Hirschi’s reconceptualization of self-control: Is truth truly the daughter of time? Evidence from eleven cultures

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Hirschi’s Reconceptualization of Self-Control:

Is Truth Truly the Daughter of Time? Evidence from Eleven Cultures

Alexander, T. Vazsonyi1

Li Huang2

Corresponding Author, Department of Family Sciences, University of Kentucky1

316 Funkhouser Building

Lexington, KY 40506-0054 (USA)

P. 859-257-9762 F. 859-257-3212

Department of Psychology and Sociology, Tuskegee University2

Acknowledgements We are indebted to all the schools, its administrators, and the students who completed the surveys; we would also like to thank Drs. Dick Hessing and Marianne Junger, Ginesa Torrente-Hernandez, and Chuen-Jim Sheu for their assistance in collecting data in the Netherlands, Spain, and Taiwan, respectively. Thank you also to Joshua Roberts who assisted with literature searches and reviews. Partial support for data collections in Slovenia and the Czech Republic were provided to the first author by a Fulbright grant and by the Fulbright-Masaryk Distinguished Chair in Social Studies, respectively. Additional support for the data collection in Japan was provided by Auburn University’s Competitive Research Grant-In-Aid Program. Please address any correspondence to the first author: [email protected].

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Abstract

Purpose: The conceptualization and measurement of self-control remains a debated topic, in

criminology as well as other social and behavioral sciences. The current study compared the

relationships between the Grasmick and colleagues (1993) self-control scale and the redefined

self-control measure by Hirschi (2004) on measures of deviance in samples of adolescents.

Methods: Anonymous, self-report data were collected from over N = 16,000 middle and late

adolescents in China, the Czech Republic, Hungary, Japan, the Netherlands, Slovenia, Spain,

Switzerland, Taiwan, Turkey, and the United States.

Results: Based on latent constructs with items parcels in an SEM framework, multi-group tests

were used to examine both the relative predictive utility of each self-control measure on deviance

and the extent to which these relationships varied across cultures. Both scales appear to tap into

self-control; however, findings provide evidence that the Grasmick et al. measure explains more

variance. These links did not vary across cultural contexts.

Conclusions: Hirschi provocatively suggested that the truth is the daughter of time; yet, we find

that the measure developed by Grasmick and colleagues, the most widely used scale, retains

greater explanatory power, and does so in an invariant manner across all eleven developmental

contexts examined.

Highlights

Anonymous, self-report data from over 16,000 adolescents, eleven cultures

Cross-cultural study tests self-control-deviance links (Hirschi versus Grasmick et al.)

SEM multi-group tests reveal invariance in these relationships across countries

Hirschi’s reconceptualization has merit, yet explains less variability in deviance Keywords: General Theory of Crime, self-regulation, delinquency, cross-national.

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Hirschi’s Reconceptualization of Self-Control:

Is Truth Truly the Daughter of Time? Evidence from Eleven Cultures

The study examined one specific redefinition to one of the most influential recent

criminological theories, namely self-control theory (Gottfredson & Hirschi, 1990). Hirschi

(2004) to differently conceptualized and operationalized self-control by linking self and with

social control theory (Hirschi, 1969); specifically, self-control was redefined to encompass

indicators of social bonds (both in number and salience). He argued that doing so truly captured

the essence of self-control, which of course departs quite radically from some of the original

arguments presented in The General Theory of Crime (Gottfredson & Hirschi, 1990), but also

from most empirical work completed over the past two decades. On the other hand, some of

Hirschi’s argument is consistent with what he has argued previously (e.g., Hirschi &

Gottfredson, 1993), namely that behavioral measures of self-control (see e.g., Keane, Maxim, &

Teevan, 1993) are preferred over attitudinal measures, such as the one developed by Grasmick

and colleagues1 (1993). In the current study, we review the modest number of scholarly efforts

that have been based on Hirschi’s (2004) redefinition of self-control, based mostly on college-

aged youth from the United States, followed by our own empirical test which juxtaposes the

Grasmick et al. measure against the redefined Hirschi measure in explaining deviance. For this,

we employ large samples of over 16,000 youth from eleven different cultural contexts, thus

adding a novel quasi-experimental (van de Vijver & Leung, 1997), cross-national comparative

piece to this literature that has followed Hirschi’s redefinition.

Literature Review

The General Theory of Crime (Gottfredson & Hirschi, 1990) has sparked a substantial

amount of empirical inquiry on self-control and its effects on crime and deviance (DeLisi &

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Piquero, 2011; Pratt & Cullen, 1990), but also victimization (Pratt, Turanovic, Fox, & Wright,

2014); this work has also often transcended disciplinary boundaries (de Ridder, Lensvelt-

Mulders, Finkenauer, Stok, & Baumeister, 2012), thus establishing self-control as a pivotal

individual difference in behavioral adjustment and developmental outcomes over the lifecourse

(Moffitt, Arsenault, Belsky, Dickson, Hancox, Harrington, Houts, Poulton, Roberts, Ross, Sears,

Thomson, & Caspi, 2011). Much of this work has been carried out with attitudinal measures of

low self-control, particularly within criminology and criminal justice, but less so in the

psychological or developmental sciences. Almost a decade and a half after the publication of the

seminal theory, Hirschi (2004) redefined what self-control was and how it should be

operationalized.

Self-Control Redefined

Hirschi (2004) redefined self-control as “the tendency to consider the full range of

potential costs of a particular act” (p. 543). This departs from the original conceptualization in

which self-control was termed to be “the tendency to avoid acts whose long-term costs exceed

their momentary advantages” (Gottfredson & Hirschi, 1990, p. 3). The redefined self-control

encompasses both short- and long-term costs, instead of merely long-term costs of deviant acts.

Self-control, as redefined by Hirschi (2004), seems more akin to rational choice theories, as

decisions are made within the moment of an act and less attuned to persistent trait-like,

individual differences. He notes, “Fortunately, in this case at least, truth is indeed the daughter of

time, and we can now see the errors introduced by our excursion into psychology and by the

measures of self-control stemming from it” (p. 542) and that most measures used since the

publication of the theory have lost what he considered “elements of cognizance and rational

choice” (p., 542).

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Hirschi (2004) further notes that self-control is a “set of inhibitions one carries with one

wherever one happens to go” (p. 543). These inhibitions are linked to social bonds (attachments,

commitments, involvements and beliefs) that Hirschi (1969) identified as part of social control

theory. The more “bonded” an individual is or the more inhibitions a person has the higher level

of self-control the person exhibits. Hirschi (2004) also includes a salience dimension, so it is not

merely a large number of inhibitions affecting self-control, but also the level or importance of

those inhibitions to the individual. This redefinition seems to offer a combination of social

control and self-control theories, perhaps a joining or equilibrating of social and self-control.

