False positive and false negative rates in self-reported intentions to offend: A replication and extension

Journal of Criminal Justice 42 (2014) 1–9

Contents lists available at ScienceDirect

Journal of Criminal Justice

False positive and false negative rates in self-reported intentions to offend: A replication and extension M. Lyn Exum a,⁎, Diana Bailey a, Eric L. Wright b a b

Department of Criminal Justice and Criminology, UNC Charlotte Department of Sociology, Indiana University

a r t i c l e

i n f o

Available online 2 November 2013

a b s t r a c t Purpose: Studies of criminal decision making commonly rely on college students’ self-reported intentions to commit a hypothetical offense. The current study evaluates the predictive validity of these intentions to offend. Methods: Undergraduate students (n = 726) read a fictitious but seemingly realistic newspaper article describing an illegal opportunity for acquiring digital music files, and then reported their intentions to act upon the opportunity. Afterward, participants’ real world attempts to follow-through on the opportunity were monitored covertly. Results: Findings reveal that participants who reported weak intentions to offend typically refrained from the act, resulting in a low false negative rate. However, those who reported strong intentions to offend also typically refrained from the act, thereby resulting in a high false positive rate. Conclusions: These findings suggest that while participants’ predictions of criminal abstention are generally accurate, their predictions of criminal involvement are more problematic. Such faulty intentions have important implications for research on criminal decision making. © 2013 Elsevier Ltd. All rights reserved.

Introduction Tests of deterrence and rational choice theory have commonly utilized the hypothetical scenario method (Bouffard, Exum, & Collins, 2010). In these studies, participants—who are often college students— are given a written account of a hypothetical criminal opportunity and are asked to report their likelihood of acting upon the opportunity, assuming it were real. These self-reported intentions to offend (SRIO) scores are frequently recorded on a 0% (no chance) to 100% (definitely would) scale, and are used as the primary dependent measure in statistical models of offender decision making. As such, SRIO scores are a staple of the deterrence/rational choice literature. Recently, Exum, Turner, and Hartman (2012) examined the predictive validity of SRIO scores by comparing college students’ intentions to engage in an act of music piracy (as described on paper) to their real world attempts to engage in the behavior about which they had read. Results revealed that those who expressed little-to-no intentions to offend did in fact abstain from the act. At the same time, those who expressed strong-to-definitive intentions to offend also abstained. Thus, despite the variability in participants’ SRIO scores, there was unanimous conformity in participants’ behaviors. Based on these results, Exum et al. conclude that “…SRIO scores are far better measures

⁎ Corresponding author at: Department of Criminal Justice and Criminology, UNC Charlotte, 9201 University City Blvd, Charlotte, NC 28223. Tel.: +1 704 687 0746. E-mail address: [email protected] (M.L. Exum). 0047-2352/$ – see front matter © 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.jcrimjus.2013.09.003

of participants’ intentions to abstain from crime than they are of participants’ intentions to offend” (p. 536, italics in the original). The current study is a modified replication of Exum et al.’s (2012) examination of self-reported intentions. Replication studies are essential to the advancement of scientific knowledge (Lamal, 1991) and have long been championed in the social sciences (e.g., Campbell & Jackson, 1979; Collins, 1985; Rosenthal, 1976). However, despite some notable exceptions, replications in the social sciences have been relatively rare (Boster, 2002; Gendreau, 2002; Hubbard & Armstrong, 1994; Lowenkamp, Cullen, & Pratt, 2003). Some have argued that the dearth of this type of research in the social sciences may be based in part on the perception that replications lack “sufficient value to take up valuable journal space” (Boster, 2002; p. 616); yet, others note that the field of criminology has a growing appreciation of replication research (Lowenkamp et al., 2003). In that same sense of appreciation, the current study seeks to replicate Exum et al.’s (2012) examination of self-reported offending intentions. In doing so, the study also addresses some of the methodological weaknesses in the original research, thereby offering a more critical assessment of the predictive validity of SRIO scores. Literature review Hypothetical offending scenarios have been used to examine the decision making processes that underlie a variety of imprudent/illegal behaviors, including sexual aggression (Bouffard, 2002), physical aggression (Exum, 2002), drunk driving (Piquero & Pogarsky, 2002),

2

M.L. Exum et al. / Journal of Criminal Justice 42 (2014) 1–9

corporate offending (Paternoster & Simpson, 1996), academic cheating (Tibbetts, 1999), tax noncompliance (Klepper & Nagin, 1989) sports doping (Strelan & Boeckmann, 2006), and even police misconduct (Pogarsky & Piquero, 2004). Generally speaking, this literature finds the distribution of SRIO scores to be positively skewed, with the majority of participants reporting little-to-no intentions of engaging in the targeted behavior (see also Bachman, Paternoster, & Ward, 1992; Nagin & Paternoster, 1993; Piquero, Exum, & Simpson, 2005; Piquero & Tibbetts, 1996; Pogarsky, 2002, 2004; Pogarsky & Piquero, 2003). However, a notable minority of participants report modest-to-strong intentions to commit the act. Researchers commonly acknowledge that SRIO scores are not measures of bona fide criminal activity (Bachman et al., 1992; Paternoster & Simpson, 1996; Piquero & Tibbetts, 1996; Rebellon, Piquero, Piquero, & Tibbetts, 2010; Tibbetts & Herz, 1996). Illustratively, Nagin and Paternoster (1993:473) write: “…an expressed intention to offend is not synonymous with actual performance,” and they subsequently refer to this discrepancy as the “principal weakness” of the hypothetical scenario method. Nevertheless, researchers also contend that behavioral intentions and actual behavior should be strongly correlated (Bachman et al., 1992; Nagin & Paternoster, 1993; Rebellon et al., 2010; Piquero & Bouffard, 2007; Piquero et al., 2005). Thus, SRIO scores can be interpreted as de facto proxies for real world offending (see Exum et al., 2012). Researchers are able to justify the use of SRIO scores as proxies for offending by invoking the theory of reasoned action (Ajzen & Fishbein, 1980; Fishbein & Ajzen, 1975) and/or the theory of planned behavior (Ajzen, 1991). Both theories assume that behavior is ultimately a function of personal attitudes and subjective norms regarding the target behavior. These attitudes and norms influence the individual’s intention to act, which is a measure of the amount of energy the individual is willing to put forth in order to accomplish the behavior. As such, behavioral intentions are not merely the proximal antecedents of human action; they are also viewed as one of the best predictors of real world behavior—hence the strong theoretical correlation between the two (Fishbein & Ajzen, 1975; see also Ajzen, 1991; Armitage & Conner, 2001; Sheppard, Hartwick, & Warshaw, 1988). At the same time, the theories of reasoned action and planned behavior also recognize that the correlation between intentions and behaviors can be moderated by additional factors, such as the degree of personal control the individual has over the completion of the task (Ajzen, 1991). Many studies have examined the relationship between intentions (I) and behaviors (B) for various conventional activities such as voting, watching television, or going to church. Meta-analytic reviews of this literature find the IB correlation to range from 0.44 to 0.82 (Armitage & Conner, 2001; Kim & Hunter, 1993; Randall & Wolff, 1994; Sheeran & Orbell, 1998; Sheppard et al., 1988). Although far fewer in number, studies examining the IB relationship for unconventional behaviors— such as lying, shoplifting, cannabis use, and digital piracy—find IB correlations to be somewhat lower, ranging from .30 and 0.48 (Armitage, Conner, Loach, & Willetts, 1999; Beck & Ajzen, 1991; Higgins, 2007).1 Thus, while they appear to be positively related to one another, criminal intentions are far from perfect approximations of actual criminal behaviors.2

