Efficacy of Low-Intensity Cognitive Behavior Intervention for Chinese Delinquent Youth

Abstract

Purpose:

Recent literature has pointed out the seriously unmet treatment needs of delinquent youth with mental health problems in Hong Kong. This study pioneers to systematically develop and evaluate the effectiveness of a structured low-intensity cognitive behavioral intervention (LICBI) to concurrently address mental health issues and delinquent behaviors among Hong Kong Chinese youth.

Method:

A quasi-experimental controlled design was adopted with three assessments at baseline, postintervention, and 6-week follow-up. One hundred and eighty participants were recruited to the LICBI and 123 to the control group.

Results:

Multilevel modeling analyses showed that the LICBI might be effective in improving mental health–related factors (impulsivity, self-esteem, negative emotions, and loneliness) and delinquent behaviors. A mediation analysis suggested that LICBI might reduce participants’ delinquent behaviors through reducing their impulsivity and enhancing their self-esteem.

Discussion:

The results provide preliminary evidence for the effectiveness of LICBI for Chinese delinquent youth in a community social service setting.

Keywords

low-intensity intervention cognitive behavioral therapy youth delinquency Chinese adolescents psychological attributes

Youth delinquency is a pervasive social problem worldwide and in Hong Kong. Juvenile delinquency is defined as the “participation by a minor child, usually between the ages of 10 and 17, in illegal behavior or activities” (Legal Dictionary, 2015). According to 2019 figures from the Hong Kong Police Force (2020), juveniles (aged 10–15 years) and young persons (aged 16–20 years) arrested by the police accounted for approximately 10%–20% of total arrests in the past decade. It is generally agreed that adolescent/youth crime has been a significant social problem in Hong Kong since the 1980s (Chui & Cheng, 2017).

Mental health problems and delinquency are closely related. Adolescents with delinquent behaviors have reported higher rates of emotional disturbance, mental health service needs (Lyons et al., 2001), and comorbidity of mental illnesses (Wasserman et al., 2010). On the other hand, youth with mental disorders (e.g., stress, anxiety, conduct problems, and psychopathy) or mental health difficulties have shown higher risks of offending and reoffending than youth on average (Grisso, 2008; Heilbrun et al., 2005). In China, Zhou et al. (2014) reported that 34.5% and 59.8% of nonviolent adolescent male offenders, respectively, met the criteria for anxiety and depression, while 36.4% and 57.2% of violent adolescent male offenders, respectively, met the criteria for anxiety and depression.

Psychological Attributes Contributing to Mental Health and Delinquency

Mental health can be defined as the absence of mental diseases or a state of being that includes the biological, psychological, or social factors that determine an individual’s mental state and ability to function within the environment (Manwell et al., 2015). Criminological and psychological theories have elucidated the critical role of mental health–related risk factors in the etiology of delinquency (Agnew & White, 1992; Gottfredson & Hirschi, 1990). General strain theory (GST) proposed by Agnew and White (1992) highlights that the occurrence of delinquency and crime is due to negative affect resulting from external strains such as stressful life events. It has been argued that people may select illegitimate means to cope with these negative affect and associated stress (Agnew & Brezina, 2019). GST further suggests that individuals’ trait-like/dispositional characteristics (e.g., self-esteem and impulsivity) and emotional states (e.g., anger, negative emotions, and loneliness) are involved in illegitimate behaviors (Agnew & Brezina, 2019).

Combining the seminal work on GST and other empirical studies on mental health and delinquency, the present study targets five mental health–related factors that are influential in maintaining delinquent behaviors in youth, namely, impulsivity, anger and aggression, low self-esteem, loneliness, and negative emotions. Literature has well-documented the robust association between impulsivity and delinquency in Western (Pratt & Cullen, 2000) and Chinese criminological studies (Weng et al., 2016). Anger and aggression have also been well-documented to be associated with offending (Assink et al., 2015) and recidivism (Mulder et al., 2011). The link between aggression and delinquency/recidivism has also been reported in Chinese studies (Wei et al., 2012). Furthermore, loneliness is one of the main indicators of social well-being. Niño et al. (2016) found that socially avoidant and socially disinterested youth were more prone to violent delinquency than sociable youth. Moreover, cumulative evidence has shown that negative emotional states such as depression and anxiety are risk factors for delinquency or crime (Fazel et al., 2008; Reising et al., 2019). A study conducted among Chinese adolescents also found that depression and anxiety mediated the relationship between life strain and minor delinquency (Bao et al., 2004). Lastly, low self-esteem has been found to predict youth offending (Tarolla et al., 2002). A meta-analysis of Chinese studies identified a robust association between self-esteem and aggressive and violent behaviors (Teng et al., 2015). All in all, these five mental health factors appear to be influential in developing and maintaining delinquency among Western and Chinese youth.

