A Test of Major Assumptions About Behavior Change: A Comprehensive Look at the Effects of Passive and Active HIV-Prevention Interventions Since the Beginning of the Epidemic
This meta-analysis tested the major theoretical assumptions about behavior change by examining the outcomes and mediating mechanisms of different preventive strategies in a sample of 354 HIV-prevention interventions and 99 control groups, spanning the past 17 years. There were 2 main conclusions from this extensive review. First, the most effective interventions were those that contained attitudinal arguments, educational information, behavioral skills arguments, and behavioral skills training, whereas the least effective ones were those that attempted to induce fear of HIV. Second, the impact of the interventions and the different strategies behind them was contingent on the gender, age, ethnicity, risk group, and past condom use of the target audience in ways that illuminate the direction of future preventive efforts.
Keywords: behavior change, active intervention, HIV, health, communication
The development of effective health behavior interventions and adequate understanding of the processes that underlie change to risky behavior continues to top the agenda for reducing disease and death among at-risk populations. For example, infection with HIV has been diagnosed in almost 1 million people in the United States (Centers for Disease Control [CDC], 2003
) as well as an estimated 40 million worldwide (UNAIDS/WHO Working Group, 2002
). In some countries, the epidemic continues to escalate, and even in nations that have successfully curbed the spread of the disease, certain groups still show increases in infection rates (see, e.g., CDC, 2003
). Given these distressing figures, it is no surprise that research on HIV prevention has become increasingly important and progressively more sophisticated. Indeed, HIV prevention presently constitutes one of the most significant paradigms for the discovery of health behavior change techniques and for the understanding of the theoretical processes that underlie such change.
In fact, the HIV epidemic of the 1980s stimulated the uniting of funds and expertise from various disciplines in the development of a shared behavior-change paradigm. As a key example, in 1992, a group of behavioral researchers joined forces—upon request from the National Institutes of Health—to develop a paradigm for behavior change that would guide research and practice in the prevention of HIV (see Fishbein et al., 1992
). Various models were examined, and the key assumptions were condensed into a limited number of premises that illuminated preventive efforts.
Although the various models had independently received broad support, this support was derived almost entirely from behavior prediction studies. However, the formulation of these general assumptions contributed to the creation of a large intervention literature. As a whole, this literature offers the perfect laboratory for a more rigorous examination of the various models applied to behavior change, rather than prediction. This article presents the results of a thorough meta-analysis of HIV interventions conducted from 1985 to 2003. Our intention was to test general health-prevention premises, identify the mediators of effective interventions, and consider the applicability of interventions to populations that vary in demographic and behavioral variables that correlate with marginalization and risk for HIV.
Of course, our article complements a large quantity of prior research on the generalizability of HIV-prevention attempts. With nearly two decades of behavioral research, considerable understanding of the effects of HIV-prevention efforts comes from multisite studies and meta-analyses. For instance, at least 12 multisite trials have demonstrated significant effects of HIV-prevention programs (see CDC AIDS Community Demonstration Projects Research Group, 1999
; Cottler, Leukefeld, et al., 1998
; Fogarty et al., 2001
; Kegeles, Hays, & Coates, 1996
; Kelly et al., 1991
; Kelly, Murphy, et al., 1997
; Lauby, Smith, Stark, Person, & Adams, 2000
; MacLachlan, Chimombo, & Mpeba, 1997
; McCusker, Stoddard, Hindin, Garfield, & Frost, 1996
; National Institute of Mental Health [NIMH] Multisite HIV Prevention Trial Group, 1998
; O’Leary et al., 1998
; Rotheram-Borus et al., 2001
). Moreover, there are now several meta-analyses of the psychological outcomes of HIV prevention that illuminate the overall effects of certain types of interventions across populations. For example, intervention studies using videos for HIV education (Healton & Messeri, 1993
) and interventions using techniques to strengthen behavioral skills relevant to condom use (Kalichman, Carey, & Johnson, 1996
) have proven effective. In contrast, interventions that contain HIV counseling and testing (Weinhart, Carey, Johnson, & Bickham, 1999
) appear to produce no overall positive increase in condom use. Likewise, communications that involve neither counseling nor behavioral training generally have no effect (Albarracín et al., 2003
Some prior meta-analyses have investigated the effects of interventions targeted to particular groups. These syntheses suggest that preventive interventions are generally effective for women (Logan, Cole, & Leukefeld, 2002
; Mize, Robinson, Bockting, & Scheltema, 2002
), heterosexual adults (Neumann et al., 2002
), drug users (Prendergast, Urada, & Podus, 2001
; Semaan et al., 2002
), adolescents (B. T. Johnson, Carey, Marsh, Levin, & Scott-Sheldon, 2003
; Kim, Stanton, Li, Dickersin, & Galbraith, 1997
; Mullen, Ramirez, Strouse, Hedges, & Sogolow, 2002
; Robin et al., 2004
), and gay men (W. D. Johnson et al., 2002
). To this extent, many HIV-prevention interventions have demonstrated effectiveness when analyzed across and within populations.
Despite the availability of prior meta-analyses examining the effectiveness of interventions to promote condom use, this literature suffers from three limitations. The first limitation concerns the lack of a thorough analysis comparing the effectiveness of the various intervention strategies. This deficiency is especially important when one considers that understanding the effects of the different strategies to increase condom use is critical to the development of behavior change theory and a set of rational implementation guidelines for practitioners. The aforementioned meta-analyses each concentrated on a single type of intervention and therefore do not adequately distinguish between strategic intervention approaches based on particular theoretical assumptions. Further, the only available metaanalysis to have estimated the differential effects of several types of HIV-prevention interventions (Albarracín et al., 2003
) considered only communications presented to relatively passive audiences, excluding more active approaches such as clientcentered counseling, practical exercises, HIV testing, and role-playing. This is an important restriction, because the more active strategies are likely to produce the greatest increases in condom use (see J. D. Fisher & Fisher, 2000
; B. T. Johnson et al., 2003
; Kalichman et al., 1996
; Kelly, 1995
A second limitation of the prior meta-analytic work has been its inability to examine whether available intervention strategies, designed to affect different psychological variables such as threat or attitudes, actually influence these variables, and whether the intervention’s influence or lack of influence on these mediators is responsible for the success or failure of the program to change behavior. The lack of a process analysis of the overall effects of HIV-prevention interventions is unfortunate because, as J. D. Fisher and Fisher (1992
; see also Cook & Campbell, 1979
) pointed out, treatments often work for reasons that the researchers do not anticipate and fail because they are unfit instantiations for the type of strategy they are supposed to model. Consequently, the present meta-analysis is the first to validate models of intervention effectiveness by looking at the sequence of psychological change that different interventions produce (e.g., attitudinal arguments should promote behavior change by first inducing procondom use attitudes, normative arguments should promote behavior change by first inducing procondom use norms, and behavioral skills training should promote behavior change by first increasing behavioral skills that promote condom use).
A third limitation concerns the generalization of specific intervention strategies to different populations. Although certain types of strategies may be differentially effective across particular audiences, current knowledge about this hypothesis is limited. For example, W. D. Johnson et al. (2002)
meta-analyzed the effects of nine controlled intervention trials on the likelihood of unprotected sex for men who have sex with men, reporting that interventions promoting interpersonal skills were most effective. This work, however, could not examine whether interventions promoting behavioral skills are more, equally, or less beneficial to men who have sex with men relative to other groups, whether different genders benefit from the same or different strategies, or whether teens or adults should be approached in the same or different ways. Given this state of affairs, one objective of our meta-analysis was to investigate the generalizability of different intervention strategies to different populations, which is essential to direct future research and prevention.
To summarize, the objective of the present meta-analysis was to synthesize research on the effects of a large number of interventions conducted since the beginning of the HIV epidemic among a variety of populations, and to compare the reality of intervention effectiveness with theoretical proposals about the nature of effective interventions. To accomplish this objective, we reviewed the outcomes reported in 194 research reports spanning the years 1985 to 2003. This collection is the most comprehensive to date, surveying 20 times as many reports as W. D. Johnson et al.’s (2002)
and almost 5 times as many reports as B. T. Johnson et al.’s (2003)
and Albarracín et al.’s (2003)
. Because of this extensive breadth, the analyses we have performed provide the most generalizable estimates of intervention outcomes available in the domain of interventions to promote condom use. Moreover, our work is both the first to examine the mediating mechanisms by which interventions have an impact and the first to estimate the generalizability of the effectiveness of certain intervention strategies across populations and settings.
Theoretical Assumptions, Intervention Strategies, and Mediating Processes
Several theoretical models that specify the motivational and cognitive antecedents of health behaviors have been advocated in the area of HIV prevention. For example, the theory of reasoned action (Fishbein & Ajzen, 1975
) and the theory of planned behavior (Ajzen & Madden, 1986
; for a meta-analysis, see Albarracín, Johnson, Fishbein & Muellerleile, 2001
) state that protection behaviors are contingent on (a) the perceived desirability of the behavior (i.e., positive attitudes and expectancies about the behavior) and (b) the normative pressure to engage in the behavior (i.e., social norms). The theory of planned behavior also considers (c) perceptions that the behavior is easy and up to the individual (i.e., perceived behavioral control). Social–cognitive theory (Bandura, 1986
) assumes that people will engage in protective behaviors when they perceive that they are capable of doing so, because self-efficacy is central to implementing behavior. Furthermore, social–cognitive theory (Bandura, 1989
) and the information–motivation–behavioral skills model (J. D. Fisher & Fisher, 1992
) both assume that people are more likely to perform a behavior once they acquire relevant (d) knowledge and (e) behavioral skills.
Other models have concentrated on the role of the perceived threat posed by a health problem and advanced conflicting predictions. On the one hand, the health belief model (Janz & Becker, 1984
; Rosenstock, 1974
; Rosenstock, Strecher, & Becker, 1994
) and the protection motivation theory (Floyd, Prentice-Dunn, & Rogers, 2000
; Rogers, 1975
) hypothesize that people are motivated to initiate healthy behaviors when they (f) fear the severity of the disease and (g) believe that they are personally susceptible to it (but see Gerrard, Gibbons, & Bushman’s 
null metaanalytic findings). On the other hand, Rothman and Salovey (1997)
have proposed and demonstrated that threatening (loss-framed
) persuasive messages are effective only when the target behavior consists of avoiding a risk factor (e.g., avoiding sun exposure). The same messages, however, are presumably detrimental when one wishes to promote a proactive measure (e.g., using sunscreen).
As Fishbein and his colleagues (Fishbein et al., 1992
; see also Albarracín, Fishbein, & Middlestadt, 1998
) observed, all of these theories suggest a number of different intervention strategies that can be expected to change behavior. Each strategy dictates the particular types of content of an intervention and the ways in which the intervention affects behavior. Interventions that attempt to modify attitudes and norms usually consist of assertions that the behavior being advocated has personally or socially beneficial consequences (see Ajzen & Fishbein, 1980
). For example, large-scale projects launched by the CDC during the 1990s were designed to induce recipients’ belief in the favorable outcomes of using condoms, including health promotion and increased psychological satisfaction (CDC, 1997
; Kamb et al., 1998
). Other interventions consist of normative appeals for college students (Reeder, Pryor, & Harsh, 1997
) or men who have sex with men (Kelly, McAuliffe, et al., 1997
; Kelly, Murphy, et al., 1997
; Kelly et al., 1991
), as well as interventions to convince a variety of higher risk populations that their social network supports condom use (see CDC, 1997
; Kamb et al., 1998
The information–motivation–behavioral skills model posits that information, motivation, and behavioral skills predict actual behaviors. Thus, one can take the model as suggesting three types of interventions to induce condom use, each of which targets information, motivation, or behavioral skills and can be used in combination with the other two (see J. D. Fisher & Fisher, 2000
). An informational communication typically conveys structured data on the nature of HIV, modes of transmission, mechanisms of the disease, and methods of prevention (e.g., Borgia et al., 1997
; Gerrard & Reis, 1989
; Gillmore et al., 1997
; Huszti, Clopton, & Mason, 1989
; J. A. Johnson et al., 1988
; Kelly, McAuliffe, et al., 1997
; Kelly, Murphy, et al., 1997
; O’Leary, Jemmott, Goodhart, & Gebelt, 1996
; Sherr, 1987
; Solomon & DeJong, 1989
). Motivational interventions attempt to induce favorable attitudes as well as social norms in support of the behavior and perceived vulnerability to HIV, typically combining the strategies we discussed in the context of the theories of reasoned action and planned behavior (e.g., W. A. Fisher, Williams, Fisher, & Malloy, 1999
According to the information–motivation–behavioral skills model, however, HIV-prevention programs are generally not successful unless they manage to increase behavioral skills as well. Thus, interventions based on this model often contain behavioral scripts about strategies that yield successful performance of the behavior. For example, a persuasive message may not only recommend condom use and mention its advantages but also describe how success in condom use depends on preparatory actions, such as carrying condoms around all the time or discussing condom use with potential partners. As another example, a widely accepted strategy is to have individuals role-play condom application or negotiation, with the idea that the behavioral practice and the instructional feedback will facilitate the acquisition of behavioral skills. In addition to teaching behavioral skills, interventions of this type presumably increase perceptions of control (i.e., perceived behavioral control and self-efficacy), which are a critical element in the theory of planned behavior and social–cognitive theory.
The health belief model and the protection motivation theory both suggest that inducing perceptions of threat concerning HIV should increase condom use, particularly when interventions also increase response efficacy (Rogers, 1975
). Communications designed on this basis typically use highly emotional scare tactics in the hope that negative affect will stimulate condom use. For example, a campaign evaluated by Rigby, Brown, Anagnostou, Ross, and Rosser (1989)
presented an image of the Grim Reaper as the source of an HIV-prevention message. Other, less extreme communications based on the same assumptions may describe the consequences of the disease (Goertzel & Bluebond-Langner, 1991
), provide data on infection rates (Ruder, Flam, Flatto, & Curran, 1990
), or conduct a detailed interview about HIV risk behaviors to sensitize participants to risk (Weinhardt, Carey, & Carey, 2000
). As noted, however, these strategies may be counterproductive for proactive target behaviors like condom use.
Estimating the Impact of Different Theory-Based Strategies
As all the past theorizing on health behavior change would suggest, understanding the impact of HIV-prevention interventions requires a lot more than estimating the average impact of all available strategies on actual behavior. Instead, an adequate conceptualization must start by establishing the effectiveness of different intervention components. In this article, we synthesized research on the impact of interventions to increase condom use on (a) attitudes, (b) norms, (c) control perceptions, (d) intentions, (e) HIV knowledge, (f) behavioral skills, (g) perceived severity of HIV, (h) perceived susceptibility to HIV, and ultimately (i) condom use. In addition to summarizing the overall effects of the interventions, we obtained separate estimates of the effects of passive and active interventions. Passive interventions are characterized by the presentation of material to an audience that has minimal participation; they comprise (a) messages to induce procondom attitudes, (b) messages to induce procondom norms, (c) messages to increase relevant knowledge, (d) messages to verbally model skills that promote condom use, and (e) messages to increase perceived threat. Active interventions generally include passive strategies as well, but their main distinguishing feature is the inclusion of client-tailored counseling, HIV testing, and/or activities to increase behavioral skills, such as role-playing of solutions for prototypical conflicts surrounding condom use. Perhaps more important, in addition to comparing the effects of passive and active approaches (with their corresponding control groups, when available), we estimated the differential effectiveness of the strategies that we previously classified as passive or active.
These analyses are essential for theory testing purposes. For example, if protection motivation theory is plausible, arguments that HIV is a threat should increase condom use if they manage to successfully sensitize the audience to the HIV threat. Similarly, if social–cognitive theory is reasonable, interventions to increase behavioral skills should be more effective when they manage to successfully increase behavioral skills. In these analyses, we also considered potential differences between designs with and without control groups, and factors related to sampling (e.g., participants of a given age, gender, or ethnicity and higher behavioral risk groups), setup of the intervention (e.g., presentation in schools and use of videotaped materials), and other features of the research design and implementation (e.g., performing formative research to adapt the intervention to the population, measuring change on the same sample instead of using between-subjects procedures). By analyzing the associations of these moderators with behavior change, we were able to estimate not only their potential impact but also the extent to which these decisions could bias the apparent effects of the different intervention strategies we summarized.
The second requisite for testing theories relevant to HIV prevention is to establish whether the supposed mediating effects are present whenever an effect on behavior is present. Without this evidence, claims that certain types of interventions are effective in virtue of a set of presumed underlying psychological mechanisms are unsubstantiated. Therefore, we conducted mediation analyses (Baron & Kenny, 1986
; Judd & Kenny, 1981
) to determine whether the pattern of change in behavior in response to different passive and active strategies was itself predicted by changes in theoretically associated variables (e.g., attitudes, knowledge, and behavioral skills).
Generalizability of Intervention Strategies to Different Populations
Our meta-analysis also had the objective of determining the generalizability of the impact of different types of interventions to various populations. The main reason behind this objective is practicality. For example, assume that behavioral skills interventions are the most effective, regardless of the number of women, teens, heterosexuals, or drug users in the audience. Such population-independent effects would call for allocation of public health resources to refine effective techniques instead of customize interventions for specific groups. Alternatively, interpersonal skills may be effective only for women who experience greater difficulty in controlling an activity that is generally in the hands of men. For the same reason, condom use skills may be effective only for men who are generally in charge of applying and monitoring condoms. When such specificity is the case, HIV-prevention efforts should increase attention to the needs of specific groups, developing new interventions that are of use for these groups.
The second reason for investigating the generalizability of different types of strategies is of a theoretical nature. As one example, the finding that women’s condom use is more influenced by perceptions of behavioral control than men’s has led to speculation about the kinds of social factors that are likely to make behavioral skills interventions effective. To this extent, empirical confirmation of differences would further support that hypothesis, whereas disconfirmation would make it more tentative. As another example, because teenagers pay greater attention to their peers’ opinions than do adults (Kerr, Stattin, Bisecker, & Ferrer-Wreder, 2002
), normative interventions emphasizing the use of condoms by similar others may be more effective for teens than for adults. As a result, establishing greater effectiveness of normative interventions for teens would further validate that proposition.
Yet another reason for analyzing the impact of HIV-prevention strategies across different populations is that the need for population-specific interventions has been advocated by almost every model of behavior change (see, e.g., Ajzen & Fishbein, 1980
). For instance, the transtheoretical model (Prochaska, Di-Clemente, & Norcross, 1992
) and the AIDS risk reduction model (Catania, Coates, & Kegeles, 1994
; Catania, Kegeles, & Coates, 1990
) have described a sequence of stages that go from behavior initiation to adoption to maintenance. Because interventions should match the behavioral stage of the audience, people who are not yet using condoms may become motivated if they are presented with an attitudinal or informational appeal. Later on, however, a focus on behavioral skills should facilitate movement toward the actual implementation of the recommended behavior (see Bandura, 1994
; Schwarzer, 1992
Review and Inclusion Criteria
We conducted a review of reports that were available by September of 2003. First, we conducted a computerized search of MEDLINE, Psyc-INFO, ERIC, Social Science Citation Index, and Dissertation Abstracts International using a number of keywords, including HIV (AIDS) messages, HIV (AIDS) communications, HIV (AIDS) interventions, HIV (AIDS) prevention, and health education and HIV (AIDS). Second, we manually searched all available issues, appearing during or after 1985, of the journals AIDS, AIDS Education and Prevention, AIDS Research, American Behavioral Scientist, American Journal of Community Psychology, American Journal of Nursing, American Journal of Public Health, Basic and Applied Social Psychology, Communication Research, Communications, Health Communication, Health Education Quarterly, Health Education Research, Health Psychology, Journal of the American Medical Association, Journal of Applied Communication Research, Journal of Applied Social Psychology, Journal of Consulting and Clinical Psychology, Journal of Personality and Social Psychology, Journal of Sex Research, Medical Anthropology, Morbidity and Mortality Weekly Report, Qualitative Health Research, and Social Science and Medicine. We also checked cross-references in the obtained reports, sent requests for information to researchers funded by the National Institutes of Health (NIH), and contacted selected experts and agencies who could provide relevant materials.
