Criminal Recidivism of Incarcerated Male Nonviolent

C h a n e t a l . P a g e | 1

This is an accepted manuscript version of an article published in the

journal: International Journal of Offender Therapy and Comparative

Criminology

Copyright to the final published article belongs to SAGE.

Chan, H. C. O., Lo, T. W., Zhong, L. Y., & Chui, W. H. (2013). Criminal recidivism of

incarcerated male nonviolent offenders in Hong Kong. International Journal of

Offender Therapy and Comparative Criminology. Advance online publication.

doi: 10.1177/0306624X13502965


Criminal Recidivism of Incarcerated Male Nonviolent

Offenders in Hong Kong

Heng Choon (Oliver) Chan1, T. Wing Lo

1, Lena Y. Zhong

1, and

Wing Hong Chui2

1 City University of Hong Kong, Kowloon, Hong Kong 2 The University of Hong Kong, Hong Kong

Abstract

Criminal recidivism of the incarcerated population in Hong Kong has rarely been

studied. The purpose of this study is to explore the recidivism rates and to identify

significant predictors of reoffending among incarcerated male offenders convicted of

a nonviolent offense in Hong Kong. Using a self-reported methodological design,

278 offenders are sampled. These offenders’ immediate past incarceration is used as

the benchmark for this recidivism study. The 1-, 2-, and 3-year recidivism rates are

21%, 68%, and 87%, respectively. The findings denote that offending history,

psychological attributes, interpersonal relationships, and environmental influences

are significant reoffending risk factors. These findings, especially the alarming failure

rates, highlight the need to seriously assess the effectiveness of intervention

strategies used by the Hong Kong correctional system in preventing future offending.

Implications for intervention strategies with emphasis on the risk factors for

recidivism are discussed.

Keywords

Recidivism, reoffending, risk factors, nonviolent offenders, reincarceration, Hong

Kong Chinese

Corresponding Author:

Heng Choon (Oliver) Chan, Department of Applied Social Studies, City University of

Hong Kong, Tat Chee Avenue, Hong Kong.

Email: [email protected]

This is an accepted manuscript version of an article published in International Journal of Offender

Therapy and Comparative Criminology. The copyright of this article is reserved by SAGE.


Introduction

Increasing attention has been placed on issues related to offenders’ propensity for

reoffending, specifically with emphasis on criminal desistance (see e.g., Farrall &

Calverley, 2006; Laub & Sampson, 2001). This criminological issue about offending,

including nonviolent offenses, is also an important one in Hong Kong. According to

the official statistics, 62,836 nonviolent offenses were reported in 2011, most of them

(56%) being theft-related offenses (Hong Kong Police Force, 2012). This trend has

been relatively consistent over the past five years (Hong Kong Police Force, 2007-

2011). According to the Hong Kong Correctional Services Department (2012), as of

December 2011, a total of 9,190 adult males and 831 young men aged 21 years and

under were imprisoned. In addition to nonviolent offenders, these numbers include

those who were incarcerated for a violent offense.

Within the last decade, empirical studies that sampled Hong Kong

incarcerated offenders have been scarce, let alone those that focus only on offenders

who were imprisoned for a nonviolent offense. Most published work focused on the

general operational functions of and services provided by the correctional services

(e.g., Jones & Vagg, 2007; Laidler, 2009; Lo, 2008; Lo, Wong, Chui, Zhong, & Senior,

2010; Tam & Heng, 2008), assistance provided to the inmates by volunteers (e.g.,

Chui & Cheng, 2012, 2013), and ex-inmates’ accounts of their imprisonment

experience (e.g., Adorjan & Chui, 2011; Chui, 2005). No study attempted to examine

the reoffending rate or risk factors of offenders, incarcerated for a nonviolent offense.

This study attempts to investigate the recidivism rate and risk factors of this often

overlooked incarcerated offender group. Prior to the discussion of this study, an

overview of the Hong Kong correctional services and factors associated with offender

recidivism are presented.

An Overview of the Hong Kong Correctional Services Department

Since 1997, Hong Kong has been a special administrative region (SAR) under the

ruling of the People’s Republic of China. It has been regarded as having one of the

lowest crime rates among developed cities or territorial regions. Contrary to

criminologists’ predictions that crime rates would be likely to soar after its handover

to the Chinese sovereignty by the British government in 1997 (Traver, 2009), Hong

Kong has evidenced a relatively low crime rate (1,081 per 100,000 in 2010) when

compared with other developed cities such as Tokyo (1,640 per 100,000) or New York

(2,257 per 100,000; Hong Kong Police Force, 2012). In view of such an arguably low

crime trend, the effort put in by the correctional system cannot be understated. In

Hong Kong, the Correctional Services Department (CSD) operates 24 correctional

institutions scattered throughout Hong Kong Island, Kowloon, the New Territories,

and outlying islands.

