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Facilitating youth self-change through school-based intervention
Addictive Behaviors 30 (2005) 1797 – 1810
Facilitating youth self-change through school-based intervention Sandra A. Brown a,T, Kristen G. Anderson b, Marya T. Schulte c, Nicole D. Sintov b, Kevin C. Frissell c a
Department of Psychiatry and Psychology, University of California, San Diego, Veterans Affairs San Diego Healthcare System, McGill Hall, 9500 Gilman Drive, MC 0109, La Jolla, CA 92093-0109, United States b Department of Psychology, University of California, San Diego, CA, USA c Joint Doctoral Program of Clinical Psychology, San Diego State University/University of California, San Diego, CA, USA
Abstract Early interventions for youth with high rates of alcohol use have often suffered from lack of willing participation due to negative stereotypes about treatment and the impression that alcohol interventions are not developmentally relevant for adolescents. This study evaluated the effectiveness of a schoolbased voluntary secondary intervention for alcohol use (Project Options). 1254 high school students (55% girls; M age = 15.9, SD = 1.2) with a history of lifetime drinking completed survey measures after the first year of Project Options in 3 schools. These results suggest that the intervention was successful in recruiting high-frequency drinkers into the intervention as well as facilitating attempts to cut down or quit alcohol use in this group of adolescents. This study provides preliminary support for a consumer-based approach to alcohol intervention and design and use of voluntary secondary interventions in a school-based population. D 2005 Elsevier Ltd. All rights reserved. Keywords: Adolescent alcohol problems; Alcohol quit attempts; School-based intervention
T Corresponding author. E-mail address: [email protected] (S.A. Brown). 0306-4603/$ - see front matter D 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.addbeh.2005.07.003
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1. Changing adolescent alcohol use: facilitation of change attempts through intervention Alcohol use among America’s youth remains prevalent and problematic, with one quarter to one-third of high school students consuming alcohol at harmful rates (i.e., 5 or more drinks in the prior two weeks; Johnston, O’Malley, & Bachman, 2003). Youth experience both immediate and long-term consequences of early alcohol involvement. Problematic use is associated with decreased academic performance, higher rates of accidents and injuries, interpersonal problems, risky sexual behavior, tobacco and other substance use, and a variety of mental health disorders (Hussong & Chassin, 1994; Lewinsohn, Hops, Roberts, & Seeley, 1993). While youth who experiment with alcohol may exhibit few problems, more frequent and higher dose consumption escalates problem rates and risk for early dependence (Brown & Tapert, 2004; O’Malley, Bachman, Johnston, & Schulenberg, 2004). Because of the spectrum of negative consequences, youth with repeated alcohol experience are a compelling target for early alcohol interventions. Unhealthy habits affecting both physical well being (Friedman, 1993; Jessor, 1984) and coping strategies (Kazdin, 1993; Compas, 1993) in adulthood begin during adolescence. Thus, making changes during adolescence may have both short- and long-term benefits. Among youth evidencing alcohol problems, traditional treatment approaches appear to have limited appeal (Brown, 1993; Brown, 2001; D’Amico, McCarthy, Metrik, & Brown, 2004) because of the associated negative stereotypes (Ackard & NeumarkSztainer, 2001) and perceptions that such treatments are developmentally unsuitable and unhelpful with regards to adolescent needs (Kelly, Myers, & Brown, 2000; Wagner, Brown, Monti, Myers, & Waldron, 1999). Few interventions are readily available to youth who drink alcohol prior to emergence of more severe external problems that often trigger formal treatment (Brown, 2001). A limited number of school-based youth-targeted alcohol treatments have proven efficacious (Hser et al., 2001; Pentz, 1998). Similarly, programs centered on teaching teens about the effects and consequences of substance use and whose main objective is total abstinence also lack support in the reduction of use among adolescents. Such programs fail to feature the salient concerns of youth that may motivate their engagement in intervention efforts (Brown, 2001) and may actively prompt resistance to the intervention (Brown, 1993; Marlatt & Witkiewitz, 2002). The limited success of traditional interventions to delay initiation and reduce continuation of alcohol use among youth demonstrates the need for interventions that fit the developmentally specific needs and interests of youth at greatest risk for developing alcohol dependence. While only a small proportion of adolescents experiencing problems related to alcohol use actually participate in formal treatment, 15–20% adolescent drinkers reduce or stop drinking without formal intervention (e.g., Brown, 2001; Fillmore, 1988; Sobell, Ellingstad, & Sobell, 2000; Stice, Myers, & Brown, 1998) and maintain changes over a 1-year time period (Brown, 2001; Sobell, Cunningham, & Sobell, 1996; Wagner et al., 1999). Given that many youth make changes in their alcohol involvement without professional intervention and a small proportion of heavy drinking youth participate in
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formal treatment, interventions that focus on facilitating change efforts youth commonly utilize may be particularly useful in reducing adolescent alcohol use and altering typical progressions of alcohol involvement. Some reductions in adolescent alcohol involvement may be incidental to environmental or role transitions experienced during this developmental period (Brown, 2001; Watson & Sher, 1998). The socialization process and preparation necessary for many of these natural transitions (e.g., academic, sports, work, parenting) become factors in access to alcohol and decisions regarding frequency and quantity of consumption (Yamaguchi & Kandel, 1985). In contrast to this incidental change, cognitive social learning theory (Bandura, 1986) informs substance use interventions which facilitate purposeful change attempts for adolescents. Cognitive social learning theory, as it is applied to the reduction of adolescent substance use (Smart & Stoduto, 1997), postulates that alcohol cessation and reduction result from cognitive appraisal (e.g., perceived norms) and evaluation processes (e.g., cessation expectancies; Klingemann, 1991; Metrik, McCarthy, Frissell, MacPherson, & Brown, 2004; Tucker, Vuchinich, & Gladsjo, 1991). More specifically, we have proposed a developmental social information processing model (e.g., Brown, 2001; Metrik et al., 2004) which posits that cognitive and emotional states influence youth drinking behavior (e.g., whether or not to drink) within a social context by incorporating distal factors (e.g., biological risk and cultural experiences) with more proximal circumstances (e.g., alcohol availability and motivational state). Motivation has proven to be a key component in understanding adolescent self-change efforts as well as the failure of many current interventions (Myers, Brown, & Kelly, 2000; Peltier, Telch, & Coates, 1982). Because youth are less likely to have experienced the severe negative consequences of drinking (Nurmi, 1997) and more likely to view the heavy levels of use observed in their environment and the media as normal, their motivation to reduce or quit their drinking may be lower, qualitatively different from that of adults and requires intervention focused on enhancing the desire for change. Thus, youth purposeful change efforts in substance use may require a perceived need for