Examining the decay of HIV risk reduction outcomes following a community-friendly intervention targeting injection drug users in treatment ([dagger]).
Keywords--community-friendly interventions, HIV risk reduction, injection drug use, outcome durability, substance abuse treatment
HIV/AIDS remains a formidable public health challenge as over 950,000 people in the U.S. live with HIV infection and 450,000 people have died due to AIDS thus far (CDC 2004; Joint United Nations Programme on HIV/AIDS 2004). In the absence of a vaccine to prevent new HIV infections, behavioral interventions remain the primary tool for reducing the risk and transmission of HIV (e.g., Semaan et al. 2002). A number of efficacious behavioral interventions are now available as complete intervention packages (http://www.effectiveinterventions.org). Thus, there is unprecedented potential to integrate efficacious interventions into clinical settings where large numbers of high-risk individuals participate in treatment. Successfully integrating efficacious interventions into clinical settings, however, can be complicated by factors that distinguish clinical settings from the research settings where they are usually tested.
Foremost, clinical settings often possess very limited resources that can be devoted to delivering, monitoring, and evaluating interventions (Sholomskas et al. 2005; Morgenstern et al. 2001). "Community-friendly" interventions are designed to promote the optimal use of limited resources in a given setting. An intervention may be characterized as community-friendly to the extent that it can be successfully implemented, as designed, in a particular clinical setting without disrupting ongoing services or overburdening organizational resources (e.g., Schoenwald & Hoagwood 2001). Interventions that are not community-friendly are unlikely to be implemented as intended in clinical settings as demonstrated by analogous efforts to disseminate behavioral interventions for treating drug dependence (e.g., Sholomskas et al. 2005; Knudsen & Roman 2004; Sanderson 2002; Morgenstern et al. 2001; Institute of Medicine 1998).
In addition to being community-friendly, an intervention must produce and maintain the desired outcomes among the target population. A growing concern involves "HIV/AIDS complacency" among high-risk populations (Hart & Williamson 2005; Jaffe 2004; Mayer, Safren, & Gordon 2004; Valdiserri 2003). HIV/AIDS complacency may be defined as the tendency for targeted individuals to minimize or discount the health threat of HIV/AIDS (Valdiserri 2003). Researchers have identified a range of potential reasons for HIV/AIDS complacency. Commonly cited reasons include "treatment optimism" (i.e., the growing perception that HIV is less threatening due to improvements in HIV medications; Valdiserri 2003; Lert 2000) and "prevention fatigue" (i.e., when the same risk reduction content is heard so often that targeted individuals tend to ignore it; e.g., Hart & Williamson 2005). Risk reduction outcomes may be enhanced to the extent that an intervention discourages HIV/AIDS complacency among a target population (e.g., Valdiserri 2003).
In terms of interventions targeting IDUs, a recent meta-analysis of randomized controlled trials (RCTs) reported that positive outcomes tend to be greatest among IDUs when content equivalently addresses drug- and sex-related risks (Copenhaver et al. 2006). The durability of outcomes, however, may be expected to vary by risk domain. No decay tends to occur across drug-related outcomes whereas the decay of sex-related outcomes becomes more pronounced over time (Copenhaver et al. 2006; Fogarty et al. 2001; El-Bassel & Schilling 1992) and this represents another key consideration. In summary, findings to date indicate that the implementation of a risk reduction intervention in community-based settings for IDUs may be enhanced when the intervention is designed to be community-friendly, focuses equivalently on sex- and drug-related risks, and maintains potency.
In an effort to effectively integrate a risk reduction intervention within community- based treatment settings for IDUs, the authors developed the Community-Friendly Health Recovery Program, an abbreviated form of the comprehensive evidence-based Holistic Health Recovery Program (HHRP; see Copenhaver, Lee & Margolin 2007). In two RCTs, the comprehensive HHRP intervention demonstrated efficacy as assessed by self-reported data (e.g., reported reductions in drug risk behavior) as well as objective data (e.g., urine toxicology tests, videotaped demonstrations of sex- and drug-related risk reduction skills that were blindly rated, and improvement in risk reduction knowledge; Avants et al. 2004; Margolin et al. 2003). Though substantially shortened, as needed for use in clinical settings, the CHRP intervention has also shown favorable outcomes including enhanced HIV-related knowledge, motivation, behavioral skills, and reported drug- and sex-risk reduction behaviors (Copenhaver, Lee & Margolin 2007). Given these findings to date, the objective of present study was (1) to examine whether the observed intervention effects decayed over time and (2) to determine whether there was benefit associated with repeating the intervention at a follow-up point.
