Multidimensional perfectionism in a sample of middle school students: An exploratory investigation

MULTIDIMENSIONAL PERFECTIONISM IN A SAMPLE OF MIDDLE SCHOOLSTUDENTS: AN EXPLORATORY INVESTIGATION

RICH GILMAN

University of Kentucky

JEFFREY S. ASHBY

Georgia State University

In this exploratory study, 185 middle school students were administered the Almost PerfectScale-Revised and the Behavioral Assessment System for Children-Self Report. Self-reportedgrade-point average was also obtained. Students who established high personal standards butnonetheless recognize their limitations (adaptive perfectionists) reported significantly higher(i.e., more positive) scores on a number of academic, intrapersonal, and interpersonal variables.However, the perceived inability for some students to consistently meet their high standards(maladaptive perfectionists) was significantly and negatively related to perceptions of schooland family relationships, and greater emotional distress. Implications of these findings and futureresearch and clinical suggestions are provided. © 2003 Wiley Periodicals, Inc.

Although a precise definition of perfectionism remains subject to debate (Chang, 2000; Parker,1997), current consensus identifies the construct as the setting of excessively high personal stan-dards (Burns, 1980), doubts about the effectiveness of meeting those standards, concerns aboutmeeting social expectations (typically those of parents and teachers; Frost, Marten, Lahart, &Rosenblate, 1990), and an excessive focus on personal control (Chang, 2000). Given this concep-tualization, the majority of research among adults continues to investigate the relationship betweenperfectionism and maladaptive outcomes including depression (Enns & Cox, 1999), anxiety (Flett,Hewitt, & Dyck, 1989), personality disorders (Hewitt, Flett, & Turnbull-Donovan, 1992), andeating disorders (Axtell & Newlon, 1993).

Nevertheless, it may be incorrect to assume that perfectionism is wholly synonymous withpsychopathology (Parker, 2000). Although some major personality theorists (e.g., Ellis, 1962;Freud, 1923/1959) viewed individuals with perfectionistic tendencies as a product of abnormalintrapsychic development, others have stressed that some aspects of perfectionism are positiveand essential to the human condition. For example, Adler (1956) contended that striving to max-imize one’s talents or potential is a major aspect of human development, and is viewed as healthywhen it includes positive interactions with others (see also Maslow, 1970). Perfectionism becomesmaladaptive when the standards one is striving towards become too unrealistic, precluding theactual attainment of the goal, and thus leading to intrapersonal and social stress (Parker, 1997).Based on these disparate views, Hamachek (1978) conceptualized perfectionism as consisting oftwo subtypes: normal and neurotic. Normal perfectionists are individuals who set high standardsfor themselves and are highly motivated by the need for achievement, yet recognize and accepttheir limitations in striving to meet these standards. Neurotic perfectionists, on the other hand, sethigh standards in every situation and do not accept their limitations. Given this small room forerror, they are driven more by a fear of failure than the pursuit of achievement excellence. As aresult, neurotic perfectionists are never completely satisfied with themselves or their performance(Hill, McIntire, & Bacharach, 1997; Nugent, 2000; Pacht, 1984).

Hamachek’s (1978) conceptualization of perfectionism has been empirically supported overthe years (e.g., Owens & Slade, 1987; Piirto, 1994). Although a number of authors using various

Correspondence to: Rich Gilman, Department of Counseling and Educational Psychology, 245 Dickey Hall, Univer-sity of Kentucky, Lexington, KY 40506. E-mail: [email protected]

Psychology in the Schools, Vol. 40(6), 2003 © 2003 Wiley Periodicals, Inc.Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/pits.10125

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multidimensional scales have demonstrated support for the multidimensionality of perfectionism(see Frost et al., 1990; Hewitt & Flett, 1990), the present study will focus on the work of Slaneyand colleagues (Slaney, Rice, & Ashby, 2002; Slaney, Mobley, Rice, Trippi, & Ashby, 2001) usingthe recently developed Almost Perfect Scale-Revised (APS-R: Slaney et al., 2001). Research usingthis particular scale appears appropriate considering that it is the only instrument that is specifi-cally designed to assess both positive and negative dimensions of perfectionism and has consis-tently yielded adequate psychometric properties among college students. Specifically, the two-factor structure of the APS-R has been supported via both exploratory and confirmatory factoranalyses (Rice, Ashby, & Slaney, 1998; Slaney et al., 1996). The first factor (Standards) is inter-preted as a positive indicator of perfectionism, and reflects high personal standards and expecta-tions. The second factor (Discrepancy) is interpreted as a negative aspect of perfectionism, andassesses the degree of distress experienced when an individual’s performance does not consis-tently meet their expected standards. The relationship between the two factors has been reportedas mild (e.g., r � �.12; Slaney et al., 2002), suggesting that, although related, each factor mea-sures a unique aspect of perfectionism.

