syringe disinfection

Drug and Alcohol Dependence42 ( 1996) 183..196

Ethnic differences in the psychosocial antecedents of needle/syringe disinfection Douglas Longshore”-b,*, Judith A. Stein’, M. Douglas Anglin” “UCLA

Drug ‘I’C‘LA

Abuse Research Center, 1100 Glendon Ave. # 763, Lo.v Angeles. CA 90024. 15.4 ‘RAND Corporation, Santa Monica CMfornia, USA Department of’ Psychology, 405 Hilgard Are.. Los Ang~ks, C.4 90024. LJSA Received

12

March 1996:accepted IS July

1996

Abstract This study examined psychosocial antecedents of needle/syringe disinfection by 209 injection drug users in three ethnic groups. Among Whites, high perceived self-efficacy for risk reduction had a positive effect on subsequent disinfection attempts. Among African Americans and Mexican Americans, peer norms favorable to risk reduction had a positive effect on subsequent disinfection attempts, while self-efficacy had no effect. These results suggest that risk-reduction capabilities may be rooted in individualistic perceptions of the self among White drug users, while ‘collective self perceptions are more relevant to these capabilities among African American and Mexican American drug users. HIV risk intervention may have more impact in specific ethnic groups if these distinctions are taken into account. Results also demonstrate the importance of comparing models of behavior change across ethnic groups. Ke,vwords: Injection drug use; HIV risk reduction; Ethnicity

and to identify leverage points for behavior change, i.e. factors that explain a substantial portion of the variance in risk behavior and are amenable to intervention (DiClemente and Peterson, 1994; Fishbein et al., 1991, unpublished). Psychosocial factors such as perceived infection risk and self-efficacy for changing one’s behavior may serve as leverage points for intervention. However, findings from prior research on the relationship between such factors and IDU risk behavior are inconsistent and, for the most part. have not been based on prospeetive multivariate designs. In addition, while some research suggests possible ethnic differences in the antecedents of behavioral risk reduetion, no study has directly compared any model of IDU behavior change across ethnic groups. For these reasons the causal relevance of psychosocial factors in IDU risk behavior remains unclear, and psychosocial leverage points for intervention among IDIJs have yet to be identified.

1. Introduction injection drug users (IDUs) have responded to the threat of AIDS by reducing their behavioral risks to some degree (Colon et al., 1992; Longshore et al., 1993b; McCusker et al., 1992; Vlahov et al., 1991). However, the prevalence of needle/syringe sharing is still alarmingly high, and, although many IDUs now say they disinfect their needles/syringes on an occasional basis, few report doing so consistently. In addition, interventions tested in experimental designs have not produced sizable and lasting reductions in IDU risk behavior (Longshore, 1992; Magura et al., 1991; Mandell et al., 1994; McCusker et al., 1993; Roehrich et al., 1994). Hence there is an urgent need to improve the design of AIDS preventive interventions for drug users

* (Corresponding author 0376.8716,‘96/$15.00 PI/

s03~6-8716(96)01280-x

C3 1996 Elsevier

Science

Ireland

Ltd.

All rights

resel-ved

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In this study, we used the AIDS risk reduction model or ARRM (Catania et al., 1990) as a framework for examining psychosocial antecedents of needle/syringe disinfection among 209 HIV-negative IDUs, of whom 64 were African American, 66 Mexican American, and 79 White. Results were used to identify possible leverage points for HIV preventive intervention among IDUs in each ethnic group. The AIDS risk reduction model (Catania et al., 1990) is a synthesis of perceptual and attitudinal factors in the theory of reasoned action (Ajzen and Fishbein, 1980), social cognitive theory (Bandura, 1986, 1989, 1994) the health belief model (Rosenstock, 1990), and other sources. The ARRM views behavior change as a three-stage process. A person engaging in risk behavior may or may not perceive that it represents a possible source of HIV infection. Having arrived at that perception, the person may then form an intention to change. Finally, the person may act on this intention. Moving through this three-stage process is said to depend on psychosocial factors including AIDS knowledge, perceived response efficacy, perceived selfefficacy, aversive emotions, social factors, and cues to action. AIDS knowledge regarding virus transmission routes, symptoms, etc. may influence a person’s risk perceptions or other psychosocial factors proximal to behavior. For this reason, AIDS knowledge was included in the ARRM even though AIDS knowledge has not shown consistent or strong direct effects on risk behavior. The two efficacy factors are a person’s estimate of the degree to which changing behavior actually reduces the risk of infection (perceived response efficacy) and one’s estimated ability to perform the risk-reducing behavior (perceived selfefficacy). Aversive emotions include fear of AIDS or of people with AIDS as well as anxiety regarding possible HIV infection. Social factors include norms regarding risk behavior and social network characteristics that may affect access to health information. Finally, external cues to action are experiences or perceptions that trigger behavior change either directly or indirectly. Two such cues are, for example, programmatic HIV education and personal knowledge of someone with AIDS. It is important to test predictors of behavior change in theory-based, multivariate models rather than as stand-alone constructs (Hospers and Kok, 1995). If predictors are tested in such models, the relationship between any single predictor and behavior change is less liable to misspecification, and overall implications for theory and practice should be more clear. To date, there has been no published attempt to test the ARRM among IDUs (Fisher et al., 1994), and the evidence regarding single factors is mixed.

