Skip to main content
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2015 Jun 1.
Published in final edited form as: Am J Drug Alcohol Abuse. 2014 Aug 20;41(3):230–236. doi: 10.3109/00952990.2014.939753

Risk factors of repeated infectious disease incidence among substance-dependent girls and boys court-referred to treatment

Maria E Pagano 1, Candice M Maietti 1, Alan D Levine 2
PMCID: PMC4336215  NIHMSID: NIHMS629021  PMID: 25140672

Abstract

Background

A small portion of Americans account for a disproportionate amount of the incidences of sexually transmitted infection observed over a short period of time. Studies with adults have begun to characterize this population, yet there is very little data on adolescent sexually transmitted infection repeaters (STIR). This study explores characteristics associated with STIR among 102 girls and 93 boys (aged 14–18) court-referred for residential treatment.

Methods

Background characteristics, substance use disorders, risky and interpersonal behaviors, and history of sexually transmitted infections were collected at intake using valid and reliable instruments. A negative binomial logistic regression was performed to determine the background, risky behaviors, and social patterns associated with adolescent STIR.

Results

Approximately two out of three adolescents (62%) did not use contraception the last time they had sex, and 15% had at least one sexually transmitted infection recorded in their medical chart. Sexually transmitted infection repeaters entered treatment with higher rates of cocaine abuse (13%) than youth without multiple infections (3%, p < 0.05). History of sexual abuse, having sex with a person who said no, higher exhibitionism, and social estrangement increased the odds of adolescent STIR. Main effects of exhibitionism and social estrangement on increased odds of STIR were more pronounced for sexually abused adolescents.

Conclusions

The findings suggest a need for incorporating HIV education during residential treatment to improve health outcomes and intervention strategies that further connectedness for youth and victims of sexual abuse.

Keywords: Adolescents, infection, risky sex, sexual abuse history, STD, substance use disorders

Introduction

Sexually transmitted infections, identified antecedents of HIV infections (1), are not normally distributed in the population. Much like healthcare utilization, a small portion of Americans account for a disproportionate amount of the incidences of sexually transmitted infection. Epidemiological studies indicate that individuals with repeat infections may account for up to 38% all infections observed over a short period of time (2). Individuals who acquire more than one non-viral infection within a specific period of time, referred to as sexually transmitted infection repeaters (STIR), may behave differently than those without repeat infections. For example, recent increases in alcohol legislative tax corresponded with reduced incidence among populations without multiple infections but had no effect on STIR (3).

STIR research to date has largely been conducted with adult males in outpatient settings. Risky behaviors associated with adult STIR include criminal activity, alcohol and other drug (AOD) use, and risky sexual behaviors (2,4). There is evidence that STIR is associated with greater alcohol but not drug use, and socio-sexuality in terms of higher rates of unprotected sex, infidelity, and short-term relationships (2,4,5). Egocentric interpersonal patterns are also associated with STIR, including: higher exhibitionism in the sense of seeking the limelight; exploitative behaviors that take advantage of others for selfish purposes; and lower other-regard defined as behaviors performed without focus on another’s needs and inclinations (68). Sexual abuse (SA) also elevates risk of STIR directly and indirectly by increasing STIR antecedent behaviors (911). Paradoxically, SA victims report greater number of partners, attention-seeking behaviors, pervasive emptiness, and social isolation (1214).

In the 21st century, youth aged 13–25 are the group with the highest rates of sexually transmitted infections. High rates of intersecting antecedent behaviors increase risk of adolescent STIR, including binge-drinking, risky sex while intoxicated, use of intravenous drugs, unsafe methods of tattooing, and jail episodes (1519). Ego-centric thinking is prominent during adolescence, which diminishes cognition of negative consequences to self and others and increases rationalization of AOD experimentation and unprotected sex. Given this landscape, the sparse data on adolescent STIR is surprising. The prior, pioneering STIR research has largely been conducted with adult males in outpatient settings. Few studies have sufficient sampling of girls and boys with criminal records, severe AOD use, and risky sexual activity to allow us to unravel the risky behaviors and social patterns that distinguish adolescent STIR. In an initial effort to fill the void in this area of research, this exploratory study reports on a sample of 103 girls and 93 boys court-referred to residential treatment. The primary goal was to determine the background, substance use disorders, risky behaviors, and interpersonal patterns associated with adolescent STIR. The influence of SA on risky and interpersonal behaviors associated with STIR was also explored. By understanding the ways that STIR relate to others, more targeted safe sex education approaches can be incorporated into care settings for high risk juveniles with substance dependency.

Methods

Procedures

All subjects were recruited as part of an ongoing investigation of 12-step affiliation among juvenile offenders court-referred to AOD treatment (20). Recruitment for this study was conducted from February 2007 to August 2009 at New Directions, the largest adolescent residential treatment provider in northeast Ohio. Inclusion criteria included: aged 14–18 years, English speaking, stable address and telephone, met diagnostic criteria for current AOD dependency, not currently suicidal/homicidal, and medical clearance verifying the absence of acute intoxications and withdrawal symptoms. Participants were admitted into AOD treatment one week after a three-day AOD detoxification (if required). In the week before admission date, participants were sent an information packet with an invitation letter to participate in the study. On the day of admission, participants were approached to participate and given a brief description of the study. Eligible participants signed statements of informed consent/assent. Participants were paid $25 for completed assessments. All procedures of this study were approved by the Case Medical Center Institutional Review Board for human investigation, and a Certificate of Confidentiality from the National Institute on Alcohol Abuse and Alcoholism was obtained. Additional information regarding the study design and methods is detailed elsewhere (21).