The APS-R Standards and Discrepancy factors have also been combined to identify individ-uals with adaptive (i.e., those reporting high standards and low discrepancy scores) and maladap-tive (i.e., students reporting high standards and high discrepancy scores) perfectionistic tendencies.Research investigating these perfectionism subtypes has revealed differential patterns of scores onvarious psychosocial and personality measures. For example, adaptive perfectionists have reportedsignificantly higher scores on measures of self-esteem (Ashby & Rice, 2002), and internal locus ofcontrol (Perisamy & Ashby, in press) than maladaptive perfectionists. Further, LoCicero andAshby (2000) reported that adaptive perfectionists scored significantly higher on measures ofgeneral self-efficacy and social self-efficacy than both maladaptive perfectionists and nonperfec-tionists (i.e., low personal standards and low discrepancy scores).

The majority of research investigating perfectionism has been conducted using college stu-dent or adult populations. Very little research has explored the multidimensionality of the con-struct among a general sample of school-aged students. In the only published study to date,Accordino, Accordino, and Slaney (2000) administered the APS-R to a group of high schoolstudents. The findings revealed that students endorsing high standards reported higher grade-pointaverage (GPA) and lower scores on measures of depression and self-esteem. The opposite findingwas noted among students endorsing high discrepancy scores. However, although Accordino et al.established support for the distinction between the positive and negative indicators of perfection-ism, the relationship between intrapersonal and academic factors and students identified as adap-tive and maladaptive perfectionists was not explored.

Although Accordino et al. (2000) used high school samples, evidence obtained from studiesamong gifted children suggest that manifestations of perfectionism can be observed among youn-ger adolescents as well (see Parker & Adkins, 1995), with the subtypes differentially related to anumber of intra- and interpersonal variables including parental expectations and interpersonaldifficulties (Parker, 1997). Nevertheless, no research investigating perfectionism has used generalsamples of middle-school students. This dearth of research is interesting considering that perfec-tionism should not be construed as specific only to children with high intellectual ability (Nugent,2000). Given that parental expectations and pressures for schools to promote academic achieve-ment become more prominent in middle school (Eccles & Midgley, 1989; Roeser, Midgley, &Urdan, 1996; Wentzel, 1997), it is important to understand how perfectionism may differentiallyinteract with various academic and mental health variables among middle-school students in gen-eral. If psychosocial and academic differences between perfectionistic subtypes (and betweenperfectionistic subtypes and nonperfectionists) noted among college students are also found among

678 Gilman and Ashby

middle-school students, potential psychoeducational intervention strategies should likely take intoaccount whether or not (a) there is the presence of perfectionistic tendencies within the student,and (b) the type of perfectionism that the student endorses. Stated differently, interventions designedto enhance psychosocial outcomes of students with maladaptive perfectionistic tendencies (whomaintain high standards but find it difficult to continually meet these standards) may be funda-mentally different from strategies that target students who may be experiencing psychosocialand/or academic difficulties but do not establish high personal standards.

In this study, which in part replicates research conducted by Accordino et al. (2000), a groupof middle-school students were administered the APS-R and the Behavioral Assessment Systemfor Children (BASC: Reynolds & Kamphaus, 1992). Aside from its strong psychometric proper-ties (Reynolds & Kamphaus, 1992), the BASC was chosen due to its inclusion of both negative(psychopathology-based) and positive (adaptive well-being) indicators. Self-reported GPA wasalso attained. Considering previous findings related to perfectionism among college students andgifted students (e.g., Ablard & Parker, 1997; Hill, Zrull, & Turlington, 1997), specific school (i.e.,Attitude to School, Attitude to Teachers), interpersonal (Social Stress), and parent-related (Rela-tions with Parents) subscales, as well as the four composite scales of the BASC (Emotional Symp-toms Index, Clinical Maladjustment, School Maladjustment, and Personal Adjustment) werecompared with the Standards and Discrepancy scales of the APS-R. Further, to extend the findingsreported in Accordino et al. (2000), a cluster analysis was conducted to identify adaptive, mal-adaptive, and nonperfectionistic students. The selected BASC variables and self-reported GPAwere then compared across the cluster groups.

