Preventing Negative Behaviors Among Elementary-School ...people.oregonstate.edu/~flayb/MY PUBLICATIONS/Positive Action/Snyder etal13 SECD...The present study examines the effects of

Social Health; Emotional Health; Youth

Preventing Negative Behaviors Among Elementary-SchoolStudents Through Enhancing Students’ Social-Emotional andCharacter DevelopmentFrank J. Snyder, PhD, MPH; Alan C. Acock, PhD; Samuel Vuchinich, PhD; Michael W. Beets, PhD,MPH, MEd; Isaac J. Washburn, PhD; Brian R. Flay, DPhil

Abstract

Purpose. Examine the effects of a comprehensive, school-wide social-emotional and characterdevelopment program using a positive youth development perspective. Specifically, we examined amediation mechanism whereby positive academic-related behaviors mediated the intervention effects onsubstance use, violence, and sexual activity.

Design. Matched-pair, cluster-randomized, controlled design.

Setting. Twenty (10 intervention and 10 control) racially/ethnically diverse schools in Hawaii.

Subjects. Elementary-aged students (N ¼ 1784) from grade 5.

Intervention. The Positive Action program.

Measures. Students self-reported their academic behaviors, together with their substance use, violence,and voluntary sexual activity; teachers rated students’ academic behaviors, substance use, and violence.

Analysis. Structural equation modeling.

Results. Students attending intervention schools reported significantly better academic behavior (B ¼.273, SE ¼ .039, p , .001) and significantly less substance use (B ¼�.970, SE ¼ .292, p , .01,incidence-rate ratio [IRR]¼ .379), violence (B¼�1.410, SE¼ .296, p , .001, IRR¼ .244), and sexualactivity (B¼�2.415, SE¼ .608, p , .001, odds ratio¼ .089); boys reported more negative behaviors thangirls. Intervention effects on student-reported substance use, violence, and sexual activity were mediated bypositive academic behavior. Teacher reports corroborated these results, with rated academic behaviorpartially mediating the effects of the intervention on rated negative behaviors.

Conclusion. This study (1) provides evidence that adds insight into one mechanism through which asocial-emotional and character development program affects negative outcomes and (2) supports social-emotional and character development and positive youth development perspectives that posit that focusingon youths’ assets may reduce negative behaviors. (Am J Health Promot 2013;28[1]:50–58.)

Key Words: School-Based Prevention, Randomized Trial, Social-Emotional and CharacterDevelopment, Positive Youth Development, Mediation, Prevention Research. Manuscriptformat: research; Research purpose: intervention testing/program evaluation; Study design:randomized trial; Outcome measure: behavioral; Setting: school; Health focus: intellectualhealth; Strategy: skill building/behavior change; Target population age: youth; Targetpopulation circumstances: education/income level, geographic location, race/ethnicity

INTRODUCTION

Negative behaviors among youth,such as substance use, violence, andsexual activity, continue to be notablepublic health concerns in the UnitedStates.1 In an endeavor to reduce thesebehaviors, the positive youth develop-ment (PYD) perspective focuses on thestrengths of youth and their positivebehaviors.2,3 The perspective hasgained acceptance among researchers,practitioners, and policy makers, andinvolves viewing youth as resources tobe developed.4 For optimal personalgrowth, youth require access to envi-ronments that enhance their develop-ment, such as positive and safe schoolsettings that increase school involve-ment and motivation to learn academ-ic and life skills.

Recent decades have also seen anincrease in social-emotional and char-acter development (SECD),5 whichseeks to foster an improvement innumerous behavioral domains, such asprosocial skills, self-control, and aca-demic achievement, and correspond-

Frank J. Snyder, PhD, MPH, is with the Division of Prevention and Community Research, Department of Psychiatry, Yale University School ofMedicine, New Haven, Connecticut. Alan C. Acock, PhD; Samuel Vuchinich, PhD; and Brian R. Flay, DPhil, are with the School of Social andBehavioral Health Science, College of Public Health and Human Sciences, Oregon State University, Corvallis, Oregon. Michael W. Beets, PhD,MPH, MEd, is with the Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina.Isaac J. Washburn, PhD, is with the Oregon Social Learning Center, Eugene, Oregon.

Send reprint requests to Frank J. Snyder, PhD, MPH, Division of Prevention and Community Research, Department of Psychiatry, Yale UniversitySchool of Medicine, 389 Whitney Avenue, New Haven, CT 06517, [email protected]; or Brian R. Flay, DPhil, School of Social and BehavioralHealth Sciences, College of Public Health and Human Sciences, Oregon State University, 457 Waldo Hall, Corvallis, OR 97331, [email protected].

This manuscript was submitted April 19, 2012; revisions were requested July 6 and September 2, 2012; the manuscript was accepted for publication September 28, 2012.