Participants

A total of 482 adolescents were admitted into residential treatment during the enrollment period of the study. All youth with scheduled admission appointments and those unscheduled occurring during regular weekday hours (08:00–18:00 h), one weekday evening (17:00–20:00 h), and one weekend day (09:00–17:00 h) were approached by research staff. Of the 211 patients approached, none were ineligible and 16 refused, resulting in an enrollment sample of 195 participants. Initial analyses investigated potential differences between patients not enrolled versus enrolled for whom baseline data and discharge status were available. There were no significant differences between patients not enrolled (n = 271), enrolled (n = 195), and refusals (n = 16) in terms of background characteristics, trauma history, juvenile justice involvement, AOD severity, years of illicit drug use, HIV/AIDs incidence, proportion of adolescent parents, prescribed psychotropic medication, and rates of treatment completion. There were more females in the enrollment sample (50%) that the population not enrolled (17%; p < 0.0001) due to the gender stratification of the study design.

Measures

Data were gathered at intake via rater-administered, semi-structured interviews, medical chart review, biomarkers, clinician reports, and youth self-reports. Interviews were conducted by trained, experienced clinical interviewers whose levels of certification ranged from bachelor’s level to doctor of medicine. Sixty-minute clinician-administered interviews were conducted at the scheduled admission appointment as part of clinical procedures. Ninety-minute baseline interviews were conducted with eligible and consenting participants within approximately one week following the admission interview (M = 7.5 days, SD = 1.2). All individuals involved in collecting data from subjects completed the National Institute of Health required courses on human subjects’ protection.

Background

Participant age, gender, minority status, single parent household, and parental education were assessed with the Health Care Data Form (22). SA history was assessed with the clinician-administered Childhood Sexual Abuse questionnaire (23).

Substance use disorders

Substance use disorders (current) were assessed using the Mini International Neuropsychiatric Interview Plus (MINI-Plus), a widely-used structured diagnostic interview for assessing substance abuse and dependency disorders and Axis I psychiatric disorders (24,25). Results of an inter-rater reliability study with 30 participants showed good to excellent inter-rater reliability for abuse and dependency disorders (κ = 0.63–0.96).

Risky behaviors

Felony history was assessed using adapted items from the Teen Treatment Services Review (26). Percent days abstinent (PDA) in the prior month was assessed using the rater-administered Time Line Follow Back Interview (27). Age of first consensual sex, condom use and AOD use at last intercourse, and sexual partner history were assessed with four Youth Risky Behavior Survey (YRBS) items (28), and one item from the Sexual Experiences Survey (29) indexed whether participants ever had sex with someone even after the person said no.

Interpersonal

Two subscales from the Narcissistic Personality Inventory (30,31) indexed exhibitionism (7 items, e.g. I like to show off my body), and exploitativeness (5 items, e.g. I find it easy to manipulate others). Using a YRBS item, volunteerism was indexed as the average number of hours/per month of charitable giving to others outside the home; a binary (Y/N) variable was created to indicate no volunteerism (“0 hours”) versus at least some volunteerism (e.g. 1–21 hours). Feeling detached or estranged from others in the past six months (Y/N) was indexed using an item from the Post Traumatic Stress Disorder Checklist (PCL-C; 32). Test-retest reliability analysis of the PCL-C item collected at the clinician-administered admission interview and baseline interview (M = 7.5 days) showed substantial agreement (κ = 0.61). Prior work has shown the utility of single item ratings of social behavior with AOD populations (33,34).

Sexually transmitted infections

Sexually transmitted infection incidences were recorded in medical physical exams and were reviewed by registered nurses at the time of admission. Admission procedures required clients to bring original copies of a medical physical exam performed in the month prior to intake. Female clients were also required to bring OB/GYN exam records of a pelvic exam and PAP smear conducted within the 12 months prior to intake. Clients were screened for Chlamydia, Herpes, genital warts, syphilis, gonorrhea, crabs, pelvic inflammatory disease, trichomoniasis, hepatitis B, C, and HIV. A binary variable was created to indicate STIR (2+ infections) versus non-STIR (0–1 infection).

Statistical analyses

Statistical analyses were performed using the procedures CORR, FREQ, and GENMOD of SAS Version 9.2 (SAS Institute Inc., Cary, NC, USA). Distributions of variables were first examined for normality. Positively skewed variables (PDA, number of felonies, lifetime sexual partners) were given a log-transformation, and the negatively skewed PDA variable received an arcsine transformation (e.g. 35). Fisher’s exact test for categorical variables and Wilcoxon Mann-Whitney rank-sum tests for continuous variables were used to test for differences between groups. To examine the association between explanatory variables and the probability of STIR, a fixed-effects zero-truncated Poisson model was specified with a logit link function and a Pearson correction for dispersion (36). Three explanatory variable sets (background, risky behaviors, interpersonal) were selected based on individual characteristics associated with sexually transmitted infection or AOD use (5,37,38). Initial descriptive analyses examined differences in explanatory variables between girls and boys with and without SA using the method of Tukey to preserve 1% pairwise comparisons between groups. Four interaction terms between SA and interpersonal variables were selected based on Tukey-Kramer comparisons with significance values greater than 90% (p < 0.01). A gender by SA interaction term was not included in the logit model given non-significant univariate comparisons and to preserve a recommended predictor/subject ratio (1:10–20). Because logit models yield superior estimates when all relevant covariates are included (39), model covariates included age, age of first sex, gender, minority status, parental marital status, and parental education. Preliminary analyses suggested that linear modeling was adequate, and the logit model showed a good fit, χ2(179) = 165.74, p = 0.59. Examination of the correlation matrix for explanatory variables found no correlation to exceed r = 0.2, and collinearity diagnostics indicated no problems. All p values were calculated with two-sided tests.

