Abstract
Objective Maltreated female adolescents are at risk for engaging in sexual behaviors consistent with HIV infection and teen pregnancy. The current study applied a model positing the key role of psychological dysregulation in the development of adolescent females’ sexual behavior. Methods The sample consisted of adolescent females aged 14–17 years who had experienced substantiated childhood maltreatment (n = 275) and a demographically matched, non-maltreated comparison group (n = 210). Results Multiple mediator analysis revealed that, when in company with a host of plausible mechanisms, sexual preoccupation mediated the relationship between psychological dysregulation and risky sexual behaviors. Conclusion Maltreated females may have difficulty regulating emotions, cognitions, and behaviors, which, when coupled with a propensity to entertain sexual thoughts and consume sexually explicit materials, may increase the likelihood that they act on sexual impulses and engage in high-risk sexual behaviors.
Keywords: adolescent sexual behavior, maltreatment, psychological dysregulation, structural modeling
Introduction
Over 1.2 million children are determined to be victims of childhood maltreatment, including neglect, physical abuse, and sexual abuse, each year in the United States (Sedlak et al., 2010). Research on the short- and long-term effects of childhood maltreatment suggests that it may play a role in the development of adverse sexual outcomes in pediatric and adult populations. For instance, childhood maltreatment has been associated with several risky sexual behaviors, including early coital initiation, sexual engagement without contraceptives, and prostitution (Houck, Nugent, Lescano, Peters, & Brown, 2010; Jones et al., 2010; Noll, Trickett, & Putnam, 2003) as well as the contraction of sexually transmitted infections and HIV (Wilson & Widom, 2008; Wingood & DiClemente, 1997). Although this risk applies to both males and females who have been maltreated (Jones et al., 2010), females are at risk for additional sexual health outcomes including teenage pregnancy and motherhood (Noll, Shenk, & Putnam, 2009).
There is scant research aimed at explicating specific mechanistic processes involved in high-risk sexual behaviors for maltreated females. There is some evidence that childhood maltreatment may result in a breakdown in global regulatory processes associated with pediatric outcomes. For instance, childhood maltreatment has been linked to disruptions in the hypothalamic–pituitary adrenal axis (Trickett, Noll, Susman, Shenk, & Putnam, 2010), neurological structures responsible for behavior regulation (De Bellis & Kuchibhatla, 2006), and systems involved in affect regulation (Shipman, Zeman, Penza, & Champion, 2000). Maltreated females also report significantly higher levels of sexual preoccupation, such as intrusive sexual thoughts, pornography consumption, and frequent masturbation, which have accounted for individual differences in subsequent HIV-risk behaviors and teen pregnancy (Noll et al., 2003). This breakdown in regulatory processes is thought to be indicative of further disruption, especially in the face of other risk factors such as peer influences and substance use that are common in adolescence (Crockett, Raffaelli, & Shen, 2006).
The bulk of research tying regulatory deficits to risky adolescent behaviors has been done in the substance use field where global regulatory deficits have been operationalized in terms of “psychological dysregulation” comprising three distinct but related components: cognitive dysfunction, behavioral impulsivity, and emotional lability (Tarter et al., 2003). At the broadest level, psychological dysregulation is the inability to optimally and willfully control and guide one’s cognitions, behaviors, and emotional responses in a goal-directed manner (Thatcher & Clark, 2008). There are several aspects of psychological dysregulation which are often studied separately including: (a) cognitive self-regulation defined as attentional focus, inhibitory control or the suppression of off-task cognitions, planning and organizing, and effortful control or the ability to exert the effort needed to achieve goal-directed action (Murray & Kochanska, 2002); (b) behavior self-regulation defined as control of behavioral impulses in social contexts, delayed gratification or enacting patience, refraining from impulsivity and weighing options in social contexts (Sprague & Walker, 2000); and (c) emotion self-regulation defined as modulating internal feeling states and emotion-related physiological and attentional processes in the service managing volatile social and emotional states (Eisenberg & Spinrad, 2004). Albeit inclusive of many components, the warp of psychological dysregulation is comprised of several threads which have very specific implications for the development of problematic behaviors in adolescence. Woven through this warp is a large social component wherein it is recognized that social contexts offer unique challenges to self-regulatory capacities. Adolescence is arguably one of the most difficult periods to navigate with respect to self-regulation as there are ample social challenges, such as engagement in romantic and sexual relationships, which prompt the use of these developing capacities. If self-regulatory capacities are disrupted or inadequately developed in the presence of such challenges, adolescent health can be affected.
