Psychometric properties of the Propensity to Morally Disengage Scale in Peruvian university students: internal structure and association with the dark triad

Introduction: Human morality is an important topic because the fact that human beings can determine if a behavior is correct or incorrect, good or bad, shows that they are endowed with moral conscience, but In the Peruvian context, there are no valid and reliable scales to measure moral disengage trend. This study aimed to analyze the psychometric properties of the Propensity to Morally Disengage Scale in Peruvian university students.

Method: The number of university students who participated in the study was 591 (women = 71.7%; M_age = 21.5; SD_age = 3.60), and the data analysis was carried out under a factor analysis approach.

Results: The results showed a unidimensional structure in both men and women. As for the invariance results according to sex, there is favorable evidence of configural and weak invariance; however, there is no evidence of strong invariance. Furthermore, the reliability of the construct (coefficient ω) and its scores (coefficient α) reached acceptable dimensions in each group and positive associations with the dark triad (Machiavellianism, psychopathy, and narcissism).

Discussion: The Propensity to Morally Disengage Scale is a unidimensional measurement that shows acceptable psychometric evidence in men and women separately. The theoretical and practical implications are discussed.

1 Introduction

Human morality is an important topic that is of great interest for research in different disciplines. The fact that human beings can determine if a behavior is correct or incorrect, good or bad, shows that they are endowed with moral conscience. Therefore, questions about morality are raised based on the need to coexist in harmony, since without consensual moral codes, people would disengage from the rights and wellbeing of others every time their wishes come into social conflict (Bandura, 1990). In this way, social codes and sanctions are articulated with collective moral imperatives and have an impact on social behavior (Bandura, 1990, 1991, 1999).

Albert Bandura introduced the concept of moral disengagement (hereinafter MD) from the social cognitive learning theory. Within this framework, MD is defined as the voluntary inactivation of the self-regulation processes that lead to the selective use of a series of socio-cognitive mechanisms that favor transgressing rules, as well as the disinhibition of aggressive impulses and immoral behaviors (Bandura, 1990, 2002). These mechanisms imply reinterpreting harmful and inhumane behaviors, minimizing the role of damage perpetrators or making it darker, falsifying or distorting the consequences of violent or immoral behavior, and blaming and dehumanizing victims.

Such theory states that moral operation is self-regulated by showing some self-control on behavior, judgments of such behavior, and on the arising affective responses. While developing the moral self, people adopt rules on what is correct and incorrect, through direct or indirect experiences of the environment where they develop, and such rules guide behavior (Bandura, 1990, 1999, 2002). That way, self-behavior is supervised and judged according to internal moral rules and the circumstances where it is produced. For that reason, individuals try to behave in a way that keeps them from transgressing their own moral rules so as to avoid self-condemnation. Such continuous self-evaluation motivates and regulates moral behavior, acting as an activation and inhibition system. However, self-regulation mechanisms depend on the context and they also allow moral self-sanctions to be selectively disassociated from the non-moral behavior (Bandura, 1990, 1999, 2002).

In this context, MD (Bandura, 1990) provides a specific model that explains how people transgress their personal ethics. Normally, people seek consistency between what they think is right and their behaviors, since any discrepancies between both aspects normally generates feelings of psychological discontent. In this way, MD is based on the cognitive restructuring of immoral behavior, which turns it into justified behavior. That is, if people can step away from their moral rules, it is easier to justify their participation in behaviors that they would normally consider immoral.

Therefore, Bandura (1990) described eight cognitive mechanisms that can generate MD. The first three of these mechanisms make the cognitive restructuring of cruel and unlawful acts easier. Hence, in this manner, actions can seem less harmful and somehow beneficial. Moral justification refers to justifying an unlawful act as being acceptable depending on the perceived potential result. Euphemistic labeling occurs when certain language is used to hide the blame by distorting what happened. Advantageous comparison refers to justifying an unlawful act by comparing it to even more harmful acts. The next two cognitive mechanisms minimize the individual’s role in the damage caused. Thus, in displacement of responsibility, the responsibility of harmful or unlawful behaviors tends to be attributed to some authority figure that exercises pressure or issues orders. Diffusion of responsibility occurs when immoral behavior is shared, the trend being that no person involved in the unlawful act finds themselves completely guilty of such event. The three last cognitive mechanisms distort the effects of self-actions. Distortion of consequences means minimizing the impact or effect of the unlawful behavior. Dehumanization means denying the human qualities or characteristics of the victim of the unlawful act in order to refer to them as brutal. Finally, attribution of blame proposes that the blame of unlawful acts lies in provoking the victim that caused the problem. The eight mechanisms mentioned above restructure the way people make decisions or perform non-moral actions.

Individuals’ trend toward MD is an important indicator of society’s wellbeing. This can be seen in the scientific evidence that shows how MD is associated with frequent social problems, such as crime (Shulman et al., 2011), aggression and violence in different environments (Bandura et al., 1996; Obermann, 2011; Gini et al., 2014; Wang et al., 2017), alcohol and other drug consumption (Newton et al., 2012; Passini, 2012), white-collar crimes (Barsky, 2011; Christian and Ellis, 2014), fraud-related conducts, (Moore et al., 2012) and antisocial behaviors (Hyde et al., 2010).

Regarding university students, it has been proven that MD is an indicator of academic dishonesty, which within the academic context can be expressed as cheating behaviors, plagiarism, and unauthorized collaboration (Farnese et al., 2011; Risser and Eckert, 2016; Ampuni et al., 2020). Furthermore, MD has been associated with cyber aggression, and aggressors are those students that use, to a larger extent, the advantageous comparison, distortion of consequences, and attribution of blame mechanisms (Lee and Jang, 2022). It has also been proved that MD impacts the perception of violence based on belonging to a group (McCreary et al., 2016). For this reason, it can be inferred that the degree of MD of university students will affect their interpersonal relationships in fields where social bonds are relevant.

On the other hand, the foregoing literature proves that gender is an important factor to be considered when studying MD, as men get higher scores than women (Bandura, 2002; Obermann, 2011; De Caroli and Sagone, 2014; Wang et al., 2017; Gómez-Tabares and Narváez-Marín, 2019; Gómez-Tabares et al., 2021); furthermore, it has been found that gender differences in unethical behaviors increase in magnitude when considering the role of MD (Detert et al., 2008). These differences can be attributed to the role society plays in assigning gender as according to Bandura (2002), MD makes no difference in gender in the first years of life, but as time goes by, boys become more vulnerable to morally disassociate compared to girls. Thus, the vicarious and social modeling processes established during upbringing and in the first years of socialization are fundamental for the development and manifestation of moral behavior in adolescence and adulthood (Carlo et al., 1999). Gilligan (1982) states that the differences in childhood socialization experiences of girls and boys ensure that gender plays a relevant role in moral decision-making and explains the differences in moral orientation of boys and girls. Schminke (1997) offers a similar explanation, pointing out that gender socialization determines differences in the configuration of the ethical frameworks that men and women use in their moral judgments. Therefore, men’s moral judgment and behavior would be oriented by the search for personal achievement, competitive success, and extrinsic rewards. In contrast, in the case of women, morality would be oriented to the care of interpersonal relationships and effective fulfillment of tasks; thus, they would be more sensitive to adhering to ethical norms and more concerned about the consequences of their actions. In Peru, these differences stand out due to gender inequalities, as it is currently ranked 90th in the Gender Inequality Index Rank and 37th in the Global Gender Gap Index Rank, which assesses gaps at the economic, political, educational and health levels (United Nations-Women, 2023).

