The Age-Graded Consequences of Justice System Involvement for Mental Health

Abstract

Objectives:

Drawing on the life course and social stress perspectives, this paper examines age variation in the mental health consequences of justice system involvement by assessing arrest, conviction, or incarceration as possible age-graded stressors that amplify harm at younger ages of involvement.

Methods:

Individual fixed effect regression models utilizing National Longitudinal Survey of Youth (1997) data test whether age moderates the mental health impact of arrest, conviction, or incarceration. Follow-up analyses for moderated associations compute and compare age-specific relationships to identify differences in the significance and magnitude of mental health consequences for contacts spanning late adolescence, emerging adulthood, and adulthood.

Results:

The incarceration-mental health relationship is moderated by age, as significant harms to mental health are exclusively observed following secure confinement in late adolescence (ages 16–17) and emerging adulthood (18–24), but not in adulthood (25–33). The lack of moderation between arrest and mental health indicates a universally harmful experience at all ages.

Conclusions:

Evidence supports conceptualizing incarceration as an age-graded social stressor that is correlated with pronounced harm to mental health during late adolescence and emerging adulthood. Future research should identify the mechanisms of this unique stress response following earlier incarcerations and its long-term salience for processes of cumulative disadvantage.

Keywords

collateral consequences mental health issues life-course theory developmental theories criminological theory

Within the now robust collateral consequences literature, varied types of system contact have been correlated with declines to mental health, including police stops (Geller et al. 2014; McFarland, Geller, and McFarland 2019), arrests (Fernandes 2020; Sugie and Turney 2017), and incarceration (Baćak, Andersen, and Schnittker 2019; Boen 2020; Porter 2019; Porter and DeMarco 2019; Schnittker, Massoglia, and Uggen 2012). This literature base elucidates the average impact of justice system involvement for mental health, finding support for conceptualizing justice contacts as social stressors that provoke adverse health responses (Link et al. 1997; Pearlin 1999). However, many questions remain regarding heterogeneity in these general associations (e.g., Kirk and Wakefield 2018).

This paper explores one important but understudied potential source of variation: the timing of system involvement. While some scholarship suggests the importance of earlier entry into prison for mental health (Baćak et al. 2019; Barnert et al. 2018; Boen 2020), less is known about the relative difference in the impact of justice system contacts—carceral and non-carceral alike—across age of experience. This gap in the literature materializes despite theoretical insights from the life course perspective and the social stress process that collectively envision an age-graded relationship in mental health (and other) consequences. The timing principle suggests that justice system involvement earlier in the life course will correlate with heightened immediate and prolonged negative consequences (e.g., Avison 2010; Elder 1998; Kurlychek and Johnson 2019; Sampson and Laub 1995). For mental health outcomes, this amplified harm may be especially likely for justice-involved adolescents and emerging adults for whom social stress from the justice system likely compounds with stressors inherent in these transitional developmental phases (e.g., Altschuler and Brash 2004; Shanahan 2000). However, research has yet to thoroughly examine this possibility.

In this analysis, I advance understanding of the mental health consequences of justice system involvement by investigating how variation in the timing of justice involvement may generate variation in observed outcomes. It is guided by two research questions: (1) are associations between various forms of justice system contact (arrest, conviction, and incarceration) and mental health variant across age of contact?, and, if so, (2) which ages of justice system contact are most impactful for mental health? The analytic design invokes the logic of moderation analysis (e.g., Baron and Kenny 1986) to explore age variation using data from the National Longitudinal Survey of Youth, 1997 cohort and fixed effect regression models. I find evidence of an age-graded relationship between incarceration and mental health where negative impacts are concentrated for incarceration at ages 16 through 22 (and marginally at 23) during late adolescence and emerging adulthood, and do not materialize for incarceration at 24 or older throughout adulthood. However, age does not moderate the arrest-mental health relationship, as being arrested is correlated with harm at all examined ages. I begin by overviewing studies on the mental health consequences of justice involvement, then motivate this analysis by drawing on integrated insights from the life course perspective and social stress process.

Reviewing the Mental Health Consequences of Justice System Involvement

An overview of prior research indicates that varied types of involvement with the justice system are, on average, deleterious to individuals’ mental health. Outside of prisons, being stopped by the police in adolescence and young adulthood has been associated with heightened anxiety, worsened emotional wellbeing, higher stress levels, and increased symptoms of post-traumatic stress disorder and psychological distress (Baćak and Nowotny 2020; Baćak and Apel 2019; Del Toro et al. 2019; Geller et al. 2014; Geller, Fagan, and Tyler 2017; Jackson et al. 2019; McFarland et al. 2019; Turney 2020). Arrests in adulthood have also been correlated with worsened mental health (Fernandes 2020; Sugie and Turney 2017). Formal convictions are inconsistently related to mental health, with some evidence failing to find an independently significant association following a juvenile adjudication (Craig et al. 2018) or adult conviction (Sugie and Turney 2017). Piquero and colleagues (2010) found that convictions during adolescence were associated with an increased likelihood of life failure, a composite measure that includes dimensions of mental health; however, these scale elements were not independently significant.

With respect to incarceration, going to prison in adulthood has been associated with declines in varied aspects of mental health, including elevated levels of mood disorders (Schnittker et al. 2012), depression and/or anxiety symptoms (Barnert et al. 2017; Boen 2020; Esposito et al. 2017; Fernandes 2020; Porter and DeMarco 2019; Porter and Novisky 2017), psychological distress (Turney, Lee, and Comfort 2013) and seeking treatment for psychiatric disorders (Baćak et al. 2019). Reflecting a need for more research in this area, the mental health impact of incarceration prior to adulthood is less clear (Kinner and Young 2018). Some evidence finds a positive association between secure placement (e.g., juvenile incarceration) and reporting of depressive symptoms in adulthood (Lanctôt, Cernkovich, and Giordano 2007; Ziegler 2014) or increased demand for mental health treatment (Verbruggen, Van Der Geest, and Bijleveld 2018). Others similarly observed harm to mental health and overall health following incarceration during emerging adulthood (Esposito et al. 2017). Conversely, Gilman and colleagues (2015)’s propensity score analysis did not detect a significant impact of placement for major depression or generalized anxiety disorder in adulthood. However, previously placed individuals did face numerous other challenges later in the life course, including an increased likelihood of spending time in prison, abusing alcohol and substances, and receiving welfare (Gilman, Hill, and Hawkins 2015).

