Attitude to Non-Violence Scale: Validity and Practical Use.

590785 research-article2015

JIVXXX10.1177/0886260515590785Journal of Interpersonal ViolenceCraven et al.

Article

Attitude to Non-Violence Scale: Validity and Practical Use

Journal of Interpersonal Violence 1–28 © The Author(s) 2015 Reprints and permissions: sagepub.com/journalsPermissions.nav DOI: 10.1177/0886260515590785 jiv.sagepub.com

Rhonda G. Craven,1 Marjorie Seaton,1 and Alexander S. Yeung1

Abstract This study used recent advances in attitude and self-perception research to develop an Attitude to Non-Violence Scale (ANVS). Participants were students from six high schools in Australia (N = 727). Confirmatory factor analysis using within-construct and between-construct validation approaches found two positive attitude sub-scales: Cognitive (proactive understanding) and Affective (do not endorse violence), both showing convergent and discriminant validity. Scale equivalence tests found that the sub-scales were applicable to boys and girls and to junior and senior grades. Structural equation modeling found that boys had less supportive attitudes to nonviolence cognitively, whereas female students in senior secondary classes had less positive attitudes to non-violence affectively. The ANVS can be easily administered to assess youth’s non-violence attitudes, which may direct interventions focusing on boys’ cognitive aspects while maintaining girls’ positive affective attitudes toward non-violence as they mature. The positively framed instrument is suitable for education settings especially in high-risk locations where violence is prevalent. Keywords bullying, youth violence, mental health and violence 1Australian

Catholic University, Strathfield, New South Wales, Australia

Corresponding Author: Marjorie Seaton, Institute for Positive Psychology and Education (IPPE), Australian Catholic University, Strathfield Campus, Sydney, Locked Bag 2002, Strathfield, New South Wales 2135, Australia. Email: [email protected]

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Journal of Interpersonal Violence

School violence has immediate and long-lasting effects on adolescents’ physical and mental health (Copeland, Wolke, Agnold, & Costello, 2013; KaltialaHeino, Fröjd, & Marttunen, 2010; Ttofi, Farrington, & Lösel, 2012). It is a significant problem for schools and society worldwide (Marsh et al., 2011; Ryan & Smith, 2009; Sullivan, 2000), including Australia where the present study was conducted. As attitudes toward violence have the capability to predict violent behavior (e.g., Foshee, Linder, MacDougall, & Bangdiwala, 2001; Lanier, 2001; Pardini, Loeber, Farrington, & Stouthamer-Loeber, 2012), it is important for educators, researchers, and for those conducting interventions that instruments that assess attitudes to violence are psychometrically sound. However, current attitudes to violence measures have limitations. Hence, the purpose of the present study was to develop and validate a psychometrically sound measure of violence-related attitudes, which is brief, easy to administer, and suitable for adolescents. We begin by examining the link between behavior and attitudes to demonstrate the importance of holding attitudes that condemn violence. We continue by discussing the limitations of current attitudes to violence scales and outlining research pertinent to the different groups that we tested in our study (sex and year in school). We conclude by describing constructs used in the present investigation for validation purposes.

Attitudes and Behavior Attitudes have been defined as dispositions “to respond favorably or unfavorably to an object, person, institution or event” (Ajzen, 2005, p. 3). Attitudes are evaluative and, as with self-perceptions, can have both affective and cognitive components (Arens, Yeung, Craven, & Hasselhorn, 2011; Conner, Godin, Sheeran, & Germain, 2013). These two components are important for attitude formation. The affective component is composed of “positive and negative emotions associated with the attitude’s object” (Taut & Baban, 2012, p. 405), whereas the cognitive component taps into beliefs and judgment about the attitude’s object. Theoretical and empirical work on the nature of attitudes and their relation to behavior suggest that attitudes supportive of violence are associated with violent behavior. For example, Polaschek, Collie, and Walkey (2004) found that offenders currently jailed for violent crimes had attitudes that were more supportive of violence than offenders without a conviction for violence. Regarding adolescents in particular, Mueller, Jouriles, McDonald, and Rosenfield (2013) found that perpetration of dating violence at Time 1 was a significant predictor at Time 2 of holding beliefs about the acceptability of such violence, although previous beliefs were not associated with subsequent


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violent behavior. In contrast, Pardini et al. (2012) found that 12-year-old boys who had more negative attitudes to violence were less at risk of perpetrating violence at ages 13 to 14 (see also Foshee et al., 2001; Lanier, 2001).

Limitations of Existing Measurements Many previous scales devised to measure attitudes to violence have a variety of theoretical and methodological weaknesses. These include failure to (a) use the most appropriate statistical methodology, (b) control for measurement error, (c) demonstrate both convergent and discriminant validity, (d) demonstrate that the scale is appropriate for different groups (e.g., sex,), (e) include both affective and cognitive components, and (f) take a positive perspective. In particular, few scales have been devised specifically for use with adolescents and most contain many items, resulting in an unduly long administration time. For example, the Attitudes to Violence Scale, first proposed by Bardis (1973), was examined by Velicer, Huckle, and Hansen (1989). Exploratory factor analysis (EFA) was used to test the psychometric properties of Bardis’s original scale, which found the 25 items loading onto four factors. Velicer et al. then added a new factor and used confirmatory factor analysis (CFA) to demonstrate a 48-item instrument comprising 5 first-order and 2 secondorder factors. The application of CFA is of particular importance as it is hypothesis- and theory-driven (Brown, 2006), and has advantages over EFA because CFA can also evaluate method effects and invariance across time and groups (Brown, 2006), and control for measurement errors, making the estimates more accurate. However, Velicer et al. (1989) did not examine the invariance of their measure across relevant groups. This was subsequently tested by Anderson, Benjamin, Wood, and Bonacci (2006). The revised model was largely invariant across sex and was predictive of self-reported aggression. However, some of the items assessing attitudes to war violence loaded more highly for men than women. Whereas the instrument seems to be appropriate for adults (university students), the large number of items for each scale, which required item parcels to be formed for the modeling, does not suit our purpose of an easy-to-administer instrument. Also, it does not address the affective and cognitive components of attitudes from a positive perspective. Refining Velicer et al.’s (1989) 48-item scale, Lonsway and Fitzgerald (1995) used 20 items, but no psychometric tests were performed on this revised scale. Subsequently, Davidson and Canivez (2012) used EFA to test its psychometric properties. A strength of the Davidson and Canivez (2012)


