Neurocognitive deficits associated with shoplifting in young adults

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Comprehensive Psychiatry 53 (2012) 1049 – 1055 www.elsevier.com/locate/comppsych

Neurocognitive deficits associated with shoplifting in young adults Jon E. Grant a,⁎, Samuel R. Chamberlain b , Liana R.N. Schreiber a , Brian L. Odlaug a a Department of Psychiatry, University of Minnesota Medical Center, Minneapolis, MN 55454, USA Department of Psychiatry & MRC/Wellcome Trust Behavioural and Clinical Neurosciences Institute, University of Cambridge, Cambridge CB2 2QQ, United Kingdom

b

Abstract Objectives: Shoplifting is a relatively common behavior in young adults, but the demographic and neuropsychological correlates of shoplifting remain poorly characterized in this context. Method: Non–treatment-seeking young adults (18-29 years) were recruited from the general community on the basis of having no Axis I disorders, no history of illicit substance use, and no history of conduct disorder or antisocial personality disorder. Participants were grouped according to presence or absence of shoplifting (at least 1 time over the past 12 months). Measures relating to impulsivity along with objective computerized neuropsychological measures were collected. Results: Shoplifters (n = 14) and controls (n = 95) did not differ significantly in terms of salient demographic characteristics. Compared with controls, shoplifters endorsed higher impulsivity on the Barratt Impulsiveness Scale and Eysenck Impulsivity Questionnaire, gambled significantly more points on the Cambridge Gambling Task, and showed deficits on the hardest level of difficulty on the Spatial Working Memory task. Performance on executive planning, set-shifting, and response inhibition did not differ significantly between shoplifters and controls. Conclusions: This study identified significant cognitive deficits in those with past-year shoplifting behavior even in the absence of Axis I disorders and a history of illicit drugs or alcohol. These preliminary findings inform our understanding of the neurocognitive sequelae of shoplifting and its relationship with other impulse control problems, subclinical and clinical. Future work should use longitudinal designs to examine the temporal relationship between these deficits, shoplifting behavior, other impulsive behavior, and functional impairment. © 2012 Elsevier Inc. All rights reserved.

1. Introduction

Abbreviations: CGT, Cambridge Gambling Task; IDED, Intradimensional/Extradimensional Set-Shift Task; SWM, Spatial Working Memory; SST, Stop Signal Task; OTS, One-Touch Stockings of Cambridge Task. This research is supported by a Center for Excellence in Gambling Research grant by the Institute for Responsible Gaming to Dr Grant. The funding agency had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, or approval of the manuscript. Dr Grant has received research grants from the National Institute on Drug Abuse (RC1DA028279-01) and from Psyadon Pharmaceuticals. Mr Odlaug has received honoraria from Oxford University Press and Current Medicine Group, LLC. Dr Chamberlain has consulted for Cambridge Cognition, P1Vital, Shire, and Lilly. Ms Schreiber reports no biomedical financial interests or potential conflicts of interest. ⁎ Corresponding author. Department of Psychiatry, University of Minnesota School of Medicine, Minneapolis, MN 55454, USA. Tel.: +1 612 273 9736; fax: +1 612 273 9779. E-mail address: [email protected] (J.E. Grant). 0010-440X/$ – see front matter © 2012 Elsevier Inc. All rights reserved. doi:10.1016/j.comppsych.2012.04.012

The lifetime prevalence of shoplifting appears to be fairly high. In a recent epidemiological study of adults, it was estimated that 11.3% of the general US population shoplift during their lifetimes [1]. According to a Department of Justice annual survey in 2008, more than 1 million shoplifting offenses were committed that year (http://www. fbi.gov/about-us/cjis/ucr). The National Association for Shoplifting Prevention estimates that for every incident of shoplifting that is caught by store security, another 48 incidents go undetected (http://www.shopliftingprevention. org). In 2009, the University of Florida National Retail Security Survey reported an annual loss of $11.7 billion due to shoplifting (http://soccrim.clas.ufl.edu/criminology/srp/ srp.html). A study of 3999 high school students found that 15.2% had stolen at some time in their lives [2]. Shoplifting in adults and adolescents has been associated with other antisocial behaviors, alcohol, nicotine and drug use, psychiatric comorbidity (eg, substance use disorders,