For example, the ARRM and other theories suggest that AIDS-related behavior change is more likely among people who believe they incur a greater degree of infection risk by continuing to engage in the behavior. However, cross-sectional studies have found no consistent relationship between perceived risk and various indicators of ‘safer’ injection (e.g. Booth, 1994; Falck et al., 1995; Huang et al., 1989; Magura et al., 1989; Sibthorpe et al., 1991). The picture is no more clear in prospective studies. While Camacho et al. (1995) found that higher perceived risk at baseline predicted safer drug injection at a 6-month follow-up, Robles et al. (1995) found that IDUs who reported being at higher risk at baseline subsequently engaged in riskier injection practices, while Magura et al. (1991) found no relationship between perceived risk at baseline and change in injection risk behavior across a 2-month follow-up period. Prior research is more consistent regarding another ARRM predictor, perceived self-efficacy for behavior change. This predictor was correlated positively with safer injection practices in cross-sectional studies by Falck et al. (1995) Gibson et al. (1993), and Kok et al. (1991), though it was unrelated to injection practices in a similar study by Huang et al. (1989). A prospective study by Longshore et al. (in press) found that perceived self-efficacy predicted subsequent reductions in HIV risk behavior among IDUs. Bandura (1994) and Fisher and Fisher (1992) have cited selfefficacy as an essential factor in HIV risk reduction among IDUs and other at-risk populations. Evidence is particularly sparse on the question of ethnic differences in the psychosocial antecedents of behavior change. Perceived self-efficacy and related factors (e.g. internal locus of control) appear generally lower among African Americans and Latinos than among Whites (Gecas, 1989) but there are exceptions to this pattern (see Long et al., 1994; Osmond et al., 1993; Schilling et al., 1991). On the other hand, group means on any psychosocial characteristic may be less relevant to the question at hand than the strength of the association between that characteristic and behavior change. No study of IDUs has provided a direct comparison across ethnic groups in the relative strength of psychosocial factors as predictors of behavior change. There are, however, hints of important ethnic differences in studies of other populations. Among incarcerated men studied by Thompson et al. (1996) perceived control was inversely related to distress among Whites but bore no relationship to distress among African Americans. This suggests that perceived control, or self-efficacy, may be less salient in African Americans’ cognitions about the self. On the other hand, social support, social norms, and collective self-esteem may have more effect on behavior among African Americans

D. Longshore et al. / Drug and Alcohol Dependence 32 (1996) 183 194

Table 1 Background characteristics of each ethnic group African Americans Gender (‘% women) Age (mean)* Years of formal education (mean)* Employed (‘% yes) Annual income (dollars) Age of first heroin/cocaine use (mean) Drug treatment in past 2 years (% yes) Currently in drug treatment (“A;,yes)

48.1 41.4 12.3 21.9 20047 21.0 65.4 30.8

Mexican Americans

Whites

58.9 37.9 10.9 26.6 20345 18.9 70.5 44.2

51.6 36.4 12.0 37 I 21347 19.8 69.2 37.7

* Significant difference between any two groups, PI .05.

and/or Latinos than among Whites (Cracker et al., 1994; Horvkz and Reinhard, 1995; Nyamathi and Shin, 1990: Nyamathi et al., 1995). Citing the dearth of comparative evidence in health behavior research, White-Means (1995) has called for more careful attention to the relevance of ethnicity. In particular, she suggested that ethnicity be treated as a blocking variable--not merely a covariate, as is common practice-so that the predictive value of models and individual factors can be directly compared across groups. We followed this suggestion in the analyses reported below. 2. Method 2.1. Sample

In 1986 and 1987, the Los Angeles County Department of Health Services conducted three surveys of HIV serostatus and risk behavior among injectiondrug users entering all publicly funded residential or methadone clinics in the county. The combined sample totaled 1506 cases. In 1989, we blocked this sample by ethnicity and gender and then randomly selected 465 cases for an additional study designed to monitor HIV seroconversion and risk behavior over three annual waves of data collection. This sample appears to be representative of the population of injection drug users enrolled in publicly funded drug treatment in the county during 1986-1987 (Longshore, 1989, unpublished memo dated July 10). Findings on seroconversion have been reported in Longshore and Anglin (1992, 1994, 1996). By late 1992 we had completed the first and second waves of interviews with 379 (82%) of these 465 cases. Sources of attrition were death (n = 38 or 8%), refusal to participate (n = 13 or 3%), and inability to recontact (n = 35 or 8%). Our completion rate among living cases is 89% (379/427). IDUs who completed the interview were paid $25. A total of 209 IDUs were HIV-negative and reported injecting heroin or

