Risk, protective, AOD knowledge, attitude, and AOD behavior. Factors associated with characteristics of high-risk youth

Emlucrtion

and Program

Pergamon f

1997 cj 1997 Elsevier Science Ltd All rights reserved. Printed in Great Britain 0149-7189/97 $17.00+0.00 Pluming.

Vol. 20, No. I, pp. 2745,

RISK, PROTECTIVE, AOD KNOWLEDGE, ATTITUDE, AND AOD BEHAVIOR. FACTORS ASSOCIATED WITH CHARACTERISTICS OF HIGH-RISK YOUTH

JOANNA

TYLER

and

CAROLYN

R.O.W.

LICHTENSTEIN

Sciences Inc.

ABSTRACT Assessment of risk, protective, alcohol and other drug (AOD) knowledge, attitude, and AOD behavior of I797 high-risk youth ages 12-18 who participated in the Community Youth Activity Program demonstration project funded to 14 grantees was accomplished using the Knowledge, Attitude, and Behavior instrument. Findings of three AN0 VA and MAN0 VA models show that (a) males demonstrate more risk than females; (b) A,frican Americans and Native Americans show higher protective levels than whites and Hispanics; (c) males, as grade level increases, report more AOD knowledge than females: (d) males show more unhealthy attitudes than females, but as grade levels increase, attitudes improve ,for both males and females; fe) males report more AOD behavior than females, and both genders report increased usage as grade levels increase; and (f) protection level is directly related to AOD knowledge and attitude and inversely related to AOD behavior. Therefore, the more protection, the greater the AOD knowledge, the more positive the attitude, and the lower the risk of AOD behavior. 0 1997 Elsevier Science Ltd

INTRODUCTION

munity, project implementation (including participants’ characteristics), and individual participant outcomes. This paper describes the characteristics of the highrisk youth who participated in the CYAP projects, specifically their demographics, risk, resiliency, AOD knowledge, attitudes, and AOD behavior. The broad question examined was: “What is the nature of the population being served by CYAP projects?” This primary question was refined and augmented by several additional questions around which the analyses of the characteristics of CYAP youth were structured. These specific, additional questions were:

The Community Youth Activity Program (CYAP) was a grantee demonstration program of the Center for Substance Abuse Prevention (CSAP). It was the first CSAP program with a community prevention emphasis to be mandated by Congress in Section 3521(a)(3)(b) of the Anti-Drug Abuse Act of 1988 (Public Law 100-690). Not only were CYAP grantees to establish innovative alcohol and other drug (AOD) use prevention activities for youth, they were encouraged to form partnerships with other organizations in the community to implement these activities. CYAP was directed toward high-risk youth and their families. It consisted of 31 grantees represented by each region of the United States plus the territory of Puerto Rico. R.O.W. Sciences, Inc. conducted the National Evaluation of the CYAP. The CYAP National Evaluation was designed to evaluate state agency participation, community partnership formation, impact on the com-

Requests for reprints MD 21044, U.S.A.

should

be addressed

to Joanna

Tyler, Columbia

Do participants’ risk, protection, AOD knowledge, attitude, and AOD behavior levels vary by gender, ethnicity, or grade level? Do participants with different levels of risk and protection have different levels of AOD knowledge, attitude, and AOD behavior? Do participants’ AOD knowledge, attitude, and AOD behavior levels vary across CYAP projects?

Medical

27

Center,

11055 Little Patuxent

Parkway,

Suite 201, Columbia,

28

JOANNA TYLER and CAROLYN LICHTENSTEIN

The task of determining the best or most appropriate AOD use prevention program has a lot to do with knowing the levels of risk and protection factors and the AOD knowledge, attitude, and behavior factors demonstrated by the target youth. Clearly, this is important for CYAP programs because the knowledge, attitude, and behavior of CYAP youth can be expected to vary across programs. Examining youths’ existing levels of risk, protection, knowledge, attitude, and behavior for specific projects can be helpful in refining program content. Such information can play an important role in helping program managers and community partnerships/coalitions design appropriate prevention and intervention programs.

BACKGROUND Risk Factors Risk factors include both elements in a youth’s environment (such as living in a single-parent home or having moved place of residence frequently) and his or her responses to these factors (such as school truancy, violence, and AOD use). Swadi (1992) investigated individual behaviors that included truancy, peer AOD behavior, law infringements, conflict with parents, and school misbehavior. Peer AOD behavior and serious school misbehavior were found to be the most significant risk factors associated with adolescent AOD use. Iannotti and Bush (1992) found that youths’ perceptions of their three best friends’ AOD behavior, perceptions of their family’s AOD behavior, and actual AOD behavior of classmates were better predictors of AOD use than their best friends’ actual use. Again, this suggests that peer behaviors, whether perceived or actual, are strongly related to youths’ AOD behavior. Social factors also have been investigated as potential risks. Schinke and colleagues (1992) noted that ethnicity is not the strongest predictor of AOD behavior; rather, socioeconomic factors such as school grades and maternal education play a more significant role in whether adolescents will use alcohol or other drugs. Johnson and Pandina (1991) examined the role of family environment in youths’ AOD use, delinquency, and dysfunctional coping mechanisms. In general, they found that a family environment characterized by hostility and lack of warmth rather than by tolerance and warmth contributed most to AOD behavior. Davis and Tunks (1991) conducted an extensive investigation of social risk factors and proposed a taxonomy relating environment to addiction. Although addiction and AOD use are different outcomes that may be predicted by slightly different variables, the taxonomy presented by Davis and Tunks (1991) provides insight useful for the analysis discussed in this paper. A

variety of environments - social/interpersonal (peer, family, group influences), organizational (occupation, legislation, social pressure), cultural (time spent in social activities), and physical (location, living arrangement, income level) -contribute to addictive behaviors. Each of these environments features specific variables that interact with the life history of the user, the kind of addiction, and the life history of the user’s addictions from acquisition through maintenance, cessation, and relapse. Each of these environments also interacts with the person’s age, sex, and individual life skills. An important research problem Davis and Tunks (1991) identified was that many variables in the social/interpersonal environment often covary, confounding attempts to determine causation (e.g., peer use and availability). For example, following the theory that social variables play a dominant role in youths’ AOD use, Silverman (199 1) investigated youth lifestyle variables such as musical taste, sexual activity, and socialization sites (e.g., physical living settings). His findings showed that heavy metal musical tastes and sexual activity were related to AOD behavior, but it was not proposed that they directly caused this behavior. The importance of isolating meaningful etiological factors - and therefore appropriate targets of prevention programs remains a priority on the agenda of prevention researchers. Risk factors for AOD behavior also often vary among various ethnic and racial groups. In a recent study of risk factors for early adolescent AOD behavior among African Americans, non-Hispanic whites, Cubans, and Hispanics other than Cubans, Vega and colleagues (1993) reported that African Americans had the highest mean number of risk factors. This may be important in light of the suggestion by several researchers (Bry et al., 1982; U.S. General Accounting Office, 1993) that the number of risk factors an individual must cope with may be more important than exactly what those factors are. In Vega and coworker’s study, however, non-Hispanic whites with no risk factors were nearly twice as likely as African-Americans to have tried alcohol. Cubans exhibiting no risk factors showed a lifetime AOD use similar to non-Hispanic whites, and Hispanics other than Cubans had lifetime AOD use similar to African Americans. With respect to risk factors, African Americans and Hispanics other than Cubans were more vulnerable to depressive mood and low self-esteem. Cubans and non-Hispanic whites were most likely to believe that their friends used alcohol or other drugs, whereas non-Hispanic whites reported the lowest levels of family pride. Risk factors were found to be related to alcohol and illicit drug use among the study sample. Thus, this study demonstrated the value of considering risk factors for predicting AOD behavior among early adolescents separately for each ethnic and cultural group (Vega et al., 1993).