Copyright � 2013 by American Journal of Health Promotion, Inc.0890-1171/13/$5.00 þ 0DOI: 10.4278/ajhp.120419-QUAN-207.2

50 American Journal of Health Promotion September/October 2013, Vol. 28, No. 1

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ing reductions in negative behaviors.These programs are often compre-hensive (i.e., involve students, teachers,whole schools, families, and commu-nities), attempt to bolster youths’positive behaviors, and have beenshown to improve multiple indicatorsof SECD6 and reduce negative behav-iors when implemented comprehen-sively and with fidelity.7,8

PurposeWe do not fully understand the

mechanisms through which PYD orSECD efforts affect youth outcomes,and the content of PYD- and SECD-related programs often overlaps con-siderably. The present study examinesthe effects of one example of aprogram—the Positive Action (PA)program—that reflects both the PYDand SECD perspectives. The presentstudy builds upon recent research9 thatreported the effects of PA on reducingsubstance use, violent behaviors, andsexual activity among elementary-school students (using data from thesame randomized trial). The purposeof the present study is to examine amechanism through which the PAintervention worked and, specifically, ifbolstering positive behavior—which isthe primary concentration of manyPYD/SECD programs, including PA—mediated the intervention effects onreducing substance use, violence, andsexual activity. Based on the PYD andSECD perspectives, and the theoryunderlying the PA program that in-cludes a link between increased posi-tive behavior and reduced negativebehavior,10 we hypothesized that (1)student self-reports and teacher re-ports on students attending PA inter-vention schools would reflectsignificantly more positive academicbehaviors (ABs) as compared to thosestudents attending control schools and(2) positive AB would partially orcompletely mediate the effect of the PAintervention on substance use, violentbehaviors, and voluntary sexual activity.

Although previous research has useda mediation analysis to find that SECD-related skills (e.g., I follow school rules,I listen to my parents) mediated the PAprogram’s effects on substance use,11

the present study is the first to examinea mechanism whereby positive ABsmediate the effect of PA on violence

and sexual activity as well as substanceuse. The program seeks to achieve thisby focusing on developing positivebehaviors, without instructional timedevoted to negative behaviors. Forexample, although substance use andviolence behaviors (harassment, bully-ing, fighting, etc.) are mentioned, theyare used only as example behaviors(sexual activity is never mentioned). Todate, scant research has examinedmechanisms regarding how PYD/SECD-related interventions, with theirfocus on development of children’sassets, can reduce negative behav-iors.11–14

Prior PA StudiesPrevious research has shown PA to

positively influence school quality,15

school-level outcomes related to aca-demic achievement, absenteeism, anddisciplinary measures,16–18 student-lev-el positive behaviors associated withcharacter,11,19 and student substanceuse, violent behavior, and sexual activ-ity.9,11,20 More specifically, using datafrom the Hawaii randomized trialdescribed herein, Beets and col-leagues9 showed that a small minorityof the participating elementary-agedchildren engaged in negative behav-iors, but those students who receivedthe PA intervention had significantlylower substance use, violent behaviors,and voluntary sexual activity. However,a mediation mechanism has not yetbeen explored using the Hawaii ran-domized trial data.

METHODS

Description of the PA Program and theHawaii Trial

The PA program (http://www.positiveaction.net) is a comprehensive,school-wide PYD/SECD program de-signed to positively influence multiplebehavioral domains such as studentacademic achievement and substanceuse. First developed in 1977 andrevised since then, the program isgrounded in a broad theory of self-concept,21–23 and is consistent withintegrative, ecological theories ofhealth behavior such as the theory oftriadic influence.24,25 The programposits a theoretical link between posi-tive and negative behaviors, whereby afocus on positive actions leads to a

cycle of positive outcomes and, there-fore, a reduction in negative behav-iors.10

The full PA program consists of K-12classroom curricula, of which theelementary curriculum was used in thistrial; a school-wide climate develop-ment component, including teacher/staff training by the developer, a PAcoordinator’s (principal’s) manual,school counselor’s program, and PAcoordinator/committee guide; andfamily- and community-involvementprograms. The family-involvementprogram is available in various levelsand is designed for parents to use athome to promote the core elements ofthe classroom curriculum; it reinforcesschool-wide positive actions. This trialdid not include the more intensivefamily component or the community-development component.

The sequenced elementary curricu-lum consists of 140 lessons per gradeper academic year, offered in 15- to 20-minute lessons by classroom teachers.Lessons cover six major units on topicsrelated to self-concept (i.e., the rela-tionship of thoughts, feelings, andactions), physical and intellectual ac-tions (e.g., nutrition, physical activity,learning skills, decision-making skills,creative thinking), social/emotionalactions for managing oneself responsi-bly (e.g., self-control, time manage-ment), getting along with others (e.g.,empathy, altruism, respect, conflictresolution), being honest with yourselfand others (e.g., self-honesty, integrity,self-appraisal), and continuous self-improvement (e.g., goal setting, prob-lem solving, persistence). The class-room curricula utilize an interactiveapproach, whereby interaction be-tween teacher and student is encour-aged through the use of structureddiscussions and activities, and interac-tion between students is encouragedthrough, for example, structured orsemistructured small group activities,including games, role plays, and prac-tice of skills.