Results

Intake profile of sample

The intake profile of the sample is presented in Table 1. On average, participants were 16 years old (SD = 1.1) and in 10th grade (M = 10.1 years of education). Approximately half (48%) were male, from a single parent household (50%), and 27% had a parent with a bachelor’s degree or more. Approximately one in four youths (23%) entered treatment with a history of SA, which was significantly higher among girls (19%) than boys (4%; χ2 = 21.2, p < 0.0001). Youths used AOD on 6 out of 10 days in the month prior to treatment. The majority had a history of parole/probation (85%) and a felony record (87%), with an average of 2.7 committed felonies in the prior 2 years. Ninety-five percent of the sample was heterosexual, 1% was homosexual, and 4% was bisexual. All juveniles had a sexual partner history (M = 2.2 partners) beginning at age 14 (M = 14.3 years), and 6% had sex with someone even after the person said no. Most (62%) did not use a condom or use AOD (89%) the last time they had sexual intercourse. Approximately one in four subjects (26%) felt estranged from others. Rates of no volunteerism (48%) were comparable to normative youth attending high school in the region (52%; 40). Intake characteristics of the sample (Table 1) were comparable to other youth populations in residential treatment (4144). Additional information regarding the clinical profile of the sample at intake is detailed elsewhere (21,34).

Table 1.

Intake profile of boys and girls with and without sexual abuse (SA).

195 (100%) Boys (93, 48%)
Girls (102, 52%)
SA
8 (4%)
No SA
85 (44%)
SA
37 (19%)
No SA
65 (33%)
Background
 Age 16.2 (1.1) 17.1 (1.0)a 16.0 (1.1)a 16.0 (1.1)a 16.4 (1.0)a
 Minority 59 (30%) 4 (50%)a 30 (35%)a 7 (19%)a 18 (28%)a
 Single parent household 98 (50%) 4 (50%)a 37 (44%)a 16 (43%)a 41 (63%)a
 Parent with BA+ 53 (27%) 1 (13%)a 22 (26%)a 11 (30%)a 19 (29%)a
Risky behavior
 Prior felonies 2.7 (2.4) 3.0 (3.5)a 3.0 (2.4)a 2.6 (2.6)a 2.4 (2.0)a
 Percent days abstinent 0.4 (0.4) 0.4 (0.4)a 0.4 (0.4)a 0.3 (0.4)a 0.4 (0.4)a
 Substance use with sex 22 (11%) 0 (0%)a 8 (9%)a 5 (14%)a 9 (14%)a
 Had sex with person who said no 11 (6%) 0 (0%)a 5 (6%)a 1 (3%)a 5 (8%)a
 Age of first sex 14.3 (1.7) 14.0 (1.5)a 14.7 (1.6)a 14.3 (1.6)a 14.1 (1.7)a
 No. sexual partners 2.2 (1.2) 3.0 (1.0)b* 2.0 (1.3)a* 2.7 (1.0)b* 2.0 (1.2)a*
 Unprotected sex 120 (62%) 6 (75%)b* 40 (47%)a* 33 (90%)b* 41 (63%)a*
Interpersonal
 Exhibitionism 2.9 (1.6) 3.3 (1.5)a** 2.8 (1.6)b** 3.6 (1.7)a** 2.9 (1.8)b**
 Exploitation 2.2 (1.6) 3.8 (1.8)c* 2.4 (1.4)b* 2.3 (1.6)bc* 1.9 (1.4)a*
 No volunteerism 93 (48%) 6 (75%)b** 39 (46%)a** 26 (70%)b** 22 (34%)a**
 Estrangement 51 (26%) 2 (25%)b** 8 (9%)a,b** 28 (76%)d** 13 (20%)b,c**
*

p < 0.05,

**

p < 0.01;

Data are unadjusted means (SD) or n (%). Levels not sharing the same letter are significantly different based on Tukey-Kramer post hoc analysis. Groups sharing the same letter indicate that there are no significant differences between them.

Descriptive analysis of explanatory variables

Given the gender stratification of the study design and high overlap of female gender and SA, initial descriptive analyses examined differences between girls and boys with and without SA (Table 1). There were no significant differences between SA boys and girls, and no gender distinction of variables (see 398 for a detailed report of gender comparisons). However, SA boys and girls were distinguished from their peers without SA in terms of more sexual partners (M = 2.8 vs. M = 2.1, F = 4.7, p < 0.05), and higher rates of unprotected sex (87% vs. 54%, F = 8.2, p < 0.05), exhibitionism (M = 3.5 vs. M = 2.8, F = 6.2, p < 0.01), estrangement (67% vs. 14%, χ2 = 40.2, p < 0.0001), and no volunteerism (80% vs. 59%, χ2 = 6.9, p < 0.01). There was no SA main effect on exploitative scores due to the similarity of exploitation scores between SA girls (M = 2.3) and boys without SA (M = 2.4; Table 1). However, SA boys (M = 3.8) had significantly higher exploitation scores than non-abused girls (M = 1.9; F = 6.5, p < 0.05) and boys (M = 2.4, F = 5.1, p < 0.05).