cocaine in the 12-month periods preceding both interviews. These IDUs included 111 women (53%) and 98 men (47%). The ethnic breakdown was 31”io African American, 32% Mexican American, and 38% White (non Mexican American). (Because random sampling was stratified, representation of each ethnic group was roughly equal.) These three groups were similar on most though not all of the background characteristics we measured. As shown in Table 1, no differences emerged in the gender breakdown, percent employed, annual income, or age of first use of heroin or cocaine. In view of other research documenting lower rates of risk behavior among users in treatment (e.g. Longshore et al., 1993a. 1994) it is important to note that the three ethnic groups were also similar in recent treatment history and current treatment status. African Americans in the sample were older than Mexican Americans and Whites, and Mexican Americans reported fewer years of formal education than the other two groups. While statistically significant, these differences were, in our view, not substantial. 2.2. Variables

Interview questions intended to capture the psychosocial constructs of interest were factor analyzed with the BMDP 4M program using maximum likelihood estimation and direct quartimin rotation. Items that formed reliable and distinct factors corresponding to the intended constructs were retained as factor indicators in subsequent latent variable analyses. Where ap propriate, items were scored in reverse. Unless otherwise noted, we used Likert-type items with four response values, ranging from strongly agree (1) to strongly disagree (4). AIDS knowledge was measured as the sum of correct answers to ten items, including, for example, ‘AIDS affects only gay men’ and ‘AIDS cannot be spread by sharing food’ (reverse scored). The construct was indicated by three subfactors: sex-related risks, drug-related risks, and general knowledge.

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Four items served as indicators of the perceived infection risk construct. These included, for example, ‘I never do anything that could give me AIDS’ and ‘I’ve already done things that could have exposed me to AIDS’ (reverse scored). Higher scores indicate higher perceived risk. Response efficacy was composed of three attitudinal items reflecting beliefs about injection risk behaviors. Items included, for example, ‘cleaning works with bleach doesn’t really affect a person’s chance of getting AIDS’ and ‘people who do not share their works with anyone are at lower risk of getting AIDS’ (reverse scored). Higher scores indicate higher perceived response efficacy. Self-efficacy was indicated by three items reflecting IDUs’ perceived ability to reduce their injection risk behavior. For example, one item was ‘it is no trouble for me to clean my works’ (reverse scored). Higher scores indicate higher perceived self-efficacy. Peer norms were assessedwith eight items regarding behavioral risk-reduction norms among ‘the drug users I know’. For example, one item was worded as follows: ‘the drug users I know do not like to shoot up without first cleaning their works’ (reverse scored). (‘works’ refers to needles and syringes.) Items formed three subfactors including peer norms about drug risk behavior, peer norms about sex risk behavior, and peer norms about general AIDS concerns. Higher scores indicate stronger risk-reduction norms. Intention to disinfect was indicated by one item, ‘if I use drugs over the next year, I will not always disinfect the works before using them’. Scoring was reversed so that higher scores indicate a stronger intention to always disinfect one’s needles/syringes. 2.2.1. Frequency of disinfection attempts We measured this construct with indicators of attempts to disinfect needles/syringes during the two lyear recall periods, the year before the first interview and the year before the second. Although all cases had injected drugs during both years, the frequency of injection varied across years as well as cases. We accounted for this variation by adjusting each indicator by the frequency of drug injection during each recall period. One indicator was the number of agents used as disinfectants. In yes/no items we asked whether IDUs had rinsed or soaked their needles/syringes with either bleach or alcohol or had boiled them in water. The second indicator, scored from 0 to 4, was the reported frequency of using each agent: never, sometimes, half the time, usually, or always. 2.3. Analyses In the EQS structural equations modeling program (Bentler, 199.5),covariance structure analyses are used

to compare a hypothesized model with a set of actual data. The closeness of the model to the data is evaluated statistically through goodness-of-fit indexes, one of which is the chi-square/degrees of freedom ratio. A chi-square value no more than twice the degrees of freedom in the model generally indicates a plausible, well-fitting model inasmuch as large sample sizes make it difficult to obtain non-significant chi-squares. In addition, the comparative fit index (CFI), which ranges from 0 to 1, indicates the improvement in fit of the hypothesized model compared with a model of complete independence among the measured variables (Bentler, 1990, 1995). Values of 0.9 and higher are desirable and indicate that 90% or more of the covariation in the data is reproduced by the hypothesized model (Bentler and Stein, 1992). 2.3.1. Confirmatory factor analyses In model development, we first performed individual confirmatory factor analyses for each ethnic group. These analyses tested the adequacy of the proposed measurement model (factor structure) and proposed relationships among the latent constructs for each group. Each hypothesized latent construct predicted its proposed manifest indicators, and all latent constructs were allowed to intercorrelate without any imputation of causality among them. 2.3.2. Multiple group comparisons Subsequently, we performed multiple group analyses in which various parameters of the models were constrained to equality between groups. An initial model with no constraints established a baseline for further comparisons. Next, the factor structures of the three groups were constrained to be equal. Following that test, correlations (covariances) between the constructs were posited as equal. Finally, the variances were set as equal. The tenability of each more stringent set of constraints was assessed with chisquare difference tests. The LaGrange Multiplier test (Chou and Bentler, 1990) indicated which constraints were not tenable and should be dropped from the model. We also contrasted the latent means in a procedure analogous to a z-test by successively pairing the three groups (White vs. African American, White vs. Mexican American, and African American vs. Mexican American). We could not directly compare all three groups simultaneously when assessingdifferences in the latent means as could be done in a traditional ANOVA procedure. 2.3.3. Path models Finally we tested separate predictive path models for each ethnic group. Perceived infection risk, peer norms, and AIDS knowledge predicted the interven-

