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. Author manuscript; available in PMC: 2025 Aug 19.
Published in final edited form as: Child Youth Serv Rev. 2024 Aug 19;164:107871. doi: 10.1016/j.childyouth.2024.107871

The Unintended Consequence of School Suspension: How School Suspension Impacted Future Grades and Misconduct

Lin Liu 1
PMCID: PMC12291156  NIHMSID: NIHMS2018696  PMID: 40727084

Abstract

The goals of this study were to explore the mechanism via which school suspension leads to adverse academic and behavioral consequences. The author utilized the theoretical framework of general strain theory and assessed whether bonds with school, a prosocial bond preventing deviant outcomes, functioned as a mediator in the path between school suspension and students’ future performance. Based on four waves of longitudinal data of at-risk youth, the study employed structural equation modeling and bootstrapping methods to examine the nexus of suspension, perceived school environment, and adverse academic and behavioral outcomes. Findings revealed that school suspension deteriorated subsequent ratings of school environment among youth respondents. Further, an indirect effect between suspension and worsening of grades was observed and this indirect effect resulted in low ratings of school environment. Although suspension directly predicted future misconduct, no mediation effect of school environment was identified in this link. Implications for intervention programming are discussed.

Keywords: strain, school suspension, perceived school environment, academic performance, school misconduct

Introduction

School environment plays a huge role in shaping the cognitive, motivational, emotional, and behavioral outcomes of students (Blitz et al., 2020; Chaabane et al., 2021; Fraser & Fisher, 1982; Lüdtke et al., 2009). Students are exposed to a variety of characteristics of the school context, and their ratings are the most appropriate source of data for assessing the school environment (Raniti et al., 2022; Wright & Cowen, 1982). Students’ subjective ratings of school environment are particularly vital in studies examining how students’ behavior can be affected by their perceived school context (McCabe et al., 2022). There are many dimensions of school environment students emphasize, which include the physical environment, rule clarity, extracurricular activities, and feeling of support and encouragement.

An encouraging school environment can facilitate positive cognitive, motivational, emotional, and behavioral outcomes of youth (Morris et al., 2020; Smith et al., 2020). However, against the backdrop of the adoption of a zero-tolerance approach to school discipline, the use of exclusionary discipline such as suspensions and expulsions for students in elementary and secondary schools is frequently observed (Cohen et al., 2023; Losen & Martinez, 2013; Hopkins, 2021). Many researchers have indicated that these policies have the potential to trigger a perception of a less encouraging school environment particularly among marginalized youth (Bowditch, 1993; Marchbanks et al.,2014, Rausch & Skiba, 2005; Skiba et al.,1997; Hirschfield, 2008). Suspension and expulsion have been found to predict poor academic performance (Perry & Morris, 2014) and increased risk of future delinquency (Fabelo et al., 2011). These findings seem to defy the rationale of school suspension: using school exclusion as a type of punishment to deter rebellious students from engaging in future delinquency and analogous behaviors.

However, researchers pointed out that studies linking suspension and school failure sometimes did not control for preexisting issues of grades and behaviors (Valdebenito et al., 2018). It is possible that students already achieved lower academic grades before suspension, and the trajectory of the worsening of grades would occur regardless of the experience of suspension (Balfanz & Fox, 2014). Another question left unaddressed is the mechanism of suspension on future adverse outcomes: in what ways can school suspension inadvertently lead to a decline in academic performance and an increase in aggressive and antisocial behaviors among youth? Given that how students feel about the school environment was posited to influence their academic and behavioral outcomes, could it be that school suspension triggers lowered ratings of the school environment, which in turn induces poor grades and antisocial behavior? This mechanism has been rarely tested among the general youth population, let alone justice-involved youth, a social group that disproportionately receives harsh school disciplinary measures in the form of school suspension and expulsion.

To further our understanding of the link between suspension and adverse outcomes among justice-involved youth, the study drew insights from the general strain theory especially a recent elaboration of the theory to examine the correlation between school suspension and delinquent behavior resulting from perceptions of inadequate support within the school environment. In particular, to assess the mediation of the school environment in this context, this study leveraged four waves of longitudinal data of a large sample of justice-involved youth and examined the path of school suspension, perceived school environment, and adverse academic and behavioral outcomes.

