Resiliency Scales

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Psychology Canadian Journal of School

DOI: 10.1177/0829573508316592 8, 2008;

2008; 23; 41 originally published online AprCanadian Journal of School PsychologySandra Prince-Embury

Symptoms, and Clinical Status in AdolescentsThe Resiliency Scales for Children and Adolescents, Psychological

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41

Canadian Journal ofSchool Psychology

Volume 23 Number 1June 2008 41-56

© 2008 Sage Publications10.1177/0829573508316592

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The Resiliency Scales forChildren and Adolescents,Psychological Symptoms, andClinical Status in AdolescentsSandra Prince-EmburyResiliency Institute of Allenhurst LLC

Abstract: The Resiliency Scales for Children and Adolescents (RSCA) are three scalesfor assessing the relative strength of three aspects of personal resiliency as a profile inchildren and adolescents. This article presents preliminary evidence to support the useof the RSCA in preventive screening. First, this article examines associations betweenthe RSCA Global scale and index scores and psychological symptoms as assessed bythe Beck Youth Inventory–II in a normative sample of adolescents. A normative sam-ple was chosen as screening would presumably occur in a nonclinical setting. Findingssuggest associations between psychological symptoms and the RSCA scale and indexscores. Specifically, positive associations were found between psychological symptomsand the RSCA Vulnerability Index and the Emotional Reactivity scale score. Negativeassociations were found between psychological symptoms and the RSCA ResourceIndex, Sense of Mastery, and Sense of Relatedness scale scores. Second, the RSCA isexamined as a potential predictor of clinical status differentiating the normative samplefrom a clinical sample. Results support the use of the RSCA in screening protocols forthe identification of vulnerability that does not rely on the presence of an identified dis-order or clearly defined psychological symptoms.

Résumé: Les Resiliency Scales for Children and Adolescents (RSCA), constituéesde trois échelles, servent à évaluer la force relative de trois aspects de la résiliencepersonnelle en tant que profil chez les enfants et les adolescents. Nous présentonsici des données préliminaires qui soutiennent l’emploi des RSCA lors de dépistagespréventifs. Dans un premier temps, nous examinons, dans un échantillon normatifd’adolescents, des associations entre l’échelle globale des RSCA et des symptômespsychologiques établis selon l’Inventaire Beck-II pour adolescents. Notre choix a portésur un groupe normatif, car le dépistage se ferait probablement dans un cadre non clin-ique. Les résultats suggèrent des associations entre les symptômes psychologiques etles scores sur l’échelle et les index des RSCA. Plus précisément, on note des associa-tions positives entre les symptômes et l’index de Vulnérabilité et le score de l’échellede Réactivité émotionnelle des RSCA. Des associations négatives apparaissent entre lessymptômes psychologiques et l’index de Ressource, l’échelle du Sens de la maîtrise etcelle du Sens de connexion des RSCA. Dans un deuxième temps, nous évaluons les RSCAen tant que prédicteurs potentiels de l’état clinique, pour différencier un échantillon



normatif d’un groupe clinique. Les résultats soutiennent l’emploi des RSCA dans lesprotocoles de dépistage destinés à identifier la vulnérabilité en l’absence d’un troubleidentifié ou de symptômes psychologiques clairement définis.

Keywords: resiliency; vulnerability; psychological symptoms; clinical status

Studies of psychological vulnerability and associated variables in children and ado-lescents have been complex, multifaceted, interactive, and longitudinal (Garmezy,

1971; Garmezy, Masten, & Tellegen, 1984; Luthar, 1991; Luthar, Cicchetti, &Becker, 2000; Luthar & Zelazo, 2003; Luthar & Zigler, 1991; Masten, 2001; Masten& Powell, 2003; Rutter, 1987; Wright & Masten, 1997). According to this research,risk and vulnerability are the cumulative effects of multiple environmental and per-sonal circumstances (Fischhoff, Nightingale, & Iannotta, 2001). However,researchers have not reached consensus on terminology, on the underlying constructsof vulnerability and resiliency, or on whether they are systematically related to eachother (Blum, McNeely, & Nonnemaker, 2001; Luthar & Zelazo, 2003). Severalresearchers have suggested that vulnerabilities are counterbalanced by resources(Patterson, McCubbin, & Warwick, 1990), assets (Bensen, 1997), protective factors(Blum, 1998), and resilience (Masten & Coatsworth, 1998; Masten & Curtis, 2000).

