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Justice Quarterly

ISSN: 0741-8825 (Print) 1745-9109 (Online) Journal homepage: http://www.tandfonline.com/loi/rjqy20

“No Remorse, No Repent”: Linking Lack of Remorse to Criminal Offending in a Sample of Serious Adolescent Offenders

Alex R. Piquero

To cite this article: Alex R. Piquero (2016): “No Remorse, No Repent”: Linking Lack of Remorse to Criminal Offending in a Sample of Serious Adolescent Offenders, Justice Quarterly, DOI: 10.1080/07418825.2016.1185530

To link to this article: http://dx.doi.org/10.1080/07418825.2016.1185530

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“No Remorse, No Repent”: Linking Lack of Remorse to Criminal Offending in a Sample of Serious Adolescent Offenders

Alex R. Piquero

Linking emotions to offender decision-making has only recently become of theoretical interest to criminologists, but empirical work in this area has not kept pace nor has such research examined the role of emotions to offending in offender-based samples. Recently, Warr outlined regret as one such emotion that may be useful in thinking about offending. Specifically, he argued that regret may be related to discontinuity in offending, or con- versely that a lack of remorse may be related to continuity in offending. This paper uses data from a sample of serious adolescent offenders followed for seven years to investigate this hypothesis. Results provide support for Warr’s hypothesis that remorse-resistant adolescents incur a higher number of re-arrests, while remorse-prone adolescents incur fewer re-arrests, even after controlling for other relevant risk factors.

Keywords remorse; regret; offending; adolescent offenders

Introduction

-“Remorse, the fatal egg that pleasure laid.” -“Remorse begets reform.” -William Cowper

Alex R. Piquero is Ashbel Smith Professor of Criminology and Associate Dean for Graduate Programs in the School of Economic, Political and Policy Sciences at the University of Texas at Dallas; adjunct professor at the Key Center for Ethics, Law, Justice, and Governance, Griffith University Australia; and faculty affiliate with the Center for Violence and Injury Prevention, George Warren Brown School of Social Work, Washington University in St. Louis. He has received several research, teaching, and mentoring awards and is a fellow of both the American Society of Criminology and the Academy of Criminal Justice Sciences. In 2014, he received the University of Texas System Regents’ Outstanding Teaching Award. Correspondence to: Alex R. Piquero, University of Texas at Dallas, Program in Criminology, 800 W. Campbell Rd., GR31, Richardson, TX, 75080-3021, USA. E-mail: [email protected]

� 2016 Academy of Criminal Justice Sciences

Justice Quarterly, 2016 http://dx.doi.org/10.1080/07418825.2016.1185530

The role of emotions has long occupied an important place in the social sciences (Collins, 1990; Kahneman, 2011; Massey, 2002; Tangney, Stuewig, &

Mashek, 2007), but emotions have not received as extensive empirical attention in criminology (Karstedt, Loader, & Strang, 2011) or criminal justice

(Sherman, 2003).1 To be sure, although there have been several important examples of how various emotions (especially anger, shame, and guilt) have been integrated into certain criminological theories, primarily general strain

(Agnew, 1992), reintegrative shaming (Braithwaite, 1989), rational choice (Bouffard, Exum, & Paternoster, 2000; Grasmick & Bursik, 1990; Katz, 1988),

and defiance (Rice, Dirks, & Exline, 2009; Sherman, 1993), “emotional processes have not been central to criminological theorizing” (Giordano,

Schroeder, & Cernkovich, 2007, pp. 1603–1604).2 That is, until recently. In a timely and influential article, Warr (in press) proposed that criminol-

ogy’s understanding of criminal decision-making in general and continuity/ desistance from offending in particular would be strengthened by incorporating

the notion of regret into its theoretical and especially empirical research. Informed by the work of several social scientists outside of criminology (see e.g. Landman, 1993, p. 47, 1987), Warr (in press, p. 2) construes regret as the

“outcomes of choices—the path taken versus the one(s) not taken” and a key hallmark of regret is a “desire for undoing” (p. 3, emphasis in original) or self-

blame (p. 4). And while Warr (in press, p. 3) takes great care to differentiate regret from similar (and more often studied) emotions, especially disappoint-

ment, sadness, shame, and guilt (see also Tangney, 1991), he does acknowl- edge regret’s close affiliation with remorse, which results when one recognizes

that they are responsible for harming another individual (see also Proeve & Tudor, 2010, pp. 32–33); that is, the offender acknowledges “personal culpa- bility” (Warr, in press, p. 4).3 Applied to the study of crime, then, an offender

1. Sherman’s (2003) Presidential Address to the American Society of Criminology advanced a new paradigm of sorts that would focus on “the explicit recognition and management of the effects of emotions in causing the behavior of both officials and offenders” (p. 2). 2. Although not as explicit, Gottfredson and Hirschi’s (1990) general theory of crime also incorpo- rates some emotions into the decision-making process (see also Piquero, Gomez-Smith, & Langton, 2004), while psychologically-based theories have focused on hostile attribution bias, which cer- tainly incorporates emotions in the decision-making process (see Lochman & Dodge, 1994). 3. Warr (in press, p. 5) further notes that “Genuine regret reveals a change of heart, from offen- der to desister.” Some psychologists have further considered the inter-relationships between shame, guilt, and remorse, noting that guilt may be a more useful “umbrella term, subsuming ‘remorse’” (Tangney, Stuewig, & Hafez, 2011a, p. 706), while at the same time taking more care to distinguish between shame and guilt. For Tangney and her colleagues (2011b, p. 712), there are two ways that individuals may feel bad about their transgressions, one (guilt) is more adaptive than the other (shame). It would not be a stretch to expect Warr to hold to the idea that regret/ remorse is more adaptive than it would be dysfunctional.

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is remorseful when s/he realizes that they are responsible for the harm and they internalize this deep emotion.4 In other words, remorse is “deep regret”

(Warr, in press, p. 4) and should, in turn, lead to less offending. The converse, of course, would also be true, as a lack of remorse would entail an offender

not caring about their actions and the harms caused to others as a result of their actions. This emotion would be expected to lead to continued (or increased) offending. As Warr (in press, p. 4) surmises “… remorse may be

more relevant than regret in general when it comes to understanding criminal behavior.”5

Conceptual Overlap of Remorse & Regret to Other Psychological Constructs

For many years, the American Psychological Association’s (APA) Diagnostic and

Statistical Manual of Mental Disorders had the lack of remorse (or being indif- ferent to harming others), as one of the key features of antisocial personality

disorder (Warr, in press, p. 8). Not surprisingly, then, measuring and studying the lack of remorse has been most common among psychologists, as evidenced

by the incorporation of a lack of remorse into various versions of the Psychopa- thy Checklist (Forth, Kosson, & Hare, 2003) and Youth Psychopathy Inventory

