Advanced Search Abstract Currently, most surveys assessing adolescent health concerns focus primarily on risk behaviors and negative influences rather than positive influences such as assets. This instrument was developed to measure the prevalence of youth health risk behaviors, attitudes towards adolescent sexual behavior and youth assets in a statewide evaluation effort.
The questionnaire was completed by public high school students in Grades 9— Content validity was established through an extensive review of literature, a group process and factor analyses. Factor loadings ranged from 0. Because of several limitations e. Additional psychometric work will provide program practitioners and evaluators with a psychometrically sound tool to measure behaviors, attitudes and assets.
Introduction Adolescence is the period in life characterized by significant change. Biological, psychological changes and social learning changes occur at an astonishing rate Lerner, Adolescents are more capable of making decisions Hoffman et al.
It is also a time when youth are particularly impressionable and vulnerable to many environmental factors Fullerton, that positively or negatively influence their future health behaviors. Adolescent risk behaviors and choices tend to occur in a social context and may be synergistic.
For example, evidence suggests that teenage substance abuse is correlated with numerous risk behaviors including delinquency, conduct disorders at school, school dropout, violent and aggressive behaviors, and unplanned and unprotected sexual intercourse Jessor and Jessor, ; Zabin et al. According to Hawkins et al. As a result of this focus on risk factors, the majority of current surveillance efforts assessing adolescent health issues focus primarily on negative behaviors and influences Kolbe, ; Garrison et al.
However, an increasingly popular approach to youth prevention involves investigation beyond risk factors to include identifying and establishing the prevalence of protective factors among adolescents. Over time, protective factors can help an adolescent become more resilient and more able to resist negative influences Benard, ; Rak and Patterson, ; Benson, They found that the greater number of protective factors present in the lives of adolescents, the lower engagement in problem behaviors.
Researchers who have studied resiliency have identified certain characteristics that make adolescents more resilient. Examples of resiliency factors include involvement in structured activities, parental boundary setting, religious commitment and adult mentors Jessor et al.
Building on the research of resiliency and protective factors are youth development interventions. The emergence of the youth development approach with its focus on positive adolescent competencies, protective factors and resources has shown promise in adolescent pregnancy prevention Kirby, and other adolescent health issues.
The youth development approach considers the common underpinnings of multiple problem behaviors such as teen pregnancy, substance abuse, delinquency and school dropout. By simultaneously addressing multiple risk behaviors and building resiliency, youth development interventions are comprehensive and possibly more effective Barton et al.
Furthermore, while youth development programs tend to focus on building competencies and empowering responsible behavior, they naturally address personal deficits. Programs that enhance protective factors and take into account risk factors i. The Developmental Assets Framework suggests 40 assets that can be enhanced when present or established when initially absent in youth.
Half of these assets are suggested as internal and are labeled as the following domains: The other 20 assets are external, suggesting that they support resources available to adolescents and are labeled as the following domains: Currently, few instruments with strong psychometric properties exist that assess both risk and protective factors. Therefore, the purpose of this paper is to describe the development, validity and reliability of the Adolescent Health Attitude and Behavior Survey AHABS that measures risk behaviors, attitudes towards adolescent sexual behavior and youth developmental assets.
As an impact evaluation instrument, the survey was designed to assess intervention effectiveness in producing change in knowledge, attitudes, beliefs and behaviors Windsor et al. This survey also includes two other subscales that measure sexual knowledge and other psychosocial variables related to adolescent sexual behaviors. For the purpose of this paper, we will describe three sections of the survey: Each section will be described individually and in relationship to one another. The results of correlating one of the measures of risk taking, the level of sexual activity, to the attitudes and assets subscales also will be presented.
Second, based on the literature review, we identified the following instruments: However, none of these instruments provided the full compilation of measures needed for our evaluation efforts. Next, through a group process, we identified the need for five different sections on the AHABS instrument. Based on the results from the pilot test, the wording for several items was altered to clarify the meaning of the questions.
Reliability and validity estimates were calculated for the scales measuring attitudes towards adolescent sexual behavior and youth assets. Based on those calculations, several items were dropped for the final version of the instrument. A variety of risk behaviors were included because of their documented association with risk for unintended pregnancy Richter et al.
Response options for the risk questions were designed so that lower numbers represented lower risks. One risk behavior item, the level of sexual activity based on number of lifetime sexual partners , was used to examine validity with the scales measuring attitudes toward adolescent sexual behavior and youth assets. Past research has suggested that risks and assets are inversely correlated Jessor et al.