High-Risk Youth Protective Factors Involvement in religious activities and contact with parents and other adults are considered positive features of youths’ social and emotional development that may confer resiliency or protection against the development of AOD problems. These positive features are referred to as protective factors. A variety of studies suggest that stability and structure, including a support system, and religious involvement in the social environment, can all serve as protective factors against AOD use (Barrett et al., 1988; Ogborne et al., 1985; Brisbane & Womble, 1985-1986). Specifically, Eng et al. (1990) concluded that religious norms have a greater influence than cultural norms in cohesive religious groups, whereas cultural norms are more influential than religious norms among less cohesive religious groups. Brown and Horowitz (1993) have argued recently that future prevention programs should focus more on protective factors as a way of avoiding the problems of labeling or inherent in the risk factor “deviance assumption” approach. Knowledge Factors AOD knowledge and its role in adolescent AOD prevention programs has been widely studied. Recent studies generally have focused on either youth subculture and “streetwise” knowledge or the more formal, standard AOD curriculum presented in school health classes or in AOD prevention program formats. For example, a recent study by Raskin et al. (1992) examined AOD knowledge within the context of a subculture or “culture of drugs” among a sample of 2635 middle and high school students. Specifically, the study examined the concept colloquially known as “streetwise.” Using the Drug Knowledge Questionnaire (30 multiple-choice items), they found the following: (1) Knowledge of the drug culture is positively correlated with AOD behavior; (2) AOD knowledge is more reliable and coherent in older youths; and (3) AOD knowledge is unrelated to other kinds of knowledge acquired in school. Raskin and coworkers also noted that youth exposed to peers’ AOD use in school have more AOD knowledge; also, the earlier young people begin AOD behavior, the more they know about the drug culture. These researchers suggest that if youth are persuaded by “street” knowledge, then knowledge acquired within the context of a prevention program may have an impact only if the youth respects the source and level of the knowledge they acquire within a prevention program. Attitude Factors The importance of changes in attitude relating to changes in AOD behavior has been another widely studied area of AOD prevention, usually in the context of school-based education programs (see Kumpfer, 1990

29

for a review). The attitude issues that appear most persistent are those relating to (1) feelings of self-esteem and reasons for using alcohol or other drugs (also referred to in the literature as intrapsychic or intrapersonal concepts), and (2) peer influence (also referred to as interpersonal concepts). One recent study (Novacek et al., 1991) of youths’ drug use behavior examined the relationships among the variables typically studied and indicated that a more differentiated understanding of the complex relationships among AOD attitudes and behavior may be emerging. The study focused on young people’s intrapersonal or intrapsychic attitudes (their reasons for using alcohol or other drugs). These adolescents gave five reasons for their AOD use: desire to belong, a means of helping them cope, desire for pleasure, desire to enhance creativity, and a way of acting out feelings of aggression. There were reported differences in characteristics of these adolescents, specifically their age and sex, as well as in their reasons for AOD use. The researchers concluded that using alcohol or other drugs for pleasure or to cope is associated with more frequent AOD use, whereas using them to belong, to become more creative, or for aggressive purposes is related to less frequent use.

METHOD Instrumentation The Knowledge, Attitude and Behavior instrument (the KAB - see Appendix A) was developed to measure participants’ responses to the CYAP activities by measuring their AOD knowledge, attitudes, behavior, and behavior intent; interpersonal and intrapersonal attitudes; and grade at first AOD use. These factors were to be measured when participants first entered the program (preprogram), when they finished the program (postprogram), and some time between 3 and 6 months after they left the program (follow-up). The KAB also measured youths’ self-reported demographic characteristics, risk factors and protective factors. The five broad factors measured by the KAB (risk, protection, AOD knowledge, attitude, and AOD behavior) are made up of several subfactors, as follows: Risk Living with a single parent Average grade received in school Number of school days missed in past month Having to repeat a year in school Number of times moved Self-reported deviant behavior Perceived friends’ deviant behavior 0 Protection Involvement in religious activities Adult interaction Parent interaction l

30

l

l

l

JOANNA

TYLER

and CAROLYN

Spare time activities Recreational activities AOD knowledge Source of AOD knowledge Level of AOD knowledge Attitude Self-esteem (intrapersonal attitude) Peer resistance skills (interpersonal attitude) AOD attitude AOD behavior AOD use (including the use of cigarettes, alcohol, and marijuana) Grade at first use Plans for future use

The KAB was modeled on the Monitoring the Future instrument used in the annual High School Senior Survey conducted by the National Institute on Drug Abuse. To make the KAB appropriate for use with high-risk youth, it was uniquely designed with a modified language level, a lower reading level (seventh grade readability level as measured by the SMOG test), shorter and fewer items, and modified instructions. The KAB is also different from other AOD knowledge, attitude, and behavior instruments in that design emphasis was placed on making the instrument culturally competent. To accomplish this, a panel of experts consisting of individuals representing a range of racial/ethnic groups, who work with and evaluate highrisk youth, participated in the KAB instrument development. The National Evaluation Expert Advisory Panel called attention to several important points critical to designing an instrument appropriate for use with CYAP high-risk youth. The panel cited several failings of existing instruments. First, they did not meet the criteria for being culturally appropriate for CYAP’s diverse population. They did not demonstrate both sensitivity to cultural differences and similarities and effectiveness in using cultural symbols to communicate a message. Second, existing instruments lacked cultural sensitivity. An inherent awareness of the nuances of other cultures was conspicuously absent. Third, language usage presented in existing instruments was considered “mainstream English.” There was no reference to “spiritual leaders,” a term Native Americans association with their religious leaders. Parentheses were commonly used -a puncuation style not readily understood by African American high-risk youth. Finally the reading level of existing instruments appropriate for use with adolescent youth were written at a reading level above seventh grade and considered too difficult for CYAP high-risk youth to read. The KAB was pilot-tested twice with high-risk youth representing CYAP projects in 19 states. Based on these data, the instrument items were refined, item reliability (Table 1) and validity (Table 2) were established, and

