Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2026 Feb 19.
Published in final edited form as: Deviant Behav. 2019 Sep 25;42(3):297–312. doi: 10.1080/01639625.2019.1666610

Teen Pregnancy, Depression, and Substance Abuse: The Conditioning Effect of Deviant Peers

D’Andre Walker a, Kristy Holtfreter b
PMCID: PMC12915692  NIHMSID: NIHMS2144029  PMID: 41717310

Abstract

General Strain Theory (GST) suggests that individuals who experience strain are pressured into criminal and deviant behavior. Consistent with GST, the current study assesses the relationship between strain in the form of teenage pregnancy and substance use behavior, specifically alcohol problems and marijuana use. In addition, deviant peer association is a robust predictor of criminal behavior, therefore, we also investigate the role of deviant peers in the coping process among females who experience teenage pregnancy. Data for the analysis were obtained from Waves I and II of the National Longitudinal Study of Adolescents to Adult Health (Add Health). In a sample of 5,236 adolescent females drawn from Waves I and II, results show that teenage pregnancy is a significant predictor of depression and substance use involvement. Furthermore, a 3-way-interaction effect was observed, specifically teenage pregnancy, association with deviant peers, and depression was a significant predictor of substance use behaviors. Implications for theory, research, and social programs for teen parents are discussed.

Introduction

While the rate of teen pregnancy has declined in recent decades, it remains high in the United States relative to other developed countries (McDonnell, Limber, and Connor-Godbey 2007). The 2014 birth rate was 24.2 per 1,000 females aged 15–19 (Hamilton et al. 2015). The negative consequences of teenage pregnancy as a significant social and public health problem are widely recognized. Teenage mothers often have their educational journeys truncated, and their children tend to under-perform in school and exhibit problem behaviors (Letourneau, Stewart, and Barnfather 2004). Young mothers are more likely to live in poverty and rely on public assistance (Borkowski et al. 2016). Data from the National Campaign to Prevent Teen and Unplanned Pregnancy show that teenage pregnancy and childbearing cost American taxpayers nearly $9.4 billion in 2010 alone (Shuger 2012). While the economic and societal costs of teen pregnancy are well documented, less is known about the ways teens themselves cope with the strains of pregnancy. Evidence suggests that early use of substances is a precursor to teen pregnancy, and that adolescent mothers are at heightened risk for substance abuse in the post-partum period (Chapman and Wu 2013). Reducing substance abuse and teen pregnancy are both goals of Healthy People 2020 (United States Department of Health and Human Services 2016).

Several studies have explored links between teen pregnancy, substance abuse, and negative outcomes such as delinquency (Barnet et al. 1995; Cavazos-Rehg et al. 2012; DeGenna, Cornelius, and Donovan 2009; Hope et al. 2003; Salas-Wright et al. 2015). Apart from recognizing these relationships as consistent with problem behavior theory (Jessor 1987), little research relies on theory. A theoretically informed understanding of teen pregnancy can better inform public health interventions, especially with regard to its negative consequences (Blue et al. 2016). Toward that end, Agnew’s (1992, 2006) General Strain Theory (GST), a social-psychological perspective that has been extensively tested in criminology, offers some useful direction. Specifically, the current study conceptualizes teen pregnancy as a strain.

According to Agnew’s (1992) GST, strains and stressors – like teen pregnancy – increase negative emotions (e.g., anger, depression and frustration), and, in turn, maladaptive coping (e.g., delinquency and substance use). A main assumption of GST is that individuals are “pressured” into crime (Agnew 2006). Past research exploring the relationship between teenage pregnancy and delinquency revealed that those who become pregnant during adolescence have higher levels of involvement in delinquency than never pregnant teenagers (Hope et al. 2003). However, one limitation of previous studies is the use of a general delinquency measure as the primary dependent variable, resulting in a failure to examine involvement in specific maladaptive coping behaviors, such as substance use. Also, past research has not thoroughly investigated the role of negative emotionality or the conditioning impact that deviant peers may have in explaining the links between teen pregnancy and delinquency. There is a robust relationship between deviant peers and deviant behavior (Hoeben et al. 2016). A relationship between deviant peers and substance use has also been established (Fergusson, Swain-Campbell, and Horwood 2002). However, in the context of GST, less is known about the role of deviant peers in the coping process; specifically, whether deviant peers moderate the relationship between strain and maladaptive behaviors. In sum, there are gaps in the literature on teenage pregnancy and maladaptive coping. Using data from the National Longitudinal Study of Adolescent to Adult Health (Add Health), the current study relies on GST to address this void by investigating the relationship between teenage pregnancy and maladaptive coping. Drawing from Agnew’s (1992, 2006) theoretical framework, it is anticipated that teenage pregnancy will contribute to depression and create pressure for corrective action, in the form of substance use, deviant peers will moderate the relationship between teenage pregnancy and maladaptive outcomes, and those who experience teenage pregnancy, depression, and associate with deviant peers will be more likely to engage in substance use behaviors.

Literature review

According to GST, experiencing strain – or stress – increases negative emotional states (e.g., anger, depression and frustration), creating pressure for coping. Strains refer to events or conditions that are disliked. Agnew (1992) describes three sources of strain: (1) the failure to achieve positively valued goals (e.g., not graduating from high school or receiving bad grades); (2) the removal of positive stimuli (e.g., death of a close family member or friend); and (3) the presentation of negative stimuli (e.g., criminal victimization or discrimination). Indeed, teenage pregnancy may hinder achievement of goals, such as high school graduation (Weimann et al. 2005). Pregnant teens may experience removal of positive stimuli, such as diminished relationships with friends and family. Weimann et al. (2005) found that the majority of females who became pregnant in adolescence reported feeling stigmatized. In addition, they were at an increased risk for social isolation and abuse. Pregnancy may result in stigmatization, forcing teens to associate with deviant peers (e.g., through rejection by prosocial peers or limited access to prosocial others due to dropping out of school). The adoption of deviant peers leads to negative consequences like delinquency and substance use (Fergusson, Swain-Campbell, and Horwood 2002; Hoeben et al. 2016). The final source of strain, presentation of negative stimuli, is also apparent for pregnant teens. This may include challenges of caring for an infant, and past victimization experiences (Garwood et al. 2016; Roosa et al. 1997).

Agnew (2001) argues that strains are most conducive to crime when they are seen as unjust, high in magnitude, associated with low social control, and create pressure or stimulus to engage in criminal coping. Individuals may turn to crime as a method to reduce strain (e.g., stealing money that is desired), seek revenge, or alleviate negative emotions (e.g., through illicit drug use). GST suggests that there are multiple variables that influence or condition the effect of strain on crime, specifically coping skills and resources, social support, social control, and deviant peer association. Empirical assessments of various conditioning effects in tests of GST have produced mixed results (Agnew 2006, 2013). Agnew (2013) argues that scholars have neglected to focus on key conditioning variables, such as criminal propensity and gang membership. Thaxton and Agnew’s (2018) study attempted to address this void in literature. They found that delinquent involvement was more prevalent among individuals with a strong propensity for criminal coping, and among gang members.

There are two types of strains: objective and subjective (Agnew 2002). Agnew (2001: 320) describes objective strains as “events or conditions that are disliked by most members of a given group,” while subjective strains pertain to events or conditions that are disliked by individuals who are experiencing or have experienced them. Most empirical research examining the strain-crime relationship focuses on objective strains, like victimization (Golladay and Holtfreter 2017; Hay and Meldrum 2010; Turanovic, Travis, and Pratt 2013). When it comes to crime, Froggio and Agnew (2007) found that subjective strains are more strongly associated with breaking the law than objective strains. Teenage pregnancy reflects a subjective strain as reaction to the event may be based on personal perspectives, feelings, or opinions.