We used several eligibility criteria to gather an optimal, relatively homogeneous sample of studies that could serve our objectives well, as explained below.
- Studies were included if they described the outcomes of an intervention to promote the use of condoms. We excluded interventions to promote safer intravenous-drug-related behaviors or abstinence from sex, except when they also included a condom use component.
- The studies we included concerned outcomes of different types of interventions. Therefore, we included simple communications as well as interventions in which recipients engaged in behaviors as part of the intervention (i.e., role-playing, practicing condom-use-related skills, and HIV counseling and testing).
- We included only studies that provided information to calculate the effect of interventions over time and excluded reports without a pretest. Most of the reports obtained pre- and posttest measures on the same sample, but others used independent samples at each time (for an explanation of the advantages of the use of independent samples for longitudinal studies, see Cook & Campbell, 1979).2
Coding of Study Characteristics
Two independent raters coded characteristics relevant to the report and the methods used in the studies. Intercoder agreement for all categories included in the coding sheet was 85%, and intercoder reliability coefficients (kappas for categorical variables and simple correlations for continuous variables) are summarized in . Disagreements were resolved by discussion and further examination of the studies.
We coded studies for characteristics of the report, including the (a) publication year, (b) first author’s affiliation to behavioral (e.g., psychology or social work) or medical sciences (e.g., epidemiology, community health, or medicine), (c) country of intervention, (d) state of intervention, and (e) language of intervention.
We recorded the type of intervention and strategy
used in each case. Passive strategies included (a) attitudinal arguments, such as discussions of the positive implications of using condoms for the health of the partners and for the romantic relationship; (b) normative arguments about support of condom use provided by friends, family members, or partners; (c) factual information (i.e., mechanisms of HIV, HIV transmission, and HIV prevention); (d) arguments designed to model behavioral skills (what to do when partners do not want to use a condom, when recipients or their partners are sexually excited, and when alcohol or drugs are involved); and (e) threat-inducing arguments, such as discussions about the recipients’ personal risk of contracting HIV or other sexually transmitted infections (STIs). We also recorded the use of active interventions, namely behavioral strategies to train audiences in condom-use-promoting skills and the administration of HIV counseling and testing. Strategies to induce behavioral skills comprised (f) condom use skills (e.g., practice with unwrapping and applying condoms), (g) interpersonal skills (e.g., role playing of interpersonal conflict over condom use and initiation of discussions about protection), and (h) self-management skills (e.g., practice in decision making while intoxicated, avoidance of risky situations),3
whereas (i) HIV counseling and testing involved the administration of a seropositivity test as well as the type of counseling in place. When the counseling was described as involving specific arguments or training aspects, we coded for those in addition to noting the presence of counseling and testing. Finally, we kept a record of whether, prior to the posttest, the researchers provided research participants with condoms. On the basis of these codings, control groups were those to whom no passive or active intervention was applied, although some control participants received condoms as part of the study. These codings allowed us to establish the likely effects of each type of strategy and of mere condom provision.
We also recorded characteristics of the participants
, including demographics of the target group as well as specific characteristics and behaviors of the target group that are associated with HIV-infection risk. To describe the target population, we retrieved the (a) sample size; (b) percentage in each group that was male; (c) mean or median age; (d) percentage of participants of European, African, Latin, Asian, and AmericanIndian descents as measures of ethnic diversity;4
(e) percentage of participants who completed at least high school; and (f) population of the city or village at the time the intervention was conducted.
To further describe the sampling of participants in relation to characteristics or behaviors associated with HIV-infection risk, we registered the (a) inclusion of behaviorally at-risk groups in each sample (i.e., men who have sex with men, intravenous drug users, partners of intravenous drug users, commercial sex workers, multiple-partner heterosexuals, participants with a history of STIs, participants with severe mental illness, drug users, college students, middle-school or high school students, and teachers). We also recorded the (b) baseline level of condom use for each sample, which we classified as low (i.e., mean of never or almost never when a subjective frequency scale was used to measure condom use, as well as 40% or less of the time when the mean percentage of condom use over intercourse occasions was reported), moderate (i.e., sometimes as well as 40% to 80% of the time), and high (i.e., always or almost always, as well as 80% or more of the time); (c) percentage of condom use over intercourse occasions at pretest, and (d) rate of HIV at pretest.
We coded for methodological characteristics that related to intervention setup. Thus, we classified each intervention group according to (a) the setting of the intervention (i.e., whether the intervention was delivered via mass media, clinics, community settings, or schools). We also recorded (b) the media selected to deliver the intervention, including face-to-face interactions and video- or audiotaped materials, (c) whether exposure to the communication was individual or in groups, (d) whether the researchers made efforts to produce a culturally appropriate intervention, and (e) the duration of the communication in hours.
Finally, we coded issues related to research design and implementation, including (a) whether the design was within subject or whether different samples were used at pre- and posttests; (b) whether participants were randomly assigned to conditions; (c) the amount of money (in U.S. dollars) received in exchange for participation (0 when none was mentioned); (d) the mean and median number of days between the intervention and the posttest; (e) whether the researchers acknowledged formal theory as a basis for the intervention and, if not, whether theory-relevant literature was at least cited; (f) whether there was formative research to adapt the intervention to the target population and media; and (g) whether the intervention was targeted to a specific group or attempted to reach general population recipients. When there was a specific target sample, we further recorded whether the target was a specific (h) ethnic or (i) gender group. We also coded groups that partook in the study voluntarily as (j) self-selected, relative to captive groups that had less flexibility in refusing to participate (i.e., volunteers vs. participants in classroom, inpatient units, or prison settings). Finally, we calculated (k) the percentage of attrition for each group included in the meta-analysis when sample sizes for the pre- and posttests were exactly reported.
Retrieval of Effect Sizes
Two raters calculated effect sizes independently. Disagreements were checked with a third researcher and resolved by discussion. Raters were instructed to calculate effect sizes representing change from the pretest to the most immediate posttest. Efforts were made to calculate effect sizes for all measures of the constructs of interest that each study measured. When there was more than one measure of a construct in one particular study, we first calculated effect sizes for each one and then obtained the average, which was used as the effect size for that particular variable.
To represent change from pretest to posttest measures, we used B. J. Becker’s (1988) g
, which is calculated by subtracting the mean at the posttest from the mean at the pretest and dividing the difference by the standard deviation of the pretest measure. This measure controls for the inflation in the standard deviation following treatment (for an excellent analysis of the problem, see Carlson & Schmidt, 1999
). Effect sizes were also derived from exact reports of t
ratios, proportions, p
values, and confidence intervals. To derive effect sizes for within-subject studies, one needs the correlation between posttest and pretest measures. Because some reports did not offer this information, we adopted procedures recommended by B. J. Becker (1988)
as well as by Dunlap, Cortina, Vaslow, and Burke (1996)
. We explain these procedures when they become relevant.
We also estimated effect sizes when a report contained inexactly described p values—such as when the authors indicated that a given finding was not significant at .05—using the appropriate within- or between-subjects procedures. Thus, a reported nonsignificant finding was estimated to have a probability of .99, whereas a significant finding was estimated to have a probability at the level of the cutoff value used in the study (e.g., .05 or .01). However, because the use of such reports may lead to incorrect estimations, we conducted separate analyses on the set of exactly reported effect sizes and all the effect sizes (including the ones estimated on the basis of inexactly reported p values). Because these sets of analyses yielded similar results, we report only the results that included all effect sizes.
We calculated effect sizes representing change in attitudes, norms, control perceptions, intentions, behavioral skills, knowledge, perceived severity, perceived susceptibility, and condom use behavior. We describe typical measures of each variable below.
Attitudes toward the behavior were typically measured with semantic differential types of scales (e.g., “Do you think using a condom every time you have vaginal sex with your main partner would be pleasant or unpleasant? And would you say it would be extremely, quite
, or slightly
)?”; CDC, 1993
, p. 12). Researchers sometimes obtained expectancy–value estimates of attitude by subjectively weighting the belief that a behavioral outcome will occur by the evaluative implications of that outcome (e.g., “showing that you care” or “making you worry less”; CDC, 1993
, p. 3 and p. 5, respectively). Behavioral or outcome beliefs were typically measured with bipolar probability statements linking the behavior to a set of outcomes (e.g., “using a condom would take all the fun out of sex for me”; O’Leary et al., 1996
), whereas outcome evaluations were measured by means of bipolar evaluative items (e.g., “becoming pregnant now would be good
”; CDC, 1993
Change in overall and outcome-specific measures was combined into a global index of change in attitudes.
According to Fishbein and Ajzen (1975)
, subjective norms are influenced by a set of salient beliefs about the normative prescriptions of specific (salient) referents, weighted by the motivation to comply with each of those referents. For example, a man may perceive social pressure to use condoms if he believes that his partner thinks he should use condoms and he is motivated to comply with the partner. In this meta-analysis, we combined both overall and belief-based measures of norms to assess the normative influence of the communications. Subjective norms were typically measured with probability scales in response to statements such as “Would you say that most of the people who are important to you think that you should or should not use a condom for vaginal sex with your main partner?” (CDC, 1993
, p. 12). Normative beliefs were generally assessed with bipolar probability statements about the opinion of a specific referent (e.g., “Do you feel that your main partner thinks you should or should not use a condom every time you have vaginal sex with her?”; CDC, 1993
, p. 6), whereas motivations to comply were typically measured with unipolar scales in response to items such as “When it comes to protecting yourself from AIDS, do you want to do what your main partner thinks you should do?” (CDC, 1993
, p. 6).
Control perceptions refer to self-efficacy as well as expectations of personal control over condom use. Measures of self-efficacy comprised items that relate control to specific events. For example, the Community Demonstration Projects Research Group (CDC, 1993
) included items such as “How sure are you that you can use condoms every time for vaginal sex with your main partner when your partner does not feel like using them?” or “When there aren’t any condoms around, how sure are you that you can wait until you get one every time before having vaginal sex with your main partner?” (p. 7). Similarly, O’Leary and her colleagues (1996)
asked participants to report whether “it would be easy or hard to refuse to have sex with a person if s/he will not use a condom” (p. 520). Measures of control perceptions included items like “Now it is just a ‘what if’ question, but if you wanted to use a condom every time you have anal sex with your main partner, how sure are you that you could?” (CDC, 1993
, p. 17). Other researchers asked participants to rate statements such as “I can use a condom without fumbling around” (Kelly, McAuliffe, et al., 1997
, p. 1285).
Measures of intentions assessed the intent or willingness to use condoms in the future. Typical items were “In the future, do you plan to use condoms?” (Eldridge et al., 1997
, p. 67) and “In the next six months, how likely do you think it is that you will start using a condom every time you have vaginal sex with your main partner?” (CDC, 1993
, p. 11).
A large number of studies assessed the participant’s knowledge about HIV or AIDS, typically through a series of statements that the participant evaluated as true or false (e.g., “The AIDS virus can be caught through ordinary close social contact, such as sitting next to an infected person”; Rigby et al., 1989
, p. 149). Knowledge scores in most cases were calculated by computing the percentage of questions a participant answered correctly. When researchers reported statistics for individual items, we calculated effect sizes for each question and then averaged those effects into a global measure of change in knowledge.
Typically, measures of behavioral skills assessed the participant’s ability to use (acquire and apply) condoms and to negotiate condom use (i.e., communication about sex or sexual assertiveness skills). In one study, researchers measured negotiation skills by presenting participants with coercive sexual situations leading to unsafe sex and asking them to respond as they would in that situation (Eldridge et al., 1997
). Independent raters then evaluated participants’ negotiation skills on a scale from 1 (unlikely to prevent risk behavior
) to 10 (likely to prevent risk behavior
Perceived severity and susceptibility (perceived threat)
Studies often assessed perceived HIV/AIDS severity
by having participants rate their agreement with statements such as “Fear of infection with HIV and AIDS affects my life” (Hämäläinen & Keinähen-Kiukaanniemi, 1992
, p. 138). Perceived susceptibility
was typically measured with participants’ assessments of the likelihood that they could become infected with HIV in the future (e.g., “There is practically no chance I could get AIDS”; O’Leary et al., 1996
, p. 520).
Stages of change
According to Prochaska, Redding, Harlow, Rossi, and Velicer (1994)
, during the precontemplation stage, individuals may be aware that their behavior is problematic but not intend to change it. During the contemplation stage, people consider performing the behavior at some point in their lives but have no actual plans to change their routine behavior (Prochaska et al., 1994
). A person in the preparation stage is committed to changing his or her behavior within the next month and may engage in the behavior occasionally. People who engage in a behavior on a regular basis for less and more than 6 months are considered to be in the action and maintenance stages, respectively. Only nine studies reported usable statistics for stages of change (e.g., 1 [precontemplation
] to 5 [maintenance
Condom use measures included assessments on subjective frequency scales, as well as reports of the percentage and number of times participants use condoms over a period of time. For example, the Community Demonstration Projects Research Group (CDC, 1993
) asked participants, “When you have vaginal sex with your main partner, how often do you use a condom?” (p. 11), and participants provided their response on a scale from 1 (every time
) to 5 (never
). To obtain a more precise report of condom use, Ploem and Byers (1997)
asked participants to report the frequency of sexual intercourse over the previous 4 weeks, as well as the number of occasions of sexual intercourse for which condoms were used. The researchers then derived the percentage of condom use for each participant. Similarly, Belcher et al. (1998)
asked participants to list the first name of all of their sex partners in the previous 90 days. For each name listed, participants were asked to identify the partner’s gender, the partner type (regular, casual, or new), the total frequency of vaginal sex, the frequency of condom-protected vaginal sex, the total frequency of anal sex, and the frequency of condom-protected anal sex. Percentages were again derived on the basis of relative frequencies.
Effect Size Calculation and Analytic Strategy
We calculated weighted mean effect sizes to examine change over time in intervention and control groups and performed corrections for samplesize bias to estimate d
. We used Hedges and Olkin’s (1985)
procedures to correct the effects for sample-size bias;6
calculate weighted mean effect sizes, d
.; confidence intervals; and homogeneity statistics, Q
, which test the hypothesis that the observed variance in effect sizes is no greater than that expected by sampling error alone. Calculations of the between-subjects variance followed procedures developed by Hedges and Olkin (1985)
. For within-subject designs, we calculated the variance of effect sizes using Morris’s (2000)
procedures. Specifically, we performed calculations for the variance of within-subject effect sizes using three alternate correlations between pre- and posttest measures (see also Albarracín et al., 2003
). Thus, we assumed r
= .00 and r
= .99 as the most extreme values and also imputed correlations from Project RESPECT (see Kamb et al., 1998
), which provided moderate values of this association. Because results were similar regardless of the correlation we used, we present only the ones with the imputed correlations (see also Albarracín et al., 2003
Computations of effect sizes were performed using fixed- and random-effects procedures. In the first case, one assumes a fixed population effect and estimates its sampling variance, which is an inverse function of the sample size of each group. The inverse of the effect size’s variance is used to weigh effect sizes prior to obtaining average values. Thus, effect sizes from studies with larger sample sizes are considered more precise and carry more weight than effect sizes obtained from studies with smaller sample sizes. These procedures are powerful and produce narrow confidence intervals (Rosenthal, 1995
; Wang & Bushman, 1999
). In contrast, random-effects procedures are based on the assumption that the effect sizes are sampled from a population of effect sizes. Thus, the effect size from a given study results from sampling an effect size at random but also contains measurement error, which is again an inverse function of the sample size in that particular study. Because random-effects procedures use the variance of a sample of effect sizes as well as the variance in each study to estimate the variance in the population of effect sizes, the error term is larger and the procedure may overestimate Type I error (Hedges & Olkin, 1985
; Hedges & Vevea, 1998
; but see Hunter & Schmidt, 2000
). Presumably, fixed-effects models are reasonable when one assumes that effect sizes vary as a result of a few, identifiable study characteristics, whereas random-effects models are appropriate when variation derives from multiple, unidentifiable sources (Raudenbush, 1994
Sample of Interventions and Controls
We included 194 reports, which provided 354 independent intervention groups and 99 independent control groups. Of the 194 reports, 44 provided a single data set, 91 provided two data sets, 28 provided three data sets, 21 provided four data sets, 3 provided five data sets, 6 provided six data sets, and 1 provided eight data sets. summarizes information about the included reports, as well as their types of interventions, participants, and methods, with separate columns for intervention and control groups. As can be seen from the table, most studies were published around 1996 and the median sample sizes of participant groups was around 100. Most reports were affiliated with the medical sciences, with psychology as the second most frequent affiliation. Although most studies were conducted in the United States, 33 countries were represented. Of the U.S. studies, 33 states were represented, with California providing more groups than any other state.
With respect to intervention strategies, 48% of the interventions contained arguments designed to induce a positive attitude about condom use outcomes, 15% contained normative arguments in support of condom use, 94% contained HIV-relevant information, 20% included arguments designed to verbally promote recipients’ behavioral skills, 47% included persuasive arguments designed to increase perceptions of threat among recipients, an average of 22% trained participants in some type of behavioral skill, and 18% administered an HIV test. Given the different combination of strategies, 51% of groups were exposed to interventions that simply presented arguments (passive interventions), whereas the remaining 49% engaged in activities to promote condom use (active interventions, i.e., HIV counseling and testing or behavioral skills training). Researchers distributed condoms to 22% of the intervention groups and to 7% of the controls.
There was great methodological variability in the studies we examined, in terms of the participants, intervention setup, and research design and implementation. Samples comprised both female and males, and participants were relatively young in age. On average, only 36% of participants were of European descent and only 35% of participants had completed high school. The samples included men who have sex with men, intravenous drug users, partners of intravenous drug users, commercial sex workers, multiple-partner heterosexuals, participants with a history of STIs, and patients with severe mental illness. Some samples included drug rehabilitation patients and general drug users; many included college, middle-school, or high school students; and a small percentage sampled teachers. Most participants for whom a measure of condom use was obtained had low condom use, and only a small percentage of participants were using condoms consistently. The average rate of infection with HIV was 20%, although most studies had no information on this issue.
More communications were presented in school and clinical settings than in any other place, although many of the messages were delivered in community settings, and some through mass-communication media. The communications were generally presented face-to-face, and video- and audiotaped materials were included in many cases. The intervention was applied exclusively to individuals (as opposed to group) in only 20% of the cases and lasted an average of 7.94 hr.
Finally, there was considerable variability in research design and implementation across the studies. For example, although all studies included pre- and posttest measures, some used different samples, whereas the majority were done within subject. The allocation of participants to study groups was done at random in 46% of the cases, and intervention participants were compensated an average of U.S. $18.31. The mean length of time between the intervention and the posttest was slightly over 3 months, although the median was about 1 month. Half of the intervention groups in our sample were explicitly based on theory, and 33% were designed from formative research with the target population. Most of the studies targeted a specific population. Quite frequently, samples were self-selected; attrition was around 12% across intervention and control groups.
Overall effects across interventions and control groups
The weighted mean effect sizes for intervention and control groups appear in , along with confidence intervals and homogeneity indexes. The last two columns of present QB
statistics, which in this case are analogous to F
ratios comparing change across intervention and control groups. The fixed-effects procedures followed Hedges and Olkin’s (1985)
recommendations and fit weighted factorial models to compare d
across intervention and control groups. The weights for fixed effects followed Hedges and Olkin’s computational formulas, whereas the weights for random-effects models followed Lipsey and Wilson’s (2001)
approach. The first QB
in the table compared all interventions with all controls, whereas the second excluded interventions that lacked a control. As these statistics suggest, the interventions were associated with increases in recipients’ knowledge about HIV, procondom use attitudes, control perceptions, norms, intentions, behavioral skills, and actual condom use. In addition, the analyses that included all intervention groups revealed an effect on perceived severity, but this effect did not emerge when we considered only interventions coupled with controls.