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study was the use of a one-way MANOVA to examine differences across sex. However, this procedure used manifest variables without accounting for measurement errors. Hence, a stronger approach would be the validation of the instrument by applying a CFA approach so that the researchers have “knowledge of the underlying latent variable structure” (Byrne, 2012, p. 6), based on which, accurate estimates of sex differences would be possible. For group differences, a multiple-indicator-multiple-cause (MIMIC) approach to structural equation modeling (SEM) would control for measurement error (Yeung, Taylor, Hui, Lam-Chiang, & Low, 2012). Indeed, Davidson and Canivez noted that not using CFA was a limitation of their study. As such, in the current study, we adopted a CFA approach to testing convergent and discriminant validity, and consistent with their emphasis on the importance of studying secondary student samples, we focused on this age group and used the MIMIC approach to more accurately test group differences. Focusing on secondary students, an Attitudes to Violence Scale was developed by Funk, Elliott, Urman, Flores, and Mock (1999). Using EFA, the 15 items they tested revealed two factors (Culture of Violence and Reactive Violence). As EFA was used, it is unclear whether the factors had the same meaning for different groups. In addition, differences in attitudes to violence between sex, year in school, and ethnicity were tested using correlations. Hence, again, measurement error was not controlled for. The child version of the Attitudes to Violence Scale, adapted from the adolescent version (Funk, Elliott, Bechtoldt, Pasold, & Tsavoussis, 2003) also has similar limitations. However, a strength of the study was that convergent validity was tested, as attitudes to violence were found to be negatively correlated with empathy, although discriminant validity was not investigated. Most other instruments measuring attitudes to violence for adolescents suffer from similar limitations (Kingery, 1998; Walker, 2005), with some not reporting the factor structure of their instrument at all (Merwin & Ellis, 2004). Alternatively, scales have been devised to test a specific aspect of violence such as war, killing, and punishment of children (McAlister et al., 2001), guns and violence (Shapiro, Dorman, Burkey, Welker, & Clough, 1997), aggression (Buss & Perry, 1992), violence in dating relationships (Wolfe et al., 2001), and street violence (Taylor, Esbensen, Brick, & Freng, 2010), rather than a general attitude toward violence. These scales could also cause concerns from the stakeholders’ perspective, as teachers and parents may fear that the psychological instruments presented in a negative sense could cause discomfort and distress to at least some of the students surveyed. Hence, our purpose was to develop an instrument from a positive perspective, shifting from attitudes to violence to attitudes to non-violence.


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Group Differences: Sex and Year in School Studies examining differences across sex have generally shown that males endorse violence more than women do (e.g., Anderson et al., 2006; Davidson & Canivez, 2012; Funk et al., 1999, 2003; Kingery, 1998; Thornton, Graham-Kevin, & Archer, 2013; Vernberg, Jacobs, & Hershberger, 1999, Walker, 2005). For example, a study of attitudes toward street violence demonstrated that acceptance of street-related violence was higher for males than for females (Taylor et al., 2010), and Buss and Perry (1992) found that men scored more highly on their physical aggression, verbal aggression, and hostility scales. However, Fives, Kong, Fuller, and DiGiuseppe (2011), using the Buss and Perry Aggression Questionnaire, found sex differences only for physical aggression, with males scoring more highly. With regard to year in school, no difference in attitudes toward violence has been found across Years 8 to 12 and Years 4 to 6 (Funk et al., 1999, 2003, respectively).

Between-Construct Validation Constructs Bullying Bullying behaviors have been associated in the literature with perpetrating violence and having more positive attitudes toward violence. Kim, Catalano, Haggerty, and Abbott (2011) showed that, after accounting for demographics and impulsivity, being a bully in Year 5 was significantly predictive of committing violent acts at age 21. Moreover, compared with students in general, bullies tend to have more positive attitudes toward violence (Olweus, 1994; Rigby & Slee, 1993). For example, Poteat, Kimmel, and Winchins (2011) demonstrated that there was a substantial significant correlation between being a bully and having attitudes supportive of violence.

Psychological Well-Being Lower levels of perceived competence at school have been associated with higher levels of violence (O’Moore & Kirkham, 2001). For example, Ochao, Lopez, and Elmer (2007) found a significant negative correlation between school self-concept and violent behavior at school. With regard to self-esteem, although many studies have shown that low selfesteem is associated with violent behavior (e.g., Corwyn & Benda, 2001; Fong, Vogel, & Vogel, 2008; Marsh, Parada, Yeung, & Healy, 2001), others have provided evidence to the contrary (e.g., Baumeister, Smart, & Boden, 1996).