(YPI) (Andershed, Kerr, Stattin, & Levander, 2002) (although the APA has moved away from using the term psychopath). As well, several meta-analyses

reveal at least a moderate relationship of psychopathy to antisocial behavior, delinquency, and recidivism (see Asscher et al., 2011; Leistico, Salekin, DeCoster, & Rogers, 2008), with recent studies highlighting the relevance of

specific psychopathic traits in distinguishing between distinct offending trajec- tories above and beyond common risk factors (see Corrado, McCuish, Hart, &

DeLisi, 2015).6

As can be seen, remorse and regret occupy conceptual overlap with other

individual characteristics, such as psychopathy and in particular callous/ unemotional (CU) traits that have been studied in psychology. CU traits, which

include shallow affect, callousness, and lack of empathy/remorse, are broadly

4. For example, King’s (2013) qualitative study of desistance narratives among twenty individuals under probation supervision in England revealed a strong sentiment for the impact of the offen- der’s actions on victims and significant others; as one offender put it: “I felt very remorseful for the people that I caused injuries to” (p. 155). 5. In the restorative justice literature, Ahmed, Harris, Braithwaite, and Braithwaite (2001) have highlighted the role of shame acknowledgement as an inhibitor of subsequent offending. The over- lap between remorse and shame acknowledgement is an important one, and will be further dis- cussed in the discussion section regarding policy implications. 6. Specifically, the four and three factor model of the PCL:YV was associated with the most chronic and serious offending trajectory, as were the lifestyle and antisocial factors, but the inter- personal and affective factors did not predict membership in the high-rate chronic group (Corrado et al., 2015, p. 357).

REMORSE AND OFFENDING 3

considered to be affective features of psychopathy (Kahn, Byrd, & Pardini, 2013, p. 1; see also Hart & Hare, 1996) and have been found to be predictive

of offending, especially violence (see Porter & Woodworth, 2006).7 In that regard, then, Warr’s conceptualization of regret can be construed as a specific

aspect of CU traits, broadly speaking. Links between CU traits, antisocial disor- der, and criminal offending have often been made in a range of studies using a wide array of CU measures (see Frick & White, 2008), and a few relevant stud-

ies are highlighted here. Pardini and Fite (2011) used community data from the Pittsburgh Youth

Study that examined a large CU measure, of which an item indicating remorse was included.8 After finding that their CU scale evinced good stability over

twelve months with respect to the affective features of psychopathy, they found that CU traits positively and significantly predicted moderate/serious

violence, while CU traits were associated with lower anxiety/depression over time. Pardini, Stepp, Hipwell, Stouthamer-Loeber, and Loeber (2012) examined

CU in a community sample of young girls and found that their proposed CU subtype of conduct disorder identified young girls who exhibited lower anxiety problems with more severe aggression, CD symptoms, academic problems and

global impairment across time than girls with CD alone. In short, CU traits aided in the prediction of adverse problems. Kahn et al. (2013) use data from

the early adulthood follow-up interviews with subjects in the Pittsburgh Youth Study (PYS) to examine the extent to which CU traits predicted future official

arrest records above and beyond more common risk factors. Their measure of CU traits was expansive, including 24 items, and also contained items related

to what they term as “deficient guilt/remorse”.9 Their findings showed that

7. Pardini and Byrd (2013) recently provided an overview of the psychopathy literature. Of rele- vance to the current study, these authors noted that the affective features of psychopathy are commonly referred to as CU traits, and remorse is an affective component within both CU and psy- chopathy (the latter which is more expansive than CU). The affective component includes “experi- encing affective discomfort following wrongdoing (i.e. guilt) and having empathic concern for the well-being of others [citations omitted], which are core characteristics of CU traits” (Pardini & Byrd, 2013, p. 64). They also pointed out that there was a solid base of longitudinal research docu- menting the stability of psychopathic features in children and adolescents (Frick, Cornell, Barry, Bodin, & Dane, 2003; Obradović, Pardini, Long, & Loeber, 2007). 8. Specifically, the remorse item was: “When he does something wrong, does he feel bad about it?”. 9. For example, “I am concerned about the feelings of others” and “I feel bad or guilty when I do something wrong”. It is also worth noting that aside from the conceptual overlap between remorse, regret, psychopathy, and CU traits, basic definitions also point to quite a bit of common ground. According to Webster’s Dictionary, shame is defined as a feeling of guilt, regret, or sadness that you have because you know you have done something wrong; guilt is defined as a bad feeling caused by knowing or thinking that you have done something bad or wrong; regret is defined as to feel sad or sorry about (something that you did or did not do); remorse is defined as a feeling of being sorry for doing something bad or wrong in the past/a feeling of guilt. In short, there is quite a bit of both conceptual and definitional overlap among these individual characteristics (see Tangney, Miller, Flicker, & Barlow, 1996).

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men with elevated CU traits had a greater number of arrests and criminal charges and were more likely to be charged with a serious offense.

Prior Empirical Research

Unfortunately, the empirical research in criminology focusing on regret/ remorse has been virtually absent, largely because of the recency of Warr’s

regret framework. Some studies that indirectly assess remorse/regret are worth noting.

In a cross-sectional study of tax evaders, Murphy and Harris (2007) examined the extent to which feelings of shame mediated the link between shaming

practices and offending (within the context of tax non-compliance). Aside from finding support for Braithwaite’s (1989) hypothesis that disintegrative shaming was associated with higher reoffending, the authors also found that “desire to

put matters right” was an important inhibitor of reoffending.10 Tangney et al. (2011b) investigated the reliability and validity of the Test of Self Conscious

Affect-Socially Deviant Version (TOSCA-SD) as a measure of proneness to shame and proneness to guilt in a sample of jail inmates. Their analysis indicated that

proneness to shame and proneness to guilt were differentially related to vari- ous risk measures, including in particular antisocial personality as measured

through the Psychopathy Checklist. In line with Tangney and colleagues’ expec- tations, results showed that guilt-proneness was a protective factor while

shame-proneness was not. For example, while guilt-proneness was significantly and negatively related to psychopathy and antisocial personality disorder, it was positively related to self-control, whereas shame-proneness was positively

and significantly related to antisocial personality disorder and negatively and significantly related to self-control.

Hosser, Windzio, and Greve’s (2008) longitudinal, event-history analysis of young offenders in Germany also revealed that feelings of guilt at the begin-

ning of the inmate’s prison term were associated with lower recidivism, while feelings of shame were related to higher rates of recidivism. In a longitudinal

study of jail inmates, Tangney, Stuewig, and Martinez (2014) examined the extent to which shame- and guilt-proneness predicted re-offending in the first- year post-release. Results showed that while guilt-proneness was negatively

related to re-offending, shame-proneness was not. Additional mediational anal- yses however, showed that externalization of blame mediated the link

10. Specifically, “desire to put matters right” was measured with an item “Felt concerned to put matters right and put it behind me.” As well, Murphy and Harris incorporated several measures associated with shame acknowledgement and shame displacement in their analysis. Within the shame acknowledgement construct in particular, two items (“Felt what I’d done was wrong” and “Felt regret”) would be consistent with Warr’s notion of regret/remorse. Yet, while more shame acknowledgement was associated with a higher “desire to put matters right”, it was not related to re-offending (p. 909).

