The purpose of this research study was to examine the effect of a multiple risky behaviors prevention program applied comprehensively throughout an entire school system involving universal, selective, and indicated levels of students at a local private high school during a 4-year period. The noncurriculum prevention program was created based upon the key elements of effective prevention programming and the need to address the growing variety of risky behaviors that the youth face today. Results (
In the United States, the average age of the first use of alcohol and marijuana is between 15 and 17 [
Empirical evidence of the effectiveness of prevention programs indicates that certain risky behaviors have been prevented or reduced for up to 15 years [
Although most prevention programs in the United States are universal, they focus only on two to three risky behaviors. However, evidence indicates that integrated, multiple-risk prevention programs can be effective across a range of health risk behaviors prevalent in adolescence [
The development of the Choices program was guided by empirical studies involving meta-analysis and reviews of school-based prevention models that have revealed key elements of effective prevention programming [
Visual representation of the key elements of prevention programs beginning with Tobler et al.’s [
Including the entire student body, family, school, and community produces larger and longer lasting effects on the high-risk behaviors of students who participate in such programs [
Prevention outcome research indicates that change is more likely to occur when students practice new skills in dynamic interactions throughout the entire school system, including peers, parents, and community [
In the extant literature, interactive teaching techniques emerged as an essential element, with interactive programs showing a 21% reduction in risky behaviors prevalence rates as opposed to 4% for noninteractive programs [
After 2 years of Choices programming, a random sample of faculty members chosen to facilitate Choices activities was interviewed in order to understand their lived experiences of participating in program implementation [
Choices programming utilizes education and skills training for all prevention programming and activities. Educational components include refusal skills, improving executive functioning skills, and healthy coping skills. Life skills, social and emotional, and positive behavior skills training are integrated and tailored to fit the school’s culture. Relationship building is emphasized through the creation of Choices faculty, parent, and student collaborative work groups.
Guided by Bronfenbrenner’s ecological systems theory, the program curriculum is based on an integrated theoretical perspective that considers behavior as the result of complex interactions among person-, situation-, and environment-level variables within a community [
This study represented a quasi-experimental, longitudinal design conducted in a medium-sized private high school in a large metropolitan city in the Southwest United States, with national survey data serving as the nonrandomized control group for 2 of the 4 years. The national data include public and private school students and, thus, served as an appropriate comparison group for this study’s local private school population because it allowed the researchers to situate the findings within a national context, thereby enhancing the external validity of the findings. The following research questions were addressed: (a) what is the difference between the prevalence rates of risky behaviors for the youth who participate in the program and the national rates of the same year? and (b) what is the difference between pretest data and each subsequent year’s data of the youth who participate in the program? Permission to conduct the research was obtained through a local university institutional review board, the school, and the local agency providing the program.
During each year of the program, 4 to 6 universal prevention presentations were offered to the entire student body, parents, and faculty/administration depending upon allotted time determined by the school. The presentation topics were chosen based on the risky behaviors having the highest prevalence rates in the previous year’s survey. After each school-wide presentation, all students engaged in a topic discussion or activity during their advisory or home-room class. In addition, prevention activities, groups, and events were held each month. Once again, these activity topics were chosen with regard to survey results or current needs determined by school administration and offered to selective groups of students, faculty members, and parents. Indicated students were seen each day, on an as-needed basis, by the prevention program counselor. Also, interactive prevention program presentations regarding each culturally relevant topic were offered each semester during health classes.
Student risky behaviors were measured via a convenience sample of all students available to respond to the survey given once per year. Participants included all students enrolled in the school from May 2009 to May 2013. Students and parents were given consent forms as a procedure of school enrollment. In the 2008-2009 school year, the Pretest Year, 93.1% of the student body responded to the survey. In the 2009-2010 school year, 86% of the student body responded to the survey, and 70.6% of the student body responded to the survey in the 2010-2011 school year. In the 2011-2012 school year, 84.6% of the student body responded to the survey, and 83.9% of the student body responded to the survey in the 2012-2013 school year. Table
Demographics of student body and survey respondents by gender, grade, ethnicity, and total by year of study programs.
