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Annex

Annex 1. Characteristics of included studies

Annex 2. Quality assessment

Annex 3. Results of studies

Annex 1. Characteristics of included studies

Characteristics of studies

Study/Intervention(Refs)Design

Sample Content of intervention/model Providers Follow-up

A cognitive-behavioral approach to substance abuse

Botvin et al. (1990)

Cluster RCT

1311 eighth grade students from 10 suburban New York junior high schools.

N 1-yr follow-up= 998 (76%)Gender: 49% male; 51% female. Ethnicity: 13% black; 80% white; 2% hispanic; 2% oriental and 4% other

Four interventions:(1) program implemented by older peer leaders,(2) program implemented by regular classroom teachers,(3) program with booster sessions implemented by older peer leaders,(4) program with booster sessions implemented by regular classroom teachers.The booster sessions were given during the eight grade and were conducted by older (10th, 11 th, and 12th grade) peer leaders for the students in condition 3; the booster sessions were implemented by regular classroom teachers in condition 4. No other intervention activities were conducted for students in conditions 1, 2, and 5 (control condition). The intervention in this study is a multi-component substance abuse prevention curriculum designed to focus on the major social, psychological, cognitive, and attitudinal factors which appear to promote the use of tobacco, alcohol, and marijuana. The 20-session program, delivered in 7th grade, focuses on the consequences of substance use and its social acceptability, decision-making, resisting social influences to engage in substance use, self-directed behavior change, cognitive-behavioral techniques for coping with anxiety, communication skills, general interpersonal skills, and assertiveness. The booster curriculum, delivered in 8th grade was designed to reinforce the material contained in the 20-session substance abuse prevention program previously implemented with these students during the seventh grade.

Peers (peer leaders from 10th, 11th and 12th grade) and regular classroom teachers. There was no difference between teacher-led and peer-led prevention programs, Both the peer leaders and teachers received a 4 hour training workshop, conducted by the members of the project staff. Peer leaders participated in a series of briefing sessions which provided them with more specific preparation for each upcoming session.

One-year follow-up.





A school-based alcohol education intervention

Morgenstern et al. (2008)

Cluster RCT

1875 seventh grade students from thirty schools in Schleswig-Holstein, a Bundesland (state) of Germany,Baseline: Gender: 51,8 % male; 48,2 % femaleMean age: 13,0 years

The program consisted of four specified class units, a booklet for students and a parent booklet. The materials were designed for students under the age of 16 years. The main message of the materials was ‘no alcohol for minors’ and the intervention focused on addressing social influences and enhancing motivation to avoid substance use. Each teaching unit had a standard structure that included a schedule, an overarching theme, the main objectives and a list of ‘hands-on’ materials. Instructions for working interactively were described for each teaching unit.

Teachers of 7th grade students implemented the intervention. In the run-up to the implementation teachers received a 3-hour workshop introducing the underlying concepts and materials for the intervention and demonstrating potential realizations in the class.

Data were collected in three waves: (i) prior to the start of the intervention in February 2006 (Baseline); (ii) shortlyafter the intervention in May/June 2006 (post-test); and (iii) 1 year after the start of the intervention in February 2007 (follow-up).







Life Skills Training and Timewise combined

Ferrer-Wreder et al. (2010)

quasi-experimentalage-cohort design

715 students from a northeastern American city ranging in age from 11–16 years old (M = 12).

Gender: 45% male; 54% female; 1% missing.Ethnicity: 64% Black; 13% ‘‘Other’’ ethnic identifier; 10% Hispanic; 4% American Indian; 3% White; 2% Asian; 4% missing.

Life skills Training (LST): is a universal school-based drug prevention program that is designed for elementary and middle school students. LST is grounded in social learning, communication, and problem behavior theories. LST consists of activities designed to help youth learn how to say no when tempted to engage in substance use and aims to help youth learn to make good decisions, set goals for themselves, and realize the impact of their behaviors Further, LST consists of activities aimed at improving general social skills. Other LST targets for change include identity development, problem solving or decision-making, interpersonal relationships, physical health maintenance, and correcting normative expectations about substance use. Taking Charge of Leisure Time (Timewise): is a universal school-based health promotion intervention that is designed to educate youth about how to use their leisure time in healthy ways. TimeWise’s core lessons focus on helping students to (a) determine personally satisfying and meaningful leisure activities and interests, (b) understand the benefits of participating in healthy leisure, (c) understand how one’s motivation affects one’s experience and participation in healthy behaviors, (d) alleviate boredom and increase optimal experience in leisure time, (e) learn how to take responsible action to participate in desired activities, and (f) identify and overcome constraints that get in the way of participation in desired activities. TimeWise focuses largely on health promotion rather than risk reduction. It specifically targets the reduction of drug use in leisure time by helping youth better understand the connection between their leisure time and development. In TimeWise, youth learn that what they do in their leisure time and why they do it may lead to either positive or negative forms of development, including substance use and abuse.

Teachers whom were trained in LST and Timewise. Teachers had a two-day on-site LST training by National Health Promotion Associates and a one-day on-site TimeWise training by the intervention’s developer. Intervention training and programmatic lessons/ activities were not integrated but rather occurred or were implemented sequentially (e.g., LST then TimeWise).

Intervention participants were exposed to LST and TimeWise as 6th graders and then surveyed as they entered the 7th grade. A non-intervention-exposed cohort of 7th graders in the same school district was surveyed the previous fall.



Study/Intervention(Refs)Design Sample Content of intervention/model Providers Follow-up

Project ALERT

Clark et al. (2011); Ringwalt et al. (2010)

Cluster RCT1

7,742 sixth-grade students from 34 schools, which represented 21 school districts located in California, Idaho, Indiana, Kansas, New Jersey, New Mexico, North Carolina, South Carolina, Texas, Virginia, and Washington.

N 1-yr follow-up= 4940 (64%)Baseline:Gender: 49% male, 51% femaleEthnicity2: 52% Caucasian; 16% African American; 27% Hispanic.

Project ALERT, a 2-year manualized classroom-based substance use prevention curriculum which targets cigarette, alcohol, marijuana, and inhalant use. 11 lessons are given during 6th grade and three during 7th grade. Project ALERT’s lessons were designed to fit within 45-minute class periods. The lessons stress motivating nonuse, identifying internal and external pressures to use drugs and practicing skills to resist those pressures, and identifying the benefits of nonuse. Two of the lessons cover inhalant abuse and smoking cessation specifically. Activities include guided class discussions, small group activities, role-playing exercises, and videos. These activities address a variety of putative mediators, including resistance self-efficacy, perceived consequences of use, normative perceptions about peer use and acceptance, and expectations of future use. Students in the control condition did not receive any evidence-based substance use prevention program nor did they receive project ALERT.