1x7

D. Longshore et al. / Drug and Alcohol Dependence 42 (1996) 183- 196

Table 2 Confirmatory factor analysis of model components -____ Factors

Factors loadings* African American

Mexican American

White

Perceived infection risk Exposed to AIDS (R) Never expose to AIDS Not worried about AIDS Not the type to get AIDS

0.66 0.56 0.32 0.55

0.76 0.76 0.55 0.6X

0.63 0.68

Peer norms Safer drug behaviors Safer sex behaviors General AIDS concern

0.69 0.55 0.69

0.45 0.94 0.52

0.48 (f.53 II 80

AIDS knowledge Sex-related Drug-related General knowledge

0.93 0.74 0.63

0.74 0.73 0.75

0.71 0.67 0.65

Response efficacy Cleaning works no help Lower risk if no sharing (R) Cleaning not worth effort

0.64 0.53 0.77

0.52 0.54 0.54

0.50 0.3x 0.80

Self efficacy Prefer ‘dope sick’ to sharing (R) No trouble for me to clean (R) I’ll share works if someone says they are clean

0.63 0.50 0.88

0.67 0.3 I 0.92

IV.

Intention to disinfect

1.OO”

1.00"

i .Ooi’

VII

Disinfection attempts at baseline Bleach/boil percentage Cleaning frequency

0.96 0.92

1.00

0.77

0.96 I .04

Disinfection attempts at follow-up Bleach/boil percentage Cleaning frequency

0.91 I .oo

0.94 1.oo

0.92 1.oo

I.

II

III.

IV.

V.

VIII.

0.5(1 0.62

(R 1. reverse scored. * All loadings significant, P
ing variables, response efficacy and self-efficacy. Disinfection attempts at baseline was included as a control variable for prior behavior. These six constructs in turn predicted intentions to disinfect, and all preceding constructs predicted the outcome measure, Disinfection attempts at follow-up. Predictor constructs were allowed to intercorrelate freely among themselves as were the residual error variances of the intervening constructs. Covariances and predictive paths among the constructs were dropped from the path model if they were not significant. The significance of possible indirect effects of the predictor constructs was also examined.

3. Results 3.1. Conjirmatory jbctor analyses

Table 2 presents the factor loadings for the hypothesized latent variables for each group. All manifest variables loaded significantly (P < 0.001) on their hypothesized latent factors. For Whites, the comparative fit index (CFI) = 0.98; x2 (162, n = 79) = 176.76. For African Americans, the CFI =0.88; xZ (161, ra= 64) = 228.28. For Mexican Americans, the CFI = 0.88; x2 (161, IZ= 66) = 232.39. All three CFIs were acceptable. However, to improve the fit of the initial models

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Table 3 Multiple group analyses among African American, Mexican American, and White injection drug users Model 1. 2. 3. 4. 5.

x2 No constraints (baseline model) Constrained measurement model Constrained measurement model and covariances among factors Constrained measurement model, covariances, and variances Absolute null model

637.44 661.20 124.11

792.96 2369.90

df

CFI”

x2 difference from Model 1

484 510 566 582 630

0.91 0.91 0.91 0.88 NAb

NAb 23.76126df 86.67182df 155.52/98* df NAb

* P10.001. “CFI, comparative fit index. bNA, not applicable.

for African Americans and Mexican Americans, one supplementary correlated error residual suggested by the Lagrange Multiplier (LM) test (Chou and Bentler, 1990) was added for each group. A covariance between the error residuals of the measured variables ‘exposed to AIDS’ (reverse scored) and ‘drug related AIDS knowledge’ was added for Mexican Americans (Y= 0.62), and a covariance between ‘not the type to get AIDS’ and ‘lower risk if no sharing’ was added for African Americans (r = 0.55). 3.2. Multiple

group comparisons

Results of the sequential multiple group analyses are summarized in Table 3, which reports chi-square values and associated degrees of freedom for the successive models. Chi-square differences from the baseline are also reported. A baseline multiple group model with no equality constraints imposed on it served as a comparison for further models (Model 1 of Table 3, x2 (484, IZ= 209) = 637.44; CFI = 0.91). Values for an absolute null model are also reported (Model 5). We used Whites as the reference group in each model. Thus, we set up equality constraints in which various parameters of White IDUs were equated with those of the African American IDUs and those of the Mexican American IDUs. This methodology does not allow a direct comparison among all three groups simultaneously because the equality relationships are commutative. However, fit statistics would be exactly the same if either the African American or Mexican American IDUs were used as the reference group instead of the Whites. 3.2.1. Factor structure

