Abstract
Myths refer to misperceptions, overgeneralizations, or ideas that most people believe in but do not necessarily reflect the truth. To date, research on the myths surrounding dating violence (DV) has not received much attention, most probably due to the lack of a validated measure. Thus, we developed a standardized measure to gauge DV myths and test its psychometrics. The instrument’s design is based on three studies utilizing cross-sectional and longitudinal sets of data. In Study 1, in a sample of 259 emerging adults, predominantly college students, the explanatory factor analysis revealed a solid three-factor structure. In Study 2, in a separate sample of 330 emerging adults, primarily college students, we cross-validated the factor structure via confirmatory factor analysis. We also provided evidence for concurrent validity. In Study 3, we revealed that our newly developed scale had predictive validity among dating and non-dating emerging adults, mostly college students, via longitudinal data. Based on the findings from three studies, we can buoyantly announce that the Dating Violence Myths scale is a promising novel and standardized tool for measuring beliefs about DV. The cross-sectional and longitudinal evidence alludes to a need for DV myths to be debunked to reduce psychological DV attitudes, perceptions, and behaviors among emerging adults.
Keywords
Dating violence (DV) is defined as “the threat or actual use of physical, sexual or psychological abuse perpetrated by a person on his/her partner within the context of a dating relationship” (Anderson & Danis, 2007, p. 88). High rates of DV in young adults across countries and contexts have been documented in systematic review studies (e.g., Krahé et al., 2015; Wincentak et al., 2017), including a few individual studies from Turkey (i.e., Toplu-Demirtaş et al., 2013; Toplu-Demirtaş & Fincham, 2022). College students may occupy a special place in the study of DV because DV has been shown to peak among young adults between the ages of 18 and 25 (Johnson et al., 2014). In an analysis of 35 studies, Taquette and Maia-Monteiro (2019) found the consequences of adolescent DV to be low self-esteem, depressive symptoms, psychiatric disorders, drug abuse, risky sexual behavior, and low academic achievement. Another recent systematic review of 23 articles (Duval et al., 2020) regarding DV among undergraduate students indicated that individual risk factors were studied more often than other factors (e.g., familial, peer, and social) with the use of descriptive cross-sectional approaches being well-ahead, and the authors called for new modifiable risk factors for DV plus the inclusion of multiple methodologies in the future studies.
Although there are several causes and correlates of DV, this study focuses on the ways in which cultures construct beliefs, norms, and attitudes about dating relationships, which in turn shapes the behavior of partners either in a constructive or destructive manner. Notably, negative beliefs entail risk because people in abusive partner relationships justify behaviors to preserve internal consistency and the relationship itself (Arriaga et al., 2016). Also, attitudes toward violence could mediate between hostile feelings and their translation into aggressive behavior (Velicer et al., 1989). Riggs and O’Leary (1989) proposed one of the most comprehensive models of DV, entitled the “background-situational model,” by drawing heavily on social learning theory. It comprised various contextual and situational factors and was the first theory focusing on violence in non-marital relationships. “Acceptance of aggression as an appropriate response to conflict” was a contextual factor that the authors deemed to be a responsible agent operating behind DV. Indeed, among the various risk factors of DV, attitudinal factors were frequently addressed, and the literature is full of consistent findings as to the strong association between positive attitudes toward DV-related variables (e.g., DV itself, intimate partner violence, violence in general, physical violence, interpersonal aggression) and one’s a higher likelihood of DV perpetration and victimization in adolescent and young adult romantic relationships (e.g., Fincham et al., 2008; Kim et al., 2021; Luthra & Gidycz, 2006; Toplu Demirtaş et al., 2017; Wang, 2016). On the other hand, according to Ajzen’s (Ajzen, 1991, 2012, 2020; Bosnjak et al., 2020) theory of planned behavior, actions are followed by intentions and attitudes, respectively, all of which are rooted in beliefs. Upon this framework, the scientific efforts to explain the background factors of DV perpetration and victimization would be inadequate if they bypass the “belief” component and focus solely on “attitude.”
Ajzen (1991, 2012) adds that beliefs can be irrational, inaccurate, biased to conform with preconceptions or motives, and based on fallible inferential processes. As defined by Burt (1980, p. 217), myths are “prejudicial, stereotyped, or false beliefs.” She studied cultural myths about rape, creating a lead article addressing the dynamics of myths in violence literature, and “Burt’s Rape Myth Acceptance Scale” was also the first to utilize rape myth terminology. Lonsway and Fitzgerald (1994, p. 134) proposed a more comprehensive conceptualization of “myths” in the context of rape as “attitudes and beliefs that are generally false but are widely and persistently held, and serve to deny and justify male sexual aggression against women.” As can be seen in both definitions, myths do not represent facts but distorted and false facts at the most. After a detailed examination of the perspectives from different disciplines (i.e., psychology, anthropology, philosophy, and sociology), Lonsway et al. (1994) argued that myths explicate salient cultural phenomena and serve to justify existing cultural agreements and structures.