Instructors completed training at the study’s expense, either online (n=43) or at an in-person workshop (n=28). Forty-four teachers and one counselor administered the core curriculum to sixth graders in the treatment schools, and 43 teachers and one counselor administered the curriculum’s booster lessons to seventh graders the followingyear. Of these, 18 teachers facilitated both the core and booster lessons.

Measures were taken before implementation in the sixth grade, after the seventh grade booster lessons and 1 year later (follow-up).

1 This study is based on a RCT, but whether or not certain schools were included was dependent on a number of criteria.2 The total percentage of ethnicity is not 100, nevertheless these numbers are reported in the article.



Project ALERT

St. Pierre et al. (2005)

Cluster RCT

1,649 7th-grade students from eight Pennsylvania middle schools in suburban, urban, and rural locations. Schools varied in socioeconomic level: the percentage of students eligible for free/reduced lunch ranged from a low of 10% of students in one suburban school to a high of 60% in one urban school.

N 1-yr follow-up = 1196 (72,5 %) Gender: 50.5% male; 49,5% femaleEthnicity: 81.4% Caucasian; 5.4% African American; 2.2% Native American; 1.3% Hispanic; 1.1% Asian American and 8.5% “other”.

The revised Project ALERT delivered contains 11 lessons offered weekly in 7th grade, , and 3 lessons in 8th grade. The new lessons emphasize smoking cessation skills, consequences of alcohol misuse, alternatives to drinking, and consequences of inhalant use. The two experimental conditions consisted of an adult-led Project ALERT condition and an adult-led, teen-assisted Project ALERT condition. For classrooms in the adult-led teen-assisted condition, teen leaders assisted with program delivery for 5 of the 11 7th-grade lessons.

Penn State Cooperative Extension (CE) Educators hired qualified adults in the community, who had experience with youth programs and who related well to young people, as adult program leaders. Over the course of the study, twelve female Caucasian program leaders taught the program. All had work or volunteer experience with young people. Adult program leaders received the same training that classroom teachers normally receive from Project ALERT’s professional training through the BEST Foundation. For classrooms in the adult-led teen-assisted condition, teen leaders assisted with program delivery for 5 of the 11 7th-grade lessons. In collaboration with middle schools, local high schools selected teen leaders from grades 10–12. They participated in a 1-day training conducted by the researchers, CE Educators and adult program leaders.

A pretest before program implementation in 7th grade, followed by posttests after the 7th-grade curriculum, and before and after the 8th-grade curriculum. An additional follow-up posttest was administered one year after program delivery when students were in 9th grade.

Study(Refs)Design


Reconnecting Youth

Hallfors et al. (2006) ; Cho et al. (2005)

RCT

1370 high-risk 9th to 11th grade students, recruited from 9 high schools in 2 large urban school districts in the United States. One school district was located in a large city in the Southwest (site A) and the other in a large metropolis on the Pacific coast (site B).

Gender: 49% male; 51% female.

Site A: Ethnicity: 87% Hispanic; 9% Black; 4% White; 4%

The intervention is an "indicated" drug abuse prevention program and consists of a 1 -semester class with the objective of improving academic achievement, preventing or reducing illegal drug use, and improving mood management. The intervention was offered during regular school hours and included 55 core lessons and 24 booster lessons focusing on 4 main themes: self-esteem, decision making, personal control, and interpersonal communication. Students monitored their school attendance, academic achievement, drug use, and moods, and set personal goals in each of these areas. Students practiced skills related to the 4 main themes and their goals and also practiced giving and receiving positive social support.

Teachers were either regular classroom teachers or school health personnel (2 of the 36 classes were taught on contract by recently retired high school teachers). All RY teachers completed an intensive 4-day training session, conducted by certified RY trainers. The principal investigator and two doctoral-level research site coordinators completed one or more of these intensive teacher trainings; site coordinators

Measures were gathered at 3 time points: at student invitation, at the end of the next semester and at the end of the following semester (follow-up).

Annex 2. Quality assessment

Methodological quality of studies

Botvin et al. (1990)

A) Selection bias Q1 1Motivation Every adolescent participated in the drug prevention curriculum.Q2 5Motivation NR1

Rating selection bias Moderate

1 NR: Not reported

Study(Refs)Design


Toward No Drug Abuse (TND) and TND network

Valente et al. (2007)

Cluster RCT

938 students from 14 continuation high schools in southern California.

N 1-yr follow-up = 594 (63%). Baseline: Average age = 16,3Average grade = 10,6Gender: 62% male; 38 % female Ethnicity: 72% Hispanic/Latino; 6% African-American; 11% white and11% other.

TND focuses on motivation, skills and decision making. Although TND addresses the social environment, it devotes only minimal attention to re-norming and does not instruct refusal skill training, hallmarks of social influence programs. TND uses a school-based, lesson delivery model consisting of 12 lessons. Each lesson is designed to teach specific cognitive, motivational or behavioral skills that can lead to reductions in substance use. In the present study, the TND curriculum was modified to increase the number of group activities and tocreate small groups (three to five students) composed of their own social network members. In addition, each group was led by a peer leader chosen by their peers. The traditional form of TND has interactive discussions led by a health educator or a trained classroom teacher conducted at the classroom level whereas the modified version, TND Network, encourages small-group discussions in groups created from naturally occurring friendships and led by a student-chosen leader.

Sixteen health educators were trained by program staff to teach TND and TND Network. In many cases the same teachers taught both curricula. Prior to the start of the TND network, peer leaders were identified using social network nominations. Peer leaders were taught how to facilitate group discussion, how to manage group interaction and encouraged to embrace antisubstance use norms. Normative restructuring about drug use was an essential part of the peer leader training. In addition, a manual was developed for health educators to use in the training.

Measures were gathered at baseline and at one-year follow-up.

B) Study Design Study Design 1Motivation The participating schools were randomly assigned to the different

conditions.Was the study described as randomized yesIf yes, was the method of randomization described noMotivation NRIf yes, was the method of randomization appropriate?MotivationRating study design Weak

C) Confounders Q1 3Motivation NRQ2 4Motivation NRRating Confounders Weak

D) Blindings Q1 3Motivation NRQ2 3Motivation NRRating Blindings Moderate

Botvin et al. (1990) (continued)

E) Data collection methods Q1 3Motivation NRQ2 3Motivation NRRating Data collection methods Weak

F) Withdrawals and Dropouts Q1 2Motivation Number of dropouts were mentioned, but no reasons were given.Q2 2Motivation 998 of the original sample of 1311 students were available for

follow-up (76%).

Rating Withdrawals and drop-outs ModerateG) Intervention integrity Q1 1

Motivation Every student received the allocated intervention.Q2 1Motivation Observations by field staff indicated that the intervention was

implemented with alow degree of fidelity by many teachers.

Q3 4Motivation Because of the low degree of fidelity, there's a risk that the

subjects received an unintended intervention.H) Analyses Q1 Organization/institution

Motivation Every participating school was assigned to a condition.Q2 Organization/institutionMotivation In the analyses of the results, the different conditions were

compared to each other and thus the schools were compared to each other.