The mental health needs among youth at risk for delinquency and those involved in the criminal justice system have been inadequately addressed (Chitsabesan et al., 2006; Townsend et al., 2010). Critics have questioned both the lack of referral to mental health treatments for delinquent youth in the social service system and the lack of community services targeting delinquent behaviors and mental health problems among at-risk youth (Young et al., 2017). Indeed, there is scant evaluation of intervention programs that addressed both mental health issues and delinquent behaviors of Chinese at-risk youth and juvenile delinquents (Wong et al., 2018). Given the sheer size of the youth population in Chinese communities, there is a strong need to develop and evaluate intervention programs that target mental health problems and delinquent behaviors among at-risk youth and juvenile delinquents in Chinese communities.

Current Forensic Psychiatry Models in Western Countries

Cognitive behaviorial–oriented approaches have been widely used among various Western forensic psychiatry models (Lipsey et al., 2007). These models are Reasoning and Rehabilitation program, Moral Reconation Therapy, Aggression Replacement Training, and Thinking for a Change. The mentioned models mainly emphasize the modification of dysfunctional cognitive and behavioral patterns by cultivating critical thinking, social perspective taking, moral reasoning, problem-solving skills, and anger management (Lipsey et al., 2007). According to the literature, the above models could significantly reduce the recidivism, impulsivity, tolerance of law violation, and criminal identification (Berman, 2004) and increase social skills (Gundersen & Svartdal, 2006). These results suggested that the high-intensity cognitive behavioral intervention (CBI) approach can be effective in concurrently addressing delinquent behaviors and mental health–related psychological attributes.

Recently, CBI has been adapted as a low-intensity intervention program using a stepped care model for people with delinquent behaviors (Bower & Gilbody, 2005). As informed by the stepped care model, different mental health intervention programs should address people with different levels of mental health needs. Those with mild mental health problems require low-intensity interventions, while high-intensity CBT services are offered by skilled therapists for people with more severe conditions (National Institute for Health and Clinical Excellence, 2011). Thus, the low-intensity treatment models have become an indispensable and critical component in the implementation of the stepped care model. Several meta-analyses have identified LICBI as an effective low-intensity intervention for reducing recidivism in juvenile offenders (Lipsey & Landenberger, 2006; Lipton et al., 2002), fitting very well into a stepped care model of interventions. Indeed, as an early intervention and preventive approach, low-intensity CBI (LICBI) is characterized by reduced therapist-patient contact time, reduced intensity level, and quick access to CBI treatment (Bennett-Levy et al., 2010) and are considered less burdensome for patients.

Effectiveness of LICBI Approach to the Provision of Mental Health Services for Delinquent Youth

LICBI has received preliminary support for reducing mental health problems such as anger (Novaco & Javis, 2002), psychological distress (McHugh et al., 2014), depression (Freire et al., 2015), anxiety (Delgadillo et al., 2016), and other affective disorders (Tolin et al., 2005) in the general population. However, there is a lack of studies investigating the effectiveness of CBI in reducing recidivism and mental health problems among young delinquents and offenders (Adamson et al., 2015; Liau et al., 2004). First, Miles et al. (2012) developed and examined the effectiveness of a program called “Coping Inside” that offered a 4-hour LICBI group workshop to UK young offenders with anxiety and/or obsessive-compulsive disorder (OCD). The results found that the workshop was able to decrease the participants’ self-consciousness. Second, Adamson et al. (2015) evaluated a LICBI for young adult offenders in the UK, namely Improving Access to Psychological Therapies (IAPT). It was concluded that IAPT could produce large effect sizes for reductions in anxiety and depression. Third, Dembo et al. (2013, 2016) compared a brief intervention (BI) designed for truancy adolescents with standardized truancy care (Dembo et al., 2013; Dembo et al., 2016). Results revealed that youth receiving the BI service had a significantly lower rate of arrest charges and self-reported delinquency at 6-month follow-up. Lastly, Carney et al. (2020) developed and evaluated the effectiveness of a brief cognitive behavioral–based model called Reducing Alcohol and Drug use and other Problem behavior in Adolescent Learners among African adolescents. Results showed that the participants reported a decreasing level of delinquent-type behaviors.

In Hong Kong, the past 5 years have witnessed a marked shift toward a stepped care model in the medical and social welfare systems for people with common mental health disorders (W. Lee et al., 2019). The incorporation of a low-intensity intervention model into the systems has the advantage of better and more efficient use of resources, thus potentially yielding economic benefits and responding more promptly to patients’ needs. However, there is no published empirical study in Hong Kong that has examined the effectiveness of any low-intensity intervention model. This study represents the first of its kind in examining the effectiveness of LICBI on mental health of delinquent youth.

A search of the literature reveals only five Chinese studies on the efficacy of CBI in reducing delinquency and related risk factors in youth. None of them used a low-intensity/BI modality. The five studies that used CBI revealed that delinquent youth in Hong Kong saw significant reductions in overall delinquency, impulsivity (Wong et al., 2018), and aggressive behaviors (Fung et al., 2013) after CBI. In Mainland China, Chen et al. (2014) and Zhang and Zhang (2016) found that CBI was effective in reducing overt aggressive behaviors and enhancing social-cognitive information processing skills, social skills, and self-efficacy among Chinese young male offenders.