change, either from external or personal factors, and may be facilitated by interventions which normalize (verify social models of) change efforts of peers. Using this developmental social information processing approach, early interventions to facilitate adolescent self-change efforts for alcohol and drug use problems may benefit from attending to these natural role and environmental changes, fluctuations in level and focus of motivation, and the influence of perceived drinking norms. Furthermore, our social cognition model hypothesizes that youth self-change occurs in two phase: 1.) quit/reduction attempts and 2.) subsequent maintenance efforts (Brown, 2001). Although research from the smoking cessation literature indicates that attempts to cut down or quit smoking are critical to the long-term process of smoking cessation, there is a dearth of knowledge about adolescent quit attempts for alcohol and how motivation and perceived norms lead from quit attempts to maintenance skills required for youth to sustain alcohol-related behavioral changes. The current study examines alcohol change efforts in a school-based high school alcohol intervention (Project Options) designed to reduce adolescent alcohol involvement
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through the facilitation of personal change attempts. The intervention incorporates motivational enhancement techniques (e.g., Miller & Rollnick, 2002), normative feedback, and skills training within a developmentally sensitive framework in order to target adolescent drinkers experiencing common developmental transitions (e.g., increased independence, autonomy, acquisition of adult responsibilities) and varying in level of motivation to change (Table 1). It was hypothesized that, compared to students with extensive alcohol experience who did not receive the intervention, similar heavydrinking students participating in the intervention would attempt to reduce or stop their alcohol involvement at greater rates. The intervention was predicted to have the greatest impact on youth with the most alcohol use experience and alcohol-related problems such that these youth would evidence the highest rates of attempts to cut down or quit alcohol in comparison to youth with limited and moderate lifetime alcohol use experience. Table 1 Project Options: intervention session content Session
Title
Content
1
Normative feedback (Miller & Rollnick, 2002)
2
Outcome expectancies (Darkes & Goldman, 1998)
3
Coping (Monti & Rosenhow, 1999)
4
Alternative activities (Marlatt & Witkiewitz, 2002)
5
Behavioral management (Wagner, Myers, & Brown, 1994)
6
Communication (Wagner et al., 1994)
–Estimates of perceived peer use –Graphs depicting actual peer use –Discussion of how students cease or reduce substance use –Education about alcohol and the actual effects of alcohol –Discuss people engaging in disinhibited and dangerous behaviors when using –Alcohol effect expectancies discussed –Coping with common adolescent stress and conflict without using substances –Elicit feedback regarding common stressors among students –Discussion of alternative ways of coping with stress –Discussion about how experimental use can lead to problem use –Elicit feedback about use and alternatives –Problems that can be avoided and benefits that can be gained from change efforts –Discussion of situations where alcohol or drugs may be present –Develop strategies for abstinence –Elicit feedback regarding how to anticipate, plan and prepare, and evaluate effectiveness of plans –Discussion of alternatives to use and maintaining personal goals –Substance resistance/refusal skills training –Communication breakdowns that may exacerbate alcohol use –Communication role plays –Common communication mistakes of teens and parents and teens and peers
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2. Method 2.1. Participants In the current study, students in 9th through 12th grades at three high schools in San Diego County had the opportunity to voluntarily participate in an alcohol intervention (Project Options). Project Options was developed to be appealing to youth (e.g., focus on socially valued content), minimize barriers related to participation (e.g., convenient times and location), to provide a range of participation format choices (e.g., participate independently or with others) and reflect service preferences of teens (Brown, 2001). The student population at the same three high schools (school-wide surveys; N = 2554) was surveyed in the spring of the initial year of Project Options at each site. Youth with a history of at least one standard alcohol drink were selected for analyses. Of the 60% of students reporting lifetime alcohol use, 11% were omitted due to inconsistent responding or missing data on one or more variables under study. The final sample included 1249 youth. Comparison of youth who were selected for these analyses versus those excluded suggests included and excluded youth were not significantly different of either sex or school placement (i.e., Schools 1, 2, or 3). As expected, youth with alcohol experience were significantly older, t(2541) = 5.63, p = .001, more likely to be in 11th or 12th grade, v 2 = 63.30, df = 7, p b .0001, and Caucasian, v 2 = 38.80, df = 5, p b .0001. For confidentiality purposes, no personally identifying information was collected from students at the school-wide surveys. The final sample was comprised of youth with limited lifetime experience with alcohol (V 10 lifetime drinking episodes: 48%), 24% with moderate lifetime experience with alcohol (11–50 lifetime episodes), and 28% with high lifetime experience (51+ lifetime alcohol use episodes). A comparison of the demographic and alcohol use characteristics for the three alcohol use groups (limited experience, moderate experience, and high experience) is presented in Table 2. Use groups were significantly different on the basis of age, F[2, 1236] = 36.30, p b .0001, grade, v 2 = 91.47, df = 6, p b .0001, and ethnicity, v 2 = 16.92, df = 4, p b .01, and recent alcohol use variables (max drinks/episode: F[2, 1216] = 255.64, p b .0001; average drinks/episode: F[2, 1224] = 260.76, p b .0001; binge (5 + drinks) episodes: F[2, 1209] = 132.96, p b .0001). Youth in the high experience group were more likely to be older, be in the 11th or 12th grade, and use alcohol at higher rates for the past 30-day period (maximum drinks, average drinks and binge drinking episodes). Youth in the limited experience group were more likely to identify themselves as bMultiracial/otherQ. 2.2. Procedures Using procedures approved by the University of California, San Diego Committee for the Protection of Human Subjects, the school district, and the individual high schools, data for the current study were collected as part of larger study of adolescent substance use behavior (e.g., Brown, 2001; Metrik et al., 2004) and included parent permission for student voluntary participation in the intervention and annual surveys (see Frissell et al., 2005 for survey details).
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Table 2 Demographic and past 30-day alcohol use characteristics of high school students with lifetime alcohol experience (N = 1249)
Background variables AgeT Sex Boys (%) Girls (%) GradeT 9 (%) 10 (%) 11 (%) 12 (%) EthnicityT Caucasian (%) Mixed/other (%) Latina/o (%) Alcohol use (30 day) Max drinks/episodeT Average drinks/episodeT Binge episodesT (5+ drinks)
Limited (1–10 episodes) alcohol use (48%)
Moderate (11–50 episodes) alcohol use (24%)
High (50+ episodes) alcohol use (28%)
15.7 (1.2)
16.0 (1.2)
16.3 (1.2)
41.1 58.9
45.6 54.4
49.0 51.0
37.9 26.8 22.6 12.7
22.8 26.6 29.4 21.2
13.7 24.8 31.2 30.3
54.3 40.0 5.7
65.9 29.7 4.4
65.6 30.0 4.4
1.8 (3.0) 1.7 (2.4) 1.0 (3.5)
4.3 (4.0) 3.7 (3.2) 2.2 (4.4)
7.7 (4.8) 6.6 (4.1) 6.2 (6.5)
T p b .0001.