Hirschi (2004) found empirical support for this redefinition by developing a nine item

dichotomous scale, focusing on social bonds and their importance based on the Richmond Youth

Project. The items focused on parents, teachers, and school. He found that the more inhibitions

an individual possessed, the less likely the person was to commit delinquent acts. Basing the

measure upon inhibitions, instead of traits or behaviors (i.e., past offenses predicting future

offenses), permitted Hirschi to effectively address one of the strongest criticisms of self-control

theory, namely the tautology issue raised by Akers (1991), although Hirschi (2004) suggests that

the redefinition was not influenced by the issue. Self-control, redefined, according to Hirschi

(2004), enhances the General Theory by placing self-control decisions into the realm of cognitive

processes in a given instance. The redefinition of self-control encompasses elements of social

control theory and also aligns with rational choice theory, attempting to expand self-control into

a truly “general” theory.

While the redefinition of self-control would seem to be a turning point, the empirical

evidence following this fairly strong departure from the original theoretical work has generated

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only a handful of empirical efforts, which mostly mixed and inconsistent findings. Table 1

provides an overview of these studies, along with a brief synopsis of each.

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Two main themes of findings emerge from these studies. Five of the studies (Piquero &

Bouffard, 2007; Gunter & Bakken, 2012; Higgins, Wolfe & Marcum, 2008; Morris, Gerber, &

Menard, 2011; Rocque, Posick, & Zimmerman, 2013) compare and contrast different measures

of self-control. Each study uses a measure developed based on the redefinition of self-control

and compares its effectiveness of predicting or explaining deviance against the most commonly

used scale by Grasmick and colleagues (1993). The other two studies (Bouffard & Rice, 2011;

Ward, Boman, & Jones, 2012) measure self-control according to the redefinition and then

examine the influence of social bonds on self-control.

Empirical Tests of Hirschi’s Redefined Self-Control Measure

Piquero and Bouffard’s (2007) provided the initial empirical test of Hirschi’s (2004)

reformulation based on a sample of N = 212 college students, and focused on drunk driving and

sexual coercion. The study used vignettes about drunk driving as well as one about sexual

coercion (males only). Following each vignette, respondents were asked to list up to seven “bad”

things that may happen if they engaged in the activity, capturing Hirschi’s redefined self-control.

Participants rated importance of “bad” things and likelihood of not engaging in the act. Findings

showed that only the redefined self-control measure remained significant when both the

Grasmick et al. measure and the “new” measure were tested simultaneously, for both dependent

measures, thus leading Piquero and Bouffard to conclude that found potential within Hirschi’s

redefinition of self-control was more effective in predicting the likelihood of engaging in deviant

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acts. Gunter and Bakken (2012) essentially replicated this work in a random sample of N = 1,458

college students, with some minor modifications, including the focus on cheating on a test

instead of sexual coercion; they also used controls for previous offending (past-DUI’s or past-

cheating) in their analyses. Interestingly, this work showed that only the Grasmick et al. (1993)

measure remained statistically significant once combined with a reconceptualized Hirschi (2004)

measure in a regression model. Finally, Higgins, Wolfe and Marcum (2008) focused on testing

three different measures of self-control in predicting digital piracy based on a sample N = 358

college students. In contrast to previous work, the authors tested the Grasmick et al. (1993), the

Piquero and Bouffard (2007) measure based on self-generated inhibitions, and the measure

developed by Hirschi (2004) which focuses on the presence of social bonds. Based on regression

analyses, the authors found that all three measures remained statistically significant in explaining

digital piracy when tested simultaneously, where predictive strength by the Grasmick et al. scale

was largest, followed by the Piquero and Buffard measures, and Hirschi’s bonding scale.

Morris and colleagues (2011) took a slightly different approach based on data from the

National Youth Survey Family Study and focused on self-reported adult criminality. The

redefined measure by Hirschi was operationalized by different bonds (spouse or partner,

children, friends, career, involvement in community activities and religiosity) and rating the

salience of each and then compared to the Grasmick et al. (1993) measure. The authors found

that both measures predicted adult crime with similar effectiveness, but suggested that each

measures captured different self-control concepts when considering adult criminality. Most

recently, Rocque, Posick and Zimmerman (2013) used the U.S. sample part of the second

International Self-Report Delinquency (ISRD-II) project and applied Rasch analysis and negative

binomial regressions to compare both the Grasmick et al. (1993) and Hirschi’s (2004)

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reconceptualized self-control measures. Findings provided evidence that both measures were

quite similar in measurement properties and construct validity, although there was also some

evidence that the Grasmick et al. measure provided a better fit to the data. They concluded that

both measures appear to play an important and complimentary role in explaining variability in

violence, property offending, and alcohol consumption.

Redefined Self-Control and the Impact of Social Bonds

Bouffard and Rice (2011) took a slightly different approach and sought to address

response bias issues in their redefined self-control measure over work done by Piquero and

Bouffard (2007). Based on a sample of N = 311 college students and also using short vignettes

about drunk driving, the authors interpreted low salience score as indicating low self-control,

regardless of the number of inhibitions reported. This operationalization found Hirschi’s (2004)

redefinition did predict a tendency to drink and drive. Of course, it is not known the extent to

which it predicted other measures of deviance, related to the fairly narrow focus.

The study also explored the influence social bonds on self-control by considering

attachment, belief in the law, and commitment to religion, thus testing how social bonds affect

momentary self-control decisions. Path analysis provided evidence that social bonds had an

indirect effect on decisional self-control although no evidence was found that bonding itself had

a direct effect on drunk driving. Instead individuals who were more bonded to society were less

likely to drink and drive. Thus, findings provide some evidence supportive of the notion that

social bonds operate through self-control on offending.

Finally, Ward, Boman and Jones (2012) focused on testing Hirschi’s impetus based on a

Boys Town sample of N = 2,243 adolescents between the seventh and twelfth grades focused on

marijuana use. Previous efforts had difficulties with fully capturing Hirschi’s (2004) redefinition

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of self-control, as they did not tap into both number of inhibitions as well as salience. In this

effort, the number of costs was measured by using predetermined cost categories rather than

relying on self-generated costs (e.g., Piquero & Bouffard, 2007), thus more breadth of costs.