SRIO accuracy: Exum et al.’s (2012) study Recently, Exum and colleagues (2012) examined the predictive validity of self-reported criminal intentions. In their study participants were not presented with the typical hypothetical scenario; instead, participants received a copy of a (fictitious) newspaper article describing a graduate student who was distributing illegal copies of digital music files to students for free by email. The article also included the graduate student’s email address, thereby providing participants with the necessary means to contact the student if desired.

After participants read the newspaper article, they were instructed to complete a pencil-and-paper survey. (Unbeknownst to participants, each survey contained a unique identifier that corresponded to the participant’s signed consent form.) The survey asked participants how likely they were to contact the graduate student and request illegal music files. Responses were recorded on a 0% to 100% scale. In the subsequent weeks, the graduate student—who was a research confederate—monitored his email account for music requests. Any emails sent to the confederate could then be used to determine the identity of the participant, thereby making it possible to link the participants’ act of contacting the confederate back to their (non-anonymous) SRIO scores. In this way, Exum et al. (2012) sought to compare participants’ self-reported intentions to request illegal music files from the confederate with their real world attempts to do so. Results revealed that two-thirds of all participants reported no intentions of contacting the graduate student, and that no one in this group subsequently emailed the confederate. Thus, participants’ SRIO scores had a low false negative rate. By comparison, one-third of the participants reported a non-zero SRIO score, with approximately 7% of the sample reporting a more-than 50% chance that they would be requesting illegal files from the graduate student (and 2% reporting a 100% chance). Yet, no one from this group ever requested files from the confederate, thereby resulting in a high false positive rate. This led Exum and colleagues (2012) to conclude that self-reported intentions may be more accurate at lower levels of the scale (i.e., predicting abstention) than at higher levels (i.e., predicting offending). Methodological limitations of Exum et al. (2012) More than two decades ago, Grasmick and Bursik (1990) noted that individuals’ current inclinations to offend may not correspond with their future behavior; however, they did not view this as prima facie evidence that intentions are poor proxies for behavior. Instead, they argued that discrepancies between criminal intentions and future offending may be driven by an underlying change in the expected utility of the criminal opportunity. In other words, as participants read about a hypothetical offense they may initially find it to be an attractive opportunity (resulting in high SRIO scores), but with the passage of time the very same opportunity may appear less enticing (resulting in criminal abstention). Thus, to help minimize this source of discrepancy between intentions and behaviors, SRIO scores and subsequent criminal actions should be measured in close temporal proximity. Exum et al. (2012) acknowledge that the design of their study likely created a delay between the time in which participants reported their SRIO scores and the time they were able to email the confederate. The study’s survey materials were typically administered in academic classrooms where students did not have computer access and, as such, participants were likely to be unable to logon to their email accounts and contact the confederate until sometime later (although some may have had more immediate email access through smart phones or personal laptops with Wi-Fi capabilities). During this passage of time, participants who initially saw the piracy opportunity as highly attractive may have experienced a change in the expected utility of the act, prompting them to subsequently abstain. In a similar vein, when participants were eventually able to access their email accounts they were most likely in a location different from the one in which they completed the survey. Exum et al. (2012) speculate that this change in the environmental setting may have had an impact on participants’ criminal propensities, further contributing to the discrepancies between criminal intentions and criminal behavior. Additionally, Exum and colleagues recognize that some participants may have also misplaced their copy of the newspaper article with the confederate’s email address, thereby making it more difficult for them to act upon their offending intentions. Finally, Exum et al. (2012) posit that the high false positive rate of SRIO scores may be attributed to the use of a continuous measure of

M.L. Exum et al. / Journal of Criminal Justice 42 (2014) 1–9

intentions (e.g., 0% to 100%) rather than a binary measure (e.g., Will you request music files from the graduate student? Yes/No). This argument is based on the claim that a continuous measure of intentions provides participants the opportunity to report a certain degree of uncertainty in their estimated likelihood of committing the criminal act (see Piquero & Pogarsky, 2002; Sitren & Applegate, 2007). By definition, any uncertainty in self-reported offending intentions will weaken the predictive accuracy of SRIO scores. Drawing from the work of Green (1989)—who used a dichotomous measure of participants’ predictions to drive drunk and found it to be predictive of subsequent drunk driving behavior—Exum and colleagues recommend that future researchers explore the predictive accuracy of such binary measures of self-reported offending intentions. The current study The current study adopts the basic methodology of Exum et al.’s (2012) study of music piracy SRIO scores, but administers the study materials online. As a result, (1) participants should have access to their email accounts at the time they complete the study, thereby minimizing the interval of time between when they report their SRIO scores and when they are able to contact the confederate, (2) participants no longer need to be in different settings/environments when reporting SRIO scores and when actually offending, and (3) participants should be less likely to misplace their copy of the newspaper article containing the confederate’s email address (in fact, they would be able to revisit the online copy throughout the duration of the study, and could also download/print a copy for additional access). Finally, the current study measures self-reported intentions to offend with both a continuous and a binary measure. In this way, we seek to minimize any potential measurement error that may be inherent in a continuous 0% to 100% scale. For both the continuous and dichotomous measures of self-reported intentions we calculate false positive and false negative rates using a 2by-2 accuracy matrix like that shown in Fig. 1. The letters a, b, c and d represent the number of cases that fall in each corresponding cell. The false negative rate is the proportion of participants who did not intend to request music files, but eventually did so. This is computed as b/ (a + b). The false positive rate is the proportion participants who did intend to request music files, but failed to do so. This is computed as c/ (c + d). By examining these false positive and false negative rates, we can assess how accurately participants can predict their intentions to engage in and abstain from a real world criminal opportunity. Methods Sample Our study population consists of undergraduate freshmen students enrolled in one of two southeastern universities located approximately 100 miles apart but in separate states.3 We refer to the two schools here as the “in-state” and “out-of-state” university. The in-state university’s Office of Institutional Research provided us with a list of email addresses for all freshmen at that campus (n = 4,672). The Registrar at the out-ofstate university gave us permission to harvest the email addresses of