In addition to the discipline aspect of the correctional institutions,

rehabilitation is also emphasized (Laidler, 2009). Similar to the Hong Kong probation

system (Chan & Chui, 2012; Chui & Chan, 2011a, 2011b, 2012a), the CSD consistently


maintained “the rehabilitative ideal of imprisonment even when it became

discredited in the West” (Jones & Vagg, 2007, p. 597). The motto “we care” adopted

by the CSD has further underscored its commitment to instill rehabilitative

components in offender custody (Laidler, 2009). Hence, five units under its

Rehabilitation Division hav been established to offer rehabilitative programs for the

inmates: (a) Rehabilitation Unit (Assessment Services), (b) Education Unit, (c)

Industries and Vocational Training Section, (d) Psychological Services Section, and (e)

Rehabilitation Unit (Welfare and Counseling Services). As part of their training for

eventual community reintegration upon release, inmates are assigned to an

assortment of daily tasks, which include, among others, manufacturing and laundry

work that are fashioned to the current labor market (Laidler, 2009).

Static and Dynamic Risk Factors of Recidivism

An important objective of the correctional function of criminal justice systems is to

reduce the risk of offender recidivism. For this reason, risk factors for reoffending

should be identified and attempts made to interven with them. In order for an

intervention strategy to be effective, it is argued that it should follow the human

service principles of risk-need-responsivity (RNR) and professional discretion

(Andrew & Bonta, 2003; Andrew, Bonta, & Wormith, 2006). There are two primary

types of risk factors: static and dynamic factors. Simply put, static factors are

characteristics that are immutable, whereas dynamic factors are attributes that are

responsive to change (Bonta, 1996) through rehabilitative and therapeutic

interventions (Resnick, Ireland, & Borowski, 2004; van der Put, Stam, Hoeve, Deković,

Spanjaard, van der Laan, et al., 2012). These factors can be further subdivided into

individual- and environmental-level risk factors.

Static risk factors at the individual level include gender, intelligence,

neuropsychological attributes (Vermeiren, de Clippele, Schwab-Stone, Ruchkin, &

Deboutte, 2002; Vermeiren, Schwab-Stone, Ruchkin, de Clippele, & Deboutte, 2002),

type of offense committed, number of prior convictions (Archwamety & Katsiyannis,

1998; Chui & Chan, 2012a; Katsiyannis & Archwamety, 1997; Jung & Rawana, 1999;

Lattimore, Visher, & Linster, 1995), onset age of delinquent behavior, age of first

adjudication, and intensity of criminal careers (Ang & Huan, 2008; Cottle, Lee, &

Heilbrun, 2001; Dean, Brame, & Piquero, 1996; Loeber & Farrington, 1998; Loeber,

Farrington, Stouthamer-Loeber, & Raskin White, 2008; Vermeiren, de Clippele, &

Deboutte, 2000). Static environmental risk factors, conversely, include parental abuse

and neglect, and conflicts with parents (Benda & Tollet, 1999; Piquero, Brame, &

Moffitt, 2005).

In contrast, dynamic individual risk factors include personality dispositions

(e.g., high impulsivity, high negative emotionality, weaker social bond, and high pro-

offending attitudes; Caspi, Moffitt, Stouthamer-Loeber, Krueger, & Schmutte, 1994;

Ge, Donnellan, & Wenk, 2003; Krueger, Schmutte, Caspi, Moffitt, Campell, & Silva,

1994; Nagin & Tremblay, 1999; Willis & Grace, 2009), psychopathological attributes


(e.g., conduct and antisocial personality disorders, and psychopathic traits; Das, 2008;

Katsiyannis, Zhang, Barrett, & Flaska, 2004; Kotler & McMahon, 2005; van Dam,

Janssens, & De Bruyn, 2004; Vermeiren, Jespers, & Moffitt, 2005; Walters, 2003) and

substance use (Abnernathy, Massad, & Romano-Dwyer, 1995; Ford, 2005). Dynamic

environmental risk factors includes parental criminality (Hagell & Newburn, 1996),

criminal peers, residing in a disadvantaged neighborhood, and influences from a

poor economic and social environment (Kubrin & Stewart, 2006; Mennis & Harris,

2011; Oberwittler, 2004; Pardini, Obradovic, & Loeber, 2006; Rankin & Quane, 2000).

Research Questions

This study aims to explore the common recidivism risk factors for offenders who

were previously incarcerated (i.e., repeat offenders). The study of recidivism of

convicted offenders has been lacking in Hong Kong. To the authors’ knowledge, only

one recidivism study has been published with a Hong Kong sample within the last

decade. In Chui and Chan’s (2012a) study, a group of 92 male juvenile probationers

(aged 14 to 20 years) were examined for their recidivism rate within a six-month

follow-up period. A 30% recidivism rate was recorded within the six-month period,

with 82% and 18% re-adjudicated for a nonviolent and violent offense, respectively.

Several reoffending predictors were identified: negative affect, self-perceived life

problems, and self-esteem. Besides this study, no other research effort on this topic

has been conducted in Hong Kong. Hence, the general purpose of this study is to

extend the empirical efforts in this area by exploring the recidivism rate and risk

factors of incarcerated offenders who were incarcerated for a nonviolent offense. In

this study, the term “offender recidivism” is referred as “offender reincarceration.”

The series of questions of particular importance to the current study were as follows:

Research Question 1: How many of these incarcerated offenders were

recidivists?

Research Question 2: What is their reoffending rate?

Research Question 3: What are their common recidivism risk factors?