Literature Review

The missing piece of the puzzle: how social bonds mediate the effect of suspension on adverse outcomes

As one of the most popular theoretical paradigms on criminal behavior, general strain theory states simply that stressors or strains increase the likelihood of crime (Agnew, 1992, 2012). Agnew proposed three major sources of strain that individuals may confront that lead to crime and delinquency: the failure to achieve positively valued goals, the removal of positively valued stimuli, and the presence of negative stimuli (Agnew, 1992, 2012). More than a decade after the initial formation of GST, Agnew elaborated the theory by illustrating the role of social bonds in the strain-delinquency link. Strain may reduce social bonds, foster the social learning of crime, and contribute to personality traits conducive to crime (p. 114). From this recent elaboration of GST, one way that strain induces delinquency is via weakening social bonds. Deviant behavior results from the breakdown of societal bonds (Hirschi 1969). Moreover, the ability of youth to create and promote bonds with social institutions deters or prevents them from engaging in deviance. Juveniles with positive school experiences are found to achieve better academic outcomes and are less inclined to participate in delinquent behavior (Bender 2012; Espelage et al. 2000; Payne et al. 2003; Olweus et al., 1999; Olweus et al., 2007). When one’s bonds to prosocial institutions such as family and school are weakened, the person will be at a high risk of participating in criminal activities and delinquent behavior.

School Suspension Functions as a Source of Strain

Although school suspension is used for several purposes including punishing rule breakers, deterring misbehavior, and maintaining safety and order in school (Morrison et al., 2001; Smiley et al., 2023; Taras et al., 2003), what actually happens to students in the wake of school suspension can be conceptualized as a source of strain. Students who have been out of school for suspension would be excluded from school for significant periods (Rausch & Skiba, 2005). This will deprive students of the people, such as teachers and peers, upon whom they rely for school success (Marchbanks et al., 2014). When academic and behavioral support is cut off, students may find it hard to thrive academically, especially when they cannot complete their schoolwork and lose instructional time due to suspension (Rossow & Parkinson, 1999, p. 49).

Furthermore, students may feel rejected when excluded from school. Sekayi (2001) found that students in an alternative school felt “ostracized” by and resentful of “being pulled out of the ‘regular’ [school] environment” (p. 420). Likewise, Skiba and Noam (2002) suggested that students often experienced suspension and expulsion as rejection. Sekayi (2020) found that such feelings caused “indignation” (p. 414) and resistance to school programs and activities. From the general strain perspective, the lack of academic support and the emergence of negative perceptions of school represent two major types of strain: the loss of positive stimuli and the presence of negative stimuli.

Stress generated from school suspension may reduce youths’ bonds with school peers and teachers (Kuptsevych-Timmer et al., 2019). When youth do not feel they belong to the school, they are less likely to be motivated to achieve the rules and goals set by the school as an institution: to achieve better grades and engage in prosocial activities (Jang & Rhodes, 2012). As a consequence of strain, social bonds may be diminished, increasing the likelihood of delinquency and academic failure. Thus, conceptually, the low ratings of school environment may function as a possible path through which suspension induces poor grades and school misconduct down the road. While this path has been theorized in some studies, only a few studies have attempted to empirically unpack the effect of school environment as a mediator in the suspension-school failure correlation (Jang & Rhodes, 2012; Kuptsevych-Timmer et al., 2019).

In one of these studies, Jang and Rhodes (2012) used data of four waves of 9,421 students from grades 7–12 to examine this relationship. They measured the strain of victimization, abuse and neglect. Their analysis demonstrated that social bonds played a mediating role in the relationship between strain and crime. By measuring strain at the beginning of the longitudinal measurement, the authors established temporal order and observed the impact of strain on the social bonds of juveniles, increasing the likelihood of a variety of crimes. In a study of 600 male and female 9th-grade students from Ukraine, Kuptsevych-Timmer et al. (2019) attempted to examine the mediating effect of social bonds on the strain-delinquency relationship, and they focused on the strain of family abuse and strain of low-grade. Results from their analyses indicated support for the mediation of all social bonds on all forms of strain. In particular, school commitment mediated from 12–22% of all sources of strain, parental monitoring ranged from 15–20%, and parental support from 6–7%, with all of the relationships maintaining significance. The results indicate that higher levels of strain in all forms led to lower levels of social bonds, which in turn, led to higher levels of delinquency (Kuptsevych-Timmer et al, 2019).

