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A 15-Minute Interactive, Computerized Condom Use Intervention With Biological Endpoints

Grimley, Diane M. PhD*†‡; Hook, Edward W. III MD†§

Sexually Transmitted Diseases: February 2009 - Volume 36 - Issue 2 - p 73-78
doi: 10.1097/OLQ.0b013e31818eea81

Background: Brief face-to-face-behavioral interventions have been shown to be efficacious, but are costly to sustain and to widely disseminate. This study evaluated the efficacy of a 15-minute theory-based behavioral intervention designed to increase condom use and reduce new cases of Neisseria gonorrhoeae and Chlamydia trachomatis.

Methods: Participants were randomly assigned via the computer to the intervention or the comparison group stratified by gender and their baseline stage of change (motivational readiness) for using condoms consistently (100%) with their main partners. Behavioral data and biologic specimens for testing of Neisseria gonorrhoeae and Chlamydia trachomatis were obtained at baseline and at 6 months post intervention. The intervention was delivered via an audio, multimedia, computerized application that provided individualized interventions to patients based on their responses to assessment items; comparison patients interacted with a 15-minute, computerized, multiple health risk assessment with no intervention.

Results: The majority of the sample (N = 430) was black (88%); 54.5% women; with a mean age = 24.5. Assuming all participants who did not return to the clinic at 6 months were not using condoms consistently, 32% of the treatment group versus 23% in the comparison group reported consistent condom use (P = 0.03). The combined Neisseria gonorrhoeae and Chlamydia trachomatis incidence declined to 6% in the intervention group versus 13% in the comparison group (P = 0.04). Results from a regression analysis revealed that the only statically significant predictor of sexually transmitted diseases infection at the follow-up was group assignment (OR = 1.91, 95% confidence index = 1.09–3.34; P = 0.043).

Conclusions: These findings suggest that brief, interactive, computer-delivered interventions provided at the evaluation visit increase condom use and reduce sexually transmitted diseases without putting additional burden on clinicians or staff.

A brief computerized, individualized intervention provided to patients at the sexually transmitted diseases clinic during the evaluation visit can increase condom use and reduce sexually transmitted diseases.

From the *Department of Health Behavior, School of Public Health, the Divisions of †Infectious Diseases and the ‡Preventive Medicine, School of Medicine, and the §Department of Epidemiology, School of Public Health, University of Alabama, Birmingham, AL

The authors thank Lucy Annang, PhD, the Jefferson County Department of Health, the STD clinic staff, our recruiters, and our study participants.

Supported by NIH (Grant No. U19AI35814-06, to NIAID).

Correspondence: Diane Marie Grimley, PhD, 1665 University Blvd, RPHB 227, Birmingham, AL 35294-0022. E-mail:

Received for publication April 16, 2008, and accepted September 8, 2008.

PROVISION OF SEXUALLY TRANSMITTED DISEASE (STD) prevention counseling in settings such as busy STD clinics may be constrained by competing priorities for the use of clinical time.1 Nonetheless, counseling for risk reduction can change self-reported risk behaviors and prevent new STDs among patients attending public STD clinics. Further, clinic visits for acute care may be the only opportunity to promote risk reduction behaviors to some persons at increased risk.

Project RESPECT,2 a multicenter, randomized-controlled trial demonstrated the efficacy of brief counseling interventions designed for changing risk behaviors and prevention of new infections among STD clinic patients using 2 brief (15-min), face-to-face (FTF) behavioral counseling interventions provided by health department staff. Despite its demonstrated success, the intense FTF counseling approaches used in Project RESPECT have not been widely adopted. Reasons for failure to translate this intervention into routine practice include that the FTF intervention approaches require substantial personnel time, training, and continuing financial support for sustainability. Other types of interventions such as videos3–5 are less expensive to use once developed and do not require staff time but lack the ability to individualize risk reduction messages to patients’ specific needs as used successfully a decade ago with Project RESPECT.2

Technological advances in information and health communication over the past 2 decades provide opportunities to deliver tailored, theory-driven interventions.6 Computer technology uses the economics of “mass media” (public health approach), whereas at the same time has the potential to provide specific, tailored interventions to address each individual’s needs (clinical approach).7–9 Health technologies that target individuals or patients at risk at the population level may have a significant impact on the public’s health.10