Sexually transmitted incidence outcomes

Fifteen percent of the sample entered treatment with a history of at least one sexually transmitted infection, half of whom were STIR (8%). The most common infection was chlamydia (9%), followed by HPV (8%), gonorrhea (6%), genital herpes (3%), syphilis (3%), crabs (2%), and hepatitis C (2%). Initial comparisons between youth with no infection history (85%) and those with one infection (8%) found no significant differences with two exceptions; youth with one infection were more likely to be female (100% vs. 46%, respectively, χ2 = 11.1, p < 0.001) and used AOD the last time they had sex (43% vs. 9%, χ2 = 11.4, p < 0.001).

Factors associated with STIR

Initial comparisons explored current substance use disorders associated with adolescent STIR (Table 2). The majority of youth entered treatment with drug dependence (99%), and 61% met the criteria for alcohol dependence, as reported in detail elsewhere (21). The most common substance dependency disorder was marijuana (92%), followed by narcotics (30%) and hallucinogens (29%), with rates comparable to other youth populations in residential treatment (45,46). STIR had similar rates of substance abuse and dependency disorders as youth without multiple infections with exception to higher rates of cocaine abuse (13% vs. 3%, χ2 = 4.5, p < 0.05).

Table 2.

Substance use disorders associated with sexually transmitted infection repeaters (STIR).

Substance use disorder (current) Total
195 (100%)
Non-STIR
179 (92%)
STIR
16 (8%)
Alcohol
 Abuse 36 (18%) 35 (20%) 1 (6%)
 Dependency 118 (61%) 90 (89%) 11 (69%)
Drug
 Abuse 12 (6%) 11 (6%) 1 (6%)
 Dependency 193 (99%) 178 (99%) 15 (94%)
Marijuana
 Abuse 18 (9%) 17 (10%) 1 (6%)
 Dependency 179 (92%) 165 (92%) 14 (88%)
Narcotics
 Abuse 22 (11%) 20 (11%) 2 (13%)
 Dependency 58 (30%) 54 (30%) 4 (25%)
Hallucinogen
 Abuse 16 (8%) 16 (9%) 0 (0%)
 Dependency 57 (29%) 51 (29%) 6 (38%)
Cocaine
 Abuse 8 (4%) 6 (3%) 2 (13%)*
 Dependency 50 (26%) 48 (27%) 2 (13%)
Stimulants
 Abuse 11 (6%) 9 (5%) 2 (13%)
 Dependency 49 (25%) 46 (26%) 3 (19%)
Inhalants
 Abuse 5 (3%) 5 (3%) 0 (0%)
 Dependency 11 (6%) 11 (6%) 0 (0%)
Tranquilizers
 Abuse 14 (7%) 14 (8%) 0 (0%)
 Dependency 39 (20%) 35 (20%) 4 (25%)
*

p < 0.05.

The logit model next examined background, risky behaviors, and interpersonal factors associated with STIR (Table 3). Controlling for other variables in the model, the predicted odds of STIR for SA victims were 7 times the odds for youth without SA. As shown in Table 3, other significant factors increasing the odds of STIR were feeling estranged from others, higher exhibitionism, and having sex with a person who said no. When interaction terms between SA and interpersonal variables were added to the logit model, results showed pronounced effects of exhibitionism and estrangement on increased odds of STIR for youth with SA (Table 3).

Table 3.

Clinical factors associated with sexually transmitted infection repeaters (STIR).

β SE 1 LR χ2 95% CI P
Background
 Age 0.41 0.20 4.02 [0.00, 0.82] 0.06
 Male −1.38 0.82 2.84 [−3.11, 0.21] 0.10
 Minority −0.78 0.41 3.75 [−1.59, 0.01] 0.20
 Single parent household 0.19 0.40 0.21 [−0.61, 0.98] 0.64
 Parent with BA+ 0.63 0.50 1.62 [−0.28, 1.70] 0.20
 Sexual abuse (SA) 2.00 1.89 6.85 [1.26, 3.87] 0.01**
Risky behavior
 Prior felonies 0.15 0.41 0.14 [−0.65, 0.96] 0.70
 Percent days abstinent 0.55 0.59 0.89 [−0.60, 1.71] 0.35
 Substance use with sex 0.44 0.32 1.24 [−0.09, 2.35] 0.23
 Number of sexual partners 0.34 0.31 1.14 [−0.28, 0.96] 0.29
 Had sex with person who said no 0.40 0.22 3.15 [0.49, 2.12] 0.01**
 Unprotected sex 0.38 0.49 0.60 [−0.58, 1.34] 0.44
Interpersonal
 Exhibitionism 1.55 0.65 4.51 [0.02, 2.65] 0.03*
 Exploitation 0.29 0.23 1.46 [−0.18, 0.75] 0.23
 No volunteerism 0.35 0.30 1.36 [−0.24, 0.95] 0.24
 Estrangement 1.60 0.75 4.49 [0.12, 3.08] 0.03*
Interactions
 SA* Exhibitionism −0.60 0.25 2.59 [−0.35, −0.02] 0.03*
 SA* Exploitation 0.27 0.26 0.86 [−0.85, 0.29] 0.31
 SA* No volunteerism 0.30 0.37 0.63 [−0.34, 1.21] 0.43
 SA* Estrangement −1.32 1.01 2.78 [−3.30, −0.01] 0.04*
*

p < 0.05,

**

p < 0.01;

1

LR, likelihood ratio.

