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Relationships Between Problem Behaviors and Academic Achievement

in Adolescents:

The Unique Role of Attention Problems

ALVARO Q. BARRIGA, JEFFREY W. DORAN, STEPHANIE B. NEWELL,ELIZABETH M. MORRISON, VICTOR BARBETTI,

AND BRENT DEAN ROBBINS

ASUBSTANTIAL BODY OF RESEARCH

has documented associations be-tween problem behaviors and aca-

demic achievement. This topic has rele-vance from an educational perspective thatviews problem behaviors as serious im-pediments to optimal education. From apsychopathology perspective, low aca-demic achievement represents a signifi-cant risk factor for poor behavioral out-comes. A systemic viewpoint posits thatbehavioral and academic problems exertreciprocal influences on one another,which, over time, can negatively affect thedevelopment of individuals and their en-vironments. Regardless of perspective, aclear understanding of the relationship be-tween problem behaviors and academicachievement will help generate appropri-ate assessment, prevention, and interven-tion strategies for at-risk or troubledyouth.

We are using the term academic un-derachievement to denote academic per-formance that is below normative age

level rather than discrepant from one’sgeneral cognitive ability (as in the diag-nosis of learning disabilities). A wide va-riety of problem behaviors have beenlinked to academic underachievement.For example, investigations have consis-tently revealed that aggression and otherforms of antisocial behavior display in-verse relationships with academic achieve-ment (e.g., Williams & McGee, 1994).

Additionally, the symptoms of attention-deficit/hyperactivity disorder have showna robust inverse relationship with achieve-ment (Faraone et al., 1993). Problem be-haviors associated with internalizing havealso evidenced connections to academicunderachievement, though less consis-tently. Anxiety and negativism have beenidentified as key personality traits associ-ated with academic problems (Stevens &

Numerous studies have documented relationships between a variety of problem behaviors and academic

achievement measures. However, the results of these studies should be interpreted cautiously, given the

considerable comorbidity of problem behaviors that often exists among school-age youth.This study ad-

dressed the relationships between 8 teacher-reported problem behavior syndromes (withdrawal, somatic

complaints, anxiety/depression, social problems, thought problems, attention problems, delinquent behav-

ior, aggressive behavior) and standardized measures of academic achievement (overall, reading, spelling,

arithmetic, performance).The sample comprised 41 boys and 17 girls ages 11 to 19 years (M = 15.02,

SD = 1.90) enrolled in an alternative school. Although withdrawn, somatic complaints, delinquent behav-

ior, and aggressive behavior syndromes exhibited significant zero-order correlations with the academic

achievement measures,each of these relationships was mediated by attention problems. A post hoc analy-

sis suggested that the observed association between attention problems and academic achievement was

primarily due to the inattention component of the syndrome rather than the hyperactivity–impulsivity

component.The findings are discussed with reference to theoretical, research, and treatment implications.

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Pihl, 1987). Moreover, several researchershave linked depressive disorders or symp-toms to underachievement (e.g., Puig-Antich et al., 1993). It is noteworthy thatother researchers have found no connec-tions between internalizing symptomsand poor academic performance (e.g.,Reinherz et al., 1993). At this time, the ev-idence regarding this relationship remainsequivocal. In addition to externalizing andinternalizing symptoms, quality of socialrelations has been linked to academicachievement and related variables. A sub-jective sense of belonging and interper-sonal support has been associated withhigher achievement motivation and edu-cational plans (Cotterell, 1992; Goode-now, 1993). Conversely, peer rejection hasbeen found to be a risk factor for academicunderachievement (e.g., Ollendick,Weist,Borden, & Greene, 1992).

Interpretation of this research shouldproceed cautiously. Research of problembehaviors is complicated by the fact thatmany children and adolescents exhibitmultiple problem behaviors. Significantcomorbidity among a substantial propor-tion of youths has been documented inreferred and nonreferred samples (e.g.,McConaughy & Achenbach, 1994). In-vestigators should be aware of potentialconfounds that can result from associatedproblem behaviors that are not of primaryinterest in a particular study. Specifically,in the present study, a problem behaviormay exhibit a spurious correlation withacademic achievement only because it isassociated with another problem behaviorthat plays a more direct or central role inacademic achievement. Studies of exter-nalizing problems have suggested thataggressive behaviors in childhood are re-lated to underachievement primarily be-cause of their associations with attentionproblems (e.g., Frick et al., 1991). The ob-served relationships between internal-izing behaviors and academic under-achievement may also be primarily due totheir associations with attention prob-lems, although this hypothesis has nothitherto been tested. This hypothesis isplausible, however, given that attentionproblems are frequently comorbid withinternalizing problems (e.g., Jensen, Mar-tin, & Cantwell, 1997) and some internal-

izing disorders even include symptomsthat explicitly refer to attention difficul-ties (e.g., difficulty concentrating is asymptom of major depressive disorder,generalized anxiety disorder, and post-traumatic stress disorder).