A limited number of studies in this growing literature base engage with the possibility of heterogeneity in general associations. Sugie and Turney (2017) considered variation in mental health responses driven by local contextual disadvantage with respect to rates of poverty, violence, unemployment, and public assistance receipt. Their analysis found that the mental health of individuals from the most disadvantaged counties suffered the most following arrest and incarceration. Jackson and colleagues (2019) considered the nature of the contact itself as a source of variation, finding that police stops occurring at youths’ schools were most detrimental to their mental health relative to other stop locations.

Less is known about age variation in mental health outcomes because many studies limit attention to contacts prior to (Barnert et al. 2018; Craig et al. 2018; Del Toro et al. 2019; Gilman et al. 2015; Jackson et al. 2019) or after (Sugie and Turney 2017) reaching adulthood, often using the most common age of criminal responsibility—18—as the cutoff point. The handful of studies considering the specific possibility of age variation typically use discrete distinctions or finite comparisons to assess the impact of differential timing. For example, focused on very early experiences, Barnert and colleagues (2018) found that childhood carceral confinement (ages 7–13) was more harmful to mental health than confinement at 14 or older. Boen (2020) found preliminary evidence of additional symptoms of depression among those incarcerated before turning 18 relative to those incarcerated as adults, but this association was eradicated in more robust model specifications. Moving beyond such sample partitions, Baćak and colleagues (2019) leveraged a natural experiment and found that individuals entering prison earlier—that is, at age 15 relative to age 20—were more likely to seek and/or receive treatment for psychiatric disorders.

While these studies are instructive, they fail to provide detailed insight into timing-based variation in mental health consequences in two key ways. Not only do they exclusively consider incarceration, but their use of blunt age distinctions and/or narrow age windows precludes a comprehensive assessment of the possible age-graded mental health responses to justice system involvement predicted by theory. Accordingly, the relative salience of differentially timed justice system contacts (i.e., an age-graded impact) is unclear because research designs (to date) typically lack the capacity to comprehensively compare outcomes across a wide range of ages of experience. Drawing on the life course and social stress perspectives, this paper explores this potential age-graded variation. It focuses on contacts co-occurring with late adolescence and emerging adulthood that present specific risks to development and are often targeted for progressive policy responses (e.g., Farrington, Loeber, and Howell 2012).

The Possibility of Harm Amplification: Timing, Social Stress Exposure, and Mental Health for Justice Involvement in Late Adolescence and Emerging Adulthood

The timing principle of the life course perspective brings attention to potential age variation, positing that the total impact of life events or transitions will be conditioned by their relative occurrence within an individual’s life span (Elder 1998). In other words, the same life event experienced by two different people at two different ages will carry a different impact for their respective developmental trajectories. Applied to criminology, the timing of the life event of justice system involvement will make it differentially salient across life stages (Sampson and Laub 1995/1997). This importance of being arrested, convicted, or incarcerated is magnified for earlier timed contacts occurring during adolescence and/or the transition to adulthood—critical developmental phases for shaping life course trajectories (Chung, Little, and Steinberg 2005; Scott and Grisso, 1997; Shanahan, 2000). Disruption during these life stages can be more consequential because “negative experiences early in life have the greatest potential to alter life trajectories” (Kurlychek and Johnson 2019:306). Corroborating this point, prior research indeed finds evidence of numerous social disadvantages correlated with justice involvement during youth and adolescence, including: repeated criminal behavior into adulthood (Aizer and Doyle 2015; Gatti, Tremblay, and Vitaro 2009; Wiley, Slocum, and Esbensen 2013), reduced odds of high school completion (Aizer and Doyle 2015; Hjalmarsson 2008; Kirk and Sampson 2013; Sweeten 2006), decreased employment and wages (Apel and Sweeten 2010; Augustyn and Loughran 2017; Sharlein 2018), and lower likelihood of marriage (Huebner 2005) and social adjustment (Makarios, Cullen, and Piquero 2017).

The theoretical lens of the social stress process indicates potential mechanisms that can generate amplified harm to mental health following earlier timed justice contacts. Social stress can arise from a multitude of sources to provoke disruption, necessitate adaptation, and often, proliferate additional stress through primary and secondary pathways (Pearlin 1999). The former includes the immediate disruption and adaptation in response to stress exposure; the latter entails the accumulation of additional stressors that generate adverse health consequences across the life span, especially if the initial stressor engenders stigmatization and generates perceived discrimination (Kessler, Mickelson, and Williams 1999; Link et al. 1997; Pearlin et al. 2005; Thoits 2010). In addition to the structure of the system itself (Baćak, Lageson, and Powell 2020), criminal justice contacts like arrests (Sugie and Turney 2017), conviction records (Asad and Clair 2018), and incarcerations (Massoglia and Pridemore 2015) are increasingly recognized as social stressors and stigmatizing events that are immediately detrimental and continually harmful to individuals’ health.

Together, these two theoretical perspectives suggest that justice system involvement will have a non-uniform impact on health outcomes because differences in the timing of exposure will produce a different stress experience and response (e.g., Pearlin and Skaff 1996; Wheaton and Gotlib 1997). Other stressors have been associated with varied outcomes, contingent upon their timing in the life course. Examples include correlations between childhood stress and adversity and adult stress burden and marriage (Umberson et al. 2005), emerging adulthood social stress and mitigated developmental progress toward social maturity (Bell et al. 2008), and self-perceived economic stress during emerging adulthood and declines in wellbeing (Ranta et al. 2020).