The CHRP intervention was conducted within ongoing treatment groups at methadone maintenance facilities owned by the APT Foundation, Inc. in New Haven, CT. Briefly, the CHRP intervention is a manual-guided behavioral intervention comprised of four 50-minute group sessions (Active Health Care Participation; Reducing the Harm of Injection Drug Use; Harm Reduction with Latex; Negotiating Harm Reduction with Partners) that target sex- and drug-related HIV risks among IDUs in treatment. Sessions are led by two trained facilitators who deliver intervention content using cognitive remediation strategies designed to accommodate cognitive difficulties that may impede participation in this patient population (Copenhaver et al. 2003; Avants et al. 1997).
Sixty-two of the full sample of 226 subjects who enrolled in the first CHRP intervention returned approximately 10 months later to provide follow-up data and to participate in the repeated CHRP intervention. Patients were not compensated for their participation and their status in the treatment program was not affected by whether they participated. Thus, the follow-up rate was lower than in trials of similar interventions in which participant incentives were offered (e.g., Sterk et al. 2003; Stein et al. 2002). Importantly, no differences were found between follow-up participants and the full sample of participants in terms of pre-intervention or post-intervention measures including HIV-related knowledge, attitudes, behavioral skills, drug use, or demographic characteristics (all ps > .25) with the exception of race. Individuals who participated in the follow-up and repeated the intervention were more likely to be racial minorities, [chi square] (df = 1, N = 225) = 7.34, p < .01.
The characteristics of the follow-up sample of participants were as follows: Caucasian (55%), never married (57%), unemployed (55%), English speaking (87%), and injection drug users (79%). The study protocol was approved by the Investigational Review Board (IRB) at the University of Connecticut and by a research review board at the APT Foundation, Inc. and all participants provided signed informed consent prior to their participation.
Several items from the Risk Assessment Battery (RAB; Metzger et al. 1993) were used to assess participants' sex-and drug-related HIV risk behavior. The scale required participants to categorize and quantify their drug use and sexual activity during the prior week. Drug use related items included how they used drugs, whether they used new syringes or cleaned syringes, and if so, how they cleaned them, and whether they shared syringes, rinse water, cookers, or cotton. Sexual activity related items assessed whether they used a condom and, if not, whether it was due to their abstinence from sexual activity.
Based on the Information-Motivation-Behavior skills (IMB; J. Fisher & Fisher 1992) model of health behavior change, a brief assessment (see Fisher et al. 2004) was used to measure participants' HIV-related knowledge, motivation, and behavioral skills. Four items were used to assess knowledge about safer sex and safer injection drug use (e.g., "If an HIV+ person only has sex with another HIV+ person, they don't need to use condom"; "If an HIV+ person shared needles with another HIV+ person, they don't need to clean the needles."). Six items were used to examine participants' personal and social motivation to use condoms and clean needles, such as their intentions to engage in safer sexual activity and safer injection drug use practices and perceptions of significant others' beliefs about the importance of using condoms and using clean needles. Four items assessed participants' behavioral skills in the form of their self-efficacy about abstaining from sexual activity and using a condom and about abstaining from injecting drugs and using clean needles.
First, the immediate post-intervention outcomes (Copenhaver, Lee & Margolin 2007) will be summarized to provide a context for the present analysis. A repeated measures analysis of variance was performed with Intervention (pre- vs. post-intervention) as a within-subjects variable and with HIV Risk Group (high, moderate, and low, based on composite HIV risk scores at pre-test) as a between-subjects variable on all variables pertaining to drug-related and sex-related outcomes. Analyses of drug- and sex-related risk reduction outcomes were performed separately so that outcomes could be compared across these two different domains.