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pathological gambling, and bipolar disorder), and impaired psychosocial functioning [1,2]. Despite the fairly high prevalence of shoplifting behavior, as well as the significant morbidity associated with it, virtually no research has examined cognitive functioning in those who shoplift. Limited research from one study suggests that adolescents (n = 11) who steal have impairments in problem-solving skills (using the MeansEnds Problem Solving Test) and a cognitive bias toward inappropriate solutions to problems [3]. This study, however, recruited participants with potentially confounding Axis I disorders (eg, conduct disorder) [3]. Elsewhere, a single previous study examined neurocognitive functions in people with kleptomania (n = 15), an extreme pathological manifestation of stealing. This study reported that, in general, patients did not differ substantially from agematched normative participants in terms of cognitive abilities, quantified using a range of pen/paper tests [4]. Insights into the cognitive problems likely to be associated with shoplifting can be gleaned by considering cognitive findings in related conditions. Shoplifting shares phenomenological similarities and comorbid overlap with impulse control disorders such as pathological gambling and with substance addiction—disorders for which more research data are available. Pathological gambling has been associated with impairments on tests of frontal lobe integrity, such as tests of cognitive flexibility, response inhibition, and executive planning, but not with more general intellectual impairment [5,6]. However, perhaps the most consistent profile of impairment in pathological gambling has been on tests of decision making, such as the Bechara Gambling Task and Cambridge Gambling Task (CGT), which are dependent on the integrity of the orbitofrontal cortices and other affective-related neural circuitry [7]. Indeed, impaired decision making on the CGT extends into people at risk of developing pathological gambling, even in the absence of formal disorder [8]. These findings, along with results in people with substance use disorders suggesting similar cognitive problems (eg, [6,9]), have led support to the hypothesis of overlapping neural and neurocognitive dysfunction between pathological gambling as a putative “behavioral addiction” and substance addiction per se [6,7]. Given the extreme paucity of data regarding neurocognitive functioning in shoplifting, we investigated cognitive functions in young adults with a past-year history of shoplifting compared with controls using a range of wellvalidated translational computerized paradigms. Potential advantages of these paradigms include their validation in animal models and in human studies involving focal lesions and neuroimaging, and sensitivity to neuropsychiatric sequelae ([10]; see also descriptions of tasks below). Tasks were selected to tap those domains found to be abnormal in the context of pathological gambling and substance addictions, considered above. We included people with shoplifting behaviors but no history of impulse control disorders or substance use disorders to study their

cognitive profile in the absence of these potential confounds. We hypothesized that participants who shoplift would exhibit impairments on decision making, impulse control, memory, and executive planning, consistent with a degree of underlying dysregulation of frontostriatal circuitry and overlap with pathological gambling and substance use disorders. 2. Method 2.1. Participants Participants comprised 109 non–treatment-seeking individuals aged 18 to 29 years consecutively recruited via media advertisements for a study examining impulsivity in young adults. Volunteers were enrolled on the basis of no current or lifetime presence of Axis I disorders according to the Mini-International Neuropsychiatric Interview (MINI [11], see below), no history of illicit substance use, no history of conduct disorder or antisocial personality disorder, and an ability to understand/undertake the procedures and to provide written consent. These participants were grouped into 2 categories based on whether they had a past-year history of shoplifting (shoplifters) or had no such history (hereafter referred to as controls). The study procedures were carried out in accordance with the Declaration of Helsinki. The Institutional Review Board of the University of Minnesota approved the study and the consent statement. After all study procedures were explained to the participants, voluntary written informed consent was obtained. 2.2. Assessments 2.2.1. Psychiatric evaluation Raters assessed each participant using the MINI [11] and with a semistructured instrument to examine a range of behaviors (eg, nicotine, alcohol, and illicit substance use). Impulse control disorders (ICDs) and shoplifting behavior were examined using the adapted Minnesota Impulsive Disorders Interview (MIDI), a reliable and valid scale that has been used in young adults in previous research [12]. This instrument assesses compulsive buying, kleptomania, pyromania, intermittent explosive disorder, trichotillomania, pathological gambling, compulsive sexual behavior, and binge-eating disorder. 2.2.2. Impulsivity questionnaires Barratt Impulsivity Scale, Version 11 (BIS-11) [13,14]: This valid, reliable, 30-item, self-report measure assesses general impulsivity. Subscales of the BIS-11 include attentional impulsivity (inability to concentrate attention), motor impulsivity (acting without thinking), and nonplanning impulsivity (being present in the moment, lack of future thinking). Eysenck Impulsivity Questionnaire (EIQ) [15]: This valid, reliable, 54-item, self-report measure assesses 3