Salience on the other hand was measured by asking participants how important “others” (parents,

family members, friends, peers, older others and the law) were in helping them to decide whether

to use or not use marijuana. This operationalization replies on the salience of “others”

specifically. Based on clustering of the sample by these two constructs, findings showed that

those who have more costs and that consider “others” more are less likely to use marijuana. They

also found that individuals who faced a high number of costs but did not consider “others” in

their decisions tended to refrain from using marijuana. However, the inverse (low number of

costs but high salience) did not show similar results. Again, this emphasized the importance of

social bonds and how they impact momentary decision making about norm-violating conduct. As

in some previous work, Ward et al. (2012) also found that social bonds had an influence on

marijuana use through the redefined self-control measure, where almost half of this effect (45%)

was indirect or mediated.

In conclusion, the empirical evidence on Hirschi’s (2004) redefined self-control remains

inconclusive and often contradictory, depending on the specific manner in which self-control

was redefined and assessed, depending on what norm-violating conduct was tested, and

depending on the sample used, mostly US college students. Clearly, a number of studies do find

merit to the Hirschi’s redefinition, yet some simply show that very little is added by Hirschi’s

reconceptualization, in terms of understanding and explanatory power. Support for strongly

linking self-control to social bonds has also been inconsistent, though not surprisingly, there is a

link, since self-control theory in fact specifies that social bonds (parents, teachers and so forth)

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are instrumental in the development and establishment of self-control during the first decade of

life (in addition to individual differences present at birth).

The Current Study

In the current investigation, we were interested in adding to this relatively modest body

of literature, characterized by inconsistent and at times contradictory evidence related to the

conceptual as well as the practical significance of Hirschi’s (2004) reconceptualization of self-

control in the understanding of and prediction of norm violating, deviant behaviors. To do so, we

applied a quasi-experimental, cross-national comparative lens to improve upon mostly local

efforts in terms of sampling, with some exceptions, but also to apply more rigorous analytic tests

of an idea or competing ideas. Gottfredson and Hirschi (1990) spent a sizable amount of their

theoretical treaties on self-control theory focused on this hallmark of science, namely the idea

that powerful concepts, predictions, or relationships should, in fact, hold up across different

developmental contexts, across different cultures.

We apply sophisticated data analytic techniques (item parceling, structural equation

modeling, and multi-group structural equation modeling) to test a relatively simple, yet elegant

idea, namely, to what extent is Hirschi’s re-conceptualized self-control measure unique or

redundant in our understanding of explaining variability in deviant behaviors vis-à-vis the most

frequently used attitudinal self-control measure control, the Grasmick et al. (1993) scale. We

hypothesize direct effects by Hirschi’s self-control measure as well as Grasmick et al.’s measure

and seek to develop a greater understanding the extent to which they explain unique variability in

deviance and the extent to which one or the other has the greater explanatory power. In addition,

and related to using a cross national comparative approach, we examine the extent to which these

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observed links between the self-control measures and deviance very as a function of cultural

developmental context. Based on previous empirical work as well as conceptual work by

Gottfredson and Hirschi, we expect great similarity in the extent to which the hypothesized

model will fit the data; on the other hand, we do not have specific hypotheses related to whether

one measure or the other measure will be a more potent predictor of deviant behaviors, simply

related to previous empirical efforts as well as to conceptual issues rooted Hirschi’s (2004)

chapter.

Method

Participants

Anonymous self-report data were collected from convenience samples of middle and late

adolescents in medium-sized cities in China (n=1,373), the Czech Republic (n=890), Hungary (n

= 871), Japan (n = 355), the Netherlands (n = 1,315), Slovenia (n = 1,422), Spain (n = 1,030),

Switzerland (n = 4,018), Taiwan (n = 1,443), Turkey (n = 1,447), and the United States (n =

2,213). The samples include youth from secondary schools in all countries except Japan as well

as college students in Slovenia, Spain, and the United States. Cities and schools were

purposively sampled in each country based on established relationships. For each some European

country (Netherlands, Spain, and Switzerland), different schools (college bound versus non-

college bound, technical schools) were selected to obtain representative samples of the local

population. Usually the entire student population was invited to participate at each school;

response rates at schools varied (range: 73% to 95% at individual schools). Table 2 includes

descriptive statistics by country on background variables (age, sex, family structure,

SES/primary wage earner).

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Procedures

A standard data collection protocol was followed across all study locations. The study

was approved by a university institutional review board and consisted of a self-report data

collection instrument that included instructions on how to complete the survey, a description of

the project, and assurances of anonymity. The questionnaires were administered in classrooms by

project staff or teachers who had received extensive verbal and written instructions. This was

done to maintain a standardized protocol across all study locations. Students had a 1- to 2- hour

period to complete the survey. Much attention was given to the development of the survey

instrument, particularly by developing new or employing existing behavioral measures that could

be used cross-culturally without losing nuances or changing meanings. To illustrate with some

concrete examples from the deviance measures: Although it may have been appropriate to ask

European youth about the theft of mopeds, American adolescents generally are unaware of this

mode of transportation. Americans use checks writing as legal tender, on the other hand, most

Europeans have never written a check. The survey was translated from English into the target

languages (Chinese, Czech, Dutch, German, Hungarian, Japanese, Slovenian, Spanish, and

Turkish) and back translated by bilingual translators. Surveys were examined by additional

bilingual translators, and when translation was difficult or ambiguous, consensus was used to

produce the final translation.

Measures

Participants in all countries were asked to fill out the same questionnaire including

demographic variables (age, sex, family structure, and socioeconomic indictors), measures of

family processes, school behaviors, and deviance.

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Age. Adolescents indicated their birth month and year. To maintain anonymity, the 15th

of each month was used to calculate participants’ ages.

Sex. Participants were asked to indicate their gender. Responses were given as 1 (male) or

2 (female).

Family Structure. Adolescents were asked, “Which of the following home situations best

applies to you?” Responses included 1 (biological parents), 2 (biological mother only),

3(biological father only), 4 (biological mother and stepfather), 5 ( biological father and

stepmother), 6 ( biological parent and significant other), and 7 (other). In the current study, we

coded this variable as 1 (two biological parent family) and 0 (other).

SES. This variable was computed based on one item. Adolescents were asked to indicate

the job type of the primary wage earner in their family, ranging from 1 (laborer) to 6 (executive).