2009 | 2010 | 2011 | 2012 | 2013 | ||||||||||||||||
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Student body | Survey respondent | Student body | Survey respondent | Student body | Survey respondent | Student body | Survey respondent | Student body | Survey respondent | |||||||||||
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Gender | ||||||||||||||||||||
Male | 316 | 48 | 306 | 49.8 | 308 | 46.6 | 252 | 44.3 | 292 | 44 | 208 | 44.3 | 309 | 45.5 | 266 | 46.3 | 331 | 49.2 | 275 | 50.0 |
Female | 343 | 52 | 308 | 50.2 | 353 | 53.4 | 317 | 55.7 | 372 | 56 | 261 | 55.7 | 370 | 54.5 | 309 | 53.7 | 342 | 50.8 | 290 | 50.0 |
Grade | ||||||||||||||||||||
9th | 167 | 25.4 | 154 | 25.1 | 171 | 25.9 | 154 | 27.1 | 163 | 24.5 | 144 | 30.7 | 166 | 24.4 | 158 | 27.5 | 164 | 24.4 | 154 | 30.0 |
10th | 165 | 25.0 | 154 | 25.1 | 168 | 25.4 | 156 | 27.4 | 176 | 26.5 | 110 | 23.5 | 169 | 24.9 | 156 | 27.1 | 166 | 24.7 | 143 | 30.0 |
11th | 165 | 25.0 | 158 | 25.7 | 160 | 24.2 | 144 | 25.3 | 169 | 25.5 | 125 | 26.7 | 173 | 25.5 | 123 | 21.4 | 172 | 25.6 | 159 | 30.0 |
12th | 162 | 24.6 | 148 | 24.1 | 162 | 24.5 | 115 | 20.2 | 156 | 23.5 | 90 | 19.2 | 171 | 25.2 | 138 | 24.0 | 171 | 25.4 | 109 | 20.0 |
Ethnicity | ||||||||||||||||||||
African American | 38 | 5.8 | — | — | 41 | 6.2 | — | — | 50 | 7.5 | — | — | 52 | 7.7 | — | — | 55 | 8.2 | — | — |
Asian | 23 | 3.5 | — | — | 22 | 3.3 | — | — | 25 | 3.8 | — | — | 21 | 3.1 | — | — | 18 | 2.7 | — | — |
Latino/Hispanic | 48 | 7.3 | — | — | 43 | 6.5 | — | — | 43 | 6.5 | — | — | 39 | 5.7 | — | — | 48 | 7.1 | — | — |
Middle Eastern | 13 | 2 | — | — | 12 | 1.8 | — | — | 11 | 1.7 | — | — | 6 | 0.9 | — | — | 9 | 1.3 | — | — |
Multiracial | 0 | 0 | — | — | 4 | 0.6 | — | — | 2 | 0.3 | — | — | 12 | 1.8 | — | — | 11 | 1.6 | — | — |
International | 0 | 0 | — | — | 7 | 1.1 | — | — | 7 | 1.1 | — | — | 12 | 1.8 | — | — | 10 | 1.5 | — | — |
White | 534 | 81 | — | — | 532 | 80.5 | — | — | 526 | 79.2 | — | — | 536 | 78.9 | — | — | 521 | 77.4 | — | — |
Other | 3 | 0.5 | — | — | 0 | 0 | — | — | 0 | 0 | — | — | 1 | 0.1 | — | — | 1 | 0.1 | — | — |
The Youth Risk Behavior Survey (YRBS) was utilized to collect a pretest measure in 2009 and 4 years of students’ behavioral data after the implementation of the prevention program between 2010 and 2013. Developed by the Centers for Disease Control and Prevention (CDC), the YRBS serves as a national source of information about risky behaviors among adolescents in Grades 9 to 12 and has been given to randomly selected public and private schools in the United States every 2 years since 1991 [
However, to address the specific goals of this study, the program developer added items pertaining to additional risky behaviors not included in the YRBS (e.g., pornography, gambling, self-injury, video game use, and date rape). The additional topic items were constructed in an identical format to the existing YRBS item format. In addition, certain original items in the YRBS that did not apply to the present sample were excluded from the survey (e.g., seatbelt or helmet safety questions, dietary questions, and physical activity questions). The YRBS questions regarding bullying, date rape, and dating violence query both whether the student has perpetrated and whether he/she has been the victim of the act. For the purpose of this study, only questions wherein the student endorsed being a victim of the act were utilized for analysis.
The quantitative analysis of data included examining the differences between the student data and the national CDC sample data trends as well as differences between the pretest survey data and each subsequent year of the student surveys. The independent variable was time (i.e., before measure versus 1–4 years after measure). The dependent variables, namely, (a) selected student risky behaviors of the local students (i.e., one dependent variable for each risky behavior for the univariate analyses) and (b) the type of students (i.e., the local students versus the national students), were measured as categorical variables. Therefore, a chi-square test was employed to compare pretest data (2009) and study Years 1–4 data (2010–2013) for 20 risky behaviors variables (representing the 15 different risky behaviors), using the Bonferroni adjustment (i.e., .05/20 = .0025) to ensure that the total experiment-wise error rate did not exceed 5% [
High-risk behaviors and corresponding variables.
High-risk behavior | Corresponding variables |
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(1) Alcohol use | Lifetime alcohol |
Drinking 1 or more times in the past 30 days | |
Drinking 5 or more times in the past 30 days | |
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(2) Drinking and driving | Drinking and driving in the past year |
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(3) Marijuana use | Lifetime marijuana use |
Marijuana use in the past 30 days | |
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(4) Heavy drug use | Lifetime cocaine use |
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(5) Cigarette use | Cigarette use in the past 30 days |
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(6) Eating disordered behavior | Fasting in the past 30 days |
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(7) Bullying | Bullied in the past year |
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(8) Suicide | Suicide attempts in the past year |
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(9) Sex/oral sex | Sex/oral sex in the past year |
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(10) Dating violence | Dating violence in the past year |
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(11) Date rape | Date rape in the past year |
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(12) Gambling | Gambling in the past year |
Tried to win back money | |
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(13) Pornography use | Pornography in the past 30 days |
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(14) Self-injury | Self-injury in the past year |
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(15) Video game overuse | Video game use |
Video game use for 5 or more hours |
The national YRBS survey did not assess some of the risky behaviors that the local modified YRBS did (e.g., gambling, pornography, self-injury, date rape, and video game use) yielding 10 risky behaviors (13 variables) in common. To address Research Question
Local versus national risk behavior as a percentage of the sample: Pretest year (2009), Year 2 (2011), and Year 4 (2013).
