight, measurements, and toned muscles) and five competence-based (i.e., health, physical fitness level, strength, coordination, and stamina). Participants’ scores were calculated by separately summing the appearance and competence ranks, and then subtracting the sum of the competence ranks from the sum of the appearance ranks. This produced a score ranging from −25 to 25, with higher scores reflecting greater objectification. For ease of interpretation, 25 was then added to all scores to create positive numbers.

Dehumanization

To assess the tendency to deny human nature and human uniqueness, we asked participants to rate a specific woman, as is typical in the literature that has employed these scales. There were four human nature items (e.g., “[this woman] Is emotional, responsive, and warm”; Bastian et al. 2012), measured from 1 (Not at all) to 7 (Very much so) (α = .76). Similarly, there were four human uniqueness items (e.g., “[this woman] Is rational, logical, and intelligent”; Bastian et al. 2012), measured from 1 (Not at all) to 7 (Very much so) (α = .70).

Sexual Harassment Interest

The Likelihood to Sexually Harass Scale (LSH; Pryor 1987) consists of ten scenarios involving a man and a woman and in which male participants are asked to imagine themselves as the male character. To reduce participant fatigue, we modified this scale such that only the five shortest scenarios were used. In each scenario, the male character is in a position of power and three possible courses of action are listed. An example scenario is:

Imagine that you are a Hollywood film director. You are casting for a minor role in a film you are planning. The role calls for a particularly stunning actress, one with a lot of sex appeal. How likely are you to do the following things in this situation?

Participants are asked to assume there would be no consequences for their actions and then rate the likelihood of their engaging in three possible behaviors listed (e.g., as related to the example scenario: “Would you ask the actress to whom you were most personally attracted to talk with you about the role over dinner?”) from 1 (Not at all likely) to 5 (Very likely). Only one of the three courses of action involves sexual harassment, and it is the five summed responses to these critical items across the five scenarios used that form participants’ scale score. The critical response in relation to the example scenario is to the item asking: “Would [you] give the role to the actress who agreed to have sex with you?” Higher scores indicate higher likelihood to sexually harass (α = .90).

Rape Proclivity

The Attraction to Sexual Aggression Inventory (ASAI; Malamuth 1989) measures attraction to various sexual behaviors, including those involved in conventional, unconventional, and deviant sex. For our study, only those 14 items assessing attitudes related specifically to rape and sexual assault were used because they were most relevant to our research question. An example item from this scale is: “How arousing would it be to force a female to do something sexual she did not want to do,” rated from 1 (Not Very Arousing) to 5 (Very Arousing). Mean participant scores were calculated, with higher scores indicating greater rape proclivity (α = .91).

Unfavorable Attitudes Toward Rape Victims

The Attitudes toward Rape Victims Scale (ARVS; Ward 1988) consists of 25 items assessing attitudes concerning victims of rape that correspond with common rape myth endorsement. For example, “the extent of the woman’s resistance should be the major factor in determining if a rape has occurred,” measured from 1 (Strongly Disagree) to 5 (Agree Strongly). Participants’ scores were computed by summing the responses across items, with higher scores indicative of more unfavorable attitudes toward rape victims (α = .91).

Ambivalent Sexism

The Ambivalent Sexism Inventory is a 22-item scale (Glick and Fiske 1996) measuring two facets: benevolent sexism (BS; α = .84) and hostile sexism (HS; α = .94), scaled from 1 (Disagree Strongly) to 6 (Agree Strongly). An example item from the benevolent sexism subscale is: “No matter how accomplished he is, a man is not truly complete as a person unless he has the love of a woman,” whereas an example of an item from the hostile sexism subscale is: “Women seek to gain power by getting control over men.” These related, yet functionally distinct, aspects of sexism are reflected in the two subscales of the measure. Scores for each subscale were averaged, and higher scores indicate stronger levels of sexism.

Masculinity Factors

The Masculinity Contingency Scale (MCS; Burkley et al. 2016) measures the extent that men’s self-worth and identity depend on their personal masculinity, without relying on specific, often culturally dependent norms. We employed the five-item threat subscale, which assesses how much one’s sense of self-worth is threatened by failure to live up to the demands of masculinity (e.g., “My self-worth suffers if I think my manhood is lacking”), rated from 1 (Strongly Disagree) to 5 (Strongly Agree). The threat subscale is more related to negative outcomes for men than the un-used subscale related to boosting self-worth through masculinity (Burkley et al. 2016). Scores were computed by averaging across items, with higher scores indicating greater contingency of self-worth based on masculinity, α = .88.

