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. Author manuscript; available in PMC: 2017 Jun 1.
Published in final edited form as: J Crim Justice. 2016 Feb 15;45:94–100. doi: 10.1016/j.jcrimjus.2016.02.012

Risk Factors and Risk-Based Protective Factors for Violent Offending: A Study of Young Victorians

Sheryl A Hemphill 1, Jessica A Heerde 2, Kirsty E Scholes-Balog 3
PMCID: PMC4912019  NIHMSID: NIHMS760758  PMID: 27325904

Abstract

Purpose

The present study aims to examine risk factors and risk-based and interactive protective factors for violent offending in a group of 437 young Australians.

Methods

Participants were recruited into the study when they were in Grade 5 (10-11 years) and followed up almost annually until young adulthood (18-19 years). Measures of violent offending, risk and protective factors, and demographics were obtained through a modification of the Communities That Care youth survey. The data collected enabled identification of groups of students at-risk of violent offending according to drug use, low family socioeconomic status, and antisocial behavior.

Results

Results showed that there were very few associations between the risk factors and risk-based protective factors measured in this study (e.g., belief in the moral order, religiosity, peer recognition for prosocial involvement, attachment to parents, low commitment to school, and poor academic performance) and later self-reported violent offending. There were no statistically significant interactive protective factors.

Conclusions

Further longitudinal analyses with large sample sizes are needed to examine risk factors and risk-based protective factors and interactive protective factors in at-risk groups. The findings support the need for multi-faceted prevention and early intervention approaches that target multiple aspects of youth’s lives.

Keywords: violent offending, risk factors, risk-based protective factors, longitudinal study, cumulative risk index, cumulative protective index

Introduction

Youth violence, particularly violent offending, is a major health and social issue in many countries around the world (Katsiyannis, Ryan, Zhang, & Spann, 2008). The rate of juvenile offending has increased in Australia every year since 2004, with rates of assault increasing by 48% between the periods of 1996-97 and 2006-07 (Australian Institute of Criminology, 2009). There are a range of costs associated with violent offending for the offender, the victim, and the broader community. Progress has been made in understanding the risk factors for violent offending across a range of contexts including intra-individual, family, peer groups, schools, and communities. Less is known about the protective factors that may reduce the likelihood of violent offending and/or moderate the effect of risk factors on violent offending. The current paper will seek to add to the existing literature by examining changeable protective factors measured in late childhood and mid-adolescence for violent offending in late adolescence and young adulthood.

Risk and Protective Factors for Violent Offending

It has been noted that the terminology used in relation to risk and protective factors is not consistent in the literature (Lösel & Farrington, 2012). Protective factors are usually conceptualized as variables thought to mitigate the impact of risk factors on later outcomes. Risk factors are prospective predictors that increase the likelihood that an individual or group will engage in problem behaviors such as violent offending (National Crime Prevention, 1999). In the current article, the authors draw on the conceptualization of protective factors described by Farrington and Ttofi (2011), distinguishing between risk-based protective factors (factors that predict a low probability of negative outcomes such as violent offending) and interactive protective factors (factors that moderate the effects of risk factors (e.g., poor family management) on negative outcomes including violent offending; (Farrington & Ttofi, 2011)).

Modifiable risk and protective factors within the domains of the individual, peer group, family, school, and community have been linked to violent behavior in young people. Individual factors associated with violent behavior and offending include impulsivity (Herrenkohl et al., 2000; Vassallo et al., 2002), early concentration problems and hyperactivity (Hawkins et al., 2000; Hemphill et al., 2009), low achievement at school (Hemphill et al., 2011; Hemphill, Toumbourou, Herrenkohl, McMorris, & Catalano, 2006), low commitment to school (Hawkins et al., 2000; Herrenkohl, Lee, & Hawkins, 2012), belief in the moral order (Catalano & Hawkins, 1996), and attendance at religious activities (Herrenkohl et al., 2003). In the context of the peer group, interaction with prosocial peers is predicted to be associated with less violent offending (Catalano & Hawkins, 1996). It is well established that having antisocial and/or violent friends is associated with violent behavior (Hawkins et al., 2000; Hemphill et al., 2009). Within the family, conflict has been associated with violent behavior (Hemphill et al., 2009), whereas good family management is linked with less violent and antisocial behavior (Herrenkohl et al., 2003; Sullivan, 2006). Finally, the Social Development Model (Catalano & Hawkins, 1996) postulates that bonding, opportunities to participate in prosocial activities, and recognition for prosocial activities in all contexts (peer group, family, school, community) are associated with less antisocial and violent behavior and engaging in prosocial behavior

The Present Study

Here, risk factors and risk-based and interactive protective factors measured in Grades 5 and 9 for self-reported violent offending in Grade 11 and young adulthood (18-19 years) were examined among an Australian sample. Analyses were completed separately for different groups at-risk for violent offending: drug users, participants from low socioeconomic status (SES) families, and participants who reported high levels of antisocial behavior in Grade 9. It was hypothesised that the risk factors and risk-based and interactive protective factors for violent offending would be similar across at-risk groups, and that these factors would span individual, peer, family, school, and community domains.