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Boden, Fergusson, and Horwood (2007) attempted to reconcile these differing viewpoints using a longitudinal prospective design. They showed that low selfesteem was associated with higher rates of self-reported and other-reported violent offending. However, when they controlled for socio-economic status, childhood, family, and related factors, these relations became non-significant. Nevertheless, when self-esteem and attitudes toward violence are examined, adolescents with low self-esteem appear to be more accepting of violence than those with moderate or high self-esteem (Merwin & Ellis, 2004). When assessed against opposite-sex relations self-concept (perceptions of how one relates to members of the opposite sex), a theoretically different construct, the association with attitudes to violence has been non-significant. For example, in their large representative study of high school troublemakers and self-concept, Marsh et al. (2001) found that there was no association between being a troublemaker and opposite-sex relations self-concept.

The Present Study Focusing on positive aspects is superior for children’s well-being than focusing on those that are negative. For example, Krug, Mercy, Dahlberg, and Zwi (2002) asserted that to prevent violence “Programmes focusing on individuals tend to encourage positive attitudes and behaviour in children and young people and can change the behaviour of individuals who have already become violent” (p. 1085). Hence, the purpose of the current study was to design and test the newly devised Attitude to Non-Violence Scale (ANVS), composed of cognitive and affective factors, that is positively oriented so as to be acceptable to both the school community and parents. Thus, higher scores on our scale reflect attitudes that are less supportive of violence and more supportive of non-violence. We tested the validity of the ANVS using both within- and between-construct validity (see Hinkin, 1998) and continued by examining group differences (sex and year in school).

Within-Construct Validity Within-construct validity relates to the internal structure of the construct (internal reliability), the specific components of which it is comprised and the structure among these components (factor structure). We also assessed whether the scale had a similar meaning for both sexes and year in school groups. As this is a newly developed scale, we posed the following research questions:


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Research Question 1 (RQ1): Will the newly devised ANVS display within-construct validity as evidenced by the proposed factor structure of the ANVS being supported, good internal reliability, and the sub-scales being separable from each other? Research Question 2 (RQ2): Will the factor structure of the ANVS be invariant across males and females and across years in school?

Between-Construct Validity Between-construct validity is demonstrated when the construct is shown to relate to another independent construct with which it is theoretically similar (convergent validity). In our study, we expected that attitudes to non-violence would be negatively related to bullying behavior as students who disapprove of violence, we theorized, would not participate in bullying. We further expected that those who condemned violence would have higher scores in measures of psychological well-being (criterion-related validity). As such, the following hypotheses were posed: Hypothesis 1 (H1): The ANVS will be negatively related to bullying behaviors. Hypothesis 2 (H2): Those who condemned violence (and so had high scores on the ANVS) will also have higher school self-concept and higher self-esteem. Between-construct validity can also be demonstrated if the construct has no association with another independent construct with which it is theoretically dissimilar (discriminant validity). For example, it appears that self-concepts of relations with the opposite sex may not be associated with violence. Hence, we hypothesized that Hypothesis 3 (H3): There will be no relation between opposite-sex selfconcept and anti-violence attitudes.

Group Differences On the basis of previous research, we posed the following hypothesis: Hypothesis 4 (H4): Year in school and sex differences observed in the ANVS will be consistent with predictions from the literature, such that males will be more supportive of violence than females and there will be no difference across years in school in ANVS scores.


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Method Participants Approval to conduct the study was obtained from the university’s human ethics research committee and from the New South Wales (NSW) Department of Education and Communities. The study was conducted in six public high schools in NSW, Australia (N = 774, 67.8% boys). The average age was 13.33 years (SD = 1.26), ranging from 10 to 17 years. Students were in Years 7 to 10, and the number of students in the schools in these years ranged from 180 to 488. When multivariate outliers were examined, 45 cases were identified that had extreme Mahalanobis distance scores, and 2 cases were missing on all variables. Thus, these cases were removed from the analysis, leaving 727 participants (67.2% boys). The proportion of boys was high as there were 2 boys-only schools in the study. All students who participated had parental consent to be involved in the study and provided informed consent themselves. The response rate was 38%. Students were informed that participation was voluntary, that they could withdraw at any time, and that their answers would be kept anonymous. The schools were located in Western Sydney, which has been recognized as one of the socially disadvantaged areas of Australia (Yeung, 2012). As such, the sample, living in locations where poverty, crime, and violence are more prevalent than others, would provide interesting insights into our understanding of the key issue of students’ attitudes to violence. In the present sample, more than 10 different languages were spoken although they all spoke English at school. Students were asked to answer survey questions about their attitudes to non-violence (i.e., in a positive sense). They were also asked about their own bullying behavior, if any, and their perceptions of themselves.

Materials Participants completed a survey containing demographic items and items pertaining to bullying behaviors, self-perceptions, and attitudes to nonviolence. The students responded to the survey items in a random order. For self-perceptions and attitudes to non-violence, they responded on a 6-point Likert-type scale ranging from 1 (strongly disagree) to 6 (strongly agree). For bullying behaviors, they responded on a 6-point Likert-type scale ranging from 1 (never) to 6 (everyday). Higher scores were reflective of higher bullying behaviors, self-perceptions, and attitudes to non-violence. All ANVS items and sample items for the remaining scales can be found in Table 1.


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Table 1. Sub-Scales and Items of the ANVS and Other Scales Used in the Study. Cognitive 1. Violence is not an appropriate way to solve problems 2. Violence is not a solution to problems 3. I would ignore a person who tried to encourage me to use violence 4. I think people who try to encourage others to use violence are wrong Affective 1. I do not like people who encourage others to use violence 2. I do not like people who use violence to solve problems 3. I do not like people who are members of gangs that use violence 4. I would not be interested in joining a gang that used violence Sample items of other scales Self-esteem 1. Overall, I have a lot to be proud of 2. Most things I do, I do well School self-concept 1. I get bad marks in most school subjects (R) 2. I learn things quickly in most school subjects Bully–Physical 1. I pushed or shoved a student 2. I hit or kicked a student hard Bully–Relational 1. I got other students to dislike another student 2. I told my friends something about a student to get them into trouble Opposite-sex relations (OSR) 1. I am not very popular with members of the opposite sex (R) 2. I have lots of friends of the opposite sex Note. R = reverse scored.