The Conformity to Masculine Norms Inventory-46 (CMNI-46; Parent and Moradi 2009; Parent and Moradi 2011) measures conformity to specific masculinity norms. We employed four subscales, totaling 19 items, which were the most theoretically relevant to sexual aggression: risk taking (e.g., “I frequently put myself in risky situations,” α = .87), violence (e.g., “Sometime violent action is necessary,” α = .82), power over women (e.g., “In general, I control the women in my life,” α = .79), and playboy (e.g., “If I could, I would frequently change sexual partners,” α = .80). All items were rated from 1 (Strongly Disagree) to 4 (Strongly Agree), with higher mean scores indicating greater conformity to masculine norms.

Dark Triad/Tetrad Personality Factors

The dark triad is a constellation of traits including narcissism, psychopathy, and Machiavellianism, which are associated with non-pathological, yet negative and “dark” personalities (Paulhus and Williams 2002). In addition, emerging literature has suggested a fourth dimension, sadism, forms a “dark tetrad” of personality traits with these others (Chabrol et al. 2009). We measured psychopathy, narcissism, and sadism. We did not measure Machiavellianism because we did not expect it to predict sexual aggression based on lack of theoretical relevance as well as lack of prior literature making such a link. We employed the Short Dark Triad (SD3; Jones and Paulhus 2014), which has nine items per scale, rated from 1 (Disagree Strongly) to 5 (Agree Strongly), to measure narcissism (e.g., “Many group activities tend to be dull without me,” α = .69) and psychopathy (e.g., “Payback needs to be quick and nasty,” α = .70). Participants’ mean scores were computed for each scale, with higher scores indicative of stronger endorsement of each factor. We measured sexual sadism using the Multidimensional Inventory of Development, Sex, and Aggression (MIDSA; Knight and Cerce 1999; Knight et al. 1994; MIDSA 2011). The two subscales we used in our study were the seven-item sadistic fantasy subscale (e.g., “I have thought about embarrassing or humiliating a woman or girl during sex,” α = .77) and the eight-item sadistic behavior subscale (e.g., “I have purposely hurt a woman or girl physically during sex,” α = .83). Both range responses from 1 (Disagree Strongly) to 5 (Agree Strongly), with higher mean scores indicating greater endorsement of sexual sadism.

Physical Aggression

The Physical Aggression Scale (Wrench 2002) is a 15-item scale measuring general physical aggression across three factors: object violence, physical confrontation, and control. Responses are made on a scale ranging from 1 (Strongly disagree) to 5 (Strongly agree), scores were averaged across all items, and higher overall scores indicate greater aggression (α = .85). A sample item is: “When I get upset, I have a tendency to throw objects.”

Results

Analysis Plan and Supplements

Initial t-tests confirmed that there were no significant differences between the two subsamples that were collected on measures of dehumanization, objectification, or sexual aggression (ps > .227), and thus the groups were combined into a single sample for analysis. Pearson’s correlations and descriptive statistics were then computed for all measures in relation to the primary variables of interest and these can be found in Table 1.

Table 1 Study 1 descriptive statistics and correlations among study variables, study 1 Full size table

We next sought to test the relative contributions of objectification, human nature, and human uniqueness to each of the sexual aggression attitudes outcome measures (rape proclivity, unfavorable attitudes toward rape victims, and sexual harassment interest) by running three individual initial regression models (one for each outcome). We then tested the predictor variables retained in each of these initial models against control variables that were correlated with the given outcome to determine if their contribution would remain significant when taking each of these factors into account. To help control for overall error, only variables with correlations at or below the significance level of .001 were entered into these models.

Compiled materials and measures can be viewed at https://osf.io/v3d8x/. Additional analyses for Study 1 were run, including using bootstrapping for all regression models. These produced a similar pattern of results to those reported here and can be found in the authors’ online supplementary analyses (https://osf.io/r832j/ & https://osf.io/s6p3k/). All data for this project are open access, and data for Study 1 can be accessed at https://osf.io/24zbw/ .

Rape Proclivity (ASAI)

The ASAI was positively correlated at p < .001 with both the other sexual aggression attitudes measures and four of the control variables (i.e., the masculine norm of power over women, physical aggression, psychopathy, and hostile sexism) (see Table 1). Of note, the correlation with objectification was in the opposite direction from predictions. We then ran a regression model to test the relative contributions of dehumanization and objectification measures to rape proclivity (Model 1 in Table 2). In this initial regression model, objectification, human nature, and human uniqueness were entered (Adj. R2 = .08). Both objectification (b = −.01, SE = .00, β = −.15, p = .034) and human nature (b = −.14, SE = .05, β = −.29, p = .007) were found to be significant predictors of rape proclivity.