Grasmick et al.’s Low Self-Control. A revised 22-item version of Grasmick, Bursik, and

Arneklev’s (1993) low self-control measure was used (Vazsonyi et al., 2001; Vazsonyi &

Belliston, 2007). Previous studies provided evidences that the instrument was both valid and

reliable. The measure includes six subscales: Impulsiveness, simple tasks, risk seeking, physical

activity, self-centeredness, and temper. Responses were given on a 5-point, Likert-type scale,

instead of a 4-point scale as originally proposed, ranging from 1 (strongly disagree) to 5

(strongly agree). In the current study, items were assigned into two parcels to measure a latent

self-control construct.

Hirschi’s Self-Control. Hirschi (2004) measure of self-control included items, such as

“Do you like or dislike school?”, “How important is getting good grades to your personally?”

“Do you finish your homework?”, “Does your mother know who you are with when you are

away from home?”, and “Do you share your thoughts and feelings with your mothers?”

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Responses to these items were either no (0) or yes (1), where yes indicated evidence of self-

control; the nine items were then summed to obtain a self-control score ranging from 0 to 9.

In the current study, we used very similar items as Hirschi proposed, including “I like

school”, “Getting good grades is important to me”, “I finish my homework”, “In my free time

away from home, my mother knows who I’m with and where I am”, “My mother wants me to

tell her where I am if I don’t come home right after”, “How often do you talk to your mother

about the boy/girl whom you like very much”, “How often do you talk to your mother about

questions or problems about sex”, “How often do you talk to your mother about other things that

are important to you”, “How often do you talk to your mother about things you have done about

which you feel guilty”, and “How often do you talk to your mother about major personal

decision.” However, to capture greater variability, we used 4 and 5 point response scales for the

items; in the case of the 4-point scale, we did the following coding: A = strong disagree to D =

strongly agree, which we coded as A and B = 0, C and D = 1. For the 5 points scale, = strongly

disagree, B = disagree, C = neither disagree nor agree, D = agree, E = strongly agree, we coded

as A, B, C = 0, D and E = 1). So, for instance, for Hirschi’s (2004) item: “Do you like or dislike

school,” in the current study we used “I like school” and coded responses A and B as 0, while C

and D as 1. Similarly, for the item “In my free time away from home, my mother knows who

I’m with and where”, we coded A, B, and C as 0, whereas D and E as 1. Table 3 provides the full

details on both Hirschi’s (2004) reconceptualization as well as the measurement used in the

current study.

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Normative Deviance Scale (NDS). Total deviance was measured by the 55-item

Normative Deviance Scale (NDS; Vazsonyi et al., 2001; Vazsonyi & Belliston, 2007). The NDS

assessed a broad spectrum of deviant activities and norm-violating conduct independent of

cultural definitions of crime and deviance. A total deviance score was computed by summing

items measuring vandalism, alcohol use, drug use, school misconduct, general deviance, theft,

and assault. Responses for items were given on a 5-point, Likert-type scale and identified

lifetime frequency of norm-violating behaviors. Responses included 1 (never), 2 (one time), 3

(two to three times), 4 (four to six times), and 5 (more than six times).

Plan of Analysis

To test the study hypotheses, we used structural equation modeling (SEM) with latent

constructs, based on multiple observed indicators. SEM has numerous advantages over analyses

simply focused on observed variables, including modeling and specifying measurement error,

and the explicit application of hypothesis testing. Model fit was evaluated by the standard chi-

square fit statistics as well as the Comparative Fit Index (CFI) and the Root Mean Square Error

of Approximation (RMSEA) (Browne & Cudeck, 1993; Loehlin, 1992). For the CFI, a fit

between .90 and 1.0 is considered an acceptable (Bentler, 1992). An RMSEA value of less than

.05 demonstrates excellent fit, while a value between .05 and .08 suggests a reasonable fit

(Browne et al., 1993). In addition, differences in model fit as part of multi-group modeling were

evaluated following the recommendation by Cheung and Rensvold (2002), which addresses the

sensitivity of the chi square statistics to sample size which was certainly an issue in our analyses,

where a difference in the CFI of +/- .01 or smaller was insufficient evidence to reject model

comparisons, or in other words, considered sufficient evidence of no difference between the free

and constrained models. We used item parcels as a more efficient means of modeling latent

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constructs, as recommended by Little, Cunningham, and Shahar (2002). In the work, Little and

colleagues carefully describe and weigh the philosophical, conceptual, and empirical pros and

cons of using parcels in SEM; they recommend parceling if researchers are interested in

understanding and modeling the relationships among a set of constructs, what one might consider

a more molar approach. Using such an approach in effect minimizes or reduces “nuisance

factors,” what we consider “noise” (lower level constructs that constitute a higher level one). On

the other hand, if a researcher is interested in understanding the dimensionality of a construct, a

more micro approach, how specific items “behave” in a model and load onto a latent construct,

then parceling is, as they note, contraindicated as it would obscure these goals. To parcel or not,

in the end, according to Little and colleagues, needs to be carefully weighed by the researcher

and depends on philosophical, conceptual and empirical goals – it depends on the specific

questions being posed by the researcher. They conclude that parceling should never be dismissed

out of hand, nor should it be applied in an unconsidered manner.

We applied an item-to-construct balance method to develop parcels that were balanced in

terms of their difficulty and discrimination. Parcels were developed and computed based on

findings from EFAs. In order to develop the parcels, the items for each scale were rank-ordered

from highest to lowest loadings based on exploratory factor analyses and then alternatively

assigned to the first and second parcels for each main study construct. To remove potential

confounds by differences in samples and sample composition, all parcels were residualized by

age, sex, family structure, and SES.

Results

Initially, descriptive statistics were computed for demographic variables by samples.

Table 2 presents descriptive statistics, which include sample size, age, sex, family structure, and

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SES by each sample. These variables were subsequently used as control variables in multi-group

SEM and for computing the observed indicators in multi-group SEM. Table 4 includes the

means, standard deviations, and reliability estimates for the Grasmick low self-control scale, for

Hirschi’s self-control, and for deviance by country. It also includes descriptive statistics on the

two parcels that were developed for each of the measures to be used in latent construct SEM.

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A series of structural equation models were tested for the each of the samples by using

AMOS. We used item parcels to specify observed variables, known to improve construct

reliability and model fit (Bentler & Chou, 1987). We also used the multi-group latent structural

model tests to examine the hypothesized model shown in Figure 1. It simultaneously examined

the relationships among the Grasmick et al. low self-control measure, Hirschi’s redefined self-

control measure, and NDS deviance measure. For this purpose, a series of four models was tested

using multi-group invariance tests. This meant in Model 1(default), all parameters were free to

vary to establish a baseline model and model fit. Next, in model 2 (multi-group), structural paths

(ɑ and b) were constrained to equality, while in model 3 (multi-1), path ɑ constrained to equality,

whereas in model 4 (multi-2), path b was constrained to equality.