Method

Participants

A total of 185 middle school students enrolled in three schools in one school district in thesoutheast completed the research instruments. Permission to obtain individual socioeconomicstatus (SES) was not obtained, although the school populations were known to include a widerange of SES levels. The sample was comprised of 63% female and 68% Caucasian (vs. 22%African-American vs. 9% “Other”) students. There were 92 seventh graders and 93 eighth graders.The students ranged in ages between 12 and 15 years (M � 13.10, SD � .73). Because thisresearch was interested in potential differences in perfectionism among a general (i.e., nonclini-cal) sample of middle school students, and to maximize the probability that the APS-R and BASCitems would be interpreted with little difficulty, students formally diagnosed with learning and/oremotional disorders were excluded from the study.

Procedure

Approval to collect data was secured through the Superintendent’s office and from eachparticipating school’s principal. Participants in the study were required to obtain parental or guard-ian permission via a signed informed consent letter and to give written assent as well. Thirty-fivepercent of eligible students returned the parent consent form and thus participated in the study. Allparticipants assembled in their respective school cafeterias and were administered the test instru-ments. Students completed the instruments and also answered questions regarding their age, eth-nicity, gender, grade, and approximate grade average (i.e., A, B, C, D, or F). The surveys wereadministered in counterbalanced fashion. Students were also instructed to sit at least two seatsapart from each other. Further, at least one teacher/administrator was assigned to a specific testinglocation to monitor the students’ behavior and to help answer questions. These strategies weredesigned to reduce potential order and/or social desirability effects.

Perfectionism and Middle School Students 679

Measures

The Almost Perfect Scale–Revised (APS-R; Slaney et al., 1996) contains 23 items designed tomeasure adaptive and maladaptive components of perfectionism. Participants respond to the itemsusing a seven-point Likert rating scale (ranging from 1 � strongly disagree to 7 � strongly agree).The APS-R consists of three scales: Standards (seven items measuring personal standards, such as“I have high expectations of myself,” “I try to do my best at everything I do”), Discrepancy (12items measuring distress caused by the discrepancy between performance and standards, such as“My best just never seems to be good enough,” “I am hardly ever satisfied with my performance”)and Order (four items measuring degree of orderliness, such as “I am an orderly person”). Giventhe relatively lower internal consistency of the Order scale and its irrelevance in classifying per-fectionists (LoCicero & Ashby, 2000; Slaney et al., 1996), only the Standards and Discrepancyscales were used in the present study. Scores for the Standards scale range from 7 to 49, withhigher scores denoting higher self-imposed standards. Scores for the Discrepancy scale rangefrom 12 to 84, with higher scores denoting higher levels of perceived stress when establishedstandards are not achieved. Scoring of each subtest is attained by summing and dividing by thenumber of relevant items. Cronbach’s coefficient alphas among high school students have beenreported as .87 for the Standards scale and .92 for the Discrepancy scale (Accordino et al., 2000).In the current study, the internal consistency of the Standards scale (.82) and the Discrepancy scale(.87) were considered adequate for research purposes (Nunnally, 1978). The readability of theAPS-R (using the Flesch-Kincaid analysis: Microsoft Word, 2000) was determined to be at thefourth-grade level, suggesting that the items were easily interpretable for most middle schoolstudents. Support for the convergent and discriminant validity of the APS-R has also been obtainedvia significant and expected correlations related to the two factors. For example, the Standardssubscale has yielded positive relationships with measures of adaptive functioning including self-efficacy (r � .61; Braver, 1996) and self-esteem (r � .25; Ashby & Rice, 2002), while the Dis-crepancy factor has been significantly related to measures of psychological maladjustment includingdepression (r � .52; Rice et al., 1998), self-doubt (r � .62; Slaney et al., 2002), self-criticism (r �.64; Ashby & Rice, 2002), and excessive worry (r � .46; Slaney et al., 2002).