General Intervention Effectiveness
Furthermore, we compared the characteristics of intervention and control groups summarized in to detect systematic biases that may confound the reported differences in effect sizes across intervention and control groups. For that purpose, we used independent-sample t
and chi-square tests (Albarracín et al., 2003
). Although intervention and control samples were highly comparable across most dimensions, there were five significant differences across these groups. First, condoms had been distributed more often to intervention than to control groups, χ2
(1) = 13.76, p
< .001. Second, the intervention groups were more likely to include drug rehabilitation patients and general drug users than the controls, χ2
(1) = 4.39, p
< .03. Third, compared with interventions, control groups were more often from the United States, χ2
(1) = 3.83, p
< .05; had less self-selection, χ2
(1) = 3.88, p
< .05; and came from studies based on past research with the target group, χ2
(1) = 10.48, p
< .001. Yet when these variables were added as covariates in the mean comparisons in , the differences between intervention and control groups remained statistically significant.
Even when the covariance analyses were reassuring, comparing all interventions with all control groups is insufficient to rule out two important rival hypotheses. First, considering interventions without controls allows for the possibility that spontaneous maturation might be responsible for the observed increases in condom use (see Cook & Campbell, 1979
). Second, comparing interventions and controls that did not use random assignment cannot control for selection biases. This difficulty leaves open the possibility that the group assigned to the intervention was simply easier to change than the group assigned to the control. In light of these alternative hypotheses, an additional analysis was conducted in which we calculated scores representing controlled change. For this purpose, we selected only studies that used random assignment as well as a control group and subtracted the d
representing change in the control group from the d
representing change in the treatment group. The variance of the resulting delta (B. J. Becker, 1988
) equals the inverse of the sum of the variances of the ds
that entered the calculation of delta, and was used to derive a confidence interval for the overall effectiveness of HIV prevention intervention when one selects only controlled randomized trials (k
= 33). The result from the fixed-effects analysis was an average controlled change of 0.06 (95% CI = 0.003–0.123, Q32
= 167.28, p
< .001), which was small but significantly different from zero. Although the convergence of this analysis and those in is not surprising given that delta correlated .82 with the d
representing change in the treatment group for those studies that provided both statistics, it provides further support for the use of d
in our subsequent analyses.
Effects of passive and active interventions
More important than estimating the overall effects of HIV-prevention interventions is to determine what interventions are most effective. For instance, interventions differ in their inclusion of active strategies in which participants role-play problem situations, practice applying condoms to a model, or take an HIV test, which invariably involves some form of counseling (see ). Therefore, we first attempted to determine whether the inclusion of such activities led to greater impact than the use of merely passive strategies in which participants just receive a communication. The data in show the weighted average effects of interventions that we classified as passive and active on behavioral change, in addition to change in control groups. As can be seen, active interventions were associated with stronger improvements in condom use than passive approaches to prevention and control groups: fixed-effects QB1 = 484.25, p < .001, and random-effects QB1 = 24.71, p < .001, k = 258. Passive interventions did not differ significantly from control groups in a consistent way: fixed-effects QB1 = 4.18, p < .05, and random-effects QB1 = 1.40, ns, k = 90.
Behavior change for active interventions, passive interventions, and control groups. Weighted mean change as a function of condition (passive intervention, active intervention, or control group). A: Fixed-effects models. B: Random-effects models.
Effects of different passive strategies in passive and active interventions
It was also important to determine whether different types of arguments that are common to passive and active strategies were more or less successful at increasing condom use. We thus analyzed d for condom use in all intervention groups as a function of whether interventions attempted to verbally enhance (a) positive attitudes toward condom use, (b) supporting norms concerning condom use, (c) behavioral skills, (d) knowledge, and (e) perceived threat. Whether the intervention was active or passive was also included, as was the provision of condoms as an additional factor.
The fixed-effects mean analyses conducted to describe the effects of different passive strategies are summarized in . (Random-effects analyses from here on are not reported for the sake of brevity, as the patterns were the same but the number of significant effects decreased.) Following the means, we present QBs for each type of argument alone and in interaction with the passive or active nature of the intervention. These analyses show that whereas attitudinal arguments, behavioral skills arguments, and condom provision were associated with significant increases in condom use, threat and normative arguments were associated with decreases in condom use. In addition, most of these patterns were stronger when the intervention was active rather than passive, as judged by the significant interactions that appear in the last column of the table. The only exception was that the provision of condoms was significant only when interventions were passive.
Condom Use Change as a Function of Passive Strategy Across Passive and Active Interventions (k = 200)
Influence of the various strategies used in active interventions
The fixed-effects estimates of the impact of different strategies when the interventions included an active component (either skills training or an HIV test) appear in . These analyses imply that allowing participants to gain practice with self-management strategies and undergo HIV counseling and testing coincided with greater increases in condom use, whereas practice with interpersonal skills coincided with unexpected decreases in condom use and practice with condom use skills had no association with change in condom use.7
Condom Use Change as a Function of Active Strategy (k = 123)
Effects of Intervention Strategies Across Participant Populations and Intervention Setups
Given the need to assess intervention outcomes across different populations and intervention setups, we entered dummy-coded variables describing the nature of the groups under study in an analysis of the effectiveness of the different types of strategies. These analyses appear in – and were conducted on passive and active interventions considered simultaneously.
Influence of Participants’ Characteristics and Intervention Setup on Behavior Change
Change as a Function of Strategy Across Intervention Setups
To analyze the generalizability of different interventions across populations, we performed analyses with gender, age, and ethnicity; the inclusion of men who have sex with men, intravenous drug users, partners of intravenous drug users, and multiple-partner heterosexuals; and past condom use. (Other groups in were not sufficiently represented to perform these analyses.) The analyses with gender, age, and ethnicity were replicated using continuous variables in addition to the breakdowns presented here: gender = predominantly male when more than 50% of the sample was male; ethnicity = predominantly European background when more than 50% of the sample had that background; age = under 21 years when the mean or median age was under 21. The analyses using dichotomous and continuous predictors were very similar, which led to presenting the ones with dichotomous predictors for interpretational purposes. The analyses with past condom use required collapsing moderate and high condom use owing to the low number of conditions with high condom use (see ).
To estimate the effects of the setup of the intervention, we first considered whether the intervention was presented in a school, a clinic, or a community setting. Most of the interventions in our meta-analysis were delivered face-to-face (see ), which made it impossible to analyze interactions between face-to-face presentation and type of strategy. However, we considered the inclusion of video- or audiotapes, which may increase the impact of certain strategies but can also detract from the interaction with real-life facilitators, as well as the use of group or individual formats for the intervention sessions.
presents the QB statistics for the main effects of the population and intervention factors. It also includes the control means for different populations to permit comparison with the mean change in different intervention groups when applied to the same population. and present the QBs for the interaction between a given population or setting variable and a specific argument or behavioral strategy, as well as the QB for the simple effects of a strategy in a particular group. In the following sections, we summarize the significant interactions and highlight simple effects only when the statistical interaction was significant. When the interaction was not significant, one should rely on the main effects reported in and to reach conclusions.
Change as a Function of Strategy Across Different Participants
Independent influence of population participant characteristics and intervention setup
Not surprisingly, population and intervention factors influenced the amount of behavior change in the studies we summarized. Male, older, and minority recipients showed greater increases in condom use than female, younger, and majority recipients. Whereas groups including men who have sex with men changed more than groups not including them, the inclusion of partners of intravenous drug users and multiple-partner heterosexuals was associated with less behavior change. The inclusion of intravenous drug users and initial condom use had no significant main effects on the amount of behavior change observed.
It is important to note that even when different groups had different rates of behavior change overall, as shown in the first two sections of , the means for interventions were greater than control means in most cases. The only exception was the mean change for intervention recipients under 21, which did not differ significantly from the change in control condition. (As shall be seen from further analyses reported below, however, our meta-analysis later identified effective interventions for people under 21.)
With respect to the intervention setup, we examined the effects of presenting the intervention in a school, a clinic, or the community, as well as playing video- or audiotaped materials and performing group sessions. Of all these, only playing video- or audiotaped materials had a significant main effect on behavior change. Specifically, the use of these materials was associated with decreased behavior change.
Analysis of interactions between intervention strategies and characteristics of the populations
As suggested by the statistics in , there were manysignificant interactions. For example, an examination of the first panel, which is relevant to gender effects, reveals that the negative effect of presenting threat-inducing arguments and interpersonal skills training was stronger for predominantly male groups, whereas the negative effect of presenting normative arguments was stronger for predominantly female groups. In addition, the presentation of behavioral skills arguments as well as condom use skills training had positive effects among males but null or negative effects among females, whereas attitudinal arguments, information, self-management skills training, and HIV counseling and testing exerted more positive impact among females than among males. Actually, attitudinal arguments and information had nonsignificant effects among males.
Age also moderated which strategies were successful, with greater age generally amplifying effects that were observed across the board. Groups over 21 years of age responded more negatively to normative appeals and threat-inducing arguments than did groups under 21, which were positively affected by normative arguments and unaffected by threat-inducing arguments. At the same time, groups over 21 showed significant positive effects of behavioral skills arguments, self-management skills training, and HIV counseling and testing, whereas groups under 21 showed a nonsignificant effect of behavioral skills arguments, a positive but weaker effect of self-management skills training, and a significant negative effect of HIV counseling and testing. In addition, the provision of condoms had a positive effect for audiences under 21 but a negative effect for audiences over 21.
The ethnicity findings also suggested various ways in which the background of the sample moderated the effectiveness of the different intervention strategies. Samples of predominantly European backgrounds were less negatively affected by normative and threat-inducing arguments than those with a predominantly African background. In addition, as shown by the simple effects in , whereas condom provision benefited only samples with predominantly European backgrounds, behavioral skills arguments and HIV counseling and testing benefited only samples with predominantly African backgrounds. Finally, interpersonal skills training had stronger negative effects when the predominant background was European, and self-management skills training had stronger positive effects when the predominant background was African.
The middle set of panels of summarizes the outcomes of different strategies for different HIV risk groups, including men who have sex with men, intravenous drug users, partners of intravenous drug users, and multiple-partner heterosexuals. One notable finding that appears to characterize all these groups is that compared with lower risk populations, most strategies had weaker effects for these high-risk populations. For instance, groups explicitly including men who have sex with men, intravenous drug users, partners of intravenous drug users, and multiple-partner heterosexuals generally showed weaker negative effects of normative arguments (three out of four interactions were statistically significant), threat-inducing arguments (three out of four interactions were statistically significant), and interpersonal skills training (two out of three available interactions were statistically significant). Actually, interpersonal skills training had a significant positive effect when the condition included partners of intravenous drug users. The positive effects of attitudinal arguments, self-management skills training, and HIV counseling and testing were also weaker in these high-risk groups, with the exception of men who have sex with men. Further, attitudinal arguments were less effective when the samples included men who have sex with men but more effective when the samples included partners of intravenous drug users, and information was more effective when intravenous drug users were excluded rather than included. Of importance, the only strategy consistently associated with more positive effects when conditions included high-risk participants was the provision of condoms as part of the intervention.
The last section of presents the effects of each strategy on change in condom use as a function of the level of past condom use. As suggested by most of the analyses of risk factors, low condom use as a risk factor moderated the impact of some of the strategies (see ). Although consistent with Prochaska et al.’s (1992)
predictions, the beneficial effects of self-management skills training were smaller among higher condom users than among low users; contrary to their predictions, the influence of attitudinal arguments and information did not vary significantly as a function of condom use. In addition, there were significant negative effects of interpersonal skills and condom provision when condom use was either moderate or high.
Analysis of interactions between intervention strategies and intervention setups
We were also interested in evaluating potential interactions between the strategies used in an intervention and characteristics of the intervention setup. The relevant fixed-effects analyses are summarized in , organized by (a) setting (clinical, school, or community), (b) use of audiovisual media, and (c) presentation to groups (vs. individuals). Again, apparent differences in simple effects were interpreted only when accompanied by a significant interaction.
As can be seen from the first three panels, all intervention strategies but condom use skills training had stronger effects in clinical than other settings. The stronger effects included lesser change in response to normative arguments, threat-inducing arguments, and interpersonal skills training, as well as greater change in response to information, behavioral skills arguments, condom provision, self-management strategies, and HIV counseling and testing. In addition, attitudinal arguments, which had favorable effects in nonclinical settings, had a reverse effect in clinical contexts.
We next compared intervention strategies for school and nonschool settings. As judged by the significant interactions in the last column of , behavioral skills arguments and threat-inducing arguments both had less impact in schools than in other places. Notably, however, normative arguments and condom use skills training had significant positive effects only in schools. When the setting was not a school, normative arguments continued to have the previously reported reverse effect and condom use skills training had a nonsignificant effect.
With respect to community settings, the effects of information, behavioral skills arguments, threat-inducing arguments, interpersonal skills training, and self-management skills training, which were significant in noncommunity settings, were nonsignificant when the intervention was conducted in the community. Normative arguments had a significant negative effect in community settings, although the effect was weaker than the one in noncommunity settings. HIV counseling and testing continued to have a positive effect in community settings, although it was smaller in size relative to the one in noncommunity settings.
The second to last panel in presents the effects of playing a video- or audiotape. As can be seen, playing a tape was associated with an increased positive impact of attitudinal and behavioral skills arguments and HIV counseling and testing, as well as with increased negative effects of normative arguments and interpersonal skills training. In contrast, the favorable effects of self-management skills training were stronger when the intervention did not include a tape, and the provision of condoms had a positive effect when no video was used but a negative effect when a video was used.
Finally, we analyzed whether the use of group sessions as part of the intervention coincided with increases or decreases in the effects of different intervention strategies. As seen from the last panel of , attitudinal arguments, information, self-management skills training, and HIV counseling and testing were more effective when the intervention included group sessions, whereas behavioral skills arguments and condom use skills training were more effective when the intervention did not include group sessions. Finally, normative arguments had stronger negative effects during group than individual sessions.
We also examined the possibility that other participant and intervention factors could moderate behavior change and also be responsible for the outcomes. First, we regressed d. for behavior on the participant and intervention variables in that we had not previously analyzed. As could be observed from the fixed-effects simple regressions, change in condom use was positively associated with percentage of high school graduates (β = .13, p < .001, k = 83); city population (β = .37, p < .001, k = 180); rate of HIV infection at pretest (β .42, p < .001, k = 50); and face-to-face presentation of the intervention (β = .12, p < .001, k = 200). Also, change in condom use correlated negatively with inclusion of participants with a history of STIs (β = −.16, p < .001, k = 200); inclusion of college students (β = −.12, p < .001, k = 200); and inclusion of middle and high school students (β = −.33 and −.12, respectively,p < .001 and k = 200 in both cases).
We also analyzed other associations with methodological features of the studies. These analyses revealed significant positive associations of behavior change with (a) the use of within-subject designs (β = .18, p < .001, k = 200); (b) random assignment of participants to conditions (β = .29, p < .001, k = 200); (c) amount of payment (β = .05, p < .05, k = 200); (d) number of days between the intervention and the posttest (β = .09, p < .001, k = 191); (e) the use of a theory-based intervention (β = .10, p < .001, k = 200); (f) targeting interventions to specific genders (β = .11, p < .001, k = 200); and (g) self-selection bias (β = .13, p < .001, k = 200). Moreover, change in condom use correlated negatively with (h) the use of formative research (β = −.12, p < .001, k = 200) and (i) attrition (β = −.07, p < .001, k = 111, k = 200). However, the negative effect of using formative research became nonsignificant (β = −.12, ns) when we reran that predictor in a multiple regression including all the methodological and population predictors entered simultaneously.
Because these supplementary analyses identified a number of factors that influence behavior change, we reran the analyses in – to ensure that the described effects were not due to the association of the population and intervention characteristics we analyzed with other methodological features of this study. Education, pretest HIV infection rates, and attrition could not be introduced owing to low report of these factors. However, introducing the other methodological variables in did not alter the patterns of findings we discussed.
The analyses in suggest that arguments designed to improve attitudes and behavioral skills in favor of condom use increase condom use across passive and active interventions. However, these analyses cannot confirm that these strategies have an impact because they affect the mediator they are supposed to affect. For example, it is unclear thus far whether the interventions designed to improve attitudes and behavioral skills actually managed to do so. In addition, attitudinal arguments convey not only that “using condoms is good” but also that “the communicator thinks that using condoms is good.” Consequently, the impact of attitudinal arguments on condom use could be mediated by changes in norms instead of changes in attitudes. Similarly, hearing a message about protection from a disease could spontaneously arouse anxiety, in which case perceived threat could be the mediator as well.
Two caveats are necessary when considering the use of path analyses in meta-analysis. There is pressure both to maximize the inclusion of effect sizes and to maintain the included effect sizes across analyses (avoiding pairwise deletion procedures). For example, because we concluded that attitudinal arguments were effective on the basis of an analysis of 200 conditions, the mediational analyses should include those 200 effects. This strategy, however, is complicated by the fact that not all studies measured the same variables, and data on potential mediators are much less frequent than data on condom use itself (see ). Therefore, to maintain the original 200 units while including the available data on a particular mediator, one must resort to pairwise deletion procedures, which often produce nonpositive definite matrices (Shadish, 1996
In light of the complications involved with the study of mediation in meta-analysis, several approaches were explored. First, we attempted to fit models to a matrix that included, in addition to condom use, the indicators for all the intervention strategies in and and all psychological variables in . These models yielded impossible solutions and were therefore discarded. Next, we proceeded to fit models to smaller matrices. Of the various possibilities, we chose to report models that would parallel the analyses in and . These models included the indicator variable for the strategy being considered, the likely mediator for that strategy, and change in condom use, plus the indicators for all other strategies in and . However, the matrices involving normative arguments and change in norms as well as threat-inducing arguments and either perceived risk or threat were non-positive definite, which led us to analyze the mediation of only the strategies that had favorable effects on condom use. The analyses we report were estimated using maximum likelihood methods and the lowest N
in pairwise deletion matrix. Sobel (1982)
tests were calculated and are presented along with the path diagrams in –. For the sake of simplicity, these path diagrams show only the paths relevant to the strategy that is the focus of each panel, even when all the models included the predictors in and , depending on whether passive or active strategies were analyzed.
Figure 2 Path analyses to determine the mediating effects of change in specific psychological variables on changes in condom use among passive interventions. A: Effects of attitudinal arguments. B: Effects of behavioral skills arguments. Both models also included (more ...)
Figure 4 Path analyses to determine the mediating effects of change in specific psychological variables on changes in condom use as a function of active strategies among active interventions. A: Effects of self-management behavioral skills training. B: Effects (more ...)
summarizes the findings from the path analysis for the effects of attitudinal and behavioral skills arguments, which had significant, positive main effects across passive and active interventions. As shown in Panel A, the positive effects of attitudinal arguments on behavior change were mediated by changes in attitudes. The influence of attitudinal arguments, however, was also mediated by norms and perceived threat, which suggests various ways in which this type of strategy has an influence. In addition, the analyses in Panel B indicate that the possible influence of behavioral skills arguments on condom use change was mediated by control perceptions. However, as can be seen, the direct effect of behavioral skills arguments on behavior became nonsignificant only once we introduced changes in behavioral skills, and the mediation test suggested that behavioral skills was in fact a plausible mediator.
summarizes the effects of information, which was significant only in the context of active interventions (see ). As can be seen, the favorable effects of information on condom use were in fact mediated by increases in knowledge about HIV. The path model shows that the positive direct effect of information on behavior change became slightly negative once changes in knowledge were included.
