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Predictors of Change in HIV Risk Factors for Adolescents Admitted to Substance Abuse Treatment Passetti, L. L., Garner, B. R., Funk, R., Godley, S. H.,

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Presentation on theme: "Predictors of Change in HIV Risk Factors for Adolescents Admitted to Substance Abuse Treatment Passetti, L. L., Garner, B. R., Funk, R., Godley, S. H.,"— Presentation transcript:

1 Predictors of Change in HIV Risk Factors for Adolescents Admitted to Substance Abuse Treatment Passetti, L. L., Garner, B. R., Funk, R., Godley, S. H., & Godley, M. D. Chestnut Health Systems JMATE 2008

2 Acknowledgements Preparation of this presentation was supported by funding from the following sources: –Center for Substance Abuse Treatment (Strengthening Communities-Youth project grant no. TI 13356) –National Institute on Drug Abuse (grant no. DA ) –National Institute on Alcohol Abuse and Alcoholism (grant no. AA ).

3 HIV Infection in Adolescents Estimated 5,322 adolescents living with AIDS in the U.S. –46.7% increase since 2001 (CDC, 2005) Average of 10 years from HIV infection to development of AIDS –Many young adults likely infected as teenagers (National Institute of Allergy and Infectious Disease, 2000)

4 HIV Risk in Adolescents Presenting to Substance Abuse Treatment (Ammon et al., 2005; Deas-Nesmith et al., 1999; Jainchill et al., 1999; Malow et al., 2001; Tapert et al., 2001) Sexual activity at early age Injection drug use Unprotected sex Sex with injection drug users Multiple partners Victimization Sex under the influence Multiple risk behaviors

5 Purpose For adolescents admitted to substance abuse treatment, identify variables that most strongly predict the transition from: Presence of any HIV risk factor Absence of HIV risk factors Follow-up InterviewNext Follow-up Interview

6 Sample 283 adolescents –Strengthening Communities - Youth (SCY) n=113 Admitted to outpatient substance abuse treatment –Assertive Continuing Care (ACC-2) n=170 Admitted to residential substance abuse treatment

7 Participant Characteristics at Intake (n=283) Average Age: 16 Caucasian: 70% Male: 65% Main substances of choice: marijuana, alcohol Average years of education: 9 In school: 83% Employed: 39% Involved with criminal justice system: 78%

8 Measurement Global Appraisal of Individual Needs (GAIN) –Administered at intake and quarterly follow-up intervals 3, 6, 9, and 12 months post-intake for SCY 3, 6, 9, and 12 months post-discharge for ACC-2 –Follow-up rates ranged from 90% to 96%

9 Analysis Step One - Univariate logistic regression –Identify variables that predict the transition from: (i.e., from 3 to 6 months, 6 to 9 months, 9 to 12 months) Presence of any HIV risk factor Absence of HIV risk factors Follow-up InterviewNext Follow-up Interview

10 Analysis Step Two - Multivariate mixed nominal regression –Identify strongest predictors of transition –Enter significant predictors from univariate analysis simultaneously

11 Unit of Analysis 283 adolescents –477 observations in which adolescents reported at least one risk factor for HIV infection

12 Predictors Intake Variables –Age –Gender –Minority (Yes/No) –Years of education –Symptoms of internalizing disorder (Yes/No) –Symptoms of externalizing disorder (Yes/No)

13 Predictors Follow-up Variables (During the past 90 days) –In school (Yes/No) –Employed (Yes/No) –Involved with the criminal justice system (Yes/No) –Substance Frequency Scale (SFS) – 8 items –Substance Problem Scale (SPS) – 16 items –Recovery Environment Risk Index (RERI) – 13 items

14 Predictors Follow-up Variables (During the past 90 days) –Social Risk Index (SRI) – 6 items –Treatment Motivation Index (TMI) – 5 items –Treatment Resistance Index (TRI) – 4 items –Problem Orientation Scale (POS) – 5 items –Weeks in substance abuse treatment –Weeks in mental health treatment –Weeks in a controlled environment

15 Outcome Measure –HIV Risk Status (Yes/No) Endorsed any of the following HIV risk factors during the past 90 days: –Needle use –Sex with a needle user –Sex while adolescent or partner was high on alcohol or drugs –Unprotected sex –Multiple sex partners (two or more) –Trading sex for drugs/money –Victimized (sexually, physically, or emotionally)

16 Transition Period: 3 to 6 months Presence (n = 117) Presence Absence HIV Risk Status: 3 Months HIV Risk Status: 6 Months 67% 33%

17 Transition Period: 6 to 9 months Presence Absence HIV Risk Status: 6 Months HIV Risk Status: 9 Months 71% 29% Presence (n = 174)

18 Transition Period: 9 to 12 months Presence Absence HIV Risk Status: 9 Months HIV Risk Status: 12 Months 61% 39% Presence (n = 186)

19 Results Univariate Logistic Regression Odds Ratio95% CIp = Intake Variables Age0.83(0.71, 0.99)0.03 Female0.72(0.48, 1.07)0.11 Minority0.99(0.65, 1.50)0.96 Years of Education 0.82(0.71, 0.94)0.01 Symptoms of internalizing disorder 0.80(0.55, 1.18)0.26 Symptoms of externalizing disorder 1.37(0.90, 2.08)0.15

20 Results Univariate Logistic Regression Odds Ratio95% CIp = Follow-up Variables In School1.15(0.77, 1.71)0.50 Employed0.87(0.59, 1.27)0.47 Involved with CJS1.82(0.87, 1.90)0.22 Substance Frequency Scale 0.83(0.69, 0.98)0.03 Substance Problem Scale 0.81(0.68, 0.97)0.21

21 Results Univariate Logistic Regression Odds Ratio95% CIp = Follow-up Variables Recovery Environment Risk Index 0.82(0.67, 0.99)0.03 Social Risk Index0.79(0.65, 0.97)0.02 Treatment Motivation Index1.00(0.82, 1.23)0.99 Treatment Resistance Index0.79(0.66, 0.95)0.01 Problem Orientation Scale0.90(0.73, 1.09)0.28 Weeks in SA Treatment1.10(1.06, 1.51)0.00 Weeks in MH Treatment1.02(0.99, 1.04)0.07 Weeks in a Controlled Environment 1.09(0.99, 1.19)0.06

22 Results Multivariate Mixed Nominal Regression β Odds Ratio95% CIp = Intercept1.65 Age (0.63, 1.00)0.05 Recovery Environment Risk Index (0.62, 0.98)0.04 Treatment Resistance Index (0.64, 0.98)0.03

23 Conclusions In this sample, the strongest predictors of transitioning to the absence of any HIV risk factors were: –Younger age –Lower recovery environment risk –Lower treatment resistance

24 Strengths –Few studies examining change in HIV risk factors over time –Adolescents in OP and residential treatment –High follow-up rates

25 Limitations –Self-report –No measure of HIV risk interventions received during or after treatment

26 Implications Interventions with this population may be developed and tested that are tailored by: Age Level of risk in the recovery environment Level of treatment resistance

27 Implications While 1/3 of the analyzed transitions demonstrated improvement in HIV risk, 2/3 represented the same or greater levels of risk Longer and/or repeated assessments and interventions may be required to initiate and sustain a reduction in HIV risk


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