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Article |

Early Effects of a School-Based Human Immunodeficiency Virus Infection and Sexual Risk Prevention Intervention FREE

David M. Siegel, MD MPH; Marilyn J. Aten, PhD RN; Klaus J. Roghmann, PhD; Maisha Enaharo, MPH
[+] Author Affiliations

From the Department of Pediatrics (Drs Siegel and Roghmann and Ms Enaharo) and the School of Nursing (Dr Aten), University of Rochester, Rochester General Hospital, Rochester, NY.


Arch Pediatr Adolesc Med. 1998;152(10):961-970. doi:10.1001/archpedi.152.10.961.
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Published online

Objective  To determine the short-term effect of a middle and high school–based human immunodeficiency virus and sexuality intervention (Rochester AIDS Prevention Project for Youth [RAPP]) on knowledge, self-efficacy, and behavior intention.

Design  Nonrandomized intervention study with 2 intervention groups and 1 control group.

Setting  Middle and high school health classes in an urban, predominantly minority school district.

Participants  Middle and high school students (N=3635) enrolled in health classes in 9 schools; 50% African American, 16% Hispanic, 20% white, and 14% other. Less than 10% of students refused participation.

Intervention  There were 3 study conditions: (1) Control, usual health education curriculum taught by classroom teacher; (2) RAPP adult health educator, intervention curriculum implemented by ethnically diverse male-female pairs of highly trained health educators; and (3) RAPP peer educator, intervention implemented by male-female pairs of extensively trained high school students. Health classes within schools were assigned to 1 of the 3 conditions each semester, and simultaneous implementation of the control program with health educators or peer educators in the same school and during the same semester was not permitted.

Main Outcome Measure  A confidential questionnaire administered to all study subjects before and immediately after the intervention, containing scales to measure knowledge, sexual self-efficacy, and safe behavior intention.

Results  Preintervention data indicated that the study population was involved in sexual activity and other risk behaviors at rates comparable to those of other urban adolescent populations. Examination of 3 outcome constructs as dependent variables (knowledge, sexual self-efficacy, and safe behavior intention) revealed that the health educators and peer educators increased students' knowledge significantly more than did the control condition for both middle (females, P<.01; males, P<.01) and high (females, P<.001; males, P<.001) school. Comparisons of self-efficacy changes across intervention groups did not reach statistical significance, and safe behavior intention changes differed significantly by intervention group for high school but not for middle school students. For all analyses, the preintervention scores for each outcome variable were the most powerful predictors of postintervention scores, and analysis of variance models predicted substantial overall variance.

Conclusions  At short-term follow-up, the RAPP intervention had a powerful effect on knowledge for all students and a moderate effect on sexual self-efficacy and safe behavior intention, particularly for high school students. The peer educators were found to be equally and, for some variables, more effective than the highly trained adult educators. The substantial effect of the baseline scores and the high prevalence of risk behavior already evident by seventh grade indicate the importance of early implementation of school-based sexuality programs.

Figures in this Article

ADOLESCENT sexual risk behaviors continue to represent one of the most serious public health problems in the United States.14 Consequences of these activities include pregnancy,2,5,6 sexually transmitted diseases (STDs)712 and, most recently, human immunodeficiency virus infection and the acquired immunodeficiency syndrome (HIV/AIDS).1318 While adolescents still represent less than 1% of the nation's identified HIV/AIDS population,16,17 the disease incubation period extends well beyond 10 years and it is currently estimated that 1 in 5 Americans with AIDS was infected during adolescence.18 In response to this increasing and profound HIV/AIDS risk, as well as those of STDs and pregnancy, a multitude of strategies have been developed to address sexual risk reduction among adolescents.

These preventive and risk reduction efforts include school-based curricula reflecting a wide variety of informational content and methods. Program goals can be categorized as abstinence only, sex education, or HIV/STD education. Key distinguishing features exist among these program categories. Abstinence programs do not include discussion of birth control aside from contraceptive failure and/or disease prevention.19,20 In contrast, sex education and HIV/STD education programs include information about abstinence, sexuality, contraception, and disease prevention.21 A range of methods have been used by school-based interventions to disseminate information and impart behavioral skills. These include teaching by peers, classroom teachers, and/or adults from outside agencies; incorporation of highly interactive exercises and skill-based methods with or without didactic presentations; and the direct or indirect involvement of parents and guardians.1925 Curricula also vary widely in duration, consisting of anywhere from 1 to 30 classroom sessions.

Program effectiveness, as measured by changes in knowledge, attitudes, self-efficacy, behavioral intention, and behavior, has varied. The importance of examining self-efficacy (the adolescent's belief in his or her ability to engage in a specific behavior) and behavior intention (the adolescent's belief that he or she will engage in a particular behavior within the next year) is derived from theories of behavior change. Social learning theory,26 the theory of reasoned action,27 and the theory of planned behavior28 all hold that in addition to knowledge about the ramifications of chosen behaviors, one's self-efficacy regarding the behavior is an important predictor of one's intention to behave in a certain way. Further, behavior intention is proposed to be closely linked to behavior. The ultimate effectiveness of risk reduction programs can only be meaningfully assessed by measuring the maintenance of safe behavior or adherence to safer sex practices over a significant duration (eg, ≥6 months). As a potential first step to long-term change it is also important to address early program effects (1-3 months after intervention).

While knowledge alone has not been found to be sufficient to change behavior, it is certainly a necessary prerequisite.29,30 Several studies have reported success in improving students' information base around sexuality and HIV/AIDS. Project SNAPP,24 a randomized study based in 6 urban middle schools, used an 8-session, peer-taught, skills-based, highly interactive HIV and pregnancy prevention intervention, which was compared with the existing school curriculum. While a positive effect on knowledge was noted, the 17-month follow-up revealed an improvement in only 2 of 21 relevant attitudes or beliefs, and there was no significant change in sexual or contraceptive behaviors. Other investigators have similarly described knowledge increases, but with mixed results in other measured constructs.29,3133 Main et al,31 reporting on a 15-session, skills-based HIV prevention curriculum implemented in Colorado, noted significant HIV knowledge increases among students in 10 intervention schools as opposed to students in 7 comparison schools. The experimental students also expressed greater intentions to engage in safer sex practices within the next 2-month period.