Although previous studies have found gender differences in studies of MD, few investigations have verified the measurement invariance of the instrument used; those that do exist focus on the child population (García-Vásquez et al., 2019), which would not be extrapolable to this study. Therefore, to better understand the effect of gender on MD, the equivalence of the factorial structure of the MD measures should be studied according to gender, because, if differences are found at the statistical level, we must know whether they are due to mean bias or if they represent legitimate differences in the manifestation of MD.

The association of MD with the dark triad of personality has also been studied. It refers to the constellation of three features representing questionable social behaviors: psychopathy, narcissism, and Machiavellianism (Paulhus and Williams, 2002). Psychopathy is characterized by the absence of empathy, lack of remorse or guilt, indifference, and poor and irresponsible behavior control (Muris et al., 2017). However, Machiavellianism can be seen through cynical contempt for morality, lack of empathy, and an excessive focus on personal ambition and interest, since Machiavellian people manipulate and exploit others with the goal of obtaining personal benefits (Muris et al., 2017). Finally, narcissism is characterized by a strong need of recognition and admiration, as well as a huge sense of self-worth. Narcissist people are egocentric, and they often consider that they deserve special treatment (Muris et al., 2017).

In addition, the dimensions’ characteristics of the dark personality suggest that those personalities with a high level of Machiavellianism and psychopathy are more susceptible to cross the moral boundaries that lead to poor ethical behaviors (Sijtsema et al., 2019); while people with high levels of narcissism can be drawn to transgress moral rules due to the fact that they prioritize their personal interest over the interest of others (Egan et al., 2015). In this context, several studies have proved the positive association of MD and the dark triad components in diverse groups that present perpetrators of violence against women and men in the community (Navas et al., 2022b), organizations, (Yanuari, 2022), penitentiary field (Brugués and Caparrós, 2022), adolescents (Navas et al., 2022a), consumers (Kapoor et al., 2021), and university students (Qiao et al., 2021).

Despite the relevance of MD and considering how it is associated with other variables, most of the psychological research linked to the moral field is restricted to studying moral thinking or judgment; this can be the result of the rational bias of many moral theories (Bandura, 1991) that set aside the problem of measuring the construct. This can be shown in the scarce instrumental research regarding the MD construct in Latin America, especially in Peru, where citizens perceive a lot of corruption (Transparency International, 2021).

Regarding MD measurement, Bandura et al. (1996) developed an instrument for children and adolescents that considers 32 items and measures the eight previously described mechanisms of moral disengagement. However, when analyzing the factorial structure of the instrument using the principal component method, authors found a unidimensional structure that explains 16.2% of the total variance, with a reliability of 0.82. This instrument has been adapted by different authors in different countries.

The findings of various studies that have analyzed the internal structure of the scale developed by Bandura et al. (1996) are not consistent; some authors have reported evidence in favor of the unidimensional structure (Paciello et al., 2008; Bautista et al., 2020), while other authors found a four-factor solution that corresponds to the four categories included in the moral disengagement mechanisms (Newton et al., 2016). Other studies present results supporting the eight-factor model that corresponds to each moral disengagement mechanism (Boardley and Kavussanu, 2007). Meanwhile, Rubio-Garay et al. (2017), in a sample of Spanish adolescents and youths, found evidence in favor of a structure with a general second-order factor (moral disengagement) and three first-order factors.

Additionally, there are other ways to measure MD in specific situations, such as school harassment (García-Vásquez et al., 2019), ethnic harassment (Lo Cricchio et al., 2022), legal violations (Kirshenbaum et al., 2021), non-compliance of ethical rules in research (DuBois et al., 2016), violations in the military context (McAlister, 2001), and collective moral disengagement (Gini et al., 2014), among others.

Moore et al. (2012) developed an eight-item measurement for MD that shows some advantages against the previously developed instruments. First of all, the eight moral disengagement mechanisms are evaluated in a unidimensional way this is consistent with the premise that moral disengagement is a multifaceted and not a multifactorial construct (Bandura et al., 1996). Moreover, as it is brief, the tool can be easily and rapidly implemented and uses a language than can be understood by different adult populations, which expands its application. Regarding its psychometric properties, Moore et al. (2012) used a confirmatory factor analysis that confirmed that the instrument is unidimensional; furthermore, they gathered evidence of the connection between the expected theoretical relationships of MD and other associated constructs, such as Machiavellianism (r = 0.46), moral identity (r = −0.42), empathy (r = −0.48), and the obtained correlations among its measurements, and the authors reported an acceptable reliability coefficient (α = 0.80). Likewise, in Ukraine, the eight-item version was found to be the one with the most acceptable statistical indicators both at the level of internal structure and reliability (Karkovska, 2020).

In the Peruvian context, there are no valid and reliable scales to measure MD’s trend, or scales that can also include the advantages shown in the scale developed by Moore et al. (2012). Accordingly, this study aims to analyze the psychometric properties of the Propensity to Morally Disengage Scale proposed by Moore et al. (2012) among Peruvian university students.

As for the research hypotheses, the internal structure is expected to be unidimensional in men and women (Hypothesis 1) given the preliminary evidence. Moreover, the measure is not expected to be invariant between men and women (Hypothesis 2) due to cultural and socialization aspects that have already been described above. Furthermore, a direct and significant relationship is expected between MD and the Dark Triad dimensions (Hypothesis 3). Further, that there are differences between men and women in relation to the association between MD and the dimensions of the Dark Triad (Hypothesis 4). Finally, that the measure presents acceptable reliability in men and women (hypothesis 5).

This study is justified because if there is a Peruvian version of the scale with adequate psychometric properties, it can be implemented in studies that address MD in a series of social phenomena where citizens’ wellbeing is being violated. Examples of such phenomena are violence; corruption, crime; and in general, all behaviors against morality and ethical principles, which take place in a country characterized by high rates of violence and corruption (Montero, 2017; Transparency International, 2021). In addition, the study of MD in university students highlights the relevance of assessing morality-related aspects in future professionals, since as the empiric evidence shows, high MD levels are associated with unethical personal and professional behaviors, which then results in an inefficient professional exercise that undermines societies’ wellbeing.

2 Materials and methods

2.1 Participants

This research is an instrumental study (Ato et al., 2013). The minimum sample size required (n = 256) was defined based on specific recommendations (Soper, 2023) by considering statistical power (0.95), effect size (0.50 as the minimum value of the factorials), probability level (0.05), number of latent variables (3, for the oblique model), and number of observed variables (8 items). In this sense, intentional non-probabilistic sampling was used, where 591 university students participated (71.7% women), of Peruvian nationality who live in the Metropolitan area of Lima and within the age group between 18 and 40 years (M_age = 21.5; SD_age = 3.60). Among the participants, 77% and 23% are private and public university students, respectively. Undergraduate students from different majors and academic years were included, and the majors related to social sciences (e.g., anthropology; 25.9%) and health sciences (e.g., nursing; 24%) were the most frequent. No statistical differences were found between men and women with respect to age (t = 0.368, p = 0.713) or university of origin (χ² = 0.968, p = 325).