Using a randomized controlled trial, we evaluated the efficacy of a single, brief (15-min), theory-based intervention designed to increase condom use (fewer episodes of unprotected sex) and to reduce new cases of Neisseria gonorrhoeae (GC) and Chlamydia trachomatis (CT). The intervention does not involve clinic personnel, delivers individualized behavioral messages, and is standardized, sustainable, replicable, and potentially cost-effective.1,11 Study hypotheses were that participants assigned to the intervention group would increase self-reported condom use (100%) and experience lower rates of STDs (GC and CT) than patients in the comparison group. Behavioral and biologic data were obtained at baseline and 6 months post intervention.

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Conceptual Framework Underlying the Intervention

Client-centered counseling12,13 based on a person’s readiness for changing behavior has been accepted as a tenet of STD/HIV prevention.14,15 Thus, we based SOLUTIONS on the framework of the transtheoretical model (TTM; also known as the “stages-of-change” model).16,17 This model postulates that when modifying behaviors individuals go through a series of 5 stages: (1) not ready to change); (2) seriously considering making a change; (3) ready to take action; (4) adopting or quitting the target behavior; and (5) sustaining the behavior change over time. Once a person’s stage of change (readiness) has been identified, intervention messages are provided that match where that person is in the process of change. Other constructs from the model (decisional balance, self-efficacy, and the processes of change) have been described in detail elsewhere18,19 and were utilized in the development of our stage-based interventions.

The study’s design and protocol were approved by the institutional review boards at the University of Alabama at Birmingham and the Jefferson County (Alabama) Department of Public Health before study implementation. This randomized-controlled trial follows an earlier feasibility study with this clinic population.11

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Study Sample

Participants were recruited from the population of lower-income, predominately black men and women seeking care at an urban STD clinic. Eligibility criteria included: age 18 to 44; no plans to move out of the area in the next 6 months; provision of written informed consent; and voluntarily seeking an STD evaluation.

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Participants were recruited from the clinic waiting area before being seen by a clinician. Patients were approached by being called, using their clinic registration number, and escorted to a private room within the clinic where they were asked several screening questions to determine eligibility for the study. Data were collected from 2002 to 2005.

The SOLUTIONS data are from patients reporting a main (or steady) sexual partner. A total of 456 patients were approached; 6 were not eligible. Of the 450 eligible men and women participants, 430 (96%) agreed to participate, completed the baseline assessment, and were randomized to study condition (Fig. 1). After providing written informed consent, participants were presented with brief, automated, interactive instructions on how to use the pointing device (mouse) to select response options on the assessment. Participants could prompt the system to repeat assessment items as well as response options. All participants received $25.00 at baseline and $35.00 at the 6-month follow-up assessment for their time and travel.

Fig. 1

Fig. 1

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Intervention Method

Using Macromedia Authorware software (Version 7.1) authoring environment, SOLUTIONS was programmed to deliver automated, individualized patient feedback in a systematic and standardized manner. The intervention application permits the inclusion of graphics, photographs, and multimedia to help reinforce particular topics, messages, or intervention strategies. Sound Forge audio editing package was used to create high quality audio. The intervention was delivered via a standard, personal computer. The behavioral intervention, SOLUTIONS, was delivered through a computerized multimedia interactive application. The system is programmed to assess risks behaviors, generates brief, tailored counseling messages selected as a result of preprogrammed theory-based decision rules and/or algorithms.1,18 Intervention messages simultaneously appeared on the computer screen and are heard by users through headphones to protect privacy and limit literacy concerns.11 The comparison patients interacted with a 15-minute, computerized multiple health risk assessment (MHRA) with no intervention.

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Intervention Randomization

Using the “random path” function within the Authorware interaction icon, the computer program randomly assigned participants to either the condom use intervention or the MHRA comparison condition. The randomization was stratified by gender and stage of change (readiness) for condom use with a main partner.

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Baseline Behavioral Assessment

Intervention Group.

