Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2016 Mar 8.
Published in final edited form as: Health Psychol. 2008 Sep;27(5):638–644. doi: 10.1037/0278-6133.27.5.638

Beyond the Most Willing Audiences: A Meta-Intervention to Increase Exposure to HIV-Prevention Programs by Vulnerable Populations

Dolores Albarracín 1, Marta R Durantini 2, Allison Earl 3, Joanne B Gunnoe 4, Josh Leeper 5
PMCID: PMC4783148  NIHMSID: NIHMS454538  PMID: 18823190

Abstract

Objective

Enrollment in HIV-prevention interventions is more likely when the audience has safer rather than riskier HIV-relevant behavior. Thus, a meta-intervention was designed to increase participation by an audience of infrequent condom users in Florida.

Design

Participants (N = 400) were randomly assigned to 1 of 4 conditions varying the introduction to a counseling program. In the experimental condition, participants were told that the intervention gave participants options but might not change their behavior. In a standard-introduction condition, participants were told that the program was highly effective at changing participants’ behaviors. There was also an information-control group containing a description of the program, and a no-information-control group solely containing an invitation.

Main outcome measures

The outcome measure was actual participation in the offered counseling.

Results

Findings indicated that the experimental introduction was the most successful at yielding participation in the counseling program when the audience had low intentions to use condoms in the future.

Conclusion

Intervention introductions countering participants’ resistance to change increase participation in HIV-prevention counseling among reluctant clients. Other meta-interventions may be explored to systematically augment the effectiveness of evidence-based health-promotion interventions.

Keywords: HIV prevention, intervention, selective exposure, health behavior, participation in health promotion programs

A number of interventions have been produced to change behaviors that put people at risk for HIV (Albarracin et al., 2005; Centers for Diseases Control and Prevention, 2001). These interventions are typically tested under conditions that ensure the validity of the outcome assessments (Cook & Campbell, 1979). Thus, researchers try to involve community members to see if a particular intervention works for them. Social networks are called on to recruit these participants and numerous incentives and facilitators are used to ensure the desired sample of exposed participants (Ehrhardt et al., 2002; Rabinowitz, 2002; Raj et al., 2001; Tobias, Wood & Drainoni, 2006). Although these procedures are necessary to determine if a program works for an exposed population, they remove the reluctance to participate present when the intervention is implemented (Catania, Gibson, Chitwood, & Coates, 1990; Lauby, Kotranski, Feighan, & Collier, 1996).

Despite the dominant approach to intervention research, in real-world conditions, people choose to take part in preventive interventions (DiFrancesco et al., 1998; Hennessy, Mercier, Williams, & Arno, 2002; Veach, Ramley, Kippers, & Sorg, 2000). Given limited time and interest, clients of health facilities can accept or refuse to take part in an HIV-prevention counseling session (Grady, Kegeles, Lund, Wolk, & Farber, 1983; Minder, Müller, Gillmann, Beck, & Stuck, 2002). Moreover, some of the audiences most vulnerable to HIV are the least likely to enroll in HIV-prevention interventions (Noguchi et al., 2007; Yancey, Ortega, & Kumanyika, 2006). In particular, frequent condom users are more likely to enroll in pro-condom-use interventions than infrequent ones (Noguchi et al., 2007). Thus, efficacious interventions may never reach these vulnerable audiences.

Given that interventions need to reach vulnerable audiences—not just willing ones—it is imperative to develop and test procedures that increase participation by these populations. Procedures can be designed to change an audience’s behavior with respect to the preventive interventions themselves, including participation in them. These procedures, hereafter termed meta-interventions, entail a standardized introduction or context change (e.g., delivery setting) intended to increase exposure to a behavioral intervention. In the present study, participants with prior infrequent condom use were offered an HIV-counseling session using one of four scripted introductions to the program. A randomly assigned meta-intervention conveying that counseling participants are free to not change was expected to be more effective than other introductions (one promising change and another providing basic information about the counseling) or no introduction (just an offer to take part). Unobtrusive observers recorded the extent to which participants agreed to the counseling when asked and also collected supplementary data on participants reading of brochures and viewing of videos. The present paper focuses on acceptance of the counseling as a function of the meta-intervention.