The school-climate kit coordinatesschool-wide implementation and con-sists of materials to encourage andreinforce the six units of PA, anddirects the use of materials such asposters, music, tokens, and certificates.It also includes information on plan-ning and conducting assemblies, cre-

American Journal of Health Promotion September/October 2013, Vol. 28, No. 1 51


ating a PA newsletter, and establishinga PA committee that typically includesa school-level PA coordinator, a leadteacher from each grade, a parentrepresentative, and a student repre-sentative. Additionally, a counselor’sprogram, implemented by schoolcounselors, focuses on developingpositive actions with students at higherrisk and their classrooms, families, andthe school as a whole.

Prior to the beginning of eachacademic year, teachers, administra-tors, and support staff (e.g., counsel-ors) attended PA program trainingsessions conducted by the programdeveloper. The training sessions lastedapproximately 3 to 4 hours in theinitial year, and 1 to 2 hours thefollowing years. Booster sessions, con-ducted by a project coordinator andlasting approximately 30 to 50 minutes,were provided an average of once peracademic year for each school andintended to increase implementationfidelity.

Several measures of fidelity of im-plementation were collected duringthe PA Hawaii trial and are describedin more detail elsewhere.18,26 Resultsshowed that there was some variabilityin implementation between interven-tion schools, with slight gains acrossyears. Although implementation wasgood for each indicator, results showedthat PA intervention schools couldhave implemented the program withgreater fidelity. Additionally, controlschools reported devoting instruction-al time for SECD-related activities andimplemented more SECD-related pro-grams (other than PA) than interven-tion schools.

DesignThe PA Hawaii trial was a matched-

pair, cluster-randomized, controlledtrial, conducted in Hawaii elementaryschools during the 2002–2003 through2005–2006 school years, and is de-scribed in detail elsewhere.9,18 Thestate is one large school district withdiverse ethnic groups and a recognizedneed for improvement (i.e., low stan-dardized test scores and a high per-centage of students receiving free orreduced-price lunch). The trial tookplace in 20 public elementary (K-fifthor K-sixth) schools (10 matched pairs)on three Hawaiian islands, and stu-

dents began the intervention in thefirst or second grade and received theprogram for 4 to 5 years. To ensurecomparability of the intervention andcontrol schools with respect to baselinemeasures, archival school report carddata were used to stratify schools intostrata ranked on an index risk scorebased on demographic variables.27–29

Schools were randomly selected fromwithin strata and randomly assigned tointervention or control conditions be-fore recruitment. Intervention schoolswere offered the complete PA programfree of charge and control schools wereoffered a monetary incentive duringthe randomized trial and the PAprogram upon completion of the trial.At baseline, intervention and controlschools were similar on matchingindicators (Table 1). The HawaiiSchool Board and the institutionalreview boards (IRBs) at the Universityof Illinois and Oregon State Universityapproved the trial methods.

SampleBecause of school board and IRB

requirements, students must have en-tered grade 5 to become eligible toanswer questions related to substanceuse, violent behaviors, and voluntarysexual activity; thus, data from the finalwave of the longitudinal study wereutilized in the present research. Thetrial used a cluster-focused intent-to-treat approach,30 whereby data werecollected from all schools assigned toconditions and we surveyed studentswho entered study schools during thetrial and did not follow those who left.After students entered grade 5 theywere asked to procure active parentalconsent and give verbal assent torespond to 11 items querying aboutsubstance use (five items), violentbehavior (five items), and sexual activ-ity (one item). Among treatment andcontrol schools, nearly 1800 students(50% female) gained permission toparticipate, a consent rate of over 85%.The final sample of students’ self-identified ethnicity was primarily Ha-waiian or part Hawaiian (26.1%) orthey reported multiple ethnic back-grounds (22.6%). The others self-identified as white non-Hispanic(8.6%), African American (1.6%), Na-tive American (1.7%), other PacificIslander (4.7%), Japanese (4.6%),

other Asian (20.6%), other (7.8%),and unknown (1.6%).