REMORSE AND OFFENDING 5

between shame-proneness and recidivism, with shame being positively related to externalization of blame (which itself was positively related to recidivism)

and negatively and significantly related to recidivism (see especially, Figure 2, p. 802).11 And most recently, Stuewig et al. (2015, p. 217) found a relationship

between guilt-proneness among fifth graders and fewer sexual partners, less illegal drug and alcohol use, and less involvement with the criminal justice sys- tem at ages 18–21, but adverse long-term effects of shame-proneness for later

deviant behavior, unprotected sex, and illegal drug use.12

In two closely related studies, Spice (2013; see also Spice, Vilojean, Douglas,

& Hart, 2015) examined the relationships between remorse, psychopathology, psychopathic characteristics and self-reported re-offending in a small sample

of adolescent offenders followed for six months. Although several important findings emerged from his work, the ones most relevant to the current analyses

focus on remorse, which was measured using items from the Psychopathy Checklist: Youth Version (PCL:YV), the Structured Assessment of Violence Risk

in Youth (SAVRY), and the Youth Level of Service/Case Management Inventory (YLS/CMI). First, at the bivariate level, Spice found that the PCL:YV’s “lack of remorse” item as well as the SAVRY’s “low empathy/remorse” item were posi-

tively and significantly associated with total self-reported re-offending at both the three- and six-month follow-ups,13 but the YLS/CMI item “inadequate guilt

feelings” was not related to total offending.14 Second, his results showed that guilt was negatively related to re-offending and that it provided additional

explanatory power over remorse, which was still significant, when predicting self-reported re-offending.

In the second study, Spice et al. (2015) examined the inter-relationships between the over-lapping constructs of remorse, psychopathology, and psy- chopathy in a sample of 97 adolescents on probation aged 12–17. These

authors made the important observation that there is “no well-articulated and consistent definition of [remorse]” (p. 1), and as a consequence there have

been many different conceptualizations and operationalizations of the

11. As Tangney et al. (2014, p. 799, emphasis added) observe: “When people feel guilt about a specific behavior, they experience tension, remorse, and regret. Research has shown that this sense of tension and regret typically motivates reparative action—confessing, apologizing, or somehow repairing the damage done [citations omitted]” and this is especially the case when the feelings arise over the “bad things done” (Stuewig et al., 2015, p. 218). 12. Stuewig and McCloskey (2005) examined the link between shame- and guilt-proneness to depression and delinquency and found that shame-proneness in childhood was significantly associ- ated with higher depression in a two-year follow-up, whereas guilt-proneness was linked to signifi- cantly less delinquency and (marginally significantly) to less depression. They also found that harsh parenting in childhood was associated with higher shame-proneness but lower guilt-proneness. 13. An anonymous reviewer correctly pointed out that these are single items of a broader mea- sure. 14. The one-item measure of remorse could be viewed as weak from a psychometric perspective.

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construct. Due to this lack of consensus, these authors considered the topic of remorse within the context of the guilt and shame frameworks, which they

argued “aligns with the typical usage of remorse in forensic contexts (e.g. Frick & Hare, 2001)” (p. 1). This is so because “remorse is treated as being

similar to guilt (Forth et al., 2003) or as an unpleasant emotion after a misdeed (Frick & Hare, 2001)” (p. 2).

Their analyses revealed that shame was positively associated with numerous

mental health difficulties, while guilt was negatively associated with anger, depression, and anxiety (p. 6). More detailed analysis looking at the affective

component of the PCL:YV (which includes lack of remorse), indicated that the measure was negatively and significantly related to two different guilt scales,

and negatively but not significantly related to two different shame scales. The relationship of the affective subscale remained virtually the same when the

lack of remorse item was removed as well. In short, their analysis indicated that shame was positively related to psychopathy whereas guilt was negatively

related to psychopathy. As well, shame was related to several mental health problems (such as depression, anxiety, suicide ideation, and somatic com- plaints), while guilt was negatively related to anger, depression, and anxiety.

In short, shame is counter-productive and guilt is associated with not only acceptance of responsibility and constructive intentions (Tangney & Dearing,

2002), but guilt-prone individuals are less likely to react with anger and also aggression (Tangney et al., 1996; Spice et al., 2015, p. 9). Thus, much like

guilt, remorse can be a positive emotion/characteristic that leads to lower offending.

Limitations of Prior Research

Although the two studies from Spice and his colleagues are important contribu-

tions to the literature, several limitations constrain generalizaibility. For example, the studies were cross-sectional in nature, focused only on offending

in the adolescent period, and contained less than a hundred cases. It is impor- tant, therefore, to extend these works to a larger sample, in a longitudinal

manner, and cover the important transition between mid-adolescence and early adulthood when some offenders desist but others persist (cf. Loeber &

Farrington, 2012). As well, Kahn and her colleagues (2013) observed more gen- erally that research in the area of CU traits has been limited by its neglect of

investigation among adult samples, failure to control for common risk factors, lack of longitudinal analysis, and primary focus on community samples to the neglect of analyses within detained/incarcerated populations. This latter fea-

ture is especially important because high rates of offending as well as the lack-of-remorse and related characteristics (especially psychopathy) are not

sufficiently prevalent in normative samples (cf. Corrado et al., 2015), thereby

REMORSE AND OFFENDING 7

supporting the need to study these relationships among offender-based samples in order to assess generalizability of study findings. The current study

overcomes these limitations.

Current Study

Theoretical and empirical research on emotions has been an important focus in

psychology and sociology, but commensurate attention to emotions and their linkage to antisocial behavior within criminology has not kept pace. Recently,

Warr (in press) opened up a useful line of inquiry with his consideration of the emotion regret/remorse (or its antithesis, lack of remorse) as a potentially

importantly emotion for understanding desistance (or its antithesis, continuity) from offending. In an effort to provide some preliminary empirical evidence on his hypothesis, this paper uses data from a longitudinal study of serious youth-

ful offenders to examine the relationship between the lack of remorse and offending. In so doing, this paper assesses Warr’s hypothesis that remorse

leads to lower offending, or inversely that the lack of remorse leads to higher offending. Importantly, the paper builds off the “exceptionally rare” empirical

research concerning the relationship between moral emotions and criminal behavior among criminal/incarcerated offenders (see Tangney et al., 2011b,

p. 713) and overcomes some of the limiting features of previous research, primarily small samples and short-term follow-ups.

Data

Participants in the Pathways Study were adolescents who were found guilty of a serious offense (almost entirely felony offenses) in the juvenile or adult

court systems in Maricopa County, AZ or Philadelphia County, PA (see e.g. Piquero, Cardwell, Piquero, Jennings, & Reingle Gonzalez, 2016; Schubert

et al., 2004).15 These youth were ages 14 through 17 at the time of the study index petition (or juvenile court referral) (M = 16.2). A total of 1,354 adoles- cents were enrolled into the study, representing approximately one in three

adolescents adjudicated on the enumerated charges in each locale during the

15. Specifically, the committing offenses included: 41% for violent crimes against persons (e.g. murder, rape, robbery, assault), 26% for property crimes (e.g. arson, burglary, receiving stolen property), 10% for weapons, 4% for sex crimes, and 4% for other crimes (e.g. conspiracy, intimida- tion of a witness).