The Behavioral Assessment System for Children (BASC: Reynolds & Kamphaus, 1992) is a186-item multimethod, multidimensional measure used to evaluate the behavior and self-perceptions of children and adolescents. For this study, the self-report version was utilized. Con-sidering that the BASC is comprised of 14 separate subscales that measure negative as well aspositive dimensions of mental health, and considering the relatively low sample size, only selectedBASC subscales were considered in this study to preserve statistical integrity. Based on concep-tual (e.g., Parker, 1997) and empirical evidence (e.g., Accordino et al., 2000) to suggest thatperfectionism may differ with respect to school and family experiences as well as interpersonalrelations, the clinical subscales used in this study were Attitude to School, Attitude to Teachers,and Social Stress, with higher scores on these particular scales indicating higher levels of distress.The BASC Relations with Parents, which is an adaptive subscale, was also included. A higherscore on this particular subscale tends to reflect more positive parental relations. To also captureinformation that may not be specifically assessed by the BASC subscales, the BASC compositesscores (comprising a number of select subscales) were also analyzed (i.e., Clinical Maladjustment,School Maladjustment, and Personal Adjustment composites, as well as the Emotional SymptomsIndex). The BASC demonstrates good internal consistency with coefficient alphas ranging from.61 (Self-Reliance) to .89 (Depression) among the subscales (Reynolds & Kamphaus, 1992). Forillustrative purposes, the manual reported the internal consistency estimates for the select sub-scales used in this study as: Attitude to School (.82), Attitude to Teachers (.81), Relations with


Parents (.86), and Social Stress (.88). Coefficient alphas for the BASC Composite scores are:School Maladjustment (.89), Clinical Maladjustment (.95), Personal Adjustment (.90), and Emo-tional Symptoms Index (.96). Factor analytic techniques support the hypothesized factor structureof the instrument (Reynolds and Kamphaus, 1992).

Cumulative GPA was obtained by asking students to report their GPA since their entry intomiddle school. Similar to the rationale reported in Accordino et al. (2000), average GPA across allgrades was computed because it was believed to be more reliable than GPA obtained from one ortwo selective courses. Self-reported GPA ranged between 1.2 to 4.0 (M � 3.2, SD � .84). Althoughpermission to obtain actual grade-point average could not be obtained, analyses of the distributionof scores revealed a slight negative skew but not significantly different from normal. Kurtosis ofthe distribution also did not indicate any significant departure from normal. Thus, there appearedto be minimal evidence of response distortion. Nevertheless, self-reported GPA must be acknowl-edged as a limitation in this study.

Data Analyses

Analyses of the data were explored using several methods. First, bivariate correlations wereconducted to determine whether the relationship between the APS-R Standards and Discrepancyscales differed across self-reported GPA and various BASC scales in expected directions. Second,separate multiple regression analyses were conducted to determine how the independent variables(i.e., the APS-R Standards and Discrepancy Scales) predicted the dependent variables (i.e., self-reported GPA and the BASC scales). Given the number of variables used in the regression analy-ses, the alpha was adjusted to .001 (� � .05/9) to reject the null hypothesis. The Variance InflationFactor (VIF) was computed to detect the presence of multicollinearity. Neither independent vari-able had an individual VIF greater than 2, suggesting little evidence of substantial correlationamong the Standards and Discrepancy Scales. Finally, following the strategy of previous recom-mendations for conducting cluster analysis (i.e., Hair, Anderson, Tathan, & Black, 1995; Parker,1997; Rice, Mirzadeh, & Ali, 2000), the APS-R Standards and Discrepancy subscale scores werestandardized and submitted to an initial hierarchical cluster analysis. Ward’s agglomorative min-imum variance technique was employed, which measures squared Euclidian distances from anobtained data matrix (Ward, 1963) to identify individuals sharing similar perfectionism profiles.

Results

Pearson bivariate correlations between the APS-R Standards and Discrepancy scales, theBASC scales, and self-reported GPA are presented in Table 1. All correlations were in the expecteddirection and all were statistically significant, with the exception of the relationship between theBASC Social Stress subscale, the Clinical Maladjustment composite, and the APS-R Standardsscale. Self-reported GPA was significant and positively correlated with the APS-R Standards scale(r � .50, p � .01) and negatively correlated with the Discrepancy scale (r � �.29, p � .01). TheStandards subscale was significantly and positively related to the BASC adaptive indicators (Par-ent Relations, Personal Adjustment composite), and negatively related to the BASC clinical scales,particularly those measuring negative school experiences. Relationships with the Discrepancyscales were most robust, with a number of moderate but significant positive correlations with theBASC clinical indicators (Social Stress subscale, and the Clinical Maladjustment and EmotionalSymptoms Index Composite scores). The highest negative correlation was obtained between theDiscrepancy scale and the BASC Personal Adjustment Composite (r � �.46, p � .01).