Method

Participants

Data from Victorian participants of the International Development Study (IYDS) were analysed in this study. The IYDS is a longitudinal study of antisocial and prosocial behaviours among adolescents in Victoria, Australia, and Washington State, United States (U.S.). The Victorian sample consisted of 927 (481 female, 446 male) students first surveyed in 2002 at age 10-11 years (M = 11.0, SD = .41). These students were re-surveyed in 2003-4, 2006-8, and 2010-12. Of the original sample, 791 (85%) completed the survey at age 16-17 years (367 males, 424 females; Mage = 17.0, SDage = 0.4), and 809 (87%) completed the survey at age 18-19 years (365 males, 444 females). Original sampling and recruitment for the IYDS has been described elsewhere (McMorris, Hemphill, Toumbourou, Catalano, & Patton, 2007). Briefly, the IYDS used a two-stage cluster sampling approach: 1) random selection of public and private schools stratified according to geographic location, using a probability proportionate to grade-level size sample procedure; and 2) one class at each grade level (Grade 5, 7, and 9), within each school, was selected at random.

Measures

The self-report measures of violent offending, risk factors and risk-based protective factors, and demographic variables were contained within a modified version of the Communities that Care (CTC) survey used in the IYDS which has been adapted for use in Victoria (Hemphill et al., 2011). All risk and risk-based protective factors were scored so that high scores reflected greater occurrence of the outcome (e.g. poor academic performance, high opportunities for prosocial involvement in the family). Table 1 describes the scales measured, example items, Cronbach’s alphas, and descriptive statistics.

Table 1.

Descriptive statistics and rates of Grade 5 and 9 risk factors and risk-based protective factors, at-risk groups, and violent offending in Grade 11 and young adulthood (n = 437).

Grad
e 5
Grad
e 9

No.
of
scal
e
item
s
Respons
e
options
Cronbach
’s alpha
(G5, G9)
Low
(n)
Low
(%)
Hig
h
(n)
Hig
h
(%)
Low
(n)
Low
(%)
Hig
h
(n)
Hig
h
(%)
Individual
factors
Belief in the
moral order
(e.g., I think
it is okay to
take
something
without
asking if you
can get away
with it)
4 1-4
(definite
ly
no to
definitel
y
yes)
.56, .69 267 61.1
0
170 38.9
0
261 59.7
3
176 40.2
7
Religiosity^
(e.g., How
often do you
attend
religious
services or
activities?)
2 1-4
(never to
about
once a
week or
more)
n/a, .83 303 69.3
4
134 30.6
6
232 53.0
9
205 46.9
1
Interaction with
prosocial
peers
(e.g., How
many of
your best
friends have
tried to do
well in
school?)
2 0-4
(none of
my
friends
to 4 or
more of
my
friends)
.30, .45 266 60.8
7
171 39.1
3
309 70.7
1
128 29.2
9
Recognition
for prosocial
involvement
(e.g., What
are the
chances you
would be
seen as cool
if you
worked hard
at school?)
2 1-5 (no
to very
good
chance)
.41, .38 320 73.2
3
117 26.7
7
236 54.0
0
201 46.0
0
Poor
academic
performance
(e.g., Are
your school
grades better
than the
grades/mark
s of most
students in
your class?)
2 1-4
(definite
ly
no to
definitel
y
yes)
.44, .66 81 18.5
4
365 81.4
6
88 20.1
4
349 79.8
6
Low
commitment
to school
(e.g., How
often do you
feel that the
schoolwork
you are
assigned is
meaningful
and
important?)
7 1-5
(never to
almost
always)
.69, .78 73 16.7
0
364 83.3
0
144 32.9
5
293 67.0
5
High
impulsivity
(e.g., It’s
important to
think before
you act)
3 1-4
(definite
ly
no to
definitel
y
yes)
.53, .55 95 21.7
4
342 78.2
6
139 31.8
1
298 68.1
9
Family
factors
Parent
attachment
(e.g., Do
you feel
very close to
your father?)
4 1-4
(definite
ly
no to
definitel
y
yes)
.70, .79 290 66.3
6
147 33.6
4
316 72.3
1
121 27.6
9
Opportunitie
s for
prosocial
involvement
(e.g., If I had
a personal
problem, I
could ask
my mum or
dad for help)
3 1-4
(definite
ly
no to
definitel
y
yes)
.65, .77 299 68.4
2
138 31.5
8
371 92.0
6
32 7.94
Recognition
for prosocial
involvement
(e.g., My
parents
notice when
I am doing a
good job and
let me know
about it)
4 1-4
(definite
ly
no to
definitel
y
yes)
.63, .77 271 62.0
1
166 37.9
9
280 64.0
7
157 35.9
3
Poor family
management
(e.g., The
rules in my
family are
clear)
9 1-4
(definite
ly
no to
definitel
y
yes)
.70, .82 97 22.2
0
340 77.8
0
93 21.2
8
344 78.7
2
Family
conflict
(e.g., People
in my family
have serious
arguments
(reverse
coded))
3 1-4
(definite
ly
no to
definitel
y
yes)
.80, .81 90 20.5
9
347 79.4
1
121 27.6
9
316 72.3
1
School
factors
Opportunitie
s for
prosocial
involvement
(e.g., I have
lots of
chances to
be part of
class
discussions
or activities)
5 1-4
(definite
ly
no to
definitel
y
yes)
.49, 328 75.0
6
109 24.9
4
320 73.2
3
117 26.7
7
Recognition
for prosocial
involvement
(e.g., The
school lets
my parents
know when I
have done
something
well)
4 1-4
(definite
ly
no to
definitel
y
yes)
.62, .71 258 59.0
4
179 40.9
6
312 71.4
0
125 28.6
0
Community
factors
Opportunitie
s for
prosocial
involvement
(e.g., There
are lots of
adults in my
neighbourho
od I could
talk to about
something
important)
5 1-4
(definite
ly
no to
definitel
y
yes)
.65, .66 322 73.6
8
115 26.3
2
298 68.1
9
139 31.8
1
Recognition
for prosocial
involvement
(e.g., There
are people in
my
neighbourho
od who are
proud of me
when I do
something
well)
3 1-4
(definite
ly
no to
definitel
y
yes)
.85, .71 297 67.9
6
140 32.0
4
318 72.7
7
119 27.2
3
Risk groups
Drug use
(e.g.,
smoked
cigarettes;
had more
than just a
few sips of
an alcoholic
beverage
(like beer,
wine or
liquor/spirits
); used
marijuana
(pot, weed,
grass); used
other drugs
(LSD,
cocaine,
inhalants,
stimulants,
ecstasy,
heroin, and
other illegal
drugs) and
binge
drinking)
5 1-8
(never to
40 times
or more)
.30, .64 222 50.8
0
215 49.2
0
173 39.5
9
264 60.4
1
Antisocial
behaviour
(e.g., How
many times
in the past
year (12
months)
have you
carried a
weapon?)
2 1-8
(never to
40 times
or more)
.14, .64 - - - - 373 85.3
5
64 14.6
5
Family
socio-
economic
status
(e.g., Parent
highest level
of education
and level of
family
income (e.g.
less than
$10,000)).
2 n/a n/a 340 81.3
4
78 18.6
6
- - - -
Violent
offending
Low (n, %) High (n, %)
Grade 5
(e.g., Have
you ever
beat up
someone so
badly that
they
probably
needed to
see a doctor
or nurse?)
2 1-4
(never to
3 or
more
times in
the last
year)
.42 396, 90.62 41, 9.38
Grade 9
(e.g., How
many times
in the past
year have
you
threatened
someone
with a
weapon?)
2 1-8
(never to
40 times
or more)
.70 397, 90.85 40, 9.15
Grade 11
(e.g., How
many times
in the past
year have you
threatened
someone
with a
weapon?)
2 1-8
(never to
40 times
or more)
.79 407, 93.14 30, 6.86
Young
adulthood
(e.g., How
many times
in the past
year have
you
threatened
someone
with a
weapon?)
2 1-8
(never to
40 times
or more)
.67 317,72.54 120, 27.46

