Attitude May Be Everything,But Is Everything an Attitude? Cognitive Distortions May Not Be Evaluations of Rape

Abstract

Cognitive distortions are often referred to as attitudes toward rape in theory, research, and clinical practice pertaining to sexual aggression. In the social-psychological literature, however, attitudes are typically defined as evaluations; thus, in this context, attitudes toward rape are considered evaluations of rape (e.g., rape is negative vs. positive). The purpose of the current study was to explore whether a widely used measure of cognitive distortions (RAPE Scale; Bumby, 1996) assesses evaluation of rape, and, if not, whether evaluation of rape and the cognitions assessed by the RAPE Scale are independently associated with sexually aggressive behavior. Participants (660 male undergraduate students) completed the RAPE Scale as well as measures of evaluation of rape and sexually aggressive behavior. An exploratory factor analysis revealed that the RAPE Scale items formed a correlated but distinct factor from the Evaluation of Rape Scale items. Regression analyses indicated that the Evaluation of Rape Scale and the RAPE Scale had small to moderate independent associations with self-report measures of sexually aggressive behavior. Our results suggest that evaluation of rape may be distinct from cognitive distortions regarding rape, and both evaluation and cognitive distortions may be relevant for understanding sexual violence.

Keywords

attitudes cognitive distortions sexual aggression rape factor analysis

Consider the following scenario: Ron is 6-feet tall and weighs 150 pounds. He is a long-distance runner and runs 2 or 3 marathons each year. Ron meets with a personal trainer who asks Ron to do the “barbell test,” in which he must lift the heaviest barbell he can. The trainer explains that cardiovascular fitness is the ability to lift heavy weight, and that he uses the barbell test to assess cardiovascular fitness. The heaviest weight Ron can lift is 30 pounds. Based on Ron’s relatively poor performance on the barbell test, the trainer tells Ron that he has poor cardiovascular fitness and explains the associated increased risk of heart attack and stroke. He prepares a training program for Ron to remedy his poor cardiovascular fitness that involves lifting heavy weights at the gym. At the end of the training program, the trainer again assesses Ron on the barbell test and finds that Ron can now lift 100 pounds. He congratulates Ron and tells him that his performance on the barbell test indicates he has made dramatic improvements in his cardiovascular fitness.

Ron’s trainer has conflated cardiovascular fitness with muscle strength. Although cardiovascular fitness and muscle strength are related, they are distinct aspects of one’s fitness. Ron likely had excellent cardiovascular fitness to begin with (marathon runner), but he was lacking in muscle strength (could not lift more than 30 pounds). Contrary to the trainer’s intentions and interpretations, neither his assessment nor intervention actually addressed Ron’s cardiovascular fitness. Have theorists, researchers, and clinicians made a similar mistake by conflating cognitive distortions regarding rape with attitudes toward rape? Although the definition of cognitive distortions is usually unclear and inconsistent in the literature, “the general consensus is that sexual offenders’ cognitive distortions reflect thoughts about children, women, the world, and themselves that seem to facilitate and maintain sexual offending” (Ward, Gannon, & Keown, 2006, p. 324). As we have argued elsewhere, the term “attitude” is ubiquitous in the criminological literature and is often used to refer to a wide range of cognitions, such as cognitive distortions, which seem to extend beyond the social-psychological definition of attitude (Nunes, Hermann, Maimone, & Woods, 2015; Nunes, Hermann, & Ratcliffe, 2013). The purpose of the current study was to explore the extent to which cognitive distortions regarding rape represent attitudes toward rape.

There is general agreement in the social-psychological literature that the key feature of attitudes is evaluation (e.g., Albarracín, Johnson, Zanna, & Kumkale, 2005; Conrey & Smith, 2007; Eagly & Chaiken, 2007; Fazio, 2007; Gawronski & Bodenhausen, 2007; Petty, Briñol, & DeMarree, 2007; Schwarz, 2007). More specifically, attitudes are typically defined as evaluations (e.g., positive vs. negative) of psychological objects, such as people, things, or behaviors (e.g., Ajzen, 2001; Eagly & Chaiken, 1993, 2007; Fazio, 2007). In one of the most widely cited definitions, Eagly and Chaiken (1993) defined attitude as “a psychological tendency that is expressed by evaluating a particular entity with some degree of favor or disfavor” (p. 1). Another widely accepted definition of attitudes is that they are associations in memory between a psychological object and a summary evaluation of that object (Fazio, 1995, 2007; Fazio, Chen, McDonel, & Sherman, 1982). Similarly, Ajzen (1991) defined attitudes toward behavior as “the degree to which a person has a favorable or unfavorable evaluation or appraisal of the behavior in question” (p. 188). Importantly, it is further recognized that attitudes are distinct from other commonly studied cognitions, such as beliefs, excuses, and justifications (e.g., Ajzen, 2001; Albarracín, Johnson, Zanna, & Kumkale, 2005; Maruna & Mann, 2006; Nunes, Pettersen, Hermann, Looman, & Spape, 2016). From these definitions, attitudes toward rape would be conceptualized as how negatively or positively one views rape.

Attitudes can be important determinants of behavior. Many theories propose that attitudes influence behavior (e.g., Ajzen, 1991, 2001; Ajzen & Fishbein, 1980, 2005). Research indicates that, although the influence of attitudes on behavior is moderated by a number of variables such as the accessibility and stability of the attitude (Glasman & Albarracín, 2006; Kraus, 1995), the relationship between attitudes and behavior can be strong. Meta-analyses have revealed medium (average r = .38; Kraus, 1995) to large (average r = .52, 95% confidence interval [CI] = [0.49, 0.54]; Glasman & Albarracín, 2006) average correlations between attitudes and subsequent behavior. Consistent with this more general theory and evidence, many explanatory models of violent behavior hypothesize that attitudes toward violence influence whether one engages in violent behavior (e.g., Anderson & Bushman, 2002; Andrews & Bonta, 2010; Bandura, 1973).

Although a few studies have focused specifically on evaluation of rape (for a review of these studies, see Nunes et al., 2013), the term attitude is more often used to refer to a wide range of cognitions that appear to extend beyond evaluation of rape. More specifically, in theory, research, assessment, and treatment regarding sexual aggression, attitude is often used as either a synonym or superordinate label for terms such as excuses; justifications; minimizations; rationalizations; hostility toward women; and stereotypes about rape, rape victims, and women in general.

To illustrate this point further, consider the following items from some widely used self-report measures of cognitions regarding rape: “A raped woman is a less desirable woman” (Feild, 1978, p. 162); “One reason that women falsely report a rape is that they frequently have a need to call attention to themselves” (Burt, 1980, p. 223); “Generally, rape is not planned—a lot of times it just happens” (Bumby, 1996, p. 53); and “Rape is unlikely to happen in the woman’s own familiar neighborhood” (Payne, Lonsway, & Fitzgerald, 1999, p. 49). Although not all the authors of these scales have used the term attitudes, responses to the items above and other items from such measures are often interpreted as reflecting attitudes toward rape (e.g., Anderson, Cooper, & Okamura, 1997). However, it is unclear whether endorsing such items necessarily indicates or requires that respondents view rape as a positive (or a negative) behavior. In light of the definition of attitudes presented above, if these items do not reflect evaluation of rape, then this raises questions about the extent to which these scales measure attitudes toward rape.