Defining meta-interventions opens the door to a systematic empirical analysis of how to increase the effectiveness of available programs. To our knowledge, no program introduction has ever been validated to increase participation in health-promotion interventions. Nonetheless, if simple meta-interventions, such as the introduction to the program, are developed, there will be more tools to promote behavior change in vulnerable populations. These tools may significantly advance public health toward the use of inexpensive devices that augment the effectiveness of existing interventions. One such device was designed in this research, and tested using a randomized-controlled trial.

A Meta-Intervention to Increase Participation in HIV-Risk-Reduction Counseling

Any intervention to change behavior faces resistance on the part of participants (Albarracín & Mitchell, 2004; Canon, 1964; Watzlawick, Weakland, & Fisch, 1974). This resistance is expressed at many levels, including refusal to participate, lack of attention to the program, drop out, and reactance against the program recommendation. Given that participation is the first roadblock on the way to intervention effectiveness, having a technique to increase enrollment in HIV-prevention interventions is key.

When practitioners want a client to enroll in an HIV-prevention program, how should they issue this invitation? How should out-reach workers promote a counseling program to community members? Clinical observations suggest that a common strategy is to support the program offer with a justification about the appropriateness of the program to solve a particular problem (Donawa, 2006; Stewart-Williams & Podd, 2004). Nonetheless, theories about behavior change and social communication principles imply potential problems for this approach. On the one hand, this meta-intervention may be received with relief that the public health system can provide a solution to the problems of community members. It may also increase recipients’ efficacy in their own ability to change (Bandura, 1989: Fisher & Fisher, 1992). On the other hand, this meta-intervention does not empower the audience because the program is described as responsible for the change. Moreover, describing interventions as effective obscures the fact that not all HIV-intervention recipients change (Albarracín et al., 2005; Herbst et al., 2005; Johnson et al., 2002; Weindhart, Carey, Johnson, & Bickham, 1999). From this point of view, a different meta-intervention may have greater credibility.

A more empowering meta-intervention consistent with extant evidence on behavior change entails presenting the recipient as the motor of the behavior change. One such strategy is to emphasize that the program cannot change behavior unless the person does so. First, this type of meta-intervention may yield a more active role on the part of recipients by placing the burden of change on them (Amaro, 1995, 2000; Freire, 1972; Putnam, 1911). That is, people who are told that change is up to them may be encouraged to seek ways to change. Second, people are more likely to expose themselves to persuasive communications if they believe that they can resist their influence (Albarracín & Mitchell, 2004; Brehm, 1972; Brehm & Cohen, 1962; Watzlawick, 1978). As infrequent condom users often do not want to use condoms (Albarracín, Johnson, Fishbein, & Muellerleile, 2001), highlighting the option of resistance may increase exposure among these participants.

The Present Research

A sample of sexually active men and women with infrequent past condom use was recruited for a health interview. Halfway through the interview, the interviewer paused the administration, announcing a 30-min break. At this point, an observer/counselor entered the room to do work unrelated to the interview, and unobtrusively observed the participant’s exposure to the available intervention (Webb, Campbell, Schwartz, & Sechrest, 1966). Of interest in this paper, participants had the opportunity to participate in a brief HIV-risk-reduction counseling session. Thus, the participation behavior could be recorded and analyzed as a function of a scripted introduction accompanying the counseling offer. The key meta-intervention consisted of offering the counseling in a way that emphasized that the participant was free to not change (experimental condition). The other three conditions entailed stating that the counseling was successful at inducing condom use (standard), simply describing the counseling (information control), or simply offering the counseling (no information control). Analyses were conducted for the overall sample as well as for break-downs of condom-use intenders and nonintenders.

Method

Participants and Design

Participants were 400 community members (295 women and 105 men) from the Gainesville (FL) area. They were paid $5 for the eligibility screening and $40 for participation in the main study if eligible. Noneligible participants were paid a total of $5, and completers were paid a total of $45. The design was a randomized-controlled trial with four meta-intervention conditions (experimental, standard, information control, and no-information control).

Procedures

Recruitment

Patients were either recruited by flyers placed in the community and around the health department, or through a personal referral from members of the community or the staff of clinics of the health department. To prevent contamination and reduce self-selection, the flyer and instructions for referrals described the study as a “general health study;” there was no mention of HIV or condom use in either the flyer or the referral instructions.