Risk behavior | Pretest year (2009) | Year 2 (2011) | Year 4 (2013) | ||||||
---|---|---|---|---|---|---|---|---|---|
Local ( |
National ( |
Difference | Local ( |
National ( |
Difference | Local ( |
National ( |
Difference | |
(%) | (%) | (%) | (%) | (%) | (%) | (%) | (%) | (%) | |
Lifetime alcohol use | 76.2 | 73.9 | 2.3 | 71.0 | 68.4 | 2.6 | 67.0 | 67.7 | −0.7 |
Drinking in the last 30 days | 54.2 | 42.0 | 12.2 |
43.7 | 39.0 | 4.7 | 43.4 | 35.6 | 7.8 |
Drinking 5 or more times in the last 30 days | 38.3 | 24.0 | 14.3 |
27.5 | 21.9 | 5.6 |
27.8 | 20.1 | 7.7 |
Drinking and driving in the last year | 21.0 | 9.9 | 11.1 |
10.7 | 8.3 | 2.4 | 10.3 | 9.7 | 0.6 |
Lifetime marijuana use | 38.3 | 38.3 | 0.0 | 27.7 | 39.9 | −12.2 |
28.7 | 43.7 | −15.0 |
Marijuana in the last 30 days | 24.6 | 20.9 | 3.7 | 16.0 | 23.6 | −7.6 |
9.9 | 25.3 | −15.4 |
Lifetime cocaine use | 7.7 | 7.3 | 0.4 | 5.3 | 7.2 | −1.9 | 2.5 | 5.6 | −3.1 |
Cigarettes in the last 30 days | 19.4 | 18.9 | 0.5 | 11.7 | 17.2 | −5.5 |
14.9 | 14.5 | 0.4 |
Fasting in the last 30 days | 5.4 | 11.1 | −5.7 |
7.0 | 12.7 | −5.7 |
6.9 | 13.3 | −6.4 |
Bullied last year | 9.9 | 19.0 | −9.1 |
17.5 | 18.0 | −0.5 | 20.0 | 18.6 | 1.4 |
Suicide attempts in the last year | 1.3 | 7.2 | −5.9 |
3.4 | 8.7 | −5.3 |
4.3 | 8.5 | −4.2 |
Sex/oral sex in the last year | 38.1 | 50.4 | −12.3 |
31.1 | 50.5 | −19.4 |
32.4 | 49.7 | −17.3 |
Dating violence | 8.5 | 11.1 | −2.6 | 6.6 | 10.5 | −3.9 | 4.6 | 10.7 | −6.1 |
In Pretest Year 2009, three variables displayed statistically significant differences above national rates: drinking at least one drink within the past 30 days (current drinking), drinking five or more alcoholic drinks on a single occasion within the last 30 days (binge drinking), and drinking and driving. In the same year, four variables displayed statistically significant differences lower than national rates: fasting as diet method within the past 30 days, being bullied within the past 12 months, suicide attempts, and sex/oral sex. In 2011, one variable yielded statistically significant differences above national rates: binge drinking. In the same year, six variables yielded statistically significant differences below national rates: lifetime marijuana use, marijuana use within the last 30 days, cigarettes within the last 30 days, fasting as diet method within the past 30 days, suicide attempts, and sex/oral sex. In 2013, two variables yielded statistically significant differences above national rates: current drinking and binge drinking. In the same year, seven variables yielded statistically significant differences below national rates: lifetime marijuana use, marijuana use within the last 30 days, lifetime cocaine use, fasting as diet method within the past 30 days, suicide attempts, sex/oral sex, and dating violence. The effect sizes for all variables in all years were small.
When compared to the Pretest Year, nine out of 20 risky variables representing seven risky behaviors displayed statistically significant decreases for each of the 4 years of the study, eight of which were substance-use behaviors. Lifetime alcohol use, current drinking, binge drinking, and drinking and driving all decreased statistically significantly each subsequent year of the study when compared to the Pretest Year. The same result was achieved for lifetime marijuana use, current marijuana use, lifetime cocaine use, and current cigarette use. These results indicate that the prevention program likely had a positive effect on reducing substance use.
However, non-substance-use behaviors yielded variable results, an indicator that the program likely had little effect on these behaviors. Regarding eating disordered behaviors, more students reported engaging in fasting as a diet method each year of the program when compared to the Pretest Year 2009. The same was true for suicide attempts, although no increases were statistically significant for either behavior. The experience of being bullied was statistically significantly higher in each subsequent year of the study when compared to the Pretest Year, doubling by 2013. Regarding being a victim of dating violence, students reported a statistically significant increase in Year 1, followed by two decreases in Year 2 and Year 3, ending in a statistically significant drop in Year 4 when compared to the pretest scores. Video game use decreased statistically significantly each year of the program. However, the number of students who engaged in 5 or more hours of video game use per day statistically significantly increased in Years 1, 2, and 4. Though not statistically significant, students reported decreasing rates of gambling during each year of the program. However, of those who gambled, the rates at which students reported attempting to win back their money increased in Year 1, decreased statistically significantly in Year 2, and increased statistically significantly in Year 3 and Year 4. Another conflicting result was the reported use of pornography, which statistically nonsignificantly decreased in Year 1, statistically significantly decreased in Year 2, and statistically significantly increased in Year 4. The incidence of reported date rape appeared to remain stable except for a statistically significant increase in Year 2. Table
Risk behavior per year of study as a percentage of the sample—all years.