A positive main effect was found for Intervention, F (1, 223) = 9.81, p < .01 as well as for HIV Risk Group, F (5, 211) = 3.36, p < .01 on drug-related risk reduction, and F (5, 211) = 10.60, p < .001 on sex-related risk reduction. Interestingly, the main effects were superseded by significant Intervention x HIV Risk Group interactions, F (10, 424) = 9.05, p < .001 for drug-related risk reduction, and F (10, 424) = 9.40, p < .001 for sex-related risk reduction.
In terms of drug-related outcomes, the interaction was driven by greater improvement among the high-risk group in personal motivation, F (2, 215) = 19.05, p < .001, social motivation, F (2, 215) = 6.27, p < .01, self-efficacy, F (2, 215) = 20.17, p < .001, and reported injection drug use behavior, F (2, 215) = 4.63, p < .05. For sex-related outcomes, the interaction was fueled by greater improvement among the high risk group in personal motivation to engage safer sex, F (2, 215) = 25.36, p < .001, social motivation to engage in safer sex, F (2, 215) = 12.10, p < .001, and self-efficacy for safer sex, F (2, 215) = 12.51, p < .001. The interaction effect was also marginally significant with regard to sex-related HIV risk reduction knowledge, F (2, 215) = 2.40, p = .09. In short, participants at higher risk for HIV tended to show greater relative improvement across both risk domains at the immediate post-intervention point.
The immediate post-intervention effects spurred an analysis of the durability of the intervention outcomes. Based on prior research (Copenhaver et al. 2006; Fogarty et al. 2001; El-Bassel & Schilling 1992), we expected decay to become particularly pronounced with regard to sex-related outcomes such as condom use.
Examining the Decay of Risk Reduction Outcomes
The present study examined (1) the degree to which the outcomes changed over time and (2) whether participants benefited from repeating the intervention. Analyses first focused on changes in risk reduction from immediately post-intervention to the follow-up point approximately 10 months later. Repeated-measures MANOVAs were performed using post-intervention and follow-up risk reduction scores as dependent variables and HIV Risk Group (low vs. high, based on composite HIV risk scores at pre-test) as the independent variable. The omnibus F-test, which included both drug- and sex-related risk reduction scores, did not reach significance. However, an individual F-test revealed a decline in social motivation about condom use among participants in the low HIV risk group by the follow-up point, F (1, 30) = 5.03, p < .05 (Table 1).
Further analyses were used to investigate whether any changes in risk reduction outcomes were attributable to decay (i.e., negative changes in outcomes due to diminishing intervention effects over time). This was accomplished by examining the associations between (1) the number of days that elapsed between post-intervention and the follow-up point and (2) variation in scores from post-intervention to follow-up. No evidence of decay was found in any of the outcomes. Instead, a longer time lapse was associated with increases (or smaller decreases) in social motivation to reduce drug-related risk behavior, r (N = 62) = -.31, p < .03 (Table 1). A regression model was employed to explain this unexpected finding. Using a stepwise method, we entered demographic variables that may have moderated changes over time in social motivation. The only significant predictor was number of children, (Beta = -.31, p < .05). Participants who reported having a greater number of children were more likely to gain social motivation (or to show less decreases in social motivation) over time compared to participants with fewer or no children.
The Benefit of Repeating the Intervention
As reported above, no evidence of decay was found in risk reduction outcomes leading to the follow-up point. However, a gradual decline was noted in some of the outcomes and, of particular concern, this appeared to be more pronounced for the high HIV risk group (Figure 1). Analyses therefore focused on whether outcomes were bolstered by participants repeating the intervention starting immediately after the follow-up point. A repeated-measures MANOVA was performed using follow-up and post-repeated intervention risk reduction scores as dependent variables and HIV Risk Group (low vs. high) as the independent variable. A distinct trend toward enhanced risk reduction was observed across sex-related outcomes for the high HIV risk group following the repeated intervention (Figure 1). These effects, however, did not reach conventional levels of significance.
[FIGURE 1 OMITTED]
The present study tackled issues surrounding the durability of risk reduction outcomes among IDUs in treatment following the implementation of a community-friendly intervention. With the rapid availability of behavioral interventions, considering features such as whether an intervention is community-friendly and produces durable outcomes will become increasingly essential in order to match the risk reduction needs of patients with the resource constraints of particular clinical settings. Findings from the present study are encouraging as they suggest positive changes among participants rather than complacency in response to the CHRP intervention.