LICHTENSTEIN

scales to be used as measures of the factors and subfactors described previously were developed. The statistic used most frequently to assess the reliability of a set of items in measuring a particular factor is Cronbach’s alpha. An estimate of the lower bound of the reliability coefficient is given by Cronbath’s alpha as shown in Table 1. All the values are no smaller than 0.60, and most of them are greater than 0.70. Thus, the scale items on the survey are measuring consistently and reliably the factors they were supposed to measure. The construct validity of the scales developed to measure the factors and subfactors described previously is also assessed. Nunnally (1967) describes the validation of constructs as the determination of whether or not the variables being used act as though they measure the constructs they are supposed to be measuring, which can be assessed by examining whether the measures correlate in expected ways. The construct validity of the KAB scales is investigated by examining the correlation matrix of the scale scores, which is given in Table 2. The pattern of correlations in this table indicates that correlations between two “positive” subfactors or two “negative” subfactors are generally greater than zero (indicating that the two subfactors are directly related), whereas correlations between one “positive” and one “negative” subfactor are generally less than zero (indicating that the two subfactors are inversely related). Sample Included Since many states had not collected postprogram and program follow-up data by the specified deadline for this study, only data gathered during preprogram KAB administrations were included in this study. Fourteen of the thirty-one CYAP grantees provided preprogram KAB data on a total of 1797 self-selected youth. The participants providing KAB data ranged in age from 9 to 21, with most being between 12 and 18 years old. Slightly more males (51.6%) than females provided preprogram KAB data, and more African Americans (49.0%) than any other group participated (24.6% whites and smaller percentages of other racial groups). Although the youth involved in the CYAP programs are self-selected and, therefore, may not be representative of the population of youth available to participate in the programs, describing their characteristics does provide insight into the types of youth who are likely to participate in such programs. Procedure The preprogram KAB was to be administered to all participants before they began involvement in any CYAP prevention or intervention activities. In many programs, however, the KAB was administered to all participants at the same time near the beginning of the program. Thus, each participant in these programs had

High-Risk Youth

31

TABLE 1 VALUES OF CRONBACH’S ALPHA FOR KAB FACTORS Factor

Items on survey

Alpha

Protective subfactors Involvement in religious activities Adult interaction All together, including parent interaction+

lOe, 13i, 15 1Oa-1 Od,l Of-l Oj lOa-lOj,11,13i,15

0.63* 0.74 0.76’

14a-l4c,l4h,14i,14k, 14m,14n,14r,l4s,14v,14w 17a-179 As in individual factors

0.71 0.60 0.63*

16a-161 18a-189 19a-19n As in individual factors

0.63 0.84 0.93 0.74*

13a-13n 14d-14g,14j,141, 14o-14q,14t,14u 20a-201 21a-21j As in individual factors

0.71

23,24,27-30” 37b,37c,37k,371 23,24,27_30,37b,37c, 37k,371,38

0.88’ 0.80’

AOD knowledge subfactors Source of knowledge Level of knowledge All together Attitude subfactors Intrapersonal attitude Interpersonal attitude AOD attitude All together Nondrug behavior subfactors Spare time activities Recreational activities Perceived deviant behavior in friends Perceived deviant behavior in self All together AOD behavior subfactors AOD use Grade at first use All together, including plans for future use+

0.67 0.90f 0.83 0.77’

0.89*

Notes: ‘This value is computed using standardized values for the individual items because items with different scales are included. +The parent interaction factor and the plans for future use factor are measured by single items on the survey, so no alpha was necessary for these factors by themselves. *This alpha was computed with a response of 5 = Don’t Know set to missing (so that response choices l-4 would constitute a scale). 1 The other items referring to AOD use (25 and 31-36) were not included because most of the respondents in our sample had never tried those drugs. In addition, item 22 is omitted because it is not a scale. This alpha was computed with a response of 1 = Never set to missing (so that response choices 2 through 8 would constitute a scale).

been exposed to the program for a different length of time before taking the preprogram KAB. This means that the responses may not truly measure preprogram levels of knowledge, attitude, and behavior; however, it is likely to represent the “state” of knowledge, attitude, and behavior before substantial program effect. All programs were established for the original 3-year period, although specific program activities varied in type and length. Nevertheless, most youth participated in the programs as an ongoing experience in a variety of activities for various periods of time. KAB data were summarized using several statistical procedures. Each participant’s responses for all KAB items constituting a single subfactor were combined into

a single score. If all the items in a subfactor had the same scale for their response choices, then the nonmissing responses were averaged to create the subfactor score. However, when the items’ response choices were not compatible, each nonmissing response was converted to a Z-score (standardized on the mean and standard deviation of that item across all respondents) before averaging across items (Snedecor & Cochran, 198 1). By definition, the Z-scores for a particular item will have a mean of zero and a standard deviation of 1. Therefore, the subfactor scale scores computed from Zscores for nonmissing items will have means very close to zero as well. In combining subfactor scale scores into the broader factor scale scores, all subfactor scale scores

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High-Risk Youth were standardized and averaged. Thus, the scores for the five broad scales are approximately centered on 0. The scores for the five scales measuring the five broad factors (risk, protection, AOD knowledge, attitude, and AOD behavior) are computed so that the direction of each scale is sensible. A higher risk scale score indicates that the participant is at greater risk. A higher protective scale score indicates more protection. A higher AOD knowledge scale score indicates the participant has greater knowledge about AOD issues. A higher score on the attitude scale indicates a better attitude about oneself and one’s peers, and a more prudent attitude about AOD use. A higher AOD behavior scale score indicates greater involvement with alcohol and other drugs.

RESULTS

TABLE 3 MODELS FOR ASSESSING PATTERNS OF AOD KNOWLEDGE, ATTITUDE, AND BEHAVIOR Model 1 Dependent variables Risk scale Protective scale AOD knowledge scale Attitude scale AOD behavior scale Model 2 Dependent variables AOD knowledge scale Attitude scale AOD behavior scale

AND DISCUSSION

Three models were developed research questions:

to answer

33

Independent variables Gender Ethnicity Grade Grade and gender interaction Grade and ethnicity interaction

Independent variables Gender Ethnic@ Grade Grade and ethnicity interaction Risk scale Protective scale Risk scale and ethnicity interaction Protective scale and ethnicity interaction

the following

Do participants’ risk, protection, AOD knowledge, attitude, and AOD behavior levels vary by gender, ethnicity, or grade level? Do participants with different levels of risk and protection have different levels of AOD knowledge, attitude, and AOD behavior? Do participants’ AOD knowledge, attitude, and AOD behavior levels vary across CYAP projects? Table 3 presents the dependent and independent variables found in the models. ANOVA and MANOVA techniques were used for assessing Models 1, 2, and 3. A separate ANOVA was carried out relating each dependent variable to all the independent variables in the model. In addition, a MANOVA was carried out combining all the dependent variables in a model into a single dependent variable because the dependent variables in each model are conceptually interrelated. A MANOVA taking the interrelationships into account provides different results from the results arising from separate ANOVAs. The data from participants in all 14 grantees’ programs, including several programs in some states, were combined for these analyses in an effort to describe the entire population of CYAP participants. Model 1 Model 1 was constructed to test for differences in the levels of the five scales among youths of differing gender, ethnicity, and school grade, thus answering research question 1. Model 1 included all five scales as dependent variables, with only demographic characteristics as predictor variables (including grade as a covariate). Table 4 presents the ANOVA and MANOVA results. The ANOVA findings show that gender is associated

Model 3 Dependent variables AOD knowledge scale Attitude scale AOD behavior scale

Independent variables Gender Ethnicity Program Grade Grade and ethnicity interaction Risk scale Protective scale Risk scale and ethnicity interaction Protective scale and ethnicity interaction

with risk, attitude, and AOD behavior (i.e., the risk, attitude, and behavior levels of males and females are significantly different). The ANOVA findings also show that ethnicity is associated with protection only (i.e., only levels of protection differ significantly among different ethnic groups). In addition, separate analyses showed that African-American and Hispanic youth have higher mean scores for participation in religious activities than do white youth. Grade level is significantly associated with all factors except risk, meaning that protection, AOD knowledge, attitude, and AOD behavior levels are significantly different for participants in different grades. In addition, the grade and ethnicity interaction is significant in predicting AOD knowledge and behavior, which means that the grade differences in knowledge and behavior have different patterns for the different ethnic groups. When all the dependent scales are combined in a MANOVA, gender, ethnicity, grade, and the grade-byethnicity interaction are all significant predictors of the combined measure. This means that the combination of the five factors varies across all the demographic characteristics considered.