Figure 3 Path analyses to determine the mediating effects of change in specific psychological variables on changes in condom use as a function of information among active interventions. This model also included all the strategies used in active interventions (see (more ...)
presents the effects of self-management skills training and HIV counseling and testing, which had significant effects in the sample of active interventions (see also ). As one might expect, the effects of self-management behavior skills training strategies were mediated by changes in both control perceptions and behavioral skills. The effects of HIV counseling and testing were less clear, which led us to conduct analyses with various potential mediators. These analyses (see , Panel B) indicated that HIV counseling and testing contributed to changes in skills. Changes in skills, in turn, correlated with changes in condom use, and their inclusion reduced the size of the direct effect from HIV counseling and testing to condom use.8
Assessment of Publication and Eligibility Biases
Of course, publication practices and eligibility criteria shape the sample of reports that are included in a meta-analysis. For instance, 12 of the examined reports contained insufficient statistics to derive the necessary effect sizes (see footnote 1). In addition, although we closely examined 15 unpublished reports, only one was ultimately included. To estimate potential biases in the report of findings and study inclusion, we examined the funnel plot of behavior change effect sizes (see ) and the normality of the distribution under examination (see ). If no bias is present, the plot takes the form of a funnel centered on the mean effect size, with smaller variability as the sample size increases. In the presence of publication bias, there is a distortion in the shape of the funnel. If the true effect size is zero and there is bias, the plot has a hollow in the middle. If the true effect size is not zero, the plot tends to be asymmetrical, having a large and empty section where the estimates from studies with small sample sizes and small effect sizes would otherwise be located. Following these guidelines, a subjective examination of the plot in thus suggests no publication or selection bias in our meta-analysis.
Funnel plot. Two effects with extremely large sample sizes were excluded to make the shape of the plot more apparent. These large sample groups had average effect sizes.
Normal quantile plot. The line on the diagonal indicates normality; the lines around the diagonal represent the 95% confidence interval around the normality line.
In addition to examining the funnel plot, we used the normal quantile plot method to uncover evidence of bias (Wang & Bushman, 1999
). In a normal quantile plot, the observed values of a variable are plotted against the expected values given normality. If the sample of effect sizes is from a normal distribution, data points cluster around the diagonal; if the sample of effect sizes is biased by publication practices or eligibility criteria, data points deviate from the diagonal (Wang & Bushman, 1999
). As can be seen from , the standardized behavior effect sizes followed a straight line and generally fell within the 95% confidence intervals of the normality line. This conclusion was supported by the fact that our findings remained unaltered after excluding the most extreme outliers from the sample of conditions (see the seven extreme observations in ). In sum, there was convincing evidence that even if one determined that a large number of studies have been kept in researchers’ file cabinets, inclusion of these studies would be unlikely to alter our conclusions about the effectiveness of HIV-prevention interventions.
The theoretical assumptions that we examined in this article constitute a general paradigm for health intervention, which has been used and advocated for a number of health problems, including smoking, unsafe dietetic practices, disease screening, and drug abuse. By testing these assumptions with the intervention literature from HIV prevention, our work provides the first and most comprehensive examination of models that are influential in many areas of health behavior change, as well as behavior change in general. In the following sections, we summarize our present empirical and theoretical contributions in light of relevant conceptualizations and prevention objectives.
Intervention Efficacy and Mediating Processes: Status of Theoretical Assumptions in Health- and HIV-Related Behavior
We conducted this meta-analysis with the idea of testing assumptions shaped by various models of behavior change. In the following sections, we comment on our findings’ support for each of the models’ premises, which are summarized in . For the first six models in the table, we verified whether (a) strategies targeting the theoretical causal variable effectively change behavior, (b) strategies targeting the theoretical causal variable influence changes in measures of it, (c) changes in measures of the theoretical variable influence behavior change, and (d) changes in measures of the theoretical variable mediate the effects of the strategy that targets it on behavior. (For the framing and stage models, however, only the first assumption applied, as the models make no specific claims about mediators.) When a majority of the applicable criteria (more than 50%) were met, we characterized support for the assumption as “good”; when only half of the applicable criteria were met, we characterized support for the assumption as “fair”; when less than half of the applicable criteria were met, we characterized support for the assumption as “poor.”
Summary of Support for Assumptions of Behavior-Change Theories
Theory of reasoned action Fishbein and Ajzen’s (1975
; Ajzen & Fishbein, 1980
) theory of reasoned action assumes that people’s actions are a function of their intention, which is in turn influenced by the attitude toward performing the behavior (i.e., the degree to which one has a positive vs. a negative evaluation of the behavior) and the subjective norm (i.e., the expectation that important others think that one should or should not perform the behavior). Consistent with the successful behavioral prediction achieved by this theory across studies and samples (see Albarracín et al., 2001
), the present meta-analysis suggests that arguments that tout condom use (attitudinal arguments) effectively increase behavior change across many populations and across passive and active interventions. This behavioral impact is mediated by changes in attitudes and also by changes in social norms (see , Panel A), implying that the attitudes of others (in this case, intervention facilitators) can simply exert desirable normative influences on the recipients. Such a mediation may be moderated by characteristics of the population, but we lacked the number of studies with attitude measures that would allow us to perform that test in this review.
Further, our meta-analysis also hints that the success of straight normative arguments describing social consensus for a behavior is contingent on the population one is targeting. Such attempts appear to instill reactance in most cases but are effective when the audience is under 21. However, this result does not imply that younger individuals are normatively driven whereas older ones are not. Instead, it appears to suggest that younger individuals do not perceive that making decisions based on social consensus is undesirable, whereas adults are more prone to try to act independently even when they cannot escape being influenced by norms—even if the influence ends up being a reaction against the norms.
Theory of planned behavior
According to Ajzen’s (1985) theory of planned behavior
, considering perceived behavioral control can improve the prediction of intentions and behavior. One important conclusion from the present meta-analysis is that even when measures of perceived control generally exert small direct effects on behavior (Albarracín et al., 2001
), arguments and training designed to teach behavioral skills are successful at changing behavior for most people using either passive or active interventions. Of course, one might argue that these strategies are not truly influencing control perceptions (see ) and that the key mediator is instead changes in actual behavioral skills. However, as shown in , the effects of self-management skills training were mediated by control perceptions in addition to actual skills.
Self-efficacy Bandura’s (1989
) social–cognitive theory is a general theory of self-regulatory agency, which proposes that perceived self-efficacy lies at the center of human behavior. According to this model, effective self-regulation of behavior and personal change requires that people believe in their efficacy to control their motivation, thoughts, affective states, and behaviors. In other words, people are unlikely to change unless they want to, believe they can, feel they will, and have the behavioral skills to actually change.
Because motivation, beliefs, perceptions of control, and actual skills are all implicated in Bandura’s model, support for the theories of reasoned action and planned behavior also constitutes support for social–cognitive theory. In addition, the effect of behavioral skills training—which was developed by psychologists in the domain of HIV prevention (Kelly, St. Lawrence, Betts, Brasfield, & Hood, 1990
; Kelly, St. Lawrence, Hood, & Brasfield, 1989
)—on changes in condom use permits an assessment of the viability of this model for HIV prevention and for behavioral change in general. In this regard, our meta-analysis suggests that self-management skills are essential to regulate condom use, whereas condom use skills are important for males and interpersonal skills are important for females who are strongly motivated to avoid unsafe sex with their intravenous drug use partners. Future research may develop training in additional skills and increase understanding of what makes certain skills useful for some people but not for others.
Information–motivation–behavioral skills model
Just like support for the theory of planned behavior renders support for Bandura’s (1989)
social–cognitive theory, our meta-analysis’ support for the theory of reasoned action, the theory of planned behavior, and Bandura’s model also renders support for J. D. Fisher and Fisher’s (1992
; J. D. Fisher, Fisher, Misovich, Kimble, & Malloy, 1996
; J. D. Fisher, Fisher, Williams, & Malloy, 1994
; W. A. Fisher et al., 1999
) assumption that information, motivation, and behavioral skills underlie behavioral change. The information–motivation–behavioral skills model, however, presents the additional assumption that the three components exert potentiating effects on each other. To this extent, the finding that information has positive influences on behavior only
when accompanied with active, behavioral strategies can be taken as evidence that the confluence of strategies is as important as the selection of each individual approach.
Protection motivation theory
Protection motivation theory emphasizes the cognitive processes that mediate health behavior change. Although Rogers (1975)
initially developed protection motivation theory to clarify the influence of fear appeals (Rogers, 1975
), the theory has been applied to health prevention more generally (Prentice-Dunn & Rogers, 1986
; Rogers, 1983
). Rogers (1975)
argued that people who confront external information about a disease (e.g., verbal persuasion, observational learning, and experience with a disease) engage in threat and coping appraisal (see also Prentice-Dunn & Rogers, 1986
). In the case of condom use, threat appraisal involves an evaluation of the factors that influence the probability of not using a condom (perceived barriers, such as decreases in physical pleasure) as well as the threat associated with not using a condom (perceptions of severity and vulnerability). Coping appraisal comprises judgments of the efficacy of a preventive response, as well as the assessment of one’s ability to successfully accomplish the adaptive response (i.e., self-efficacy). Threat appraisal and coping appraisal combine to form protection motivation, or the intention to perform the behavior, which then yields a behavioral response (Prentice-Dunn & Rogers, 1986
To the extent that this model advocates the use of fear appeals to induce threat appraisal, we can conclude that the results from our meta-analysis disconfirm it. In fact, no tested interactions between threat-inducing arguments and strategies that can increase threat coping (i.e., behavioral skills arguments, condom use skills training, interpersonal skills training, self-management skills training, and condom provision) yielded the predicted positive effect of threat appraisal plus coping (footnote 3), nor were threat-inducing arguments effective for a single population or intervention context.
Framing models Rothman and Salovey (1997)
have conceptualized the need for certain types of message frames for specific types of health behavior. When one is trying to get people to avoid a risk factor, a “loss,” fear-inducing frame appears effective. However, when one is trying to instill a proactive behavior, a “gain,” positive frame is more appropriate. To this extent, the model qualifies the protection motivation theory by specifying the conditions under which threat appeals will be influential.
In many ways, our finding that threat-inducing arguments have no positive influence whatsoever under any of the conditions that we examined is consistent with Rothman and Salovey’s (1997)
model. Conceivably, people who are trying to implement a behavior such as condom use may need “gain” frames of the type that attitudinal messages normally present. Correspondingly, the use of fear may be more appropriate in the context of abstinence from a behavior (e.g., sexual abstinence) or detection of a risk (e.g., getting an HIV test), because such behaviors are similar to the ones Rothman and Salovey describe as benefiting from “loss” frames.
Another direction for future research concerns understanding the mechanisms that make certain frames more effective for certain behaviors. Recent research appears to suggest that mere fit between the chronic motivation of a recipient and the motivation a given message induces increases persuasion because of the intrinsic value of “fit” (Higgins, 2000
). Even when our results for the effects of threat are suggestive of such a direct mechanism, future experimental work may be able to identify the affective mediation of value for fit.
Health belief model
The health belief model is an expectancy–value model developed during the 1950s by a group of social psychologists in the United States Public Health Service in an effort to understand the failure of people to participate in healthscreening and disease-prevention programs (Rosenstock, 1960
). The model has since been adapted to explore a number of health domains and to include all types of preventive actions (M. H. Becker, 1974
). In the domain of HIV prevention, the health belief model predicts that people will use condoms when (a) they believe HIV poses a threat (perceived threat = perceptions of susceptibility, which are judgments of risk of contracting HIV, and perceptions of severity, which involve assessments that contracting HIV would be serious); (b) they expect considerable benefits from the behavior and do not foresee barriers to it; and (c) they feel capable of succeeding and actually performing the behavior (Janz & Becker, 1984
; Rosenstock et al., 1994
Like the theory of reasoned action, the theory of planned behavior, social–cognitive theory, and the information–motivation–behavioral skills model, the health belief model incorporates various psychological variables that our meta-analysis shows are influential. After all, the relevance of attitudes, control perceptions, information, and behavioral skills is clear from the findings. However, even when increases in perceived threat were positively associated with behavior change (see ), no threat-inducing argument had any positive behavioral effect whatsoever. As a result, the most distinctive prediction of the health belief model and protection motivation theory was disconfirmed.
Stage models of change
Several models assume that behavioral change is a multiple-stage process that starts at the point of not performing the behavior at all and ends with the incorporation of the new actions into routines. The transtheoretical model (Prochaska et al., 1992
) and the AIDS risk reduction model (Catania et al., 1990
), as well as Bandura (1997)
, all attempt to define a sequence of stages that go from behavior initiation to adoption to maintenance. Successful interventions should be the ones that focus on the particular stage of change the individual is experiencing and facilitate forward progression (Prochaska et al., 1994
Some stage-of-change conceptualizations have made more specific predictions about the types of interventions that are likely to be more effective depending on the stage of change of recipients (Prochaska et al., 1992
). Presumably, knowledge of HIV/AIDS or more general risk perceptions may serve to prompt change when people are not yet performing the behavior, but may not elicit movement beyond the initial stage. Similarly, inducing favorable attitudes may be important at the very initial stages but not when people are already performing the behavior and are aware of its outcomes. People who have already adopted the idea of change and begun to perform the behavior may need new skills to foster complete success (see Bandura, 1994
; Schwarzer, 1992
The analysis of the behavioral effects resulting from the various intervention strategies we synthesized (see and ) as a function of level of initial condom use has important implications for Prochaska and colleagues’ (1992)
predictions. On the one hand, consistent with their framework, our findings suggest that behavioral skills arguments and self-management skills training are more important later than earlier in the change process, which supports their contentions. On the other hand, contrary to Prochaska et al.’s expectations, attitudinal and informational arguments were equally important for both inconsistent and more consistent condom users. From this point of view, our data suggest that everything
might be more effective when people have previously engaged in condom use, rather than supporting the specific predictions made by Prochaska and his colleagues.
Decision tree for selection based on the array of available preventive interventions
By identifying strategies that change HIV risk behavior, this meta-analysis can help guide the design of effective HIV-prevention interventions. However, for the findings to have an impact, such guidance should be communicated to practitioners in a clear way. With simplicity in mind, we summarized the study’s findings that are most relevant from an epidemiological perspective in a series of decision trees.
The first decision tree (see ) presents courses of action when one needs to decide whether to deliver an intervention at all. Because control groups had little effect on condom use (d. = 0.08; see ), not implementing interventions seems justified only when one is satisfied with the current level of condom use of a target audience. In contrast, because the use of any intervention strategy appears to increase condom use in at least one population, interventions must be implemented when one intends to increase condom use. Of the available strategies, however, whenever possible, practitioners should first consider approaches that involve clients behaviorally, rather than merely presenting passive audiences with persuasive arguments.
Decision tree 1 (initial decisions).
Readers may wonder how much of a difference interventions might make if applied to a given audience. Considering the findings in , the d
. obtained for active interventions represents a 1.98 to 1 likelihood (1.10 to 1 for passive interventions) that participants will have increased their condom use 3 months after the intervention. Moreover, given an average condom use of 32.20% over total intercourse occasions (SD
= 20.56; see ), a d
. of .38 for the active intervention implies a mean increase of 7.8% of the time over total condom use occasions. Also, given an initial group in which 36% of people are using condoms at least sometimes (see ), a d
. of .38 implies that an additional 17% will use condoms at least sometimes following the intervention. Correspondingly, such an increase as a result of active interventions when the average HIV seroprevalence is 16.48 (SD
= 27.15) is suggestive of great public health gains as well as the prevention of significant social and financial losses for the affected nations (for similar conclusions, see Kahn, Kegeles, Hays, & Beltzer, 2001
; Pinkerton et al., 2000
; Sweet, O’Donnell, & O’Donnell, 2001
This meta-analysis also has implications for the way in which intervention content is selected and interventions are framed. To begin with, our results suggest that HIV practitioners aiming to motivate audiences to increase condom use are more likely to succeed if they avoid aversion- or fear-inducing approaches. Presumably, these strategies induce avoidance processing and are mainly effective when people must simply abstain from a behavior to protect their health (Rothman & Salovey, 1997
). Further, our findings permit conclusions about what interventionists should do. Because active interventions are generally more effective, they should be preferred to passive ones. If one can implement only a passive intervention, it makes sense to select attitudinal and behavioral skills arguments and also to distribute condoms to the audience. If, however, one is in a position to deliver an active intervention, the presentation of information and behavioral skills arguments in combination with self-management training or HIV counseling and testing seems advisable.
A comment on the effects of condom provision
The provision of condoms to communities also appears to be an effective way of intervening to curb HIV infection. There are at least two likely reasons for the effects of condom provision we uncovered in this meta-analysis. First, the availability of resources required for a behavior ought to enable the performance of that behavior. Thus, people who have a condom handy at a particular instance are more likely to use that condom when the opportunity of sexual intercourse arises. In addition, the availability of condoms can produce more permanent psychological changes under certain conditions. In particular, social psychologists have demonstrated that behavioral practices can alter people’s attitudes and subsequent behaviors. People who are asked about their attitudes, for example, are likely to reflect on whether they recently performed a behavior that suggests a particular attitude (Bem, 1965
; see also Albarracín & Wyer, 2000
). In the domain of condom use, individuals who wonder about their attitudes about condom use may try to recall whether they recently used condoms. To the extent that they infer a favorable attitude about condom use from their recall of recent condom use, the availability of condoms may well foster a behavior that later induces important inferential changes capable of eliciting consistent practices (e.g., self-initiated acquisition of condoms).
Effects of Types of Strategies Across Different Populations
Another contribution of this meta-analysis to understanding HIV preventions for specific populations concerned clarifying interactions between the various intervention strategies and characteristics of the recipients. These interactions were fairly complex and are summarized in , with particular attention to strategies that were equally effective for two groups, effective for two groups but more effective for one of the two, or effective for a single group. The first panel of the table summarizes the effects of specific strategies across demographic groups, and the second, as a function of inclusion of various behavioral risk groups.
Summary of Findings Concerning Intervention Strategies
Effectiveness of intervention strategies across genders
With the exception of condom provision, which was effective for both males and females, all strategies had different impact for males than for females (see ). For example, even when self-management skills training and HIV counseling and testing were effective across genders, these effects were all stronger for females than for males. Further, whereas attitudinal arguments and information were linked to increased condom use among females alone, behavioral skills arguments and training in condom use skills were linked to increased condom use among males alone. Thus, although these findings point to numerous strategies that can be effective for women (e.g., self-management skills training), they suggest that men are the ones who most benefit from condom use skills training approaches. As Logan et al. (2002)
concluded, investments in interventions that are effective for women are still imperative.
Effectiveness of intervention strategies across ages
Just as gender moderated the impact of different intervention strategies, so did age (see ). Behavioral skills arguments and HIV counseling and testing were associated with increased condom use only among populations with an average age over 21 years. Further, even when self-management skills training was effective regardless of age, the effect was stronger when the audience averaged over 21 years. However, people under 21 were positively influenced by normative arguments that others support condom use. This finding is not surprising given the developmental literature on the influence of peers for adolescents (e.g., Atwater, 1988
; Dusek, 1996
; Sprinthall & Collins, 1995
) but is nevertheless the only instance in which we found a favorable effect of the use of this type of argument. In the future, researchers should investigate other ways in which persuasive communications create norms (for a recent review on normative influences, see Prislin & Wood, 2005
), such as analyzing the effects of different communicators and intervention facilitators.