The Association with Struggle against Sexual Violence (2018), a local NGO in Turkey, published a manual for counselors working with youth as part of the project entitled “Working on Safe Relationships with Youth,” aiming to prevent DV in high schools. The project team reached 5518 high school students and generated several myths on DV in group meetings from the participants. “DV perpetrators are always men,” “Partners spend all their time together in a good relationship,” “Emotional violence is not that much serious,” “A no might mean a yes,” “Men cannot control their sexual impulses due to their hormones,” “Victimized people are weak in character,” “A relationship free of personal boundaries is always more independent,” “What happens in a relationship stays in the relationship,” “Violence perpetrators are mostly un or under-educated people,” “Jealousy is a sign of love” were some of the salient DV myths that participants typically voiced. Furthermore, myths on romantic love (e.g., considering jealousy as a sign of love; perceiving love as suffering) (Cava et al., 2021), domestic violence (e.g., “women who flirt are asking for it,” “many women have an unconscious wish to be dominated by their partners,” “domestic violence does not affect many people,” “whatever happens between married couples is a personal matter and other people should not interfere even if hitting or threatening is involved”) (Peters, 2018), gender stereotypes (e.g., “women are more likely to be sexually abused by a stranger than someone they know,” “when a girl says no to her partner’s sexual advances, this often means yes”) (Sotiriou, 2011), traditional gender myths (e.g., “a husband can love and strike his wife”) (Husnu & Mertan, 2017) have been argued to pave the way for violent acts.
Sosa-Rubi et al. (2017) applied the inventory recommended by Redondo et al. (2011) to assess attitudes on gender stereotypes in relationships among youths. The concepts they measured included accepting sexist beliefs in dating, knowledge on gender-based violence, and myths about gender roles in relationships. However, neither sexist beliefs in dating, knowledge on gender violence, nor accepting myths about gender roles in relationships are tools particularly tailored to measure false beliefs on DV. In brief, while several existing instruments measure attitudes and sometimes beliefs on several DV-related variables, none specifically or exclusively measures the construct of DV myths. Although such tools, to some extent, may assess beliefs on DV, a lack of a sound and standardized tool still remains as an issue in the DV literature. Moreover, the lack of longitudinal studies on the association between false beliefs about and perpetration of DV among undergraduate students is evident. Despite the awareness of the existence of DV myths, no reliable and valid measure currently exist. Based on various DV issues such as consent, psychological and physical violence, personal boundaries, and gender norms, we aimed to develop a new measure—the Dating Violence Myths Scale (DaVi-M)—and present longitudinal and cross-sectional evidence to evaluate its psychometric properties in the current study. Such an instrument could help us know if DV myths are linked or even predict the likelihood of DV perpetration and victimization; and if and under what circumstances they are amenable to change.
To achieve the main aim (to develop a new measure), we created sub-aims for each study. In Study 1, our sub-aim was to provide the initial evidence for the content and construct validity and internal consistency reliability of the DaVi-M.
In Study 2, as the sub-aim, we intended to (1) cross-validate the DaVi-M and (2) present evidence of concurrent validity in the samples of dating and non-dating emerging adults. Regarding the concurrent validity in the dating sample, we expected that DV myths would positively correlate with psychological DV perpetration, irrational romantic relationship myths, and attitudes toward psychological abuse. In the non-dating sample, we anticipated positive associations from DV myths to perceptions of psychological abuse, irrational romantic relationship myths, and attitudes toward psychological abuse.
In Study 3, as the third sub-aim, we sought to illustrate evidence of predictive validity in the longitudinal samples of dating and non-dating emerging adults. In the dating sample, we proposed that
Hypothesis 1 (H1). DV myths at T1 would predict attitudes toward psychological violence at T2,
Hypothesis 2 (H2). DV myths at T1 would predict psychological DV perpetration at T2, and
Hypothesis 3 (H3). Attitudes toward psychological violence at T2 would mediate the association between DV myths at T1 and psychological DV perpetration at T2.
In the non-dating sample, we expected that
Hypothesis 4 (H4). DV myths at T1 would predict attitudes toward psychological violence at T2,
Hypothesis 5 (H5). DV myths at T1 would predict perceptions of psychological DV at T2, and
Hypothesis 6 (H6). Attitudes toward psychological violence at T2 would mediate the association between DV myths at T1 and perceptions of psychological DV at T2.
Study 1
Participants
In Study 1, we collected data in July 2020 from 318 participants who voluntarily attended the survey, in which the only inclusion criterion was being an emerging adult between 18 and 30 years old. We excluded 59 participants as they did not meet the inclusion criteria; 5 were below 18 years old, and 54 were over 30. Thus, the final sample of Study 1 comprised 259 emerging adults, predominantly college students.
Out of 259, 178 (69.0%) of the emerging adults identified as female, 80 (31.0%) male, and 1 nonbinary. The ages ranged between 18 and 30, with a mean of 22.81 (SD = 2.76). Of the sample, 107 (41.5%) participants reported an ongoing relationship, and 113 (43.8%) reported a previous relationship at the time of data collection. The rest (n = 38, 14.07%) had never had a prior relationship.