Within the larger adolescent development literature, there is convincing evidence to support models that place risky sexual behaviors within the framework of general problem behaviors that interact with one another to impact optimal development. For example, involvement in a deviant peer group has been shown to be particularly pronounced and detrimental for female adolescent sexual development (Caspi, Lynam, Moffitt, & Silva, 1993). Experimentation with alcohol and drugs often first occurs within a peer group and can result in sexual enhancement expectancies and remove inhibitions that disrupt adolescents’ decision-making around sexual activity (Mason et al., 2010). In addition to alcohol and drug use, more general delinquency and conduct problems have been shown to be prognostic of later adverse outcomes including risky sexual behaviors (Fergusson, Horwood, & Ridder, 2005). Conversely, parenting practices can be powerful protective factors in the family-peer mesosystem (Bronfenbrenner & Crouter, 1983) buffering against the harmful effects of problematic behaviors and peer influences during adolescence (O'Donnell et al., 2006). Adolescents who report being emotionally connected and supported by parents (Crosby et al., 2001) and whose parents are present and monitor their whereabouts and activities (Miller, Benson, & Galbraith, 2001) have reported lower rates of risky sexual behaviors. Parental influences have been shown to be especially effective in curtailing risky sexual behaviors in females (Hutchinson, Jemmott, Jemmott, Braverman, & Fong, 2003). Hence, models of adolescent female risky sexual behaviors should simultaneously consider various interrelated behavioral processes and contexts.
Although a comprehensive picture of the myriad of psychosocial risk factors associated with adolescent female risky sexual behaviors is beginning to be painted, key variables are too often studied in isolation and are rarely incorporated on the same canvass. This makes it difficult to discern the unique contribution of each risk and protective factor and precludes our ability to articulate important pathways to risky sexual behavior that will bolster prevention and intervention efforts. The purpose of this article is to: (a) test a comprehensive model where childhood maltreatment is associated with higher rates of psychological dysregulation which in turn is associated with risky sexual behaviors in adolescent females; and (b) isolate indirect pathways to risky sexual behaviors that function independently from one another while taking into account simultaneously occurring alternative pathways. The present study focuses on pathways to risky sexual behaviors for adolescent females aged 14–17 years and explicitly tests associations between risky sexual activities and a circumscribed set of the most often cited and developmentally relevant risk factors.
Methods
Sample
Maltreated adolescents (n = 275) were recruited from local child protective service (CPS) agencies and had experienced substantiated incidences of physical neglect, physical abuse, or sexual abuse via state and local standards. Abuse type was distributed as follows: sexual abuse (47%), physical abuse (32%), physical neglect (16%), with 51% of the sample experiencing multiple types. Because of this high overlap among types of maltreatment, discrete categories of abuse types were not examined. Hence, sexual abuse, physical abuse and physical neglect were combined into a single category and analyzed as such. Assessments were scheduled 3–12 months after disclosure of abuse.
Comparison females (n = 239) were recruited from a hospital-based, primary care teen health center and were matched to at least one abused female regarding race/ethnicity, family income level, age, and family constellation (one or two parent households). To obtain mutually exclusive groups, comparison females were screened for CPS involvement prior to enrollment. In addition, a validated instrument assessing prior trauma histories (Barnes, Noll, Putnam, & Trickett, 2009) was administered to both adolescents and caregivers. As a result, 29 comparison females were excluded because of reports of childhood maltreatment resulting in a final comparison sample of 210.
The total sample was mean age of 15.74 years (SD = 1.10), had a median family income level of $20,000–$29,000, was 53% single-parent households, and had a racial make-up at 46% Caucasian, 45% African-American, 8% Bi- or Multi-racial, 0.5% Hispanic, and 0.5% Native American.
Procedures
Participants resided in the catchment area of a Children’s Hospital located in the Mid-west region of the US. Non-maltreating caregivers accompanied adolescents to the lab session to provide informed consent and information about adolescents’ well-being. Adolescents provided assent and then completed questionnaires and semi-structured interviews regarding sexual attitudes and activities, substance use, peer involvement, and parental connectedness. High-risk behaviors and attitudes (e.g., sexual behaviors, substance use, and high-risk peer affiliations) were assessed via multimedia computers to provide an atmosphere of anonymity without embarrassment or fear of offending a live interviewer. Caregivers completed the behavior problems questionnaire and the trauma history reports in a separate testing area. The study received approval from the Institutional Review Board.
Measures
Maltreatment
Based on substantiated caseworker reports, maltreatment was quantified as 1 = “maltreated”, 0 = “comparison”. We did not conduct analyses by type of maltreatment due to sample size limitations, but performed post hoc exploratory analyses to ascertain if type of maltreatment contributed meaningfully to the understanding of the multivariate system.
Risky Sexual Behaviors
The Sexual Attitudes and Activities Questionnaire (SAAQ; Noll et al., 2003) was administered to assess high-risk sexual behaviors. We defined the latent variable, “risky sexual behaviors” for structural equation modeling (SEM) analyses using the following five compellations: (a) number of HIV risk behaviors including “yes” = 1 or “no” = 0 to having ever had intercourse without a condom, condoms failing during intercourse, intercourse or oral sex with an intravenous drug user, used intravenous drugs, shared needles, intercourse or oral sex with a bisexual partner, unprotected intercourse with a homosexual male, multiple concurrent intercourse partners, one night stands, and intercourse while drunk or high; (b) age at first voluntary intercourse was scored according to risk level in that lower ages received high scores [i.e., (age at first intercourse)*-1] and those who had never had intercourse were given the lowest risk score; (c) number of sexually transmitted diseases including “yes” = 1 or “no” = 0 to having ever had chlamydia, gonorrhea, syphilis, pelvic inflammatory disease, genital warts, genital herpes, HIV, or hepatitis B or C; (d) number of sexual intercourse partners in the past year; and (e) number of additional risky sexual behaviors including the number of lifetime partners with whom the following occurred: oral sex, one night stands, unprotected sex, and sex while under the influence of alcohol or drugs.