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Findings from the multi-group SEM analysis are shown in Tables 5, 6, and 7. Table 5

includes standardized structural path coefficients from the default model (all paths free to vary).

Again, coefficients are reported for both the total sample and for individual country samples. The

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regression coefficients demonstrated that the relationship between Grasmick self-control and

NDS were consistently larger and stronger (range: 0.24 – 0.47), which also indicated that the

links between Hirschi’s reconceptualized measure and deviance were consistently smaller

(range: -0.27 to -0.06).

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Tables 6 and 7 include model fit of the invariance tests of all four models described. Fit

indices indicated that all models fit the data very well across country samples (CFI range = .932 -

.975, RMSEA range = 0.018-0.026). Analyses of chi-square did indicate that each of the

subsequent models were significantly different from the default model, though the difference

tests of alternative fit indices that are less sensitive to sample size (CFI and RMSEA) provided

no evidence of differences in model fit across groups (∆ CFI range: .001-.043, ∆ RMSEA range;

.000-.010). These difference statistics all well below the threshold established by Cheung and

Rensvold (2002). The most conservative invariance test (model 2, both paths fixed across

samples) demonstrated excellent fit (χ² = 4654, 56, df = 103, χ² /df = 23.94, p = .000, CFI = .932,

RMSEA = 0.02), indicating that there existed effectively no differences in how these latent

constructs co-varied across the samples. Other models provided similar evidence and

demonstrated slightly improved fit simply because fewer parameters were constrained to

equality.

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Insert Tables 6 and 7 about here __________________________

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Discussion

Hirschi (2004) distanced himself from the original conceptualization and subsequent

operationalization of self-control theory (Gottfredson & Hirschi, 1990) by noting that measures

of self-control in the literature combined both attitudinal and behavioral indicators. Although

Grasmick et al.’s (1993) scale is the most widely used, one of its criticisms is that it is not

consistent with the behavioral requirement Gottfredson and Hirschi have emphasized (Evans, et

al., 1997; Hirschi, 2004; Hirschi & Gottfredson, 1993, 1994, 1995, 2000; Junger, West, &

Timman, 2001; Marcus, 2003; 2004). Thus, Hirschi (2004) proposed a more “accurate” revised

measurement of self-control which includes elements a number of elements reminiscent of social

control theory. Given the modest number of studies that have tackled this issue and larger

question as well as the inconsistent evidence to date about the relative merit of Hirschi’s

reconceptualization, the current study juxtaposed the effects by Hirschi’s (2004) redefinition of

self-control and by Grasmick et al. (1993) self- control measure on adolescent deviance across

eleven different cultural contexts.

Key findings from the current study include that both scales were internally consistent

across the eleven samples from different cultural contexts, although there was some evidence

that Hirschi’s (2004) measure was less consistently reliable, particularly among Taiwanese

adolescents. Secondly, and consistent with previous research (e.g., Morris et al., 2011; Piquero &

Bouffard, 2007; Higgins, Wolfe, & Marcum, 2008; Ward, Gibson, Boman, & Leite, 2010), both

Hirschi’s self-control measure and Grasmick et al.’s instrument uniquely explained variance in

adolescent deviance across each of the eleven cultures. Next, when comparing whether these

measures were unique, redundant, or additive in their effects on deviance, the evidence supported

that they were both unique and additive in their effects. In fact, the Grasmick et al. (1993) scale

20

consistently explained more variance (range: 24.3% to 46.9%) in deviance in comparison to

Hirschi’s (2004) self-control measure (range: 6.2% - 19.3%). This is consistent with some

previous work, including the study by Piquero and Bouffard (2007), yet different from what

Morris et al., (2011) found, namely a similar effect size in explaining adult offending, something

also echoed by Tittle, Ward and Grasmick (2003). Ward, Gibson, Boman and Leite (2010)

compared Marcus’ (2003) Retrospective Behavioral Self-Control Scale (RBS) and the Grasmick

et al. (1993) self-control measure and found that the modified RBS and original RBS had greater

explanatory power than the Grasmick et al.(1993) scale.

Finally, and perhaps most importantly, beyond comparing variance estimates, rigorous

SEM multi-group tests of the two key links between self-control measures and deviance

provided no evidence of contextual or cultural differences in the extent to which the measures

were associated. This is perhaps the most profound piece of evidence because of its implications

for the generalizability of the relationships between self-control and deviance, of the findings,

but also because they are so consistent with one of the key tenets of self-control theory as

originally specified by Gottfredson and Hirschi (1990).

Although certainly beyond the scope of the current effort which largely focused on a core

theoretical and measurement issue proposed by Hirschi (2004) following a wealth of empirical

evidence supporting the original theoretical work by Gottfredson and Hirschi (1990), a few

concluding comments related to the current status of the theory seem warranted. As we argue and

illustrate in greater detail elsewhere (Vazsonyi, Roberts, & Huang, 2014), perhaps one of the

most salient issues, both theoretically and methodologically, are the extent to which biology was

both acknowledged originally and incorporated subsequently into scholarship testing self-control

theory. We find that Gottfredson and Hirschi in fact acknowledged the salience of individual

21

differences in self-control and its developmental course, but that they focused on socialization

effects, largely related to our ability to influence the same. Piquero, Jennings, and Farrington

(2009) have since provided ample evidence that in fact self-control is malleable, despite strong

evidence that self-control and its development are biologically informed (Beaver, Ratchford, &

Ferguson, 2009; Boisvert et al., 2013; Vazsonyi & Huang, 2010). Delisi (2013) has so aptly

argued that the importance of self-control is a today a transdisciplinary phenomenon. One might

disagree on the extent to which self-control theory has been instrumental in this development as

scholars tend to operate in an insular fashion, rarely acknowledging ideas, predictions or

evidence from outside their discipline or subdiscipline. We find it has been pivotal and in fact

shaped so much of what we know, discuss, and test today since its publication a quarter century

ago. This includes initial critics of the theory who today embrace self-control, embrace it in no

uncertain terms based on extensive empirical evidence spanning decades, including biological

informed evidence – “self-control will provide essential for humanity’s long-term health, wealth,

safety, and happiness” (Moffitt, Poulton & Caspi, 2013, p. 359). Of course the same can be said

for a number of competing theoretical frameworks in criminology that have emerged over the

past two decades, which have consistently sought to incorporate self-control, self-control theory

or the general approach of a General Theory, but also about work from other disciplines,

including education and psychology or developmental sciences. On this latter issue, the original

theoretical work on the development of self-control was in fact consistent with human

developmental theory, with developmental sciences. In a characteristically understated manner,

Gottfredson (2006) so aptly notes:

If theories may be judged by how much research they stimulate, control theory is doing exceptionally well. If theories may be judged by their consistency with the facts, control theory is doing exceptionally well. And if theories may be judged by the frequency with which other perspectives seek to incorporate them, control

22

theory is, perhaps, without peer (p. 96).