2.2.1. Intervention The Project Options intervention was initially implemented during the 1999–2000 school year at School 1 and the 2000–2001 school year at Schools 2 and 3. Upon implementation at each school, the opportunity to voluntarily participate in the intervention was available to all students regardless of substance use history. To address diverse adolescent preferences for intervention delivery (Brown, 2001; D’Amico et al., 2004), the intervention was offered in three formats: group, individual, and website. The three intervention formats were jointly advertised and simultaneously offered (e.g., during lunch period) and consisted of a maximum of six 30-min group sessions, four 30-min individual sessions, and unlimited website access. All Project Options formats were offered once per week at each school during lunchtime in convenient classrooms and the website was also accessible 24 h a day from either school or off site locations. Youth choosing any format received a lunch during their noontime participation and $5 incentive (gift certificates for clothing, movies, music, or restaurants) at the end of their first session following the completion of a brief questionnaire assessing background characteristics and alcohol use. Based on the developmental social information processing model (Brown, 2001), the Project Options intervention focused on increasing motivation to change alcohol use (e.g., reduction and cessation) and related risk behaviors, generating resources for alternative behaviors, and teaching behavioral skills to increase the likelihood of successful personal change efforts. The content of Project Options was similar across formats and included topics
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addressing normative feedback on peer use and change attempts, alcohol outcome expectancy challenges, coping skills, recognizing personal need to change, behavioral management strategies, and effective communication. Students were able to select any of the 6 topic sessions advertised (Table 1). The style of interactive activities for students as well as motivational and marketing elements (i.e., style of advertising) was based on student pilot focus groups from demographically similar schools and preintervention surveys. 2.2.2. School-wide survey All data examined for the current study comes from the school-wide surveys in the second semester after Project Options was implemented at each school. Respondents included 810 School 1 students, 1168 School 2 students and 576 students at School 3. One month prior to each school-wide survey, parent information and consent packets were mailed to student homes. Each packet included parent consent forms for the intervention and survey, a letter from the principal and informational sheets (bCommon QuestionsQ). Additionally, one week prior to the survey date, each student was given a consent form and common questions sheet to hand-carry home to his/her parent to help ensure parents were informed of the study and to give an additional opportunity for parents to ask questions and to respond to the consent request. Trained proctors administered surveys in each classroom when normal absentee rates were expected (e.g., 5%) during a specified time determined by the school (e.g., homeroom and first-period class). Student assent was also obtained at the time of the survey through written informed assent forms. 2.3. Measures Outcome data consist of responses to the second semester school-wide surveys described above. Surveys assessed an array of background characteristics, alcohol and other substance use and problems, and related risk behaviors. 2.3.1. Personal characteristics Background variables included gender, grade (9th–12th), ethnicity, and age. Ethnicity was reported from a list of choices: American Indian/Alaska Native, Asian American, Black/ African American (non-Hispanic), Hispanic or Latino/Latina, Native Hawaiian/Pacific Islander, White (Caucasian/non-Hispanic), or Other/Multiracial. Intervention attendance was determined by students indicating whether or not they had attended one or more Project Options meeting (group or individual) or used the Project Options website during the academic year (yes/no). 2.3.2. Alcohol involvement Students reported past month average number of drinks consumed per drinking occasion (range = 0 to 15 drinks), frequency of binge drinking (defined as five or more drinks per occasion; range = 0 to 15 times), and largest number of drinks consumed on a drinking occasion (range = 0 to 15 drinks). One standard drink was defined as one can/bottle of beer or wine cooler, one glass of wine, or one shot glass of liquor. Using items from well-established
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measures such as Monitoring the Future survey (Johnston et al., 2003) and the Youth Risk Behavior Survey (CDC, 1990), students also reported lifetime use (range = never, 1–10 times, 11–50 times, and 51+ times) of alcohol. 2.3.3. Outcome variables Students responded yes or no to whether they had made a personal attempt to cut down their alcohol use (Have tried to cut down alcohol in the past year?) and, on a second question, whether they had attempted to quit drinking in the past year (Have you tried to quit drinking alcohol in the past year?). 2.4. Analyses Students were first separated into three groups on the basis of their self-reported lifetime use episodes for alcohol: the limited experience group (n = 603) used alcohol on 1–10 occasions during their lifetime; the moderate experience group (n = 297) used alcohol on 11– 50 occasions during their lifetime; the high experience group (n = 348) used alcohol on 51 or more occasions during their lifetime. Youth were further classified into intervention group (participated in Project Options during the school year) and no intervention group (no participation in Project Options). Logistic regressions were used to investigate the impact of Project Options (no intervention versus intervention) on student attempts to cut down (yes/no) or quit (yes/no) alcohol in the past year. In addition, subsample analyses were conducted on smaller cohort of matched youth (n = 276) to address issues related to demographic differences found between groups. Conditional logistic regression, matching individuals in the no intervention and intervention groups on age, sex, grade and ethnicity, was also performed separately for each use group.
3. Results 3.1. Intervention participation First, we examined demographic and use pattern differences between youth with lifetime use of alcohol who self-selected into Project Options and No Intervention students. Approximately 18% of students with lifetime alcohol experience (N = 223) reported voluntarily attending Project Options intervention during the first year of implementation. Project Options youth and No Intervention students were similar in age (M = 16.0 and 15.9 years, respectively) and grade. 22.8% of intervention participants reported being in the 9th grade, 31.3% in 10th grade, 28.1% in 11th grade, and 17.9% in 12th grade. Similarly, 28.6% of No Intervention students were in the 9th grade, 24.9% in 10th grade, 26.7% in 11th grade, and 19.8% in 12th grade. Half of the Project Options group (51.1%) were Caucasian, 7.8% were Hispanic–American, 2.4% African–American, 1.7% Asian American, 6.7% Native American, and 30.0% identified themselves as bMultiracial/OtherQ. Among other students, 62.1% were Caucasian, 4.9% were Hispanic–American, 6.1% African–American, 0.7%
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Asian–American, 1.6% Native American, and 24.9% identified themselves as bMixed/OtherQ. Of the intervention participants, 54.5% were male whereas 42.4% of No Intervention students were male (v 2 = 10.88, df = 1, p b .001). Project Options youth were more likely to be nonwhite, v 2 = 34.06, df = 5, p b .0001, and have greater alcohol use in the prior 30 days (binge episodes: t (1219) = 2.20, p b .05; maximum drinks/episode: t (1227) = 2.09, p b .05) than No Intervention students. 3.2. Personal change efforts The prevalence rate for personal attempts to cut down alcohol use in the entire high school sample was 21.0% and 17.0% of the students attempted to quit using alcohol in the past year. Approximately 21.6% of Project Options youth attempted to cut down their drinking in the past year compared to 20.6% of No Intervention youth. For quit attempts, 19.6% of Project Options youth compared to 16.5% of No Intervention youth attempted to stop drinking in the past year. Table 3 provides the results of the logistic regressions for the three alcohol use groups separately for attempts to cut down or quit alcohol use. As can be seen, Project Options was effective in fostering attempts to cut down and stop alcohol use for youth with the highest lifetime experience with alcohol use. Fig. 1 displays the proportion of cut down attempts for intervention and no intervention samples in relation to lifetime exposure to alcohol. Examination of the odds ratios across alcohol use groups indicates that youth in the high alcohol use group were 1.84 times ( p b .05) more likely to attempt to cut down their alcohol use in the last year compared to 0.69 (ns) for the infrequent experience and 0.78 (ns) in the moderate experience group. Conditional logistic regression was used to examine the impact of Project Options on attempts to cut down on drinking using groups matched on the basis of grade, sex, school and ethnicity (n = 276) separately for each use group. In the high alcohol experience group, it was found that the odds of cutting down on alcohol use was 2.42 times (95% CI = 1.18–4.95) greater for youth in Project Options compared to No Intervention youth, log likelihood = 122.23, v 2 = 5.88, df = 1, p b .05. Conditional logistic regressions for attempts to cut down alcohol use were not significant for the infrequent and moderate experience groups.
Table 3 Logistic regressions predicting youth attempts to cut down and stop alcohol use from Project Options participation: comparison across alcohol use levels Lifetime exposure level DV: attempts to cut down alcohol use Limited experience Moderate experience High experience DV: attempts to stop alcohol use Limited experience Moderate experience High experience
Log likelihood
OR
95% CI
p-value
233.50 176.01 201.77
0.69 0.78 1.84
0.35–1.34 0.38–1.63 1.05–3.21
.27 .52 .03
246.44 143.76 122.23
0.85 1.09 2.42
0.46–1.56 0.49–2.42 1.18–4.95
.60 .83 .05
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40
Percent with Cut Down Attempts
No Intervention Project Options
30
* 20
10
0 Limited
Moderate
Frequent
Lifetime Use Group Fig. 1. Proportion of cut down attempts for alcohol among Project Options and No Intervention youth: lifetime use groups. *p b .05.