Note.

^

= Religiosity comprised 1 item at Grade 5, thus Cronbach’s alpha has not been calculated.

Self-reported violent offending

Participants were asked how often they had engaged in various types of violent offending over their lifetime (Grade 5) and in the past year (Grades 9, 11, and young adulthood). At Grade 5, participants were asked two questions: 1) if they had beat up someone so badly that they probably needed to see a doctor or nurse, and 2) attacked someone with the idea of seriously hurting them. At Grades 9 and 11 and in young adulthood, participants were asked the two items measured in Grade 5, in addition to the item: “How many times in the past year have you threatened someone with a weapon?” At each timepoint, responses were recoded to give participants a score of 0 if they answered Never and a score of 1 if they reported engaging in violent behavior one or more times, allowing a distinction to be made between participants who had and had not engaged in violent behaviour.

Risk factors and risk-based protective factors

Risk factors and risk-based protective factors spanned the individual, family, peer group, school, and community domains. All factors were dichotomized similar to previous analyses of this nature (e.g. Hemphill, Tollit, & Herrenkohl, 2014), to identify high levels of ‘protection’ (scored as 1). For variables originally classified as protective factors, the top quartile (75%) was used as the scale cut-point and responses were coded 0 if they fell into the bottom quartile (25%), and 1 if they fell into the top quartile (75%). For variables originally classified as risk factors, the bottom quartile (25%) was used as the scale cut-point and responses were coded 0 if they fell into the top quartile (25%), and 1 if they fell into the bottom quartile (75%).

At-risk groups

Risk factors and risk-based protective factors were examined for three at-risk groups, defined on behaviour (drug use and engagement in antisocial behaviour) or personal circumstance (family SES).