Attention problems may represent asyndrome that is not only comorbid with,and conceptually related to, a variety ofother syndromes but also fundamentallyinvolved in academic underachievement.Attention deficiencies could representcore elements of poor academic function-ing that can coexist with a variety of otherproblem behaviors that do not necessarilyhave a direct impact on academic achieve-ment. To evaluate this hypothesis, therelationships between eight teacher-reported problem behavior syndromes(withdrawal, somatic complaints, anxiety/depression, social problems, thoughtproblems, attention problems, delinquentbehavior, aggressive behavior) and stan-dardized measures of academic achieve-ment (overall, reading, spelling, arith-metic, performance) were assessed. Ourprimary aim was to determine whether ornot attention problems mediate the rela-tionships between other problem behav-iors and academic underachievement. Asecondary aim was to explore possiblecurvilinear and moderated relationshipsbetween these sets of variables.

METHOD

Participants

Participants were 41 boys and 17 girlsages 11 to 19 years (M = 15.02, SD = 1.90)enrolled in an alternative school thatserved a predominantly urban area of alarge eastern city. Students were referredto the alternative school by school ad-ministrators in their home districts whohad determined that interventions at-tempted to that point had proven inef-fective for them. The vast majority ofstudents were referred for disruptive be-havior (especially aggression) and poorinterpersonal relationships with peers andteachers. A minority of students were re-ferred for other problems such as truancy,depression, and school phobia. Althougharchival data were not available for each

student, the attending psychologist at theschool approximated that 70% of thesechildren were identified with severe emo-tional disturbance, and their IQs were gen-erally in the low average and borderlineintellectual functioning ranges. The par-ticipants were 55% Caucasian and 45%African American.

Measures

Teacher’s Report Form for Ages 5 to18 (TRF; Achenbach, 1991b). The TRFis a multidimensional behavior ratingscale designed to appraise youths’ aca-demic and adaptive functioning as well astheir problem behaviors. The AcademicPerformance scale, which assesses teach-ers’ perceptions of students’ academicwork across several subjects relative tograde level, was used as a teacher-reportedmeasure of academic achievement. Theeight problem scales (Withdrawal, So-matic Complaints, Anxiety/Depression,Social Problems, Thought Problems, At-tention Problems, Delinquent Behavior,and Aggressive Behavior) were used torepresent the various problem behaviorsof interest in the present study. Achenbach(1991a) reported extensive favorable reli-ability (test–retest, internal consistency,interrater) and validity (content, con-vergent, divergent, discriminant, factor-analytic) findings for the TRF.

Because we investigated the TRF prob-lem scales in relation to academic achieve-ment measures, we eliminated four TRFproblem items that were judged to beconfounded with academic achievement:“Has difficulty learning,” “Poor schoolwork,” “Messy work,” and “Underachiev-ing, not working up to potential.” Re-moving these items was necessary toavoid a tautologous comparison (i.e., cri-terion contamination that could producespuriously high correlation estimates).The four eliminated items were on the 20-item Attention Problems scale, which wasconsequently reduced to 16 items. To re-store the scale to its original magnitude,raw scale scores computed from the re-maining 16 items were multiplied by 1.25so that they then could be meaningfullyconverted to t scores that were designedto be derived from a 20-item scale.

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Wide Range Achievement Test, ThirdEdition (WRAT3; Wilkinson, 1993). TheWRAT3 was designed to measure aca-demic achievement in three areas: reading(recognizing and naming letters, pro-nouncing words out of context), spelling(writing name, writing letters and wordsto dictation), and arithmetic (counting,reading number symbols, solving oralproblems, performing written computa-tions). For each participant, these threestandard scores were averaged to com-pute an Overall Achievement score. TheWRAT3 has demonstrated extensive fa-vorable reliability (test–retest, internalconsistency, alternate forms) and validity(content, convergent, discriminant) find-ings (Wilkinson, 1993).