In a review of the effectiveness of 40 interventions designed to reduce AIDS risk in adolescents, Kim et al33 reported that of the 12 studies that assessed changes in attitudes toward personal preventive behavior, 7 (58%) found significant improvement, but that most of these were nonrandomized designs. Other articles describing knowledge and attitude changes tended to find improvement in the former but not consistently in the latter.23,3133 Weeks et al34 reported significant increases in contraceptive self-efficacy among middle school students in Chicago, Ill, after a 15-session classroom-based intervention. Walter and Vaughan25 also observed significant, albeit modest, changes in self-efficacy related to HIV preventive actions among high school students participating in a 6-session AIDS prevention curriculum. However, Newman et al35 reported a decrease in middle school students' self-efficacy related to AIDS prevention behaviors as well as their level of communication with peers and family members about AIDS following a 1-hour HIV education program developed and taught by the Red Cross. In this study knowledge scores also failed to increase as a result of the brief intervention. Thus, school-based programs aimed at HIV risk among adolescents seem to have some successes, consistently in the area of knowledge change and somewhat in self-efficacy and attitudes, but only in the context of substantial content and duration. The reasons for intervention success or failure have yet to be fully explained.

An important factor both for implementation and evaluation of school-based studies is student attendance. That is, students may not be present for an entire intervention and yet they participate in pretesting and posttesting and become part of the outcome database. While this, of course, is consistent with all clinical trials, the methodologic consideration is whether to eliminate students who have not attended all sessions (a severely compromising choice that ignores the realities of generalizability) or make an attempt to measure the "dose," or degree of exposure to the program.36 Surprisingly, intervention dose and its relation to intervention effect has been rarely considered in school-based work. Additionally, studies often fail to include any measure of the learning adequacy of the existing classroom environment. Relevant variables include the physical environment, support of the learning process, and control of students in the classroom.

The Rochester AIDS Prevention Project for Youth (RAPP) is a middle and high school–based intervention trial. We report below on preintervention to immediate postintervention changes in knowledge concerning HIV/AIDS and sexuality, self-efficacy, and behavior intention. The effects on these dependent variables of dose as well as the adequacy of the learning environment are included in the analyses.

SAMPLE

The subjects (N=3696, Table 1) were drawn from 9 urban schools in Rochester, NY (population, 250000). The criteria for study inclusion were that students be (1) enrolled in required health education classes and (2) fluent in either English or Spanish. Ethnicity of the sample was diverse: 50% African American, 16% Hispanic, 20% white non-Hispanic, and 14% other ethnic backgrounds, including Asians, Native Americans, and those who indicated that they were biracial. The socioeconomic status (SES) of the sample was assessed by subject-reported ZIP code and street address (socioeconomic area, or SEA [described later]) and the mean SEA rating was 5.2 (SD=2.7), slightly lower for middle than high school students. Approximately 70% of the families with children in this school district have incomes placing them below the federal poverty line.

Table Graphic Jump LocationTable 1. Comparison of Sample Descriptive Characteristics by Intervention Group Within School Level
PROCEDURE
Intervention

Students were recruited within their regular school health education classes to participate in RAPP, a quasi-experimental, classroom-based intervention designed to increase knowledge and skills aimed at safe behavior regarding sexuality and HIV/AIDS. Classes were assigned within semesters to 1 of 3 conditions: (1) control, the usual health education curriculum taught by the regular health education teacher; (2) RAPP adult health educator, the RAPP intervention implemented by an ethnically diverse male-female pair of highly trained adult educators; or (3) RAPP peer educator, volunteer high school students who completed approximately 50 hours of preparation by RAPP staff and taught the RAPP curriculum as pairs of educators. Health education in middle school was taught in seventh grade only, while in high school students had the option to take health class in 10th, 11th, or 12th grade; most students chose 10th or 11th grade. The semester assignments of classes to intervention condition was based on feasibility issues and availability of peer educators. The primary goals were that (1) all conditions were to occur in all classes and schools by the conclusion of the study; and (2) control and experimental conditions could not coexist in the same school during a given semester. These design features enhanced generalizability by ensuring that the intervention was spread across a variety of different schools, and helped to avoid contamination between intervention and control classrooms. The RAPP intervention consisted of 10 (high school) or 12 (middle school) consecutive health class sessions (usually 2 or 3 sessions per week) delivered for a period of 2 to 7 weeks. The intervention was integrated into the regular school health education schedule to avoid disruption within schools and to build an intervention that might generalize to other schools in the future. With one exception during the intervention period of 2.5 years, all study conditions took place at both middle and high schools.

The content of the intervention was based on current literature concerning school-based interventions, expertise of the RAPP health educators, and principles from the theory of reasoned action and normal adolescent development. Early sessions emphasized self esteem and decision-making strategies, while later classes progressed through in-depth discussion and skill-based activities concerning sexuality, STDs, pregnancy, and finally HIV/AIDS. This last topic received particular emphasis, and all sessions included small and large group activities such as games, role playing, and take-home exercises, often requiring parental input. Priority was placed on maximum engagement of the students in a highly interactive and dynamic learning experience in both intervention conditions. In this article we focus on the preintervention to immediate postintervention measurement of knowledge, sex self-efficacy, and behavior intention and compare observed changes in intervention groups with each other and with the control group.