Risk behavior | 2009 ( |
2010 ( |
2011 ( |
2012 ( |
2013 ( |
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(%) | (%) | (%) | (%) | (%) | |
Lifetime alcohol use | 76.2 | 68.0 |
68.4 |
68.0 |
67.1 |
Drinking in the last 30 days | 54.2 | 45.3 |
43.7 |
43.7 |
43.5 |
Drinking 5 or more times in the last 30 days | 38.3 | 33.2 |
27.5 |
29.4 |
28.0 |
Drinking and driving in the last year | 21.0 | 15.8 |
10.7 |
12.5 |
10.4 |
Lifetime marijuana use | 38.3 | 28.1 |
27.7 |
26.1 |
28.8 |
Marijuana in the last 30 days | 24.6 | 16.5 |
16.0 |
13.4 |
10.1 |
Lifetime cocaine use | 7.7 | 5.4 |
5.3 |
2.1 |
2.7 |
Cigarettes in the last 30 days | 19.4 | 11.4 |
11.7 |
12.2 |
15.0 |
Fasting in the last 30 days | 5.4 | 7.7 | 7.0 | 6.6 | 7.1 |
Bullied last year | 9.9 | 16.0 |
17.5 |
15.3 |
20.2 |
Suicide attempts in the last year | 1.3 | 3.9 | 3.4 | 3.3 | 4.4 |
Gambling in the last year | 22.6 | 19.5 | 17.5 | 18.6 | 20.2 |
Winning back money | 8.1 | 9.0 | 2.1 |
11.8 |
14.7 |
Pornography in the last 30 days | 28.3 | 21.8 | 17.5 |
25.0 | 29.7 |
Self-injury in the last year | 12.4 | 10.4 | 8.3 | 9.9 | 9.6 |
Sex/oral sex in the last year | 38.1 | 32.3 | 31.1 | 32.0 | 32.6 |
Dating violence | 8.5 | 16.5 |
6.6 | 5.2 | 4.8 |
Date rape | 0.7 | 0.7 | 2.3 |
0.9 | 1.1 |
Video game use | 49.8 | 38.8 |
10.7 |
42.3 |
41.4 |
Video game use for 5 or more hours | 1.5 | 2.1 |
2.3 |
1.2 |
2.5 |
Table
Logistic regression analysis of gender, grade, and subsequent study years for substance-use risk behaviors.
|
SE | Wald’s test ( |
Odds ratio | 95% CI | |
---|---|---|---|---|---|
Lifetime alcohol use | |||||
Intercept | −1.09 | 0.44 | 6.29 |
0.34 | |
Gender | −0.15 | 0.09 | 3.16 | 0.86 | 0.72, 1.02 |
Sophomore | 0.54 | 0.11 | 25.34 |
1.72 | 1.39, 2.12 |
Junior | 1.01 | 0.11 | 77.85 |
2.74 | 2.19, 3.43 |
Senior | 1.84 | 0.14 | 162.25 |
6.28 | 4.73, 8.33 |
Pretest (2009) to 2010 | 0.68 | 0.19 | 12.43 |
1.98 | 1.35, 2.90 |
Pretest (2009) to 2011 | 0.47 | 0.13 | 12.72 |
1.61 | 1.24, 2.08 |
Pretest (2009) to 2012 | 0.34 | 0.10 | 10.95 |
1.40 | 1.15, 1.71 |
Pretest (2009) to 2013 | 0.27 | 0.08 | 10.44 |
1.30 | 1.11, 1.53 |
Drinking in the last 30 days | |||||
Intercept | −2.41 | 0.40 | 36.45 |
0.09 | |
Gender | −0.08 | 0.08 | 1.01 | 0.92 | 0.79, 1.08 |
Sophomore | 0.71 | 0.11 | 38.57 |
2.03 | 1.62, 2.53 |
Junior | 1.22 | 0.11 | 115.79 |
3.38 | 2.70, 4.22 |
Senior | 2.14 | 0.13 | 290.71 |
8.49 | 6.36, 10.85 |
Pretest (2009) to 2010 | 0.70 | 0.17 | 15.87 |
2.01 | 1.42, 2.83 |
Pretest (2009) to 2011 | 0.45 | 0.12 | 14.15 |
1.57 | 1.24, 1.99 |
Pretest (2009) to 2012 | 0.32 | 0.09 | 12.00 |
1.38 | 1.15, 1.65 |
Pretest (2009) to 2013 | 0.26 | 0.07 | 12.39 |
1.30 | 1.12, 1.50 |
Drinking 5 or more times in the last 30 days | |||||
Intercept | −3.35 | 0.42 | 65.01 |
0.03 | |
Gender | 0.23 | 0.09 | 7.08 |
1.26 | 1.06, 1.49 |
Sophomore | 0.85 | 0.13 | 39.95 |
2.34 | 1.80, 3.05 |
Junior | 1.31 | 0.13 | 99.47 |
3.69 | 2.86, 4.77 |
Senior | 1.89 | 0.13 | 201.67 |
6.64 | 5.11, 8.63 |
Pretest (2009) to 2010 | 0.65 | 0.18 | 13.10 |
1.91 | 1.35, 2.72 |
Pretest (2009) to 2011 | 0.34 | 0.12 | 7.922 |
1.41 | 1.11, 1.79 |
Pretest (2009) to 2012 | 0.27 | 0.09 | 8.012 |
1.31 | 1.09, 1.58 |