Although the aforementioned studies have demonstrated positive effects of CBI for Chinese delinquent adolescents, these studies showed a number of limitations. Firstly, none of these studies adopted a LICBI modality. Secondly, all of these studies had a small sample size of less than 66 participants and were mainly focusing on the male subjects. There are limited research on the effectiveness of CBI with female delinquents (Hubbard & Matthews, 2008). Thirdly, despite the fact that CBI could produce positive effects on some risk factors related to delinquency (e.g., impulsivity, anxiety, coping), the impacts of these positive changes on the reductions in delinquency and recidivism are unclear (Kazdin & Nock, 2003). Furthermore, many of the studies did not include a follow-up evaluation (i.e., Chen et al., 2014; Wong et al., 2018), and thus the longer term effects of the CBI could not be determined. Lastly, most of the treatment protocols adopted a behavior-oriented approach and emphasized the development of adaptive coping and social skills (Chen et al., 2014; Zhang & Zhang, 2016). The cognitive and emotional components have been much less in focus (Wong et al., 2018).

Self-Developed LICBI for Chinese Delinquent Youth With Mental Health Needs

LICBI shares the same principles as high-intensity CBI in terms of focusing on the present, viewing symptoms resulting from interactions between cognitions, behaviors, emotions and the physical responses, being based on a scientific approach, and being collaborative and structured. The current LICBI model was developed by incorporating different cognitive and behavioral techniques to address issues on anger (Novaco & Jarvis, 2002), aggression (Valliant & Antonowicz, 1991), and anxiety and depression (Adamson et al., 2015) among delinquent youth. First, emotion management training helped the participants to be self-aware of and to self-monitor their patterns of automatic negative thoughts associated with their negative emotions. Strategies to recognize the triggering cognitions associated with negative emotions (e.g., anger, depression, anxiety, distress) and understand the dysfunctional cycle of responses, namely, negative thoughts, negative emotions, physiological responses, and maladaptive behaviors, were taught to delinquent youth. Second, the delinquent youth were introduced to cognitive and behavioral skills relating to interpersonal problem-solving, goal setting, long-term planning, and perspective taking (Lipsey et al., 2007). They were also encouraged to role-play or practice the adaptive cognitive and behavioral skills in the counseling sessions and outside.

The Current Study

Given the potential cost-effectiveness of a low-intensity/brief modality of CBI and the preliminary support for such a modality in reducing delinquent behaviors and mental health problems among Chinese delinquent adolescents, there was a great need to develop and systematically evaluate a structured LICBI to address the mental health needs of at-risk youth. In addition, there was a need to examine the mechanisms of change in LICBI for Chinese delinquent youth so as to identify how it works and what works for whom? (Weisz et al., 2006). To conclude, there were four hypotheses in this study:

Hypothesis 1: Participants in the treatment condition would demonstrate a greater reduction in the frequency of delinquency compared to participants in the control condition.

Hypothesis 2: Participants in the treatment condition would have better improvements in mental health (i.e., lower impulsivity, aggression, negative emotions and loneliness, and higher self-esteem) compared to participants in the control condition.

Hypothesis 3: Changes in mental health–related risk factors would mediate the treatment effect of the LICBI on the change in participants’ frequency of delinquency.

Hypothesis 4: There is no gender difference in the treatment effects of LICBI on the frequency of delinquency and mental health–related risk factors.

Method

Procedures and Participants

The current study followed the guidelines laid out in the CONSORT statement and adopted a quasi-experimental controlled design with three assessments at baseline, postintervention, and 6-week follow-up. As recommended by Gold et al. (2017) and Karlsson and Bergmark (2015), the choice of the control condition was based on the trial purpose. Since the main interest of this study was to determine the efficacy of LICBI compared to the existing community intervention approach (i.e., the usual standard treatment provided by local social service agencies), the treatment as usual (TAU) approach was adopted.

The participants in the experimental and control groups were recruited by outreaching social workers of Hong Kong Federation of Youth Groups (HKFYG) Youth Crime Prevention Centre. The selection criteria included the following: (1) Hong Kong Chinese adolescents aged 10–24 years, (2) able to understand Chinese, (3) mentally stable (i.e., no acute psychotic symptoms or suicidal ideation) at the time of recruitment, (4) able to complete the questionnaire by themselves, and (5) identified as being at risk for deviant and delinquent behaviors or having mild delinquent behaviors by experienced social workers. The sample size was calculated based on an effect size of 0.4 found in previous research on CBI delinquency conducted in Hong Kong (Wong et al., 2018). Given 80% power, a two-tailed error of 0.05, and a test of two independent groups, the required minimum sample size should be 120 for each condition. Among 400 youth who were screened, 348 were deemed eligible and 303 youth consented and were assigned to the treatment group (n = 180) or the control group (n = 123). The flowchart of the present study is presented in Figure 1. Due to ethical considerations by the agencies concerned, we could not randomize the participants into treatment conditions. However, we tried to guarantee that gender and age factors were comparable in the two groups.

Figure 1.

The flow diagram of the intervention through the stages of the study.