I hypothesize that justice system involvement will similarly function as an age-graded social stressor in which the significance and/or magnitude of mental health outcomes of being arrested, convicted, or incarcerated will depend upon their relative occurrence in the life span. Compared to those occurring at older ages, I expect to observe amplified harm to mental health associated with contacts at younger ages, especially those that occur during late adolescence and the transition to adulthood—two pre-adulthood transitional phases that are characterized by numerous role transitions and associated instability (Arnett 2000). Anticipated pronounced and adverse consequences likely emerge from the co-occurrence of stress exposure from system involvement and stress exposure from the numerous social changes embedded in these developmental stages (Almeida and Wong 2009; Shanahan 2000). System-involved adolescents face a contemporaneous challenge of navigating the justice system and the transition to adulthood (Altschuler and Brash 2004) during a developmental period featuring substantial major and minor stressors (Shanahan 2000) and pronounced reactions to stressors and other negative stimuli (Tanner and Arnett 2009). To complicate further, mental health problems often develop and emerge during adolescence in the form of anxiety symptoms and disorders (Adkins et al. 2009; Beesdo, Knappe, and Pine 2009; Kessler et al. 2005; Merikangas et al. 2010; Rapee, Schniering, and Hudson 2009). Through this compounding process, justice system involvement may be an age-graded social stressor that correlates with pronounced harms for earlier timed contacts through a uniquely amplified adverse mental health response to this stress exposure.

Current Study

This study advances understanding of the mental health consequences of justice system involvement by investigating two research questions: does the impact of being arrested, convicted, or incarcerated for mental health vary by the age of experience? If so, which ages of contact are the most consequential? While I expect justice system involvement to be deleterious to mental health at all ages, I anticipate the outcomes to be age-graded in nature: justice involvement during late adolescence (defined here: ages 16–17) or emerging adulthood (defined here: ages 18–24) will produce quantitatively larger harms for mental health than involvement during adulthood (defined here: ages 25 and above).¹ I now describe the data and method leveraged to test these hypotheses using age-specific associations across developmental stages.

Data

This analysis uses data from the National Longitudinal Survey of Youth 1997 (NLSY97 hereafter), a cohort of youth (N = 8,984) born between 1980 and 1984. The survey questionnaire inquires broadly about employment and wellbeing throughout the transition to adulthood. Importantly for this work, respondents repeatedly provide information on self-reported justice system involvement, delinquent and/or criminal behaviors, and mental health. This analysis uses data from 7 interview waves (Waves 4, 6, 8, 10, 12, 14, and 16), a range capturing recent symptoms of depression and anxiety in adulthood and justice system contacts in late adolescence and adulthood. The analytic sample is constructed from respondents participating in all seven specified interview waves. I perform multiple imputation using 25 chained equations in Stata 16 to impute values for question nonresponse for the following variables included in the analysis: mental health, delinquency, poverty, alcohol use, substance use, smoking, and employment. The analytic sample includes cases with complete information on the dependent variable, yielding a final sample of 39,320 person-years for analysis (N = 7,598).

Measures

Dependent Variable: Mental Health

The outcome variable is self-reported mental health problems, measured using individuals’ average responses to the shortened form of the Mental Health Inventory scale (MHI-5; range = 1–4, with increments of .2). Beginning in Wave 4 and biannually thereafter, respondents are asked how often in the past month they have: been a nervous person (reverse coded), felt calm and peaceful, felt downhearted and blue (reverse coded), been a happy person, or felt so down in the dumps nothing could cheer them up (reverse coded). The scale’s anchor points range from reporting feeling symptoms none of the time (=1) to all of the time (=4), with higher values on this variable indicating more frequently experienced symptoms of depression and anxiety in the past month (e.g., reporting more time feeling downhearted and blue, less time being happy, and so on). This short scale has been validated as a screening instrument for depression and anxiety disorders (Cuijpers et al. 2009, Rumpf et al. 2001).

Independent Variables

I consider the mental health consequences of three types of self-reported justice system contact—arrest, conviction, or incarceration. These stages of system involvement are used here because they invoke unique stressors and carry the highest risk of stigmatization: arrest, which initiates formal institutional involvement; conviction, which issues a formal criminal status; or incarceration, which bestows a custodial sanction. Each variable is a binary measure reflecting whether a respondent has been arrested, convicted, or incarcerated since the last interview (approximately 12–18 months). The incarceration measure captures various forms of confinement in jails, prisons, juvenile facilities, or training schools and includes respondents currently incarcerated at the time of interview. Starting with arrest experiences, the NLSY97 questionnaire sequence progressively limits the respondent universe of criminal justice contact items to those reporting continued system involvement. Measures of deeper system contact, like conviction and incarceration, thus capture both stage-specific and, to a degree, accumulated involvement. Accordingly, conviction and incarceration regression models include a control for arrest to parse out their unique mental health consequences from those associated with the entirety of justice system processing.

Time-Varying Covariates

Regression models include several covariates to control for competing observable factors that can affect levels of mental health and/or the likelihood of involvement with the justice system. These variables and their descriptive statistics are listed in Table 1. Age indicates the respondents’ age (in years) at the time of completion of each survey wave. Self-reported delinquency is computed as a variety score capturing the incidence of six illegal behaviors: destruction of property, petty theft, grand theft, other property offenses, attacking someone, and selling drugs.² I approximate socioeconomic status by including a dummy variable (poverty) of whether a respondent’s household income (parental or personal) falls at or below the poverty line. The contextual variables of urban and South indicate whether the respondent lived in a city or in the southern region of the country, respectively. I measure educational attainment (education) by summing the total number of years of completed schooling at the time of interview. I include three measures of individuals’ health behaviors. Smoking flags whether a respondent reports smoking cigarettes since the last interview; alcohol use indicates if a respondent reports having a drink before or during school or work at least one day within the past month; substance use indicates if a respondent reports using cocaine, crack, heroin, or other drugs to get high. Finally, I include a measure of whether a respondent is or was married to their partner within the reference period and whether a respondent was employed full-time within the last year (e.g., worked 35 hours or more at any job in a week).

Table 1.

Descriptive Statistics of Outcomes and Covariates.