Procedure

All newly enrolled students over thecourse of an entire academic year wereconsidered for inclusion in the study. In-formed parental consent and personal as-sent were obtained for every potentialparticipant, and all the students weresubsequently assessed. Approximately 1month after admission, students were ad-ministered the WRAT3 on an individualbasis (in a quiet, distraction-free roomwithin the school, during a study hall pe-riod, with breaks offered) by a licensedpsychologist or an intern trained and su-pervised by the psychologist. Duringschool break periods (e.g., recess, studyhall), each student’s primary teacher (i.e.,the teacher that provided the greatestamount of instruction time to the student)completed a TRF for the student within 1 week of the time he or she completedachievement testing. Teachers were keptunaware of the students’ achievementscores.

RESULTS

Demographic Variable Analyses

Analyses were conducted to determinewhether any demographic variables (gen-der, ethnicity, chronological age) shouldbe used as control variables in subsequentcorrelational analyses. Because our prin-ciple analyses involved correlations be-

tween problem behavior and academicachievement, potential demographic con-founds (i.e., any demographic variablesthat might be associated simultane-ously with problem behaviors and aca-demic achievement) were investigated. AMANOVA was used to test for gender,ethnicity, and gender × ethnicity effects onthe eight problem behaviors. TRF rawscores (rather than t scores) were used inthese analyses because TRF t scores werederived separately for boys and girls in thenormative sample (Achenbach, 1991a)and could obscure any potential gender ef-fects. The only significant effect was forethnicity, F(8, 47) = 2.23, p < .05. Subse-quent ANOVAs were conducted to test forethnicity effects on each of the eight prob-lem behaviors, but none of the effectswere significant.

Another MANOVA was conducted totest for gender, ethnicity, and gender ×ethnicity effects on four of the academicachievement measures (Reading, Spell-ing, Arithmetic, Performance). OverallAcademic Achievement was not includedin this analysis because it represented theaverage of the Reading, Spelling, andArithmetic variables, and would have pro-duced multicollinearity problems (i.e., asingular matrix). The only significant ef-fect was for ethnicity, F(4, 51) = 2.75, p <.05. Subsequent ANOVAs revealed thatAfrican American students (N = 26) scoredsignificantly lower than Caucasian stu-dents (N = 32) on achievement measures.On the Reading subscale, African Ameri-can students (M = 84.00, SD = 17.23)scored lower than Caucasian students (M = 95.94, SD = 16.57), F(1, 56) = 7.18,p < .01. On the Spelling subscale, AfricanAmerican students (M = 83.77, SD =16.93) scored lower than Caucasian stu-dents (M = 97.69, SD = 15.99), F(1, 56) =10.31, p < .01. On the Arithmetic sub-scale, African American students (M =78.31, SD = 15.31) scored lower than Cau-casian students (M = 88.84, SD = 13.51),F(1, 56) = 7.74, p < .01. On the OverallAchievement scale (the average of theReading, Spelling, and Arithmetic scales),African American students (M = 82.03,SD = 14.98) scored lower than Caucasianstudents (M = 94.16, SD = 14.18), F(1,56) = 9.98, p < .01. In teacher-rated aca-

demic performance scores, however, Afri-can American students (M = 41.62, SD =6.77) did not differ from Caucasian stu-dents (M = 46.29, SD = 7.46), F(1,56) = 3.10, ns.

In addition to gender and ethnicity, weinvestigated the demographic variable ofchronological age. Among the eight prob-lem behaviors, only thought problemscorrelated with age, r (58) = .33, p < .05.None of the academic achievement mea-sures correlated with age, and there wereno significant gender, ethnicity, or gen-der × ethnicity effects for age.

In sum, gender was not associated withproblem behaviors or academic achieve-ment. Although ethnicity was associatedwith the academic achievement measures,it was not associated with any of the prob-lem behavior measures. Chronological agewas associated with only one of the prob-lem behavior measures and none of theacademic achievement measures. Giventhese findings, we determined that therewas no need to use any demographic vari-ables as control variables in subsequentanalyses.

