University of Southern California Dissertations and Theses

Competing risks: the role of the perceived consequences of refusing to share injection equipment among injection drug users

(USC Thesis Other)

Competing risks: the role of the perceived consequences of refusing to share injection equipment among injection drug users

PDF

Download a page range

Download transcript

Copy asset link

Request this asset

Transcript (if available)

Content COMPETING RISKS: THE ROLE OF THE PERCEIVED CONSEQUENCES OF REFUSING TO SHARE INJECTION EQUIPMENT AMONG INJECTION DRUG USERS by Karla Dawn Wagner A Dissertation Presented to the FACULTY OF THE GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (PREVENTIVE MEDICINE: HEALTH BEHAVIOR) December 2009 Copyright 2009 Karla Dawn Wagner ii ACKNOWLEDGEMENTS I give a heartfelt thanks to the faculty of IPR, particularly the dissertation committee members who supported me through this project. To Dr. Jennifer Unger, who patiently allowed me to chart my own course and provided insight and guidance throughout. To Dr. Jean Richardson, who provided sincere feedback and wisdom. To Dr. Steve Lankenau, who grounded my work and encouraged my ambitions. To Dr. Chih-Ping Chou, who was so generous with his unparalleled statistical expertise. To Dr. Lawrence Palinkas, who reminded me of the importance of my anthropological roots. There are so many others, too many to name, who have inspired me through my long journey, helping me discover my path and be true to my aims. Among them: Mr. D. Huffman, Dr. Dennis Van Gerven, Dr. Jack Kelso, Dr. Robert T. Trotter II, Dr. Beatrice Krauss, and Dr. Thomas Valente. I convey my deepest gratitude to the study participants who allowed me a glimpse of their lives and shared their thoughts, perspectives, and stories with me. I am also absolutely indebted to the staff of the field site for their unflagging support of my research goals and their generosity. In particular, Mark Casanova and James Hundley provided access and insight that made this project possible. To Brett Mendenhall, who might not have known what he was getting in to, but stuck with me through two studies and several years of research. I am so thankful that he was willing to work with me, and so proud of what he has accomplished. Thank you to Marny Barovich, who shepherded me with care and enthusiasm. Enormous thanks go to my fellow students Dr. Courtney Byrd-Williams, Dr. Kate Coronges, and Liz Barnett; all of whom were kind, giving, critical, challenging, and encouraging. And, of course, thanks to Bob DeMaa for providing daily doses of love, humor, and reality when I needed them most. This research was supported by a National Institute on Drug Abuse Dissertation Award (R36 DA024968-01). iii TABLE OF CONTENTS Acknowledgements ii! List of Tables v! List of Figures vi! Abbreviations vii! Abstract viii! Chapter 1. Introduction 1! Background & Significance 1! HIV/AIDS and Injection Risk Behavior Among IDUs 1! Cognitive Behavioral Theory in the Study of HIV Risk Behavior Among IDUs 3! Perceived Consequences of Refusing to Share Injection Equipment 6! Female IDUs and HIV 8! Overview of the Dissertation 9! Methods 10! Phase One – Qualitative Interviews 10! Phase Two – Cross-sectional Quantitative Survey 11! Chapter 2. Gender Differences in the Perceived Consequences of Safer Injection: A Qualitative Study 13! Chapter 2 Abstract 13! Introduction 14! Methods 16! Results 18! Discussion 27! Conclusions 32! Chapter 3. Competing Risks: The Influence of the Perceived Consequences of Refusing to Share on Risky Injection Practices Among IDUs 33! Chapter 3 Abstract 33! Introduction 34! Methods 37! Results 43! Discussion 53! Conclusions 57! iv Chapter 4. Psychosocial Correlates of Risky Injection Behavior Among IDUs: Moderation by Perceived Consequences of Refusing to Share Injection Equipment 58! Chapter 4 Abstract 58! Introduction 59! Methods 62! Results 70! Discussion 79! Conclusions 82! Chapter 5. Summary, Implications, and Conclusions 84! Summary 84! Implications for Intervention 89! Conclusions 92! References 93! v LIST OF TABLES Table 2.1. Demographic characteristics of study sample (N=26). 19! Table 3.1. Demographic characteristics and drug use behavior of study sample, by gender (N=187). 44! Table 3.2. Perceived consequences items and factor loadings (N=187). 46! Table 3.3. Summary statistics for four perceived consequences subscales by gender (N=187). 47! Table 3.4. Frequency of perceived consequences of refusing to share syringes or paraphernalia at the most recent risky injection episode, by gender. 48! Table 3.5. Bivariate correlations between perceived consequences, psychosocial scales, and injection risk behaviors (N=187). 50! Table 3.6. Results from multiple linear regression of perceived consequences and psychosocial scales on log syringe sharing (N=130). 51! Table 3.7. Results from multiple linear regression of perceived consequences and psychosocial scales on log paraphernalia sharing (N=130). 52! Table 4.1. Demographic characteristics of study sample (N=130). 70! Table 4.2. Correlations among model constructs (N=130). 71! Table 4.3. Results of multiple group model-fitting process, by perceived social/internal consequences (N=130). 73! Table 4.4. Results of multiple group model-fitting process, by perceived structural/external consequences (N=130). 77! vi LIST OF FIGURES Figure 4.1. Multiple group structural equation model depicting significant regression paths between psychosocial variables and injection risk behavior, moderated by perceived social/internal consequences of refusing to share injection equipment (N=130). 74! Figure 4.2. Multiple group structural equation model depicting significant regression paths between psychosocial variables and injection risk behavior, moderated by perceived structural/external consequences of refusing to share injection equipment (N=130). 78! vii ABBREVIATIONS AIDS = Acquired Immunodeficiency Syndrome CA = NIDA Cooperative Agreement CBT = Cognitive Behavioral Theory HCV = Hepatitis C Virus HIV = Human Immunodeficiency Virus IDU = Injection Drug Use(r) NADR = NIDA National AIDS Demonstration Research Program NIDA = National Institute on Drug Abuse RSS = Receptive Syringe Sharing RPS = Receptive Paraphernalia Sharing SEM = Structural Equation Modeling SEP = Syringe Exchange Program viii ABSTRACT Background: Injection drug users (IDUs) are at risk for HIV and other bloodborne pathogens. Though reductions in injection risk behavior have been observed, residual risk behavior persists. Female IDUs are at elevated risk compared to their male counterparts, and this elevated risk appears to be grounded in the social and environmental context. The perceived consequences of refusing to share injection equipment have yet to be investigated as a factor that may help explain persistent injection risk behavior. Methods: The current study used a two-phase, mixed-methods design to identify the perceived consequences of refusing to share injection equipment, assess the relationship between perceived consequences and injection risk behavior, and explore whether perceived consequences moderate the effects of other correlates of injection risk behavior in a sample of IDUs recruited from a large syringe exchange program. In addition, the study assessed gender differences in the both the qualitative and quantitative data. Results: Findings from the qualitative analysis suggest that perceived consequences of refusing to share can be organized into four domains: individual, social, physical, and economic/policy. Gender differences were particularly evident in the social domain. Findings from the first quantitative analysis suggest that the consequences can be assessed using two sub-scales: perceived social/internal and structural/external consequences. In multiple linear regression perceived social/internal consequences were associated with greater frequency of reported injection risk behavior, even when controlling for other correlates of injection risk behavior. The perceived structural/external consequences were not associated with injection risk behavior. Few gender differences emerged in the quantitative results. Findings from the second quantitative analysis suggested that perceived consequences moderated the association between peer norms and injection risk behavior, and also moderated the associations amongst other correlates of injection risk behavior. Moderation results suggest that the associations between some theoretical correlates of behavior may be stronger in individuals who report greater influence of perceived consequences. ix Conclusion: Assessing the perceived consequences of refusing to share injection equipment may help explain some residual injection risk behavior. Addressing the individual, social, physical, and economic/policy-level consequences of safer behavior may help IDUs reduce injection risk behavior. 1 CHAPTER 1. INTRODUCTION Background & Significance HIV/AIDS and Injection Risk Behavior Among IDUs Acquired Immunodeficiency Syndrome (AIDS) was first identified in the United States in 1981, though it took an additional three years to identify its cause, the Human Immunodeficiency Virus (HIV). In the early years of what would soon be characterized as the HIV/AIDS epidemic, “behavioral risk groups” such as men who have sex with men and injection drug users (IDUs) were identified as individuals at elevated risk for HIV/AIDS. Since 1985, IDUs have accounted for between 19% and 30% of all AIDS cases in the United States (Centers for Disease Control and Prevention, 2008). The number of AIDS diagnoses among IDUs peaked in the early 1990s with an estimated 23,364 diagnoses in 1993, after which a decreasing trend was observed – in 2006, an estimated 7,153 AIDS diagnoses were made among IDUs (Centers for Disease Control and Prevention, 2008). In 2006, 12% of incident HIV infections were attributable to injection drug use (Centers for Disease Control and Prevention, 2006). HIV/AIDS prevention efforts among IDUs have involved a variety of complementary components, including individual, community, and structural interventions. One structural intervention that has been effective in reducing risky injection practices is the provision of sterile injection supplies via Syringe Exchange Programs (SEPs; Heimer, 1998b; Ksobiech, 2003). Early evaluation of SEPs found that providing new sterile injection equipment to IDUs reduced the prevalence of detectable HIV found in syringes returned from the community (Heimer et al., 1993). A 2006 review paper highlighted seven reviews of SEP evaluation research conducted from 1991 to 2001, all of which found that SEPs help prevent HIV while not increasing the prevalence of injection drug use (Wodak & Cooney, 2006). The same review paper presented evidence from an additional 44 empirical studies conducted between 1989-2002 that evaluated the effect of SEPs on injection-related risk behaviors and HIV seroconversion or seropositivity; virtually all research findings demonstrated protective effects of SEPs (Wodak & Cooney, 2006). 2 Others have shown that in the absence of bureaucratic barriers, SEPs can also serve as a conduit to other types of care such as drug treatment (Heimer, 1998a). Individual, community, and group-level behavioral interventions have also been implemented on a fairly widespread basis, though evidence from evaluation studies suggests that sustained behavioral change is difficult to achieve. Some of the earliest interventions took place within the context of the National Institute on Drug Abuse (NIDA)-funded National AIDS Demonstration Research (NADR) and Cooperative Agreement (CA) projects. The NADR began in 1987, and included 41 projects in 50 cities (Booth et al., 1998). Building on the NADR, the CA began in 1990 and included 23 projects that drew on a number of theoretical orientations including several Cognitive Behavioral Theories, community outreach approaches, Social Context Theory, and Social Network Theory (Stevens et al., 1998). In most NADR/CA projects, both enhanced and standard intervention participants significantly reduced risk behaviors, though enhanced intervention participants were more likely to discontinue IDU and also more likely to enter drug treatment (Booth et al., 1998). A review of 19 psychosocial interventions implemented during a similar time period (1990 – 1998) found four without serious design limitations that demonstrated significant intervention effects (Gibson et al., 1998). The effective interventions were characterized by intensive and sustained interventions with stable and motivated participants. More recently, a meta-analysis of 49 randomized controlled trials conducted from 1991 to 2004 found that behavioral interventions had more effect on changing some behaviors (e.g., frequency of injection drug use and entry into drug treatment) than others (e.g., syringe sharing; Copenhaver et al., 2006). In a more recent behavioral intervention trial for young IDUs conducted from 2002 to 2004, both the experimental and control conditions significantly reduced injection risk behavior at follow-up (Garfein et al., 2007a). While individual measures of injection risk behavior (i.e., receptive syringe sharing, syringe mediated drug splitting, number of injection partners, and sharing cookers, cotton, or water) did not differ significantly between conditions, an overall composite score created from the six risk behavior items did achieve statistical significance – there was a 29% greater decline in 3 overall injection risk among the participants in the experimental condition compared to the control condition. Overall, behavioral interventions have yielded some effects in reducing injection risk behavior, though effects in some studies have been modest. It also appears that some protective effects may be attributable solely to the effect of participating in evaluation research itself (Gibson et al., 1998). Despite some gains associated with structural and behavioral interventions, injection risk behavior persists. Nearly 20 years after the first NIDA NADR studies were implemented, the 2005/2006 National HIV Behavior Surveillance Survey among IDUs found that 31% of surveyed IDUs reported sharing syringes and 33% reported sharing paraphernalia in the past year (Centers for Disease Control and Prevention, 2009). Importantly, only 27% of IDUs reported that they had participated in a behavioral intervention. And over two decades after the implementation of the first SEP, most IDUs still have too few new, sterile syringes to meet their daily needs (Bluthenthal et al., 2007; Monterroso et al., 2000). Thus, continued research into the individual, social, and environmental factors associated with persistent injection risk behavior is still needed, even among IDUs who have access to SEPs. The next section reviews one theoretical approach that has been widely applied to the study of injection risk behavior, and provides the theoretical orientation that guided this dissertation research. Cognitive Behavioral Theory in the Study of HIV Risk Behavior Among IDUs Over several decades, myriad studies have attempted to understand the factors associated with injection risk behavior among IDUs. Cognitive Behavioral Theories (CBTs), which focus on properties of the individual, are among the most commonly employed frameworks in the health research and intervention literature (Glanz et al., 1997), including the literature on individual-level correlates of risky injection behavior (Gibson et al., 1998), and form the theoretical basis for many of the individual- and group-level interventions discussed above. Among IDUs, considerable support has been amassed for some CBT constructs, while other theoretically- relevant constructs have received less empirical support or less scientific attention. For example, self-efficacy for safer behavior (i.e., one’s confidence in his/her ability to practice a behavior) is a 4 central construct in Social Cognitive Theory (Bandura, 1977), the Health Belief Model (Strecher & Rosenstock, 1997), Protection Motivation Theory (Rogers & Prentice-Dunn, 1997), the AIDS Risk Reduction Model (Catania et al., 1990), and the Information-Motivation-Behavioral Skills Model (Fisher & Fisher, 1992). In studies of injection risk behavior, high self-efficacy for safer injection has consistently been associated with lower levels of risk behavior (Avants et al., 2000; Brown, 1998; Falck et al., 1995; Gibson et al., 1993; Longshore et al., 1997; Longshore et al., 2004; Racz et al., 2007; Thiede et al., 2007) and changes in self-efficacy have been associated with changes in injection risk behavior over time (Kang et al., 2004). Social factors have also been identified as significant correlates of injection risk behavior in several studies. Perceived social or subjective norms represent the individual’s perception of his/her associates’ approval or disapproval of a behavior (i.e., normative beliefs), and are included in theories such as the AIDS Risk Reduction Model (Catania et al., 1990), the Information-Motivation-Behavioral Skills Model (Fisher & Fisher, 1992), and the Theory of Planned Behavior (Ajzen, 1991). Perceived social or subjective norms supporting safer injection practices have been found most frequently to be inversely associated with risky injection (Avants et al., 2000; Bailey et al., 2007; Jamner et al., 1996; Longshore et al., 1997; Longshore et al., 2004). Other social factors such as the structure and composition of the social network of IDUs have also been identified as important correlates of injection risk behavior (De et al., 2007). Other constructs such as response efficacy and perceived severity of HIV, though included in several CBTs, have received little attention and less empirical support. Response efficacy represents an individual’s belief that engaging in a protective behavior will successfully avert the health threat. One small cross-sectional study among in-treatment, HIV-positive IDUs found that individuals who engaged in syringe sharing were less confident that not sharing injection equipment reduces HIV risk (Avants et al., 2000), but others have found no association with injection risk behavior (Gibson et al., 1993; Hartgers et al., 1992; Jamner et al., 1996; Longshore et al., 1997; Longshore et al., 2004). Perceived severity, or the individual’s opinion of the seriousness of the illness in question and its consequences, is also an important variable in 5 several theoretical models, but has been examined by relatively few studies of injection risk behavior. Most have not identified strong associations between the construct and behavior (Brown, 1998; Hartgers et al., 1992; Racz et al., 2007), though Longshore and colleagues (2004) did find that fear of AIDS, measured with a single item “Getting AIDS is just about the worst thing that could happen to me,” had a significant indirect effect on injection risk behavior. A similarly worded question had no effect on syringe disinfection in another study (Longshore et al., 1997). Perceived risk is also a theoretically-important construct in CBTs including the Health Belief Model (Strecher & Rosenstock, 1997), Protection Motivation Theory (Rogers & Prentice- Dunn, 1997), the AIDS Risk Reduction Model (Catania et al., 1990), and the Information- Motivation-Behavioral Skills Model (Fisher & Fisher, 1992). However, there has been less scientific consensus about both the measurement and the magnitude and direction of effect of perceived risk on injection risk behavior. In research focusing on HIV, the perceived risk of becoming infected with HIV via injection-related behaviors has been measured variously as “perceived risk”, “perceived susceptibility”, and “perceived vulnerability” (Kowalewski et al., 1997). CBTs predict that increased perceived risk of HIV should be associated with decreased injection risk behavior. In fact, findings regarding the association between perceived risk and injection risk behavior have been mixed. Some studies have found an association in the expected direction - that is, high perceived risk of HIV infection via injection drug use has been associated with lower levels of risk behavior (Bailey et al., 2007; Smyth et al., 2001; Smyth & Roche, 2007). However, others have found the inverse – that increased perceptions of risk or susceptibility to HIV are associated with increased risk behavior (Booth, 1994; Falck et al., 1995; Hartgers et al., 1992; Racz et al., 2007; Robles et al., 1995). In still other cross-sectional studies, multivariate analyses detected no association between perceived vulnerability (Avants et al., 2000), perceived susceptibility (Gibson et al., 1993), or perceived risk (Stein et al., 2007) and syringe sharing. Several explanations have been put forth for these inconsistent findings. The inconsistencies may be an artifact of study design; in cross-sectional studies, a positive association may demonstrate an accurate assessment of risk (Kowalewski et al., 1997). Mixed findings may also reflect 6 differences in operational definitions; variously referred to as perceived susceptibility, perceived vulnerability, and perceived risk, the underlying concept has been measured differently, possibly leading to variations in results (Kowalewski et al., 1997; Strecher & Rosenstock, 1997). It is also possible that interactions with other variables may be confounding or moderating the effect of perceived risk and other CBT variables such that its influence is strengthened or attenuated in the presence of other variables. Perceived Consequences of Refusing to Share Injection Equipment The previous section summarized some of the most commonly employed CBT constructs in the research literature surrounding risky injection behavior. One factor that has received considerably less attention, but which may have an important role in explaining the “residual risk behavior” (Des Jarlais et al., 2007b) that persists in the presence of both structural and individual interventions, is the perceived consequences of refusing to share injection equipment. That is, the consequences that IDUs associate with refusing to use contaminated injection equipment. For over two decades, public health professionals have recommended that IDUs use only new, sterile syringes if they are going to inject drugs. While the perceived consequences associated with sharing injection equipment have been relatively well studied in terms of the risk of becoming infected with HIV or viral hepatitis (with mixed results, as reviwed above), fewer studies have investigated the consequences that IDUs might face if they follow the public health advice to refuse to use contaminated equipment. In the early stages of the HIV epidemic, Connors (1992) used qualitative methods to identify a “risk hierarchy” that included not only risks associated with sharing a syringe, but also risks associated with other behaviors involved in the IDU lifestyle. These included risks associated with stealing, dealing drugs, carrying drug injection equipment, and buying drugs. Participants identified both positive and negative outcomes associated with each behavior. For example, IDUs reported that there were some negative outcomes associated with sharing a syringe (i.e., infection with viral hepatitis, HIV, or other pathogens), but there were also positive outcomes (i.e., reduced chance of arrest, someone to 7 ‘get high’ with). Losing the opportunity to achieve these positive outcomes can be thought of as a perceived consequence of refusing to share the syringe. Other qualitative studies have identified risks associated with not sharing injection equipment that include violating social norms, economic consequences, and involvement with the criminal justice system. In a multi-year ethnography with a cohort of IDUs in San Francisco, Bourgois and Schonberg (2009) found that members of the group were highly economically and emotionally interdependent, relying on each other for protection, emotional support, housing, drugs, and access to other resources. Refusing to share injection equipment with friends or partners was virtually unthinkable due to the emotional and physical closeness of individuals. A refusal to lend or use a partner’s injection equipment would be a violation of social norms that bonded the group in a network of reciprocity. Koester and colleagues (1996; 2005) have shown how properties of the drug, the economic, and structural environment interact to create economic consequences of refusing to share injection equipment. Economic instability is pervasive among IDUs, who often form temporary or semi-permanent partnerships with others in order to accumulate enough money to purchase their daily supply of heroin. Since black tar heroin (the form typically available in the Western United States, including California) is generally purchased in sticky, resinous form, IDUs who pool money to purchase drugs together usually dissolve the drug into a liquid prior to dividing their purchase. Because syringes are scarce and few IDUs have sufficient coverage of syringes to meet their daily needs, syringes are often re-used multiple times before they are replaced. Refusing to use the contaminated equipment used in the preparation or injection of a shared drug purchase would result not only in a violation of social norms, but also in the loss of one’s share of the pooled drug purchase. The threat of arrest or incarceration is also a consequence that weighs heavily on IDUs (Burris et al., 2004; Connors, 1992). Because the possession of injection paraphernalia is illegal in the United States (despite sanctioning of SEPs by local jurisdictions), IDUs must contemplate the legal ramifications of maintaining a supply of sterile injection equipment in their possession 8 (Friedman et al., 2006). In California, individuals using locally-sanctioned SEPs were found to be at increased risk of arrest for violating paraphernalia laws (Martinez et al., 2007). Others have found that IDUs who are concerned about arrest due to possession of drug paraphernalia are more likely to report syringe sharing (Bluthenthal et al., 1999a; Bluthenthal et al., 1999b). Understanding the perceived consequences of engaging in safer injection behavior (i.e., of refusing to share injection equipment) is important because individuals weigh many risks when they decide whether or not to engage in a behavior that places them at risk for HIV – the risk of HIV infection is contextualized within a hierarchy of other possible outcomes that also affect the decision (Kowalewski et al., 1997). The studies reviewed here provide some hint about the types of consequences that might be perceived by IDUs: social consequences such as the violation of social norms, economic consequences such as loss of resources, and legal consequences such as the risk of being arrested or incarcerated for possession of drug paraphernalia. It is unknown how these consequences might interact with other, more well studied theoretical constructs posited to explain HIV risk behavior, such as perceived risk of HIV via IDU or self-efficacy for safer injection. However, it is possible that accounting for the perceived consequences of safer injection behavior might help explain inconsistent or null findings, or may explain additional variance in injection risk behavior that is not explained by other theoretical constructs. Female IDUs and HIV Among IDUs, women have been shown to be at elevated risk for HIV infection via injection drug use compared to their male IDU counterparts (Dwyer et al., 1994; Fennema et al., 1997; Garfein et al., 1996; Monterroso et al., 2000). Though biological differences such as the way women metabolize drugs may have some effect (Hankins, 2008), the difference in risk between men and women has generally been attributed to higher-level factors. In fact, many of the factors that increase women’s risk for HIV pertain to the social environment in which women live and use drugs (Barnard, 1993; Bourgois et al., 2004; Cruz et al., 2006; Epele, 2002; Latkin et al., 1998; Miller & Neaigus, 2001). Women more commonly use drugs with individuals with whom they have a relationship (Barnard, 1993; Cruz et al., 2006), and women’s social networks tend to 9 include more hard drug users and IDUs (Montgomery et al., 2002). Women also report more overlap between drug and sexual networks, increasing their exposure to bloodborne pathogens among both their drug-using and sexual partners (Latkin et al., 1998; Miller & Neaigus, 2001). Further, women share syringes with riskier individuals in their social networks, such as those known to be HIV-positive (Dwyer et al., 1994). Dependence on others for access to drugs is associated with increased syringe sharing (Sherman et al., 2001), and women’s access to drugs, injection paraphernalia, and other resources is often controlled or determined by others (Barnard, 1993; Bourgois et al., 2004; Epele, 2002; Simmons & Singer, 2006). Finally, women often relinquish control over the preparation and injection processes to others, usually their male partners (MacRae & Aalto, 2000). Not feeling in control over the injection event has been associated with unsafe injection among women (Tortu et al., 2003), and HIV infection has been shown to be almost twice as high among those who require help injecting (O'Connell et al., 2005). Given the persistent gender differences in HIV risk, and women’s heightened vulnerability due largely to social and environmental factors, it is incumbent upon researchers to evaluate the role of gender when investigating factors associated with injection risk behavior. Based on the findings presented above, it is likely that the perceived consequences of safer injection will differ for men and women. Specifically, women’s risk behavior is likely to be more strongly associated with social consequences, such as those relating to violation of social norms or dependence on others for money, drugs, or other resources. Further, it is likely that the association between perceived consequences and injection risk behavior is stronger for women, who may be less in control of their drug use and drug preparation, and who may have less access to resources than their male counterparts. Overview of the Dissertation This dissertation study was designed to identify the perceived consequences of refusing to engage in risky injection behavior (i.e., “refusing to share”), to determine whether those consequences interact with other cognitive behavioral constructs in explaining injection risk behavior, and to evaluate gender differences in the observed associations. These aims were 10 accomplished in a two-phase, mixed-method study. Detailed analytic methods specific to each analysis are presented in the corresponding chapters. The next section presents an overall description of the study design and methods employed in the larger study. Methods Study Design. In brief, the study was conducted in two phases using a mixed-methods design. In Phase One, in-depth qualitative interviews were conducted with 30 male and female IDUs recruited from a single SEP in Los Angeles, California. The in-depth interviews explored the circumstances surrounding the most recent episode of risky injection, and identified the perceived consequences of refusing to share injection equipment in that instance. In Phase Two, findings from the qualitative study were used to develop a series of quantitative items that assessed the perceived consequences of refusing to share. A quantitative survey containing the perceived consequences items, as well as measures of demographics, injection risk behavior, and other theoretical correlates of injection risk behavior was administered to a larger sample of 200 male and female IDUs recruited from the same SEP. Field Site. All study activities took place at a single SEP located in Los Angeles, California. This SEP is located in an area characterized by high rates of homelessness and drug use (Los Angeles Homeless Services Authority, 2007). The SEP provides services to approximately 600 active IDUs who access a variety of services at its store-front location, including syringe exchange, referrals to drug treatment, HIV testing, and primary medical and wound care. Participants in the SEP are approximately 25% female, 37% African American, 59% White, and 33% Latino. A recent survey reported significant past-30 day injection risk behavior among participants in this SEP: 26% report sharing a syringe, 49% report sharing a cooker to prepare drug solution, and 40% report sharing rinse water (Bluthenthal, unpublished). Phase One – Qualitative Interviews Detailed descriptions of the eligibility criteria, sampling strategy, interview guide, and analysis methods for Phase One are presented in Chapter 2. Briefly, Phase One consisted of in- depth qualitative interviews. Qualitative methods have been successfully employed in a variety of 11 IDU populations, and are valued for the detailed insider’s view that they provide (Clatts et al., 1995; Singer et al., 2000). Qualitative interviews yield narrative data and “thick description,” which can be presented alone or combined with quantitative findings to provide additional insight into the topic of interest (Agar, 1997; Lankenau & Clatts, 2004). The qualitative interview consisted of a one-hour, in-depth, semi-structured interview that was digitally recorded and transcribed in its entirety. Qualitative interviews explored the circumstances surrounding the most recent occasion of risky injection, and elicited the perceived consequences that would have resulted if the individual had refused to share injection equipment at that time. The interview guide was pilot tested with five IDUs prior to implementation to ensure comprehension, and adjustments in question wording were made prior to implementation. Findings from a qualitative analysis investigating gender differences in the perceived consequences of refusing to share are presented in Chapter 2. Phase Two – Cross-sectional Quantitative Survey Detailed descriptions of the eligibility criteria, sampling strategy, measures, and analyses for Phase Two are presented in Chapters 3 and 4. Briefly, in Phase Two findings from the qualitative analysis were used to develop a quantitative measure of perceived consequences of refusing to share injection equipment, which was included in a cross-sectional survey of 200 IDUs at the same field site. In addition to the perceived consequences measure, the survey assessed demographics, drug use behavior, injection risk behavior, and other correlates of injection risk behavior. Surveys were administered at the SEP using Audio Computer Assisted Self- Interviewing (ACASI) technology, in which participants listened to the questions being read to them through headphones and entered their answers directly into a laptop computer. ACASI methods have been shown to be particularly effective in capturing sensitive behavioral data (such as HIV risk behaviors) that might otherwise be heavily biased by socially desirable reporting (Des Jarlais et al., 1999; Macalino et al., 2002). Previous research indicates that IDUs can provide reliable and unbiased responses to questions using a 30-day reference period (Needle et al., 1995), therefore all risk behavior questions referred to the previous 30 days. The survey was 12 pilot tested with five IDUs and necessary adjustments in question wording or formatting were made prior to implementation. Two analyses resulted from the second phase. First, the psychometric properties of the perceived consequences measure were assessed, and multiple linear regression was used to investigate the association between perceived consequences, injection risk behavior, and gender. Findings from this analysis are presented in Chapter 3. Second, structural equation modeling was used to assess the association between theoretically relevant constructs and injection risk behavior, and to determine whether the associations were moderated by the perceived consequences of refusing to share. Results of this analysis are presented in Chapter 4. 