Differential selection bias was as-sessed to compare students whoseparents provided active consent andstudents who did not receive consent,with no significant (p � .05) differ-ences observed between the twogroups.9 To determine whether stu-dents who dropped out of the studywere different at baseline from thosewho remained in the study afterbaseline, demographic characteristics(e.g., ethnicity and gender) were ana-lyzed for intervention and controlgroups separately. Further, interven-tion- and control-group students whodropped out of the study after baselinewere compared. Additionally, at year 5,control-group students were assessedto examine whether those control-group students who were surveyed ateach the 5 years were significantlydifferent from those control-groupstudents who entered the study afterbaseline. No significant differenceswere found for these analyses.9

Measures

Academic Behavior. Student Self-Reports.In grade 5, AB was measured by fiveexperimenter-developed items to assessstudent involvement in school andmotivation to learn. Grade 5 studentswere asked how much of the time they(1) work hard in school, (2) set goals,(3) manage time wisely, (4) try to betheir best, and (5) solve problems well,and to respond on a scale of 1 to 4 (1¼none of the time, 2¼ some of the time,3 ¼most of the time, 4¼ all of thetime). The a was .725. In a principalcomponent (PC) analysis, all five itemsloaded over .660 on the first PC andthis component explained 48.4% ofthe variance in the set of items. Thesefive items relating to AB were chosenfor the reported analysis because theywere answered by both students andteachers.

Teacher Reports of Student Behavior.Teachers were asked to rate how welleach of the five aforementioned itemsdescribed the student and to respondon a scale of 1 to 3 (1 ¼ not at all, 2¼moderately well, 3 ¼ very well). All ofthe items loaded at least .766 on thefirst PC, and this component explained64.8% of the variance in the item set (a¼ .863).



Negative Behaviors. Student Self-Reports.Fifth-grade respondents answered sur-vey questions adapted from Monitor-ing the Future31 and the Aban AyaYouth Project.28 Questions were askedregarding lifetime substance use (fiveitems [a ¼ .856]: smoked a cigarette,drank alcohol, gotten drunk on alco-hol, used an illegal drug like marijuanaor cocaine, gotten high on drugs),violent behaviors (five items [a¼ .794]:carried a knife or razor to use to hurtsomeone, threatened to cut or stabsomeone, cut or stabbed someone onpurpose to hurt them, carried a gun,shot at someone), and one itemquerying voluntary sexual activity (i.e.,voluntary sex with someone of theopposite gender). Students were askedto respond on a scale of 0 to 2 (0¼ no,never; 1¼ yes, once; and 2¼ yes, morethan once). A PC analysis revealed thatthe substance use and violent behavioritems loaded at least .741 and .646,respectively, on their first PC, and thecomponent explained 73.7% and59.9% of the variance in the item sets,respectively. Because of the small oc-

currence of the affirmative ratings,each of the 11 items was dichotomized(0 ¼ no, never; 1 ¼ ever) and, for thesubstance use and violent behaviorindicators, items were summed togenerate a count variable (0–5) re-flecting how many of the five behaviorsthe student had ever performed. Re-search has shown that self-reports ofsubstance use and violent behavior canprovide valid measures of studentbehavior.32–36 Additionally, researchindicates that the prevalence of grade 5student self-reported negative behav-iors was similar to rates reported inother studies.28

Teacher Reports of Student Behavior.Teachers of grade 5 students wereasked to rate how well each of threesubstance use–related items (a ¼ .803;smokes or may smoke cigarettes or usesother forms of tobacco, drinks or maydrink alcohol, uses drugs like marijua-na or cocaine) and four violent be-havior–related items (a ¼ .804; getsinto a lot of fights, physically hurtsothers, threatens others, destroysthings belonging to others) described

the student and to respond on a scaleof 1 to 3 (1¼ not at all, 2¼moderatelywell, 3 ¼ very well). A PC analysisshowed that the substance use andviolent behavior items loaded at least.789 and .626, respectively, on theirfirst PC, and the component explained75.1% and 63.1% of the variance in theitem sets, respectively. As with thestudent items, the affirmative ratings oftwo and three items were combinedand each item was dichotomized (0 ¼does not describe child at all, or 1 ¼describes child well) and, in turn, theitems were summed to generate acount of substance use (0–3) andobserved violent behavior (0–4).

Analytic StrategyTo test for mediation, we used a

framework described by Baron andKenny,37 MacKinnon,38 and MacKin-non et al.39,40 Figure 1 displays a simplemodel (Model 1) relating an indepen-dent variable (X) to a dependentvariable (Y) and a traditional media-tion model (Model 2) where themediator (M) mediates the effect of Xon Y. Model 1 estimates the bivariateeffect (c) without the mediator includ-ed in the model.

Model 2 simultaneously estimatesthe direct effect (c0) of X on Y (with themediator in the model) and theindirect effect (ab), which comprisesthe effect of X on M (a) and the effectof M on Y (b).38 Mediation can beclassified into one of three categories:(1) complete mediation, when the path-way from intervention X to outcome Yis significantly mediated by M, with nosignificant direct effect from X to Yremaining; (2) partial mediation, whenthe pathway from X to Y is significantlymediated by M, with a significant, butreduced, direct effect remaining fromX to Y; and (3) nonsignificant mediation,when mediation was tested for andfound to be nonsignificant.37,40 In thepresent study, we hypothesized thatboth the student and teacher modelswould demonstrate partial or completemediation.