Discussion

Results of this study indicate distinctive differences between youth with and without multiple STIs. Fifteen percent of juveniles entered AOD treatment with a sexually transmitted infection, approximately half of whom were STIR. The rate of infection (15%) is consistent with other young adult populations with AOD dependency (4749) and less severe AOD use (19,50), but double the rate of normative youth with no AOD history from the same region (40,51). Youth with one infection were similar to peers with no infection with exception to a greater proportion of girls and higher rates of substance-involved sex. Anatomical and physiological differences may increase girls’ risk of infection; male genitalia are less susceptible to infection sequelae (52) and become impaired from intoxication, which reduces male exposure to infection transmission (5355). Results suggest gender-specific sex education approaches to reinforce the female vulnerability of sexually transmitted infection acquisition and negative impact of AOD use.

Risk factors other than gender and AOD-involved sex appear to drive the behavior of adolescent STIR. While indistinguishable in terms of criminal activity, percent days abstinent, and abuse and dependency of most substances, STIR were more likely to abuse cocaine, a drug associated with increased hypersexuality and risk of infection acquisition (56). Other differences that distinguished adolescent STIR point to themes of social disconnectedness and low other-regard. The higher rate of having sex with a person who said no associated with adolescent STIR can be understood through AA’s theorized trait of self-centeredness carried to the extreme (e.g. “My whole life seemed to be centered around doing what I wanted to do without regard for the wishes or privileges of others” (57). Another interpretation points to genetic causes with growing evidence of addicts’ blunted responsivity to others from neuroimaging genetic research (58). Yet the higher levels of estrangement and exhibitionism associated with STIR suggests a deficit in social connectedness despite attention-seeking behaviors. This dichotomy is well synthesized in 12-step literature. “Almost without exception, alcoholics are tortured by loneliness… that we didn’t quite belong. Either we were shy or we were apt to be noisy and craving attention and companionship” (59). As opposed to psychopaths, study findings suggest that STIR are innately social beings (60). Social skills deficits are implicated in the social anxiety-problematic drinking that this report expands to include infectious disease.

Sexual abuse appears to further magnify the impact of estrangement and exhibitionism on increased risk of STIR. SA youth had more sexual partners, higher rates of unprotected sex, estrangement, less volunteerism, and higher levels of exhibitionism than their peers without SA. The loneliness often described by SA victims (10,13) may drive higher rates of attention-seeking behaviors in attempts for meaningful connections that they may fear would be broken by assertion of contraceptive use. While rates of SA were higher among girls than boys, the impairment associated with SA was similar for both genders. However, there was evidence to suggest higher exploitative behaviors among SA boys. Future research is warranted with higher sampling of SA males to determine whether exploitative behaviors are pronounced among SA males that increases their risk of STIR and transmission. Nonetheless, the interpersonal patterns associated with STIR that are pronounced among SA victims have implications for STI/HIV interventions in addressing how STIR relate to others. Longitudinal investigations with treatment-seeking adults suggests that helping others may shift an object-orientation of others to increased other-oriented awareness and interest (34). Prospective study of youth service participation in 12-step contexts is needed to determine the impact of this activity on rehabilitated behaviors and social interactions.

Some limitations of our study merit attention. First, contextual information of infection acquisition was not assessed, and it is possible that multiple infections accrued from repeated unprotected sex with an infected partner. This information would be useful to collect particularly among SA victims to discern if infection acquisition and high rates of unprotected sex stem from issues of self-esteem, insensitivity, or mistaken invincibility. Second, data were gathered concurrently at intake and causal ordering cannot be inferred. Prospective studies are needed to discern the course of youth behaviors in relation to infectious disease. Third, findings may not generalize to youth populations with less severe AOD use and without judicial involvement. However, rates of infection, SA, risky sex, and social patterns are comparable to young adult populations with less severe AOD use and related problems (31,42,50,61). Despite these limitations, our results extend previous work conducted largely with adult Caucasian males to a mixed gender sample of juveniles with high representation of minority youth. Data were collected with valid instruments that employed multiple informants and methods (i.e. semi-structured interviews, medical records, clinician assessments, youth reports).

Conclusions

Results implicate the incorporation of assertiveness training, condom skills, and HIV education into gender-specific trauma therapies during treatment to improve youth skills in relating to others. Increased awareness of how their actions impact others may further other-oriented behaviors that are associated with decreased risk of infection acquisition and AOD relapse (20,51). Helping youth get engaged service in 12-step contexts may prevent acquisition and transmission of new infections by reducing AOD use and substance-involved risky sex while furthering social connectedness and consideration of others.

Acknowledgments

Portions of results of this paper were presented at the 36th annual meeting of the Research Society on Alcoholism (RSA) in Orlando, FL, USA. This research was supported in part by grants awarded to Dr Pagano from the National Institute on Alcohol Abuse and Alcoholism (NIAAA, K01 AA015137) and the John Templeton Foundation (#13591). The NIAAA and the John Templeton Foundation had no further role in study design, in the data collection and analysis, writing of the report, or decision to submit the paper for publication. The authors wish to thank New Directions treatment staff and participants in this study.

Footnotes

Declaration of interest

The authors report no conflicts of interest. The authors alone are responsible for the content and writing of this paper.