Drug use was assessed in Grade 5 (lifetime use) and Grade 9 (past month use). In Grade 5, participants were asked if they had used alcohol (“have you ever had more than just a sip or two of an alcoholic drink (like beer, wine, or liquor/spirits)”) or tobacco (“have you ever smoked a cigarette, even just a puff’”) in their lifetime. In Grade 9, participants were asked how often in the past month they had: smoked cigarettes; had more than just a few sips of an alcoholic beverage (like beer, wine or liquor/spirits); used marijuana (pot, weed, grass); and used other drugs (LSD, cocaine, inhalants, stimulants, ecstasy, heroin, and other illegal drugs). Participants were also asked about binge drinking over the last fortnight using the item “How many times have you had five or more drinks in a row’” Responses to all substance use measures were recoded to give participants a score of 0 if they answered ‘never’ to all questions and a score of 1 if participants reported engaging in any type of drug use one or more times, allowing a distinction to be made between participants who had and had not engaged in drug use (lifetime for Grade 5, and past month for Grade 9).

Antisocial behavior

An at-risk group based on antisocial behavior in Grade 5 could not be formed due to the small number of cases identified. In Grade 9, participants were asked about five types of antisocial behaviour: carried a weapon; stolen something worth more than $10; sold illegal drugs; stolen or tried to steal a motor vehicle; and been drunk or high at school. Responses were recoded to give participants a score of 0 if they answered ’never’ on all items and a score of 1 if participants reported engaging in any antisocial behavior one or more times, allowing a distinction to be made between participants who had and had not engaged in antisocial behaviour in their lifetime (Grade 5) or past year (Grade 9).

Family SES

Parent-reported level of socio-economic (dis)advantage was assessed in Grade 5. Parents reported their highest level of education (mother and father) (e.g., less than secondary school, completed secondary school, completed post-secondary school, other) and level of family income (ranging from ‘less than $10,000’ to ‘$200,00 and above’).

Procedure

Ethics approval for this study was obtained from The University of Melbourne Human Ethics in Research Committee and relevant educational authorities. The survey required approximately 50-60 minutes to complete, and was administered within the students’ classroom setting for data collection during Grades 5-11. Students no longer attending school during the follow-up surveys, or who were absent on the day of the survey, were surveyed individually by trained personnel. For each student participant, both parental written informed consent and student assent were obtained. For the young adult survey, the participants completed surveys individually, online, after providing informed consent.. As an alternative to the online survey, participants could request a telephone interview or a hard copy survey to be returned by post. After each survey, participants received a small gift.

Student honesty

Drawn from early studies of the development and validity of the Communities That Care youth survey (Arthur, Hawkins, Pollard, Catalano, & Baglioni, 2002), items were included to assess whether or not students answered the survey questions honestly. Students were categorized as dishonest if they reported any of the following: (1) that they were not honest at all when filling out the survey; (2) that they had used a fake drug in their lifetime or in the past 30 days; or (3) that they had used illicit drugs on more than 120 occasions in the past 30 days. A single, dichotomous measure of honesty was calculated using these items.

Statistical Analyses

Data analyses were performed using Stata/IC 13.1 for Windows (StataCorp, 2013) for participants with complete data on all analyzed variables and those who did not meet the criteria for dishonesty (n = 65). First, partially adjusted logistic regression analyses were performed to examine associations between risk factors and risk-based protective factors at Grade 5 and 9 and engagement in violent offending in Grade 11 and in young adulthood.

Analyses were conducted separately for each of the three at-risk groups (drug use, antisocial behavior, family SES). The partially adjusted analyses controlled for age, gender, and the clustering of students in schools (using robust ‘information-sandwich’ estimates of standard errors).

Next, dichotomized scores for each factor were summed to create a total risk and protective factor score (i.e., a cumulative measure of risk and risk-based protective factors) at Grade 5 and 9. Partially adjusted analyses (controlling for age, gender, and the clustering of students in schools) were conducted to examine associations between total risk and protective factor scores and later engagement in violent offending.

In the final analysis step, the influence of interactive protective factors on later violent offending was examined. For statistically significant risk factors and risk-based protective factors in the partially adjusted logistic regression analyses, all possible combinations of interactions at Grade 5 and 9 were examined as predictors of engagement in violent offending in Grade 11 and in young adulthood. Statistically significant risk factors and risk-based protective factors were multiplied by one another at the corresponding grade level (5 or 9) and for the relevant risk group. Statistically significant interaction terms were retained and added as a final step in the partially adjusted logistic regression analyses described above.

Results

Rates of Violent Offending, At-Risk Groups, and Risk Factors and Risk-Based Protective Factors

Table 1 presents the rates of violent offending at Grade 11 and young adulthood, and at-risk groups and risk/protective factors in Grades 5 and 9. Rates of engagement in violent offending were four times greater in young adulthood compared to that in Grade 11 (27% and 6% respectively). For at-risk groups, rates of drug use were higher in Grade 9 compared to Grade 5.