Justice-Involved Youth

Justice-involved youth are a particularly vulnerable population of youth who, due to their exposure to compounded disadvantages and trauma within the family and community domains, have intense educational, mental health, medical, and social needs (Skowyra & Cocozza, 2007). Justice-involved youth tend to be exposed to trauma beginning early in life and their deviant coping to traumatic experiences leads them onto a path of arrest and adjudication, which can also be traumatic (Abram et al., 2004). Due to disrupted school and lack of education aspirations, justice-involved youth have lower grades and standard achievement scores and are more likely to have failed a grade (Mazerolle, 1998; Wang et al., 2005). At least 33% of justice-involved youth have received special education services, which is four times higher than the rate found in the general population of youth (Quinn et al., 2005; Wolford, 2000). As many as 13% of delinquent youth demonstrate a serious learning disability (Murphy, 1986; Quinn et al., 2005; Rutherford et al., 1985). Furthermore, justice-involved youth were found to have lower attachment to parents, higher rates of gang membership, weakened commitment to school, and low academic aspirations (Mazerolle, 1998). For those whose academic performance remained low after adjudication, they are more likely to reoffend and transition into chronic offenders compared to their peers who managed to improve their academic performance after adjudication (Maguin & Loeber, 1996).

The Present Study

There have not been studies that assess whether the stress associated with suspension can trigger adverse academic and behavioral outcomes among justice-involved youth via negative ratings of school environment. This study focused on testing the mediation effect in this path. Conceptualizing school suspension as a type of strain in justice-involved youth’s life, it is expected that suspension triggers a poor rating of school environment, and that the perceived problematic environment triggers an amplified risk of academic failure and delinquency.

Methods

Data

This study leveraged data from a sample of justice-involved youth who were placed in moderate-risk facilities in Florida across four fiscal years (July 2009 through June 2012). Moderate-risk facilities are environmentally secure, staff secure, or hardware secure. These facilities provide 24-hour supervision, custody, care, and treatment of residents. Youth in this type of facility represent a moderate- risk to public safety (Florida Department of Juvenile Justice, 2023). The Florida Department of Juvenile Justice collaborates with the Florida Department of Education and local district school boards to provide education programs for justice-involved youth in juvenile justice facilities. Teachers and education staff from district schools are assigned to juvenile justice facilities to provide education programming for justice-involved youth.

Due to the longitudinal nature of the study, multiple waves of data were needed. Thus, the study focused on a sample of youth who all stayed in moderate-risk facilities for at least 270 days, during which four waves of data were recorded: at the time of admission (T1), 90 days after the admission (T2), 180 days after the admission (T3), and 270 days after the admission (T4). Administrative archival data of the youth were maintained by the Florida Department of Juvenile Justice (FDJJ) regarding their demographic, school grades, and school misconduct information. FDJJ used the Residential Positive Achievement Change Tool Assessment (RPACT) to measure the risk/need assessment of the youth who came in contact with the juvenile justice system, which included youth background characteristics such as criminal history as well as their change of attitudes and behaviors in the facilities.1 The RPACT is administered within 30 days of admission, every 90 days thereafter (to indicate behavioral progress, or guide care plan revisions), and prior to discharge.

In total, 3,660 youth in moderate-risk facilities had four waves of RPACT data recorded. The average duration of their confinement was 312 days (ranging from 270 and 340 days). Among the four race/ethnic categories of youth in the sample—white, black, Hispanic and other—only 0.6% of youth (n=22) fell into the ‘other’ category, making it unrealistic to compare the ‘other’ category with the white, black and Hispanic categories. These cases (0.6%) were excluded from the current study. The final sample consisted of 3,638 youth.

Measures

Dependent Variable

For the purposes of this research, the dependent variables included school misconduct and school grades of the youth in the sample. T4 school misconduct was a binary variable representing whether youths engaged in school misconduct during their stays, with a value of one indicating that youths engaged in at least one of the following behaviors: 1) fighting or threatening students; 2) threatening teachers/staff; 2) overly disruptive behavior; 3) crimes in school (e.g., theft, vandalism); and 4) lying, cheating, and dishonesty. When youth engaged in any of these acts in the facilities, case managers would make a record, which became a part of the RPACT data. Due to data limitations, there was only a binary variable of school misconduct: a youth would have a value of one as long as he or she engaged in any one of the above behaviors. T4 grades were represented by another binary variable with a value of 1 representing a GPA equal or above 3.0 while a value of 0 indicated a GPA below 3.0. It would be ideal to use a continuous variable of GAP which would show subtle differences in school performance; however, due to data limitations, a measure of such was not available.