Q3 3Motivation NRQ4 3Motivation NR

Clark et al. (2011); Ringwalt et al. (2010)

A) Selection bias Q1 1Motivation Study participants comprised all sixth graders in recruited schools,

with the exception of students in self contained classrooms and those who did not attend classes on campus (e.g., were home schooled).

Q2 2Motivation At baseline, 7,742 students were eligible for participation. Ninety-

two percent of students (n=7,147) returned parental consent forms with 78% of eligible students receiving consent for participation (n=6,040).

Rating selection bias ModerateB) Study Design Study Design 1

Motivation Schools were randomly assigned to either an intervention or control condition, blocked by school district.

Was the study described as randomized YesIf yes, was the method of randomization described NoMotivation NRIf yes, was the method of randomization appropriate?MotivationRating study design Weak

C) Confounders Q1 2Motivation We did not find any evidence of statistically significant

differences between the intervention and control group in regard to variables related either to students (gender, race, or ethnicity) or schools (urbanicity, FRPL, the semester in which baseline data were collected, or AYP status).

Q2MotivationRating Confounders Strong

Clark et al. (2011); Ringwalt et al. (2010) (continued)

D) Blindings Q1 2Motivation Each survey was identified only by a unique code number that had

been previously assigned by the project office, which maintained exclusive possession of the link to their names.

Q2 3Motivation NRRating Blindings Moderate

E) Data collection methods Q1 3Motivation NR: Students completed an 81-item self-report questionnaire

that has been used in previous evaluations of Project

ALERT.Q2 3Motivation NRRating Data collection methods Weak

F) Withdrawals and Dropouts Q1 2Motivation Number of dropouts were mentioned, but no reasons were given.Q2 1Motivation 4940 of the original sample of 6040 students completed the survey

at follow-up (81,8%).Rating Withdrawals and drop-outs Strong

G) Intervention integrity Q1 1Motivation Attendance records and classroom observations indicate that at

least 97% of the total number of Project ALERT’s lessons were taught.

Q2 1Motivation We examined several measures to determine the extent to which

Project ALERT was implemented with fidelity.Q3 5Motivation Results indicated that instructors adequately implemented the

lessons.

Clark et al. (2011); Ringwalt et al. (2010) (continued)

H) Analyses Q1 Organization/institutionMotivation We employed a randomized controlled trial that used school as the

unit of assignment.Q2 Organization/institutionMotivation Schools making AYP and schools not making AYP were

compared (Clark et al., 2011).

Schools assigned to the control condition or the experimental condition, were compared to each other (Ringwalt et al., 2010).

Q3 1

Motivation Analyses were performed using hierarchical nonlinear modeling (HNLM), which assumes that substance use outcomes had a Bernoulli distribution (Ringwalt et al., 2010).

The two sets of three-way interactions provided the appropriate tests for examining whether Project ALERT had a differential effect on substance use that was a function of AYP status (Clark et al., 2011).

Q4 3Motivation NR


A) Selection bias Q1 4Motivation NRQ2 5Motivation NRRating selection bias Weak

B) Study Design Study Design 7: quasi-experimentalage-cohort design

Motivation This effectiveness trial used a quasi-experimental age-cohort design.

Was the study described as randomized NoIf yes, was the method of randomization describedMotivationIf yes, was the method of randomization appropriate?MotivationRating study design Moderate

C) Confounders Q1 2Motivation Two Pearson chi-square tests (Intervention vs. Comparison Group

on gender and ethnicity) and an independent samples t test (Intervention vs. Comparison on age) showed no statistically significant differences between the Intervention (n = 250) and Comparison Groups (n = 465) on key demographic variables.


D) Blindings Q1 3Motivation NRQ2 3Motivation NRRating Blindings Moderate

Ferrer-Wreder et al. (2010) (continued)

E) Data collection methods Q1 3Motivation NRQ2 2Motivation Another limitation involved the less-than-ideal internal

consistency of selected scales. For example, the Lifetime and Recent Drug Use Scales as well as the Assertiveness and Anxiety Management Skills Scales had alphas ranging from .52 to .64.

Rating Data collection methods WeakF) Withdrawals and Dropouts Q1 2

Motivation Number of dropouts were mentioned, but no reasons were given.Q2 2Motivation The loss of intervention participants when process data was linked

to outcome data was 37%.Rating Withdrawals and drop-outs Moderate

G) Intervention integrity Q1 2Motivation When process data were merged with student survey responses by

ID number, there was a 37% loss of intervention participants with 63% of the sample was retained (i.e., 433 sixth-grade students should have been exposed to the interventions and dosage information was linked to 271 students; 63% of the sample was retained).

Q2 1Motivation In the present trial, implementation was indexed by dosage (i.e.,

the quantity of program exposure). Dosage was operationalized as the amount of curriculum covered by intervention teachers and the number of prevention lessons attended by students.

Q3 4Motivation The only measure for the consistency of the intervention

mentioned, was the dosage of the intervention.

Ferrer-Wreder et al. (2010) (continued)

H) Analyses Q1 Organization/institutionMotivation Gradelevel

cohort was the unit of assignment in this study.Q2 Organization/institutionMotivation The first set of analyses conducted did not account for dosage

(i.e., an ‘‘intention to treat’’-type analysis approach). In these models, Group was specified as the fixed factor (Intervention, Comparison).

Q3 1Motivation The researchers employed multilevel modeling to examine the

effect of the interventions while accounting for the clustering of individual students within schools as well as within classrooms/teachers. Outcome analyses were conducted with and without regard to dosage to highlight the level of variability found across analyses as well as to demonstrate what may be gained from dosage information.

Q4 1Motivation The first set of analyses conducted did not account for dosage

(i.e., an ‘‘intention to treat’’-type analysis approach). In these models, Group was specified as the fixed factor (Intervention, Comparison). In the second set of analyses, Dosage was specified as a series of four dummy coded variables.


A) Selection bias Q1 1Motivation Study participants were randomly selected from each school's pool

of students identified as being at high risk for school dropout.Q2 5Motivation NRRating selection bias Moderate

B) Study Design Study Design 1Motivation Participants were randomly assigned.Was the study described as randomized YesIf yes, was the method of randomization described NoMotivation NRIf yes, was the method of randomization appropriate?MotivationRating study design Weak

C) Confounders Q1 1Motivation Attendance was lower and smoking was higher in the

experimental group than in the control group. Students in the on-treatment group had lower personal control than those in the control group and were younger.

Q2 1Motivation Analysis of covariance was used to evaluate program effect with

control for the outcome value at time 1, as well as for gender, grade and school.

Rating Confounders StrongD) Blindings Q1 2

Motivation HSQ was administered in an audio computer-assisted interview format.