3

freshmen at that campus using a paper copy of the university’s telephone directory (to identify the names of freshmen) and the university’s online email directory (where we could submit names and retrieve email addresses). In some instances, the email addresses for out-of-state students were not listed online or were invalid. However, we were successfully able to obtain working email addresses for 6,298 of the 7,642 persons identified as freshmen in the telephone directory. Our final population therefore consists of all freshmen from the two universities for whom we had valid email addresses (n = 10,970). Each person in the population received an email inviting them to participate in the study, and included the hyperlinks needed to view the online study materials. The email also explained that everyone who took part the study would be eligible to enter into a drawing for a computer tablet valued at approximately $500, or for one of four $50 gift cards to their university’s bookstore. During the ten days following this initial email, two “reminder emails” were sent to those who had not yet responded to the survey. All totaled, 775 students took part in the study; however, 49 participants indicated they were unable to view all of the online materials. After removing these individuals from the analyses, the final sample was reduced to 726 participants (6.6% of the population).4 Note that more than half of the participants in the study (56%) admitted to downloading music files illegally during the past six months. The average age of the sample is 19.23 years (SD = 3.11), with the majority of participants (59%) being female. Collectively, 78% of the sample is White/non-Hispanic, 9% are African American, 6% are Asian, and 4% are Hispanic with the remaining 3% identified as some ‘other’ race/ethnicity. These characteristics are largely in-line with those of the target population. Using publicly available data from the two universities, we estimated the average age of the collective Freshman population during the time of the study to be 19.10 years, with the majority of Freshmen being female (53%). Furthermore, approximately 76% of the population was estimated to be White/non-Hispanic, with 10% estimated to be African American, 4% Asian, 5% Hispanic, and 5% classified as some other race/ethnicity. Materials All materials for this study were distributed electronically. The informed consent information was included in the initial recruitment email and in the two reminder emails. These emails described the study as an examination of freshmen students’ attitudes regarding music piracy. Included in the consent information were two URLs: one that would direct participants’ internet browser to a scanned copy of a fictitious newspaper article, and one that would connect participants to an online survey about the article. All students who agreed to participate in the study were instructed to read the newspaper article and answer the online survey. The fictitious newspaper article used in the current study was largely identical to that used by Exum et al. (2012). The article was formatted to appear as if it had been cut from the print-edition of the in-state university’s local city paper, and then scanned/saved as a PDF file (see Appendix A for a copy of the unformatted text of the article).5 The

Fig. 1. Accuracy matrix.

4

M.L. Exum et al. / Journal of Criminal Justice 42 (2014) 1–9

article, which was described in the recruitment emails as having been published approximately three months prior, states that a graduate student at the in-state university is emailing illegal music files for free to any student with an email account ending in “.edu.” The graduate student mentioned in the article—whom we refer to here as “Arthur Radley”—was our research confederate. There are additional aspects of the newspaper article that bear noting. First, the article clearly states that it is against the law to distribute or download copyright protected music files. This information is included so that participants are under no illusion that receiving digital files from Radley is legal. Second, in the article Radley claims that his emails are protected by Federal law and therefore cannot be read by anyone other than the intended recipient. The article also mentions that the in-state university will be challenging Radley’s claims of email privacy in an upcoming court case, but that Radley vows to continue distributing music files by email until a judge orders him to stop. The acknowledgement of a pending court case coupled with Radley’s vow to continue sharing files was included to inform participants that Radley’s music piracy operation would remain in effect until (at a minimum) the date of his court appearance—scheduled to take place four weeks from the date participants received the initial recruitment email. In this way, the article effectively conveys that despite the university’s awareness of Radley’s illegal activities (and despite his activities being reported in the local newspaper), Radley’s music piracy operation stands as an ongoing criminal opportunity and will continue to function for at least another month. Finally, Radley’s email address is prominently featured in a “call out box” at the end of the article, thereby giving participants the necessary means of contacting him.6 With thorough vetting and full approval from the Institutional Review Board, our online survey surreptitiously recorded participants’ email addresses when they opened the survey link. As a result, the surveys were not anonymous—although participants were not informed of this at the time they completed the study. The survey contained a battery of demographic questions as well as a series of questions about Radley and his scheduled court appearance. To measure self-reported intentions to offend in a binary fashion, participants were asked: “Between now and March 3rd (Arthur Radley’s scheduled court date), will you be emailing Mr. Radley to request music files from his collection?” Participants then reported their intentions to offend with either a ‘yes’ or ‘no’ response. To measure self-reported intentions along a continuum, participants were also asked: “What is the chance that you will email Arthur Radley before his March 3rd court date and request music files from his collection?” Consistent with Exum et al. (2012), responses to this question were recorded on an 11-point scale ranging from 0% (No Chance) to 100% (Definitely Would). Using an identical 0% to 100% scale, participants also rated the perceived certainty of experiencing several negative consequences if they were to contact the confederate (e.g., getting in trouble with the law, with their school, etc.). Likewise, participants rated the severity of each of these consequences using a 0 (Not at all) to 100 (Extremely) scale. We recognize that some readers may feel that the criminal opportunity described in the newspaper article may be “too risky” to expect students to act upon (after all, the article states the university is aware of Radley’s actions and has a pending court case against him). Although our newspaper article is intentionally silent regarding the university’s intent to seek action against those who requested music files from Radley, it is reasonable to assume that some participants may feel that the university’s persecution of Radley will spill-over to those who received his illegal music files. In theory, this “spill-over effect” will impact the distribution of participants’ intentions to offend as well as their actual offending behaviors. As a result, some readers may feel that the risk conveyed in our newspaper article presents a fatal design flaw. We wish to address these concerns. First, we should note that (by definition) all criminal offending scenarios—be them about sexual aggression, physical aggression, drunk driving, shoplifting, etc.,—convey an element of legal risk. (When studying