Risk Factors and Risk-Based Protective Factors for Violent Offending

Results of partially adjusted logistic regression models testing longitudinal associations between Grade 5 risk factors and risk-based protective factors and violent offending in Grade 11 and young adulthood are presented in Table 2 for two at-risk groups (i.e., drug use, living with low SES family). None of the Grade 5 factors were predictive of violent offending in Grade 11 for participants in the drug use at-risk group. For participants living in a low SES family, interaction with prosocial peers was the only Grade 5 factor associated with Grade 11 violent offending. With regard to violent offending in young adulthood, Grade 5 belief in the moral order was the only predictor among the at-risk drug use group, while Grade 5 religiosity was the only predictor among the at-risk low family SES group.

Table 2.

Associations between risk factors and risk-based protective factors in Grade 5 and violent offending in Grades 11 and young adulthood.

Risk Group Grade 5 high drug use (n = 215) Grade 5 low family socio-economic
status (n = 78)

Outcomes/
Factors
Grade 11 violent
offending OR
[95% CI]
Young adult
violent offending
OR [95% CI]
Grade 11 violent
offending OR
[95% CI]
Young adult
violent offending
OR [95% CI]
Grade 5 Individual factors
Belief in the
moral order
.37 [.07, 1.89] .36** [.18, .74] - .26 [.06, 1.06]
Religiosity
Interaction with
prosocial peers
.37 [.08, 1.69]
1.58 [.64, 2.36]
.76 [.40, 1.46]
.76 [.44, 1.33]
.53 [.07, 3.87]
5.14* [1.08,
24.57]
.34* [.13, .88]
.40 [.12, 1.32]
Recognition for
prosocial
involvement
1.31 [.42, 4.07] .76 [.33, 1.72] .43 [.07, 2.79] .78 [.25, 2.45]
Poor academic
performance
.60 [.18, 2.04] 1.31 [.71, 2.41] - 3.24 [.74, 14.13]
Low commitment
to school
.78 [.16, 3.81] 1.37 [.43, 4.31] - -
High impulsivity 2.73 [.33, 22.57] .88 [.42, 1.85] 2.04 [.18, 23.05] 1.60 [.40, 6.42]
Grade 5 Family factors
Parent attachment .56 [.17, 1.87] .88 [.47, 1.67] .69 [.11, 4.23] .64 [.21, 2.00]
Opportunities for
prosocial
involvement
1.12 [.33, 3.80] 1.04 [.52, 2.10] 1.76 [.31, 10.05] 1.18 [.43, 3.27]
Recognition for
prosocial
involvement
1.11 [.36, 3.47] .90 [.44, 1.82] 1.11 [.21, 5.88] .30* [.11, .80]
Poor family
management
.73 [.30, 1.79] 1.10 [.59, 2.04] - .83 [.21, 3.30]
Family conflict .49 [.13, 1.79] 1.11 [.52, 2.40] .49 [.06, 3.78] 1.63 [.37, 7.29]
Grade 5 school factors
Opportunities for
prosocial
involvement
1.59 [.45, 5.56] 1.03 [.51, 2.05] 4.66 [.87, 24.85] 1.24 [.37, 4.18]
Recognition for
prosocial
involvement
1.12 [.40, 3.15] 1.05 [.58, 1.91] .99 [.18, 5.51] 1.12 [.39, 3.17]
Grade 5 Community factors
Opportunities for
prosocial
involvement
.84 [.23, 3.05] 1.13 [.60, 2.13] 2.84 [.46, 17.76] 1.14 [.31, 4.15]
Recognition for
prosocial
involvement
1.32 [.44, 3.92] .85 [.49, 1.46] 3.54 [.39, 31.87] .92 [.19, 4.50]

Note. OR = odds ratio. CI = confidence interval. - = analyses would not run due to small number of cases available. Analyses controlled for age, gender, and clustering of students in the schools at Grade 5.

*

= p <0.05,

**

= p < 0.01

Table 3 presents the results from partially adjusted logistic regression analyses testing longitudinal associations between Grade 9 risk factors and risk-based protective factors and violent offending in Grade 11 and young adulthood, for the three at-risk groups (i.e., drug use, high antisocial behavior, low family SES). For the at-risk high drug use group, recognition for prosocial involvement in the family in Grade 9 showed a small, but statistically significant, association with decreased violent offending in Grade 11. For this at- risk group, both belief in the moral order and high parent attachment decreased the risk of young adult violent offending, while low commitment to school showed a two-fold increase in risk for young adult violent offending. For the at-risk group reporting high antisocial behaviour in Grade 9, no factors showed statistically significant associations with violent offending in Grade 11. Low academic performance in Grade 9 increased the odds of violent offending by over ten times in young adulthood. Finally, for the at-risk low SES group, community recognition for prosocial involvement was associated with an increased risk of Grade 11 violent offending. There were no statistically significant predictors of young adult violent offending for this group.

Table 3.

Associations between risk factors and risk-based protective factors in Grade 9 and violent offending in Grades 11 and young adulthood.