Limitations

Despite its many strengths, the current study also contains an inherent number of

limitations. First, Hirschi’s measure was a very close approximation to what he originally

proposed, but not identical, and thus, one threat to the current conclusions is that perhaps using

all the items verbatim as proposed by Hirschi might slightly alter or change the study findings.

Second, additional work should also include other operationalizations of self-control as well as

deviance when examining the core issue addressed in the current work, to provide more

extensive and comprehensive tests of the idea. Third, the samples were convenience samples of

adolescents in each of the respective cultures, and thus, they cannot be considered truly

representative of their culture as youth who do not attend school were omitted, for example.

Finally, related to the method of assessment, it relied exclusively on adolescent self-reports, and

although challenging to address, future work might also incorporate additional sources of data to

eliminate potential method variance. It is also important to note that previous work has shown

how different data sources impact the observed relationships between self-control and deviance,

for instance (e.g., Boman & Gibson, 2011; Meldrum et al., 2013).

23

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29

Notes:

1 A number of studies have examine the psychometric properties of the Grasmick et al. (1993)

measure as well as its usefulness and support for males and females (e.g., Gibson et al., 2010;

Higgins, 2007; Delisi et al., 2003; Piquero et al., 2000; Vazsonyi et al., 2001, 2004; Williams et

al., 2007;).

30

Figure 1. Self-Control Predicting Deviance

Note: = The direct path from Hirschi’s self-control measure to deviance and b = the direct path from Grasmick et al.’s low self- control measure to deviance.

Deviance

Hirschi’s Self-Control

Grasmick et al.’s Low Self-Control

a

b

Parcel 1 Parcel 2

Parcel 1 Parcel 2

Parcel 1 Parcel 2

31

Table 1 Studies testing Hirschi’s reconceptualized self-control

Study N Mage

Measurement Key Findings

Piquero and Bouffard (2007) N = 212

Mage = 20.6

1. Hirschi’s redefined self-control

(self-generated inhibitions) 2. Grasmick et al. (1993)

Only Hirschi’s measure remained significant for drunk driving (both sexes) and sexual coercion (males only).

Higgins et al. (2008) N = 358

Mage = 21

1. Self-generated inhibitions (Piquero and Bouffard measure) 2. Bonding self-control measure (Hirschi measure) 3. Grasmick et al. (1993)

All three measures showed modest predictability for digital piracy.

Morris et al. (2011) N = 1,139

Mage = 36-44

1. Hirschi’s redefined self-control 2. Grasmick et al. (1993) attitudinal

self-control measure

Similar effects of predicting adult offending was found from both measures.

Bouffard and Rice (2011) N = 311

Mage = 20.8

1. Hirschi’s redefined self-control (modified Piquero and Bouffard ) 2. Social bonding measure

Hirschi’s measure was a significant predictor of drunk driving. Social bonds were shown to operate through self-control alone.

Gunter and Bakken (2012) N = 1,458

Mage = 20.2

1. Hirschi’s redefined self-control (replication of Piquero and

Bouffard) 2. Grasmick et al. (1993)

Only the Grasmick et al. (1993) measure remained significant for drunk driving and cheating on an exam.

Ward et al. (2012) N = 2,243

Mage = 15.4 1. Hirschi’s redefined self-control 2. Social bonding measure

Hirschi’s redefined self-control was a significant predictor of marijuana use. Social bonds had a 45% effect on self-control at predicting marijuana use.

Rocque, Posick and

Zimmerman (2013)

N = 2,400

Mage = 12-14

1. Grasmick et al. (1993) attitudinal self-control measure

2. Hirschi (2004) self-control measure

Both self-control measures both have similar measurement properties (item fit statistics, unidimensinality, reliability). Both scales are significantly related to deviant behaviors (violence, property crime, and alcohol consumption).

32

Table 2 Descriptive of Age, Sex, Family Structure, and SES by Country

China n =1,373

Czech Republic n = 890

Hungary n = 871

Japan

n = 355

Netherlands

n = 1,315

Slovenia n = 1,422

Spain

n = 1,030

Switzerland n = 4,018

Taiwan

n = 1,443

Turkey

n = 1,447

USA

n = 2,213

Age (M) 13.25 17.97 16.56 20.10 16.12 16.75 18.30 18.23 16.48 16.53 16.36

Sex

Male 47.8 56.4 67.3 33.5 46.6 35.8 34.7 62.0 57.7 43.2 49.4

Female 52.2 43.6 31.1 66.5 53.1 62.9 64.8 37.0 42.3 56.1 49.3

Family Structure

Traditional 83.0 60.4 79.7 30.7 86.3 75.7 82.3 81.7 80.7 90.7 65.0

Non-traditional 17.0 39.6 19.9 61.4 12.5 24.2 17.6 17.8 19.1 8.7 33.3

SES

Laborer 14.1 0 10.1 37.4 0.7 1.4 4.9 1.6 2.9 8.4 14.0

Semi-skilled 47.3 9.0 19.1 20.6 2.5 14.1 17.5 3.4 25.7 9.4 15.3

Clerical 24.7 5.8 21.4 24.6 10.6 17.1 15.7 11.9 22.6 29.3 10.4

Semi-Prof. 9.1 26.0 13.4 10.6 24.6 28.8 8.1 31.9 7.9 23.3 10.6

Professional 4.7 38.5 25.6 3.7 32.8 29.5 32.9 35.1 16.1 21.1 29.4

Executive 0.2 18.2 10.3 3.1 16.0 9.0 21.0 16.1 24.8 8.5 20.2

33

Table 3 Hirschi (2004) Self-Control Conceptualization versus Current Study

Hirschi (2004)

Current Study

1. Do you like or dislike school. (Like it)

I like school. A = strongly disagree, B = disagree, C = agree, D = strongly agree Coding (0/1): A and B = 0; C and D = 1