J.E. Grant et al. / Comprehensive Psychiatry 53 (2012) 1049–1055

facets of impulsivity, including impulsivity (failure to evaluate risk), venturesomeness (consciousness and acceptance of risk), and empathy (ability to identify with other peoples' experiences). 2.2.3. Cognitive assessments Participants completed the following selected cognitive paradigms from the Cambridge Neuropsychological Test Automated Battery in a fixed order (CANTABeclipse, version 3, Cambridge Cognition Ltd, Cambridge, UK). Cambridge Gambling Task [16]: The CGT measures aspects of decision making and has been shown to be sensitive to frontal lesions [17]. For example, people with ventromedial/orbitofrontal damage gamble elevated quantities of points on the task [17]. On each trial, participants are presented with a mix of red and blue boxes (10 in total) onscreen and are told that the computer has hidden a “token” behind one of them; they have to choose (a) what color of box they believe the token is hidden behind (red or blue) and (b) the number of accumulated points they want to gamble on having made the correct color choice. The proportion of red to blue boxes (“box ratio”) is varied over the task pseudorandomly to assess influence of statistical risk on decision making. On half the task, the number of points gambled increases the longer the participant waits before making this decision (ascend condition) and vice versa (descend condition). The key outcome measures for this task are the proportion of rational decisions made (choosing the most logical color—the one in the majority on the screen) and the proportion of points gambled. These 2 measures are considered across the different box ratios (red/blue) and as a function of condition (ascend/descend). The task also quantifies how many times the participant goes bankrupt and loses all his or her points overall. One-Touch Stockings of Cambridge Task (OTS) [18]: The OTS is derived from the classic Tower of Hanoi task of executive function. Executive planning is dependent on the integrity of the dorsolateral prefrontal cortices, according to data from this and similar paradigms (eg, [18,19]). Participants attempt to work out “in mind” the minimum possible number of moves it would take to rearrange a set of snooker balls in pockets shown on-screen to meet a goal arrangement indicated by the computer. They then indicate this estimated “minimum possible number of moves” by pressing the corresponding numerical button on-screen. The key outcome measure, for each level of task difficulty, is the number of attempts the volunteer makes to achieve correct solutions. Spatial Working Memory (SWM) [18]: The SWM is a test of strategy and working memory. Participants attempt to locate tokens hidden underneath boxes on-screen and try to avoid returning to boxes that previously yielded such tokens. The key outcome measures include the “total number of errors” (inappropriately returning to boxes that previously yielded tokens) and “strategy score” (lower score equates to superior strategy use) for each level of task difficulty.