Procedure
We gathered data through Google Docs during COVID-19, in which people worldwide were either required or highly encouraged to stay at home. As a result, we had no other option than collecting data online due to pandemic circumstances. It took approximately 10 minutes for participants to complete the survey, and we offered no incentives to participate. We gained ethical approval from the MEF University Human Researches Ethics Committee.
Data Collection Instruments
Demographics
We created a form to collect demographics, including age, gender, sexual orientation, previous courses or seminars on DV, and duration of the relationship, if any.
DaVi-M
We developed a new scale to gauge people’s misinformation on DV through DV myths.
Development process of the instrument
The items in the instrument were previously generated by the activists of the Association for Struggle Against Sexual Violence (after the relevant literature on DV was reviewed). A total of 20 items were a selection of myths representing different aspects of DV issues such as consent, psychological and physical violence, personal boundaries, gender norms, and so on. Thus, we expected a scale with more than one-factor structure. For content validity, apart from the Association for Struggle Against Sexual Violence activists, we received expert opinions from two people; one was a researcher/practitioner on DV. The other was a Turkish language teacher.
Data Analysis
We conducted an exploratory factor analysis (EFA) to document the factor structure of the proposed scale to evince its construct validity.
Results
The Results of the EFA
We conducted an EFA to reach a proper factor structure out of 20 items. Heretofore, we checked certain assumptions that needed to be met. The sample size was large enough to conduct an EFA (259 participants; over n = 200 as to the 10:1 criterion). The Kaiser–Mayer–Olkin value (KMO = .75) was above the recommended minimum (.60). The Bartlett’s Test of Sphericity was significant χ2(36) = 365.315, p = .00.
We elected principal axis factoring for factor extraction as advised by Fabrigar et al. (1999) due to its robustness against the violation of the assumption of multivariate normality. We picked oblique rotation (direct oblimin) as we waited for our factors to be correlated (Preacher & MacCallum, 2003). In deciding on the number of factors to retain, we regarded various criteria such as Kaiser’s criterion (eigenvalues greater than 1) and Catell’s scree test.
The scree plot implied a three-factor solution with a clear break after the third factor. As illustrated in Table 1, the EFA also yielded three factors with eigenvalues greater than 1, which explained a total of 57.53% of all variance (for Factor 1, eigenvalue = 2.68 and variance = 30.754%; for Factor 2, eigenvalue = 1.307 and variance = 14,527%; for Factor 3, eigenvalue = 1.103 and variance = 12.255%). All items loaded on their relevant factors with factor loadings over .30.
Factor Loadings of the Scale Items, Percentages of the Variances, Eigenvalues, and Alphas in Study 1.
We titled the 9-item scale out of 20 items as the DaVi-M. Each factor reflected itself with 3 items. We labeled the first, second, and third factors as myths on victims/survivors (a sample item; the person subjected to violence must have acted in a way that caused it), dating relationships (a sample item; jealousy and possessiveness in a dating relationship are a sign of love), and sexual violence (a sample item: if the person says yes to sexual behavior, it is unacceptable to change their minds later), respectively.
The Results of the Reliability Analysis
We computed Cronbach’s alphas to test the internal consistency of the factors and whole scale. The coefficients (.647 for Factor 1, .610 for Factor 2, and .604 for Factor 3) were lower than the recommended minimum (.70; Nunnally, 1978). The reason behind the low-reliability scores might be the number of items for each factor, as further reliability analyses did not display a positive change when any item was deleted. The alpha for the full 9-item scale was calculated as .680. In sum, we inferred that the DaVi-M could be used either as the full scale to gauge the myths toward DV or separately as each factor to measure the relevant construct.
Study 2
Studies 2 and 3: Data Collection Procedure
For Studies 2 and 3, we collected data over 2 months, from February 2021 to April 2021. We launched the initial link via Google Survey, detailing the research and requesting participation in the study. On the first page of the online survey, we thoroughly explained the purposes of the research. We stated that participation was voluntary, and one might prefer not to participate or to discontinue participation at any time. We told the possible participants that the purpose of the study was to better understand if some dating beliefs are related to healthy and unhealthy relationship behaviors. The inclusion criteria for Studies 2 and 3 were that participants should be between 18 and 30. The survey took, on average, 15 to 20 minutes to complete. We asked the participants if they would like to take place in the second phase of Study 2 and requested their emails to call them to the second phase of longitudinal data. To increase participation rates for the longitudinal data, we offered an incentive. Those who met the inclusion criteria (aged between 18 and 30 and passed the check items in the survey) and whose data matched (Time 1 and Time 2 data) had the chance for a draw: A gift card worth 50 Turkish Liras from D&R (an online bookstore in Turkey). The winners (10 participants) were randomly selected via an online platform. The participants did not receive any incentive just for their participation in Study 2. We gained ethical approval from MEF University Human Researches Ethics Committee.