Data Collection

Students were asked to complete a confidential survey before intervention and immediately after intervention, as well as 6 and 12 months after intervention, after verbal and written study explanation. Passive parental consent for student participation was obtained. Parent(s) of all students scheduled to take health education in the upcoming school year are routinely sent a letter from the district Director of Health and Physical Education informing them that family life education, including sexuality, will be taught and they can request their son or daughter not participate in that unit. During the time of the study, a description of the RAPP program was a part of this letter and parents were given the opportunity to inquire further about RAPP and/or refuse participation. Questions were directed to the study's principal investigator (D.M.S.), who met with parents individually to address their concerns. Very few (<10) families withdrew their children from the program. The study was reviewed and approved by both the administration of the local school district and the university institutional research review board. Students were assured that no names would be used on any surveys, that their answers would be seen only by research staff, and that they could participate in the health classes in which the education and skills project occurred without completing the research instrument. Few eligible students refused to participate in the study; more than 90% completed the survey before intervention. Subjects were tracked over time by using (1) a school district–assigned identification number; and (2) a RAPP study identification number. This procedure ensured that, despite student mobility, duplicate subject enrollment did not occur. The survey instrument, available in both English and Spanish, was read to students during class by the project health educators and required approximately 40 minutes for completion.

Study Instrument

The survey questionnaire, pilot tested on 450 students preceding the main study, was composed of sections measuring constructs determined to be important in assessing the effects of the RAPP curriculum. Those reported here include demographics, knowledge, self-efficacy regarding sexual matters, behavior intention within the next year, history of risk behaviors, and history of sexual experiences. In addition to the student-completed questionnaires, the RAPP health educators measured the adequacy of the existing health education learning environment in each class, resulting in a "class climate" score.

VARIABLES MEASURED
Demographics

Age in years, gender, ethnicity, and a proxy for SES were measured. Although the student population of the school district is generally of low SES, there was concern that some differences might exist across study subjects and potentially confound our findings. For confidentiality reasons, and recognizing that younger teenagers often do not know about household income or employment and education of family members, we used an SES proxy as follows. Street name and ZIP code for the student's residence (as given on the questionnaire) were used to code census tracts, and this allowed a 1 to 10 SEA ranking for each student. The 10-point ranking was based on median house value, rent, and family income, as well as educational level of the adult population and proportion of professionals and executives among the employed population within each census tract. The median house value in the city in 1990 was $60700, the average monthly rent was $360, the mean annual family income was $25000, and 16% of the adults had a college degree. While a family's SES might rarely be inconsistent with that of the census tract in which they resided, we decided that SEA was more reliable and valid than household-specific income and educational data provided by the students. The large study sample also minimized the influence of potential remaining measurement error.

Knowledge

The 26-item knowledge scale tested information concerning human reproduction, decision making, communication with others concerning sexual matters, HIV/AIDS and other STDs, high-risk behaviors and their sequelae, and other adolescent sexuality items. Students responded to statements with yes if they believed the statement was true, no if they believed the statement was false, and "not sure" (a choice scored as incorrect and included to minimize guessing and the possible inflation of correct response scores). To avoid a ceiling effect, individual items were included only if they were shown to have less than 80% correct responses by middle and high school students during the pilot phase. The scale score range was from 0 to 26, and α reliability was .79.

Sexual Self-Efficacy

Eight items, each with a 7-point response scale, measured sex self-efficacy. This was adapted from similar work developed by Misovich et al37 and tested how hard (score of 1) or easy (score of 7) it would be to carry out each of 8 behaviors in relation to sexuality (eg, How hard or easy would it be for you to "convince your partner that a condom must be used before you have intercourse," "remain abstinent and avoid having sex," and others). Efficacy was scored as the sum of the 8 items and ranged from 8 to 56, α reliability was .74, and test-retest reliability, based on 450 control subjects during a 4-week period, was 0.66. Principal component factor analysis supported a 1-factor solution (eigenvalue=2.9), accounting for 36% of variance.

Safe Behavior Intention

An index of intention to behave in safe ways (Figure 1) was developed using 9 items asking students to indicate their agreement or disagreement (on 7-point response scales) with statements such as "I will be abstinent (not do it) this year" or "If someone wanted to have sexual intercourse (do it) with me, I would probably do it." Items measured intention to engage in the following risk behaviors: sexual behavior (intention to be abstinent or have intercourse during the next year, intention to have multiple partners), becoming a teenage parent, disease risks (HIV/AIDS, STDs), and substance abuse. Items were scored with anchors of risk (1) or safe intention (7) and summed. The possible score range was 9 to 63; α reliability was .74 (N=2385) and .74 (N=1526) for middle and high school students, respectively. Test-retest correlations across 2 to 4 weeks were 0.77 (N=381) and 0.81 (N=380) for middle and high school students, and a principal component factor analysis suggested a 1-factor solution (eigenvalue=3.2), accounting for 35% of variance.

Place holder to copy figure label and caption

Safe behavior intention scale.

Graphic Jump Location
Life Risk History

To measure the risk history of each subject, 15 items from the Youth Risk Behavior Survey38 were used, including questions about school- and community-related behaviors (eg, skipping school, getting into fights, carrying weapons, crime conviction), substance abuse, and cigarette smoking. We asked a panel of 25 experts in adolescent health (both clinicians and behavioral scientists) to rank the behavior items from low to high risk as follows: 0 for no or minimal risk (eg, missed school without permission), 1 for some risk (eg, tried marijuana), or 2 for substantial risk (eg, used marijuana regularly). Students responded as to whether they had ever participated in these behaviors. There was a possible score range of 0 to 31, α reliability was .79, and test-retest reliability during a 4-week period was 0.84. Factor analysis again suggested a 1-factor solution (eigenvalue=4.3), accounting for 25% of variance.

History of Sexual Intercourse

Before intervention, students were asked about their history of sexual intercourse as part of 7 different questionnaire items addressing onset, frequency, and multiple partner experience. We examined the degree to which students were consistent across all 7 items in which there was an opportunity to answer "I have never had sex," to be confident regarding the validity of response, and, particularly for the younger students, to assure that subjects understood the concept of sexual intercourse prior to initiating the intervention. Students were categorized as ever having had sexual intercourse (score of 1) or never having had sexual intercourse (score of 0).

Dose

The dose of intervention (number of classes attended) may represent an important contribution to change in HIV prevention studies.36 Thus, we asked students to indicate the extent to which they attended RAPP classes from 1 (not at all) to 5 (all classes).