13 CHAPTER 2. GENDER DIFFERENCES IN THE PERCEIVED CONSEQUENCES OF SAFER INJECTION: A QUALITATIVE STUDY Chapter 2 Abstract Injection drug users (IDUs) are at risk for HIV and other bloodborne pathogens via syringe and paraphernalia sharing, and women are at elevated risk. Consequences of injection risk behavior such as the risk of becoming infected with HIV have been relatively well studied, though less is known about the consequences of refusing to share injection equipment. We conducted in-depth qualitative interviews with 26 IDUs to understand the consequences that IDUs associate with refusing to share injection equipment and to determine whether consequences differ by gender. Using the Risk Environment framework, consequences were organized into four domains: individual (drug withdrawal, forgoing drug use), social (trust, IDU social norms, non-IDU social norms), physical (syringe access/inconvenience), and economic/policy (economic consequences, legal consequences, threats to housing). Gender differences were identified in some, but not all areas. Implications for integrated intervention strategies are discussed. 14 Introduction Since the beginning of the AIDS epidemic, dramatic decreases in HIV-risk behavior have been observed among injection drug users (IDUs; Des Jarlais & Semaan, 2008; Santibanez et al., 2006), particularly among those who access Syringe Exchange Programs (SEPs; Ksobiech, 2003). In some communities that experienced early HIV epidemics among IDUs (e.g., New York City) SEPs have been credited with reductions of HIV incidence, while in other areas (e.g., the U.K.) the early implementation of SEPs may be at least partly responsible for the avoidance of large-scale HIV epidemics altogether (Stimson, 1995). Despite these advances, even in areas with active SEPs many IDUs continue to engage in risky injection behavior. The most recent National HIV Behavior Surveillance Survey among IDUs found that from 2005-2006, 31% of surveyed IDUs reported sharing of syringes and 33% reported sharing paraphernalia in the past 12 months (Centers for Disease Control and Prevention, 2009). Consequently, IDUs continue to be at risk for both HIV and other blood-borne pathogens such as hepatitis C virus (HCV), and research is needed to understand factors contributing to continued risk behavior. Theories of health behavior such as the Theory of Reasoned Action propose that behavioral intentions and, ultimately, behavior, are influenced by attitudes towards a behavior (Fishbein, 1967). A major contributor to the formation of attitudes towards the behavior is the perceived risk, or consequences, associated with the behavior. The perceived consequences of sharing injection supplies have been relatively well studied in terms of the risk of HIV or HCV infection, though findings about the direction of influence have been mixed (e.g., Bailey et al., 2007; Racz et al., 2007; Robles et al., 1995). It has been argued that the identification of HIV and HCV risk as the primary outcome of interest represents an externally constructed, or outsider’s perspective, formulated by well-meaning public health practitioners with a focus on prevention of infectious disease transmission (Connors, 1992; Kowalewski et al., 1997). Though less well-studied, other risks or consequences may be equally or more important in influencing behavior from the IDU’s insider perspective. In one early study, Connors (1992) investigated risk perceptions among a small sample of IDUs enrolled in drug treatment. She 15 identified a “risk hierarchy,” in which IDUs considered a host of socially- and environmentally- contextualized risks in addition to the risk associated with syringe sharing; reducing the risk of HIV via syringe sharing often required increasing risk in other areas such as risk of arrest, death from overdose, or rejection by peers. Since then, few studies have examined the perceived consequences or risks associated with adhering to public health recommendations that IDUs use new, sterile injection supplies for each injection and refuse to share equipment with others. Understanding the perceived consequences of engaging in safer injection behavior is important because individuals weigh many risks when they decide whether or not to engage in a behavior that places them at risk for HIV – the risk of HIV infection is contextualized within a hierarchy of other possible outcomes that also affect the decision (Kowalewski et al., 1997). Among IDUs, certain subgroups may be particularly vulnerable, and studies have found women to be at elevated risk for HIV infection via injection drug use (Fennema et al., 1997; Garfein et al., 1996). The social environment in which women use drugs has been identified as an important risk factor (Miller & Neaigus, 2001), which is relevant to a discussion of the consequences that might be associated with refusing to share injection equipment. Women’s drug-using network are frequently composed of friends or sexual partners (Barnard, 1993; Cruz et al., 2006), and their drug and sexual networks often overlap (Latkin et al., 1998; Miller & Neaigus, 2001). This implies that women may be more sensitive to social consequences of refusing to share injection equipment, since the individuals with whom they use drugs are more likely to be intimates. Some studies have found that women’s access to drugs, injection paraphernalia, and other resources is often controlled or determined by others (Barnard, 1993; Bourgois et al., 2004; Epele, 2002; Simmons & Singer, 2006). Finally, women’s preparation and injection of drugs is also often controlled by others, usually their male partners (MacRae & Aalto, 2000). These findings suggest that there could be serious consequences associated with violating social norms or expectations regarding syringe or paraphernalia sharing – namely the withholding of drugs and/or supplies by partners – and that women may be more vulnerable to these consequences. 16 In order to more fully understand the risks associated with refusing to share injection equipment, we conducted in-depth qualitative interviews with IDUs recruited from a large SEP who reported recent syringe or paraphernalia sharing. We asked these individuals to describe the circumstances surrounding their most recent risky injection event, and to identify the perceived consequences of refusing to share injection equipment in that instance. We use Rhodes’ (2002) Risk Environment framework as a heuristic for understanding the environmentally-situated nature of these risky injection events. The Risk Environment framework is comprised of four types of environmental influence: physical, social, economic, and policy. Because, ultimately, perceived consequences are still situated on the individual level, we also include discussion of individual-level factors. In addition, since epidemiological and behavioral data have found women to be at elevated risk for HIV via injection drug use when compared to men (Monterroso et al., 2000), and since it is likely that these differences are due at least in part to higher level social and environmental factors (Bourgois et al., 2004; Epele, 2002; Latkin et al., 1998; Miller & Neaigus, 2001), we examined whether the narrative accounts differed by gender. Methods Setting and Participants Study participants were recruited from an SEP Los Angeles, California. The SEP operates for a total of 34 hours, Monday through Friday and provides services to approximately 600 individuals. A maximum variation sampling strategy (Patton, 2002) was employed to capture diversity of opinions and experiences. Recruitment occurred during a variety of days and times when the SEP was open, in order to generate a diverse sample of SEP participants. A recruiter approached individuals presenting at the SEP for any reason (i.e., to access syringe exchange services, medical care, case management, etc.) to ask if they were interested in participating in a research study. Interested individuals were escorted to a semi-private area where they were asked a series of screening questions to determine eligibility. The eligibility criteria for the study were: 1) being at least18 years old, 2) having injected any drug at least once in the past 30 days, and 3) having engaged in a risky injection event at least once in the past 30 days. Risky injection 17 was defined as any of the following: using a previously used needle, sharing a previously used cooker, sharing a cotton or rinse water, or syringe-mediated drug splitting (i.e., backloading or piggybacking) with previously used needles or cookers. The eligibility criteria were embedded in a longer screening interview that also contained “red herring” questions in order to mask the eligibility criteria, similar to other studies (Garfein et al., 2007b). Eligible individuals were invited to participate in the study, and provided written informed consent. Interviews were conducted in a private office at the SEP. In order to allow for gender comparisons, the goal of the sampling strategy was to enroll 50% women. All eligible participants were enrolled until 15 men were sampled, after which only women were screened and enrolled until a total of 30 interviews had been conducted. Interview participants received $25 for their participation. The first author conducted all study activities. The University of Southern California Health Sciences Institutional Review Board approved all study procedures. Measures First, the interviewer administered a short questionnaire containing closed-ended questions about demographics (e.g., age, race, sex etc.), HIV and HCV status, and drug use behavior. Next, the interviewer administered a semi-structured qualitative interview. The qualitative interview guide was based on a “last event” methodology (see Tortu et al., 2003), which asked the participant to describe the most recent injection episode in which he/she shared any injection equipment. Participants described the circumstances surrounding the injection, including the person or people present, the location, time, day, and other environmental factors. Next, participants described the decision-making process that lead to the occasion of risky injection. Finally, participants discussed the consequences or problems that might have arisen if they had refused to engage in the risky behavior on that occasion and about the kinds of responses that such a refusal might generate from others. Analysis Quantitative data from the demographic and drug use questionnaire were entered into a database and exported to SAS 9.1 for analysis. Univariate statistics were generated for all 18 variables in order to describe the sample, including measures of central tendency and dispersion. Qualitative interviews were digitally recorded, transcribed in their entirety, and imported into the ATLAS.ti software program for analysis. First, transcripts were read in their entirety and a series of “memos” was developed, which documented initial impressions (Miles & Huberman, 1994). Second, a list of codes was developed, based on a priori categories from the literature, as well as emergent themes from the interviews (also known as “open coding”; Strauss & Corbin, 1997). These codes were applied to segments of text and organized into a series of hierarchical “trees”, with higher- and lower-order codes within each “tree”. When new codes emerged from the transcripts during the coding process, the emergent codes were added to the existing list, and all transcripts were reviewed again to ensure the coding of relevant passages. Third, interview transcripts were again read in their entirety and a summary of each “case” was created. Fourth, two types of reports were generated. Network diagrams, which graphically illustrated the relationship between higher- and lower-order codes, were created in order to identify the density and interconnectedness of relationships between codes. Thematic reports, which contain blocks of coded text from all the interview transcripts, were generated through use of the method of constant comparison (Glaser & Strauss, 1967) in order to identify common themes and to allow for gender comparisons of findings. All names used in this report are pseudonyms. Results Recruitment and data collection occurred during July 2008. During this time, 43 individuals were screened for eligibility. Of those, 30 (70%) reported any injection risk behavior and were determined to be eligible for the current study. Of the 30 IDUs enrolled, 4 were dropped from analysis due to inconsistencies in their answers, or the later discovery of their ineligibility. This left an analytic data set of 26. The demographic characteristics of the sample are presented in Table 2.1. Participants had a mean age of 43 years, and initiated injection drug use approximately 20 years prior. Just over half of the sample was female. The racial composition of the sample was 46% Hispanic/Latino, 23% White, 19% African American, and 12% other. Over three-fourths reported being currently homeless, with 45% reporting that they 19 lived most frequently in a shelter during the past 30 days. Twenty-five individuals had ever received and HIV test, and three (12%) reported being HIV positive. Twenty-four had ever received an HCV test, and 16 (67%) reported being HCV positive. Heroin was by far the most frequently used drug, with 96% reporting it as the drug they injected most in the past 30 days. Participants reported injecting an average of 4.2 times per day (SD = 2.1), 6.4 days per week (SD = 1.5). All had used an SEP prior to the day they were interviewed; the mean duration of SEP use was 5.8 years (SD = 4.7), and 73% accessed the SEP once a week or less. Table 2.1. Demographic characteristics of study sample (N=26). n % Age (mean; SD) 42.9 (9.2) Age at initiation of IDU (mean; SD) 22.3 (9.0) Female 14 54% Race/Ethnicity Hispanic/Latino 12 46% White 6 23% African American 5 19% Other 3 12% Homeless 20 77% HIV Positive* (n=25) 3 12% HCV Positive* (n=24) 16 67% Drug of choice: Heroin 25 96% Daily frequency of injection (mean; SD) 4.2 (2.1) Weekly frequency of injection (mean; SD) 6.4 (1.5) Duration of SEP use (years; mean; SD) 5.8 (4.7) *self-report Perceived risk of HIV or HCV The perceived risk or consequence of becoming infected with HIV or HCV via shared injection equipment has been relatively well studied, and emerged as a theme in this study as well. However, participants painted a complicated picture of the perceived risk or consequence of becoming infected with HIV or HCV. When speaking generally about the re-use of injection supplies, participants said that they “never” shared needles, and alluded to needle sharing as being especially risky in terms of the consequence of HIV infection. However, among the 26 participants, 14 (54%) said that their most recent risky injection episode involved using a needle previously used by someone else. When asked whether they trusted the individual with whom they shared injection equipment, most emphatically replied “no.” However, few had explicitly 20 discussed the individuals’ HIV or HCV status before using the donated equipment; moreover, despite previously saying that they do not generally trust their injection partners, many said that they believed their friends or partners would tell them if they had HIV. An exception was Samantha, an HIV/HCV-positive 44-year-old white woman who described an injection event in which her HIV/HCV-positive friend surprised her with heroin that he had bought for the both of them. He prepared the drugs and injected himself in the bathroom, and then injected her with the same syringe. She explained her rationale for using the shared equipment, “His HIV is barely detectable. [And] he’s got hep C. It’s just not as bad as me. Let’s just put it that way. He’s more lucky than I have been.” She believes he would have gone out and bought a new syringe and cooker for her, if she had asked, however she did not consider asking. Unlike Samantha, many HIV-negative individuals said they definitely would not share with someone who was HIV positive; however, few reported having a recent HIV test, and among the three HIV-positive individuals, two said that they had passed on their used injection equipment to others. Due to a perception of the near-universal prevalence of HCV, few individuals in this sample appeared concerned about their risk of becoming infected with HCV. In fact, 67% of individuals in this sample said that they were HCV-positive. Thus, while participants did identify the consequence of HIV infection as something they were concerned about, it appears that there are other influences affecting risk behavior that may be more immediate, more severe, more certain, or in some other way more salient than the risk of HIV or HCV infection. The remainder of this manuscript will describe individual, social, physical, and economic/policy consequences of refusing to share injection equipment that might be useful in understanding the persistence of risk behavior among IDUs. Individual Factors: Withdrawal and forgoing drug use Withdrawal. The risky injection events described by participants were overwhelmingly characterized by the desire to avoid the consequence of experiencing severe withdrawal symptoms associated with delayed use of heroin. This is perhaps not surprising given that the majority identified heroin as their drug of choice, and they injected quite frequently – an average 21 of four times per day, six times per week. Respondents generally stated that they already were or were on the verge of becoming “dopesick”, and were attempting to avoid the symptoms associated with withdrawal from heroin, including nausea, vomiting, runny noses, or aches and pains. Dopesickness was described as an everyday problem associated with heroin addiction, and a highly significant consequence of refusing to share injection equipment. Sarah, a 48-year old Latina, described sharing a single needle and cooker with her injection partner for the entire day, since they had missed coming to the SEP that day. When asked what the consequence would have been if she had refused to use the previously used needle and cooker, she said: We would have stayed sick. So there’s no way in the world. I’m sorry, if there’s an outfit on the ground that I find, and I don’t have money for a needle, and nobody’s going to give me one, and I’m sick, I’m gonna use that damn outfit! And I’m not gonna sit there trying to sterilize it. While some individuals like Sarah expressed a degree of defiance or resignation in their account of sharing equipment in order to prevent withdrawal symptoms, several others expressed a sense of regret or heightened vulnerability after the fact, stating that they “knew better,” but couldn’t act on that knowledge in the moment. For example Chloe, a 47-year-old Latina said: I got up that morning, and I was sick. And I didn’t have my own equipment. And after [my injecting partners] had used it, I asked them if I could – God – I asked them if I could use theirs… And then I kind of like, hesitated for a moment …and that- that’s sad. You know? I just went ahead and used it and didn’t think about it. Not even twice. And then it didn’t dawn on me until after – “What the hell am I doing?” I know better. And it’s just…I was sick. Forgoing drug use. For some respondents, the consequence associated with refusing to share injection equipment was forgoing drug use altogether. Men and women differed in the frequency with which they said they would have gone without drugs. Men were more likely than women to describe scenarios in which they were using drugs spontaneously with friends, often who provided the drugs for free. Some men said that they were already high at the time of the event they described. For these men, a refusal to engage in the risky injection event would have simply meant they would not have used at all. For example Carlos, a 34-year-old Latino man, had picked up his injection supplies at the SEP and stayed to watch a movie. Because he had not planned on using again that afternoon, he did not pick up any cookers. After leaving the SEP, he 22 was invited for a “pit stop” in a public toilet that is frequently used by IDUs as a place to inject. Realizing that he had not picked up any cookers, he prepared his drugs in a cooker used previously by his friend. When asked what would have happened if he had refused to use that cooker, he said, “Probably nothing. But my dumb ass wanted to get more high, so…that’s all the brain was thinking. Get loaded. Get loaded.” Others said that they were not “strung out” (i.e., dependent on the drug) and therefore were not concerned about experiencing withdrawal. Only two women described such a scenario. Social Factors: Trust, IDU social norms, non-IDU social norms Trust and social norms among IDUs. Some individuals said that a refusal to share injection equipment, particularly the equipment of someone with whom they had shared before, would result in hurt feelings – though these type of social consequences were rarely volunteered and were usually discussed only after an explicit probe by the interviewer. For example, Sarah described the expected response from her female injection partner, who she previously described as “like a sister to me”: She’d probably feel a little sad because I don’t trust her. We’re so close. It would kind of hurt her a little bit, you know? Because if somebody don’t want to fix after me, I’m like, you know, “There’s nothing wrong with me, you know?” Or “You’re scared of me. That’s why you won’t fix behind me.” It’s weird, you know? Often, respondents said that a refusal to share injection equipment would be tantamount to an accusation that the individual was HIV-positive, conferring a great deal of stigma. However, in most cases respondents said that the social consequences carried very little severity; although respondents did identify the hurt feelings of their partner as a consequence, most said that it would not have had much significance in determining their behavior. Descriptions of the social consequences of refusing to share injection equipment were relatively consistent between men and women. Differences emerged, however, in the types of relationships that participants described. Men were more likely to report sharing equipment with a stranger – no women reported this. Women were more likely to describe events that involved sex partners – no men reported this. Men and women were about equal in the frequency with which they described events involving friends and acquaintances, but women were much more 23 likely to report that these friends or acquaintances were of the opposite sex, while men generally reported same-sex friends. Non-IDU social norms. For some, the social consequence of carrying syringes or injection supplies had to do with a concern about violating the social norms of non-IDU peers, or having to conceal drug use from non-drug using friends or family. Sometimes, these relationships with non-IDUs were valued due to their ability to provide resources. For example, women who engaged in sex work said they do not carry syringes so that their clients do not discover their IDU status, a discovery which could compromise their ability to earn money. IDUs who did not carry syringes in order to avoid violating social norms of their non-IDU peers frequently found themselves in situations in which they were forced to borrow used equipment in order to inject. Carlos, who previously described using a cooker after his friend when they stopped to inject in the public bathroom on their way home from the SEP, said that he was not carrying cookers because he had planned to spend the evening with a non-IDU friend who would not tolerate his drug use. Physical Factors: Syringe access/inconvenience Even among IDUs who have fairly regular and reliable access to injection supplies via the SEP and over-the-counter pharmacy sales, the inconvenience of accessing sterile injection supplies was a common theme. For some, the time or difficulties involved with procuring sterile supplies were too great of an inconvenience, when presented with the opportunity of injecting immediately with used equipment. Jose, a 47-year-old Latino man, described what he would have had to do to get his own injection equipment, which he had hidden in the park where he sleeps: Oh, wow. I would have had to walk …[it] takes 10 minutes to walk waaaay to the other side of the park. Then, you got to look around, see if it’s safe. Because they have those, ah, like some type of cops patrol the area. And then you’ve got to walk all the way back to the other side, and it’s hot and I’m sick. And you know, all the shit that you’re supposed to look at that you don’t want to look at. That you don’t want to focus on. Others described the potential of having to wait hours until they would have been able to travel to the SEP, or to their home or camp, usually walking or via public transportation. Mike, a 24 28-year-old Latino man, described how he had pooled his money with a stranger he met while buying drugs, and proceeded to prepare and inject with her on the street. His injection supplies were with his possessions at a local shelter located 0.2 miles from where they injected (a five minute walk, from his account); however, rather than returning to the shelter to procure his own supplies, he allowed her to inject him in his neck using one of her previously used syringes. He said he was more concerned about the inconvenience and the consequence of police involvement due to the high visibility location in which they were injecting (particularly because he was absconding from parole), rather than the risk associated with using contaminated injection equipment. Economic/Policy Factors: Economic consequences, legal consequences, threats to housing Economic consequences. Respondents discussed two related forms of economic consequences: the expense related to purchasing injection supplies, and the expense of the drugs. Several individuals said that if they had not used the shared injection supplies, they would have had to spend money (which they often did not have) to buy new ones. Though the SEP is open for 7.5 hours, five days per week, there are still days and times that the SEP is closed. Packaged syringes are generally available for purchase on the street for about one dollar. However, the availability and pricing of syringes and other injection supplies varies depending on the day, time, and neighborhood. One man described how some IDUs lend, or “pimp”, their used needles over long weekends, when they know that the SEP is closed and they can take advantage of those IDUs who do not have sufficient supplies to get through the weekend. Frequently, respondents who did not have injection supplies with them and who did not have money to purchase new supplies would “borrow” a needle or cooker, and return it to the donor after using it. Similarly, some respondents described “kicking down” the cotton filter or cooker, both of which contain drug residue, to another IDU in exchange for use of the equipment. There was generally an assumption of reciprocity – people expected that if they helped a friend, it would come back to them in the form of help when they were in need. Violation of this norm of reciprocity was rarely considered, and such a violation would confer its own set of social 25 consequences. In this way, the interaction of two types of consequences – economic and social – led to informal barter and exchange of drugs and injection supplies in a network of distributive and receptive sharing that was rarely acknowledged as a risky activity by respondents. The consequences of violating such arrangements involve having to procure additional funds and the risk of offending injection partners. Others said that they had contributed money to the purchase of shared drugs, and needed to share the communal drug preparation equipment in order to make good on their investment. The obvious consequence of refusing to use the shared equipment was the loss of the investment in the shared drug purchase – a risk few heroin-using IDUs would consider. In still other cases, purchasing drugs or facilitating a purchase resulted in receiving drugs in the form of a “kick down” from others, often using shared equipment. Tammy, a 41-year-old Latina describes such an arrangement, which resulted in using her friend’s used syringe to split the drug solution. She said that a friend arrived at her house with two friends and asked her to purchase heroin for them, because they could not find a dealer on their own. Tammy is known as someone who always has a good “connection,” and who can be relied upon to find heroin if others are having trouble. In return for the favor of purchasing the heroin for them, Tammy demanded a “kick down”, or a share of the purchase. She explains: I told them, “…. I know you guys come from the old school. You know you kick down.” If somebody scores for you – that’s how old school is. So I got everything [the drugs and injection supplies]. Two of the guys were going in [purchasing] with each other already, so the one that was buying on his own, I told him, “You’re going to kick me down, OK?” So in order for me to get kicked down, they had to go to my house and do it. Or else I wasn’t going to get the kick down. It was important for Tammy to preserve her reputation as someone who can find drugs when others are unable, and it was critical that she receive payment for the service. Refusing to take her share of the purchase might have led others to take advantage of her services in the future. Legal consequences. For some, injecting with shared equipment avoided the need to commit crimes in order to earn money to purchase sterile injection supplies, with the potential consequence of being arrested for that crime. Others reported preparing and injecting the drugs with the available (used) equipment in order to minimize their risk of being cited or arrested for 26 possession of needles or drugs. Lamar, a 49-year-old African American man, described his fear of being arrested for the heroin he had in his possession when he was in a group that had been stopped by police. While the police did not detain him, they did keep one of his peers for questioning. He explained, “I felt that [the police] saw our faces, and if they saw us again they may stop us. And I didn’t want to go through the same thing [my friends] just went through.” He slipped away to the public restroom around the corner with four other people, where he and two of his friends prepared the drugs with a previously used cooker and cotton, and