2.2 Measurements

2.2.1 Propensity to Morally Disengage Scale

Created by Moore et al. (2012), it is a unidimensional scale that measures the propensity of people to disconnect morally. It is composed of eight items and each item represents one of the mechanisms of moral disengagement proposed by Bandura (2016) (moral justification, euphemistic labeling, advantageous comparison, displacement of responsibility, diffusion of responsibility, distortion of consequences, dehumanization, and attribution of blame). The items have a Likert-type response format with seven alternatives: from strongly disagree (1 point) to strongly agree (7 points). Full questionnaire is included in the Supplementary material.

2.2.2 Dirty dozen dark triad (DDDT)

Created by Jonason and Webster (2010), it is a measurement of the personality dark triad that includes 12 items, organized into three sub-scales: Machiavellianism [e.g., “Manipular a los demás para conseguir lo que quiere.” (Manipulate others to get what you want)], psychopathy [e.g., “No preocuparse mucho por la moralidad de sus acciones.” (Not worry too much about the morality of your actions)], and narcissism [e.g., “Querer que otras personas lo admiren.” (Want others to admire you)]. The version used was the one of Copez-Lonzoy et al. (2019), which was adapted to the Peruvian context. The items are scored using a Likert-type scale of five points: from never (1 point) to almost always (5 points). From the data collected in this research, the reliability indicators found were considered acceptable for the sub-scales of Machiavellianism (α = 0.866), psychopathy (α = 0.775), and narcissism (α = 0.838).

2.3 Procedure

The processes included translating and validating the measurement of the trend to morally disassociate, which was proposed by Moore et al. (2012). The translation process was carried out following the recommendations proposed by Guillemin et al. (1993), including the stages of initial and back translation. All were performed by different translators who did not know the content of the original instrument. The revision committee performed the evaluation and a focus group did the pre-testing.

Three professional translators with an advanced English level were considered for the initial translation stage to translate the original version of the scale into Spanish, specifically as spoken in Peru. The answers of the three translators were checked, compared, and assessed. The revision committee took into consideration the clarity criterion and made any necessary adjustments to ensure the content of the items could be understood.

After choosing the most adequate Spanish version for each of the items, the back translation was done; two translators, different from the initial three, performed an independent translation of the Spanish version of the scale into English. Finally, researchers compared the answers of the second group of translators with the original version of the instrument, and they prepared a consolidated version of the translated scale.

A focus group of 12 volunteer students (six men and six women) from a private university in Lima evaluated the clarity of the items of the consolidated version and confirmed the clarity of the translated items.

Later on, an online form was designed using the Google Forms platform that included the informed consent form, personal data sheet, and the previously presented questionnaires. The online form was shared by email and social networks like Facebook and WhatsApp during the first quarter of 2022. Emails and cell phone numbers were accessed through the records of the courses in which they were enrolled, with the consent of the students.

As part of the ethical considerations, voluntary and anonymous participation and confidentiality were guaranteed, in compliance with the guidelines provided in the Declaration of Helsinki and the ethics code of the College of Psychologists of Peru (Colegio de Psicólogos del Perú., 2017).

2.4 Data analysis

2.4.1 Validity evidence based on internal structure

A confirmatory factor analysis (CFA) of the Propensity to Morally Disengage Scale was conducted in men and women using the weighted least square mean and variance adjusted estimator (WLSMV) due to its suitability for ordinal items (Li, 2016a,b), and the polychoric correlations matrix. Two models were evaluated; a three-factor oblique model (moral justification, diffusion of responsibility and attribution of blame; García-Vásquez et al., 2019) and a unidimensional model (Moore et al., 2012).

The models were evaluated according to the dimensions of the fit indices CFI, NFI, and TLI (>0.90; McDonald and Ho, 2002), RMSEA (<0.08; Browne and Cudeck, 1993), and WRMR (<1; DiStefano et al., 2018). Furthermore, factor loadings (>0.50; Dominguez-Lara, 2018) and potential misspecification associated to correlated residuals were considered (Saris et al., 2009). Thus, measurement invariance was assessed in the model that presented the best psychometric evidence.

2.4.2 Measurement invariance

A multi-group factor analysis was implemented to obtain evidence of the measurement invariance according to sex for which, factorial parameters were gradually restricted to evaluate the configural, weak, and strong invariance (Pendergast et al., 2017). The degree of measurement invariance was generally evaluated, considering the variation of its fit indices (CFI and RMSEA); that is, there is not enough evidence of measurement invariance if ΔCFI < −0.01 and ΔRMSEA ≥ 0.015 (Chen, 2007). Specifically, factorial parameters were compared (factor loadings, thresholds, and residuals) under an effect size approach (ES) applied to the measurement invariance (Pornprasertmanit, 2014). When comparing the factor loadings, thresholds, and residuals, the q (0.10, small difference; 0.30, medium; 0.50, big; large, 1988), d (0.20, small difference; 0.50, medium; 0.80, large; Choi et al., 2009), and h (0.20, small difference; 0.50, medium; 0.80, large; Cohen, 1988) coefficients were used, respectively.

2.4.3 Validity evidence based on relations to other variables

Moral disengagement association with the dark triad dimensions (Machiavellianism, narcissism, and psychopathy) was analyzed using the Pearson correlation coefficient (>0.20; Ferguson, 2009), separately in men and women. A confidence interval for the difference between coefficients was obtained (CI_diff; Zou, 2007); that is, if the CI = 0, it is concluded that there is no significant difference in the strength of association of the variables.

2.4.4 Reliability

The construct and scores reliability were calculated by means of the omega (ω > 0.70; Hunsley and Marsh, 2008) and alpha coefficient (α > 0.70; Ponterotto and Charter, 2009), respectively, which were both compared in each group (men and women); the difference between α and ω was considered significant if is greater than | 0.06| (Gignac et al., 2007). At the same time, the comparison between men and women in such coefficients was done considering the CI_diff (Moreta-Herrera et al., 2021).

2.4.5 Software

The analytic-factorial processes were done with the software Mplus version 7 (Muthén and Muthén, 1998–2015), and the effect size (ES) applied to the invariance, misspecification, and comparison of the reliability coefficients with the specialized modules (Dominguez-Lara and Merino-Soto, 2018, 2019; Dominguez-Lara et al., 2018).

3 Results

3.1 Validity evidence based on internal structure

First, the three-factor oblique model was evaluated for men and women. The fit indices were adequate in men (CFI = 0.946; NFI = 0.931; TLI = 0.911; RMSEA = 0.146; CI 90% = 0.113, 0.180; WRMR = 0.706) and women (CFI = 0.982; NFI = 0.956; TLI = 0.970; RMSEA = 0.058; CI 90% = 0.035, 0.081; WRMR = 0.507), although in the case of men, the RMSEA exceeds the established value. Moreover, the interfactor correlations were high for both groups (ϕ > 0.85), which did not provide favorable evidence of multidimensionality.

Meanwhile, the unidimensional model had an acceptable fit in men and women regarding the CFI and WRMR, although RMSEA only reached an adequate dimension in women (Table 1). This provides empirical support for Hypothesis 1.

TABLE 1

Table 1. Factor analysis and measurement invariance according to sex.