To make an appointment, participants called a designated number. During this phone call, a brief eligibility prescreening (ages 18 to 50) was conducted. Participants had to be sexually active, not be pregnant or be trying to get pregnant, and report using condoms “never,” “almost never,” or “sometimes” during the last 6 months. Individuals reporting to be sexually inactive, pregnant, trying to get pregnant, or using condoms “almost always” or “always” were excluded.

Rescreening, procedures, and measures

The random assignment of participants was done using a random number generator and assigning time slots to conditions. When participants arrived for their interview, they checked in at the front desk of the Alachua County Health Department and waited to be seen. When the interviewer was ready, the participant was taken to the interview room where s/he was rescreened for eligibility using the brief phone questionnaire. If the participant was still eligible, the interview began.

An interviewer and a counselor were involved during each session. The interviewer recorded gender, age, past condom use, presence of a main sexual partner, years of education, income, and ethnicity. There were also general health questions (e.g., “Do you feel tightness in your chest? YES/NO,” “On average, how many cigarettes do you smoke per day?”), including number of past STD/STIs (“In the past year, how many times have you had a sexually transmitted disease such as Syphilis, Gonorrea, Herpes, and Chlamydia?”) and questions about condom use. The questions about condom use included items measuring intentions to use condoms with main and occasional partners, with the partner types defined subjectively by the participants (M number of months of relationship with main partner = 83 months, SD = 87). These two measures were averaged in analysis. Specifically, using scales with numerical anchors of 1 to 7, participants answered the questions: “How likely is it that, for the next six months, you and your main (occasional) partner will use a condom every time you have vaginal sex?,” “How strong are your intentions to use condoms with your main (occasional) partner in the next six months?,” and “How motivated are you to use condoms with your main (occasional) partner in the next six months?” The six intention items had a Cronbach’s alpha of .80 and were averaged as a measure of intentions to use condoms at baseline.

After approximately 30 min elapsed, and while the first part of the interview was being completed, the counselor knocked on the door of the interview room and requested to use the space to do some work. The interviewer responded that they were in the middle of the interview, but that s/he would call the counselor during the break. Subsequently, when the first half of the questionnaire was complete, the interviewer called the counselor and excused her/himself from the room.

This break provided opportunities for measuring exposure to various materials and the counseling itself. While the counselor was in the room, the participant had 10 min to peruse the six brochures sitting on the table. After 10 min elapsed, the interviewer knocked on the door and offered the participant a 10-min video about HIV. The client could either accept or decline to watch the video. Next, the interviewer returned and offered the participant the option of undergoing an HIV-prevention counseling session. If the participant previously accepted the video, the interviewer waited 10 min before returning to offer the counseling. In contrast, if the participant declined to watch the video, the interviewer would only wait 5 min before returning to the room to offer the counseling to the participant. After the interviewer offered the counseling, if the participant accepted, the counselor was asked to administer the counseling session and call the interviewer afterward. If the participant declined, the interviewer exited the room and returned 5 min later to administer the remainder of the questionnaire. Our key outcome measure was acceptance of this counseling session. The measures of exposure to the brochures and video are of concern in other reports. After these opportunities to observe exposure, participants responded to another set of questions, including their intentions to use condoms in the future. These immediate follow-up measures were used for supplementary analyses of change.

The counseling session was adapted from Project Respect (see Kamb et al., 1998), and focused on condom use behavioral skills, condom use negotiation skills, and self-management skills—skills to promote perceived behavioral control over condom use despite unfavorable mood or circumstances (Kelly, St. Lawrence, Betts, Brasfield, & Hood, 1990). The counseling session also served to correct misconceptions about HIV and HIV transmission as well as to foster positive attitudes toward condom use (Fisher & Fisher, 1992, 2000). Nonetheless, we were interested in acceptance of the counseling and not on the counseling session itself.

Checks for potential contamination, sensitivity of the exposure measure, and debriefing

A naïve sample unaware of the observation is necessary for this type of study. Thus, during the prescreening, participants were asked what they had heard about the study. Participants who mentioned condoms, HIV, brochures, videos, or counseling were excluded from participation. At the end of the study, participants were asked whether they had an appointment for HIV counseling and testing, which could reduce the sensitivity of our counseling-exposure measure. Finally, participants were fully debriefed by reading them an extended explanation of the study, the objectives, and the need for the unobtrusive observation without their knowledge. No participant reported suspecting that they were being observed.