The intervention produced durable drug-related risk reduction outcomes. In fact, there was a tendency for effects pertaining to social motivation to emerge over time for participants with children. Participants with children may have made greater efforts over time to revamp their social network and therefore benefited from increasing support for prorecovery behaviors including risk reduction. Indeed, recent reviews point to the effectiveness of enhancing social support as a risk reduction strategy in behavioral interventions targeting drug users (Strathdee & Patterson 2006; van Empelen et al. 2003). Future studies should pursue this question by explicitly examining the impact of family and social support variables on risk reduction outcomes among IDUs.
The robust sex-related risk reduction outcomes also retained potency from post-intervention to follow-up. This is particularly noteworthy as sex-related risk reduction effect sizes are typically smaller vs. drug-related outcomes (Strathdee & Patterson 2006), and tend to decay more rapidly (Copenhaver et al. 2006), thus necessitating "booster sessions" (e.g., Fogarty et al. 2001; El-Bassel & Schilling 1992). Interestingly, even though no significant amount of decay occurred by 10 months post-intervention, repeating the intervention at that point did tend to bolster the sex-related outcomes back to or above post-intervention levels for those at higher risk for HIV (Figure 1). Based on the continuation of the observed trend, it may be most effective to provide a sex-risk focused booster session at a later time point (e.g., 15 to 18 months; Fogarty et al. 2001; El-Bassel & Schilling 1992) in order to optimize sex-risk reduction among individuals at highest risk. Future studies in similar treatment settings should address this question.
Findings from the present study are consistent with the large body of literature evaluating behavioral interventions that target difficult-to-change behaviors (e.g., substance use, smoking) in that, even when positive intervention outcomes occur, they tend to be modest in terms of effect size (Pigott 2001). Further, the present study extends the literature by systematically examining the array of issues involved in successfully integrating an intervention into clinical settings (e.g., Sholomskas et al. 2005; Knudsen & Roman 2004; Sanderson 2002; Morgenstern et al. 2001; Hoagwood et al. 1995). The fundamental challenge involves how to implement an intervention in such a manner that it remains potent among a target population without overburdening the scarce resources typical of clinical settings. In the present study, findings indicated that a risk reduction intervention can be both community-friendly and potent over time in a common type of clinical setting.
Limitations of the present study should also be acknowledged. Foremost, this study was conducted and evaluated as a fully integrated clinical intervention within community-based methadone maintenance programs and this resulted in some inherent limitations. First, because participation was only encouraged (without any compensation), participation in the follow-up evaluation and repeated intervention was at a lower rate than would be expected in a conventional controlled study in which significant participant incentives were offered over a longer follow-up period. In addition, because the intervention was funded by a small grant of relatively short duration, it was not possible to conduct follow-up evaluations and repeat the intervention for many participants. However, we note that the observed correlations between time lapse and changes in risk reduction scores--though nonsignificant--were in the opposite direction from correlations that would point to a tendency toward decay of intervention effects. Thus, it is unlikely that even a substantially greater participation rate over a longer follow-up period would have resulted in different conclusions.
In addition, because our primary focus was on integrating and evaluating a community-friendly intervention, this study used a within-subjects design--with participants serving as their own controls--rather than a stringent between-subjects design. There are clearly limitations to the use of a single-group, within-subjects design in terms of experimental control. Likewise, due to the clinical context in which this study was implemented, a very brief assessment battery was employed that necessarily relied on self-report questionnaires and quizzes to measure changes in risk reduction knowledge, motivation, skills, and behaviors. Among our reported outcomes, however, were objective improvements (e.g., significant gains in participants' knowledge pertaining to drug- and sex-related HIV risks) that cannot readily be explained as artifacts, such as demand characteristics. It is also unlikely that external influences led to changes in what are widely acknowledged as difficult-to-change behaviors (Pigott 2001).
Despite the noted limitations, findings of this study demonstrate that a comprehensive evidence-based intervention (HHRP; Avants et al. 2004; Margolin et al. 2003) that has been adapted to be more community-friendly (Copenhaver, Lee & Margolin. 2007) can also produce desirable effects over time. Thus, interventions of this type have the potential to be successfully integrated, as designed, into settings in which large numbers of high risk IDUs may be efficiently reached. The present study may also serve as an exemplar by outlining the key issues surrounding intervention design that may become increasingly relevant to the successful implementation of risk reduction interventions in other types of clinical settings.