References

  • 1.Chan YF, Passetti LL, Garner BR, Lloyd JJ, Dennis ML. HIV risk behaviors: risky sexual activities and needle use among adolescents in substance abuse treatment. AIDS Behav. 2011;15:114–124. doi: 10.1007/s10461-010-9702-3. [DOI] [PubMed] [Google Scholar]
  • 2.Leichliter JS, Ellen JM, Gunn RA. STD repeaters: implications for the individual and STD transmission in a population. In: Aral SO, Douglas JM, editors. Behavioral Interventions for Prevention and Control of Sexually Transmitted Diseases. New York: Springer Science Business Media, LLC; 2007. pp. 354–373. [Google Scholar]
  • 3.Wagenaar A. Alcohol policy interventions reduce STD cases: the 2009 Illinois on alcohol excise tax increase. Alcohol Clin Exp Res. 2013;37:208–209. [Google Scholar]
  • 4.Jackson-Walker S, Nitz K. Depression and behavior problems in urban adolescents: risk factors for recurrent sexually transmitted diseases. J Adolesc Health. 1996;18:270–275. [Google Scholar]
  • 5.Bjekic M, Vlajinac H, Marinkovic J. Behavioural and socal characteristics of subjects with repeated sexually transmitted diseases. Acta Derm Venereol. 2000;80:44–47. [PubMed] [Google Scholar]
  • 6.Bjekic M, Lecic-Tosevski D, Vlajinac H, Marinkovic J. Personality dimensions of sexually transmitted disease repeaters assessed with the Millon Clinical Multiaxial Inventory. J Eur Acad Dermatol Venereol. 2002;16:63–65. doi: 10.1046/j.1468-3083.2002.00367.x. [DOI] [PubMed] [Google Scholar]
  • 7.Bjeckic M, Valjjnac H, Marinkovic J. Sociopathologic behavior and repeated infection with venereal disease. Srp Arh Celok Lek. 1999;127:254–257. [PubMed] [Google Scholar]
  • 8.Roth G. Perceived parental conditional regard and autonomy support as predictors of young adults’ self- versus other-oriented prosocial tendencies. J Personality. 2008;76:513–533. doi: 10.1111/j.1467-6494.2008.00494.x. [DOI] [PubMed] [Google Scholar]
  • 9.Senn TE, Carey MP, Vanable PA, Coury-Doniger P, Urban M. Characteristics of sexual abuse in childhood and adolescence influence sexual risk behavior in adulthood. Arch Sex Behav. 2007;36:637–645. doi: 10.1007/s10508-006-9109-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Beitchman JH, Zucker KJ, Hood JE, DaCosta GA, Akman D, Cassavia E. A review of the long-term effects of child sexual abuse. Child Abuse Negl. 1992;16:101–118. doi: 10.1016/0145-2134(92)90011-f. [DOI] [PubMed] [Google Scholar]
  • 11.Zierler S, Feingold L, Laufer D, Velentgas P, Kantrowitcz-Gordon I, Mayer K. Adult survivors of childhood sexual abuse and subsequent risk of HIV infection. Am J Public Health. 1991;81:572–575. doi: 10.2105/ajph.81.5.572. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.National Institute of Mental Health (NIMH) Multisite HIV Prevention Trial Group. A test of factors mediating the relationship between unwanted sexual activity during childhood and risky sexual practices among women enrolled in NIMH multisite HIV prevention trial. Women & Health. 2001;33:163–180. doi: 10.1300/j013v33n01_10. [DOI] [PubMed] [Google Scholar]
  • 13.Browne A, Finkelhor D. Impact of child sexual abuse. A review of the research. Psychol Bull. 1986;99:66–77. [PubMed] [Google Scholar]
  • 14.Thompson NJ, Potter JS, Sanderson CA, Maibach EW. The relationship of sexual abuse and HIV risk behaviors among heterosexual adult female STD patients. Child Abuse Negl. 1997;21:149–156. doi: 10.1016/s0145-2134(96)00140-8. [DOI] [PubMed] [Google Scholar]
  • 15.Baljunas D, Rehm J, Irving H, Shuper P. Alcohol consumption and risk of incident human immunodeficiency virus infection: a meta-analysis. Int J Public Health. 2010;55:159–166. doi: 10.1007/s00038-009-0095-x. [DOI] [PubMed] [Google Scholar]
  • 16.Molitor F, Truax SR, Ruiz JD, Sun RK. Association of methamphetamine use during sex with risky sexual behaviors and HIV infection among non-injection drug users. West J Med. 1998;168:93–97. [PMC free article] [PubMed] [Google Scholar]
  • 17.Shuper PA, Joharchi N, Irving H, Rehm J. Alcohol as a correlate of unprotected sexual among people living with HIV/AIDS: review and meta-analysis. AIDS Behav. 2009;13:1021–1036. doi: 10.1007/s10461-009-9589-z. [DOI] [PubMed] [Google Scholar]
  • 18.Miller JW, Naimi TS, Brewer RD, Jones SE. Binge drinking and associated health risk behaviors among high school students. Pediatrics. 2007;119:76–85. doi: 10.1542/peds.2006-1517. [DOI] [PubMed] [Google Scholar]
  • 19.Sosman J, MacGowan R, Margolis A, Gaydos CA, Eldridge G, Moss S, Flanigan T, et al. Sexually transmitted infections and hepatitis in men with a history of incarceration. Sex Transm Dis. 2011;38:634–639. doi: 10.1097/OLQ.0b013e31820bc86c. [DOI] [PubMed] [Google Scholar]