Grade 9 high drug use
(n = 264)
Grade 9 high antisocial
behaviour
(n = 64)
Grade 5 low family socio-
economic status
(n = 78)

Grade 11
violent
offending
OR [95%
CI]
Young adult
violent
offending
OR [95% CI]
Grade 11
violent
offending
OR [95%
CI]
Young adult
violent
offending
OR [95% CI]
Grade 11
violent
offending
OR [95%
CI]
Young adult
violent
offending
OR [95% CI]
Grade 9 Individual factors
Belief in the
moral order
.36 [.08,
1.64]
.38** [.19,
.77]
- - .25 [.03,
2.00]
.30* [.11,
.79]
Religiosity .62 [.20,
1.89]
.83 [.44,
1.54]
1.05
[.32,
3.43]
.46 [.14,
1.50]
.48 [.07,
3.19]
.50 [.17,
1.52]
Interaction with
prosocial peers
.50 [.16,
1.51]
.91 [.50,
1.65]
1.66
[.42,
6.61]
.98 [.28,
3.47]
.72 [.08,
6.87]
.65 [.16,
2.60]
Recognition for
prosocial
involvement
.12**
[.03,
.56]
.98 [.57,
1.67]
.50 [.12,
2.14]
.95 [.33,
2.72]
- .76 [.29,
2.01]
Poor academic
performance
3.32
[.41,
27.19]
1.45 [.67,
3.16]
- 10.86*
[1.32,
89.65]
- 3.80 [1.05,
13.80]
Low
commitment to
school
- 2.31**
[1.36, 3.92]
3.32
[.37,
29.91]
2.17 [.55,
8.49]
- 2.01 [.64,
6.27]
High
impulsivity
3.03
[.72,
12.73]
1.28 [.60,
2.71]
.62 [.13,
2.84]
.51 [.11,
2.28]
1.27 [.21,
7.52]
2.41 [.75,
7.79]
Grade9 Family factors
Parent
attachment
.45 [.14,
1.50]
.52* [.27,
.99]
1.46
[.36,
5.94]
1.88[.30,
12.02]
.60 [.06,
6.27]
1.05 [.28,
3.95]
Opportunities
for prosocial
involvement
- .43 [.11,
1.70]
3.66
[.35,
38.53]
1.16 [.11,
12.27]
- 1.16 [.13,
10.09]
Recognition for
prosocial
involvement
.64 [.22,
1.85]
.65 [.37,
1.15]
2.50 [.84,
7.49]
1.22 [.37,
4.08]
1.21 [.19,
7.76]
.4 [.25,
2.18]
Poor family
management
1.43
[.34,
6.04]
1.36 [.60,
3.11]
.79 [.19,
3.38]
2.55 [.65,
10.07]
.21 [.04,
1.17]
2.28 [.48,
10.91]
Family conflict 1.67
[.48,
5.79]
1.08 [.54,
2.16]
.99 [.25,
3.97]
1.20 [.28,
5.16]
2.45 [.27,
22.56]
2.24 [.71,
7.04]
Grade 9 school factors
Opportunities
for prosocial
involvement
.38 [.09,
1.55]
.73 [.36,
1.49]
1.30
[.22,
7.87]
.38 [.06,
2.20]
.91 [.09,
8.88]
1.23 [.33,
4.55]
Recognition for
prosocial
involvement
.40 [.10,
1.72]
1.10 [.57,
2.11]
1.87
[.45,
7.72]
.83 [.21,
3.19]
- 1.49 [.46,
4.81]
Grade 9 Community factors
Opportunities
for prosocial
involvement
.64 [.25,
1.65]
.86 [.51,
1.47]
1.93
[.45,
8.26]
2.83 [.69,
11.55]
1.37 [.22,
8.70]
.86 [.33,
2.23]
Recognition for
prosocial
involvement
1.30
[.54,
3.16]
.84 [.48,
1.49]
3.52
[.88,
14.10]
1.38 [.38,
4.95]
6.79*
[1.09,
42.11]
1.14 [.33,
4.01]

Note. OR = odds ratio. CI = confidence interval. - = analyses would not run due to small number of cases available. Analyses controlled for age, gender, and clustering of students in the schools at Grade 5 and Grade 9.

*

= p <0.05,

**

= p < 0.01.

Cumulative Risk and Protective Scores and Later Violent Offending

Table 4 presents the findings from partially adjusted associations between the cumulative risk and protective scores in Grades 5 and 9 and violent offending in Grade 11 and young adulthood. For the high drug use risk group at Grade 5, neither of the cumulative risk and protective scores was associated with Grade 11 or young adult violent offending. At Grade 9, for this at-risk group, the cumulative risk score was associated with over a thirty times greater odds of Grade 11 violent offending, while the cumulative protective score showed a small, but statistically significant association, with decreased violent offending in both Grade 11 and young adulthood. For participants in the at-risk low family SES group in Grade 5, the Grade 5 cumulative protective score was associated with decreased odds for young adult violent offending. Further, for this at-risk group the Grade 9 cumulative risk score was associated with increased odds for violent offending in young adulthood but not Grade 11. Finally, for the high antisocial behavior at-risk group in Grade 9, neither of the cumulative risk and protective scores was associated with violent offending at Grade 11 or young adulthood.

Table 4.