In the case of men, the misspecification potential analysis suggested that the residuals of items 3 [Considerando las formas descaradas en que las personas falsifican su información, no es pecado inflar un poco tus credenciales (Considering the ways people grossly misrepresent themselves, it’s hardly a sin to inflate your own credentials a bit.)] and 4 [Las personas no deberían ser responsables por hacer cosas cuestionables cuando solo estaban haciendo lo que una autoridad les ordenó (People shouldn’t be held accountable for doing questionable things when they were just doing what an authority figure told them to do.)] should be associated [Modification Index (MI) = 29.483; Expected Parameter Change (EPC) = 0.460], in a similar way to the residuals of items 6 [Llevarse el crédito por ideas que no son tuyas, no es gran cosa (Taking personal credit for ideas that were not your own is no big deal.)] and 8 [Las personas que son maltratadas, por lo general, han hecho algo para provocarlo (People who get mistreated have usually done something to bring it on themselves)] (MI = 32.605; EPC = 0.520). However, regarding women, the results suggest the association of the residuals of items 1 [Está bien difundir rumores para defender a los que queremos (It is okay to spread rumors to defend those you care about.)] and 2 [Es aceptable tomar algo sin el permiso del dueño, siempre y cuando solo lo tomemos prestado (Taking something without the owner’s permission is okay as long as you’re just borrowing it.)] (MI = 16.309; EPC = 0.273), as well as the residuals of items 7 [Algunas personas deben ser tratadas con rudeza porque no tienen sentimientos que se puedan herir (Some people have to be treated roughly because they lack feelings that can be hurt.)] and 8 [Las personas que son maltratadas, por lo general, han hecho algo para provocarlo (People who get mistreated have usually done something to bring it on themselves.)] (MI = 14.218; EPC = 0.333).

3.2 Measurement invariance according to sex

The configural invariance reached adequate dimensions considering the fit indices, and the weak invariance is supported, even though the results could not endorse the strong invariance (Table 1). Specifically, considering the configural invariance data (Table 2), significant differences can be seen in the factor loading of item 2, as well as in at least half of the thresholds of six items and two residuals (Table 3). Consequently, the Propensity to Morally Disengage Scale is not invariant between men and women, supporting Hypothesis 2.

TABLE 2

Table 2. Descriptive statistics and factorial parameters (configural invariance) in men and women.

TABLE 3

Table 3. Measurement invariance between men and women: comparison of factor parameters using effect size.

3.3 Validity evidence based on relations to other variables

All of the cases show significant relationships (r > 0.20), supporting Hypothesis 3, and without differences between men and women regarding the association between Propensity to Morally Disengage Scale and the dark triad dimensions (Table 4). This finding does not support Hypothesis 4.

TABLE 4

Table 4. Association with the dark triad: calculation and differences according to sex.

3.4 Reliability

The reliability coefficients of the construct (coefficient ω) and scores (coefficient α) had acceptable dimensions (>0.70; Table 5). Nevertheless, the differences between coefficients were not significant in men (Δ_{ω –α} = 0.032), but in women, they were (Δ_{ω –α} = 0.074). As for the comparison between men and women, only the reliability of the scores showed significant differences (coefficient α) in favor of the group of men (Table 5). Taken together, these findings support Hypothesis 5.

TABLE 5

Table 5. Reliability of the Propensity to Morally Disengage Scale: calculation and differences according to sex.

4 Discussion

This study aimed to analyze the psychometric properties of the Propensity to Morally Disengage Scale proposed by Moore et al. (2012), in its eight-item version, among Peruvian university students. Regarding the internal structure, the results found using the CFA show adequate fit indices for the single factor model in the sample of women; while in the sample of men, the fit indices had acceptable values in CFI and WRMR, but not in RMSEA. This can be explained by the fact that in the presence of asymmetric data, the RMSEA does not achieve acceptable magnitudes (Cook et al., 2009), while the magnitudes of CFI and TLI are not affected by data asymmetry (Ainur et al., 2017). Even though previous studies to contrast the findings are scarce, it can be assured that they are partially compatible with the findings of the study of Moore et al. (2012) and Karkovska (2020). Those studies show that the single factor model of the Propensity to Morally Disengage Scale has adequate fit indices, although, the psychometric analysis in the studies of Moore et al. (2012) and Karkovska (2020) were performed in the whole sample without considering the sex.

Regarding the potential misspecification analysis, in the case of women, the results suggest the association of the residuals of item 1 [Está bien difundir rumores para defender a los que queremos (It is okay to spread rumors to defend those you care about.)] and item 2 [Es aceptable tomar algo sin el permiso del dueño, siempre y cuando solo lo tomemos prestado (Taking something without the owner’s permission is okay as long as you’re just borrowing it.)], which corresponds to the MD mechanisms moral justification and euphemistic labeling, respectively. Thus, the common aspect among residuals, which is not part of the MD construct, is explained because both mechanisms promote the cognitive restructuring of immoral or reprehensible behaviors to turn them into less harmful behaviors (Bandura, 1990, 1991, 1999). Additionally, regarding the group of women, results suggest the association of the residuals of item 7 [Algunas personas deben ser tratadas con rudeza porque no tienen sentimientos que se puedan herir (Some people have to be treated roughly because they lack feelings that can be hurt.)] and item 8 [Las personas que son maltratadas, por lo general, han hecho algo para provocarlo (People who get mistreated have usually done something to bring it on themselves.)], which corresponds to MD mechanisms dehumanization and attribution of blame, respectively. Similar to the previous case, this association among residuals would be explained considering that both mechanisms lead to the distortion of the victim’s perception, whether by denying their human qualities or by attributing the victim the responsibility of causing unlawful behaviors that have harmed them (Bandura, 1990, 1991, 1999).

In the case of men, the misspecification potential analysis suggests that the residuals that should be associated are those of item 3 [Considerando las formas descaradas en que las personas falsifican su información, no es pecado inflar un poco tus credenciales (Considering the ways people grossly misrepresent themselves, it’s hardly a sin to inflate your own credentials a bit.)] and item 4 [Las personas no deberían ser responsables por hacer cosas cuestionables cuando solo estaban haciendo lo que una autoridad les ordenó (People shouldn’t be held accountable for doing questionable things when they were just doing what an authority figure told them to do.)], which corresponds to MD mechanisms advantageous comparison and displacement of responsibility, respectively, since both mechanisms promote cognitive distortion of behaviors that are reprehensible and that fall under the responsibility of the agent executing such behavior (Bandura, 1990, 1991, 1999). Furthermore, it is suggested to associate the residuals of item 6 [Llevarse el crédito por ideas que no son tuyas, no es gran cosa (Taking personal credit for ideas that were not your own is no big deal.)] and item 8 [Las personas que son maltratadas, por lo general, han hecho algo para provocarlo (People who get mistreated have usually done something to bring it on themselves)], which corresponds to MD mechanisms distortion of consequences and attribution of blame, since these mechanisms seek to avoid self-censorship by distorting the causes and consequences of immoral actions. On the one hand, the mechanisms attribute the responsibility for the immoral act’s origin to the victim itself, and on the other hand, they minimize its consequences (Bandura, 1990, 1991, 1999).

The residuals’ association can be related to factors that are external to the item’s substantive content, such as the writing and numerical proximity within the questionnaire. Nevertheless, in this study, the potential associations among residuals, even if they are not directly related to the common variance (corresponding to the MD construct), could be related to the similarity of the specificity of each of the involved items. This would be consistent with Bandura’s theory when it is stated that moral disengagement is a multifaceted and not a multifactorial construct (Bandura et al., 1996).

Two sources of information stand out when it comes to measurement invariance according to sex. In the first place, fit indices support the configural and weak invariance, but they do not support strong invariance. Therefore, even if the unidimensional structure and the construct representativeness are equivalent regarding factor loadings, DM has a different measurement scale in men and women, and the scores could not be compared. Second, the effect’s measurement dimensions support the foregoing since there is no equivalence in the factor loading of item 2 (euphemistic labeling), as well as in a significant number of thresholds of six items and two residuals.