Participants
For Study 2, a total of 403 participants volunteered. Seventy-three participants were excluded from the sample due to (1) incorrect response to the check item (n = 30), (2) age requirement (n = 10), and (3) submission of the form more than once (n = 33). After the exclusion of the participants, 330 eligible participants, predominantly college students, constituted the sample for Study 2, Time 1 of the longitudinal data.
In the dating sample, the total number of participants was 162; 141 were female, 20 were male, and 1 identified as queer. The mean age of participants was 22.44 (SD = 2.17). In the non-dating sample, the total number of participants was 168, 121 were female, 46 were male, and 1 was queer. The mean age of participants was 21.77 (SD = 2.00).
Data Collection Instruments
Multidimensional Measure of Emotional Abuse
We assessed psychological DV perpetration via the shorter form (16 items; Maldonado et al., 2020) of the Multidimensional Measure of Emotional Abuse (MMEA) (28 items; Murphy & Hoover, 1999). The longer version of the MMEA previously appeared to be a psychometrically sound measure (Toplu-Demirtaş et al., 2018). The items in the shorter version were derived from the longer version.
The measure has four subscales: The Restrictive Engulfment subscale (4 items; e.g., I secretly searched my partner’s belongings), Hostile Withdrawal subscale (4 items; e.g., I acted cold or distant when angry), Denigration subscale (4 items; e.g., I called my partner person ugly), and the Dominance/Intimidation subscale (4-item; e.g., I threatened to throw something at my partner). This scale measured psychological violence on a 7-point Likert-type scale (0 = never, 6 = more than 20 times, and 7 = has not occurred recently within 6 months but did before). Higher scores reflect more use of psychological violence toward partners (min = 0, max = 96). In the current study, the alpha for the MMEA scale was .808. We computed alphas for each subscale as follows: .726, .812, .614, and .674 for the Restrictive Engulfment, Denigration, Hostile Withdrawal, and Dominance/Intimidation, respectively.
Intimate Partner Violence Attitude Scale–Revised
We measured attitudes toward psychological violence via the Turkish version (Toplu Demirtaş et al., 2017) of the Intimate Partner Violence Attitude Scale–Revised (IPVAS-R) (Fincham et al., 2008). The measure has three subscales: The Violence subscale (4 items; e.g., It would not be appropriate to ever kick, bite, or hit a partner with one’s fist), Control subscale (6 items; e.g., It is okay for me to tell my partner not to talk to someone of the opposite sex), and Abuse subscale (7 items; e.g., As long as my partner does not hurt me, “threats” are excused). The Violence items assess the attitudes toward physical violence, and the Control and Abuse items gauge the attitudes toward psychological violence. Participants indicate their responses on a 5-point Likert-type scale (1 = disagree strongly to 5 = agree strongly, with Items 2, 4, 5, 8, 12, 13, 14, 17 reverse coded). Higher scores reflect more accepting attitudes of physical and psychological violence (min = 17; max = 85). We used only the Abuse subscale in the current study, and the alpha was reported as .600.
Romantic Beliefs Scale
We assessed irrational romantic beliefs via the Turkish version (Küçükarslan et al., 2013) of the Romantic Beliefs Scale (Sprecher & Metts, 1989). The scale consists of four factors: Love Finds A Way (5 items; e.g., If I love someone, I know I can make the relationship work, despite any obstacles.), One and Only subscale (3 items; e.g., I believe that to be truly in love is to be in love forever), Idealization subscale (3 items; e.g., The relationship I will have with my “true love” will be nearly perfect), and Love at First Sight subscale (2 items; e.g., When I find my “true love,” I will probably know it soon after we meet). Participants responded to items on a 5-point Likert-type scale (1 = strongly disagree to 5 = strongly agree). Higher scores signify more irrational romantic beliefs (min = 13; max = 65). In the current study, we used the whole scale and computed alpha for the whole scale, which was .884.
Perceptions of Dating Violence Scale
We gauged perceptions of psychological DV via the 15-items and single-factor Perceptions of Dating Violence (Toplu-Demirtaş et al., 2022). Respondents first read a vignette and then rate their agreement on a 6-point Likert-type scale (1 = strongly disagree to 6 = strongly agree). A sample from the scale is “Hakan should blame himself for what happened.” There are 3 reverse-coded items (Items 7, 8, and 11). Higher scores reflect that one perceives violence as more abusive (min = 15; max = 90). In the present study, Cronbach’s alpha for the perceptions of psychological violence sample was found as .731.