Attitudes to non-violence. After a pilot test of more than 12 items, 8 items were developed and differentiated hypothetically into 4 cognitive and 4 affective aspects of attitudes to non-violence. They were worded in a positive sense. The 4 hypothesized cognitive items were used to tap into students’ proactive understanding of violence. Following self-concept research, these cognitive items included perceived knowledge and behavior reflecting such knowledge (Marsh, Craven, & Debus, 1999). Higher scores reflected being more supportive of non-violence (i.e., positive understanding of the wrongdoing and the ability to keep away from violence). The 4 hypothesized affective items asked students the extent to which they emotionally supported non-violence (i.e., dislike gangs and violence). Consistent with self-concept research


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operationalizing an individual’s affective self-perception in terms of interest (Marsh et al., 1999), higher scores for this affective aspect reflected students’ interest in violence-free environments. The items that were removed from the original battery include, “I would never join a gang that used violence,” which may reflect a behavioral choice based on a combination of cognitive and affective aspects of attitude; “I do not like listening to the views of people who promote violence,” which may not be purely cognitive or affective; and “I understand why some people may encourage others to use violence,” which was a reversed item that complicated the factor structure. Self-esteem. The scale was adapted from Marsh (1993). Five items concerned students’ general perception of themselves as an individual, sometimes referred to as self-worth (Arens, Yeung, Nagengast, & Hasselhorn, 2013). School self-concept. Adapted from Marsh (1993), four items concerned students’ perceptions of their competence in school subjects. Opposite-sex relations. The scale, also adapted from Marsh (1993), had four items, which concerned students’ interactions with peers of the opposite sex. Physical bullying. Six items were adapted from Parada’s (2006) Adolescent Peer Relations Instruments (APRI). Physical bullying included hitting and hurting someone else physically. Relational bullying. Six items were adapted from Parada’s (2006) APRI for students to report on the frequency of causing social, relational, and emotional harm to others.

Procedure The survey was administered by a research assistant in large groups either in the school hall or in a large classroom. The research assistant read each survey item aloud to aid those students with less developed literacy skills. In some schools, the class teacher also assisted to ensure students who needed help would be supported.

Statistical Analyses Surveys with extreme Mahalanobis distance scores (45) and those missing on all variables (2) were removed from analyses. To account for school effects, all items were centered within school to remove “all


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between-cluster variation” (Enders & Tofighi, 2007, p. 127). To cater for missing data, full information maximum likelihood (FIML; the default in the Mplus software; Muthén & Muthén, 2013) was used. Many methods used to overcome missing data, such as replacing missing values with means and listwise deletion, are problematic (Peugh & Enders, 2004). The advantage of using FIML is that “parameter estimates and standard errors are estimated directly from the observed data in an iterative fashion, rather than being imputed as such” (Marsh & O’Mara, 2010, p. 58). Moreover, even when data are not missing at random (MAR), when compared with other techniques, FIML yields results that are less biased (Hallgren & Witkiewitz, 2013). Descriptive statistics and the alpha reliability of each a priori factor were first examined (RQ1). CFA was used to further examine the within- and the between-construct validity of the refined scale. The procedures for conducting CFA have been described elsewhere (e.g., Jöreskog & Sörbom, 2006) and are not further detailed here. Following widely accepted criteria for assessing model fit, comparative fit index (CFI) and Tucker–Lewis index (TLI) values of .90 or above and root mean square error of approximation (RMSEA) values of below .08 were used as indication of acceptable model fit (Bentler, 1990; Browne & Cudeck, 1993). Within-construct validity (RQ1 and RQ2). To answer RQ1, we first examined a measurement model with eight items forming two ANVS factors (Model A1). Then, a one-factor congeneric model (A2) was conducted to ascertain whether Model A1 fitted the data better. Last, we conducted a model (A3) that tested whether a higher order factor accounted for the two aspects of nonviolence (cognitive and affective). For RQ2, a series of invariance tests were conducted (Models B and C), first across years in school (junior comprising 7th and 8th grades vs. senior comprising 9th and 10th grades) and then across sex (boys and girls). First, a model with no constraints imposed was conducted (B1 and C1), followed by one in which factor loadings were constrained to equality (B2 and C2), then factor loadings and intercepts (B3 and C3) were constrained to equality, which enabled us to compare the means of the latent variables across years in school and sex. Following that, factor loadings, variances, and covariances (B4 and C4) were constrained, and last, an extremely restrictive model (B5 and C5) was conducted in which factor loadings, variances, covariances, intercepts, and uniquenesses were all constrained to equality. The more constrained model is supported if the fit is reduced by less than .01 for fit indices such as CFI and TLI (Cheung & Rensvold, 2002) and if the fit increases by less than .015 for RMSEA (Chen, 2007).