2. How important is getting good grades to your personally? (very important)

Getting good grades is important to me. A = strongly disagree, B = disagree, C = agree, D = strongly agree Coding (0/1): A and B = 0; C and D = 1

3. Do you finish your homework? (Always)

I finish my homework. A = strongly disagree, B = disagree, C = agree, D = strongly agree Coding (0/1): A and B = 0; C and D = 1

4. Do you care what teachers think of you? (I care a lot).

N/A

5. It is none of the school’s business if a student wants to smoke outside of the classroom? (strongly disagree).

N/A

6. Does your mother know who you are with when you are away from home (usually)

In my free time away from home, my mother knows who I’m with and where I am. A = strongly disagree, B = disagree, C = neither disagree nor agree, D = agree, E = Strongly agree Coding (0/1): A, B, C = 0; D and E = 1

7. Does your mother know where you are when you are away from home (usually)

My mother wants me to tell her where I am if I don’t come home right after school. A = strongly disagree, B = disagree, C = neither disagree nor agree, D = agree, E = strongly agree Coding (0/1): A, B, C = 0; D and E = 1

8. Do you share your thoughts and feelings with your mothers (often)

How often do you talk to your mother about the boy/girl whom you like very much. How often do you talk to your mother about questions or problems about sex. How often do you talk to your mother about other things that are important to you How often do you talk to your mother about things you have done about which you feel guilty How often do you talk to your mother about major personal decision. A = never, B = occasionally, C = sometimes, D = often, E = very often Coding (0/1): A B, C = 0; D and E = 1

9. Would you like to be the kind of person your mother is (In every way, In most ways).

N/A

34

Table 4 Scale and Parcel Descriptive Statistics

China n=1,373

Czech Republic n=890

Hungary n = 871

Japan n = 355

Netherlands n = 1,315

M/SD α M/SD α M/SD α M/SD α M/SD α

Grasmick LSC

2.72/0.56

0.91 2.66/0.64 0.93

2.78/0.3

0.80

2.65/0.35

0.70

2.82/0.40 0.77

Parcel 1 2.71/0.69 2.86/0.77 2.83/0.54 2.62/0.45 2.94/0.54 Parcel 2 2.63/0.69 2.76/0.75 2.75/0.49 2.44/0.48 2.71/0.53

Hirschi’s SC

0.40/0.20

0.58 0.40/0.25 0.78

0.51/0.22

0.65

0.44/0.22

0.65

0.47/0.22 0.63

Parcel 1 2.33/1.18 1.71/0.79 2.88/1.28 1.90/1.26 2.84/1.18 Parcel 2 1.58/1.08 2.12/0.79 1.92/1.24 2.45/1.16 1.80/1.24

Deviance

1.50/0.71

0 .98 1.88/.77 0.97

1.71/0.60

0.80

1.41/0.34

0.90

1.79/0.60 0.95

Parcel 1 1.46/0.72 2.28/1.42 1.60/0.60 1.24/0.31 1.67/0.62 Parcel 2 1.58/0.73 1.75/1.32 1.86/0.64 1.68/0.49 1.93/0.61

Notes. Grasmick LSC = Grasmick et al.’s low self-control measure; Hirschi SC = Hirschi’s self-control measure

35

Table 4 continued Scale and Parcel Descriptive Statistics

Slovenia n = 1,422

Spain

n = 1,030

Switzerland n = 4,018

Taiwan n = 1,443

Turkey

n = 1,447

USA n = 2,213

M/SD α M/SD α M/SD α M/SD α M/SD α M/SD α

Grasmick LSC 2.89/0.40 0.80 2.73/0.39 0.77 2.56/0.35 0.77 2.78/0.40 0.72 2.84/0.57 0.85 2.84/0.48 0.87

Parcel 1 2.91/0.73 2.74/0.48 2.51/0.45 2.93/0.47 2.78/0.68 2.81/1.26 Parcel 2 2.80/0.75 2.47/0.50 2.39/0.44 2.82/0.45 2.78/0.69 2.58/1.20

Hirschi’s SC

0.53/0.24

0.68

0.52/0.21

0.62

0.50/0.21

0.63

0.42/0.20

0.57

0.54/0.22

0.68

0.55/0.22

0.66

Parcel 1 3.06/1.33 3.01/1.19 2.15/1.23 2.35/1.17 3.06/1.24 3.31/0.61 Parcel 2 2.21/1.34 2.16/1.20 2.89/1.23 1.86/1.01 2.43/1.22 2.190/.60

Deviance

1.86/0.72

0.95

1.79/0.56

0.95

1.92/0.67

0.96

1.29/0.32

0.92

1.55/0.67

0.97

1.87/0.70

0.96

Parcel 1 1.71/0.58 1.59/0.54 1.86/0.69 1.21/0.30 1.49/0.68 1.71/0.66

Parcel 2 2.04/0.55 2.07/0.62 1.96/0.68 1.43/0.43 1.63/0.70 2.08/0.77


36

Table 5 Standardized Path Coefficients and Latent Construct Loadings by Country

China n = 1,373

Czech

Republic n = 890

Hungary n = 871

Japan

n = 355

Netherlands

n = 1,315

Slovenia n = 1,422

Spain

n = 1,030

Switzerlandn = 4,018

Taiwan

n = 1,443

Turkey

n = 1,447

USA

n = 2,213

Hirschi SC → Deviance ‒.062 ‒.137 ‒.208 ‒.062 ‒.189 ‒.227 ‒.193 ‒.235 ‒.131 ‒.170 ‒.189

Grasmick LSC→ Deviance .375 .243 .378 .375 .469 .326 .410 .389 .337 .392 .467

Hirschi SC Parcel 1 .463 1.08 .758 .463 .779 .927 .861 .649 .952 .796 .852

Hirschi SC Parcel 2 1.10 .568 .676 1.11 .625 .555 .561 .806 .502 .666 .622

Grasmick LSC Parcel 1 .807 .933 .835 .963 .872 .854 .886 .770 .815 .903 .882

Grasmick LSC Parcel 2 .788 .942 .846 .735 .854 .847 .805 .838 .817 .876 .885

Deviance Parcel 1 .963 .887 .926 .807 .950 .922 .933 .952 .867 .945 .953

Deviance Parcel 2 .735 .969 .904 .788 .875 .937 .888 .911 .851 .908 .905


37

Table 6 Model Fit Summary Statistics

χ² df χ²/df p CFI RMSEA

Model 1: Default 355.49 68 5.23 .000 .996 .012

Model 2: Paths ɑ and b 471.23 86 5.48 .000 .994 .013 Model 3: Path ɑ

399.89

77

5.19

.000

.995

.012

Model 4: Path b 432.75 77 5.62 .000 .995 .013

Note. Models 2 through 4: Multi-group model tests, paths constrained to equality.