JOANNA TYLER and CAROLYN

34

TABLE 4 ANOVA AND MANOVA

LICHTENSTEIN

RESULTS*

Risk scale+

Protective scale+

AOD knowledge scale+

Attitude scale+

AOD behavior scale+

0.0001 NS NS NS NS

NS 0.0001 0.0001 NS NS

NS NS 0.0029 NS 0.0031

0.0088 NS 0.0001 NS NS

0.0085 ND 0.0001 NS 0.0007

0.0004 0.0001 0.0001 NS 0.0001

Model 2 Gender Ethnicity Grade Grade and ethnicity interaction Risk scale Protective scale Risk scale and ethnicity interaction Protective scale and ethnicity interaction

0.0001 NS 0.0001 NS NS 0.0001 NS NS

0.0002 NS 0.0001 NS 0.0001 0.0001 NS NS

0.0001 NS 0.0001 0.0059 0.0001 0.0001 0.0001 0.0005

0.0001 NS 0.0001 0.0016 0.0001 0.0001 0.0001 0.0001

Model 3 Gender Ethnicity Program Grade Grade and ethnicity interaction Risk scale Protective scale Risk scale and ethnicity interaction Protective scale and ethnicity interaction

0.0001 NS 0.0001 0.0002 NS NS 0.0001 NS 0.0033

0.0001 NS 0.0001 0.0001 NS 0.0001 0.0001 NS NS

0.0001 NS 0.0001 0.0001 0.0015 0.0001 0.0001 NS 0.0007

0.0001 NS 0.0001 0.0001 NS 0.0001 0.0001 NS 0.0001

Independent

variables

Model 1 Gender Ethnicity” Grade Grade and gender interaction Grade and ethnicity interaction

All five combined*

‘The results presented here are either the actual pvalue of the F-test for the particular variable, if the test was significant, or “NC?’ for not significant. The significance level used was different for each model because it depended on the number of independent variables included: For Model 1 the cutoff pvalue was .Ol (.05/5); for Model 2 the cutoff pvalue was .0063 (.05/8); and for Model 3 the cutoff p-value was .0056 (.05/g). +These analyses were ANOVAs. *This analysis was a MANOVA. nA gender-by-ethnicity interaction was originally included in the model, but it was never significant, so it was dropped.

It appears from an examination of a series of confidence intervals that females have lower risk and better attitudes and behavior than males and that whites have the least protection in their environment. In addition, the level of protection is higher in the lower grades than in the higher grades, AOD knowledge is greater in the higher grades, attitude is more positive in the higher grades, and there is greater involvement in AOD behavior in the higher grades. Tukey’s Studentized Range Test was used to test all pairwise comparisons among the ethnic group means. The comparisons showed that the significant result for ethnicity as a predictor of the protective factor occurred largely because of the significant differences between the protective factor scores for African-Americans and Hispanics, African-Americans and whites, and Native Americans and whites. In summary, the ANOVA analyses of Model 1 show

that youths’ risk scale scores vary only by their gender, whereas the protective scale scores vary only by ethnicity and school grade. School grade and gender have important bearing on attitude and behavior scales, but ethnicity does not (although the relationship between grade and AOD behavior is different for different ethnic groups). Also, AOD knowledge scale scores are different only across school grade, although again the patterns in the levels of knowledge across grades are different for different ethnic groups.

Model 2 Model 2 was constructed to examine whether knowledge, attitude, and behavior scale scores were related to risk and protection scale scores, statistically controlling for demographic characteristics, thus answering research question 2. An ANOVA and a MANOVA

High-Risk

were applied using the risk and protective scales and their interactions with ethnicity as covariates. The ANOVA results given in Table 4 show that youths’ risk level is significantly associated with attitude and AOD behavior, whereas their protection level is significantly associated with AOD knowledge, attitude, and AOD behavior. Specifically, the greater the level of risk, the poorer the attitude and the greater the involvement in AOD behavior. The greater the level of protection, the greater the AOD knowledge and the better the attitude and AOD behavior. This fact suggests that protection is key to having good AOD knowledge, a positive attitude, and very little AOD behavior. The interactions of ethnicity with the risk and protective scales are associated with AOD behavior only (i.e., the risk and protective scales have different relationships with AOD behavior for different ethnic groups). When a MANOVA is performed for Model 2, statistically significant results are shown for both the risk and protective scales as well as for their interactions with ethnicity. In addition, gender, grade, and the grade-byethnicity interaction are still significant. This indicates that even youth with the same levels of risk and protection in their lives differ in their AOD knowledge, attitude, and AOD behavior by gender and grade in school. However, ethnicity is no longer important when the protective scale is included, implying that the only differences in the five scales among ethnic groups are in the protective factor. In summary, these results suggest that risk and protective factors are more important than ethnicity in predicting whether youth will use alcohol and other drugs, because ethnicity is no longer significant in the model that includes the risk and protective scales. This finding adds another dimension to the finding of Schinke et al. (1992) that socioeconomic factors play a much stronger role than race/ethnicity in whether youth use drugs. Youth who are more exposed to risk factors seem to be more involved in AOD behavior and have less AOD knowledge and a less positive attitude regardless of ethnicity, although the specific relationships between risk and protection and knowledge, attitude, and behavior will be different for different ethnic groups. It would help program managers at each site to know the relative status of the youth population in the areas of risk and protective factors as well as AOD knowledge, attitude, and behavior. Such information can play a role in helping program managers and partnership coalitions design appropriate CYAP prevention and intervention strategies for the population at risk. Model 3 Model 3 was constructed to consider whether participants of different CYAP projects had different levels of knowledge, attitude, and behavior, controlling for