Avants, S.K.; Margolin, A; Usubiaga, M.H. & Doebrick, C. 2004. Targeting HIV-related
outcomes with intravenous drug users maintained on methadone: A randomized clinical trial of a harm reduction group therapy. Journal of Substance Abuse Treatment 26: 67-78.
Avants, S.K.; Margolin, A.; McMahon, T.J. & Kosten, T.R. 1997. Association between
self-report of cognitive impairment, HIV status, and cocaine use in a sample of
cocaine-dependent methadone-maintained patients. Addictive Behaviors 22 (5): 599-611.
Centers for Disease Control and Prevention (CDC). 2004. Special! data request. Retrieved from http://www.statehealthfacts.kff.org.
Copenhaver, M.; Lee, I.C. & Margolin, A. 2007. Successfully integrating an HIV risk reduction intervention into a community-based substance abuse treatment program. American Journal of Drug and Alcohol Abuse 33 (1): 109-20.
Copenhaver, M.; Johnson, B.T.; Lee, I.C.; Carey, M. & Harman, J. 2006. HIV risk reduction among injection drug users: Meta-analytic evidence of efficacy. Journal of Substance Abuse Treatment 31: 163-71.
Copenhaver, M.; Margolin, A.; Avants, K. & Warburton, L. 2003. Intervening effectively with drug abusers infected with HIV: Taking into account the potential for cognitive impairment. Journal of Psychoactive Drugs 35 (2): 209-18.
El-Bassel, N. & Schilling, R.F. 1992. 15-month follow-up of women methadone patients taught skills to reduce heterosexual HIV transmission. Public Health Reports 107: 500-04.
Fogarty, L.A.; Heilig, C.M.; Armstrong, K.; Cabral, R.; Galavotti, C.; Gielen, A.C. & Green, M. 2001. Long-term effectiveness of a peer-based intervention to promote condom and contraceptive use among HIV-positive and at-risk women. Public Health Reports 116 (1): 103-19.
Fisher, J.D.; Cornman, D.H; Osborn, C.Y.; Amico, K.R.; Fisher, W.A. & Friedland, G.A. 2004. Clinician-initiated HIV risk reduction intervention for HIV-positive persons: Formative research, acceptability, and fidelity of the OPTIONS project. Journal of Acquired Immune Deficiency Syndrome 37 (2): S78-S87.
Fisher, J.D. & Fisher, W.A. 1992. Changing AIDS-risk behavior. Psychological Bulletin 111: 455-47.
Hart, G.J. & Williamson, L.M. 2005. Increase in HIV sexual risk behaviour in homosexual men in Scotland, 1996-2002: Prevention failure? Sexually Transmitted Infections 81: 367-72.
Hoagwood, K.; Hibbs, E.; Brent, D. & Jensen, P. 1995. Introduction to the special section: Efficacy and effectiveness in studies of child and adolescent psychotherapy. Journal of Consulting and Clinical Psychology 63: 683-87.
Institute of Medicine. 1998. Bridging the Gap between Practice and Research: Forging Partnerships with Community-Based Drug and Alcohol Treatment. Washington, DC: National Academy Press.
Jaffe, H. 2004. Whatever happened to the U.S. AIDS epidemic? Science 305: 1243-44.
Joint United Nations Programme on HIV/AIDS. 2004. Q&A II: Basic facts about the AIDS epidemic and its impact, UNAIDS questions and answers. Available at http://www.unaids.org.
Knudsen, H.K. & Roman, P.M. 2004. Modeling the use of innovations in private treatment organizations: The role of absorptive capacity. Journal of Substance Abuse Treatment 16: 353-61.
Lert, F. 2000. Advances in HIV treatment and prevention: Should treatment optimism lead to prevention pessimism? AIDS Care 12 (6): 745-55.
Margolin, A.; Avants, S.K.; Warburton, L.A.; Hawkins, K.A. & Shi, J. 2003. A randomized clinical trial of a manual-guided risk reduction intervention for HIV-positive injection drug users. Health Psychology 22 (2): 223-28.