A key proposition of GST is that strain and stressors lead to negative emotions, such as anger, depression, and frustration. GST literature suggests that females are likely to respond to strain with anger, however, their anger is likely to co-occur with other negative emotions such as depression, guilt, anxiety and shame (Agnew 2006; Broidy and Agnew 1997; Daniels and Holtfreter 2019). Depression and guilt may cause females to blame themselves, consequently resulting in self-destructive deviance such as eating disorders and substance use behavior (Agnew 2006). Consistent with GST, some studies have found a link between teen pregnancy and depression (Hall, Richards, and Harris 2017; Mollborn and Morningstar 2009; Whitworth 2017). Although females who become pregnant during adolescence are likely to experience depression, what matters most according to GST is the ways in which they cope with this event.

While some individuals cope with stress in healthy ways, such as seeking the support of prosocial family members, others do so maladaptively (Holtfreter, Reisig, and O’Neal 2015; Reisig, Holtfreter, and Turanovic 2018). Agnew (2006) identifies several forms of maladaptive coping, including delinquency and substance abuse. Most GST studies have explored the relationship between strain and traditional delinquent behavior outcomes (Agnew 2001; Agnew et al. 2002; Broidy 2001; Hay and Evans 2006; Moon, Blurton, and McCluskey 2008), while seldomly investigating the link between strain and substance use (Hoffmann and Su 1997; Peck et al. 2017). This shortcoming is problematic as GST literature suggests that there are gender differences in coping with strain. Studies show that females are likely to respond to strain and negative emotions (e.g., depression) with externalizing behaviors, such as overeating and substance use (Broidy and Agnew 1997; Peck et al. 2017). Regarding research on teenage pregnancy and parenthood, Hope et al. (2003) found that those who become pregnant during adolescence had higher levels of involvement in delinquency. However, this study used a general delinquency outcome, preventing examination of specific maladaptive behaviors, such as substance use. Walker and Holtfreter (2016) found that adolescent motherhood was negatively associated with delinquency, which they attributed to restricted opportunity. There has also been empirical evidence suggesting that motherhood is a turning point. For example, motherhood is shown to have a suppression effect on delinquency, substance use, gang membership, and criminal offending (see Hope et al. 2003; Kreager, Matsueda, and Erosheva 2010; Pyrooz, McGloin, and Decker 2017). Most studies examining the link between strain and maladaptive coping exclude the role of deviant peers.

Deviant peer association is linked to increased involvement in delinquency (Fergusson, Swain-Campbell, and Horwood 2002), alcohol use (Barnes et al. 2006), substance use (Simons-Morton et al. 2001), and risky sexual behavior (French and Dishion 2003; Miller 2002). Less is known about the moderating effect of deviant peers on the strain and delinquency relationship. GST suggests that deviant peers promote criminal and deviant behavior among those who experience strain by (1) supplying a form of support for maladaptive behavior, (2) considering certain acts as an appropriate response to strain, and (3) serving as instigators. Agnew (1992, 2006) argues that those with deviant peers are more likely to have access to deviant coping strategies and view deviance as an attractive or appropriate response to stressful situations. While literature suggests that deviant peers are influential in the coping process, there is a lack of empirical research assessing whether deviant peers increase the effect of strain on negative emotions, and whether deviant peers elevate the effect of negative emotions on maladaptive coping. Individuals who experience strain, negative emotions, and associate with deviant peers may be more likely to cope in a maladaptive manner. While prior research has contributed to understanding the consequences of teenage pregnancy, it has been limited in three important ways: (1) the use of a general measure of delinquency; (2) a focus on offending as the sole maladaptive coping outcome; and (3) the failure to consider the potential moderating role of deviant peers.

Current focus

This study uses data from the National Longitudinal Survey of Adolescent to Adult Health (Add Health) to assess whether becoming pregnant as a teenager influences maladaptive coping in the form of alcohol problems and marijuana use. Guided by GST, the analyses test the following direct, mediating, and moderating hypotheses:

H1. Teenage pregnancy will be a significant predictor of depression.

H2. Females who experience teenage pregnancy and associate with deviant peers will be likely to experience depression.

H3. Teenage pregnancy will be positively associated with substance use behaviors.

H4. Depression will mediate the relationship between teenage pregnancy and substance use behaviors.

H5. Females who experience teenage pregnancy and associate with deviant peers will be at an increased risk for engaging in substance use behaviors.

H6. The interactive effect of teenage pregnancy, association with deviant peers, and depression will be a significant predictor of substance use behaviors.

Data and methods

The current study uses data from Waves I and II of the National Longitudinal Study of Adolescent to Adult Health (Add Health). Add Health is a nationally representative, school-based sample of approximately 20,000 adolescents in the United States who were in grades 7 through 12 between September 1994 and December 1995. The initial sampling frame consisted of 26,666 schools which were stratified by level of urbanization, school type, school size, ethnicity, and census region. Participating high schools were requested to identify feeder schools, which are schools that included a 7th grade and sent a minimum of five students to that particular high school. The top feeder school for each high school was selected for participation in the study. If the feeder school declined to participate in the study, a replacement school was selected. Recruitment efforts yielded a total of 132 schools for the core study, 80 of which were high schools and 52 were middle schools. Students attending the participating schools were eligible to take part in an in-school questionnaire, in-home survey, and in-home interview. Information obtained from these sources includes the respondent’s social and demographic characteristics, education and occupation of parents, household structure, risky behaviors, criminal activities, substance use, sexual history, employment history, health status, and self-esteem.

In addition to baseline measures at wave I, behavioral measures from wave II were used to investigate the relationship between teenage pregnancy and substance use involvement. Wave II data collection was conducted in 1996 consisting of follow-up in-home interviews with young adults and follow-up school administrator interview. There were nearly 15,000 adolescents surveyed in Wave I who were also surveyed in Wave II. Because the main focus is on adolescents and teenage pregnancy, the sample was limited to those participants aged 17 years and younger. After excluding cases of respondents who identified as males, and cases where there were missing data, the final sample size is 5,236 female respondents.

Dependent variables

The dependent variables are from wave II of the in-home survey. Following previous research (Turanovic 2015), alcohol problems was assessed using a 7-item summated scale asking respondents to report how often during the past 12 months: “you got into trouble with your parents because you had been drinking”, “you had problems at school or with work because you had been drinking”, “you had problems with your friends because you had been drinking”, “you had problems with someone you were dating because you had been drinking”, “you did something you later regretted because you had been drinking”, “you were hungover”, and “you were sick your stomach or threw up after drinking.” Items were coded as 0 = never, 1 = once, 2 = twice, 3 = three of four time, and 4 = five or more times. The items were summed to create the alcohol problems scale (mean = 1.08, SD = 2.58), which has a good level of internal consistency (α = 0.81).

During wave II data collection, marijuana use was assessed using a single item that asked respondents during the past 30 days, “how many times have you used marijuana?” The item was originally coded as a count variable (M = 1.09, SD = 5.14), with the majority of respondents reporting no marijuana use. Accordingly, to capture any marijuana use, the item was coded dichotomously (1 = yes, 0 = no). Approximately 14 percent (n = 746) of respondents reported using marijuana in the past 30 days.

Independent variables

The current study is primarily concerned with the event of becoming pregnant as a teenager rather than the outcome of the pregnancy. To measure strain, teenage pregnancy was captured by asking respondents “have you ever been pregnant?” A significant number of female adolescents became pregnant between waves I and II data collection. Therefore, to capture all who have experience teenage pregnancy, data for the variable was taken from waves 1 (42% or n = 111) and II (58% or n = 154) of data collection (n = 265). The pregnancy measure was combined into a single item for respondents reporting pregnancy at either wave I or wave II data collection (1 = yes, 0 = no). It is important to note that this subsample does not include females who were currently pregnant at wave II data collection.