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recruitment period (November, 2000 through January, 2003).16 The study sam- ple is comprised mainly of non-White (41% Black, 34% Hispanic) males (86%),

who were, on average, 14.9 years old at the age of their first petition, with an average of three petitions prior to the baseline interview. Study participants

completed a baseline interview at the time of enrollment followed by inter- views every six months for the first three years of the study and annually thereafter through seven years. Sample retention for the Pathways Study was

high at each follow-up, averaging 90% across all interview waves. Information regarding the rationale and overall design of the study can be found in both

Mulvey et al. (2004) and Schubert et al. (2004) as well as the study website http://www.pathwaysstudy.pitt.edu/.

Variables

Dependent Variable (Frequency of Re-arrests)

An indicator of the total number of re-arrests by the 84-month follow-up per- iod is derived from official records. Information on arrests before the age of

18 were based on petitions to juvenile court recorded in each county, while arrests after age 18 were based on a combination of the county court record information and Federal Bureau of Investigation (FBI) arrest records (see

Piquero, Schubert, & Brame, 2014; Schubert, Mulvey, & Glasheen, 2011). Probation violations were not counted as rearrests, as they do not necessarily

represent a new criminal act (Schubert et al., 2011, p. 928). By the 84-month follow-up, over two-thirds of the Pathways youth were re-arrested (73.4%),

with an average number of re-arrests of 3.25 (SD = 3.35, Range 0–24).

16. Schubert et al. (2004, pp. 247–250) provided a detailed comparison of the enrolled cases com- pared to the non-enrolled cases that went through the courts during the enrollment period. Because of space constraints, it is noted here that comparisons between the adjudicated-but-not- enrolled cases versus the enrolled cases revealed only slight differences. For example, the enrolled group was slightly younger (15.9 vs. 16.1), had a slightly higher number of prior petitions (2.1 vs. 1.5), were younger at first prior petition (13.9 vs. 14.2), were less likely to be male (86% vs. 91%, due to the fact that very few females met all of the criteria for inclusion during the enrollment period in both locales), were more likely to be white (25% vs. 20%, though no other race/ethnicity differences emerged), and were less likely to be adjudicated with later case dismissal at the time of disposition at adjudication (1% vs. 2%). In all, based on the many similarities and few substantive differences across groups, as well as qualitative information gleaned from the Pathways to Desis- tance Working Group with project staff as well as personnel in both locales, there is a high degree of confidence that the enrolled group is representative of the types of cases that were being pro- cessed during the enrollment period and that met the study eligibility criteria.

REMORSE AND OFFENDING 9

Independent variables

Lack of Remorse

There are a variety of different measures used (primarily) in psychology that

measure remorse, but it is also the case that there is little consensus regard- ing the concept’s definition and the ideal method with which to measure it (Proeve & Tudor, 2010). The current study used a five-item subscale to mea-

sure lack of remorse that was assessed as part of the Youth Psychopathic Traits Inventory (YPI) containing the following questions: (1) I have the ability

not to feel guilt and regret about things that I think other people would feel guilty about; (2) I seldom regret things I do, even if other people feel that

they are wrong; (3) When someone finds out about something that I’ve done wrong, I feel more angry than guilty; (4) To feel guilty and remorseful about

things you have done that have hurt other people is a sign of weakness; and (5) To feel guilt and regret when you have done something wrong is a waste of time. Response options: (1) Does not apply at all, (2) Does not apply well,

(3) Applies fairly well, and (4) Applies very well. Higher scores indicate a lack of remorse (or remorse-resistant). This subscale was collected starting in the

first follow-up interview at 6-months and continuing at every interview there- after through the 84-month follow-up. As can be seen from Table 1, correla-

tions of the lack of remorse measure over time were, as expected, all positively and statistically significant and in the moderate range (3–.5; Cohen,

1988).17 The adjacent time periods, not surprisingly, evidenced the strongest correlations and the correlations did not diminish that greatly over time. As

well, a factor analysis of all ten assessments revealed a first factor with an eigenvalue of 4.08, with the next factor at .33. All factor loadings on the first factor were very strong, with nine of the ten loading at over .60 (and one at

.50). Cronbach’s alpha for each wave indicated good internal consistency: 6-months: α = .71, 12-months: α = .70, 18-months: α = .72, 24–months:

17. An anonymous reviewer correctly pointed out that there is variation among social scientists in how they interpret and describe the strength of correlations, especially with respect to the terms “moderate” or “strong”. For example, Hinkle, Wiersema, and Jurs (2003) suggest that correlations between .3 and .5 are low positive while correlations between .5 and .7 are moderate. On the other hand, Bergström, Forth, and Farrington (2015) recommend that correlations between .2 and .39 reflect moderate stability/strength, while correlations of .4 to .59 reflect high stability/ strength. Although correlations between earlier and later observations ebb over time (i.e. 6 to 84 months) as expected in longitudinal analysis, correlations in adjacent time periods are much stronger, ranging between .43 and .53.

10 PIQUERO

T a b le

1 D e sc ri p ti ve

st at is ti cs

an d co

rr e la ti o n m at ri x fo r la ck

o f re m o rs e .

re m

6m re m

12 m

re m

18 m

re m

24 m

re m

30 m

re m

36 m

re m

48 m

re m

60 m

re m

72 m

re m

84 m

re m

6m 1. 00

0

re m

12 m

.4 34

1. 00

0

re m

18 m

.3 81

.4 68

1. 00

0

re m

24 m

.3 30

.4 17

.5 20

1. 00

0

re m

30 m

.3 69

.3 97

.4 65

.5 10

1. 00

0

re m

36 m

.3 19

.4 04

.4 41

.4 44

.5 27

1. 00

0

re m

8m .2 89

.3 56

.4 21

.3 97

.4 48

.4 89

1. 00

0

re m

60 m

.2 30

.3 19

.3 67

.4 21

.4 41

.4 06

.4 63

1. 0 00

re m

72 m

.3 11

.3 47

.3 33

.4 08

.4 37

.4 13

.4 61

.5 07

1. 00

0

re m

84 m

.2 85

.3 60

.3 90

.4 30

.3 88

.3 86

.4 20

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.5 03

1. 00

0

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M e an

St d . D e v.

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ge

re m

6m 10

.1 34

3. 30

1 1–

20

re m

12 m

9. 62

4 3. 19

1 4–

20

re m

18 m

9. 44

7 3. 19

1 3–

20

re m

24 m

9. 67

1 3. 12

3 5–

20

re m

30 m

9. 23

9 3. 12

9 1–

20

re m

36 m

9. 31

4 3. 22

5 4–

20

re m

48 m

8. 92

8 3. 12

0 5–

20

re m

60 m

8. 79

2 3. 12

0 2–

20

re m

72 m

8. 67

2 3. 11

5 5–

20

re m

84 m

8. 75

5 3. 00

4 4–

18

N o te .r e m

6m = re m o rs e at

6 m o n th s,

re m

12 m

= re m o rs e at

12 m o n th s …

re m

84 m

= re m o rs e at

84 m o n th s.