Class Climate

To test for any differences across various learning settings that might have influenced the effect of the intervention, the learning adequacy of the existing health education class environment was observed and scored by the adult RAPP educators for all participating teachers and classrooms. Working independently, each member of a pair of educators in a classroom rated the physical environment and the regular health teacher's facilitation of the RAPP curriculum. The 18 items were summed to form an overall "class climate" score (scale score range, 0-36). Rater agreement was high (r>0.80) and the 2 scores were averaged.

DATA ANALYSES

Recognizing that age and gender would likely significantly affect baseline findings as well as intervention effect, we stratifed all data into 4 groups: (1) middle school females, (2) middle school males, (3) high school females, and (4) high school males. Intervention effect was then tested within these groups. Before intervention, all study variables were compared within school level for the 3 intervention groups using the χ2 statistic for categorical data and analyses of variance (ANOVA) for continuous level variables (Table 1 and Table 2). To examine differences between pretest and posttest scores, repeated-measure ANOVAs were used with demographics (age, SEA), the existing life risk score, the class climate score, and the relevant pretest score for the scale in question (knowledge, self-efficacy, or behavior intention) introduced first as covariates. Then the factors of ethnicity and sex history were entered, followed by the intervention level factor (1=control, 2=health educator, 3=peer educator). Because the sample was large and statistical significance may be easily reached with large samples, a more rigorous significance threshold of P<.01 (rather than .05) was chosen.

Table Graphic Jump LocationTable 2. Comparison of Study Variables by Intervention Within School Level

To test for the dose effect, Pearson product moment correlations were computed between the student's self-report of attendance and the 3 outcome variables of interest. These analyses were compared only for the students in the 2 RAPP intervention groups (health educator and peer educator classes), because controls were prevented from any RAPP class attendance. This characteristic of control subjects (ie, by definition their dose was 0) precluded entering dose in the ANOVA analyses.

PREINTERVENTION COMPARISONS BY SCHOOL LEVEL AND GENDER

The total sample consisted of 1028 female and 971 male middle school students and 877 female and 820 male high school students. Within school level, comparable proportions of students were assigned to each of the 3 intervention groups. As compared with middle school, the high school students were approximately 4 years older (F3,3631=7901.5, P<.001), and of slightly higher SEA status (F=10.4, P<.001). There were ethnic differences (χ29=44.4, P<.001), with somewhat greater percentages of Hispanic and "other" ethnic backgrounds represented among the younger students (Table 1). The life risk history mean scores by groups (in ascending order) were 5.7 (middle school females), 6.8 (high school females), 7.2 (middle school males), and 8.3 (high school males) (F=39.4, P<.001). There were no significant differences across the 3 intervention groups for middle school students. However, for high school students, the peer educator group was slightly younger (F=72.5, P<.000), of higher SEA (F=12.0, P<.000), included fewer Hispanic students and more non-Hispanic white students (χ2=35.4, P<.000), and were less likely to have reported a history of sexual intercourse (χ2=21.1, P<.000) (Table 1). Further, peer-taught high school students reported lower life risk scores (F=5.6, P<.000) and greater safety intention (F=13.3, P<.000) than controls or adult-taught students (Table 2). In addition, there were several significant gender-specific differences. While only 26.9% of the younger females indicated that they had experienced intercourse, the majority of the younger males (64.7%) indicated that they were sexually experienced. For the older students, 67% of female and 79% of male high school students reported that they had been sexually active. In relation to the class climate score, there were significant differences by school level (F=278.9, P<.001), with the class environments of the older students rated as being higher (that is more conducive to learning) than those at middle school.

The 3 variables of interest for examination of intervention effects (knowledge, self-efficacy, and behavior intention) were also compared before intervention by school level and gender. As would be expected, knowledge was greater at the high school level (F=208.9, P<.001), while there were no gender differences at either school level. For self-efficacy, there were both school level and gender differences (F=94.8, P<.001); self-efficacy was greater for females than for males at both school levels, and mean scores were higher at high school in comparison with middle school. Safe behavior intention was greater for females than males overall, but scores were lower for high school students in comparison with middle school students (F=289.1, P<.001).

COMPARISON OF QUESTIONNAIRE SCORES FROM BEFORE INTERVENTION TO AFTER INTERVENTION

Table 3 (knowledge), Table 4 (self-efficacy), and Table 5 (behavior intention) present preintervention to postintervention changes in questionnaire responses, including the effect of the interventions compared with each other and with controls using ANOVA. Beginning with knowledge as the dependent variable (Table 3), all covariates were significant except life risk, and significant main effects were found for ethnicity and, most important, for the intervention. There was no significant difference for knowledge change based on sex history among any of the 4 age and gender groups. In each of the 4 age and gender groups, the pretest score for knowledge outstripped all other covariates at striking F magnitudes (from 224-399). Age was significant, even after controlling for differences between middle and high school students, indicating that older students did less well on knowledge. In relation to ethnicity, white non-Hispanics had slightly higher mean knowledge scores and Hispanics had somewhat lower mean scores than either the African American or "other" groups.

Table Graphic Jump LocationTable 3. Prediction of Immediate Postintervention Knowledge Scores (ANOVA) Among 2758 Middle and High School Students*
Table Graphic Jump LocationTable 4. Prediction of Immediate Postintervention Sexual Self-Efficacy Scores (ANOVA) Among 2678 Middle and High School Students*
Table Graphic Jump LocationTable 5. Prediction of Immediate Postintervention Safe Behavior Intention Scores (ANOVA) Among 2660 Middle and High School Students*

For the intervention effect, there were significant differences between the control and the 2 intervention groups among all 4 of the age and gender groups. Means for the intervention students (both health educator and peer educator) were significantly higher after intervention, while the control group maintained their preintervention mean scores for the middle school students and rose only about 1 to 1.5 points in mean score at the high school level. There were notable (high school females only) 2-way interactions for ethnic group × sex history (F=3.7, P<.01) and sex history × intervention (F=4.3, P<.01). Thus, there was a substantial effect of the intervention beyond the covariates and independent of the other factors. For the 4 age and gender groups the model explained substantial variance, ranging from 41% to 55% (R2).