Time to nonviolent recidivism

Past studies have found that most offenders who recidivated typically reoffend within

the first year after their release, but the recidivism rate continues to increase in the

first five to eight years upon release (Mulder, Brand, Bullens, & van Marle, 2011). Of

note, many studies have indicated higher reoffending rates with nonviolent offenders

over a three-year period. More interestingly, a number of studies have reported

higher rates of recidivism among nonviolent offenders than other groups of

offenders (Bureau of Justice Statistics, 2002; McCoy & Miller, 2013; Washington State

Sentencing Guideline Commission, 2005). For instance, the Bureau of Justice Statistics

(2002) found an 80% recidivism rate for property offenders over a three-year


assessment period. McCoy and Miller (2013), on the other hand, reported that 52%

of male and 48% of female nonviolent offenders were rearrested an average of two

years after release, with the most common recidivistic offense being drug offenses.

Method

Participants and Procedure

From the twenty-four Hong Kong correctional institutions that include drug

addiction treatment centers, rehabilitation centers, training centers, detention centers,

and prisons, 12 institutions were selected randomly using a computerized

randomization process. The selected institutions were located in different

geographical regions: Hong Kong Island, Kowloon, New Territories, and the outlying

islands. The participants in this study were 278 incarcerated male offenders convicted

of a nonviolent offense. To explore the reincarceration dynamics of the imprisoned

offenders, all participants sampled were recidivists who were previously imprisoned.

Specifically, participants recruited were those have been re-admitted to the CSD

institutions within five years of their prior release. These participants were surveyed

once and were asked to recall information over a three-year period.

Following approval from both the CSD and university’s institutional review

board (IRB), the participants’ informed consent was acquired with no financial

rewards or benefit in other forms (e.g., reduction in incarceration term, additional

daily recreational time). For those under the age of 18, in addition to their personal

consent parental consent was also sought. Importantly, their participation in this

study was completely voluntary. An average response rate of 75% was obtained. The

recruitment process was assisted by the personnel of the CSD by seeking the

participants’ initial willingness to partake in this study. Anonymous paper/pencil

questionnaires were administered to consenting participants. Participants were

assured that their responses would be kept confidential and used only for this study.

Questionnaires were administered to a group of four to 10 participants at a time by

two trained research assistants (RAs). Both RAs had an academic background in

behavioral sciences and were trained to administer the questionnaire in a consistent

manner. Discussion among participants regarding the questionnaire content was

prohibited during the survey administration. An average of 20 minutes was used by

the participants to complete the questionnaire.

Demographic Characteristics of the Sample

Out of the total participants who aged between 17 and 75 years (M = 34.81, SD =

12.07), nearly 59% were young adults between 21 and 40 years (refer to Table 1).

Pertaining to the type of nonviolent offense committed, nearly two-thirds of them

were convicted of a nonproperty offense (e.g., drug-related and financial crimes).

About 60% of the participants were unmarried at the time of the data collection and

about 74% of them were at least secondary school educated. Roughly 41% of them


were found to have at least six previous convictions, with an average of 6.85

convictions (SD = 6.15). Their average age prior release was 32.80 years (SD = 12.29),

with most (53%) aged between 21 and 40 years. Interestingly, more than two-thirds

(72%) of the participants claimed themselves to be an active triad member.

Table 1. Sample demographic characteristics (N = 278).

Variable N Percentage

Age group (N = 275)

17 to 20 years old 35 12.7%

21 to 40 years old 161 58.5%

41 to 60 years old 72 26.2%

61 years and above 7 2.6%

Type of crime committed (N = 278)

Nonviolent property crime 98 35.3%

Nonviolent nonproperty crime 180 64.7%

Marital status (N = 274)

Single 163 59.5%

Married 76 27.7%

Separated/Divorced 31 11.3%

Widowed 4 1.5%

Highest educational level (N = 275)

Primary school or below 73 26.5%

Secondary school 187 68.0%

Vocational training 11 4.0%

University or above 4 1.5%

Number of prior conviction (N = 272)

1 to 5 convictions 160 58.8%



16 convictions and above 21 7.7%

Age of prior release (N = 278)

20 years and below 57 20.5%

21 to 40 years 148 53.2%

41 to 60 years 66 23.7%

61 years and above 7 2.5%

Self-proclaimed triad member (N = 264)

Yes 190 72.0%

No 74 28.0%


Measures

For the purpose of this study, criminal recidivism was operationally defined as

reoffending that eventually resulted in conviction and incarceration. Official

recidivism by a different time period of interest served as the binary outcome

variable (i.e., 0 = not reincarcerated, 1 = reincarcerated). Aside from examining the

reincarceration rate of imprisoned nonviolent offenders in Hong Kong1, a number of

static (e.g., offending history) and dynamic factors (e.g., psychological attributes,

interpersonal attachment and relationship, and situational criminogenic influences)

were explored to uncover potential risk factors of recidivism for offenders who

commit nonviolent offenses. A number of scales were constructed to assess the

participants’ psychological attributes (i.e., pro-offending attitudes, impulsivity, and

negative self-perception), attachment or relationship with others (i.e., familial

detachment, deviant peer attachment, and general prosocial attachment deficiency),

and potential exposure to criminogenic circumstances (i.e., domestic and community

criminogenic exposures), in addition to questions asking for the participants’

demographic information and offending history. Items of these scales were

measured on a 4-point Likert response format (1 = strongly disagree; 4 = strongly

agree)2. Of note, no significant mean differences were found in these measures

between participants who were convicted of a property and nonproperty offense.