Depression was operationalized as a 16-item summated scale consisting of measures adapted from the CES-D (Radloff 1977). Specifically, participants were asked during the past seven days how often: (1) “you were bothered by things that usually don’t bother you”; (2) “you didn’t feel like eating, or your appetite was poor”; (3) “you felt that you could not shake off the blues, even with help from your family and your friends”; (4) “you felt that you were just as good as other people”; (5) “you had trouble keeping your mind on what you were doing”; (6) “you felt depressed”; (7) “you felt hopeful about the future”; (8) “you thought your life had been a failure”; (9) “you felt fearful”; (10) “you were happy”; (11) “you talked less than usual”; (12) “you felt lonely”; (13) “people were unfriendly to you”; (14) “you enjoyed life”; (15) “you felt sad”; and (16) “you felt that people disliked you.” Responses to each question ranged from 0 (never or rarely) to 3 (most of time or all of the time). Items 4, 7, 10, and 14 were recoded so that higher values indicated greater levels of depression. A summated scale using the 16-items was constructed where higher values reflect greater levels of depression (α = 0.86).

Moderating variable

Deviant peer association is a 3-item additive scale using information from wave II. Respondents were asked of your three best friends, how many “smoke at least one cigarette a day”, “drink alcohol at least once a month”, and “use marijuana at least once a month” (0 = no friends, 1 = one friend, 2 = two friends, 3 = three friends). The items were averaged with greater values indicating higher levels of association with deviant peers (α = 0.77). This coding strategy is consistent with prior research (Tillyer and Rob Tillyer 2016).

Control variables

In an effort to guard against spuriousness, we control for a number of variables that have been empirically linked to teen pregnancy, substance abuse, and/or association with deviant peers. Low self-control is a 6-item summated scale using data from wave 1 (see McGloin and Shermer 2009). Respondents were asked, during the past week (1) “when you have a problem to solve, one of the first things you do is get as many facts about the problem as possible,” (2) “when you are attempting to find a solution to a problem, you usually try to think of as many different ways to approach the problem as possible,” (3) “when making decisions, you generally use a systematic method for judging comparing alternatives,” and (4) “after carrying out a solution to a problem, you usually try to analyze what went right and what went wrong” (1 = strongly agree, 2 = agree, 3 = neither agree nor disagree, 4 = disagree, 5 = strongly disagree). The last two items asked respondents during the past school year, how often have you had trouble “getting your homework done” (0 = never to 4 every day), and “paying attention in school” (0 = never to 4 = every day). Since the response sets varied between questions, the items were standardized prior to creating a summated scale, with higher values reflecting lower levels of self-control (α = 0.70).

Low self-esteem is assessed using 6-items from Rosenberg’s (1965) low self-esteem scale. Respondents were asked how much did they agree with the following statements: “you have a lot of good qualities,” “you have a lot to be proud of,” “you like yourself the way that you are,” “you feel like you are doing everything just about right,” “you feel socially accepted,” and “you feel loved and wanted.” Participants responded to the statements using a 5-point scale: strongly agree (1), agree (2), neither agree nor disagree (3), disagree (4), and strongly disagree (5). The items were then summed to create a low self-esteem index (α = 0.86).

Consistent with prior research (Wight, Botticello, and Aneshensel 2006), social support was measured using a 7-item index asking respondents how much they felt “that adults care about you,” “your teachers care about you,” “your parents care about you,” “your friends care about you,” “people in your family understand you,” “your family pays attention to you,” and “you and your family have fun together” (0 = not at all, 1 = very little, 2 = somewhat, 3 = quite a bit, and 4 = very much). The items were summed so that higher values indicate greater levels of social support (α = 0.78).

Similar to Demuth, Susan, and Brown (2004), parental attachment was operationalized using 4-items from wave II that asked respondents about their relationships with their mother and father. More specifically, respondents were asked how much did they agree with the following statements: “Most of the time, {mom/dad} is warm and loving towards you,” “you are satisfied with the way {mom/dad} and you communicate with each other,” “Overall, you are satisfied with your relationship with {mom/dad},” and “how close do you feel to {mom/dad}.” The first three items were coded as strongly agree (1), agree (2), neither agree nor disagree (3), disagree (4), and strongly disagree (5), while the latter was coded as not close at all (1), not very close (2), somewhat close (3), quite close (4), extremely close (5). The first three items were recoded so that the higher values indicated greater levels of parental attachment. For adolescents residing in two-parent households, the higher score between maternal and paternal attachment was used to indicate parental attachment (α = 0.87).

Low school attachment was assessed using a 3-item index adapted from McGloin and Shermer (2009). On a five-point scale (1 = strongly agree, 2 = agree, 3 = neither agree nor disagree, 4 = disagree, 5 = strongly disagree), respondents were asked how much they agreed with the following statements: “you feel close to people at your school,” “you feel like you are part of your school,” and “you are happy to be at your school.” Responses were summed so that higher values represented lower levels of school attachment (α = 0.80).

We also control for demographic correlates. Age was measured in years at wave II (M = 15.47, SD = 1.25). Race/ethnicity was controlled for using a host of dichotomous variables, specifically Black, Asian, Latina, and Other (1 = yes, 0 = no) with non-Hispanic Whites as the reference group. Respondents who were currently pregnant at the time of wave II interview (n = 67) were also controlled for in the analyses. Baseline (wave I) measures of depression (α = 0.86) and substance use behaviors, specifically alcohol problems (α = 0.78), and marijuana use (10% reported involvement) were controlled for.

Analytic strategy

The analysis proceeds in several stages. First, a test for multicollinearity was conducted, which revealed no problems (VIF range = 1.04 to 1.70, mean VIF = 1.29). Second, following descriptive statistics, a series of negative binomial regression models were estimated to examine the relationship between teenage pregnancy and depression, net of control variables. Third, a series of negative binomial regression models were estimated examining the relationship between teenage pregnancy and alcohol problems. This particular statistical model is warranted due to the overdispersion in the depression (mean = 1.08, variance = 6.68) and alcohol measures (mean = 13.96, variance = 46.96). Fourth, to check for heteroscedasticity in the negative binomial regression models, the Bruesch-Pagan test was used. The results indicated the presence of heteroscedasticity; therefore, robust standard errors were estimated. Given the dichotomous nature of marijuana use, a series of logistic regression models were estimated to test the relationship between teenage pregnancy and marijuana use.

Several interaction terms were created to investigate moderation effects regarding deviant peers. Initial two-way interactions were created between teenage pregnancy and deviant peers, as well as teenage pregnancy and depression. A three-way interaction term (Teenage Pregnancy × Depression × Deviant Peers) was also created to test the hypothesis that those who experience strain, negative emotions, and associate with deviant peers are more inclined to engage in deviant behavior. It is hypothesized that the effect of teenage pregnancy on substance use outcomes will increase as both association with deviant peers and depression increase. Analysis of three-way interaction requires the inclusion of various two-way interactions between the variables that make up the three-way interaction term (Baron 2011). To reduce issues related to multicollinearity, variables were mean-centered prior to creating interaction terms (Aiken and West 1991). All analyses were estimated in STATA 13 (StataCorp, College Station, TX).

Results

Table 1 summarizes descriptive statistics for study variables. Recall the sample is comprised solely of female adolescents. The average age is 15.47 years. Approximately 60 percent of the sample is white, while the remaining 40 percent is other races and ethnicities. Approximately 5 percent of the sample reported having ever been pregnant (n = 265). With regards to the binary dependent variable, nearly 14 percent reported marijuana use (n = 746).

Table 1.