Correlation and RegressionAnalysesIn order to explore the possibility ofcurvilinear problem behavior–academicachievement relationships, we conductedmultiple regression analyses that pre-dicted Overall Achievement and Aca-demic Performance on each of the eightproblem scale scores along with its corre-sponding squared scale score. We did notpredict results on the Reading, Spelling,and Arithmetic Achievement subscalesseparately because they were highly in-tercorrelated (see Table 1), and the height-ened number of comparisons (24) wouldhave significantly raised the likelihood ofa Type I error (incorrectly detecting acurvilinear relationship). All variableswere zero-centered in these regressionanalyses to reduce problems associatedwith multicollinearity. None of the qua-dratic terms resulted in a significant in-crease in the amount of variance explainedin Overall Achievement or Academic Per-formance beyond that explained by thecorresponding linear term.



After establishing that the relation-ships of interest were linear, we used cor-relations to estimate the degree of asso-ciation between problem behaviors andacademic achievement measures (see Ta-ble 1). We did not employ any correctionsto probabilities (such as the Bonferronimethod) because all of these compari-sons were planned (see Keppel, 1991).The Withdrawal, Somatic Complaints,Attention Problems, Delinquent Behav-ior, and Aggressive Behavior scalesexhibited significant correlations withacademic achievement measures. TheAnxiety/Depression, Social Problems, andThought Problems scales did not correlatesignificantly with the academic achieve-ment measures.

Multiple regression analyses were con-ducted to assess the relationships betweenwithdrawal, somatic complaints, delin-quent behavior, and aggressive behaviorand each of the academic achievementmeasures, while controlling for attentionproblems. The same pattern of signifi-cance emerged for each analysis. Only at-tention problems were associated withunique variance in each of the academicachievement measures (see Table 2). Thus,attention problems mediated each of therelationships between the other four prob-lem behaviors and the academic achieve-ment measures.

The possibility of moderated problembehavior–academic achievement relation-

ships was explored through multiple re-gression analyses. Moderated effects weretested by predicting Overall Achievementand Academic Performance scores fromeach possible combination of two prob-lem scales along with their correspondinginteraction term. As in the analysis ofcurvilinear relationships, we avoided an-alyzing Reading, Spelling, and ArithmeticAchievement scores separately because oftheir high intercorrelations and to reducethe probability of a Type I error (incor-rectly detecting a mediated relationship).No interaction effects were significant inthese analyses.

Post Hoc Analyses

Because only attention problems were as-sociated with unique variance in academicachievement across multiple regressionanalyses, post hoc analyses were con-ducted to explore this relationship further.In addition to an overall Attention Prob-lems score, the TRF produces a score oneach of two subscales that have been factor-analytically derived from the At-tention Problems scale (Achenbach & McConaughy, 1997): Inattentive andHyperactive–Impulsive. We first deter-mined that there were no gender, ethnic-ity, gender × ethnicity, or chronologicalage effects for either subscale. We thencomputed zero-order correlations be-tween the two subscales and the measures

of academic achievement (see Table 3). Asnoted in Table 3, both the Inattentive andHyperactive–Impulsive subscales exhib-ited significant correlations with the aca-demic achievement measures.

In order to assess which of the twoAttention Problems subscales was mostdirectly associated with academic achieve-ment, we conducted simultaneous multi-ple regression analyses in which each ofthe academic achievement measures waspredicted from both subscales (see Ta-ble 3). In combination, the two subscaleswere significantly associated with eachacademic achievement measure (note theFmodel estimates). When considered sepa-rately, the standardized partial correlationcoefficients were not significant, but werehigher for the Inattentive subscale than the Hyperactive–Impulsive subscale forOverall, Reading, Spelling, and Arith-metic Achievement (though the differ-ences in magnitude were not statisticallysignificant). The Inattentive subscale wasa significant predictor of Academic Per-formance, whereas the Hyperactive–Impulsive subscale was not.

DISCUSSION

Results from our zero-order correlationalanalyses provide further support for theproblem behavior–academic achievementconnections observed in previous studies.As expected, aggressive and delinquent

TABLE 1Zero-Order Correlations Between Teacher-Reported Problem

Behaviors and Academic Achievement Measures

Overall Reading Spelling Arithmetic AcademicVariable achievement achievement achievement achievement performance M SD

Withdrawn behavior –.23 –.16 –.23 –.25 –.35** 57.64 6.76Somatic complaints –.26 –.23 –.25 –.23 –.30* 57.67 8.74Anxiety/depression –.10 –.07 –.09 –.14 –.07 54.55 4.63Social problems –.14 –.11 –.09 –.21 –.17 58.81 6.69Thought problems –.02 –.00 –.01 –.04 .00 55.66 8.99Attention problems –.44*** –.38** –.41** –.44*** –.37** 57.91 7.29Delinquent behavior –.28* –.31* –.28* –.19 –.24 60.76 8.17Aggressive behavior –.28* –.28* –.23 –.25 –.33* 61.48 7.40