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Table 7 Nested Model Comparison

Default vs. Model 2: Paths a and b

Default vs. Model 3: Path a

Default vs. Model 4: Path a

χ² 115.74 44.406 77.26

p .000 .000 .000

df 18 9 9

∆NFI .002 .001 .001

∆CFI .001 .000 .001

∆IFI .002 .001 .001

∆RFI 001 .000 .001

∆TLI .001 .000 .001

Note. Models 2 through 4: Multi-group model tests, paths constrained to equality.

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APPENDIX The Normative Deviance Scale (NDS) Please answer the next few questions in the following way: A = no/never, B = once, C = 2-3 times, D = 4-5 times, E = Always. Vandalism: Have you ever…. Smashed bottles on the street, school grounds, or other areas? Intentionally damaged or destroyed property belonging to your parents or other family members (e.g., brothers or sisters)? Intentionally damaged or destroyed property belonging to a school, college, or university? Intentionally damaged or destroyed other property (e.g., signs, windows, mailboxes, parking meter, etc.) that did not belong to you? Intentionally damaged or destroyed property belonging to your employer or at your workplace? Slashed or in any way damaged seats on a bus, in a movie theater, or something at another public place? Written graffiti on a bus, on school walls, on rest room walls, or on anything else in a public place? Committed acts of vandalism when coming or going to a football game or other sports events? Alcohol use: Have you ever ….. Consumed hard liquor (e.g., tequila, whiskey, vodka, or gin) before you were 16? Consumed alcoholic beverages (e.g., beer, wine, or wine coolers) before you were 16? Got drunk (intentionally) just for the fun of it (at any age)? Got drunk just to fit in and be part of the crowd (at any age)? Lied about your age to buy alcohol before you turned 16? Had an older brother/sister or friend buy alcohol for you? Bought alcohol for a brother/sister or friend? Drug use: Have you ever…. Used tobacco products regularly (e.g., cigarettes, chew, snuff, etc.)? Used “soft” drugs such as marijuana (grass, pot)? Used “hard” drugs such as crack, cocaine, or heroin? Gone to school when you were drunk or high on drugs? Gone to work when you were drunk or high on drugs? Gone to a concert when you were drunk or high on drugs? Gone to a club/dance/party when you were drunk or high on drugs? Gone to a club/dance/party to get drunk or high on drugs? Sold any drugs such as marijuana (grass, pot), cocaine, or heroin? School misconduct: Have you ever…. Cheated on school tests (e.g., cheat sheet, copy from neighbor, etc.)? Been sent out of a classroom because of “bad behavior (e.g., inappropriate behaviors, cheating, etc.)? Been suspended or expelled from school? Stayed away from school/classes when your parent(s) thought you were there? Intentionally missed classes more than a number of days for “no reason”, just for fun (e.g., there was no family emergency)? Been in trouble at school so that your parents received a phone call about it? Skipped school/work (pretending you were ill)?

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General deviance: Have you ever…. Intentionally disobeyed a stop sign or a red traffic light while driving a vehicle? Been on someone else’s property when you knew you were not supposed to be there? Failed to return extra change that you knew a cashier gave you by mistake? Tried to deceive a cashier to your advantage (e.g., flash a larger bill and give a smaller one)? Let the air out of the tires of a car or a bike? Lied about your age to get into a nightclub/bar? Made nuisance/obscene telephone calls? Avoided paying for something (e.g., movies, bus or subway rides, food, etc.)? Used fake money or other things in a candy, coke, or stamp machine? Shaken/hit a parked car just to turn on the car’s alarm? Stayed out all night without informing your parents about your whereabouts? Theft: Have you ever… Stolen, taken, or tried to take something worth 20 U.S dollar or less (e.g., newspaper, pack the gum, mail, money, etc.)? Stolen, taken, or tried to take something worth between 20-150 U.S dollar or less( e.g., shirt, watch, cologne, video game cartridge, shoes, money)? Stolen, taken, or tried to take something worth more than 150 U.S dollar (e.g., leather jacket, car stereo, bike, money, etc.)? Stolen, taken, or tried to take something that belonged to “the public” (e.g., street signs, construction signs, etc.)? Stolen or tried to steal a motor vehicle (e.g., car or motorcycle)? Bought, sold, or held stolen goods or tried to do any of these of things? Assault: Have you ever…. Hit or threatened to hit a person? Hit or threatened to hit your parent(s)? Hit or threatened to hit other students/peers or people? Used force or threatened to beat someone up if they didn’t give your money or something else you wanted? Been involved in gang fights or other gang activities? Beaten someone up so badly they required medical attention?

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Grasmick et al. (1993) Low Self-Control Measure Please answer the next few questions in the following way: A = strongly disagree, B = disagree, C = neither disagree nor agree, D = agree, E = strongly agree. Impulsivity

1. I often act on the spur of the moment without stopping to think 9. I often do whatever brings me pleasure here and now, even at the cost of some distant goal 13. I’ m more concerned with what happens to me in the short run than in the long run

Simple Tasks

5. I frequently try to avoid projects that I know will be difficult 7. I dislike really hard tasks that stretch my abilities 15. When things get complicated, I tend to quit or withdraw 19. The things in life that are easiest to do bring me the most pleasure

Risk seeking

3. I like to test myself every now and then by doing something a little risky 4. Sometimes I will take a risk just for the fun of it 1. I sometimes find it exciting to do things for which I might get in trouble 11. Excitement and adventure are more important to me than security

Physical activities 8. If I had a choice, I would almost rather do something physical than something mental 10. I almost always feel better when I am on the move than when I am sitting and thinking 16. I like to get out and do things more than I like to read or contemplate ideas 18. I seem to have more energy and a greater need for activity than most other people my age

Self-Centeredness

12. I try to look out for myself first, even if it means making things difficult for other people 14. I will try to get the things I want even when I know it’s causing problems for other people 17. I’m not very sympathetic to other people when they are having problems

Temper

21. I lose my temper pretty easily 22. Often, when I’m angry at people I feel more like hurting them talking to them about why I am angry 23. When I’ m really angry, other people better stay away from me 24. When I have a serious disagreement with someone, its usually hard for me to talk calmly about it without getting upset.

Hirschi’s reconceptualization of self-control: Is truth truly the daughter of time? Evidence from eleven cultures

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