Level of sexual activity among the respondents was measured through an item asking how many people the survey respondent has had sex with in their lifetime. Attitudes towards adolescent sexual behavior Eleven items measuring attitudes towards sexual intercourse during adolescence were included in the survey. Instead, the investigators created new items to measure sexual attitudes. These items measured attitudes regarding self and peer sexual behavior.
Higher scores indicated higher risks. Because the attitude items were new, psychometric evaluation was needed along with analyses of the associations between risks, assets and attitudes. Youth assets Items in this section of AHABS were chosen because they measured assets that a teen pregnancy prevention project in a community setting would be most likely to change. Based on the desire to measure certain assets, concepts or actual items from the survey of Student Resources and Assets by the Search Institute Leffert et al.
Several items, with permission, were taken from the Search Institute survey; some modified based on formatting or content. Other items were developed based on the description of the assets provided by the Search Institute. Past reporting of the psychometric properties of the Search Institute surveys does not specifically delineate which survey items are measuring which assets and some assets are measured by single items Leffert et al. Additionally, the individual asset categories are not scored in any analyses.
Higher scores indicated lower assets. Data collection Participants were recruited from public high schools in 45 South Carolina counties that received funding for the Adolescent Pregnancy Prevention Initiative. In counties that had three or fewer high schools, all of the high schools were contacted regarding participation.
Once a school agreed to participate, a number of second period classes were randomly selected. All students in those classes received a passive parental consent form. Questionnaires were administered by trained evaluation staff during Period 2. Teachers were asked to remain present for survey administration; however, staff handled all aspects of data collection as one method for assisting in ensuring student anonymity. Most important in assuring student anonymity was that students were asked not to provide their name or any other identifying information on the answer sheets.
Completion of the questionnaire took 30—40 min. Data were analyzed descriptively such that mean scores, standard deviations, frequencies and ranges were calculated. Exploratory factor analysis identified two subscales measuring Attitudes Towards Adolescent Sexual Behavior and seven subscales measuring Youth Assets.
All factor analyses utilized principal axis with promax rotation. An item was assigned to a factor when its loading was at least 0. Analysis of the eigenvalues in the scree plot was also used to confirm the number of factors identified by the factor loadings Cattell, a ,b; Kim and Mueller, ; Hatcher, We created subscale scores by averaging the item scores for each scale. To further validate the scales, relationships between each subscale and one risk item were explored.
The relationships between the continuous subscales representing attitudes towards youth sexual behavior and youth assets was explored using Pearson correlations significance level was set at 0. Relationships between the continuous scales and one ordinal risk item, the level of sexual activity of the respondents, was explored using Spearman correlations. Grade 9 and 10 students made up The students represented 43 high schools.
Schools in the upstate counties of the state, typically more conservative with a higher proportion of Caucasians, declined to participate in the study more often than other schools in the state.
Reasons for declining included: Descriptive results Table I displays the descriptive characteristics of the subscales measuring attitudes towards adolescent sexual behavior and youth assets. Mean scores on the subscales ranged from 2. Descriptive results also indicated respondents used all response options available, thus decreasing the likeliness of subscales being skewed. Standard deviations ranged from 0. Although not reported here, the prevalences of these behaviors in this study population are similar to other published studies of national and statewide adolescent health risk behaviors Kolbe, ; Valois et al.
One health behavior that was chosen to include in this psychometric study was level of sexual activity measured by the number of lifetime sexual partners. Factor analysis results Attitudes towards adolescent sexual behavior subscales The attitudes towards adolescent sexual behavior section of the survey emerged with seven items 11 originally which created two subscales.
Two items were discarded because they did not load high enough on any one factor and two other items created a content cluster. Factor loadings for these two scales ranged from 0. This correlation provide some evidence for discriminate validity Hatcher, in that the scales are associated.
However, the correlations are not so strong to indicate that they are measuring the same construct. Two items clustered together creating a content cluster labeled Perceptions of Others Sexual Involvement. This content cluster had only two items and a reliability of 0. Therefore, the content cluster is presented to show an area of promise for future scale development. Youth assets subscales The assets section of the survey initially contained 43 items. In the end, 33 items were retained and yielded seven subscales Table III.
Four items were dropped either because their loadings were below 0. All remaining items loaded at 0. The factor pattern was consistent for the factor analysis using the entire sample and for the two randomly selected subsamples.