The factor structure is the relationship between the latent and measured variables. A multiple group comparison in which the factor structures were constrained to equality across the three groups (Model 2) suggested that the factor structures for the groups were similar (CFI = 0.91). There was no significant

decrement in fit from unrestricted Model 1. The chisquare difference between Model 2 with equality constraints on the factor structure and unrestricted Model 1 was 23.76, 26 df, which is nonsignificant. Thus we did not find any ethnic difference in the relationships among measured variables and how they related to their associated latent variables. 3.2.2. Correlations between factors

This more restrictive analysis tested whether there were significant differences among the correlations between factors after the factor structures were constrained to equality between groups. In Model 3 the matrix of factor covariances was constrained to equality. The chi-square difference between Models 2 and 3 was 63.61, 56 dJ The chi-square difference between Models 1 and 3 was 86.67, 96 d$ Neither difference was statistically significant. However, as reported below, some individual covariances were significantly different from each other, as indicated by the LM test, and were dropped after the full model with restricted variances was tested (Model 4). 3.2.3. Factor variances

When factor variances were constrained as equal across the groups (Model 4), the model showed a significant decrement in fit. The chi-square difference between Models 3 and 4 was 68.85, 16 dJ The chisquare difference between Models 1 and 4 was 155.52, 98 dJ The CFI dropped to 0.88 for Model 4. Several equivalence constraints on variances and covariances in this model were reported as untenable in the LM test and were dropped from the model. Individual constraints were dropped sequentially to assess the degree of model improvement after each modification. The sequence was determined by successive results of the LM test regarding both univariate and multivariate improvement in chi-square when individual parameters of the model were dropped from the analysis. A chi-square difference value of 3.84 was the criterion for significance (1 df, 0.05 level).

D. Longshore et al. / Drug and Alcohol Dependem? 42 (1996) 183 196

184

Table 4 Results of successiveremoval of equality constraints from Model 4 ____________ -.. .- ~.~. ----. ___--A L’ Constraint deleted ___~ --48.78 I. Variance of needle/syringe disinfection at baseline for Whites and Mexican Americans (larger for Mexican Americansi 12.70 2. Variance of needle/syringe disinfection at follow-up for Whites and African Americans (larger for African Americans) 10.62 3. Covariance of needle/syringe disinfection at baseline and needleipyringe disinfection at follow-up for Whites and Mexican Americans (larger for Mexican Americans) 4. Covariance of peer norms and needle/syringe disinfection at baseline for Whites and Mexican Americans (larger for Whites) 6.28 4.29 5. Covariance (negative) of peer norms and perceived infection risk for Whites and African Americans (larger for Whites) Note: all r’ differences based on I df: A 1’23.84; P~0.05: A ~‘~6.63; P~0.01: A ~‘2 10.83; P
32.4. Dropping constraints

As reported in Table 4, five relationships among the latent variables were significantly different in the fully constrained model. The largest improvement in chi-square resulted from dropping the equivalence constraint between the variances of needle disinfection at Baseline for the White and Mexican American IDUs (there was a significantly larger variance for the Mexican Americans). Additional improvement in chisquare resulted from removing constraints on the variances of needle disinfection at follow-up for Whites and African Americans (the variance for African Americans was larger). Fit improved further when we dropped equality of constraints on the covariance between needle disinfection at baseline and needle disinfection at follow-up for Whites and Mexican Americans (it was larger for Mexican Americans); the covariance of peer norms and needle disinfection at baseline for Whites and Mexican Americans (larger for Whites); and the covariance of peer norms and perceived AIDS risk for Whites and African Americans (larger for Whites). 3.2.5. Latent means models

In contrasting the latent means for each two-group comparison, we found that peer norms were significantly lower for Mexican American than for African American IDUs (z = 2.17, P < 0.05); peer norms were significantly lower for Mexican American than for White IDUs (z = 2.89, P < 0.01); AIDS knowledge was significantly lower for Mexican American than for White IDUs (s = 2.27, P < 0.05); and AIDS knowledge was significantly lower for African American than for White IDUs (z = 2.33, P < 0.05) All of these significance levels are based on two-tailed tests.