Meta-Intervention Conditions

Two years of pilot work with community members and professionals provided the qualitative and quantitative data to develop the meta-intervention. The final pilot work indicated that all introductions were clear, and the experimental manipulation in fact produced greater perceptions of freedom than the other conditions.

Attempts were made to vary the introductions of the brochures and the video. With this objective, small signs were posted next to the brochures and a scripted introduction for the video was attempted. In practice, however, participants paid no attention to the signs and the introduction of the video was frequently interrupted because most participants readily accepted the video. In contrast, the introduction to the counseling could be fully delivered and evaluated. Depending on experimental conditions, at the moment the counseling session was offered to the participant, the interviewer could give one of the following introductions:

  • Experimental meta-intervention: While you are waiting, you have the choice to speak with a certified HIV-prevention counselor. The counseling session provides information about HIV and condom use. It will also help you figure out your risk for HIV infection. The point of the counseling session is to provide you with the most current information, not to influence your opinion or make you use condoms if you don’t want to. [Would you be interested?]

  • Standard meta-intervention: While you are waiting, you have the choice to speak with a certified HIV-prevention counselor. The counseling session provides information about HIV and condom use. It will also help you figure out your risk for HIV infection. A counselor can show you ways to help you make your behavior safer. Most of the people who participate in counseling said that it improved their lives and they wished they had participated sooner. [Would you be interested?]

  • Information-only control: While you are waiting, you have the choice to speak with a certified HIV-prevention counselor. The counseling session provides information about HIV and condom use. It will also help you figure out your risk for HIV infection. [Would you be interested?]

  • No-information-control: While you are waiting, would you be interested in taking part in a counseling session?

Results

Preliminary Analyses

Description of sample

Participants were 400 community members living in Alachua County (FL). Seventy-four percent of the participants were women, the M age was 33.73 (SD = 10.41), and the sample was ethnically diverse (59% African American, 34% European American, 4% Latino American, 1% American Indian, 1% Asian American, 3% other ethnicities). Fifty-four percent of the sample had an income of less than $10,000 a year, and 78% graduated from high school, with an average of 12.77 (SD = 2.45) years of school. Ninety-five percent of the sample reported having a main partner, and 19% of the participants reported having an STD/STI in the previous year. In terms of reported condom use in the previous 6 months, 46% of the participants never used them, 36% used them sometimes, and 19% almost never used them.

With respect to the behavior during the interview, participants read an average of 1.76 brochures (SD = 1.85). In addition, 84% accepted to watch the video and 52% accepted the counseling. Only 3 participants had appointments to obtain HIV counseling and testing in the appropriate clinic, but excluding them did not alter the study findings. Reactions to the debriefing were favorable in all cases. Representative comments were “Wow, this is really interesting!” “Keep up the good work;” “Can I sign my brother/sister/daughter/son up for this?”

Correlates of exposure to the counseling

Exposure to the counseling (1 = yes, 0 = no) was analyzed in relation to gender, age, years of education, income, ethnicity, number of past STD/STIs, and having a main partner. Due to the exploratory nature of these analyses, these predictors were introduced in a forward logistic regression that used Likelihood Ratios to identify the most critical predictors. Age, income, years of education, and number of past STDs were continuous predictors, whereas gender, race, and having a main partner were categorical predictors. This analysis only retained ethnicity as a significant predictor of participation in counseling. In particular, African Americans participated in counseling more than European Americans (59% vs. 29%). Given its influence, this predictor was used in the main analyses.

Ruling out differences across experimental conditions

We also analyzed gender, age, years of education, income, race, past condom use, number of past STD/STIs, and presence of a main partner as a function of experimental condition. These analyses entailed ANOVA for continuous dependent measures (including the average of condom use scales across main and occasional partners) and chi-squares for discrete dependent measures, and are summarized in Table 1. We found a significant difference between the number of reported STD/STIs between the information-only and no-information-control conditions, for contrast: F(1, 396) = 6.2, p < .001. In addition, there were marginal differences in the presence of main partners as well as education (see Table 1). These three variables were controlled for in the main analysis of the effect of the meta-intervention.