Whatever constructs are being assessed by these measures, they generally appear to be relevant to understanding sexual aggression as evidenced by their observed association with sexual aggression (e.g., Anderson et al., 1997; Bumby, 1996; DeGue, DeLillo, & Scalora, 2010; Murnen, Wright, & Kaluzny, 2002; Suarez & Gadalla, 2010). Clearly, these scales were designed to measure a range of cognitions possibly including, but not limited to, evaluation of rape, but do any of the items reflect evaluation of rape? If these scales are measuring constructs in addition to or instead of evaluation of rape, then it may be beneficial for researchers and clinicians to be aware of this. It is possible that different types of cognitions have different causal associations with sexually aggressive behavior; for example, some constructs may be more important than others, some may facilitate persistence whereas others may facilitate desistance, and some may be causes of sexually aggressive behavior whereas others may be consequences of sexually aggressive behavior (e.g., Gannon & Polaschek, 2006; Maruna & Copes, 2005; Maruna & Mann, 2006). If such distinctions do exist, examining these cognitions separately may facilitate more informative assessments and more effective interventions.

To the best of our knowledge, no published studies have tested whether cognitive distortion scales assess evaluation of rape; however, we have found preliminary evidence that some measures designed to assess attitudes toward non-sexual violence may not actually assess evaluation of violence, and that both evaluations and other cognitions may be independently associated with violent behavior (Nunes et al., 2015). These findings are consistent with the reasoning outlined above that evaluation of sexual aggression may be distinct from other cognitions, such as cognitive distortions, that are often referred to as “attitudes” in the criminological literature, and both evaluation and these other cognitions may be relevant for understanding and managing sexual aggression.

The purpose of the current study was to explore the extent to which a widely used self-report measure of cognitive distortions regarding rape (RAPE Scale; Bumby, 1996) assesses evaluation of rape. We also explored the practical value of any distinctions between evaluation and cognitive distortions. More concretely, we addressed two main research questions:

Research Question 1: Does the RAPE Scale assess evaluation of rape?

Research Question 2: If not, are evaluations and the cognitions assessed by the RAPE Scale independently associated with sexually aggressive behavior?

We used the same general approach as in our study on non-sexual violence cognitions (Nunes et al., 2015). Specifically, to address the first question we conducted an exploratory factor analysis (EFA) of the RAPE Scale and a semantic differential scale assessing evaluation of rape (Evaluation of Rape Scale). The use of semantic differential scales is a widespread, long-standing, and well-validated approach to assessing attitudes in social-psychological research (e.g., Gawronski & Bodenhausen, 2006; Glasman & Albarracín, 2006; Hofmann, Gawronski, Gschwendner, Le, & Schmitt, 2005; Osgood, Suci, & Tannenbaum, 1957; Taylor, 1971). If the RAPE Scale and Evaluation of Rape Scale items load on the same factor, then that would suggest that they measure the same latent construct. Conversely, if the Evaluation of Rape Scale items form a distinct factor from the RAPE Scale items, then that would suggest the RAPE Scale may measure cognitions other than evaluation of rape. We expected that at least some of the RAPE Scale items would be distinct from the Evaluation of Rape Scale items. To address our second research question, we conducted regression analyses with the latent factors derived from EFA as predictors and self-reported sexually aggressive behavior as the outcomes. If the Evaluation of Rape Scale items and the RAPE Scale items were to separate into distinct factors and if these factors were independently associated with sexually aggressive behavior, then that would suggest that scores on these measures may provide distinct and complementary information relevant to sexual aggression.

Method

Participants

Participants were 666 male undergraduate students at Carleton University who reported heterosexual orientation and ability to understand written English. Although we aim to understand sexual aggression in general, we focused on university students in the current study because sexual aggression by students is a real and serious problem worthy of research and intervention (e.g., Abbey, McAuslan, Zawacki, Clinton, & Buck, 2001; Hermann, Nunes, & Maimone, 2015; Nunes et al., 2013; Zinzow & Thompson, 2015). This more accessible population is also ideal for exploratory research requiring large samples. We included only heterosexual male participants because most measures—in the current study and in general—focus on sexual aggression against women rather than men, and the vast majority of sexual aggression against adults appears to be man against woman rather than man against man (e.g., Brennan & Taylor-Butts, 2008). Of the 666 participants, 0.9% (n = 6) had missing data on at least one of the variables of interest (RAPE Scale = 0.2%, n = 1; Evaluation of Rape semantic differential scale = 0.2%, n = 1; and Likelihood to Rape [LR] Question = 0.9%, n = 6). Little’s missing completely at random (MCAR) test was not significant, and it was concluded that data were missing completely at random, χ²(4) = 2.49, p = .647. Given these findings, listwise deletion was used for missing data resulting in a final sample size of 660 participants. Listwise deletion would not be expected to bias our findings or render our statistical power inadequate, given that data were missing completely at random and the remaining number of participants with complete data was large (see Allison, 2001). For the final sample of 660 participants, the median age category was 18 and 19 (52.4%, n = 346); 2.9% of participants were 17 or younger (n = 19), 42.3% were between 20 and 29 (n = 279), and 2.4% were 30 or older (n = 16).

Measures

Evaluation of Rape Scale

Seven semantic differential items were used to assess evaluation of rape. Each item was rated by participants on a 7-point scale; anchors are presented in Table 2. This scale fits the social-psychological definition of attitudes as evaluations and is a commonly used and well-validated method for assessing attitudes in the social-psychological literature (e.g., Gawronski & Bodenhausen, 2006; Glasman & Albarracín, 2006; Hofmann et al., 2005; Osgood et al., 1957; Taylor, 1971). Total scores were computed by averaging responses across the items, with higher scores reflecting more positive evaluation of rape. Scores showed adequate internal consistency in the current sample (Cronbach’s α = .79). In terms of validity, we have found moderate to large correlations between the Evaluation of Rape Scale and other self-report measures designed to assess evaluation of rape in samples of students and community men (e.g., Hermann et al., 2015).

The RAPE Scale

The RAPE Scale is a 36-item self-report measure designed by Bumby (1996) to assess endorsement of cognitive distortions regarding rape (items are presented in Table 2). Although others have often referred to the RAPE Scale as a measure of attitudes toward rape, Bumby referred to cognitive distortions rather than attitudes and presented the RAPE Scale as a measure of “learned assumptions, sets of beliefs, and self-statements about . . . rape which serve to deny, justify, minimize, and rationalize an offender’s actions” (p. 38). Participants respond to each item on a 4-point Likert-type scale from 1 (strongly disagree) to 4 (strongly agree). A total score is computed by summing all item responses, and higher scores indicate greater endorsement of cognitive distortions regarding rape. The RAPE Scale is commonly used in research and practice (e.g., R. McGrath, personal communication, November 9, 2012; Nunes, Babchishin, & Cortoni, 2011; Nunes et al., 2016). High internal consistency has been found in past research (average Cronbach’s α = .95; Nunes et al., 2016) and in the current sample (α = .93). Test–retest reliability after a 2-week interval was also high (r = .86; Bumby, 1996).