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Intradimensional/Extradimensional Set-Shift Task (IDED) [20]. The IDED task includes aspects of rule learning and behavioral flexibility. On each trial, volunteers are presented with 2 stimuli and attempt to work out an underlying rule about which picture is “correct” based on feedback (“wrong” or “correct” presented after each selection). Reversal learning refers to the ability to switch from one aspect of a stimulus to another on the same dimension and is a relatively low-level type of flexibility. Extradimensional set-shifting refers to the ability to inhibit and shift attention away from one aspect of the stimuli that was important to another previously irrelevant aspect of the stimuli (conceptually more challenging). Translational research in humans and other species suggest that reversal learning is dependent on orbitofrontal cortices, whereas ED shifting is dependent on lateral aspects of the prefrontal cortices [21,22]. Primary outcome measures are the number of errors made during reversal learning and during ED shifting; errors during a control condition (ID shifting) are also examined. Stop Signal Task (SST) [23,24]: The SST is a test of response inhibition in which volunteers respond to a series of directional arrows appearing one at a time on-screen (for a left arrow, they press a left button and vice versa). On a subset of trials, an auditory “stop signal” occurs, indicating to the participants that they should try to suppress their motor response for that given trial. Inhibition on this and related tasks is dependent on a right-lateralized neural network including the inferior frontal gyrus [24,25]. This task estimates the time taken by each volunteer's brain to suppress an already triggered command (the “stop-signal reaction time” [SSRT]). Longer SSRTs correspond to worse inhibitory control. Median reaction times for go trials are also recorded. 2.3. Data analysis Differences between shoplifters and controls were examined using the following approaches depending on the nature of variables being considered: (a) analysis of variance (ANOVA) (for cognitive tasks with within-subject factors, eg, difficulty level on the executive planning task), (b) independent-sample t tests (majority of measures that were single in nature), or (c) χ 2 tests (for binary variables). This being a pilot study where the behavior of interest was limited to a small group of recruits, significance was defined as P b .05 uncorrected. Where significant differences between the study groups were identified on given measures, effect sizes were reported (Cohen D). 3. Results Of the 109 participants recruited (32.1% female; mean age = 20.5 ± 2.8 years), 14 (12.8%) were characterized as having shoplifted during the past year. There were no significant differences between the 2 groups on demographic

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Table 1 Demographic comparisons of shoplifters and controls

Age, y Sex, n (%) Female Education, n (%) High school or less Some college At least a college graduate Relationship status, n (%) Single Living together/engaged/married Race, n (%) White Other

Shoplifters (n = 14)

Controls (n = 95)

Statistic⁎

P value

21 ± 3.1

20 ± 2.8

0.73t

.467

5 (35.7)

30 (31.6)

f

.765

1 (7.1) 12 (85.7) 1 (7.1)

7 (7.4) 67 (70.5) 21 (22.1)

f

.426

14 (100) 0 (0)

91 (95.8) 4 (4.2)

f

1

12 (85.7) 2 (14.3)

83 (87.4) 12 (12.6)

f

1

All values are mean ± SD unless otherwise stated. ⁎ t: t test, f: Fisher exact test.

variables that were examined (Table 1). Analysis of the MIDI revealed that n = 2 participants (14.3%) in the shoplifting group had one or more current ICDs (1 participant had compulsive buying disorder and compulsive sexual behavior; the other had compulsive buying disorder, kleptomania, and pathological gambling). In the control group, n = 8 participants (8.4%) had one or more current ICDs according to the MIDI (4 had pathological gambling, 1 had compulsive buying, 1 had trichotillomania and pathological gambling, 1 had compulsive buying and pathological gambling, and 1 had pathological gambling plus compulsive sexual behavior). Self-reported measures of impulsivity are presented in Table 2, where it can be seen that shoplifters manifested significantly elevated motor impulsiveness on this subscale from the BIS and elevated impulsivity as indexed by this subscale from the EIQ. Group performances on the CGT are displayed in Fig. 1. In terms of the proportion of points gambled, there was a main effect of group (F = 5.923, P = .017); but there was no significant group by box ratio interaction or group by ascend_descend interaction (both P N .10). As expected, there was a significant main effect of box ratio (F = 175.569, P b .001) and of ascend_descend (F = 63.102, P b .001). In Table 2 Self-report impulsivity measures Task BIS Attention impulsiveness Motor impulsiveness Nonplanning impulsiveness EIQ Impulsivity Venturesomeness Empathy

Shoplifters Controls (n = 14) (n = 95) 16.4 ± 3.2 16 ± 3.5 25.4 ± 4.9 21.9 ± 4.2 25 ± 6.3 22.4 ± 5.1

Statistic P

ES

0.454t .651 0.77 2.788t .006 1.703t .091

9 ± 4.4 6.4 ± 4.3 2.076t .040 0.60 11.8 ± 2 10.5 ± 3.4 1.341t .183 11.8 ± 4.5 12 ± 3.3 − 0.205t .838

Abbreviation: ES: effect size (Cohen D). All values are mean ± SD unless otherwise stated.