college students, the risk for academic consequences such as expulsion is also an inherent concern.) Thus, the presence of risk in our newspaper article is not unusual; instead, what may be a concern to some readers is the level of this risk. There is no guidance in the deterrence/rational choice literature as to how much risk in hypothetical scenarios is too much; however, it is notable that prior scenario research has depicted such risky criminal opportunities as: drunk driving despite the presence of numerous police roadblocks (Thurman, Jackson, & Zhao, 1993), physical assault despite the presence of many bystanders/witnesses (Kennedy & Forde, 1996), and corporate offending despite the company’s practice of internal audits/inspections (Piquero et al., 2005). Furthermore, studies of deterrence that examine real world acts of academic dishonesty have presented college students with an opportunity to cheat on a test, but have done so with a proctor in the room during the test (Nagin & Pogarsky, 2003). Using this collective literature as a point of comparison, we do not believe that the risk depicted in our hypothetical criminal opportunity is either unusually high or methodologically inappropriate. Second, recall that participants in the current study were asked to rate the perceived certainty and severity of various formal/informal sanctions associated with requesting illegal music files from the confederate. This, in turn, allows us to examine whether participants found the opportunity depicted in the newspaper article to be extremely risky. As our results will show, this was not the case; on average, participants found the opportunity to present a moderate amount of risk for a moderately severe sanction. Such certainty and severity levels are not outof-bounds with other deterrence/rational choice studies using hypothetical scenarios (Bouffard, 2011; Exum, 2002; Grasmick & Bursik, 1990; Loewenstein et al., 1997; Pogarsky & Piquero, 2004; Rebellon et al., 2010; Simpson & Piquero, 2002), and in some cases reflect lower risk levels than in these other studies. Lastly, for those readers who may still have reservations about the newspaper article, we note that the goal of the current study is not to present a hypothetical offending scenario that carries a specific level of risk—be it very low or very high. Instead, the goal is to see how accurate SRIO scores are by comparing them to participants’ real world behavior. Thus, if participants perceive little risk in the newspaper article (and as a result report high SRIO scores), then we would expect participants to subsequently make contact with the confederate. By the same token, if participants feel the opportunity depicted in the newspaper article is too risky (and therefore report low SRIO scores), then we would expect participants to refrain from making contact with the confederate. In sum, and regardless of the risk level associated with the criminal opportunity, SRIO scores—if indeed accurate—should be predictive of real world behavior. This is the issue we explore in the current study. Procedure All freshmen for whom we had valid email addresses received a recruitment email containing the informed consent information and the URL links to the newspaper article and online survey. The survey remained open to participants for a period of one month, eventually closing on March 3rd—the date of Radley’s supposed court appearance. Throughout the four week data collection period, our research confederate monitored his email account for any requests for illegal music files. Per study protocol, the confederate was instructed to reply to these requests with the following response: “Thanks for your email. I’m currently working on a back-log of requests and should be able to work on your order shortly. – Arthur”. The confederate was also instructed to forward any emails he received to a fellow member of the research team, who would then use the hidden identifiers in the online survey to link participants’ email requests to their SRIO scores. (Note that no music files were actually distributed in this study.) Immediately after the data collection period ended, everyone who received a recruitment email was sent a debriefing email. This email explained the true purpose of the study, indicated the newspaper article

M.L. Exum et al. / Journal of Criminal Justice 42 (2014) 1–9

was fictitious, and notified participants that the online survey was not anonymous. The email also explained that because participants were initially deceived as to the purpose and nature of the study, they could have their data purged from the study upon request. No one expressed interest in having this done. Results In order to determine if our music piracy opportunity was perceived to be too risky to act upon, we examined participants’ perceptions of risk associated with contacting the confederate. Participants were instructed to envision themselves contacting Radley, and then rate the certainty and severity of a series of potential negative consequences. Table 1 summarizes these scores. As seen in the table, participants felt that getting into trouble with their university was the most likely of all the consequences, and also the most severe. However, neither of these average ratings exceeded the mid-point on the certainty/severity rating scale. Getting into trouble with the law and feeling guilty were viewed as slightly less certain/ severe, while social consequences such as getting into trouble with parents and peers were found to be far less likely and far less troubling. Collectively, these ratings suggest that the piracy opportunity described in our newspaper article came with (at most) a moderate amount of risk for a moderately severe punishment. As previously discussed, this degree of risk is well within the levels commonly found in other hypothetical offending scenarios, and therefore does not appear to present a concern to the integrity of the current study’s methodology. Next, we turn our attention to participants’ self-reported intentions to contact the confederate. Table 2 summarizes the distributions of both the continuous and binary SRIO scores. Consistent with Exum et al. (2012)— as well as the larger body of research using hypothetical scenarios to study criminal decision making—the distribution of the continuous measure of offending intentions is positively skewed, with the mean falling toward the lower-end of the scale ( x ¼ 9:39 , SD = 20.97). Similarly, the overwhelming majority of participants (93.8%) who completed the binary intentions measure reported they would not be engaging in the act. Based on the distributions in Table 2, we can predict how many participants will request illegal music files from Radley—assuming, of course, that these SRIO measures are valid. The predictions based on the binary measure are the most straightforward to deduce. As seen in the table, 45 participants responded “yes” they would contact Radley, and so we would expect these 45 participants to actually offend. We can also estimate the number of participants who will email Radley based on the continuous SRIO scores using the formula: 1:0 X

ni  i

i¼0

where i = the self-reported offending probability, and ni = the number of participants who reported the given offending probability. Illustratively, of the 531 participants who reported a 0% chance of contacted Radley, we would expect none of them to actually send him

Table 1 Certainty and severity ratings for negative consequences associated with contacting the confederate (0 to 100 rating scale) Certainty

Severity

Consequence

Mean (SD)

Mean (SD)

Getting into trouble with your University Getting into trouble with the law Feeling guilty Getting into trouble with your parents Getting in to trouble with your friends

48.28 (32.22) 45.26 (32.50) 41.38 (37.81) 27.03 (33.89) 14.05 (25.40)

46.76 (32.82) 46.32 (33.04) 37.59 (36.92) 25.71 (32.30) 13.20 (23.76)

5

Table 2 Frequency distribution for the continuous measure (n = 719) and binary measure (n = 724) of SRIO scores SRIO Measure Continuous 0% – No chance 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% – Definitely Would Binary No Yes

n

%

531 68 21 14 15 30 10 6 10 9 5

73.9 9.5 2.9 1.9 2.1 4.2 1.4 0.8 1.4 1.3 0.7

679 45

93.8 6.2

an email (531*0.0 = 0). However, of the 68 participants who expressed a 10% chance of requesting music files from Radley, we would expect approximately 7 of them to do so (68*0.1 = 6.8). By continuing to calculate the number of expected offenders within each SRIO level and then summing these values together, we estimate that approximately 68 participants (Σ = 67.5) will request illegal music files from Radley— again, assuming SRIO scores valid. Note that this estimated number of offenders is slightly greater than the 45 persons predicted to offend based on the binary measure of offending intentions. Such a difference may be a reflection of the degree of uncertainty thought to be embedded in continuous measures of offending intentions (Piquero & Pogarsky, 2002; Sitren & Applegate, 2007). We now turn to the number of participants who did, in fact, email Radley. Compared to Exum et al.’s (2012) study in which none of the participants made contact with the confederate, the current study had a total of three participants who requested illegal music files—all of whom did so within one hour of completing the survey (as determined by the time stamps on their completed surveys and on their submitted emails). This number of actual offenders is in stark contrast to the 68 (or even the 45) persons estimated to offend. Note that the continuous SRIO scores for these three offenders are 100%, 100% and 10%, and their responses to the binary SRIO measure were Yes, Yes and No, respectively. With this information in hand, we can begin calculating the false positive and false negative rates of SRIO scores. In order to do so, we must first determine the minimum score on the continuous SRIO scale that constitutes a true intent to offend. This minimum score will serve as our cut-point through which we can dichotomize participants’ offending intentions, thereby making it possible to construct an accuracy matrix like that shown in Fig. 1. With no clear guidance in the literature as to what this cut-point should be, we adopt the different thresholds used by Exum et al. (2012) and define the intent to offend as: (1) any non-zero SRIO score, (2) an SRIO score greater than 50%, and (3) an SRIO score of 100%. The binary SRIO measure—which is already expressed as a dichotomy—provides yet another opportunity to construct an accuracy matrix and to compute false positive and false negative rates. Collectively, these four matrices are shown in Table 3. As seen in the table, regardless of the threshold used to determine the intent to offend, the false negative rate is always extremely low and the false positive rate is consistently high. For example, when using the most liberal threshold for determining the intent to offend on the continuous scale (i.e., SRIO N 0%), the false positive rate is at its highest—0.98. When adopting the most conservative threshold (i.e., SRIO = 100%), the false positive rate drops to 0.60. While this represents a dramatic improvement, the latter rate nevertheless suggests that participants who assert they “definitely would” email the confederate are still more likely to refrain from the act than to follow-through on their intentions. When examining the binary measure of SRIO scores,

6

M.L. Exum et al. / Journal of Criminal Justice 42 (2014) 1–9

Table 3 Accuracy matrices, with corresponding false negative and false positive rates Did the Participant Intend to Offend?