For self-efficacy regarding sexual matters, there was statistical significance for both the covariates and main effects across the 4 groups of students (Table 4). Similar to the knowledge scores, the covariates of age, SEA, class climate score, and the self-efficacy pretest score were significant. In each of the comparisons, the F for the pretest score (ranging from 182-554) was of much greater magnitude than for the other covariates. While there were no mean differences in self-efficacy by sex history, gender proved to be important, with females reporting higher posttest self-efficacy scores at both age levels. There were also significant differences by ethnicity for middle and high school females (but not males). Hispanic students tended to have mean scores that were somewhat lower for middle school students (36-36.8) in comparison with white non-Hispanic middle school students (37.6-42.6), and for high school females. Hispanic and "other" students had lower scores in comparison with African American and white non-Hispanic students. There were no mean differences for the ethnic groups among high school males. Statistically significant differences were not found between intervention and control but trends suggested an intervention effect; that is, the means for the control subjects were lower than for the health educator or peer educator intervention groups. The 4 models predicted from 24% to 46% of variance in self-efficacy, with most of the variance attributed to the covariates.

Finally, safe behavior intention was tested for the same set of covariates, as well as the ethnicity, sex history, and intervention factors (Table 5). Again, the covariates and main effects were significant, but there was a different pattern to the relationship with behavior intention than for knowledge or self-efficacy. While the pretest score for intention was the covariate with the greatest significance (F range, 277-447 across the 4 age and gender groups), the general life risk (F range, 6.3-54) emerged as being inversely related to safe behavior intention. In this analysis, there were no ethnic differences in safe behavior intention but sex history status was statistically significantly different in 3 of the 4 groups (F range, 10.6-25.1). Thus, students who indicated that they had already experienced sexual intercourse also reported less intention to behave in safe ways. While not statistically significant for high school males, the mean scores suggested the same relationship (51.2 vs 41.8). Overall, middle school students were more likely to intend to engage in safe behaviors than were high school students. Intervention students demonstrated greater safe behavior intention at posttest than controls for high school males (F = 4.5, P<.01) and high school females (F=4.0, P<.05). The models explained variance in behavior intention ranging from 0.45 to 0.55 (R2).

LEVEL OF ATTENDANCE AT RAPP SESSIONS (DOSE OF INTERVENTION)

Data regarding the correlations between the student's self-report of RAPP participation and knowledge, self-efficacy, and safe behavior intention scores are presented in Table 6. The magnitude of knowledge score increases from pretest to posttest correlated positively with reports of RAPP participation; that is, as self-report of attendance increased, total knowledge scores increased with correlations ranging from modest (0.14) to strong (0.50), and were most significant at high school level. For sex self-efficacy, there was less of a relationship with attendance report (r=0.00-0.28) with only 1 of the correlations (health educator, high school females) reaching significance. Overall, correlations for females (range, 0.08-0.28) were greater than for males (range, 0.00-0.06). There was no correlation between safe behavior intention and participation reports with the exception of a modest correlation for high school males (0.19).

Table Graphic Jump LocationTable 6. Relationship Between Student-Reported Attendance and Posttest Scores in Knowledge, Sexual Self-Efficacy, and Safe Behavior Intention by Gender and School Level

This early examination of the effects of RAPP reveals first that the population was comparable to other urban settings, particularly with regard to the high risk attributable to male gender3840 and age. Against this generalizable sociodemographic backdrop we found that a large-scale, school-based, explicit sexual risk reduction intervention can be implemented and have a successful effect on important outcomes. Limitations of this research must, however, be considered when interpreting the results. To begin, all longitudinal school-based studies are biased by inherent subject attrition resulting from both graduation and school dropout. The higher SEA score found among the high school subjects is consistent with previous reports that urban students who stay in school are more likely to be members of families with greater income.41,42 While the SEA ranking we used may not precisely measure each subject's true SES, we believe it is more valid than other self-reported SES data among adolescents, which usually rely on youth to report family income and parental education or occupation (as discussed earlier in the "Participants and Methods" section).

Our finding that the high school classes were more conducive to learning than were the middle school classes is probably rooted in certain classroom characteristics related to the age groups. High school classroom enrollments tended to be smaller than in middle school and there may again be some contribution of a dropout-induced bias toward more motivated students at the higher grade levels. Older students were, perhaps, more able to pay attention and participate in sexuality-focused sessions than were younger students. The learning environment clearly warrants measurement in school-based research and must be factored into interpretation of intervention effectiveness.

The higher levels of self-efficacy we found among females is consistent with the recognition that many of our cultural and educational messages around sexual safety are often directed toward girls and young women as opposed to boys and young men.43 Intention to behave in safer ways concerning sex was also a female attribute in this study, a theoretically consistent extension of the self-efficacy findings. The inability of the older students to translate their greater knowledge and self-efficacy into safer behavioral intention points out the urgent need to focus prevention interventions on the younger population. It may, however, also suggest that for adolescents the link between self-efficacy and behavior intention is not as tight as theory might otherwise propose.

As we examined differences between intervention and control groups, the ANOVA models included important covariates that might explain findings that would have been incorrectly attributed solely to intervention effect in a less sophisticated analysis. Knowledge gains observed in RAPP (which were greater than those reported in other school-based programs35) were likely due to interactive teaching techniques, the use of gender and ethnically diverse educator pairs, the careful inclusion of this program within the regular school environment, and the length of the intervention (10-12 sessions). It is notable that the peer educator condition produced results comparable to the health educator condition (Table 3). The RAPP study confirms that, at least in certain content areas and over short follow-up, extensively prepared high school students can be effective teachers for their peers.