  • 20.Pagano ME, Kelly JF, Scur MD, Ionescu RA, Stout RL, Post SG. Assessing youth participation in AA-related helping: validity of the Service to Others in Sobriety (SOS) questionnaire in an adolescent sample. Am J Addict. 2013;22:60–66. doi: 10.1111/j.1521-0391.2013.00322.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Kelly JF, Pagano ME, Stout RL, Johnson SM. Influence of religiosity on 12-step participation and treatment response among substance-dependent adolescents. J Stud Alcohol Drug. 2011;72:1000–1011. doi: 10.15288/jsad.2011.72.1000. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Zywiak W, Larson MJ, Lawson C, Rubin A, Zwick W, Stout RL. Test-retest reliability of the health care data form. Alcohol Clin Exp Res. 1999;23:84–85. [Google Scholar]
  • 23.Martin J, Anderson J, Romans S, Mullen P, O’Shea M. Asking about child sexual abuse: methodological implications of a two-stage survey. Child Abuse Negl. 1993;42:383–392. doi: 10.1016/0145-2134(93)90061-9. [DOI] [PubMed] [Google Scholar]
  • 24.Sheehan DV, Lecrubier Y, Sheehan KH, Amorim P, Janavs J, Weiller E, et al. The Mini-International Neuropsychiatric Interview (MINI): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry. 1998;59:22–33. [PubMed] [Google Scholar]
  • 25.Humeniuk R, Ali R, Babor TF, Farrell M, Formigoni ML, Jittiwutikarn J, et al. Validation of the alcohol, smoking, and substance involvement screening test (ASSIST) Addiction. 2008;103:1039–1047. doi: 10.1111/j.1360-0443.2007.02114.x. [DOI] [PubMed] [Google Scholar]
  • 26.Kaminer Y, Blitz C, Burleson JA, Sussman J. The Teen Treatment Services Review (T-TSR) J Subst Abuse Treat. 1998;15:291–300. doi: 10.1016/s0740-5472(97)00187-6. [DOI] [PubMed] [Google Scholar]
  • 27.Donohue B, Azrin NH, Strada MJ, Silver NC, Teichner G, Murphy H. Psychometric evaluation of self- and collateral timeline follow-back reports of drug and alcohol use in a sample of drug-abusing and conduct disordered adolescents and their parents. Psychol Addict Behav. 2004;18:184–189. doi: 10.1037/0893-164X.18.2.184. [DOI] [PubMed] [Google Scholar]
  • 28.Kann L, Brener ND, Warren CW, Collins JL, Gioviono GA. An assessment of the effect of data collection setting on the prevalence of health risk behaviors among adolescents. J Adolesc Health. 2002;31:327–335. doi: 10.1016/s1054-139x(02)00343-9. [DOI] [PubMed] [Google Scholar]
  • 29.Koss MP, Abbey A, Campbell R, Cook S, Norris J, Testa C, et al. Revising the SES: a collaborative process to improve assessment of sexual aggression and victimization. Psychol Women Q. 2007;31:357–370. [Google Scholar]
  • 30.Raskin R, Terry H. A principal-components analysis of the Narcissistic Personality Inventory and further evidence of its construct validity. J Pers Soc Pychol. 1998;54:890–902. doi: 10.1037//0022-3514.54.5.890. [DOI] [PubMed] [Google Scholar]
  • 31.Del Rosario PM, White RM. The Narcissistic Personality Inventory: test-retest stability and internal consistency. Pers Individ Dif. 2005;39:1075–1081. [Google Scholar]
  • 32.Blanchard EB, Jones-Alexander J, Buckley TC, Forneris CA. Psychometric properties of the PTSD checklist (PCL) Behav Res Ther. 1996;34:669–673. doi: 10.1016/0005-7967(96)00033-2. [DOI] [PubMed] [Google Scholar]
  • 33.Murphy DA, Lamonda KH, Carney JK, Duncan P. Relationships of a brief measure of youth assets to health-promoting and risk behaviors. J Adolesc Health. 2004;34:184–191. doi: 10.1016/j.jadohealth.2003.05.004. [DOI] [PubMed] [Google Scholar]
  • 34.Pagano ME, White WL, Kelly JF, Stout R, Tonigan JS. The 10-year course of Alcoholics Anonymous participation and long-term outcomes: a follow-up study of outpatient subjects in Project MATCH. Subst Abuse. 2013;34:51–59. doi: 10.1080/08897077.2012.691450. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Tabachnick BG, Fidell L. Using multivariate statistics. 4. New York: HarperCollins; 2011. [Google Scholar]
  • 36.Allison PD. Fixed effects regression methods for longitudinal data using SAS. Cary, NC: SAS Press; 2005. [Google Scholar]
  • 37.Carter RR, Johnson SM, Exline JJ, Post SG, Pagano ME. Addiction and “Generation Me”. Alcohol Treat Q. 2012;30:163–178. doi: 10.1080/07347324.2012.663286. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Johnson SM, Carter RR, Pagano ME. Sexual abuse, risky sexual behaviors, and sexual beliefs among substance-dependent adolescents court-referred to residential treatment. Alcohol Clin Exp Res. 2011;35:12–13. [Google Scholar]