Did the Participant Actually Offend?

False Negative Rate

False Positive Rate

No

Yes

No (SRIO = 0%) Yes (SRIO N 0%)

531 185

0 3

0.00

0.98

No (SRIO b=50%) Yes (SRIO N 50%)

678 38

1 2

0.001

0.95

No (SRIO b=90%) Yes (SRIO = 100%)

713 3

1 2

0.001

0.60

No (Binary Measure) Yes (Binary Measure)

678 43

1 2

0.001

0.96

the results are largely the same. Those who predict they will abstain do so with great accuracy (false negative rate = 0.001), whereas those who predict they will offend are almost always mistaken (false positive rate = .96). Finally, it is possible that those who expressed strong intentions to offend completed the survey very late in the four-week data collection period, leaving them little time to identify and submit requests for music files before the study terminated. If such a strong, positive relationship between the number of “days passed” and SRIO were found to exist, it could help to explain the high false positive rate reported above; yet, the data do not support this alternative explanation. On average, participants completed the survey within one week of receiving the recruitment email ( x ¼ 5:86 days, SD = 4.94). Furthermore, the correlation between days passed and SRIO scores was negative (r = -0.08, p b .05), suggesting that participants with strong intentions to offend completed the survey earlier rather than later in the data collection period. In fact, all participants with an SRIO score ≥ 80% completed the survey during the first ten days of data collection, and all but two participants with an SRIO ≥ 50% completed the survey within this same period of time. With nearly three weeks remaining until Radley’s supposed court date, it seems unlikely that the participants who indicated they intended to email Radley failed to do so because they did not have sufficient time.

Discussion Hypothetical scenarios and their corresponding SRIO scores are popular tools through which to study criminal decision making. Much of the research in this area finds evidence of a deterrent effect (e.g., Bachman et al., 1992; Higgins, Wilson, & Fell, 2005; Klepper & Nagin, 1989; Piquero & Pogarsky, 2002; Pogarsky, 2002; Pogarsky & Piquero, 2004; Sitren & Applegate, 2007; Thurman et al., 1993); yet, this conclusion is valid only to the degree that participants’ self-reported criminal intentions are predictive of their real world behaviors. While there is evidence to suggest that intentions are reasonably strong predictors of prosocial behaviors, Exum et al. (2012) raised questions about the predictive accuracy of individuals’ intentions to engage in an illegal activity—specifically, a certain form of music piracy. However, Exum et al.’s methodology introduced a delay between the time in which SRIO scores were recorded and when participants were actually able to commit the offense. Such a delay may account for the weak relationship between intentions and offending. Furthermore, their study also measured intentions to offend as a continuum rather than as a dichotomy, which may have introduced a source of measurement error in the SRIO scores. The current study sought to overcome these problems while also replicating the basic elements of Exum et al.’s (2012) methodology. In contrast to the original study in which no participant contacted the confederate, three participants in the current study requested illegal music files from our confederate. This is far fewer than the 45 to 68

participants expected to offend based on the distribution of SRIO scores. Furthermore, regardless of whether SRIO scores were measured along a continuum or as a dichotomy, participants who expressed little-to-no intentions to offend generally abstained from the behavior, resulting in a low false negative rate. At the same time, those who expressed strong-to-definitive intentions to offend also generally abstained, resulting in a high false positive rate. Thus, consistent with Exum et al.’s earlier research, we find that participants are far better at predicting their abstention from crime than they are at predicting their commission of a criminal act. The results from the current study—along with those from Exum et al. (2012)—raise some questions about the feasibility of using hypothetical offending scenarios to study criminal decision making. The central concern with using an SRIO score with a high false positive rate is the increased risk of committing a Type I error—that is, concluding that the perceived costs/benefits of crime are significant predictors of real world criminal behavior when in fact they are not. Although more research is needed, it is possible that hypothetical scenario research that finds evidence of a significant deterrent effect may be uncovering (in part) a methodological artifact stemming from measurement error in the dependent variable (see Bouffard et al. (2010) for other examples of possible methodological artifacts in hypothetical scenario research). We recognize that some readers may feel that the conditions described in our fictitious newspaper article created a criminal opportunity that was so risky that it encouraged abstention, thereby explaining the small number of offenders. Assuming this was true and assuming SRIO scores have strong predictive validity, then we would expect participants’ SRIO scores to be uniformly 0%. The fact that participants reported a nonzero score despite being (presumably) deterred from the offense is yet another indication that SRIO scores have questionable predictive value. There are several potential explanations for the SRIO score’s high false-positive rates. For example, some readers may feel that participants who expressed strong intentions to offend may have refrained from contacting Radley because they had access to illegal music files through other avenues. Illustratively, given that 56% of the sample reported they had previously downloaded music illegally, it may be the case that Radley’s piracy operation was simply unnecessary to many would-be offenders. Those reporting strong intentions to pirate may have gone on to engage in music piracy—but did so through more familiar venues. However, recall that our measure of self-reported offending intentions was very specific. We asked “What is the chance that you will email Arthur Radley before his March 3rd court date and request music files from his collection?” We purposefully did not inquire about the possibility of engaging in acts of piracy more generally, be it through other means or at other time periods. According to the theory of reasoned action, intentional measures that are highly specific should also be highly congruent with actual behavior (Fishbein & Ajzen, 1975; see page 369). Thus, the fact that we asked about a specific type of piracy during a specific time period should have minimized rather than inflated the SRIO score’s false-positive rates. Some readers may also wonder if participants who initially expressed intentions to email Radley subsequently sought additional information about him before making contact, and in the absence of such evidence they eventually refrained from emailing him. We anticipated this concern and designed the study in such a way to minimize the likelihood of this happening. For example, had participants searched through the university’s telephone directory, they would have found Radley’s name listed therein. Furthermore, had participants searched for information about Radley using the university website, they would have found him identified (with photo) on the Sociology department’s webpage of current Master’s students, which is exactly how he was described in the newspaper article. Lastly, had participants searched the city newspaper for an original copy of our fictitious article, they would, of course, find no record of it. However, when participants received their study materials in early February, they were told the article had appeared in print in October