Descriptive Statistics for Study Variables

Variables Mean SD
Dependent Variables
 Alcohol Problems 1.08 2.58
 Marijuana Use 0.14 –
Independent Variables
 Teenage Pregnancy 0.05 –
 Depression 9.96 6.85
 Deviant Peer Association 0.81 0.86
Controls
 Low Self-Control 0.00 3.82
 Low Self-Esteem 11.18 3.58
 Parental Attachment 17.09 3.26
 Low School Attachment 6.79 2.59
 Social Support 21.56 4.07
 Black 0.22 –
 Asian 0.06 –
 Latina 0.15 –
 Other 0.04 –
 Age 15.47 1.25
 Currently Pregnant 0.01 –
 Depression (Wave I) 9.97 6.90
 Alcohol Problems (wave I) 0.91 2.26
 Marijuana Use (wave I) 0.10 –
Open in a new tab

Source: National Longitudinal Study of Adolescent to Adult Health.

Note: N = 5,236; SD = Standard Deviation.

Agnew (1992) argues that that strain leads to negative emotions. Model 1 in Table 2 provides results of a negative binomial regression used to test this hypothesis. Teenage pregnancy is statistically significant and positively associated with an increase in depression (b = 0.11, p < .01), consistent with the predictions of GST. To assess the moderating effect of deviant peers, model 2 in Table 2 includes the two-way interaction term (i.e., deviant peers × teenage pregnancy). The interaction effect between deviant peers and teenage pregnancy was not significantly associated with depression. Across both models, several statistical controls significantly predict depression: low self-control, low self-esteem, low school attachment, social support, and race/ethnicity were significant predictors of depression.

Table 2.

Effect of teenage pregnancy on depression (N = 5,236).

Model 1 Model 2
Variable b SE b SE
Teenage Pregnancy 0.11** 0.04 0.10* 0.03
Low Self-Control −0.00** 0.00 −0.01** 0.00
Low Self-Esteem 0.05*** 0.00 0.05*** 0.00
Parental Attachment −0.00 0.00 −0.00 0.00
Low School Attachment 0.02*** 0.00 0.01*** 0.00
Social Support −0.02*** 0.00 −0.02*** 0.00
Black 0.09*** 0.03 0.12*** 0.03
Asian 0.10** 0.04 0.13** 0.04
Latina 0.07** 0.02 0.08*** 0.02
Other 0.12** 0.04 0.12** 0.04
Age 0.01 0.01 −0.00 0.01
Depression (wave 1) 0.04*** 0.00 0.04*** 0.00
Deviant Peers – – 0.07*** 0.01
Deviant Peers × Teenage Pregnancy – – −0.04 0.04
LR test of α=0 2641.14*** 2691.93***
Wald χ2 1959.13*** 1997.84***
McFadden R2 0.08 0.08
Open in a new tab

Note: LR = likelihood ratio chi-square statistic; SE = robust standard errors; b = negative binomial regression coefficients.

*

p < .05,

**

p < .01,

***

p < .001.

Table 3 displays the results of negative binomial regression models investigating the relationship between teenage pregnancy and alcohol problems. In model 1, the effect of teenage pregnancy is positive and significant (b = 0.44, p < .05). Low self-control, social support, race/ethnicity, and age were all significant predictors of alcohol problems. Regarding social support, females with higher levels of social support were less likely to engage in alcohol related behaviors (b = −0.05, p < .001). As for race/ethnicity, Blacks (b = −0.93, p < .001), Asians (b = −0.73, p < .001), and Latinas (b = −0.36, p < .01) were all significantly less likely to report alcohol problems when compared to their white female counterparts. The prevalence of alcohol problems increased with age (b = .09, p < .01).

Table 3.

Effect of teenage pregnancy on alcohol problems (N = 5,236).

Model 1 Model 2 Model 3 Model 4
Variable b SE b SE b SE b SE
Teenage Pregnancy 0.44* 0.18 0.38* 0.17 0.27 0.20 0.28 0.19
Low Self-Control 0.04*** 0.01 0.04*** 0.01 0.04** 0.01 0.04** 0.01
Low Self-Esteem 0.02 0.01 −0.01 0.01 0.01 0.01 0.00 0.01
Parental Attachment −0.02 0.01 −0.02 0.01 −0.03* 0.01 −0.02 0.01
Low School Attachment −0.01 0.02 −0.03 0.02 −0.05*** 0.02 −0.05*** 0.02
Social Support −0.05*** 0.01 −0.03* 0.01 −0.01 0.01 −0.01 0.01
Black −0.93*** 0.11 −0.98*** 0.11 −0.72*** 0.11 −0.75*** 0.11
Asian −0.73*** 0.17 −0.78*** 0.18 −0.48** 0.17 −0.52*** 0.16
Latina −0.36** 0.12 −0.41** 0.14 −0.24 0.14 −0.24 0.14
Other −0.19 0.19 −0.24 0.19 −0.37* 0.17 −0.40* 0.17
Age 0.09** 0.03 0.09** 0.03 0.08* 0.03 0.08* 0.03
Currently Pregnant −0.26 0.33 −0.30 0.31 −0.29 0.31 −0.24 0.30
Alcohol Problems (wave 1) 0.30*** 0.02 0.29*** 0.02 0.22*** 0.02 0.22*** 0.02
Depression – – 0.04*** 0.01 0.03*** 0.01 0.04*** 0.01
Deviant Peers – – – – 0.88*** 0.05 0.92*** 0.05
Deviant Peers × Teenage Pregnancy – – – – −0.25 0.14 −0.32* 0.14
Deviant Peers × Depression – – – – – – −0.03*** 0.01
Teenage Pregnancy × Depression – – – – – – −0.03 0.02
Teenage Pregnancy × Depression × Deviant Peers – – – – – – 0.05* 0.02
LR test of α=0 768.22*** 821.12*** 1286.81*** 1314.27***
Wald χ2 700.94*** 688.96*** 896.89*** 994.63***
McFadden R2 0.06 0.07 0.10 0.11
Open in a new tab

Note: LR = likelihood ratio chi-square statistic; SE = robust standard errors; b = negative binomial regression coefficients.

*

p < .05,

**

p < .01,

***

p < .001.

According to Agnew, negative emotions should mediate the relationship between strain and coping. In model 2 depression is added into the equation, but it does not mediate the relationship between teenage pregnancy and alcohol problems (see Table 3). The teenage pregnancy estimate remains significant but is reduced from 0.44 to 0.38. After testing the equality of regression coefficients (see Paternoster et al. 1998), the z-test revealed that there is no significant difference between coefficients (z = 0.25; p > .05, one-tailed test).1 The third model investigates the moderating effect of deviant peers and teenage pregnancy on alcohol problems. After controlling for other theoretically relevant factors, no significant two-way interaction effect was observed. Consistent with prior research, deviant peers, is significantly associated with alcohol problems (Dishion and Loeber 1985). Individuals who associate with deviant peers are more likely to report having alcohol related problems (b = 0.88, p < .001). Model 4 adds the three-way interaction term between teenage pregnancy, depression, and deviant peers. Following past research, this model controls for the other two-way interaction effects that make up the three-way interaction term (Baron 2011). The three-way interaction term is positively and significantly associated with alcohol problems (b = 0.05, p < .05), suggesting that adolescents who experienced teenage pregnancy, depression, and associated with deviant peers reported higher levels of alcohol problems (see Figure 1).

Figure 1.

Figure 1.

Open in a new tab

Teenage pregnancy × depression × deviant peers on alcohol problems.