Data Analysis
We first carried out a confirmatory factor analysis (CFA) in the first set of longitudinal data to provide evidence for construct validity (cross-validation). Following this step, we generated two groups in the first set of longitudinal data (those in current dating relationships and those in noncurrent dating relationships). The participants in current dating relationships completed the DaVi-M, MMEA, Relationship Beliefs Scale (RBS), and Abuse subscale of the IPVAS. In contrast, participants in the non-dating sample responded to the DaVi-M, PDVS, RBS, and Abuse subscale of the IPVAS. The rationale was that the non-dating emerging adults were not eligible to complete the MMEA, which gauges psychological DV perpetration. Instead, they replied to the PDVS, which measures perceptions of psychological DV. Upon creating two separate samples, we conducted separate correlation analyses in both samples to provide evidence for concurrent validity. In the dating sample, we analyzed the correlations of the DaVi-M with four subscales and the total score of the MMEA, the RBS, and the Abuse subscale of the IPVAS scale. We did the same analyses in the non-dating sample, albeit with a change of inspecting correlations of the DaVi-M with the PDVS. We utilized AMOS for the CFA and SPSS for the rest of the analyses.
Results
CFA of the DaVi-M
We conducted a CFA to confirm the factor structure of the DaVi-M in the first dataset from the longitudinal data. The χ2 test of the model was not statistically significant, χ2 (24, N = 330) = 30.476, (p = .169), and the obtained χ2/d ratio was 1.270, less than the recommended value of 3 (Kline, 2005). The RMSEA value was .029 (90% confidence interval [CI] [.000, .056]), lower than the .05 for perfect fit (Browne & Cudeck, 1993). The standardized RMR was .037, lower than the proposed cutoff value (Hu & Bentler, 1999). The other fit index CFI had a value of .989, higher than the suggestion (Hu & Bentler, 1999). The overall fit indices for the DaVi-M implied a perfect model fit.
In addition to model fit, we checked the results of parameter estimates and significance tests and observed that all items were appropriately loaded on the relevant constructs (p < .001). No modification indices emerged. As depicted in Table 2, the standardized regression weights varied between .340 and .650 for the myths on victims/survivors, .564 and .893 for the myths on dating relationships, and .358 and .636 for the myths on sexual violence. As also presented in Table 2, the item-total statistics for relevant factors and total DV myths were higher than .30 (the rule of thumb). For example, the item-total statistics ranged between .597 and .792 for the myths on sexual violence.
Factor Loadings of the Scale Items, Item-Total Correlations, and Alphas in Study 2.
Note. N = 330.
p < .001.
All in all, the findings of the CFA revealed acceptable evidence for the construct validity of the DaVi-M and confirmed the proposed three-factor structure. The positive and significant correlations between the sub-factors of the DaVi-M also depicted that they were related but distinct concepts—the correlation between myths on survivors and myths on relationships is r = .484, p < .001; the correlation between myths on survivors and myths on sexual violence is r = .288, p < .001; and correlation between myths on relationships and myths on sexual violence is r = .271, p < .001.
Correlation Analyses
We did the correlation analyses separately in both groups (dating and non-dating samples) to present concurrent validity evidence. Of 330 participants, 168 were in the non-dating sample, and 162 were in the dating sample.
We first inspected correlations (Table 3) in the dating group (n = 162). DV myths correlated significantly with psychological DV perpetration, r(160) = .301, p < .05. Dating emerging adults accepting more myths tended to commit more psychological DV toward their partners. The associations were also evident with the subscales of the MMEA, except for the Hostile Withdrawal, r(160) = .127, p > .05. Irrational romantic beliefs and DV myths were also related to each other, r(160) = .250, p < .05. Dating emerging adults who believed more in irrational romantic relationship myths were more inclined to favor DV myths. Furthermore, the results revealed that dating emerging adults with more myths on DV tended to accept psychological aggression in their relationships, r(160) = .399, p < .05. Overall, the significant associations from DV myths to psychological DV perpetration, attitudes toward psychological abuse, and romantic relationship beliefs unveiled that the DaVi-M has satisfactory concurrent validity evidence among a sample of dating college students.
Correlations Between the Study Variables Among Dating Sample in Study 2.
Note. MMEA = multidimensional measure of emotional abuse; DaVi-M = Dating Violence Myths Scale; RBS = Relationship Beliefs Scale.
Correlation is significant at the .01 level (two-tailed).
Correlation is significant at the .05 level (two-tailed).
Next, we explored the relationships among the study variables in the non-dating sample (n = 162) to present concurrent validity evidence. The DaVi-M was significantly associated with perceptions of psychological abuse, r(166) = .205, p < .01. Those who favored DV myths perceived psychological aggression as less abusive. Similarly, those who believed in DV myths held more accepting attitudes toward psychological abuse, r(166) = .357, p < .01. DV myths and romantic relationship myths were correlated with each other, as well, r(166) = .499, p < .01. In sum, as in the dating sample, the results verified that the DaVi-M has satisfactory concurrent validity evidence among a sample of non-dating emerging adults (Table 4).
Correlations Between the Study Variables Among Non-Dating Sample in Study 2.
Note. Abuse = attitudes toward psychological violence; Perceptions = perceptions of psychological violence.
Correlation is significant at the .01 level (two-tailed).
Correlation is significant at the .05 level (two-tailed).