REMORSE AND OFFENDING 11

α = .72, 30-months: α = .73, 36-months: α = .75, 48-months: α = .75, 60- months: α = .75, 72-months: α = .77, and 84-months: α = .77.18

Gender coded participants as male (=1, 86.41%) or female (=2, 13.59%). Race/Ethnicity includes four separate indicators for Black (=1, else = 0),

White (=1, else = 0), and Hispanic (=1, else = 0). The majority of respondents were Black (41%), followed by Hispanic (34%), and White (20%) youth. There were too few youth who selected “Other Race/Ethnicity” for separate analy-

ses. Number of prior petitions/arrests reflects the participant’s history of legal

involvement based on the total number of prior petitions to court before the baseline assessment. This count includes the study initial referring petition as

well as petitions prior to the initial referring petition (M = 2.91, SD = 2.14, Range 1–15).

18. There is some debate over whether emotions like remorse, guilt, and shame are (relatively) stable over the life course or if there is significant heterogeneity, especially in the adolescent as opposed to adult years. Unfortunately, there are very few offender-based longitudinal studies of remorse in particular, with frequent assessments obtained during the mid-adolescence to early- adulthood time period, so stability or variability remains an open question. There is some literature on the extent to which there is stability in psychopathy in longitudinal studies—but these studies do not converge on a single answer, i.e. stability or variability, in large part because they are con- tingent on the type of sample and its age range. Several studies indicate that total psychopathy scores are quite stable during childhood and adolescence (Frick et al., 2003; Lynam, Loeber, & Stouthamer-Loeber, 2008; Salihovic, Kerr, Ozdemir, & Pakalniskiene, 2012), while other studies indicate that mean levels of psychopathic traits generally decline from late adolescence and into early adulthood (Hawes, Mulvey et al., 2014). Other studies indicate differences within the sub- scales of the most common psychopathy measures, the Psychopathy Checklist (PCL), with studies indicating that the affective subscale (which includes remorse) is more stable than other subscales (see Blonigen, Hicks, Krueger, Patrick, & Iacono, 2006; Brandt et al., 1997). Very few studies have prospectively examined the stability of psychopathy scores in the transition from adolescence to adulthood and those that do yield mixed evidence (Lynam, Caspi, Moffitt, Loeber, & Stouthamer- Loeber, 2007; Hawes et al., 2014). One early study following 889 prisoners between ages 16 and 70 revealed very good stability in Factor 1 of the PCL-R, which measures interpersonal and affective traits—the latter of which includes items related to remorse (Harpur & Hare, 1994). Cauffman, Skeem, Dmietrieva, and Cavanagh’s (2015) recent study examined stability in the PCL:YV and PCL: R in two samples of offenders, 202 adolescents (ages 14–17) and 134 adults (ages 26–29) in three assessments at one month, twelve months, and twenty-four months after a baseline assessment. Their findings indicated that, at an absolute level, adolescents’ scores were moderately stable over a two-year period, but that total scores dropped an average of 2 points between ages 14–17; rela- tive to adults, adolescents’ scores were less stable than adults’ scores; and that psychosocial matu- rity was related to decreases in psychopathy scores among adolescents but not adults. As well, there was variability in adolescent subscale scores, with more stability observed in the interper- sonal and antisocial scales than the affective and lifestyle scales. In a recent review of the research on the stability of psychopathy, Bergström et al. (2015) observed that the existing knowl- edge base, as well as their own forty-year analysis using data from the Cambridge Study in Delin- quent Development, consistently documents moderate to high stability at the rank-order level with respect to psychopathic trait measures, with very little changes within persons: “…people keep their relative position on psychopathic traits within the sample over time (Roberts, Caspi, & Moffitt, 2001)” (p. 17). The findings of moderate to strong stability across different studies, with different samples, and with different measures is, according to Bergström and her colleagues “quite remarkable” (p. 17).

12 PIQUERO

Family member criminal history obtained from the youth at the baseline assessment regarding whether anyone in the respondent’s family had ever been

arrested (yes = 1, 78.3%). Exposure to violence (ETV; Selner-O’Hagan, Kindlon, Buka, Raudenbush, &

Earls, 1998) was obtained at the baseline interview and was modified for this study to assess the frequency of exposure to violent events. Items from the ETV document the types of violence the adolescent has both experienced (i.e.

Victim—6 items, e.g. “Have you ever been chased where you thought you might be seriously hurt?”) and observed (i.e. Witnessed—7 items, e.g. “Have

you ever seen someone else being raped, an attempt made to rape someone or any other type of sexual attack?”). The total measure, which includes the

count of items where the subject was a victim and the count of items where the subject witnessed violence, was used, with higher values reflecting more

exposure to violence (M = 5.34, SD = 2.99, Range 0–13). A multidimensional two-factor CFA model where certain measurement errors were allowed to cov-

ary was fit to the baseline data, with the following fit statistics: NFI = .92, NNFI = .92, CFI = .94, RMSEA = .04 (http://www.pathwaysstudy.pitt.edu/code book/etv-sb.html). For purposes of this analysis, the experienced and observed

indexes were collapsed into one scale because the two individual scales were moderately correlated (r = .53). As well, there was no theoretical reason to

demarcate the victimization and witnessing subscales for this particular analy- sis, as the main interest lies in whether the effect of remorse remains as a sig-

nificant correlate of re-arrest frequency controlling for exposure to violence— regardless of the type of exposure.

Neighborhood conditions (disorder) was adapted for this study to assess the environment surrounding the adolescent’s home (Sampson & Raudenbush, 1999). Items from the self-report measure obtained at baseline tap physical

disorder of the neighborhood (e.g. “cigarettes on the street or in the gut- ters,” “graffiti or tags”), as well as social disorder (e.g. “adults fighting or

arguing loudly,” “people using needles or syringes to take drugs”). The scale contains 21 items to which participants responded on a 4-point Likert scale

ranging from “Never” to “Often,” with higher scores indicating a greater degree of disorder within the community. An additional item was included to

determine the amount of time the participant spends within his/her neighbor- hood where responses range from “None of my time” to “All of my time.”

The total score was used in this study, with higher values indicating more neighborhood disorder (α = .94; M = 2.34, SD = .75, Range 1–4) (see also Piquero et al., 2016).

Peer delinquent behavior are a subset of items used by the Rochester Youth Study (Thornberry, Lizotte, Krohn, Farnworth, & Jang, 1994) to assess the

degree of antisocial activity among the adolescent’s peers. The current study uses the peer antisocial behavior measure, which contained twelve items

obtained at baseline (e.g. “During the last six months how many of your friends have sold drugs?”). Scale responses were on a 5-point Likert scale

REMORSE AND OFFENDING 13

ranging from “None of them” to “All of them”, with higher values indicating more delinquent peer associations (α = .92; M = 2.31, SD = .93, Range 0–5).