Due to the dichotomous nature of marijuana use, the next two tables present results from a series of logistic regression models to test the hypotheses. Model 1 in Table 4 examines the relationship between teenage pregnancy and marijuana use. The effect of teenage pregnancy is positive and significantly associated with smoking marijuana (b = 0.47, p < .05). Other predictors of marijuana use include low self-control, low self-esteem, low school attachment, social support, being black, and being currently pregnant. These findings are consistent with previous research. Model 2 in Table 4 examines the mediating impact of depression on the relationship between teenage pregnancy and marijuana use. Depression fails to mediate the relationship between teenage pregnancy and marijuana use. Results from the z-test indicate that there is no significant difference between regression coefficients (z = 0.14, p > .05). In model 3, the interactive effects of teenage pregnancy and deviant peers on marijuana use are tested. No moderating effects were observed for the two-way interaction term. While that is the case, it is important to note that the relationship between teenage pregnancy and marijuana use is fully mediated after the inclusion of depression, deviant peers, and the two-way interaction term into the equation. Finally, model 4 examines a three-way interaction between teenage pregnancy, depression, and deviant peers. Individuals who experience teen pregnancy, have high levels of depressive symptoms, and associate with deviant peers were likely to report using marijuana (b = 0.07, p < .05; See Figure 2).

Table 4.

Effect of teenage pregnancy on marijuana use (N = 5,236).

Model 1 Model 2 Model 3 Model 4
Variable b SE b SE b SE b SE
Teenage Pregnancy 0.47* 0.21 0.43* 0.21 0.09 0.32 0.25 0.31
Low Self-Control 0.05*** 0.01 0.05*** 0.01 0.03* 0.01 0.04* 0.01
Low Self-Esteem 0.03* 0.01 0.00 0.02 0.01 0.02 0.01 0.02
Parental Attachment −0.01 0.02 −0.01 0.02 −0.02 0.02 −0.01 0.02
Low School Attachment 0.06*** 0.02 0.06*** 0.02 0.02 0.02 0.02 0.02
Social Support −0.06*** 0.01 −0.05*** 0.01 −0.02 0.02 −0.02 0.02
Black −0.48*** 0.13 −0.53*** 0.13 −0.00 0.14 −0.02 0.14
Asian −0.16 0.23 −0.22 0.22 0.20 0.25 0.17 0.24
Latina 0.07 0.13 0.02 0.13 0.29 0.16 0.29 0.16
Other 0.29 0.18 0.23 0.19 0.22 0.23 0.19 0.23
Age −0.01 0.04 −0.01 0.04 −0.06 0.04 −0.06 0.04
Currently Pregnant −2.06*** 0.58 −2.15*** 0.58 −2.26*** 0.60 −2.32*** 0.67
Marijuana Use (wave 1) 2.46*** 0.10 2.44*** 0.10 1.84*** 0.11 1.84*** 0.11
Depression – – 0.04*** 0.01 0.02** 0.01 0.04*** 0.01
Deviant Peers – – – – 1.32*** 0.06 1.35*** 0.06
Deviant Peers × Teenage Pregnancy – – – – −0.03 0.22 −0.17 0.22
Deviant Peers × Depression – – – – – – −0.01 0.01
Teenage Pregnancy × Depression – – – – – – −0.08* 0.03
Teenage Pregnancy × Depression × Deviant Peers – – – – – – 0.07* 0.03
Wald χ2 938.96*** 1008.90*** 1305.74*** 1390.42***
McFadden R2 0.21 0.21 0.35 0.35
Open in a new tab

Note: Entries are unstandardized logistic regression coefficients (b), and robust standard errors (SE).

*

p < .05,

**

p < .01,

***

p < .001.

Figure 2.

Figure 2.

Open in a new tab

Teenage pregnancy × depression × deviant peers on marijuana use.

Overall, these findings highlight both the relationship between teenage pregnancy and maladaptive behaviors, and the moderating impact of deviant peers. Deviant peers facilitate maladaptive behavior in the form of alcohol problems and marijuana use among females who experience pregnancy during adolescence and have symptoms of depression. In the discussion that follows, the implications of these results for theory, research, and social programs designed to assist teen parents are discussed.

Discussion

This study examined the connections between teen pregnancy and substance use. Building on prior research (Hope et al. 2003), the analyses were informed by Agnew’s (1992, 2006) general strain theory. Within this theoretical framework, teenage pregnancy reflects a stressful life event for young women that leads to negative emotionality (i.e., depression), and ultimately increases the risk of maladaptive coping in the form of substance use. Criminologists have long been aware of the consequences of deviant peer associations and their role in facilitating delinquency (Hoeben et al. 2016). Less is known about the impact of deviant peers in the coping process, especially for individuals who experience the strain of teenage pregnancy. This study investigated the moderating effect of deviant peers on the relationship between strain and substance use outcomes. The findings reported here contribute to the GST literature, identify some avenues for future research, and also provide direction for strategies aimed at addressing adolescent females at risk for substance abuse and pregnancy.

In support of the GST hypothesis that strain leads to negative emotions, teenage pregnancy was a significant predictor of depression (H1). Agnew (2002) argues that anger is a key emotion likely to produce criminal behavior. It is important to note that teenage pregnancy may lead to other emotions, such as anger, frustration, and/or anxiety. However, being that Add Health does not measure adolescents’ levels of anger until later waves of data collection, depression was used. Indeed, it has been argued that women are more likely to respond to strain with depression than anger (Broidy and Agnew 1997). We did not find support for hypothesis 2 as deviant peers did not moderate the relationship between teenage pregnancy and depression.

Also consistent with GST, teenage pregnancy was a significant predictor of substance use (H3). However, the effect of teen pregnancy on these forms of maladaptive coping was not mediated by negative emotionality (H4). In addition to lending support to GST, the results underscore the importance of including unique types of maladaptive coping in future studies. In line with research on juvenile delinquency, the analyses revealed that deviant peer association was a consistent predictor of alcohol and marijuana outcomes. Deviant peer association in the form of peer substance use also played a role in the relationship between teenage pregnancy and substance use. Although there were no significant effects detected for the two-way interaction term (Teenage Pregnancy × Deviant Peers) on substance use outcomes (H5), there were significant effects observed for the three-way interaction term (Teenage Pregnancy × Depression × Deviant peers). The effect of teen pregnancy on alcohol problems and marijuana use was stronger when respondents reported depressive symptoms and had deviant peers (H6). These findings highlight the importance of deviant peers in the coping process, in that teens may seek out deviant peers to help them deal with strain. The combination of strain, negative emotions, and deviant peers increases the risk of maladaptive coping. Future tests of GST should include deviant peers in examining the relationship between other forms of strain and maladaptive coping.

Consistent with a host of studies focused on juvenile populations and other offending contexts, the analyses demonstrated that a variety of well-known crime correlates were linked to substance abuse outcomes. For example, low self-control was a consistent and robust predictor of alcohol problems and marijuana use. Similarly, low school attachment and low self-esteem were associated with increased marijuana use. All too often, criminological research takes a “glass half empty” approach. It is important to also acknowledge factors and circumstances that decrease maladaptive coping. Toward that end, the salience of social support and parental attachment in reducing substance abuse warrants further attention. Coping with strain is arguably influenced by access to supportive networks. Social programs and related efforts designed to assist adolescents would be well-advised to help them identify sources of support beyond the family (e.g., teachers, coaches, or community leaders) who are able to promote involvement in positive activities and encourage prosocial ways of coping with the stress of pregnancy.

Due to the secondary nature of the Add Health data, it is not possible to determine whether the sample had access to any interventions, and the extent to which the availability and use of services lessened the impact of teen pregnancy on maladaptive coping. Subsequent efforts relying on original data collection to address teen pregnancy and its consequences should directly measure access to interventions. This study was primarily concerned with teenage pregnancy. However, prenatal depression can be a precursor to postpartum depression (Mollborn and Morningstar 2009). Future studies might consider the role of postpartum depression in maladaptive coping outcomes. Another limitation of the study is causal ordering. Data for the strain measure (i.e., teenage pregnancy) were drawn from waves I and II, asking females if they have ever been pregnant, and the dependent variables were taken from wave II. A large number of females became pregnant between waves I and II data collection. Although the observed relationships between strain and the outcomes of interest were in the direction predicted by GST, the results presented are nonetheless somewhat limited. To address this limitation, additional analyses were conducted assessing the relationship between teenage pregnancy and substance use behaviors longitudinally, specifically using the wave I teenage pregnancy measure to predict wave II outcomes. Similar findings emerged. Teenage pregnancy was a significant predictor of depression, alcohol problems, and marijuana use. The three-way interaction terms remained significant suggesting that the effect of teen pregnancy on alcohol problems and marijuana use is strongest when depression is high and when respondents associate with deviant peers.