terms of the proportion of rational decisions made, there was no main effect of group; nor was there significant group by box ratio or group by ascend_descend interaction (all P N .10). The overall effect of box ratio was not significant (P N .10), whereas the main effect of ascend_descend was (F = 7.159, P = .009). Groups did not differ significantly in terms of number of bankruptcies ([mean ± SD] shoplifters: 0.857 ± 1.292, controls: 0.527 ± 0.880; P N .10). The OTS results are indicated in Fig. 2. There was no main effect of group, nor was there a significant group by difficulty level interaction (both P N .10). As expected, there was a significant main effect of difficulty level (F = 78.957, P b .001). Group performances on the SWM task for total errors are summarized in Fig. 3. There was no main effect of group (P N .10), but there was a significant group by difficulty level interaction (F = 4.879, P = .008). There was the expected main effect of difficulty level (F = 65.078, P b .001). Groups did not differ significantly for strategy scores (shoplifters: 28.5 ± 6.24, controls: 27.17 ± 5.69; P N .10). The 2 groups did not differ significantly in terms of performance on the set-shift task for reversal errors (shoplifters: 6.86 ± 6.96, controls 5.57 ± 5.05; P N .10), ID errors (shoplifters: 0.14 ± 0.36, controls 0.44 ± 0.60; P N .05), or ED errors (shoplifters: 10.36 ± 10.05, controls 9.01 ± 9.83; P N .10). There were no significant group effects in terms of SSRTs (shoplifters: 171.1 ± 31.9 milliseconds, controls: 173.4 ± 47.8 milliseconds) and median go reaction times for the SST (shoplifters: 451.6 ± 134.1 milliseconds, controls: 436.9 ± 142.5 milliseconds) (both P N .10). 4. Discussion This is the first study to explore associations between stealing and CANTAB cognitive performance. We focused on young people who were free from Axis I disorders according to the MINI (although MIDI ICDs were permitted), antisocial personality disorder, and free from a history of substance use disorders, to avoid these potential confounding factors. The key finding was that, in comparison to controls, shoplifters displayed elevated impulsivity on questionnaire measures, gambled more points on the decision-making task (Fig. 1), and showed spatial working memory impairment (Fig. 3). These findings were of medium to large effect size (Cohen D range, 0.54-0.87). The rate of ICDs was numerically higher in the shoplifters vs the controls (14.3% vs 8.4%). Stealing is a relatively common yet potentially serious impulsive behavior, which can lead to contact with authorities and legal consequences. It is also likely that occasional stealing for some may later develop into kleptomania, an impulse control disorder characterized by failure to resist urges to steal objects not needed for personal use or monetary value [26]. The important question therefore arises as to whether stealing as a phenomenon is associated

Proportion of rational decisions

J.E. Grant et al. / Comprehensive Psychiatry 53 (2012) 1049–1055 1.05

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CGT: Proportion of rational decisions, ascend condition

1.00 .95 .90 .85 .80 9_1

8_2

7_3

6_4

Box ratio Controls

Proportion of rational decisions

1.05

Shoplifters

CGT: Proportion of rational decisions, descend condition

1.00 .95 .90 .85 .80 9_1

8_2

7_3

6_4

Box ratio Controls

Shoplifters

Proportion of points gambled

CGT: Proportion of points gambled, ascend condition 0.73

**

0.57

**

0.42 0.26 0.10

9_1

8_2

7_3

6_4

Box ratio Controls

Shoplifters

Proportion of points gambled

CGT: Proportion of points gambled, descend condition 1.00 0.90

t

0.80 0.70 0.60 0.50 0.40 0.30

9_1

8_2

7_3

6_4

Box ratio Controls

Shoplifters

Fig. 1. Performance on the CGT. **P b .01, t: .05 b P b .10, by post hoc t test following significant main effect of group in ANOVA. Effect sizes (Cohen D) were 0.65 and 0.87, respectively, for the 2 significant findings in the third panel.

with neuropsychological differences compared with people who do not steal. We predicted that stealing would be linked with dysfunction across a range of domains based on theorized overlap between stealing (as a candidate “behavioral addiction”), pathological gambling, and substance abuse. This hypothesis was partially confirmed by this study using questionnaires alongside objective computerized neuropsychological tests.