Table 1.

Differences in Intentions, Past Condom Use, and Demographic Variables Across Experimental Conditions

Variable Experimental
meta-intervention
(N = 112)		 Standard
(N = 111)		 Information
control
(N = 117)		 No-information
control
(N = 60)		 Comparison across
all conditions		 Comparison across
experimental versus
control conditions
Intentions to use condoms 4.43 4.51 4.53 4.43 F (3, 393) = 0.14 F (1, 395) = 0.22
Past condom use 2.10 2.06 1.88 1.96 F (3, 393) = 0.95 F (1, 395) = 1.36
Age 34.27 33.69 33.55 33.15 F (3, 393) = 0.17 F (1, 395) = 0.42
Gender χ2 (3, N = 400) = 5.57 χ2 (1, N = 400)) = 0
  Women 75% 80% 67% 75%
  Men 25% 20% 33% 25%
Income level 16,850 18,270 17,010 18,310 F (3,393)=0.55 F (1,395)=0.62
Number of STIs in past year 0.24 0.18 0.09 0.29 F (3, 393) = 2.89** F (1, 395) = 1.97
Has a main partner χ2 (3, N = 400)) = 7.02* χ2 (1, N = 400)) = 1.92
  Yes 92% 93% 99% 93%
  No 8% 7% 1% 7%
Years of education 12.51 13.26 12.67 12.53 F (3, 393) = 2.19* F (1, 395) = 1.77
Ethnicity χ2 (6, N = 400)) = 6.62 χ2 (1, N = 400)) = 2.32
  African American 63% 51% 60% 55%
  European American 29% 37% 34% 40%
  Other 8% 12% 6% 5%
Open in a new tab

Note. Unless otherwise indicated, all entries are means. Income was coded from 1 = 0 to 9,999 to 8 = 80 to 89,999.

*

p < .10.

**

p < .05.

Test of Hypothesis

Overall effect of meta-intervention

We hypothesized that the experimental introduction to the program would be the most effective. The relevant percentages of participation are depicted in Figure 1A (experimental = 59%, standard = 54%, information only = 51%, and no-information = 45%). Statistical analyses were conducted using logistic regressions that compared each condition with each other, as well as (a) the experimental and standard conditions with the information-only and no-information control and (b) the experimental condition with all other conditions. Condom use intentions as reported at baseline were also included in the model as they have been shown to influence participation in interventions (Noguchi et al., 2007). The results from these analyses revealed that even when the experimental condition had the highest percentage of acceptance; it did not differ significantly from the standard condition. Both conditions, however, significantly differed from the information-only and no-information controls, whereas these two controls did not differ from each other. The results from this comparison appear in the top panel of Table 2.

Figure 1.

Figure 1

Open in a new tab

Percentage of participation in counseling as a function of experimental condition. The top panel presents all participants. The bottom panel presents participants with low intentions to use condoms at baseline.

Table 2.

Analysis of the Effects of Experimental Conditions on Acceptance Rates

Variable Logit
coefficient		 Odd
ratio		 95% Confidence
interval		 p
Overall sample −1.07 0.34 0.65 1.47 .92
  No. of STIs in past year (continuous) −0.02 0.98
  Having a main partner (dummy variable) 0.22 1.25 0.52 3.01 .62
  Ethnicity (continuous) .02*
    African American (vs. European American) 0.58 1.79 1.15 2.76 .01**
    African American (vs. other) −0.18 0.89 0.41 1.96 .77
  Condom use intentions (continuous) 0.06 1.06 0.99 1.14 .12
  Experimental and standard versus information-only and no-information conditions (dummy variable) 0.41 1.50 1.00 2.26 .05*
Low-intention group
  Constant −0.61 0.55
  Number of STIs in past year (continuous) −0.05 0.95 0.51 1.77 .88
  Having a main partner (dummy variable) 0.09 1.09 0.25 4.70 .91
  Ethnicity (continuous) .11
    African American (vs. European American) 0.52 1.69 0.94 3.03 .08
    African American (vs. other) −0.37 0.69 0.27 2.29 .54
  Experimental versus control conditions (dummy variable) 0.69 1.99 1.05 3.78 .04*
Open in a new tab
*

p < .05.