These findings are explained due to the relevance of the items to measure MD, and the moral values implied in their contents are weighted differently for the men and women under evaluation. Therefore, the Propensity to Morally Disengage Scale measures MD differently in each group. According to Bandura (2002), these differences can be attributed to the role society plays in assigning gender, since MD makes no difference in sex over the first years of life, but with time, boys become more vulnerable to morally disassociate compared to girls. Indeed, from the theory of social cognitive learning, it can be expected that the meaning and relevance of the items that measure DM are different for men and women if it is considered that this is related to the expectations of results of moral actions, which in turn, depend on social learning experiences that tend to be different for men and women (Bandura, 1986). These experiences include personal history of rewards and punishments received for moral behavior, observation of the consequences that other people receive for moral behavior, and verbal instructions about moral aspects that boys and girls receive in interactions with socialization agents. For that matter, even if the resulting means of the items in the groups of men and women show that men present higher scores than women in the Propensity to Morally Disengage Scale items (Bandura, 2002; Obermann, 2011; De Caroli and Sagone, 2014; Wang et al., 2017), it is known that the measurement invariance according to sex has not been previously evaluated in such studies, in a way that guarantees that there is no bias and that the differences in the findings could be analyzed in depth. Due to this lack of evidence and given the underlying possibility that there is a measurement bias inherent to a construct that depends greatly on the social context, it would be advisable to be cautious when considering those results. Even though the limited background in this field prevents from reaching firm conclusions, the findings obtained seem to match those studies that analyzed constructs of moral nature and that could not prove the weak, strong, or strict invariance according to sex (Grigoraş et al., 2020; Bretl and Goering, 2022; Nilsson, 2022).

Regarding the evidence of validity due to its relationship with other variables, positive correlations were found between the Propensity to Morally Disengage Scale and the dark triad dimensions (psychopathy, Machiavellianism, and narcissism) in both the groups of men and women. This is consistent with the current scientific literature that demonstrated the direct association of MD with the personality dark triad in different contexts (Sijtsema et al., 2019; Kapoor et al., 2021; Qiao et al., 2021; Brugués and Caparrós, 2022; Navas et al., 2022a,b; Yanuari, 2022), including the original study of Propensity to Morally Disengage Scale (Moore et al., 2012). Additionally, while it was postulated, based on previous literature, that this association is likely to differ between men and women, the absence of differences would reflect the complexity of the DM construct in that, regardless of whether it is assessed differently for men and women, its association with Dark Triad traits remains significant.

However, regarding reliability, coefficients α and ω reached adequate values in the group of men and women. However, the measurement seems to be more robust in men since the measurement error tolerated at the construct level (coefficient ω) and scores (coefficient α) remained constant in this group, while the women’s group showed an increase in the measurement error in the coefficient α. Therefore, it is implied that the Propensity to Morally Disengage Scale is a reliable instrument, just as the study of Moore et al. (2012) has proven, although it is more consistent in men.

The practical implications of this study are mainly related to the fact that a brief and easy to use measurement instrument was provided, and it can be implemented as a unidimensional way of measuring MD among Peruvian university students. As such, it is possible to implement the instrument in the educational context to prevent and address different moral problems, such as dishonest behaviors in academic environments (e.g., plagiarism) or harassment among students. Additionally, using the Propensity to Morally Disengage Scale in the research context will help broaden knowledge and understanding the characteristics, predictors, and consequences of MD in order to create explanatory models appropriate for each context.

The findings’ interpretation should take into consideration some limitations. The first limitation is the non-probabilistic nature of the sampling used, which restricts the generalization of the results. Second, the reliability of the Propensity to Morally Disengage Scale considered only the internal consistency perspective, so the conclusions regarding the measurement’s temporary stability are pending. Third, the instruments that were used are only self-report measures; this could create bias related to the social desirability of the participants, especially in variables linked to morality. Finally, based on the relationship with other variables, validity has only been evaluated from the perspective of convergent validity through its association with dark triad. Therefore, the evaluation of divergent validity considering variables linked to the orientation toward ethical or prosocial behaviors is still pending.

Therefore, it is concluded that the Propensity to Morally Disengage Scale is a unidimensional measurement that shows acceptable psychometric evidence (robust internal structure, adequate reliability coefficients, and coherent theoretical association with the dark triad) in men and women separately. However, given that one of the fit indices obtained in the CFA for the male group is above the expected value, the factor structure of the instrument should be further evaluated to explore the consistency of this finding.

Finally, it is recommended for future research to use samples that are representative of the Peruvian university population, and that are homogeneous in terms of gender or other relevant characteristics. Additionally, considering the findings, it is expected that future studies can replicate the invariance analysis and verify if the absence of invariance according to sex was unique for this study or if it is a steady aspect among samples. Moreover, using complementary approaches could help understand the differences in the invariance analysis of each item, like the item response theory. Thus, the items’ differential performance in the group of men and women could be studied in depth from a different perspective, other than based on the classic test theory. Finally, additional psychometric properties must be explored, like the test-retest reliability, the divergent and convergent validity evidence with other psychological and social variables, and the invariance measurement according to age group or other relevant sociodemographic variables.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The studies involving humans were approved by the Comité Evaluador de la Carrera de Psicología, Universidad San Ignacio de Loyola. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

SL-H: Conceptualization, Methodology, Project administration, Writing—original draft, Writing—review and editing. SD-L: Conceptualization, Data curation, Formal analysis, Writing—original draft, Writing—review and editing. AS-B: Methodology, Writing—original draft, Writing—review and editing.

Funding

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/feduc.2023.1275951/full#supplementary-material

References

Ainur, A., Sayang, M., Jannoo, Z., and Yap, B. W. (2017). Sample size and non-normality effects on goodness of fit measures in structural equation models. Pertanika J. Sci. Technol. 25, 575–586.

Google Scholar

Ampuni, S., Kautsari, S., Maharani, M., Kuswardani, S., and Suryo, S. (2020). Academic dishonesty in Indonesian college students: an investigation from a moral psychology perspective. J. Acad. Ethics. 18, 395–417. doi: 10.1007/s10805-019-09352-2

Crossref Full Text | Google Scholar

Ato, M., López, J., and Benavente, A. (2013). Un sistema de clasificación de los diseños de investigación en psicología. An. Psicol. 29, 1038–1059. doi: 10.6018/analesps.29.3.178511

Crossref Full Text | Google Scholar

Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Hoboken, NJ: Prentice-Hall, Inc.

Google Scholar

Bandura, A. (1990). Selective activation and disengagement of moral control. J. Soc. Issues. 46, 27–46. doi: 10.1111/j.1540-4560.1990.tb00270.x

Crossref Full Text | Google Scholar

Bandura, A. (1991). “Social cognitive theory of moral thought and action,” in Handbook of moral behavior and development: Theory, research and applications, eds W. M. Kurtines and J. L. Gewirtz (Londres: Psychology Press), 71–129.

Google Scholar

Bandura, A. (1999). Moral disengagement in the perpetuation of inhumanities. Pers. Soc. Psychol. Rev. 3, 193–209. doi: 10.1207/s15327957pspr0303_3

PubMed Abstract | Crossref Full Text | Google Scholar

Bandura, A. (2002). Selective moral disengagement in the exercise of moral agency. J. Moral Educ. 31, 101–119. doi: 10.1080/0305724022014322

Crossref Full Text | Google Scholar

Bandura, A. (2016). Moral disengagement: How people do harm and live with themselves. New York, NY: Worth Publishers.