Youth

35

their risk and protection levels and demographic characteristics, thus providing an answer to research question 3. The answer comes from an examination of the average levels of the five factors found among different programs’ participants, in addition to the statistical results. Analytical procedures included using an ANOVA and a MANOVA that added an indicator for program as an independent variable. In addition, the AOD knowledge, attitude, and AOD behavior levels were examined for each program separately. Results from this analysis can provide program managers with insight as to how they might create successful prevention and intervention strategies given the level of AOD knowledge of youth in their programs, the kinds of attitudes the youth exhibit, and the kinds of AOD behavior in which CYAP youth are involved. The ANOVA and MANOVA results presented in Table 4 for Model 3 show that program is significantly associated with AOD knowledge, attitude, and AOD behavior even when the effects of risk and protective factors (and demographic characteristics) are controlled. This suggests that AOD knowledge, attitude, and AOD behavior levels vary across programs. It is interesting to note that the grade-by-race interaction is no longer significant, suggesting that it was serving as a proxy for different programs in the earlier models. Gender, grade, and the risk and protective scale covariates are still associated with knowledge, attitude, and behavior as in Model 2. Mean scores for the program-level factor for each program are shown in Table 5. Arizona and California grantees provide two examples of the way in which KAB information can be used to determine effective prevention and intervention strategies. First, youth participating in the Phoenix, AZ, gang prevention program show some interesting characteristics. The standardized average risk scale score (- .1526) is low, indicating the group is at less risk than many other programs’ youth. The group’s average score on the protective factor (- .1858) is also low, indicating that there is little in the way of protective features in their environment. Their average scores for AOD knowledge (.0568) and attitude (.1591) are slightly higher than their average score for AOD behavior (.0339). This suggests that AOD behavior inhibition is less well-developed than positive attitudes and good AOD knowledge. In comparison, participants of the California program located in the San Jacinto Valley are similar to the Arizona group on average risk scale score (- .I2 14) and average protective score (- .1757). However, as a group their AOD average knowledge score (- .0993) and attitude score (- .0361) are low and their average AOD behavior score (.O 144) is positive (i.e., their knowledge and attitude are poor relative to their AOD behavior).

JOANNA

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and CAROLYN

LICHTENSTEIN

TABLE 5 MEAN SCALE SCORES BY PROGRAM

Risk

Program name New Turf-Gang Prevention Program, Phoenix, AZ San Jacinto Valley-wide Teen Project St. Cyprian Community Action Group Project SUCCESS Black Alcoholism Council (BAC) Mothers Against Drugs Project Uplift Save a Child Hillside Village and Crescent Court Development Bromley-Heath Eliot Church of Roxbury Project Unity Northern Educational Services Aureus Co.: A Management Company for Non-Profit Pleasant Homes Boards in Motion Crow Cultural Youth at Risk Libby Cares HELP Human Resources Council Jr High Lock-In PLAS4FN BSA Family Advocate Ohio (50) Character Formation Institute of Volunteers Corporation Peer Counseling Better Kids Project Prevention Project for Group Homes John De La Howe Thornwell Carolina Project Harambee *These are standardized

-.1526 -.1214 .0310 .0049 .0758 - .3654 -.0516 - .2635 - .0415 - .0444 .1599 .0575 - .0852 - .0576 - .3279 - .2487 .0895 -.3124 - .4062 .3728 -.1458 - .3559 .0368 .0174 .1862 .3291 -.1965 .2314 -.1256 .1497 - .0604 .0625

-.1858 -.1757 - .0708 .lOOO .2846 .2205 .0340 .2891 - .0661 .1695 .0032 - .0735 .3487 .5912 .2213 - .2483 .1785 .0427 - .0334 -.1994 - .3230 -.1079 - .5626 -.5188 .0783 - .0065 -.1222 -.1217 p.1436 -.1224 .0913 .0838

AOD knowledge

Attitude

AOD behavior

.0568 - .0993 - .4580 -.2715 .2746 .1352 -.1071 - .2514 .1964 .4901 -.0618 .2836 .5258 .3309 .2243 - .0466 .1844 .0717 -.1565 - 1.0623 - .0969 .1138 .1194 .3976 -.1503 ~ .2542 .2647 .0397 - .0539 .1137 .4524 -.0213

.1591 - .0361 .3523 -.1238 .2322 .4884 .1863 - .0190 - .0504 .0758 - .0027 - .0609 .2447 .0661 .3283 -.1305 -.1208 .3273 .1205 - .5969 -.1210 .1439 .0670 .1071 p.1681 - .2683 .3176 - .2789 - .5087 -.4418 - .2803 .1269

.0339 .0144 -.1065 -.1784 - .0804 - .3302 - .0970 - .3736 -.1860 -.1369 .1135 - .0184 -.1044 - .3509 - .2608 - .0390 .2999 - .0655 - .2707 .9444 - .0420 - .0638 .2272 .2793 -.1052 n/a -.0718 .4407 .0412 .6792 .1660 - .2705

Z-scores.

This information may be helpful to program managers because it indicates where they should focus CYAP project content. In Arizona, it seems that it would be more important to stress the need for less AOD use, thus attempting to increase positive behavior. In California, this focus also is important, but the population in the San Jacinto Valley project may need more information to improve AOD knowledge and more selfesteem work to improve attitude. This discussion illustrates how an examination of the average scale scores for individual projects can support the statistical finding of knowledge, attitude, and behavior variation across programs by providing insight into areas of weaknesses of particular programs. Although such a broad numerical pattern cannot possibly determine the types of intervention activities appropriate for a particular project, it can contribute one piece of information to program managers in planning project activities.

SUMMARY

AND CONCLUSIONS

The first research question addressed by the analysis focused on patterns in CYAP participants’ risk, protection, AOD knowledge, attitude, and AOD behavior. The analysis examined ways in which these factors vary by gender, ethnicity, and grade level and revealed that patterns for each factor are different. In general, only protection varies across ethnic groups, while risk, attitude, and AOD behavior vary for males and females, and protection, AOD knowledge, attitude, and AOD behavior vary by grade in school. When the five factors are analyzed separately, the following specific conclusions can be stated: Risk factors vary only by gender, with males demonstrating more risk behaviors than females. Youth showing elevated risk factors in their lives also have poor attitudes while showing elevated AOD behavior. Therefore, high-risk youth seem to be in danger of

High-Risk Youth being attracted toward AOD use. This appears to be true regardless of ethnicity. Protection factors vary across ethnicity, with African Americans and Native Americans demonstrating that they are the most protected among high-risk ethnic and racial groups. Youth with a strong protective factor show high levels of AOD knowledge and positive attitudes while demonstrating low levels of AOD behavior. Therefore, participation in religious and recreation activities and consistent contact with parents and other adults may help steer youth away from AOD use. Protection levels also vary across grade level. However, this finding may be a function of how programs were implemented. (That is, different programs were aimed both at youth of different backgrounds and youth in different grades.) AOD knowledge varies only across grade level with youth in higher grades having more knowledge than youth in lower grades; however, there is variation in this pattern for each ethnic and racial group. Attitude varies across gender and grade level, showing that males have a less healthy attitude about themselves and about drug use than females, with improvement in everyone’s attitude as grade level increases through high school. AOD behavior also varies across gender and grade. Males report more AOD behavior than females, with the reported AOD behavior of both increasing as they progress through high school. This general finding remains true, although the frequency of AOD behavior varies across grade for each ethnic and racial group. AOD knowledge, attitude, and AOD behavior do not vary across ethnic groups. Investigating the second research question focused on examining how AOD knowledge, attitude, and AOD behavior vary with risk and protection level, controlling for gender, ethnicity, and grade level. When this kind of analysis was performed, the following conclusions were reached: AOD knowledge, attitude, and AOD behavior vary across gender and grade, but not across ethnicity. This conclusion reinforces the conclusion reached in the prior analysis. Higher levels of risk are related to poorer attitude and more involvement in AOD behavior. Therefore, youths at greater risk have more vulnerable attitudes and behavior. Protection level is directly related to AOD knowledge and attitude and inversely related to AOD behavior. Therefore, youths with more protection have greater AOD knowledge and more positive attitudes and lower risk of AOD behavior. The third research