The Human Research Ethics Review Committee of the University of Hong Kong approved the study. All participants completed a written assent/consent form and a battery of standardized measurement instruments. Parental consent was sought for participants under 18 years of age at the time of participation. A research assistant who was blind to the treatment allocation administered and collected the consent forms and questionnaires from each participant.

Intervention

LICBI

The current LICBI protocol consisted of four sessions over 2 months, with 45 min per session. In the first session, participants were educated to recognize different types of emotions that they commonly experience. The session then focused on helping participants understand the patterns of their physiological, cognitive, behavioral, and emotional responses to external stressful triggers. The second session was dedicated to helping the participants understand their own negative automatic thought patterns (i.e., cognitive distortions) and associated negative emotions in relation to external stressful triggers. Both cognitive and behavioral skills (e.g., perspective taking and problem-solving skills) were taught and practiced to cope with stressful triggers and negative emotions. In Sessions 3 and 4, participants were guided to examine how their cognitions, negative emotions, and maladaptive behavioral coping might affect their interpersonal relationships with families and peers. Interpersonal social skills and five cognitive and behavioral strategies (Five-Step Strategies) were introduced to help the participants to manage their negative emotions and interpersonal conflicts. Detailed information of the session plan can be found in the Appendix.

TAU

Routine individual counseling services were given to participants in the control condition by the outreaching social workers of the HKFYG Youth Crime Prevention Centre. Generally speaking, the key elements of the individual counseling services include practical support and advice, crisis intervention, and family counseling. Nothing about CBI materials was shared in the counseling process. Each session lasted for 45 min, with an average of four sessions over 2 months.

Measurement

Mental health–related risk factors for delinquency

The Adolescent Mental Health Risk Factors for Delinquency Scale was developed by the research team to cover the five mental health–related risk factors discussed in the literature review section. The five subscales are impulsivity, aggression, low self-esteem, negative emotions, and loneliness. The items in the developed scale were written based on several well-established psychometrically sound psychological instruments: the Rosenberg Self-Esteem Scale (Rosenberg, 1962); the Barratt Impulsivity Scale (Patton et al., 1995); the Aggression Scale (Orpinas & Frankowski, 2001); the Depression, Anxiety, and Stress Scale (Taouk et al., 2001); and the De Jong Gierveld Loneliness Scale (Gierveld & Tilburg, 2006). This instrument consists of 25 items rated on a 4-point response format. Each subscale is measured by five items. A confirmatory factor analysis was conducted to examine the factorial validity of the self-developed scale. The Root Mean Square Error of Approximation (RMSEA), Comparative Fit Index (CFI), Non-Normed Fit Index (NNFI) and Standardized Root Mean Square Residual (SRMR) were used to determine the data-model fit. The results indicated a good model fit for the scale, S-B χ²(265, N = 332) = 447.41, RMSEA = 0.046, 90% confidence interval (CI) [0.038, 0.053], CFI = 0.98, NNFI = 0.97, and SRMR = 0.072. The Cronbach’s α values of the five subscales and the total scale ranged from 0.70 to 0.89, indicating acceptable to good internal consistency reliability.

Quality of life

The 18-item Abbreviated Quality of Life Enjoyment and Satisfaction Questionnaire (Q-LES-Q-18) was developed by Endicott et al. (1993). It attempts to tap a person’s level of satisfaction in the five dimensions of physical health, subjective feelings, leisure activities, social relationships, and medication. The scale has been translated and used among Chinese populations (Y.-T. Lee et al., 2014). It uses a 5-point scale where 1 denotes “not at all” and 5 “all the time.” The internal consistency of the Q-LES-Q-18 was found to be 0.87 and the test–retest reliability was 0.75 (Y.-T. Lee et al., 2014). The scale and its subscales achieved high internal consistency in this study with Cronbach’s α values ranging from 0.79 to 0.82.

Delinquency

The Hong Kong Delinquency Behavior Scale developed by Wong et al. (2018) was adopted to index the delinquent behavior of participants. This instrument was modified from the 17-item Delinquency Scale developed by Miller et al. (2007). The scale asks about the frequency with which participants have engaged in a series of delinquent behaviors in the past few months. Sample items are “argue/fight with parents” and “take drugs.” The scale ranges from 0 to 4 (0 = never and 4 = always). Cronbach’s αs of the whole scale were good (0.87–0.89 across 12 months; Wong et al., 2018). In this study, the Cronbach’s α value for the total scale was 0.85.