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Between-construct validity (H1-H3). To examine between-construct validity in testing H1 to H3, we added self-esteem, school self-concept, physical and relational bullying, and opposite-sex relations to the two-factor ANVS, resulting in a model with 33 items forming seven factors (D1). In this instance, it was the correlations between factors that were of interest. Tests of mean differences (H4). We examined group differences by testing a MIMIC model (E1). The MIMIC approach is a special application of SEM that is similar to multiple regression (Yeung, Lau, & Nie, 2011). The MIMIC model examined the paths from discrete grouping variables (i.e., year in school, sex, and Year in school × Sex interaction in the current study) to the two latent variables (cognitive and affective) that comprised the ANVS. To accomplish this, three grouping variables were constructed: (a) year in school (1 = junior secondary, 2 = senior secondary), (b) sex (1 = male, 2 = female), and (c) Year × Sex interaction.

Results Preliminary Analyses Descriptive statistics and the alpha reliability of each a priori factor are reported in Table 2. The reliabilities were good for all the factors (all αs > .70).

Within-Construct Validity (RQ1 and RQ2) All models reported here converged to proper solutions (Table 3). Model A1, with eight items forming two ANVS factors, provided a good fit to the data (TLI = .947, CFI = .964, RMSEA = .056, with the upper bound of the 90% confidence interval [CI] being .073). Factor loadings (see Table 4) were moderate to large and significant. In contrast, Model A2, a one-factor model, indicated an unacceptable fit (TLI = .863, CFI = .902, RMSEA = .090, upper bound CI = .105). As the correlation between the two factors in Model A1 was high (.79), we also tested the ability of a higher order factor (Model A3) to explain the correlation between the two ANVS first-order factors. The results show that the second-order factor is well defined with the two factor loadings being large and statistically significant (.81 and .97). The goodness of fit for this model (A3) is similar to Model A1 (TLI = .947, CFI = .966, RMSEA = .056, upper bound CI = .073). Furthermore, the chi-square values of Model A3, χ2(df = 18, N = 727) = 56.19, and Model A1, χ2(df = 19, N = 727) = 59.31 (Δχ2 value



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Senior Secondary

−.01 .12 −.02 −.03 −.10 −.06 .01

Self-esteem School self-concept Bully–Physical Bully–Relational Opposite-sex relations Attitude (cognitive) Attitude (affective)

Note. Standardized scores reported.

M

Factors

.75 .76 .65 .69 .77 .74 .77

SD

.06 .07 −.31 −.22 .08 .25 .29

M .61 .76 .34 .38 .72 .63 .69

SD .01 .10 −.11 −.09 −.04 .04 .10

M .71 .76 .58 .61 .76 .72 .76

SD .04 −.07 .05 .01 .05 −.05 −.01

M .72 .79 .71 .68 .69 .77 .77

SD −.07 −.13 −.26 −.20 .04 .10 −.06

M

.73 .84 .40 .40 .76 .79 .89

SD

.00 −.09 −.07 −.07 .05 .00 −.03

M

.72 .81 .63 .60 .72 .78 .81

SD

Male (n = 264) Female (n = 117) Total (N = 381) Male (n = 224) Female (n = 122) Total (N = 346)

Junior Secondary

Table 2. Reliabilities and Descriptive Statistics (N = 727).

.75 .82 .80 .79 .74 .75 .83

α

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19 20 18 38 44 50 47 63 38 44 50 47 63 474 37

78.20 82.27 94.99 88.24 124.17 76.70 93.34 106.74 99.20 138.00 880.37 101.20

df

59.31 130.21 56.19

χ2

.950 .945 .944 .945 .941 .917 .936

.948 .957 .955 .957 .952

.947 .863 .947

TLI

.966 .957 .950 .954 .934 .925 .955

.964 .966 .960 .964 .946

.964 .902 .966

CFI

.055 .058 .058 .057 .059 .034 .049

.056 .051 .052 .051 .054

.056 .090 .056

RMSEA

[.037, .073] [.041, .074] [.043, .073] [.042, .073] [.046, .073] [.031, .038] [.038, .060]

[.038, .074] [.033, .068] [.036, .067] [.034, .067] [.040, .067]

[.040, .073] [.076, .105] [.040, .073]

RMSEA 90% CI

Note. The two year levels are junior secondary (Years 7 and 8) and senior secondary (Years 9 and 10). CFI = comparative fit index; TLI = Tucker– Lewis index; RMSEA = root mean square error of approximation; FO = first order; HO = higher order; MIMIC = multiple-indicator-multiple-cause.

A. CFA A1. Two factors (8 items) A2. One factor (8 items) A3. Higher order model (2FO, 1HO) B. Invariance across two year group levels (junior and senior) B1. All free B2. Factor loadings (FL) invariant B3. FL + Intercept (INT) invariant B4. FL, Factor variances and covariances (FV FC) invariant B5. All invariants (FL + INT + FV/FC + Uniquenesses) C. Invariance across sex (male and female) C1. All free C2. Factor loadings (FL) invariant C3. FL + Intercept (INT) invariant C4. FL, Factor variances (FV), and covariances (FC) invariant C5. All invariants (FL + INT + FV/FC + Uniquenesses) D1. Seven Factors (33 items) E1. MIMIC (two factors, based on Model A1)

Model

Table 3. Goodness-of-Fit Summary (N = 727).


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Self-Esteem

School .60* .70* .64* .69* .60* .59*

1 −.01 −.14* −.20*

1 .82* .09 −.22* −.26*

Relational

.59* .68* .65* .65* .69* .58*

Physical

1 .03 .01

.49* .75* .73* .58*

OSR

1

.81*

.97*

.76* .79* .70* .67*

Affective

1 .79*

.58* .53* .73* .77*

Cognitive

1

.97* .81*

ATV

Note. Factor loadings for Model A1 were equivalent to those in Model D, which are shown here. School = school self-concept; Physical = physical bullying; Relational = relational bullying; CFA = comparative fit index; OSR = opposite-sex relations; Cognitive = attitude to non-violence (cognitive); Affective = attitude to non-violence (affective); ATV = attitude to non-violence. *p < .05.