question

dealt with prevention

pro-

37

gram type. Knowing the level of high-risk youths’ AOD knowledge, attitude, and AOD behavior before they begin to participate in a CYAP program has some important implications for program development. In designing prevention / intervention strategies, emphasis can be placed on activities that address youths’ weak areas, whether those areas are AOD knowledge, attitude, or AOD behavior. If all three areas are weak, then an appropriately balanced prevention program can be created. If only one of these areas is weak, then more emphasis can be placed where it appears to be needed. Therefore, examining youths’ factor levels for each specific program is helpful. Last, the knowledge, attitude, and behavior of the youth vary across gender and grade even after statistically controlling for the program variable. Yet, the pattern shown across grade level is no longer different for each ethnic/racial group, suggesting that this variable may have been just a proxy for the type of CYAP implemented. Thus, administering the KAB to all highrisk youth in a preprevention program setting has merit in allowing program managers to accurately assess individual and group levels of youths’ risk and protective factors as well as their AOD knowledge, attitude, and AOD behavior. Most recent reviews of adolescent AOD prevention research comment on the flaws and methodological inadequacies of both etiological research and program evaluations in the field (Harmon, 1993; Peterson et al., 1992; Stoil, 1993). Inherent in the present study is the commonly mentioned problem of having a self-selected target population on which self-reported AOD information is gathered. This limitation is problematic in each program type and is compounded by program managers and evaluators’ lack of rigor in using control or comparison groups. Other limitations of the study discussed here arise from the nature of the evaluation and the nature of the KAB. First, both the national evaluation and the local evaluations were structured quite loosely, in that there was no mandate about evaluation designs to be used. This lead to samples at the local level that were selfselected so that the youth participating in a particular project were not necessarily representative of the population targeted by that project. This loose structure also lead to the use of the KAB instrument by only a subsample of all the CYAP projects, rather than the uniform use by all CYAP projects. Second, the use of the KAB had two limitations. First, it is a self-administered instrument, making the levels of risk, protection, AOD knowledge, attitude, and behavior obtained self-reported (and, therefore, open to some inaccuracy). Second, the reading ability of the youth completing the KAB may have limited the accuracy of the results obtained, despite the efforts taken in designing the KAB to lower the reading level.

38

JOANNA TYLER and CAROLYN LICHTENSTEIN

Overall, the KAB has good reliability and validity psychometrics and appears to be appropriate for use with high-risk youth for whom it is designed. Analyses of characteristics of youth measured on the KAB present findings that are similar to findings reported in other recent research efforts to investigate adolescents’ AOD risk, protection, and lifestyle. Similarity of results is encouraging as it helps establish the KAB as a viable tool for measuring high-risk youth populations.

REFERENCES Barrett, M.E., Simpson, D.D., & Lehman, W.E. (1988). Behavioral changes of adolescents in drug abuse intervention programs. Journal qf Clinical Psychology, 44, 461413. Brisbane, F.L., & Womble, M. (198551986). Afterthoughts and recommendations. Alcohol Treatment Quarterly, 2(34), 249-270. Brown, J.H., & Horowitz, J.E. (1993). Deviance and deviants: Why adolescent substance abuse prevention programs do not work. Eoaluation Review, 17, 529-555. Bry, B.H., McKeon. P., & Pandina, R.J. (1982). Extent of drug use as a function of number of risk factors. Journal of Abnormal Psychology. 91, 271-279. Davis, J.R., & Tunks, E. (1991). Environments proposed taxonomy. The International Journal 25(27A and SA), 805-826.

and addiction: A of the Addictiom.

Eng, R.C., Hanson, D.J., Gliksman, L., & Smythe, C. (1990). Influence of religion and culture on drinking behaviours: A test of hypotheses between Canada and the USA. British Journal of Addictions, 85, 1475-1482. Harmon, M. A. (1993). Reducing the risk of drug involvement among early adolescents: An evaluation of Drug Abuse Resistance Education (DARE). Etraluation Reriebv. 17, 22 l-239. Iannotti, R.J., & Bush, P.J. (1992). Perceived vs. actual friends’ use of alcohol, cigarettes, marijuana, and cocaine: Which has the most influence? Journal of Youth and Adolescence, 21(3), 375-389. Johnson, V., & Pandina, R.J. (1991). Effects of the family environment on adolescent substance use, delinquency, and coping styles. American Journal qf Drug and Alcohol Abuse, 17(l), 11-88.

Kumpfer, K.L. (1990). Challenges to prevention in schools: The thousand flowers must bloom. In K.H. Rey, C.L. Faegre, & P. Lowery (Eds.), Prevention researchfindings: 1988. Office for Substance Abuse Prevention Monograph No. 3 (pp. 108-123). (DHHS Publication No. ADM 91-1665). Rockville, MD: OSAP. Novacek, J., Ruskin, R., & Hogan, R. (1991). Why do adolescents use drugs? Age, sex, and user differences. Journal of‘ Youth and Adolescence, 20(5), 415492. Nunnally. Hill.

J.C. (1967).

Psychometric

theory.

New

York:

McGraw-

Ogborne, A.C., Sobell, M.B., & Sobell, L.C. (1985). The significance of environment factors for the design and the evaluation of alcohol treatment programs. In M. Galizio & S.A. Maisto (Eds.), Determinants of substance abuse: Biological, psychological, and emironmental factors. New York: Plenum. Peterson, P. L., Hawkins, S. D., & Catalono, R. F. (1992). Evaluating comprehensive community drug risk reduction interventions. Design challenges and recommendations. Evaluation Retries, 16, 579-602. Raskin, R., Novacek, J., & Hogan, R. (1992). Drug culture expertise and substance use. Journal of‘ Youth and Adolescence, 21(5), 625-637. Schinke, S., Orlandi, M., Vaccaro, D., Espinoza, R., McAlister, A., & Botvin, G. (1992).Substance use among Hispanic and non-Hispanic adolescents. Addictive Behaviors, 17. 117-124. Silverman, population. 117.

W.H. (1991). Prevalence Journal qf Adolescent

of substance use in a rural teenage Chemical Dependency. 2(l), 107-

Snedecor, G.W., & Cochran, W.G. (1981). Statisticalmethods. IA: The Iowa State University Press.

Ames,

Stoil, M. (1993). The National Structured Evaluation of drug abuse prevention approaches. Paper presented at annual meeting of the American Public Health Association, San Francisco. CA. Swadi, abuse.

H. (1992). Relative risk factors in detecting Drug and Alcohol Dependence, 29, 253-254.

adolescent

drug

U.S. General Accounting Office. (1993). Community-based drug prevention: Comprehensicr eraluations of efyorts are needed. (Publication No. GAO/GGD-93-75). Washington, DC. Vega, W., Zimmerman, R.S., Warheit, G.J., Apospori, E., & Gil, A.G. (1993). Risk factors for early adolescent drug use in four ethnic and racial groups. American Journal of Public Health, 83(2), 1855 189.