The Coercive Sexuality Scale–Revised (CSS-R)

The original Coercive Sexuality Scale (CSS; Rapaport & Burkhart, 1984) is a 19-item self-report scale designed to assess the frequency of past sexually coercive and aggressive behaviors on a 4-point Likert-type scale (never, once or twice, several times, or often). Responses are summed to compute a total score, and higher total scores indicate more sexually coercive behavior.

For the current study, we modified the scoring of the CSS by expanding the response scale from the original 4-point scale to a 10-point scale (0 = never, 1 = once, 2 = twice, 3 = 3 times, 4 = 4 times, 5 = 5 times, 6 = 6 times, 7 = 7 times, 8 = 8 times, and 9 = 9 times or more) and excluding Item 12 (“Since age 16, how many times have you attempted to verbally convince a woman to have sex?”) because it is not unambiguously coercive. Finally, consistent with scoring methods for other measures of past sexually aggressive behavior (see Cue Davis et al., 2014), we organized the items into varying levels of intrusiveness and assigned weights accordingly: 1 for Items 1 to 5 because these items were considered the least intrusive forms of sexual coercion (e.g., unwanted touching); 2 for Items 6 to 10 because they reflect more intrusive forms of sexual coercion (e.g., removing a woman’s clothing against her will); and 3 for Items 11 to 19 because they reflect the most intrusive forms of sexual coercion (e.g., forced sexual intercourse) using a variety of increasingly violent tactics. Total scores were computed by multiplying each item response by its intrusiveness weighting and summing the products. Total scores can range from 0 to 420; higher scores indicate more frequent and intrusive sexually coercive behavior.

The CSS has demonstrated high internal consistency (Cronbach’s α of .96 for the original CSS; Hall & Hirschman, 1994; and .92 for the CSS-R in the current study). Although there is little relevant evidence regarding validity of CSS scores, variables associated with other measures of sexual aggression have also been found to be associated with the CSS (e.g., beliefs about rape and violence; Murnen et al., 2002; Rapaport & Burkhart, 1984). Furthermore, self-reported rates of sexually aggressive behavior on the CSS are similar to those reported on other widely used measures of sexual aggression (i.e., Sexual Experiences Survey; Koss & Oros, 1982; Rapaport & Burkhart, 1984). More generally, self-report measures of delinquent and criminal behavior are considered to be reliable and valid (see Thornberry & Krohn, 2000; Piquero, Schubert, & Brame, 2014, for an overview), and self-report measures of sexually aggressive behavior align with independent indicators of such behavior, such as official criminal records (Pham et al., 2015; Weinrott & Saylor, 1991; Woods, Hermann, Nunes, McPhail, & Sewell, 2011).We conducted the analyses below with both the original CSS and our revised version, and the pattern of results was the same (only the results for the revised CSS are presented in the “Results” section).

The LR Question

On the LR Question (Malamuth, 1981), participants rate the likelihood that they would rape a woman if they could be assured of not being caught and punished on a 5-point Likert-type scale ranging from 1 (not at all likely) to 5 (very likely). Past research has found moderate to large positive correlations between self-reported proclivity to rape and self-reported past sexually aggressive behavior in student and community samples (e.g., Hermann, 2015; Maimone, Hermann, Atlas, Berliant, & Nunes, 2013; Nunes et al., 2013). Gidycz, Warkentin, Orchowski, and Edwards (2011) found that male college students’ reported likelihood of engaging in sexually coercive and aggressive behavior was significantly associated with perpetrating future sexually coercive and aggressive behavior during a 3-month follow-up period. Hermann (2015) found that community men’s reported likelihood to rape was significantly associated with perpetrating future sexually coercive and aggressive behavior during a 4-month follow-up period.

Procedure

Participants were recruited from the psychology participant pool and received course credit for participation. Interested students signed up online and arrived for their appointment at our lab at the university. Upon arrival, participants were greeted by a research assistant, given a brief overview of the study, signed the consent form, and were then left alone in a private office to complete the measures on a laptop computer. The presentation order of the measures varied across participants. Participants were tested individually, and their data were anonymous. Upon completion of the measures, the research assistant provided debriefing information and a corresponding debriefing form, addressed any questions, and thanked the participants.

Statistical Analyses

EFA was used to examine the underlying latent construct(s) of the RAPE Scale and Evaluation of Rape Scale. MPlus version 7.3 (Muthén & Muthén, 2010) was used to conduct the EFA. There are several important methodological considerations that can affect the statistical validity and generalizability of the results of EFA (for an overview, see Schmitt, 2011), including the type of correlation matrix analyzed, model estimation and factor rotation methods, and the criteria used to determine the number of factors to retain. In the current study, factors were extracted from a polychoric correlation matrix using the Weighted Least Square estimator (WLSMV). Factors were rotated using oblique rotation (Geomin) and, to estimate the number of factors to retain, four methods were used: Kaiser’s criterion, Scree plot, Parallel Analysis (O’Connor, 2000), and Velicer’s Minimum Average Partial Test (MAP test; O’Connor, 2000). After the number of factors to retain was approximated, model fit indices (i.e., root mean square error of approximation [RMSEA], comparative fit index [CFI], standardized root mean square residual [SRMR]) and the significance and magnitude of the factor loadings (≥.40) were used to determine the final factor structure (Cudeck & O’Dell, 1994; Schmitt & Sass, 2011). If an item cross-loaded equally across factors, the content of the item was used to determine final placement. This methodology has been used with similar types of data in past research (Brouillette-Alarie, Babchishin, Hanson, & Helmus, 2015; Hermann, Babchishin, Nunes, Leth-Steensen, & Cortoni, 2012; Jung et al., 2017; Nunes et al., 2015).

Results

Pearson’s correlations,¹ means, standard deviations, and internal consistencies (Cronbach’s α) for all measures are presented in Table 1. Approximately one third (38.6%) of participants reported at least some past sexually aggressive behavior, as indicated by a score of 1 or greater on the CSS-R. Approximately one fifth (20.5%) of participants reported at least some likelihood to rape, as indicated by a score of 2 or greater on the LR Question. All of the measures were significantly intercorrelated with correlations ranging from small (r = .16) to moderate (r = .35). Higher scores on the Evaluation of Rape Scale were moderately associated with higher scores on the RAPE Scale (r = .34). More importantly, higher scores on both the Evaluation of Rape Scale and the RAPE Scale were moderately associated with higher frequencies of self-reported past sexually aggressive behavior (CSS-R; r = .25 and r = .26, respectively) and higher self-reported likelihood to rape (LR Question; r = .32 and r = .35, respectively).

Table 1.

Bivariate Correlations and Descriptive Statistics (N = 660).