Pretest (2009) to 2013 | 0.20 | 0.08 | 7.09 |
1.23 | 1.06, 1.43 |
Drinking and driving in the last year | |||||
Intercept | −6.02 | 0.55 | 119.13 |
0.00 | |
Gender | 0.40 | 0.11 | 12.43 |
1.50 | 1.20, 1.87 |
Sophomore | 1.20 | 0.24 | 25.37 |
3.33 | 2.09, 5.32 |
Junior | 1.75 | 0.23 | 58.42 |
5.73 | 3.66, 8.97 |
Senior | 2.57 | 0.22 | 133.54 |
13.11 | 8.48, 20.29 |
Pretest (2009) to 2010 | 1.09 | 0.23 | 23.56 |
2.99 | 1.92, 4.65 |
Pretest (2009) to 2011 | 0.58 | 0.15 | 14.418 |
1.78 | 1.322, 2.40 |
Pretest (2009) to 2012 | 0.46 | 0.12 | 14.93 |
1.58 | 1.25, 2.00 |
Pretest (2009) to 2013 | 0.33 | 0.10 | 12.03 |
1.40 | 1.16, 1.69 |
Lifetime marijuana use | |||||
Intercept | −4.00 | 0.43 | 87.96 | 0.02 | |
Gender | 0.19 | 0.09 | 4.56 |
1.21 | 1.02, 1.43 |
Sophomore | 0.91 | 0.14 | 40.63 |
2.48 | 1.87, 3.27 |
Junior | 1.46 | 0.14 | 112.97 |
4.30 | 3.29, 5.63 |
Senior | 2.08 | 0.14 | 221.50 |
7.97 | 6.07, 10.48 |
Pretest (2009) to 2010 | 0.81 | 0.18 | 20.07 |
2.25 | 1.58, 3.22 |
Pretest (2009) to 2011 | 0.55 | 0.12 | 19.12 |
1.73 | 1.35, 2.20 |
Pretest (2009) to 2012 | 0.37 | 0.10 | 14.75 |
1.45 | 1.20, 1.75 |
Pretest (2009) to 2013 | 0.33 | 0.08 | 18.08 |
1.39 | 1.20, 1.62 |
Marijuana in the last 30 days | |||||
Intercept | −5.74 | 0.51 | 126.30 |
0.00 | |
Gender | 0.35 | 0.11 | 10.18 |
1.41 | 1.14, 1.75 |
Sophomore | 1.04 | 0.20 | 26.67 |
2.83 | 1.91, 4.21 |
Junior | 1.39 | 0.19 | 51.12 |
4.03 | 2.75, 5.91 |
Senior | 2.26 | 0.19 | 142.67 |
9.57 | 6.60, 13.89 |
Pretest (2009) to 2010 | 1.16 | 0.21 | 30.13 |
3.18 | 2.10, 4.80 |
Pretest (2009) to 2011 | 0.77 | 0.14 | 28.14 |
2.16 | 1.62, 2.87 |
Pretest (2009) to 2012 | 0.50 | 0.11 | 19.90 |
1.65 | 1.32, 2.05 |
Pretest (2009) to 2013 | 0.34 | 0.09 | 14.28 |
1.41 | 1.18, 1.68 |
Lifetime cocaine use | |||||
Intercept | −6.53 | 0.83 | 62.27 |
0.00 | |
Gender | 0.01 | 0.18 | 0.00 | 1.01 | 0.071, 1.44 |
Sophomore | 1.11 | 0.34 | 10.54 |
3.04 | 1.55, 5.94 |
Junior | 1.00 | 0.35 | 8.39 |
2.73 | 1.38, 5.38 |
Senior | 1.84 | 0.33 | 32.18 |
6.32 | 3.34, 11.95 |
Pretest (2009) to 2010 | 1.28 | 0.35 | 13.70 |
3.59 | 1.86, 7.06 |
Pretest (2009) to 2011 | 0.86 | 0.24 | 13.07 |
2.36 | 1.48, 3.76 |
Pretest (2009) to 2012 | 0.38 | 0.18 | 4.55 |
1.46 | 1.03, 2.06 |
Pretest (2009) to 2013 | 0.36 | 0.15 | 6.13 |
1.44 | 1.08, 1.92 |
Cigarettes in the last 30 days | |||||
Intercept | −5.59 | 0.54 | 105.74 |
0.00 | |
Gender | 0.46 | 0.11 | 16.87 |
1.59 | 1.27, 1.98 |
Sophomore | 1.03 | 0.20 | 25.59 |
2.81 | 1.88, 4.18 |
Junior | 1.40 | 0.20 | 50.88 |
4.06 | 2.76, 5.97 |
Senior | 1.82 | 0.19 | 87.53 |
6.17 | 4.22, 9.04 |
Pretest (2009) to 2010 | 0.84 | 0.22 | 14.21 |
2.32 | 1.50, 3.60 |
Pretest (2009) to 2011 | 0.58 | 0.15 | 14.06 |
1.79 | 1.32, 2.42 |
Pretest (2009) to 2012 | 0.43 | 0.12 | 12.92 |
1.54 | 1.21, 1.95 |
Pretest (2009) to 2013 | 0.40 | 0.10 | 16.79 |
1.49 | 1.23, 1.81 |
Concerning other drugs, grade, gender, and years in the study contributed to the change in lifetime and current marijuana as well as cigarette use. Girls were more likely to report lifetime and current marijuana use (
Table
Logistic regression analysis of gender, grade, and subsequent study years for non-substance-use risk behaviors.