The use of secondary data like the Add Health has both strengths and weaknesses (Greenhoot and Dowsett 2012). For example, the longitudinal design makes it well-suited to address developmental questions, and it includes reliable measures of constructs that are frequently included in tests of general strain theory. Whether replication of the current study using more recent data on adolescent mothers would produce similar results remains an open empirical question, however. One possible influence on current generation teens is the media, a factor that was not available in the Add Health data. While this influence certainly existed in the 1990s when these data were collected, its potential reach has grown through forums such as social media and reality television. Along those lines, a few recent studies have tested the hypothesis that exposure to reality shows such as MTV’s “16 and Pregnant” will encourage teen pregnancy. Contrary to expectations, research has found that the shows have reduced teen pregnancy by encouraging contraceptive use (Kearney and Levine 2015). Similarly, moderating factors – such as positive parental communication about sex – also play a role in reducing the impact of reality television viewing on teen pregnancy (Wright, Randall, and Arroyo 2013). Outside the scope of the current study, future research informed by general strain theory may also consider the extent to which reality programming featuring teen mothers depicts the strains of pregnancy and parenting. Limitations of secondary data aside, it is important to note that the demonstrated validity of GST in a variety of historical contexts suggests that the explanatory power of the models tested in the current study are is in no way restricted by time and place (Baumer and Gustafson 2007; Wang and Holtfreter 2012).

Available evidence shows that females who become pregnant as teens are likely to be stigmatized, experience social isolation and abuse, and have poor educational achievement (Weimann et al. 2005). Based on this study’s results, surrounding individuals who experience strains with prosocial others is important. Counseling programs and support groups may be beneficial in alleviating strain associated with teenage pregnancy. To prevent school failure, alternative education programs may benefit adolescent mothers. A recent review of interventions for teen mothers found that all too often, such programs occur too late to effectively target the precursors of pregnancy (SmithBattle et al. 2017). Given the empirical evidence supporting reverse causality (i.e., substance abuse precedes risky sex and teen pregnancy) early interventions targeting substance abuse could have the added benefit of reducing pregnancy (Cavazos-Rehg et al. 2012). In the end, this study highlights the salience of going beyond predicting teen pregnancy itself to its diverse set of consequences associated. Although this approach has become increasingly common in other crime and victimization contexts, this study is one of just a few efforts to address teen pregnancy from a GST perspective. In doing so, this study contributes to the extant literature on GST, and to parallel efforts examining the consequences of teen pregnancy beyond delinquency outcomes. More research into the role that peers play in the lives of teen parents is needed. There is still much to learn to better serve this vulnerable population.

Acknowledgments

The authors thank Mike Reisig and Jacob Young for their helpful comments on an earlier version of this article.

Biographies

D’Andre Walker is an assistant professor in the Department of Legal Studies at the University of Mississippi. He received his Ph.D. in Criminology and Criminal Justice from Arizona State University in 2018. His work has appeared in the Journal of Child & Family Studies and the Journal of Criminal Justice.

Kristy Holtfreter is a professor in the School of Criminology and Criminal Justice and Faculty Affiliate in the Women and Gender Studies Program at Arizona State University. She received her Ph.D. in 2004 from Michigan State University. Her research has appeared in a variety of scholarly journals, including Criminology, Journal of Research in Crime & Delinquency, Justice Quarterly, and Criminal Justice & Behavior. She is the Editor of Feminist Criminology, the official journal of the American Society of Criminology’s Division on Women and Crime.

Footnotes

1

To assess the slope invariance between two unstandardized regression slope coefficients, the z-test was used (Paternoster et al. 1998: 862): Z=b1−b2SEB12+SEB22.