Data Analysis

Data analysis was performed based on the intention-to-treat principle. Missing values were replaced by their expected value computed using the expectation maximization algorithm. Firstly, χ² tests were performed to examine differences between the LICBI and control groups in terms of the demographic characteristics of participants. Secondly, a series of linear random-effects models (multilevel models) with random intercepts and random slopes were conducted using HLM Version 6.08 to examine the effectiveness of LICBI on various outcomes. A two-level model was specified with repeated measures (Level 1) nested within individuals (Level 2). At Level 1, time was entered as a continuous predictor. The pretest was coded as 0, the posttest as 8, and the 6-week follow-up as 14. These values represent the unequal intervals between time points. At Level 2, besides treatment condition, we entered age, gender, birthplace, family income, education, and mental illness in the model to control for the potential confounding effects. Gender, birthplace, and education were dummy coded and the reference groups were male, places other than Hong Kong, and education attainment of lower than Form 3, respectively. Family income was coded as either income lower than HK$30,000 (including HK$30,000) or income higher than HK$30,000, with the reference group of unknown level of income. Similarly, mental illness was coded as three dummy variables, having Attention Deficit Hyperactivity Disorder (ADHD), having depression, and having other mental illnesses with the reference group of not having mental illness. These models estimated the main effects of time (trajectory of change across the three assessment points) and treatment (1 = LICBI, 0 = social activity) and the interaction between time and treatment. Multilevel models have numerous advantages over the traditional analysis of covariance: (a) they account for the nonindependence of observations associated with repeated measurement, reducing the risk of a Type I error, and (b) they can accommodate unequal time periods between assessment points (Gueorguieva & Krystal, 2004). Cohen’s d was used to measure the magnitude of change in outcome variables between preintervention and 8-week intervention and between preintervention and 14-week intervention in both the experimental and control groups (Cohen, 1988). The Multilevel Modeling (MLM) model equations were presented as below:

Level 1 model:

Y = π_{0} + π_{1} (time) + e .

Level 2 model:

π_{0} = β_{00} + β_{01} (gender) + β_{02} (education) + β_{03} (birthpalce) + β_{04} (age) + β_{05} (income\_below) + β_{06} (income\_above) + β_{07} (ADHD) + β_{08} (Depression) + β_{09} (other mental illness) + β_{10} (treatment) + r_{0}, π_{1} = β_{11} + β_{12} (treatment) + r_{1} .

Y refers to the outcome variables, which is a function of a systematic growth trajectory plus random error. The term $t i m e$ specified the linear change for Y. The linear time variable was the rate of change per unit of time over the three measurement time points. The terms $π_{0}$ and $π_{1}$ referred to the initial Y (intercept) as well as the rates of linear changes and rates over time. The random terms (i.e., r₀ and r₁) allowed individuals to have different initial statuses as well as different rates of linear changes.

Moreover, another sets of multilevel models were performed within the LICBI group to examine the gender effect on the outcome variables. Gender × Time interaction effects were specified to indicate the gender differences. The MLM equations can be found as below:

Level 1 model:

Y = π_{0} + π_{1} (time) + e .

Level 2 model:

π_{0} = β_{00} + β_{01} (gender) + r_{0},

π_{1} = β_{10} + β_{11} (gender) + r_{1} .

Thirdly, we conducted a multiple mediation analysis using PROCESS, a statistical macro for conducting path and mediation analyses (Preacher & Hayes, 2008). The mediators are changes of the five mental health–related factors between pretest and follow-up test. Indirect effects were calculated to test whether the LICBI treatment reduced delinquency by reducing levels of mental health risk factors. Bias-corrected bootstrap analyses (5,000 resamples) were used to estimate the 95% CIs for the indirect effects (Preacher & Hayes, 2008).

Results

Participants’ demographic information can be found in Table 1. Independent t tests and χ² tests of independence found no significant differences in the demographic characteristics between the two groups, including gender (χ² = 1.51, p > .05), age (χ² = 5.37, p > .05), birthplace (χ² = 2.76, p > .05), mental illness (χ² = 2.57, p > .05), educational attainment (χ² = .41, p > .05), and family income (χ² = 6.05, p > .05). In the two groups, around 50%–60% of participants are males. Around 67% of participants were between 15 and 19 years old, and 25% were aged between 10 and 14 years. More than 86% of participants were born in Hong Kong and the majority (80%) of the participants did not have a mental illness diagnosis. Up to 60% and 70%, respectively, were students from Form 2 to Form 4, which is equivalent to Grades 8–10, and a substantive proportion of participants reported a family income of below HK$50,000.

Table 1.

Demographic Information of Participants.

Variables	Experimental GroupN (%)	Control GroupN (%)	χ² Test
Age			5.37
10–14	47 (26.1)	35 (28.5)
15–19	122 (67.8)	82 (66.7)
20 or above	9 (5.0)	0
Missing	2 (1.1)	6 (4.9)
Gender			1.51
Male	92 (51.1)	72 (58.5)
Female	86 (47.8)	49 (39.8)
Missing	2 (1.1)	2 (1.6)
Birthplace			2.76
Hong Kong	155 (86.1)	112 (91.1)
Mainland China	21 (11.7)	8 (6.5)
Others	4 (2.2)	3 (2.4)
Mental illness			2.57
No	145 (80.6)	106 (86.2)
Yes	35 (19.4)	17 (13.8)
Mental illness types
ADHD	16	4	3.45
Depression	9	3
Other mental illness	10	10
Education			0.41
Primary or below	9 (5.0)	1 (0.8)
Form 1 to Form 3	47 (26.1)	36 (29.3)
Form 4 to Form 6	108 (60.0)	86 (69.9)
Diploma/degree or above	15 (8.3)	0
Missing	1 (0.6)	0
Family income			6.05
HK$10,000 or below	7 (3.9)	4 (3.3)
HK$10,001–HK20,000	18 (10.0)	9 (7.3)
HK$20,001–HK30,000	19 (10.6)	8 (6.5)
HK$30,001–HK40,000	10 (5.6)	4 (3.3)
HK$40,001–HK50,000	3 (1.7)	4 (3.3)
HK$50,001 or above	7 (3.9)	10 (8.1)
Unknown	113 (62.8)	80 (65.0)
Missing	3 (1.7)	4 (3.3)

Note. None of the group differences was significant.