Study 3
Participants
In the second phase of the longitudinal data for Study 3, we reached the participants through the emails they provided to us. Overall, the data of 166 participants matched. Twenty-three participants were omitted from the data due to incorrect answers to the check item (n = 2) and submission of the survey more than once (n = 21). The participants who changed their relationship status in the 8-week interval were also dropped from the sample (n = 8).
Therefore, the sample was composed of young adults, predominantly college students (N = 135) between 18 and 30 years (M = 21.94, SD = 1.87) from Turkey. Of the sample, 114 were women (84.4%), and 21 were men (15.6%). A majority (86.7%) identified as heterosexual, with eight people as often heterosexual/sometimes gay, one as gay, and seven as bisexual. Sixty-nine (51%) participants reported that they were currently in a dating relationship. The rest defined their relationship status as currently single, but they previously had a relationship (37.8%) or never had a relationship (11.1%). Of the dating sample, 45 (33.3%) lived in the same city with their partners, and 9 people (6.7%) lived with their partners. Twenty-one participants were in a long-distance relationship. The relationship duration differed between 2 to 168 months (M = 16.47 months, SD = 25.16 months).
Additionally, as in Study 2, we formed two samples: dating and non-dating. The dating (n = 69) and non-dating samples (n = 66) completed the MMEA and PDVS, respectively.
Data Collection Tools
Except for the RBS, we applied the same instruments as Study 2: the DaVi-M, MMEA, Abuse of the IPVAS-R, and PDVS. In the non-dating sample, we reported αs as .690 for the DaVi-M, .647 for the Abuse of the IPVAS-R, and .702 for the PDVS. For the dating sample, we computed αs as .670 for the DaVi-M, .780 for the MMEA, and .665 for the Abuse of the IPVAS-R.
Data Analysis
For dating and non-dating samples, we employed a simple mediation analysis via PROCESS to test our hypotheses below to present predictive validity evidence (Model 4, Hayes, 2018, v3.5). For each mediation analysis, we used bootstrapping with 10,000 resamples.
In the dating sample, we proposed that
Hypothesis 1 (H1). DV myths at T1 would predict attitudes toward psychological violence at T2,
Hypothesis 2 (H2). DV myths at T1 would predict psychological DV perpetration at T2, and
Hypothesis 3 (H3). Attitudes toward psychological violence at T2 would mediate the association between DV myths at T1 and psychological DV perpetration at T2.
In the non-dating sample, we expected that
Hypothesis 4 (H4). DV myths at T1 would predict attitudes toward psychological violence at T2,
Hypothesis 5 (H5). DV myths at T1 would predict perceptions of psychological DV at T2, and
Hypothesis 6 (H6). Attitudes toward psychological violence at T2 would mediate the association between DV myths at T1 and perceptions of psychological DV at T2.
In the dating sample, the independent variable was DV myths at Time 1 (T1), the dependent variable (output) was psychological DV perpetration at Time 2 (T2), and the mediator variable was attitudes toward psychological violence at T2. In the non-dating sample, the independent variable was DV myths at T1, the dependent variable was perceptions of psychological DV at T2, and the mediator variable was attitudes toward psychological violence at T2.
Results
The Results of Mediation Analysis for Dating Sample
As illustrated in Table 5, for the dating sample, the model in which attitudes toward psychological violence at T2 was the outcome, was not significant, R2 = .004, F(1, 67) = .270, p > .05. DV myths at T1 did not predict attitudes toward psychological violence at T2, β = .063, t(67) = .519, 95% CI [−.126, .215]. Our first hypothesis was not supported. The second model, in which psychological DV perpetration at T2 was the outcome, was significant, R2 = .208, F(2, 66) = 8.687, p < .001. DV myths at T1, β = .298, t(66) = 2.718, 95% CI [.222, 1.452], and attitudes toward psychological violence at T2, β = .327, t(66) = 2.982, 95% CI [−1.796, −0.461], significantly predicted psychological DV perpetration at T2. Our second hypothesis was supported. Regarding indirect effects, we found no evidence of mediation, β = .058, 95% CI [−.165, .370]. Our third hypothesis was not supported.
Model Summary for Mediation Analyses Both for Dating and Non-Dating Samples in Study 3.
Note. N = 69 for dating sample; N = 66 for non-dating sample. 10000 bootstrap samples. MMEA= multidimensional measure of emotional abuse; Abuse = attitudes toward psychological violence; DV = dating violence; Perceptions = perceptions of psychological dating violence; LLCI = lower level of confidence interval; ULCI = upper level of confidence interval.
The Results of Mediation Analysis for Non-Dating Sample
For the non-dating sample, the model in which attitudes toward psychological violence at T2 was the outcome was significant, R2 = .204, F(1, 64) = 16.382, p < .001. DV myths at T1 predicted attitudes toward psychological violence at T2, β = .451, t(64) = 4.047, 95% CI [.217, .640]. The second model, in which perceptions of psychological DV at T2 was the outcome, was also significant, R2 = .227, F(2, 63) = 9.229, p < .001. DV myths at T1, β = .286, t(63) = 2.305, 95% CI [.031, .436], and attitudes toward psychological violence at T2, β = 273, t(63) = 2.195, 95% CI [.021, .448] significantly predicted perceptions of psychological DV at T2. In addition to the direct effects, we gathered evidence of mediation, β = .100, 95% CI [.021, .228]. Non-dating college students who believed in more DV myths favored attitudes toward psychological violence more and thus perceived psychological DV as less abusive. Regarding the results, our fourth, fifth, and sixth hypotheses were supported.