The modest effect of RAPP on self-efficacy may reflect the possibility that assessment immediately following the intervention is too early to detect a difference in this construct. If a knowledge, self-efficacy, and behavior intention link does exist (as proposed by the theory of reasoned action), knowledge change will temporally precede observable efficacy change. Intervention effect on safe behavior intention was positive among the high school subjects, especially the females, but not for the middle school students. In the case of middle school females, this lack of intervention effect could be an artifact of measurement. That is, these students scored quite high at baseline in all 3 study conditions (mean score, 55; maximum, 63) and this "ceiling effect" limited the ability of our analyses to detect a difference. These results might evidence a pressure felt by 13-year-old girls to provide (at pretest) what they perceive to be socially acceptable responses to questions about safe sex behavior intention. The high school students, on the other hand, did show greater increases in safe behavior intention after the test in the intervention groups than in control groups. Perhaps their developmental attainment was better suited to the effect of the intervention. Our future analyses will document the longer-term status of these variables as well as the most important outcome, that of behavior and its relationship to behavior intention. Our findings regarding intervention dose and its positive correlation with outcome measures (especially knowledge) not only reinforces the conclusion that it was RAPP curriculum exposure that affected posttest scores, but also points out the importance of factoring attendance into analyses of school-based interventions.

It should not be forgotten that for the 3 constructs and for all age and gender groups our models explained significant variance, with R2 ranging from 0.41 to 0.58 for knowledge and behavior intention and somewhat less for self-efficacy (0.24-0.46) (Table 3, Table 4, and Table 5). As stated earlier, it is the burden of the past (pretest scores) that casts a long shadow over predictions of intervention-inducedj change in knowledge, self-efficacy, and behavior intention. This finding not only mandates the testing of interventions among subjects younger than middle school age, but also illustrates the need for researchers and clinicians to be methodologically sejnsitive to removing the variance attributable to pretest scores when interpreting intervention study data. Finally, despite substantial predictive power of our model, the influences on pretest scores go beyond age and personal experience to include parental, family, cultural, and community forces. More comprehensive and multidimensional interventions that reinforce school-based activities with other sites and contexts for prevention strategies must be considered.

Accepted for publication May 14, 1998.

This research was supported by grant R01-MH 49037 from the National Institutes of Mental Health, Rockville, Md.

We thank Barbara Thompson for her tireless preparation of the manuscript. We also thank the staff of the Rochester AIDS Prevention Project for Youth; the health educators, Margaret Cain, BA; Raul Corujo-Molina; Desiree Voorhies, RN, MSEd; and Lennard Wedderburn, CSW; and research assistant Terri Vaughn, CSW, for their dedication, commitment, and hard work on behalf of the project. Special thanks to the staff and students of the participating schools.

Corresponding author: David M. Siegel, MD, MPH, Department of Pediatrics, Rochester General Hospital, 1425 Portland Ave, Rochester, NY 14621 (e-mail: david.siegel@viahealth.org).

Editor's Note: The 2 interventions seem to be effective in changing short-term knowledge. I hope that the authors plan a follow-up on student-reported behavior . . . and then wouldn't it be great to determine actual practice. I can dream, can't I?—Catherine D. DeAngelis, MD