Hallfors et al. (2006) ; Cho et al. (2005) (continued)

E) Data collection methods Q1 1Motivation The High School Questionnaire (HSQ) is a three-part instrument

developed and validated by Leona Eggert and colleagues, multi-item scales have demonstrated reliability and validity in both the efficacy trial and the present effectiveness trial.

Q2 1Motivation HSQ multi-item scales have demonstrated reliability and validity

in both the efficacy trial and the present effectiveness trial.Rating Data collection methods Strong

F) Withdrawals and Dropouts Q1 1Motivation A total of 1220 students completed the HSQ at time 2 and 1178

completed at time 3, yielding an overall attrition rate of 10,9% and 14,0%, respectively. The main reasons for experimental protocol noncompliance were a move from the school, class schedule conflicts, or counselor refusal to place the student in an elective class because the student was behind in core credits.

Q2 1Motivation At time 3, 1178 of 1370 students completed the HSQ (86%).Rating Withdrawals and drop-outs Strong

G) Intervention integrity Q1 3Motivation Attendance was less than 50%.Q2 1Motivation Multiple instruments, adapted from the developers’ tools, were

used to evaluate implementation via classroom observation, teacher documentation, and student feedback. Each RY class was observed four times each semester (without notice to the teacher) to assess the quality of the RY lesson. Evaluators and on-site coordinators provided RY teachers with feedback based on these observations; additional supervision and support were provided at regular monthly meetings.

Hallfors et al. (2006) ; Cho et al. (2005) (continued)

G) Intervention integrity Motivation Teachers maintained daily lesson logs to track the number of lessons taught, the time spent on skill development, and their assessment of students’ reaction to the lesson.

Q3 5Motivation Across schools, the implementation dose (i.e., the number of

lessons delivered) was high and the quality was acceptable (data not shown).

Q1 IndividualH) Analyses Motivation Individuals, not schools, were the unit of analysis. Students were

randomly selected from each school’s pool of those at high risk for school dropout.

Q2 IndividualMotivation The intervention group was compared with the control group.Q3 1Motivation Group equivalence was evaluated using time 1 demographic and

outcome variables. Outcome changes before and after the intervention were then compared between all experimental and control students (intent-to-treat approach), and then just the students who attended 50% or more of the Reconnecting Youth class and control students (on-treatment approach). Analysis of covariance (ANCOVA) was used to evaluate program effect with control for the outcome value at time 1, as well as for gender and grade. Furthermore, they also controlled for differences across schools by including school as a fixed factor in the ANCOVA models.

Q4 1Motivation Outcome changes before and after were compared between all

experimental and control students.

Hansen & Graham (1991)

A) Selection bias Q1 4Motivation 12 junior high schools in Los Angeles and Orange Counties,

California, were recruited to participate in the study. Prior todelivery of the program, seventh-grade students and parents gave informed consent.

Q2 5Motivation There was no information concerning the number of participants

who agreed to participate.Rating selection bias Weak

B) Study Design Study Design 1Motivation Schools were stratified by size, test scores, and ethnic composition

and then randomly assigned to receive one of four intervention programs


C) Confounders Q1 3Motivation NRQ2 4Motivation Pretest scores associated with post-test variables were used as

covariates.Rating Confounders Weak

D) Blindings Q1 2Motivation Students were identified only by coded number.Q2 3Motivation NRRating Blindings Moderate

Hansen & Graham (1991) (continued)

E) Data collection methods Q1 3Motivation Validity of self-reports was not expected to vary by condition.Q2 1Motivation For the alcohol index, Cronbach α‘s were 0.84 for seventh grade

and 0.86 for eighth-grade reports. For the marijuana index, α‘s were 0.58 and 0.60 for seventh- and eighth-grade measures, respectively. For tobacco use at seventh and eighth grades, α’s were 0.81 and 0.87.

Rating Data collection methods WeakF) Withdrawals and Dropouts Q1 1

Motivation Of the total sample (N = 3,011) who were pretested, 2,135 (70.9%) were located and post-tested in program schools. An additional 77 students who were absent at the time of testing subsequently completed the survey when they returned to school. Of those not located in the program schools, 204 were successfully contacted either at their new schools (N = 188) or at home (N = 16). Thus, 80.2% of eligible students (N = 2,416) were successfully tracked and tested. Of the 595 subjects who did not participate in repeated measurement, 330 (11 .0%) were located but were excluded because of personal or parental decline at the post-test or because they failed to return informed consent at the post-test. The remainder were absent without completed survey (N = 37), had moved from schools involved in the study and could not be located (N = 123), or did not return mailed follow-up surveys (N = 105).

Q2 1Motivation Thus, 80.2% of eligible students (N = 2,416) were successfully

tracked and tested.Rating Withdrawals and drop-outs Strong

Hansen & Graham (1991) (continued)

G) Intervention integrity Q1 4Motivation NR, only differences between conditions in attrition rate were

reported.Q2 2Motivation NRQ3 6Motivation NR

H) Analyses Q1 Organization/institutionMotivation Schools were the unit of assignment.Q2 ClassroomMotivation Classroom of program delivery was selected as the unit of

analysis.Q3 1Motivation A general linear model analysis of covariance approach was used

with classroom means for each composite index and for each dichotomous item. Analyses tested for main effects of Resistance Training (Resistance Training and Combined programs vs Information and Normative Education programs) and Normative Education (Normative Education and Combined programs vs Information and Resistance Training programs) and for interactions between the two programs. Pretest scores associated with post-test variables were used as covariates.

Q4 2Motivation The unit of analysis was classroom, while schools were the unit of

allocation.


A) Selection bias Q1 2Motivation Thirty schools with 81 7th grade classes and 1875 students agreed

to participate in the study. One hundred and fifty-seven students (8.4%) were excluded in advance, as they did not provide parental written permission for participation; 32 students (1.7%) were absent on the day of the baseline survey, resulting in a final sample at baseline of 1686 students.

Q2 1Motivation Letters were sent to 106 secondary schools in Schleswig-Holstein

and thirty schools agreed to participate (28,3 %). One hundred and fifty-seven students (8.4%) in these schools did not provide parental written permission for participation.


Motivation After consenting to study participation, schools were assigned randomly to the experimental (intervention) or the control arm with stratification for type of school.

Was the study described as randomized YesIf yes, was the method of randomization described YesMotivation Schools were sorted by type of school and then assigned to two

groups by drawing lots.If yes, was the method of randomization appropriate?

Yes

Motivation The allocating person was blind to the meaning of group number and the purpose of the study.

Rating study design Strong

Morgenstern et al. (2008) (continued)

C) Confounders Q1 1Motivation Compared to the control group, students of the intervention group

more often reported life-time experience with smoking and current smoking. Intervention students also reported more alcohol use of their social environment and had more smoking friends; furthermore, they had higher average values on the rebelliousness scale and fewer correct items in the alcohol quiz.