Table 2 reports the regression equations for the APS-R Standards and Discrepancy scalespredicting self-reported GPA and BASC variables. Effect sizes across all equations ranged frommedium to large (Cohen, 1988). Given the number of variables analyzed, only significant findings


will be reported. The APS-R Standards subscale was a positive predictor of the BASC adaptiveindicators (i.e., the Parent Relations subscale and Personal Adjustment cluster) and was also aunique negative predictor of school-related variables (i.e., the BASC Attitude to Teacher andAttitude to School subscales and the School Maladjustment cluster). The APS-R Discrepancysubscale was a unique negative predictor of the BASC Social Stress and interpersonal distressindicators (i.e., Clinical Maladjustment and the Emotional Symptoms Index).

Standards and Discrepancy were also differentially predictive of GPA, parental relations, andpositive adjustment. The effect size with respect to GPA was the largest of the regression equations

Table 1Correlations between APS-R Standards and Discrepancy Scales,Select BASC Scales, and Self-Reported Grade Point Average

APS-R Scale

Standards Discrepancy

GPA .50** �.29**BASC subscales

Parent relations .31** �.37**Social stress �.11 .45**Attitude to school �.37** .19**Attitude to teacher �.24** .21**

BASC composite scalesSchool maladjustment �.29** .20**Clinical maladjustment �.13 .45**Personal adjustment .29** �.46**Emotional Symptoms Index (ESI) �.17* .45**

Note: Ns range between 165 to 185; APS-R � Almost Perfect Scale–Revised; BASC � Behavioral Assessment Scale for Children.

*�p � .05.**�p � .01.

Table 2Multiple Regression Analyses for the APS-R Standards and Discrepancy Scales Predicting Reported GPAand BASC Variables

Standards Discrepancy

B SE B � B SE B � R 2 Radj2 ES

Social stress �.12 .11 .08 �.31* .05 .44 .21 .20 .45Parent relations .42* .11 �.08 �.22* .04 �.34 .21 .20 .45Attitudes to school �.53* .12 �.32 .11 .05 .15 .14 .13 .37Attitudes to teachers �.39* .13 �.22 .14 .05 .18 .09 .08 .30School maladjustment �.46* .12 �.27 .12 .05 .17 .11 .10 .33Clinical maladjustment �.14 .10 �.09 .30* .05 .45 .22 .21 .47Personal adjustment .37* .11 .24 �.29* .04 �.43 .27 .26 .52ESI �.07 .05 �.11 .13* .02 .43 .21 .20 .46GPA .61* .01 .48 �.14* .01 �.26 .31 .30 .56

Note: *�p � .001.


and closely paralleled that found among high school students (Accordino et al., 2000). In general,every unit increase in a student’s standards represented almost half a unit increase in their GPA,while a unit decrease in their perceived failure to meet these standards yielded almost a third of aunit decrease in their GPA.

Although the correlation and regression analyses revealed differences with respect to theAPS-R Standards and Discrepancy scales, it was also important to determine how perfectionisticsubtypes may report school, intrapersonal, and interpersonal differences. Using Ward’s (1963)cluster analytic technique, agglomeration coefficients supported a three-cluster solution. Clustercentroids derived from the hierarchical cluster analysis were then used in a subsequent nonhier-archical k-means cluster analysis. Convergence on the final clusters was achieved after seveniterations and yielded 58 participants in the first cluster, 46 participants in the second cluster, and81 participants in the third cluster. Average APS-R subscale scores for these clusters appear inTable 3.

A one-way analysis of variance revealed significant differences between clusters on the Stan-dards and Discrepancy APS-R scales ( p � .0001). Results from Tukey pairwise comparisonsfacilitated the labeling of the clusters. For example, participants in Clusters 1 and 3 were notsignificantly different on Standards, although both had significantly higher scores than those inCluster 2. However, Cluster 1 had significantly higher Discrepancy scores than Cluster 3. Conse-quently, Cluster 1 appeared to be theoretically consistent with maladaptive perfectionism (highstandards and high discrepancy), whereas Cluster 3 appeared to be consistent with adaptive per-fectionism (high standards and low discrepancy). Participants in Cluster 2 had significantly lowerStandards scores, consistent with nonperfectionism. The percentage of children placed in eachcategory was consistent with previous cluster analyses utilizing gifted children (e.g., Ablard &Parker, 1997; Parker, 1997).