Effectiveness of intervention strategies across ethnic groups
During the last decade, concerns that ethnic minorities and disadvantaged populations are at increased risk for HIV infection have increased. Even when this concern has motivated the testing of interventions with minority groups (e.g., Raj et al., 2001
; Sterk, Theall, & Elifson, 2003
; St. Lawrence, Wilson, Eldridge, Brasfield, & O’Bannon, 2001
; Toro-Alfonso, Varas-Díaz, & Andújar-Bello, 2002
) and even when ethnicity has been examined as a moderator of intervention effectiveness (see Albarracín et al., 2003
; B. T. Johnson et al., 2003
), to our knowledge, there has been no research comparing the effects of the various strategies available for program implementation as applied with participants with European and African backgrounds.
Our meta-analysis was intended to reduce past limitations of the prior knowledge about the generalizability of intervention strategy effectiveness across minority and majority populations. Its findings suggest that samples with a greater number of people with African backgrounds show more behavior change in general and that this change is attributable to behavioral skills arguments, self-management strategies, and HIV counseling and testing. However, condom provision appears more effective for populations from European backgrounds (see ). These findings are intriguing and suggest that extensive empirical and theoretical work on intervention effectiveness across ethnic groups is warranted.
Effectiveness of condom provision for high-risk groups
A quick examination of highlights the finding that distributing condoms was more effective when the sample included groups possessing a variety of behavioral risk factors. Providing condoms to participants was effective only when samples included men who have sex with men, intravenous drug users, partners of intravenous drug users, and multiple-partner heterosexuals.
Effectiveness of intervention strategies when men who have sex with men are included
Leaving condom provision aside, samples including men who have sex with men changed more in response to interventions than other samples (see ). However, this group was generally insensitive to the type of intervention strategy that was used, with the exception of greater behavior change in response to condom provision and lesser change in response to attitudinal arguments (see ). Future research might concentrate on improving the efficacy of other techniques that are efficacious for other at-risk populations.
Effectiveness of intervention strategies when intravenous drug users are included
Intravenous drug use continues to pose substantial HIV risks, and it is no surprise that researchers and practitioners need preventive tools for this group. In this regard, our findings ( and ) indicate that attitudinal and behavioral skills arguments work as well when the groups contains intravenous drug users as when they do not, and that condom use skills training, in addition to condom provision, should be strategies of choice for this population. Although our conclusions are similar to Prendergast et al.’s (2001)
conclusion that more focused interventions are better, they provide more information concerning the necessary focus in the area of condom use.
Effectiveness of intervention strategies when partners of intravenous drug users are included
Perhaps our most striking finding concerning behavioral intervention strategies is that interpersonal skills training was associated with successful increases in condom use only when the sample included partners of intravenous drug users. Because of the predominantly female composition of this sample, this result may not be surprising. After all, interpersonal skills training has been advocated for situations in which using a condom depends on obtaining the agreement of the sexual partner (e.g., Amaro, 1995
; el-Bassel & Schilling, 1992
; St. Lawrence et al., 2001
). In this regard, female partners of intravenous drug users probably constitute the single population in which sexual assertiveness is essential to avoid HIV.
In addition to the benefits of interpersonal skills training among partners of intravenous drug users, this group also presented increases in condom use when attitudinal arguments were presented. This finding is consistent with the present similar effect of attitudinal arguments among females in general and with earlier reports that women’s intentions to use condoms are more influenced by attitudes than are men’s (Albarracín, Kumkale, & Johnson, 2004
). Instead, behavioral skills arguments had similar effects when conditions included this group and when they did not.
Effectiveness of intervention strategies when multiple-partner heterosexuals are included
The practices of multiple-partner heterosexuals represent a major health problem, particularly because increasing HIV rates among women are attributable to sexual infection (CDC, 2003
). In addition to increasing condom use with condom availability, this group manifested behavior change when attitudinal arguments and condom use skills training were provided. Future research might explore the reasons that favor these strategies among multiple-partner heterosexuals and perhaps identify ways to make other strategies more effective for this group as well.
Effectiveness of intervention strategies when initial condom use is low
Of course, regardless of the specific risk behavior of a sample, the key objective of condom-use-promoting interventions is to increase condom use among individuals who presently fail to use condoms. As presented in detail in and summarized in , behavioral skills arguments and self-management skills training were associated with most beneficial effects among higher condom users, even when these effects were also present among low condom users. In addition, our analyses indicated that information, attitudinal arguments, and HIV counseling and testing were associated with favorable effects across the board. Thus, continued efforts to increase testing appear justified, not only for HIV treatment purposes but also for its influence on behavior change.
Decision trees for the design of interventions for specific populations
The second and first decision trees we constructed represent the differences in the implementation of passive and active interventions for different groups of participants ( and ). For example, as shown in , this synthesis supports peer-oriented approaches for adolescents and children but discourages the application of normative arguments for all other groups. As another example, practitioners may strive to make condoms available to groups that reap high benefits from the mere provision of condoms. Thus, funding for HIV prevention among men who have sex with men, intravenous drug users, female partners of intravenous drug users, and multiple-partner heterosexuals must go beyond dispersing two or three condoms at a time to ensuring a continued supply of condoms when individuals leave the intervention setting.
Decision tree 2 (passive interventions). MSM = men who have sex with men; IDUs = intravenous drug users; PIDUs = partners of intravenous drug users; MPHs = multiple-partner heterosexuals; LCUs = low condom users.
Decision tree 3 (active interventions). MSM = men who have sex with men; IDUs = intravenous drug users; PIDUs = partners of intravenous drug users; MPHs = multiple-partner heterosexuals; LCUs = low condom users.
Similarly, the selection of active strategies should be contingent on the characteristics of the target audience (see ). Possibly because most men are still in charge of buying, keeping, and applying condoms, men tend to benefit from the condom use skills training to a greater extent than women. Given this fact, practitioners may wish to implement strategies to increase women’s responsibility over condom use (e.g., popularization of the female condom) before expanding programs to teach condom use skills to women. Further, although men and women both benefit from receiving condoms, not all age and ethnic groups do. Specifically, condom provision is influential only for recipients under 21 and for people from European backgrounds. Thus, even when research has yet to uncover the mediating mechanisms driving these differences, this meta-analysis supports consistent decisions whenever possible.
We expect that the decision aids in and will be updated as the HIV intervention literature grows in size and allows researchers to understand higher order interactions among different demographic and behavioral risk variables. However, the present results may increase the flexibility of practitioners who want to effectively target specific populations and previously had only general recommendations about how to structure a preventive program.
Effects of Types of Strategies Across Intervention Setups
Perhaps the most important contribution with respect to methods is the finding that the intervention setup moderates the effectiveness of particular intervention strategies. Some of these effects must be understood as being derived from a rather exploratory strategy, but nevertheless they provide key information for the design of future campaigns. First, when interventions are delivered in clinical settings, information, behavioral skills arguments, condom provision, self-management strategies, and HIV counseling and testing seem optimal. Second, when interventions are introduced in schools (see also findings for recipients under 21), normative arguments and condom use skills training work particularly well, whereas behavioral skills arguments are substandard relative to nonschool settings. Third, the only effective community interventions in our meta-analysis were the ones implementing HIV counseling and testing, even when this strategy was still less effective in community than in noncommunity settings.
With respect to the use of audiovisual media and group sessions, using media was linked to an increased impact of attitudinal and behavioral skills arguments but to decreased effects of information and self-management skills training, which seem more effective when more time is spent in a personal interaction with the intervention facilitator. Moreover, even though behavioral skills arguments and condom use skills training were more effective when the intervention entailed individual sessions with the recipients, the inclusion of group sessions improved effectiveness when interventions included attitudinal arguments, information, self-management skills training, and HIV counseling and testing.
Finally, the impact of intervention setup, media, and session format brings attention to the processes of reception and attention in HIV prevention. Without a doubt, the effectiveness of any program is contingent on exposure to and understanding of that program (McGuire, 1968
). However, because research on these aspects has been practically nonexistent in the domain of HIV prevention, efforts should be allocated to understanding the mechanisms that make certain setups or media more or less effective as a function of the intervention content. Our meta-analysis is only a first step in such an endeavor.
Limitations of the Present Meta-Analysis
There are several limitations of this study. These limitations concern the correlational nature of the results, the validity of condom use reports, the impossibility of analyzing more complex interactions, the selection of behavioral measures, and the generalizability of the current conclusions to the sample of studies and to the population of potential studies on the topic.
Correlational nature of many of the results
An obvious limitation of our work is the correlational nature of the analyses. Although the assignment to interventions and control groups was often conducted at random, the specific selection of intervention strategies is contingent on the preferences of particular researchers, which can covary with other characteristics of the studies, the populations, or the methods used. Fortunately, however, this limitation is mitigated by the use of mediation analysis and the various controls implemented to rule out spurious findings.
Factors related to measures of condom use
The current results assume that self-reported behaviors are accurate reflections of individuals’ actual behaviors. Although the reliability of self-reports of sexual behavior has been established by the use of interpartner reports (Coates et al., 1986
; Jaccard & Wan-Choi, 1995
; McLaws, Oldenburg, Ross, & Cooper, 1990
) and infection rates (CDC, 1997
; Winkelstein et al., 1987
), the accuracy of self-reports varies largely with the population and the behavior. For example, if groups have particularly high alcohol or drug consumption rates, reports by their members could be less reliable than reports by other persons. Similarly, self-reports could have different reliability for frequent or infrequent behaviors, depending on the standards people use to assess sexual events or on temporal factors, such as primacy or recency (for a review of such phenomena, see Wyer & Srull, 1989
). In view of these possibilities, the extent and nature of self-report biases under different circumstances should be determined more precisely in the future.
Impossibility of analyzing more complex interactions
One important objective of this article was to analyze the extent to which intervention strategies impact different populations. Despite the contribution of these findings, the reality of intervention effectiveness may be even more complex. To that extent, as new findings accumulate in the literature, researchers could consider higher order interactions that our meta-analysis was not well suited to study.
Limited data about HIV-positive individuals
The same problem that prevented us from examining higher order interactions restricted consideration of intervention effectiveness among HIV-positive individuals, those capable of transmitting HIV. We reported specifically the association between HIV-infection rates at the point of the pretest and behavior change (β = .42, p < .001, k = 50) based on the joint consideration of experimental and control groups. This finding is important because it suggests that HIV-positive people generally increase their condom use. However, seroprevalence data for intervention groups were available only in 22 cases, which severely limited the possibility of analyzing the effectiveness of different intervention components as a function of this factor. In fact, a previously unreported analysis of behavior change as a function of seroprevalence and intervention type could be conducted only for attitudinal arguments, fear-inducing arguments, and condom use provision. Of these three intervention components, only attitudinal arguments had a significant interaction with seroprevalence (Q1 = 15.84,p < .001). This interaction reflected a favorable association between behavior change and seroprevalence when attitudinal arguments were absent (β = .71, p < .001), accompanied by a negative association between these two variables when attitudinal arguments were present (β = −.37,p < .001). Unfortunately, an understanding of this interaction may become possible only when more reports are available for a future meta-analysis of the influence of seroprevalence on intervention effectiveness.
Selection of behavioral measures
As described earlier, a commonly used measure of condom use was to obtain a percentage of condom use occasions over number of intercourses. Because the epidemiological impact of change depends not only on the amount of change but also on the baseline level of condom use (see Fishbein & Pequegnat, 2000
; J. B. Jemmott & Jemmott, 2000
; Pinkerton & Abrahamson, 1993
; Schroeder, Carey, & Vanable, 2003
), our meta-analysis incorporated a measure of initial levels of condom use that we introduced in some analyses. Even this treatment, however, should be complemented with a variety of behavioral and biological outcome measures that are likely to become common practice in the years to come.
Further mediation analyses
Another limitation of our metaanalysis is that despite the use of mediation analyses, the number of effect sizes available for the mediators did not allow for separate consideration of some potentially distinct constructs. For example, to increase the power of some analyses, change in attitudes was combined with change in intentions, as were change in perceived behavioral control and change in self-efficacy. Clearly, attitudes and intentions reflect different levels of behavioral commitment, and perceived behavioral control has been suggested to be different from self-efficacy (Armitage & Conner, 1999
; Armitage, Conner, & Loach, 1999
; Povey, Conner, & Sparks, 2000
; but see Ajzen, 2002
). In light of these subtleties, future reviews as well as primary research should examine other mediational models.
Generalizability to the sample of studies and to the population of all possible studies
The current findings from the present meta-analysis are probably the most generalizable to date. In particular, the results from the random-effects mean comparisons suggest that HIV-prevention interventions are effective no matter what sample of the potential universe of studies one might consider. The described analyses of the effects of specific intervention strategies, however, were obtained with fixed-effects models. Thus, even when the patterns did replicate when we reran the findings in – using random-effects, the number of significant results dropped considerably. We hope that future research will provide a sufficiently large number of effect sizes to estimate the population variance more precisely and thus reconcile the discrepancies between the fixed- and random-effects findings.
Efforts to prevent the spread of HIV have united scholars in psychology, sociology, education, anthropology, public policy, law, epidemiology, and medicine. A clear example of this joint expertise was the NIH (1997)
consensus development conference, which recommended the dissemination of behavioral interventions to reduce HIV/AIDS, lifting legislative restrictions on needle-exchange programs and effective prevention programs for youth, and halting the erosion of funding for drug abuse treatment programs. In addition, the panel recommended the development of new research on at-risk groups, such as young people, gay individuals, ethnic minorities, and women, in the hope of reducing one of the most pressing public health problems in the world. We hope that the results from this meta-analysis will contribute to precise knowledge about intervention effectiveness and make preventive programs more effective for the people who need them the most.
The research was supported by Grant K01-MH01861 from the National Institute of Mental Health and facilitated by Grants R03-MH58073 and R01-NR08325 from the National Institutes of Health. We thank Ece Kumkale, Cynthia Klein, Penny S. McNatt, Amy L. Mitchell, and G. Tarcan Kumkale for their invaluable assistance organizing this project. We also thank Matthew Lindberg and the project assistants during the years 1997–2004, along with Rick Brown, Ian Handley, Blair T. Johnson, and G. Tarcan Kumkale for detailed comments on an earlier version of this article.
Dolores Albarracín, Department of Psychology, University of Florida.
Jeffrey C. Gillette, Department of Psychology, University of Florida.
Allison N. Earl, Department of Psychology, University of Florida.
Laura R. Glasman, Department of Psychology, University of Florida.
Marta R. Durantini, Department of Psychology, University of Florida.
Moon-Ho Ho, Department of Psychology, McGill University, Montreal, Quebec, Canada.
References marked with an asterisk indicate studies included in the meta-analysis.
- Ajzen I. From intentions to actions: A theory of planned behavior. In: Kuhi J, Beckmann J, editors. Action-control: From cognition to behavior. Heildelberg, Germany: Springer; 1985. pp. 11–39.
- Ajzen I. The theory of planned behavior. Organizational Behavior and Human Decision Processes. 1991;50:179–211.
- Ajzen I. Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior. Journal of Applied Social Psychology. 2002;32:665–683.
- Ajzen I, Fishbein M. Understanding attitudes and predicting social behavior. Englewood Cliffs, NJ: Prentice Hall; 1980.
- Ajzen I, Madden TJ. Prediction of goal-directed behavior: Attitudes, intentions, and perceived behavioral control. Journal of Experimental Social Psychology. 1986;22:453–474.
- Albarracín D, Fishbein M, Middlestadt S. Generalizing behavioral findings across times, samples, and measures: A study of condom use. Journal of Applied Social Psychology. 1998;28:657–674.
- Albarracín D, Johnson BT, Fishbein M, Muellerleile P. Reasoned action and planned behavior as models of condom use: A meta-analysis. Psychological Bulletin. 2001;127:142–161. [PubMed]
- Albarracín D, Kumkale GT, Johnson BT. Influences of social power and normative support on condom use decisions: A research synthesis. AIDS Care. 2004;16:700–723. [PubMed]
- Albarracín D, McNatt PS, Klein C, Ho R, Mitchell A, Kumkale GT. Persuasive communications to change actions: An analysis of behavioral and cognitive impact in HIV prevention. Health Psychology. 2003;22:166–177. [PubMed]
- Albarracín D, Wyer RS. The cognitive impact on past behavior: Influences on beliefs, attitudes and future behavioral decisions. Journal of Personality and Social Psychology. 2000;79:5–22. [PubMed]
- Allen S, Serufilira A, Bogaerts J, Van de Perre P, Nsengumuremyi F, Lindan C, et al. Confidential HIV testing and condom promotion in Africa. JAMA. 1992;68:3338–3343. [PubMed]
- Allen S, Tice J, Van de Perre P, Serufilira A, Hudes E, Nsengumuremyi F, et al. Effect of serotesting with counselling on condom use and seroconversion among HIV discordant couples in Africa. British Medical Journal. 1992;304:1605–1609. [PMC free article] [PubMed]
- Amaro H. Love, sex, and power. Considering women’s realities in HIV prevention. American Psychologist. 1995;50:437–447. [PubMed]
- Armitage CJ, Conner C. Distinguishing perceptions of control from self-efficacy: Predicting consumption of a low-fat diet using the theory of planned behavior. Journal of Applied Social Psychology. 1999;29:72–90.
- Armitage CJ, Conner C, Loach J. Different perceptions of control: Applying an extended theory of planned behavior to legal and illegal drug use. Basic and Applied Social Psychology. 1999;21:301–316.
- Asamoah-Adu A, Weir S, Pappoe M, Kanlisi N, Neequaye A, Lamptey P. Evaluation of a targeted AIDS prevention intervention to increase condom use among prostitutes in Ghana. AIDS. 1994;8:239–246. [PubMed]
- Atwater E. Adolescence. Englewood Cliffs, NJ: Prentice Hall; 1988.
- Baldwin JI, Whiteley S, Baldwin JD. Changing AIDS-and fertility-related behavior: The effectiveness of sexual education. Journal of Sex Research. 1990;2:245–262.
- Bandura A. Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice Hall; 1986.
- Bandura A. Perceived self-efficacy in the exercise of control over AIDS infection. In: Mayes VM, Albee GW, Schneider SF, editors. Primary prevention of AIDS: Psychological approaches. London: Sage; 1989. pp. 128–141.
- Bandura A. Social-cognitive approach of thought to the exercise of control over AIDS infection. In: DiClemente JR, editor. Adolescents and AIDS: A generation in jeopardy. Newbury Park, CA: Sage; 1992.
- Bandura A. Social cognitive theory and control over HIV infection. In: DiClemente R, Peterson J, editors. Preventing AIDS: Theories and methods of behavioral interventions. New York: Plenum Press; 1994. pp. 25–59.
- Bandura A. Self-efficacy: The exercise of control. New York: Freeman; 1997.
- Baron RM, Kenny DA. The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology. 1986;51:1173–1182. [PubMed]
- Barros T, Barreto D, Pérez F, Santander R, Yépez E, Abad-Franch F, Aguilar M. Un modelo de prevención primaria de las enfermedades de transmisión sexual y del VIH/SIDA en adolescentes [A primary prevention model for sexually transmitted diseases and HIV/ AIDS in adolescents] Revista Panameña de Salud Pública. 2001;10:86–94. [PubMed]
- Basen-Engquist K. Evaluation of a theory-based HIV prevention intervention for college students. AIDS Education and Prevention. 1994;6:412–424. [PubMed]
- Becker BJ. Synthesizing standardized mean-change measures. British Journal of Mathematical & Statistical Psychology. 1988;41:257–278.
- Becker MH. The health belief model and personal health behavior. Health Education Monographs. 1974;2:324–473.
- Belcher L, Kalichman S, Topping M, Smith S, Emshoff J, Norris F, Nurss J. A randomized trial of a brief HIV risk reduction counseling intervention for women. Journal of Consulting and Clinical Psychology. 1998;66:856–861. [PubMed]
- Bell RA, Grissom S, Stephenson JJ, Fricrson R, Hunt L, Lace-field P, Teller D. Evaluating the outcomes of AIDS education. AIDS Education and Prevention. 1990;2:71–84.