Pro-offending attitudes (Cronbach’s α = 0.78). In this study, nine items were used

to assess the participants’ general attitudes towards offending. The overall score was

the sum of all nine items (ranging from 9 to 36), with a higher pro-offending

attitudes score denoting a higher favorable attitude towards offending. Sample items

include, “Crime allows me to get things that I want” and “Committing crime is

exciting and rewarding.” Participants in this study were averagely scored 19.38 for

this scale (SD = 4.13).

Impulsivity (Cronbach’s α = 0.51). The participants’ impulsivity was measured in two

items: “I cannot control my impulses” and “I cannot resist temptation.” The total

score ranged from two to eight points, with a higher score indicating greater

impulsivity. The alpha coefficient of this measure was below the acceptable level of

0.70 (see Cronbach, 1951). However, the alpha estimate should be interpreted

cautiously given that the Cronbach’s α mainly measures the “interrelatedness of the

items” (Sijtsma, 2009). Besides, a low internal consistency estimate could partly due

to the highly skewed distributions of included items as this reduces “the size of the

correlation between items and therefore also the alpha” (Straus & Kantor, 2005, p.

25). Importantly, Cronbach’s α is “dependent not only on the magnitude of the

correlations among items, but also on the number of items” (Streiner & Norman,

1989, p. 64). The participants scored an average point of 4.93 (SD = 1.31) in

impulsivity.


Negative self-perception (Cronbach’s α = 0.88). Nine items were utilized to assess

the participants’ negative perceptions of themselves. The overall score of this

measure was determined by summing the scores of all items, which ranged from

nine to 36 points. A higher score denotes higher negative observation or perception

of themselves. Sample items include, “I am a victim of this unjust world” and “Society

will not accept offenders like me.” The participants scored an average 20.68 points

(SD = 5.31).

Familial detachment (Cronbach’s α = 0.79). A measure that consists of four items

was used to assess the participants’ lack of positive (or poor) attachment and

relationship with their family members. The overall score of this measure ranged

from four to 16 points, with a higher score indicating poor attachment and

relationship with their family members. Sample items include, “I often have conflicts

with my family” and “My family did not and will not support me.” An average point of

8.79 (SD = 2.56) was found among the participants.

Deviant peer attachment (Cronbach’s α = 0.69). The participants’ attachment with

delinquent and deviant peers was measured with 4 items in this study. The sum of all

these items ranged from four to 16 points. A higher point in this measure denotes

greater attachment with and influence from delinquent and deviant peers. Sample

items include, “Most of my friends are criminals” and “Most of my friends are

associated with triad societies.” The participants scored an average point of 9.31 (SD

= 2.58).

General prosocial attachment deficiency (Cronbach’s α = 0.76). In order to assess

the participants’ overall lack of prosocial attachment with others, three items were

used. The sum of all items ranged from three to 12 points, with a higher score

indicating greater absence of prosocial attachment with other individuals. Sample

items include, “There is no individual that I can trust” and “I do not have anyone that

can share my problems.” On average, the participants scored 6.53 points (SD = 2.11).

Domestic criminogenic exposure (Cronbach’s α = 0.74). Two items were utilized to

assess the participants’ exposure to criminal behavior within their family setting: “I

am aware of the criminal activities of my family members” and “I am aware of the

drug-taking habits of my family members.” The total score of this measure ranged

from two to eight points, with a higher score indicating greater criminality exposure

and influence from their family members. The participants averagely scored 2.80

points (SD = 1.22).

Community criminogenic exposure (Cronbach’s α = 0.85). To assess the criminality

influence from the participants’ community, 3 items were used: “I am living in a

community full of triad members,” “I am aware of the many opportunities to commit

crime in the community where I am currently staying,” and “Crimes are regularly


occurred in my community.” The sum of score ranged from three to 12 points, with a

higher score denoting greater criminality exposure within the participants’ residential

community. On average, the participants scored 7.22 points (SD = 2.07).

Analytic strategy

In this study, several statistical analyses were performed. Pearson correlations were

used to examine the inter-relationships of different constructs. Logistic regression

was performed using the sample of 278 incarcerated male offenders convicted of a

nonviolent offense to identify the predictors of recidivism risk within the first-,

second-, and third-year following release. The offenders’ incarceration upon

reconviction was their recidivism indicator. Participants were included in different

tested time-point models according to their respective recidivism time-point. To

illustrate, 58 participants were included in the first time-point model (i.e., re-

incarcerated within one year postrelease), 188 participants in the second time-point

model (i.e., re-incarcerated within 2 years postrelease), and 243 participants in the

final time-point model (i.e., re-incarcerated within 3 years postrelease). Of note,

despite the number of previous imprisonment, the offenders’ immediate past

conviction that led to incarceration was used as the benchmark for the analyses of

their recidivism rates and risk factors. Static (i.e., number of prior conviction and age

of prior release) and dynamic (i.e., pro-offending attitudes, impulsivity, negative self-

perception, familial detachment, deviant peer attachment, general prosocial

attachment deficiency, domestic criminogenic exposure, and community

criminogenic exposure) factors as independent variables were entered in three

multivariate analytic models. Pearson correlations of the tested constructs were

computed and findings did not reveal any correlations at or above 0.70, indicating no

collinearity.