|
SE | Wald’s test ( |
Odds ratio | 95% CI | |
---|---|---|---|---|---|
Fasting in the last 30 days | |||||
Intercept | 0.30 | 0.78 | 0.14 | 1.35 | |
Gender | 0.91 | 0.17 | 29.03 |
2.49 | 1.79, 3.47 |
Sophomore | −0.22 | 0.20 | 1.27 | 0.80 | 0.55, 1.18 |
Junior | 0.53 | 0.24 | 5.00 |
1.70 | 1.07, 2.69 |
Senior | −0.08 | 0.21 | 0.13 | 0.93 | 0.61, 1.41 |
Pretest (2009) to 2010 | 0.46 | 0.35 | 1.71 | 1.59 | 0.79, 3.18 |
Pretest (2009) to 2011 | 0.34 | 0.24 | 1.97 | 1.40 | 0.86, 2.24 |
Pretest (2009) to 2012 | 0.27 | 0.18 | 2.22 | 1.32 | 0.92, 1.89 |
Pretest (2009) to 2013 | 0.19 | 0.15 | 1.67 | 1.21 | 0.91, 1.62 |
Bullied last year | |||||
Intercept | −0.47 | 0.57 | 0.66 | 0.63 | |
Gender | −0.20 | 0.11 | 3.54 | 0.82 | 0.67, 1.01 |
Sophomore | 0.02 | 0.13 | 0.01 | 1.02 | 0.78, 1.32 |
Junior | 0.56 | 0.15 | 14.31 |
1.75 | 1.31, 2.35 |
Senior | 0.59 | 0.16 | 13.92 |
1.81 | 1.32, 2.46 |
Pretest (2009) to 2010 | 1.09 | 0.26 | 17.30 |
2.97 | 1.78, 4.95 |
Pretest (2009) to 2011 | 0.69 | 0.18 | 14.90 |
1.99 | 1.40, 2.83 |
Pretest (2009) to 2012 | 0.56 | 0.14 | 16.79 |
1.75 | 1.34, 2.28 |
Pretest (2009) to 2013 | 0.38 | 0.11 | 11.79 |
1.46 | 1.18, 1.81 |
Suicide attempts last year | |||||
Intercept | −0.80 | 1.42 | 0.31 | 0.45 | |
Gender | 0.76 | 0.22 | 11.46 |
2.14 | 1.38, 3.32 |
Sophomore | 0.45 | 0.32 | 1.94 | 1.57 | 0.83, 2.95 |
Junior | 0.31 | 0.33 | 0.88 | 1.36 | 0.71, 2.61 |
Senior | 0.79 | 0.31 | 6.38 |
2.21 | 1.20, 4.10 |
Pretest (2009) to 2010 | −1.99 | 0.67 | 8.96 |
0.14 | 0.04, 0.50 |
Pretest (2009) to 2011 | −1.36 | 0.45 | 9.30 |
0.26 | 0.11, 0.61 |
Pretest (2009) to 2012 | −1.04 | 0.34 | 9.44 |
0.35 | 0.18, 0.69 |
Pretest (2009) to 2013 | −0.77 | 0.27 | 7.94 |
0.46 | 0.27, 0.79 |
Gambling last year | |||||
Intercept | −4.10 | 0.48 | 73.77 |
0.02 | |
Gender | 1.27 | 0.10 | 150.89 |
3.56 | 2.91, 4.36 |
Sophomore | 0.05 | 0.13 | 0.16 | 1.05 | 0.81, 1.37 |
Junior | 0.05 | 0.13 | 0.15 | 1.05 | 0.81, 1.37 |
Senior | −0.09 | 0.14 | 0.43 | 0.91 | 0.69, 1.21 |
Pretest (2009) to 2010 | 0.36 | 0.20 | 3.12 | 1.44 | 0.96, 2.15 |
Pretest (2009) to 2011 | 0.19 | 0.14 | 1.91 | 1.21 | 0.92, 1.60 |
Pretest (2009) to 2012 | 0.16 | 0.11 | 2.17 | 1.17 | 0.95, 1.45 |
Pretest (2009) to 2013 | 0.14 | 0.09 | 2.61 | 1.15 | 0.97, 1.37 |
Winning money back | |||||
Intercept | 6.60 | 0.81 | 66.89 |
737.67 | |
Gender | −2.29 | 0.19 | 139.17 |
0.10 | 0.07, 0.15 |
Sophomore | −0.06 | 0.19 | 0.08 | 0.95 | 0.65, 1.38 |
Junior | −0.05 | 0.19 | 0.08 | 0.95 | 0.65, 1.38 |
Senior | −0.21 | 0.19 | 1.18 | 0.81 | 0.56, 1.18 |
Pretest (2009) to 2010 | −0.20 | 0.34 | 0.35 | 0.82 | 0.42, 1.60 |
Pretest (2009) to 2011 | 0.39 | 0.21 | 3.51 | 1.47 | 0.98, 2.21 |
Pretest (2009) to 2012 | −0.17 | 0.18 | 0.94 | 0.84 | 0.59, 1.19 |
Pretest (2009) to 2013 | −0.19 | 0.14 | 1.67 | 0.83 | 0.63, 1.10 |
Pornography in the last 30 days | |||||
Intercept | −6.72 | 0.52 | 166.95 | 0.00 | |
Gender | 2.63 | 0.12 | 447.47 |
13.86 | 10.86, 17.68 |
Sophomore | 0.12 | 0.14 | 0.66 | 1.12 | 0.85, 1.49 |
Junior | 0.40 | 0.14 | 8.08 |
1.49 | 1.13, 1.96 |
Senior | 0.66 | 0.14 | 21.58 |
1.94 | 1.47, 2.57 |
Pretest (2009) to 2010 | 0.44 | 0.21 | 4.31 |
1.55 | 1.03, 2.36 |
Pretest (2009) to 2011 | 0.18 | 0.14 | 1.56 | 1.20 | 0.90, 1.59 |
Pretest (2009) to 2012 | 0.26 | 0.11 | 5.47 |
1.30 | 1.04, 1.63 |
Pretest (2009) to 2013 | 0.26 | 0.09 | 8.30 |
1.30 | 1.09, 1.56 |
Self-injury in the last year | |||||
Intercept | 2.75 | 0.59 | 21.87 |
15.67 | |
Gender | 0.53 | 0.13 | 16.47 |
1.70 | 1.31, 2.19 |
Sophomore | −0.13 | 0.18 | 0.50 | 0.88 | 0.62, 1.26 |
Junior | −0.25 | 0.18 | 2.00 | 0.78 | 0.55, 1.10 |
Senior | −0.42 | 0.18 | 5.31 |
0.66 | 0.46, 0.94 |
Pretest (2009) to 2010 | −0.57 | 0.26 | 4.91 |
0.57 | 0.34, 0.94 |
Pretest (2009) to 2011 | −0.30 | 0.17 | 2.96 | 0.74 | 0.56, 1.04 |
Pretest (2009) to 2012 | −0.27 | 0.14 | 4.00 |
0.76 | 0.58, 1.00 |
Pretest (2009) to 2013 | −0.21 | 0.11 | 3.75 |
0.81 | 0.65, 1.00 |
Sex/oral sex | |||||
Intercept | 3.36 | 0.42 | 63.40 |