he injected with his own, previously used syringe. Several individuals were concerned about violating the stipulations of their parole or probation if they were to be caught with injection equipment, and said that as a rule they do not carry injection supplies with them. Rather, they purchase them on the street or pick them up at the SEP immediately before they plan to inject. For many, this policy of not carrying injection supplies to avoid the consequence of arrest or possible incarceration created scenarios in which spontaneous drug injection often required borrowing previously used equipment from other IDUs. Threats to housing. Most of the individuals in this sample (77%) were homeless, and many reported spending at least some nights in a shelter or other type of transitional housing. Most shelters are drug-free, and residents are not allowed to possess drugs or drug paraphernalia on the premises. For some, then, maintaining a supply of sterile injection supplies in the shelter carried the consequence of losing their bed in the shelter if they were to be caught. Several individuals described hiding places outside the shelter such as in the bed of a truck, behind trashcans, or in the bushes. Others said that they simply did not carry injection supplies, since they knew they could not bring them into the shelter, and ended up borrowing supplies when they were in need. Particularly among women, homelessness or precarious housing situations interacted with social consequences to contribute to risky injection behavior. For example Carmen, a 38- year-old Latina, described camping out for the first time with a group of IDUs in a parking lot. She had recently left a different camping area because a man had been making sexual advances 27 towards her – touching her and touching her hair. She knew some, but not all, of the individuals in this new camping area, and when someone in the group asked for a cooker, she lent him hers. Later, she used that cooker for her own injection. Given that she had recently left her other housing situation and was attempting to integrate herself into this group, refusing to share her supplies would have made this integration problematic, possibly leaving her without a safe place to sleep: It would have made me feel bad. But it would have been smarter for me to do. And it probably would have, um, not gotten me on their bad side, but, I guess, [I would have been] not so accepted. Like, they probably would have put up a little wall or something. In another example of how precarious housing, addiction, and social forces interact, Beth, a 42-year-old Latina, described how after her husband went to jail, the landlord of her SRO where she lived started making sexual advances towards her. After refusing him, he kicked her out of her apartment. She felt vulnerable on the street without her husband to protect her, and appealed to her dealer for a place to stay for the three weeks until her husband was released. She describes negotiating the use of the dealer’s syringe the first day that she stayed with him: When I went back with him, he goes, “You haven’t fixed [injected heroin] yet, huh?” I go, “No.” He goes, “OK, where’s your syringe?” I go, “I don’t have a syringe, you know that. I already tell you, I never carry nothing. You know that.” He usually has new ones for me when I go down there…he says, “Well, I don’t have a new one today. What do you want to do? You want to snort it? Or you want to use my needle?” I go, “Do you have anything? Are you sick? You don’t look it, but are you?” He goes, “No. C’mon, man. If I was sick, I would tell you. We’ve known each other too long.” I go, “Yeah, that’s what they all say. But just do what you got to do. I’ll rinse it out. Give me some bleach.” If she had refused to use his needle, she risked offending him by implying she did not trust him or that he was “sick.” Because she was depending on him for a safe place to sleep until her husband was released, the consequence to her housing situation and safety could have been dire. This quid pro quo of borrowing and lending injection supplies in return for a safe place to live was unique among women in this sample – no men described such arrangements. Discussion In this study we asked IDUs recruited from an SEP to describe the circumstances surrounding their most recent risky injection episode and to identify the perceived consequences of refusing to share injection equipment. We used a Risk Environment framework to organize 28 the individual, social, physical, and economic/policy factors associated with the most recent risky injection episode. Individual-level consequences included experiencing withdrawal symptoms or forgoing drug use altogether. Social-level consequences included: violating the trust of an IDU partner, accusing an IDU partner of having HIV, and violating social norms against drug use held by non-IDU peers. Physical-level consequences included difficulty or inconvenience associated with accessing sterile injection supplies. Economic/Policy-level consequences included: the risk of being arrested or cited for drug or paraphernalia possession or, violating the stipulations of probation, the expense of buying new supplies, the risk of losing ones investment in a shared drug purchase, the risk of losing a shelter bed due to paraphernalia possession, and the risk of getting kicked out of safe housing. Importantly, few individuals in this study reported a single consequence, or described a single domain affecting their injection behavior. More frequently, individuals described interactions between individual, social, physical, and economic/policy-level factors, or between several different consequences. Often, the consequence of experiencing withdrawal symptoms (an individual-level consequence) interacted with social (e.g., violating social norms related to trust) or economic (e.g., being dependent on another IDU for a share of the drugs or for safe housing) consequences. For many participants, the immediate concern of avoiding withdrawal symptoms trumped any other concerns. Given the long injection careers (approximately 20 years) and high frequency of injection (average of 4 times per day, 6 days per week) reported by this heroin-using sample, it can be surmised that the avoidance of withdrawal symptoms is an everyday challenge and a very serious consequence to be avoided (Bourgois & Schonberg, 2009; Connors, 1992). Several individuals described being unable to act on the knowledge or intentions that they hold in regards to safer injection, when faced with the more immediate or more severe consequence of experiencing withdrawal symptoms. The risk of experiencing withdrawal symptoms appeared to more severely affect women, who may have fewer resources and/or fewer connections from whom to obtain drugs and/or injection supplies. Some have proposed that drug treatment 29 (specifically methadone maintenance) can be an effective form of HIV prevention intervention (Sorensen & Copeland, 2000), though support for the effectiveness of other treatment modalities may require more research. Our findings support the idea that drug treatment, even if resulting in only temporary reductions in use, may be an important risk reduction intervention, particularly for individuals who articulate their inability to act on behavioral intentions due to the overwhelming influence of the effects of drug addiction. Social norms that favor risky injection practice have been associated with injection risk behavior (Bailey et al., 2007; Hawkins et al., 1999; Latkin et al., 2003). In this study, we found that the violation of social norms for syringe or paraphernalia sharing had the potential to alienate individuals from their social network, create conflict, or interact with economic dependence to create a scenario where an individual may risk losing access to other resources that are provided through the social network (e.g., a safe place to sleep). In networks of IDUs that rely heavily on trust, reciprocity, and mutual caretaking, the isolation that could result from violating social norms can be devastating (Bourgois & Schonberg, 2009). Others have found that IDUs living with non- IDU friends or family attempt to abstain from drug use in the shared dwelling (Dickson-Gomez et al., 2009). In this study, attempts to avoid or conceal drug use from non-IDU friends appeared to influence IDUs’ decisions not to carry injection supplies, which sometimes resulted in borrowing supplies from others. Homeless individuals who utilized shelters reported that they frequently hid or disposed of their injection supplies in order to comply with the drug-free policies of the shelters. Several respondents described hiding their equipment in public areas such as bushes, vehicles, or behind trashcans, which has been reported by others (Dickson-Gomez et al., 2009). This strategy presents two obvious problems: 1) the equipment may not be there when the individual returns, either because it has been stolen, or inadvertently (or deliberately) disposed of; and 2) particularly because many respondents re-use their own syringes several times before disposing of them, there is a possibility that unknown people may use and replace the injection equipment, unbeknownst to its owner. In other studies, unstable housing has been associated with an 30 elevated risk of syringe sharing (Des Jarlais et al., 2007a), and improvement in housing status over time has been associated with decreases in risk behavior (Dickson-Gomez et al., 2009). Interventions that address unstable housing situations may serve as a structural intervention to prevent new HIV infections (Aidala et al., 2005; Dickson-Gomez et al., 2009), particularly if they are not contingent on abstinence. Participants identified real and serious consequences to carrying syringes that may make it difficult or nearly impossible to return used syringes to the SEP. These include not only jeapordizing housing arrangements in shelters or other drug-free housing arrangements, but also risking citation or arrest for drug paraphernalia or violating conditions of probation. Several studies have documented that IDUs who are concerned about arrest due to possession of drug paraphernalia are more likely to report syringe sharing (Bluthenthal et al., 1999a; Bluthenthal et al., 1999b). It may be that concerns over the legal consequences are not overstated; individuals using locally-sanctioned syringe exchange programs may actually be at increased risk of arrest for violating paraphernalia laws in California (Martinez et al., 2007). Policies that emphasize syringe exchange, rather than distribution, may further penalize IDUs who do not bring in used syringes by reducing the number of new sterile syringes they can pick up. A move towards distribution-based policies at SEPs, coupled with education about safer disposal options and community-based programs that provide such options, may help mitigate some of the consequences surrounding syringe disposal without penalizing IDUs who face significant barriers to returning used syringes to SEPs. Women’s risky injection episodes were almost always characterized by dependence on another individual for the provision and preparation of the drugs, and most frequently involved opposite-sex individuals. In contrast, men more frequently described events in which they were using alone, or in which exchanges with other men were described without the power differential that characterized women’s events. Men were also more likely than women to describe events that were not characterized by the imminent threat of withdrawal. Differences in the composition of the social networks of male and female IDUs have been described elsewhere (Miller & 31 Neaigus, 2001; Montgomery et al., 2002) and the multiplicity, or overlap of network types, of women’s networks has been identified as a risk factor for HIV and HCV infection (Latkin et al., 1998; Miller & Neaigus, 2001). Women in this sample weighed many different consequences of a refusal to share injection equipment, including not only the violation of social norms, but also consequences related to safety, housing, and access to drugs. Skills related to negotiating safer behavior with injection partners have been targeted by some theoretically-based interventions (Garfein et al., 2007a; Sorensen et al., 1994). Our findings suggest that such negotiation skills do not operate in a vacuum – negotiations about safer behavior must also consider outcomes other than HIV or HCV infection, and the social and environmental context of the event. Limitations Qualitative methods are valued more for their ability to provide rich narrative description and an “insider’s view” into the daily lives of research participants (Clatts et al., 1995; Singer et al., 2000) than for their generalizability. Thus, due to the small sample size and sampling strategy that included only one SEP in one U.S. city, the generalizability of our findings is limited. It is possible that the consequences associated with refusing to share are different among IDUs with more limited access to sterile syringes, or in municipalities that are less tolerant of SEPs. Even within the same city, IDUs who access syringes via SEPs may differ from those who do not. Grau and colleagues (2005) found that SEP customers engaged in less frequent injection risk behavior and reported higher self-efficacy for obtaining sterile syringes as compared to non-customers, but that customers and non-customers did not differ on other psychosocial measures. Participants in our study overwhelmingly reported heroin as their drug of choice, which makes our findings difficult to generalize to IDUs who prefer other substances such as methamphetamine or cocaine. Heroin IDUs generally inject more frequently and with more regularity than those who prefer stimulants and are more likely to experience the physiological effects of intense withdrawal symptoms, while injection of stimulants such as methamphetamine, cocaine, or crack is often characterized by binging in social settings and increased sexual risk behaviors (Santibanez et al., 2006; Shoptaw & Reback, 2007). Similarly, individuals who have access to more stable housing 32 and employment, or who purchase syringes at pharmacies rather than obtaining them mostly for free at an SEP, may differ in terms of the types of legal, economic, or housing-related consequences that they identify. Our findings may also be affected by bias due to socially desirable reporting and recall. To minimize this risk, the research team was careful to assure participants that the information they provided would not be shared with SEP staff, and interviews were conducted in private offices. Further, since the primary eligibility criterion was self-reported risky injection in the past 30 days, it is unlikely that risk behavior was underreported. More likely, past risk behavior was described as having occurred more recently, or several previous risky injection events were conflated to provide details about the event described in the interview. Details about events that occurred too long ago may have attenuated, yielding a less precise description of events. However, given the frequency of injection and the long duration of injection careers, the narrative accounts provided by study participants are likely to be representative of their actual behavior. Conclusions We have described the perceived consequences of refusing to share injection equipment reported by SEP participants, many of which are amenable to structural interventions. These results should not be interpreted to mean that IDUs perceive sharing injection equipment as a desirable outcome. Instead, an understanding of the multiple challenges and risks faced by IDUs helps contextualize the risk of HIV amongst a host of other consequences, many of which are perceived as more imminent or more severe (Connors, 1992). While from an outsider’s, or public health, perspective the most important outcome may be the prevention of HIV or HCV infection, from the IDU’s insider perspective there may be other equally or more important outcomes to be achieved (or avoided). Rather than imposing external priorities, effective public health interventions among IDUs will benefit from a holistic perspective that considers the “situated rationality” (Kowalewski et al., 1997) of decisions regarding injection risk behavior, and assists individuals in addressing the consequences that they perceive to be most salient. 33 CHAPTER 3. COMPETING RISKS: THE INFLUENCE OF THE PERCEIVED CONSEQUENCES OF REFUSING TO SHARE ON RISKY INJECTION PRACTICES AMONG IDUS Chapter 3 Abstract Injection drug users (IDUs) are at risk for HIV and other bloodborne pathogens through injection practices such as receptive syringe sharing (RSS) and receptive paraphernalia sharing (RPS). Studies investigating the perceived risk of HIV infection associated with sharing have had mixed findings; fewer have studied the perceived risk or consequences of refusing to share. We investigated the perceived consequences of refusing to share injection equipment among IDUs (N=187) recruited from a large syringe exchange program to determine their influence on RSS and RPS, and to identify gender differences. Two perceived consequences subscales were identified: structural/external and social/internal. In multiple linear regression, the social/internal consequences of refusing to share were associated with both RSS and RPS, after controlling for other psychosocial constructs and demographic variables. Few statistically-significant gender differences emerged, though there were some apparent gender differences in the types of consequences experienced at the most recent risky injection episode. 34 Introduction While the certainty of prevalence estimates varies, experts place the global prevalence of injection drug use at approximately 13.2 million people, with approximately 1.3 million residing in the United States (Aceijas et al., 2004). Injection drug users (IDUs) are at risk for a number of negative health outcomes, including infection with human immunodeficiency virus (HIV). Global estimates of HIV prevalence in IDU populations range from 0% to 80%, with prevalence in some U.S. sites as high as 42% (Aceijas et al., 2004). Risk factors for HIV and other bloodborne pathogens such as hepatitis C virus (HCV) among IDUs include receptive syringe sharing (RSS) and receptive paraphernalia sharing (RPS); that is, the shared use of contaminated injection equipment such as syringes, “cookers” (i.e., receptacles for preparing drug solution), or filtration cottons (Centers for Disease Control and Prevention, 1998; Garfein et al., 1996). Though the frequency of RSS and RPS among IDUs in the U.S. has declined dramatically since the beginning of the HIV epidemic (Des Jarlais & Semaan, 2008), recent surveillance surveys report that up to one-third of IDUs continue to practice injection behaviors that put them at risk for HIV infection (Centers for Disease Control and Prevention, 2009). Myriad studies have examined correlates and predictors of risky injection behavior. Many of these studies employ cognitive behavioral theories of health behavior, which emphasize characteristics of the individual (Gibson et al., 1993). A theoretical construct common to many cognitive behavioral theories is the perceived risk of a negative outcome resulting from a particular behavior. In research focusing on HIV infection among IDUs, the perceived risk of becoming infected with HIV via injection-related behaviors has been an area of intense interest, and has been measured variously as “perceived risk”, “perceived susceptibility”, and “perceived vulnerability” (Kowalewski et al., 1997). Theories such as the Health Belief Model (Strecher & Rosenstock, 1997) and the Theory of Reasoned Action (Fishbein, 1967) predict that individuals who perceive a high risk of HIV infection associated with RSS or RPS, or who perceive themselves to be highly susceptible to HIV infection via RSS or RPS, will be less likely to engage in injection risk behavior. 35 In fact, findings regarding the association between perceived risk and injection risk behavior have been mixed. Some studies have found an association in the expected direction - that is, high perceived risk of HIV infection via injection drug use has been associated with lower levels of risk behavior (Bailey et al., 2007; Smyth et al., 2001; Smyth & Roche, 2007). However, others have found the inverse – that increased perceptions of risk or susceptibility to HIV are associated with increased risk behavior (Booth, 1994; Falck et al., 1995; Hartgers et al., 1992; Racz et al., 2007; Robles et al., 1995). In still other cross-sectional studies, multivariate analyses detected no association between perceived vulnerability (Avants et al., 2000), perceived susceptibility (Gibson et al., 1993), or perceived risk (Stein et al., 2007) and RSS. Some authors have offered critiques of this construct in the literature on HIV risk behavior, noting that differences in the operational definitions, study design, or subgroup differences may contribute to the mixed findings reported in the literature (Kowalewski et al., 1997). In fact, it appears that studies that define the risk conditionally (i.e., the risk of HIV associated with injection drug use) are more likely to find negative associations, while studies that define the risk non-conditionally (i.e., the general risk of HIV), or using scales that mix conditional and non-conditional statements, are more likely to find positive or null effects. Another possible explanation for the mixed findings is that there are other potential outcomes in addition to the risk of HIV infection that individuals are weighing when they make decisions about whether or not to engage in HIV risk behaviors (Kowalewski et al., 1997). These other outcomes might be equally or more influential than the perceived risk of HIV in determining attitudes towards the recommended health behavior. Qualitative and epidemiological studies have identified some risks associated with not sharing injection equipment. Connors (1992) identified a “hierarchy of risks” identified by IDUs that included risks such as legal consequences (e.g., arrest or incarceration) and withdrawal symptoms. Others have noted the risk of alienation or loss of resources by violating established social norms for sharing injection equipment (Bourgois & Schonberg, 2009) or the risk of losing one’s share of a pooled drug purchase (Koester, 1996; Koester et al., 2005). In our previous work, we used findings from in-depth 36 qualitative interviews with IDUs to identify the perceived consequences of refusing to share injection equipment, and used the Risk Environment Framework (Rhodes, 2002) to organize them into individual, social and structural-level consequences of refusing to share. These consequences included factors such as the risk of experiencing withdrawal symptoms (individual), of offending or alienating injection partners (social), and of receiving a citation or being arrested for possession of drugs and/or drug paraphernalia (structural; Wagner, in preparation). Among IDUs, certain subgroups may be particularly vulnerable to HIV, and studies have found women to be at elevated risk for HIV infection via injection drug use (Fennema et al., 1997; Garfein et al., 1996). While biological factors pertaining to drug metabolism may form the foundation of some differences (Hankins, 2008), the social environment in which women use drugs has been identified as an important risk factor (Miller & Neaigus, 2001). Women more commonly use drugs with individuals with whom they have a relationship (Barnard, 1993; Cruz et al., 2006), and women’s social networks tend to include more hard drug users and IDUs (Montgomery et al., 2002). Women also report more overlap between drug and sexual networks (Latkin et al., 1998; Miller & Neaigus, 2001). Women’s access to drugs, injection paraphernalia, and other resources is often controlled or determined by others (Barnard, 1993; Bourgois et al., 2004; Epele, 2002; Simmons & Singer, 2006), and dependence on others for access to drugs is associated with increased syringe sharing (Sherman et al., 2001). Finally, women often relinquish control over the preparation and injection processes to others, usually their male partners (MacRae & Aalto, 2000). Not feeling in control over the injection event has been associated with unsafe injection among women (Tortu et al., 2003), and HIV infection has been shown to be almost twice as high among those who require help injecting (O'Connell et al., 2005). In the current study, we hypothesized that the perceived risks or consequences of refusing to share injection equipment would be associated with injection risk behavior, independent of other psychosocial constructs commonly assessed by studies grounded in cognitive behavioral theory (e.g., perceived risk of HIV or HCV, self-efficacy for safer injection, 37 response efficacy, perceived severity of HIV or HCV, knowledge, and peer norms for safer injection). We further hypothesized that the influence of the perceived consequences of refusing to share would differ by gender. More specifically, we expected women to identify more social consequences, and expected that social consequences would be more influential in explaining injection risk behavior among women. Methods Sample Data for the current study were collected as the second phase of a larger, mixed method study conducted at a large Syringe Exchange Program (SEP) in Los Angeles, California from July 2008 to April 2009. Methods and findings from the first phase of the study are described in detail elsewhere (Wagner et al., in preparation). Briefly, in the first phase of the study 30 IDUs participated in in-depth, qualitative interviews that explored the circumstances surrounding their most recent risky injection episode. Eligibility criteria for the first phase of the study were: 1) being > 18 years old, 2) having injected any drug at least once in the past 30 days, and 3) having engaged in a risky injection event at least once in the past 30 days. Risky injection was defined as any of the following: using a previously used syringe, sharing a cooker when any of the equipment had been previously used, sharing a cotton or rinse water, or syringe-mediated drug splitting (i.e., backloading or piggybacking) with previously used syringes or cookers. Data from those qualitative interviews were used to construct the perceived consequences items for the current analysis, as will be described below. For the second phase of the study, 200 IDUs were recruited from the same SEP to participate in a structured interview that yielded the quantitative data used in the current analysis. Participants were recruited via word of mouth and outreach by study staff within the SEP. Due to the challenges inherent in sampling from a population with an unknown denominator such as IDUs, it was not feasible to collect a random sample. Rather, the days and times that the SEP was open were divided into 4-hour blocks that were randomly sampled, so that data collection occurred for approximately 16 hours per week on randomly selected days and times that the SEP 38 was open. Eligibility criteria for the second phase of the study were: 1) being at least 18 years old, 2) having injected any drug at least once in the past 30 days, and 3) not having participated in the first phase of the study. Current IDU status (having injected at least once in the past 30 days) was assessed by visual examination of injection stigmata and through a series of screening questions that evaluated the participant's knowledge about typical injection procedures, similar to other studies (Garfein et al., 2007b). Study staff members who conducted the eligibility screening have several years experience working with IDUs and have an in-depth knowledge of injection practices. Though the population of SEP participants is approximately 25% female, the sampling strategy was adjusted so that at least 33% of the sample was female in order to facilitate gender comparisons. Both men and women were sampled until 133 men (67% of the proposed sample of 200) were interviewed, after which only women were interviewed until the total sample size of 200 was achieved. Eligible participants provided written informed consent and were compensated $25 for their participation. Data were collected via Audio Computer Assisted Interview (ACASI). The use of ACASI is an effective means of reducing bias associated with socially desirable reporting among IDUs (Des Jarlais et al., 1999). Participants listened to the questions and answers being read through a set of headphones and entered their answers directly into laptop computers. The computers were fitted with touch-screen adapters so that participants could enter their answers directly into the screen, and they were given the option of using the computer mouse. A research assistant was present at all times to answer questions and assist participants with the computer. The University of Southern California Health Sciences Institutional Review Board approved all study procedures. Of the 200 IDUs who were initially enrolled, 13 were later excluded due to ineligibility: 1 suspected non-IDU who appeared to have misrepresented his status as an IDU, 7 IDUs who reported in the ACASI that they had not injected at all in the past 30 days, 2 IDUs who completed the interview more than once, 1 IDU who participated in both phase one and phase two, and 1 IDU who was incoherent for a majority of the interview. One IDU who identified as transgender 39 was excluded in order to allow for male/female gender comparisons. After these exclusions, the final analytic sample consisted of 187 individuals. Measures Demographics. Demographic characteristics assessed in the interview included age, sex, race/ethnicity, education, and history of incarceration. Housing status was assessed by asking where participants had lived or slept the most in the past 30 days (e.g., on the streets, in their own home, in a friend’s home, in a shelter, in a hotel or motel, etc.) and also whether they considered themselves homeless in the past 30 days. Participants also provided information about the date of their most recent HIV and HCV test, and their HIV and HCV status. Drug use and injection risk behavior. Current drug use was assessed with three variables: injection drug of choice (i.e., drug most frequently injected in the past 30 days), and daily and weekly frequency of drug injection. Injection risk behavior was assessed in a series of questions based on those used by the CIDUS III study (Garfein et al., 2007a) and the NIDA Risk Behavior Assessment (Needle et al., 1995). Five items assessed the frequency with which individuals engaged in each risk behavior in the past 30 days (0-4; “never” – “almost always”): 1) RSS, 2) backloaded with equipment previously used by anyone else, 3) prepared drugs in a cooker previously used by anyone else, 4) used a cotton filter previously used by anyone else, 5) used rinse water previously used by anyone else. For some analyses, the three paraphernalia items were collapsed into a single variable representing RPS. Previous research indicates that IDUs can provide reliable and unbiased responses to questions using a 30-day reference period (Needle et al., 1995), therefore all questions referred to the previous 30 days. Perceived consequences. Perceived consequences were measured using a series of items that were developed by the research team using qualitative data provided in the first phase of the larger mixed-methods study. In the first phase, participants were asked to describe their most recent risky injection episode (in which they used previously used drug injection supplies), and to describe the consequences that they believe would have occurred had they refused to share on that occasion. Questions were open-ended, and interviews were digitally-recorded and 40 transcribed in their entirety for analysis. The qualitative data were reduced into 11 possible consequences using established methods for qualitative analysis (Wagner et al., in preparation). In the second phase of the study, participants were asked how frequently each of the 11 consequences influenced their decision whether or not to share injection equipment in the past 30 days (0-4; “never” – “almost always”). For example, “How often did the possibility of becoming dopesick (i.e., experiencing withdrawal symptoms) because you didn't have any equipment to use influence whether or not you used a syringe that had been used before?” The questions were asked separately for two behavioral outcomes of interest: RSS and RPS. After answering the question about the frequency with which each consequence influenced their decision, participants were asked to identify the importance of the consequence by indicating how much of a problem it would be if it were to occur (1-4; “not much of a problem” – “a very big problem”). For example, “How much of a problem would it be for you if you were dopesick because you didn't have any equipment to use?” This weighting method is similar to recommendations made by the Theory of Reasoned Action (Fishbein, 1967) and is useful since more severe consequences may be more salient in their influence on behavior (Colon et al., 2005). Then, participants were asked to consider their most recent risky injection episode and to choose which consequences influenced their decision at that time from a list of all 11 consequences (again, asked separately for each of the two behavioral outcomes). Psychosocial variables. Perceived risk of HIV/HCV was defined conditionally – that is, the probability that the threat (i.e., HIV or HCV infection) will occur given certain conditions or behaviors (Millstein & Halpern-Felsher, 2002). Four questions were developed for this study that asked how likely subjects think it is that they will become infected with HIV (or HCV) via RSS or RPS, rated on a 4-point scale from “very likely” to “very unlikely”. Questions were asked separately for risk of HIV and HCV infection. In the current study, the items had Cronbach’s alphas of 0.86 for HIV and 0.89 for HCV. HIV/HCV knowledge was measured using 14 items developed for use among IDUs (Garfein et al., 2007a), which assessed knowledge about the natural history of HIV and HCV 41 infection (e.g., “You can tell by looking at a person that they have HIV infection. [True/False]”) and the relative risk of injection-related behaviors (e.g., “Re-using your own syringe is just as safe as using a brand new syringe every time [True/False]”). The scales were originally designed to represent two subscales – however, the internal consistency of the scales was low (Cronbach’s alphas = 0.44 and 0.24). We used exploratory factor analysis to select the six items that loaded most strongly on a single HIV/HCV knowledge factor, and calculated the score of correct answers to these six items to represent HIV/HCV knowledge. This six-item scale had a Cronbach’s alpha of 0.70. Perceived severity represents the degree of harm associated with the outcome (i.e., HIV infection; Rogers & Prentice-Dunn, 1997) and was measured using eight questions adapted from a study based on the Health Believe Model (Falck et al., 1995) such as “Getting HIV is the worst possible thing that could happen to me,” rated on a 4-point scale from “strongly agree” to “strongly disagree”. Questions were asked separately for the severity of HIV and HCV infection. In the current study, these items had a Cronbach’s alpha of 0.79 for HIV and 0.81 for HCV. Self-efficacy for safer injection was measured using six items developed for use among IDUs, such as “I can avoid sharing a syringe even if I am dopesick or in withdrawal”, rated on a 4- point scale from “strongly agree” to “strongly disagree”, which have shown good internal consistency in other studies (Garfein et al., 2007a). In the current study, these items had a Cronbach’s alpha of 0.92. Response efficacy was measured using six questions that assess one’s confidence that a particular activity (i.e., using new syringes, using new paraphernalia, not splitting drug solution with a syringe) will reduce the risk of contracting HIV or HCV on a four-point scale of “definitely will not” to “definitely will” (e.g., “Using a brand new syringe every time will reduce my chances of becoming infected with HIV”). The items were developed for the current study, based on previous work (e.g., Falck et al., 1995). In the current study, these items had a Cronbach’s alpha of 0.94. 