Participants randomized to the intervention group (n = 203) completed a brief behavioral assessment regarding (1) basic demographic characteristics (age, gender, race/ethnicity, highest grade completed in school, marital status, etc.);(2) sexual risk behaviors (condom use with main partner, condom use at last sexual encounter, age of sexual initiation, history of STDs, and (3) number of partners (lifetime and in the past year). Then, using the preprogrammed algorithms utilizing patients’ responses to the stage-of-change items and gender, the individualized, theory-based, intervention messages, and strategies simultaneously appeared on the computer screen and heard through headphones. The assessment and intervention were designed to take about 15-minutes to complete, depending on the pace of each participant.

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Comparison Group.

Participants randomized to the comparison group (n = 227) interacted with a computer-based MHRA with no intervention. Behaviors assessed among comparison patients included the identical items provided to the intervention group, along with additional risk behaviors such as cigarette smoking, alcohol/other drug use, violence, depression, etc.) in an effort to have both groups interact with the “medium” or delivery channel (computerized application) for approximately the same length of time.

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Follow-Up Behavioral Assessment

Six months after their single intervention session, participants in both the conditions returned to the clinic and completed a paper-and-pencil survey that assessed condom use only.

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Biologic Assessments

At enrollment, specimens for culture were organism-specific tests for gonococcal and chlamydial infection collected in the context of routine STD clinical care. Test results for gonorrhea and chlamydia at baseline were obtained through electronic chart reviews for participants in the intervention and the comparison group.

After completing the 6-month follow-up assessment, noninvasive urine samples (ligase chain reaction; LCR) were collected by the SOLUTIONS’ staff and transported to the UAB STD Research Laboratory for testing in accordance with the manufacturer’s instructions. A single urine sample was used to evaluate both infections. All positive LCR reactions were verified through repeat testing of both the original specimen and the processed reaction mixture to verify test results to insure that positive results were not, in fact, false positives.

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STD Treatment

Participants who tested positive for chlamydia and/or gonorrhea at baseline or follow-up were treated in accordance to the CDC’s STD Treatment Guidelines13 as soon as possible after positive test results became available.20 Medications for treatment of gonococcal and chlamydial infections were provided by the Jefferson County Department of Health. Persons with chlamydial infection received 1g azithromycin (single oral dose), whereas those who tested positive for gonorrhea received 400 mg ofloxacin (single oral dose) plus azithromycin. Infected participants were instructed to notify their partners and to abstain from sexual intercourse until their sex partners had completed treatment.

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Tracking and Retention of Study Participants

At baseline, participants in both conditions scheduled their 6-month follow-up visit and provided their names, addresses, home/cell phone numbers, and contact numbers of friends or relatives they could trust. Two weeks before the scheduled visit, patients names were flagged, labels for mailing printed, and a reminder card that looked like an invitation were sent out. On the reminder card (which was placed inside an envelope) we included only the project’s name along with the date and time of their return appointment. A dedicated project phone line could be used to reschedule appointments. Participants who did not keep the 6-month appointment were called repeatedly using the contact information provided at enrollment over the subsequent 4 weeks to encourage and facilitate follow-up. If participants did not return after the 1-month “window”, they were considered lost to follow-up.

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Data Analysis Plan

The primary outcome was specified as 100% condom use with a main partner. A secondary outcome was the prevalence of new STDs (CT and/or GC) at the 6-month follow-up. Sample size calculations were conducted based on a previous study using various dose responses to promote movement through the stages of change.21 We projected a 20% increase in consistent condom use in the intervention group as compared with a 10% increase in the control group. Our sample size calculation indicated that N = 438 (219 per group) would provide statistical power = 0.80 with a 2-tailed test with P = 0.05. Participants lost to follow-up were assumed not to be using condom consistently with main partners.

Baseline behavioral data were downloaded from both conditions weekly and transported into SPSS (Version 12.0; SPSS, Inc. Chicago, IL); whereas at follow-up data on condom use was hand entered into the database. Descriptive statistics are presented as means (standard errors), medians (ranges), or differences in proportions as indicated. Comparisons across conditions at baseline were performed using chi-square or Fisher exact test (2-tailed). At both baseline and follow-up, chlamydia and gonorrhea infection rates were combined. Individuals found to be in the 2 more advance stages of change (action or maintenance) for 100% condom use were combined to represent the proportion of patients using condoms consistently, but for varying lengths of time (<6 months or >6 months). A logistic regression analysis was conducted to predict STD infection at the 6-month assessment with the selected baseline characteristics of the sample (Table 1) and baseline condition (intervention or comparison) as predictors.