- Bellingham K, Gillies P. Evaluation of an AIDS education programme for young adults. Journal of Epidemiology and Community Health. 1993;47:134–138. [PMC free article] [PubMed]
- Bem DJ. An experimental analysis of self-persuasion. Journal of Personality and Social Psychology. 1965;1:199–218.
- Bentley ME, Spratt K, Shepherd ME, Gangakhedkar RR, Thilikavathi S, Bollinger RC, Mehendale SM. HIV testing and counseling among men attending sexually transmitted disease clinics in Pune, India: Changes in condom use and sexual behavior over time. AIDS. 1978;1:1869–1877. [PubMed]
- Berrier J, Sperling R, Preisinger J, Evans V, Maso J, Walther V. HIV/AIDS education in a prenatal clinic: An assessment. AIDS Education and Prevention. 1991;3:100–117. [PubMed]
- Bhave G, Lindan CP, Hudes ES, Desai S, Wagle U, Tripathi SP, Mandel JS. Impact of an intervention on HIV, sexually transmitted diseases, and condom use among sex workers in Bombay, India. AIDS. 1995;9:521–530. [PubMed]
- Boekeloo BO, Schamus LA, Simmens SJ, Cheng TL, O’Connor K, D’Angelo LJ. A STD/HIV prevention trial among adolescents in managed care. Pediatrics. 1999;103:107–115. [PubMed]
- Booth-Kewley S, Minagawa RY, Shaffer RA, Brodine SK. A behavioral intervention to prevent sexually transmitted diseases/human immunodeficiency virus in a Marine Corps sample. Military Medicine. 2002;167:145–150. [PubMed]
- Booth-Kewley S, Shaffer RA, Minagawa RY, Brodine SK. Effectiveness of two versions of a sexually transmitted diseases/human immunodeficiency virus prevention program. Military Medicine. 2002;167:254–259. [PubMed]
- Borgia P, Spadea T, Perucci CA, de Pascali V, Fano V, Schifano P, Abeni DDC. Limited effectiveness of a school-based HIV prevention campaign in Italy. European Journal of Public Health. 1997;7:411–417.
- Boyer C, Barrett DC, Peterman TA, Bolan G. Sexually transmitted disease (STD) and HIV risk in heterosexual adults attending a public STD clinic: Evaluation of a randomized controlled behavioral risk-reduction intervention trial. AIDS. 1997;11:359–367. [PubMed]
- Boyer CB, Shafer MA, Tschann JM. Evaluation of a knowledge and cognitive—behavioral skills-building intervention to prevent STDs and HIV infection in high school students. Adolescence. 1997;32:25–42. [PubMed]
- Branson BM, Peterman TA, Cannon RO, Ransom R, Zaidi AA. Group counselling to prevent sexually transmitted disease and HIV: A randomized trial. Sexually Transmitted Disease. 1998;25:553–560. [PubMed]
- Brown LK, Barone VJ, Fritz GK, Cebollero P, Nassau JH. AIDS education: The Rhode Island experience. Health Education Quarterly. 1991;18:195–206. [PubMed]
- Brown LK, Fritz GK, Barone VJ. The impact of AIDS education on junior and senior high school students. Journal of Adolescent Health Care. 1989;10:386–392. [PubMed]
- Brown LK, Reynolds LA, Lourie KJ. A pilot HIV prevention program for adolescents in a psychiatric hospital. Psychiatric Services. 1997;48:531–533. [PubMed]
- Brown WJ. An AIDS prevention campaign. American Behavioral Scientist. 1991;34:666–678.
- Butler RB, Schultz JR, Forsberg AD, Brown LK, Parsons JT, King G, et al. Promoting safer sex among HIV-positive youth with haemophilia: Theory, intervention, and outcome. Haemophilia. 2003;9:214–222. [PubMed]
- Butts JB, Hartman S. Project BART: Effectiveness of a behavioral intervention to reduce HIV risk in adolescents. American Journal of Maternal/Child Nursing. 2002;27:163–169. [PubMed]
- Caceres CF, Rosasco AM, Mandel JS, Hearst N. Evaluating a school-based intervention for STD/AIDS prevention in Peru. Journal of Adolescent Health. 1994;15:582–591. [PubMed]
- Calsyn DA, Saxon AJ, Freeman G, Jr, Whittaker S. Ineffectiveness of AIDS education and HIV antibody testing in reducing high-risk behaviors among injection drug users. American Journal of Public Health. 1992;82:573–575. [PubMed]
- Carey MP, Braaten LS, Maisto SA, Gleason JR, Forsyth AD, Durant LE, Jaworski BC. Using information, motivational enhancement, and skills training to reduce the risk of HIV infection for low-income urban women: A second randomized clinical trial. Health Psychology. 2000;19:3–11. [PubMed]
- Carey MP, Maisto SA, Kalichman SC, Forsyth AD, Wright EM, Johnson BT. Enhancing motivation to reduce the risk of HIV infection for economically disadvantaged urban women. Journal of Consulting and Clinical Psychology. 1997;65:531–541. [PMC free article] [PubMed]
- Carlson KD, Schmidt FL. Impact of experimental design on effect size: Findings from the research literature on training. Journal of Applied Psychology. 1999;84:851–862.
- Catania JA, Coates TJ, Kegeles S. A test of the AIDS risk reduction model: Psychosocial correlates of condom use in the AMEN cohort survey. Health Psychology. 1994;13:548–555. [PubMed]
- Catania JA, Kegeles SM, Coates TJ. Towards an understanding of risk behavior: An AIDS risk reduction model (ARRM) Health Education Quarterly. 1990;17:53–72. [PubMed]
- CDC AIDS Community Demonstration Projects Research Group. Community level HIV intervention in 5 cities: Final outcome data from the CDC AIDS Community Demonstration Projects. American Journal of Public Health. 1999;89:336–345. [PubMed]
- Centers for Disease Control. Documentation for the brief street intercept and coffee shop interview questionnaires. Atlanta, GA: Community Demonstration Projects Research Group; 1993.
- Centers for Disease Control. Project Respect: Preliminary outcome study. Atlanta, GA: Project Respect Group; 1997.
- Centers for Disease Control. HIV/AIDS surveillance report. 2003. Retrieved October 2003 from http://www.cdc.gov/hiv/stats.htm#cumaids.
- Chifunyise T, Benoy H, Mukiibi B. An impact evaluation of student teacher training in HIV/AIDS education in Zimbabwe. Evaluation and Program Planning. 2002;25:377–385.
- Choi KH, Lew S, Vittinghoff E, Catania JA, Barrett D, Coates TJ. The efficacy of brief group counseling in HIV risk reduction among homosexual Asian and Pacific Islander men. AIDS. 1996;10:81–87. [PubMed]
- Clark LR, Brasseux C, Richmond D, Getson P, D’Angelo LJ. Effect of HIV counseling and testing on sexually transmitted diseases and condom use in an urban adolescent population. Archive of Pediatrics and Adolescence Medicine. 1998;152:269–273. [PubMed]
- Clift SM, Stears DF. Beliefs and attitudes regarding AIDS among British college students: A preliminary study of change between November 1986 and May 1987. Health Education Research. 1988;3:75–88.
- Coates RA, Soskilne CL, Calzavara L, Read SE, Fanning MM, Shepherd FA, et al. The reliability of sexual histories in AIDS-related research: Evaluation of an interview-administered questionnaire. Canadian Journal of Public Health. 1986;77:343–348. [PubMed]
- Collins C, Kohler C, DiClemente R, Wang MQ. Evaluation of the exposure effects of a theory-based street outreach HIV intervention on African-American drug users. Evaluation and Program Planning. 1999;22:279–293.
- Cook TD, Campbell DT. Quasi-experimentation: Design and analysis issues for field settings. Boston: Houghton Mifflin; 1979.
- Cottler LB, Compton WM, Ben Abdallah A, Cunningham-Williams R, Abram F, Fichtenbaum C, Dotson W. Peer-delivered interventions reduce HIV risk behaviors among out-of-treatment drug abusers. Public Health Reports. 1998;113:31–41. [PMC free article] [PubMed]
- Cottler LB, Leukefeld C, Hoffman J, Desmond D, Wechsberg W, Inciardi J, et al. Effectiveness of HIV risk-reduction initiatives among out-of-treatment non-injection drug users. Journal of Psychoactive Drugs. 1998;30:279–290. [PubMed]
- Deren S, Davis WR, Beardsley M, Tortu S, Clatts M. Outcomes of a risk-reduction intervention with HIV-risk populations: The Harlem AIDS project. AIDS Education and Prevention. 1995;7:379–390. [PubMed]
- DiClemente RJ, Pies CA, Stoller EJ, Straits C, Olivia GE, Haskin J, Rutherford GW. Evaluation of school-based AIDS education curricula in San Francisco. Journal of Sex Research. 1989;26:188–198.
- Diers JA. Efficacy of a stage-based counseling intervention to reduce the risk of HIV in women. 1999 Unpublished dissertation, Princeton University.
- Dilley JW, Woods WJ, Sabatino J, Lihatsh T, Adler B, Casey S, et al. Changing sexual behavior among gay male repeat testers for HIV. Journal of Acquired Immune Deficiency Syndromes. 2002;30:177–186. [PubMed]
- Dommeyer CJ, Marquardt JL, Gibson JE, Taylor RL. The effectiveness of an AIDS education campaign on a college campus. College Health. 1989;38:131–135. [PubMed]
- Dunlap WP, Cortina JM, Vaslow JB, Burke MJ. Meta-analysis of experiments with matched groups or repeated measures designs. Psychological Methods. 1996;1:170–177.
- Dusek JB. Adolescent development and behavior. Englewood Cliffs, NJ: Prentice Hall; 1996.
- el-Bassel N, Schilling RF. 15-month follow-up of women methadone patients taught skills to reduce heterosexual HIV transmission. Public Health Reports. 1992;107:500–504. [PMC free article] [PubMed]
- Eldridge GD, St Lawrence JS, Little CE, Shelby MC, Brasfield TL, Service JW, Sly K. Evaluation of an HIV risk reduction intervention for women entering inpatient substance abuse treatment. AIDS Education and Prevention. 1997;9:62–76. [PubMed]
- Elkins D, Maticka-Tyndale E, Kuyyakanond T, Miller P, Haswell-Elkins M. Toward reducing the spread of HIV in northeastern Thai villages: Evaluation of a village-based intervention. AIDS Education and Prevention. 1997;9:49–67. [PubMed]
- Elliott L, Gruer L. Theatre in AIDS education: A controlled study. AIDS Care. 1996;8:321–340. [PubMed]
- Farley TA, Pompitius PF, Sabella W, Helgerson SD, Hadler JL. Evaluation of the effect of school-based education on adolescents’ AIDS knowledge and attitudes. Connecticut Medicine. 1991;55:15–18. [PubMed]
- Fawole JO, Asuzu MC, Oduntan SO, Brieger WR. A school-based AIDS education programme for secondary school students in Nigeria: A review of effectiveness. Health Education Research. 1999;14:675–683. [PubMed]
- Ferreira-Pinto JB, Ramos R. HIV/AIDS prevention among female sexual partners of injection drug users in Ciudad Juarez, Mexico. AIDS Care. 1995;7:477–488. [PubMed]
- Fishbein M, Ajzen I. Belief, attitude, intention and behavior: An introduction to theory and research. Reading, MA: Addison Wesley; 1975.
- Fishbein M, Bandura A, Triandis HC, Kanfer FH, Becker MH, Middlestadt S. Report prepared for the National Institute of Mental Health (NIMH) Bethesda, MD: National Institute of Mental Health; 1992. Factors influencing behavior and behavior change.
- Fishbein M, Pequegnat W. Evaluating AIDS prevention interventions using behavioral and biological outcome measures. Sexually Transmitted Diseases. 2000;27:101–110. [PubMed]
- Fishbein M, Trafimow D, Francis C, Helquist M, Eustace MA, Ooms M, Middlestadt SE. AIDS knowledge, attitudes, beliefs, and practices (KABP) in two Caribbean countries: A comparative analysis. Journal of Applied Social Psychology. 1993;23:687–702.
- Fishbein M, Trafimow D, Middlestadt SE, Helquist M, Francis C, Eustace MA. Using an AIDS KABP survey to identify determinants of condom use among sexually active adults from St. Vincent and the Grenadines. Journal of Applied Social Psychology. 1995;25:1–20.
- Fisher JD, Fisher WA. Changing AIDS-risk behavior. Psychological Bulletin. 1992;111:455–474. [PubMed]
- Fisher JD, Fisher WA. Theoretical approaches to individual-level change in HIV risk behavior. In: Peterson JL, DiClemente CC, editors. Handbook of HIV prevention. New York: Kluwer Academic/Plenum Press; 2000. pp. 3–55.
- Fisher JD, Fisher WA, Bryan AD, Misovich SJ. Information-—otivation—behavioral skills model—based HIV risk behavior change intervention for inner-city high school youth. Health Psychology. 2002;21:177–186. [PubMed]
- Fisher JD, Fisher WA, Misovich SJ, Kimble DL, Malloy TE. Changing AIDS risk behavior: Effects of an intervention emphasizing AIDS risk reduction information, motivation, and behavioral skills in a college student population. Health Psychology. 1996;15:114–123. [PubMed]
- Fisher JD, Fisher WA, Williams SS, Malloy TE. Empirical tests of an information—motivation—behavioral skills model of AIDS-preventive behavior with gay men and heterosexual university students. Health Psychology. 1994;13:238–250. [PubMed]
- Fisher WA, Williams SS, Fisher JD, Malloy TE. Understanding AIDS risk behavior among sexually active urban adolescents. An empirical test of the information—motivation—behavioral skills model. AIDS and Behavior. 1999;3:13–23.
- Fitzgerald AM, Stanton BF, Terreri N, Shipena H, Li W, Kahihuata J, et al. Use of Western-based HIV risk-reduction interventions targeting adolescents in an African setting. Journal of Adolescent Health. 1999;25:52–61. [PubMed]
- Flaskerud JH, Nyamathi AM. Effects of an AIDS education program on the knowledge, attitudes and practices of low income Black and Latina women. Journal of Community Health. 1990;15:343–355. [PubMed]
- Flaskerud JH, Nyamathi AM, Uman GC. Longitudinal effects of an HIV testing and counseling programme for low-income Latina women. Ethnicity and Health. 1997;2:89–103. [PubMed]
- Floyd DL, Prentice-Dunn S, Rogers RW. A meta-analysis of research on protection motivation theory. Journal of Applied Social Psychology. 2000;30:407–429.
- Fogarty LA, Heilig C, Armstrong K, Cabral R, Galavotti C, Gielen AC, Green BM. Long term effectiveness of a peer-based intervention promoting condom and contraceptive use among HIV-positive and at-risk women. Public Health Reports. 2001;116:103–119. [PMC free article] [PubMed]
- Ford K, Wirawan DN, Reed BD, Muliawan P, Wolfe R. The Bali STD/AIDS study: Evaluation of an intervention for sex workers. Sexually Transmitted Diseases. 2002;29:50–58. [PubMed]
- Ford N, Koetsawang S. A pragmatic intervention to promote condom use by female sex workers in Thailand. Bulletin of the World Health Organization. 1999;77:888–894. [PubMed]
- Fox LJ, Bailey PE, Clarke-Martínez KL, Coello M, Ordoñez FN, Barahona F. Condom use among high-risk women in Honduras: Evaluation of an AIDS prevention program. AIDS Education and Prevention. 1993;5:1–10. [PubMed]
- Gerrard M, Gibbons FX, Bushman BJ. Relation between perceived vulnerability to HIV and precautionary sexual behavior. Psychological Bulletin. 1996;119:390–409. [PubMed]
- Gerrard M, Reis TJ. Retention of contraceptive and AIDS information in the classroom. Journal of Sex Research. 1989;26:315–323.
- Gielen AC, Faden RR, Kass NE, O’Campo P, Chaisson R, Watkinson L. Evaluation of an HIV/AIDS education program in an urban prenatal clinic. Women’s Health Issues. 1997;7:269–279. [PubMed]
- Gillies PA, Stork A, Bretman M. Streetwize UK: A controlled trial of an AIDS education comic. Health Education Research. 1990;5:27–33.
- Gillmore MR, Morrison DM, Richey CA, Balassone ML, Gutierrez L, Farris M. Effects of a skill-based intervention to encourage condom use among high risk heterosexually active adolescents. Health Education Research. 1997;9:22–43. [PubMed]
- Goertzel TG, Bluebond-Langner M. What is the impact of a campus AIDS education course? College Health. 1991;40:87–92. [PubMed]
- Gold RS, Rosenthal DA. Preventing unprotected anal intercourse in gay men: A comparison of two intervention techniques. International Journal of STD and AIDS. 1995;6:89–94. [PubMed]
- Gyarmathy VA, McNutt LA, Molnaár A, Morse D, DeHovitz J, Ujhelyi E, Szamadoó S. Evaluation of a comprehensive AIDS education curriculum in Hungary: The role of good educators. Journal of Adolescence. 2002;25:495–508. [PMC free article] [PubMed]
- Hämäläinen S, Keinähen-Kiukaanniemi S. A controlled study of the effect of one lesson on the knowledge and attitudes of school children concerning HIV and AIDS. Health Educational Journal. 1992;51:135–138.
- Harris RM, Barker Bausell R, Scott DE, Hetherington SE, Kavanagh KH. An intervention for changing high-risk HIV behaviors of African-American drug-dependent women. Research in Nursing & Health. 1998;21:239–250. [PubMed]
- Harvey B, Stuart J, Suan T. Evaluation of a drama-in-education programme to increase AIDS awareness in South African high schools: A randomized community intervention trial. International Journal of STD and AIDS. 2000;11:105–111. [PubMed]
- Hastings GB, Eadie DR, Scott AC. Two years of AIDS publicity: A review of progress in Scotland. Health Education Research. 1990;5:17–25.
- Healton CG, Messeri P. The effect of video interventions on improving knowledge and treatment compliance in the sexually-transmitted disease clinic setting: Lesson for HIV health-education. Sexually Transmitted Diseases. 1993;20:70–76. [PubMed]
- Hedges LV, Olkin I. Statistical methods for meta-analysis. Orlando, FL: Academic Press; 1985.
- Hedges LV, Vevea JL. Fixed-and random-effects models in meta-analysis. Psychological Methods. 1998;3:486–504.
- Higgins ET. Making a good decision: Value from fit. American Psychologist. 2000;55:1217–1230. [PubMed]
- Hillman E, Hovell MF, Williams L, Hofstetter R, Burdyshaw C, Rugg D, et al. Pregnancy, STDs, and AIDS prevention: Evaluation of new image teen theatre. AIDS Education and Prevention. 1991;3:328–340. [PubMed]
- Hobfoll SE, Jackson AP. Effects of generalizability of communally oriented HIV-AIDS prevention versus general health promotion groups for single, inner-city women in urban clinics. Journal of Consulting and Clinical Psychology. 2002;70:950–960. [PubMed]
- Hobfoll SE, Jackson AP, Lavin J, Britton P, Shepherd JB. Reducing inner-city women’s AIDS risk activities: A study of single, pregnant women. Health Psychology. 1994;13:397–403. [PubMed]
- Hoffman HJA, Klein H, Crosby H, Clark DC. Project Neighborhoods in action: An HIV related intervention project targeting drug abusers in Washington, DC. Journal of Urban Health: Bulletin of the New York Academy of Medicine. 1999;76:419–434. [PMC free article] [PubMed]
- Hovell MF, Blumberg EJ, Liles S, Powell L, Morrison TC, Duran G, et al. Training AIDS and anger prevention social skills in at-risk adolescents. Journal of Counseling and Development. 2001;79:347–355.