Factor loadings 1 .62* .56* 2 .56* .71* 3 .69* .85* 4 .60* .80* 5 .62* 6 Factor correlations Self-esteem 1 School .76* 1 Physical −.13* −.23* Relational −.15* −.21* .20* .04 OSR Cognitive .27* .25* Affective .31* .32* Higher order factor loading (Model A3) Cognitive Affective Higher order factor correlations (Model A3) ATV

Items

Table 4. Factor Loadings and Inter-Scale Correlations in CFA (Model D; N = 727).

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= 3.12 with 1 df), were not significantly different from each other. Taken together, these findings suggest that the ANVS can be taken as a higher order factor model although the two aspects (cognitive and affective) are clearly separable from each other. Invariance testing was conducted based on Model A1. For year in school, Model B2 positing invariance of factor loadings had a comparable fit (TLI = .957, CFI = .966, RMSEA = .051, upper bound CI = .068) to Model B1 positing no invariance for all parameters (TLI = .948, CFI = .964, RMSEA = .056, upper bound CI = .074; see Table 3). According to Cheung and Rensvold (2002) and Chen (2007), the difference between the two models in CFI was not large enough to claim a significant difference in the factor loadings (difference < .01). Model B3 positing invariance of factor loadings and the intercepts (TLI = .955, CFI = .960, RMSEA = .052, upper bound CI = .067) further allowed a comparison of the mean scores for the latent factors across years in school. Factor loadings and latent factor variances and covariances were also invariant (Model B4; TLI = .957, CFI = .964, RMSEA = .051, upper bound CI = .067). Model B5 is reported for completeness of the group invariance analysis, although total invariance was not supported. For sex, Model C2 positing invariance of factor loadings had a comparable fit (TLI = .945, CFI = .957, RMSEA = .058, upper bound CI = .074) to Model C1 positing no invariance for all parameters (TLI = .950, CFI = .966, RMSEA = .055, upper bound CI = 073; see Table 3). In Model C3, intercept invariance was added to Model C2 and was supported (TLI = .944, CFI = .950, RMSEA = .058, upper bound CI = .073), further allowing a comparison of the mean scores for the latent factors. Factor loadings and latent factor variances and covariances were also invariant (TLI = .945, CFI = .954, RMSEA = .057, upper bound CI = .073). Again, Model C5 is reported for completeness of the group invariance analysis, although total invariance was not supported. Hence, the newly devised ANVS displayed within-construct validity as (a) it showed good internal reliability, (b) the proposed factor structure of the ANVS was supported, and (c) the sub-scales were separable from each other. Moreover, the factor structure of the ANVS was invariant across males and females and across years in school.

Between-Construct Validity (H1-H3) Model D1 had 33 items forming seven factors (self-esteem, school self-concept, physical and relational bullying, opposite-sex relations, and the twofactor ANVS). This model provided a reasonable fit to the data (TLI = .917, CFI = .925, RMSEA = .034, upper bound CI = .038). An inspection of the


17

Craven et al.

Year

-.04

Non-Violence Cognitive

.17* .05

-.06

-.01

Sex -.10*

.05

.08

Year x Sex

-.12*

Non-Violence Affective

Figure 1. MIMIC model.

Note. Bold arrows are statistically significant. MIMIC = multiple-indicator-multiple-cause. *p < .05. Year: 1 = junior, 2 = senior. Sex: 1 = male, 2 = female.

factor correlations in Table 4 found that self-esteem was closely related to school self-concept (r = .77), consistent with previous findings in selfconcept research (Marsh & Yeung, 1999). Physical and relational bullying were also closely related (r = .81) to each other, consistent with Parada’s (2006) findings. In support of H1, both ANVS factors were negatively related to bullying behaviors (cognitive and physical bullying = −.22; cognitive and relational bullying = −.14; affective and physical bullying = −.26; affective and relational bullying = −.20). H2 was also supported: Those who condemned violence had higher school self-concept (cognitive and school selfconcept = .25; affective and school self-concept = .32) and higher self-esteem (cognitive and self-esteem = .27; affective and self-esteem =. 31). Neither the cognitive nor the affective attitudes had any relations with opposite-sex relations, providing evidence of discriminant validity (.03 and .01, respectively). Hence, between-construct validity was demonstrated in terms of convergent validity, criterion-related validity, and discriminant validity.

Tests of Group Differences (H4) Model E was a MIMIC model examining group differences (Figure 1). Year in school differences were found (β = −.10) for the affective component of ANVS indicating that younger students had more positive affect to a nonviolent environment. Sex differences were found for the cognitive aspect of attitudes to non-violence (β = .17), indicating that girls were more positive in


18


Atude to Non-violence Affecve 0.5

Mean Score

0.3 0.1 Male Female

- 0.1 - 0.3 - 0.5

Junior

Senor

Figure 2. Year in school × Sex interaction effect for attitude to non-violence (affective).

cognitive beliefs concerning non-violence. The Year in school × Sex interaction was statistically significantly negative for the affective component of the ANVS (β = −.12), indicating that as girls entered their senior years, they became less affectively supportive of non-violence (Figure 2).