Descriptive statistics of the study variables are presented in Table 2. Most of the variables showed changes in the expected direction. The results of multilevel modeling are presented in Table 3. Time × Treatment interaction effects were found for the following outcome variables: the mental health total score (β = −0.007, p < .01), impulsivity (β = −0.02, p < .05), low self-esteem (β = −0.007, p < .05), loneliness (β = −0.008, p < .05), negative emotions (β = −0.009, p < .1), the Leisure Activity subscale of the Q-LES-Q-18 (β = 0.02, p < .01), and the Medical Health subscale of the Q-LES-Q-18 (β = 0.04, p < .01) as well as delinquent behaviors (β = −0.006, p < .05). Across time, there were significantly greater improvements in the above-listed outcome variables reported by participants in the LICBI condition compared to those reported by the participants in the TAU condition (Tables 2 and 3). As shown in Table 4, Cohen’s d values indicated that the changes achieved moderate effect sizes (i.e., 0.17–0.62). The results of the mediation analysis can be found in Table 5. We examined whether the changes from pre- to follow-up in the five mental health factors mediated the treatment effect of the LICBI on the change in delinquency. As hypothesized, the results suggested that changes in impulsivity (β = 0.03, p < .05) and low self-esteem (β = 0.04, p < .05) significantly explained the treatment effect on the change in delinquency from pre- to follow-up tests.

Table 2.

Means and Standardized Deviations of Outcome Variables.

Outcome Variables	Experimental Group			Control Group
Outcome Variables	Pretest	Posttest	Follow-Up Test	Pretest	Posttest	Follow-Up Test
AMHRFDS
Impulsivity	2.29 (0.64)	2.11 (0.63)	2.08 (.60)	2.17 (0.59)	2.09 (.56)	2.13 (.61)
Aggression	1.39 (0.60)	1.33 (0.50)	1.29 (.43)	1.38 (0.54)	1.34 (.55)	1.23 (.38)
Low self-esteem	2.66 (0.61)	2.46 (0.58)	2.36 (.48)	2.67 (0.56)	2.48 (.57)	2.47 (.56)
Loneliness	2.44 (0.58)	2.36 (0.57)	2.22 (.47)	2.42 (0.62)	2.36 (.48)	2.31 (.47)
Negative emotions	2.28 (0.75)	2.04 (0.76)	1.92 (.69)	2.21 (0.80)	2.06 (.78)	1.97 (.87)
Mental health total	2.21 (0.42)	2.05 (0.41)	1.97 (.35)	2.17 (0.41)	2.07 (.42)	2.02 (.39)
Q-LES-Q-18
Physical health	2.97 (0.87)	3.21 (0.86)	3.25 (.73)	3.01 (0.83)	3.19 (.88)	3.17 (.80)
Subjective feelings	3.32 (0.75)	3.55 (0.81)	3.53 (.63)	3.32 (0.75)	3.54 (.75)	3.39 (.79)
Leisure activities	3.27 (0.98)	3.50 (0.89)	3.61 (.73)	3.29 (0.87)	3.40 (.86)	3.31 (.82)
Social relationship	3.24 (0.88)	3.39 (0.88)	3.39 (.72)	3.13 (0.91)	3.23 (.83)	3.26 (.76)
Medication	2.99 (1.09)	3.15 (1.10)	3.23 (.82)	3.18 (2.79)	3.00 (.93)	2.89 (.91)
Total score	3.21 (0.71)	3.40 (0.73)	3.43 (.59)	3.17 (.68)	3.32 (.68)	3.27 (.69)
Delinquency	0.21 (0.22)	0.19 (0.32)	0.17 (.39)	0.18 (0.30)	0.27 (.53)	0.21 (.39)

Note. AMHRFDS = Adolescent Mental Health Risk Factors for Delinquency Scale; Q-LES-Q-18 = 18-item Abbreviated Quality of Life Enjoyment and Satisfaction Questionnaire.

Table 3.

Results of Multilevel Modelling.

Outcome Variables	Time × Treatment	Simple Effect of Time
Outcome Variables	Time × Treatment	Experiment	Control
AMHRFDS
Impulsivity	−.02*	−.01***	−.003
Aggression	.003	−.01**	−.01**
Low self-esteem	−.007*	−.02***	−.01***
Loneliness	−.008*	−.02***	−.008*
Negative emotions	−.009^†	−.03***	−.02***
Mental health total	−.007**	−.02***	−.01***
Q-LES-Q-18
Physical health	.008	.02***	.01*
Subjective feelings	.005	.01**	.006
Leisure activities	.02**	.02***	.002
Social relationship	.002	.10**	.01*
Medication	.04**	.01**	−.02
Total score	.008	.02***	.008^†
Delinquency	−.006*	−.003^†	.003

Note. AMHRFDS = Adolescent Mental Health Risk Factors for Delinquency Scale; Q-LES-Q-18 = 18-item Abbreviated Quality of Life Enjoyment and Satisfaction Questionnaire.