References

  1. Agnew R 2006. Pressured into Crime: An Overview of General Strain Theory. Los Angeles, CA: Roxbury. [Google Scholar]
  2. Agnew R, Brezina T, Wright JP, and T Cullen F. 2002. “Strain, Personality Traits, and Delinquency: Extending General Strain Theory.” Criminology 40 (1):43–72. doi: 10.1111/crim.2002.40.issue-1 [DOI] [Google Scholar]
  3. Agnew Robert. 1992. “Foundation for a General Strain Theory of Crime and Delinquency.” Criminology 30 (1):47–87. doi: 10.1111/j.1745-9125.1992.tb01093.x [DOI] [Google Scholar]
  4. Agnew Robert. 2001. “Building on the Foundation of General Strain Theory: Specifying the Types of Strain Most Likely to Lead to Crime and Delinquency.” Journal of Research in Crime & Delinquency 38 (4):319–61. doi: 10.1177/0022427801038004001 [DOI] [Google Scholar]
  5. Agnew Robert. 2002. “Experienced, Vicarious, and Anticipated Strain: An Exploratory Study on Physical Victimization and Delinquency.” Justice Quarterly 19 (4):603–32. doi: 10.1080/07418820200095371 [DOI] [Google Scholar]
  6. Agnew Robert. 2013. “When Criminal Coping Is Likely: An Extension of General Strain Theory.” Deviant Behavior 34 (8):653–70. doi: 10.1080/01639625.2013.766529 [DOI] [Google Scholar]
  7. Aiken Leona and West Stephen G.. 1991. Multiple Regression: Testing and Interpreting Interactions. Thousand Oaks, CA: Sage. [Google Scholar]
  8. Barnes Grace M., Hoffman Joseph H., Welte John W., Farrell Michael P., and Dintcheff Barbara A.. 2006. “Effects of Parental Monitoring and Peer Deviance on Substance Use and Delinquency.” Journal of Marriage & Family 68 (4):1084–104. doi: 10.1111/j.1741-3737.2006.00315.x [DOI] [Google Scholar]
  9. Barnet Beth, Duggan Anne K., Wilson Michelle D., and Joffe Alain. 1995. “Association between Postpartum Substance Use and Depressive Symptoms, Stress, and Social Support in Adolescent Mothers.” Pediatrics 96 (4):659–66. [PubMed] [Google Scholar]
  10. Baron Stephan W. 2011. “Street Youths and the Proximate and Contingent Causes of Instrumental Crime: Untangling Anomie Theory.” Justice Quarterly 28 (3):413–36. doi: 10.1080/07418825.2010.512871 [DOI] [Google Scholar]
  11. Baumer Eric P. and Gustafson Regan. 2007. “Social Organization and Instrumental Crime: Assessing the Empirical Validity of Classical and Contemporary Anomie Theories.” Criminology 43 (3):617–63. doi: 10.1111/j.1745-9125.2007.00090.x [DOI] [Google Scholar]
  12. Blue Stanley, Shove Elizabeth, Carmona Chris, and Kelly Michael P.. 2016. “Theories of Practice and Public Health: Understanding (Un)Healthy Practices.” Critical Public Health 26 (1):36–50. doi: 10.1080/09581596.2014.980396 [DOI] [Google Scholar]
  13. Borkowski John G., Farris Jaelyn R., Whitman Thomas L., Carothers Shannon S., Weed Keri, and Keogh Deborah A., Eds. 2016. Risk and Resilience: Adolescent Mothers and Their Children Grow Up. Matwah, NJ: Lawrence Erlbaum Associates. [Google Scholar]
  14. Broidy Lisa. 2001. “A Test of General Strain Theory.” Criminology 39 (1):9–36. doi: 10.1111/j.1745-9125.2001.tb00915.x [DOI] [Google Scholar]
  15. Broidy Lisa and Agnew Robert. 1997. “Gender and Crime: A General Strain Theory Perspective.” Journal of Research in Crime & Delinquency 34 (3):275–306. doi: 10.1177/0022427897034003001 [DOI] [Google Scholar]
  16. Cavazos-Rehg PA, Krauss MJ, Spitznagel EL, Schootman M, Cottler LB, and J Bierut L. 2012. “Brief Report: Pregnant by Age 15 Years and Substance Use Initiation among US Adolescent Girls.” Journal of Adolescence 35 (5):1393–97. doi: 10.1016/j.adolescence.2012.03.001 [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Chapman SLC and T Wu L. 2013. “Substance Use Among Adolescent Mothers: A Review.” Children & Youth Services Review 35 (5):806–13. doi: 10.1016/j.childyouth.2013.02.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Daniels Ana Z. and Holtfreter Kristy. 2019. “Moving beyond Anger and Depression: The Effects of Anxiety and Envy on Maladaptive Coping.” Deviant Behavior 40 (3):34–352. doi: 10.1080/01639625.2017.1422457 [DOI] [Google Scholar]
  19. DeGenna Natacha M., Cornelius Marie D., and Donovan John E.. 2009. “Risk Factors for Young Adult Substance Use among Women Who Were Teenage Mothers.” Addictive Behaviors 34 (5):463–70. doi: 10.1016/j.addbeh.2008.12.014 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Demuth Stephen, Susan L, and Brown SL. 2004. “Family Structure, Family Processes, and Adolescent Delinquency: The Significance of Parental Absence versus Parental Gender.” Journal of Research in Crime & Delinquency 41 (1):58–81. doi: 10.1177/0022427803256236 [DOI] [Google Scholar]
  21. Dishion Thomas. J. and Loeber Rolf. 1985. “Adolescent Marijuana and Alcohol Use: The Role of Parents and Peers Revisited.” The American Journal of Drug & Alcohol Abuse 11 (1–2):11–25. doi: 10.3109/00952998509016846 [DOI] [PubMed] [Google Scholar]
  22. Fergusson David M., Swain-Campbell Nicola R., and Horwood L. John. 2002. “Deviant Peer Affiliations, Crime and Substance Use: A Fixed Effects Regression Analysis.” Journal of Abnormal Child Psychology 30:419–30. [DOI] [PubMed] [Google Scholar]
  23. French David C. and Dishion Thomas J. 2003. “Predictors of Early Initiation of Sexual Intercourse among High-Risk Adolescents.” Journal of Early Adolescence 23 (3):295–315. doi: 10.1177/0272431603254171 [DOI] [Google Scholar]
  24. Froggio Giacinto and Agnew Robert. 2007. “The Relationship between Crime and “objective” versus “subjective” Strains.” Journal of Criminal Justice 35 (1):81–87. doi: 10.1016/j.jcrimjus.2006.11.017 [DOI] [Google Scholar]
  25. Garwood Sarah K., Gerassi Lara, Melissa Johnson-Reid Plax Katie, and Brett Drake. 2016. “More than Poverty: The Effect of Child Abuse and Neglect on Teen Pregnancy Risk.” Journal of Adolescent Health 57 (2):164–68. doi: 10.1016/j.jadohealth.2015.05.004. [DOI] [Google Scholar]
  26. Golladay Katelyn A. and Holtfreter Kristy. 2017. “The Consequences of Identity Theft Victimization: An Examination of Emotional and Physical Health Outcomes.” Victims & Offenders 12 (5):741–60. doi: 10.1080/15564886.2016.1177766 [DOI] [Google Scholar]
  27. Greenhoot AF and Dowsett CJ. 2012. “Secondary Data Analysis: An Important Tool for Addressing Developmental Questions.” Journal of Cognition & Development 13 (1):2–18. [Google Scholar]
  28. Hall Kelli S., Richards Jennifer L., and Harris Kathleen M.. 2017. “Social Disparities in the Relationship between Depression and Unintended Pregnancy during Adolescence and Young Adulthood.” Journal of Adolescent Health 60 (6):688–97. doi: 10.1016/j.jadohealth.2016.12.003 [DOI] [Google Scholar]
  29. Hamilton Brady, Martin Joyce A., Osterman Michelle J., Curtin Sally C., and Mathews TJ. 2015. “Births: Final Data for 2014.” National Vital Statistics Reports 64 (12):1–64. [Google Scholar]
  30. Hay Carter and Evans Michelle M.. 2006. “Violent Victimization and Involvement in Delinquency: Examining Predictions from General Strain Theory.” Journal of Criminal Justice 34 (3):261–74. doi: 10.1016/j.jcrimjus.2006.03.005 [DOI] [Google Scholar]
  31. Hay Carter and Meldrum Ryan. 2010. “Bullying Victimization and Adolescent Self-Harm: Testing Hypotheses from General Strain Theory.” Journal of Youth & Adolescence 39 (5):446–59. doi: 10.1007/s10964-009-9502-0 [DOI] [PubMed] [Google Scholar]
  32. Hoeben Evelien M., Meldrum Ryan C., Walker D Andre, and Young Jacob T.N.. 2016. “The Role of Peer Delinquency and Unstructured Socializing in Explaining Delinquency and Substance Use: A State-Of-The-Art Review.” Journal of Criminal Justice 47:108–22. doi: 10.1016/j.jcrimjus.2016.08.001 [DOI] [Google Scholar]
  33. Hoffmann John P and Su S. Susan. 1997. “The Conditional Effects of Stress on Delinquency and Drug Use: A Strain Theory Assessment of Sex Differences.” Journal of Research in Crime & Delinquency 34 (1):46–78. doi: 10.1177/0022427897034001004 [DOI] [Google Scholar]
  34. Holtfreter Kristy, Reisig Michael D., and O’Neal Eryn N.. 2015. “Prescription Drug Misuse in Late Adulthood: An Examination of Competing Explanations.” Journal of Drug Issues 45 (4):351–67. doi: 10.1177/0022042615589405 [DOI] [Google Scholar]