	(1)Full Sample		(2)Arrested	(3)Convicted	(4)Incarcerated
Variable	Mean	SD	Mean	Mean	Mean
Mental Health (Range: 1–4)	1.89	(.49)	2.08***	2.07***	2.09***
Arrest	.05	(.21)
Conviction	.03	(.16)
Incarceration	.01	(.12)
Age (Range: 17–33)	24.64	(4.10)	23.64***	24.18***	23.94
Delinquency (Range: 0–6)	.22	(.66)	.89***	.89***	1.16***
Poverty	.22	(.41)	.33***	.33***	.41***
Urban	.78	(.41)	.77	.77	.75*
South	.40	(.49)	.44***	.41	.43⁺
Education	13.01	(2.49)	11.47***	11.41***	10.96***
Smoking	.42	(.49)	.73***	.74***	.74***
Alcohol Use	.07	(.26)	.12***	.11***	.10**
Substance Use	.05	(.21)	.19***	.21***	.23***
Married	.24	(.43)	.09***	.08***	.09***
Employed	.65	(.48)	.64	.66	.68**
N (Person-Years)	39,320		1,820	1,147	774

Note: Variables are dummy-coded, unless the range is specifically mentioned. Significant values are results of t-tests comparing differences in means across groups with and without the indicated level of justice system contact. Values of 1 on the mental health scale indicate reports of feeling symptoms none of the time; values of 4 indicate reports of symptoms all of the time.

⁺ p < .10; *p < .05; **p < .01; ***p < .001.

Analytic Strategy

To test age-graded hypotheses, the analytic design follows the logic and strategy of moderation analysis, a method used to examine whether a third variable alters the directionality and/or magnitude of the association between an independent and dependent variable (e.g., Baron and Kenny 1986; Holmbeck 1997). As stated simply by Frazier and colleagues, “a moderator effect is nothing more than an interaction whereby the effect of one variable depends on the level of another” (Frazier et al. 2004, p. 116). In this analysis, the question is whether the “effect” of justice system involvement for mental health depends on the level of the respondent’s age at the time of involvement. Figure 1 visualizes the application of this framework to this analysis. Pathway A captures the ‘main effect’ between justice system contact and mental health, or the relationship often reported in studies estimating average effects across all ages. Pathway B reflects the impact of age on mental health. Of most interest to age-graded hypotheses, Pathway C is the focal relationship that indicates if the age of justice system contact affects mental health.

The analysis is carried out in two stages. The first step tests whether moderation exists between the independent and dependent variables, ascertained through the significance of the interaction pathway (C, Figure 1) in regression models. I estimate multivariable individual fixed effect linear regression models that include main effects for the independent variable (arrest, conviction, or incarceration), the potential moderator (age), an interaction term between the independent and the moderator variables (age of justice contact), and time-varying covariates. For all justice contacts during the analytic period, these models simultaneously estimate three associations: the ‘main effect’ of mental health following a recent justice system contact (e.g., within-individual change in the independent variable; Pathway A Figure 1); the independent impact of age, the proposed moderator (Pathway B); and the interaction between justice contact and age of experience (Pathway C). Using a .05 threshold, the statistical significance of the interaction term provides evidence of linear moderation by indicating a conditional relationship between the independent and dependent variables whereby the main effect relationship differs in magnitude and/or slope across levels of the moderator (Baron and Kenny 1986).³ I estimate separate models to assess age moderation for each form of system contact.

While the first stage focuses on the significance of the interaction term as evidence of moderation, the second stage quantifies the degree of variation in significantly moderated associations using the magnitude and directionality of this coefficient. In this step, I compute average marginal effects (AME) from regression models estimated in Step 1 that indicate the mean impact of the linear predictor term (net of covariates and individual fixed effects) on the outcome variable, accounting for differences in relationship slope and/or direction detected by the interaction term. I calculate the AME of justice contact for mental health at all ages in the analytic sample, yielding 18 associations for each type of contact. Substantively, these values are the regression-predicted average change in mental health for persons recently (or currently, for some cases of incarceration) in contact with the justice system at the specified age. This method produces directly comparable values of the mental health consequences of system involvement specific to age of contact. Using this approach, comparisons of their significance, magnitude, and direction identifies the exact ages at which justice system contact is most consequential.

Characteristics of this two-step analytic design provide three new insights into the justice contact-mental health literature. First, the moderation framework can uniquely examine theoretically predicted age-graded heterogeneity because it can detect the conditional relationships posited by the timing principle and social stress process. In other words, this analytic design can more directly operationalize and test theoretically-predicted variation in how timing contours mental health repercussions than designs used in prior research. Second, these conditioned relationships can be further analyzed and directly compared to pinpoint the most (or least) consequentially timed justice system involvement(s) and answer questions about age-graded stress and mental health outcomes. Finally, I leverage a relatively wide range of ages of justice system contact (16–33) available in NLSY97 data to assess age variation spanning varied developmental phases—late adolescence, emerging adulthood, and adulthood.

Selection Bias

As noted in many reviews (Kirk and Wakefield 2018; Massoglia and Pridemore 2015; Wildeman and Muller 2012), there are several challenges in using observational data to identify the health (and other) consequences of justice system involvement. Inferential hurdles arise from the significant overlap in observable and unobservable risk factors between the treatment (arrest, conviction, or incarceration) and outcomes (levels of mental health) of interest. Any study seeking to isolate the impact of justice involvement on health-based outcomes requires extra attention to ensure relationships are not an artifact of selection bias or a conflation of pre-existing circumstances, especially because youth and adults alike tend to suffer from poor health and inconsistent access to care prior to entering the justice system (Barnert, Perry, and Morris 2016; Teplin et al. 2005; Wildeman and Muller 2012).