Alan Guttmacher Institute, Sex and America's Teenagers.  New York, NY Alan Guttmacher Institute1994;
Harvey  SMSpigner  C Factors associated with sexual behavior among adolescents: a multivariate analysis. Adolescence. 1995;30253- 264
Rotheram-Borus  MJKoopman  CHaignere  C Reducing HIV sexual risk behaviors among runaway adolescents. JAMA. 1991;2661237- 1241
Link to Article
Epner  JEGed Policy Compendium on Reproductive Health Issues Affecting Adolescents.  Chicago, Ill American Medical Association1996;
Forrest  JDSingh  S The sexual reproductive behavior of American women, 1982-1988. Fam Plann Perspect. 1990;22206- 214
Link to Article
Bayne Smith  MA Teen-incentives program: evaluation of a health promotion model for adolescent pregnancy prevention. J Health Educ. 1994;2524- 29
Bell  THein  K The adolescent and sexually transmitted diseases. Holmes  Ked.Sexually Transmitted Diseases New York, NY McGraw-Hill International Book Co1984;73- 84
Cates  W The epidemiology and control of sexually transmitted diseases in adolescents. Schydlower  MShafer  Meds.Adolescent Medicine: State of the Art Reviews Philadelphia, Pa Hanley & Belfus Inc1990;409- 428
Centers for Disease Control and Prevention, National Center for HIV, STD, and TB Prevention, Sexually Transmitted Disease Surveillance, 1997.  Atlanta, Ga Centers for Disease Control and Prevention1997;
Schacter  J Why we need a program for the control of Chlamydia trachomatisN Engl J Med. 1989;320802- 804
Link to Article
Moscicki  APaletsky  JGonzales  JSchoolnik  GK Human papilloma virus infection in sexually active adolescent females: prevalence and risk factors. Pediatr Res. 1990;28507- 513
Link to Article
Centers for Disease Control, Annual Report.  Atlanta, Ga Centers for Disease Control1991;
Sonnenstein  FLPleck  JHKu  LC Sexual activity, condom use and AIDS awareness among adolescent males. Fam Plann Perspect. 1989;21152- 158
Link to Article
Romer  DBlack  MRicardo  I Social influences on the sexual behavior of youth at risk for HIV exposure. Am J Public Health. 1994;84977- 985
Link to Article
Levy  SRHandler  ASWeeks  K Correlates of HIV risk among young adolescents in a large metropolitan midwestern epicenter. J Sch Health. 1995;6528- 32
Link to Article
Centers for Disease Control and Prevention, HIV/AIDS Surveillance Report. 9 Atlanta, Ga Centers for Disease Control and Prevention1997;
Hein  K "Getting real" about HIV in adolescents. Am J Public Health. 1993;83492- 494
Link to Article
Boyer  CBKegeles  SM AIDS risk and prevention among adolescents. Soc Sci Med. 1991;3311- 23
Link to Article
Kirby  D No Easy Answers: Research Findings on Programs to Reduce Teen Pregnancy.  Washington, DC The National Campaign to Prevent Teen Pregnancy1997;
Klein  NAGoodson  PSerrins  DSEdmundson  EEvans  A Evaulation of sex education curricula: measuring up to the SIECUS guidelines. J Sch Health. 1994;64328- 333
Link to Article
Kirby  DShort  LCollins  J School-based programs to reduce sexual risk behaviors: a review of effectiveness. Public Health Rep. 1994;109339- 360
Kirby  D School-based programs to reduce sexual risk-taking behaviors. J Sch Health. 1992;62280- 287
Link to Article
Sunwoo  JBrennan  AEscobedo  J School-based AIDS education for adolescents. J Adolesc Health. 1995;16309- 315
Link to Article
Kirby  DKorpi  MAdivi  CWeissman  J An impact evaluation of Project SNAPP: an AIDS and pregnancy prevention middle school program. AIDS Educ Prev. 1997;9 ((suppl A)) 44- 61
Walter  HVaughan  R AIDS risk reduction among a multiethnic sample of urban high school students. JAMA. 1993;270725- 730
Link to Article
Bandura  A Social Foundations of Thought and Action: A Social Cognitive Theory.  Englewood, NJ Prentice-Hall1986;
Ajzen  IFishbein  M Understanding Attitudes and Predicting Social Behavior.  Englewood, NJ Prentice-Hall International Inc1980;
Terry  DJO'Leory  JE The theory of planned behavior: the effects of perceived behavioural control and self-efficacy. Br J Soc Psychol. 1995;34199- 220
Link to Article
Kirby  DBarth  RLeland  NFetro  JV Reducing the risk: impact of a new curriculum on sexual risk taking. Fam Plann Perspect. 1991;23253- 263
Link to Article
Whitley  BESchofield  JW A meta-analysis of research on adolescent contraceptive use. Popul Environ. 1986;8173- 203
Link to Article
Main  DSIverson  DCMcGloin  J Preventing HIV infection among adolescents: evaluation of a school-based education program. Prev Med. 1994;23409- 417
Link to Article
Brown  LKBarone  VJFritz  GK AIDS education: the Rhode Island experience. Health Educ Q. 1991;18195- 206
Link to Article
Kim  NStanton  BLi  X Effectiveness of the 40 adolescent AIDS-risk reduction interventions: a quantitative review. J Adolesc Health. 1997;20204- 215
Link to Article
Weeks  KLevy  SRZhu  C Impact of a school-based AIDS prevention program on young adolescents' self-efficacy skills. Health Educ Res. 1995;10329- 344
Link to Article
Newman  CDuRant  RHAshworth  CSGaillard  G An evaluation of a school-based AIDS/HIV education program for young adolescents. AIDS Educ Prev. 1993;5327- 339
Miller  BCPaikoff  RL Comparing adolescent pregnancy programs: methods and results. Miller  BCCard  JJPaikoff  RLPeterson  JLeds.Preventing Adolescent Pregnancy Newbury Park, NJ Sage Publications1992;265- 284
Misovich  SJFisher  WAFisher  JD Understanding and promoting AIDS preventive behaviors: measures of AIDS risk reduction information, motivation, behavioral skills, and behavior. Davis  CMYarbor  WHBauserman  RScheer  GDavis  SLeds.Sexuality Related Measures: A Compendium Newbury Park, NJ Sage Publications1998;
Warren  CWKann  LSmall  MLSantelli  JSCollins  JLKolbe  LJ Age of initiating selected health-risk behaviors among high school students in the United States. J Adolesc Health. 1997;21225- 231
Link to Article
Siegel  DMAten  MJRoghmann  KJ Self-reported honesty among middle and high school students responding to a sexual behavior questionnaire. J Adolesc Health. 1998;2320- 28
Link to Article
Aten  MJSiegel  DMRoghmann  KJ Use of health services by urban youth: a school-based survey to assess differences by grade level, gender, and risk behavior. J Adolesc Health. 1996;19258- 266
Link to Article
National Research Council, Losing Generations: Adolescents in High Risk Settings.  Washington, DC National Academy Press1993;42- 43
US Department of Education, National Center for Education Statistics, Dropout Rates in the United States.  Washington, DC US Dept of Education1997;NCES publication 97-473
Hayes  CDed   Risking the Future: Adolescent Sexuality, Pregnancy, and Childbearing.  Washington, DC National Academy Press1987;241

Figures

Place holder to copy figure label and caption

Safe behavior intention scale.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1. Comparison of Sample Descriptive Characteristics by Intervention Group Within School Level
Table Graphic Jump LocationTable 2. Comparison of Study Variables by Intervention Within School Level
Table Graphic Jump LocationTable 3. Prediction of Immediate Postintervention Knowledge Scores (ANOVA) Among 2758 Middle and High School Students*
Table Graphic Jump LocationTable 4. Prediction of Immediate Postintervention Sexual Self-Efficacy Scores (ANOVA) Among 2678 Middle and High School Students*
Table Graphic Jump LocationTable 5. Prediction of Immediate Postintervention Safe Behavior Intention Scores (ANOVA) Among 2660 Middle and High School Students*
Table Graphic Jump LocationTable 6. Relationship Between Student-Reported Attendance and Posttest Scores in Knowledge, Sexual Self-Efficacy, and Safe Behavior Intention by Gender and School Level