Previous work identified elevated impulsivity in kleptomania patients (n = 11) vs other psychiatric disorders (n = 29 psychiatric comparison participants, n = 60 participants with alcohol abuse/dependence) as measured by the Barratt Impulsiveness scale [27]. Specifically, the authors found numerically higher impulsivity across all 3 Barratt subscales; but only the cognitive impulsivity subscale differed significantly. Somewhat consistent with these findings, the

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Choices to correct solution

OTS: Choices to correct solution 2.50 2.25

Controls Shoplifters

2.00 1.75 1.50 1.25 1.00

1

2

3

4

5

6

Difficulty level

Fig. 2. Performance on the OTS.

current study found elevated total Barratt scores in shoplifters not fulfilling criteria for the more extreme manifestation of kleptomania. However, it was the motor subscale that appeared to be particularly impacted. It is likely that impulsive personality traits predispose toward not only subclinical but also pathological stealing. We could identify only 2 previous studies of cognitive function in people who steal—one reported impaired planning in young people who steal (Means-Ends Problem Solving Test [3]), whereas the other reported generally intact cognition in middle-aged adults with kleptomania using a range of pen/paper tests [4]. Here, we identified decisionmaking and spatial working memory deficits in people with recent history of shoplifting using translational computerized paradigms capable of fractionating specific aspects of cognition. On the CGT, groups did not differ on likelihood of making rational decisions, indicating that task comprehension was intact. However, the shoplifters gambled more points overall irrespective of box ratio. This finding is similar to previous reports in people with damage to the ventromedial prefrontal cortices, who likewise gamble disproportionate quantities of points across box ratios on this paradigm [17]. Elevated betting behavior in stealers was not severe enough to significantly impact catastrophic outcomes, as rates of bankruptcy did not differ significantly from controls. In addition to the decision-making deficit, we found some evidence that people who shoplift had impaired spatial working memory under the most challenging task conditions. SWM: Total errors 20

*

Controls Total errors

15

Shoplifters

The spatial working memory paradigm is based on foraging behavior in animals and is dependent on distributed circuitry including the prefrontal cortices (eg, [18]). Despite the decision-making and working memory deficits identified herein, shoplifters did not differ from controls on the other tasks examined: stop-signal response inhibition, set-shifting, and executive planning. Caution is warranted in concluding that these domains are unaffected in people with stealing in view of the preliminary nature of this study (small sample size for stealers and therefore limited power). It may well be that a larger study would identify deficits across a broader range of functions than the current study did. It appears however that shoplifting—at least in the current recruits—was associated with increased impulsive personality traits alongside objective and specific decisionmaking and working memory deficits, rather than more generalized impairment in the ability to suppress simple prepotent responses, to flexibly adapt behavior in light of changing environmental factors, and to appropriately plan ahead of time and coordinate behavior. It is noteworthy that studies in the context of other impulsive behaviors have found risk taking, Barratt impulsivity, and stop-signal impulsivity to be potentially dissociable (eg, [28]). Several additional limitations should be noted. With the exception of antisocial personality disorder, we did not screen for Axis II personality disorders across this cohort. Research examining personality dimensions in shoplifting addiction has demonstrated high rates of comorbid personality disorders [29] that may impact cognitive performance. Because Axis I disorders were exclusionary, however, this should limit the presence of Axis II in our sample given that Axis I and II disorders often co-occur [30]. This study did not correct for the number of multiple comparisons, as it was not powered to do so. It represents a pilot study to guide future larger studies. Furthermore, although we had valid reasons to exclude Axis I disorders in stealers, the consequence of this is that these results may not generalize to shoplifters with more extreme problems and/or Axis I disorders. In summary, this study showed that young people who shoplift manifest relative deficits in decision making and spatial working memory, in the absence of differences on demographic measures and other cognitive domains. Future work should use longitudinal designs to track whether such shoplifters develop kleptomania and other impulse control disorders over time and how this relates to neuropsychological function and any functional impairment.

10

Acknowledgment 5

None. 4

6 Difficulty level

8

References Fig. 3. Performance on the SWM. * P b .05, by post hoc t test following significant interaction between group and difficulty level in ANOVA. The effect size (Cohen D) for total errors on the 8-level difficulty level was 0.54.

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