High-Risk

Youth

39

APPENDIX A

KNOWLEDGE, ATTITUDE, AND BEHAVIOR INSTRUMENT (KAB) Introduction This instrument was developed for the Center for Substance Abuse Prevention (CSAP), Substance Abuse and Mental Health Services Administration (SAMHSA), Public Health Service, U.S. Department of Health and Human Services, as part of the Community Youth Activity Program (CYAP) demonstration program. The Knowledge, Attitude, and Behavior instrument (KAB) was developed to be used as a tool with which high-risk youths’ lifestyle changes can be measured and monitored. It was designed as a self-report instrument, and it is recommended that it be administered prior to youth participation in a program (pretest), after the youth have completed the program (posttest), and at a later time, such as 3 months, after the posttest (followup). KAB was extensively pilot-tested among youth from different racial and ethnic groups and was adjusted to be culturally sensitive across these groups. Youth voluntarily participating in CYAP projects in 19 States were surveyed using KAB. The information was used to refine questions further and establish parameters of reliability and validity. It is recommended that this instrument be used with youth ages 12 to 18. There are no established norms for KAB at this time. Instructions This instrument was designed either to be administered orally or to be self-administered. Selfadministered forms can be completed either in a group setting or individually. When administering the instrument orally, the interviewer should complete the information box (below) before beginning the interview. When the instrument is self-administered either individually or in a group, the information may be completed after the interview. The youths name may be used as the You-. However, the interviewer may wish to use a neutral code such as a case number to protect the confidentiality of the interviewee. Youth should be told at the beginning of the interview that all information will be kept confidential. The interviewer should instruct youth to answer all questions completely and honestly. They should be told that it is not a test, so there are no right or wrong answers. Some questions ask for opinions or impressions. Youth should be instructed to respond exactly as they feel or think.

To be completed by the interviewer or the person administering the instrument: Program Identifier (Name or Activity) Program Location (Address or Site) Date

/

/

Youth Identifier

Sequence (Check one): 0

1st (Pretest)

Cl

2nd (Posttest)

0

3rd (Followup)

JOANNA

40

TYLER

and CAROLYN

LICHTENSTEIN

KNOWLEDGE, ATTITUDE, AND BEHAVIOR INSTRUMENT (KAB) 1. What is your grade level in school? If this is summer vacation time for you, in what grade will you be this fall? Circle one answer. 1. 6th grade 2. 7th grade 3. 8th grade 4. 9th grade 5. 1Othgrade 6. llthgrade 7. 12thgrade 8. Not cunently attending school 2. What is your sex? Circle one answer. 1. Male 2. Female

6. How many times have you moved from one home to another? Circle one answer. 1. Notimes 2. Once 3. Twice 4. Three times 5. Four or more times 7. Which of the following best describes most of your grades during the past school year? Circle one answer. 1. EorF 4. B 5. A 2. D 6. Not in school 3. c 8. During the last 30 days that you were in school, how many days of school did you miss? Circle one answer for each line.

3a. In what year were you born? 19_ _ 3b. In what month were you born? Circle one. 1. January 2. February 3. March 4. April 5. May 6. June 7. July 8. August 9. September 10. October 11. November 12. December 3c. On what day (number) of the month were you born? _ _ 4. How do you describe yourself? Circle one answer. 1. American Indian/Native American 2. Black or African-American 3. Mexican American or Chicano 4. Puerto Rican 5. Cuban 6. Other Latin American, South American, or Spanish 7. Pacific Islander such as Hawaiian, Samoan 8. Oriental or Asian American 9. White or Caucasian 10. Other racial or ethnic group Please let us know which:

a. Because you were sick b. Because you skipped or “cut” c. For other reasons

1234567 1234567 1234567

9. Have you been held back in school or had to repeat a grade level? Circle one answer. 1. No 2. Yes 10. Adults and youth do all sorts of things together. In a typical week approximately how many times do you do the following activities with an adult? Circle one answer for each line.

a. Eat dinner b. Listen to music c. Play sports d. WatchTV

5. With whom do you live? Circle one answer. 1. Two parents. May include a stepparent. 2. Only your mother 3. Only your father 4. Only adult relatives 5. A guardian 6. Others (Please tell us who: 7. Group home 6/O 1193

e. Attend church, temple, or religious or spiritual meetings f. Clean house g. Visit relatives h. Play video games i. Cook meals )

j. Discuss daily events

41

High-Risk Youth 11 When you have problems, can you talk to your mother. father. or other adult about your problems? Circle one answer. 1. Never 2. Sometimes 3. Always

14. Have you been involved with any of the following activities in the past year? Circle one answer for each line.

t

12. Where would you gofirst if you had a question about alcohol or other drugs? Circle one answer. 1. Mother. father, or both

C.

d.

2. Brothers or sisters e. f. g.

3. Uncle or aunt or older relative 4. A friend your age 5. An older friend 6. Teachers

h. i. j. k.

7. Kids who are leaders 8. Books 9. School counselors 10. Hotlines or crisis centers 11. Medical doctor or muse 12. Police 13. Minister, priest, rabbi, or other spiritual leader

1. m. n.

13. How often do you do each of the following? Circle one answer for each line.

0.

t. a. Watch TV

b. Go out with your girlfriend or boyfriend C. Play video games d. Attend afterschool activities, drama, school clubs e. Play sports, coach sports f. Work for pay g. Attend school dances h. Do volunteer work i. Attend religious meetings or spiritual activities j. Go to the movies k. Read books, magazines, and newspapers I. Go to parties m. Ride around in a car for fun n. Hang out with friends

1 1

2 2

3 3

4 4

5 5

1 1

2 2

3 3

4 4

5 5

1 1 1 1 1

2 2 2 2 2

3 3 3 3 3

4 4 4 4 4

5 5 5 5 5

1 1

2 2

3 3

4 4

5 5

1 1

2 2

3 3

4 4

5 5

1

2

3

4

5

U. V.

w.

Drug education classes TV or magazine drug-f= messages Stress management or wellncss c1assc.s Sports. fitness, or martial arts programs Wilderness programs and camping craft programs Community service projects. health fairs, celebrations. environment improvement projects Individual counseling Group counseling Summer school Self-help groups or support groups such as ALATEEN. ALANON. or Narcotics Anonymous Job training programs Health education classes Reading brochures, pamphlets or seeing videos on alcohol and other drugs Social events such as dances and parties Cultural events or heritage awanncss activities Afterschool programs or extended day-school programs Family counseling Crisis counseling or hotline counseling Youth leadership training Tutoring others Involvement with a caseworker Pnscntations by community or police programs or leaders such as Officer Friendly or DARE

8 1 1 1

8 2 2 2

1

2 2 2 2

2 2 2 2

2 2 2 1

2

1

2

1

2

1 1

2 2 2 2 2 2

15. How important is religion in your life? Circle one answer. 1. Not important 2. A little important 3. velyimpoltant

3

6/01/93

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JOANNA TYLER and CAROLYN

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18. Here are some questions that ask about how sure you are that you would be able to do certain things. Circle one answer for each line.

16. To what extent do you agne with the following statements? Circle the answer that tells how you feel about yourself. Circle one answer for each line.

a. I could go up to someone my age and start talking to that person. b. If a friend wants me to do something that I don’t want to do, I could tell my friend that I don’t want to do it. C. If a friend wanted to give me alcohol, I could say no. d. If a friend wanted to give me marijuana, I could tell my friend that I didn’t want any. e. If friends did something that I didn’t like, I could ask them to change what they were doing. f. If some of my friends are playing a game, I could ask them if I could join. g- If a friend wanted to give me some cocaine or crack, I could say no.

a. I take a positive attitude toward myself. b. Life often seems meaningless. c. People should do their own thiig. even if other people think it is strange. d. I feel I do not have much to bc proud of. e. IfeelIamapersonofworth and equal to others. f. I get a teal kick out of doing things that are a little dangerous. g. Sometimes I think that I am no good at all. h. I am able to do things as well as most other people. i. The future often seems hopeless. j. I like to test myself every now and then by doing something a little risky. k. I feel that I can’t do anything right, 1. I feel that my life is not very useful.