Measure	1	2	3	M	SD	α
1. Evaluation of Rape Scale	—			1.17	0.37	.79
2. RAPE Scale	.34	—		64.89	14.69	.93
3. CSS-R	.25	.26	—	3.66	10.00	.92
4. LR	.32	.35	.16	1.29	0.68

Note. CSS-R = Coercive Sexuality Scale–Revised; LR = Likelihood to Rape Question.

All correlations are statistically significant (p < .05).

Do The Cognitive Distortion and Evaluation Scales Reflect Distinct or Overlapping Factors?

An EFA was conducted to examine the underlying factor structure of the RAPE Scale and Evaluation of Rape Scale. As noted above, the EFA was estimated using the WLSMV estimator from a polychoric correlation matrix. Many of the polychoric correlations were greater than .30 but less than .90, suggesting that the matrix was factorable and that multicollinearity between items was not an issue. Estimates for the number of factors to retain ranged from 2 to 8, with the Scree plot and Parallel Analysis estimating three factors, the MAP test estimating two to five factors, and Kaiser’s criterion estimating eight factors. Models with two to eight factors were computed, and model fit indices and overall factor structure fit were used to determine the final EFA model. The two-factor model was selected as it was the most parsimonious and demonstrated good fit with a RMSEA of .039 (90% CI = [.036, .042]), CFI of .96, and SRMR of .05. The Eigenvalues and proportion of variance explained for each factor are presented in Table 3. All the Evaluation of Rape Scale items loaded primarily on Factor 1, and all the RAPE Scale items loaded primarily on Factor 2. The rotated factor loadings and their standardized scores are presented in Table 2. There was a strong positive correlation between the factors (r = .46, p < .05). Thus, the RAPE Scale items formed a correlated but distinct factor from the Evaluation of Rape Scale items.

Table 2.

Exploratory Factor Analysis: Rotated Factor Loadings and Standardized Scores.

	Rotated factor loading (standardized score)
Item	Factor 1	Factor 2
Factor 1: Evaluation of Rape Scale
1. Rape is negative vs. positive	.69 (15.56*)	−.02 (−0.44)
2. Rape is bad vs. good	.93 (27.33*)	−.05 (−0.82)
3. Rape is wrong vs. right	.93 (28.43*)	−.05 (−0.78)
4. Rape is immoral vs. moral	.88 (17.27*)	.03 (0.41)
5. Rape is not enjoyable vs. enjoyable	.87 (17.30*)	.08 (1.10)
6. Rape is not fun vs. fun	.87 (23.53*)	.04 (0.57)
7. Rape is unpleasant vs. pleasant	.76 (14.08*)	.10 (1.17)
Factor 2: RAPE Scale
1. Men who commit rape are probably responding to a lot of stress in their lives.	.18 (2.97)	.37 (7.23*)
2. Women who get raped probably deserved it.	.27 (3.88*)	.52 (8.672*)
3. Women generally want sex no matter how they can get it.	.19 (3.60*)	.58 (13.82*)
4. Since prostitutes sell their bodies for sexual purposes anyways, it is not as bad if someone forces them into sex.	.15 (3.07)	.61 (14.38*)
5. If a woman does not resist strongly to sexual advances, she is probably willing to have sex.	−.00 (−0.06)	.68 (22.75*)
6. Women often falsely accuse men of rape.	−.02 (−0.27)	.54 (13.88*)
7. A lot of women who get raped had “bad reputations” in the first place.	.05 (1.14)	.69 (20.90*)
8. If women did not sleep around so much, they would be less likely to get raped.	.04 (0.73)	.65 (17.33*)
9. If a woman gets drunk at a party, it is really her own fault if someone takes advantage of her sexually.	−.02 (−0.43)	.65 (17.69*)
10. When women wear tight clothes, short skirts, and no bra or underwear, they are just asking for sex.	−.11 (−2.33)	.76 (23.39*)
11. A lot of women claim they were raped just because they want attention.	−.03 (−0.55)	.65 (18.57*)
12. Victims of rape are usually a little bit to blame for what happens.	.10 (1.90)	.65 (18.31*)
13. If a man has had sex with a woman before, then he should be able to have sex with her any time he wants.	.03 (0.51)	.75 (20.17*)
14. Just fantasizing about forcing someone to have sex isn’t all that bad since no one is really being hurt.	.27 (4.94*)	.28 (5.51*)
15. Women who go to bars a lot are mainly looking to have sex.	.07 (1.17)	.62 (16.40*)
16. A lot of times, when women say “no,” they are just playing hard to get and really mean “yes.”	−.05 (−0.93)	.75 (23.05*)
17. Part of a wife’s duty is to satisfy her husband sexually whenever he wants it, whether or not she is in the mood.	.08 (1.39)	.65 (16.38*)
18. Often, a woman reports rape long after the fact because she gets mad at the man she had sex with and is trying to get back at him.	−.09 (−1.53)	.71 (19.24*)
19. As long as a man does not slap or punch a woman in the process, forcing her to have sex is not as bad.	.07 (1.18)	.71 (17.94*)
20. When a woman gets raped more than once, she is probably doing something to cause it.	−.06 (−1.08)	.75 (23.18*)
21. Women who get raped will eventually forget about it and get on with their lives.	.08 (1.30)	.51 (10.11*)
22. On a date, when a man spends a lot of money on a woman, the woman ought to at least give the man something in return sexually.	.07 (1.50)	.71 (21.06*)
23. I believe that if a woman lets a man kiss her and touch her sexually, she should be willing to go all the way.	.00 (0.13)	.73 (29.40*)
24. When women act like they are too good for men, most men probably think about raping the women to put them in their place.	.18 (3.26)	.55 (12.65*)
25. I believe that society and the courts are too tough on rapists.	.14 (2.39)	.51 (10.78*)
26. Most women are sluts and get what they deserve.	.15 (2.87)	.69 (16.28*)
27. Before the police investigate a woman’s claim of rape, it is a good idea to find out what she was wearing, if she had been drinking, and what kind of person she is.	−.05 (−1.03)	.66 (19.23*)
28. Generally, rape is not planned—a lot of time it just happens.	.08 (1.30)	.37 (8.15*)
29. If a person tells himself that he will never rape again, then he probably won’t.	−.02 (−0.27)	.42 (9.77*)
30. A lot of men who rape do so because they are deprived of sex.	.06 (1.03)	.45 (10.37*)
31. The reason a lot of women say “no” to sex is because they don’t want to seem loose.	−.04 (−0.58)	.63 (15.95*)
32. If a woman goes to the home of a man on the first date, she probably wants to have sex with him.	−.17 (−2.64)	.68 (18.16*)
33. Many women have a secret desire to be forced into having sex.	−.03 (−0.54)	.71 (21.96*)
34. Most of the men who rape have stronger sexual urges than other men.	−.05 (−0.92)	.40 (9.47*)
35. I believe that any woman can prevent herself from being raped if she really wants to.	−.11 (−1.91)	.54 (13.35*)
36. Most of the time, the only reason a man commits rape is because he was sexually assaulted as a child.	−.01 (−0.21)	.34 (7.88*)

Note. For the standardized score, the critical z score was 3.50, α = .000298. Bolded values indicate item placement on the factors.