Psychological Dysregulation
The Dysregulation Inventory (DI; Mezzich, Tarter, Giancola, & Kirisci, 2001) is a 92-item adolescent self-report measure assessing difficulties in modulating problematic cognitions, affect, and behaviors. The DI is comprised of three subscales which we used to define the 3-indicator latent construct, “psychological dysregulation,” for SEM analyses: affective (α = .87), cognitive (α = .83) and behavioral (α = .91) dysregulation.
Sexual Preoccupation
The SAAQ measures risky sexual attitudes such as sexual preoccupation (Noll et al., 2003) which is comprised of 15 items (α = .91) including frequent masturbation, pornography consumption, intrusive sexual thoughts, and being turned-on by sexual themes and fantasies. We split the items into three even groups (1–5, 6–10, and 11–15) to define the three-indictor latent construct, “sexual preoccupation,” included in SEM analyses.
Substance Use
Substance use was defined as smoking, drinking, and illicit drug use during the past year via items excerpted from the Monitoring the Future (MTF) national survey questionnaires (Johnston, O'Malley, Bachman, & Schulenberg, 2005). Smoking was defined as frequency of smoking cigarettes (from 0 = “none” to 4 = “four time or more”). Drinking was defined by two items reflecting the number of occasions (from 0 = “none” to 6 = “40 or more”) adolescents had “more than just a few sips of alcohol” and were “drunk or very high from drinking”. Illicit drug use was defined as the number of occasions adolescents used a variety of illicit substances including marijuana, lysergic acid diethylamide (LSD), cocaine, amphetamines, barbiturates, tranquilizers, and other narcotics. These compilations were included in the SEM analysis to define the three-indicator latent construct, “substance use.”
Risky Peers
Affiliation with high-risk peers was defined via two broad aspects of risk: (a) peer substance use (α = .79)—a compellation MTF items measuring how many close friends (0 = “none,” 1 = “a few,” 2 = “some,” 3 = “most,” 4 = ‘all”) smoke cigarettes, drink alcohol, get drunk, smoke marijuana, use illegal drugs; and (b) peer sexual involvement (α = .88)—a compellation of SAAQ items measuring whether or not (from 0 = “definitely no” to 5 = “definitely yes”) adolescents’ best friend has had oral sex, intercourse, multiple partners, one night stands, intercourse while drinking or high, or unprotected sex. These aspects of high-risk peer behaviors were included in the SEM analysis to define the 2-indicator latent construct, “risky peers.”
Parental Connectedness
This construct was measured in two ways to define a three-indicator latent construct. The first was “parental warmth” as measured by the 10-item subscale of the Children’s Report of Parent Behaviors Inventory-30 (Schluderman & Schluderman, 1988) which is a well-established measure with strong psychometric properties (Schwarz, Barton-Henry, & Pruzinsky, 1985). Internal consistency for the warmth scale in the current sample is (α = .88). The second was “caregiver presence” as measured by a composite scale of 12 items (α = .91) derived from the Add Health survey (Chandy, Blum, & Resnick, 1996) and includes the frequency of caregiver presence at mealtimes, before school, after school, and at bedtime.
Behavior Problems
Internalizing and externalizing behavior problems were assessed via caregiver reports on the Child Behavior Checklist (Achenbach, 1991). The CBCL is a widely used, valid measure for assessing internalizing and externalizing behaviors. Internal consistencies for internalizing (α = .89) and externalizing (α = .91) scales are excellent in the current sample. Given their high inter-correlation (r = .69), the internalizing and externalizing scales were used to define the two-indicator latent construct, “behavior problems,” for the SEM.
Analytic Plan
Using a mediational framework, we first conducted an individual mediator analysis to test whether psychological dysregulation mediated the relationship between maltreatment and risky sexual behaviors using the Sobel test (Sobel, 1982) to evaluate the significance of the indirect effect and the degree of mediation (i.e., full vs. partial). If partial mediation were to emerge, we sought to further understand the role of dysregulation by using Mplus to perform a multiple mediator test of the extent to which other associated risk factors would further mediate the relationship between dysregulation and risky sexual behaviors. SEM is a sound and state-of-the-art approach to error-free parameter estimation and the use of Mplus (Muthen & Muthen, 2007; Los Angeles, CA) allows us to test multiple pathways simultaneously. Although a host of alternative models could have been tested, we adhered to strong a priori hypotheses and theoretical parsimony in selecting the resultant model and identified pathways. For each latent variable, individual indicators were standard scores prior to inclusion in SEM analysis. Variables defining unit-weighted linear composites of constructs included in the SEM were contrasted via an overall, omnibus multivariate analysis of variance (MANOVA) model followed by individual post hoc F-tests to discern group differences (Table I).