Q2 1Motivation Baseline differences in covariates were controlled for by including

these variables into the model. Covariate measures were derived from studies that focus on risk factors of adolescent alcohol use, so we were able to control for variables that are related relevantly to the primary outcome measures.


Motivation Data were collected through self-completed questionnaires, administered by trained research staff. To permit a linking of individual information on subsequent surveys each questionnaire was labelled with a seven-digit individual code generated bythe student, a procedure that had been tested in previous studies.


E) Data collection methods Q1 1Motivation We also used the ‘Evaluation Instruments Bank’ (EIB, which is an

online archive of freely available instruments for evaluating drug-related interventions.) for the selection of our measures (http://eib. emcdda.europa.eu/).


E) Data collection methods Motivation The website of the European Monitoring Centre for Drugs and Drug Addiction stated that the syntheses of evidence published in the best practice portal are mainly based on the Cochrane systematic reviews of evidence and that they are a source of evidence for the World Health Organisation's Health Evidence Network (HEN).

E) Data collection methods Q2 1Motivation We also used the ‘Evaluation Instruments Bank’ (EIB, which is an

online archive of freely available instruments for evaluating drug-related interventions.) for the selection of our measures (http://eib. emcdda.europa.eu/).

Rating Data collection methods StrongF) Withdrawals and Dropouts Q1 1

Motivation Experimental group:-lost to post test: 40 students (absent)-lost to follow-up: 85 students (absent, changed school)Control group:-lost to post-test: 32 students (absent)-lost to follow-up: 96 students (absent, changed school)

Q2 1Motivation The follow-up assessment was completed by 1433 students

(85%).Rating Withdrawals and drop-outs Strong

G) Intervention integrity Q1 1Motivation Dropout was not related to condition (15.1% in the control, 14.9%

in the intervention group, P = 0.902),Q2 2Motivation Although teachers were asked to document

implementation, we have little information about implementationfidelity in each class.

Q3 6Motivation There's too little information about the implementation.


H) Analyses Q1 organization/institutionMotivation After consenting to study

participation, schools were assigned randomly to theexperimental (intervention) or the control arm withstratification for type of school.

Q2 organization/institutionMotivation The effects of the intervention were

tested with generalized linear latent and mixed models.Q3 1Motivation Outcome variables,

i.e. alcohol-related measures, were regressed on group(treatment versus control) with a random effect forschool, as students were nested within schools. Baselinedifferences in covariates were controlled for by includingthese variables into the model.

Q4 1Motivation The intention-to-treat

analyses involved all students who completed the baselineassessment (n = 1686).

St. Pierre et al. (2005)

A) Selection bias Q1 1Motivation Participants were two consecutive student cohorts at eight

Pennsylvania middle schools.Q2 5Motivation NRRating selection bias Moderate

B) Study Design Study Design 1Motivation Each of the eight schools randomly assigned two 7th-grade

classrooms to each of three conditions.Was the study described as randomized YesIf yes, was the method of randomization described NoMotivation NRIf yes, was the method of randomization appropriate?MotivationRating study design Weak

C) Confounders Q1 2Motivation There was satisfactory evidence of equivalence among the

treatment and control conditions at the pretest. Preliminary analyses indicated only one difference nominally significant at the .05 level for Cohort 1. For Cohort 2, however, a more consistent pattern of differences emerged. Site-specific analyses revealed that most of the Cohort 2 differences resulted from two sites, which were therefore removed from further analyses. After eliminating these sites, only three nominally significant differences remained, no more than would be expected by chance.


St. Pierre et al. (2005) (continued)

D) Blindings Q1 2Motivation Each student’s questionnaire contained a personalized

identification number for linking data across testing waves. Students were told that the sealed envelopes would be sent to the university and their responses scanned into a computer with everyone else’s answers.



F) Withdrawals and Dropouts Q1 2Motivation Percentage of dropout was given, but no reasons were given.Q2 2Motivation 72.5% completed the questionnaires on all five waves.Rating Withdrawals and drop-outs Moderate

G) Intervention integrity Q1 4Motivation NRQ2 1Motivation The authors analyzed several measures of implementation.Q3 5Motivation Results indicated that Project ALERT was implemented with high

quality both years. In addition, student ratings on reaction forms after each program year indicated high quality implementation

St. Pierre et al. (2005) (continued)

H) Analyses Q1 ClassroomMotivation Each of the eight schools randomly assigned two 7th-grade

classrooms to each of three conditions.Q2 ClassroomMotivation The treatment and control condition were compared to each other.

We address the remaining dependence through a three-level hierarchical linear model with waves of data as Level 1, individual students as Level 2, and classrooms as Level 3.

Q3 1Motivation A three-level hierarchical lineair model with waves of data as

Level 1, individual students as Level 2, and classrooms as Level 3 was used. In addition, the statistical analysis included six other control variables: gender, family structure, race/ethnicity, self-reported grade point average, parents’ education and parental supervision.

Q4 2Motivation Site-specific analyses revealed that most of the Cohort 2

differences resulted from two sites, which were therefore removed from further analyses.

Valente et al. (2007)

A) Selection bias Q1 2Motivation 25 continuation high school districts were contacted to participate

in the study and 17 did not participate for various reasons.Q2 2Motivation 8 of 25 high school districts agreed to participate. Thereafter, 1493

students were invited to participate with 980 providing valid consent and assent forms (65.6%)


Motivation Of the eight districts used for thestudy, one served as a pilot location and the remainingseven provided classrooms that could be assigned randomlyto one of three conditions: control (prevention asusual), TND and TND Network.


C) Confounders Q1 1Motivation There were no differences on any study variables between

conditions, with the following exceptions. Participants in TND Network were at a slightly lower grade and those in TND and TND Network made fewer network nominations than those in the control condition. Peer use was also different between study conditions such that it was lowest in TND Network compared to TND and the control group.

Q2 1

Valente et al. (2007) (continued)

C) Confounders Motivation The authors regressed current use of each substance and the composite score at 1-year follow-up on baseline use and included the demographic (age, grade in school, gender, mother’s education level and ethnicity) and network (network size, social support and peer use) control variables. Furthermore, all regression analyses controlled for within classroom clustering by specifying school as the clustering variable.


Motivation NRQ2 3Motivation NRRating Blindings Moderate


F) Withdrawals and Dropouts Q1 2Motivation Number of dropouts were mentioned, but no reasons were given.Q2 2Motivation Of these 938, 344 were lost to follow-up, yielding a 1-year

retention rate of 63.3%Rating Withdrawals and drop-outs Moderate

G) Intervention integrity Q1 1Motivation Of the 980, 29 students were not interviewed at baseline because

they were absent on multiple visits and 13 neglected to report data on their substance use behavior.

Q2 2Motivation NR

Valente et al. (2007) (continued)

G) Intervention integrity Q3 6Motivation There's little information about the implementation of the

intervention programs.H) Analyses Q1 Classroom

Motivation 75 classes were randomized to a condition.Q2 IndividualMotivation They regressed current use of each substance and the composite

score at 1-year follow-up on baseline use and included the demographic and network control variables.