Predictor

T2 school suspension. This was a binary variable indicating whether the youth experienced school suspension at T2.

Mediator

T3 perceived school environment. This was an ordinal variable that measures how youth believe school provides an encouraging environment. The responses included: (1) Does not believe school is encouraging; (2) Somewhat believes school is encouraging; and (3) Believes school is encouraging. Many distinct dimensions of the school environment exist, which include but are not limited to physical space, extracurricular activities, quality of counseling services, and percentage of minority students (Martinez et al., 2016). Due to data limitations, few studies have assessed all dimensions of school environment, given that these dimensions are qualitatively and conceptually different, which require different approaches to measure them. This study was no exception. Based on existing literature, how encouraged students feel at school should be a primary aspect of school environment to focus on when predicting academic and behavioral outcomes of students (Sutherland et al., 2010). Thus, the current study focused on the encouraging environment of school.

Control variables

To obtain reliable estimates on the effect of school suspension on subsequent ratings of school environment and academic and behavioral outcomes, a range of primary risk factors for school grades and misconduct was included in the models as controls. First, the baseline level of misconduct and grades were controlled, which were represented by T1 school misconduct and T1 grades. These variables were measured at T1 in a similar manner as T4 school misconduct and T4 grades, the outcomes of interest. T1 school misconduct and grades could impact not only future misconduct and grades but also decreased satisfaction of school environment, given that students who received poor grades and disciplinary enforcement were found to have low school satisfaction (Huebner & Gilman, 2006). Thus, the effects of T1 misconduct and grades on T3 rating of school environment were controlled for. The next aspect of control variables were adverse childhood experiences (ACEs), which were widely found to affect academic performance and misconduct in school (Blodgett & Lanigan, 2018; Leban & Masterson, 2022). Four ACE variables were included in the models: experiencing sexual abuse (0=no; 1=yes), enduring physical abuse (0=no; 1=yes), being a victim of neglect (0=no; 1=yes), and witnessing violence (0=no; 1=yes). Given that misconduct was one of the outcomes of interest, proxies of aggressive behavior were included as the third aspect of control variables, which included whether the youth was placed in a residential facility due to a weapon offense (0=no; 1=yes), an offense against persons (0=no; 1=yes), and a felony offense (0=no; 1=yes). Past drug and drinking history included two binary variables indicated whether a youth used drugs and engaged in drinking before admission into the facility. Lastly, the effects of demographics were taken into consideration in the model. Demographics included youth gender (male = 1), age at release from the focal residential placement (measured continuously), and self-identified race/ethnicity (non-Hispanic white, non-Hispanic Black, Hispanic).

Analytical Strategy

To examine whether and how school suspension influences subsequent school misconduct and grades, the author estimated the direct effect of school suspension on the two outcomes, as well as the indirect influence through the perceived school environment. Structural equation modeling (SEM) served as the primary analytical approach, which enables researchers to examine structural relationships among variables of interest together and allows multiple endogenous variables to be predicted either directly or indirectly by exogenous and endogenous variables (Kline 2005). The lavaan package in R (v. 4.1.1) was used to conduct the SEM analyses (Rosseel, 2012). Because the endogenous variables (school misconduct and grades) were categorical, weighted least squares means and the variance adjusted (WLSMV) estimator for SEM models were employed to address non-normality and kurtosis. Baseline school misconduct and grades, facility type, and demographic variables were included as controls in all models.

The analysis was conducted in two steps. First, a structural equation model was used to assess the effect of school suspension both directly on school misconduct and indirectly on school misconduct through perceived school environment. The author utilized bootstrapping to assess the significance of the indirect pathway school suspension → perceived school environment → school misconduct, a robust approach to test indirect paths that outperforms other approaches such as the product-of-coefficient (Bollen & Stine, 1990) and causal steps approaches (Fritz & MacKinnon, 2007). In the present study, the author used the bootstrapping approach to generate 1,000 samples that estimate the indirect effect. Second, in another structural equation model, how perceived school environment mediates the effects of school suspension on grades was examined. Standardized effect size was obtained for all coefficients in the models, which facilitated the comparison of effect size.