Using structural equation modeling(SEM; performed with Mplus v5.1), aconceptual model (Figure 2) wasspecified based on the hypothesis thatthe latent construct, AB, mediated theeffect of the PA intervention on theobserved negative-outcome variables.

Table 1Characteristics of Study Schools at Baseline*

2002 (Baseline)

Control Positive Action

Mean SD Mean SD p†

Enrollment 478.80 207.06 609.40 330.07 0.303

Racial/ethnic distribution, %

African-American 1.79 3.20 1.66 2.03 0.915

Chinese 2.05 3.66 1.88 2.75 0.908

Filipino 11.61 14.20 15.83 9.75 0.449

Hawaiian 5.61 5.98 5.74 4.16 0.956

Hispanic 2.45 2.35 3.28 3.11 0.510

Indochinese 2.02 5.62 0.34 0.69 0.361

Japanese 4.26 3.57 6.50 6.16 0.333

Korean 1.19 2.12 1.71 3.50 0.692

Native American 0.44 0.37 0.47 0.47 0.876

Part Hawaiian 31.86 28.37 28.81 21.61 0.790

Portuguese 1.41 1.94 1.99 1.77 0.494

Samoan 3.11 4.83 5.23 8.78 0.512

White 17.52 18.05 13.05 10.81 0.510

Other 14.69 14.01 13.48 8.61 0.879

Stability, % 90.82 2.36 91.71 3.18 0.487

Free/reduced lunch, % 54.32 26.40 59.78 22.95 0.628

Limited English proficiency, % 11.83 15.30 15.58 14.10 0.576

Special education, % 10.56 5.41 9.76 2.99 0.687

* Adapted from Snyder et al., 2010.18

† 2-tailed t-test; 18 df.



Student and teacher data were utilizedindependently to fit two separate con-ceptual models (n.b., the sexual activityvariable is not included in the teachermodel). Because of the age of thestudents and seriousness of the out-comes, the distributions of responseswere skewed for the count outcomes(student-reported: substance use x ¼.30, SD ¼ .91, skewness ¼ 3.8, violentbehaviors x¼ .22, SD¼ .78, skewness¼4.4; teacher-reported: substance use x¼ .28, SD¼ .74, skewness¼ 2.7, violentbehaviors x¼ .89, SD¼1.30, skewness¼1.2), with the majority of students andteachers (range ¼ 85.1%–97.8% acrossbehaviors) reporting zero. Accordingly,the variance of the outcome scales waslarger than the mean, and we ac-counted for this overdispersion byestimating a negative binomial modelfor the count outcomes.

A full-information maximum likeli-hood estimator was used for modelestimates. Standard error computationwas adjusted with the Huber-Whiteprocedure41,42 to account for the non-independence of students and teacherswithin schools. Low intraclass correla-tions (ICCs; student median¼ .05;teacher median¼ .03) and a smallnumber of clusters (i.e., 20) did notallow a multilevel SEM to converge.43–47

Further, our approach is justified in thatthe between-cluster component of themodel can be eliminated when smallICCs are observed; thus, the presentstudy focused on within-cluster individ-ual differences.46

In our models, the AB constructrepresents a continuous latent variableand, as mentioned previously, the

student model was specified usingcount outcome variables (i.e., sub-stance use and violent behavior) andthe dichotomized sexual activity vari-able; the teacher model included onlythe count outcomes as teacher data onstudent sexual activity were not col-lected. To test for differences amongboys and girls, a binary gender variablewas included in the models (boys ¼ 1,girls¼ 0). Further, in both student andteacher models, we tested an interac-tion term (intervention 3 gender) toexplore whether the treatment effectdiffered between boys and girls. Resultsshowed a nonsignificant interactionterm; therefore, the term was removedfor parsimony.

We implemented a two-stage processto examine mediation. First, we calcu-lated the bivariate effect (c) of the PAintervention on the outcomes withoutthe AB mediator present. Second, weincluded the AB mediator in themodel to calculate direct (c0) andindirect effects (ab). The indirecteffects were computed by calculatingthe product of the unstandardizedregression coefficients (i.e., a 3 b), andwe used the delta method38 to calcu-late the corresponding standard errors.In turn, for all of our outcomes, weexponentiated unstandardized esti-mates48 to produce more interpretableresults.