This analysis minimizes inferential threats from unobserved selection bias by estimating individual fixed effect regression models. Fixed effects difference out time-stable individual characteristics in longitudinal data applications by effectively using persons as their own controls over time to assess within-person change (Allison 2009). These models eliminate the influence of time-stable variables not captured in the NLSY97, such as factors in early childhood. To mitigate selection bias from observable factors, models include the aforementioned time-varying covariates that could also affect entry into the justice system and symptoms of mental health disorders. For example, the inclusion of the delinquency scale is intended to rule out the correlation between delinquent behaviors and mental health disorders (Huesmann et al. 2019; Jolliffee et al. 2019). Controls for substance use capture a problem commonly comorbid with mental health disorders among correctional populations (e.g., Teplin et al. 2005). I control for socioeconomic status using measures of education, employment, and poverty levels, as socioeconomic disadvantage is strongly associated with levels of health (Elo 2009; Link and Phelan 1995; Reiss 2013) and justice involvement (Pettit and Western 2004; Sampson 1986; Western 2006). Finally, variables for marital status and employment capture the stabilizing impact of these life transitions for mental health. While causality still remains elusive, this approach maximally leverages available data to minimize the impact of competing explanations.

Results

Table 1 provides descriptive statistics of all variables included in this analysis. Column 1 provides means and standard deviations for the full analytic sample, while Columns 2–4 provide group means and differences for persons ever arrested, convicted, and incarcerated and their non-contact peers. Arrested, convicted, and incarcerated individuals report significantly more average symptoms of depression and anxiety than those without those forms of involvement. Justice-involved persons also differ in numerous other observed ways: on average, they are slightly younger (with the exception of incarceration), engaged in more delinquent behavior, are more likely impoverished, have lower educational attainment, and are less healthy (more likely to smoke, use alcohol before school/work, and use illicit substances). While all justice-involved are significantly less likely to be married, a slightly but significantly higher proportion of individuals who have been incarcerated have full-time employment.

Moving beyond sample-wide comparisons, Figure 2 disaggregates total reported justice system involvement across age of experience by plotting the volume of contacts at each age in the analytic period. Table 2 provides the exact values of each bar in Figure 2. There is a substantial amount of institutional contact among NLSY97 youth. Unsurprisingly, arrest is the most frequently reported form of system involvement. Overall, the number of justice-involved respondents at each age provides the basis for the moderation analysis and investigation of age variation.

Table 2.

Mental Health at Age of Justice System Contact.

	(1) Arrest				(2) Conviction				(3) Incarceration
	Not Arrested		Arrested		Not Convicted		Convicted		Not Incarcerated		Incarcerated
Age	MentalHealth	N	MentalHealth	N	MentalHealth	N	MentalHealth	N	MentalHealth	N	MentalHealth	N
16	1.93	1,437	2.13***	98	1.94	1,497	2.14*	38	1.94	1,519	2.38	16
17	1.93	1,542	2.11*	98	1.94	1,597	2.22***	43	1.94	1,620	2.38**	20
18	1.92	2,996	2.09***	231	1.93	3,126	2.16***	101	1.93	3,176	2.23***	51
19	1.93	2,987	2.11***	226	1.94	3,084	2.15***	129	1.94	3,153	2.19***	60
20	1.94	4,120	2.10***	262	1.94	4,241	2.09***	141	1.95	4,326	2.12**	56
21	1.93	3,089	2.14***	181	1.93	3,170	2.17***	100	1.94	3,216	2.19***	54
22	1.92	4,030	2.06***	215	1.92	4,121	2.07**	124	1.93	4,180	2.05⁺	65
23	1.87	3,059	2.10***	164	1.87	3,111	2.12***	112	1.87	3,166	2.15***	57
24	1.89	4,001	2.05***	189	1.89	4,063	2.00*	127	1.89	4,124	2.06**	65
25	1.88	3,038	2.13***	139	1.89	3,084	2.12***	93	1.89	3,128	2.16***	49
26	1.87	3,970	2.06***	175	1.88	4,041	2.04***	104	1.88	4,089	2.07*	56
27	1.87	2,820	2.12***	119	1.88	2,862	2.05**	77	1.88	2,897	1.99	42
28	1.88	2,667	2.03**	88	1.88	2,699	1.99	56	1.88	2,728	1.93	27
29	1.83	2,606	1.93*	110	1.83	2,632	1.90	84	1.83	2,664	1.93	52
30	1.85	2,426	1.95⁺	84	1.85	2,443	1.89	67	1.85	2,468	1.89	42
31	1.82	1,290	2.07***	53	1.83	1,301	1.94	42	1.83	1,318	1.87	25
32	1.81	1,269	2.07***	46	1.81	1,279	2.10***	36	1.81	1,301	1.97	14
33	1.81	1,090	2.03**	36	1.81	1,095	2.02*	31	1.81	1,106	1.97	20

Note: Mental health is the average reported symptoms for justice-involved respondents; significance indicates whether this value differs from non-justice-involved respondents.

⁺ p < .10, ^* p < .05, ^** p < .01, ^*** p < .001.

Table 2 provides preliminary insight into differences in the mental health of these justice-involved respondents by tabulating age-specific means of mental health across subgroups of forms of contact. Recently arrested individuals (Column 1) report significantly more symptoms of depression and anxiety than their same-age peers without a recent arrest at nearly all examined ages. Persons formally convicted of crimes in late adolescence and parts of early adulthood (Column 2) report significantly worse mental health than their same-age counterparts without a conviction, but these differences mostly taper off by age 26. There is a similar pattern for conviction and incarceration: average symptoms of depression and anxiety are significantly higher for those reporting any conviction or confinement during late adolescence or emerging adulthood, but there are no detectable differences for persons 27 or older. Overall, mental health differences across age of contact appear most pervasive for arrested persons, whereas differences for convicted and incarcerated persons are limited to earlier-timed contacts.

Determining Age Moderation

Applying a moderation analysis framework, I now investigate whether these differences in mental health persist in a more robust specification of linear regression models with individual fixed effects and controls for time-varying covariates. Regression results reported in Table 3 tackle the first step of assessing age-based moderation in the justice contact and mental health association by investigating the significance of the independent variable/moderator interaction (e.g., Figure 1, Pathway C).

Table 3.

Regression Models with Individual Fixed Effect: Mental Health Following Justice System Contact.