2

3

4

2

3

4

2

3

4

2

3

4

2

3

4

2

3

4

2

3

4

19. People use alcohol and other drugs for different masons. Do you think it is okay to drink alcohol or use other drugs for the following reasons? Circle one answer for each line .

17. Circle the answer that describes how you think. Circle one answer for each line.

a. “Downers” can be taken safely with alcohol. b. Drinking coffee after drinking alcohol is a good way to sober up. c. Babies of mothers who are cocaine or heroin addicts am likely to be born addicted. d. Heavy alcohol use hurts the family. e. Heavy drinking over a long period of time kills brain cells. f. Smoking marijuana can hurt a person’s ability to drive a car. g. Pregnant women who have two drinks a day may harm their unborn babies.

6101193

2”

$

Q2

1

2

3

1

2

3

1

2

3

1 1

2 2

3 3

1

2

3

1

2

3

$

s 9 2 a. b. c. d.

To see what it is like To relax or feel less tense To feel good or get high To seek deeper insights or understandings e. To have a good time f. To fit in with a group g. To get away from my problems h. To relieve boredom or nothing to do i. To nlease anger or frustration j. To be more creative k. To do better in sports 1. To look better m. To get to sleep n. To lose weight 4

1 1 1 1

2 2 2 2

3 3 3 3

1 1 1 1

2 2 2 2

3 3 3 3

1 1 1 1 1 1

2 2 2 2 2 2

3 3 3 3 3 3

High-Risk Youth 22. Have you ever smoked cigarettes7 Circle one answer. 1. Never 2. Once or twice 3. Now and then but not everyday 4. Everyday in the past, but quit 5. Everyday now

20. During the past 30 days, how many of your friends did the following things? Circle one answer for each line.

a. Smoked cigarettes b. Usedalcohol orotherdrugs C. Hit teachers or work supervisors d. Gotintoseriousfightsat school or at work e. Stole from otherpeople f. Took something from aston without paying for it g. Damagedschoolpropetty on purpose h. Argued with their parentsor hit their parents 1. Tookpartinafightwhete a group of your friends were against another group j. Set fue to someone’s property on purpose k. Got into trouble with police because of something they did 1. Used snappers, or inhaled gas, glue, or cleaners

12 1 2 12

34 3 4 34

1

2

3

4

5

1 1

2 2

3 3

4 4

5 5

1

2

3

4

5

1

2

3

4

5

1

2

3

4

5

12

34

5

12

34

5

1

2

3

4

43

23. During the past 30 days, how many cigarettes did you smoke? Circle one answer. 1. None 2. 1 cigarette per day but not everyday 3. l-5 cigatettes per day, but not everyday 4. 1-5 cigarettes per day 5. 5-20 cigarettes per day 6. About one pack or mote per day 24. Do you plan to smoke cigarettes in the future? Circle one answer. 1. No 2. Not sure 3. Yes

25. In the past, how many times, if any, did you use smokeless tobacco, snuff, chew, or dip? Circle one answer for each line.

5

21. During the past 30 days, have you done any of the following things that may be against the rules or against the law? Circle one answer for each line.

a. Hit a teacher or supervisor b. Got into a fight at school or work C. Took something not belonging to you from a person Took something from a store without paying for it Damaged school property on purpose Argued or had a fight with either of your parents Took part in a fight where a group of your friends wen against another group h. Went into a house or building when you were not supposed to be there 1. Set fire to someone’s property on purpose j. Got into trouble with police because of something you did

a. During the past 30 days b. During the past 12 months c. In your lifetime I

2

1

2

1

2

1

2

1

2

1

2

1

2

1234567 1234567 1234567

26. Do you plan to use smokeless tobacco, snuff, dip, or chew in the future? Circle one answer. 1. No 2. Not sure 3. Yes

5

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JOANNA TYLER and CAROLYN LICHTENSTEIN

27. How many times, if any, have you drunk any alcohol such as beer, wine, or hard liquor7 Circle one answer for each line.

a. During the past 30 days b. During the past 12 months c. In your lifetime

31. How many times, if any, have you used cocaine, sometimes called crack, coke, rock, snow, sugar, toot. or white? Circle one answer for each line.

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a Duringthepast 30 days b. Duringthe past 12 months c. In your lifetime

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28. Do you plan to drink alcohol in the future? Circle one answer. 1. No 2. Not sure 3. Yes

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32. How many times, if any, have you used hallucinogens such as LSD, mescaline, angel dust, acid, windowpane, cubes, shrooms, mushrooms, or PCP? Circle one answer for each

29. Think back over the past 30 days. How many times have you had five or more drinks “in a day?” A ‘drink” is a glass of wine, a bottle or can of beer, a shot glass of liquor, or a mixed drink. Circle one answer. 1. None 2. l-2 times 3. 3-5 times 4. 6-9 times 5. 10 or more times

a. During the past 30 days b. During the past 12 months c. In your lifetime

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30. How many times, if any, have you used marijuana, which is sometimes called smoke, joint, tea, weed, sezz, sen, reefer, pot. or grass? Circle one answer for each line. 33. How many times, if any, have you used “downers” or barbiturates such as sleeping pills, yellows, teds, red devils, ludes, yellow jackets, or Quaaludes? Circle one answer for each line.

a. Duringthepast 30 days b. During the past 12 months c. In your lifetime

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High-Risk Youth

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37.When. if ever, did you first try each of the following drugs? Circle one answer for each line.

34. How many times, if any, have you used “uppers” such as black beauties, crank, speed, meth, crystal, pep pills, or bennies? Circle one answer for each line

a. Smoked cigarettes on a

a. During the past 30 days b. During the past 12 months c. In your lifetime

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b. c. d. e.

35. How many times, if any, have you used medicines or tranquilizers such as Valium or Librium or pain medicines such as codeine, Dilaudid, or Percodan? Circle one answer for each line.

f. g. h. i. j.

a. During the past 30 days b. During the past 12 months c. In your lifetime

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k. E?IItour fust cigatette 1. Drankenoughtofeeldrunk or very high

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c. In your lifetime

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38. Do you plan to use drugs in the future? Circle one answer. 1. No 2. Not sure 3. Yes

36. How many times, if any, have you inhaled or sniffed poppers, snappers, Amys, gas, glue. sprays, locker room, whiteout, push, cleaning fluids, or paints? Circle one answer for each line.

a. During the past 30 days b. fi”Eo”,z past

regular basis Tried an alcoholic beverage for mote than just a few sips Tried marijuana or hashish Tried LSD or mescaline Tried uppers, speed, pep pills, meth, etc. Tried downers, yellow, h&s. barbs, etc. Tried painkillers Tried cocaine or crack Tried snappers, poppers, or other things you inhale to get high Tried smokeless tobacco,

THE END Thank you for helping us with our survey.

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