M.L. Exum et al. / Journal of Criminal Justice 42 (2014) 1–9

of the previous year. Our hope was that any student who sought to find the article online but was unable to do so using the newspaper’s electronic archives would assume they were not using the correct search strategy, or that the electronic article had somehow gotten “lost” over time. We also assumed that those participants with strong intentions to offend would not have the corresponding level of self-control needed to visit the library and thumb through archived hard-copies of the newspaper in search of our particular article (see Gottfredson & Hirschi, 1990). Even so, we purposefully omitted any reference to a precise publication date and section/page number for the article in order to make the thought of this type of search more tedious and less attractive to would-be offenders. Thus, while it is quite possible that participants who sought to validate Radley’s existence on campus may have felt the evidence they uncovered was not sufficient to allay their concerns (which in turn resulted in their abstention from emailing Radley), we believe the more likely explanation for the discrepancy between participants’ intentions and behavior is also a more parsimonious one— namely, that participants over-estimated their intentions to engage in this particular act of music piracy. Given that a large body of psychological research has typically found support for the intentions/behavior relationship (e.g., Armitage & Conner, 2001; Kim & Hunter, 1993; Randall & Wolff, 1994; Sheeran & Orbell, 1998; Sheppard et al., 1988), the incongruity between intentions and behaviors uncovered in the current study appears somewhat anomalous. However, research in other fields of study has also called into question the accuracy of behavioral intentions. For example, marketing researchers have found that the predictive validity of consumers’ self-reported intentions to make a purchase or to recommend a product is inversely related to the strength of those intentions (i.e., stronger intentions are less accurate; McQuarrie, 1988; Pickering & Isherwood, 1974; Romaniuk, Nguyen, & East, 2011). As Romaniuk and colleges (2011) explain: [T]he accuracy of self-reported intentions…is substantially lower than the 100% indicated by the respondent’s certainty. However, it seems that self-reported estimates are a good indicator of behaviour in cases where the consumer’s initial response indicates that they are inclined not to act” (p. 508-509, italics in the original). These findings precisely mirror those of the current study, and suggest that the results uncovered here are not as anomalous as they may first appear. Finally, we should note that other scholars have questioned (either directly or indirectly) the accuracy of participants’ selfreported intentions—be them intentions for prosocial or deviant acts. For example, Wright, Caspi, Moffitt, and Paternoster’s (2004:189) remarked that SRIO scores may be a form of “boastful ‘trash talk.’” In other words, when in the midst of a research study, participants may seek to distinguish themselves from the typical crowd of “do-gooders” by reporting strong criminal intentions—regardless of how genuine these intentions may be. Additionally, although Kahneman (2011, 2003) does not directly speak to self-reported offending intentions, one can infer from his research on cognitive processing that the high false-positive rate uncovered here may be a function of the inherent complexity of determining one’s own SRIO score, coupled with a tendency to shirk cognitively demanding tasks. In other words, when faced with an issue that requires slow and deliberative mental calculation (e.g., “On a scale of 0 to 100, how likely are you to engage in the criminal act?”), many individuals may default to a faster, more intuitive cognitive processing system that can lead to erroneous predictions if left unchecked. Future research should explore these (and other) possible explanations for the apparent incongruity between criminal intentions and future criminal behaviors. In sum, the findings from the current study indicate that participants typically know when they are going to abstain from a criminal act, but can rarely predict when they will seize a real world criminal opportunity. Clearly, more research is needed to further assess the accuracy of

7

SRIO scores, and to do so across a diverse set of criminal opportunities. This line of future research has important implications for what we think we know about criminal decision making. Appendix A. Unformatted text from the fictitious newspaper article {NAME OF UNIVERSITY} STUDENT EMAILS FREE MUSIC University lawyers will challenge claims of email privacy in March 2011. BY DONALD M. LAND Arthur Radley has more than 35,000 digital music files in his personal collection, and he is distributing them free of charge to any student with an email address ending in “.edu”. Although it is illegal to distribute or download copyright protected music without the permission of the owner, the Masters student in {In-State University’s} Sociology program is not worried about being prosecuted. “When I write a letter using pen and paper and mail it with a stamp, Federal law mandates the letter should arrive unopened and free from tampering,” says Radley. “I believe that same level of protection also extends to communications sent from one university email account to another.” If Radley’s arguments are correct, then the emails he sends with music files attached cannot be opened by law enforcement officials. “Not even by university officials,” he adds. When asked to comment on Radley’s file sharing operation, {In-State University’s} legal counsel provided a written statement indicating they will be challenging Radley’s claims of email privacy in court. However, the case will not be heard until March 3, 2011, allowing Radley at least another four months to continue to distribute files to other college students across the country. University officials have not yet said if they will seek action against those who are downloading files from Radley. Radley began emailing music files to his fellow classmates earlier this year after writing a paper for his Public Policy Law and Management course. The topic of his paper was the 2001 litigation between Napster and the Recording Industry Association of America, in which a District Court judge shut down Napster’s free file sharing service, citing copyright infringement. In his paper, Radley concluded the judge’s ruling was correct, but then proposed an alternative strategy for sharing copyright protected files free of legal purview. Citing more than three dozen State and Federal court decisions and challenging the boundaries of the 1994 congressional wiretapping law as well as the Patriot Act, Radley concluded electronic files sent from one university email account to another are guaranteed protection against mail tampering. According to Radley, universities assign students an “.edu” email account so that the university can easily distribute official school information, such as when to register for class or to inform students their library books are overdue. Prior to this reliance on email, universities would have mailed such information to the student’s home address, and the letter would have been protected from tampering under Federal law. Now that universities are using “.edu” email accounts to distribute this official information, Radley believes communications sent through university email accounts should receive this same level of Federal protection. The result, he concludes, is that university emails cannot be opened legally by anyone other than the intended recipient. Radley notes that commercially available email accounts to which individuals voluntarily subscribe, such as gmail or yahoo, would not qualify for Federal protection. While Radley admits he is breaking the law, he claims there is no legal way to obtain evidence of his file sharing activities. “Is it against the law to distribute or download pirated material? Yes. But it is also against the law to open my university emails to see if I am doing it.” But make no mistake, he is doing it. What began as a way to share a few songs with a small circle of friends has become a grassroots peer-topeer network in which thousands of files are being emailed to college