	(1)Arrest	(2)Conviction	(3)Incarceration
Variable	β (SE)	β (SE)	β (SE)
Arrest	.08 (.06)	.09*** (.01)	.09*** (.01)
Conviction		.12 (.08)
Incarceration			.27* (.11)
Age	−.01*** (.00)	−.01*** (.00)	−.01*** (.00)
Interaction	.00 (.00)	−.00 (.00)	−.01* (.00)
Delinquency	.04*** (.01)	.04*** (.01)	.04*** (.01)
Poverty	−.00 (.01)	−.00 (.01)	−.00 (.01)
Urban	.01 (.01)	.01 (.01)	.01 (.01)
South	.01 (.01)	.01 (.01)	.01 (.01)
Education	−.00 (.00)	−.00 (.00)	−.00 (.00)
Alcohol Use	.06*** (.01)	.06*** (.01)	.06*** (.01)
Substance Use	.09*** (.01)	.09*** (.01)	.09*** (.01)
Smoking	.07*** (.01)	.07*** (.01)	.07*** (.01)
Married	−.02** (.01)	−.02** (.01)	−.02** (.01)
Employed	−.02** (.01)	−.02** (.01)	−.02** (.01)
Constant	2.04*** (.02)	2.04*** (.02)	2.04*** (.02)
N (Person-Years)	7,598(39,320)	7,594(39,167)	7,594(39,168)

Note: Fixed effects model preferred over random effects model (Hausman test; p = .0000). Models estimated with 25 chained imputations.

⁺ p < .10, ^* p < .05, ^** p < .01, ^*** p < .001.

Starting with arrest (Table 3, Column 1), model results do not detect a significant main effect association nor a moderated association between arrest and mental health. The relationship between the independent and dependent variable—that is, the coefficient for arrest—points in the expected direction, as a positive directionality indicates increased reported symptoms of depression and anxiety. Contrary to expectations from descriptive differences in means, this main effect association is not statistically significant. Further, the interaction term testing moderation fails to meet the significance threshold for evidence of moderation. Thus, for arrest, I do not find evidence that mental health responses are conditioned by the age at which individuals are arrested—in other words, the arrest-mental health relationship does not appear to be age-graded in nature and is consistent across age of experience.

The estimated association between conviction and mental health is displayed in Column 2. As was the case with arrest, the main effect relationship is positive but not statistically significant (p = .109). Further, the lack of significance of the interaction term (p = .130) does not provide evidence of age-based moderation. Despite observing differences in means in t-test results (Table 2), results here suggest that they do not persist in a more robust specification. Apparent age variation in the conviction-mental health response does not persist after accounting for competing explanations, both observed and unobserved. Interestingly, the included control for arrest is positive and highly significant in this model, unlike in the arrest-only model (Column 1).

Finally, with respect to incarceration (Column 3), regression estimates detect a significant and sizable main effect between incarceration and mental health. This coefficient is positive and significant (p < .05), indicating that recently spending time in carceral facilities is related to declines in mental health net of observed covariates, individual fixed effects, and being arrested. There is evidence of moderation in this model: the statistical significance of the interaction term (p = .020) signals that the main effect relationship between incarceration and mental health is indeed conditioned by the age at which individuals report confinement. Because this specification controls for recent arrest, this result points to the salience of spending time in carceral spaces for mental health conditioned by the timing of the experience.

Comparing Age-Specific Associations between Incarceration and Mental Health

The second analytic step delves deeper into the significantly moderated association between incarceration and mental health to quantify how the age at which individuals are incarcerated differentially affects symptoms of depression and anxiety. To accomplish this, I calculate AME of justice system contact at ages 16–33 from regression model results estimated and presented in Table 3. These values capture the age-specific linear predictor of the outcome, given that the first step of moderation analysis revealed that these relationships are heterogenous across the ages at which they transpire. The substantive interpretation of AME is the total combined predicted impact of incarceration, age, and age of incarceration—net of included covariates and individual fixed effects—for mental health.

Table 4 presents age-specific AME values that are visualized and plotted in Figure 3. The pattern of statistical significance paired with the directionality of AME values indicates an age-graded pattern in the impact of incarceration for mental health. More specifically, confinement earlier in the life course—at ages 16, 17, 18, 19, 20, 21, and 22 (and marginally at 23)—is correlated with significant increases in the number of reported symptoms of depression and anxiety⁴. AME values indicate that these earlier incarcerations are associated with a predicted average rise in disorder symptoms ranging from .05 to .10, which translates to an increase of one-quarter to one-half on the MHI-5 scale in self-reported symptoms within the past month. Importantly, these earlier timed incarcerations are the exclusive points at which there is a statistically significant association. Declines to mental health observed following confinement during late adolescence and the first half of emerging adulthood are not observed following incarceration at age 24 or older. In other words, there is no discernable impact of incarceration for individuals’ mental health at ages 24 or older. These results indicate that the general main effect of incarceration and mental health observed in Table 3 is driven exclusively by experiences of confinement during late adolescence and emerging adulthood.

Table 4.

Age-Specific Average Marginal Effects of the Impact of Incarceration for Mental Health.

Age of Contact	Average MarginalEffect (SE)
16	.11** (.04)
17	.10* (.04)
18	.09* (.04)
19	.08* (.03)
20	.07* (.03)
21	.06* (.03)
22	.05* (.02)
23	.04+ (.02)
24	.03 (.02)
25	.02 (.02)
26	.01 (.02)
27	.00 (.03)
28	−.01 (.03)
29	−.02 (.03)
30	−.03 (.03)
31	−.05 (.04)
32	−.06 (.04)
33	−.07 (.04)
Observations (Person-Years)	7,594 (39,168)

Note: Values estimated from regression models specified and displayed in Table 3 using 25 chained imputations.

⁺ p < .10, ^* p < .05, ^** p < .01, ^*** p < .001.