40
Percent with Quit Attempts
No Intervention Project Options
30
* 20
10
0 Limited
Moderate
Frequent
Lifetime Use Group Fig. 2. Proportion of quit attempts for alcohol among Project Options and No Intervention youth: lifetime use groups. *p b .05.
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The proportion of quit attempts in relation to lifetime use status is presented in Fig. 1. For attempts to stop alcohol use, individuals in the high alcohol use group were again more likely to attempt to stop alcohol use in the past year if they attended Project Options (Fig. 2). Odds ratios suggested that youth in the high experience group were 1.85 times ( p b .05) more likely to attempt to stop using alcohol compared to youth in the limited experience (OR = 0.85, ns) or moderate experience (OR = 1.09, ns) groups. Conditional logistic regressions were also conducted for youth attempts to quit alcohol use in the past year based on the same matching criteria listed above. In none of the groups were significant findings found for conditional analyses.
4. Discussion This investigation constitutes a preliminary test of the effectiveness of the Project Options intervention in engaging youth and facilitating attempts to cut down or quit alcohol use among teens who have a history of alcohol use. In this sample of high school students who drink, 18% of drinkers voluntarily self-selected into the school-based intervention. Youth who participated in the intervention had greater drinking rates in the past 30 days (maximum drinks per occasion and binge drink episodes) than youth who did not participate in the intervention. Further, males and non-Whites, both groups likely to experience alcohol-related problems, were voluntarily recruited into Project Options. As past research suggests that the lack of teen involvement in intervention is function of negative beliefs about treatment effectiveness and a lack of focus on the needs of adolescents (Ackard & Neumark-Sztainer, 2001; Kelly et al., 2000), the higher rates of alcohol involvement for youth who self-select into Project Options provide preliminary support for the developmentally sensitive design of this intervention, both in recruitment and intervention. The intervention appears to be most likely to promote personal efforts to stop or cut down alcohol use among youth at greatest risk for progression to an alcohol use disorder. Youth who had the highest exposure to drinking seemed to benefit most from the intervention; participation in Project Options increased their odds of cutting down drinking over 1 3/4 times compared to youth who did not self-select into the intervention and increased the likelihood of quit attempts by almost 2 1/2 times. By contrast, participation did not significantly influence youth attempts to cut down or quit drinking for the limited or moderate experience drinkers. Students with the most experience with drinking were more likely to be older, be in the later grades, and had used alcohol in greater quantities during the last month. These findings are consistent with what might be expected for individuals with greater lifetime drinking experience, supporting the use of these distinctions in preliminarily evaluating the effectiveness of Project Options in facilitating youth attempts to cut down or stop alcohol use. While intervention was most effective for high school students with the greatest alcohol use, their exposure to youth with limited and moderate alcohol use histories either in person or though normative feedback is hypothesized to be an important aspect of this intervention. The ability for the highest
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risk youth to be exposed to change information and alternative alcohol use models is an important aspect of intervention, both in modeling alternative alcohol-related behaviors (cessation or reduced use) and providing more appropriate information regarding normative peer use. The rate at which youth attempted to cut down or quit alcohol use in this sample, about 20%, is consistent with rates evidenced in the literature on alcohol change efforts in adolescents (e.g., Stice et al., 1998; Wagner et al., 1999). However, these rates are substantially lower than youth attempts to cut down or quit smoking. More than half of adolescent smokers report intentions to quit smoking and a majority of youth smokers report prior cessation attempts (Burt & Peterson, 1998; Ershler, Leventhal, Fleming, & Glynn, 1989; Stanton, Lowe, & Gillespie, 1996; Sussman, Dent, Severson, Burton, & Flay, 1998). This difference between alcohol cessation attempts and smoking quit attempts might be a function of youth perceptions of risks associated with smoking versus alcohol use (e.g., social acceptability of use and perceived anticipated consequences of cessation) or biological processes of development (e.g., appetitive drives) or pharmacological drug effects. However, future investigations are needed to understand factors influencing youth quit attempts across substances. While this investigation provides preliminary support for the developmentally sensitive design of the Project Options self-selection paradigm in attracting and influencing attempts to cut down or quit drinking for youth with the greatest frequency of use, some caveats should be considered. First, this study does not address the issue of whether selection factors in place prior to participation influenced outcomes for youth. Youth entering Project Options might have been more motivated to change, have more alcohol-related problems, or a greater history of quit attempts than youth who chose not to participate. However, Project Options youth with less experience with alcohol did not report greater rates of attempts to cut down or quit; only targeted youth for whom the intervention was designed exhibited significantly more selfchange efforts. In addition, the assessment time point included reports of participation in Project Options throughout the school year. Attempts to cut down/quit may be most prevalent during intervention participation or shortly thereafter; the end-of-year assessment may mask the temporal patterns of these outcomes. To our knowledge, this is the first voluntary secondary intervention for alcohol-using youth that has demonstrated the ability to engage this underserved group of youth and promote personal change efforts. Future investigations to examine how proximal outcomes (i.e., change efforts) relate to longer term alcohol use outcomes and the generalizability of this developmental paradigm for early intervention in schools will be the next step in validating the Project Options approach.
Acknowledgements We would like to thank the programs, staff, and participants in this study. This research supported by National Institute on Alcohol Abuse and Alcoholism grants AA12171 (S. Brown).
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Lewinsohn, P. M., Hops, H., Roberts, E., & Seeley, J. R. (1993). Adolescent psychopathology: Prevalence and incidence of depression and other DSM-III-R disorders in high school students. Journal of Abnormal Psychology, 102, 133 – 144. Marlatt, G. A., & Witkiewitz, K. (2002). Harm reduction approaches to alcohol use: Health promotion, prevention, and treatment. Addictive Behaviors, 27, 867 – 886. Metrik, J., McCarthy, D. M., Frissell, K. C., MacPherson, L., & Brown, S. A. (2004). Adolescent alcohol reduction and cessation expectancies. Journal of Studies on Alcohol, 65(2), 217 – 226. Miller, W. R., & Rollnick, S. (2002). Motivational Interviewing: Preparing people to change (2nd Edition). New York7 The Guilford Press. Monti, P. M., & Rosenhow, D. J. (1999). Coping-skills training and cue-exposure therapy in the treatment of alcoholism. Alcohol Research and Health, 23(2), 107 – 115. Myers, M. G., Brown, S. A., & Kelly, J. F. (2000). A cigarette smoking intervention for substance abusing adolescents. Journal of Cognitive and Behavioral Practice, 7, 64 – 82. Nurmi, J. E. (1997). Self-definition and mental health during adolescence and young adulthood. In J. Schulenberg, J. L. Maggs, & K. Hurrelmann (Eds.), Health risks and developmental transitions during adolescence (pp. 395 – 419). New York7 Cambridge University Press. O’Malley, P. M., Bachman, J. G., Johnston, L. D., & Schulenberg, J. (2004). Studying the transition from youth to adulthood: Impacts on substance use and abuse. In J. S. House, F. T. Juster, R. L. Kahn, H. Schuman, & E. Singer (Eds.), A telescope on society: Survey research and social science at the University of Michigan and beyond (pp. 305 – 329). Ann Arbor, MI7 The University of Michigan