Table I.
Group Differences for Variables Used in Mediational Analyses
Variables | Total M (SD) | Comparison M (SD) | Maltreated M (SD) | F | d |
---|---|---|---|---|---|
Sexual preoccupation | 0 (1) | −0.03 (0.99) | 0.02 (0.99) | 1.00 | .09 |
Behavioral problems | 0 (1) | −0.32 (0.89) | 0.26 (0.99) | 24.78** | .61 |
Parental connectedness | 0 (1) | 0.13 (0.97) | −0.12 (1.02) | 7.95** | .25 |
Risky peers | 0 (1) | −0.14 (0.94) | 0.09 (1.03) | 6.14** | .23 |
Substance use | 0 (1) | −0.24 (0.85) | 0.17 (1.08) | 19.46** | .41 |
Psychological dysregulation | 0 (1) | −0.26 (0.94) | 0.20 (1.01) | 23.49** | .46 |
Risky sexual behaviors | 0 (1) | −0.28 (0.91) | 0.16 (1.01) | 20.90** | .45 |
Note. Degrees of freedom are 1,483 for all contrasts shown except for behavioral problems which is 1,469. Standard scores (M = 0; SD = 1) were calculated from unit-weighted linear combinations of indicators described in the ‘Measure’ section.
*p < .05, **p < .01.
Results
Descriptives
There were no demographic differences across maltreated versus comparison groups. To control for Type I error, we conducted an overall omnibus MANOVA model to test group differences in all other variables included in analyses. The overall F-test for the MANOVA was significant, F (7, 447) = 9.98, p < .01. Post hoc analyses revealed that maltreated adolescents scored significantly higher than comparison females regarding risky sexual behaviors, psychological dysregulation, substance use, risky peers, lack of parental connectedness, and behavior problems (Table I).
Psychological Dysregulation as an Individual Mediator
An individual mediator analysis was conducted to assess whether the indirect pathway between maltreatment, psychological dysregulation, and risky sexual behaviors significantly accounted for the relationship between maltreatment and risky sexual behaviors. The Sobel statistic was Z = 3.12, p < .01, indicating significance for the indirect pathway. However, as can be seen in Figure 1, even in the company of psychological dysregulation, maltreatment continued to be a significant predictor of risky sexual behaviors, β = .16, p < .01, indicating that psychological dysregulation functions only as a partial mediator in the proposed system. However, the associational and squared associational effect sizes for the relationship between psychological dysregulation and risky sexual behaviors were relatively small, r = .18 and R2 = .07, respectively. Small effects indicate that shared variance is minimal and that there is ample variability in the constructs of interest that has been left unexplained (Ferguson, 2009).
Figure 1.
Individual mediator analysis showing partial mediation for psychological dysregulation. Standardized β parameter estimates shown. *p < .05, **p < .01.
Multiple Mediator Model
A multiple mediator analysis using Mplus was then conducted to further account for the relationship between psychological dysregulation and risky sexual behaviors (Figure 2). Fit indices suggest that the proposed model fits the observed data well; χ2 (188) = 470.95, Comparative Fit Index = 0.95, and Root Mean Square Error of Approximation = 0.05. The fit indices indicate that the measurement model is sound and that the proposed paths are specified such that latent variable interrelationships are accounted for, and that the observed covariance matrix is adequately reproduced. Results indicated that childhood maltreatment was significantly and positively related to psychological dysregulation, suggesting that various forms of abuse may disrupt cognitive, affective, and behavioral processes. Psychological dysregulation was, in turn, significantly related to all of the additional risk factors of interest including sexual preoccupation, behavior problems, parental connectedness, risky peers, and substance use. Taken together, these results suggest that, while psychological dysregulation does not fully mediate the relationship between maltreatment and risky sexual behaviors, it indeed plays a role in additional hypothesized processes that might contribute to risky sexual behaviors.
Figure 2.
Multiple mediator analysis showing a total indirect effect by the set of risk factors modeled. Sexual preoccupation emerged as a unique indirect pathway between psychological dysregulation and risky sexual behaviors. Inter-correlations among risk factors were freely estimated and are reported in Table II but are not shown in order to simplify the figure. Standardized β parameter estimates shown. *p < .05, **p < .01.
To test whether psychological dysregulation plays a role in additional processes that are associated with risky sexual behaviors, simultaneous tests of indirect pathways were conducted. The sum of the total indirect effects was significant, Z = 5.47, p < .001, indicating that the set of mediators explained the relationship between psychological dysregulation and risky sexual behaviors. Although all risk factors were correlated with risky sexual behaviors at the zero-order level (Table II), only sexual preoccupation and risky peers emerged as independent predictors of risky sexual behaviors when in company with the entire set. Moreover, Figure 2 shows that the β-values from psychological dysregulation to risky sexual behaviors is not significantly different from 0, β = .03, p = .26, indicating that the set of risk factors fully mediated the relationship between psychological dysregulation and risky sexual behaviors. Indeed, when the entire set of independent variables was included, the R2 for risky sexual behaviors was .62 which constitutes a strong effect size indicating a relatively high practical impact of the findings reported (Ferguson, 2009).