Results

Descriptive Statistics

Table 2 reports the descriptive statistics for all variables used in this analysis. The largest proportion of youth were non-Hispanic Black (50%), followed by non-Hispanic White (38%) and Hispanic (12%). Nearly 82% of the youth were male. On average, youth were 16 years old, with a range of ages from 10–18. Nearly 89% engaged in school misconduct at T1, and the rate of school misconduct at T4 is 84%. School performance seemed to have improved from T1 to T4, with 12% having a GPA equal or above 3.0 at T1 and 40% having a GPA equal or above 3.0 at T4. About 18% received suspension at T2. On a scale from one to three, the average rating of school environment at T3 is 2.5, indicating overall the perceived school environment tends to skew positively. The rates of ACEs were alarming. About 24% experienced physical abuse, 77% witnessed violence, 13% experienced sexual abuse, and 12% experienced neglect. About 66% and 84% of the youths engaged in drinking and drug use before admission into the facilities, respectively. Regarding the proxies of aggression, 88% of them were convicted of felony offenses, followed by offenses against persons (68%) and weapon offenses (16%).

Table 2.

Structural Equation Model Results on School Grades

Model 1
T3 perceived school environment T4 grade
Exogenous variables b (SE) β b (SE) β
Female 0.33***(0.04) 0.11
Black −0.41***(0.05) −0.18
Hispanic −0.08(0.05) −0.02
Age 0.04(0.03) 0.04
T1 grade −0.28***(0.01) −0.16 0.99***(0.01) 0.29
T2 suspension −0.23***(0.02) −0.15 −0.34***(0.05) −0.12
T3 perceived school environment 0.52***(0.02) 0.26
Felony offense 0.11†(0.06) 0.03
Weapon offense −0.02(0.07) −0.01
Person offense −0.02(0.04) −0.01
Past drinking 0.22***(0.05) 0.09
Past drug use 0.01(0.08) 0.00
Was a victim of sexual abuse 0.00(0.06) 0.00
Was a victim of physical abuse 0.06(0.06) 0.02
Witnessed violence 0.03(0.07) 0.01
Was a victim of neglect −0.03(0.07) −0.01
Bootstrapping results for total effects (direct + indirect): T2 suspension (predictor) → T3 perceived school environment (mediator) → T4 school grade (outcome) Direct effect: b = −0.34***(0.05), β = −0.12 Indirect effect: b = −0.12***(0.01), β = −0.04 Total effect: b = −0.46***(0.05), β = −0.16
Model fit indices χ2 = 10.00; CFI = 0.97; SRMR = 0.00; RMSEA = 0.01
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†

p< .10;

*

p ≤ .05;

**

p ≤ .01;

***

p ≤ .001;

b = unstandardized coefficient; SE = standard error; β = standardized coefficient

Structural Equation Models Predicting Two School Outcomes

Model 1 of Table 2 presents the results of the structural equation testing the mediating effect of perceived school environment on the path between school suspension and grades. All control variables were estimated in the model, the standardized and unstandardized coefficients of which can be found in the table. In this model, the mediation effect size was based on the two path coefficients: school suspension → perceived school environment, and perceived school environment → grades. At the same time, given that prior studies generally found that the medication effect is partial mediation—not all the effect of the predictor on the outcome is exerted via the mediator (e.g., Vargas-Madriz et al., 2021), the author followed past practices to assume the direct effect of school suspension on grades to be non-zero. Therefore, the direct path between school suspension → grades was not constrained to zero.

As shown in Table 2, T2 school suspension was negatively associated with T3 perceived school environment (β=−.15, p < .001). In turn, T3 perceived school environment showed a positive correlation with T4 grades (β =.26, p < .001). Not surprisingly, the model also shows that T1 grades were positively associated with T4 grades, with a standardized effect size of .29 (p < .001). Interestingly, youth who reported having a drinking history achieved better grades at T4 than those who reported no drinking history (β =.09, p < .001). With regard to demographic variables, female youth were more likely to achieve better grades than male youth in facilities (β =.11, p < .001). Finally, the model shows that Black youth had a significantly higher risk of receiving lower grades than White youth (β =−.18, p < .001), while no significant difference was discovered between Hispanic and White youth.

The total, indirect, and direct effects of these paths were obtained via bootstrapping (Figure 1). Bootstrapping results show that there was a statistically significant indirect effect of school suspension → grades through perceived school environment (β =−.04, p < .001). Regarding total effects (standardized direct + standardized indirect effects) relevant to Model 1, the total effect of school suspension on grades was −.16 (p < .001). The last section of Table 2 displays the fit indices for Model 1, indicating an acceptable level of model fit (χ2 = 10.00, p < .001, CFI = .97, RMSEA = .02).

Figure 1. Mediation analysis results on T4 grade.

Figure 1.