The many facets of risk and vulnerability and their interactive effects have madetranslation of research findings into assessment tools for clinical application quitedifficult. Fischhoff et al. (2001) suggested that measures that tap adolescent vulner-ability are sorely needed. Previous research has identified lists of risk and protectivefactors, but in ways that are not simple to measure, are not systematically related toeach other, may not be generalizable across populations, and are not easily translatedinto tools for clinical application. This study employs the Resiliency Scales forChildren and Adolescents (RSCA; Prince-Embury, 2006, 2007) to assess both per-sonal resource and vulnerability in adolescents as these are related to self-reportedpsychological symptoms and clinical status.

Particularly challenging is the assessment of personal vulnerability that is notbased on preexisting syndrome-related symptoms. Presumably, the distinctionbetween assessing vulnerability in adolescents as opposed to symptoms in adoles-cents is the increased opportunity for preventive screening. Once psychologicalsymptoms have occurred, there is more of a chance that the symptoms have alreadyinterfered with the youth’s functioning and a greater likelihood that the symptomsmight crystallize into a psychological disorder.

This article presents preliminary evidence to support the use of the RSCA(Prince-Embury, 2006, 2007) for use in preventive screening in adolescent popula-tions before the emergence of psychopathology. The RSCA is based on three theo-retical constructs that emerge from developmental theory and previous research (seePrince-Embury, 2006, 2007). Two of these constructs represent sense of mastery andsense of relatedness, which have previously been identified as protective personal

42 Canadian Journal of School Psychology



characteristics. The third construct, emotional reactivity, is arousability that mightput an individual at risk when confronted with adversity.

The present study is a preliminary examination of the relationship among RSCAGlobal scale and index scores, psychological symptoms, and clinical status toexplore the potential use of the RSCA in screening for psychological vulnerabilityin adolescents.

Vulnerability Index

The Vulnerability Index is a summary score that is based on the three-factor struc-ture underlying the RSCA. See Prince-Embury (2006, 2007) for development of theRSCA and Prince-Embury and Courville (2008 [this issue]) for a more comprehen-sive examination of the three-factor framework. The RSCA Vulnerability Index rep-resents a systematic, quantified estimate of psychological vulnerability in relation topersonal resiliency. The RSCA Vulnerability Index reflects the discrepancy betweena youth’s experience of emotional reactivity, represented by the Emotional Reactivityscale score, and his or her perceived personal resources represented by his or herRSCA Resource Index score. The Vulnerability Index is consistent with theories thatvulnerability and resources counterbalance each other. Specifically, resiliency isdefined as having sufficient personal resources to match one’s emotional reactivity.Conversely, personal vulnerability is defined as having personal resources that aresignificantly below one’s level of emotional reactivity.

Emotional Reactivity

The RSCA Emotional Reactivity scale is one component of the VulnerabilityIndex discussed above. Much research in the field of developmental psychopathol-ogy has found that a child’s development of pathology in the presence of adversityis related in some way to the child’s emotional reactivity and his or her ability tomodulate and regulate this reactivity. Strong emotional reactivity and associated dif-ficulty with self-regulation have been associated with behavioral difficulty and vul-nerability to pathology. Conversely, the ability to modulate or otherwise manageemotional reactivity has been found to be a significant factor in fostering resiliency(Cicchetti, Ganiban, & Barnett, 1991; Cicchetti & Tucker, 1994; Rothbart & Bates,1998; Thompson, 1990). Emotional reactivity has been alternately labeled as vul-nerability, arousability, or threshold of tolerance prior to the occurrence of adverseevents or circumstances. Rothbart and Derryberry (1981) indicated that reactivity isthe speed and intensity of a child’s negative emotional response and that regulationis the child’s capacity to modulate that negative emotional response. The RSCAEmotional Reactivity scale is designed to tap the youth’s perceived sensitivity,recovery time, and impairment because of emotional arousal.