Results

Offending History, Psychological Characteristics, Interpersonal Relationships,

and Criminogenic Exposures

Table 2 presents the inter-scale relationship of different constructs of interest: two

offending history constructs (i.e., number of prior conviction and age of prior release),

three psychological characteristics (i.e., pro-offending attitudes, impulsivity, and

negative self-perception), three interpersonal attachment constructs (i.e., familial

detachment, deviant peer attachment, and general prosocial attachment deficiency),

and two criminogenic exposure constructs (i.e., domestic criminogenic exposure and

community criminogenic exposure). Significantly, the offenders’ number of prior

convictions and age at time of prior release were positively correlated with their

negative self-perception (r = 0.24 and r = 0.28, p < .01), familial detachment (r = 0.21

and r = 0.19, p < .01), and general prosocial attachment deficiency (r = 0.24 and r =

0.25, p < .01), respectively. Interestingly, all psychological characteristics,


interpersonal attachment, and criminogenic exposure constructs were significantly

and positively inter-correlated, with the strength of the correlational effects ranging

from 0.24 to 0.67 (p < .01).

Table 2. Pearson correlations of the observed indicators of convicted offenders of

nonviolent property and nonproperty crime (N = 278).

Indicators NC AR PO IP NS FD DP AD DC CC

Number of prior 1.00

conviction (NC)

Age of prior release 0.49** 1.00

(AR)

Pro-offending 0.12 0.07 1.00

attitudes (PO)

Impulsivity (IP) 0.12 0.03 0.53** 1.00

Negative self- 0.24** 0.28** 0.58** 0.41** 1.00

perception (NS)

Familial detachment 0.21** 0.19** 0.43** 0.38** 0.59** 1.00

(FD)

Deviant peer 0.07 -0.05 0.57** 0.50** 0.56** 0.47** 1.00

attachment (DP)

Attachment 0.24** 0.25** 0.43** 0.24** 0.55** 0.67** 0.38** 1.00

deficiency (AD)

Domestic 0.11 0.08 0.41** 0.23** 0.28** 0.31** 0.42** 0.27** 1.00

criminogenic (DC)

Community 0.07 0.02 0.52** 0.45** 0.50** 0.37** 0.59** 0.25** 0.32** 1.00

criminogenic (CC)

** p < .01

Offending History and Reincarceration Rates

The offenders’ number of prior convictions and age at prior release, and their one-

year, two-year, and three-year reconviction rates were examined for their inter-

indicator relationships (refer to Table 3). The offender’s age at prior release was

positively related with their number of prior convictions (r = 0.49, p < .01).

Surprisingly, only the offenders’ number of prior convictions was positively correlated

with their reconviction rate within the first- (r = 0.06, p < .05), second- (r = 0.16, p

< .01), and third-year (r = 0.09, p < .05) upon release.

Identifying the Reincarceration Risk Factors of Nonviolent Offenders

Table 4 presents the findings of three logistic regression models with the odds ratios

(ORs) whereby reincarceration, at different time periods, is the predicted outcome. In

this study, adjusted ORs were computed, exp(B) – 1 X 100 = adjusted OR, to report

the statistically significant effects on the percentage change in the odds. In terms of

the offenders’ criminal background, their number of prior conviction was found to be

the only significant predictor of their reoffending risk. To illustrate, when a unit


increased in the number of prior convictions, the offenders’ odds of reincarceration

was increased by 6% within two years and 10% within three years upon their release.

The offenders’ negative self-perception and impulsivity were found to be significant

psychological attribute predictors of their reincarceration risk. Unexpectedly, every

one-unit increase in the offenders’ negative self-perception resulted in the odds of

reoffending that led to reincarceration decreasing by 9% within the first year, and

14% within the second and third year upon release. In contrast, the odds of the

offenders being re-incarcerated within three years following release was increased by

47% if they were impulsive.

In relation to the offenders’ relationship with others in predicting their

recidivism risk, when the offenders were lacking positive attachment with their

families, the odds of their being re-incarcerated within the first year following release

increased by 20%. Besides, the odds of the offenders being re-incarcerated within

two years after release were found to increase by 21% and 20% when they were

associated with deviant peers and absence of prosocial attachment with others,

respectively. Pertaining to the situational recidivism risk factors, when the offenders

were exposed to criminogenic incidents within their community, the odds of

reoffending and eventually to be re-incarcerated increased by 34% within the third

year upon release. However, unexpectedly, every one-unit increase in the offenders’

exposure to criminogenic incidents within their family resulted in the odds of their

reincarceration decreasing by 40% within three years upon release.

Overall, chi-square analyses of these 3 testing models indicated significant

models fit (χ2 = 20.69, p < .05 for Model I, χ2 = 32.01, p < .001 for Model II, and χ2 =

24.72, p < .01 for Model III). The Hosmer-Lemeshow Test (Hosmer & Lemeshow,

2000) of all models also suggested no difficulties with the fit model. The area under

the curve (AUC) of the receiver operating characteristics (ROC) yielded values of 0.71

for Model I, 0.72 for Model II, and 0.69 for Model III, suggesting that all these models

reached an adequate level of predictability, specificity, and sensitivity (see Kleinbaum

& Klein, 2010).