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Note: Covariates controlled in the model: gender, race, age, T1 grade, felony offense, weapon offense, person offense, past drinking, past drug use, was a victim of sexual abuse, was a victim of physical abuse, witnessed violence, and was a victim of neglect. Due to limited space, the coefficients of covariates were not presented in the figure.

***p ≤ .001

Model 2 in Table 3 tested the mediation hypothesis with school misconduct as the outcome. In this model, the paths of school suspension → perceived school environment were statistically significant (β =−.15, p < .001), but the path of perceived school environment → school misconduct was not statistically significant (β =.01, p=.70). Bootstrapping results showed that the indirect effect of school suspension → school misconduct was not statistically significant (β =−.00, p=.69), yielding little evidence that perceived school environment mediated the effect of school suspension on school misconduct (Figure 2). However, a direct and strong effect of suspension on misconduct was discovered (β =.08, p < .001). In other words, although suspension did not affect misconduct via perceived school environment, the suspension did have a significant impact on misconduct.

Table 3.

Structural Equation Model Results on School Misconduct

Model 2
T3 perceived school environment T4 school misconduct
Exogenous variables b (SE) β b (SE) β
Female 0.61***(0.04) 0.20
Black −0.07(0.04) −0.02
Hispanic 0.09(0.09) 0.02
Age −0.19***(0.04) −0.20
T1 school misconduct −0.12***(0.03) −0.07 1.69***(0.09) 0.44
T2 suspension −0.22***(0.02) −0.15 0.25**(0.08) 0.08
T3 perceived school environment 0.01(0.04) 0.01
Felony offense 0.02(0.04) 0.00
Weapon offense 0.10(0.09) 0.03
Person offense −0.05(0.06) −0.02
Past drinking 0.02(0.06) 0.01
Past drug use 0.16†(0.09) 0.05
Was a victim of sexual abuse 0.19†(0.11) 0.05
Was a victim of physical abuse 0.07(0.08) 0.03
Witnessed violence −0.05(0.08) −0.02
Was a victim of neglect 0.01(0.09) 0.00
Bootstrapping results for total effects (direct + indirect): T2 suspension (predictor) → T3 perceived school environment (mediator) → T4 school misconduct (outcome) Direct effect: 0.25**(0.09), β = 0.08 Indirect effect: −0.00(0.01), β = −0.00 Total effect: 0.25**(0.09), β = 0.08
Model fit indices χ2 = 29.74; CFI = 1.00; SRMR = 0.00; RMSEA = 0.01
Open in a new tab
†

p ≤ 010;

*

p ≤ .05;

**

p ≤ .01;

***

p ≤ .001;

b = unstandardized coefficient; SE = standard error; β = standardized coefficient

Figure 2. Mediation analysis results on T4 school conduct.

Figure 2.

Open in a new tab

Note: Covariates controlled in the model: gender, race, age, T1 school misconduct, felony offense, weapon offense, person offense, past drinking, past drug use, was a victim of sexual abuse, was a victim of physical abuse, witnessed violence, and was a victim of neglect. Due to limited space, the coefficients of covariates were not presented in the figure.

**p ≤ .01; ***p ≤ .001

Not surprisingly, T1 school misconduct was negatively related with T4 school misconduct, with a nontrivial standardized effect size of .44 (p < .001). Younger (βage=−.20, p < .001) and female youth (β =.20, p < .001) were more likely to engage in school misconduct than older and male youth in facilities. Finally, no significant difference in the risk of school misconduct was discovered between White, Hispanic and Black youth. The fit index of Model 2 was acceptable (χ2 = 29.74, p < .001; CFI = 1.002; RMSEA = .02).

Discussion

There has been a large body of research linking suspension to students’ behavior and academic outcomes (Marchbanks et al., 2014, Crosby et al., 2017; Hemphill et al., 2006; Umeh et al., 2020; Rausch & Skiba, 2005; Hirschfield, 2008). However, so far there has been little research attention dedicated to assessing the mechanism via which such a path occurs. Drawing insights from general strain theory (Agnew, 1992, 2012), the author argues that school suspension can be conceptualized as a type of strain in youth’s life and that suspension triggers a decrease in ratings of school environment, a vital type of pro-social social bond in youth’s life. When youth do not feel bonded with school, they may demonstrate an amplified risk of academic failure and misconduct. This study not only contributed to the literature by conducting a mediation test in which school suspension was conceptualized as a source of strain but also extended prior studies by testing the mediation based on a sample of justice-involved youth (average age = 16). Some important findings emerged from the analyses.