Prince-Embury / Resiliency Scales for Children and Adolescents 43



Perceived Personal Resources

Two of the constructs within the three-factor framework of the RSCA may be col-lectively considered perceived personal resources. These two constructs are assessedby the Sense of Mastery and the Sense of Relatedness scale scores. These two scoresare averaged and standardized as the RSCA Resource Index (Prince-Embury, 2007).Although these constructs are theoretically distinct, the two scale scores are highlycorrelated with each other (see Prince-Embury & Courville, 2008) and, for the pur-pose of creating an index score of perceived personal resources, may be combined.

Sense of Mastery

The Sense of Mastery scale builds on previous definitions of self-efficacy. RobertWhite (1959) introduced the construct as a sense of mastery or efficacy in childrenand youth that enables them to interact with and enjoy cause-and-effect relationshipsin the environment. According to White, a sense of competence, mastery, or efficacy isdriven by an innate curiosity, which is intrinsically rewarding and the source of prob-lem-solving skills. Albert Bandura (1977) believed that self-efficacy could be devel-oped through learning. Sense of mastery as represented by the Sense of Masteryscale score includes the youth’s sense of optimism, self-efficacy, and adaptability(Prince-Embury, 2006, 2007).

Sense of Relatedness

Prior research has suggested that sense of relatedness may provide a buffer fromexternal adversity in two ways. First, the youth may view relationships as availablefor specific supports in specific situations. Second, internal mechanisms reflectingthe cumulative experience of previous support may in some way shield the childfrom potential negative psychological impact of specific events. Relationships andrelational ability as mediators of resilience have been supported in research by devel-opmental psychopathologists such as Werner and Smith (1982, 1992). Sense of relat-edness, as assessed here, includes the experiences of trust, comfort with others,perceived access to support, and tolerance of differences.

Questions Addressed by This Study

1. Preliminary concurrent validity for the RSCA was examined through the associa-tion of the RSCA scale and index scores with symptom severity in depression, anx-iety, anger, and disruptive behavior assessed by the Beck Youth Inventory–II(BYI-II) scale scores in a normative sample. A normative rather than clinical sam-ple was selected because the question addressed is one of screening in a nonclini-cal sample. These associations are examined through correlations between RSCAand BYI-II scores. Previous research has suggested that symptom severity would




be positively associated with higher scores on the Vulnerability Index and theEmotional Reactivity scale score representing vulnerability variables. Conversely,lower symptom severity would be associated with a higher Resource Index score,higher Sense of Mastery score, and higher Sense of Relatedness score representingresource variables.

2. In what way and to what extent of accuracy the RSCA scale and index scores pre-dict clinical status, defined as presence or absence of a clinical diagnosis, wasexamined. This relationship was examined through comparison of mean scores forthe clinical and nonclinical groups, through discriminant function analysis (DFA),and through the calculation of sensitivity, specificity, and positive and negative pre-dictive validity of the prediction equation. However, it is important to clarify thatthe prediction of general clinical status rather than prediction of specific disorderis of interest here. This is because the RSCA used as a screener would be generalrather than specific. In other words, use of the RSCA as a screener would be todetect vulnerability for the development of pathology in general and not as a diag-nostic predictor of specific disorders.

Method

Samples

The normative sample consisted of 100 males and 100 females, 15 to 18 yearsold, and was stratified to match the U.S. 2002 census by ethnicity, parent educationlevel, and region (Prince-Embury, 2006). Ethnicity of the clinical group was as fol-lows: 66% White, 15% Hispanic, 15% African American, 1% Other, and 3% Asian.Parent education level was distributed as follows: 22% had less than 12 years, 36%had 12 years, 28% had 13 to 15 years, and 15% had 16 years or more. The norma-tive sample included nine clinical cases to match the 5% prevalence of psy-chopathology that is customarily estimated for normative samples. Examinersadministered the test to individuals and to small groups in academic and office set-tings. Parents signed consent forms for teens younger than 18 years of age, and 18-year-olds signed an adult consent form. Participants were paid for their participation.Testing took place between May 2004 and April 2005.

A total of 37 examiners tested the entire sample. Examiners represented a varietyof education, health, and mental health professions and were paid examiners or con-sultants for PsychCorp. All were clinicians, teachers, and counselors who held amaster’s degree or PhD. Of these examiners, 20 were from urban areas (populationgreater than or equal to 50,000), 6 from suburban areas (population of 2,500 to50,000), and 11 from rural areas (population less than 2,500). The sample was drawnfrom 20 states across the United States.