Q3 1Motivation This lagged regression model included dummy variables for TND

and TND Network to test for intervention effects. In addition to individual substances, they created a composite substance use variable by standardizing the four monthly use variables and calculating the average. All regression analyses controlled for within classroom clustering by specifying school as the clustering variable. This multi-level model helps control for the greater covariation within schools relative to thatbetween schools.

Q4 3Motivation NR

Annex 3. Results of studies

Results of studies

Intervention Authors and year Outcomes significant negative effects


Botvin et al. (1990) Self-reported smoking, drinking, and marijuana use behaviors. Cognitive, attitudinal, and personality measures.

Substance use behavior:-Alcohol use:The control group had significantly fewer drinkers based on the monthly measure (mean control group = ,38 ; mean teacher booster group = ,55 ; p < 0.0001), the weekly measure (mean control group = ,20; mean teacher booster group = ,33 ; p < 0.001), and had a lower score on the drinking frequency index (mean control group = 2,03 ; mean teacher booster group = 2,32 ; p < 0.0002).Mediating variables:-Main effects: The teacher-led booster condition had significantly lower (more positive) drinking attitudes ( mean teacher booster group = 38,36 ; mean control group = 39,60 ; p < 0.04) and marijuana use attitudes ( mean teacher booster group = 43,39 ; mean control group = 45,20 ; p < 0.02) than the control condition.

Intervention Authors and year Comments General conclusion


Botvin et al. (1990) There was a fidelity check, which indicated that there was a low degree of fidelity by many teachers. Additional analyses were conducted to determine the effectiveness of the intervention when implemented by teachers with a reasonable degree of fidelity. In the analyses of the restricted sample, which consisted of 145 eighth graders at the one-year follow-up, there were no iatrogenic effect.

The results of this follow-up study provide support for the efficacy of this type of substance abuse prevention approach. The peer-led conditions were more effective than the teacher-led conditions both in terms of substance use behavior and in terms of impacting on the cognitive, attitudinal, and personality mediating variables. Moreover, where prevention effects were found, the booster condition was superior to the non-booster condition. In fact, the peer-led booster condition was not only the most effective condition with respect to the mediating variables, but was the only condition to produce significant behavioral results. Nonetheless, the teacher booster group appeared to produce iatrogenic effects in terms of alcohol use, more positive drinking and marijuana use attitudes.

Authors and year Comments General conclusion

I Authors and year

type of outcome measures

significant negative effects

AMorgenstern et al. (2008)

Student self-report measures included (i) dem

Programme effects:Changes in alcohol-related knowledge, attitudes and intentions:

Intervention

A school-based alcohol education intervention.


The iatrogenic effect mentioned was not stable considering that, on the follow-up assessment, the mean overall attitude index of the two groups were similar again (mean Intervention = 1.31 versus mean Control = 1.29).

During data collection, teachers of all classes were requested to remain seated at the front desk to emphasize confidentiality of responses and facilitate honest reporting of alcohol use. After completion of the survey, questionnaires were placed into an envelope and sealed in front of the class. Students were assured that their individual information would not be seen by parents or school administrators.

Covariate measures were derived from studies that focus on risk factors of adolescent alcohol use, so we were able to control for variables that are related relevantly to the primary outcome measures.

Analyses showed evidence of intervention–control differences in alcohol-related knowledge and in the initiation of binge drinking. These effects were detected at post-test as well as the 12-month follow-up assessment, after controlling for baseline covariate differences. The intervention yielded only little effect on students’ attitudes towards alcohol use or on self-reported future use and refusal intentions. Students from the interventiongroup showed lower levels of negative alcohol-related attitudes at post-test, a difference that was not detectable at baseline; however, this opposite effect was no longer seen at the 1-year follow-up and therefore doesnot seem to be a stable phenomenon. We found no group effect on past-month alcohol use and on the initiation of alcohol use without parental knowledge, indicating that the programme was more successful in reducing the initiation of problematic alcohol use than in reducing or stabilizing the frequency of already users or in delaying first experiences with alcohol. No group differences in life-time drunkenness might be due to the more subjective nature of this item compared to the binge drinking item.

Intervention Authors and year type of outcome measures significant negative effects



Measures were gathered through use of a self-report survey (demographics, drug use, LST-related scales, Timewise-related scales and dosage).

No Dosage versus Dosage Outcome Analyses—Family 1: Drug UseThere was a significant result on one group contract, namely the Comparison versus the LST Mixed Group (β = 0.09, t = 2.26, p < .05). The mean difference indicated that the Mixed Group was elevated on Lifetime Drug Use relative to the Comparison Group.

No Dosage versus Dosage Outcome Analyses—Family 2: LST-Related OutcomesAnalyses without dosage information showed that the Comparison Group reported better drug refusal skills than the Intervention Group (β = -,36 ; t = 2,33 ; p = 0, 053).




The present study was embedded in a larger four-year, school-district-wide Safe Schools Healthy Students (SSHS) initiative. SSHS is a series of interventions designed to improve social emotional learning and academic achievement and reduce school dropout. Interventions were predominately

Two empirically supported interventions, LST and Time- Wise, were implemented in a school-based effectiveness trial context. Across the analyses, with and without dosage information, intervention-related benefits were found on anxiety management skills as well as external and introjected motivations relative to a Comparison Group. When considering dosage information only, the findings expand to

implemented by grade level, and no other SSHS interventions were implemented with the participants in this trial.

include program related benefits on assertiveness skills and drug use intentions. There was an observed iatrogenic finding for drug refusal skills. In this case, the Comparison Group reported better drug refusal skills than the Intervention Group. Contrasts by dosage group indicated that the LST Hi Group was the group that reported the improvements relative to the Comparison Group. The LST_TW Hi Group had lower reported drug use intentions than the Comparison Group. The LST Mixed Group was elevated on lifetime ATOD relative to the Comparison Group. Intervention-related benefits tended to be found when the paired (i.e., LST_TW) and stand alone (i.e., LST Only) interventions were implemented with a moderate-to-high level of dosage. Another finding was that the LST Groups (Hi and Mixed) showed a program-related benefit on a TimeWise-related outcome (the External Motivation scale).


Project ALERT Clark et al. (2011) Self-report questionnaires were used in order to measure use of cigarettes, alcohol, marijuana, and inhalants. Intentions to use, number of times offered a substance, race and ethnicity were also measured using the same questionnaire. Dichotomous data

AYP as a moderator:-The differential effect of Project ALERT on lifetime marijuana use reflected a slight iatrogenic program effect in schools that were making AYP (significant ALERT × AYP × quadratic three-way interaction for lifetime marijuana use; r = -0,02; p < 0,05). More specifically, among students in schools that made AYP, students in control schools that received

concerning each school’s AYP status as of their first school year in this study was collected from state or school district websites. In addition, data was obtained from the 2004-2005 Common Core of Data (U.S. Department of Education, n.d.) on schools’ urbanicity (urban, suburban, or rural) and the percentage of students at each school who received free or reduced price lunch (FRPL), a proxy for low socioeconomic status.