Discussion Our aim in this study was to develop a psychometrically sound, brief, and easy-to-use attitudes to non-violence instrument. To achieve this, we tested the within- and between-construct validity of our scales according to a strict set of criteria, all of which were attained. Our Affective and Cognitive sub-scales had good reliability estimates of .83 and .75, respectively. Our CFA indicated that the factor structure was sound. Interestingly, whereas the correlation between the two sub-scales representing the cognitive and affective aspects of attitudes to non-violence was on the high side, a two-factor solution proved to be better than a one-factor solution, suggesting that the two aspects were distinct from each other. However, our higher order model also provided a good fit to the data, meaning that researchers can choose to use either the one-factor or the two-factor model, depending on their purpose. Previous research (Davidson & Canivez, 2012; Funk et al., 1999; Velicer et al., 1989) has not taken into account affective and cognitive aspects in scale design. Hence, our scale is consistent with


Craven et al.

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research that has shown that attitudes are composed of these two components (Arens et al., 2011; Conner et al., 2013; Taut & Baban, 2012). This is an important step forward for intervention design as both emotional and thought processes concerning attitudes to violence can be targeted. We also demonstrated that the meaning of our scale was similar across year groups and across sex. Hence, it is appropriate to use our scale for junior and senior secondary students and for males and females. In sum, the ANVS was shown to have within-construct validity as results indicated that our scale was reliable, that the factor structure was sound, and that two sub-scales could be used. We demonstrated that the ANVS also had between-construct validity. Convergent validity was evidenced in that students who reported that they were involved in physical and relational bullying had more supportive attitudes to violence (i.e., bully behaviors had a negative relation with the ANVS). Students who refuted violence were less likely to display bullying behaviors, physical or relational. This is consistent with previous research that has shown that bullies tend to have more pro-violence attitudes (Olweus, 1994; Poteat et al., 2011; Rigby & Slee, 1993). Students whose attitudes toward violence were non-supportive had higher self-esteem and higher school self-concept, thus demonstrating criterion-related validity. These findings are in line with research showing that individuals with high self-esteem and high school self-concept are less accepting of violence (Merwin & Ellis, 2004; Ochao et al., 2007). In practical terms, having a non-supportive attitude to violence, whether cognitive or affective, has positive relations with (a) student’s self-esteem, which is an important educational outcome for longterm well-being (Arens et al., 2013), and (b) school self-concept that is an important educational outcome and mediating variable that significantly influences academic performance (Marsh et al., 1999). Discriminant validity was also evidenced in that there was no relation between the ANVS and opposite-sex relations self-concept, a finding consistent with that of Marsh et al. (2001) who found no association between opposite-sex relations self-concept and being a troublemaker. These patterns of correlations from a betweennetwork validation perspective provided a strong test of the validity and practicality of the ANVS (see Arens et al., 2011). In support of our hypothesis, males reported more supportive beliefs and judgments about violence than females. This is consistent with previous research that has shown that males are more likely to endorse violence than females (Anderson et al., 2006; Davidson & Canivez, 2012; Funk et al., 1999, 2003; Kingery, 1998; Thornton et al., 2013; Vernberg et al., 1999; Walker, 2005). However, this was only for the cognitive component as there was no difference across sex for the affective component. Although previous research


20


has shown that there was no difference across year groups in attitudes to violence (Funk et al., 1999, 2003), the present investigation found that senior students endorsed items showing a dislike of violence significantly less than their junior counterparts, meaning that they were more emotionally supportive of violence than junior students. These less positive attitudes for senior secondary students are consistent with findings in motivation research showing a decline in attitudes as students grow up (e.g., Watt, 2008; Yeung et al., 2011), as the senior students’ attitudes to non-violence were significantly lower than those of junior students. Moreover, senior female students were more emotionally supportive of violence than males and junior students as they endorsed items showing a dislike of violence significantly less than their male and junior counterparts. As previous research with adolescents has not used Attitudes to Violence Scales that could differentiate affective and cognitive components, these are important findings with practical implications. The separation of the cognitive and affective aspects has enabled a clearer delineation of sex differences, which had not been considered before. The difference in the cognitive component suggests that sex differences found previously may have been due to boys’ lower awareness of violence issues and higher tendency of displaying behaviors of violence (i.e., the cognitive component), not necessarily due to their lower interest in a violence-free environment (i.e., the affective component). Hence for males, interventions should target the cognitive aspects of attitudes to violence. In contrast, for females, as indicated in Figure 2, interventions should target the affective aspect of attitudes, which seemed to worsen as they matured. Why girls seemed to become less positive in the affective aspect of non-violence is unclear. Perhaps the decline in positive affect is consistent with a general trend of female students’ larger drop in motivational constructs in secondary schools as shown in other studies (e.g., Yeung et al., 2011). However, as suggested by an anonymous reviewer, perhaps this finding can be explained by the area in which this study was conducted. As students came from a socially disadvantaged area where poverty and crime are prevalent, perhaps the females became more emotionally supportive of violence as they aged because they were more likely to be exposed to violence, viewed it as normal, and this was their way of coping with it. Nevertheless, this remains a question for future research to explore.