Mayer, K.H.; Safren, S.A. & Gordon, C.M. 2004. HIV care providers and prevention: Opportunities and challenges. Journal of Acquired Immune Deficiency Syndrome 37 (2): S130-32.
Metzger, D.; Woody, G.E.; Navaline, H.; McLellan, A.T.; Meyers, K.; Boney, T.; Mulvaney, F.; Williams, J.; Dyanick, S.T.; Jonson, A.; Davis, B.; Green, P.; Abrams, M.; Oglesby, P.; Davis, R.; Zanis, D.; Abellanas, L.; Incmicoski, R., & O'Brien, C.P. 1993. The Risk Assessment Battery (RAB): Validity and reliability. Paper presented at the Sixth Annual Meeting of National Cooperative Vaccine Development Group for AIDS, Alexandria, VA.
Morgenstern, J.; Morgan, T.J.; McCrady, B.S.; Keller, D.S. & Carroll, K.M. 2001. Manual-guided cognitive behavioral therapy training: A promising method for disseminating empirically supported substance abuse treatments to the practice community. Psychology of Addictive Behavior 5: 83-88.
Pigott, T.D. 2001. Missing predictors in models of effect size. Evaluation & the Health Professions 24: 277-307.
Sanderson, W.C. 2002. Are evidence-based psychological interventions practiced by clinicians in the field? Medscape General Medicine 4 (1).
Schoenwald, S.K. & Hoagwood, K. 2001. Effectiveness, transportability, and dissemination of interventions: What matters when? Psychiatric Services 52: 1190-97.
Semaan, S.; Des Jarlais, D.C.; Sogolow, E.; Johnson, W.D.; Hedges, L.V.; Ramirez, G.; Flores, S.A.; Norman, L.; Sweat, M.D. & Needle, R. 2002. A meta-analysis of the effect of HIV prevention interventions on the sex behaviors of drug users in the United States. Journal of Acquired Immune Deficiency Syndrome 30: S73-S93.
Sholomskas, D.E.; Syracuse-Siewert, G.; Rounsaville, B.J.; Ball, S.A.; Nuro, K.F. & Carroll, K.M. 2005. We don't train in vain: A dissemination trial of three strategies of training clinicians in cognitive-behavioral therapy. Journal of Consulting and Clinical Psychology 73: 106-15.
Stein, M.D.; Anderson, B.; Charuvastra, A.; Maksad, J. & Friedmann, P.D. 2002. A brief intervention for hazardous drinkers in a needle exchange program. Journal of Substance Abuse Treatment 22: 23-31.
Sterk, C.E.; Theall, K.P.; Elifson, K. & Kidder, D. 2003. HIV risk reduction among African-American women who inject drugs: A randomized controlled trial. AIDS and Behavior 7: 73-86.
Strathdee, S.A. & Patterson, T.L. 2006. Behavioral interventions for HIV-positive and HCV-positive drug users. AIDS and Behavior 10 (2): 115-30.
van Empelen, P.; Kok, G.; van Kesteren, N.M.; van den Borne, B.; Bos, A.E. & Schaalma, H.P. 2003. Effective methods to change sex-risk among drug users: Areview of psychological interventions. Social Science & Medicine 57: 1593-608.
Valdiserri, R. 2003. Symposium conducted on CDC's Initiative: "Advancing HIV Prevention": Implications for Policy, Research, and Practice at the Center for Interdisciplinary Research on AIDS and the Institution for Social and Policy Studies (CIRA), New Haven, CT, December.
([dagger]) Funding to support this study was provided by the Connecticut Department of Public Health - AIDS Division (DPH Log #2004-154) to Michael M. Copenhaver. Funding to support data analyses and preparation of this manuscript was provided by the National Institute on Drug Abuse, grant K23-DA017015 to Michael M. Copenhaver.
Michael M. Copenhaver, Ph.D. * & I-Ching Lee, Ph.D. **
* Assistant Professor, University of Connecticut, Center for Health/ HIV Intervention & Prevention (CHIP), Storrs, CT.
** Assistant Professor, National Chengchi University, Taipei, Taiwan.
Please address correspondence and reprint requests to Michael M. Copenhaver, University of Connecticut, 2006 Hillside Drive, Unit 1248, Storrs, CT 06269; email: firstname.lastname@example.org.