  35. Hope Trina L., Esther I, Wilder EI, and Watt Toni T. 2003. “The Relationships among Adolescent Pregnancy, Pregnancy Resolution, and Juvenile Delinquency.” The Sociological Quarterly 44 (4):555–76. doi: 10.1111/j.1533-8525.2003.tb00525.x [DOI] [Google Scholar]
  36. Jessor Richard. 1987. “Problem Behavior Theory, Psychosocial Development, and Adolescent Problem Drinking.” British Journal of Addiction 82 (4):31–342. [DOI] [PubMed] [Google Scholar]
  37. Kearney Melissa S. and Levine PB. 2015. “Impact of MTV’s “16 and Pregnant” on Teen Childbearing.” American Economic Review 105 (12):3597–632. [DOI] [PubMed] [Google Scholar]
  38. Kreager Derek A., Matsueda Ross L., and Erosheva Elena A.. 2010. “Motherhood and Criminal Desistance in Disadvantaged Neighborhoods.” Criminology 48 (1):221–58. doi: 10.1111/j.1745-9125.2010.00184.x [DOI] [Google Scholar]
  39. Letourneau Nicole L., Stewart Miriam J., and Barnfather Alison K.. 2004. “Adolescent Mothers: Support Needs, Resources, and Support-Education Interventions.” Journal of Adolescent Health 35 (6):1509–25. doi: 10.1016/S1054-139X(04)00069-2 [DOI] [Google Scholar]
  40. McDonnell James R., Limber Susan P., and Connor-Godbey Jennifer. 2007. “Pathways Teen Mother Support Project: Longitudinal Findings.” Children & Youth Services Review 29 (7):840–55. doi: 10.1016/j.childyouth.2007.01.001 [DOI] [Google Scholar]
  41. McGloin Jean M. and Shermer Lauren O.N. 2009. “Self-Control and Deviant Peer Network Structure.” Journal of Research in Crime & Delinquency 46 (1):35–72. doi: 10.1177/0022427808326585 [DOI] [Google Scholar]
  42. Miller Brent C. 2002. “Family Influences on Adolescent Sexual and Contraceptive Behavior.” Journal of Sex Research 39 (1):22–26. doi: 10.1080/00224490209552115 [DOI] [PubMed] [Google Scholar]
  43. Mollborn Stefanie and Morningstar Elizabeth. 2009. “Investigating the Relationship between Teenage Childbearing and Psychological Distress Using Longitudinal Evidence.” Journal of Health & Social Behavior 50 (3):310–26. doi: 10.1177/002214650905000305 [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Moon Byongook, Blurton David, and McCluskey John D.. 2008. “General Strain Theory and Delinquency: Focusing on the Influences of Key Strain Characteristics on Delinquency.” Crime & Delinquency 54 (4):582–613. doi: 10.1177/0011128707301627 [DOI] [Google Scholar]
  45. Paternoster Raymond, Brame Robert, Mazerolle Paul, and Piquero Alex. 1998. “Using the Correct Statistical Test for the Equality of Regression Coefficients.” Criminology 4:859–66. doi: 10.1111/j.1745-9125.1998.tb01268.x [DOI] [Google Scholar]
  46. Peck Jennifer H., Childs Kristina K., Jennings Wesley G., and Brady Caitlin M.. 2017. “General Strain Theory, Depression, and Substance Use: Results from a Nationally Representative, Longitudinal Sample of White, African-American, and Hispanic Adolescents and Young Adults.” Journal of Child & Adolescent Substance Abuse 27 (1):11–28. doi: 10.1080/1067828X.2017.1396516. [DOI] [Google Scholar]
  47. Pyrooz David C., McGloin Jean M., and Decker Scott H.. 2017. “Parenthood as A Turning Point in the Life Course for Male and Female Gang Members: A Study of Within-Individual Changes in Gang Membership and Criminal Behavior.” Criminology 55 (4):869–99. doi: 10.1111/1745-9125.12162 [DOI] [Google Scholar]
  48. Radloff Lenore S. 1977. “The CES-D Scale: A Self-Report Depression Scale for Research in the General Population.” Applied Psychological Measurement 1 (3):385–401. doi: 10.1177/014662167700100306 [DOI] [Google Scholar]
  49. Reisig Michael D., Holtfreter Kristy, and Turanovic Jillian J.. 2018. “Criminal Victimization, Depressive Symptoms, and Behavioral Avoidance Coping in Late Adulthood: The Conditioning Role of Strong Familial Ties.” Journal of Adult Development 25 (1):13–24. doi: 10.1007/s10804-017-9270-0 [DOI] [Google Scholar]
  50. Roosa Mark W., Tein Jenn-Yun, Reinholtz Cindy, and Angelini Patricia J.. 1997. “The Relationship of Childhood Sexual Abuse to Teenage Pregnancy.” Journal of Marriage & Family 59 (1):119–30. doi: 10.2307/353666 [DOI] [Google Scholar]
  51. Rosenberg Morris. 1965. Society and the Adolescent Self-image. Princeton, NJ: Princeton University Press. doi: 10.1515/9781400876136. [DOI] [Google Scholar]
  52. Salas-Wright CP, Vaughn MG, Ugalde J, and Todic J. 2015. “Substance Use and Teen Pregnancy in the United States: Evidence from the NSDUH 2002–2012.” Addictive Behaviors 45:218–25. doi: 10.1016/j.addbeh.2015.01.039 [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Shuger Lisa. 2012. Teen Pregnancy and High School Dropout: What Communities Can Do to Address These Issues. Washington, DC: The National Campaign to Prevent Teen and Unplanned Pregnancy. [Google Scholar]
  54. Simons-Morton Bruce, Haynie Denise L., Crump Aria D., Eitel Patricia, and Saylor Keith E. 2001. “Peer and Parent Influences on Smoking and Drinking among Early Adolescents.” Health Education & Behavior 28 (1):95–107. doi: 10.1177/109019810102800109 [DOI] [PubMed] [Google Scholar]
  55. SmithBattle Lee, Loman Deborah G., Chantamit-o-pas Chutima, and Schneider Joanne K.. 2017. “An Umbrella Review of Meta-Analyses of Interventions to Improve Maternal Outcomes for Teen Mothers.” Journal of Adolescence 50:97–111. doi: 10.1016/j.adolescence.2017.05.022 [DOI] [Google Scholar]
  56. Thaxton Sherod and Agnew Robert. 2018. “When Criminal Coping Is Likely: An Examination of Conditioning Effects in General Strain Theory.” Journal of Quantitative Criminology 34 (4):887–920. doi: 10.1007/s10940-017-9358-5 [DOI] [Google Scholar]
  57. Tillyer Marie S. and Tillyer R. Rob. 2016. “Race, Ethnicity, and Adolescent Violent Victimization.” Journal of Youth & Adolescence 45 (1):1–15. doi: 10.1007/s10964-016-0416-3 [DOI] [PubMed] [Google Scholar]
  58. Turanovic Jillian J. 2015. “The Age-Graded Consequences of Victimization.” Doctoral dissertation, Arizona State University.
  59. Turanovic Jillian J. and Pratt Travis C. 2013. “The Consequences of Maladaptive Coping: Integrating General Strain and Self-Control Theories to Specify a Causal Pathway between Victimization and Offending.” Journal of Quantitative Criminology 29 (3):321–45. doi: 10.1007/s10940-012-9180-z [DOI] [Google Scholar]
  60. United States Department of Health and Human Services. 2016. Healthy People 2020. Washington, D.C.: U.S. Department of Health and Human Services. [Google Scholar]
  61. Walker D’Andre and Holtfreter Kristy. 2016. “Adolescent Motherhood, Depression, and Delinquency.” Journal of Child & Family Studies 25 (3):939–48. doi: 10.1007/s10826-015-0268-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Wang Xia and Holtfreter Kristy. 2012. “The Effects of Corporation- and Industry-Level Strain and Opportunity on Corporate Crime.” Journal of Research in Crime & Delinquency 41 (2):151–85. doi: 10.1177/0022427810395321 [DOI] [Google Scholar]
  63. Whitworth Tanya R. 2017. “Teen Childbearing and Depression: Do Pregnancy Attitudes Matter?” Journal of Marriage & Family 79 (2):390–404. doi: 10.1111/jomf.12380 [DOI] [Google Scholar]
  64. Wiemann Constance M., Rickert Vaughan I., Berensen Abbey B., and Volk Robert J.. 2005. “Are Pregnant Adolescents Stigmatized by Pregnancy?” Journal of Adolescent Health 36:352e1–352e7. doi: 10.1016/j.jadohealth.2004.06.006 [DOI] [Google Scholar]
  65. Wight Richard G., Botticello Amanda L., and Aneshensel Carol S.. 2006. “Socioeconomic Context, Social Support, and Adolescent Mental Health: A Multilevel Investigation.” Journal of Youth & Adolescence 35 (1):109–20. doi: 10.1007/s10964-005-9009-2 [DOI] [Google Scholar]
  66. Wright Paul J., Randall Ashley K., and Arroyo Analisa. 2013. “Father-Daughter Communication about Sex Moderates the Association between Exposure to MTV’s 16 and Pregnant/Teen Mom and Female Students’ Pregnancy-Risk Behavior.” Sexuality & Culture 17 (1):50–66. doi: 10.1007/s12119-012-9137-2 [DOI] [Google Scholar]

RESOURCES