**

p < .001.

Effects of meta-intervention among participants with low intentions to use condoms at baseline

Ideally, interventions should reach vulnerable audiences that are not considering change, not simply willing audiences. Thus, it was important to verify that our meta-intervention increased participation even when participants had low intentions to use condoms, based on a median split for baseline intentions. Raw percentages for the low-intention group appear in Figure 1B (experimental = 60%, standard = 45%, information-only = 42%, and no-information = 41%). Logistic regression analyses for this group of participants revealed no significant differences across the standard, information-only, and no-information conditions. However, according to expectations, the experimental meta-intervention significantly differed from the other three conditions. This analysis suggests that the meta-intervention was in fact effective for the population that has the highest need for it.1

One potential concern, however, might be that the meta-intervention might attract low intenders, yet these participants may not change when exposed to the intervention. To examine this possibility, we analyzed the effect of the counseling on change in intentions as a function of initial intentions. Specifically, intentions at baseline were subtracted from intentions at the end of the study and these scores were regressed on a dummy variable for presence or absence of counseling, initial intentions, and the interaction between the two. Results revealed a significant interaction between initial intentions and reception of counseling (βintentions = −0.10, ns, βcounseling = 1.05, p < .001, βinteraction = −0.86, p < .001). This pattern underlying this interaction was such that the counseling had a more positive effect among low than high intenders (βcounseling = 0.39, p < .001, vs. 0.11, ns).

Discussion

Several decades of HIV-prevention-intervention research have yielded ample knowledge of how interventions change the behavior of the targets (for a review, see e.g., Albarracin et al., 2005). This sophisticated body of knowledge has also provided the tools to reduce HIV infection among the most vulnerable populations in the world (Albarracín et al., 2005; Herbst et al., 2005; Johnson et al., 2002; Weinhardt, Carey, Johnson, & Bickham, 1999). Nonetheless, existing interventions have not been designed to influence participants’ participation, just behavior change when participation is a given. In this context, this study’s contribution is to validate the first meta-intervention to increase participation.

In this study, a randomized-controlled trial with a high-risk sample of people from the Southeast of the United States confirmed that the counseling introduction determines participation by vulnerable audiences. Specifically, a counseling program attracted most participants when the offer highlighted the audience’s options rather than behavior change. More important, this program was superior to all the controls when the audience did not intend to use condoms in the future (see Figure 2).

As a result of this work, a seconds-long meta-intervention is available that adds little or no cost to the existing HIV-prevention programs but can multiply its effectiveness. Moreover, our meta-intervention may also amplify intervention efficacy, by making participants more sensitive to the contents of upcoming interventions. For example, future research may determine whether the program introduction influences involvement with and corresponding attention to the counseling program. Likewise, people may be better retained by multisession HIV-prevention programs when they are open to start the intervention. This hypothesis may also be examined by future work.

Some limitations must be noted, however. First, not all populations may react equally well to the validated meta-intervention. Our technique was tested with a predominantly female and African American sample, and power was insufficient to look at effectiveness across demographic groups. Hence, the generalizability of this meta-intervention across populations needs to be established in the future. Second, the meta-intervention was designed for recruitment in contexts of a relatively anonymous target audience (i.e., a waiting room). Although similar techniques may be developed for a close professional–patient interaction, this adaptation has not yet been conducted. Similarly, the same program may be adapted for wide-reaching promotion of HIV-prevention programs, including counseling and testing. For example, videos with messages that convey the audience’s freedom may be developed for use in the media or large-scale health facilities, but this approach would require further research work.

In closing, other systematic meta-interventions could be designed to more effectively deliver and target the arsenal of successful programs currently available. For example, simple devices to increase systematic attention to the counseling program are likely to increase behavioral impact. Similarly, specific procedures may increase later recall of behavioral commitments made during a counseling session, thus enhancing the behavioral-change impact of commonly used behavioral-skills training. We hope that this work will stimulate such developments to reduce infection with HIV.

Footnotes

1

A formal statistical test indicated no-significant interaction between condition and initial condom use intentions. Nonetheless, the low-intention group is the most relevant from a public health perspective and thus was analyzed separately in addition to the overall analyses. Similar analyses revealed no differences across conditions for the group with high initial intentions to use condoms.