Factor loading significantly differs from 0 (p < .0003).

Table 3.

Eigenvalues and Proportion of Variance Explained for Retained Factors.

	Eigenvalue	Proportion of variance (%)	Cumulative proportion of variance (%)
Factor 1: Evaluation of Rape Scale	16.21	37.70	37.70
Factor 2: RAPE Scale	3.79	8.82	46.52

Note. Oblique rotation was used; as a result, the proportion of variance explained by each factor only applies to the unrotated factor structure solution.

Are the Cognitive Distortion and Evaluation Scales Independently Associated With Sexually Aggressive Behavior?

Two separate hierarchical regression analyses were conducted on the RAPE Scale and Evaluation of Rape Scale to investigate whether each scale independently predicted scores on the LR Question and CSS-R. As shown in Tables 4 and 5, both the RAPE Scale and Evaluation of Rape Scale were independently associated with the LR and CSS-R. The partial correlations indicate that these independent associations were small to moderate. Furthermore, the RAPE Scale and Evaluation of Rape Scale together showed a significantly stronger association with the CSS-R and LR than did the RAPE Scale alone, as indicated by the significant increase in R² for Step 2 over Step 1 (Tables 4 and 5). This significantly stronger association for Step 2 over Step 1 (both measures vs. one measure) was also found when the Evaluation of Rape Scale was entered in the first step and the RAPE Scale entered in the second step. Although the LR scale and CSS-R scale were positively skewed, we found the same pattern of results when we conducted logistic regression analyses with dichotomized sexual aggression variables. Thus, the Evaluation of Rape Scale and the RAPE Scale had small to moderate independent associations with the self-report measures of sexually aggressive behavior.

Table 4.

Hierarchical Multiple Regression Predicting Past Sexually Aggressive Behavior (CSS-R) From the RAPE Scale and Evaluation of Rape Scale.

Predictor	R	R ²	Adjusted R²	ΔR²	B	B SE	β	r partial
Step 1	.26	.07	.06	.07*
RAPE Scale					0.17*	0.03	.26
Step 2	.31	.10	.09	.03*
RAPE Scale					0.13*	0.03	.19	.19
Evaluation of Rape Scale					5.09*	1.07	.19	.18

Note. CSS-R = Coercive Sexuality Scale–Revised.

p < .05.

Table 5.

Hierarchical Multiple Regression Predicting Likelihood to Rape (LR Question) From the RAPE Scale and Evaluation of Rape Scale.

Predictor	R	R ²	Adjusted R²	∆R²	B	B SE	β	r partial
Step 1	.35	.12	.12	.12*
RAPE Scale					0.02*	0.002	.35
Step 2	.41	.17	.17	.05*
RAPE Scale					0.01*	0.002	.27	.27
Evaluation of Rape Scale					0.42*	0.07	.23	.23

p < .05.

Discussion

The purpose of the current study was to explore the extent to which the RAPE Scale assesses evaluation of rape, and, if it does not, whether evaluation and the cognitions assessed by the RAPE Scale are independently associated with sexually aggressive behavior. An EFA indicated that items from the RAPE Scale and Evaluation of Rape Scale reflected two distinct but correlated factors. More specifically, all the RAPE Scale items loaded primarily on one factor and all the Evaluation of Rape Scale items loaded primarily on another factor. These results suggest that the RAPE Scale may not assess attitudes toward rape (i.e., evaluation of rape). In addition, hierarchical regression analyses indicated that the RAPE Scale and Evaluation of Rape Scale had independent small to moderate associations with self-reported past sexually aggressive behavior and self-reported likelihood to rape. Furthermore, the RAPE Scale and Evaluation of Rape Scale provided complementary information, such that together they were more strongly associated with sexually aggressive behavior than was either one alone. These findings suggest that evaluation of rape may be distinct from the cognitions measured by the RAPE Scale, and that both cognitive constructs may be independently associated with sexually aggressive behavior.

If the RAPE Scale does not assess evaluation of rape, what does it assess? A number of interesting hypotheses have been proposed regarding the constructs that may underlie cognitive distortions, such as hostility toward women or excuses, which may serve to reduce cognitive dissonance before, during, or after sexually offending (Gannon & Polaschek, 2006; Hermann et al., 2012; Maruna & Copes, 2005; Maruna & Mann, 2006; Ward et al., 2006). It is also possible that the RAPE Scale may assess respondents’ perceptions of their social group’s acceptance and perpetration of sexual aggression (i.e., normative beliefs; Ajzen, 1991; Ajzen & Fishbein, 2005). Although further examination of the construct(s) assessed by measures like the RAPE Scale is needed, past research and the current results generally suggest that such scales are relevant to understanding sexually aggressive behavior as evidenced by their observed association with sexually aggressive behavior (Bumby, 1996; Murnen et al., 2002; but see Nunes et al., 2016). Future research should investigate how evaluation of rape and the constructs assessed by measures like the RAPE Scale may influence each other and sexually aggressive behavior (e.g., moderation, mediation), and how they may be affected by other factors such as treatment. It would also be valuable to determine what cognitive constructs are assessed by the RAPE Scale. The method used in the current study would be a useful approach for studying this issue. Specifically, responses to items that reflect the construct of interest (e.g., a scale assessing normative beliefs regarding rape) could be entered into a factor analysis with items from the RAPE Scale. If the additional items reflect a separate factor from the RAPE Scale items, then that would suggest the RAPE Scale measures a different construct. Conversely, if the additional items load on the same factor as the RAPE Scale items, then that would suggest they are measuring the same construct.

There are a number of limitations to this study in terms of the sample, measures, and design. The sample was comprised of university students and the extent to which the findings would generalize to other populations (e.g., incarcerated offenders, community men, etc.) is unknown. The RAPE Scale was developed for and has typically been used for assessing adjudicated adult sexual offenders, and students would be expected to differ from that population in a variety of ways (e.g., more educated, younger [“emerging adults”], fewer atypical/paraphilic sexual interests, and fewer antisocial characteristics). For example, in contrast to the one-factor structure for the RAPE Scale we found with students in the current study, our past research with adjudicated sexual offenders has yielded a two-factor structure for the RAPE Scale (Hermann et al., 2012). Thus, it is possible that the distinctiveness of the RAPE Scale and the Evaluation of Rape Scale observed in the current study may not hold with correctional/forensic populations. Nevertheless, it is not a foregone conclusion that this would be the case (e.g., Anderson & Bushman, 1997; Anderson, Lindsay, & Bushman, 1999).