42 Social norms against syringe and paraphernalia sharing were measured using two items developed by Garfein and colleagues (2007a) based on the work of Jamner and colleagues (1998). Questions elicited views about the expectations of peers regarding syringe and paraphernalia sharing, for example, “People I inject with think that cookers, cotton or water should never be shared when they inject,” measured on a four-point scale from “strongly disagree” to “strongly agree”. Analysis All analyses were undertaken using SAS 9.1. Univariate analyses included calculation of measures of central tendency and dispersion. Bivariate comparisons were made to explore gender differences in demographics, drug use variables, and perceived consequences using t- tests for means, and Chi-square tests or Fisher’s Exact Tests for frequencies (when expected cell frequencies were less than 5). We then conducted a series of analyses to establish the psychometric properties of the perceived consequences items. Each perceived consequence item was weighted by its importance by taking the product of the consequence item and the problem item (Montaño et al., 1997). Exploratory factor analysis (EFA) was conducted to identify the factor structure of the weighted perceived consequences measure. EFA was conducted separately for questions related to each behavioral outcome (i.e., RSS and RPS). In each analysis the 11 weighted items were entered into EFA using promax oblique rotation, and items loading >0.40 on factors with a minimum Eigenvalue of 1.0 were retained. The mean of the weighted items representing each factor was used to create sub-scales. Internal consistency reliability of all psychosocial scales was assessed using Cronbach's alpha. Scales were standardized so that each had a mean of 0 and standard deviation of 1. Pearson's correlation coefficients were calculated to assess the bivariate association between perceived consequences, psychosocial scales, and each injection risk behavior. Then, multiple linear regression analyses were conducted separately for the two behavioral outcomes of interest: 1) RSS and 2) RPS. A composite score for RPS was created by taking the mean of the items that assessed the frequency of using previously used cookers, cottons, and rinse water, 43 similar to others (Booth et al., 1999; Garfein et al., 2007a). Because the residuals from the regression models were skewed we log-transformed the dependent variables prior to entry into the models, which helped normalize the distribution of the residuals. All regression results are reported for the log-transformed outcomes. The regression models were created in a series of steps. First, the outcome was regressed on the psychosocial scales (i.e., self-efficacy, response efficacy, perceived risk, severity, knowledge, and peer norms) and demographic covariates selected based on previous studies (i.e., sex, age, HIV and HCV status, current homelessness, and daily frequency of injection drug use). Second, the perceived consequences scales were added to the model. Third, product terms were included in the models to assess the moderating effect of gender on the association between the perceived consequences scales and injection risk behavior. If the product terms were not statistically significant at the p<0.05 level they were dropped from the model and we report the main effects for the overall sample. Fourth, we performed an F-test using the Extra Sums of Squares Principle to determine whether the addition of the perceived consequences scales contributed significantly to model fit. Results Sample Description Demographics of the sample are shown in Table 3.1. Few significant differences between men and women were detected. Participants had an average age of 43 years and 35% were female. The sample was ethnically diverse; just over one-third was Hispanic/Latino, followed by White (31%), African American (20%), Native American/Hawaiian Native (7%), Asian/Pacific Islander (4%), and other (2%). Though not statistically significant, women more frequently reported being Native American/Hawaiian Native, while men were slightly more likely to report being African American. Over three-fourths reported ever being homeless, and 74% reported being homeless in the past 30 days. Almost all (92%) had a lifetime history of incarceration, and just over one-quarter reported being incarcerated in the past 30 days. Men were statistically significantly more likely to report being ever incarcerated (p<0.01), but were as 44 likely as women to report recent incarceration. Half did not graduate high school. Eighty-five percent had ever been tested for HIV, and 9% of those reported being HIV positive. Men were significantly more likely than women to report being HIV positive (p<0.01). Seventy-four percent had ever been tested for HCV, and 59% of those reported being HCV positive. Table 3.1. Demographic characteristics and drug use behavior of study sample, by gender (N=187). Overall Female (n=66) Male (n=121) N % N % N % Age (mean; SD) 42.9 (11.5) 42.2 (11.7) 43.2 (11.3) Race/Ethnicity: Hispanic/Latino 68 37.0 24 36.9 44 37.0 White 57 31.0 19 29.2 38 31.9 African American 36 19.6 9 13.9 27 22.7 Native American/Hawaiian Native 12 6.5 8 12.3 4 3.4 Asian/Pacific Islander 7 3.8 3 4.6 4 3.4 Other 4 2.2 2 3.1 2 1.7 Ever homeless 144 77.0 54 81.8 90 74.4 Homeless in past 30 days 107 74.3 41 75.9 66 73.3 Ever incarcerated a 172 92.0 56 84.9 116 95.9 Incarcerated in past 30 days 48 28.0 16 28.6 32 27.6 Education: Less than high school graduation or GED 94 50.3 29 43.9 64 52.9 HIV Positive* (n=156) a 14 9.0 1 1.6 13 14.0 HCV Positive* (n=138) 81 58.7 35 67.3 46 53.5 Drug injected most frequently in past 30 days Heroin only 165 88.2 61 92.4 104 86.0 Heroin mixed with cocaine 11 5.9 3 4.6 8 6.6 Methamphetamine only 7 3.7 1 1.5 6 5.0 Other** 4 2.2 1 1.5 3 2.4 Injected with previously used equipment in past 30 days (Y/N) Syringe 67 35.8 21 31.8 46 38.0 Cooker 92 49.2 31 47.0 61 50.4 Cotton 97 51.9 30 45.5 67 55.4 Rinse water 86 46.0 29 43.9 57 47.1 Syringe mediated drug splitting in past 30 days (Y/N) 79 42.3 29 43.9 50 41.3 Age at IDU initiation (mean; SD) 22.7 (8.3) 21.9 (7.3) 22.9 (8.7) Daily frequency of injection (mean; SD) 4.1 (2.4) 4.2 (2.4) 4.1 (2.4) Weekly frequency of injection (mean; SD) 6.3 (1.4) 6.3 (1.5) 6.4 (1.3) *self-report, % of those who have ever been tested **includes crack cocaine, heroin mixed with methamphetamine, powdered cocaine, and prescription drugs a p<0.01 45 Injection Risk Behavior Drug use and injection risk behavior are also shown in Table 3.1. The average age at IDU initiation in this sample was 23 years (SD = 8.3); the average participant had been injecting for 20 years. Participants reported injecting an average of 4 times per day (SD = 2.4), 6.3 days per week (SD = 1.4). The majority of individuals identified heroin as the drug most frequently injected in the past 30 days (n=165; 88%), which may account for the high frequency of daily injection. A much smaller proportion identified speedball (i.e., heroin mixed with cocaine; n=11, 6%) and methamphetamine (n=7, 4%) as their injection drug of choice. Other drugs identified by less than 1% of the sample included powdered or crack cocaine by itself, heroin mixed with methamphetamine, or prescription drugs. Between one-third and one-half of participants reported engaging in at least one of five injection risk behaviors in the past 30 days, including 52% who used a previously used cotton, 49% who used a previously used cooker, 46% who used previously used rinse water, 42% who backloaded with used equipment, and 36% who reported RSS. No significant gender differences were detected in drug use or injection risk behavior. Exploratory Factor Analysis of Perceived Consequences Items Factor loadings and Cronbach's alphas from the exploratory factor analysis of the Perceived Consequences items are shown in Table 3.2. For each behavioral outcome, EFA yielded two factors with Eigenvalues >1.0. We devised two sub-scales based on the factor structure. The first consists of items relating to structural or external consequences (i.e., threat of arrest for drug paraphernalia or drug possession, risk of losing housing, financial hardship such as having to buy new equipment or losing out on a shared drug purchase, or inconvenience in finding new equipment). The second factor consists of social or internal consequences (i.e., the risk of offending injection partner(s) based on a perceived lack of trust or accusation of HIV- positive status, the risk that injection partner(s) would lose their share of the drug purchase if preparation equipment was not shared, the risk of having to forgo drug use altogether). The factor structure was nearly identical for the questions relating to each behavioral outcome, with 46 one exception; the item referring to the threat of becoming dopesick, or experiencing withdrawal symptoms, loaded on the structural/external factor in the questions related to syringe use, while in the questions related to paraphernalia use it loaded on the social/internal factor. All four sub- scales showed good internal consistency reliability, with all Cronbach's alphas > 0.70 (Table 3.2). Summary statistics for the four sub-scales are shown in Table 3.3. There were no significant differences in the mean or median values based on gender. Table 3.2. Perceived consequences items and factor loadings (N=187). Previously used syringe Previously used paraphernalia “If I had not used that previously used equipment… Structural/ external (alpha = 0.84) Social/ internal (alpha = 0.70) Structural/ external (alpha = 0.85) Social/ internal (alpha = 0.70) I might have gotten arrested for carrying cookers or syringes 0.78 - 0.92 - I could have gotten kicked out of or lost my housing 0.76 - 0.63 - I would have had to spend money to get new equipment 0.76 - 0.72 - I might have gotten arrested for drug possession 0.76 - 0.74 - I would have had to go out of my way to get a new syringe or cooker 0.72 - 0.77 - I might have lost my share of the drugs we were using together 0.67 - 0.62 - I might have become dopesick 0.48 - - 0.57 My injection partner(s) would have been angry or hurt I didn't trust them - 0.80 - 0.73 My injection partner(s) would have lost their share of the drugs we used together - 0.78 - 0.71 My injection partner(s) would have been angry or hurt that I thought they had HIV/AIDS - 0.57 - 0.54 I might not have been able to get high at all - 0.52 - 0.63 47 Table 3.3. Summary statistics for four perceived consequences subscales by gender (N=187). Mean (SD) 95% C.I. Range Syringe – Structural/External Consequences Overall 3.07 (2.14) 2.76, 3.38 0-16 Female 3.15 (3.97) 2.17, 4.12 Male 3.02 (3.20) 2.45, 3.60 Syringe – Social/Internal Consequences Overall 2.13 (2.71) 1.74, 2.52 0-14 Female 1.99 (2.81) 1.30, 2.68 Male 2.21 (2.66) 1.73, 2.69 Paraphernalia – Structural/External Consequences Overall 2.88 (3.67) 2.35, 3.41 0-16 Female 2.80 (4.06) 1.80, 3.80 Male 2.93 (3.45) 2.31, 3.55 Paraphernalia – Social/Internal Consequences Overall 2.39 (3.61) 1.87, 2.91 0-12 Female 2.41 (2.74) 1.73, 3.08 Male 2.38 (2.61) 1.91, 2.85 Perceived Consequences at Most Recent Risky Injection Episode In addition to answering questions about the perceived consequences over the past 30 days, participants were asked to identify the perceived consequences that influenced their behavior during their most recent injection episode, again asked separately for RSS and RPS. Of those who reported that they had ever used a previously used syringe (n=156), 20 (13%) identified no perceived consequences of refusing to use that syringe. Half (53%) identified one consequence, 10% identified two consequences, and 24% identified three or more consequences. As shown in Table 3.4, the most frequently endorsed consequence was the risk of becoming dopesick or experiencing withdrawal symptoms (n=63; 40%), followed by the need to go out of one's way to get a new syringe (n=48; 31%), to spend money to buy a new syringe (n=36; 23%), the risk of being arrested for drug possession (n=31; 20%), and the risk of losing one's share of the pooled drug purchase (n=25; 16%). Other consequences were endorsed by less than 15% of the sample. Though there were no statistically significant associations between the perceived consequences of syringe sharing and gender, women appeared slightly more likely than men to endorse consequences related to becoming dopesick and having to go out of their way to get new equipment. Men appeared slightly more likely than women to report that their injection partner would have been angry or hurt due to a lack of trust. 48 Table 3.4. Frequency of perceived consequences of refusing to share syringes or paraphernalia at the most recent risky injection episode, by gender. Syringe (n=156) Paraphernalia (n=154) n % n % You would have ended up being dopesick Overall 63 40.4 65 42.2 Female 24 45.3 25 51.0 Male 39 37.9 40 38.1 You would have had to go out of your way to get a new syringe/cooker Overall 48 30.8 41 26.6 Female 21 39.6 17 34.7 Male 27 26.2 24 22.9 You would have had to spend money to buy a new syringe/cooker Overall 36 23.1 29 18.8 Female 13 24.5 9 18.4 Male 23 22.3 20 19.1 You might have been arrested for possession of drugs Overall 31 19.9 25 16.2 Female 10 18.9 10 20.4 Male 21 20.4 15 14.3 You would have lost your share of the drugs you and your partner(s) were sharing Overall 25 16.0 15 9.7 Female 9 17.0 6 12.2 Male 16 15.5 9 8.6 You could have been kicked out of your housing Overall 23 14.7 20 13.0 Female 7 13.2 7 14.3 Male 16 15.5 13 12.4 Your injection partner(s) would have been angry or hurt that you didn’t trust them Overall 23 14.7 19 12.3 Female 5 9.4 4 8.2 Male 18 17.5 15 14.3 You might have gotten a ticket/been arrested for carrying syringes/cookers Overall 21 13.5 18 11.7 Female 8 15.1 7 14.3 Male 13 12.6 11 10.5 Your injection partner(s) would have been angry/hurt because you think they have HIV/AIDS Overall 15 9.6 15 9.7 Female 5 9.4 4 8.2 Male 10 9.7 11 10.5 Your injection partners wouldn’t be able to get their share of the drugs Overall 14 9.0 17 11.0 Female 4 7.6 5 10.2 Male 10 9.7 12 11.4 49 Of those who reported ever participating in an injection event in which they prepared drugs with previously used cookers, cotton, or water (n=154), 20 (13%) identified no perceived consequences of refusing to share that equipment (Table 3.4). Half (55%) identified one consequence, 10% identified two consequences, and 23% identified three or more consequences. The frequency of endorsed consequences were similar to those for the events involving a shared syringe; 42% said they would have become dopesick, 27% said they would have had to go out of their way to obtain new equipment, 19% said they would have had to spend money to purchase new equipment, and 16% said they might have been arrested for drug possession. Again no significant associations with gender were detected, but women appeared slightly more likely than men to report concerns about becoming dopesick, inconvenience, arrest or citation due to drug possession, and losing their share of a pooled drug purchase. Men appeared slightly more likely than women to report concerns over their injection partners being hurt or angry due to a lack of trust. There were no significant gender differences in the mean number of consequences reported at the most recent injection event. Association Between Perceived Consequences, Psychosocial Constructs, and Injection Risk Behavior Correlations between the perceived consequences scales and injection risk behavior are shown in Table 3.5. Pearson correlation coefficients ranged from 0.11 to 0.32, and with three exceptions were statistically significant (all p <0.05). Correlations between the other psychosocial constructs and injection risk behavior are also shown in Table 3.5. Self-efficacy for safer drug injection was significantly and negatively associated with all five injection risk behaviors (all p <0.01), such that those who reported greater confidence in their ability to avoid risky injection reported less injection risk behavior. Perceived risk of HIV was significantly and negatively associated with lower rates of using previously used cotton, shared rinse water, and backloading (all p <0.05). Perceived risk of HCV was similarly associated with less frequent use of used cottons, and backloading (all p <0.05), but its association with using shared rinse water was marginally significant. HIV/HCV knowledge was significantly and negatively correlated only with 50 backloading (p<0.05). Response efficacy, perceived severity of HIV, and perceived severity of HCV were not significantly correlated with any injection risk behaviors. Table 3.5. Bivariate correlations between perceived consequences, psychosocial scales, and injection risk behaviors (N=187). Injection Risk Behaviors Used Syringe Used Cooker Used Cotton Used Water Backloading Perceived Consequences: Structural/external (syringe) 0.19** 0.16* 0.20** 0.15* 0.11 Social/internal (syringe) 0.24*** 0.27*** 0.32*** 0.25** 0.18* Structural/external (paraphernalia) 0.18* 0.15* 0.20** 0.13+ 0.09 Social/internal (paraphernalia) 0.23** 0.24*** 0.29*** 0.24*** 0.14* Self-efficacy -0.23** -0.23** -0.22** -0.23** -0.28*** Response Efficacy -0.03 -0.04 -0.06 -0.01 -0.03 Perceived risk (HIV) -0.13+ -0.08 -0.16* -0.16* -0.16* Perceived risk (HCV) -0.12 -0.08 -0.16* -0.14+ -0.17* Severity (HIV) -0.07 -0.03 -0.03 -0.09 -0.09 Severity (HCV) -0.05 -0.06 -0.07 -0.13+ -0.07 HIV/HCV Knowledge -0.11 -0.06 -0.03 -0.09 -0.14* Peer Norms against syringe sharing -0.15* -0.20** -0.13+ -0.13+ -0.17* Peer Norms against paraphernalia sharing -0.16* -0.22** -0.17* -0.15* -0.28*** +p<0.10, *p<0.05, **p<0.01, ***p<0.001 Results of the first linear regression model, in which log RSS was the outcome, are shown in Table 3.6. In model 1, which regressed log RSS on the psychosocial scales and demographic covariates, greater self-efficacy for safer injection was associated with lower frequency of log RSS. Female gender, HIV-positive status, and homelessness were also associated with injection risk behavior. The Extra Sums of Squares F-test showed that including the perceived consequences sub-scales significantly improved the model (F 2, 113 = 7.17, p = 0.001). In model 2, both social/internal perceived consequences and self-efficacy for safer injection were associated with log RSS, independent of the other variables in the model (all p <0.01). Participants who reported greater influence of social/internal consequences reported 51 more frequent log RSS, while those who reported higher self-efficacy for safer injection reported less frequent log RSS. The significant associations between injection risk behavior and female gender, HIV-positive status, and homelessness did not persist in model 2. The product terms testing the moderating influence of gender on the association between perceived consequences and injection behavior were not statistically significant (p >0.05) and were therefore not included in the final model. Table 3.6. Results from multiple linear regression of perceived consequences and psychosocial scales on log syringe sharing (N=130). Model 1 – reduced model F = 2.21, Adj R-Sq = 0.12 Model 2 – full model F = 3.03, Adj R-Sq = 0.20 Parameter estimate SE p-value Parameter estimate SE p-value Perceived Consequences of refusing to share syringes Structural/external 0.03 0.05 0.48 Social/internal 0.14 0.05 0.008 Psychosocial scales Self-efficacy -0.10 0.04 0.01 -0.10 0.04 0.009 Response Efficacy 0.09 0.05 0.06 0.07 0.05 0.13 Perceived risk (HIV) 0.04 0.06 0.52 0.02 0.06 0.76 Perceived risk (HCV) -0.05 0.07 0.44 -0.02 0.07 0.73 Severity (HIV) -0.02 0.05 0.68 -0.01 0.05 0.87 Severity (HCV) -0.01 0.05 0.83 -0.03 0.05 0.50 HIV/HCV knowledge -0.08 0.05 0.14 -0.07 0.05 0.19 Peer norms -0.01 0.04 0.78 -0.01 0.04 0.85 Female -0.17 0.08 0.04 -0.14 0.08 0.09 Age -0.001 0.004 0.78 -0.001 0.004 0.87 HIV positive -0.31 0.15 0.04 -0.22 0.15 0.13 HCV positive 0.10 0.09 0.29 0.07 0.09 0.41 Homeless (past 30 days) 0.19 0.09 0.03 0.11 0.08 0.19 Daily frequency of IDU 0.03 0.02 0.07 0.01 0.02 0.41 52 Table 3.7. Results from multiple linear regression of perceived consequences and psychosocial scales on log paraphernalia sharing (N=130). Model 1 – reduced model F = 2.97, Adj R-Sq = 0.18 Model 2 – full model F = 3.58, Adj R-Sq = 0.24 Parameter estimate SE p-value Parameter estimate SE p-value Perceived Consequences of Refusing to share paraphernalia Structural/external 0.03 0.05 0.55 Social/internal 0.14 0.06 0.02 Psychosocial scales Self-efficacy -0.09 0.04 0.05 -0.08 0.04 0.06 Response Efficacy 0.12 0.05 0.02 0.11 0.05 0.05 Perceived risk (HIV) -0.006 0.07 0.93 -0.03 0.07 0.60 Perceived risk (HCV) -0.06 0.07 0.40 -0.03 0.07 0.70 Severity (HIV) -0.002 0.06 0.97 0.004 0.06 0.95 Severity (HCV) -0.01 0.05 0.82 -0.04 0.05 0.48 HIV/HCV Knowledge -0.05 0.06 0.36 -0.04 0.05 0.45 Peer norms -0.10 0.05 0.03 -0.11 0.05 0.02 Female -0.08 0.09 0.38 -0.05 0.09 0.58 Age -0.002 0.004 0.60 -0.0006 0.004 0.89 HIV positive -0.22 0.16 0.17 -0.13 0.16 0.40 HCV positive 0.23 0.10 0.02 0.19 0.10 0.05 Homeless (past 30 days) 0.28 0.09 0.003 0.20 0.09 0.03 Daily frequency of IDU 0.02 0.02 0.29 0.009 0.02 0.62 Results of the second linear regression model, in which log RPS was the outcome, are shown in Table 3.7. In model 1, which regressed log RPS on the psychosocial scales and demographic covariates, response efficacy (i.e., confidence that not sharing injection supplies will prevent HIV and HCV infection) was significantly and positively associated with higher frequency of log RPS, while self-efficacy and peer norms against paraphernalia sharing were significantly inversely related with log RPS (all p <0.05). Individuals who reported being HCV positive and who were currently homeless also reported more log RPS. The Extra Sums of Squares F-test showed that including the perceived consequences scales significantly improved the model 53 (F 2, 113 = 6.05, p = 0.003). In model 2, social/internal perceived consequences were again significantly and positively associated with increased injection risk behavior (p<0.05). The significant association between peer norms against paraphernalia sharing and RPS persisted, as did the association between response efficacy and RPS (all p<0.05). The association between self-efficacy and injection risk behavior became marginally significant (p=0.06). Positive HCV status and current homelessness continued to be associated with increased log RPS in the final multivariate model. The product terms testing the moderating influence of gender on the association between perceived consequences and injection behavior were not statistically significant (all p >0.05) and were therefore not included in the final model. Discussion In this sample of IDUs who were recruited from a large SEP, social/individual consequences of refusing to share injection equipment were associated with increased rates of both RSS and RPS. The inclusion of the perceived consequences measures contributed significantly to the explanation of risky injection behavior, independent of other theoretically- important psychosocial predictors of injection risk including the perceived risk of HIV and HCV, self-efficacy for safer injection, perceived severity of HIV/HCV, knowledge, and social norms. The measure of perceived consequences had good internal consistency reliability and a factor structure consistent with the theoretical underpinnings of the study, suggesting that it may also have good validity. In the multivariate analyses assessing perceived consequences and behavior in the past 30 days, structural/external consequences were not associated with injection risk behavior. In contrast, when we asked participants to identify those consequences that influenced their most recent risky injection episode, many of the most frequently endorsed items were structural/environmental items, including: the inconvenience of finding new equipment, the need to spend money to purchase new equipment, the risk of being arrested for drug possession, and the risk of losing one’s share of a pooled drug purchase. It may be that the types of consequences comprising the external/structural sub-scale are more rare or more distal to the 54 injection event, thus making them less influential in explaining injection risk behavior over the course of a 30-day period. For example, while the risk of offending an injection partner or forgoing drugs (social/internal consequences) will likely occur immediately and frequently, the risk of being arrested for possession of drugs or paraphernalia (structural consequences) may be less immediate or less certain threats. Therefore, while the external/structural consequences that influenced the most recent injection event may be most immediately available in memory, over the course of a 30-day period they may be less memorable than the social/internal consequences. While the rate of recent incarceration was high (28% in the past month), injection episodes that occur with partners multiple times a day may be more influential in determining habitual behavior. Future studies employing a “last event” methodology in which the predictors of risk behavior are assessed in immediate proximity to the risky event may help to further elucidate these relationships. In the qualitative research that informed the current study, we found that women were more likely to engage in risky injection behavior with friends or sex partners of the opposite sex, while men were more likely to engage in risky injection with other men who they identified as friends, acquaintances, or strangers (Wagner, in preparation). We also found that women appeared to be more significantly affected by their dependence on others to provide drugs or resources, and often described injection episodes characterized by more desperation and urgency to alleviate withdrawal symptoms. Based on in part on our findings, as well as a considerable literature describing gender differences in injection-related risk factors for HIV and HCV infection (Anglin et al., 1987; Barnard, 1993; Bourgois et al., 2004; Bruneau et al., 2001; Clements et al., 1997; Cruz et al., 2006; Davey-Rothwell & Latkin, 2007; Epele, 2002; Evans et al., 2003) we hypothesized that the influence of perceived consequences would vary based on gender. To the contrary, in the current study we found few associations with gender. Women reported similar rates of syringe and paraphernalia sharing to men, there was no difference in the mean number of consequences reported by women and men, and there was no statistical interaction between gender and perceived consequences in their association with RSS and RPS. 55 The absence of gender differences in injection risk behavior is consistent with some other epidemiological studies (Fennema et al., 1997; Garfein et al., 1996). While we did not detect significant differences in the types of consequences reported at the last injection event, women appeared slightly more likely to endorse consequences related to becoming dopesick and the inconvenience of acquiring new equipment. This is consistent with findings that women are more dependent on others for access to drugs or equipment (Barnard, 1993; Bourgois et al., 2004; Epele, 2002; Simmons & Singer, 2006), and our previous work in which women described risky injection episodes characterized by more severe withdrawal symptoms than men. In contrast, men were more likely to report concerns about upsetting their injection partners. Though most of the literature focusing on gender differences has emphasized the socially-situated nature of women’s injection events, men’s relationships with (usually male) drug using partners may also influence injection related risk, a phenomenon which has been illustrated in ethnographic work with male IDUs (Bourgois & Schonberg, 2009). Two demographic variables were also associated with RPS. Individuals who reported being HCV positive were more likely to report RPS, as were those who reported being homeless in the past 30 days. HCV is more efficiently transmitted perenterally compared to HIV and RPS is an important mode of transmission for HCV (Hagan et al., 2005), therefore it is not surprising that those who report being HCV positive were also more likely to report RPS. In the qualitative phase of the current study we found that homeless IDUs reported significant barriers to maintaining a supply of sterile injection supplies, despite their participation in the SEP. Street-based homeless IDUs may be less likely to carry injection paraphernalia due to concerns about increasing their vulnerability to citation or arrest by law enforcement (Dickson-Gomez et al., 2009). Similarly, those IDUs who use homeless shelters are often prohibited from carrying injection supplies into the shelter and therefore may have more difficulty maintaining a supply of sterile supplies (Dickson-Gomez et al., 2009; Wagner et al., in preparation). Therefore, homeless IDUs, both street-based and shelter-using, may require greater and more frequent access to injection supplies in order to reduce RPS. 56 Limitations These findings should be considered in light of some limitations. Given the cross- sectional nature of the current study, no assumptions about directionality of influence or causation can be made. Study participants were recruited from a single SEP in Los Angeles, a large urban city that has relatively good access to sterile injection supplies via multiple SEPs and pharmacies. Therefore, our findings may not generalize to IDUs who do not access SEPs. Grau and colleagues (2005) found that SEP customers engaged in less frequent injection risk behavior and reported higher self-efficacy for obtaining sterile syringes as compared to non-customers, but that customers and non-customers did not differ in perceived vulnerability to HIV, perceived severity of HIV, response efficacy, or social norms. Participants in our study overwhelmingly reported heroin as their drug of choice, which makes our findings difficult to generalize to IDUs who prefer other substances such as methamphetamine or cocaine. Heroin IDUs generally inject more frequently and with more regularity than those who prefer stimulants and are more likely to experience the physiological effects of intense withdrawal symptoms, while injection of stimulants such as methamphetamine, cocaine, or crack is often characterized by binging in social settings and increased sexual risk behaviors (Santibanez et al., 2006; Shoptaw & Reback, 2007). The measure of perceived consequences of safer injection was developed using qualitative data elicited from the same population of SEP users and therefore will require further research to determine its reliability and validity in a broader sample of IDUs. The absence of statistically-significant associations with gender in this study should be considered in light of the preliminary nature of this assessment, as well as the relatively small sample size. The between- gender differences were small in magnitude, particularly in comparison to the relatively large within-gender variance in the perceived consequences measures. Future studies with larger sample sizes and better refinement of survey items may be required to generate more precise estimates. Further, while significant efforts were made to enroll a sufficient proportion of women, even larger proportions of women may be required to detect gender differences in these measures, if they exist. 