are good: White 2’ (176, n = 79) = 182.56, CFI = 0.99; African American x3 (182, n = 64) = 236.96, CFI = 0.90; Mexican American 1’ (181, n = 66) = 252.38, CFI = 0.88. For all groups, intentions to disinfect did not significantly predict more needle disinfection at follow-up. For White IDUs, needle disinfection at follow-up was significantly predicted by disinfection at baseline and by greater self-efficacy. For both African American and Mexican American IDUs, disinfection at follow-up was directly predicted by peer norms. Also, for Mexican Americans, disinfection at baseline predicted more disinfection at follow-up. Indirect effects mediated through the significant direct predictors were examined for significance as well. For White IDUs, we found sign&ant indirect effects on intentions to disinfect by greater peer norms (P c 0.01) and greater AIDS knowledge (P < 0.05), both of which were mediated through the significant infhtence of self-efficacy. For African American IDUs, there were significant indirect effects on intentions to disinfect by greater peer norms (P < 0X11), greater AIDS knowledge (P < O.Ol), and lower perceived AIDS risk (P < O.Ol), which were also mediated through s&efficacy. No indirect effects were found in the final model for Mexican Americans. Inasmuch as intentions had no direct effect on disinfection attempts at follow-up, neither peer norms nor AIDS knowledge nor perceived AIDS risk appeared to play any significant role as determinants of behavior change in any of the three groups. Correlation matrices on which these models were based appear in the Appendix A.

4. Discussion 3.3. Path models

The final path models for the three ethnic groups appear in Figs. l-3. Only significant paths and covariances are included. The fit indexes of these model

Although IDUs’ intentions to always disinfect their needles/syringes did not predict subsequent disinfection attempts in any ethnic group, it is possible that our measure of intentions failed to capture enough of

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\ Altempts at

Fig. 1. Path model for white injection drug users. Notes: regression coefficients and covariances are standardized. Residual variances are in circles. a P 5 0.05; b P so.01; c P $0.001.

the variance in actual intentions. This could be because it was based on a single item or because it focused too restrictively on intentions to always disinfect. It is also possible that self-reported intentions partly reflect the social desirability of intended risk reduction as well as one’s true intentions. However, baseline attempts to disinfect did predict future intentions, as measured here, among Whites and Mexican Americans. Moreover, we detected direct or indirect relationships between intentions and self-efficacy, peer norms, perceived risk, and AIDS knowledge among Whites and/or African Americans. These findings, especially the correlation between past behavior and future intention, are not consistent with the argument that our measure of intentions was too weak or too heavily influenced by social desirability to play in the model. Another possibility is that IDUs’ stated intentions reflected behavioral goals more than actual expectations (Ajzen, 1991). That is, even if self-reported intentions were not influenced by social desirability, IDUs may have interpreted the question to refer to goals, not actual plans. We return to these issues below. In the theory of planned behavior, the predictive value of perceived control, or perceived self-efficacy, depends on how accurately it reflects one’s actual control over the behavior in question (Ajzen, 1987; Ajzen and Madden, 1986). Perceived self-efficacy

emerged as a significant antecedent of needle/syringe disinfection only among the White IDUs in our sample. Thus, the efficacy perceptions of Whites may have reflected their actual degree of control more accurately than the perceptions of African Americans and Mexican Americans. Whites may have had more reliable access to bleach or sterile needles, for example, or may have injected with other users whose own commitment to needle/syringe disinfection was more reliable. Under such circumstances, the perceived selfefficacy of Whites might have been more congruent with their actual control on subsequent occasions of drug use. It is important to note here that levels of perceived self-efficacy for risk reduction did not vary by ethnicity. This was true even though we found (small) ethnic differences in formal education, a variable associated with self-efficacy in other domains (Gecas, 1989). Thus, while efficacy perceptions may have been distributed similarly in each group, their stability and congruence with actual control may differ. On the other hand, peer norms regarding risk reduction predicted needle/syringe disinfection among African American and Mexican American IDUs but not among White IDUs. Thus, apart from possible ethnic differences in actual control over needle/syringe disinfection, self-efficacy perceptions may simply be less salient or influential among African American

D. Longshore

et ul. i Drug

and Alcohol

Dependence

42 (1996)

183 .. 196

rcIIt.=I”ci”

lnfeclion Risk

Fig. 2. Path model for African American injection drug users. Notes: regression coefficients and covariances are standardized. Residual variances are in circles. ” P 5 0.05; b P 5 0.01: CP < 0.001.

and Mexican American IDUs, and peer norms more so. Notably, the influence of peer norms was not mediated by behavioral intentions or personal efficacy perceptions. These findings are consistent with research citing a stronger direct link between group norms and behavior among non-Whites than among Whites (Foster et al., 1993; Mays and Cochran, 1988; Randolph and Banks, 1993). It is also consistent with cross-cultural research suggesting that, among African and Mexican Americans as well as other non-Whites, ‘self perceptions are collective or sociocentric as well as egocentric (Cracker et al., 1994; Foster et al., 1993; Luhtanen and Cracker, 1992) and behavior is governed more by a sense of responsibility and connectedness to one’s ethnic group (Butler, 1992; Kim et al., 1994; Marin and Marin, 1991). To illustrate this distinction, a traditional Western view of self (‘I think therefore I am’) can be juxtaposed with a traditional African view (‘I am because we are’) (Mbiti, 1972). It would be a mistake to overgeneralize from such broad cultural differences, and we do not read these findings to mean that peer norms have no bearing on behavior change among Whites or that personal efficacy perceptions do not matter among African Americans and Mexican Americans. Rather, we read the findings from a cross-cultural perspective in which ethnic groups may place greater or lesser emphasis on two distinctive views of self, individualistic and collective. Implications of these findings are cited below.