At the same time, a considerable amount of research on sexual aggression has been conducted with university students and, although they undoubtedly differ from adjudicated sexual offenders, some students also commit acts of sexual aggression (e.g., Abbey et al., 2001; Hermann et al., 2013, 2015; Zinzow & Thompson, 2015). Furthermore, past research has found cognitions regarding rape to be associated with sexually aggressive behavior in samples of students, community men, and sexual offenders (e.g., Bumby, 1996; DeGue et al., 2010; Hermann et al., 2015; Nunes et al., 2013; Suarez & Gadalla, 2010; Widman & Olson, 2013), suggesting that our results may also generalize to samples of community men and sexual offenders. Thus, although we wish to address sexual aggression in general, sexual aggression by university students in particular is also a significant problem that warrants continued research and intervention, and evidence from student samples may be relevant to explaining sexual aggression by non-students. Moreover, the economy and efficiency of conducting research with more accessible population, such as university students, make them ideal for the first step in exploring fundamental questions and hypotheses before moving to the more time-consuming and costly process of attempting to replicate these findings with, for example, a similarly large sample of incarcerated offenders. The fact that we can find distinctions between evaluation of rape and cognitive distortions with any population is important in its own right, and it is the first step in a prudent process of replication and extension. Future research should attempt to replicate our findings with other samples of students or non-student samples in the community, and ultimately examine samples of offenders for whom measures like the RAPE Scale were developed.

The validity of scores on the Evaluation of Rape Scale is also an important consideration. Although the specific semantic differential scale we used in the current study has not been validated per se, the use of similar semantic differential scales is a widespread, long-standing, and well-validated approach to assessing attitudes in social-psychological research (e.g., Gawronski & Bodenhausen, 2006; Glasman & Albarracín, 2006; Hofmann et al., 2005; Osgood et al., 1957; Taylor, 1971). For example, Osgood et al. (1957) found that several evaluative semantic differential scales including good-bad, pleasant-unpleasant, and positive-negative loaded together on an evaluative factor. In the current study, these and the other evaluative semantic differential items we used to assess evaluation of rape all loaded together on the same factor. Taken together, the available evidence allows some confidence regarding the construct validity of scores on our semantic differential scale. Nevertheless, future research should examine other self-report measures as well as implicit measures to assess evaluation of rape (Gannon & Polaschek, 2006; Hermann, 2015; Nunes et al., 2013; Widman & Olson, 2013). We have recently developed a self-report measure intended to provide a more comprehensive assessment of evaluation of sexual aggression that may be useful for future research in this area: Evaluation of Sexual Aggression Against Women (ESAW) scale (Hermann & Nunes, 2015).

The reliance on self-report measures for assessing sexually aggressive behavior is another possible cause for concern. Even though participants were informed that their responses were anonymous, they may not have been willing or able to accurately report such information. However, other research clearly indicates that antisocial behavior (e.g., criminal history) can be accurately assessed with self-report measures (e.g., Farrington et al., 2003; Huizinga & Elliott, 1986; Jones & Miller, 2012; Kroner, Mills, & Morgan, 2007; Pham et al., 2015; Piquero et al., 2014; Thornberry & Krohn, 2000; Weinrott & Saylor, 1991; Woods et al., 2011). More specifically, other self-report measures of sexually aggressive behavior have been found to align with independent indicators of such behavior, such as official records (Pham et al., 2015; Weinrott & Saylor, 1991; Woods et al., 2011).

Finally, because of the cross-sectional and correlational design of the current study, it was not possible to test whether the different cognitive factors we found had different causal associations with sexually aggressive behavior. Perhaps, some of these constructs could be causes of sexually aggressive behavior, others could be consequences of such behavior, and still others could be both cause and consequence (e.g., Gannon, Ward, & Collie, 2007; Maruna & Copes, 2005; Maruna & Mann, 2006). Based on the general social-psychological literature, we would expect evaluation to affect behavior and behavior to affect evaluation (Albarracín, Johnson, & Zanna, 2005). If our findings are replicated, future research should use more rigorous methodology (e.g., longitudinal and experimental designs) to explore questions about the potential causal connections between different cognitions and sexually aggressive behavior.

The current study indicates that evaluation of rape may be distinct from other cognitions often referred to as “attitudes” in the criminological literature. Just as Ron’s trainer mistakenly overlooked cardiovascular fitness in the scenario presented in the Introduction section, theorists, researchers, and clinicians may have overlooked evaluation of rape. Despite the ubiquity of the term attitudes, we may actually know very little about the role of evaluation of rape in sexually aggressive behavior. It is important to make these distinctions, refine definitions and measurement as needed, and specifically examine the potential role of evaluation in sexually aggressive behavior. Greater precision and clarity in conceptualization and measurement of cognitions regarding sexually aggressive behavior will facilitate further advances in understanding of the cognitive underpinnings of such behavior, which in turn will facilitate further improvements in assessment and treatment aimed at managing and reducing sexual violence.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was facilitated by a grant from the Social Sciences and Humanities Research Council of Canada.

Notes

References

Abbey

McAuslan

Zawacki

Clinton

Buck

P. O.

(2001). Attitudinal, experiential, and situational predictors of sexual assault perpetration. Journal of Interpersonal Violence, 16, 784-807.

Ajzen

(1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179-211.

Ajzen

(2001). Nature and operation of attitudes. Annual Psychological Review, 52, 27-58. doi:10.1146/annurev.psych.52.1

Ajzen

Fishbein

(1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice Hall.

Ajzen

Fishbein

(2005). The influence of attitudes on behavior. In Albarracín

Johnson

B. T.

Zanna

M. P.

(Eds.), The handbook of attitudes (pp. 173-221). Mahwah, NJ: Lawrence Erlbaum.

Albarracín

Johnson

B. T.

Zanna

M. P.

(2005). The handbook of attitudes. Mahwah, NJ: Lawrence Erlbaum.

Albarracín

Johnson

B. T.

Zanna

M. P.

Kumkale

G. T.

(2005). Attitudes: Introduction and scope. In Albarracín

Johnson

B. T.

Zanna

M. P.

(Eds.), The handbook of attitudes (pp. 3-19). Mahwah, NJ: Lawrence Erlbaum.

Allison

P. D.

(2001). Missing data. Thousand Oaks, CA: Sage.

Anderson

C. A.

Bushman

B. J.

(1997). External validity of “trivial” experiments: The case of laboratory aggression. Review of General Psychology, 1, 19-41.

10.

Anderson

C. A.

Bushman

B. J.

(2002). Human aggression. Annual Review of Psychology, 53, 27-51. doi:10.1146/annurev.psych.53.100901.135231

11.

Anderson

C. A.

Cooper

Okamura

(1997). Individual differences and attitudes toward rape: A meta-analytic review. Personality and Social Psychology Bulletin, 23, 295-315.

12.

Anderson

C. A.

Lindsay

J. J.

Bushman

B. J.

(1999). Research in the psychological laboratory: Truth or triviality? Current Directions in Psychological Science, 8, 3-9.

13.

Andrews

D. A.

Bonta

(2010). The psychology of criminal conduct (5th ed.). Cincinnati, OH: Anderson.

14.

Bandura

(1973). Aggression: A social learning analysis. Englewood Cliffs, NJ: Prentice Hall.

15.

Brennan

Taylor-Butts

(2008). Sexual assault in Canada: 2004 and 2007 (Catalogue Number 85F0033M, number 19). Ottawa, Ontario: Canadian Centre for Justice Statistics, Statistics Canada.

16.