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Study Population

The CONSORT statement22,23 was used to ensure an adequate report of the study’s findings. The flow of study participants is shown in Figure 1. All study participants were assessed via the SOLUTIONS system. Basic demographic and sexual risk characteristics of participants in the intervention (n = 203) and comparison (n = 227) groups at enrollment are presented in Table 1. The average age of the overall sample was 24.5 years (±0.23); 56.7% women and 88% were black. The majority (89%) of study participants reported being single and about half (50.5%) had a high school diploma/GED. No statistical differences were found across conditions for any of the selected demographic variables.

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Sexual Activity

Mean age of sexual initiation was 14.9 years for individuals in both arms of the study (Table 1). Over two-thirds (70.1%) of the sample reported having 6 or more lifetime sexual partners; 60% had less than 3 partners in the past year. Nearly two-thirds (64%) of the overall sample reported no condom use at their last sexual encounter and 65.5% reported a history of STDs. Again, no statistically significant between group differences emerged for any of the sexual risk variables.

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Consistent Condom Use at Baseline

Table 1 shows that at baseline 100% condom use with a main partner was low. The proportion of participants randomized to the intervention group who reported 100% condom use in the preceding 2 months was 14% (29/203); 19% (44/227) of participants assigned to the comparison group reported 100% condom use during the same time period. The differences in self-reported condom use for the 2 conditions at enrollment was not significant (14% vs. 19%; P = 0.22. In addition, no gender differences were detected for consistent condom use across the 2 groups (P = 0.32; data not shown).

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STDs at Baseline

At enrollment, a total of 103 cases of infection were found: CT n = 59; GC n = 42; both CT/GC n = 2. Table 1 shows that no significant differences in the combined gonorrhea and/or chlamydia rates were detected across the 2 groups at baseline (intervention: 25% (51/203) vs. comparison: 23% (52/227); P = 0.29). Overall, women in both conditions were more likely to be infected with CT (P = 0.04) than their men counterparts whereas, more men in both conditions were infected with GC (P = 0.001). (data not shown).

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At 6 months post intervention, substantially more individuals assigned to the treatment group returned to be reassessed. A total of 158 (78%) of participants allocated to the intervention group returned; whereas, 132 (58%) of those allocated to the comparison condition returned to the clinic (75% vs. 58%, P = 0.02). Comparisons of baseline characteristics for those who completed the follow-up assessment versus those who did not, revealed no group differences. All returning participants reported engaging in sexual activity with a main partner in the preceding 2 months.

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Six Month Condom Use

The difference in proportions on self-reported condom use at the 6-month assessment is shown in Table 2. Study participants receiving the intervention were more likely to report using condoms 100% of the time with a main partner in the preceding 2 months compared with those in the comparison condition (32% vs. 23%;χ2 = 2.34, P = 0.03). No significant gender differences were found in terms of consistent condom use (P >0.05) at the 6-month follow-up.



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Six Month Gonorrhea and Chlamydial Infection Rates

Table 3 shows that 6% (12/203) of study participants who received the brief intervention was diagnosed with either chlamydia and/or gonorrhea (CT n = 8, GC n = 3; and both GC/CT n = 1) at 6-months post intervention. For those in the MHRA comparison Group 13% (30/227) tested positive for infection (CT n = 18; GC n = 9; both GC/CT n = 3). Compared with baseline STD prevalence, the difference in proportions of STD rates decreased 22% for those in the intervention group versus 3% for those in the comparison group (χ2 = 4.16, P = 04).



Results from a logistic regression analysis using the selected baseline characteristics of the sample (Table 1) revealed that the only significant predictor for an STD at 6 months was group assignment (odds ratio = 1.91, 95% confidence index = 1.09–3.34; P = 0.043). This suggest that participants who did not receive the intervention were nearly 2 times more likely to have an STD at the 6-month assessment that those who received the brief, individualized intervention.