Table II.
Inter-correlations among Variables Included in Analyses
Variables | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 |
---|---|---|---|---|---|---|---|---|
1. Sexual preoccupation | 1.0 | |||||||
2. Behavioral problems | .07 | 1.0 | ||||||
3. Parental connectedness | −.05 | −.28** | 1.0 | |||||
4. Risky peers | .19** | .16** | −.11* | 1.0 | ||||
5. Substance use | .22** | .21** | −.10* | .40** | 1.0 | |||
6. Psychological dysregulation | .19** | .44** | −.17** | .15** | .27** | 1.0 | ||
7. Risky sexual behaviors | .36** | .21** | −.13* | .41** | .48** | .18** | 1.0 | |
8. Maltreatment | .08 | .30** | −.15** | .11* | .20** | .23** | .22** | 1.0 |
Note. Pearson product–moment correlations shown except in the case of correlations with maltreatment status which is scored as a dichotomous variable (1 = maltreated, 0 = comparison) warranting the presentation of point-biserial correlations.
*p < .05, **p < .01.
Specific indirect effects for each mediator were then examined to ascertain whether any proposed pathway significantly accounted for the relationship between psychological dysregulation and risky sexual behaviors while simultaneously estimating other plausible mediators. As can be seen in Figure 2, the only significant indirect pathway was that from dysregulation, through sexual preoccupation, to risky sexual behaviors, Z = 3.33, p < .01. Using effect size calculations for mediational/indirect effects (MacKinnon, 2008), the significant indirect effect accounted for 38% of the total zero-order direct effect. Although there are no guidelines yet available to judge the relative magnitude of indirect effect sizes, the proportion of variation accounted for by this indirect effect corresponds to a moderate to strong squared associational effect (Ferguson, 2009). Although the β-values from psychological dysregulation to risky peers and from risky peers to risky sexual behaviors were both significant, the indirect effect was not significant.
Discussion
This study tested indirect pathways of a host of risk factors in an effort to better understand the links between maltreatment, psychological dysregulation, and risky sexual behaviors. The results support an association between psychological dysregulation and a host of key variables that can place adolescent females at risk for further developmental disruption. These include behavior problems, lack of parental connectedness, risky peer affiliations, substance use, and sexual preoccupation. All of these variables were associated with risky sexual behaviors at the zero-order, correlation level. These associational patterns suggest that dysregulation likely plays an important role in the development of risky sexual behaviors at the level of affective, behavioral and cognitive processing.
Associated risk factors were then simultaneously assessed in a multiple mediator analysis to determine unique pathways to risk sexual behaviors. Sexual preoccupation was the most potent predictor of sexual risk-taking when evaluated along with risky peers, parental connectedness, behavior problems, substance use. Out of all these risk factors, only sexual preoccupation helped explain the process by which psychological dysregulation operates on adolescent risky sexual behavior. Indeed, the results suggest that psychological dysregulation and sexual preoccupation function together to illuminate an important indirect pathway to sexual risk-taking above and beyond other plausible avenues. Female adolescents who have difficulty regulating their emotions, cognitions, and behaviors may be unable to effectively compartmentalize these preoccupations to a degree that keeps them from acting on sexual impulses and resisting the propensity to engage in sexual behaviors.
The inability to effectively regulate emotions, cognitions, and behaviors, coupled with a preoccupation with sexual thoughts and stimuli, can help explain why maltreated adolescent females are at risk for engaging in risky sexual behaviors. According to the Traumagenics Dynamics model (Finkelhor & Browne, 1986), childhood maltreatment may result in cognitive distortions around sexuality stemming from the severe boundary violations, betrayal, stigma, shame, and powerlessness that characterize extreme traumatization. Hence, when faced with sexual impulses, especially those that are difficult to regulate, maltreated adolescents may act accordingly and adopt risky sexual behaviors. Theses results suggest that maltreatment might dysregulate one’s ability to modify or alter cognitions, putting those who have higher sexual preoccupation—a cognitive process itself—at risk for further disruption and for engagement in risky sexual behaviors.
As such, this study offers potential implications for prevention efforts and clinical interventions in the pediatric setting. These data suggest that psychological dysregulation increases the risk for engagement in risky sexual behavior. However, further examination of this relationship indicated that sexual preoccupation, including frequent masturbation, pornography consumption, and intrusive sexual thoughts, fully mediated the relationship between psychological dysregulation and risky sexual behavior even when accounting for other associated risk factors. Pediatric psychologists should assess the presence of psychological dysregulation, sexual preoccupation, and sexual activity when working with female adolescents with a maltreatment history. In turn, interventions should focus on addressing current sexual thoughts, attitudes, and behaviors in order to reduce engagement in risky sexual activity. This can be accomplished through cognitive-behavioral interventions or even education about safe sex hygiene for those not yet engaging in sexual activity. Parents and pediatric practitioners should emphasize ways in which adolescents can field sexual thoughts and feelings and should discuss various healthy means of sexual expression. Being especially vulnerable, female adolescents who have been maltreated may need augmented interventions regarding effective strategies to deal with sexual thoughts and warding-off sexual advances.