The clinical sample was obtained by examiners described above who regularlytested adolescents and/or provided counseling or therapy. Most adolescents in theclinical samples were individually tested by individual examiners. A few were tested




in small groups of four or five individuals. A portion of the clinical samples was pro-vided by clinical sites, including a residential facility for children and adolescents inTexas and a correctional institution for juvenile offenders in Colorado. These exam-iners had a master’s degree or above. Criteria for inclusion in the clinical samplewere as follows:

The diagnosis needed to have been made within 3 three months prior to testing.The diagnosis needed to be made on the basis of a standard structured diagnostic inter-

view or standard diagnostic assessment tool plus an independently obtained confir-mation of the diagnosis.

The clinical sample of 169 adolescents, 48% females and 52% males, consistedof five groups of teens aged 15 to 18 diagnosed with depressive disorder (48), anxi-ety disorder (30), conduct disorder (55), or bipolar disorder (9) and a mixed clinicalgroup that included youth with dual diagnoses including attention-deficit/hyperac-tivity disorder (27). Ethnicity of the clinical group was as follows: 66% White, 15%Hispanic, 8% African American, 7% Other, and 4% Asian. For the clinical sample,parent education level was distributed as follows: 32% had less than 12 years, 28%had 12 years, 26% had 13 to 15 years, and 15% had 16 years or more. Although therewas an attempt to match the normative sample in collecting the clinical sample, therewere two significant demographic differences between the clinical sample and thenormative sample. These samples were the same in ethnic distribution, except thatthe clinical sample had 6% more youth identified as Other and 7% fewer identifiedas African American. The clinical sample had more youth whose parents had lessthan a 12th grade education and fewer students whose parents had a 12th grade edu-cation. The decision was made not to use matched samples as this would havereduced both sample sizes. Instead, the decision was made to include demographicvariables in the analyses.

Measures

RSCA. The Sense of Mastery scale is a 20-item self-report questionnaire writtenat a third grade reading level. Response options are ordered on a 5-point Likert-typescale: 0 (never), 1 (rarely), 2 (sometimes), 3 (often), and 4 (almost always). TheSense of Mastery scale consists of three conceptually related content areas: opti-mism about life and one’s own competence; self-efficacy associated with developingproblem-solving attitudes and adaptability, demonstrated by receptivity to criticism;and the ability to learn from one’s mistakes. Internal consistency for the Sense ofMastery scale was excellent, with an alpha of .95 for youth aged 15 to 18. Thetest–retest reliability coefficient for the Sense of Mastery scale was .86 for youthaged 15 to 18.

The Sense of Relatedness scale is a 24-item self-report questionnaire written at athird grade reading level. Response options are frequency based, ordered on a 5-point




Likert-type scale: 0 (never), 1 (rarely), 2 (sometimes), 3 (often), and 4 (almostalways). As used in this scale, a sense of relatedness refers to comfort with others,trust in others, perceived access to support by others, and the capacity to tolerate dif-ferences with others. Internal consistency was excellent for the Sense of Relatednessscale (.95 for youth aged 15 to 18). Test–retest reliability coefficients were good (.86for youth aged 15 to 18).

The Emotional Reactivity scale is a 20-item self-report questionnaire written at athird grade reading level. Response options are ordered on a 5-point Likert-type scale:0 (never), 1 (rarely), 2 (sometimes), 3 (often), and 4 (almost always). Unlike the Senseof Mastery and Sense of Relatedness scales, lower scores on the Emotional Reactivityscale are indicative of resiliency, and high scores are indicative of vulnerability. Thisscale consists of three conceptually related content areas: sensitivity or the thresholdfor reaction and the intensity of the reaction, length of time it takes to recover fromemotional upset, and impairment while upset. Internal consistency for the EmotionalReactivity scale was excellent, with an alpha coefficient of .94 for youth aged 15 to 18.The test–retest reliability coefficient was .88 for youth aged 15 to 18.

The Resource Index is the standardized average of the Sense of Mastery scale andSense of Relatedness scale T-scores. This average is an estimate of the youth’s per-sonal strength or resources weighting Sense of Mastery and Sense of Relatednessequally. Internal consistency for the Resource Index was excellent, with an alphacoefficient of .97 for youth aged 15 to 18. The test–retest reliability coefficient was.77 for youth aged 15 to 18.