Contributor Information

Dolores Albarracín, University of Illinois at Urbana Champaign.

Marta R. Durantini, University of Florida

Allison Earl, University of Illinois at Urbana Champaign.

Joanne B. Gunnoe, Alachua County Health Department, Gainesville, Florida

Josh Leeper, University of Florida.

References

  1. Albarracín D, Mitchell AL. The role of defensive confidence in preference for proatttitudinal information: How believing that one is strong can be a weakness. Personality and Social Psychology Bulletin. 2004;30:1565–1584. doi: 10.1177/0146167204271180. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. 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. doi: 10.1037/0033-2909.127.1.142. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Albarracín D, Gillette J, Earl A, Glasman LR, Durantini MR, Ho MH. A test of major assumptions about behavior change: A comprehensive look at HIV prevention interventions since the beginning of the epidemic. Psychological Bulletin. 2005;131:856–897. doi: 10.1037/0033-2909.131.6.856. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Amaro H. Love, sex, and power: Considering women’s realities in HIV prevention. American Psychologist. 1995;50:437–447. doi: 10.1037//0003-066x.50.6.437. [DOI] [PubMed] [Google Scholar]
  5. Amaro H. On the margin: Power and women’s HIV risk reduction strategies. Sex Roles. 2000;42:723–749. [Google Scholar]
  6. 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. [Google Scholar]
  7. Brehm JW. Responses to loss of freedom: A theory of psychological reactance. Morristown, New Jersey: General Learning Corporation; 1972. [Google Scholar]
  8. Brehm JW, Cohen AR. Explorations in cognitive dissonance. New York: Wiley; 1962. [Google Scholar]
  9. Canon LK. Self-confidence and selective exposure to information. In: Festinger L, editor. Conflict, decision, and dissonance. Vol. 1. Stanford, CA: Stanford University Press; 1964. pp. 83–95. [Google Scholar]
  10. Catania JA, Gibson DR, Chitwood DD, Coates TJ. Methodological problems in AIDS behavioral research: Influences on measurement error and participation bias in studies of sexual behavior. Psychological Bulletin. 1990;108:339–362. doi: 10.1037/0033-2909.108.3.339. [DOI] [PubMed] [Google Scholar]
  11. Center of Disease Control and Prevention. HIV/AIDS prevention research synthesis project. Compendium of HIV prevention interventions with evidence of effectiveness. Atlanta, GA: Author; 2001. [Google Scholar]
  12. Cook TD, Campbell DT. Quasi-experimentation: Design and analysis issues for field settings. Boston: Houghton Mifflin; 1979. [Google Scholar]
  13. DiFrancesco W, Kelly JA, Sikkema KJ, Somlai AM, Murphy DA, Stevenson LY. Differences between completers and early dropouts from 2 HIV intervention trials: A health belief approach to understanding prevention program attrition. American Journal of Public Health. 1998;88:1068–1073. doi: 10.2105/ajph.88.7.1068. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Donawa M. US regulation of advertising and promotional materials: Medical device manufacturers do not always properly control the development of new or modified promotional labeling and advertising materials. Medical Device Technology. 2006;17:26. [PubMed] [Google Scholar]
  15. Ehrhardt AA, Exner TM, Hoffman S, Silberman I, Lew CS, Miller S, et al. A gender-specific HIV/STD risk reduction intervention for women in a health care setting: Short-and long-term results of a randomized clinical trial. AIDS Care. 2002;14:147–161. doi: 10.1080/09540120220104677. [DOI] [PubMed] [Google Scholar]
  16. Fisher JD, Fisher WA. Changing AIDS-risk behavior. Psychological Bulletin. 1992;111:455–474. doi: 10.1037/0033-2909.111.3.455. [DOI] [PubMed] [Google Scholar]
  17. 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; 2000. pp. 3–55. [Google Scholar]
  18. Freire P. Pedagogy of the oppressed. Harmondsworth, England: Penguin; 1972. [Google Scholar]
  19. Grady KE, Kegeles SS, Lund AK, Wolk CH, Farber NJ. Who volunteers for a breast self-examination program? Evaluating the bases for self-selection. Health Education Quarterly. 1983;10:79–94. doi: 10.1177/109019818301000201. [DOI] [PubMed] [Google Scholar]