- Hunter JE, Schmidt FL. Fixed effects vs. random effects meta-analysis models: Implications for cumulative research knowledge. International Journal of Selection and Assessment. 2000;8:275–292.
- Huszti HC, Clopton JR, Mason PJ. Acquired immunodeficiency syndrome educational program: Effects on adolescents’ knowledge and attitudes. Pediatrics. 1989;84:986–994. [PubMed]
- Jaccard J, Wan-Choi K. A paradigm for studying the accuracy of self-reports of risk behavior relevant to AIDS: Empirical perspectives on stability, recall basis, and transitory influences. Journal of Applied Social Psychology. 1995;25:1831–1858.
- Jackson DJ, Rakwar JP, Richardson BA, Mandaliya K, Chohan B, Bwayo JJ, et al. Decreased incidence of sexually transmitted diseases among trucking company workers in Kenya: Results of a behavioural risk-reduction programme. AIDS. 1997;11:903–909. [PubMed]
- James NJ, Gillies PA, Bignell CJ. Evaluation of a randomized controlled trial of HIV and sexually transmitted disease prevention in a genitourinary medicine clinic setting. AIDS. 1998;12:1235–1242. [PubMed]
- Janz NK, Becker MH. The health belief model: A decade later. Health Education Quarterly. 1984;11:1–47. [PubMed]
- Jaworski BC, Carey P. Effects of a brief, theory-based STD-prevention program for female college students. Journal of Adolescent Health. 2001;29:417–425. [PMC free article] [PubMed]
- Jemmott JB, III, Jemmott LS. HIV risk reduction behavioral interventions with heterosexual adolescents. AIDS. 2000;14:40–52. [PubMed]
- Jemmott LS, Jemmott JB., III Increasing condom-use intentions among sexually active Black adolescent women. Nursing Research. 1992;41:273–279. [PubMed]
- Johnson BT, Carey MP, Marsh KL, Levin KD, Scott-Sheldon LA. Interventions to reduce sexual risk for the human immunodeficiency virus in adolescents, 1985–2000: A research synthesis. Archives of Pediatrics and Adolescent Medicine. 2003;157:381–388. [PubMed]
- Johnson JA, Sellew JF, Campbell AE, Haskell EG, Gay AA, Bell BJ. A program using medical students to teach high school students about AIDS. Journal of Medical Education. 1988;63:522–530. [PubMed]
- Johnson WD, Hedges LV, Ramirez G, Semann S, Norman LR, Sogolow E, et al. HIV prevention research for men who have sex with men: A systematic review and meta-analysis. Journal of Acquired Immune Deficiency Syndromes. 2002;30:18–29. [PubMed]
- Judd CM, Kenny DA. Process analysis: Estimating mediation in treatment evaluations. Evaluation Review. 1981;5:602–619.
- Kagimu M, Marum E, Wabwire-Mangen F, Nakyanjo N, Walakira Y, Hogle J. Evaluation of the effectiveness of AIDS health education interventions in the Muslim community in Uganda. AIDS Education and Prevention. 1998;10:215–228. [PubMed]
- Kahn JG, Kegeles SM, Hays R, Beltzer N. Cost-effectiveness of the Mpowerment Project, a community-level intervention for young gay men. Journal of Acquired Immune Deficiency Syndromes. 2001;27:482–491. [PubMed]
- Kalichman SC, Carey MP, Johnson BT. Prevention of sexually transmitted HIV infection: A meta-analytic review of the behavioral outcome literature. Annals of Behavioral Medicine. 1996;18:6–15.
- Kalichman SC, Cherry C, Browne-Sperling F. Effectiveness of a video-based motivational skills-building HIV risk-reduction intervention for inner-city African American men. Journal of Consulting and Clinical Psychology. 1999;67:956–966. [PubMed]
- Kalichman SC, Kelly JA, Hunter TL, Murphy DA, Tyler R. Culturally tailored HIV-AIDS risk-reduction messages targeted to African-American urban women. Journal of Consulting and Clinical Psychology. 1993;61:291–295. [PubMed]
- Kalichman SC, Rompa D, Coley B. Experimental component analysis of a behavioral HIV-AIDS prevention intervention for inner-city women. Journal of Consulting and Clinical Psychology. 1996;4:687–693. [PubMed]
- Kalichman SC, Rompa D, Coley B. Lack of positive outcomes from a cognitive—behavioral HIV and AIDS prevention intervention for inner-city men: Lessons from a controlled pilot study. AIDS Education and Prevention. 1997;9:299–313. [PubMed]
- Kalichman SC, Sikkema KJ, Kelly JA, Bulto M. Use of a brief behavioral skills intervention to prevent HIV infection among chronic mentally ill adults. Psychiatric Services. 1995;46:275–280. [PubMed]
- Kamb ML, Fishbein M, Douglas JM, Jr, Rhodes F, Rogers J, Bolan G, et al. Efficacy of risk-reduction counseling to prevent human immunodeficiency virus and sexually transmitted diseases: A randomized controlled trial. Project RESPECT Study Group. JAMA. 1998;280:1161–1167. [PubMed]
- Katz RC, Westerman C, Beauchamp K, Clay C. Effects of AIDS counseling and risk reduction training on the chronic mentally ill. AIDS Education and Prevention. 1996;8:457–463. [PubMed]
- Kaul R, Kimani J, Nagelkerke NJ, Fonck K, Keli F, MacDonald KS, et al. Reduced HIV risk-taking and low HIV incidence after enrollment and risk-reduction counseling in a sexually transmitted disease prevention trial in Nairobi, Kenya. Journal of Acquired Immune Deficiency Syndromes. 2002;72:69–72. [PubMed]
- Kegeles SM, Hays RB, Coates TJ. The Mpowerment project: A community-level HIV prevention intervention for young gay men. American Journal of Public Health. 1996;86:1129–1136. [PubMed]
- Kelly JA. Advances in HIV/AIDS education and prevention. Family Relations. 1995;44:345–352.
- Kelly JA, McAuliffe TL, Sikkema KJ, Murphy DA, Somlai AM, Mahy GM, et al. Reduction in risk behavior among adults with severe mental illness who learned to advocate for HIV prevention. Psychiatric Services. 1997;18:1283–1288. [PubMed]
- Kelly JA, Murphy DA, Sikkema KJ, McAuliffe TL, Roffman RA, Solomon LJ, et al. Randomised, controlled, community-level HIV-prevention Intervention for sexual-risk behavior among homosexual men in US cities. Lancet. 1997;350:1500–1505. [PubMed]
- Kelly JA, Murphy DA, Washington CD, Wilson TS, Koob JJ, Davis DR, Ledezma G, Davantes B. The effect of HIV/AIDS intervention groups for high-risk women in urban clinics. American Journal of Public Health. 1994;84:1918–1922. [PubMed]
- Kelly JA, St Lawrence JS, Betts R, Brasfield TL, Hood HV. A skills-training group intervention model to assist persons in reducing risk behaviors for HIV infection. AIDS Education and Prevention. 1990;1:24–35. [PubMed]
- Kelly JA, St Lawrence JS, Diaz YE, Stevenson LY, Hauth AC, Brasfield TL, et al. HIV risk behavior reduction following intervention with key opinion leaders of population: An experimental analysis. American Journal of Public Health. 1991;81:168–171. [PubMed]
- Kelly JA, St Lawrence JS, Hood HV, Brasfield TL. Behavioral intervention to reduce AIDS risk activities. Journal of Consulting and Clinical Psychology. 1989;57:60–67. [PubMed]
- Kelly JA, St Lawrence JS, Stevenson LY, Hauth AC, Kalichman SC, Diaz YE, et al. Community AIDS/HIV risk reduction: The effects of endorsements by popular people in three cities. American Journal of Public Health. 1992;82:1483–1489. [PubMed]
- Kerr M, Stattin H, Bisecker G, Ferrer-Wreder L. Parents and peers as developmental context. In: Lerner RM, Easterbrooks MA, Mistry J, Weiner IB, editors. Comprehensive handbook of psychology: Developmental psychology. New York: Wiley; 2002. pp. 395–422.
- Kim N, Stanton B, Li X, Dickersin K, Galbraith J. Effectiveness of the 40 adolescent AIDS-risk reduction interventions: A quantitative review. Journal of Adolescent Health. 1997;20:204–215. [PubMed]
- Kindeberg T, Cristensson B. Changing Swedish students’ attitudes in relation to the AIDS epidemic. Health Education Research. 1994;9:171–181. [PubMed]
- Kipke MD, Boyer C, Hein K. An evaluation of an AIDS risk reduction education and skills training (arrest) program. Journal of Adolescent Health. 1993;14:533–539. [PubMed]
- Kirby D, Korpi M, Adivi C, Weissman J. An impact evaluation of project SNAPP: An AIDS and pregnancy prevention middle school program. AIDS Education and Prevention. 1997;9:44–61. [PubMed]
- Klepp KI, Ndeki SS, Leshabari MT, Hannan PJ, Lyimo BA. AIDS education in Tanzania: Promoting risk reduction among primary school children. American Journal of Public Health. 1997;87:1931–1936. [PubMed]
- Kotranski L, Semaan S, Collier K, Lauby J, Halbert J, Feighan K. Effectiveness of an HIV risk reduction counseling intervention for out-of-treatment drug users. AIDS Education and Prevention. 1998;10:19–33. [PubMed]
- Landis SE, Earp JL, Koch GG. Impact of HIV testing and counseling on subsequent sexual behavior. AIDS Education and Prevention. 1992;4:61–70. [PubMed]
- Lauby JL, Smith PJ, Stark M, Person B, Adams J. A community-level HIV prevention intervention for inner-city women: Results of the Women and Infants Demonstration Projects. American Journal of Public Health. 2000;90:216–222. [PubMed]
- Lazebnik R, Grey SF, Ferguson C. Integrating substance abuse content into an HIV risk-reduction intervention: A pilot study with middle school-aged Hispanic students. Substance Abuse. 2001;22:105–117. [PubMed]
- Leonard L, Ndiaye I, Kapadia A, Eisen G, Diop O, Mbourp S, Kanki P. HIV prevention among male clients of female sex workers in Kaolack, Senegal: Results of a peer education program. AIDS Education and Prevention. 2000;12:21–37. [PubMed]
- Li X, Stanton B, Feigelman S, Galbraith J. Unprotected sex among African-American adolescents: A three-year study. Journal of the National Medical Association. 2002;94:789–796. [PMC free article] [PubMed]
- Lindenberg CS, Solorzano RM, Bear D, Strickland O, Galvis C, Pittman K. Reducing substance use and risky sexual behavior among young, low-income, Mexican-American women: Comparison of two interventions. Applied Nursing Research. 2002;16:137–148. [PubMed]
- Lipsey MW, Wilson DB. Practical meta-analysis. Thousand Oaks, CA: Sage; 2001.
- Logan TK, Cole J, Leukefeld C. Women, sex, and HIV: Social and contextual factors, meta-analysis of published interventions, and implications for practice and research. Psychological Bulletin. 2002;128:851–885. [PubMed]
- Ma S, Dukers NHTM, van den Hoek A, Yuliang F, Zhiheng C, Jiangting F, et al. Decreasing STD incidence and increasing condom use among Chinese sex workers following a short term intervention: A prospective cohort study. Sexually Transmitted Infections. 2002;78:110–114. [PMC free article] [PubMed]
- MacLachlan M, Chimombo M, Mpeba N. AIDS education for youth through active learning: A school-based approach from Malawi. International Journal of Educational Development. 1997;17:41–50.
- MacNair RR, Elliott TR, Yoder B. AIDS prevention groups as persuasive appeals: Effects on attitudes about precautionary behaviors among persons in substance abuse treatment. Small Group Research. 1991;22:301–319.
- MacNair-Semands RR, Cody WK, Simono RB. Sexual behavior change associated with a college HIV course. AIDS Care. 1997;9:727–738.
- Malow RM, Corrigan SA, Pena JM, Calkin AM, Bannister TM. Effectiveness of a psychoeducational approach to HIV risk behavior reduction. Psychology of Addictive Behaviors. 1992;6:120–125.
- Malow RM, West JA, Corrigan SA, Pena JM, Cunningham SC. Outcome of psychoeducation for HIV risk reduction. AIDS Education and Prevention. 1994;6:113–125. [PubMed]
- Mansfield CJ, Conroy ME, Emans SJ, Woods ER. A pilot study of AIDS education and counseling of high-risk adolescents in an office setting. Journal of Adolescent Health. 1993;14:115–119. [PubMed]
- Martin GS, Serpelloni G, Galvan U, Rizzetto A, Gomma M, Morgante S, Rezza G. Behavioural change in injecting drug users: Evaluation of an HIV/AIDS education. AIDS Care. 1990;2:275–279. [PubMed]
- McCusker J, Stoddard AM, Hindin RN, Garfield FB, Frost R. Changes in HIV risk behavior following alternative residential programs of drug abuse treatment and AIDS education. Annals of Epidemiology. 1996;6:119–125. [PubMed]
- McCusker J, Stoddard AM, Zapka JG, Lewis BF. Behavioral outcomes of AIDS education interventions for drug users in short term treatment. American Journal of Public Health. 1993;83:1463–1466. [PubMed]
- McGuinness T, Mason M, Tolbert G, DeFontaine C. Becoming responsible teens: Promoting the health of adolescents in foster care. Journal of the American Psychiatric Nurse Association. 2002;8:92–98.
- McGuire WJ. Personality and attitude change: An information-processing theory. In: Greenwald AG, Brock TC, Ostrom TM, editors. Psychological foundations of attitudes. San Diego, CA: Academic Press; 1968. pp. 171–196.
- McLaws ML, Oldenburg B, Ross MW, Cooper DA. Sexual behaviour in AIDS-related research: Reliability and validity of recall and diary measures. Journal of Sex Research. 1990;27:265–281.
- McMahon RC, Malow RM, Jennings TE, Gómez CJ. Effects of a cognitive—behavioral HIV prevention intervention among HIV negative male substance abusers in VA residential treatment. AIDS Education and Prevention. 2001;13:91–107. [PubMed]
- Mercer MA, Gates N, Holley M, Malunga L, Arnold R. Rapid KABP survey for evaluation of NGO HIV/AIDS prevention projects. AIDS Education and Prevention. 1996;8:143–154. [PubMed]
- Miller RL. Assisting gay men to maintain safer sex: An evaluation of an AIDS service organization’s safer sex maintenance program. AIDS Education and Prevention. 1995;7:48–63. [PubMed]
- Miller RL, Klotz D, Eckholdt HM. HIV prevention with male prostitutes and patrons of hustler bars: Replication of an HIV preventive intervention. American Journal of Community Psychology. 1998;26:97–131. [PubMed]
- Miller TE, Booraem C, Flowers JV, Iversen AE. Changes in knowledge, attitudes, and behavior as a result of a community-based AIDS prevention program. AIDS Education and Prevention. 1990;2:12–23. [PubMed]
- Mills S, Campbell MJ, Waters WE. Public knowledge of AIDS and the DHSS advertisement campaign. British Medical Journal. 1986;293:1089–1090. [PMC free article] [PubMed]
- Mize SJ, Robinson BE, Bockting WO, Scheltema KE. Meta-analysis of the effectiveness of HIV prevention interventions for women. AIDS Care. 2002;14:163–180. [PubMed]
- Morris SB. Distribution of the standardized mean change effect size for meta-analysis on repeated measures. British Journal of Mathematical & Statistical Psychology. 2000;53:17–29. [PubMed]
- Mullen PD, Ramirez G, Strouse D, Hedges LV, Sogolow E. Meta-analysis of the effects of behavioral HIV prevention interventions on the sexual risk behavior of sexually experienced adolescents in controlled studies in the United States. Journal of Acquired Immune Deficiency Syndromes. 2002;1:94–105. [PubMed]
- National Institutes of Health. Progress and future directions for management of hepatitis C: Expand access to treatment to IVDUs, persons who use alcohol, suffer from co-morbid conditions such as depression, who are coinfected with HIV, children and older adults from treatment and research; Paper presented at the National Institutes of Health HCV Consensus Development Conference; June, 2002.1997.
- Neaigus A, Sufian M, Friedman SR, Goldsmith DS, Stepherson B, Mota P, et al. Effect of outreach intervention on risk reduction among intravenous drug users. AIDS Education and Prevention. 1990;2:253–271. [PubMed]
- Neumann MS, Johnson WD, Semaan S, Flores SA, Peersman G, Hedges LV, Sogolow E. Review and meta-analysis of HIV prevention intervention research for heterosexual adult populations in the United States. Journal of Acquired Immune Deficiency Syndromes. 2002;1:106–117. [PubMed]
- Newman C, Durant RH, Seymore Ashworth C, Gaillard G. An evaluation of a school-based AIDS/HIV education program for young adolescents. AIDS Education and Prevention. 1993;5:327–339. [PubMed]
- Ngugi EN, Plummer FA, Simonsen JN, Cameron DW, Bosire M, Waiyaki P, Ronald AR, Ndinya-Achola JO. Prevention of transmission of human immunodeficiency virus in Africa: Effectiveness of condom promotion and health education among prostitutes. Lancet. 1988;15:887–890. [PubMed]
- NIMH Multisite HIV Prevention Trial Group. Social—cognitive theory mediators of behavior change in the National Institute of Mental Health Multisite HIV Prevention Trial. Health Psychology. 1998;20:369–376.
- Nyamathi AM, Flaskerud J, Bennett C, Leake B, Lewis C. Evaluation of two AIDS education programs for impoverished Latina women. AIDS Education and Prevention. 1994;6:296–309. [PubMed]
- Nyamathi AM, Flaskerud JH, Leake B, Dixon EL, Lu A. Evaluating the impact of peer, nurse case-managed, and standard HIV risk-reduction programs on psychosocial and health-promoting behavioral outcomes among homeless women. Research in Nursing and Health. 2001;24:410–422. [PubMed]
- Nyamathi AM, Stein JA. Assessing the impact of HIV risk reduction counseling in impoverished African American women: A structural equations approach. AIDS Education and Prevention. 1997;9:253–273. [PubMed]
- O’Hara P, Messick B, Fichtner RR, Parris D. A peer-led AIDS prevention program for students in an alternative school. Journal of School Health. 1996;66:176–182. [PubMed]
- O’Leary A, Ambrose TK, Raffaelli M, Mailbach E, Jemmott LS, Jemmott JB, III, et al. Effects of an HIV risk reduction project on sexual risk behavior of low-income STD patients. AIDS Education and Prevention. 1998;10:483–492. [PubMed]
- O’Leary A, Jemmott LS, Goodhart F, Gebelt J. Effects of an institutional AIDS prevention intervention: Moderation by gender. AIDS Education and Prevention. 1996;8:516–528. [PubMed]
- Orr D, Langefeld CD, Katz BP, Caine VA. Behavioral intervention to increase condom use among high-risk female adolescents. Journal of Pediatrics. 1996;128:288–295. [PubMed]
- Otto-Salaj LL, Kelly JA, Stevenson LY, Hoffmann R, Kalichman SC. Outcomes of a randomized small-group HIV prevention intervention trial for people with serious mental illness. Community Mental Health Journal. 2001;37:123–144. [PubMed]
- Ozer EJ, Weinstein RS, Maslack C. Adolescent AIDS prevention in context: Impact of peer educator qualities and classroom environments on intervention efficacy. American Journal of Community Psychology. 1997;25:289–323. [PubMed]
- Papaevangelou G, Roumeliotou A, Kallinikos G, Papoutsakis G, Trichopoulou E, Stefanou T. Education in preventing HIV infection in Greek registered prostitutes. Journal of Acquired Immune Deficiency Syndromes. 1988;1:386–389. [PubMed]
- Pauw J, Ferrie J, Rivera Villegas R, Medrano Martínez J, Gorter A, Egger M. A controlled HIV/AIDS-related health education programme in Managua, Nicaragua. AIDS. 1996;10:537–544. [PubMed]
- Perlini AH, Ward C. HIV prevention interventions: The effect of role-play and behavioural commitment on knowledge and attitudes. Canadian Journal of Behavioural Science. 2000;23:133–143.