^†p < .1. *p < .05. **p < .01. ***p < .001.

Table 4.

Effect Size Cohen’s d Values of Pre–Post and Pre-Follow-Up Changes.

Outcome Variables	Experimental Group		Control Group
	Effect Size Cohen’s d	Effect Size Cohen’s d	Effect Size Cohen’s d	Effect Size Cohen’s d
	Pre–Post	Pre-Follow-Up	Pre–Post	Pre-Follow-Up
AMHRFDS
Impulsivity	.28	.34	.14	.07
Aggression	.11	.19	.07	.32
Low self-esteem	.34	.55	.34	.36
Loneliness	.14	.42	.11	.20
Negative emotions	.32	.50	.19	.29
Mental health total	.39	.62	.24	.37
Q-LES-Q-18
Physical health	.28	.35	.21	.20
Subjective feelings	.29	.30	.29	.09
Leisure activities	.25	.39	.13	.02
Social relationship	.17	.19	.11	.16
Medication	.15	.25	−.22	.36
Total score	.26	.34	.22	.29
Delinquency	.07	.17	−.21	−.09

Note. Small effect size: 0.2 ≤ Cohen’s d < 0.5; medium effect size 0.5 ≤ Cohen’s d < 0.8; and big effect size: Cohen’s d ≥ 0.8; negative values represent unexpected changes. AMHRFDS = Adolescent Mental Health Risk Factors for Delinquency Scale; Q-LES-Q-18 = 18-item Abbreviated Quality of Life Enjoyment and Satisfaction Questionnaire.

Table 5.

Mediation Analysis of Mental Health Factors on Treatment Effect on Delinquency.

Mediators (M)	Effect of IV on M (a)	Effect of M on DV (b)	Total Effect (c)	Direct Effect (c′)	Indirect Effect (ab) [BC 95% CIs]
Impulsivity	−.29*	−.09	−.20^†	−.26*	.03* [.002, .08]
Aggression	.08	.33***			.03 [−.05, .13]
Low self-esteem	−.20^†	−.19**			.04* [.002, .12]
Loneliness	−.19^†	.06			−.01 [−.07, 007]
Negative emotions	−.16	.11^†			−02 [−.09, .01]

BC = Bias-corrected; DV = Dependent Variable; IV = Independent Variable.

^†p < .1. *p < .05. **p < .01. ***p < .001.

The results of multilevel modeling examining whether gender moderated the effect of time on outcome variables among participants in the LICBI condition are presented in Table 6. It was revealed that male participants achieved greater changes in impulsivity (β = −0.01, p < .1), whereas female participants achieved better improvement in self-esteem (β = 0.01, p < .05) over time.

Table 6.

Predictors of Changes in Treatment Outcomes.

Outcome Variables	Gender × Time
AMHRFDS
Impulsivity	−.01^†
Aggression	.0002
Low self-esteem	.01*
Loneliness	.002
Negative emotions	.0005
Mental health total	.001
Q-LES-Q-18
Physical health	.02
Subjective feelings	.01
Leisure activities	−.005
Social relationship	−.004
Medication	−.001
Total score	.001
Delinquency	.003

Note. AMHRFDS = Adolescent Mental Health Risk Factors for Delinquency Scale; Q-LES-Q-18 = 18-item Abbreviated Quality of Life Enjoyment and Satisfaction Questionnaire.

^†p < .1. *p < .05.

Discussion and Applications to Practice

To the best of our knowledge, the present study is the first attempt to systematically develop and evaluate the efficacy of an LICBI in eliminating mental health–related risk factors and decreasing delinquent behaviors among Chinese youth at risk or with a mild level of delinquency. As supported by our results, participants in the LICBI condition reported greater improvements in various mental health–related risk factors, quality of life, and delinquent behaviors when compared to participants in the control condition. The results are encouraging, because these constitute initial empirical evidence to support the effectiveness of LICBI for Chinese delinquent youth in a community setting.

To begin with, Hypothesis 1 that participants in the treatment condition would demonstrate a greater reduction in the frequency of delinquency was supported. And Hypothesis 2 that participants in the treatment condition would have better improvements in mental health (i.e., lower impulsivity, aggression, negative emotions and loneliness, and higher self-esteem) compared to participants in the control condition was partially supported. Compared to the participants in the control group, participants in the experimental group showed significantly greater improvements in a number of mental health–related risk factors for delinquency (e.g., impulsivity, loneliness, self-esteem, and negative emotions), quality of life subdomains (leisure activity and medical condition), and total number of delinquent behaviors. The effects were maintained at 6-week follow-up. The magnitudes of changes in various outcome variables generally achieved small to moderate effect sizes. These positive changes echo previous Western studies which have found that low-intensity/brief CBI is effective in treating mental health problems (i.e., anxiety, OCD, and depression) and self-reported delinquency among offenders and delinquent youth (e.g., Adamson et al., 2015).