Strengths, Limitations, and Future Research Previous research in this area has mainly used EFA and manifest variables, which means that measurement error has not been accounted for appropriately. Instead, we used current theoretical thinking on the composition of


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attitudes by assessing both cognitive and affective components and tested this theorizing using a construct validation approach applying CFA and examined group differences in latent variables with a MIMIC model. This distinction will allow future interventions to target attitude to violence in general or specific attitude components more effectively. First, to promote positive attitudes to non-violence, we need to choose effective means that have the ability to generate positive non-violence attitudes (e.g., self-esteem and school selfconcept enhancement) and proactively address factors that stimulate proviolence attitudes (e.g., physical and relational bullying interventions). Second, depending on the purpose of the intervention, we may target the cognitive construct or the affective construct for groups of students with different characteristics. For example, more focus on the affective aspect would benefit senior students more, whereas a stronger focus on the cognitive aspect would benefit boys more. Hence, the separation of cognitive and affective aspects is useful for guiding intervention for different samples and for monitoring intervention progress and outcomes. Regarding the ANVS, the results suggest that it is appropriate to use them with high school students, and both boys and girls. We have also demonstrated the convergent and discriminant validity of our instrument, which not all previous research has done. This means that we know that our tool is a valid one that assesses what it purports to assess. Nevertheless, it is important to note that there are also other statistical approaches that other researchers and practitioners may prefer (e.g., the Rasch approach; see Fox & Brockmyer, 2013), although we considered our approach to be appropriate for the current purpose. By keeping our instrument brief, it was not possible to measure attitudes to different kinds of violence. Although brevity is a strength, in that our instrument can be used easily within a battery of tests, it is also a limitation as there may be important aspects of attitudes to non-violence that our instrument does not capture. Future research could expand our scale to other aspects of attitudes to non-violence with a focus on affective and cognitive components. Students in our sample spoke up to 10 different languages. Although the size of our sample did not allow us to test invariance over these differing cultures, assessing cultural variability in the ANVS is an avenue for future research. In addition, as the participants self-reported their attitudes to non-violence, this may have introduced bias to our results as they may have responded in a socially desirable manner. This may have led to students overestimating their anti-violence attitudes. Although future research could consider adding a lie scale to assess social desirability, many researchers suggest that corrections made for social desirability are ineffective (Ellingson, Sackett, & Hough, 1999; McCrae & Costa, 1983; Zettler, Hilbig, Moshagen,


22


& de Vries, 2015). That the two sub-scales were highly correlated could also be viewed as a limitation. However, we have demonstrated that a two-factor conceptualization and operationalization of the attitudes have the advantage of providing us with more informative findings for practical purposes such as identifying the focus for intervention. Nevertheless, we leave it to future research to further explore the distinctness of the two factors and the practical value of their differentiation. A possible limitation is that our scale used a mix of positive and negative items. There is much controversy over this approach to scale creation, with some saying that it reduces response bias and others that it results in method effects related especially to the negatively worded items (Roszkowski & Soven, 2010). However, as demonstrated in the current study, the reliability of the scales was good as were the factor loadings. Moreover, the scales demonstrated between-construct validity in the appropriate directions suggesting that adolescents are well able to respond to a mix of positive and negative items. Another limitation concerns the causality issue. Being based on correlational data, the present investigation cannot infer causality between holding attitudes that support violence and violent behavior, such as physical bullying. Future research should consider examining longitudinal data to explore this issue more fully.

Conclusion This brief psychometrically sound scale is an important addition to the battery of scales in the extant literature. We have provided a scale that is grounded in theory, suitable for adolescents, practical to use, and more importantly, positively oriented so as to be acceptable to both the school and wider community. Declaration of Conflicting Interests The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The authors acknowledge the research funding support provided by the Australian Government Attorney General’s Department, New South Wales Police Force, and the Australian and New Zealand Counter-Terrorism Committee (ANZCTC).

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Author Biographies Rhonda G. Craven is the director of the Institute of Positive Psychology and Education at the Australian Catholic University, Sydney, Australia. She is a highly accomplished researcher, having successfully secured nationally competitive funding for 47 large-scale research projects. She is the recipient of the Meritorious Service to Public Education Award, the Betty Watts Award (Australian Association for Research in Education), the Vice Chancellor’s Award for Excellence in Postgraduate Research Supervision and Training, and the Vice Chancellor’s Award for Excellence in Social Justice Research. Her research interests include the structure, measurement, development, and enhancement of self-concept and key psycho-social drivers of potential; the effective teaching of indigenous studies and indigenous students; maximizing life potential in diverse settings; and interventions that make a tangible difference in educational settings. Her research has resulted in extensive publications including 10 edited research monographs, 8 books, 6 commissioned national reports, 73 articles in top-tier refereed journals, 48 book chapters, and 176 refereed conference papers. Marjorie Seaton is a research lecturer in the Institute of Positive Psychology and Education at the Australian Catholic University, Sydney, Australia. She is a trained teacher, who has had commercial experience both in Australia and overseas. Her awards include an honors scholarship from Macquarie University for academic


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excellence, the prestigious Australian Association for Research in Education PhD award for the best Australian PhD thesis in 2009, and an International Self-Concept Enhancement and Learning Facilitation Research Center Doctoral Award for an outstanding dissertation in the field of educational psychology. Her work has been published in highly ranked refereed journals and influential monographs. Her research interests include gifted and talented education, social comparison, self-concept, antibullying interventions, youth violence, and teacher feedback. Alexander S. Yeung is the deputy director of the Institute for Positive Psychology and Education at the Australian Catholic University, Sydney, Australia. He is a registered teacher, a psychologist, a professional translator, a linguist, and an educational researcher. He has taught in various educational settings from preschool to tertiary levels, and has been a teacher educator for 40 years. His research expertise includes self and identity, equity, motivation, measurement and evaluation, cognition and instruction, language research, and psychological studies.


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Reliability and validity of the Abusive Violence Scale.

A rating scale for mania: reliability, validity and sensitivity.

Reassessing the validity and reliability of the MMPI Alexithymia Scale.

The Patient Learning Needs Scale: reliability and validity.

Identifying vulnerability in grief: psychometric properties of the Adult Attitude to Grief Scale.

Factor Validity of a Proactive and Reactive Aggression Rating Scale.

Lumbar spinal stenosis-specific symptom scale: validity and responsiveness.

Reliability and validity of the Menopausal Symptom Scale.