Unsupervised routine activities were drawn from the “Monitoring the Future Questionnaire” (Osgood, Wilson, O’Malley, Bachman, & Johnston,

1996) and are used to assess the frequency of unstructured socializing. Items obtained from respondents at the baseline interview specifically tap activities that occur in the absence of an authority figure (e.g. “How often

did you get together with friends informally?”). The scale contains 3 items to which participants responded at baseline on a 5-point Likert scale ranging

from “Never” to “Almost every day”. Higher scores indicate a greater involvement in unstructured activities. A fourth item was asked to specify

the number of evenings in a typical week the participant spends on “fun” activities. Items were previously scored independently without an “unstruc-

tured socializing” total score (Osgood et al., 1996); however, a combined score was created for the purpose of this study (α = .62; M = 3.82, SD = .84,

Range 1–5). Impulse control was assessed at the baseline interview using the Weinberger

Adjustment Inventory (WAI; Weinberger & Schwartz, 1990), which is an assess-

ment of an individual’s social-emotional adjustment within the context of external constraints. The impulse control portion is the mean of eight items

(α = .76; sample item “I say the first thing that comes into my mind without thinking enough about it” [reverse coded]), with higher values indicating more

impulse control (M = 2.96, SD = .95, Range 1–5). The Appendix A contains a correlation matrix of all the variables.

Analytic Plan

The nature of the data being used to explore the link between the time- varying lack of remorse measure and the total number of re-arrests at the end

of the 84-month follow-up period raises a few questions, namely what feature (s) of the time-varying lack of remorse measure is important to model as a

preliminary assessment of Warr’s hypothesis? Is it the overall average level over the study period? Is it the amount of change or average change over the study period? Or is it the trend (up or down) over time? For purposes of the

current study, the focus resides on the population-average, mainly because there is a great deal of stability in the time-varying lack of remorse measure.

As can be seen from Figure 1, there is not much change in the lack of remorse assessments over time (albeit with some improvement in the sample becoming

more remorse-prone over the follow-up period), the standard deviations hover in the 3.1 range for the majority of the seven-year period, and the confidence

intervals are tightly bound. With this in mind, the analyses will proceed by

14 PIQUERO

focusing on a pooled longitudinal negative binomial model,19 and then

estimate a series of supplemental models, including a Generalized Estimating Equation (GEE),20 to gauge the sensitivity of the population averaged model.

To presuppose the findings, there is no substantive change in the pattern of results or conclusions regardless of which models are relied upon.

Results

Starting with a naı̈ve model that contains only the pooled lack of remorse mea- sure, the first column of Table 2 shows that it has a positive and significant

relationship to the frequency of re-arrests (IRR = 1.03, SE = .00). Specifically, the frequency of re-arrests increases by 3.6% with every one unit increase in the lack of remorse. Thus, remorse-resistant youth are more likely to accumu-

late a higher number of re-arrests than remorse-prone youth. The second column of Table 2 contains the results of an expanded model

that includes a wider range of risk factors that have been found in previous

0 5

10 15

20 Lack of Remorse: 6 Months - 84 Months

6 months 12 months 18 months 24 months 30 months 36 months 48 months 60 months 72 months 84 months

Figure 1 Lack of remorse over time.

19. In the pooled negative binomial regression, the standard errors were cluster-corrected, which relaxes the usual requirement that the observations be independent (Stata 11.2). As well, regres- sion coefficients from count-based models are expressed in the form of Incidence Rate Ratios (IRRs). That is, the parameter estimates may be interpreted as the log of the ratio of expected counts, or a “ratio of ratios” and counts by definition can also be referred to as a rate. A rate is the number/frequency of events per time or space, and the rate at which these events occur can be considered an incidence rate (see Long, 1997; Long & Freese, 2014). 20. GEE is a form of population-averaged model, where the longitudinal data are treated in a cross-sectional manner and where the main interest lies in the population-averaged response (in this case, the lack of remorse).

REMORSE AND OFFENDING 15

research to be related to criminal activity generally, and in the Pathways Study

in particular. The purpose of this more comprehensive model was to examine if the lack of remorse continues to be related to re-arrest frequency indepen-

dent of these additional variables. Most importantly, these results show that the lack of remorse continues to exert a positive and significant effect on the

frequency of re-arrests (IRR = 1.02, SE = .00) with virtually little substantive change from the results in the more naı̈ve model. Other coefficients are

related to the frequency of re-arrests as expected. For example, females and youth with more impulse control are less likely to incur many re-arrests, while

those youth with more priors and who have had a family member arrested being more likely to incur a higher number of re-arrests. The coefficients for black and Hispanic youth (compared to whites), exposure to violence, neigh-

borhood disorder, peer delinquency, and routine activities were not signifi- cantly related to the frequency of re-arrests. Nevertheless, controlling for

these risk factors does not alter the conclusion that remorse-resistant adolescents are more likely to incur a higher number of re-arrests than are

remorse-prone adolescents. In one final descriptive analyses, Figure 2 presents the results of a ROC anal-

ysis examining the predictive accuracy of the lack of remorse measure on a dichotomous re-offending item. Although the area under the ROC curve is not particularly impressive (.58), this is not terribly surprising given the use of the

continuous lack of remorse measure to distinguish between whether a subject re-offended or not by the end of the seven-year follow-up period. Still, the

small area under the ROC curve does predict better than chance.

Table 2 Pooled negative binomial regression predicting frequency of re-arrests by 84 months.

Model 1 Model 2

Variable IRR SE 95% CI IRR SE 95% CI

Lack of Remorse 1.03 .00* 1.02–1.04 1.02 .00* 1.01–1.03

Gender .44 .05* .35–.56

Black .94 .07 .80–1.10

Hispanic .97 .07 .82–1.13

Priors 1.08 .01* 1.05–1.11

Family Member Arrested 1.27 .10* 1.09–1.48

Exposure to Violence 1.00 .01 .98–1.03

Neighborhood Disorder 1.01 .04 .93–1.09

Peer Delinquency .95 .04 .87–1.03

Impulse Control .90 .03* .84–.96

Routine Activities 1.03 .04 .95–1.12

Note. Model 1 (n of observations = 11,972, n of subjects = 1,197); Model 2 (n of observa- tions = 11,628, n of subjects = 1,162). *p < .05

16 PIQUERO

Supplemental Analyses

A number of different analyses were undertaken to gauge the sensitivity of the

findings with respect to model selection. In the first set of these estimations, the frequency of re-arrests at the end of the follow-up period was regressed on each of the assessments of the lack of remorse, i.e. the first model looked

at the relationship between the lack of remorse at the six month interview and the frequency of re-arrests at 84 months, the second model looked at the

relationship between the lack of remorse at the twelve month interview and the frequency of re-arrests at 84 months, and so forth. For each of these indi-

vidual estimations, the lack of remorse measure was positively and significantly related to the frequency of re-arrests, and the IRR estimates were virtually

the same (IRR = 1.03) as was found in the pooled model discussed earlier. Relatedly, a test that all of the lack of remorse coefficients (taken as a whole) were jointly zero was rejected (χ2 = 26.91, p < .002). In the second set of sup-

plementary estimations, two GEE models were estimated, one with only the lack of remorse measure and a second one that included the full range of

covariates. In both cases, the lack of remorse was positively and significantly related to the frequency of re-arrests, and all other covariate relationships

remained much as they were in the pooled model described earlier. Although the pooled and GEE models discussed in the main results section can adjust for

the lack of independence between the observations for each case, they do not allow for the inflated sample size. Thus, in the third supplemental analyses, a

linear combination of estimators model in which all ten of the lack of remorse coefficients (6 months through 84 months) was estimated after the estimation of a model containing each of the lack of remorse measures as covariates.