5. Iqkations This study supported the applicability of the AIDS risk reduction model as a heuristic for organizing research on AIDS-related behavior change among injection drug users. First, we used the model as a framework for testing psychosocial factors as potential leverage points for behavior change in a prospective multivariate design. Results su sted that perceived self-efficacy and peer norms for risk reduction may be crucial psychosocial pathways to injection-related behavior change. Second, this study provided a direct comparison of the relative strength of psychosocial factors as predictors of behavior chme across ethnic groups, and, although ethnic subsample sizes were small, we were able to detect potentially important differences. Self-efficacy was the sole pathway to behavior change for White IDUs, and peer norms was the sole pathway for African American and Mexican American IDUs. These differences ihustrate the insights to be gained by treating ethnicity as a blocking variable, not merely a covariate, in tests of health behavior models (White-Means, 1995). Third, other studies have discounted AIDS knowledge as a factor in behavior change (Fisher and Fisher, 1993). However, while AIDS knowledge was not directly related to behavior change in our study, it was strongly related to perceived self-efficacy, which was in turn the final pathway to behavior change among White IDUs. Thus, AIDS knowledge, and perhaps other factors as well, may

192

D. Longshore et al. 1 Drug and Alcohol Dependence 42 (1996) 183-196

F-e .94

Intantinn

,

&

at I

Fig. 3. Path model for Mexican American iniection drug users. Notes: regression coefficients and covariances are standardized. Residual variances are in circles. a P 5 0.05; b P 5 0.01; c PI 01001,

emerge as important antecedents if tested in models that view behavior change as a process occurring in definable steps, not merely as an end-point. The ethnic subsamples available to us were similar on most background characteristics, most notably on the crucial characteristics of recent treatment history and current treatment status. They also appeared similar to the population of IDUs in each ethnic group enrolled in publicly funded residential and methadone treatment in Los Angeles County. However, Whites were slightly younger on average, and we were unable to determine whether each subsample was representative of IDUs regardless of treatment experience or how pathways to treatment compare across ethnic groups. In addition, the subsamples were not very large. For these reasons we believe the findings are best regarded as illustrative of the general value of the multivariate, model-driven approach and the possible importance of ethnic variations in leverage points for HIV risk reduction. Findings will become more definitive if derived from larger samples, consistent across studies, and based on research in which the personal and social backgrounds of drug users in each ethnic group can be specified more fully. Perceived risk has shown a direct association with IDUs’ behavior change in some studies and an inverse association, or no association at all, in others. Making sense of this prior research has been difficult because of the variability in research design, cross-sectional or prospective, and because the relevance of

perceived risk was not tested in multivariate designs. In our study, perceived risk did not predict subsequent behavior change among IDUs in any ethnic group when tested along with other factors comprising the AIDS risk reduction model. It is tempting to conclude that perceived risk has no important role in AIDS-related behavior change. However, perceived risk was correlated, inversely, with self-efficacy among the African American and Mexican American IDUs in our sample. While self-efficacy did not predict behavior change for those IDUs, efficacy perceptions may bear upon IDUs’ injection-related HIV risk behavior in ways not captured by our analysis, and perceived risk may influence HIV risk behavior in other domains. Further research, again in a prospective multivariate framework, is needed. Intention is, in theory, most likely to predict behavior when the expression of an intention is followed closely by an opportunity to engage in the behavior and when measures of intention and behavior are both quite specific as to the act and the situation (Ajzen, 1987; Bagozzi, 1981; Terry, 1993). Thus, the path from intention to behavior might have emerged in our data if the lag between measures had been shorter, days or weeks rather than a full year. Also, we asked about intention to disinfect needles/syringes without regard to the identity of sharing partners or other aspects of the drug-use situation. Intention might have predicted behavior if we had described specific scenarios (e.g. disinfecting needles/syringes af-