8

M.L. Exum et al. / Journal of Criminal Justice 42 (2014) 1–9

students across the country, with some as far away as Louisiana. Last month alone, Radley filled more than 2,000 requests—all free of charge—with only about half coming from {University} students. Unlike traditional peer-to-peer networks such as Napster or iTunes, Radley does not have a searchable database of files for others to view. For now, students must request the songs they want, and Radley delivers them by email. As his collection grows closer to 36,000 songs, Radley has been able to fill most every request, be it country, rock, pop, rap or R and B. For the moment, Radley has no plans of slowing down his file sharing operation. He is receiving requests for music on a daily basis, and states he will continue to distribute the files until a court orders him to stop. “Before you buy from iTunes,” recommends Radley, “you should check with me first.” How does it work? ▪ Students with an email account ending in .edu email Arthur Radley at [email protected] ▪ In their email, students specify the songs they are seeking. ▪ Radley then emails the requested song files, free of charge. Notes 1. See Exum et al. (2012) for a discussion of potential methodological/measurement problems that may impact the interpretation of these IB correlation values. 2. In a novel study, Pogarsky (2004) examined the relationship between participants’ self-reported intentions to drive drunk and their contemporaneous, real world involvement in cheating on a trivia test. He found that those who cheated reported higher drunk driving intentions than those who did not (SRIO scores = 31% vs. 22%, respectively). However, given that SRIO scores are viewed as an indicator of committing the offense in the scenario, the criterion for validating SRIO scores should be whether or not participants subsequently engaged in the hypothetical behavior. In contrast, Pogarsky’s study sought to validate participants’ drunk driving SRIO scores against a different criterion behavior (cheating). Thus, while Pogarsky’s study reveals that SRIO scores are related to the commission of certain imprudent acts, the study cannot speak to the true predictive validity of SRIO scores. 3. Freshmen are targeted in this study because they are (arguably) more naïve to research, including research that involves deception. 4. In recent decades, low response rates have become increasingly more common in survey research (Laguilles, Williams, & Saunders, 2011), and this is especially true in studies using online surveys (Puleston, 2011). Low response rates, such as that in the current study, typically raise concerns about the generalizability of the study’s findings. However, in the current study we do not necessarily seek to assess the predictive validity of SRIO scores in a randomly-selected (and generalizable) sample of students—in large part because deterrence/rational choice studies that administer hypothetical scenarios to college students typically do not use such samples. Instead, they commonly rely on a convenience sample of students recruited through announcements made in non-randomly selected undergraduate classes and/or through fliers posted around the university campus (e.g., Bouffard, 2011; Exum, 2002; Higgins, 2005; Loewenstein, Nagin, & Paternoster, 1997; Nagin & Paternoster, 1993; Piquero & Tibbetts, 1996; Pogarsky, 2002; Pogarsky & Piquero, 2003; Rebellon et al., 2010; Sitren & Applegate, 2007; Tibbetts, 1999; Tibbetts & Herz, 1996; Wolfe, Higgins, & Marcum, 2008). We therefore believe our sample is a reasonable reflection of the types of students/student samples that have participated in prior hypothetical scenario studies. 5. Focus group feedback we received on the formatted article indicated that it appeared highly realistic, and at no time during the current study did participants express reservations about the genuineness of the article. In fact, we learned that one participant— a journalism major who worked for his university’s school newspaper—shared the article with a reporter from the paper in which the article was allegedly published. Neither questioned the article’s authenticity. 6. While Radley’s email address was placed in a call out box in order to make it more pronounced, we have no way to verify that participants actually noticed the address (or read the newspaper article, for that matter). Some readers may see this as a threat to the integrity of the study and its ability to assess the intentions/behavior relationship. We disagree, and suspect that any participant who did not attend to the article well enough to notice Radley’s email address probably had little-to-no intentions of contacting him, and that those who had strong intentions of doing so would have read the article with enough interest to have noticed the email in the call out box. Note that if those with strong intentions did somehow manage to overlook the email address in the article, they could have uncovered it on their own by conducting a simple search on the university’s website. In sum, we suspect that those who truly intended to contact Radley had the means in which to do so, and that our inability to document whether participants actually noticed Radley’s email address in the newspaper article poses no great threat to the validity of the research study.

References Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179–211. Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice-Hall. Armitage, C., & Conner, M. (2001). Efficacy of the theory of planned behavior: A metaanalytic review. British Journal of Social Psychology, 40, 471–499. Armitage, C., Conner, M., Loach, J., & Willetts, D. (1999). Different perceptions of control: Applying an extended theory of planned behavior to legal and illegal drug use. Basic and Applied Social Psychology, 21, 301–316. Bachman, R., Paternoster, R., & Ward, S. (1992). The rationality of sexual offending: Testing a deterrence/rational choice conception of sexual assault. Law and Society Review, 26, 343–372. Beck, L., & Ajzen, I. (1991). Predicting dishonest actions using the theory of planned behavior. Journal of Research in Personality, 25, 285–301. Boster, F. J. (2002). On making progress in communication science. Human Communication Research, 28, 473–490. Bouffard, J. A. (2002). The influence of emotion on rational decision making in sexual aggression. Journal of Criminal Justice, 30, 121–134. Bouffard, J. (2011). ‘In the heat of the moment:’ Mediating versus moderating relationships between sexual arousal and perceived sanctions. Journal of Crime and Justice, 34, 24–44. Bouffard, J. A., Exum, M. L., & Collins, P. A. (2010). Methodological artifacts in tests of rational choice theory. Journal of Criminal Justice, 38, 400–409. Campbell, K. E., & Jackson, T. T. (1979). The role and need for replication research in social psychology. Replications in Social Psychology, 1, 3–14. Collins, H. M. (1985). Changing order: Replication and induction in scientific practice. Beverly Hills, CA: Sage. Exum, M. L. (2002). The application and robustness of the rational choice perspective in the study of intoxicated and angry intentions to aggress. Criminology, 40, 933–966. Exum, M. L., Turner, M. G., & Hartman, J. L. (2012). Self-reported intentions to offend: All talk and no action? American Journal of Criminal Justice, 37, 523–543. Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley Publishing. Gendreau, P. (2002). We must do a better job of cumulating knowledge. Canadian Psychology, 43, 205–210. Gottfredson, M., & Hirschi, T. (1990). A general theory of crime. Palo Alto, CA: Stanford University Press. Grasmick, H. G., & Bursik, R. J. (1990). Conscience, significant others, and rational choice: Extending the deterrence model. Law and Society Review, 24, 837–861. Green, D. E. (1989). Measures of illegal behavior in individual-level deterrence research. Journal of Research in Crime and Delinquency, 26, 253–275. Higgins, G. E. (2005). Can low self-control help with the understanding of the software piracy problem? Deviant Behavior, 26, 1–24. Higgins, G. E. (2007). Digital piracy: An examination of low self-control and motivation using short-term longitudinal data. Cyberpsychology and Behavior, 10, 523–529. Higgins, G. E., Wilson, A. L., & Fell, B.D. (2005). An application of deterrence theory to software piracy. Journal of Criminal Justice and Popular Culture, 12, 166–184. Hubbard, R., & Armstrong, J. S. (1994). Replications and extensions in marketing—rarely published but quite contrary. International Journal of Research in Marketing, 11, 233–248. Kahneman, D. (2003). Maps of bounded rationality: Psychology for behavioral economics. The American Economic Review, 93, 1449–1475. Kahneman, D. (2011). Thinking, fast and slow. New York, NY: Farrar, Straus and Giroux. Kennedy, L. W., & Forde, D. R. (1996). Pathways to aggression: A factorial survey of ‘routine conflict’. Journal of Quantitative Criminology, 12, 417–438. Kim, M., & Hunter, J. E. (1993). Relationships among attitudes, behavioral intentions, and behavior: A meta-analysis of past research, part 2. Communication Research, 20, 331–364. Klepper, S., & Nagin, D. (1989). The deterrent effect of perceived certainty and severity of punishment revisited. Criminology, 27, 721–746. Laguilles, J. S., Williams, E. A., & Saunders, D. B. (2011). Can lottery incentives boost web survey response rates? Findings from four experiments. Research in Higher Education, 52, 537–553. Lamal, P. A. (1991). On the importance of replication. In J. W. Neuliep (Ed.), Replication research in the social sciences (pp. 31–36). Newbury Park, CA: Sage. Loewenstein, G., Nagin, D., & Paternoster, R. (1997). The effect of sexual arousal on expectations of sexual forcefulness. Journal of Research in Crime and Delinquency, 34, 443–473. Lowenkamp, C. T., Cullen, F. T., & Pratt, T. C. (2003). Replicating Sampson and Groves’s test of social disorganization theory: Revisiting a criminological classic. Journal of Research in Crime and Delinquency, 40, 351–373. McQuarrie, E. F. (1988). An alternative to purchase intentions: The role of prior behaviour in consumer expenditure on computers. Journal of the Market Research Society, 30, 407–437. Nagin, D. S., & Paternoster, R. (1993). Enduring individual differences and rational choice theories of crime. Law and Society Review, 27, 467–496. Nagin, D. S., & Pogarsky, G. (2003). An experimental investigation of deterrence: Cheating, self-serving bias, and impulsivity. Criminology, 41, 167–194. Paternoster, R., & Simpson, S. (1996). Sanction threats and appeals to morality: Testing a rational choice model of corporate crime. Law and Society Review, 30, 549–583. Pickering, J. F., & Isherwood, B. C. (1974). Purchase probabilities and consumer durable buying behaviour. Journal of the Market Research Society, 16, 203–226. Piquero, A.R., & Bouffard, J. A. (2007). Something old, something new: A preliminary investigation of Hirschi’s redefined self-control. Justice Quarterly, 24, 1–27. Piquero, A.R., & Pogarsky, G. (2002). Beyond Stafford and War’s reconceptualization of deterrence: Personal and vicarious experiences, impulsivity, and offending behavior. Journal of Research in Crime and Delinquency, 39, 153–186.