Discussion
We primarily aimed in this study to develop a novel and standardized tool to measure DV myths and test its psychometrics. For this purpose, we collected one cross-sectional and one longitudinal set of data and designed three studies using these datasets. In Study 1, we conducted a series of exploratory factor analyses to reach a sound factor structure for the scale. In Study 2, we first confirmed the factor structure and tested the concurrent validity via the first set of longitudinal data. Then, Study 3 showed that our newly developed scale had significant predictive validity via the longitudinal data, encompassing the sample of dating and non-dating emerging adults. Overall, we can buoyantly announce that the DaVi-M has the potential to fill a gap in the national and international literature by providing a promising tool for measuring myths about DV.
In Study 1, the explanatory factor analysis revealed a solid three-factor structure. Each factor had 3 items and accounted for 57.53% of the total variance. We named the first, second, and third factors as myths on (1) victims/survivors, (2) dating relationships, and (3) sexual DV, respectively. All the items loaded quite well onto the related factors with factor loadings greater than .30. We estimated Cronbach’s alphas to test the internal consistency of the factors and the whole scale. The coefficients (.647 for Factor 1, .610 for Factor 2, and .604 for Factor 3) were lower than the suggested minimum (.70; Nunnally, 1978), most probably influenced by the number of items for each factor. Cronbach’s alpha for the full 9-item scale was calculated as .680. We inspected the results of the further reliability analyses, and they did not offer any deletion. Some authors, such as Aiken (2000), suggest that a Cronbach’s alpha between .60 and .70 is acceptable.
In Study 2, we cross-validated the factor structure in a separate sample via CFA, in which the proposed three-factors solution perfectly fit with the actual data sample. All items were appropriately loaded on the relevant constructs with factor loadings over .30, and no modification indices were suggested. The findings of the CFA revealed once more satisfactory evidence for the construct validity of the DaVi-M. The positive and significant associations between the subscales of the DaVi-M further delineated that they were associated but discrete concepts.
In Study 2, we also calculated associations from DV myths to psychological DV perpetration, irrational romantic beliefs, and attitudes toward psychological violence in the dating sample and found the correlations as significant and positive, which aligned with the previous literature. Dating emerging adults with higher DV myths tended to use more psychological DV toward their partners. For example, Hou et al. (2020) uncovered that one of the predictors for perpetrating DV among young women and men was misconceptions about DV. Besides, those who believed in DV myths were more inclined to favor irrational romantic relationship beliefs. We also discovered that dating college students who held more myths on DV favored more acceptable attitudes toward psychological violence in dating relationships.
In Study 3, we set each three hypotheses in the dating and non-dating sample using the longitudinal data. We first hypothesized that DV myths at T1 would predict attitudes toward psychological violence at T2 in the dating sample, which we could not support. This may result from the dating sample’s potential tendency to interpret the partner’s behaviors in terms of personality rather than the degree to which the partner accepts the myths about DV. Fundamental attribution error is deemed as the tendency for an individual to explain behaviors by overestimating dispositional factors and underestimating situational factors’ influence on another individual’s behavior (Ross & Nisbett, 2011). For example, Harvey et al.’s (2014) study claimed that people tend to make dispositional rather than situational attributions for an individual’s unfavorable behavior in a workplace context. Besides, Gable et al. (2003) found that intimate partners’ beliefs and interpretations about their partner’s behavior can influence their daily mood and relationship satisfaction. The evidence suggests that partners’ interpretation and perception of the partner’s behavior can potentially affect relationship satisfaction levels. In line with this information, we concluded that fundamental attribution error could justify the results in the dating sample by interpreting the partner’s behaviors based on personality rather than the degree to which the partner believes in DV myths.
Our second hypothesis was that DV myths would predict psychological DV perpetration at T2 in the dating sample. We found indirect evidence supporting the second hypothesis, as reflected in the literature. Several studies revealed a positive correlation between attitudes toward DV and DV perpetration and/or victimization in young romantic relationships. (e.g., Fincham et al., 2008; Kim et al., 2021; Luthra & Gidycz, 2006; Toplu Demirtaş et al., 2017; Wang, 2016). Following, in our third hypothesis, we expected that attitudes toward psychological violence at T2 would mediate associations between DV myths at T1 and psychological DV perpetration at T2. Unfortunately, we could not support the third hypothesis. When we looked at the previous research, there were studies on how cognitive schemas could become a predictor of psychological DV perpetration (e.g., Gay et al., 2013). Additionally, Hamby and Grych (2016) clearly stated that growing up in a society or family that boosts rigid ideas about honor and identity can create cognitive schemas about self-worth or social status, leading to violence. For example, cognitive schemas and rigid beliefs could generate hostile and denigrating attitudes toward women, increasing the risk of physical intimate partner violence and sexual violence. Thus, the sort of attitudes toward partners might play a predictor role in perpetrating DV itself rather than false beliefs about DV, and it may offer an explanation for the understanding of the unsupported results (H1 and H3) associated with DV myths as a predictor of psychological DV in the dating sample.