Project ALERT exhibited similar trajectories from the pretest to the first posttest, but those who received Project ALERT showed a steeper increase in lifetime marijuana use from the first to the second posttest.-The pattern for 30-day alcohol use of students who received Project ALERT in non-AYP schools was significantly different from the pattern of the control group (significant ALERT × AYP × quadratic three-way interaction for 30-day alcohol use; r = .02; p < 0,05). That is, students in intervention schools, whom were not making AYP, increased their 30-day alcohol use between the two posttests more than did students in the control schools (also non-AYP).


Project ALERT Clark et al. (2011) All schools received financial incentives for each year they participated in the study, and for returning parental consent forms when 90% of their active consent forms were returned, regardless of whether parents provided or withheld consent.

The purpose of this exploratory study, conducted within the context of a randomized controlled effectiveness trial, was to determine if Project ALERT showed meaningful effects on adolescents’ lifetime and 30-day substance use in schools meeting AYP.This study found significant three-way interactions for two of eight outcomes tested, which provided some support for their hypothesis; however, the magnitude of

The authors did not randomly assign schools to condition based on their AYP status; therefore, they considered their study to be exploratory.

Students completed an 81-item self-report questionnaire that has been used in previous evaluations of Project ALERT.

Their data analysis was thoroughly elaborate.

the effects was very small. In non-AYP schools, it appeared that students who received Project ALERT had poorer outcomes on measures of lifetime cigarette use and 30-day alcohol use than those in the control group. The trajectory of the control group departed from that of the other groups, which suggested that Project ALERT had a negative and iatrogenic effect in schools that were not making AYP. Additionally, adherence was assessed using an ex post facto analysis, a common way to measure fidelity, in the intervention schools. The results of a three-level random-intercept hierarchical linear model, in which lessons were nested within teachers and teachers within schools, suggested that there was no difference in adherence as a function of AYP status (t(15) = –.80, p = .44). Therefore, it seems unlikely that a lack of fidelity in non-AYP schools was to blame. Furthermore, Project ALERT had a significant negative effect, albeit of very small magnitude, on lifetime marijuana use in schools that made AYP.


Project ALERT Ringwalt et al. (2010) Self-report questionnaires in order to measure use of cigarettes, alcohol, marijuana, and inhalants. Intentions to use, number of times offered a substance, race and ethnicity were also measured using the same questionnaire. . School-level covariates included schools’ urbanicity

Ex Post Facto Analyses:Differential Program Effects by Mode of Teacher Training:Students taught by teachers trained in person for the booster lessons manifested higher lifetime marijuana and inhalant use, as well as higher 30-day alcohol and inhalant use, at the time of the second posttest (no data was given in the article).

(urban, suburban, or rural) and the percentage of students at each school receiving free and reduced price lunch (FRPL), both obtained from the 2004–2005 Common Core of Data (U.S. Department of Education n.d.).


Project ALERT Ringwalt et al. (2010) Eligible for participation in the study were all public schools in the U.S. that: housed at least grades 6 through 8, were not currently delivering any evidence-based substance use prevention programs to students in any of these grades, comprised at least 100 students per grade, and committed themselves to including all their sixth grade

Findings from the initial posttest, which followed the conclusion of the 2-year program, demonstrated a positive effect on 30-day alcohol use but none on the other seven substance use-related outcomes targeted. Analyses of data yielded by surveys that were administered to students 1 year later, as eighth graders, revealed that this finding did not persist. The authors continued to find no effects for lifetime alcohol use and both the lifetime and 30-day use of cigarettes, marijuana,

students.

To facilitate their school recruitment, the authors promised schools $500 for each year that it participated in thestudy, and an additional $1,000 if it was assigned to the control group and thus did not receive Project ALERT. Additionally, participating teachers were also given a monetary reward if they recorded the Project ALERT lessons they taught.

Study participants comprised all sixth graders in recruited schools, with the exception of students in selfcontained classrooms and those who did not attend classes on campus (e.g., were home schooled).

Implementation analysis and data analysis were thoroughly elaborated.

and inhalants. Their tests of moderation also failed to yield convincing evidence of differential program effects related to schools’ AYP and FRPL status and urbanicity, and students’ race, ethnicity, and gender. Their analysis of the more proximal effects of the program on its mediators also yielded no support for the program, which may constitute the primary reason for their failure to find effects on substance use behavior. On the other hand, analyses of the effects of the mediators on students’ behavioral intentions, and of intentions (in turn) on their substance use behaviors, provided abundant support for ALERT’s conceptual theory.


Project ALERT St. Pierre et al. (2005) Data was gathered through use of a self-report questionnaire on substance use, mediating variables for substance use,demographic variables, indicators of use and cognitive mediators.

Program Impact on Substance UseHLM analyses:The only estimates of program effects that reach the standard .05 level of statistical significance correspond to harmful effects on past year marijuana use for the teen-assisted version of the program and the combination of both versions. The logistic coefficient of .914 for the teen-assisted version would correspond to a 149% greater increase in the odds of

past year marijuana use for students receiving that version of the program, relative to the increase between the pretest and posttests for students in the control condition. The logistic coefficient of the combined treatment is .624.More generals test for program effects:These are multiple parameter Wald tests for the interactions of treatment condition with the three time contrast terms. The only significant result from these 21 tests reflects the same negative impact of the teen-assisted version of the program on past year marijuana use.Program Impact on MediatorsOnly one contrast between the pretest and the combined posttests reached statistical significance, and again it indicated a harmful effect: compared to the control group, expectations of future marijuana use were higher among participants in the teen-assisted version of the program.


Project ALERT St. Pierre et al. (2005) Attrition was very low across the five waves of data collection. Furthermore, attrition was comparable across the three conditions, with students in the control condition completing a mean of 4.51 waves, students in the adult-led condition, 4.43 waves, and students in the teen-assisted condition, 4.54 waves (F=1.94, p=.14).

Results of this independent effectiveness study of Project ALERT failed to yield any positive effects for substance use or mediators for use in the adult or teen-assisted delivery of the curriculum. Furthermore, an extensive set of additional analyses detected no differential program effects by student risk level, gender, school, or implementation quality. Moreover, it appears that the outcomes were not due to the differences in research design, sample size, and/or data analysis approaches. Given the adequacy of statistical power,

The HLM analyses was elaborated, but not all data was given in the article.

Similarly, the implementation analyses was also elaborate.

the rigor of their data analysis approach, the comparability of study conditions at baseline, and replication of analyses employed in the South Dakota study, which confirm their results, they are confident that findings were not due to deficiencies in these areas. Because their study did not compare outcomes for types of implementers, they cannot conclude that failure to detect positive effects was due to implementation by outside program leaders.