Another important question that we intended to address was the exploration of the mechanism of change of the LICBI on delinquency. Hypothesis 3 that changes in mental health–related risk factors would mediate the treatment effect of the LICBI on the change in participants’ frequency of delinquency was partially supported. The mediating analysis revealed two mediators of the treatment effect, namely impulsivity and low self-esteem. These two psychological factors have been identified as being associated with delinquent behaviors (Chen et al., 2014; Chui & Chan, 2012). As one important CBI strategy taught involved awareness of one’s dysfunctional response patterns and the development of functional responses toward an impending stressor. These awareness and functional strategies might be useful for helping the participants develop a sense of self-control, thus reducing impulsivity and the subsequent delinquent behaviors in the participants. In addition, low self-esteem may weaken social ties by causing a person to withdraw or disengage from prosocial others or social institutions, which in turn constitutes greater associations with deviant peers and delinquency behaviors (Mason, 2001). Our LICBI could enhance the participants’ self-esteem by validating their strengths and helping them develop better interpersonal relationships with peers and families.

Surprisingly, Hypothesis 4 that there is no gender difference in the treatment effects of LICBI on the frequency of delinquency and mental health–related risk factors was not supported. We found that males achieved a greater decrease in impulsivity, whereas females reported a stronger improvement in self-esteem. The results echo theoretical and empirical evidence on gender differences in the course of development of delinquency. Impulsivity has been found to be a greater risk factor for delinquency for boys than for girls (Meier et al., 2008). According to power control theory (Hagan et al., 1987), boys are socialized and allowed to take risks and act impulsively, which may ultimately lead to delinquency. In contrast, compared with boys, girls usually experience a higher level of internalization when faced with external stressors and ascribe failures to internal causes, resulting in lower self-esteem (Epstein et al., 2004). Moreover, compared with boys, girls’ self-esteem and self-worth are more strongly based on interpersonal connections and relationships (Epstein et al., 2004; Guthrie & Flinchbaugh, 2001). Therefore, girls with low self-esteem might be more susceptible to the influence of delinquent peers and turn to delinquent behavior in order to enhance their self-esteem and self-worth. The findings on the mediating effects of impulsivity and self-esteem provide implications for future program design for male and female offenders. For example, improving the ability to curb impulses and to improve self-control may be more important and applicable to male delinquent youth than to females.

The current study provided preliminary positive evidence for the efficacy of a culturally adapted LICBI model to address mental health issues and deviant behaviors of Chinese youth. The findings offer a promising treatment model that can feature in the establishment and localization of the stepped care model in the youth service system in Hong Kong. Furthermore, possible process variables that may mediated the treatment effects of the LICBI program for delinquent youth were identified, namely, self-esteem and impulsivity. Therefore, practitioners can develop and emphasize therapeutic components of CBI programs that facilitate youth’s understanding of the cognitive and behavioral processes underlying their impulsive acts and self-constructs (McKay & Fanning, 2016; Wong et al., 2018). Furthermore, future studies may try to explicate specific cognitive and behavioral strategies that may facilitate the two mediating factors/mechanisms in producing the treatment effects. Lastly, the gender differences in the treatment effects offer insights into the design of future juvenile offender programs. Impulsivity and self-esteem should be emphasized for male and female offenders, respectively, to tailor such gender differences.

There are several limitations to this study. Firstly, this study used a quasi-experimental design, and the threat of selection bias needs to be acknowledged. Although we have ruled out the possible confounding effects of all the demographic variables and adopted multilevel modeling analysis to minimize the effect of possible selection bias (Larzelere et al., 2004), the results should still be interpreted cautiously. In addition, the participants were service recipients of the participating social service organization, but we did not collect information in our questionnaire pertaining to the specific living conditions of these youth. Thus, the possible influence of the living conditions on the treatment effects cannot be determined. Secondly, the long-term effect of a LICBI program is uncertain. The current study only had a 6-week follow-up assessment, and a longer follow-up period is suggested to examine the longer term effects of LICBI for delinquent youth. Thirdly, the current study excluded the young people with severe mental illness or suicidal ideations/attempts, thus the generalization of the current treatment model to other young people under such mental condition may be limited. Last but not the least, the current study could potentially lack treatment integrity such that the treatments might have been differently implemented than planned. However, we indeed have adopted several mechanisms to attenuate the negative influences. First, the social workers who provided the service to the participants received biweekly supervisions from one of the coauthors. Second, the social workers ran the intervention based on a structured and standardized protocol so that they could be strictly guided to perform the intervention.

Footnotes

Appendix

Acknowledgments

Special thanks should be given to the D. H. Chen Foundation sponsoring this Project E.Positive (“Education and Counselling Service for Youth With Deviant Behaviour and Mental Health Issue”) which was conducted and operated by the Hong Kong Federation of Youth Groups Youth Crime Prevention Centre.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The study was funded by the Hong Kong Federation of Youth Groups.

ORCID iD

Xiaoyu Zhuang

Daniel Fu Keung Wong

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