Discussion

Research on the non-criminogenic outcomes of involvement with the justice system is robust with respect to estimating averaged effects, but is limited in the extent to which it generates knowledge on variation in impacts across the entirety of the justice-involved population (e.g., Kirk and Wakefield 2018). Informed by an integration of the social stress perspective and the life course paradigm (e.g., Pearlin and Skaff 1996), this paper advances existing scholarship on age variation by leveraging the logic of moderation analysis to test hypotheses of an age-graded impact of justice contact for mental health—specifically, of amplified harm for contacts occurring during late adolescence and emerging adulthood. The analysis detected, estimated, and compared quantitative differences in the justice contact-mental health association across ages of experience, finding results that were both consistent and inconsistent with hypotheses. Considering the age of system contact provided new insight into the mental health consequences of incarceration, but not arrest nor conviction. This section discusses these two takeaways and their contribution to understanding the heterogeneous impacts of justice system involvement for mental health.

Age-Graded Impact of Incarceration

Prior studies find evidence suggestive of pronounced mental health harms following earlier incarcerations (Baćak et al. 2019; Barnert et al. 2018; Boen 2020), but fall short of fully identifying the salience of early contact by not comparing them to outcomes following contacts in adulthood. Results of this analysis extend understanding in this key area by demonstrating age as a moderating variable, whereby the incarceration-mental health relationship varies in significance and magnitude across ages of confinement experience. There is a substantive and statistical significance of incarceration during late adolescence and emerging adulthood that materializes net of controls for recent arrests. Because this significance does not emerge for incarceration at age 24 or older, this finding suggests an age-graded correlation between incarceration and mental health that is masked in prior research estimating average effects. Since these models control for arrest, this negative impact of incarceration largely reflects the unique adversity associated with serving a custodial sentence at younger ages. In this way, this finding aligns with other studies finding that incarceration affects health outcomes above and beyond interactions with law enforcement (e.g., Boen 2020).

Consistent with predictions from the life course perspective and social stress process, this concentrated impact underscores the stressful and disruptive nature of carceral confinement at younger ages and during the vital developmental phases of late adolescence and emerging adulthood. While an exploration of the mechanisms of this association is not possible with measures available in NLSY97 data, the directionality of results suggests that young people serving time in carceral spaces experience an amplification of primary stressors inherent in these environments, which can include isolation, material deprivation, social interactions with correctional staff, and victimization fears (Haney 2003; Massoglia 2008; Porter 2019). These negative stimuli likely transcend incarceration at all ages, but may produce heightened adverse reactions for adolescents and young adults who have been removed from positive family milieus, schools, and other social supports. Further, prisons generally lack sufficient resources to respond to the mental health needs of those incarcerated there—even when services are mandated (Ashkar and Kenny 2008; Swank and Gagnon 2017; Teplin et al. 2005). A lack of sufficient care for ongoing or emergent symptoms of mental illness may exacerbate the salience of incarceration-initiated stressors, amplifying their total impact for mental health (Haney 2003; Lambie and Randell 2013).

Because of the breadth of experiences captured in the incarceration measure, it is possible that some of this damage transpires following confinement in juvenile justice facilities operating within the scope of an institution purported to use developmentally-informed practice to improve youths’ outcomes (Sullivan, Piquero, and Cullen 2012). However, youth correctional facilities typically fail to deliver upon goals of corrective treatment and skills training, leaving released youth without the tools necessary to remain out of institutions (Cox 2018; Fader 2013). Together, an enhanced immediate stress response to carceral environment exposure during this pivotal point in the life course is likely worsened due to removal from physical homes, reduced access to social support networks, and a lack of coping supports. This process, unique to these transitional phases, likely plays some role in the observed concentrated significance of earlier incarceration. Specifying the exact mechanisms of primary stress of late adolescent and emerging adulthood confinement, especially for how they compound with concurrent stressors embedded in these developmental phases, is an important topic for future research. Additionally, there is a broad need for studying how the distinct carceral contexts assessed here—jail, juvenile, adult, and training school—may proliferate distinct mechanisms of stress that can adversely affect mental health through unique pathways.

Importantly, established processes of cumulative disadvantage unfolding from incarceration during late adolescence and early adulthood (e.g., Kurlychek and Johnson 2019; Sampson and Laub 1997) may be accelerated by these adverse mental health consequences. In one way, the initial stressor of incarceration can proliferate secondary stressors, like stigma, that strongly correlate with long-term damages to mental health (Liberman, Kirk, and Kim 2014; Link et al. 1997). Less directly, worsened mental health may be sustained through associated impediments to adult status transitions believed to account for declining symptoms of depression in adulthood, like marriage (Adkins et al. 2009; Paul and Moser 2009; Schieman, Van Gundy, and Taylor 2001). Through such pathways, observed harms to mental health following early confinement may proliferate additional adversities that compound with established pathways of cumulative disadvantage throughout the life course (e.g., Sampson and Laub 1997). Put simply, there are ample reasons to expect that the “piling up” of disadvantages initiated by justice system contact (e.g., Kurlychek and Johnson 2019) is made worse by these deleterious impacts for mental health. Because this analysis does not investigate long-term consequences, open questions remain regarding the durability of these observed associations and their exact contribution to processes of cumulative disadvantage.

Finally, it was surprising that the expected significant and negative association between incarceration and mental health did not materialize across all ages. The significant main effect of incarceration detected (Table 3) is driven entirely by confinement earlier in the life course and does not persist beyond age 23. Thus, the salience of incarceration for symptoms of mental health disorders is not only magnified for late adolescent and emerging adulthood confinement—it is isolated to late adolescent and emerging adulthood confinement. These results do not conform to expectations of a universal harm that is amplified for earlier contacts, but rather suggest an exclusivity of harm for earlier contacts. This lack of significance for incarceration later in the life course may be obscured in models estimating averaged associations and indicates a topic for additional studies to continue to specify the incarceration-mental health relationship.

Consistency in the Impact of Arrest

Contrary to expectations, results indicated that the associations between arrest, conviction, and mental health were not moderated by the age of experience. Interestingly, models testing moderation did not detect a significant main effect association for arrest, a finding divergent from descriptive differences in subgroup means (Table 2) and from other studies (e.g., Fernandes 2020; Sugie and Turney 2017). To investigate, I conducted exploratory analyses of the AME of the age-specific impact of arrest that are plotted in Figure 4 and displayed in online Table 1A. There is a pervasive significant and negative impact of being arrested for mental health at all examined ages. This pattern indicates universal harm to mental health following recent arrest, as the directionality and significance of this relationship is consistent at all ages and across life stages of experience. The magnitude is strikingly similar across ages, ranging from .09 (Age 16) to .10 (Age 33) and indicating a quantitatively similar impact of arrest on reported symptoms of depression and anxiety.