M 88.72 90.59 91.45 84.12 44.19SD 15.65 17.76 17.71 15.17 7.47

Note. N = 58.*p < .05. **p < .01. ***p < .001.



behaviors were associated with academicunderachievement. The findings within theinternalizing domain were less straight-forward, much like the extant research inthis area. Although anxiety and depres-sion were not related to underachievement(consistent with a number of previousstudies), we found significant relation-ships for two other internalizing behav-iors: withdrawal and somatic complaints.Discrepancies in previous studies mayhave been attributable to the degree thatsamples exhibited or measures assessedwithdrawn and/or somatic symptoms aspart of the internalizing construct.

Two additional problem behaviorswere not associated with underachieve-ment: social problems and thought prob-lems. Previous studies that linked peerrejection to underachievement have gen-erally used a broader construct than theone assessed by the Social Problems scalein our study. When sociometric methodsare used to classify children into a rejectedgroup, that group typically includes a sub-stantial proportion of aggressive and with-drawn children (in fact, these are the majorsubtypes of rejected peer status). In con-trast, the Social Problems scale used in the

present study primarily captures socialimmaturity and victimization and is dis-tinguished from the Aggressive Behaviorand Withdrawal scales. The rejection–underachievement relationship found inprevious studies may be principally at-tributable to the aggressive and/or with-drawn behaviors exhibited by rejectedchildren. Thought problems did not relateto achievement in our sample. This islikely due to the fact that the alternativeschool setting did not enroll students withsignificant thought problems (e.g., hallu-cinations, delusions).

The significant relationships betweenthe aforementioned problem behaviorsand academic underachievement werefound to be mediated by attention prob-lems. Thus, it appears that many problembehaviors (both externalizing and inter-nalizing) are not directly related to aca-demic underachievement. Rather, they areassociated with attention problems that inturn have a negative impact on academicachievement. That attention problems canmediate the relationship between aggres-sive/delinquent behaviors and under-achievement has been documented pre-viously (e.g., Frick et al., 1991). In a

comprehensive literature review address-ing this issue, Hinshaw (1992b) con-cluded that this mediating role of attentionproblems was evident in childhood but not in adolescence. In adolescence, delin-quent behavior was a significant predictorof underachievement, even when atten-tion problems were controlled. Discrep-ant with this conclusion, our findings in-dicate that the mediating role of attentionproblems held for a referred adolescentsample. Unique to our study is the findingthat attention problems can mediate therelationships between internalizing be-haviors and underachievement.

Our results suggest that within the at-tention problems domain, the inattentioncomponent of this syndrome, rather thanthe hyperactivity–impulsivity component,is most directly related to academic un-derachievement (cf. McGee, Williams, &Silva, 1985). Previous studies have failedto find achievement differences betweeninattentive children with and without hy-peractivity (e.g., Edelbrock, Costello, &Kessler, 1984; cf. Hynd et al., 1991).However, studying inattentive childrenwith and without hyperactivity as two sep-arate groups may not be a particularly

TABLE 2Simultaneous Multiple Regression Analyses of the Effects of Teacher Reports on

Academic Achievement Measures

Overall Reading Spelling Arithmetic AcademicProblem behavior achievement achievement achievement achievement performance

Withdrawn .03 .08 .01 –.01 –.20Attention problems –.46** –.42** –.42** –.43** –.26R2 .19 .15 .17 .19 .16Fmodel 6.62** 4.70* 5.71** 6.46** 5.33**

Somatic complaints –.13 –.13 –.13 –.11 –.20Attention problems –.40** –.34* –.37** –.40** –.30*R2 .21 .16 .19 .20 .17Fmodel 7.29** 5.11** 6.38** 6.90** 5.83**

Delinquent behavior –.12 –.19 –.13 –.01 –.10Attention problems –.39** –.30* –.36** –.43** –.33*R2 .21 .17 .19 .19 .15Fmodel 7.13** 5.70** 6.25** 6.46** 4.70*

Aggressive behavior –.08 –.13 –.04 –.05 –.19Attention problems –.40** –.31* –.40** –.41** –.27R2 .20 .15 .17 .19 .16Fmodel 6.79** 5.02** 5.74** 6.53** 5.34**

Note. N = 58.*p < .05. **p < .01.



useful concept because symptoms of inat-tention are present in both groups. Com-parisons of children with attention-deficit/hyperactivity disorder should moreoften compare children who are primarilyinattentive not with combined type chil-dren, but with those who are primarilyhyperactive–impulsive (although thesechildren are rare, especially among school-age samples). An alternative, of course, isto use continuous measures of inattentionand hyperactivity–impulsivity while in-cluding statistical controls when appro-priate.