Google Scholar

Bandura, A., Barbaranelli, C., Caprara, G. V., and Pastorelli, C. (1996). Mechanisms of moral disengagement in the exercise of moral agency. J. Pers. Soc. Psychol. 71, 364–374. doi: 10.1037/0022-3514.71.2.364

Crossref Full Text | Google Scholar

Barsky, A. (2011). Investigating the effects of moral disengagement and participation on unethical work behavior. J. Bus. Ethics 104, 59–75. doi: 10.1007/s10551-011-0889-7

Crossref Full Text | Google Scholar

Bautista, G., Vera, J. A., Cuevas, M. C., and Tánori, J. (2020). Propiedades psicométricas de un instrumento de mecanismos de desconexión moral: validación en adolescentes del noroeste de México. Eur. J. Psychol. Educ. 13, 127–141. doi: 10.30552/ejep.v13i2.356

Crossref Full Text | Google Scholar

Boardley, I. D., and Kavussanu, M. (2007). Development and validation of the moral disengagement in sport scale. J. Sport. Exerc. Psychol. 29, 608–628. doi: 10.1123/jsep.29.5.608

PubMed Abstract | Crossref Full Text | Google Scholar

Bretl, B. L., and Goering, M. (2022). Age-and sex-based differences in the moral intuitions of American early adolescents. Evol. Hum. Sci. 4, e33. doi: 10.1017/ehs.2022.34

PubMed Abstract | Crossref Full Text | Google Scholar

Browne, M. W., and Cudeck, R. (1993). “Alternative ways of assessing model fit,” in Testing structural equation models, eds K. A. Bollen and J. S. Long (Newbury Park, CA: Sage), 445–455.

Google Scholar

Brugués, G., and Caparrós, B. (2022). Dysfunctional personality, Dark Triad and moral disengagement in incarcerated offenders: implications for recidivism and violence. Psychiatr. Psychol. Law. 29, 431–455. doi: 10.1080/13218719.2021.1917011

PubMed Abstract | Crossref Full Text | Google Scholar

Carlo, G., Raffaelli, M., Laible, D. J., and Meyer, K. A. (1999). Why are girls less physically aggressive than boys? Personality and parenting mediators of physical aggression. Sex Roles 40, 711–729. doi: 10.1023/A:1018856601513

Crossref Full Text | Google Scholar

Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Struct. Equ. Model. 14, 464–504. doi: 10.1080/10705510701301834

Crossref Full Text | Google Scholar

Choi, J., Fan, W., and Hancock, G. R. (2009). A note on confidence intervals for two-group latent mean effect size measures. Multivar. Behav. Res. 44, 396–406. doi: 10.1080/00273170902938902

PubMed Abstract | Crossref Full Text | Google Scholar

Christian, J., and Ellis, A. J. (2014). The crucial role of turnover intentions in transforming moral disengagement into deviant behavior at work. J. Bus. Ethics 119, 193–208. doi: 10.1007/s10551-013-1631-4

Crossref Full Text | Google Scholar

Cohen, J. (1988). Statistical power analysis for the behavioral sciences, 2nd Edn. New Jersey: Lawrence Erlbaum Associates.

Google Scholar

Colegio de Psicó,logos del Perú. (2017). Código de ética y deontología. Available online at: https://www.cpsp.pe/documentos/marco_legal/codigo_de_etica_y_deontologia.pdf (accessed March 15, 2021).

Google Scholar

Cook, K. F., Kallen, M. A., and Amtmann, D. (2009). Having a fit: impact of number of items and distribution of data on traditional criteria for assessing IRT’s unidimensionality assumption. Qual. Life Res. 18, 447–460. doi: 10.1007/s11136-009-9464-4

PubMed Abstract | Crossref Full Text | Google Scholar

Copez-Lonzoy, A., Dominguez-Lara, S., and Merino-Soto, C. (2019). ¿Inestabilidad en el lado oscuro? estructura factorial, invarianza de medición y fiabilidad de la Dirty Dozen Dark Triad en población general de Lima. Rev. Psicopatol. Psicol. Clin. 24, 153–162. doi: 10.5944/rppc.24335

Crossref Full Text | Google Scholar

De Caroli, M. E., and Sagone, E. (2014). Mechanisms of moral disengagement: An analysis from early adolescence to youth. Procedia Soc. Behav. Sci. 140, 312–317. doi: 10.1016/j.sbspro.2014.04.426

Crossref Full Text | Google Scholar

Detert, J. R., Treviño, L. K., and Sweitzer, V. L. (2008). Moral disengagement in ethical decision making: a study of antecedents and outcomes. J. Appl. Psychol. 93, 374–391. doi: 10.1037/0021-9010.93.2.374

PubMed Abstract | Crossref Full Text | Google Scholar

DiStefano, C., Liu, J., Jiang, N., and Shi, D. (2018). Examination of the weighted root mean square residual: Evidence for trustworthiness? Struct. Equ. Model. 25, 453–466. doi: 10.1080/10705511.2017.1390394

Crossref Full Text | Google Scholar

Dominguez-Lara, S. (2018). Propuesta de puntos de corte para cargas factoriales: una perspectiva de fiabilidad de constructo. Enferm. Clín. 28, 401–402. doi: 10.1016/j.enfcli.2018.06.002

PubMed Abstract | Crossref Full Text | Google Scholar

Dominguez-Lara, S., and Merino-Soto, C. (2018). Evaluación de las malas especificaciones en modelos de ecuaciones estructurales. Rev. Arg. Cs. Comp. 10, 19–24. doi: 10.30882/1852.4206.v10.n2.19595

Crossref Full Text | Google Scholar

Dominguez-Lara, S., and Merino-Soto, C. (2019). Estimación de la magnitud del efecto en invarianza de medición. Avaliac. Psicol. 18, 328–332. doi: 10.15689/ap.2019.1803.16248.13

Crossref Full Text | Google Scholar

Dominguez-Lara, S., Merino-Soto, C., and Navarro-Loli, J. (2018). Comparación de coeficientes alfa basada en intervalos de confianza. Educ. Med. 19:70. doi: 10.1016/j.edumed.2017.03.025

Crossref Full Text | Google Scholar

DuBois, J. M., Chibnall, J. T., and Gibbs, J. (2016). Compliance disengagement in research: Development and validation of a new measure. Sci. Eng. Ethics 22, 965–988. doi: 10.1007/s11948-015-9681-x

PubMed Abstract | Crossref Full Text | Google Scholar

Egan, V., Hughes, N., and Palmer, E. J. (2015). Moral disengagement, the dark triad, and unethical consumer attitudes. Pers. Individ. Dif. 76, 123–128. doi: 10.1016/j.paid.2014.11.054

Crossref Full Text | Google Scholar

Farnese, M. L., Tramontano, C., Fida, R., and Paciello, M. (2011). Cheating behaviors in academic context: does academic moral disengagement matter? Procedia Soc. Behav. Sci. 29, 356–365. doi: 10.1016/j.sbspro.2011.11.250

Crossref Full Text | Google Scholar

Ferguson, C. J. (2009). An effect size primer: A guide for clinicians and researchers. Prof. Psychol. Res. Pr. 40, 532–538. doi: 10.1037/a001580

Crossref Full Text | Google Scholar

García-Vásquez, F., Valdés-Cuervo, A., Carlos-Martínez, E., and Alcántar-Nieblas, C. (2019). Propiedades psicométricas de una escala para medir desconexión moral en niños mexicanos. Acta Colomb. Psicol. 22, 118–128. doi: 10.14718/ACP.2019.22.1.6

Crossref Full Text | Google Scholar

Gignac, G. E., Bates, T. C., and Jang, K. (2007). Implications relevant to CFA model misfit, reliability, and the Five Factor Model as measured by the NEO-FFI. Pers. Individ. Dif. 43, 1051–1062. doi: 10.1016/j.paid.2007.02.024

Crossref Full Text | Google Scholar

Gilligan, C. (1982). In a Different Voice: Psychological Theory and Women’s Development. Cambridge, MA: Harvard University Press.