These findings are considered in light of several limitations of the current study. First, the cross-sectional nature of the data precludes strong causal inferences and the indirect pathways reported should not be interpreted as temporally-ordered mediation. The testing of indirect pathways is one approach to parsing out variability according to sound theory. The model tested provides a means by which we can examine a theoretically plausible representation of a multivariate system of interrelationships and pathways that, when included in the same equation, can advance knowledge by allowing variability to be parsed in meaningful ways that are not possible when these variables are examined in isolation. Second, although there is some good evidence and sound theory to suggest that, due to its explicit nature, sexual abuse would constitute the highest risk for aberrant development, we are unable to speak to whether or not the model we tested fits the data better for one specific type of abuse versus another. Sub-sample size limitations preclude multiple group SEM, however we did examine, on an experimental basis, zero-order correlations for sexually abused, physically abused and neglected adolescents separately. Although interrelationships among key constructs were generally stronger for the sexual abuse sub-sample, no obvious appreciable differences across sub-samples were found. Future research should be aimed at articulating (a) the unique roles that different forms of childhood maltreatment might play in the development of adolescent sexuality; and (b) how the experience of multiple types of maltreatment might exacerbate vulnerability for risky behavior. Third, we utilized a sample of victims with substantiated maltreatment. While this method constitutes rigor in terms of objective confirmation of maltreatment, it may inherently decrease sensitivity by excluding cases of unreported or unsubstantiated maltreatment and, accordingly, may limit generalizability. Fourth, we are unable to comment on how effects might be different for males as compared to females. Although there is some recent evidence to suggest that trajectories to risky sexual behaviors do not necessarily differ for males versus females (Jones et al., 2010), male sexual development has been largely understudied (Senn, Carey, & Vanable, 2008) and we recognize that moderation analyses would be preferable to simply controlling for gender. Such a design would require relatively large samples of both male and female adolescents in order to adequately describe the unique pathways to risky sexual behaviors experienced by both. Finally, we are unable to speak to emerging evidence that dysregulation in maltreated adolescents may be in part due to the dynamic interplay of multiple physiological systems. Studies have linked various childhood maltreatment and violence exposures to changes in the hypothalamic–pituitary–adrenal axis (Cicchetti & Rogosch, 2001), cardiovascular (Cooley-Quille, Boyd, Frantz, & Walsh, 2001), and sympathetic-adrenomedullary systems (El-Sheik, Cummings, & Goetsch, 1989), as well as dysfunctional coordination among multiple physiological systems (Gordis, Granger, Susman, & Trickett, 2008) all of which have implications for stress modulation, vigilance and action-oriented behaviors.
Female victims of childhood maltreatment exhibit a host of behaviors and attitudes with consistent deviations in normal sexual development such as early coital initiations, (Fergusson, Horwood, & Lynskey, 1997) more sexual partners, (Luster & Small, 1997) risky sexual behavior, (Chandy et al., 1996), and teen pregnancy (Noll et al., 2009). Although one longitudinal, prospective study reported how sexual preoccupation played a key role in later risky sexual behaviors (Noll et al., 2003), there has been scant empirical devotion to the mechanisms and processes by which sexual preoccupation operates to place victims at inordinate risk. These results suggest that the concept of psychological dysregulation may be a key element that should be included in future permutations of mechanistic research and in models of aberrant sexual development.
Funding
This article was supported in part by National Institutes of Health grant R01HD052533.
Conflicts of interest: None declared.
Acknowledgment
The authors would like to acknowledge Paul Succop, PhD., Mimi L. Boheme, and Amy S. Taylor, MFA, for their instructional elegance.