Brouillette-Alarie

Babchishin

K. M.

Hanson

R. K.

Helmus

L. M.

(2015). Latent constructs of the Static-99R and Static-2002R: A 3-factor solution. Assessment, 23, 96-111. doi:10.1177/1073191114568114

17.

Bumby

(1996). Assessing the cognitive distortions of child molesters and rapists: Development and validation of the MOLEST and RAPE Scales. Sexual Abuse: A Journal of Research and Treatment, 8, 37-54. doi:10.1007/BF02258015

18.

Burt

(1980). Cultural myths and supports for rape. Journal of Personality and Social Psychology, 38, 217-230.

19.

Conrey

F. R.

Smith

E. R.

(2007). Attitude representation: Attitudes as patterns in a distributed, connectionist representational system. Social Cognition, 25, 718-735.

20.

Cudeck

O’Dell

L. L.

(1994). Applications of standard error estimates in unrestricted factor analysis: Significance tests for factor loadings and correlations. Psychological Bulletin, 115, 475-487. doi:10.1037/0033-2909.115.3.475

21.

Cue Davis

K. C.

Gilmore

A. K.

Stappenbeck

C. A.

Balsan

M. J.

George

W. H.

Norris

(2014). How to score the Sexual Experiences Survey? A comparison of nine methods. Psychology of Violence, 4, 445-461. doi:10.1037/a0037494

22.

DeGue

DeLillo

Scalora

(2010). Are all perpetrators alike? Comparing risk factors for sexual coercion and aggression. Sexual Abuse, 22, 402-426. doi:10.1177/1079063210372140

23.

Eagly

A. H.

Chaiken

(1993). The psychology of attitudes. Fort Worth, TX: Harcourt Brace Jovanovich.

24.

Eagly

A. H.

Chaiken

(2007). The advantages of an inclusive definition of attitude. Social Cognition, 25, 582-602. doi:10.1521/soco.2007.25.5.582

25.

Farrington

D. P.

Jolliffe

Hawkins

J. D.

Catalano

R. F.

Hill

K. G.

Kosterman

(2003). Comparing delinquency careers in court records and self-reports. Criminology, 41, 933-958.

26.

Fazio

R. H.

(1995). Attitudes as object-evaluation associations: Determinants, consequences, and correlates of attitude accessibility. In Petty

R. E.

Krosnick

J. A.

(Eds.), Attitude strength: Antecedents and consequences (pp. 247-282). Hillsdale, NJ: Lawrence Erlbaum.

27.

Fazio

R. H.

(2007). Attitudes as object-evaluation associations of varying strength. Social Cognition, 25, 603-637. doi:10.1521/soco.2007.25.5.603

28.

Fazio

R. H.

Chen

McDonel

E. C.

Sherman

S. J.

(1982). Attitude accessibility, attitude-behavior consistency and the strength of the object-evaluation association. Journal of Experimental Social Psychology, 18, 339-357.

29.

Feild

H. S.

(1978). Attitudes toward rape: A comparative analysis of police, rapists, crisis counselors, and citizens. Journal of Personality and Social Psychology, 36, 156-179.

30.

Gannon

T. A.

Polaschek

D. L. L.

(2006). Cognitive distortions in child molesters: A re-examination of key theories and research. Clinical Psychology Review, 26, 1000-1019. doi:10.1016/j.cpr.2005.11.010

31.

Gannon

T. A.

Ward

Collie

(2007). Cognitive distortions in child molesters: Theoretical and research developments over the past two decades. Aggression and Violent Behavior, 12, 402-416. doi:10.1016/j.avb.2006.09.005

32.

Gawronski

Bodenhausen

G. V.

(2006). Associative and propositional processes in evaluation: An integrative review of implicit and explicit attitude change. Psychological Bulletin, 132, 692-731. doi:10.1037/0033-2909.132.5.692

33.

Gawronski

Bodenhausen

G. V.

(2007). Unraveling the processes underlying evaluation: Attitudes from the perspective of the APE model. Social Cognition, 25, 687-717. doi:10.1521/soco.2007.25.5.687

34.

Gidycz

C. A.

Warkentin

J. B.

Orchowski

L. M.

Edwards

K. M.

(2011). College men’s perceived likelihood to perpetrate sexual aggression. Journal of Aggression, Maltreatment & Trauma, 20, 260-279.

35.

Glasman

L. R.

Albarracín

(2006). Forming attitudes that predict future behavior: A meta-analysis of the attitude-behavior relation. Psychological Bulletin, 132, 778-822. doi:10.1037/0033-2909.132.5.778

36.

Hall

G. C. N.

Hirschman

(1994). The relationship between men’s sexual aggression inside and outside the laboratory. Journal of Consulting and Clinical Psychology, 62, 375-380.

37.

Hermann

C. A.

(2015). Evaluations of rape: Investigations using implicit and explicit measures, online research methodology, and samples of community men (Unpublished doctoral dissertation). Carleton University, Ottawa, Ontario, Canada.

38.

Hermann

C. A.

Babchishin

K. M.

Nunes

K. L.

Leth-Steensen

Cortoni

(2012). Factor structure of the Bumby RAPE Scale: A two-factor model. Criminal Justice and Behavior, 39, 869-886. doi:10.1177/0093854812436802

39.

Hermann

C. A.

Nunes

K. L.

(2015). Evaluation of Sexual Aggression Against Women (ESAW) Scale (Unpublished instrument).

40.

Hermann

C. A.

Nunes

K. L.

Maimone

(2015). “Click here”: Examining implicit and explicit attitudes towards rape and sexually aggressive behaviour in men recruited online. Manuscript in preparation.

41.

Hermann

C. A.

Pettersen

Woods

M. E.

Lorincz

Berliant

Nunes

K. L.

(2013, November). Rape-prevention with students: Moderating effects of psychopathy and sexual coercion. In Hermann

C. A.

(Chair), Implicit and explicit cognition associated with rape. Symposium conducted at the 32nd Annual Research and Treatment Convention of the Association for the Treatment of Sexual Abusers, Chicago, IL.

42.

Hofmann

Gawronski

Gschwendner

Schmitt

(2005). A meta-analysis on the correlation between the implicit association test and explicit self-report measures. Personality and Social Psychology Bulletin, 31, 1369-1385. doi:10.1177/0146167205275613

43.

Huizinga

Elliott

D., S.

(1986). Re-assessing the reliability and validity of self-reported delinquency measures. Journal of Quantitative Criminology, 2, 293-327.

44.

Jones

Miller

J. D.

(2012). Psychopathic traits and externalizing behaviors: A comparison of self- and informant reports in the statistical prediction of externalizing behaviors. Psychological Assessment, 24, 255-260. doi:10.1037/a0025264

45.

Jung

Ennis

Hermann

C. A.

Pham

Choy

A. L.

Corabian

Hook

(2017). An evaluation of the reliability, construct validity, and factor structure of the Static-2002R. International Journal of Offender Therapy and Comparative Criminology. 61, 464–487.

46.