Google Scholar

Gini, G., Pozzoli, T., and Hymel, S. (2014). Moral disengagement among children and youth: A meta-analytic review of links to aggressive behavior. Aggress. Behav. 40, 56–68. doi: 10.1002/ab.21502

PubMed Abstract | Crossref Full Text | Google Scholar

Gómez-Tabares, A. S., and Narváez-Marín, M. (2019). Mecanismos de desconexión moral y su relación con la empatía y la prosocialidad en adolescentes que han tenido experiencias delictivas. Rev. Psicol. 37, 603–641. doi: 10.18800/psico.201902.010

Crossref Full Text | Google Scholar

Gómez-Tabares, A. S., Núñez, C., and Caballo, V. E. (2021). Mecanismos de desconexión moral, diferencias de sexo y predictores clínicos en adolescentes: Un estudio exploratorio. Psykhe 30:22451. doi: 10.7764/psykhe.2020.22451

Crossref Full Text | Google Scholar

Grigoraş, M., Butucescu, A., Miulescu, A., Opariuc-Dan, C., and Iliescu, D. (2020). The measurement invariance of the Short Dark Triad: Implications for high- and low-stakes contexts. J. Individ. Differ. 41, 207–218. doi: 10.1027/1614-0001/a000322

Crossref Full Text | Google Scholar

Guillemin, F., Bombardier, C., and Beaton, D. (1993). Cross-cultural adaptation of health-related quality of life measures: literature review and proposed guidelines. J. Clin. Epidemiol. 46, 1417–1432. doi: 10.1016/0895-4356(93)90142-n

PubMed Abstract | Crossref Full Text | Google Scholar

Hunsley, J., and Marsh, E. J. (2008). “Developing criteria for evidence-based assessment: An introduction to assessment that work,” in A guide to assessments that work, eds J. Hunsley and E. J. Marsh (Londres: Oxford University Press), 3–14.

Google Scholar

Hyde, L. W., Shaw, D. S., and Moilanen, K. L. (2010). Developmental precursors of moral disengagement and the role of moral disengagement in the development of antisocial behavior. J. Abnorm. Child. Psychol. 38, 197–209. doi: 10.1007/s10802-009-9358-5

PubMed Abstract | Crossref Full Text | Google Scholar

Jonason, P. K., and Webster, G. D. (2010). The Dirty Dozen: A concise measure of the Dark Triad. Psychol. Assess. 22, 420–432. doi: 10.1037/a0019265

PubMed Abstract | Crossref Full Text | Google Scholar

Kapoor, P. S., Balaji, M. S., Maity, M., and Jain, N. K. (2021). Why consumers exaggerate in online reviews? Moral disengagement and dark personality traits. J. Retail. Consum. Serv. 60:102496. doi: 10.1016/j.jretconser.2021.102496

Crossref Full Text | Google Scholar

Karkovska, R. (2020). The scale of propensity to moral disengagement as a psycho-diagnostic tool of an organization’s ethics development. Psychol. J. 6, 104–119. doi: 10.31108/1.2020.6.2.10

Crossref Full Text | Google Scholar

Kirshenbaum, J. M., Miller, M. K., Kaplan, T., Cramer, R. J., Trescher, S. A., and Neal, T. M. (2021). Development and validation of a general legal moral disengagement scale. Psychol. Crime Law. 27, 751–778. doi: 10.1080/1068316X.2020.1850722

Crossref Full Text | Google Scholar

Lee, H., and Jang, S. J. (2022). Associations between type D personality, moral disengagement, and cyber aggression among university students. Curr. Psychol. 42, 12648–12660. doi: 10.1007/s12144-021-02578-7

Crossref Full Text | Google Scholar

Li, C. (2016a). The performance of ML, DWLS, and ULS estimation with robust corrections in structural equation models with ordinal variables. Psychol. Methods 21, 369–387. doi: 10.1037/met0000093

PubMed Abstract | Crossref Full Text | Google Scholar

Li, C. (2016b). Confirmatory factor analysis with ordinal data: Comparing robust maximum likelihood and diagonally weighted least squares. Behav. Res. Methods 48, 936–949. doi: 10.3758/s13428-015-0619-7

PubMed Abstract | Crossref Full Text | Google Scholar

Lo Cricchio, M. G., Stefanelli, F., Palladino, B. E., Paciello, M., and Menesini, E. (2022). Development and validation of the ethnic moral disengagement scale. Front. Psychol. 12:756350. doi: 10.3389/fpsyg.2021.756350

PubMed Abstract | Crossref Full Text | Google Scholar

McAlister, A. L. (2001). Moral disengagement: Measurement and modification. J. Peace Res. 38, 87–99. doi: 10.1177/0022343301038001005

Crossref Full Text | Google Scholar

McCreary, G., Bray, N., and Thoma, S. (2016). Bad apples or bad barrels? moral disengagement, social influence, and the perpetuation of hazing in the college fraternity. Oracle 11, 1–15. doi: 10.25774/pvbg-9c47

Crossref Full Text | Google Scholar

McDonald, R. P., and Ho, M.-H. R. (2002). Principles and practice in reporting structural equation analyses. Psychol. Methods 7, 64–82. doi: 10.1037/1082-989X.7.1.64

PubMed Abstract | Crossref Full Text | Google Scholar

Montero, V. (2017). Aspectos psicosociales de la corrupción, la violencia y el ejercicio del poder en el Perú. Rev. Inv. Psic. 20, 209–230.

Google Scholar

Moore, C., Detert, J. R., Klebe Treviño, L., Baker, V. L., and Mayer, D. M. (2012). Why employees do bad things: Moral disengagement and unethical organizational behavior. Pers. Psychol. 65, 1–48. doi: 10.1111/j.1744-6570.2011.01237.x

Crossref Full Text | Google Scholar

Moreta-Herrera, R., Dominguez-Lara, S., Sánchez-Guevara, S., López-Castro, J., and Molina-Narváez, M. J. (2021). Análisis multigrupo por sexo y fiabilidad del Cuestionario de Regulación Emocional (ERQ) en jóvenes ecuatorianos. Aval. Psicol. 20, 220–228. doi: 10.15689/ap.2021.2002.19889.10

Crossref Full Text | Google Scholar

Muris, P., Merckelbach, H., Otgaar, H., and Meijer, E. (2017). The malevolent side of human nature: a meta-analysis and critical review of the literature on the dark triad (narcissism, Machiavellianism, and psychopathy). Perspect. Psychol. Sci. 12, 183–204. doi: 10.1177/1745691616666070

PubMed Abstract | Crossref Full Text | Google Scholar

Muthén, L. K., and Muthén, B. O. (1998–2015). Mplus User’s guide, 7th Edn. Los Angeles: Muthén & Muthén.