Our findings with respect to demo-graphic variables should be interpretedcautiously. We did not find gender differ-ences in problem behaviors, unlike previ-ous studies that have generally docu-mented higher levels of externalizingbehaviors in boys and higher levels of in-ternalizing behaviors in girls (e.g.,Achen-bach et al., 1990; Nolen-Hoeksema,1990). However, two aspects of our sam-ple may have contributed to this non-significant finding: (a) the fairly smallnumber of girls in our sample (n = 17) maynot have been sufficient to detect gendereffects and (b) gender comparisons basedon our referred sample may not ade-quately reflect similarities or dissimilari-ties in the general population. No genderdifferences were found in academicachievement measures, unlike previousstudies that have found higher language

achievement for girls and higher mathachievement for boys (e.g., Hedges &Nowell, 1995). As with the nonsignificantgender effect for problem behaviors, thesmall number of female participantsand/or the referred nature of our samplemay have accounted for this anomaly.

With respect to race, we found no dif-ferences between African American andCaucasian participants on problem behav-iors. Although some studies have foundheightened problem behaviors amongAfrican American youth (e.g., Hare &Castenell, 1985), other studies that havecontrolled for socioeconomic status havefound no such differences (e.g., Dodge,Pettit, & Bates, 1994). Because our Afri-can American and Caucasian participantswere referred to the alternative school set-ting from similar neighborhoods andschools, we suspect that they were simi-lar in terms of socioeconomic status. Ourfinding is thus consonant with researchthat attributes racial differences in prob-lem behaviors to socioeconomic differ-ences. Regarding academic achievement,Caucasians outperformed African Ameri-cans on the standardized measures in-cluded in our study. Although this differ-ence may reflect test bias, it may alsoreflect real racial differences in achieve-ment that are influenced by a number offactors, with socioeconomic status repre-senting only one of those factors (Ros-cigno, 2000). Generalizations from our

sample should be avoided in light of thefairly small number of African Americans(n = 26) included in our study.

Chronological age correlated withonly one out of eight problem behaviorsin our sample. Achenbach (1991a) simi-larly found negligible age effects onteacher-reported problem behaviors, withthe exception of a positive correlation be-tween age and an item that assessed alco-hol and drug use. The lack of age effectson our standardized achievement mea-sures is an artifact of age-related normingand grade-related anchoring for thesemeasures. Because our sample spannedearly to late adolescence, it was necessaryto evaluate academic achievement relativeto same age or grade peers.

Our study was not designed to test forgender, race, or age effects; rather, thesedemographic variables were investigatedas potential confounds to our primaryanalyses. We chose our sample with pri-mary concern for ecological validity; al-ternative school students represent ado-lescents with significant and variedbehavioral and academic problems andare thus of particular interest for our re-search topic. Future studies should be de-signed specifically to assess the impact ofdemographic variables in this area of re-search. Our primary findings should bereplicated with larger samples that includedifferent age and ethnic groups. It is alsoimportant to assess whether our findings

TABLE 3Zero-Order Correlations and Standardized Partial Correlation Coefficients Between

Teacher Reports and Academic Achievement Measures

Overall Reading Spelling Arithmetic AcademicProblem behavior achievement achievement achievement achievement performance

Zero-order correlationsInattentive –.39** –.36** –.37** –.37** –.37**Hyperactive–Impulsive –.31** –.31* –.32* –.34** –.24

Standardized partial correlation coefficientsInattentive –.34 –.32 –.36 –.27 –.56*Hyperactive–Impulsive –.06 –.04 –.02 –.11 .23

R2 .16 .13 .14 .14 .15Fmodel 5.08** 4.00* 4.44* 4.40* 4.99*

Note. N = 58.*p < .05. **p < .01.



are replicated for youth at various lev-els of problem behaviors and academicachievement. The referred nature of oursample may have produced a slight over-estimate of the magnitude of relationshipsbetween behavioral and academic prob-lems because youth with multiple prob-lems are those most likely to be referredfor services.