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These preliminary findings suggest that a single, interactive, computer-delivered intervention at the evaluation visit can increase consistent condom use and reduce STDs without putting any additional burden on clinic staff. A particular strength of the intervention is its use of computer programmed algorithms to evaluate patients’ risk to formulate the intervention messages that are tailored to their specific needs. We acknowledge that interactive computer-based behavior change programs tend to have lower efficacy rates that FTF or small group programs.20,24 However, the resources required for the latter interventions become prohibitively expensive for population-level interventions.

Brief computerized interventions may not be as efficacious as more intense interventions but may have a significant impact on public health.6,24,25 Specifically, advances in behavior change theory and technology have allowed for the integration of the broad reach of public health approach with the more one-on-one clinical approach. A core orienting objective in integrative behavioral health care is to increase the impact of behavioral interventions on population health by targeting individuals at greatest risk with individualized assessments and interventions. For example, if a more intense, multisession intervention resulted in a 30% efficacy rate but reached only 5% of the population at risk, the population impact (defined here as intervention efficacy X reach) would be only 1.5%. However, if an intervention resulted in a 20% efficacy rate but reached 60% of the population at greatest risk, the impact would be 12%. This would be 8 times greater than the more efficacious intervention delivery to a small proportion of the population. Even the smallest changes at the individual level that occur in larger populations at high risk can result in significant shifts in the absolute cases of disease (i.e., population outcomes).26 Funding agencies and grant reviewers must recognize the importance of funding research that investigates more efficient interventions that have high potential for population impact.27 In addition, computer-delivered interventions may overcome some of the other challenges of more traditional interventions such as competition for clinical time, facilitator issues that could affect the fidelity of intervention, and program sustainability.28

Other STD/HIV health communication applications have been developed to increase condom use with other populations including college students29 and female adolescents in managed care.30 These earlier studies were groundbreaking and demonstrated increases in condom use among study participants randomized to the experimental group. However, the current study included objective measures to lend some preliminary support for self-report data.

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There were a number of study limitations. We tested for only 2 STDs as biologic outcomes, chlamydia and gonorrhea. The intervention might have different effects on incident of other infections in the population and with different baseline prevalence rates of STDs.31 Also, the study focused on a relatively small patient sample and only those reporting a main partner. Future studies should determine the intervention’s efficacy when intervening on a larger scale and with other partner types. The majority of all patients were not infected at the evaluation visit and those who were infected may not have been reached by clinic staff. Thus, it is unlikely that all cases of STD infection found at the 6-month assessment were “new” cases. Not learning one’s test results at baseline, treatment failure, or reinfection3 could have influenced the STD rates found at follow-up. A related limitation is that 2 different STD testing methods were used. At baseline, the conventional culture was used; whereas, at follow-up a more sensitive, nonculture method was used (i.e., LCR). Thus, there is the potential that some infections were missed at baseline. Also, the relatively short follow-up period (6 months) did not allow for the determination if positive changes were maintained over a longer period of time. Although the inclusion of biologic markers represents a methodological advance over other interactive intervention applications applied to condom use, limitations in case identification remain. Unrecorded STDs may have occurred during the 6-month follow-up period. An STD may have been diagnosed and treated during this time so at the follow-up visit the participant would be diagnosed as infection free. Also, attrition was 20% higher in the comparison group than the intervention group. One speculation is that individuals who received the individualized intervention may have felt more engaged in the process than those who did not have a more personalized experience. Finally, we did not include an intent-to-treat analysis. Unlike action-oriented interventions, we included individuals at various levels of motivational readiness at enrollment. Earlier studies19,21,32,33 have shown that the amount of progress people make following an intervention tends to be a function of their stage of change at enrollment. Thus, there is no intention to treat all participants, particularly those in the earlier stages of change, within a 6-month timeframe. Although the tasks to be accomplished at each stage in the process of change are assumed invariant, the time an individual spends in each stage of change varies.19

Despite limitations, this study yields promising preliminary findings that demonstrate that brief multimedia, interactive, computer-delivered interventions may be a viable approach toward increasing condom use and reducing infections among STD clinic patients. The current findings also support earlier evidence that tailored interventions are effective for minority and lower income groups, thereby providing a potential avenue to reduce health disparities in STD/HIV.34,35

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Potentially cost-effective, standardized, sustainable, and replicable computerized interventions based on a person’s readiness for changing risk behaviors may benefit STD clinic patients if thoughtfully integrated with other activities during the evaluation visit.

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