D. Longshorr et al. / Drug and Alcohol Dependence 42 (1996) 181 ~1%

ter they are used by someone whom the IDU does not know) and measured the IDUs intention and behavior in each scenario. In view of these aspects of our study design, the implications for theories of behavioral intention are limited. Future studies are needed in which measures of intention are more reliable multi-item indexes, intentions are measured in regard to specific drug-use scenarios, and behavioral goals are clearly distinguished from behavioral expectations (Ajzen, 1991). We also suggest qualitative research in which users are asked to flesh out the meaning of stated intentions and barriers to acting on intentions in specific drug-use scenarios. implications for policy, as distinct from theory, seem more persuasive inasmuch as it would generally be impractical to deliver multiple interventions, each focusing on a specific behavior (e.g. disinfecting needles/syringes when using them after strangers have used them). On the contrary, it is important to develop interventions that can promote sustained injection-risk reduction across a wide range of drug-use scenarios faced by IDUs. Perceived self-efficacy emerged as a possible leverage point for intervention among White IDUs. As with intention, our measure of self-efficacy was conceived rather broadly, reflecting IDUs’ confidence in their ability to reduce injection risks. However, unlike intention, self-efficacy was a significant predictor of behavior change despite the one-year lag between time points. Interventions that focus on boosting self-efficacy might therefore be expected to promote sustained risk reduction across drug-use scenarios. Such interventions might be designed to boost self-efficacy by providing ‘mastery experiences’ in which clients role-play safer behavior (Basen-Enquist, 1992) and breaking behavior change into incremental steps that can be mastered consecutively, with initial steps easier than later ones (Bandura, 1994; Rosenstock, 1990). While self-efficacy did not influence behavior among African Americans and Mexican Americans in our study, perceived peer norms for risk reduction did emerge as a possible leverage point for intervention in those groups. Like self-efficacy, peer norms were a significant predictor of behavior change despite the one-year lag between time points. On its face, our measure of peer norms captures social influence. But the measure may also reflect informational and motivational aspects of normative influence. Further research is needed to identify more specifically the aspects of normative influence that are most relevant to behavior change (see also White et al.. 1994). AIDS preventive intervention might

193

gain effectiveness among African American and Mexican American IDUs if designed to boost real and perceived norms for risk reduction, to build upon the person’s sense of connectedness to the group/community, and strengthen motives to comply with group norms. Such interventions would invoke ‘social responsibility rather than individualistic self-preservation’ (Nyamathi and Shin, 1990). It would be erroneous to conclude that perceived efficacy is irrelevant to risk behavior among nonWhite IDUs. Instead, these findings are consistent with a growing body of research confirming that efficacy perceptions in non-White cultures are constructed on collective as well as personal grounds (Earley, 1994; Oettingen, 1995) and that health outcomes are affected by ‘collective efficacy’ as well as self-efficacy (Bandura, 1995). Thus, African Americans and Mexican Americans may be more likely to apply risk-reduction skills learned via AIDS education if they perceive that others in the same ethnic community are already doing so or are able to do so effectively (Earley. 1994). It has been argued that IDU risk behavior depends much more on external constraints than on individual-level decision making (Singer, 1992). We were unable to examine how the broader context of users’ lives may have influenced their behavior. Yet any behavior change that is not strictly coerced depends in part on steps chosen by the individual (Falck et al., 1995; Rosenstock et al., 1994). and one purpose of AIDS education at the individual level is to help people recognize external constraints on their behavior and to gain more control over those constraints. Interventions to boost self-efficacy among IDUs might, for example, teach clients to overcome situational constraints on accessing and using bleach. Norms-based interventions might teach risk reduction skills to intact IDU social networks or employ 1DUs as change agents in their networks (Friedman et al., 1992). In any case, AIDS education surely requires attention to both the external constraints that impinge on behavior czndthe personal resources, perceptual and motivational, that people apply to behavior change at the individual level.

Acknowledgements Data used in this report were collected and analyzed under National Institute on Drug Abuse grants DA05589, DA00146 DA07699 and DA01070.

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and Alcohol Dependence 42 (1996) 183-196

Appendix A: Correlation matrices Whites I. II. III. IV. V. VI. VII. VIII.

Perceived infection risk Peer norms AIDS Knowledge Response Efficacy Self efficacy Disinfection attempts baseline Intention to disinfect Disinfection attempts follow-up

African Americans Perceived infection risk I. II. Peer norms III. AIDS knowledge IV. Response efficacy V. Self efficacy VI. Disinfection attempts baseline VII. Intention to disinfect VIII. Disinfection attempts follow-up Mexican Americans I. Perceived infection risk Peer norms II. III. AIDS knowledge IV. Response efficacy V. Self efficacy VI. Disinfection attempts baseline VII. Intention to disinfect VIII. Disinfection attempts follow-up * p 2 0.05; ** P 2 0.01; *** P IO.001.

I

II

III

IV

V

VI

VII

-27 49** 43* -15 08 -01 08

26* 21 61*** 38** 40** - 14

76*** 44** 06 26* 10

67*** 25* 35** 27*

12 46*** 26*

28* 16

18

-18 63*** 49* -23 -10 -01 -04

00 11 53* 05 23 31*

95*** 41* -05 28* 12

41* -07 23 10

02 56*** 20

15 00

19

-48* 36* 10 -30 14 -14 -09

-11 -08 32 -13 -09 20

79** 56** 20 25 19

77** 14 34* 16

18 30* 25

25* 52***

06

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