0. 00

0. 25

0. 50

0. 75

1. 00

Se ns

iti vi

ty

0.00 0.25 0.50 0.75 1.00 1 - Specificity

Area under ROC curve = 0.5795

Figure 2 ROC analysis examining the predictive accuracy of lack of remorse on re-arrest.

REMORSE AND OFFENDING 17

This single equation model generated an estimate of IRR = 1.08 (SE = .02), which was statistically significant (p < .001). In sum, all of the methods used to

examine the relationship of the lack of remorse to re-arrest frequency provide substantively similar results.21 Thus, remorse-resistant youth are more likely to

accumulate a higher number of re-arrests than are remorse-prone youth.

Discussion

The purpose of this paper was to provide an initial, preliminary analysis linking

Warr’s (in press) concept of regret, measured in this study with a measure of a lack of remorse, in understanding continuity/discontinuity in offending over

time in a large sample of serious adolescent offenders followed from mid- adolescence into early adulthood. The main finding from this study was that the lack of remorse was associated with a higher frequency of re-arrests by

the end of the 84-month study period. This result held in both a naı̈ve and a more fully specified model that contained an array of risk factors as well in

supplemental analyses. Albeit preliminary, this study provides support for continued investigation of Warr’s regret-based framework in that remorse-

resistant youth offend more often than remorse-prone youth. Some study limitations should be highlighted. First, some readers may be

concerned with the time-ordering of the independent and dependent variables. Although it is certainly possible that some of the re-arrests came before a par-

ticular interview in which the lack of remorse measure was obtained, it should be recalled that in a series of analyses investigating the frequency of re-arrests at the end of the follow-up period using each of the individual lack of remorse

measures (starting at the six month interview and continuing onto the eighty- four month interview) revealed positive and significant relationships of the lack

of remorse to re-arrest frequency with virtually identical coefficient estimates. Still, future research should assess Warr’s hypothesis in designs that permit

more ideal time ordering. Second, Warr did not propose what a measure of regret would look like for

empirical research. As a result, indirect measures had to be used from the Pathways Study. And while the lack of remorse measure used in the Pathways Study is part of an existing psychopathy measure, and has been used in other

research investigating offending, there is a need for further research using other dispositional as well as situational or contextual lack of remorse mea-

sures. There has been some useful work more generally in criminology and psychology regarding the potential value in differentiating between disposi-

tional and situational/state-based measures of anger, guilt, and shame (see

21. The author wishes to thank David McDowall for comments and suggestions regarding the methodological issues.

18 PIQUERO

Mazerolle, Piquero, & Capowich, 2003; Tangney, 1996) and future research on remorse should consider these approaches as well.

Third, this study examined offending within the context of official re-arrests; as a result, future efforts should consider replicating the approach

undertaken by Spice (2013), which explored alternative measures of offending, such as self-reports, and also assess the extent to which a lack of remorse relates to offending at different periods of the life-course, i.e. early adoles-

cence, middle adulthood, later adulthood. As well, future studies should exam- ine the relationship between lack of remorse across different crime types,

including crime types that may involve victims in the context of persons as opposed to victims in the context of a business. It may be that different (aged)

people may feel remorse (or not) depending on whom the victim is, i.e. another person that they injured or a big-box retailer that makes billions of

dollars. Fourth, although there was quite a bit of stability in the remorse measure in

the Pathways Study data, future research should explore variability within remorse over time as there could be distinct subgroups whom evince different trajectories of remorse, which themselves could be differentially related to

different trajectories of offending. Fifth, three-quarters of the sample analyzed in the current study consisted

of non-white males, potentially limiting the generalizability of the findings. Future research should expand data collection and subsequent analyses to

include more representative samples in order to replicate the results from the current study.

Lastly, future work should consider how the lack of remorse fits alongside other emotional and personality-based explanations, including shame and guilt. Although the current study included a measure of impulse control, which was

itself predictive of re-arrests but did not alter the effect of the lack of remorse on re-arrests, it would be useful in subsequent work to consider the

inter-relationships between the various types of what Tangney has referred to as “moral emotions”.22

In that vein, Tangney et al. (2011a) correctly differentiate between risk fac- tors for recidivism that are difficult to change (within correctional systems),

such as parental incarceration, neighborhood disadvantage, age at first arrest, or socioeconomic status, and those risk factors that are amenable to change,

22. As Tangney et al. (2007, p. 345) note: “Moral emotions represent a key element of our human moral apparatus, influencing the link between moral standards and moral behavior.” An anonymous reviewer correctly noted that there remains much to be done with respect to not only creating measures of regret but also in testing how such measures are similar to or distinct from other moral emotions, especially guilt. Further, the reviewer raised the intriguing possibility that perhaps individuals need to feel guilt which then leads into regret and remorse—or perhaps that when cou- pled with shame regret and remorse may be maladaptive. Further, s/he noted that there may be different types of regret (i.e. “I regret that I committed the crime because I got caught” vs. “I regret that I harmed that person”). These are all excellent points and opportunities for future work.

REMORSE AND OFFENDING 19

such as those encompassing “moral emotions” (especially guilt), “because of their presumed roles in inhibiting immoral, socially undesirable behavior and in

fostering altruistic, prosocial behavior (Tangney et al., 2011b, p. 710). As regret/remorse is an emotion closely linked to these other emotions, it is

worthwhile to consider expanding social-cognitive and cognitive-behavioral therapies to attend to an offender’s possible remorseful feelings.