References
- Achenbach T. Integrative guide for the 1991 CBCL/4-18, YSR, and TRF profiles. Burlington, VT: University of Vermont; 1991. [Google Scholar]
- Barnes J E, Noll J G, Putnam F W, Trickett P K. Sexual and physical revictimization among victims of severe childhood sexual abuse. Child Abuse & Neglect. 2009;33(7):412–420. doi: 10.1016/j.chiabu.2008.09.013. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Bronfenbrenner U, Crouter A C. The evolution of environmental models in developmental research. In: Mussen P H, Kessen W, editors. Handbook of child psychology, (Vol.1): History, theory, methods. 4th ed. New York: Wiley; 1983. pp. 357–414. [Google Scholar]
- Caspi A, Lynam D, Moffitt T E, Silva P A. Unraveling girls' delinquency: Biological, dispositional, and contextual contributions to adolescent misbehavior. Developmental Psychology. 1993;29(1):19–30. [Google Scholar]
- Chandy J M, Blum R W, Resnick M D. Female adolescents with a history of sexual abuse: Risk outcome and protective factors. Journal of Interpersonal Violence. 1996;11(4):503–518. [Google Scholar]
- Cicchetti D, Rogosch F A. Diverse patterns of neuroendocrine activity in maltreated children. Development and Psychopathology. 2001;13(3):677–693. doi: 10.1017/s0954579401003145. [DOI] [PubMed] [Google Scholar]
- Cooley-Quille M, Boyd R C, Frantz E, Walsh J. Emotional and behavioral impact of exposure to community violence in inner-city adolescents. Journal of Clinical Child & Adolescent Psychology. 2001;30(2):199–206. doi: 10.1207/S15374424JCCP3002_7. [DOI] [PubMed] [Google Scholar]
- Crockett L J, Raffaelli M, Shen Y. Linking self-regulation and risk proneness to risky sexual behavior: Pathways through peer pressure and early substance use. Journal of Research on Adolescence. 2006;16(4):503–525. [Google Scholar]
- Crosby R A, DiClemente R J, Wingood G M, Cobb B K, Harrington K, Davies S L, Sionean C, Hook E W, III, Oh M K. HIV/STD-protective benefits of living with mothers in perceived supportive families: A study of high-risk African American female teens. Preventive Medicine. 2001;33(3):175–178. doi: 10.1006/pmed.2001.0868. [DOI] [PubMed] [Google Scholar]
- De Bellis M D, Kuchibhatla M. Cerebellar volumes in pediatric maltreatment-related posttraumatic stress disorder. Biological Psychiatry. 2006;60(7):697–703. doi: 10.1016/j.biopsych.2006.04.035. [DOI] [PubMed] [Google Scholar]
- Eisenberg N, Spinrad T L. Emotion-related regulation: Sharpening the definition. Child Development. 2004;75(2):334–339. doi: 10.1111/j.1467-8624.2004.00674.x. [DOI] [PubMed] [Google Scholar]
- El-Sheik M, Cummings E M, Goetsch V L. Coping with adults' angry behavior: Behavioral, physiological, and verbal responses in preschoolers. Developmental Psychology. 1989;25(4):490–498. [Google Scholar]
- Ferguson C J. An effect size primer: A guide for clinicians and researchers. Professional Psychology: Research and Practice. 2009;40(5):532–538. [Google Scholar]
- Fergusson D M, Horwood L J, Lynskey M T. Childhood sexual abuse, adolescent sexual behaviors and sexual revictimization. Child Abuse & Neglect. 1997;21(8):789–803. doi: 10.1016/s0145-2134(97)00039-2. [DOI] [PubMed] [Google Scholar]
- Fergusson D M, Horwood L J, Ridder E M. Show me the child at seven: The consequences of conduct problems in childhood for psychosocial functioning in adulthood. Journal of Child Psychology and Psychiatry. 2005;46(8):837–849. doi: 10.1111/j.1469-7610.2004.00387.x. [DOI] [PubMed] [Google Scholar]
- Finkelhor D, Browne A. The traumatic impact of child sexual abuse: A conceptualization. Annual Progress in Child Psychiatry & Child Development. 1986:632–648. [Google Scholar]
- Gordis E B, Granger D A, Susman E J, Trickett P K. Salivary alpha amylase-cortisol asymmetry in maltreated youth. Hormones and Behavior. 2008;53(1):96–103. doi: 10.1016/j.yhbeh.2007.09.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Houck C D, Nugent N R, Lescano C M, Peters A, Brown L K. Sexual abuse and sexual risk behavior: Beyond the impact of psychiatric problems. Journal of Pediatric Psychology. 2010;35(5):473–483. doi: 10.1093/jpepsy/jsp111. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Hutchinson M K, Jemmott J B, Jemmott L S, Braverman P, Fong G T. The role of mother-daughter sexual risk communication in reducing sexual risk behaviors among urban adolescent females: A prospective study. Journal of Adolescent Health. 2003;33(2):98–107. doi: 10.1016/s1054-139x(03)00183-6. [DOI] [PubMed] [Google Scholar]
- Johnston L D, O'Malley P M, Bachman J G, Schulenberg J E. Monitoring the Future national results on adolescent drug use: Overview of key findings, 2004 (p. 66). [NIH Publication No. 05-5726] Bethesda, MD: National Institute on Drug Abuse p; 2005. [Google Scholar]
- Jones D J, Runyan D K, Lewis T, Litrownik A J, Black M M, Wiley T, English DE, Proctor L J, Jones B L, Nagin D S. Trajectories of childhood sexual abuse and early adolescent HIV/AIDS risk behaviors: The role of other maltreatment, witnessed violence, and child gender. Journal of Clinical Child & Adolescent Psychology. 2010;39(5):667–680. doi: 10.1080/15374416.2010.501286. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Luster T, Small S A. Sexual abuse history and number of sex partners among female adolescents. Family Planning Perspectives. 1997;29(5):204–211. [PubMed] [Google Scholar]