Press. Peltier, B., Telch, M. J., & Coates, T. J. (1982). Smoking cessation with adolescents: A comparison of recruitment strategies. Addictive Behaviors, 7, 71 – 73. Pentz, M. A. (1998). Costs, benefits, and cost-effectiveness of comprehensive drug abuse prevention. In W. J. Bukoski, & R. I. Evans (Eds.), Cost–benefit/cost effectiveness research of drug abuse prevention: Implications for programming and policy. Rockville, MD7 National Institute of Drug Abuse. Research Monograph 176. Smart, R. G., & Stoduto, G. (1997). Treatment experiences and need for treatment among students with serious alcohol and drug problems. Journal of Child and Adolescent Substance Abuse, 7, 63 – 73. Sobell, L. S., Cunningham, J. A., & Sobell, M. B. (1996). Recovery from alcohol problems with and without treatment: Prevalence in two population surveys. Journal of Public Health, 86, 96 – 97. Sobell, L. S., Ellingstad, T. P., & Sobell, M. B. (2000). Natural recovery from alcohol and drug problems: Methodological review of the research and suggestions for futures. Addiction, 95, 749 – 764. Stanton, W. R., Lowe, J. B., & Gillespie, A. M. (1996). Adolescents’ experiences of smoking cessation. Drug and Alcohol Dependence, 43, 63 – 70. Stice, E., Myers, M. G., & Brown, S. A. (1998). A longitudinal grouping analysis of adolescent substance use escalation and de-escalation. Psychology of Addictive Behaviors, 1(12), 14 – 27. Sussman, S., Dent, C. W., Severson, H., Burton, D., & Flay, B. R. (1998). Self-initiated quitting among adolescent smokers. Preventive Medicine, 27, A19 – A28. Tucker, J. A., Vuchinich, R. E., & Gladsjo, J. A. (1991). Environmental influences on relapse in substance use disorders. International Journal of Addictions, 25, 1017 – 1050. Wagner, E. F., Brown, S. A., Monti, P., Myers, M. G., & Waldron, H. B. (1999). Innovations in adolescent substance abuse intervention. Alcoholism, Clinical and Experimental Research, 23, 236 – 249. Wagner, E. F., Myers, M. G., & Brown, S. A. (1994). Adolescent substance abuse treatment. In L. VandeCreek, S. Knapp, & T. L. Jackson (Eds.), Interventions in clinical practice: A source book (pp. 97 – 121). Sarasota, Fl7 Professional Resources Press. Watson, A. L., & Sher, K. J. (1998). Resolution of alcohol problems without treatment: Methodological issues and future directions of natural recovery research. Clinical Psychology: Science and Practice, 5, 1 – 18. Yamaguchi, K., & Kandel, D. B. (1985). On the resolution of role incompatibility: A life event history analysis of family roles and marijuana use. American Journal of Sociology, 90, 1284 – 1325.
Facilitating youth self-change through school-based intervention Sandra A. Brown a,T, Kristen G. Anderson b, Marya T. Schulte c, Nicole D. Sintov b, Kevin C. Frissell c a
Department of Psychiatry and Psychology, University of California, San Diego, Veterans Affairs San Diego Healthcare System, McGill Hall, 9500 Gilman Drive, MC 0109, La Jolla, CA 92093-0109, United States b Department of Psychology, University of California, San Diego, CA, USA c Joint Doctoral Program of Clinical Psychology, San Diego State University/University of California, San Diego, CA, USA
Abstract Early interventions for youth with high rates of alcohol use have often suffered from lack of willing participation due to negative stereotypes about treatment and the impression that alcohol interventions are not developmentally relevant for adolescents. This study evaluated the effectiveness of a schoolbased voluntary secondary intervention for alcohol use (Project Options). 1254 high school students (55% girls; M age = 15.9, SD = 1.2) with a history of lifetime drinking completed survey measures after the first year of Project Options in 3 schools. These results suggest that the intervention was successful in recruiting high-frequency drinkers into the intervention as well as facilitating attempts to cut down or quit alcohol use in this group of adolescents. This study provides preliminary support for a consumer-based approach to alcohol intervention and design and use of voluntary secondary interventions in a school-based population. D 2005 Elsevier Ltd. All rights reserved. Keywords: Adolescent alcohol problems; Alcohol quit attempts; School-based intervention
T Corresponding author. E-mail address: [email protected] (S.A. Brown). 0306-4603/$ - see front matter D 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.addbeh.2005.07.003
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1. Changing adolescent alcohol use: facilitation of change attempts through intervention Alcohol use among America’s youth remains prevalent and problematic, with one quarter to one-third of high school students consuming alcohol at harmful rates (i.e., 5 or more drinks in the prior two weeks; Johnston, O’Malley, & Bachman, 2003). Youth experience both immediate and long-term consequences of early alcohol involvement. Problematic use is associated with decreased academic performance, higher rates of accidents and injuries, interpersonal problems, risky sexual behavior, tobacco and other substance use, and a variety of mental health disorders (Hussong & Chassin, 1994; Lewinsohn, Hops, Roberts, & Seeley, 1993). While youth who experiment with alcohol may exhibit few problems, more frequent and higher dose consumption escalates problem rates and risk for early dependence (Brown & Tapert, 2004; O’Malley, Bachman, Johnston, & Schulenberg, 2004). Because of the spectrum of negative consequences, youth with repeated alcohol experience are a compelling target for early alcohol interventions. Unhealthy habits affecting both physical well being (Friedman, 1993; Jessor, 1984) and coping strategies (Kazdin, 1993; Compas, 1993) in adulthood begin during adolescence. Thus, making changes during adolescence may have both short- and long-term benefits. Among youth evidencing alcohol problems, traditional treatment approaches appear to have limited appeal (Brown, 1993; Brown, 2001; D’Amico, McCarthy, Metrik, & Brown, 2004) because of the associated negative stereotypes (Ackard & NeumarkSztainer, 2001) and perceptions that such treatments are developmentally unsuitable and unhelpful with regards to adolescent needs (Kelly, Myers, & Brown, 2000; Wagner, Brown, Monti, Myers, & Waldron, 1999). Few interventions are readily available to youth who drink alcohol prior to emergence of more severe external problems that often trigger formal treatment (Brown, 2001). A limited number of school-based youth-targeted alcohol treatments have proven efficacious (Hser et al., 2001; Pentz, 1998). Similarly, programs centered on teaching teens about the effects and consequences of substance use and whose main objective is total abstinence also lack support in the reduction of use among adolescents. Such programs fail to feature the salient concerns of youth that may motivate their engagement in intervention efforts (Brown, 2001) and may actively prompt resistance to the intervention (Brown, 1993; Marlatt & Witkiewitz, 2002). The limited success of traditional interventions to delay initiation and reduce continuation of alcohol use among youth demonstrates the need for interventions that fit the developmentally specific needs and interests of youth at greatest risk for developing alcohol dependence. While only a small proportion of adolescents experiencing problems related to alcohol use actually participate in formal treatment, 15–20% adolescent drinkers reduce or stop drinking without formal intervention (e.g., Brown, 2001; Fillmore, 1988; Sobell, Ellingstad, & Sobell, 2000; Stice, Myers, & Brown, 1998) and maintain changes over a 1-year time period (Brown, 2001; Sobell, Cunningham, & Sobell, 1996; Wagner et al., 1999). Given that many youth make changes in their alcohol involvement without professional intervention and a small proportion of heavy drinking youth participate in