57 Despite these limitations, the current study has provided preliminary evidence that IDUs identify negative consequences associated with refusing to share injection equipment, and these consequences may influence decisions about injection risk behavior above and beyond the influence of traditionally-studied theoretical constructs such as perceived risk of HIV. Future studies with larger samples, longitudinal design, and more diverse populations of IDUs may help to further elucidate these associations. Conclusions Our findings suggest that in addition to considering the perceived risk of HIV associated with sharing injection equipment, research should also investigate the perceived consequences of refusing to share. Decisions about whether or not to engage in risk behaviors are grounded in a “social rationality” (Kowalewski et al., 1997), in which individuals weigh a host of potential outcomes in addition to the risk of becoming infected with HIV or HCV. In attempting to comply with public health recommendations to use brand new, sterile injection supplies for each and every injection, IDUs often face other consequences that may carry equal or more significance, such as risking social consequences, arrest, incarceration, or drug withdrawal (Connors, 1992). In this study, consequences associated with offending injection partners, forgoing drug use, and experiencing drug withdrawal symptoms were significantly associated with higher rates of injection risk behavior, even after adjusting for perceived risk of HIV and HCV infection. Though not corroborated by our findings, others have found that these additional consequences may differentially increase women’s vulnerability, as compared to men (Connors, 1992). Comprehensive prevention efforts should focus on helping IDUs minimize these consequences by addressing the entire “risk environment”(Rhodes, 2002) where risk behavior occurs, rather than focusing exclusively on heightening risk perceptions related to HIV infection. 58 CHAPTER 4. PSYCHOSOCIAL CORRELATES OF RISKY INJECTION BEHAVIOR AMONG IDUS: MODERATION BY PERCEIVED CONSEQUENCES OF REFUSING TO SHARE INJECTION EQUIPMENT Chapter 4 Abstract A host of theoretical constructs have been employed to help understand persistent injection risk behavior among injection drug users (IDUs). Some constructs (e.g., self-efficacy for safer injection, peer norms against risky injection) have been more successful in explaining injection risk behavior than others (e.g., response efficacy, perceived risk of HIV or HCV infection). We used moderation analysis to determine whether the association amongst psychosocial correlates and injection risk behavior varied based on the degree to which IDUs reported that they were influenced by a third variable: the perceived consequences of refusing to share injection equipment (assessed as social/internal consequences and structural/external consequences). Results suggest that individuals who reported greater influence of the perceived consequences of safer injection may be more sensitive to the effects of some other theoretical correlates of injection risk behavior. 59 Introduction Despite declines in incidence since the beginning of the HIV epidemic, injection drug use continues to account for 12% of new HIV infections in the United States (Centers for Disease Control and Prevention, 2006), and 10% worldwide (Aceijas et al., 2004). Injection drug use is also a significant risk factor for infection with other bloodborne pathogens such as hepatitis C virus (HCV; Centers for Disease Control and Prevention, 1998). As such, injection drug users (IDUs) are an important subpopulation at risk for a number of negative health outcomes associated with a single risk behavior. Decades of research have been undertaken to understand the factors associated with risky injection practices (i.e., the “sharing” or multi-person use of contaminated injection supplies; Des Jarlais & Semaan, 2008; Santibanez et al., 2006). One area of intense study has been in the psychosocial predictors of injection risk behavior, drawing on a number of behavioral theories such as the Health Belief Model (HBM; Strecher & Rosenstock, 1997) and the Theory of Reasoned Action (TRA)/Theory of Planned Behavior (TPB; Ajzen, 1991). Additionally, newer theories have been developed specifically to explain HIV-related risk behavior, such as the stage- based AIDS Risk Reduction Model (ARRM; Catania et al., 1990) and the Information, Motivation, Behavioral Skills (IMB) model (Fisher & Fisher, 1992). These theories of health behavior share several constructs in common and, in many cases, differ primarily in their operationalization of the constructs and the hypothesized relationships between them (Bandura, 2004; Wallston & Wallston, 1984). This body of work has yielded consistent findings in some areas, but mixed or null results in others (Wagner et al., under review). For example, high self-efficacy for safer injection (i.e., one’s confidence in his/her ability to inject safely) is consistently associated with lower rates of injection risk behavior (Avants et al., 2000; Brown, 1998; Celentano et al., 2002; Falck et al., 1995; Gibson et al., 1993; Longshore et al., 1997; Longshore et al., 2004; Racz et al., 2007; Thiede et al., 2007). Perceived social or subject norms supporting safer injection practices are generally found to be associated with lower rates of injection risk behavior (Avants et al., 2000; 60 Bailey et al., 2007; Jamner et al., 1996; Longshore et al., 1997; Longshore et al., 2004; Thiede et al., 2007). Some other constructs, though important to several theories, have yielded less definitive results. For example, response efficacy (i.e., one’s confidence that engaging in a protective behavior will successfully avert the health threat) has had no association with risk behavior in most studies (Gibson et al., 1993; Hartgers et al., 1992; Jamner et al., 1996; Longshore et al., 1997; Longshore et al., 2004; cf Avants et al., 2000). Similarly, perceived severity (i.e., one’s opinion of the seriousness of the illness in question and its consequences) has not been associated with injection risk behavior in the few studies that have included it (Brown, 1998; Hartgers et al., 1992; Racz et al., 2007), though “fear of AIDS” was indirectly associated with injection risk behavior in one study (Longshore et al., 1997). Perceived risk of HIV infection, or the conditional probability that one will become infected with HIV due to one’s injection drug use, has been associated with lower levels of injection risk behavior in some studies (Bailey et al., 2007; Smyth et al., 2001), but not others (Stein et al., 2007). One construct that has received considerably less attention, but which has the potential to help explain some of the inconsistent findings regarding psychosocial predictors of injection risk behavior reported to date, is the perceived risk or consequences of refusing to share injection equipment. While perceived risk of HIV infection via risky injection practices has been relatively well-studied, the risk associated with refusing to share injection equipment has not been factored in to most behavioral studies. Decisions about whether or not to engage in risk behaviors are grounded in a “situated rationality” (Kowalewski et al., 1997), in which individuals weigh a host of potential outcomes in addition to the risk of becoming infected with HIV or HCV. For example, in an early ethnographic study, Connors (1992) identified a “hierarchy of risks” that included not only the risk of HIV via syringe sharing, but also the risk of arrest or incarceration due to paraphernalia possession and the risk of experiencing withdrawal symptoms if drug use is delayed. Both the favorable (i.e., avoiding HIV) and unfavorable (e.g., forgoing drugs, being arrested) consequences of refusing to share injection equipment may influence behavior. 61 In our previous work, we assessed the perceived consequences of refusing to share injection equipment using two subscales: social/internal consequences and structural/external consequences (Wagner et al., in preparation). These subscales were derived from qualitative interviews with IDUs who described their most recent episode of risky injection, and reported on the types of consequences they believed would have resulted had they refused to use the shared equipment. Social/internal consequences of refusing to share included: the risk of experiencing withdrawal symptoms, forgoing drug use altogether, offending injection partners by implying a lack of trust, offending injection partners by implying that they are HIV positive, or causing injection partners to lose their share of a pooled drug purchase. Structural/external consequences of refusing to share included: the risk of being arrested for paraphernalia possession, the risk of being arrested for drug possession, the possibility of losing safe housing options (e.g., getting kicked out of a house or encampment), the inconvenience of accessing sterile injection supplies, the need to spend money to purchase new supplies, or the risk of losing one’s own share of a pooled drug purchase. In bivariate analysis, both the social/internal and structural/external consequences scales were significantly correlated with syringe and paraphernalia sharing. In multiple linear regression, the perceived social/internal consequences were significantly associated with increased frequency of both syringe and paraphernalia sharing in the past 30 days. This association persisted after controlling for other psychosocial correlates of risky injection behavior such as self-efficacy for safer injection, response efficacy, social norms, and perceived risk of HIV or HCV infection. In contrast, the perceived structural/external consequences did not have a significant association with injection risk behavior. Some theorists have posited the existence of a set of “facilitating conditions”, which represent individual or environmental conditions that make it easier or more difficult to engage in a health behavior (Montaño et al., 1997). These conditions are hypothesized to moderate the influence of behavioral intentions on behavior. That is, under certain conditions individuals are more able to act on their behavioral intentions, while other conditions may inhibit that ability. 62 Similarly, we hypothesize that in addition to their main effect on behavior, the perceived consequences of refusing to share injection equipment might moderate the effects of other correlates of injection risk behavior. That is, among individuals who report that they are more strongly influenced by the perceived consequences of refusing to share injection equipment, the effects of established correlates of injection risk behavior may be inhibited. Alternately, among those who say they are less strongly influenced by the perceived consequences of refusing to share, the effects of other variables may be more evident. For example, the perceived risk of HIV infection via IDU may be significantly associated with injection risk behavior only in the absence of other competing consequences or risks. In the current study, we employed structural equation modeling to assess the cross- sectional association between injection risk behavior and established psychosocial correlates of behavior. We investigated the moderating influence of the perceived consequences of refusing to share injection equipment, using the two subscales derived from our qualitative work. We hypothesized a competitive interaction effect; that is, constructs such as self-efficacy, perceived risk of HIV/HCV infection, response efficacy, perceived severity of HIV/HCV infection, and peer norms for syringe sharing would be more strongly associated with injection risk behavior in the expected direction when participants reported that they were less influenced by the perceived consequences of refusing to share, whereas their effects would be attenuated when the influence of the perceived consequences of refusing to share was greater. Methods Sample Data for the current study were collected as the second phase of a larger, mixed method study conducted at a large Syringe Exchange Program (SEP) in Los Angeles, California from July 2008 to April 2009. Methods and findings from the first phase of the study are described in detail elsewhere (Wagner et al., in preparation). Briefly, in the first phase of the study 30 IDUs participated in in-depth, qualitative interviews that explored the circumstances surrounding their most recent risky injection episode. Eligibility criteria for the first phase of the study were: 63 1) being at least 18 years old, 2) having injected any drug at least once in the past 30 days, and 3) having engaged in a risky injection event at least once in the past 30 days. Risky injection was defined as any of the following: using a previously used syringe, sharing a cooker when any of the equipment had been previously used, sharing a cotton or rinse water, or syringe-mediated drug splitting (i.e., backloading or piggybacking) with previously used syringes or cookers. Data from those qualitative interviews were used to construct the perceived consequences items for the current analysis, as will be described below. For the second phase of the study, 200 IDUs were recruited from the same SEP to participate in a structured interview that yielded the quantitative data used in the current analysis. Participants were recruited via word of mouth and outreach by study staff members within the SEP. Due to the challenges inherent in sampling from a population such as IDUs who access SEPs, it was not feasible to collect a random sample. Rather, the days and times that the SEP was open were divided into 4-hour blocks that were randomly sampled, so that data collection occurred for approximately 16 hours per week on randomly selected days and times that the SEP was open. Eligibility criteria for the second phase of the study were: 1) being > 18 years old, 2) having injected any drug at least once in the past 30 days, and 3) not having participated in the first phase of the study. Current IDU status (having injected at least once in the past 30 days) was assessed by visual examination of injection stigmata and in a series of screening questions that evaluated the participant's knowledge about typical injection procedures, similar to other studies (Garfein et al., 2007b). Study staff members who conducted the eligibility screening have several years experience working with IDUs and have an in-depth knowledge of injection practices. Eligible participants provided written informed consent and were compensated $25 for their participation. Data were collected via Audio Computer Assisted Interview (ACASI). The use of ACASI is an effective means of helping to reduce bias associated with socially desirable reporting among IDUs (Des Jarlais et al., 1999). Participants listened to the questions and answers being read through a set of headphones and entered their answers directly into laptop computers. The 64 computers were fitted with touch-screen adapters so that participants could enter their answers directly into the screen, and they were given the option of using the computer mouse. A research assistant was present at all times to answer questions and assist participants with the computer. The University of Southern California Health Sciences Institutional Review Board approved all study procedures. Of the 200 IDUs who participated, 13 were excluded: 1 suspected non-IDU who appeared to have misrepresented his status as an IDU, 7 IDUs who reported in the ACASI that they had not injected at all in the past 30 days, 2 IDUs who completed the interview more than once, 1 IDU who participated in both phase one and phase two, and 1 IDU who was incoherent for a majority of the interview. One IDU who identified as transgender was excluded in order to allow for male/female gender comparisons. After these exclusions, the final sample consisted of 187 individuals. Individuals with missing data on any variables used in the current analysis were also excluded (n=57), yielding a final analytic sample of 130. The bulk of these exclusions were due to missing values for self-reported HIV and HCV status among individuals who said they had never been tested for HIV or HCV. Women were more likely to be retained in the final sample than men (p=0.04). There were no significant differences between those retained and those excluded in frequency of injection risk behavior, mean perceived social/internal or structural/external consequences, daily frequency of injection, age, or race/ethnicity (ps >0.10). Measures Demographics. Demographic characteristics included age, sex, self-reported HIV and HCV status, and homelessness. Homelessness was assessed by asking whether participants considered themselves homeless in the past 30 days. Injection Risk Behavior. Injection risk behavior was assessed in a series of questions based on those used by the CIDUS III study (Garfein et al., 2007a) and the NIDA Risk Behavior Assessment (Needle et al., 1995). Five items assessed the frequency with which individuals engaged in each risk behavior in the past 30 days (0-4; “never” – “almost always”): 1) receptive syringe sharing, 2) backloaded with equipment previously used by anyone else, 3) prepared 65 drugs in a cooker previously used by anyone else, 4) used a cotton filter previously used by anyone else, 5) used rinse water previously used by anyone else. Previous research indicates that IDUs can provide reliable and unbiased responses to questions using a 30-day reference period (Needle et al., 1995), therefore all questions referred to the previous 30 days. For this analysis, a composite measure of injection risk behavior was created by taking the mean score of all five items. Daily frequency of injection was assessed by asking how many times participants injected during a normal day. Perceived consequences. Perceived consequences were measured using a series of items that were developed by the research team using qualitative data provided in the first phase of the larger mixed-methods study. In the first phase, participants were asked to describe their most recent risky injection episode (i.e., an event in which they used previously used drug injection supplies), and to describe the consequences that they believe would have occurred had they refused to share on that occasion. Questions were open-ended, and interviews were digitally-recorded and transcribed for analysis. The qualitative data were reduced into 11 perceived consequences using established methods for qualitative analysis (Wagner et al., in preparation). In the second phase of the study, participants were asked how frequently each of the 11 consequences influenced their decision whether or not to share injection equipment in the past 30 days (0-4; “never” – “almost always”). For example, “How often did the possibility of becoming dopesick (i.e., experiencing withdrawal symptoms) because you didn't have any equipment to use influence whether or not you used a syringe that had been used before?” The questions were asked separately for two behavioral outcomes of interest: syringe sharing and paraphernalia sharing. After answering the question about the frequency with which each consequence influenced their decision, participants were asked to indicate how much of a problem it would be if it were to occur (1-4; “not much of a problem” – “a very big problem”). For example, “How much of a problem would it be for you if you were dopesick because you didn't have any equipment to use?” The consequence items were then weighted by their importance by creating a product score. This weighting method is similar to recommendations made by the 66 Theory of Reasoned Action (Fishbein, 1967) and is useful since more severe consequences may be more salient in their influence on behavior (Colon et al., 2005). Exploratory factor analysis of the perceived consequence items yielded a two-factor solution. The first factor consisted of items relating to structural or external consequences (i.e., threat of arrest for drug paraphernalia or drug possession, risk of losing housing, financial hardship such as having to buy new equipment or losing out on a shared drug purchase, or inconvenience in finding new equipment). The second factor consisted of social or internal consequences (i.e., the risk of experiencing withdrawal symptoms, of offending injection partner(s) based on a perceived lack of trust or accusation of HIV-positive status, the risk that injection partner(s) would lose their share of the drug purchase if preparation equipment was not shared, or the risk of having to forgo drug use altogether). Two sub-scales were created (social/internal consequences and structural/external consequences) by taking the mean of all relevant items. Because the dependent variable for this analysis consists of items assessing both syringe and paraphernalia sharing, we included items related to both syringe and paraphernalia sharing in the composite score. The sub-scales showed good internal consistency reliability, with all Cronbach's alphas > 0.70. We created dichotomous variables for use in the moderation analysis by dichotomizing on the median of each subscale, thereby creating groups for high and low structural/external consequences, and high and low social/internal consequences. Psychosocial scales. Perceived risk of HIV/HCV was defined as the probability that the threat (i.e., HIV or HCV infection) will occur given certain conditions or behaviors (i.e., RSS or RPS). Four questions were developed for this study that asked how likely subjects think it is that they will become infected with HIV (or HCV) via syringe or paraphernalia sharing, rated on a 4- point scale from “very likely” to “very unlikely”. Questions were asked separately for risk to HIV and HCV infection. In the current study, the items had Cronbach’s alphas of 0.86 for HIV and 0.89 for HCV. HIV/HCV knowledge was measured using 14 items developed for use among IDUs (Garfein et al., 2007a), which assessed knowledge about the natural history of HIV and HCV 67 infection (e.g., “You can tell by looking at a person that they have HIV infection. [True/False]”) and the relative risk of injection-related behaviors (e.g., “Re-using your own syringe is just as safe as using a brand new syringe every time [True/False]”). The scales were originally designed to represent two subscales; however, the internal consistency of the scales was unsatisfactory (Cronbach’s alphas = 0.44 and 0.24). We used exploratory factor analysis to select the six items that loaded most strongly on a single HIV/HCV knowledge factor, and calculated the score of correct answers to these six items to represent HIV/HCV knowledge. This six-item scale had a Cronbach’s alpha of 0.70. Perceived severity represents the degree of harm associated with the outcome (i.e., HIV infection; Rogers & Prentice-Dunn, 1997) and was measured using eight questions adapted from a study based on the Health Belief Model (Falck et al., 1995) such as “Getting HIV is the worst possible thing that could happen to me,” rated on a 4-point scale from “strongly agree” to “strongly disagree”. Questions were asked separately for the severity of HIV and HCV infection. In the current study, these items had Cronbach’s alphas of 0.79 for HIV and 0.81 for HCV. Self-efficacy for safer injection was measured using six items developed for use among IDUs, such as “I can avoid sharing a syringe even if I am dopesick or in withdrawal”, rated on a 4- point scale from “strongly agree” to “strongly disagree”, which have shown good internal consistency in other studies (Garfein et al., 2007a). In the current study, these items had a Cronbach’s alpha of 0.92. Response efficacy was measured using six questions that assess one’s confidence that a particular activity (i.e., using new syringes, using new paraphernalia, not splitting drug solution with a syringe) will reduce the risk of contracting HIV or HCV on a four-point scale of “definitely will not” to “definitely will” (e.g., “Using a brand new syringe every time will reduce my chances of becoming infected with HIV”). The items were developed for the current study, based on previous work (e.g., Falck et al., 1995). In the current study, these items had a Cronbach’s alpha of 0.94. 68 Social norms for syringe sharing were measured using two items developed by Garfein and colleagues (2007a) based on the work of Jamner and colleagues (1998). Questions elicited views about the expectations of peers regarding syringe and paraphernalia sharing, for example, “People I inject with think that cookers, cotton or water should never be shared whey they inject,” measured on a four-point scale from “strongly disagree” to “strongly agree”. Analysis Univariate descriptive statistics were calculated for all variables of interest using SAS 9.1.3. Structural Equation Modeling was conducted using the EQS software program (Bentler, 2004) to progressively refine a series of structural models. Because of the relatively small sample size, we used manifest indicators rather than latent factors to represent all variables in the model. Equations representing the path from psychosocial variables to injection risk behavior were controlled for gender, HIV and HCV status, homelessness, and daily frequency of injection. Equations representing the paths from peer norms and HIV/HCV knowledge to HIV and HCV severity were controlled for HIV and HCV status, respectively, as were the paths to perceived HIV and HCV risk. Adequacy of the structural equation model was evaluated using the Chi-square goodness-of-fit test statistic, comparative fit index (CFI), and root mean-square error of approximation (RMSEA). Because the Chi-square statistic is sensitive to variations in sample size, the p-value of the Chi-square test was not considered the primary criterion for a good model fit. Instead, a Chi-square:degrees of freedom ratio of less than or equal to 2:1, a CFI greater than 0.95, or RMSEA less than 0.06 were employed as alternative standards to indicate goodness of model fit (Hu & Bentler, 1999). Moderation analysis is a method for identifying variables that affect the direction or strength of the association between independent and dependent variables (Baron & Kenny, 1986). That is, moderation analysis can identify differences in main effects for subgroups of the population, or identify “for whom” certain relationships exist (Frazier et al., 2004). In the current study, we tested whether the associations between psychosocial variables and injection risk 69 behavior were moderated by either the perceived structural/external or social/internal consequences of refusing to share injection equipment. We accomplished this by conducting two separate multiple group analyses. The first analysis tested for moderation by social/internal consequences, while the second analysis tested for moderation by structural/external consequences. The methods used in each multiple group analysis were the same. The multiple group analyses were conducted using the approach described by Pentz and Chou (1994), in which regression coefficients are tested for invariance between groups. First, base models were fit separately for each subgroup – in this case, one group reporting high perceived consequences (M0 high ) and one group reporting low perceived consequences (M0 low ). Modifications were made to the separate base models by adding theoretically-appropriate parameters suggested by the LaGrange Multiplier test (Chou & Bentler, 1990) until model fit was adequate, yielding modified models (M1 high and M1 low ). Second, the models were combined into a single model containing both subgroups (M0), allowing all coefficients to vary across groups. Third, regression coefficients were constrained to be equal across the two subgroups (M1). The Chi-square difference test was used to determine whether the constrained model was significantly different from the unconstrained model (M1-M0). If the Chi-square difference between the two models was not statistically significant, the constrained model was considered to be equivalent to the unconstrained model, suggesting that the coefficients were invariant between the groups. On the other hand, if the Chi-square difference test suggested that the models were significantly different, the coefficients were compared using the LaGrange Multiplier test to determine which were not equivalent (i.e., which were moderated by perceived consequences). The inadequate constraints were then released, yielding a modified model (M1*). The process of constraining coefficients, comparing model fit, and releasing inadequate constraints was conducted in a series of four steps: 1) comparing regression coefficients from intermediary psychosocial variables to injection risk behavior (M1), 2) comparing regression coefficients from knowledge to intermediary psychosocial variables (M2), 3) comparing regression coefficients from peer norms to intermediary psychosocial variables (M3), and 4) comparing correlation coefficients 70 between peer norms and knowledge (M4). Regression and correlation coefficients identified as unequal across the two groups were considered to be modified by perceived consequences. Results from the two multiple group analyses (structural/external and social/internal) are presented separately. Results Sample Characteristics The demographic characteristics of the study sample are shown in Table 4.1. Participants were, on average, 43 years old, and were 40% female. The sample was ethnically diverse; 37% of participants were Hispanic/Latino, 31% were White, 20% were African American, and the remainder were a mix of Native American/Hawaiian Native, Asian, and other. The majority had a history of homelessness, and 65% reported being homeless in the past 30 days. Ten percent said that they were HIV positive, and 56% said they were HCV positive. The majority of the sample reported that heroin was the drug they injected most frequently in the past 30 days, and most injected an average of four times per day, six days per week. Table 4.2 shows the correlations amongst the independent and dependent variables of interest in the overall sample. Table 4.1. Demographic characteristics of study sample (N=130). N % Age (mean; SD) 43.4 (11.2) Female 52 40.0 Race/Ethnicity (n=128) Hispanic/Latino 47 36.7 White 39 30.5 African American 25 19.5 Native American/Hawaiian Native 8 6.3 Asian/Pacific Islander 5 3.9 Other 4 3.1 Ever homeless 108 83.1 Homeless in past 30 days 84 64.6 HIV Positive * 13 10.0 HCV Positive * 76 58.5 Drug injected most frequently in past 30 days: Heroin 115 88.5 Daily frequency of injection (mean; SD) 4.2 (2.5) Weekly frequency of injection (mean; SD) 6.3 (1.4) *self-report 71 Table 4.2. Correlations among model constructs (N=130). I II III IV V VI VII VIII IX X I Injection risk behavior 1.00 II Self-efficacy -0.22* 1.00 III Response Efficacy 0.05 0.22* 1.00 IV Perceived HIV Risk -0.13 0.15 0.27** 1.00 V Perceived HCV Risk -0.15 0.22* 0.36*** 0.74*** 1.00 VI Perceived HIV Severity -0.01 0.13 0.42*** 0.39*** 0.49*** 1.00 VII Perceived HCV Severity -0.002 -0.16 0.004 0.14 0.24** 0.41*** 1.00 VIII HIV/HCV Knowledge -0.16 0.24** 0.36*** 0.27** 0.32** 0.17 -0.16 1.00 IX Peer Norms Against Needle Sharing -0.11 0.19* 0.32** 0.06 0.06 0.18* -0.06 0.29*** 1.00 X Peer Norms Against Paraphernalia Sharing -0.22* 0.26** 0.33*** 0.13 0.23** 0.16 -0.12 0.28** 0.64*** 1.00 *p<0.05, **p<0.01, ***p<0.001 72 Social/Internal Perceived Consequences Model Fitting. Table 4.3 shows the results of the model-fitting process for the multiple groups analysis by social/internal perceived consequences. In step one, all regression coefficients between intermediary psychosocial variables and injection risk behavior were found to be equivalent across groups, as indicated by the non-significant Chi-square difference test (M1 – M0: ! 