Table 3. Pearson correlations of the observed indicators (N = 278).

Indicators NC AR 1YR 2YR 3YR

Number of prior conviction (NC) 1.00

Age of prior release (AR) 0.49** 1.00

1-year reconviction rate (1YR) 0.06* -0.02 1.00

2-year reconviction rate (2YR) 0.16** 0.10 0.36** 1.00

3-year reconviction rate (3YR) 0.09* 0.01 0.20** 0.55** 1.00

* p < .05, ** p < .01


Table 4. Logistic regression of convicted offenders’ 1-year, 2-year, and 3-year official recidivism rates (N = 278).

Predictor variables Model I (1-year recidivism) Model II (2-year recidivism) Model III (3-year recidivism)

B SE OR LCI, UCI B SE OR LCI, UCI B SE OR LCI, UCI

Number of prior 0.03 0.03 1.03 0.97, 1.09 0.06 0.03 1.06* 1.00, 1.13 0.09 0.05 1.10* 0.99, 1.21

conviction

Age of prior release -0.01 0.02 0.99 0.96, 1.02 0.02 0.01 1.02 0.99, 1.05 -0.01 0.02 1.00 0.96, 1.04

Pro-offending attitudes -0.07 0.06 0.93 0.83, 1.04 -0.04 0.05 0.97 0.88, 1.06 -0.07 0.07 0.94 0.82, 1.07

Impulsivity 0.20 0.15 1.22 0.90, 1.65 0.15 0.13 1.16 0.89, 1.51 0.39 0.20 1.47* 1.00, 2.16

Negative self-perception -0.09 0.05 0.91* 0.83, 1.01 -0.15 0.04 0.86*** 0.79, 0.94 -0.15 0.06 0.86* 0.76, 0.97

Familial detachment 0.18 0.10 1.20* 1.00, 1.45 0.06 0.08 1.06 0.90, 1.25 0.01 0.11 1.01 0.81, 1.26

Deviant peer attachment 0.05 0.09 1.06 0.87, 1.26 0.19 0.08 1.21* 1.03, 1.42 -0.02 0.12 0.98 0.77, 1.24

Prosocial attachment 0.17 0.11 1.19 0.96, 1.47 0.18 0.10 1.20* 0.98, 1.46 0.23 0.15 1.26 0.94, 1.70

deficiency

Domestic criminogenic 0.24 0.14 1.27 0.96, 1.69 -0.09 0.13 0.91 0.70, 1.18 -0.51 0.18 0.60** 0.43, 0.86

exposure

Community criminogenic -0.10 0.11 0.91 0.74, 1.12 0.12 0.09 1.12 0.94, 1.34 0.31 0.13 1.34* 1.05, 1.75

exposure

–2 log likelihood 258.58 308.95 180.24

Model chi-square 20.69* 32.01** * 24.72**

Hosmer–Lemeshow test χ2 (8) = 9.81, p = .28 χ2 (8) = 4.46, p = .81 χ2 (8) = 9.52, p = .30

Nagelkerke R2 0.11 0.11 0.16

AUC 0.71 0.72 0.69

Note: Odds ratio (OR), lower confidence interval (LCI), upper confidence interval (UCI).

* p < .05, ** p < .01, *** p < .001


Discussion

This study is important in not only in contributing to the repertoire of knowledge

from an empirical perspective, but also informing the field practitioners of the

findings in order facilitate the development of correctional criminology in Hong Kong.

Perhaps, these findings may be of practical utility in other countries as well.

Particularly, this study of recidivism was substantial for at least two reasons. First,

identification of key risk factors specific to the reincarceration of nonviolent

offenders is critical for intervention planning to prevent future criminal behavior

(Harland, 1996), whereby evidence indicates that programs and services targeting

specific reoffending risk factors are five times more effective than those without an

adequate conceptual model (Izzo & Ross, 1990). Second, according to Duncan et al.

(1995), identification of reoffending risk factors could help to determine the

suitability in the placement in different intervention programs based on the

differential criminogenic needs of the offenders. Evidence suggests that dynamic risk

factors are likely to reduce as age increases, which denotes the importance of early

intervention (van der Put, Deković, Stams, van der Laan, Hoeve, & van Amelsfort,

2011).

Overall, the findings indicate that the effect of dynamic risk factors appeared

to be more dominant in determining the propensity to reoffend that led to the

reincarceration among this group of nonviolent offenders. Interestingly, a display of

positive self-perception was considered to be a significant predictor of recidivism

across three tested time points. Unexpectedly, this result was inconsistent with many

past studies. Positive self-perception or evaluation in this context could be referred

to as having a high self-esteem. Existing literature indicates that low self-esteem

predicts offending persistency (e.g., Benda, 2001; Caspi, et al., 1994; Krueger, et al.,

1994). Perhaps, the finding of this study could be explicated from a cognitive model

of offending behavior. Baumeister (1997) reasoned that offending behavior is likely

to result from an inflated sense of self-esteem or grandiosity as part of the “macho”

cover-up of the individual’s embarrassment or low self-esteem (see also Walker &

Bright, 2009). This phenomenon has been evidenced more in relation to violent

behavior (e.g., Beck, 1999; Gillespie, 2005; Salmivalli, 2001). Furthermore, an

acceptance of offending behavior, particularly with violence, was also found to be

associated with a false consensus that validates offending behavior as a response to

the strength of insult or humiliation imposed by others, which possibly falsely inflate

the level of self-esteem (Walker, 2005; Walker & Gudjonsson, 2006).