Table 3APS-R Standard and Discrepancy Scores by Perfectionism Cluster

Cluster Standards Discrepancy

1(maladaptive)

N 58 58Mean 42.36 54.91

Std. Deviation 3.49 9.79

2(nonperfectionist)

N 46 46Mean 32.02 39.37


3(adaptive)

N 81 81Mean 43.91 28.79


TotalN 185 185

Mean 40.47 39.61Std. Deviation 6.28 14.56


Utilizing the derived clusters, the data were then analyzed using a one-way multivariateanalysis of variance (MANOVA). The between-subjects factor was perfectionism (adaptive per-fectionists, maladaptive perfectionists, and nonperfectionists). The dependent variables were theBASC scales and self-reported GPA. The Wilks’ Lambda served as the chosen omnibus test. Aspecific main effect was noted among the three cluster groupings, Wilks’ � � .67, F(18,268) �3.32, p � .001. The multivariate effect size (�2) was moderate (.18). Univariate F-tests were thenconducted to determine where specific differences were found.

Table 4 reports the means and standard deviation of the dependent variables by cluster group,and univariate test results. The BASC scales are reported in T-scores to facilitate ease in interpre-tation. All univariate tests were statistically significant. Tukey’s pairwise comparisons indicatedthat with the exception of the BASC Attitude to Teacher and the School Maladjustment Cluster,students identified as adaptive perfectionists were significantly different from both maladaptiveperfectionists and nonperfectionists. Adaptive perfectionists reported fewer school difficultiesand difficulties with their parents and social relations, and less intrapersonal distress than mal-adaptive perfectionists. The greatest magnitude of difference was obtained on the Personal Adjust-ment cluster, where adaptive perfectionists (M � 55.10, SD � 6.62) reported significantly higheradaptive functioning than both maladaptive perfectionists (M � 48.40, SD � 10.34) and nonper-fectionists (M � 49.39, SD � 10.64). Further, adaptive perfectionists reported significantly higherGPAs (M � 3.52, SD � .65) than both maladaptive (M � 3.12, SD � .74) and nonperfectionists(M � 2.85, SD � .87). Although no significant mean score differences were noted between mal-adaptive and nonperfectionistic students across the dependent variables, a consistent pattern emergedwhere nonperfectionists reported higher scores on the School Maladjustment cluster, and Attitudeto School and Attitude to Teacher subscales. They also reported slightly lower GPA than maladap-tive perfectionists.

Table 4GPA and BASC Means and Standard Deviations by Cluster Group, with Results of Univariate F-Tests,Tukey Post Hoc Testing, and r2 as a Measure of Effect Size

Cluster 1(MaladaptivePerfectionists)

Cluster 2(Nonperfectionists)

Cluster 3(Adaptive

Perfectionists)

M SD M SD M SD F p r2

BASC subscalesSocial Stress 52.76a 11.31 48.94ab 10.31 44.85b 8.98 8.45 .000 .11Parent Relations 46.64a 10.85 46.36a 10.36 53.73b 5.88 11.79 .000 .14Attitude to School 52.78a 11.18 56.88a 9.61 48.12b 8.69 9.47 .000 .12Attitude to Teacher 54.07abc 10.35 56.88ab 11.29 49.71ac 10.30 5.65 .004 .07

BASC cluster scoresSchool maladjustment 54.20abc 11.05 57.42ab 9.59 50.22ac 9.86 5.90 .003 .08Clinical maladjustment 52.56a 10.01 49.64a 8.75 45.40b 8.22 8.93 .000 .11Emotional Symptoms Index 50.93a 4.31 49.39a 4.92 47.10b 3.23 9.42 .000 .15Personal adjustment 48.40a 10.34 48.78a 10.64 55.10b 6.62 12.72 .000 .18GPA 3.12a .74 2.85a .87 3.52b .65 10.45 .000 .13

Note: N � 185 (cluster 1 � 58, cluster 2 � 46, cluster 3 � 81); F-test df � 2,142; rows with differing superscriptsdenote significant mean score differences.