The generalizability of these findingsshould be investigated using different in-formants to rate the problem behaviors.Although different raters evaluating youthsin the same context (e.g., school) gener-ally demonstrate good interrater reliabil-ity, substantial variation in evaluations hasbeen found among persons who observeyouths’ behaviors in different contexts(Achenbach, McConaughy, & Howell,1987). Although assessment of problembehaviors in other settings should be ex-plored, the school setting may be the mostimportant context for investigating prob-lem behavior–academic achievement re-lationships. Teachers with special educa-tion training and experience who spendlarge portions of the school day with theirstudents may be particularly well suited torate problem behaviors that are believedto interfere with academic performance.Teachers are also a common source of in-formation about students who are beingassessed for academic and behavioralproblems. It is noteworthy that the teach-ers in our study were blind to the resultsof the individual standardized assess-ments of overall, reading, spelling, andarithmetic achievement, thus avoiding cri-terion contamination.

Attention problems and academic un-derachievement are important risk fac-tors for many negative adult outcomes.Follow-up studies of children diagnosedwith attention-deficit/hyperactivity disor-der have found that as adults they havelower rates of educational attainment, oc-cupational rank, job performance, self-esteem, and social skills. They also havehigher rates of antisocial behavior, sub-stance abuse (although the evidence ismixed), and ongoing symptoms of rest-lessness, impulsivity, and distractibility(Mannuzza & Klein, 1999). Adulthoodoutcomes of academic underachievementare similarly disheartening and include

lower occupational rank and job perfor-mance (Roth, Bevier, Switzer, & Schipp-man, 1996), increased mental health prob-lems (Kaplan, Damphousse, & Kaplan,1994), and decreased cognitive abilities(Ceci & Williams, 1997).

The high correspondence between at-tention problems and underachievement,paired with their poor prognostic indica-tions, renders the development of appro-priate detection and intervention strate-gies for these problems a cardinal goal.Because inattention seems to mediate therelationships between many problem be-haviors and academic achievement, itshould receive particular emphasis in as-sessment procedures for poorly perform-ing students. Unlike some problem be-haviors that can be observed readily (e.g.,withdrawal, hyperactivity, aggression),inattention problems can be hard to detectand may be overlooked. Clinicians shouldtherefore routinely evaluate inattentionproblems according to accepted assess-ment practices (e.g., Barkley, 1997). Al-though we are emphasizing careful as-sessment of inattention due to its centralrole in underachievement, we recognizethe importance of evaluating other syn-dromes as well as contexts because theymay deserve independent clinical or edu-cational attention.

Although controversy exists regardingwhat treatments (or combinations of treat-ments) are most effective for attentionproblems and underachievement, mostexperts agree that long-term, multimodalinterventions are best suited for address-ing these conditions. Multimodal inter-ventions typically involve teachers’ andparents’ using behavior modificationstrategies, enhanced instruction in aca-demic skills, classroom accommodations,social skills training, and (in some cases)psychostimulant medication (Barkley,1998; Hinshaw, 1992a). Given the inti-mate relationship between inattention andacademic problems suggested by our re-sults, their nature and treatment shouldreceive continued focus from both re-searchers and clinicians.

About the AuthorsALVARO Q. BARRIGA, PhD, is an associ-ate professor of psychology at Seton Hill Col-

lege. His research focuses on cognitive aspectsof disruptive behavior disorders. JEFFREYW. DORAN, BS, is supervisor of the FosterCare and Adoption Program for Adelphoi Vil-lage. His scholarly pursuits include family andgroup therapy modalities. STEPHANIE B.NEWELL, BA, is a student at Seton Hill Col-lege whose interests lie in family-based treat-ment of disruptive behavior disorders. ELIZ-ABETH M. MORRISON, MA, is a graduatestudent at Indiana University of Pennsylvania.Her work centers on developmental delays andbehavioral problems in children. VICTORBARBETTI, MA, is a doctoral candidate inclinical psychology at Duquesne University.His research focuses on historical and phe-nomenological approaches to childhood dis-orders. BRENT DEAN ROBBINS, MA, is adoctoral candidate in clinical psychology atDuquesne University. His scholarship centerson the phenomenology of emotion and emo-tional behavior. Address: Alvaro Q. Barriga,Psychology Department, Seton Hill College,Seton Hill Dr., Greensburg, PA 15601, e-mail:[email protected]

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