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formal treatment, interventions that focus on facilitating change efforts youth commonly utilize may be particularly useful in reducing adolescent alcohol use and altering typical progressions of alcohol involvement. Some reductions in adolescent alcohol involvement may be incidental to environmental or role transitions experienced during this developmental period (Brown, 2001; Watson & Sher, 1998). The socialization process and preparation necessary for many of these natural transitions (e.g., academic, sports, work, parenting) become factors in access to alcohol and decisions regarding frequency and quantity of consumption (Yamaguchi & Kandel, 1985). In contrast to this incidental change, cognitive social learning theory (Bandura, 1986) informs substance use interventions which facilitate purposeful change attempts for adolescents. Cognitive social learning theory, as it is applied to the reduction of adolescent substance use (Smart & Stoduto, 1997), postulates that alcohol cessation and reduction result from cognitive appraisal (e.g., perceived norms) and evaluation processes (e.g., cessation expectancies; Klingemann, 1991; Metrik, McCarthy, Frissell, MacPherson, & Brown, 2004; Tucker, Vuchinich, & Gladsjo, 1991). More specifically, we have proposed a developmental social information processing model (e.g., Brown, 2001; Metrik et al., 2004) which posits that cognitive and emotional states influence youth drinking behavior (e.g., whether or not to drink) within a social context by incorporating distal factors (e.g., biological risk and cultural experiences) with more proximal circumstances (e.g., alcohol availability and motivational state). Motivation has proven to be a key component in understanding adolescent self-change efforts as well as the failure of many current interventions (Myers, Brown, & Kelly, 2000; Peltier, Telch, & Coates, 1982). Because youth are less likely to have experienced the severe negative consequences of drinking (Nurmi, 1997) and more likely to view the heavy levels of use observed in their environment and the media as normal, their motivation to reduce or quit their drinking may be lower, qualitatively different from that of adults and requires intervention focused on enhancing the desire for change. Thus, youth purposeful change efforts in substance use may require a perceived need for change, either from external or personal factors, and may be facilitated by interventions which normalize (verify social models of) change efforts of peers. Using this developmental social information processing approach, early interventions to facilitate adolescent self-change efforts for alcohol and drug use problems may benefit from attending to these natural role and environmental changes, fluctuations in level and focus of motivation, and the influence of perceived drinking norms. Furthermore, our social cognition model hypothesizes that youth self-change occurs in two phase: 1.) quit/reduction attempts and 2.) subsequent maintenance efforts (Brown, 2001). Although research from the smoking cessation literature indicates that attempts to cut down or quit smoking are critical to the long-term process of smoking cessation, there is a dearth of knowledge about adolescent quit attempts for alcohol and how motivation and perceived norms lead from quit attempts to maintenance skills required for youth to sustain alcohol-related behavioral changes. The current study examines alcohol change efforts in a school-based high school alcohol intervention (Project Options) designed to reduce adolescent alcohol involvement
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through the facilitation of personal change attempts. The intervention incorporates motivational enhancement techniques (e.g., Miller & Rollnick, 2002), normative feedback, and skills training within a developmentally sensitive framework in order to target adolescent drinkers experiencing common developmental transitions (e.g., increased independence, autonomy, acquisition of adult responsibilities) and varying in level of motivation to change (Table 1). It was hypothesized that, compared to students with extensive alcohol experience who did not receive the intervention, similar heavydrinking students participating in the intervention would attempt to reduce or stop their alcohol involvement at greater rates. The intervention was predicted to have the greatest impact on youth with the most alcohol use experience and alcohol-related problems such that these youth would evidence the highest rates of attempts to cut down or quit alcohol in comparison to youth with limited and moderate lifetime alcohol use experience. Table 1 Project Options: intervention session content Session
Title
Content
1
Normative feedback (Miller & Rollnick, 2002)
2
Outcome expectancies (Darkes & Goldman, 1998)
3
Coping (Monti & Rosenhow, 1999)
4
Alternative activities (Marlatt & Witkiewitz, 2002)
5
Behavioral management (Wagner, Myers, & Brown, 1994)
6
Communication (Wagner et al., 1994)
–Estimates of perceived peer use –Graphs depicting actual peer use –Discussion of how students cease or reduce substance use –Education about alcohol and the actual effects of alcohol –Discuss people engaging in disinhibited and dangerous behaviors when using –Alcohol effect expectancies discussed –Coping with common adolescent stress and conflict without using substances –Elicit feedback regarding common stressors among students –Discussion of alternative ways of coping with stress –Discussion about how experimental use can lead to problem use –Elicit feedback about use and alternatives –Problems that can be avoided and benefits that can be gained from change efforts –Discussion of situations where alcohol or drugs may be present –Develop strategies for abstinence –Elicit feedback regarding how to anticipate, plan and prepare, and evaluate effectiveness of plans –Discussion of alternatives to use and maintaining personal goals –Substance resistance/refusal skills training –Communication breakdowns that may exacerbate alcohol use –Communication role plays –Common communication mistakes of teens and parents and teens and peers
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2. Method 2.1. Participants In the current study, students in 9th through 12th grades at three high schools in San Diego County had the opportunity to voluntarily participate in an alcohol intervention (Project Options). Project Options was developed to be appealing to youth (e.g., focus on socially valued content), minimize barriers related to participation (e.g., convenient times and location), to provide a range of participation format choices (e.g., participate independently or with others) and reflect service preferences of teens (Brown, 2001). The student population at the same three high schools (school-wide surveys; N = 2554) was surveyed in the spring of the initial year of Project Options at each site. Youth with a history of at least one standard alcohol drink were selected for analyses. Of the 60% of students reporting lifetime alcohol use, 11% were omitted due to inconsistent responding or missing data on one or more variables under study. The final sample included 1249 youth. Comparison of youth who were selected for these analyses versus those excluded suggests included and excluded youth were not significantly different of either sex or school placement (i.e., Schools 1, 2, or 3). As expected, youth with alcohol experience were significantly older, t(2541) = 5.63, p = .001, more likely to be in 11th or 12th grade, v 2 = 63.30, df = 7, p b .0001, and Caucasian, v 2 = 38.80, df = 5, p b .0001. For confidentiality purposes, no personally identifying information was collected from students at the school-wide surveys. The final sample was comprised of youth with limited lifetime experience with alcohol (V 10 lifetime drinking episodes: 48%), 24% with moderate lifetime experience with alcohol (11–50 lifetime episodes), and 28% with high lifetime experience (51+ lifetime alcohol use episodes). A comparison of the demographic and alcohol use characteristics for the three alcohol use groups (limited experience, moderate experience, and high experience) is presented in Table 2. Use groups were significantly different on the basis of age, F[2, 1236] = 36.30, p b .0001, grade, v 2 = 91.47, df = 6, p b .0001, and ethnicity, v 2 = 16.92, df = 4, p b .01, and recent alcohol use variables (max drinks/episode: F[2, 1216] = 255.64, p b .0001; average drinks/episode: F[2, 1224] = 260.76, p b .0001; binge (5 + drinks) episodes: F[2, 1209] = 132.96, p b .0001). Youth in the high experience group were more likely to be older, be in the 11th or 12th grade, and use alcohol at higher rates for the past 30-day period (maximum drinks, average drinks and binge drinking episodes). Youth in the limited experience group were more likely to identify themselves as bMultiracial/otherQ. 2.2. Procedures Using procedures approved by the University of California, San Diego Committee for the Protection of Human Subjects, the school district, and the individual high schools, data for the current study were collected as part of larger study of adolescent substance use behavior (e.g., Brown, 2001; Metrik et al., 2004) and included parent permission for student voluntary participation in the intervention and annual surveys (see Frissell et al., 2005 for survey details).