2 = 12.69, df = 9, p=0.18). In step two, three regression coefficients between knowledge and intermediary psychosocial variables were found to be unequal across groups – releasing those constraints produced a non-significant Chi-square difference test (M2* – M1: ! 2 = 1.35, df = 3, p=0.71). In step three, all regression coefficients between peer norms and the intermediary psychosocial variables were equivalent across groups (M3 – M2*: ! 2 = 13.17, df = 12, p = 0.35). In step four, the correlation coefficients amongst peer norms and HIV/HCV knowledge were also equivalent across groups (M4 – M3: ! 2 = 1.04, df = 2, p=0.59). The final structural model had good fit (! 2 = 126.49, df = 118, p = 0.28; CFI = 0.98, RMSEA = 0.03). Moderation Results. Figure 4.1 shows the results of the multiple groups analysis testing the moderating effects of perceived social/internal consequences of refusing to share injection equipment. Only paths significant at the p<0.05 level are depicted, unless otherwise noted. The standardized coefficients for the high and low perceived consequences groups are reported for each significant path. The standard errors of the coefficients were not constrained to be equal; therefore, the standardized coefficients may appear slightly different even though they are statistically equivalent. Solid lines represent paths that are equivalent, while dashed lines represent paths that are significantly different across groups. Three paths were moderated by perceived social/internal consequences of refusing to share. Greater HIV/HCV knowledge was associated with less perceived HCV severity amongst those who reported greater influence social/internal consequences of refusing to share. There was no association between HIV/HCV knowledge and HCV severity in the low perceived social/internal consequences group. 73 Table 4.3. Results of multiple group model-fitting process, by perceived social/internal consequences (N=130). Model Chi-square df p-value CFI RMSEA High Consequences M0 high 80.66 50 0.004 0.87 0.10 M1 high 40.18 45 0.67 1.00 0.00 Low Consequences M0 low 85.35 50 0.001 0.85 0.10 M1 low 58.06 47 0.13 0.95 0.06 Combined M0 98.24 92 0.31 0.99 0.03 M1 110.94 101 0.23 0.98 0.04 M1-M0 12.69 9 0.18 M2 124.30 107 0.12 0.96 0.05 M2-M1 13.37 6 0.04 M2* 112.29 104 0.27 0.98 0.04 M2*-M1 1.35 3 0.71 M3 125.46 116 0.26 0.98 0.04 M3-M2* 13.17 12 0.35 M4 126.49 118 0.28 0.98 0.03 M4-M3 1.04 2 0.59 M0 = basic model combining high and low perceived consequences; M1 = model with regression coefficients between psychosocial variables and injection risk behavior constrained equal across groups; M2 = model with regression coefficients between knowledge and psychosocial variables constrained equal across groups, over M1; M2* = modified model with unequal coefficients unconstrained; M3 = model with regression coefficients between peer norms and psychosocial variables constrained equal across groups, over M2*; M4 = model with correlation coefficients between peer norms and knowledge constrained equal across groups, over M3. 74 Figure 4.1. Multiple group structural equation model depicting significant regression paths between psychosocial variables and injection risk behavior, moderated by perceived social/internal consequences of refusing to share injection equipment (N=130). All coefficients are standardized. Dashed paths differ by subgroup. All p<0.05 unless otherwise noted. n.s. = non-significant. !"#$%&'(&$)'*' +,-#$&'./ !"#$&'/0 +,-#$&'/. !"#$&'/. +,-#$&'.. !"#$%&'/( +,-#$%&'/1 !"#$&'// +,-#$&'.. !"#$&'.. +,-#$&'/2 !"#$%&'/2 +,-#$%&'&3$)'*' !"#$%&'/. +,-#$%&'/0 !"#$&'/2 +,-#$&'/0 !"#$%&'(4$ +,-#$%&'(0$$ 56&'&7 !"#$%&'(1 +,-#$%&'/1 !"#$&'/( +,-#$&'// !"#$&'/2 +,-#$&'/. !"#$&'4/ +,-#$&'40 !"#$&'/3 +,-#$&'/7 8)9:;<",)$ ="*>$ ?:@AB",C !8D$="*> !ED$="*> F:GH% :H!;A;I =:*5,)*:$ :H!;A;I !8D$ *:B:C"<I !8DJ!ED K),-G:LM: N::C$O,CP*$ Q5ACA5@:C)AG"AR N::C$ O,CP*$ Q*IC")M:R !ED$ *:B:C"<I 75 In both groups, HIV/HCV knowledge was positively associated with perceived risk of HCV, however the association was significantly stronger in the high consequences group compared to the low consequences group. There was no association between HIV/HCV knowledge and self-efficacy for safer injection in the high consequences group, while in the low consequences group HIV/HCV knowledge was significantly associated with greater self-efficacy. Several paths were similar across groups. In both the high and low perceived consequences groups, higher self-efficacy for safer injection was associated with less frequent injection risk behavior, while higher response efficacy was associated with more frequent injection risk behavior. Also in both groups, there was a marginally significant association between higher HIV/HCV knowledge and less frequent injection risk behavior (p=0.08). In both groups, peer norms against syringe sharing were negatively associated with perceived HIV and HCV risk. Peer norms against paraphernalia sharing were associated with greater levels of response efficacy and greater perceived risk of HCV. In both groups, greater HIV/HCV knowledge was associated with higher levels of response efficacy and perceived risk of HIV. Finally, in both groups there were positive correlations amongst peer norms against needle sharing, peer norms against paraphernalia sharing, and HIV/HCV knowledge. Structural/External Perceived Consequences Model Fitting. Table 4.4 shows the results of the model-fitting process for the multiple groups analysis by structural/external perceived consequences. In step one, one regression coefficient between an intermediary psychosocial variable and injection risk behavior was found to be unequal across groups – releasing the constraint yielded a non-significant Chi-square difference test (M1* – M0: ! 2 = 9.26, df = 8, p=0.32). In step two, two regression coefficients representing paths between knowledge and the intermediary psychosocial variables were found to be unequal across groups – releasing those constraints produced a non-significant Chi-square difference test (M2* – M1*: ! 2 = 2.93, df = 4, p=0.57). In step three, all regression coefficients between peer norms and the intermediary psychosocial variables were equivalent across groups (M3 – M2*: ! 2 = 13.38, df = 12, p = 0.34). In step four, all correlation coefficients amongst peer 76 norms and HIV/HCV knowledge were also equivalent across groups (M4 – M3: ! 2 = 0.32, df = 2, p=0.85). The final structural model had good fit (! 2 = 138.56, df = 116, p = 0.08; CFI = 0.95, RMSEA = 0.06). Moderation results. Figure 4.2 shows the results of the multiple groups analysis testing the moderating effects of perceived structural/external consequences of refusing to share injection equipment. Again, standardized coefficients for paths significant at the p<0.05 level are depicted for both the high and low consequences groups. The standard errors of the coefficients were not constrained to be equal; therefore, the standardized coefficients may appear slightly different even though they are statistically equivalent. Solid lines represent paths that are statistically equivalent; dashed lines represent paths that are significantly different across groups. Three paths were moderated by perceived structural/external consequences of refusing to share. HIV/HCV knowledge was significantly associated with greater perceived risk of both HIV and HCV amongst those who reported greater influence of structural/external consequences, while there was no association in the low consequences group. Peer norms against paraphernalia sharing were associated with less injection risk behavior in the high consequences group, but not the low consequences group. Again, several paths were similar across groups. In both the high and low perceived consequences groups, higher self-efficacy for safer injection was associated with less frequent injection risk behavior, while higher response efficacy was associated with more frequent injection risk behavior. Also in both groups, there was a marginally significant direct effect of higher HIV/HCV knowledge on less frequent injection risk behavior (p=0.06). In both groups, peer norms against paraphernalia sharing were significantly associated with greater response efficacy and greater perceived risk of HCV, and marginally associated with greater self-efficacy for safer injection. HIV/HCV knowledge was significantly associated with lower perceived HCV severity and greater response efficacy, and marginally associated with greater self-efficacy for safer injection. Finally, in both groups there were positive correlations amongst peer norms against needle sharing, peer norms against paraphernalia sharing, and HIV/HCV knowledge. 77 Table 4.4. Results of multiple group model-fitting process, by perceived structural/external consequences (N=130). Model Chi-square df p-value CFI RMSEA High Consequences M0 high 82.7 50 0.002 0.84 M1 high 56.27 47 0.17 0.96 0.06 Low Consequences M0 low 104.62 50 0.0001 0.80 0.13 M1 low 56.4 43 0.08 0.95 0.07 Combined M0 112.67 90 0.05 0.95 0.06 M1 129.41 99 0.02 0.94 0.07 M1-M0 16.73 9 0.05 M1* 121.94 98 0.05 0.95 0.06 M1*-M0 9.26 8 0.32 M2 136.09 104 0.19 0.93 0.06 M2-M1* 14.16 6 0.03 M2* 124.86 102 0.06 0.95 0.06 M2*-M1* 2.93 4 0.57 M3 138.24 114 0.06 0.95 0.06 M3-M2* 13.38 12 0.34 M4 138.56 116 0.08 0.95 0.06 M4-M3 0.32 2 0.85 M0 = basic model combining high and low perceived consequences; M1 = model with regression coefficients between psychosocial variables and injection risk behavior constrained equal across groups; M1* = modified model with unequal constraints released; M2 = model with regression coefficients between knowledge and psychosocial variables constrained equal across groups, over M1*; M2* = modified model with unequal constraints released; M3 = model with regression coefficients between peer norms and psychosocial variables constrained equal across groups, over M2*; M4 = model with correlation coefficients between peer norms and knowledge constrained equal across groups, over M3. 78 Figure 4.2. Multiple group structural equation model depicting significant regression paths between psychosocial variables and injection risk behavior, moderated by perceived structural/external consequences of refusing to share injection equipment (N=130). All coefficients are standardized. Dashed paths differ by subgroup. All p<0.05 unless otherwise noted. n.s. = non-significant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iscussion We hypothesized that perceived consequences of refusing to share injection equipment would moderate the associations between psychosocial variables and injection risk behavior in a competitive manner – that is, in the presence of greater influence of perceived consequences of refusing to share, constructs such as perceived risk of HIV or HCV infection would have a weaker association with injection risk behavior. Of the six associations that appeared to be moderated by perceived consequences, only one was in the expected direction – among those reporting low social/internal consequences, HIV/HCV knowledge was significantly associated with greater self- efficacy for safer injection, while in the high consequences group this association was absent. This suggests that in the presence of higher social or internal consequences of refusing to share (i.e., risking angering or upsetting injection partners, withdrawal symptoms, etc.), having more knowledge about HIV/HCV transmission is not necessarily associated with greater confidence in one’s ability to inject safely, whereas in the absence of those competing concerns, having more knowledge is associated with greater confidence. The direction of the remaining results was unexpected, but suggest an alternate explanation: those who reported that they were strongly influenced by the perceived consequences of refusing to share (the high consequences group) may be particularly sensitive to a host of factors. In the social/internal model, the association between knowledge and perceived HCV severity was moderated by perceived consequences – among those who reported stronger influence of the consequences of refusing to share, knowledge was associated with less perceived HCV severity, while there was no association in the low consequences group. The negative association between HIV/HCV knowledge and perceived HCV severity among those who perceived high social/internal consequences may represent desensitization to the severity of HCV. Individuals who are more sensitive to the consequences associated with upsetting partners or the risk of drug withdrawal and who have greater knowledge about HIV/HCV may be more likely to minimize the potential severity of HCV in relation to the other negative outcomes they are avoiding by sharing injection supplies. Those who are more educated about 80 HIV and HCV and more influenced by social factors may also have more knowledge about treatment options for HCV, and may also know that a large proportion of their peers are living relatively healthy lives with HCV. In the structural/external model, peer norms against paraphernalia sharing were strongly associated with less frequent injection risk behavior in the high consequences group, while this association did not exist in the low consequences group. This was the only path from a psychosocial variable to injection risk behavior that was moderated by perceived consequences. Again, individuals who are more concerned about the perceived consequences of refusing to share may also be more sensitive to the influence of peer norms against paraphernalia sharing. In both the social/internal and structural/external models, HIV/HCV knowledge had a stronger association with perceived risk of HCV in the high consequences group compared to the low consequences group. Among those who were particularly concerned about the perceived consequences of refusing to share, increased knowledge about HIV and HCV was associated with a heightened sense of risk for HCV via injection drug use, whereas among those who were less concerned or less influenced by the perceived consequences of refusing to share, increased knowledge about HIV/HCV did not necessarily translate into increased risk perceptions. In sum, these findings may reflect a particular sensitivity or aversion to risk. Perhaps the perceived consequences measure is assessing underlying personality differences related to the way that individuals assess or manage risk perceptions. In other respects, the two multiple group analyses yielded fairly consistent results. Several of the paths found to be equivalent between high and low perceived consequences groups (i.e., the un-moderated paths) were similar between the two models. In both in the social/internal and the structural/external models there was a strong association between self- efficacy for safer injection and less frequent injection risk behavior. This finding is consistent with those of many other investigations (Avants et al., 2000; Brown, 1998; Celentano et al., 2002; Falck et al., 1995; Gibson et al., 1993; Longshore et al., 1997; Longshore et al., 2004; Racz et al., 2007; Thiede et al., 2007). This finding suggests that those who report greater confidence in their 81 ability to inject safely are also more likely to report less injection risk behavior, regardless of whether or not they are influenced by the perceived consequences of refusing to share. Response efficacy, or confidence in the ability of a protective behavior to successfully avert the health threat, is predicted to be associated with reduced risk behavior (Rogers & Prentice-Dunn, 1997). In both final structural equation models, response efficacy was significantly associated with more frequent injection risk behavior. However, the bivariate correlation between response efficacy and injection risk behavior was small in magnitude and not statistically significant (R=0.05, p=0.61). Given the lack of direct effects between response efficacy and injection risk behavior found in other studies (Gibson et al., 1993; Hartgers et al., 1992; Jamner et al., 1996; Longshore et al., 1997; Longshore et al., 2004), cf (Avants et al., 2000), more research is needed to understand the role of this theoretical predictor of risk behavior. Also consistent were the positive correlations amongst peer norms and HIV/HCV knowledge, and the marginally- significant direct association between knowledge and HIV/HCV risk. Limitations The cross-sectional nature of the current study limits our ability to make any causal conclusions about the direction of influence represented in the structural model – such conclusions would require longitudinal studies with experimental manipulation. Because of the small sample size, we were unable to test the associations using a latent factor structural equation model. Latent factor structural equation modeling has the advantage of estimating the error variance associated with each manifest indicator, which can yield a more precise estimate of the regression and correlation coefficients. In the current analysis we used manifest, or measured, indicators of all variables, which were created by calculating the mean of responses to a series of survey items. With this method, the error associated with individual items becomes incorporated into the score. Consequently, the standard errors for some manifest variables were large, which may have inhibited our ability to detect significant differences between groups. Comparison of the regression coefficients in the subgroup models (M1 high and M1 low ) suggest that some estimates may in fact differ between groups, however due to the large standard errors the 82 differences are not statistically different in the current analysis. Future studies with larger samples that will allow for latent factor structural equation models may have the ability to more precisely estimate regression coefficients and test for statistically significant differences. The generalizability of our findings is limited by the nature of the study sample. Study participants were recruited from a single SEP in Los Angeles, a large urban city that has relatively good access to sterile injection supplies via multiple SEPs and pharmacies. Therefore, our findings may not generalize to IDUs who do not access SEPs (Grau et al., 2005). Participants in our study overwhelmingly reported heroin as their drug of choice, which makes our findings difficult to generalize to IDUs who prefer other substances such as methamphetamine or cocaine. Conclusions Behavioral theorists have posited that safer behavior is facilitated under certain conditions, while under others it is inhibited (Montaño et al., 1997). In keeping with models that seek to understand the individual, social, physical, economic, and policy environments in which risk behavior is contextualized (Rhodes, 2002), we attempted to model two sets of such conditions: the perceived social/internal and structural/external consequences of refusing to share injection equipment. In earlier analyses, the perceived social/internal consequences of safer injection (e.g., risk of withdrawal symptoms, risk of offending or upsetting injection partners, risk of forgoing drug use) were associated with more frequent injection risk behavior after controlling for other psychosocial variables. In the current analysis, we hypothesized that when IDUs reported that they were more strongly influenced by the perceived consequences of refusing to share, other theoretically supported correlates of injection risk behavior would be less strongly associated with risk behavior. In fact, the bulk of our findings support an alternate hypothesis – that some associations are stronger among those individuals who report higher perceived social/internal and structural/external consequences associated with refusing to share injection equipment. In both models, HIV/HCV knowledge was associated with increased perceived risk of HCV in the high consequences group, suggesting that individuals who perceive the negative consequences of refusing to share injection equipment may also translate their 83 knowledge of HIV and HCV into greater HCV risk perceptions. Similarly, among those who reported higher structural/external consequences, peer norms against paraphernalia sharing were strongly associated with reduced injection risk behavior, while there was no association in the low consequences group. Our findings suggest some implications for future research. First, models that explicitly account for the influence of both the negative (e.g., HIV or HCV infection) and positive (e.g., avoiding social sanctions or drug withdrawal) outcomes associated with injection risk behavior may provide critical insight into the difficult decisions faced by IDUs and the consequences that extend beyond HIV/AIDS or viral hepatitis (Connors, 1992). Decisions to engage in behavior that places one at risk for HIV or HCV may seem more rational when considered in the context of the other negative outcomes that are avoided. It is evident from our findings that mere knowledge about the risk of HIV or HCV, or a perception that the risk is likely or severe, is insufficient to explain injection risk behavior. Additional qualitative research is needed to understand the factors that are salient to IDUs during the injection process, while larger quantitative studies with multiple waves of data collection are needed to strengthen our understanding of the direction of influence among variables, and the effect of changes in psychosocial variables. Second, while it may be too early to make conclusions about the direction of the moderating effect, it appears that some psychosocial variables interact with the perceived consequences of safer injection to differently influence injection risk behavior. Future studies will be required to know whether our findings regarding the apparent influence of sensitization to negative outcomes will be confirmed. If they are, interventions to help IDUs realistically assess the level of risk associated with behavior, and to strategically address those factors amenable to intervention, will be critical. 84 CHAPTER 5. SUMMARY, IMPLICATIONS, AND CONCLUSIONS Summary Nearly three decades have passed since the identification of the AIDS epidemic, and in that time individuals at risk for HIV infection have made dramatic behavioral changes. Still, IDUs remain at risk for infection with HIV and other bloodborne pathogens, and women are at heightened risk compared to their male counterparts. Substantial resources have been dedicated to understanding the factors associated with injection risk behavior among IDUs. Research grounded in Cognitive Behavioral Theory has identified some factors that are consistently correlated with injection risk behavior, such as self-efficacy for safer injection and peer norms against paraphernalia sharing. Other factors that are important in behavioral theories have been less well investigated, or have yielded mixed findings. The current study sought to understand one set of factors, the perceived consequences of refusing to share injection equipment, which might help further our understanding of the factors associated with continued injection risk behavior. In addition, we investigated whether gender differences existed in the perceived consequences of safer injection. Chapter 2 described results from the qualitative phase of the study, which collected in- depth narratives from IDUs who had recently participated in a risky injection event. Participants described the consequences that they believed would have occurred if they had refused to inject with previously used equipment at that time. The consequences were organized into four domains: individual, social, physical, and policy/economic consequences. On the individual level, respondents’ accounts of the risky injection episode overwhelmingly contextualized the events in a climate of drug dependence – most participants said that they were already, or were on the verge, of experiencing drug withdrawal symptoms and would have done almost anything to avoid the unpleasantness experienced with drug withdrawal. Social consequences involved concerns over violating social norms of reciprocity among IDUs or of offending friends or partners by implying that they were “sick” (i.e., HIV-positive). Concerns over concealing drug use from non-IDU peers, and the consequences if discovered, were also discussed. The inconvenience of 85 having to find new injection equipment at short notice, or in a setting where availability was limited was highlighted as a physical consequence. Participants described a complicated system of economic interdependence, in which pooled drug purchases and dependence on others for safe housing created a network of reciprocity that frequently involved sharing drug injection supplies. A refusal to share in those scenarios would result in both the loss of economic resources (i.e., money, drugs, housing), but also in a violation of social norms. Finally, legal consequences such as being arrested for drug or paraphernalia possession highlighted the complicated policy environment in which the consequences of possessing injection supplies included harassment, citation, or arrest. Amidst these consequences, IDUs also described their perceptions of the risk of HIV involved in sharing injection supplies – however the more immediate or severe consequences of withdrawal, social alienation, or arrest often trumped their worry about the possibility of becoming infected with HIV. As expected, women and men differed primarily in factors related to social consequences – women described events involving male sexual partners and male friends. Men more often were involved with strangers, and never discussed risky injection events that involved women. Women’s events were also characterized by more dependence on others and a heighted concern over withdrawal symptoms, compared to men. Chapter 3 described a quantitative analysis in which the qualitative data from Chapter 2 were reduced into a series of items assessing the perceived consequences of refusing to share injection equipment. A novel assessment tool was developed to measure the perceived consequences in a larger sample of IDUs. Results suggest that the measure may have good validity and good internal consistency reliability, though more research will been needed to further validate the scale. Two subscales were derived using exploratory factor analysis: social/internal consequences and structural/external consequences. In multiple linear regression there was a significant direct effect of perceived social/internal consequences on injection risk behavior – identifying greater perceived social/internal consequences of refusing to share was associated with more syringe and paraphernalia sharing in the past 30 days. Structural/external consequences did not have a main effect in the regression models. However, when asked which 86 consequences were most influential at their last risky injection event, respondents identified several structural/external consequences that influenced their behavior, such as the inconvenience of acquiring new supplies, having to spend money to purchase new supplies, or being arrested for drug possession. Chapter 4 summarized the findings from a structural equation modeling analysis that tested the moderating effects of the perceived consequences of safer injection. It was hypothesized that in the presence of social/internal or structural/external consequences of refusing to share, the influence of other theoretical correlates of injection risk behavior would be inhibited. That is, a competitive interaction effect in which other correlates would more effectively predict injection risk behavior in an environment characterized by fewer consequences. To the contrary, most of the interaction effects detected in this analysis suggested an alternate hypothesis – that individuals who perceived greater influence of social/internal or structural/external consequences were more sensitive to the influence of other factors. For example, the association between HIV/HCV knowledge and perceived HIV risk was stronger in the high consequences group, compared to the low consequences group. And, the association between peer norms against paraphernalia sharing and injection risk behavior was statistically significant in the high structural/external consequences group, but not the low consequences group. In only one case – the association between HIV/HCV knowledge and self-efficacy for safer injection – was the interaction effect in the expected direction. Among those who reported low social/internal consequences there was a positive association between knowledge and self- efficacy, but in the high consequences group this association was absent. These findings, while counter to our original hypothesis, still suggest that research is needed into the entire range of consequences that IDUs face when making decisions about injection risk behavior. Rather than competing with concerns about HIV or HCV infection, the influence of these other consequences may signify a heightened sensitivity or aversion to negative outcomes among some individuals. Taken together, the three analyses presented here suggest that there are negative outcomes in addition to the risk of HIV/HCV infection that warrant further study amongst IDUs. 87 Assessing the multitude of potential negative and positive outcomes associated with a particular behavior may help to provide a more detailed understanding of the decision-making process involved in any health behavior. IDUs appear to be particularly sensitive to the influence of individual and social-level consequences (e.g., the threat of withdrawal, the risk of offending or upsetting injection partners), though both the social/individual and structural/external consequences had a moderating effect on the influence of some other psychosocial variables. A full assessment of these factors will be critical in formulating a more complete understanding of the mechanisms affecting behavior. The Role of Gender and the Perceived Consequences of Refusing to Share Based on a significant literature describing gender differences in the social and environmental factors associated with HIV risk (Miller & Neaigus, 2001), it was expected that gender differences would be found in the content and influence of the perceived consequences of safer behavior. These expectations were partially confirmed in the qualitative findings reported in Chapter 2, in which women appeared more likely to be dependent on others for access to drugs or resources, and women’s injection events were contextualized in social networks consisting primarily of male friends or sexual partners. Men less often described themselves as relying on others for access to resources, and never discussed risky injection events with female IDUs. In the quantitative analysis results reported in Chapter 3, however, no significant gender differences were detected in the mean number of perceived consequences, or in the effect of perceived consequences on injection risk behavior. Though not statistically significant, there was some suggestion that women were slightly more likely to endorse consequences related to becoming dopesick and the inconvenience of acquiring new equipment. Men, on the other hand, appeared slightly more likely to report concerns about upsetting their injection partners. The former is somewhat consistent with earlier qualitative findings, while the latter contradicts expectations. An absence of a statistically significant association with gender does not rule out the possibility that gender differences exist, and future research will be required to confirm the absence of this association. The findings reported in Chapter 3 regarding a lack of gender difference in the 88 frequency of injection risk behavior are similar to others who have found that women were no more likely to report injection risk behavior such as sharing injection paraphernalia, even though they were more likely than men to become infected with HIV, HBV, and HCV shortly after initiation into injection drug use (Fennema et al., 1997; Garfein et al., 1996). The fact that men were also concerned about upsetting their injection partners is consistent with some ethnographic work that has described the importance of same-sex friendships among male IDUs (Bourgois & Schonberg, 2009), and may highlight an area that has been understudied. Despite the absence of statistically significant gender differences in this study, the importance of men’s influence over women’s drug use careers should not be minimized – particularly in the qualitative interviews, women described a level of dependence on male partners for safety, drugs, and resources that was not described by men. Future analyses applying theoretical orientations that are sensitive to issues of power and control (e.g., the Theory of Gender and Power; Connell, 1987) could be useful in deconstructing the narratives provided by study participants and understanding the subtle power differentials that may not have been captured in the quantitative data. Strengths and Limitations The overall findings should be considered in light of some limitations. Sampling solely from a single SEP could have introduced bias into the study