Additionally, substantial differences in risk factors were observed in the

participants’ reoffending predictors based on different time periods. In line with the

extant literature of the importance of positive family relationship in reducing the

recidivism risk (e.g., Benda & Tollett, 1999; Watt, Howells, & Delfabbro, 2004),

participants who were having a poor attachment and social bonding with their family

were in higher likelihood to reoffend and be re-incarcerated within a 12-month

period upon release when they need close support to help them reintegrate into the

community. Those who re-incarcerated for an offense committed up to 2 years


subsequent to release, on the other hand, were found to have a weaker prosocial

attachment pattern as indicated by closely associated with deviant peers and a lack

of prosocial relationship with others. These predictive factors for reoffending were

also previously reported (e.g., Dishion, McCord, & Poulin, 1999; Mennis & Harris,

2011). These findings are substantially in line with Hirschi’s (1969) social control

theory, which essentially maintains that delinquent and criminal behavior occurs

because of weak social bonds with conventional society and individuals. Moreover,

continuing differential association or social interaction with deviant peers was also

asserted to be an important predictor of persistence in offending in Akers’ (1998)

social learning theory.

However, in the current study relatively different recidivism predictor factors

were observed for offenders who were re-incarcerated within a three-year period. In

addition to impulsivity as a significant predictor of persistent offending, as was

theorized in Gottfredson and Hirschi’s self-control theory (1990) and consistently

found in other studies (e.g., Miller-Johnson, Coie, MAumary-Gremaud, Lochman, &

Terry, 1999; Nagin & Tremblay, 1999; see Lee & Hinshaw, 2004 for an exception),

environmental influences seemed to be more dominant as indicated by both

domestic and community exposures to criminality. These findings were consistent

with the literature, whereby the familial (e.g., Hagell & Newburn, 1996; Huan, Ang, &

Lim, 2010; Katsiyannis, et al., 2004) and neighborhood (e.g., Kubrin & Steward, 2006;

Mennis, Harris, Obradovic, Izenman, Grunwald, & Lockwood, 2011) effects were

reported to at least partly predict a reoffending propensity. It is notable that the

number of prior convictions was the only significant static recidivism risk factor for

the two- and three-year risk of reoffending. This predictor was also previously

reported (e.g., Andrew & Bonta, 1998; Benda, Corwyn, & Toombs, 2001; Hoge, 1999;

Jung & Rawana, 1999; Lattimore, et al., 1995).

Looking at the reincarceration rates at three different time periods, an

interesting trend emerged. Within a 12-month post-release period, 21% of the

nonviolent offenders were reconvicted and reincarcerated. Compared with other

studies (e.g., a 30% six-month probation violation rate in 92 male juvenile

probationers in a study by Chui & Chan, 2012a; a 31% one-year violent failure rate

found in 618 mentally disordered male inmates by Harris, Rice, & Quinsey, 1993; a

26% recidivism rate in 328 juvenile probationers by Onifade, Davidson, Campbell,

Turke, Malinowski, & Turner, 2008; and a 46% 8-month failure rate found in 104

juvenile offenders by Vermeiren, et al., 2000), this one-year reoffending rate was

arguably low. Perhaps it could be reasoned that it is associated with the nonviolent

nature of the initial index offense. This reincarceration rate increased to 68% within

two years post-release. Interestingly, this reoffending rate was relatively consistent

with the rate found in other comparable studies (e.g., 65.2% rate of recidivism found

in 414 serious violent juvenile offenders by Benda, et al., 2001; a 70.1% failure rate

that excluded misdemeanors and vandalism found in 728 serious juvenile offenders

by Mulder, et al., 2011). Within three years post-release, 87% of the ex-convicts in

this study were reincarcerated. This rate was fairly high compared with other three-


year follow-up studies (e.g., a 38.5% failure rate found in 480 male boot campers by

Benda, 2001; a 15% rate of recidivisim and parole violations found in 299

incarcerated juvenile offenders by Katsiyannis, et al., 2004; a 67.5% reoffending rate

found in 272,111 former inmates in 15 states in the United States, with 73.8% of

property offenders by Langan & Levin, 2002). However, readers should be mindful of

different operational definitions of “recidivism” used in these studies.

Implications of the Findings

Nearly all of the ex-inmates examined in this study were re-incarcerated within three

years subsequent to their release. This high reincarceration rate was documented

despite the nonviolent nature of the offenders’ initial index offense, although violent

offenders have been found to have a higher risk of recidivism (e.g., Loeber &

Farrington, 2000). Thus, serious concerns should be raised about the operational

purposes and the effectiveness of the Hong Kong correctional services. The current

rehabilitative strategies ought to be strengthened. Ideally, more refined and

evidence-based intervention programs are required tailored to the criminogenic

needs of different offenders.