28.85 | |
Gender | −0.48 | 0.09 | 30.73 |
0.62 | 0.53, 0.74 |
Sophomore | −0.90 | 0.14 | 43.94 |
0.41 | 0.31, 0.53 |
Junior | −1.55 | 0.13 | 138.41 |
0.21 | 0.16, 0.28 |
Senior | −2.12 | 0.14 | 244.32 |
0.12 | 0.09, 0.16 |
Pretest (2009) to 2010 | −0.38 | 0.18 | 4.30 |
0.69 | 0.48, 0.98 |
Pretest (2009) to 2011 | −0.24 | 0.12 | 3.72 |
0.79 | 0.62, 1.00 |
Pretest (2009) to 2012 | −0.18 | 0.10 | 3.33 | 0.84 | 0.70, 1.01 |
Pretest (2009) to 2013 | −0.15 | 0.08 | 3.67 | 0.86 | 0.74, 1.00 |
Dating violence | |||||
Intercept | 3.49 | 0.68 | 26.60 |
32.84 | |
Gender | −0.78 | 0.14 | 29.26 |
0.46 | 0.35, 0.61 |
Sophomore | −0.29 | 0.21 | 1.98 | 0.75 | 0.50, 1.12 |
Junior | −0.15 | 0.21 | 0.53 | 0.86 | 0.57, 1.30 |
Senior | −0.75 | 0.20 | 14.22 |
0.47 | 0.32, 0.70 |
Pretest (2009) to 2010 | −0.20 | 0.30 | 0.43 | 0.82 | 0.45, 1.49 |
Pretest (2009) to 2011 | 0.21 | 0.20 | 1.13 | 1.24 | 0.84, 1.83 |
Pretest (2009) to 2012 | 0.24 | 0.15 | 2.36 | 1.27 | 0.94, 1.71 |
Pretest (2009) to 2013 | 0.20 | 0.12 | 2.67 | 1.23 | 0.96, 1.57 |
Date rape | |||||
Intercept | 4.14 | 2.19 | 3.56 | 62.84 | |
Gender | −0.40 | 0.37 | 1.14 | 0.67 | 0.32, 1.39 |
Sophomore | −0.83 | 0.71 | 1.35 | 0.44 | 0.11, 1.76 |
Junior | −1.31 | 0.66 | 3.92 |
0.27 | 0.07, 0.99 |
Senior | −1.61 | 0.66 | 6.04 |
0.20 | 0.06, 0.72 |
Pretest (2009) to 2010 | 1.23 | 0.96 | 1.64 | 3.41 | 0.52, 22.30 |
Pretest (2009) to 2011 | 0.40 | 0.68 | 0.35 | 1.50 | 0.39, 5.69 |
Pretest (2009) to 2012 | 0.56 | 0.51 | 1.23 | 1.76 | 0.65, 4.78 |
Pretest (2009) to 2013 | 0.41 | 0.41 | 0.99 | 1.51 | 0.67, 3.38 |
Video game use | |||||
Intercept | −6.76 | 0.46 | 216.74 |
0.00 | |
Gender | 1.96 | 0.09 | 447.30 |
7.07 | 5.90, 8.48 |
Sophomore | −0.44 | 0.12 | 12.78 |
0.64 | 0.51, 0.82 |
Junior | −0.59 | 0.13 | 21.86 |
0.56 | 0.44, 0.71 |
Senior | −0.55 | 0.13 | 18.08 |
0.58 | 0.45, 0.74 |
Pretest (2009) to 2010 | 1.88 | 0.20 | 91.37 |
6.57 | 4.47, 9.66 |
Pretest (2009) to 2011 | 0.60 | 0.13 | 22.48 |
1.82 | 1.42, 2.33 |
Pretest (2009) to 2012 | 0.97 | 0.10 | 88.30 |
2.65 | 2.16, 3.24 |
Pretest (2009) to 2013 | 0.76 | 0.08 | 82.73 |
2.14 | 1.82, 2.52 |
Video game use for 5 or more hours | |||||
Intercept | −5.62 | 1.54 | 13.25 |
0.00 | |
Gender | 1.53 | 0.34 | 20.03 |
4.63 | 2.37, 9.05 |
Sophomore | 1.25 | 0.41 | 9.12 |
3.49 | 1.55, 7.87 |
Junior | 0.19 | 0.49 | 0.16 | 1.21 | 0.46, 3.18 |
Senior | 0.65 | 0.46 | 2.00 | 1.92 | 0.78, 4.76 |
Pretest (2009) to 2010 | −0.67 | 0.66 | 1.02 | 0.51 | 0.14, 1.88 |
Pretest (2009) to 2011 | −0.39 | 0.45 | 0.74 | 0.68 | 0.28, 1.65 |
Pretest (2009) to 2012 | −0.49 | 0.34 | 2.03 | 0.61 | 0.32, 1.20 |
Pretest (2009) to 2013 | −0.24 | 0.28 | 0.74 | 0.79 | 0.46, 1.36 |
Years in the study contributed to significant variance in bullying, pornography use, and video game use. Even though the percentage of students who reported being bullied was higher for each year of the study when compared to the Pretest Year, the odds of being bullied decreased each year from 2.97 to 1.99 to 1.75 to 1.46 (
This study set out to explore the effects of Choices, a comprehensive prevention program involving all three IOM’s categories and targeting multiple risky behaviors that adolescents struggle with today. By comparing the local to the national population that served as a quasi-experimental control group, the data indicated that, prior to the introduction of the prevention program, the local students reported relatively more of a problem with alcohol use behaviors, but relatively less of an issue with eating disorders, bullying, suicide, and sex, and comparable problems with marijuana and other drugs. These results might be a reflection of socioeconomic standing (SES). Problematic alcohol consumption has been associated with higher SES [