RESULTS

A small minority of students report-ed engaging in negative behaviorsrelated to substance use, violent be-

haviors, and voluntary sexual activity atany time in the past.9 For instance,among students attending controlschools, a minority of students report-ed having ever smoked a cigarette(7.6%), drunk alcohol (18.8%),threatened to cut or stab someone(7.4%), carried a gun (10.7%), orengaged in voluntary sexual activity(6.9%). Among students receiving theprogram, results showed smaller per-centages of students having eversmoked a cigarette (4.0%), drunkalcohol (10.1%), threatened to cut orstab someone (2.8%), carried a gun(4.5%), or engaged in voluntary sexualactivity (1.2%). Teacher reports sup-ported these results.9

Table 2 displays the estimated effectsof the PA intervention on the negativebehavioral outcomes (i.e., bivariateeffect) and the results of the measure-ment and SEMs estimated (i.e., directand indirect effects) for student self-report and teacher reports of studentbehavior. Examination of the fit statis-tics suggested that the measurementmodel fit the data well (student:comparative fit index [CFI] ¼ .99,Tucker-Lewis index [TLI] ¼ .99, rootmean square error of approximation[RMSEA] ¼ .016; teacher: CFI ¼ .99,TLI ¼ .98, RMSEA ¼ .052). Fit indicesfor the overall structure of the media-tion models were unavailable, as thereis no model estimated variance forcount variables.49

Effects of PA on AB MediatorThe PA intervention had a signifi-

cant direct effect on AB in both thestudent and teacher models (student:B¼ .273, SE¼ .039, p , .001; teacher: B¼ .125, SE ¼ .045, p , .01). Boysperformed significantly lower on ABcompared to girls (student: B¼�.117,SE¼ .024, p , .001; teacher: B¼�.239,SE ¼ .025, p , .001).

Effects of PA on Negative Behaviors

Substance Use. The student modelwithout the AB mediator (i.e., bivariateeffect) indicated that the PA interven-tion was associated with decreasing theexpected count of student self-reportsubstance use by 62.1% (B¼�.970, SE¼ .292, p , .01, incidence-rate ratio[IRR]¼ .379), holding all other factorsconstant. After inclusion of the medi-ator, the direct effect of AB on sub-

Figure 1

Terminology for the Mediation Model

Adapted from MacKinnon.38



stance use showed that a one-unitincrease in AB was associated withdecreasing the expected count ofsubstance use by 88.5% (B¼�2.161, SE¼ .473, p , .001, IRR¼ .115), holdingall other factors constant. There was asignificant indirect effect mediated byAB (B¼�.590, SE¼ .154, p , .001, IRR¼ .554); thus, the expected count ofyouth engaging in substance use wasreduced by 44.6% because of theindirect effect of PA as mediated by AB.After controlling for the indirect effectof AB, the direct effect of the PAintervention on substance use wasnonsignificant, demonstrating com-plete mediation. Teacher reports ofstudent behavior corroborated theseresults, although the teacher modeldemonstrated only partial mediation.

Violent Behaviors. Without taking theAB mediator into account, the studentmodel demonstrated that being in thePA intervention was associated withdecreasing the expected count ofviolent behaviors by 75.6% (B¼�1.410,SE ¼ .296, p , .001, IRR ¼ .244),holding all other factors constant. Withthe inclusion of the mediator, thedirect effect of AB on violent behaviorshowed that a one-unit increase in ABwas associated with decreasing theexpected count of violent behavior by86.6% (B¼�2.013, SE¼ .620, p , .001,IRR ¼ .134), holding all other factorsconstant. There was a significant indi-rect effect mediated by AB; thus, theexpected count of youth engaging inviolent behavior was reduced by 42.3%(B ¼�.550, SE ¼ .187, p , .01, IRR ¼.557) because of the indirect effect.After controlling for the indirect effectof AB, the direct effect of the inter-vention on violent behavior was re-duced but still significant (B ¼�.856,SE ¼ .362, p , .05, IRR¼ .425) and,therefore, demonstrated partial medi-ation. Teacher reports of student vio-lent behavior substantiated theseresults.

Voluntary Sexual Activity. Given that theprevalence of sexual activity amongelementary-aged students was low(6.9% control; 1.2% intervention), thestudent model without the AB media-tor indicated that being in the PAintervention was associated with adecrease in the odds of reportingvoluntary sexual activity by 91.1% (B¼

�2.415, SE¼ .608, p , .001, odds ratio[OR]¼ .089), holding all other factorsconstant. After controlling for themediated effect of AB, the OR reflectsan 85.2% (B ¼�1.908, SE ¼ .667, p ,

.01, OR ¼ .148) reduction in the oddsof reporting voluntary sexual activityamong youth in the PA intervention,with a significant direct effect remain-ing, demonstrating partial mediation.The odds of a student reportingvoluntary sexual activity were reducedby 92.1% (B ¼�2.536, SE ¼ .714, p ,

.001, OR ¼ .079) because of the effectas mediated by AB. There was asignificant indirect effect mediated byAB (B¼�.692, SE¼ .219, p , .01, OR¼.500); thus, the odds of studentsengaging in voluntary sexual activitywere reduced by half because of theindirect effect of PA as mediated by AB.