Discussion

The results of this study revealed a number of findings related to perfectionism among ageneral sample of middle school students. Holding high personal standards was positively andsignificantly related to relations with parents, interpersonal relations, overall personal adjustment,positive perceptions of the school environment, and self-reported GPA. These results were con-sistent with previous studies among high school students (Accordino et al., 2000), and collegestudents (Brown, Heimberg, Frost, Makris, Juster, & Leung, 1999; Rice et al., 1998). High stan-dards were predictive of students’ positive attitudes towards their school, teachers, and generaladaptation to their school environment was also consistent with findings among high school stu-dents (Accordino et al., 2000) and provides indirect support for recently constructed models regard-ing academic motivation. In these models, establishing high internal expectancies (i.e., standards)for success is one element for positive academic outcomes and experiences (e.g., Eccles, 1998;Wigfield & Eccles, 2000). Conversely, lower standards or expectations are considered to be aprime contributor of low motivation for achievement and high intrapersonal distress (Roesser,Eccles, & Sameroff, 1998).

The present findings regarding the maintenance of high standards are also inconsistent withprevious theories of perfectionism (e.g., Burns, 1980; Pacht, 1984) that emphasized the negativeaspects of holding such standards. The current study suggests that, at least among this sample ofmiddle-school students, establishing high standards beneficially influence, rather than negativelydetract from, a number of academic, intrapersonal, and interpersonal variables. Nevertheless,what also appears to be the case is that while establishing high standards may be beneficial,believing that these standards cannot be consistently attained may contribute to negative psycho-social and educational outcomes for some children.

Up to this point, the general findings are consistent with and essentially replicate thosereported by Accordino et al. (2000). Nevertheless, it was unclear from that study how adaptiveand maladaptive perfectionistic students may differ on psychosocial and educational variables,or how each perfectionistic subgroup differed from nonperfectionistic students. In the presentstudy, the results of the MANOVA and follow-up tests indicated that adaptive perfectionists havemore positive intrapersonal, interpersonal, and academic experiences than either maladaptive ornonperfectionistic students. For example, maladaptive perfectionists reported higher intraper-sonal difficulties and greater social stress than adaptive perfectionistic children. These findingsare consistent with a recent study investigating coping resources and perfectionism in middle-school students. In that study, LoCicero, Blasko, Ashby, Bruner, Martin, and Edge (2001) foundthat adaptive perfectionists reported significantly higher confidence in social situations than mal-adaptive perfectionists. Thus, the discrepancy between established standards and the perceivedinability to consistently meet these standards may not only contribute to a student’s intrapersonaldistress, but may also hinder their comfort and flexibility in interacting with others (Hill, Zrull,& Turlington, 1997).

Further, adaptive perfectionists reported a significantly higher GPA (corresponding to a B�average) than those reported among maladaptive (corresponding to a B average) and nonperfec-tionists (corresponding to a C� average). There are obvious limitations inherent in self-reportedGPA that must be acknowledged (such as potential response bias). Nevertheless, the finding thatGPA differed across groups provides some support for the validity of these self-reports. That is, bydefinition, nonperfectionists do not establish high personal standards, and thus their collectiveGPA would be expected to be lower than students with high personal standards (which was foundin this study). On the other hand, maladaptive perfectionists, who set high personal standards butcannot accept their limitations, would be expected to have lower GPAs than peers who set similar


high standards but also are more accepting of occasions when these standards are not attained.These GPA differences among perfectionistic subtypes may be explained from the standpoint of“flow” theory (Csikszentmihalyi, 1990). In brief, for flow to occur, high concentration, interest,and enjoyment in an activity must all simultaneously occur. Recent studies have reported that highschool students who experience flow differ in psychoeducational outcomes from students engagedin experiences that evoke anxiety or apathy (see Shernoff, Csikszentmihalyi, Schneider, & Sher-noff, 2003). If such findings can be extended to the present study, it may be that maladaptiveperfectionists (who are driven more by the fear of failure than the pursuit of academic excellence)self-create situations that preclude the experience of flow, thus contributing to lower academicachievement (in comparison to adaptive perfectionists). Granted, this is speculative given that thedirect relationship between perfectionism and flow was not investigated in this study, and futureresearch should explore this hypothesis. Nevertheless, the finding that GPA differs between per-fectionistic subtypes suggests that maladaptive perfectionists not only report greater psychosocialdistress, but that this added distress may contribute to lower than expected academic achievement(insofar as grade point average is concerned).

In summary, the present study extended the research by Accordino et al. (2000), and providesfurther support for the multidimensional nature of perfectionism among middle-school students.Establishing high personal standards does not seem detrimental and may lead to positive intraper-sonal, interpersonal, and academic outcomes. What can be viewed as problematic is not the settingof high personal standards per se, but an unwillingness to accept the inevitable fact that such highstandards will not be constantly met.