First, the mediation hypothesis was confirmed when using grades as the outcome. With the effect of T1 grades controlled for, T4 higher school grades were found to be significantly associated with T3 perceived more positive school environment, which was predicted by T2 school suspension. The direct relationship between suspension and grades echoed prior findings among the general population that disciplinary incidents can trigger negative outcomes for students (Fabelo et al., 2011; Fisher et al., 2020; Perry & Morris, 2014). The at-risk sample used in this study illustrated that this detrimental effect of disciplinary incidents was also found among delinquent youth who disproportionately suffered adverse childhood experiences and other socio-economic disadvantages. Furthermore, this study revealed a mediation effect, whereby suspension from school was linked to a subsequent decline in grades through an intermediate process. Procedurally, the middle stage lay in the process that youth perceived school as less supportive after being suspended, and this negative perception of the school environment triggered their subsequent deterioration of grades. This does not necessarily indicate that all students suffered deteriorated grades in juvenile justice facilities—as the descriptive statistics showed, grades for the whole sample improved from T1 to T4. However, the mediation path illustrated that for those who received exclusionary disciplinary measures, a sequent worsening of grades followed. Findings underscored the applicability of an integrated strain and social bonds perspective to explain disciplinary incidents and future academic failure, and this theoretical lens has the potential to explain the effect of suspension on the worsening of future grades via a cognitive and emotional perspective.

Second, when using school misconduct as the outcome, the mediation hypothesis was not supported. School suspension directly affected school misconduct, but there was no indirect effect of school suspension on misconduct via the school environment. It is possible that school suspension can lead to future misconduct via other mechanisms such as decreased respect for rules and teachers. For example, students who receive harsh discipline decisions might perceive the rules as illegitimate, and no longer have a desire to obey the rules, which might likely lead to further misconduct down the road. It is also possible that students experience anger when suspended, and this negative emotion leads to acting out delinquent behaviors. A third possibility is that classroom instructors might view students who had been suspended as problematic students and that this unintentional bias, in turn, contributes to future referrals of these students. The current data does not contain information to test these possibilities. Further studies are needed to reveal the mechanism via which school suspension increases the risk of future school misconduct.

Third, Black youth and female youth fared worse than their White, male counterparts, respectively. For the analysis of academic performance, variables such as prior grades and perceived school environment did not explain away the effect of race. Black youth experienced poorer academic performance, attaining grades in school at T4 that were significantly lower than their White peers, even with covariates controlled for. It is possible that Black justice-involved youth had school experiences dissimilar from those of White justice-involved youth, given the stereotypes against Black youth. Black youth might internalize the stereotypes and lose educational aspirations and self-esteem, which might negatively impact their grades. Given that self-esteem and education aspirations were not assessed in the present study, future studies would benefit from testing whether these factors explain why Black youth achieved lower academic performance than White youth. For the analysis on misconduct, a significant gender gap still existed even when perceived school environment and prior misconduct records were controlled for. The finding is in line with Morris’s pushout theory, which posits that current beliefs, policies, and actions in school degrade and marginalize both black girls’ learning and their humanity, leading to conditions that push them out of schools and render them vulnerable to even more harm (Morris, 2016, p. 8). This present finding is an extension of how school experiences functioned as a catalyst for disengagement of education for girls: after adjudication and enrollment in alternative education, these girls continued receiving harsh disciplinary measures and were frequently labeled as rule violators. It is imperative to bring the ignored population of young women in the juvenile justice system to the forefront of the school discipline conversation.

Limitations

It bears noting particular limitations regarding the data utilized for this study. While this longitudinal database enabled the use of multiple waves of data to test the mediation path of school suspension→perceived school environment→school outcomes, the data did not include the experiences in prior schools before youth engaged in offending and became involved in the juvenile justice system. Future studies should gather data on school outcomes prior to using admission to residential facilities as control variables. The second limitation also pertains to limited data. The measure of perceived school environment was represented by how encouraging student felt at school; theoretically an encouraging school environment is a primary predictor of students academic and behavioral outcomes. However, other aspects of perceived school environment such as the cultural climate, resources, and rich extracurricular activities of school might also impact grades and misconduct. Future studies should collect data on these aspects of perceived school environment to extend this line of research. Thirdly, the youth in this study went to different alternative schools; however, the data only contained case information of individual youth, with the school names removed. Thus, the data did not allow a multi-level mediation analysis where schools are used as second level units. Lastly, school misconduct might be due to situations such as a peer’s instigation, being bullied and ridiculed, or family members’ failure to attend graduation ceremonies (Cooke et al., 2008; Gadon et al., 2006). Future studies are needed to assess simultaneously the effects of state factors (e.g., school climate) or situational factors on student misconduct.