These exploratory analyses demonstrate an invariant impact of being arrested for mental health across the life course through the minimal detected variation across ages. In other words, being arrested is deleterious to mental health at all ages, and considering the age of arrest provides little additional information. This universal harm is nonetheless concerning, given that arrest is very common experience: approximately 25–40 percent of Americans have been arrested at least once by age 23 (Brame et al. 2012), with estimated rates increasing to nearly 50 percent for young Black men (Brame et al. 2014). Because low-level justice contacts can quickly accrue throughout the life course, they may carry consequences for aggregate levels of mental health and other collateral consequences (i.e., Turney and Wakefield 2019). While this analysis did not find a heterogeneous impact, it is nonetheless important to continue to identify the impact of arrest and other non-carceral and commonly experienced justice system contacts for mental health.

The lack of detected moderation may mean that there is no quantitative difference in arrest’s mental health impact across ages, but does not necessarily mean that the mechanisms conferring this harm are the same. It is likely that the underlying response to arrest contouring the stress process is developmentally contextualized. Young people may be especially susceptible to arrest-induced stressors when the event itself involves certain characteristics. For example, youths’ interactions with law enforcement can be more stigmatizing when occurring at school and other public spaces where others can readily witness the event and label the youth (Jackson et al. 2019; Jackson et al. 2020). Further, youth and adolescents may be more greatly affected by interactions with law enforcement perceived as more invasive, procedurally unjust, or that involve force (Geller et al. 2014; Geller et al. 2017; McFarland et al. 2019; Turney 2020). These perceptions may phase out and be replaced by other stressors related to factors unique in adulthood, like employer stigma for those with formal records (e.g., Pager 2003). Because these data utilized here lack sufficient information to tease out these proposed differences, the explication of the arrest-mental health stress response across life stages remains an unresolved area to be addressed in future studies.

Limitations

The use of fixed effect models precludes estimating coefficients for time-stable individual characteristics in NLSY97 data, like race, ethnicity, or sex. These sociodemographic variables are important to explore in future research, as existing scholarship indicates that justice system contact is especially impactful for the mental health of racial and ethnic minority persons (Asad and Clair 2018) and women (van der Molen et al. 2013) and that Black youth are overrepresented in juvenile correctional facilities (Sentencing Project 2016). The survey data and study design limit the analytic scope to late ages in adolescence; the inclusion of younger teenage years in future analyses may strengthen conclusions regarding the impact of early confinement for mental health.

Commonly utilized in studies of collateral consequences, individual fixed effect models are advantageous for estimating outcomes of nonrandomly distributed “treatment” experiences (i.e., incarceration) using observational data. They are, however, not without limitations. For example, there is a possibility of reverse causality where mental health declines may precede justice contact (e.g., Hill et al. 2020). Although the NLSY97 survey does not include a pre-treatment measure of the MHI-5 to directly assess causal ordering, I am reasonably confident that these models are not susceptible to reverse causality because reports of system contact reference the period since the last survey interview (12–18 months) and reports of mental health symptoms reflect experiences within the past month. The reference windows of these survey questions suggest that justice contact precedes mental health for many individuals in the analytic sample, but I cannot definitively rule out the reverse possibility. Estimates from individual fixed effect models are also susceptible to Type II errors (e.g., failing to reject a false null hypothesis) and assume a consistent impact of unobserved variables (Hill et al. 2020), the latter of which may be challenged for measures like impulsivity (Burt, Simons, and Simons 2006; Na and Paternoster 2012).

Conclusion

This paper finds evidence that incarceration is an age-graded social stressor, with adverse consequences for mental health concentrated among experiences of confinement in late adolescence and emerging adulthood. Arrests do not have an age-graded impact on mental health, as they are correlated with universal harm across all observed ages. These findings point to the uniquely harmful consequences of early incarceration and support continued investigation of heterogeneity in collateral consequences driven by differential timing in the age of justice involvement. To build on this study, future research is needed to identify the unique stress process generated by carceral confinement during these pivotal developmental phases, explain observed harm exclusivity to these ages and life stages, and understand any long-term processes of secondary stress and cumulative disadvantage.

Supplemental Material

Supplemental Material, sj-docx-1-jrc-10.1177_00224278211023988 - The Age-Graded Consequences of Justice System Involvement for Mental Health

Supplemental Material, sj-docx-1-jrc-10.1177_00224278211023988 for The Age-Graded Consequences of Justice System Involvement for Mental Health by Kathleen Powell in Journal of Research in Crime and Delinquency

Supplemental Material

Supplemental Material, sj-pdf-1-jrc-10.1177_00224278211023988 - The Age-Graded Consequences of Justice System Involvement for Mental Health

Supplemental Material, sj-pdf-1-jrc-10.1177_00224278211023988 for The Age-Graded Consequences of Justice System Involvement for Mental Health by Kathleen Powell in Journal of Research in Crime and Delinquency

Supplemental Material

Supplemental Material, sj-pdf-2-jrc-10.1177_00224278211023988 - The Age-Graded Consequences of Justice System Involvement for Mental Health

Supplemental Material, sj-pdf-2-jrc-10.1177_00224278211023988 for The Age-Graded Consequences of Justice System Involvement for Mental Health by Kathleen Powell in Journal of Research in Crime and Delinquency

Footnotes

Acknowledgments

I would like to thank Sara Wakefield, Bob Apel, Valerio Baćak, Chris Wildeman, Jordan Hyatt, and Nate Link for providing feedback on earlier versions of this paper. I am also grateful to Dr. Jean McGloin and the three anonymous reviewers whose comments considerably enhanced this manuscript.

Declaration of Conflicting Interests

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

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Kathleen Powell

Supplemental Material

Supplemental material for this article is available online.

Notes

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