Associations between cumulative risk factor and protective factor scores in Grades 5 and 9 and violent offending in Grades 11 and young adulthood

Grade 5 high drug use
(n = 264)
Grade 5 low family
socio-economic status
(n = 78)

Grade 11
violent
offending
OR [95%
CI]
Young adult
violent
offending
OR [95%
CI]
Grade 11
violent
offending
OR [95%
CI]
Young adult
violent
offending
OR [95%
CI]
Risk/Protective factor score
Grade 5 risk
score
.30 [.01,
6.26]
1.74 [.35,
8.59]
46.30
[.05,
44902.72]
13.40 [.54,
330.54]
Grade 5
protective score
.89 [.05,
14.62]
.48 [.13,
1.74]
3.41 [.06,
206.00]
.07* [.01,
.89}

Grade 9 high drug use
(n = 264)
Grade 9 high antisocial
behaviour
(n = 64)
Grade 5 low family
socio-economic status
(n = 78)

Grade 11
violent
offending
OR [95%
CI]
Young adult
violent
offending
OR [95%
CI]
Grade 11
violent
offending
OR [95%
CI]
Young adult
violent
offending
OR [95%
CI]
Grade 11
violent
offending
OR [95%
CI]
Young adult
violent
offending
OR [95%
CI]

Risk/Protective factor score
Grade 9 risk
score
33.46*
[1.87,
597.67]
2.99 [.82,
10.93]
3.32 [.32,
33.90]
5.58 [.57,
54.98]
4.31 [.23,
81.58]
14.82*
[1.60,
136.96]
Grade 9
protective score
.02**
[.003,
.22]
.28* [.08,
.96]
4.51 [.30,
67.43]
.60 [.04,
9.54]
.08 [.003,
2.27]
.28 [.03,
2.82]

Note. OR = odds ratio. CI = confidence interval. Analyses controlled for age, gender, and clustering of students in the schools at Grade 5 and Grade 9.

*

= p <0.05,

**

= p < 0.01

Interactive Protective Factors

Tests of interactive protective factors (specifically Grade 9 belief in the moral order*low commitment to school, for the high drug use at-risk group, and parent attachment*low school commitment for the high drug use at-risk group) did not reveal any statistically significant interactions.

Discussion

The current study analyzed longitudinal data spanning eight years with detailed measures of risk factors and risk-based protective factors to demonstrate that the risk factors and risk-based protective factors, not surprisingly, differed for different at-risk groups at different ages. There were few associations between Grade 5 factors and Grade 11 and young adult offending. There were more associations between Grade 9 factors and Grade 11 and young adult offending, than for Grade 5. Likewise, for cumulative risk and protective factor indices, of the ten models tested, the cumulative risk factor score predicted later violent offending in two models and cumulative protective factors predicted subsequent violent offending in three models. Even across the shortest timeframe measured in the current study from Grade 9 to Grade 11, there were few predictors identified.

Of all the sixteen Grade 5 risk factors and risk-based protective factors examined, only three were predictors for Grade 11 and young adult offending; one for the high drug use group and two for the low family SES group. Two of the factors reduced the likelihood of later violent offending (belief in the moral order, religiosity). Belief in the moral order has been identified as a protective factor for antisocial behavior in previous studies, as has religiosity (Catalano & Hawkins, 1996; Herrenkohl et al., 2003). There was an unexpected finding with interaction with prosocial friends in Grade 5 increasing the odds of Grade 11 violent offending. However, the correlation between the two items in this scale was only 0.3, suggesting that students of this age could not reliably report whether their best friends tried to do well in school and participated in sports, clubs, organizations or other activities at school, indicating that this measure was not reliable for students of this age.

In the present study, there were six associations between Grade 9 risk factors and risk-based protective factors and Grade 11 and young adult violent offending. Most of the associations were found for the Grade 9 high drug use group; peer recognition of prosocial involvement reduced the odds of Grade 11 violent offending and for young adult violent offending, protective factors were belief in the moral order and attachment to parents, whereas low commitment to school increased the odds of young adult violent offending. Belief in the moral order and attachment to parents have both been identified as protective against violence in previous research (Catalano & Hawkins, 1996). There is an established literature demonstrating that low commitment to school is associated with later violence (e.g., Hawkins et al., 2000; Herrenkohl et al., 2012). Only one predictor was found for the Grade 9 high antisocial behavior group and that was poor academic performance increasing the odds of young adult violent offending. Again, this finding has been reported previously in the literature (Hemphill et al., 2011; Hemphill et al., 2006). Finally, for the low family SES group, Grade 9 community recognition for prosocial involvement increased the odds of Grade 11 violent offending. This finding contradicts the predictions in the Social Development Model (Catalano & Hawkins, 1996) that being recognized in the local community for prosocial behavior reduces the likelihood of engaging in violent offending and antisocial behavior more generally. Perhaps when living in a low SES family and therefore possibly a high crime area, recognition by neighbors may not necessarily promote prosocial behavior.