More efforts need to be attempted to efficiently target incarcerated offenders’

reoffending risk factors. The offenders’ dynamic criminogenic needs should be

prioritized. As evidenced, a number of domains such as the offenders’ psychological

conditions, interpersonal relationships, and environmental influences are critical in

impacting their propensity to recidivate. None of these domains should be

intervened with separately or individually, as an accumulation of risk factors in

multiple domains increases the probability to not just reoffend, but to behave

criminally in general (Loeber, Slot, & Stouthamer-Loeber, 2008). Thus, all intervention

target areas should be closely monitored concurrently during the process. Although

static risk factors are not amenable to designed change, they should also be

considered when conceptualizing and planning of intervention efforts.

To illustrate, intensive psychological services such as positive psychological

self-development in the areas of consequential thinking patterns, recognition of and

sensitivity to the feelings of others to target the offenders’ inflated self-esteem, and

interpersonal cognitive problem-solving interventions and anger management that

aim to reduce impulsivity and instantaneous anger or low frustration tolerance

should be tailored made for each offender to meet his distinctive criminogenic needs.

Social skills training should be stressed to foster prosocial relationships with others,

especially with family members. Intervention strategies that focus on healthy family

functioning could help to foster positive familial social bonding, which in turn may

reduce a reoffending propensity aided by family support to desist from offending

(Chan & Chui, 2012, 2013; Chui & Chan, 2011b, 2012a, 2012b, 2013a, 2013b).

Moreover, efforts should be made to raise awareness of peer influence, mainly those

who involved in delinquency (Benda, 2001).

Limitations and Future Research Directions


Several cautionary methodological caveats should be noted. This study was

retrospective and cross-sectional in nature. In future research, a prospective

longitudinal design with repeated measures should be considered. By doing so, the

persistence of criminal behavior could be extensively studied. In this study, only a

small group of incarcerated nonviolent offenders was examined. More importantly,

the female population was not sampled in this study. Thus, findings reported here

cannot be generalized to all incarcerated offenders convicted of a nonviolent offense.

For future studies, it will be meaningful to investigate whether the current findings

hold for not just a larger sample of incarcerated nonviolent offenders, but also across

genders. In line with this issue, current findings are limited to the incarcerated

population. Potential differences may be present for those who were initially arrested

but not convicted. Therefore, it will be fruitful to explore the similarities and

differences of these two groups of nonviolent offenders. Moreover, the present study

was limited to the examination of the recidivism profile of nonviolent offenders. The

sample of violent offenders collected in this study was insufficient to perform sound

statistical comparative analyses with nonviolent offenders. Hence, future research

may consider exploring the differences between incarcerated nonviolent and violent

offenders for their potential differential reoffending risk factors.

With regard to the predictive effect of the tested offending history,

psychological correlates, and environmental influences, the effects of these risk

factors were limited by the use of self-reported information. It is noteworthy that

offenders have a predisposition to under-report their criminal behavior and to

normalize their perceived attitudes toward criminal conduct (Breuk, Clauser, Stams,

Slot, & Doreleijers, 2007). However, the use of official data as the benchmark for the

recidivism rate also has an inherent risk of underestimating the actual nature of an

offenders’ involvement in criminal activities. Their reoffending behaviors are not

always detected, which leads to being under-registered in the official systems (van

der Put, et al., 2011). Thus, future research should consider using both official and

self-reported data to obtain findings with a higher predictive power. Moreover,

current findings were limited with the use of the regression approach in predicting

recidivism outcomes. Other routinely used probabilistic analytic methods such as cox

regression models and survival time to failure models (see Schmidt & Witte, 1988 for

a review) could be considered in future research to produce findings with better

explanatory power. Schmidt and Witte (1989) even suggested the application of

split-population survival time models in studying recidivism. This method is capable

of avoiding the over-prediction of a long-run failure rate, which is a major limitation

in most traditional failure time models.

In summary, these limitations notwithstanding, the current findings have

contributed to an under-researched component of the Hong Kong correctional

system. Findings of this study indicate that the offenders’ reoffending propensity

accounts for a multitude of risk factors, composed of their offending history,

psychological attributes, interpersonal relationships, and environmental influences.

Importantly, implications for correctional practice from an intervention perspective


and in penal policy making and refinement targeting nonviolent offenders can be

drawn from this study. Current findings also highlighted the importance of post-

release services provided by social service workers for this group of offenders to

prevent potential relapses. The motto of the Hong Kong CSD is to “support

rehabilitative offenders for a more inclusive society.” Undoubtedly, released inmates

potentially face a number of pressing challenges upon their release, including

locating accommodation, securing employment, receiving follow-up treatment, and

for some, complying with the supervision terms (Kubrin & Steward, 2006). Hence,

resources, services, and amenities from both the correctional postrelease services

and from the community are needed for ex-inmates to successfully reintegrate into

conventional society, and ultimately to desist from criminal conduct.

Notes

1. According to Hong Kong criminal law, nonviolent offending behavior includes

property (e.g., burglary, snatching, pickpocket, shop theft, criminal damage, and

deception) and nonproperty offenses (e.g., vice/brothel keeping, sexual

procuration/abduction, illegal sexual activity, fighting, illegal possession of

weapons, illegal possessions of illegal drugs, resistance to police arrest, admission

of being a member of a triad society, violation of probation order, use of other’s

identity, and public disorderly conduct). A member of a triad society can be

simply referred to as a member of a Chinese criminal organization or gang.

2. A complete measurement items will be provided upon request made to the

authors.


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Documents

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