- Peterson JL, Coates TJ, Catania J, Hauck WW, Acree M, Daigle D, et al. Education of an HIV risk reduction intervention among African-American homosexual and bisexual men. AIDS. 1996;10:319–325. [PubMed]
- Picciano JF, Roffman RA, Kalichman SC, Rutledge SE, Berghuis JP. A telephone based brief intervention using motivational enhancement to facilitate HIV risk reduction among MSM: A pilot study. AIDS and Behavior. 2001;5:251–262.
- Pinkerton SD, Abrahamson PR. Evaluating the risks: A Bernoulli process model of HIV infection and risk reduction. Evaluation Review. 1993;17:504–528.
- Pinkerton SD, Abrahamson PR. An alternative model of the reproductive rate of HIV infection and risk reduction. Evaluation Review. 1994;18:371–388.
- Pinkerton SD, Holtgrave DR, DiFrancesco W, Semaan S, Coyle SL, Johnson-Masotti AP. Cost-threshold analyses of the National AIDS Demonstration Research HIV Prevention Interventions. AIDS. 2000;14:1257–1268. [PubMed]
- Ploem C, Byers S. The effects of two AIDS risk-reduction interventions on heterosexual college women’s AIDS-related knowledge, attitudes and condom use. Journal of Psychology and Human Sexuality. 1997;9:1–23. [PubMed]
- Ponton LE, DiClemente RJ, McKenna S. AIDS education and prevention program for hospitalized adolescents. Journal of the American Academy of Child and Adolescent Psychiatry. 1991;30:729–734. [PubMed]
- Povey R, Conner C, Sparks P. Application of the theory of planned behaviour to two dietary behaviours: Roles of perceived control and self-efficacy. British Journal of Health Psychology. 2000;5:121–139.
- Prendergast ML, Urada D, Podus D. Meta-analysis of HIV risk-reduction interventions within drug abuse treatment programs. Journal of Consulting and Clinical Psychology. 2001;69:389–405. [PubMed]
- Prentice-Dunn S, Rogers RW. Protection motivation theory and preventive health: Beyond the health belief model. Health Education Research. 1986;1:153–161.
- Prislin R, Wood W. Social influence in attitude and attitude change. In: Albarracín D, Johnson BT, Zanna MP, editors. Handbook of attitudes. Hillsdale, NJ: Erlbaum; 2005. pp. 671–706.
- Prochaska JO, DiClemente CC. Stages and processes of self-change in smoking: Toward an integrative model of change. Journal of Consulting and Clinical Psychology. 1984;5:390–395. [PubMed]
- Prochaska JO, DiClemente CC, Norcross JC. In search of how people change: Application to addictive behaviors. American Psychologist. 1992;47:1002–1114. [PubMed]
- Prochaska JO, Redding CA, Harlow LL, Rossi JS, Velicer WF. The transtheoretical model of change and HIV prevention: A review. Health Education Quarterly. 1994;21:471–486. [PubMed]
- Quirk ME, Godkin MA, Schwenzfeier E. Evaluation of two AIDS prevention interventions for inner-city adolescent and young adult women. American Journal of Preventive Medicine. 1993;9:21–26. [PubMed]
- Ragon BM, Kittleson MJ, St Pierre RW. The effect of a single affective HIV/AIDS educational program on college students’ knowledge and attitudes. AIDS Education and Prevention. 1995;7:221–231. [PubMed]
- Raj A, Amaro H, Cranston K, Martin B, Cabral H, Navarro A, Conron K. Is a general women’s health promotion program as effective as an HIV-intensive prevention program in reducing HIV risk among Hispanic women? Public Health Reports. 2001;116:599–607. [PMC free article] [PubMed]
- Rao AV, Swaminathan R, Baskaran S, Belinda C, Andla G, Saleem K. Behaviour change in HIV infected subjects following health education. Indian Journal of Medical Research. 1991;93:345–349. [PubMed]
- Raudenbush SW. Random effects models. In: Cooper H, Hedges LV, editors. The handbook of research synthesis. New York: Russell Sage Foundation; 1994. pp. 301–321.
- Reeder GD, Pryor JB, Harsh L. Activity and similarity in safer sex workshops led by peer educators. AIDS Education and Prevention. 1997;9:77–89. [PubMed]
- Rhodes F, Wolitski R. Affect of instructional videotapes on AIDS knowledge and attitudes. College Health. 1989;37:266–271. [PubMed]
- Rigby K, Brown M, Anagnostou P, Ross MW, Rosser BRS. Shock tactics to counter AIDS: The Australian experience. Psychology and Health. 1989;3:145–159.
- Robin L, Dittus P, Whitaker D, Crosby R, Ethier K, Mezoff J, et al. Behavioral interventions to reduce incidence of HIV, STD, and pregnancy among adolescents: A decade in review. Journal of Adolescent Health. 2004;34:3–26. [PubMed]
- Roffman RA, Stephens RS, Curtin L, Gordon JR, Craver JN, Stern M, et al. Relapse prevention as an interventive model for HIV risk reduction in gay and bisexual men. AIDS Education and Prevention. 1998;10:1–18. [PubMed]
- Rogers RW. A protection motivation theory of fear appeals and attitude change. Journal of Psychology. 1975;91:93–114.
- Rogers RW. Cognitive and physiological processes in fear appeals and attitude change: A revised theory of protection motivation. In: Cacioppo J, Petty R, editors. Social psychophysiology. New York: Guilford Press; 1983. pp. 153–176.
- Rosenstock IM. What research in motivation suggests for public health. American Journal of Public Health. 1960;50:295–302. [PubMed]
- Rosenstock IM. Why people use health services. Milbank Quarterly. 1966;44:94–127. [PubMed]
- Rosenstock IM. Historical origins of the health belief model. Health Education Monographs. 1974;2:1–8.
- Rosenstock IM, Strecher VJ, Becker MH. The health belief model and HIV risk behavior change. In: DiClemente RJ, Peterson JL, editors. Preventing AIDS: Theories and methods of behavioral interventions. New York: Plenum Press; 1994. pp. 5–24.
- Rosenthal R. Writing meta-analytic reviews. Psychological Bulletin. 1995;118:183–192.
- Rosser BRS, Bockting WO, Rugg DL, Robinson BBE, Ross MW, Bauer GR, Coleman E. A randomized controlled intervention trial of a sexual health approach to long term HIV risk reduction for men who have sex with men: Effects of the intervention on unsafe sexual behavior. AIDS Education and Prevention. 2002;14:59–71. [PubMed]
- Rotheram-Borus MJ, Koopman C, Haignere C, Davies M. Reducing HIV sexual risk behaviors among runaway adolescents. Journal of the American Medical Association. 1991;266:1237–1242. [PubMed]
- Rotheram-Borus MJ, Lee MB, Murphy DA, Futterman D, Duan N, Birnbaum JM, et al. Efficacy of a preventive intervention for youth living with HIV. American Journal of Public Health. 2001;91:400–405. [PubMed]
- Rotheram-Borus MJ, Murphy DA, Fernández MI, Srinivasan S. A brief HIV intervention for adolescents and young adults. American Journal of Orthopsychiatry. 1998;68:553–563. [PubMed]
- Rothman AJ, Salovey P. Shaping perceptions to motivate healthy behavior: The role of message framing. Psychological Bulletin. 1997;121:3–19. [PubMed]
- Ruder AM, Flam R, Flatto D, Curran AS. AIDS education: Evaluation of school and worksite based presentations. New York State Journal of Medicine. 1990;90:129–133. [PubMed]
- Sampaio M, Brites C, Stall R, Hudes ES, Hearst N. Reducing AIDS risk among men who have sex with men in Salvador, Brazil. AIDS and Behavior. 2002;6:173–181.
- Schinke SP, Gordon AN. Self-instruction to prevent HIV infections among African-American and Hispanic-American adolescents. Journal of Consulting and Clinical Psychology. 1990;58:432–436. [PMC free article] [PubMed]
- Schroeder KEE, Carey MP, Vanable PA. Methodological challenges in research on sexual risk behavior: I. Item content, scaling, and data analytical options. Annals of Behavioral Medicine. 2003;26:76–103. [PMC free article] [PubMed]
- Schwarzer R. Self-efficacy in the adoption and maintenance of health behaviors: Theoretical approaches and a new model. In: Schwarzer R, editor. Self-efficacy: Thought control of action. Washington, DC: Hemisphere; 1992. pp. 217–242.
- Scollay PA, Doucett M, Perry M, Winterbottom B. AIDS education of college students: The effect of an HIV-positive lecturer. AIDS Education and Prevention. 1992;4:160–171. [PubMed]
- Semaan S, Des Jarlais DC, Sogolow E, Johnson WD, Hedges LV, Ramirez G, et al. A meta-analysis of the effect of HIV prevention interventions on the sex behaviors of drug users in the United States. Journal of Acquired Immune Deficiency Syndromes. 2002;1:73–93. [PubMed]
- Shadish WR. Meta-analysis and the exploration of causal mediating processes: A primer of examples, methods, and issues. Psychological Methods. 1996;1:47–65.
- Sherr L. An evaluation of the UK government health education campaign on AIDS. Psychology and Health. 1987;1:61–72.
- Shrier LA, Ancheta R, Goodman E, Chiou VM, Lyden MR, Emans SJ. Randomized controlled trial of a safer sex intervention for high-risk adolescent girls. Archive of Pediatrics and Adolescent Medicine. 2001;155:73–79. [PubMed]
- Shulkin JJ, Mayer JA, Wessel LG, de Moor C, Elder JP, Franzini LR. Effects of a peer-led AIDS intervention with university students. College Health. 1991;40:75–79. [PubMed]
- Siegel DM, Aten MJ, Roghmann KJ, Enaharo M. Early effects of a school-based human immunodeficiency virus infection and sexual risk prevention intervention. Archive of Pediatrics and Adolescent Medicine. 1998;152:961–970. [PubMed]
- Siegel DM, DiClemente R, Durbin M, Krasnorsky F, Saliba P. Change in junior high school students’ aid-related knowledge, misconceptions, attitudes, and HIV-preventive behaviors: Effects of a school-based intervention. AIDS Education and Prevention. 1995;7:534–543. [PubMed]
- Sikkema KJ, Kelly JA, Winett RA, Solomon LJ, Cargill VA, Roffman RA, et al. Outcomes of a randomized community-level HIV prevention intervention for women living in 18 low-income housing developments. American Journal of Public Health. 2000;90:57–63. [PubMed]
- Sikkema KJ, Winett RA, Lombard DN. Development and evaluation of an HIV-risk reduction program for female college students. AIDS Education and Prevention. 1995;7:145–159. [PubMed]
- Singh S. Study of the effect of information, motivation and behavioural skills (IMB) intervention in changing AIDS risk behaviour in female university students. AIDS Care. 2003;15:71–76. [PubMed]
- Singh YN, Malaviya AN. Experience of HIV prevention interventions among female sex workers in Delhi, India. International Journal of STD and AIDS. 1994;5:56–57. [PubMed]
- Slap GB, Plotkin SL, Najma K, Michelman DF, Forke C. A Human immunodeficiency virus peer education program for adolescent females. Journal of Adolescent Health. 1992;12:434–441. [PubMed]
- Smith MU, Dane FC, Archer ME, Devereux RS, Katner HP. Students together against negative decisions (STAND): Evaluation of a school-based sexual risk-reduction intervention in the rural south. AIDS Education and Prevention. 2000;12:49–70. [PubMed]
- Smith MU, Katner HP. Quasi-experimental evaluation of three AIDS prevention activities for maintaining knowledge, improving attitudes, and changing risk behaviors of high risk school seniors. AIDS Education and Prevention. 1995;7:391–402. [PubMed]
- Sobel ME. Asymptotic confidence intervals for indirect effects in structural equation models. In: Leinhardt S, editor. Sociological methodology. Washington DC: American Sociological Association; 1982. pp. 290–312.
- Solomon MZ, DeJong W. Preventing AIDS and other STDs through condom promotion: A patient education intervention. American Journal of Public Health. 1989;79:453–458. [PubMed]
- Sprinthall NA, Collins WA. A developmental view. 3rd ed. New York: McGraw-Hill; 1995. Adolescent psychology.
- St Lawrence JS, Brasfield TL, Jefferson KW, Alleyne E, O’Bannon RE., III Cognitive-behavioral intervention to reduce African American adolescents’ risk for HIV infection. Journal of Consulting and Clinical Psychology. 1995;63:221–237. [PubMed]
- St Lawrence JS, Crosby RA, Basfield T, O’Bannon RE., III Reducing STD and HIV risk behavior of substance-dependent adolescents: A randomized controlled trial. Journal of Consulting and Clinical Psychology. 2002;70:1010–1021. [PubMed]
- St Lawrence JS, Jefferson KW, Alleyne E, Brasfield TL. Comparison of education versus behavioral skills training interventions in lowering sexual HIV-risk of substance-dependent adolescents. Journal of Consulting and Clinical Psychology. 1995;63:154–157. [PubMed]
- St Lawrence JS, Wilson TE, Eldridge GD, Brasfield TL, O’Bannon RE., III Community-based interventions to reduce low income, African American women’s risk of sexually transmitted diseases: A randomized controlled trial of three theoretical models. American Journal of Community Psychology. 2001;29:937–964. [PubMed]
- Stall RD, Paul JP, Barrett DC, Crosby GM, Bein E. An outcome evaluation to measure changes in sexual risk-taking among gay men undergoing substance use disorder treatment. Journal of Studies on Alcohol. 1999;60:837–844. [PubMed]
- Stanton BF, Li X, Kahihuala J, Fitzgerald AM, Neumbo S, Kanduuombe G, et al. Increased protected sex and abstinence among Namibian youth following an HIV risk-reduction intervention: A randomized longitudinal study. AIDS. 1998;12:2473–2480. [PubMed]
- Stanton BF, Li X, Ricardo I, Galbraith J, Feigelman S, Kaljee L. A randomized, controlled effectiveness trial of an AIDS prevention program for low-income African-American youths. Archives of Pediatrics and Adolescent Medicine. 1996;150:363–372. [PubMed]
- Sterk CE, Theall KP, Elifson KW. Effectiveness of a risk reduction intervention among African American women who use crack cocaine. AIDS Education and Prevention. 2003;15:15–32. [PubMed]
- Sweet M, O’Donnell C, O’Donnell L. Cost-effectiveness of a brief video-based HIV intervention for African American and Latino sexually transmitted disease clinic clients. AIDS. 2001;15:781–787. [PubMed]
- Toro-Alfonso J, Varas-Díaz N, Andújar-Bello I. Evaluation of an HIV/AIDS prevention intervention targeting Latino gay men and men who have sex with men in Puerto Rico. AIDS Education and Prevention. 2002;14:445–456. [PubMed]
- Turner JC, Garrison CZ, Korpita E, Waller J, Addy C, Hill WR, Mohn LA. Promoting responsible sexual behavior through a college freshman seminar. AIDS Education and Prevention. 1994;6:266–277. [PubMed]
- UNAIDS/WHO Working Group on Global HIV/AIDS and STI Surveillance. Report on global HIV/AIDS epidemic. 2002 Retrieved October 2002 http://www.unaids.org/en/resources/epidemiology.asp.
- Valdiserri RO, Lyter DW, Kingsley LA, Leviton LC, Schofield JW, Huggins J, et al. The effect of group education on improving attitudes about AIDS risk reduction. New York State Journal of Medicine. 1987;87:272–278. [PubMed]
- Valente T, Bharath U. An evaluation of the use of drama to communicate HIV/AIDS information. AIDS Education and Prevention. 1999;11:203–211. [PubMed]
- Van Griensven GJP, Limanonda B, Ngaokeow S, Ayuthaya SIN, Poshyachinda V. Evaluation of a targeted HIV prevention programme among female commercial sex workers in the south of Thailand. Sexually Transmitted Infections. 1998;74:54–58. [PMC free article] [PubMed]
- Vaz RG, Gloyd S, Trindade R. The effect of peer education on STD and AIDS knowledge among prisoners in Mozambique. International Journal of STD and AIDS. 1996;7:51–54. [PubMed]
- Visser M. Evaluation of the first AIDS Kit, the AIDS and lifestyle education programme for teenagers. South African Journal of Psychology. 1996;26:103–113. [PubMed]
- Walden VM, Mwangulube K, Makhumula-Nkhoma P. Measuring the impact of a behaviour change intervention for commercial sex workers and their potential clients in Malawi. Health Education Research. 1999;14:545–554. [PubMed]
- Walter HJ, Vaughan RP. AIDS risk reduction among a multiethnic sample of urban high school students. JAMA. 1993;270:725–730. [PubMed]
- Wang MC, Bushman BJ. Cary, NC: SAS Institute; 1999. Integrating results through meta-analytic review using SAS software.
- Waters JA, Morgen K, Kuttner P, Schmitt B. The Guiding Adolescents to Prevention program: Reducing HIV transmission and drug use in youth in a detention center. Crisis Intervention. 1996;3:85–96.
- Week K, Levy SR, Zhu C, Perhats C, Handler A, Flay BR. Impact of a school-based AIDS prevention program on young adolescents’ self-efficacy skills. Health Education Research. 1995;10:329–344.
- Weinhardt LS, Carey KB, Carey MP. HIV risk sensiti-zation following a detailed sexual behavior interview: A preliminary investigation. Behavioral Medicine. 2000;23:393–398. [PubMed]
- Weinhardt LS, Carey MP, Carey KB, Verdecias RN. Increasing assertiveness skills to reduce HIV risk among women living with a severe and persistent mental illness. Journal of Consulting and Clinical Psychology. 1998;66:680–684. [PubMed]
- Weinhardt LS, Carey MP, Johnson BT, Bickham NL. Effects of HIV counseling and testing on sexual risk behavior: A meta-analytic review of published research, 1985–1997. American Journal of Public Health. 1999;89:1397–1405. [PubMed]
- Wenger NS, Linn LS, Epstein M, Shapiro MF. Reduction of high-risk sexual behavior among heterosexuals undergoing HIV antibody testing: A randomized clinical trial. American Journal of Public Health. 1991;81:1580–1585. [PubMed]
- Winett RA, Anderson ES, Moore JF, Taylor CD, Hook RJ, Webster DA, et al. Efficacy of a home-based human immunodeficiency virus prevention video program for teens and parents. Health Education Quarterly. 1993;20:555–567. [PubMed]
- Winkelstein W, Jr, Lyman DM, Padian N, Grant R, Samuel M, Wiley JA, et al. Sexual practices and risk of infection by the human immunodeficiency virus. The San Francisco Men’s Health Study. JAMA. 1987;16:321–325. [PubMed]
- Wober JM. Informing the British public about AIDS. Health Education Research. 1988;3:19–24.
- Wyer RS, Srull TK. Memory and cognition in its social context. Hillsdale, NJ: Erlbaum; 1989.
- Xiaoming S, Yong W, Choi KH, Lurie P, Mandel J. Integrating HIV prevention education into existing family planning services: Results of a controlled trial of a community-level intervention for young adults. AIDS and Behavior. 2000;4:103–110.
- Yarber WL, Torabi MR. Impact of a theory-based, school HIV/STD curriculum on eighth graders’ attitudes and knowledge. Journal of Health Education. 1997;28:74–81.
- Yzer MC, Siero FW, Buunk BP. Can public campaigns effectively change psychological determinants of safer sex? An evaluation of three Dutch campaigns. Health Education Research. 2000;15:339–352. [PubMed]