References

Alan Guttmacher Institute, Sex and America's Teenagers.  New York, NY Alan Guttmacher Institute1994;
Harvey  SMSpigner  C Factors associated with sexual behavior among adolescents: a multivariate analysis. Adolescence. 1995;30253- 264
Rotheram-Borus  MJKoopman  CHaignere  C Reducing HIV sexual risk behaviors among runaway adolescents. JAMA. 1991;2661237- 1241
Link to Article
Epner  JEGed Policy Compendium on Reproductive Health Issues Affecting Adolescents.  Chicago, Ill American Medical Association1996;
Forrest  JDSingh  S The sexual reproductive behavior of American women, 1982-1988. Fam Plann Perspect. 1990;22206- 214
Link to Article
Bayne Smith  MA Teen-incentives program: evaluation of a health promotion model for adolescent pregnancy prevention. J Health Educ. 1994;2524- 29
Bell  THein  K The adolescent and sexually transmitted diseases. Holmes  Ked.Sexually Transmitted Diseases New York, NY McGraw-Hill International Book Co1984;73- 84
Cates  W The epidemiology and control of sexually transmitted diseases in adolescents. Schydlower  MShafer  Meds.Adolescent Medicine: State of the Art Reviews Philadelphia, Pa Hanley & Belfus Inc1990;409- 428
Centers for Disease Control and Prevention, National Center for HIV, STD, and TB Prevention, Sexually Transmitted Disease Surveillance, 1997.  Atlanta, Ga Centers for Disease Control and Prevention1997;
Schacter  J Why we need a program for the control of Chlamydia trachomatisN Engl J Med. 1989;320802- 804
Link to Article
Moscicki  APaletsky  JGonzales  JSchoolnik  GK Human papilloma virus infection in sexually active adolescent females: prevalence and risk factors. Pediatr Res. 1990;28507- 513
Link to Article
Centers for Disease Control, Annual Report.  Atlanta, Ga Centers for Disease Control1991;
Sonnenstein  FLPleck  JHKu  LC Sexual activity, condom use and AIDS awareness among adolescent males. Fam Plann Perspect. 1989;21152- 158
Link to Article
Romer  DBlack  MRicardo  I Social influences on the sexual behavior of youth at risk for HIV exposure. Am J Public Health. 1994;84977- 985
Link to Article
Levy  SRHandler  ASWeeks  K Correlates of HIV risk among young adolescents in a large metropolitan midwestern epicenter. J Sch Health. 1995;6528- 32
Link to Article
Centers for Disease Control and Prevention, HIV/AIDS Surveillance Report. 9 Atlanta, Ga Centers for Disease Control and Prevention1997;
Hein  K "Getting real" about HIV in adolescents. Am J Public Health. 1993;83492- 494
Link to Article
Boyer  CBKegeles  SM AIDS risk and prevention among adolescents. Soc Sci Med. 1991;3311- 23
Link to Article
Kirby  D No Easy Answers: Research Findings on Programs to Reduce Teen Pregnancy.  Washington, DC The National Campaign to Prevent Teen Pregnancy1997;
Klein  NAGoodson  PSerrins  DSEdmundson  EEvans  A Evaulation of sex education curricula: measuring up to the SIECUS guidelines. J Sch Health. 1994;64328- 333
Link to Article
Kirby  DShort  LCollins  J School-based programs to reduce sexual risk behaviors: a review of effectiveness. Public Health Rep. 1994;109339- 360
Kirby  D School-based programs to reduce sexual risk-taking behaviors. J Sch Health. 1992;62280- 287
Link to Article
Sunwoo  JBrennan  AEscobedo  J School-based AIDS education for adolescents. J Adolesc Health. 1995;16309- 315
Link to Article
Kirby  DKorpi  MAdivi  CWeissman  J An impact evaluation of Project SNAPP: an AIDS and pregnancy prevention middle school program. AIDS Educ Prev. 1997;9 ((suppl A)) 44- 61
Walter  HVaughan  R AIDS risk reduction among a multiethnic sample of urban high school students. JAMA. 1993;270725- 730
Link to Article
Bandura  A Social Foundations of Thought and Action: A Social Cognitive Theory.  Englewood, NJ Prentice-Hall1986;
Ajzen  IFishbein  M Understanding Attitudes and Predicting Social Behavior.  Englewood, NJ Prentice-Hall International Inc1980;
Terry  DJO'Leory  JE The theory of planned behavior: the effects of perceived behavioural control and self-efficacy. Br J Soc Psychol. 1995;34199- 220
Link to Article
Kirby  DBarth  RLeland  NFetro  JV Reducing the risk: impact of a new curriculum on sexual risk taking. Fam Plann Perspect. 1991;23253- 263
Link to Article
Whitley  BESchofield  JW A meta-analysis of research on adolescent contraceptive use. Popul Environ. 1986;8173- 203
Link to Article
Main  DSIverson  DCMcGloin  J Preventing HIV infection among adolescents: evaluation of a school-based education program. Prev Med. 1994;23409- 417
Link to Article
Brown  LKBarone  VJFritz  GK AIDS education: the Rhode Island experience. Health Educ Q. 1991;18195- 206
Link to Article
Kim  NStanton  BLi  X Effectiveness of the 40 adolescent AIDS-risk reduction interventions: a quantitative review. J Adolesc Health. 1997;20204- 215
Link to Article
Weeks  KLevy  SRZhu  C Impact of a school-based AIDS prevention program on young adolescents' self-efficacy skills. Health Educ Res. 1995;10329- 344
Link to Article
Newman  CDuRant  RHAshworth  CSGaillard  G An evaluation of a school-based AIDS/HIV education program for young adolescents. AIDS Educ Prev. 1993;5327- 339
Miller  BCPaikoff  RL Comparing adolescent pregnancy programs: methods and results. Miller  BCCard  JJPaikoff  RLPeterson  JLeds.Preventing Adolescent Pregnancy Newbury Park, NJ Sage Publications1992;265- 284
Misovich  SJFisher  WAFisher  JD Understanding and promoting AIDS preventive behaviors: measures of AIDS risk reduction information, motivation, behavioral skills, and behavior. Davis  CMYarbor  WHBauserman  RScheer  GDavis  SLeds.Sexuality Related Measures: A Compendium Newbury Park, NJ Sage Publications1998;
Warren  CWKann  LSmall  MLSantelli  JSCollins  JLKolbe  LJ Age of initiating selected health-risk behaviors among high school students in the United States. J Adolesc Health. 1997;21225- 231
Link to Article
Siegel  DMAten  MJRoghmann  KJ Self-reported honesty among middle and high school students responding to a sexual behavior questionnaire. J Adolesc Health. 1998;2320- 28
Link to Article
Aten  MJSiegel  DMRoghmann  KJ Use of health services by urban youth: a school-based survey to assess differences by grade level, gender, and risk behavior. J Adolesc Health. 1996;19258- 266
Link to Article
National Research Council, Losing Generations: Adolescents in High Risk Settings.  Washington, DC National Academy Press1993;42- 43
US Department of Education, National Center for Education Statistics, Dropout Rates in the United States.  Washington, DC US Dept of Education1997;NCES publication 97-473
Hayes  CDed   Risking the Future: Adolescent Sexuality, Pregnancy, and Childbearing.  Washington, DC National Academy Press1987;241

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