  • 39.Allison PD. Logistic regression using the SAS system. Cary, NC: SAS Press; 2003. [Google Scholar]
  • 40.Ohio Center for Health Promotion Research (OCHPR) Cleveland Metropolitan School District Youth Risk Behavior Survey High School Report. 2009. [Google Scholar]
  • 41.Hawke JM, Jainchill N, De Leon G. The prevalence of sexual abuse and its impact on the onset of drug use among adolescents in therapeutic community drug treatment. J Child Adolesc Subst Abuse. 2000;9:35–49. [Google Scholar]
  • 42.Rounds-Bryant JL, Kristiansen PL, Hubbard RL. Drug abuse treatment outcome study of adolescents: a comparison of client characteristics and pretreatment behaviors in three treatment modalities. Am J Drug Alcohol Abuse. 1999;25:573–591. doi: 10.1081/ada-100101880. [DOI] [PubMed] [Google Scholar]
  • 43.Bailey SL, Pollock NK, Martin CS, Lynch KG. Risky sexual behaviors among adolescents with alcohol use disorders. J Adolesc Health. 1999;25:179–181. doi: 10.1016/s1054-139x(99)00023-3. [DOI] [PubMed] [Google Scholar]
  • 44.Calhoun GB, Glaser BA, Stefurak T, Bradshaw CP. Preliminary validation of the narcissistic personality inventory-juvenile offender. Int J Offend. 2000;44:564–580. [Google Scholar]
  • 45.Deykin EY, Buka SL. Suicidal ideation and attempts among chemically-dependent adolescents. Am J Public Health. 1994;84:634–639. doi: 10.2105/ajph.84.4.634. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Godley MD, Godley SH, Dennis ML, Funk R, Passetti LL. Preliminary outcomes from the assertive continuing care experiment for adolescents discharged from residential treatment. J Subst Abuse Treat. 2002;23:21–32. doi: 10.1016/s0740-5472(02)00230-1. [DOI] [PubMed] [Google Scholar]
  • 47.Broussard D, Leichliter JS, Evans A, Kee R, Vallury V, McFarlane M. Screening adolescents in a juvenile detention center for gonorrhea and chlamydia: prevalence and reinfection rates. Prison J. 2002;82:8–19. [Google Scholar]
  • 48.Jenkins SC, Simmons PS. Survey of genitourinary organisms in a population of sexually active adolescent males admitted to a chemical dependency unit. J Adolesc Health Care. 1990;11:223–226. doi: 10.1016/0197-0070(90)90352-3. [DOI] [PubMed] [Google Scholar]
  • 49.Tapert SF, Aarons GA, Sedlar GR, Brown SA. Adolescent substance use and sexual risk-taking behavior. J Adolesc Health. 2001;28:181–189. doi: 10.1016/s1054-139x(00)00169-5. [DOI] [PubMed] [Google Scholar]
  • 50.Liebschutz JM, Finley EP, Braslins PG, Christiansen D, Horton NJ, Samet JH. Screening for sexually transmitted infections in substance abuse treatment programs. Drug Alcohol Depend. 2003;70:93–99. doi: 10.1016/s0376-8716(02)00361-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Pagano ME, Swaringen S, Frank SH. Low-regard and adolescent addiction. Alcohol Clin Exp Res. 2014;38:270–271. [Google Scholar]
  • 52.Aral SO, Hawkes S, Biddlecom A, Padian N. Disproportionate impact of sexually transmitted diseases on women. Emerging Infect Dis. 2004;10:2029–2030. doi: 10.3201/eid1011.040623_02. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Cocores JA, Miller NS, Potlash AC, Gold MS. Sexual dysfunction in abusers of cocaine and alcohol. Am J Drug Alcohol Abuse. 1988;14:169–173. doi: 10.3109/00952999809001544. [DOI] [PubMed] [Google Scholar]
  • 54.Dachille G, Lamuraglia M, Leone M, Pagliarulo A, Palasciano G, Salerno GM, Ludivico GM. Erectile dysfunction and alcohol intake. Urol Int. 2008;75:170–176. [PubMed] [Google Scholar]
  • 55.Viiavasenan ME. Alcohol and sex. New Zealand Med J. 1981;93:18–20. [PubMed] [Google Scholar]
  • 56.Kenny JW, Reinholtz C, Angelini PJ. Sexual abuse, sex before age 16, and high risk behaviors of young females with sexually transmitted diseases. J Obstet Gynecol Neonatal Nursing. 1998;27:54–63. doi: 10.1111/j.1552-6909.1998.tb02591.x. [DOI] [PubMed] [Google Scholar]
  • 57.Big Book. (4) 2001 Alcoholics Anonymous.
  • 58.Cservenka A, Nagel BJ. Differences in brain activity during affective processing and emotional cognitive control in youth with and without a family history of alcoholism. Alcohol Clin Exp Res. 2013;37:210–211. [Google Scholar]
  • 59.Twelve steps and twelve traditions. 1981. Alcoholics Anonymous. [Google Scholar]
  • 60.Enrenreich B. Dancing in the streets: a history of collective joy. New York: Metropolitan Books; 2007. pp. 301–320. [Google Scholar]
  • 61.Kilpatrick D, Ruggiero K, Acierno R, Saunders B, Resnick H, Best C. Violence and risk of PTSD, major depression, substance abuse/dependence, and comorbidity. J Consult Clin Psychol. 2003;71:692–700. doi: 10.1037/0022-006x.71.4.692. [DOI] [PubMed] [Google Scholar]

RESOURCES