TABLE 1 Descriptive Analysis of Decay of Intervention Effects Over Time by HIV Risk Group High Risk Group Time 1 2 3 4 Drug related outcomes / N 23 23 23 15 Knowledge (accuracy) 87.0% 87.0% 84.8% 90.0% (27.0) (27.0) (27.9) (20.7) Personal motivation (2) 4.07 4.67 4.61 4.47 (0.68) (0.48) (0.64) (0.72) Social motivation (2) 3.83 4.35 4.48 4.07 (1.30) (1.07) (1.04) (1.34) Self-efficacy (2) 3.96 4.28 4.20 3.70 (0.80) (0.82) (0.96) (1.36) Reported clean 5.78 5.83 5.91 6.00 needle use (3) (0.67) (0.49) (0.29) (0.00) Sex-related outcomes / N 31 31 31 18 Knowledge (accuracy) 69.4% ** 83.9% ** 83.9% 80.6% (33.4) (27.0) (23.7) (25.1) Personal motivation (2) 3.63 *** 4.42 *** 4.21 4.47 (0.99) (0.87) (0.80) (0.85) Social motivation (2) 3.84 *** 4.58 *** 4.45 4.67 (1.42) (0.96) (1.03) (0.69) Self-efficacy (2) 2.63 * 3.08 * 2.89 3.28 (1.24) (1.28) (1.33) (1.14) Reported condom use (2) 2.81 3.19 3.03 3.78 (2.02) (1.94) (2.01) (1.80) Low Risk Group Time 1 2 3 Drug related outcomes / N 27 27 27 Knowledge (accuracy) 87.0% 90.7% 88.9% (22.3) (19.8) (21.2) Personal motivation (2) 4.94 4.72 4.76 (0.13) (0.62) (0.58) Social motivation (2) 4.96 4.70 4.33 (0.19) (0.95) (1.36) Self-efficacy (2) 4.89 4.41 4.48 (0.25) (1.10) (0.78) Reported clean 6.00 6.00 6.00 needle use (3) (0.00) (0.00) (0.00) Sex-related outcomes / N 31 31 31 Knowledge (accuracy) 71.0% 72.6% 72.6% (31.0) (25.3) (31.2) Personal motivation (2) 4.76 4.84 4.73 (0.44) (0.35) (0.55) Social motivation (2) 4.94 4.97 ** 4.74 ** (0.25) (0.18) (0.58) Self-efficacy (2) 4.40 4.11 3.73 (0.66) (1.06) (1.13) Reported condom use (2) 4.03 4.10 4.42 (1.62) (1.70) (1.36) Low Risk Group Corr. (a) Time 4 Decay Drug related outcomes / N 18 50 Knowledge (accuracy) 88.9% -.05 (21.4) Personal motivation (2) 4.56 .24 (0.73) Social motivation (2) 4.67 -.31 * (0.97) Self-efficacy (2) 4.19 -.23 (1.25) Reported clean 6.00 -.06 needle use (3) (0.00) Sex-related outcomes / N 22 62 Knowledge (accuracy) 72.7% -.07 (25.5) Personal motivation (2) 4.61 -.12 (0.63) Social motivation (2) 4.77 -.08 (0.61) Self-efficacy (2) 3.61 -.22 (1.12) Reported condom use (2) 3.95 .04 (1.76) Note. * p <.06, ** p <.05, *** p <.001 (a) Corr.: Correlations - Score changes vs. time elapsed. 1: Time 1: Pre-test, Time 2: Post-test, Time 3: Follow-up, and Time 4: After repeated intervention. 2: On a 1 to 5 scale: a higher score indicates greater personal motivation. 3: On a 1 to 6 scale: a higher score indicates reduced HIV risk.
|Printer friendly Cite/link Email Feedback|
|Title Annotation:||human immunodeficiency virus|
|Author:||Copenhaver, Michael M.; Lee, I-Ching|
|Publication:||Journal of Psychoactive Drugs|
|Date:||Sep 1, 2007|
|Previous Article:||Implementing an evidence-based practice: Seeking Safety group ([dagger]).|
|Next Article:||Death by drug overdose: impact on families ([dagger]).|