Google Scholar

Navas, M. P., Gómez-Fraguela, J. A., and Sobral, J. (2022a). Sexismo y tríada oscura de la personalidad en adolescentes: el rol mediador de la desconexión moral. Rev. Latinoam. Psicol. 54, 76–85. doi: 10.14349/rlp.2022.v54.9

Crossref Full Text | Google Scholar

Navas, M. P., Maneiro, L., Cutrín, O., Gómez-Fraguela, J. A., and Sobral, J. (2022b). Sexism, moral disengagement, and dark triad traits on perpetrators of sexual violence against women and community men. Sex. Abuse. 34, 857–884. doi: 10.1177/10790632211051689

PubMed Abstract | Crossref Full Text | Google Scholar

Newton, N. C., Havard, A., and Teesson, M. (2012). The association between moral disengagement, psychological distress, resistive self-regulatory efficacy and alcohol and cannabis use among adolescents in Sydney, Australia. Addict. Res. Theory. 20, 261–269. doi: 10.3109/16066359.2011.614976

Crossref Full Text | Google Scholar

Newton, N. C., Stapinski, L. A., Champion, K. E., Teesson, M., and Bussey, K. (2016). The reliability and validity of the Australian Moral Disengagement Scale. Behav. Change 33, 136–149. doi: 10.1017/bec.2016.9

Crossref Full Text | Google Scholar

Nilsson, A. (2022). Measurement invariance of moral foundations across population Strata. J. Pers. Assess. 105, 163–173. doi: 10.1080/00223891.2022.2074853

PubMed Abstract | Crossref Full Text | Google Scholar

Obermann, M. L. (2011). Moral disengagement among bystander of school bullying. J. Sch. Violence. 10, 239–257. doi: 10.1080/15388220.2011.578276

Crossref Full Text | Google Scholar

Paciello, M., Fida, R., Tramontano, C., Lupinetti, C., and Caprara, G. V. (2008). Stability and change of moral disengagement and its impact on aggression and violence in late adolescence. Child. Dev. 79, 1288–1309. doi: 10.1111/j.1467-8624.2008.01189.x

PubMed Abstract | Crossref Full Text | Google Scholar

Passini, S. (2012). The delinquency-drug relationship: The influence of social reputation and moral disengagement. Addict. Behav. 37, 577–579. doi: 10.1016/j.addbeh.2012.01.012

PubMed Abstract | Crossref Full Text | Google Scholar

Paulhus, D. L., and Williams, K. M. (2002). The dark triad of personality: narcissism, Machiavellianism, and psychopathy. J. Res. Pers. 36, 556–563. doi: 10.1016/S0092-6566(02)00505-6

Crossref Full Text | Google Scholar

Pendergast, L. L., von der Embse, N., Kilgus, S. P., and Eklund, K. R. (2017). Measurement equivalence: A non-technical primer on categorical multi-group confirmatory factor analysis in school psychology. J. Sch. Psychol. 60, 65–82. doi: 10.1016/j.jsp.2016.11.002

PubMed Abstract | Crossref Full Text | Google Scholar

Ponterotto, J., and Charter, R. (2009). Statistical extensions of Ponterotto and Ruckdeschel’s (2007) reliability matrix for estimating the adequacy of internal consistency coefficients. Percept. Mot. Skills. 108, 878–886. doi: 10.2466/PMS.108.3.878-886

PubMed Abstract | Crossref Full Text | Google Scholar

Pornprasertmanit, S. (2014). A Note on Effect Size for Measurement Invariance. Available online at: http://cran.irsn.fr/web/packages/semTools/vignettes/partialInvariance.pdf (accessed April 15, 2021).

Google Scholar

Qiao, X., Lv, Y., Aldbyani, A., Guo, Q., Zhang, T., and Cai, M. (2021). Chaos may prevail without filial piety: a cross-cultural study on filial piety, the dark triad, and moral disengagement. Front. Psychol. 12:738128. doi: 10.3389/fpsyg.2021.738128

PubMed Abstract | Crossref Full Text | Google Scholar

Risser, S., and Eckert, K. (2016). Investigating the relationships between antisocial behaviors, psychopathic traits, and moral disengagement. Int. J. Law Psychiatry. 45, 70–74. doi: 10.1016/j.ijlp.2016.02.012

PubMed Abstract | Crossref Full Text | Google Scholar

Rubio-Garay, F., Amor, P. J., and Carrasco, M. A. (2017). Dimensionality and psychometric properties of the Spanish version of the Mechanisms of Moral Disengagement Scale (MMDS-S). Rev. de Psicopatol. Psicol. Clin. 22, 43–54. doi: 10.5944/rppc.vol.22.num.1.2017.16014

Crossref Full Text | Google Scholar

Saris, W. E., Satorra, A., and van der Veld, W. M. (2009). Testing structural equation modeling or detection of misspecifications? Struct. Equ. Modeling. 16, 561–582. doi: 10.1080/10705510903203433

Crossref Full Text | Google Scholar

Schminke, M. (1997). Gender differences in ethical frameworks and evaluation of others’ choices in ethical dilemmas. J. Bus. Ethics 16, 55–65. doi: 10.1023/A:1017949912491

Crossref Full Text | Google Scholar

Shulman, E. P., Cauffman, E., Piquero, A. R., and Fagan, J. (2011). Moral disengagement among serious juvenile offenders: A longitudinal study of the relations between morally disengaged attitudes and offending. Dev. Psychol. 47, 1619–1632. doi: 10.1037/a0025404

PubMed Abstract | Crossref Full Text | Google Scholar

Sijtsema, J. J., Garofalo, C., Jansen, K., and Klimstra, T. A. (2019). Disengaging from evil: longitudinal associations between the dark triad, moral disengagement, and antisocial behavior in adolescence. J. Abnorm. Child Psychol. 47, 1351–1365. doi: 10.1007/s10802-019-00519-4

PubMed Abstract | Crossref Full Text | Google Scholar

Soper, D. S. (2023). A-priori Sample Size Calculator for Structural Equation Models [Software]. Available online at: https://www.danielsoper.com/statcalc (accessed April 20, 2023).

Google Scholar

Transparency International (2021). Corruption Perceptions Index. Available online at: https://www.transparency.org/en/cpi/2021 (accessed April 15, 2022).

Google Scholar

United Nations-Women (2023). Peru. Available online at: https://evaw-global-database.unwomen.org/fr/countries/americas/peru (accessed October 13, 2023).

Google Scholar

Wang, C., Ryoo, J. H., Swearer, S. M., Turner, R., and Goldberg, T. S. (2017). Longitudinal relationships between bullying and moral disengagement among adolescents. J. Youth Adolesc. 46, 1304–1317. doi: 10.1007/s10964-016-0577-0

PubMed Abstract | Crossref Full Text | Google Scholar

Yanuari, A. (2022). Peran moral disengagement sebagai mediator dalam hubungan kepribadian dark triad dan perilaku antisosial pada pelaku tindak kriminal. Master’s thesis. Indonesia: Universitas Tarumanagara.

Google Scholar

Zou, G. (2007). Toward using confidence intervals to compare correlations. Psychol. Methods. 12, 399–413. doi: 10.1037/1082-989X.12.4.399

PubMed Abstract | Crossref Full Text | Google Scholar