  20. Hennessy M, Mercier M, Williams SP, Arno JN. Client preferences for STD/HIV prevention programs. Evaluation and Program Planning. 2002;25:117–124. [Google Scholar]
  21. Herbst JH, Sherba RT, Crepaz N, Deluca JB, Zohrabyan L, Stall RD, et al. HIV/AIDS prevention research synthesis team. A meta-analytic review of HIV behavioral interventions for reducing sexual risk behavior of men who have sex with men. Journal of Acquired Immune Deficiency Syndrome. 2005;39:228–241. [PubMed] [Google Scholar]
  22. Johnson WD, Hedges LV, Ramirez G, Semaan S, Norman LR, Sogolow E, Sweat MD, Diaz RM. HIV prevention research for men who have sex with men: A systematic review and meta-analysis. Journal of Acquired Immune Deficiency Syndrome. 2002;1:S118–S129. [PubMed] [Google Scholar]
  23. Kamb ML, Fishbein M, Douglas-JM J, 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. Journal of the American Medical Association. 1998;280:1161–1167. doi: 10.1001/jama.280.13.1161. [DOI] [PubMed] [Google Scholar]
  24. 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] [Google Scholar]
  25. Lauby J, Kotranski L, Feighan K, Collier K. Effects of intervention attrition and research attrition on the evaluation of an HIV prevention program. Journal of Drug Issues. 1996;26:663–677. [Google Scholar]
  26. Minder CE, Müller T, Gillmann G, Beck JC, Stuck AE. Subgroups of refusers in a disability prevention trial in older adults: Baseline and follow-up analysis. American Journal of Public Health. 2002;92:445–450. doi: 10.2105/ajph.92.3.445. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Noguchi K, Durantini MR, Albarracín D, Glasman LR. Non-random attrition in HIV prevention. Psychological Bulletin. 2007;133:955–975. doi: 10.1037/0033-2909.133.6.955. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Putnam RD. Making democracy work. Princeton, NJ: Princeton University Press; 1911. [Google Scholar]
  29. Rabinowitz DC. Predictors of attrition in a predominantly Caucasian middle-class clinic-based weight loss program. Dissertation Abstracts International, Section B. 2002;62:5796. [Google Scholar]
  30. Raj A, Amaro H, Cranston K, Martin B, Cabral H, Navarro A, et al. 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. doi: 10.1093/phr/116.6.599. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Stewart-Williams S, Podd The placebo effect: Dissolving the expectancy versus conditioning debate. Psychological Bulletin. 2004;130:324–340. doi: 10.1037/0033-2909.130.2.324. [DOI] [PubMed] [Google Scholar]
  32. Tobias C, Wood S, Drainoni ML. Ryan White title 1 survey: Services for HIV-positive substance users. AIDS Patient Care and STDs. 2006;20:58–67. doi: 10.1089/apc.2006.20.58. [DOI] [PubMed] [Google Scholar]
  33. Veach LJ, Ramley TP, Kippers SM, Sorg JD. Retention predictors related to intensive outpatients programs for substance use disorders. American Journal of Drug Alcohol Abuse. 2000;26:417–428. doi: 10.1081/ada-100100253. [DOI] [PubMed] [Google Scholar]
  34. Watzlawick P. The language of change: Elements of therapeutic communication. New York: Norton; 1978. [Google Scholar]
  35. Watzlawick P, Weakland J, Fisch R. Principles of problem formation and resolution. New York: Norton; 1974. [Google Scholar]
  36. Webb EJ, Campbell DT, Schwartz RD, Sechrest L. Unobtrusive measures: Nonreactive research in the social sciences. Chicago: Rand McNally; 1966. [Google Scholar]
  37. Weinhardt LS, Carey MP, Johnson BT, Bickham N. Effects of HIV counseling and testing on sexual risk behavior: Meta-analytic review of published research, 1985–1997. American Journal of Public Health. 1999;89:1397–1405. doi: 10.2105/ajph.89.9.1397. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Yancey AK, Ortega AN, Kumanyika SK. Effective recruitment and retention of minority research participants. Annual Review of Public Health. 2006;27:1–28. doi: 10.1146/annurev.publhealth.27.021405.102113. [DOI] [PubMed] [Google Scholar]

RESOURCES