Gender Differences in NegativeBehaviors

Student and teacher bivariate-effectmodels demonstrated that boys hadsignificantly higher substance use (stu-dent: B¼ .481, SE¼ .202, p , .05, IRR¼1.618; teacher: B¼ .390, SE¼ .124, p ,

.01, IRR ¼ 1.477) and violent behavior(student: B¼ .962, SE¼ .245, p , .001,IRR ¼ 2.617; teacher: B ¼ .521, SE ¼.095, p , .001, IRR¼ 1.684) than girls.Boys also had greater odds of reportingvoluntary sexual activity (B¼ .728, SE¼.245, p , .01, OR ¼ 2.071) than girls.These effects were mediated by AB.

DISCUSSION

Results from this matched-pair, clus-ter-randomized, controlled trial areconsistent with previous researchdemonstrating that students attending

Figure 2

A Mediation Model of the Effects of Positive Action on Substance Use, Violent

Behaviors, and Sexual Activity

Bolded lines indicate mediation pathways; PA, Positive Action. A condition3gender effectwas nonsignificant and was not included in the model in the interest of parsimony.a Teacher data regarding student sexual activity were not collected; thus, sexual activity isincluded only in the student model.



PA intervention schools reported sig-nificantly more positive behaviors11,19

and less substance use, violent behav-iors, and voluntary sexual activity9,11,20

than students in control schools.Overall, similar to previous research,boys reported more negative behaviorsthan girls. We have built upon previous

work9 by utilizing the PYD and SECDperspectives to examine a mechanismregarding how the PA program canreduce negative behaviors. The present

Table 2Summary of the Effects of Positive Action (PA) on Academic Behavior (AB), Substance Use (SU), Violent Behaviors (VB), and

Sexual Activity (SA)†

Student Self-Report Teacher Report of Student BehaviorN ¼ 1784 N ¼ 1351

AB factor loadings, estimate (SE)

P1: Work hard at school 1.000 (0.000) 1.000 (0.000)

P2: Set goals for yourself 1.242 (0.119) 0.927 (0.093)

P3: Use or manage your time wisely 1.163 (0.075) 1.056 (0.067)

P4: Try to be your best 1.052 (0.079) 0.991 (0.095)

P5: Solve problems well 1.119 (0.099) 0.808 (0.047)

AB, B‡ (SE§)

Direct effects

PA intervention � AB 0.273**** (0.039) 0.125*** (0.045)

Boy � AB �0.117**** (0.024) �0.239**** (0.025)

SU, B‡ (SE§), IRR||

Bivariate effect without mediator

PA intervention � SU �0.970*** (0.292), 0.379 �1.055*** (0.340), 0.348

Boy � SU 0.481** (0.202), 1.618 0.390*** (0.124), 1.477

Direct effects with mediator

PA intervention � SU �0.364 (0.324), 0.695 �0.954*** (0.345), 0.385

Boy � SU 0.334* (0.199), 1.397 0.107 (0.138), 1.113

AB � SU �2.161**** (0.473), 0.115 �1.290**** (0.249), 0.275

Indirect effect

PA � AB � SU �0.590**** (0.154), 0.554 �0.161** (0.066), 0.851

VB, B‡ (SE§), IRR||

Bivariate effect without mediator

PA intervention � VB �1.410**** (0.296), 0.244 �0.810**** (0.147), 0.445

Boy � VB 0.962**** (0.245), 2.617 0.521**** (0.095), 1.684


PA intervention � VB �0.856** (0.362), 0.425 �0.711**** (0.165), 0.491

Boy � VB 0.867**** (0.248), 2.380 0.172** (0.078), 1.188

AB � VB �2.013**** (0.620), 0.134 �1.390**** (0.241), 0.249

Indirect effect

PA � AB � VB �0.550*** (0.187), 0.577 �0.174** (0.069), 0.840

SA, B‡ (SE§), OR#

Bivariate effect without mediator¶

PA intervention � SA �2.415**** (0.608), 0.089

Boy � SA 0.728*** (0.245), 2.071


PA intervention � SA �1.908*** (0.667), 0.148

Boy � SA 0.541** (0.229), 1.718

AB � SA �2.536**** (0.714), 0.079

Indirect effect

PA � AB � SA �0.692*** (0.219), 0.500

† AB measurement model fit indices: student: CFI¼0.99, TLI¼0.99, RMSEA¼0.016; teacher: CFI¼0.99, TLI¼0 .98, RMSEA¼0.052. IRR indicatesincidence-rate ratio; OR, odds ratio; CFI, comparative fit index; TLI, Tucker-Lewis index; and RMSEA, root mean square error of approximation.