Koss

M. P.

Oros

C. J.

(1982). Sexual experiences survey: A research instrument investigating sexual aggression and victimization. Journal of Consulting and Clinical Psychology, 50, 455-457. doi:10.1037/0022-006X.50.3.455

47.

Kraus

S. J.

(1995). Attitudes and the prediction of behavior: A meta-analysis of the empirical literature. Personality and Social Psychology Bulletin, 21, 58-75. doi:10.1177/0146167295211007

48.

Kroner

D. G.

Mills

J. F.

Morgan

R. D.

(2007). Socially desirable responding and the measurement of violent and criminal risk: Self-report validity. Journal of Forensic Psychology Practice, 6, 27-42. doi:10.1300/J158v06n04_02

49.

Maimone

S. A.

Hermann

C. A.

Atlas

Berliant

Nunes

K. L.

(2013, November). Implicit and explicit attitudes, rape outcome expectancies, and sexual aggression. In Hermann

C. A.

50.

Malamuth

N. M.

(1981). Rape proclivity among males. Journal of Social Issues, 37, 138-157.

51.

Maruna

Copes

(2005). What have we learned from five decades of neutralization research? Crime and Justice, 32, 221-320.

52.

Maruna

Mann

R. E.

(2006). A fundamental attribution error? Rethinking cognitive distortions. Legal and Criminological Psychology, 11, 155-177. doi:10.1348/135532506X114608

53.

Murnen

S. K.

Wright

Kaluzny

(2002). If “boys will be boys,” then girls will be victims: A meta-analytic review of the research that relates masculine ideology to sexual aggression. Sex Roles, 46, 359-375. doi:10.1023/A:1020488928736

54.

Muthén

L. K.

Muthén

B. O.

(2010). Mplus user’s guide. Los Angeles, CA: Author.

55.

Nunes

K. L.

Babchishin

K. M.

Cortoni

(2011). Measuring treatment change in sex offenders: Clinical and statistical significance. Criminal Justice and Behavior, 38, 157-173. doi:10.1177/0093854810391054

56.

Nunes

K. L.

Hermann

C. A.

Maimone

Woods

(2015). Thinking clearly about violent cognitions: Attitudes may be distinct from other cognitions. Journal of Interpersonal Violence, 30, 1322-1347. doi:10.1177/0886260514540329

57.

Nunes

K. L.

Hermann

C. A.

Ratcliffe

(2013). Implicit and explicit attitudes towards rape are associated with sexual aggression. Journal of Interpersonal Violence, 28, 2657-2675. doi:10.1177/0886260513487995

58.

Nunes

K. L.

Pettersen

Hermann

C. A.

Looman

Spape

(2016). Does change on the MOLEST and RAPE scales predict sexual recidivism? Sexual Abuse: A Journal of Research and Treatment. 28, 427–447.

59.

O’Connor

(2000). SPSS and SAS programs for determining the number of components using parallel analysis and Velicer’s MAP test. Behavior Research Methods, Instruments, and Computers, 32, 396-402. doi:10.3758/BF03200807

60.

Osgood

C. E.

Suci

G. J.

Tannenbaum

P. H.

(1957). The measurement of meaning. Urbana: University of Illinois.

61.

Payne

D. L.

Lonsway

K. A.

Fitzgerald

L. F.

(1999). Rape myth acceptance: Exploration of its structure and its measurement using the Illinois Rape Myth Acceptance Scale. Journal of Research in Personality, 33, 27-68.

62.

Petty

R. E.

Briñol

DeMarree

K. G.

(2007). The meta-cognitive model (MCM) of attitudes: Implications for attitude measurement, change, and strength [Special issue: What is an attitude?]. Social Cognition, 25, 657-686. doi:10.1521/soco.2007.25.5.657

63.

Pham

A. T.

Maimone

Nunes

K. L.

Kostiuk

Babchishin

K. M.

Malcom

J. R.

. . . Jung

(2015, June). Can sexual offender risk assessment instruments be accurately scored from self-report information alone? In Nunes

K. L.

(Chair), Examining violent behaviour with virtual reality, self-report, and vignettes. Symposium conducted at the 3rd North American Correctional and Criminal Justice Psychology Conference, Ottawa, Ontario, Canada.

64.

Piquero

A. R.

Schubert

C. A.

Brame

(2014). Comparing official and self-report records of offending across gender and race/ethnicity in a longitudinal study of serious youthful offenders. Journal of Research in Crime & Delinquency, 51, 526-556. doi:10.1177/0022427813520445

65.

Rapaport

Burkhart

(1984). Personality and attitudinal characteristics of sexually coercive college males. Journal of Abnormal Psychology, 93, 216-221.

66.

Schmitt

T. A.

(2011). Current methodological considerations in exploratory and confirmatory factor analysis. Journal of Psychoeducational Assessment, 29, 304-321. doi:10.1177/0734282911406653

67.

Schmitt

T. A.

Sass

D. A.

(2011). Rotation criteria and hypothesis testing for exploratory factor analysis: Implications for factor pattern loadings and interfactor correlations. Educational and Psychological Measurement, 71, 95-113. doi:10.1177/0013164410387348

68.

Schwarz

(2007). Attitude construction: Evaluation in context. Social Cognition, 25, 638-656. doi:10.1521/soco.2007.25.5.638

69.

Suarez

Gadalla

T. M.

(2010). Stop blaming the victim: A meta-analysis on rape myths. Journal of Interpersonal Violence, 25, 2010-2035. doi:10.1177/0886260509354503

70.

Taylor

H. F.

(1971). Semantic differential factor scores as measures of attitude and perceived attitude. Journal of Social Psychology, 83, 229-234.

71.

Thornberry

T. P.

Krohn

M. D.

(2000). The self-report method for measuring delinquency and crime. In Duffee

Crutchfield

R. D.

Mastrofski

Mazerolle

McDowall

Ostrom

(Eds.), Criminal justice 2000: Innovations in measurement and analysis (Vol. 4, pp. 33-83). Washington, DC: National Institute of Justice.

72.

Ward

Gannon

T. A.

Keown

(2006). Beliefs, values, and action: The judgment model of cognitive distortions in sexual offenders. Aggression and Violent Behavior, 11, 323-340.

73.

Weinrott

M. R.

Saylor

(1991). Self-report of crimes committed by sex offenders. Journal of Interpersonal Violence, 6, 286-300. doi:10.1177/088626091006003002

74.

Widman

Olson

(2013). On the relationship between automatic attitudes and self-reported sexual assault in men. Archives of Sexual Behavior, 42, 813-823. doi:10.1007/s10508-012-9970-2

75.

Woods

Hermann

C. A.

Nunes

K. L.

McPhail

I. V.

Sewell

(2011, June). The validity of self-reported risk among sex offenders. Poster presented at the 2nd North American Correctional and Criminal Justice Psychology Conference, Toronto, Ontario, Canada.

76.

Zinzow

H. M.

Thompson

(2015). Longitudinal study of risk factors for repeated sexual coercion and assault in U.S. college men. Archives of Sexual Behavior, 44, 213-222. doi:10.1007/s10508-013-0243-5