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Table 2 Demographic and past 30-day alcohol use characteristics of high school students with lifetime alcohol experience (N = 1249)
Background variables AgeT Sex Boys (%) Girls (%) GradeT 9 (%) 10 (%) 11 (%) 12 (%) EthnicityT Caucasian (%) Mixed/other (%) Latina/o (%) Alcohol use (30 day) Max drinks/episodeT Average drinks/episodeT Binge episodesT (5+ drinks)
Limited (1–10 episodes) alcohol use (48%)
Moderate (11–50 episodes) alcohol use (24%)
High (50+ episodes) alcohol use (28%)
15.7 (1.2)
16.0 (1.2)
16.3 (1.2)
41.1 58.9
45.6 54.4
49.0 51.0
37.9 26.8 22.6 12.7
22.8 26.6 29.4 21.2
13.7 24.8 31.2 30.3
54.3 40.0 5.7
65.9 29.7 4.4
65.6 30.0 4.4
1.8 (3.0) 1.7 (2.4) 1.0 (3.5)
4.3 (4.0) 3.7 (3.2) 2.2 (4.4)
7.7 (4.8) 6.6 (4.1) 6.2 (6.5)
T p b .0001.
2.2.1. Intervention The Project Options intervention was initially implemented during the 1999–2000 school year at School 1 and the 2000–2001 school year at Schools 2 and 3. Upon implementation at each school, the opportunity to voluntarily participate in the intervention was available to all students regardless of substance use history. To address diverse adolescent preferences for intervention delivery (Brown, 2001; D’Amico et al., 2004), the intervention was offered in three formats: group, individual, and website. The three intervention formats were jointly advertised and simultaneously offered (e.g., during lunch period) and consisted of a maximum of six 30-min group sessions, four 30-min individual sessions, and unlimited website access. All Project Options formats were offered once per week at each school during lunchtime in convenient classrooms and the website was also accessible 24 h a day from either school or off site locations. Youth choosing any format received a lunch during their noontime participation and $5 incentive (gift certificates for clothing, movies, music, or restaurants) at the end of their first session following the completion of a brief questionnaire assessing background characteristics and alcohol use. Based on the developmental social information processing model (Brown, 2001), the Project Options intervention focused on increasing motivation to change alcohol use (e.g., reduction and cessation) and related risk behaviors, generating resources for alternative behaviors, and teaching behavioral skills to increase the likelihood of successful personal change efforts. The content of Project Options was similar across formats and included topics
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addressing normative feedback on peer use and change attempts, alcohol outcome expectancy challenges, coping skills, recognizing personal need to change, behavioral management strategies, and effective communication. Students were able to select any of the 6 topic sessions advertised (Table 1). The style of interactive activities for students as well as motivational and marketing elements (i.e., style of advertising) was based on student pilot focus groups from demographically similar schools and preintervention surveys. 2.2.2. School-wide survey All data examined for the current study comes from the school-wide surveys in the second semester after Project Options was implemented at each school. Respondents included 810 School 1 students, 1168 School 2 students and 576 students at School 3. One month prior to each school-wide survey, parent information and consent packets were mailed to student homes. Each packet included parent consent forms for the intervention and survey, a letter from the principal and informational sheets (bCommon QuestionsQ). Additionally, one week prior to the survey date, each student was given a consent form and common questions sheet to hand-carry home to his/her parent to help ensure parents were informed of the study and to give an additional opportunity for parents to ask questions and to respond to the consent request. Trained proctors administered surveys in each classroom when normal absentee rates were expected (e.g., 5%) during a specified time determined by the school (e.g., homeroom and first-period class). Student assent was also obtained at the time of the survey through written informed assent forms. 2.3. Measures Outcome data consist of responses to the second semester school-wide surveys described above. Surveys assessed an array of background characteristics, alcohol and other substance use and problems, and related risk behaviors. 2.3.1. Personal characteristics Background variables included gender, grade (9th–12th), ethnicity, and age. Ethnicity was reported from a list of choices: American Indian/Alaska Native, Asian American, Black/ African American (non-Hispanic), Hispanic or Latino/Latina, Native Hawaiian/Pacific Islander, White (Caucasian/non-Hispanic), or Other/Multiracial. Intervention attendance was determined by students indicating whether or not they had attended one or more Project Options meeting (group or individual) or used the Project Options website during the academic year (yes/no). 2.3.2. Alcohol involvement Students reported past month average number of drinks consumed per drinking occasion (range = 0 to 15 drinks), frequency of binge drinking (defined as five or more drinks per occasion; range = 0 to 15 times), and largest number of drinks consumed on a drinking occasion (range = 0 to 15 drinks). One standard drink was defined as one can/bottle of beer or wine cooler, one glass of wine, or one shot glass of liquor. Using items from well-established
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measures such as Monitoring the Future survey (Johnston et al., 2003) and the Youth Risk Behavior Survey (CDC, 1990), students also reported lifetime use (range = never, 1–10 times, 11–50 times, and 51+ times) of alcohol. 2.3.3. Outcome variables Students responded yes or no to whether they had made a personal attempt to cut down their alcohol use (Have tried to cut down alcohol in the past year?) and, on a second question, whether they had attempted to quit drinking in the past year (Have you tried to quit drinking alcohol in the past year?). 2.4. Analyses Students were first separated into three groups on the basis of their self-reported lifetime use episodes for alcohol: the limited experience group (n = 603) used alcohol on 1–10 occasions during their lifetime; the moderate experience group (n = 297) used alcohol on 11– 50 occasions during their lifetime; the high experience group (n = 348) used alcohol on 51 or more occasions during their lifetime. Youth were further classified into intervention group (participated in Project Options during the school year) and no intervention group (no participation in Project Options). Logistic regressions were used to investigate the impact of Project Options (no intervention versus intervention) on student attempts to cut down (yes/no) or quit (yes/no) alcohol in the past year. In addition, subsample analyses were conducted on smaller cohort of matched youth (n = 276) to address issues related to demographic differences found between groups. Conditional logistic regression, matching individuals in the no intervention and intervention groups on age, sex, grade and ethnicity, was also performed separately for each use group.
3. Results 3.1. Intervention participation First, we examined demographic and use pattern differences between youth with lifetime use of alcohol who self-selected into Project Options and No Intervention students. Approximately 18% of students with lifetime alcohol experience (N = 223) reported voluntarily attending Project Options intervention during the first year of implementation. Project Options youth and No Intervention students were similar in age (M = 16.0 and 15.9 years, respectively) and grade. 22.8% of intervention participants reported being in the 9th grade, 31.3% in 10th grade, 28.1% in 11th grade, and 17.9% in 12th grade. Similarly, 28.6% of No Intervention students were in the 9th grade, 24.9% in 10th grade, 26.7% in 11th grade, and 19.8% in 12th grade. Half of the Project Options group (51.1%) were Caucasian, 7.8% were Hispanic–American, 2.4% African–American, 1.7% Asian American, 6.7% Native American, and 30.0% identified themselves as bMultiracial/OtherQ. Among other students, 62.1% were Caucasian, 4.9% were Hispanic–American, 6.1% African–American, 0.7%
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Asian–American, 1.6% Native American, and 24.9% identified themselves as bMixed/OtherQ. Of the intervention participants, 54.5% were male whereas 42.4% of No Intervention students were male (v 2 = 10.88, df = 1, p b .001). Project Options youth were more likely to be nonwhite, v 2 = 34.06, df = 5, p b .0001, and have greater alcohol use in the prior 30 days (binge episodes: t (1219) = 2.20, p b .05; maximum drinks/episode: t (1227) = 2.09, p b .05) than No Intervention students. 3.2. Personal change efforts The prevalence rate for personal attempts to cut down alcohol use in the entire high school sample was 21.0% and 17.0% of the students attempted to quit using alcohol in the past year. Approximately 21.6% of Project Options youth attempted to cut down their drinking in the past year compared to 20.6% of No Intervention youth. For quit attempts, 19.6% of Project Options youth compared to 16.5% of No Intervention youth attempted to stop drinking in the past year. Table 3 provides the results of the logistic regressions for the three alcohol use groups separately for attempts to cut down or quit alcohol use. As can be seen, Project Options was effective in fostering attempts to cut down and stop alcohol use for youth with the highest lifetime experience with alcohol use. Fig. 1 displays the proportion of cut down attempts for intervention and no intervention samples in relation to lifetime exposure to alcohol. Examination of the odds ratios across alcohol use groups indicates that youth in the high alcohol use group were 1.84 times ( p b .05) more likely to attempt to cut down their alcohol use in the last year compared to 0.69 (ns) for the infrequent experience and 0.78 (ns) in the moderate experience group. Conditional logistic regression was used to examine the impact of Project Options on attempts to cut down on drinking using groups matched on the basis of grade, sex, school and ethnicity (n = 276) separately for each use group. In the high alcohol experience group, it was found that the odds of cutting down on alcohol use was 2.42 times (95% CI = 1.18–4.95) greater for youth in Project Options compared to No Intervention youth, log likelihood = 122.23, v 2 = 5.88, df = 1, p b .05. Conditional logistic regressions for attempts to cut down alcohol use were not significant for the infrequent and moderate experience groups.