In Study 3, we hypothesized that DV myths at T1 would predict attitudes toward psychological violence at T2 and supported the fourth hypothesis. As the fifth hypothesis, we expected that DV myths at T1 would predict perceptions of psychological DV at T2, and indeed it did. Finally, we assumed that attitudes toward psychological violence at T2 would mediate associations between DV myths at T1 and perceptions of psychological DV at T2. Lastly, supporting the last and sixth hypothesis, we obtained that non-dating emerging adults endorsing more DV myths tended to favor more positive attitudes toward DV and thus perceived DV as less abusive.
Our findings paralleled the findings in the literature, which documented that stereotypical and pseudo beliefs might lead to DV (e.g., Reyes et al., 2016). Similarly, Ohnishi et al. (2011) concluded that adolescents with less information about DV did not recognize psychological and sexual violence acts such as controlling and unprotected sexual intercourse as abusive. Additionally, our findings unraveled that emerging adults in the non-dating sample with more DV myths also held more irrational romantic beliefs and showed more positive attitudes toward psychological violence in relationships.
Limitations and Implications for Further Research
The present study is not free from its limitations. First, our sample in all studies was conveniently selected, which is a threat to the generalization of the findings. In Studies 2 and 3, we divided the sample into dating and non-dating, which dramatically shrunk our sample size. Additionally, there was an imbalance among genders. In each sample size, women outnumbered men. The small and imbalanced samples prevented us from testing measurement invariance across gender. Therefore, we suggest keeping the sample larger, more representative, balanced, and diverse in future studies to promote diversity, equity, and inclusion (Tajima, 2021). In addition, some of the reliabilities of the scales were lower than the commonly accepted rule of thumb (.70), most probably due to the low number of items and small samples. Keeping the sample larger will likely improve the alpha scores.
In Studies 1 and 2, we strongly suggest the readers not draw causal inferences from cross-sectional data findings. Although longitudinal studies are more potent than cross-sectional ones and influential in determining patterns over time, the results must be interpreted with caution in Study 3. We designed two-wave longitudinal research with 8 weeks intervals. Further studies can extend the present research by collecting more waves and longer time intervals to provide more accurate evidence of the findings. The initial attempts indicate that the DaVi-M is a promising instrument in a unique—more collectivistic and predominantly Muslim—culture to fulfill a much-required need in the literature. Nevertheless, we need more evidence for further claims. We recommend validating the factor structure by testing its measurement invariance across socioeconomic statuses, races, ethnicities, languages, nationalities, genders, gender identities, sexual orientations, religions, geographies, abilities, and ages (Tajima, 2021). Additionally, we urge gathering evidence for the cross-cultural fit of the instrument, particularly with Western and non-Western samples, to strengthen the validity of the findings (Tajima, 2021). Furthermore, this study suffers from the limitations of any research using self-reported tools. To alleviate this limitation, dyadic research would be fruitful in uncovering crossover effects among partners.
Implications for Practice
Regardless of the limitations, we introduced a new measure—(DaVi-M)—to gauge beliefs about DV for further research. As the results showed, more myths about DV predicted more use of psychological DV. One implication for mental health professionals working with young adults would be to create inclusive, protective, and empowering preventive programs. It is critical to debunk the myths and illusions surrounding the issue of DV and go over false beliefs to avert victim-blaming. Having sufficient knowledge on this subject will play an extensive role in raising awareness when working with perpetrators or survivors of DV. Additionally, going over the myths will be beneficial to understanding the common patterns and creating social support within the group counseling settings with the survivors of DV. In the long term, this type of work could be applicable in developing culturally relevant programs to reduce DV among young adults.
Concluding Comments
Notwithstanding its limitations, the study has a lot to contribute to the blossoming literature on DV myths. First, we developed a new, up-to-date, and solid measure, which filled a huge gap regarding the lack of a standardized measure. The DaVi-M could be used either as the full scale to gauge DV myths or separately as each factor to measure the relevant construct. Using two-wave longitudinal data, we tested a mediation model in which we unraveled that DV myths at T1 significantly predicted psychological DV perpetration at T2 among dating participants. We also obtained a similar finding in the non-dating sample. DV myths at T1 predicted both attitudes toward psychological violence and perceptions of psychological DV at T2. The sum of these findings shows that DV myths function as a barrier that needs to be breached to challenge attitudes, perceptions, and behaviors of psychological DV. Thus, DV myths should be involved in prevention and intervention efforts.
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) received no financial support for the research, authorship, and/or publication of this article.