Policy Implications

The findings showed that school suspension has a consistent negative effect on long-run educational outcomes for at-risk youth. School suspension is followed by future misconduct and worsening of grades. Educators who work with justice-involved youth should be provided alternatives to punitive disciplinary practices. There has been some shift in education practices: some school districts adopted alternatives to exclusionary disciplinary measures (Mann, 2016; McNeill et al., 2016). For example, in Connecticut, alternatives to suspension and expulsion included reflective essays, apologies, and responsible thinking classrooms (Dufresne et al., 2010). When students break rules, the student would be required to fill out a reflection form and talk about the form with the principal (Dufresne et al., 2010). In this approach, the educators turned poor choices into a learning opportunity. With these alternatives implemented, there were significantly fewer incidents of student misconduct in the school districts in Connecticut (Dufresne et al., 2010). Educators in states that still solely rely on exclusionary disciplinary measures might explore the probability of adapting and applying the alternatives to suspension and expulsion that have been found effective. Shifting away from harsh disciplinary measures in education has the potential to improve school climate, reduce school misconduct, and improve academic and behavioral performance of at-risk youth, which will help them embark on a direction away from persistent academic struggles and involvement in delinquency.

Table 1.

Descriptive Statistics (n=3,638)

Focal Variables Mean/% SD Min Max
 T4 school misconduct 84.43%
 T4 grade 40.33%
 T3 perceived school environment 2.50 0.57 1.00 3.00
 T2 suspension 17.92%
 T1 grade 12.10%
 T1 school misconduct 89.20%
Control variables
 Female 18.05%
 Male 81.95%
 White 38.20%
 Black 49.89%
 Hispanic 11.91%
 Age 16.20 1.23 9.76 18.01
 Felony offense 87.46%
 Person offense 67.53%
 Weapon offense 15.60%
 Past drinking 65.60%
 Past drug use 84.32%
 Was a victim of neglect 13.12%
 Was a victim of sexual abuse 12.35%
 Witnessed violence 77.23%
 Was a victim of physical abuse 23.81%
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Acknowledgments:

The author would like to extend her gratitude for the Florida Department of Juvenile Justice for providing the access to de-identified data to support the research. The opinions, findings, and conclusions or recommendations expressed in this manuscript are those of the authors and do not necessarily reflect those of the Florida Department of Juvenile Justice.

Funding:

This study is funded by the National Institute of Mental Health. Award number: 1R21MH133905-01

Footnotes

Ethics approval and consent to participate: The study is a secondary data analysis; it does not involve recruiting human participants. Informed consent: N/A.

Consent for publication: The author confirms that the work described has not been published before, that it is not under consideration for publication elsewhere, that its publication has been approved by all co-authors (if any), and that its publication has been approved by the responsible authorities at the institution where the work is carried out.

Competing interests: The author declares that there is no conflict of interest.

1

The RPACT assessment is administered by bachelor degree-level residential program case managers. They must complete a standardized 2-day Motivational Interviewing training and a 3-day assessment and case planning training that trains participants on theory, risk-need-responsivity principles, the assessment software, scoring, and case planning process. Both trainings include inter-rater reliability exercises.

2

The degree of freedom and chi-square were both non-zero, indicating a CFI value of one in this model was not due to an under-identified model. In this analysis, CFI = 1.00 and RMSEA=.02 indicated that the model was a close fit to the data (e.g., Loukas et al., 2009, p.208).

Availability of data and materials:

The quantitative data used in this study are received from the Florida Department of Juvenile Justice (FDJJ), which contains de-identified case records of the youth in the FDJJ system. Per FDJJ policy, case-level juvenile justice data are not to be publicly shared. However, there is a set of procedures that researchers can utilize to request data from FDJJ, which is on the FDJJ official website.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The quantitative data used in this study are received from the Florida Department of Juvenile Justice (FDJJ), which contains de-identified case records of the youth in the FDJJ system. Per FDJJ policy, case-level juvenile justice data are not to be publicly shared. However, there is a set of procedures that researchers can utilize to request data from FDJJ, which is on the FDJJ official website.

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