Table 3 Logistic regressions predicting youth attempts to cut down and stop alcohol use from Project Options participation: comparison across alcohol use levels Lifetime exposure level DV: attempts to cut down alcohol use Limited experience Moderate experience High experience DV: attempts to stop alcohol use Limited experience Moderate experience High experience
Log likelihood
OR
95% CI
p-value
233.50 176.01 201.77
0.69 0.78 1.84
0.35–1.34 0.38–1.63 1.05–3.21
.27 .52 .03
246.44 143.76 122.23
0.85 1.09 2.42
0.46–1.56 0.49–2.42 1.18–4.95
.60 .83 .05
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40
Percent with Cut Down Attempts
No Intervention Project Options
30
* 20
10
0 Limited
Moderate
Frequent
Lifetime Use Group Fig. 1. Proportion of cut down attempts for alcohol among Project Options and No Intervention youth: lifetime use groups. *p b .05.
40
Percent with Quit Attempts
No Intervention Project Options
30
* 20
10
0 Limited
Moderate
Frequent
Lifetime Use Group Fig. 2. Proportion of quit attempts for alcohol among Project Options and No Intervention youth: lifetime use groups. *p b .05.
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The proportion of quit attempts in relation to lifetime use status is presented in Fig. 1. For attempts to stop alcohol use, individuals in the high alcohol use group were again more likely to attempt to stop alcohol use in the past year if they attended Project Options (Fig. 2). Odds ratios suggested that youth in the high experience group were 1.85 times ( p b .05) more likely to attempt to stop using alcohol compared to youth in the limited experience (OR = 0.85, ns) or moderate experience (OR = 1.09, ns) groups. Conditional logistic regressions were also conducted for youth attempts to quit alcohol use in the past year based on the same matching criteria listed above. In none of the groups were significant findings found for conditional analyses.
4. Discussion This investigation constitutes a preliminary test of the effectiveness of the Project Options intervention in engaging youth and facilitating attempts to cut down or quit alcohol use among teens who have a history of alcohol use. In this sample of high school students who drink, 18% of drinkers voluntarily self-selected into the school-based intervention. Youth who participated in the intervention had greater drinking rates in the past 30 days (maximum drinks per occasion and binge drink episodes) than youth who did not participate in the intervention. Further, males and non-Whites, both groups likely to experience alcohol-related problems, were voluntarily recruited into Project Options. As past research suggests that the lack of teen involvement in intervention is function of negative beliefs about treatment effectiveness and a lack of focus on the needs of adolescents (Ackard & Neumark-Sztainer, 2001; Kelly et al., 2000), the higher rates of alcohol involvement for youth who self-select into Project Options provide preliminary support for the developmentally sensitive design of this intervention, both in recruitment and intervention. The intervention appears to be most likely to promote personal efforts to stop or cut down alcohol use among youth at greatest risk for progression to an alcohol use disorder. Youth who had the highest exposure to drinking seemed to benefit most from the intervention; participation in Project Options increased their odds of cutting down drinking over 1 3/4 times compared to youth who did not self-select into the intervention and increased the likelihood of quit attempts by almost 2 1/2 times. By contrast, participation did not significantly influence youth attempts to cut down or quit drinking for the limited or moderate experience drinkers. Students with the most experience with drinking were more likely to be older, be in the later grades, and had used alcohol in greater quantities during the last month. These findings are consistent with what might be expected for individuals with greater lifetime drinking experience, supporting the use of these distinctions in preliminarily evaluating the effectiveness of Project Options in facilitating youth attempts to cut down or stop alcohol use. While intervention was most effective for high school students with the greatest alcohol use, their exposure to youth with limited and moderate alcohol use histories either in person or though normative feedback is hypothesized to be an important aspect of this intervention. The ability for the highest
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risk youth to be exposed to change information and alternative alcohol use models is an important aspect of intervention, both in modeling alternative alcohol-related behaviors (cessation or reduced use) and providing more appropriate information regarding normative peer use. The rate at which youth attempted to cut down or quit alcohol use in this sample, about 20%, is consistent with rates evidenced in the literature on alcohol change efforts in adolescents (e.g., Stice et al., 1998; Wagner et al., 1999). However, these rates are substantially lower than youth attempts to cut down or quit smoking. More than half of adolescent smokers report intentions to quit smoking and a majority of youth smokers report prior cessation attempts (Burt & Peterson, 1998; Ershler, Leventhal, Fleming, & Glynn, 1989; Stanton, Lowe, & Gillespie, 1996; Sussman, Dent, Severson, Burton, & Flay, 1998). This difference between alcohol cessation attempts and smoking quit attempts might be a function of youth perceptions of risks associated with smoking versus alcohol use (e.g., social acceptability of use and perceived anticipated consequences of cessation) or biological processes of development (e.g., appetitive drives) or pharmacological drug effects. However, future investigations are needed to understand factors influencing youth quit attempts across substances. While this investigation provides preliminary support for the developmentally sensitive design of the Project Options self-selection paradigm in attracting and influencing attempts to cut down or quit drinking for youth with the greatest frequency of use, some caveats should be considered. First, this study does not address the issue of whether selection factors in place prior to participation influenced outcomes for youth. Youth entering Project Options might have been more motivated to change, have more alcohol-related problems, or a greater history of quit attempts than youth who chose not to participate. However, Project Options youth with less experience with alcohol did not report greater rates of attempts to cut down or quit; only targeted youth for whom the intervention was designed exhibited significantly more selfchange efforts. In addition, the assessment time point included reports of participation in Project Options throughout the school year. Attempts to cut down/quit may be most prevalent during intervention participation or shortly thereafter; the end-of-year assessment may mask the temporal patterns of these outcomes. To our knowledge, this is the first voluntary secondary intervention for alcohol-using youth that has demonstrated the ability to engage this underserved group of youth and promote personal change efforts. Future investigations to examine how proximal outcomes (i.e., change efforts) relate to longer term alcohol use outcomes and the generalizability of this developmental paradigm for early intervention in schools will be the next step in validating the Project Options approach.
Acknowledgements We would like to thank the programs, staff, and participants in this study. This research supported by National Institute on Alcohol Abuse and Alcoholism grants AA12171 (S. Brown).
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