sample, and limits the generalizability of the study findings. SEP users tend to engage in less injection risk behavior than those who do not access SEPs, and may differ from non-SEP users on other psychosocial characteristics (Bluthenthal et al., 2000; Grau et al., 2005). However, since up to one-third of participants reported recent risky injection behavior, they remain a population at risk for HIV infection. Similarly, participants in this study overwhelmingly reported heroin as their drug of choice, which makes findings difficult to generalize to IDUs who prefer other substances such as methamphetamine or cocaine. Heroin IDUs generally inject more frequently and with more regularity than those who prefer stimulants and are more likely to experience the physiological effects of intense withdrawal symptoms, while injection of stimulants such as methamphetamine, cocaine, or crack is often characterized by binging in social settings and increased sexual risk 89 behaviors (Santibanez et al., 2006; Shoptaw & Reback, 2007). The cross-sectional nature of all the analyses necessarily precludes conclusions about causality or direction of influence. Only longitudinal studies with experimental manipulation can provide decisive evidence about causality, and such a study design was beyond the scope of the current work. Threats to the validity of study findings due to recall bias, socially-desirable reporting, and historical events are possible, though steps were taken to minimize such effects. Quantitative data were collected via ACASI to minimize social desirability, particularly around sensitive topics such as injection behavior. Questions about injection risk behavior were limited to the past 30 days in order to help minimize recall bias. The influence of historical events cannot be controlled, though the relatively short period of data collection may help minimize this threat. Despite these limitations, the findings presented here can provide preliminary evidence to inform future research. Strengths of the current study include its mixed methods design, in which qualitative findings were used to inform the development of a novel quantitative assessment. Qualitative research provides the rich narrative and detailed insider’s perspective that is critical to understanding and applying research findings, while quantitative methods can help expand the generalizability of study findings and provide a more objective lens through which to view research results. The measure of perceived consequences will require further validation research, but exhibited good internal consistency reliability and was consistent with the theoretical underpinnings of the study. Implications for Intervention As a whole, these findings suggest several opportunities for enhanced intervention efforts. As described previously, individual interventions designed to change cognitive behavioral correlates of injection risk behavior have been somewhat successful in changing some behaviors, but not others. And, relatively few IDUs have access to such interventions – only 27% of IDUs in the most recent National HIV Behavior Surveillance Survey said they had participated in such an intervention (Centers for Disease Control and Prevention, 2009). As such, several authors have suggested that the future of intervention efforts with IDUs will involve a focus on the “risk 90 environment” in which injection risk behavior occurs (Rhodes, 2002), and that integrated intervention efforts may have the greatest chance of success (Metzger & Navaline, 2003). Next, some suggestions are offered for how these findings may inform such integrated intervention efforts, which might focus both on properties of the individual and the risk environment. The current findings suggest that the physiological effects of heroin addiction cannot be underestimated in shaping injection risk behavior. In Chapter 2, qualitative findings were contextualized in an environment overwhelmingly influenced by the concern over experiencing withdrawal symptoms. IDUs who described risky injection episodes frequently discussed how they were, or were about to become, dopesick and were attempting to prevent or mitigate the unpleasant symptoms associated with heroin withdrawal. Within this context, other consequences of refusing to share emerged, such as social consequences associated with upsetting injection partners, concerns over loss of resources or drugs, or legal consequences of carrying drugs or paraphernalia. But narratives often began and ended with concerns over the omnipresent threat of dopesickness. Avoiding dopesickness is part of the everyday struggle of being a heroin user, and has been described in several other ethnographic studies (Bourgois et al., 2006; Bourgois et al., 2004; Bourgois & Schonberg, 2009). Though not always thought of as part of the same continuum of risk reduction that includes programs such as SEPs, increased availability of drug treatment, for those who are willing to access it, could significantly mitigate the influence of withdrawal symptoms. Substitution therapies such as methadone maintenance have been found to reduce injection related risk behaviors among IDUs (Metzger & Navaline, 2003; Sorensen & Copeland, 2000), even if they ultimately result in only temporary reductions in drug use. SEPs can be effective in helping IDUs access drug treatment, in the absence of bureaucratic barriers (Heimer, 1998a). Other structural interventions that affect the “risk environment” could dramatically decrease the consequences associated with carrying sterile drug injection supplies. The IDUs in this study injected an average of four times per day; yet if they did not return used needles to the SEP, the maximum number of needles they could receive was five. For those who were forced to 91 dispose of their needles someplace other than the SEP due to the fear of arrest, loss of housing, or other consequences, their daily needs were rarely met. Having an insufficient supply of sterile injection supplies has been associated with increased risk behavior (Bluthenthal et al., 2007). Yet in areas with increased syringe coverage, increases in unsafe disposal have not been observed (Bluthenthal et al., 2007). A move towards distribution-based SEP policies and increased options for safe disposal of syringes in the community could diminish penalties for those who are unable to return used syringes, and would provide sufficient numbers of syringes for their daily needs. Ultimately, reform to drug paraphernalia laws in order to decriminalize syringe possession would remove the legal consequences of paraphernalia possession altogether. Similarly, supportive and non-abstinence-based housing options that do not force IDUs to choose between having a safe place to sleep and complete abstinence from drug use may provide a waypoint on the journey from homelessness and addiction to safer behavior. In this study, homelessness was significantly associated with paraphernalia sharing, and respondents reported significant challenges associated with accessing shelters while attempting to maintain their supply of sterile injection supplies. Others have reported that unstable housing is associated with an elevated risk of syringe sharing (Des Jarlais et al., 2007a), while improvement in housing status over time has been associated with decreases in HIV risk behavior (Aidala et al., 2005). Likewise, the social environment can be addressed through intervention. The early NIDA NADR and CA efforts included extensive community outreach components and found significant improvements in some measures of drug use frequency and risk behavior (Coyle et al., 1998). Some social network-level interventions have attempted to change the social environment via training in peer mentoring and education, with favorable results (Latkin, 1998; Latkin et al., 1996). Network-level interventions have the potential to change social norms regarding the acceptability of injection risk behavior within whole communities (Metzger & Navaline, 2003). It is possible that such interventions may have even more success if they are implemented in a context that has already removed or minimized barriers to syringe access and other negative consequences of refusing to share injection equipment. 92 Conclusions The current findings suggest that IDUs consider a host of potential negative and positive outcomes when they weigh decisions about engaging in injection risk behavior. Further, it appears that some cognitive behavioral correlates of injection risk behavior operate differently among individuals who are more heavily influenced by the array of potential negative consequences of refusing to share injection equipment. Combining individual-level strategies that help IDUs realistically assess the relative risk of a variety of outcomes with social-level strategies for normalizing safer behavior and structural-level strategies to minimize environmental barriers to safer behavior may begin to address the host of consequences associated with safer behavior in an effort to further minimize injection risk behavior. It is likely that an integration of multi-level interventions, which address the individual, social, physical, economic, and policy factors will to be critical in further reducing injection-related risk behavior (Metzger & Navaline, 2003). 93 REFERENCES Aceijas, C., Stimson, G., Hickman, M., & Rhodes, T. (2004). Global Overview of Injecting Drug Use and HIV Infection among Injecting Drug Users. AIDS, 18, 2295-2303. Agar, M. (1997). Recasting the "Ethno" in "Epidemiology". Medical Anthropology, 16, 391-403. Aidala, A., Cross, J. E., Stall, R., Harre, D., & Sumartojo, E. (2005). Housing Status and HIV Risk Behaviors: Implications for Prevention and Policy. AIDS and Behavior, 9(3), 251-265. Ajzen, I. (1991). The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes. Special Issue: Theories of Cognitive Self-regulation, 50(2), 179-211. Anglin, M. D., Hser, Y.-I., & McGlothlin, W. H. (1987). Sex Differences in Addict Careers. 2. Becoming Addicted. American Journal of Drug and Alcohol Abuse, 13(1&2), 59-71. Avants, S. K., Warburton, L. A., Hawkins, K. A., & Margolin, A. (2000). Continuation of High-risk Behavior by HIV-positive Drug Users: Treatment Implications. Journal of Substance Abuse Treatment, 19(1), 15. Bailey, S. L., Ouellet, L. J., Mackesy-Amiti, M. E., Golub, E. T., Hagan, H., Hudson, S. M., et al. (2007). Perceived Risk, Peer Influences, and Injection Partner Type Predict Receptive Syringe Sharing Among Young Adult Injection Drug Users in Five U.S. Cities. Drug & Alcohol Dependence, 91(Suppl 1), S39-47. Bandura, A. (1977). Self-efficacy: Toward a Unifying Theory of Behavioral Change. Psychological Review, 84(2), 191-215. Bandura, A. (2004). Health Promotion by Social Cognitive Means. Health Education & Behavior, 31(2), 143-164. Barnard, M. A. (1993). Needle Sharing in Context: Patterns of Sharing Among Men and Women Injectors and HIV Risks. Addiction, 88, 805-812. Baron, R. M., & Kenny, D. A. (1986). The Moderator-Mediator Variable Distinction in Social Psychological Research: Conceptual, Strategic, and Statistical Considerations. Journal of Personality and Social Psychology, 51(6), 1173-1182. Bentler, P. M. (2004). EQS 6 Structural Equation Program Manual. Encino, CA: Multivariate Software, Inc. Bluthenthal, R. N., Anderson, R., Flynn, N. M., & Kral, A. H. (2007). Higher Syringe Coverage is Associated with Lower Odds of HIV Risk and Does Not Increase Unsafe Syringe Disposal Among Syringe Exchange Program Clients. Drug and Alcohol Dependence, 89(2-3), 214-222. Bluthenthal, R. N., Kral, A. H., Erringer, E. A., & Edlin, B. R. (1999a). Drug Paraphernalia Laws and Injection-related Infectious Disease Risk Among Drug Injectors. Journal of Drug Issues, 29(1), 1-16. Bluthenthal, R. N., Kral, A. H., Gee, L., Erringer, E. A., & Edlin, B. R. (2000). The Effect of Syringe Exchange Use on High-risk Injection Drug Users: A Cohort Study. AIDS, 14(5), 605-611. 94 Bluthenthal, R. N., Lorvick, J., Kral, A. H., Erringer, E. A., & Kahn, J. G. (1999b). Collateral Damage in the War on Drugs: HIV Risk Behaviors Among Injection Drug Users. International Journal of Drug Policy, 10, 25-38. Booth, R. E., Kwiatkowski, C. F., & Stephens, R. C. (1998). Effectiveness of HIV/AIDS Interventions on Drug Use and Needle Risk Behaviors for Out-of-Treatment Injection Drug Users. Journal of Psychoactive Drugs, 30(3), 269-278. Booth, R. E., Kwiatkowski, C. F., & Weissman, G. (1999). Health-related Service Utilization and HIV Risk Behaviors Among HIV Infected Injection Drug Users and Crack Smokers. Drug & Alcohol Dependence, 55(1-2), 69-78. Bourgois, P., Martinez, A., Kral, A., Edlin, B. R., Schonberg, J., & Ciccarone, D. (2006). Reinterpreting Ethnic Patterns Among White and African American Men Who Inject Heroin: A Social Science of Medicine Approach. PLoS Med, 3(10), e452. Bourgois, P., Prince, B., & Moss, A. (2004). The Everyday Violence of Hepatitis C Among Young Women Who Inject Drugs in San Francisco. Human Organization, 63(3), 253-264. Bourgois, P., & Schonberg, J. (2009). Righteous Dopefiend. Berkeley and Los Angeles, CA: University of California Press. Brown, E. J. (1998). Female Injecting Drug Users: Human Immunodeficiency Virus Risk Behavior and Intervention Needs. Journal of Professional Nursing, 14(6), 361-369. Bruneau, J., Lamothe, F., Soto, J., Lachance, N., Vincelette, J., Vassal, A., et al. (2001). Sex- Specific Determinants of HIV Infection Among Injection Drug Users in Montreal. Canadian Medical Association Journal, 164(6), 767-773. Burris, S., Blankenship, K. M., Donoghoe, M., Sherman, S., Vernick, J. S., Case, P., et al. (2004). Addressing the "Risk Environment" for Injection Drug Users: The Mysterious Case of the Missing Cop. Milbank Quarterly, 82(1), 125-156. Catania, J. A., Kegeles, S. M., & Coates, T. J. (1990). Towards an Understanding of Risk Behavior: An AIDS Risk Reduction Model (ARRM). Health Education and Behavior, 17(1), 53-72. Celentano, D. D., Cohn, S., Davis, R. O., & Vlahov, D. (2002). Self-efficacy Estimates for Drug Use Practices Predict Risk Reduction Among Injection Drug Users. Journal of Urban Health, 79(2), 245-256. Centers for Disease Control and Prevention. (1998). Recommendations for Prevention and Control of Hepatitis C Virus (HCV) infection and HCV-related Chronic Disease. MMWR 1998, 47(No. RR-19). Centers for Disease Control and Prevention. (2006). HIV Incidence 2006. Retrieved July 16, 2009, from http://www.cdc.gov/hiv/topics/surveillance/resources/slides/incidence/index.htm Centers for Disease Control and Prevention. (2008). HIV/AIDS Surveillance in Injection Drug Users. Retrieved August 10, 2009, from http://www.cdc.gov/hiv/idu/resources/slides/index.htm 95 Centers for Disease Control and Prevention. (2009). HIV-Associated Behaviors Among Injecting- Drug Users -- 23 Cities, United States, May 2005-February 2006. MMWR, 58(13), 329- 332. Chou, C.-P., & Bentler, P. M. (1990). Model Modification in Covariance Structure Modeling: A Comparison among Likelihood Ratio, LaGrange Multiplier, and Wald Tests. Multivariate Behavioral Research, 25, 115-136. Clatts, M. C., Davis, W. R., & Atillasoy, A. (1995). Hitting a Moving Target: The Use of Ethnographic Methods in the Evaluation of AIDS Outreach Programs for Homeless Youth in NYC. Qualitative Methods in Drug Abuse and HIV Research. NIDA Research Monograph., 157, 117-135. Clements, K., Gleghorn, A., Garcia, D., Katz, M., & Marx, R. (1997). A Risk Profile of Street Youth in Northern California: Implications for Gender-Specific Human Immunodeficiency Virus Prevention. Journal of Adolescent Health, 20(5), 343-353. Colon, H. M., Finlinson, H. A., Fishbein, M., Robles, R., Soto-Lopez, M., & Marcano, H. (2005). Elicitation of Salient Beliefs Related to Drug Preparation Practices Among Injection Drug Users in Puerto Rico. AIDS and Behavior, 9(3), 363-375. Connell, R. W. (1987). Gender & Power: Society, the Person and Sexual Politics. Stanford, CA: Stanford University Press. Connors, M. M. (1992). Risk Perception, Risk Taking and Risk Management among Intravenous Drug Users: Implications for AIDS Prevention. Social Science & Medicine, 34(6), 591- 601. Copenhaver, M. M., Johnson, B. T., Lee, I. C., Harman, J. J., Carey, M. P., & the SHARP Research Team. (2006). Behavioral HIV Risk Reduction Among People who Inject Drugs: Meta-analytic Evidence of Efficacy. Journal of Substance Abuse Treatment, 31, 163-171. Coyle, S. L., Needle, R. H., & Normand, J. (1998). Outreach-based HIV Prevention for Injecting Drug Users: A Review of Published Outcome Data. Public Health Reports, 113(Suppl 1), 19-30. Cruz, M. F., Mantsios, A., Ramos, R., Case, P., Brouwer, K. C., Ramos, M. E., et al. (2006). A Qualitative Exploration of Gender in the Context of Injection Drug Use in Two U.S.- Mexico Border Cities. AIDS and Behavior, 11(2), 253-262. Davey-Rothwell, M. A., & Latkin, C. A. (2007). Gender Differences in Social Network influence among Injection Drug Users: Perceived Norms and Needle Sharing. Journal of Urban Health, 84(5), 691-703. De, P., Cox, J., Boivin, J. F., Platt, R. W., & Jolly, A. M. (2007). The Importance of Social Networks in their Association to Drug Equipment Sharing among Injection Drug Users: A Review. Addiction, 102(11), 1730-1739. Des Jarlais, D. C., Braine, N., & Friedmann, P. (2007a). Unstable Housing as a Factor for Increased Injection Risk Behavior at US Syringe Exchange Programs. AIDS and Behavior, 11(6 Suppl), 78-84. 96 Des Jarlais, D. C., Braine, N., Yi, H., & Turner, C. (2007b). Residual Injection Risk Behavior, HIV Infection, and the Evaluation of Syringe Exchange Programs. AIDS Education and Prevention, 19(2), 111-123. Des Jarlais, D. C., Paone, D., Milliken, J., Turner, C. F., Miller, H., Gribble, J., et al. (1999). Audio- computer Interviewing to Measure Risk Behaviour for HIV Among Injecting Drug Users: A Quasi-randomised Trial. The Lancet, 353(9165), 1657-1661. Des Jarlais, D. C., & Semaan, S. (2008). HIV Prevention for Injecting Drug Users: The First 25 Years and Counting. Psychosomatic Medicine, 70(5), 606-611. Dickson-Gomez, J., Hilairo, H., Convey, M., Corbett, A. M., Weeks, M., & Martinez, M. (2009). The Relationship Between Housing Status and HIV Risk Among Active Drug Users: A Qualitative Analysis. Substance Use & Misuse, 44, 139-162. Dwyer, D., Richardson, D., Ross, M. W., Wodak, A., Miller, M. E., & Gold, J. (1994). A Comparison of HIV Risk Between Women and Men Who Inject Drugs. AIDS Education and Prevention, 6(5), 379-389. Epele, M. E. (2002). Gender, Violence and HIV: Women's Survival in the Streets. Culture Medicine and Psychiatry, 26, 33-54. Evans, J. L., Hahn, J. A., Page-Shafer, K., Lum, P. J., Stein, E. S., Davidson, P. J., et al. (2003). Gender Differences in Sexual and Injection Risk Behavior Among Active Young Injection Drug Users in San Francisco (the UFO Study). Journal of Urban Health, 80(1), 137-146. Falck, R. S., Siegal, H. A., Wang, J., & Carlson, R. G. (1995). Usefulness of the Health Belief Model in Predicting HIV Needle Risk Practices Among Injection Drug Users. AIDS Education and Prevention, 7(6), 523-533. Fennema, J. S. A., Ameijden, E. J. C. V., Hoek, A. V. D., & Coutinho, R. A. (1997). Young and Recent-Onset Injecting Drug Users are at Higher Risk for HIV. Addiction, 92(11), 1457- 1466. Fishbein, M. (Ed.). (1967). Readings in Attitude Theory and Measurement. New York: Wiley. Fisher, J. D., & Fisher, W. A. (1992). Changing AIDS-Risk Behavior. Psychological Bulletin, 111(3), 455-474. Frazier, P. A., Tix, A. P., & Barron, K. (2004). Testing Moderator and Mediator Effects in Counseling Psychology Research. Journal of Counseling Psychology, 51(1), 115-134. Friedman, S. R., Cooper, H., Templaski, B., Keem, M., Friedman, R., Flom, P. L., et al. (2006). Relationships of Deterrence and Law Enforcement to Drug-related Harms Among Drug Injectors in US Metropolitan Areas. AIDS, 20, 93-99. Garfein, R. S., Golub, E. T., Greenberg, A., Hagan, H., Hanson, D. L., Hudson, S. M., et al. (2007a). A Peer-education Intervention to Reduce Injection Risk Behaviors for HIV and HCV Infection in Young Injection Drug Users. AIDS, 21(14), 1923-1932. 97 Garfein, R. S., Swartzendruber, A., Ouellet, L., Kapadia, F., Hudson, S. M., Thiede, H., et al. (2007b). Methods to Recruit and Retain a Cohort of Young Adult Injection Drug Users for the Third Collaborative Injection Drug Users Study/Drug Users Intervention Trial (CIDUS III/DUIT). Drug and Alcohol Dependence, 91S, S4-S17. Garfein, R. S., Vlahov, D., Galai, N., Doherty, M. C., & Nelson, K. E. (1996). Viral Infections in Short-Term Injection Drug Users: The Prevalence of the Hepatitis C, Hepatitis B., Human Immunodeficiency, and Human T-Lymphotrpoic Viruses. American Journal of Public Health, 86(5), 655-661. Gibson, D. R., Choi, K. H., Catania, J. A., Sorensen, J. L., & Kegeles, S. (1993). Psychosocial Predictors of Needle Sharing Among Intravenous Drug Users. International Journal of the Addictions, 28(10), 973-981. Gibson, D. R., McCusker, J., & Chesney, M. (1998). Effectiveness of Psychosocial Interventions in Preventing HIV Risk Behaviour in Injecting Drug Users. AIDS, 12(8), 919-929. Glanz, K., Lewis, F. M., & Rimer, B. (Eds.). (1997). Health Behavior and Health Education (2nd ed.). San Francisco: Jossey-Bass. Glaser, B., & Strauss, A. (1967). The Discovery of Grounded Theory. Chicago: Aldine. Grau, L. E., Bluthenthal, R. N., Marshall, P., Singer, M., & Heimer, R. (2005). Psychosocial and Behavioral Differences Among Drug Injectors Who Use and Do Not Use Syringe Exchange Programs. AIDS and Behavior, 9(4), 495-504. Hagan, H., Thiede, H., & Des Jarlais, D. C. (2005). HIV/hepatitis C Virus Co-infection in Drug Users: Risk Behavior and Prevention. AIDS, 19(suppl 3), S199-S207. Hankins, C. (2008). Sex, Drugs, and Gender? High Time for Lived Experience to Inform Action. International Journal of Drug Policy, 19(2), 95+96. Hartgers, C., Krijnen, P., van den Hoek, J. A., Coutinho, R. A., & Van der Pligt, J. (1992, July 19- 24). Protection Motivation and Borrowing of Used Injection Equipment Among HIV- negative Injecting Drug Users. Paper presented at the International Conference on AIDS VIII, Amsterdam. Hawkins, W. E., Latkin, C., Mandel, W., & Oziemkowska, M. (1999). Do Actions Speak Louder Than Words? Perceived Peer Influences on Needle Sharing and Cleaning in a Sample Of Injection Drug Users. AIDS Education and Prevention, 11(2), 122-131. Heimer, R. (1998a). Can Syringe Exchange Serve as a Conduit to Substance Abuse Treatment? Journal of Substance Abuse Treatment, 15(3), 183-191. Heimer, R. (1998b). Syringe Exchange Programs: Lowering the Transmission of Syringe-Borne Diseases and Beyond. Public Health Reports, 113(Suppl1), 67-74. Heimer, R., Kaplan, E. H., Khoshnood, K., Jariwala, B., & Cadman, E. C. (1993). Needle Exchange Decreases the Prevalence of HIV-1 Proviral DNA in Returned Syringes in New Haven, Connecticut. The American Journal of Medicine, 95, 214-220. 98 Hu, L.-t., & Bentler, P. M. (1999). Cutoff Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria Versus New Alternatives. Structural Equation Modeling, 6(1), 1-55. Jamner, M. S., Corby, N. H., & Wolitski, R. J. (1996). Bleaching Injection Equipment: Influencing Factors Among IDUs Who Share. Substance Use & Misuse, 31(14), 1973-1993. Jamner, M. S., Wolitski, R. J., Corby, N. H., & Fishbein, M. (1998). Using the Theory of Planned Behavior to Predict Intention to Use Condoms among Female Sex Workers. Psychology and Health, 13, 187-205. Kang, S. Y., Deren, S., Andia, J., Colon, H. M., & Robles, R. (2004). Effects of Changes in Perceived Self-efficacy on HIV Risk Behaviors Over Time. Addictive Behaviors, 29(3), 567-574. Koester, S. (1996). The Process of Drug Injection: Applying Ethnography to the Study of HIV Risk Among IDUs. In T. Rhodes & R. Hartnoll (Eds.), AIDS, Drugs, and Prevention. Perspectives on Individual and Community Action. (pp. 133-148). London: Routledge. Koester, S., Glanz, J., & Baron, A. (2005). Drug Sharing among Heroin Networks: Implications for HIV and Hepatitis B and C Prevention. AIDS and Behavior, 9(1), 27-39. Kowalewski, M., Henson, K. D., & Longshore, D. (1997). Rethinking Perceived Risk and Health Behavior: A Critical Review of HIV Prevention Research. Health Education and Behavior, 24(3), 313-325. Ksobiech, K. (2003). A Meta-analysis of Needle Sharing, Lending, and Borrowing Behaviors of Needle Exchange Program Attenders. AIDS Education and Prevention, 15(3), 257-268. Lankenau, S. E., & Clatts, M. C. (2004). Drug Injection Practices Among High-risk Youths: The First Shot of Ketamine. Journal of Urban Health, 81(2), 232-248. Latkin, C. A. (1998). Outreach in Natural Settings: The Use of Peer Leaders for HIV Prevention Among Injecting Drug Users' Networks. Public Health Reports, 113(suppl 1), 151-159. Latkin, C. A., Forman, V., Knowlton, A., & Sherman, S. (2003). Norms, Social Networks, and HIV- related Risk Behaviors Among Urban Disadvantaged Drug Users. Social Science & Medicine, 56(3), 465-476. Latkin, C. A., Mandell, W., Knowlton, A. R., Doherty, M. C., Vlahov, D., Suh, T., et al. (1998). Gender Differences in Injection-related Behaviors Among Injection Drug Users in Baltimore, Maryland. AIDS Education and Prevention, 10(3), 257-263. Latkin, C. A., Mandell, W., Vlahov, D., Oziemkowska, M., & Celentano, D. D. (1996). The Long- term Outcome of a Personal Network-Oriented HIV Prevention Intervention for Injection Drug Users: The SAFE Study. American Journal of Community Psychology, 24(3), 341- 364. Longshore, D., Stein, J. A., & Anglin, M. D. (1997). Psychosocial Antecedents of Needle/syringe Disinfection by Drug Users: A Theory-based Prospective Analysis. AIDS Education and Prevention, 9(5), 442-459. Longshore, D., Stein, J. A., & Conner, B. T. (2004). Psychosocial Antecedents of Injection Risk Reduction: A Multivariate Analysis. AIDS Education and Prevention, 16(4), 353-366. 99 Los Angeles Homeless Services Authority. (2007). 2007 Greater Los Angeles Homeless Count. Los Angeles. Macalino, G. E., Celentano, D. D., Latkin, C., Strathdee, S. A., & Vlahov, D. (2002). Risk Behaviors by Audio Computer-Assisted Self-interviews Among HIV-seropositive and HIV- seronegative Injection Drug Users. AIDS Education and Prevention, 14(5), 367-378. MacRae, R., & Aalto, E. (2000). Gendered Power Dynamics and HIV Risk in Drug-using Sexual Relationships. AIDS Care, 12(4), 505-515. Martinez, A. N., Bluthenthal, R. N., Lorvick, J., Anderson, R., Flynn, N., & Kral, A. H. (2007). The Impact of Legalizing Syringe Exchange Programs on Arrests Among Injection Drug Users in California. Journal of Urban Health, 84(3), 423-435. Metzger, D. S., & Navaline, H. (2003). HIV Prevention Among Injection Drug Users: The Need for Integrated Models. Journal of Urban Health, 80(4, Suppl 3), iii59- iii66. Miles, M. S., & Huberman, A. M. (1994). Qualitative Data Analysis: An Expanded Sourcebook (2nd ed.). Thousand Oaks, CA: Sage. Miller, M., & Neaigus, A. (2001). Networks, Resources and Risk among Women Who Use Drugs. Social Science & Medicine, 52, 967-978. Millstein, S. G., & Halpern-Felsher, B. L. (2002). Perceptions of Risk and Vulnerability. Journal of Adolescent Health, 31(1, Supplement 1), 10-27. Montaño, D. E., Kasprzyk, D., & Taplin, S. (1997). The Theory of Reasoned Action and the Theory of Planned Behavior. In K. Glanz, F. M. Lewis & B. Rimer (Eds.), Health Behavior and Health Education: Theory, Research, and Practice (2nd ed., pp. 85-112). San Francisco: Jossey-Bass Publishers. Monterroso, E. R., Hamburger, M. E., Vlahov, D., Des Jarlais, D. C., Ouellet, L. J., Altice, F. L., et al. (2000). Prevention of HIV Infection in Street-recruited Injection Drug Users. The Collaborative Injection Drug User Study (CIDUS). Journal of Acquired Immune Deficiency Syndromes, 25(1), 63-70. Montgomery, S. B., Hyde, J., DeRosa, C. J., Rohrbach, L. A., Ennett, S., Harvey, S. M., et al. (2002). Gender Differences in HIV Risk Behaviors Among Young Injectors and their Social Networks. American Journal of Drug and Alcohol Abuse, 28(3), 453-475. Needle, R. H., Fisher, D. G., Weatherby, N., Chitwood, D., Brown, B., Cesari, H., et al. (1995). Reliability of Self-reported HIV Risk Behaviors of Drug Users. Psychology of Addictive Behaviors, 9(4), 242-250. O'Connell, J. M., Kerr, T., Li, K., Tyndall, M. W., Hogg, R. S., Montaner, J. S., et al. (2005). Requiring Help Injecting Independently Predicts Incident HIV Infection Among Injection Drug Users. Journal of Acquired Immune Deficiency Syndromes, 40(1), 83-88. Patton, M. Q. (2002). Qualitative Research & Evaluation Methods. Thousand Oaks, CA: Sage Publications, Inc. 100 Pentz, M. A., & Chou, C.-P. (1994). Measurement Invariance in Longitudinal Clinical Research Assuming Change from Development and Intervention. Journal of Consulting and Clinical Psychology, 62(3), 450-463. Racz, J., Gyarmathy, V. A., Neaigus, A., & Ujhelyi, E. (2007). Injecting Equipment Sharing and Perception of HIV and Hepatitis Risk Among Injecting Drug Users in Budapest. AIDS Care, 19(1), 59-66. Rhodes, T. (2002). The 'Risk Environment': A Framework for Understanding and Reducing Drug- related Harm. International Journal of Drug Policy, 13, 85-94. Robles, R. R., Cancel, L. I., Colon, H. M., Matos, T. D., Freeman, D. H., & Sahai, H. (1995). Prospective Effects of Perceived Risk of Developing HIV/AIDS on Risk Behaviors Among Injection Drug Users in Puerto Rico. Addiction, 90, 1105-1111. Rogers, R. W., & Prentice-Dunn. (1997). Protection Motivation Theory. In D. S. Gochman (Ed.), Handbook of Health Behavior Research I: Personal and Social Determinants. New York: Plenum Press. Santibanez, S. S., Garfein, R. S., Swartzendruber, A., Purcell, D. W., Paxton, L. A., & Greenberg, A. E. (2006). Update and Overview of Practical Epidemiologic Aspects of HIV/AIDS among Injection Drug Users in the United States. Journal of Urban Health, 83(1), 86-100. Sherman, S. G., Latkin, C. A., & Gielen, A. C. (2001). Social Factors Related to Syringe Sharing among Injecting Partners: A Focus on Gender. Substance Use & Misuse, 36(14), 2113- 2136. Shoptaw, S., & Reback, C. J. (2007). Methamphetamine Use and Infectious Disease-Related Behaviors in Men Who Have Sex With Men: Implications for Interventions. Addiction, 102(Suppl 1), 130-135. Simmons, J., & Singer, M. (2006). I Love You...and Heroin: Care and Collusion among Drug- using Couples. Substance Abuse Treatment, Prevention, and Policy, 1(7). Singer, M., Stopka, T., Siano, C., Springer, K., Barton, G., Khoshnood, K., et al. (2000). The Social Geography of AIDS and Hepatitis Risk: Qualitative Approaches for Assessing Local Differences in Sterile-Syringe Access Among Injection Drug Users. American Journal of Public Health, 90(7), 1049-1056. Smyth, B. P., Barry, J., & Keenan, E. (2001). Syringe Borrowing Persists in Dublin Despite Harm Reduction Interventions. Addiction, 96(5), 717-727. Smyth, B. P., & Roche, A. (2007). Recipient Syringe Sharing and its Relationship to Social Proximity, Perception of Risk and Preparedness to Share. Addictive Behaviors, 32(9), 1943-1948. Sorensen, J. L., & Copeland, A. L. (2000). Drug Abuse Treatment as an HIV Prevention Strategy: A Review. Drug & Alcohol Dependence, 59, 17-31. Sorensen, J. L., London, J., Heitzmann, C., Gibson, D. R., Morales, E. S., Dumontet, R., et al. (1994). Psychoeducational Group Approach: HIV Risk Reduction in Drug Users. AIDS Education and Prevention, 6(2), 95-112. 101 Stein, M. D., Dubyak, P., Herman, D., & Anderson, B. J. (2007). Perceived Barriers to Safe- Injection Practices Among Drug Injectors Who Remain HCV-Negative. The American Journal of Drug and Alcohol Abuse, 33, 517-525. Stevens, S. J., Kotranski, L., Williams, M., Bowen, A. E., & McCoy, H. V. (1998). Theoretical Models Used to Guide NIDA's Cooperative Agreement Research and Intervention Efforts. Journal of Psychoactive Drugs, 30(3), 231-238. Stimson, G. V. (1995). AIDS and Injecting Drug Use in the United Kingdom, 1987-1993: The Policy Response and the Prevention of the Epidemic. Social Science and Medicine, 41(5), 699-716. Strauss, A., & Corbin, J. (Eds.). (1997). Grounded Theory in Practice. Thousand Oaks, CA: Sage. Strecher, V. J., & Rosenstock, I. M. (1997). The Health Belief Model. In K. Glanz, F. M. Lewis & B. K. Timer (Eds.), Health Behavior and Health Education: Theory, Research, and Practice (2nd ed., pp. 41-59). San Francisco, California: Jossey-Bass Publishers. Thiede, H., Hagan, H., Campbell, J. V., Strathdee, S. A., Bailey, S. L., Hudson, S. M., et al. (2007). Prevalence and Correlates of Indirect Sharing Practices Among Young Adult Injection Drug Users in Five U.S. Cities. Drug & Alcohol Dependence, 91(Suppl), S39-47. Tortu, S., McMahon, J. M., Hamid, R., & Neaigus, A. (2003). Women's Drug Injection Practices in East Harlem: An Event Analysis in a High-Risk Community. AIDS and Behavior, 7(3), 317-328. Wallston, B. S., & Wallston, K. A. (1984). Social Psychological Models of Health Behavior: An Examination and Integration. In S. Baum, J. Taylor & E. Singer (Eds.), Handbook of Psychology and Health, Volume IV: Social Aspects of Psychology (Vol. IV). Hillsdale, NJ: Lawrence Erlbaum. Wodak, A., & Cooney, A. (2006). Do Needle Syringe Programs Reduce HIV Infection Among Injecting Drug Users: A Comprehensive Review of the International Evidence. Substance Use & Misuse, 41(6-7), 777-813.