‡ Unstandardized B estimate based on negative-binomial model.§ Standard error of the indirect effect estimated using the delta method.|| Incidence-rate ratio for count outcomes.# OR for dichotomous sexual activity variable.¶ Bivariate effect of the intervention on the outcome included the gender variable, without inclusion of the mediator in the model.* p , 0.10 (2-tailed).** p , 0.05 (2-tailed).*** p , 0.01 (2-tailed).**** p , 0.001 (2-tailed).



study provides empirical support forthe theory that underlies the PAprogram,10 whereby a link exists be-tween positive and negative behav-iors.50,51 Students who received the PAintervention reported significantlybetter ABs related to student involve-ment in school and motivation tolearn. Further, positive AB was associ-ated with a reduction in student self-report and teacher report of negativebehaviors. Specifically, we found thatstudent and teacher SEM models indi-cated that the positive effect of the PAintervention on substance use, violentbehaviors, and voluntary sexual activitywas partially or completely mediated byABs. The present study is strengthenedby the fact that student and teacherdata corroborated each other. Thisresearch adds to the limited amount ofresearch examining mechanismsthrough which PYD/SECD-relatedprograms work11–14 and represents thefirst effort to assess how the PAintervention reduces substance use,violence, and sexual activity by bolster-ing ABs.

With the expected outcome of in-fluencing many behaviors arises thecomplexity of evaluating the overallimpact of the PA program. The currentstudy examined one mediation mech-anism through which the PA programaffected negative behaviors. This is apossible limitation in that other vari-ables (e.g., higher teacher involvementin the intervention schools or im-proved school safety) could accountfor some of the program’s effects;however, our objective was to lookspecifically at academic-related behav-iors. Future research should examineother possible mediation and moder-ating factors that lead to the PAprogram’s effects. This may provide amore detailed understanding of themechanism(s) through which the PAprogram positively influences health-related outcomes. Further, doing sowould allow researchers and practi-tioners to gain a more thoroughunderstanding of how PYD/SECD-re-lated programming affects outcomes.In turn, practitioners might gain in-sight regarding what program compo-nents are most crucial in PYD/SECD-related interventions and how thesecomponents relate to one another.

The current findings should beviewed in the context of some otherlimitations. Because of the IRB re-quirements for the PA Hawaii trial,students had to have entered grade 5to be eligible to answer questionsrelated to the present study’s out-comes; thus, this mediation analysiswas not longitudinal, and care shouldbe taken when making causal infer-ences. Despite this limitation, ouranalysis is supported by theory thatsuggests increasing positive behaviormay decrease negative behavior.10 Fur-ther, the hypothesized direction of thePA program’s effects is based on thefact that the program was designed toincrease positive behaviors, withoutany focus on negative behaviors. Fu-ture research could provide increasedevidence through longitudinal analysis.Also, the examination of the PA inter-vention’s impact on voluntary sexualactivity could be enhanced with theinclusion of more than a single itemquerying about sexual activity. Addi-tionally, the study’s generalizability islimited to elementary-aged students.Various cultural and communal valuesand factors exist in different geo-

graphic areas, and future work couldexamine mediation pathways in dis-similar contexts. As for any similarstudy, results are only generalizable tostudents attending schools willing toconduct such a school-wide, compre-hensive program. Lastly, social desir-ability bias is a possible limitation thatall prevention studies of this type have.

In sum, the present research dem-onstrated that the PA intervention wasassociated with a reduction in negativebehaviors without including detailedinstructional time devoted to substanceuse and violent behavior, and with nomention of sexual activity. Overall, thePYD and SECD perspectives were sup-ported. The PA program effects onnegative behaviors were partially orcompletely mediated by positive aca-demic-related behaviors.

Acknowledgments

We would like to thank Niloofar Bavarian and KendraLewis for helpful comments on previous drafts of this paper.This article is based on a portion of a dissertation submittedby the first author to Oregon State University with fundingprovided by the National Institute on Drug Abuse (R01-DA13474). Additionally, the National Institute on DrugAbuse (DA018760 and T32 DA01946) provided financialsupport for the completion of the work on this manuscript.The authors would like to thankfully recognize the supportand involvement of the Hawaii school district and theprincipals, administrators, teachers, staff, and studentsand their families at the participating schools.

References

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SO WHAT? Implications for Health

Promotion Practioners and

ResearchersWhat is already known on this topic?

Recent research has shown thatappropriately designed and imple-mented social-emotional and char-acter development programs can beeffective in reducing substance use,violence, and sexual activity. Howev-er, the field lacks studies examininghow these types of programs reducenegative behaviors.What does this article add?

This study suggests that a social-emotional and character develop-ment program is associated withacademic-related behaviors that me-diate the positive program effects onsubstance use, violence, and sexualactivity.What are the implications for healthpromotion practice or research?

Focusing on youths’ assets using acomprehensive, school-wide pro-gram is one possible approach themay reduce negative behaviorsamong elementary-aged students.



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Preventing Negative Behaviors Among Elementary-School ...people.oregonstate.edu/~flayb/MY PUBLICATIONS/Positive Action/Snyder etal13 SECD...The present study examines the effects of