Reconnecting Youth


All measures were self-reported (achievement and attendance, substance use, problem behaviors, peer affiliation patterns, student connection to school and demographic variables), except academic performance variables of grade point average and truancy, which were obtained through school records.

Immediately after the intervention, there was a negative main program effect on anger (Anger: Experimental group: adjusted mean = 1,39 ; Control group: Adjusted mean = 1,22 ; p = 0,01) and on conventional peer bonding (Experimental group: mean = 1,86 ; Control group: mean = 1,89; p = 0,048). One school-by-group interaction effects was found (perceived family support: Experimental group: Adjusted mean = 1,58 ; Control group: Adjusted mean = 1,61 ; p = 0,02). For perceived family

support, 3 schools showed positive program effects and 6 schools showed negative effects. At the 6-month follow-up, negative main program effects were found on conventional peer bonding (Experimental group: Adjusted mean = 1,78 ; Control group : Adjusted mean = 1,87 ; p = 0,02), high-risk peer bonding group (Experimental group: Adjusted mean = 1,76 ; Control group : Adjusted mean = 1,62 ; p = 0,01), prosocial weekend activities (Experimental group: Adjusted mean = 3,87 ; Control group : Adjusted mean = 4,23 ; p = 0,01), GPA (Experimental group: mean = 1,93; Control group: mean = 2,01; p = 0,063), anger (Experimental group: mean = 1,16; Control group = 1,11; p = 0,058) and school connectedness (Experimental group: mean = 13,13; Control group: mean = 13,45; p = 0,06). Furthermore, at the 6 month follow-up, there was also a school-by-group interaction effect (School connectedness : Experimental group: Adjusted mean = 13,46 ; Control group : Adjusted mean = 13,41 ; p = 0,04). Four schools showed positive effects and 5 schools showed negative effects.


Reconnecting Youth


Across both sites, 47% of students assigned to the experimental group attended at least 50% of Reconnecting Youth classes. The main reasons for experimental protocol noncompliance were a move from the school, class schedule conflicts, or counselor refusal to place the student in an elective class because the student was behind in core

Findings from the Reconnecting Youth treatment effectiveness trial failed to replicate positive findings from the efficacy trial. Immediately after the intervention, intent-to-treat analyses showed no significant main effects, but 1 school-by-group interaction effect. Moreover, Reconnecting Youth failed to meet the requirement to do more good than harm. By the second follow-up period, the experimental group had worse outcomes than the control group on conventional peer bonding,

credits.Another 6% (n=43) enrolled in the class but attendance was less than 50%.

Compared with those who remained in the study, dropouts were more likely to be male and riskier by indicators such as lower GPA and school attendance; higher depression; cmd higher cigarette and marijuana use. However, no significant differences were found when we compared dropouts from the experimental, and control groups at eithertime point.

The study of Cho et al. (2005) covers data from the 2002-2003 trial, while the study of Hallfors et al. (2006) covers data from the 2002-2004 trial. However, it is not clear whether or not the study of Cho et al. (2005) is embedded in the study of Hallfors et al. (2006). Most of the sections in the articles are similar, but not all of them are.

high-risk peer bonding, and prosocial weekend activities. The effectiveness trial also uncovered a number of difficulties with implementing a semester-long course for high-school youths at risk for dropout. First, school guidance counselors hesitated—and sometimes refused—to enroll such youths in an elective course because of their need to fulfill core credit courses or obtain academic remediation. High-risk youths tend to he very mobile, changing schools, dropping out for periods, or attending altemative schools. Thus, despite strenuous efforts by research and school staff, less than half the students assigned to the experimental group were actually exposed to a substantial portion of the intervention.Given the low compliance with the intervention, on-treatment analyses were conducted to examine if there were any additional positive effects among students who actually attended the class. Instead, immediate posttreatment analyses showed worse anger outcomes for intervention students than for control students. There were no other main effects, but significant differences by school in perceived family support and smoking. At the 6-month follow-up, the experimental group had worse outcomes than the control group on high-risk peer bonding and prosocial weekend activities. In no case was the experimental group better off than the control group, and school differences appeared only for school connectedness.


Resistance skill training, normative education and both resistance skill training and normative


Measures of substance use and problem behavior were gathered through use of a survey.

Programmatic outcomes:An examination of the least-squares means suggests that the Resistance Training program was least effective in preventing the onset of marijuana use. Furthermore, the interaction between Normative Education and Resistance Training (interpreted by examining least-squares means) was the result of the Combined program being superior to allother programs and the Resistance Training Only program

education. being inferior. Additionally, the Resistance Training Only program was least effective at preventing onset of marijuana use.


Resistance skill training, normative education and both resistance skill training and normative education.


No data concerning the least square means was given.

There were main effects of normative education for summary measures of alcohol (P = 0.0011), marijuana (P = 0.0096), and cigarette smoking (P = 0.0311). All individual dichotomous measures of alcohol, marijuana, and tobacco use indicated significant reductions in onset attributable to normative education. There were no significant main effects ofresistance skill training.



Valente et al. (2007) Measures were gathered through use of surveys (substance use, demographics, network size, social support and social network data).

Predictors of change in current use:-The interaction of peer use and being in the network condition was associated with increases in marijuana (b = 0.34; 95% CI, 0.10, 0.58; P < 0.05), cocaine (b = 0.28, 95% CI: 0.05, 0.51; P < 0.05) and composite substance use (b = 0.19; 95% CI, 0.10, 0.28; P < 0.01).Conditional effects:-Peer use was associated with increased substance use (total

composite) in the network condition (b = 0.17, 95% CI: 0.08, 0.26; P < 0.01). Thus, in the TND Network condition, as peer use increases change in substance useincreases.



Valente et al. (2007) The authors acknowledged that health promotion programs may have negative or unanticipated consequences. Therefore they also evaluated the prevention program for possible iatrogenic effects.

There were no differences on any variables between the participants retained in the study

Results showed that TND Network was associated with monthly reductions in current use of marijuana, cocaine and a composite at 1-year follow-up when an interaction term composed of peer use and being in the TND Network condition was included. The TND Network curriculum was able to achieve relatively longterm behavioral effects on marijuana and cocaine use and on a composite use index when all substances were considered together. The reduced

and those lost to follow-up. substance use came at the expense of increasing use among some students with existing networks of substance-using peers. Substance use was reduced mainly for those students who nominated as friends other students who reported low levels of substance use. If a student received the network curriculum and had friends in the class who reported using substances, he/she was likely to increase his/her substance-using behaviors over the 1-year interval. Thus, the Network curriculum seemed to achieve its goal of increasing peer influence yet that peer influence, in the context of an alternative high school, was potentially negative for adolescents with drug-using friends.

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