Abstract (if available)

Abstract Background: Injection drug users (IDUs) are at risk for HIV and other bloodborne pathogens. Though reductions in injection risk behavior have been observed, residual risk behavior persists. Female IDUs are at elevated risk compared to their male counterparts, and this elevated risk appears to be grounded in the social and environmental context. The perceived consequences of refusing to share injection equipment have yet to be investigated as a factor that may help explain persistent injection risk behavior.

Linked assets

University of Southern California Dissertations and Theses

Conceptually similar

PDF

The vicious cycle of inactivity, obesity, and metabolic health consequences in at-risk pediatric populations

PDF

Opioid withdrawal symptoms, opioid use, and injection risk behaviors among people who inject drugs (PWID)

PDF

The role of depression symptoms on social information processing and tobacco use among adolescents

PDF

Mixed methods investigation of user engagement with a smoking cessation app

PDF

Addressing federal pain research priorities: drug policy, pain mechanisms, and integrative treatment

PDF

The role of social support in the relationship between adverse childhood experiences and addictive behaviors across adolescence and young adulthood

Asset Metadata

Creator Wagner, Karla Dawn (author)

Core Title Competing risks: the role of the perceived consequences of refusing to share injection equipment among injection drug users

School Keck School of Medicine

Degree Doctor of Philosophy

Degree Program Preventive Medicine (Health Behavior)

Publication Date 10/07/2009

Defense Date 09/11/2009

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag cognitive behavioral theory,hepatitis c virus,HIV,injection drug use,mixed-methods,OAI-PMH Harvest,qualitative methods,structural equation modeling

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Richardson, Jean L. (committee chair), Unger, Jennifer B. (committee chair), Chou, Chih-Ping (committee member), Lankenau, Stephen E. (committee member), Palinkas, Lawrence A. (committee member)

Creator Email karlawagner@mac.com,kdwagner@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m2652

Unique identifier UC1464404

Identifier etd-Wagner-3296 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-267158 (legacy record id),usctheses-m2652 (legacy record id)

Legacy Identifier etd-Wagner-3296.pdf

Dmrecord 267158

Document Type Dissertation

Rights Wagner, Karla Dawn

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Repository Name Libraries, University of Southern California

Repository Location Los Angeles, California

Repository Email cisadmin@lib.usc.edu