On this score, the dynamic risk literature in both criminology and forensic

psychology has revealed that certain interventions and therapies targeting dynamic (or modifiable) risk factors may be usefully applied to offenders which

has been shown to lower subsequent offending and drug use (see Andrews & Bonta, 2010; Wooditch et al., 2014). Relatedly, given the consistent findings in

the literature reporting that more empathetic offenders are less likely to offend (Broidy, Cauffman, Espelage, Mazerolle, & Piquero, 2003; Jolliffe & Farrington,

2004), several studies have highlighted the importance of expanding therapies and interventions to attend to an offender’s emotions/attitudes and CU traits,

including antisocial cognitions (Walters, 1995, 2003), psychopathy (Caldwell, Skeem, Salekin, & Van Rybroek, 2006), and empathy (Marshall, Marshall, Serran, & O’Brien, 2009; Tong & Farrington, 2008)—especially when applied early in

the life-course (Hawes et al., 2014).23 These studies underscore the need in considering identification of these types of risk factors (empathy, CU traits,

remorse) in forensic risk evaluations in order to target specific strategies to specific offenders more generally (cf. Forth, 2005; Vincent, 2006). As well,

there exist a range of evidence-based programs that can successfully improve impulse and self-control among children and adolescents (see Piquero, Jennings,

& Farrington, 2010). The coupling of these prevention and intervention strate- gies offers a comprehensive approach to increasing remorse-proneness among offenders in an effort to prevent subsequent offending.

Aside from these individual offender-based treatment efforts, alterations to criminal justice sanctioning also has some linkages to Warr’s proposed frame-

work, particularly the work on reintegrative shaming and its punishment strat- egy of restorative justice. Braithwaite’s (1989) seminal work focused on the

distinction between the more positive reintegrative shaming as compared to the more negative disintegrative shaming or stigma. The former type of sham-

ing is hypothesized to lead to less crime while the latter type of shaming is expected to lead to more crime. Restorative justice is a therapeutic approach

that suggests guilt induction given its emphasis on accountability and making amends (Umbreit & Armor, 2011). Recently, Ahmed and Braithwaite (2006, p. 350) highlighted three specific facets of restorative justice that are critical

in efforts to reduce antisocial behavior, including: forgiveness (measured in terms of being able to put others’ grievances behind you), reconciliation

(measured in terms of feeling care and support from those who have been

23. The evidence in favor of empathy-based interventions among sexual and violent offenders remains mixed (see Day, Casey, & Grace, 2010).

20 PIQUERO

harmed), and shame management (measured in terms of acknowledging the harm that has been done, and making amends). A key premise underlying

restorative justice is the need for offenders to express remorse (acknowledge shame, which is also closely related to the concept of guilt) and accept per-

sonal responsibility over wrongdoing (pp. 352–353). At its core, Ahmed and Braithwaite’s argument centers on the acknowledging of shame and responsi- bility, which in their research was found to be related to less bullying, whereas

displacing shame into anger and blaming others was found to be linked to more bullying. Thus, from a restorative justice perspective, those who are unable to

feel shame or remorse from harming others will be at greater risk of doing so in the future: shame acknowledgement is productive (admit that what has hap-

pened is wrong and involves expressing remorse) but shame displacement is counter-productive (blaming others for the wrong and expressing anger toward

them). According to Ahmed et al. (2001), persons who acknowledge shame and accept personal responsibility will refrain from further wrongdoing because

they have considered the harmful consequences and made amends to avoid them in the future (Ahmed & Braithwaite, 2005, p. 303). The practice of restorative justice may be a useful justice-centered approach for fostering the

kind of remorse needed to thwart continued criminal offending. In short, this preliminary study investigated Warr’s (in press) hypothesis that

regret (or the lack of remorse) is related to discontinuity (or continuity) in offending in a sample of serious adolescent offenders followed from mid-adoles-

cence to early adulthood. Results provide enough support for Warr’s hypothesis that remorse-resistance is related to more offending, while remorse-proneness

is related to less offending. Future research should undertake empirical investigation and extension of these findings to compare and contrast his thesis vis-à-vis other theoretical frameworks that currently dominate criminology.

Disclosure statement

No potential conflict of interest was reported by the author.

Funding

The project described was supported by funds from the following: Office of Juvenile Jus- tice and Delinquency Prevention (2007-MU-FX-0002), National Institute of Justice (2008- IJ-CX-0023), John D. and Catherine T. MacArthur Foundation, William T. Grant Founda- tion, Robert Wood Johnson Foundation, William Penn Foundation, Center for Disease Control, National Institute on Drug Abuse (R01DA019697), Pennsylvania Commission on Crime and Delinquency, and the Arizona Governor’s Justice Commission. We are grateful for their support. The content of this paper, however, is solely the responsibility of the authors and does not necessarily represent the official views of these agencies.

REMORSE AND OFFENDING 21

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26 PIQUERO

A p p e n d ix

A . C o rr e la ti o n m at ri x al l va

ri ab

le s

R e m o rs e

R e ar re st

G e n d e r

B la ck

H is p an

ic P ri o rs

Fa m

A rr

E xp

V io l

N H D is

P e e rs

Im p u ls e

R o u ti n e A ct

R e m o rs e (m

e an

) 1. 00

00

R e ar re st

.1 74

5 1. 00

00

G e n d e r

− .1 57

4 − .2 56

8 1. 00

00

B la ck

− .1 25

2 − .0 57

1 − .0 00

8 1. 00

00

H is p an

ic .0 88

7 .0 95

0 − .0 62

9 − .5 72

5 1. 00

00

P ri o rs

.0 46

0 .2 61

0 − .1 54

2 .0 31

9 .0 30

9 1. 00

00

Fa m

A rr e st

.0 92

2 .1 20

5 − .0 18

3 − .0 99

6 .0 94

6 .1 22

6 1. 00

00

E xp

V io l

.2 90

1 .1 04

9 − .1 25

5 .0 09

2 .0 88

1 .2 11

3 .1 84

1 1. 00

00

N H D is

.1 30

7 .0 5 91

.0 25

4 .2 05

4 .0 20

8 .1 34

9 .1 68

8 .3 03

0 1. 00

00

P e e rs

.3 29

9 .1 6 24

− .0 60

5 − .1 61

4 .2 27

3 .2 11

1 .1 55

0 .5 56

1 .2 34

4 1. 00

00

Im p u ls e

− .3 84

9 − .1 39

8 .0 09

9 .2 75

4 − .1 51

8 − .0 49

8 − .1 21

2 − .2 54

2 − .1 25

9 − .3 67

1 1. 00

0

R o u ti n e A ct

.1 55

3 .1 08

8 − .0 35

5 − .0 61

4 .0 12

2 .1 02

0 .0 39

3 .3 38

3 .0 45

3 .3 89

1 − .2 21

1 1. 00

0

K e y:

R e m o rs e (m

e an

)= av

e ra ge

la ck

o f

re m o rs e

o ve

r ti m e ;

R e ar re st

= n u m b e r

o f

re ar re st s

b y

84 -m

o n th

fo ll o w -u p ; G e n d e r;

B la ck ; H is p an

ic ;

P ri o rs ;

Fa m

A rr e st

= fa m il y ar re st ; E xp

V io l = e xp

o su re

to vi o le n ce

; N H D is = n e ig h b o rh o o d d is o rd e r;

P e e rs ; Im

p u ls e = im

p u ls e co

n tr o l; R o u ti n e A ct

= ro u ti n e ac

ti vi ti e s.

REMORSE AND OFFENDING 27

Young People and Crime/Perceptions of antisocial behaviour and negative attitudes towards young people focus group evidence from adult residents of disadvantaged urban.pdf