Results showed that the cumulative risk and protective factor scores were associated with Grade 11 and young adult violent offending in some of the at-risk groups. The Grade 5 protective factor score reduced the odds of young adult violent offending for the low family SES group, and the Grade 9 protective factor score reduced the likelihood of Grade 11 and young adult violent offending for the Grade 9 high drug use group. The Grade 9 risk factor score was associated with a large increased risk of Grade 11 violent offending for the Grade 9 high drug use group. Similarly the Grade 9 risk factor score was associated with a large increased risk of young adult violent offending for the low family SES group. Other studies have previously reported that cumulative risk and protective factor scores are predictors of outcomes such as violent behavior (Herrenkohl et al., 2003; Herrenkohl et al., 2000).

Strengths and Limitations of the Current Study

The present study has several strengths. The recruited sample was state-representative at the commencement of the ongoing longitudinal study in 2002. The longitudinal study also achieved good response rates for participation, it included approximately equal numbers of male and female students, and it has achieved a good sized sample with strong retention across the eight years of the study. The present study analyzed data from this existing longitudinal study that has detailed data on risk factors and risk-based protective factors. It therefore provides a unique opportunity to examine the prospective predictors of violent offending at different ages and for different at-risk groups.

The current study also has several limitations. The number of cases in some at-risk groups was small and this impacted on the analyses with some models not converging and wide confidence intervals found for associations that were detected. Some results therefore need to be interpreted with caution. Second, the measure of violent offending was based on self-reports of participants. However, the use of self-report measures in studies of pre- adolescents and adolescents is considered a reliable source of data for behavior problems such as substance use and antisocial behavior (Huizinga & Elliott, 1986; Jolliffe et al., 2003; Rutter & Giller, 1983) that are not readily visible to adults. In addition, official statistics generally provide conservative estimates given that there a number of points at which young people may or may not proceed to be counted as a “case”. In addition, there are also many errors that occur in the processing of offences that affect the reliability of the rates reported.Third, the present study examined the associations between earlier risk factors and risk-based protective factors and subsequent violent offending. Research is also needed to investigate associations from early violent behavior to subsequent risk factor and risk-based protective factor exposure, as well as reciprocal relationships between violent behavior/offending and factors.

There is debate in the literature about what constitutes a risk or protective factor and whether they are separate or part of a single underlying dimension of behavior (or surrounding context) modeled at opposite ends of that one dimension. For example, emotion control is considered protective if scored to reflect more of the skills that contribute to emotion control. Emotion control might also be considered a risk factor if scored to reflect low skill or the absence of control. Other variables are theoretically derived and are hypothesized to influence developmental outcomes as separable risk or protective factor influences (e.g., opportunities and recognition for prosocial involvement at school as distinct from opportunities and recognition for antisocial involvement at school). It is important for the reader to note that in analyses here, we have chosen to include variables that fall within both categories; those that are uniquely antisocial or prosocial according to the Social Development Model (Catalano & Hawkins, 1996), as well as those that could be conceptualized as risk and/or protective factors depending on how they are operationalized and scored.

Implications of the Findings for Future Research

In the current literature, interactive protective factors have rarely been investigated (Farrington & Ttofi, 2012). Interaction effects can be difficult to detect when analyses are underpowered (Maxwell, 2004). More longitudinal studies with large sample sizes are required in the future to continue to examine the potential role of interactive protective factors in reducing violent offending.

Given the ongoing debate about how best to conceptualize and measure risk and protective factors, additional studies of risk factors and risk-based protective factors for violent offending are needed to further elucidate the influence of risk and protective factors measured in a variety of ways. An improved understanding of this kind will result in prevention and early intervention approaches that are more likely to be effective in reducing violent offending.

Conclusions

The present study of risk factors and risk-based and interactive protective factors identified a few notable predictors of later violent offending that spanned the individual, peer, and community domains. Belief in the moral order was found to reduce the odds of violent offending at Grade 5 and Grade 9. The results of the current study demonstrated the importance of considering risk/protective factors for different at-risk groups at different ages. More research of this kind with sufficient sample sizes to conduct subgroup analyses is warranted. Ongoing consideration of the conceptualization and measurement of risk and protective factors in this (and related) field(s) of research is vital to continue to progress developmental models of violent offending and related behaviors that can then be used to inform prevention and early intervention approaches for young people.

Highlights.

  • Risk factors and risk-based protective factors spanned individual, peer, and family contexts.

  • Interactive protective factors were not detected in this study.

  • More associations with offending were found for Grade 9 (versus Grade 5) factors.

  • There were associations between cumulative risk/protective scores and offending.

Acknowledgements

The authors wish to express their appreciation and thanks to project staff and participants for their valuable contribution to the project.

Funding

The authors are grateful for the financial support of the National Institute on Drug Abuse (R01-DA012140) for the International Youth Development Study initial data collection. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute on Drug Abuse or the National Institute of Health. Continued data collection in Victoria, Australia has been supported by three Australian Research Council Discovery Projects (DPO663371, DPO877359, and DP1095744) and an Australian National Health and Medical Research Council grant (project number, 594793). The work of Dr. Heerde and Dr. Scholes-Balog is supported by funding provided through the Learning Sciences Institute Australia at Australian Catholic University.

Footnotes

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Declaration of Conflicting Interests

None declared.

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