After 2 years of prevention programming, the local students reported significant decreases in problem drinking behaviors, marijuana, and tobacco, eating disordered behavior, suicide, and sex problems. By the fourth year of programming, the local students continued to exhibit further decreases in alcohol, drug, and other risky behaviors. Although drinking behaviors remained a major problem, the prevalence of alcohol use did not reach pretest difference levels and drinking and driving behavior maintained large decreases comparable to national data. The local population also displayed sizable significant decreases in marijuana use compared to the national students.
Internally, when comparing the local population each year of the study, 12 risky behavior variables decreased—nine statistically significantly—from pretest to Year 4. Eight of these variables were alcohol and drug related to a significant portion of the variance attributable to years in the study. Thus, Choices likely had a positive effect on reducing substance use. This is an important finding in light of the research which indicates that adolescents who start using drugs and alcohol before the age of 18 have a one-in-four chance of becoming addicted, compared with a one-in-25 chance for those who began at the age of 21 or later [
Unfortunately, the results of this study revealed inconsistent outcomes for the other non-substance-use risky behaviors targeted by the Choices program. The local population in this study reported lower incidences of non-substance-use risky behaviors than did the national population. However, during the study period, four of these variables increased, one statistically significantly. Five others displayed increases and decreases from pretest to Year 4. Thus, it is likely that the program had little effect on non-substance-use risky behaviors.
Perhaps the decreases in substance-use rates suggest that the programming dosage levels for substance-use behaviors were adequate and might have assisted in achieving the positive outcomes. In fact, the amount of substance-use programming was greater due to the school’s programming needs as indicated in the student surveys. A recent review of multiple health risk behavior prevention interventions suggests that programs that target multiple substance-use behaviors also can be effective for reducing other risky behaviors [
The preliminary results of this study demonstrate the effectiveness of a comprehensive, multiple risky behaviors prevention program for substance-use behaviors and the potential for success on non-substance-use behaviors. However, only a top-level statistical analysis was completed for this study. Future examination of such a program could be improved by utilizing a control group, comparing each year’s survey data to the previous year in addition to the Pretest Year, comparing individual student survey responses over time, utilizing a cross-sectional study design, and increasing the frequency and consistency of non-substance-use programming in addition to examining the potential mediating effects such as random drug testing initiatives, dosage levels, student maturation, and peer norms. Also, future studies should adjust for socioeconomic status (SES), previous exposure to prevention programming, ethnicity, family variables, and attrition of students. Confounding variables such as the incoming freshman and outgoing seniors should be examined for year-to-year population differences as well as those students who drop out of school and why. An additional limitation of this study includes no reliability or validity ratings for the added survey questions (e.g., pornography; gambling; self-injury; video game use; date rape) included in the modified survey instrument. This study possesses limited generalizability due to the private school student body.
To conclude, in part due to the modern technological advances of our day, students are exposed earlier in life to a broad range of potentially addictive behaviors, including eating disorders, gambling, Internet, love, sex, exercise, work, and shopping [
The authors declare that they have no competing interests.