One might argue that too much is made of the current findings related to students identified asmaladaptive perfectionists. Indeed, initial interpretations of the data may lead one to conclude thatthere is no compelling reason to focus on these particular students because they did not signifi-cantly differ from children identified as nonperfectionists. However, the education and psycho-logical literature is replete with articles explicating how to motivate and teach students who aredisengaged from the learning process (see Miserandino, 1996; Wentzel, 1997). Ironically, giventheir high achievement standards, students identified as maladaptive perfectionists are motivatedto excel but are hindered from reaching their goals due to their beliefs that their work is simplynever good enough. This hindrance may subsequently lead to frustration, procrastination, and anoverall inability to reach their fullest academic and personal potential. In this regard, psychoedu-cational and/or psychosocial interventions that target maladaptive perfectionistic students may bequite different from interventions that target nonperfectionistic students. For example, given thathigh achievement expectations are already present among maladaptive perfectionists, rather thanincrease the student’s motivation and expectation to learn, the goal might be to assist their pursu-ance of their high standards in a manner that is more realistic and productive (Chang, 2000). Forexample, Hamachek (1978) suggested that psychologists and counselors can aid maladaptive per-fectionists by teaching them to: (1) be selective in tasks that require perfectionistic standards; (2)give themselves permission to be imperfect; (3) set reasonable and reachable goals; and (4) chooseat least one activity that they can do without self-criticism. Nugent (2000) outlined several ways inwhich to help maladaptive perfectionistic children accept their limitations including bibliother-apy, group therapy discussion, and art activities. Finally, Chang (2000) suggested that to help themaladaptive perfectionist, illogical and unrealistic thoughts must be replaced by more logical andrealistic expectations. For instance, a child with maladaptive perfectionistic beliefs (e.g., “I mustdo everything perfectly”) would be trained to replace that thought with a more rational one (“Imay not do it perfectly, but I will still try to do the best I can”). Finally, LoCicero, Ashby, and Kern(2000) suggested that teachers and adults may wish to validate a student’s progress towards anachievement goal rather than rewarding the student only when the goal is attained. In this manner,


acknowledging effort over outcome may help maladaptive perfectionistic students develop beliefsand behaviors more in line with adaptive perfectionists.

Limitations

Although the present study was the first to investigate the construct of perfectionism amonga general sample of middle school students, several limitations must be noted. First, and as pre-viously noted, the precise definition of perfectionism continues to be debated and is often definedby the instrument used (Parker, 1997). Although this study assessed perfectionism as measured bythe APS-R, it is by no means the only multidimensional instrument available. However, a recentconjoint factor analytic study comparing the APS-R with extant multidimensional perfectionismscales (Slaney et al., 2002) revealed highly similar factor loading across similar constructs. Nev-ertheless, it is important to examine the interaction of intrapersonal, interpersonal, family, andschool variables with other models and measures of perfectionism. Second, the selected outcomevariables investigated in this study were based on previous conceptual papers and empirical find-ings. These variables are by no means exhaustive, and it is important to assess other variables ofinterest (e.g., coping, life satisfaction, etc.) to examine how they might mediate the influence ofperfectionism.

Third, the results reported herein are based on self-report measures obtained in one setting,thus possibly introducing method variance, particularly with respect to self-reported GPA. Thismethodological concern was minimized when one considers that (a) the procedure used to obtainthe data was quite controlled, (b) the skew and kurtosis of self-reported GPA was within thenormal range of score distribution, and (c) the findings reported were all in the expected direction.Nevertheless, obtaining permanent products (e.g., actual GPA) and assessing perfectionism acrosstime may yield important information on the potential developmental progression of the constructand its vicissitudes in response to life events. Fourth, the consent rate was relatively low, intro-ducing the possibility of selection bias, which again emphasizes the need for future researchincorporating larger sample sizes to corroborate the current findings. Such research is particularlynecessary considering that this study was among the first to use the APS-R among middle-schoolstudents. Thus, the psychometric properties of the instrument for this age group await futureempirical analysis. Finally, the findings are based on a sample of students from one school districtin the southeast. Additional samples from various locations are needed to support the generaliz-ability of the findings.

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Multidimensional perfectionism in a sample of middle school students: An exploratory investigation