- MacKinnon D P. Introduction to statistical mediation analysis. New York City: Taylor and Francis Group, LLC; 2008. [Google Scholar]
- Mason W A, Hitch J E, Kosterman R, McCarty C A, Herrenkohl T I, Hawkins J D. Growth in adolescent delinquency and alcohol use in realtion to young adult crime, alcohol use disorders, and risky sex: A comparison of youth from low- versus middle-income backgrounds. The Journal Child Psychology and Psychiatry. 2010;51(12):1377–1385. doi: 10.1111/j.1469-7610.2010.02292.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Mezzich A C, Tarter R E, Giancola P R, Kirisci L. The dysregulation inventory: A new scale to assess the risk for substance use disorder. Journal of Child and Adolescent Substance Abuse. 2001;10(4):35–43. [Google Scholar]
- Miller B C, Benson B, Galbraith K A. Family relationships and adolescent pregnancy risk: A research synthesis. Developmental Review. 2001;21(1):1–38. [Google Scholar]
- Murray K, Kochanska G. Effortful control: Factor structure and relation to externalizing and internalizing behaviors. Journal of Abnormal Child Psychology. 2002;30(5):503–514. doi: 10.1023/a:1019821031523. [DOI] [PubMed] [Google Scholar]
- Muthen L K, Muthen B O. Mplus user's guide. 5th ed. Los Angeles, CA: Muthen & Muthen; 2007. [Google Scholar]
- Noll J G, Shenk C E, Putnam K T. Childhood sexual abuse and adolescent pregnancy: A meta-analytic update. Journal of Pediatric Psychology. 2009;34(4):366–378. doi: 10.1093/jpepsy/jsn098. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Noll J G, Trickett P K, Putnam F W. A prospective investigation of the impact of childhood sexual abuse on the development of sexuality. Journal of Consulting & Clinical Psychology. 2003;71(3):575–586. doi: 10.1037/0022-006x.71.3.575. [DOI] [PMC free article] [PubMed] [Google Scholar]
- O'Donnell L, Stueve A, Wilson-Simmons R, Dash K, Agronick G, JeanBaptiste V. Heterosexual risk behaviors among urban young adolescent. Journal of Early Adolescence. 2006;26(1):87–109. [Google Scholar]
- Schluderman E, Schluderman S. Questionnaire for children and youth (CRPBI-30) Winnipeg: University of Manitoba Winnipeg; 1988. [Google Scholar]
- Schwarz J C, Barton-Henry M L, Pruzinsky T. Assessing child-rearing behaviors: A comparison of ratings made by mother, father, child, and sibling on the CRPBI. Child Development. 1985;56(2):462–479. [PubMed] [Google Scholar]
- Sedlak A J, Mettenburg J, Basena M, Petta I, McPherson K, Greene A, Spencer L. Fourth National Incidence Study of Child Abuse and Neglect (NIS–4): Report to Congress. Washington, DC: U.S. Department of Health and Human Services, Administration for Children and Families; 2010. [Google Scholar]
- Senn T E, Carey M P, Vanable P A. Childhood and adolescent sexual abuse and subsequent sexual risk behavior: Evidence from controlled, methodological critique, and suggestions for research. Clinical Psychology Review. 2008;28(5):711–735. doi: 10.1016/j.cpr.2007.10.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Shipman K, Zeman J, Penza S, Champion K. Emotion management skills in sexually maltreated and nonmaltreated girls: A developmental psychopathology perspective. Development and Psychopathology. 2000;12(1):47–62. doi: 10.1017/s0954579400001036. [DOI] [PubMed] [Google Scholar]
- Sobel M. Asymptotic confidence intervals for indirect effects in structural equation models. In: Leinhardt S, editor. Sociological Methodology 1982. 1982. pp. 290–312. [Google Scholar]
- Sprague J, Walker H. Early identification and intervention for youth with antisocial and violent behavior: Building safe and responsive schools: Perspectives on school discipline and school violence. Exceptional Children. 2000;66(3):367–379. [Google Scholar]
- Tarter R E, Kirisci L, Mezzich A, Cornelius J R, Pajer K, Vanyukov M, Gardner W, Blackson T, Clark D. Neurobehavioral disinhibition in childhood predicts early age at onset of substance use disorder. American Journal of Psychiatry. 2003;160(6):1078–1085. doi: 10.1176/appi.ajp.160.6.1078. [DOI] [PubMed] [Google Scholar]
- Thatcher D L, Clark D B. Adolescents at risk for substance use disorders: Role of psychological dysregulation, endophenotypes, and environmental influences. Alcohol Research and Health. 2008;31(2):168–176. [PMC free article] [PubMed] [Google Scholar]
- Trickett P K, Noll J G, Susman E J, Shenk C E, Putnam F W. Attenuation of cortisol across development for victims of sexual abuse. Development and Psychopathology. 2010;22(1):165–175. doi: 10.1017/S0954579409990332. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Wilson H W, Widom C S. An examination of risky sexual behavior and HIV in victims of child abuse and neglect: A 30-year follow-up. Health Psychology. 2008;27(2):149–158. doi: 10.1037/0278-6133.27.2.149. [DOI] [PubMed] [Google Scholar]
- Wingood G M, DiClemente R J. Child sexual abuse, HIV sexual risk, and gender relations of African-American women. American Journal of Preventative Medicine. 1997;13(5):380–384. [PubMed] [Google Scholar]