M.L. Exum et al. / Journal of Criminal Justice 42 (2014) 1–9 Piquero, A., & Tibbetts, S. (1996). Specifying the direct and indirect effects of low selfcontrol and situational factors in offenders’ decision-making: Toward a more complete model of rational offending. Justice Quarterly, 13, 481–510. Piquero, N., Exum, M. L., & Simpson, S. S. (2005). Integrating the desire-for-control and rational choice in a corporate crime context. Justice Quarterly, 22, 252–280. Pogarsky, G. (2002). Identifying ‘deterrable’ offenders: Implications for research on deterrence. Justice Quarterly, 19, 431–452. Pogarsky, G. (2004). Projected offending and contemporaneous rule-violation: Implications for heterotypic continuity. Criminology, 42, 111–136. Pogarsky, G., & Piquero, A.R. (2003). Can punishment encourage offending? Investigating the “resetting” effect. Journal of Research in Crime and Delinquency, 40, 95–120. Pogarsky, G., & Piquero, A.R. (2004). Studying the research of deterrence: Can deterrence theory help explain police misconduct? Journal of Criminal Justice, 32, 371–386. Puleston, J. (2011). Improving online surveys. International Journal of Market Research, 53, 557–560. Randall, D.M., & Wolff, J. A. (1994). The time interval in the intention-behaviour relationship: Meta-analysis. British Journal of Social Psychology, 33, 405–418. Rebellon, C. J., Piquero, N. L., Piquero, A.R., & Tibbetts, S. G. (2010). Anticipated shaming and criminal offending. Journal of Criminal Justice, 38, 988–997. Romaniuk, J., Nguyen, C., & East, R. (2011). The accuracy of self-reported probabilities of giving recommendations. International Journal of Market Research, 53, 507–521. Rosenthal, R. (1976). Experimenter effects in behavioral research. New York, NY: Irvington. Sheeran, P., & Orbell, S. (1998). Do intentions predict condom use? Meta-analysis and examination of six moderator variables. British Journal of Social Psychology, 37, 231–250. Sheppard, B. H., Hartwick, J., & Warshaw, P. R. (1988). The theory of reasoned action: A meta-analysis of past research with recommendations for modifications and future research. The Journal of Consumer Research, 15, 325–343. Simpson, S. S., & Piquero, N. L. (2002). Low self-control, organizational theory, and corporate crime. Law and Society Review, 36, 509–548. Sitren, A. H., & Applegate, B. K. (2007). Testing the deterrent effects of personal and vicarious experience with punishment and punishment avoidance. Deviant Behavior, 28, 29–55.

9

Strelan, P., & Boeckmann, R. J. (2006). Why drug testing in elite sports does not work: Perceptual deterrence theory and the role of personal moral beliefs. Journal of Applied Social Psychology, 36, 2909–2934. Thurman, Q., Jackson, S., & Zhao, J. (1993). Drunk-driving research and innovation: A factorial survey study of decisions to drink and drive. Social Science Research, 22, 245–264. Tibbetts, S. G. (1999). Differences between women and men regarding decisions to commit test cheating. Research in Higher Education, 40, 323–342. Tibbetts, S. G., & Herz, D. C. (1996). Gender differences in factors of social control and rational choice. Deviant Behavior: An Interdisciplinary Journal, 17, 183–208. Wolfe, S. E., Higgins, G. E., & Marcum, C. D. (2008). Deterrence and digital piracy: A preliminary examination of the role of viruses. Social Science Computer Review, 26, 317–333. Wright, B. R. E., Caspi, A., Moffitt, T. E., & Paternoster, R. (2004). Does the perceived risk of punishment deter criminally prone individuals? Rational choice, self-control, and crime. Journal of Research in Crime and Delinquency, 41, 180–213.

M. Lyn Exum is an Associate Professor in the Department of Criminal Justice and Criminology at UNC Charlotte. His research interests include criminal decision making and research methodology. In recent publications he has examined potential methodological artifacts in tests of rational choice theory, examined the role of emotion/arousal in criminal decision making, evaluated Charlotte-Mecklenburg’s domestic violence police unit, and assessed situational crime prevention strategies in commercial establishments. Diana Bailey received her M.S. degree in Criminal Justice from the University of North Carolina at Charlotte. She published in the Journal of Forensic Psychology Practice. Her research interests include homelessness, effective intervention, problem solving courts and reentry. Eric L. Wright earned his M.A. in Sociology at the University of North Carolina at Charlotte in 2012 and is currently pursuing his PhD in Sociology at Indiana University. His research interests include Political Sociology, Religion, and Law and Society.