Table 2 Hierarchical linear regression models predicting rape proclivity, study 1 Full size table

Next, objectification and human nature were tested against the four control variables of interest (based on their correlations with rape proclivity) in a series of hierarchical regressions (Models 2–5 in Table 2). For each of these models, in Step 1 objectification and human nature were entered. In Step 2 of each model individual control variables were entered: the masculine norm of power over women (Model 2), physical aggression (Model 3), psychopathy (Model 4), and hostile sexism (Model 5). These results show that in Step 2, objectification was not retained in any models. Neither objectification nor human nature was retained when controlling for psychopathy or physical aggression. However, human nature was retained in Step 2 when tested against hostile sexism (p = .014) and the masculine norm of power over women (p = .029). Thus, human nature continued to significantly contribute to rape proclivity while controlling for two of four additional predictors.

Unfavorable Attitudes Toward Rape Victims (ARVS)

The ARVS was positively correlated at p < .001 with both the other sexual aggression attitude measures and nine control variables (the masculine norm of power over women, hostile sexism, psychopathy, physical aggression, masculine contingency, the masculine norm of risk taking, the masculine norm of violence, narcissism, and benevolent sexism) (see Table 1). In the initial regression model to test the relative contributions of dehumanization and objectification measures to unfavorable attitudes toward rape victims, objectification, human nature, and human uniqueness were entered (Adj. R2 = .05). Human uniqueness was the only significant predictor retained (b = −.14, SE = .07, β = −.23, p = .038). Thus, human uniqueness was then tested against the nine correlated control variables in a series of hierarchical regressions (Models 1–9 in Table 3). For each of these models, in Step 1 human uniqueness was entered, and in Step 2 individual control variables were entered. These models show that human uniqueness was retained in Step 2 when controlling for psychopathy (p = .038), benevolent sexism (p = .025), and the masculine norm of violence (p = .025). However, human uniqueness was not retained in Step 2 of the models testing against narcissism, physical aggression, hostile sexism, the masculinity contingency scale, or the masculine norms of risk taking and power over women. In sum, human uniqueness continued to contribute to negative attitudes toward rape victims in one-third of the models.

Table 3 Hierarchical linear regression models predicting unfavorable attitudes toward rape victims, study 1 Full size table

Sexual Harassment Interest (LSH)

The LSH scale was positively correlated with both the other sexual aggression attitudes measures and the majority of control measures (see Table 1). Of note, the correlation with objectification was in the opposite direction from our predictions. In the initial regression wherein objectification, human nature, and human uniqueness were entered (Adj. R2 = .04), only objectification significantly predicted sexual harassment interest (b = −.09, SE = .03, β = −.20, p = .007) and was retained for testing against control variables. However, objectification did not remain significant in any of these additional models, except for when it was tested while controlling for the masculine norm of risk taking (b = −.08, SE = .04, β = −.20, p = .048). In sum, objectification did not generally significantly contribute to men’s likelihood to sexually harass when controlling for additional variables and was acting in opposition to our predictions.

Discussion

Results of Study 1 provide initial support for a correlational relationship between dehumanization and men’s explicit endorsement of sexual aggression interest and beliefs. In multiple cases, this relationship emerged above and beyond the variance accounted for by relevant control variables. In the case of rape proclivity, human nature was retained in two of four models when tested against controls. The correlations between the controls that also correlated with rape proclivity (i.e., the masculine norm of power over women, psychopathy, physical aggression, and hostile sexism) may hint at an underlying personality construct. Endorsement of unfavorable attitudes toward rape victims retained human uniqueness in three of nine models tested. The involvement of different types of human qualities as relevant to rape proclivity versus unfavorable attitudes toward rape victims may indicate that there are differences between the role of dehumanization in attitudes about victims versus attitudes toward the act of sexual aggression itself.

Objectification yielded much less consistent results, indeed showing unexpected negative correlations with rape proclivity and likelihood to sexually harass, as well as generally failing to be maintained when controlling for other variables. On the less extreme end of our conceptualization of sexual aggression, interest in sexual harassment was in fact only correlated (negatively) with objectification, and not with measures of dehumanization. These odd results concerning objectification may be an artifact of the scale used, and results should therefore be interpreted with caution.

Despite some null and mixed findings for likelihood to sexually harass and objectification, the results for dehumanization remain strong across multiple outcomes, and they point to a robust relationship due to the amount of control exerted by including potential confounds. Dehumanization may come into play later in the progression of events leading up to violence. If sexual aggression is conceptualized as a continuum of severity ranging from sexual harassment to rape, as we did here, based on the results of Study 1, dehumanization is most relevant in contexts of extreme aggression and more severe forms of mistreatment. It is possible that dehumanization emerges as a form of self-justification as thoughts and attitudes escalate toward actual violence, and it is employed less consistently when assessing victims post-hoc. This possibility points to a potential avenue for further research on why and when some men sexually aggress.