The Vulnerability Index is the standardized difference between the EmotionalReactivity T-score and the Resource Index. Internal consistency for the VulnerabilityIndex was excellent, with an alpha coefficient of .97 for youth aged 15 to 18. Thetest–retest reliability coefficient was .90 for youth aged 15 to 18.

BYI-II. The BYI-II (Beck, Beck, Jolly, & Steer, 2005) consists of Depression,Anxiety, Anger, and Disruptive Behavior Inventories. Each 20-item self-report scaledemonstrated adequate to good reliability. The BYI-II scale scores were used to tappsychological symptoms.

Procedure

Adolescents completed the RSCA and the BYI-II within the same test period. Thesequence of tests administered was based on previous pilot studies and was designedto place tests that tapped symptoms last. The RSCA was administered before theBYI-II. The RSCA was administered in the published booklet form that presentsSense of Mastery first, Sense of Relatedness second, and Emotional Reactivity last.The BYI-II was administered in the published booklet form that presents Anxietyfirst, followed by the Depression, Anger, and Disruptive Behavior Inventories.




Analyses

Analysis 1. The association among BYI-II Depression, Anxiety, Anger, andDisruptive Behavior scores and the RSCA Vulnerability and Resource Indexes andSense of Mastery, Sense of Relatedness, and Emotional Reactivity scale scores wasexamined in a nonclinical adolescent sample using simple correlation analyses.

Analysis 2. A preliminary examination of the relative contribution of the RSCA andBYI-II scores and demographic variables to accurate classification of clinical status inadolescents was explored in two ways. First, simple t tests were used to comparemeans for nonclinical and clinical samples, and affect sizes were evaluated usingCohen’s d. Second, DFA was employed using clinical status as the dependent variableand RSCA scores, index scores, BYI-II scores, and demographic variables as inde-pendent variables. Independent variables were entered using a stepwise method allow-ing carriers to enter in the order of the size of their correlation. Sensitivity, specificity,and positive and negative predictive power yielded by the DFA are discussed.

Results

Correlations With the BYI-II in Adolescents

Table 1 illustrates a strong positive correlation between the Vulnerability Index scoreand the Emotional Reactivity score and all BYI-II scores of negative affect and behavior.The Vulnerability Index score had the following significant positive correlationswith the BYI-II scores: .65 (Anxiety), .66 (Disruptive Behavior), .75 (Depression),and .77 (Anger). Similarly, high positive correlations were found between the


Table 1Correlations Between the RSCA and Beck Youth

Inventory–II (BYI-II) Scores in a Nonclinical Adolescent Sample

BYI-II

Resiliency Scale or Index Anx Depress Anger Disrupt M SD SE

Mastery –.51 –.59 –.61 –.53 50.00 10.01 0.71Relatedness –.50 –.56 –.57 .45 49.99 10.02 0.71Reactivity .65 .74 .76 .67 50.00 9.99 0.71Resource –.53 –.61 –.62 –.51 50.00 9.48 0.67Vulnerability .65 .75 .77 .66 50.00 10.00 0.71M 50.00 50.03 49.89 50.01SD 9.94 9.88 9.97 9.99SE 0.70 0.70 0.70 0.71

Note: N = 200. Anx = Anxiety; Depress = Depression, Disrupt = Disruptive Behavior.



Emotional Reactivity score and scores on all BYI-II scores: .65 (Anxiety), .67(Disruptive Behavior), .74 (Depression), and .76 (Anger).

These findings provide support for the hypothesis that vulnerability, representedby the RSCA Vulnerability Index and Emotional Reactivity score, is associated withpsychological symptoms represented by the BYI-II in a normative group. In addi-tion, the Vulnerability Index score and the Emotional Reactivity score correlate withBYI-II scores across affective domains. Table 1 also illustrates high negative corre-lations between the Resource Index score and the BYI-II scores: –.51 (DisruptiveBehavior), –.53 (Anxiety), –.61 (Depression), and –.62 (Anger). Similarly, high neg-ative correlations were found between the Sense of Mastery (–.51 to –.61) and theSense of Relatedness (–.45 to –.57) scales and all BYI-II scores.

Predicting Clinical Status

All differences between RSCA and BYI-II mean scores for nonclinical and clin-ical groups are significant in the predicted direction (see Table 2). The nonclinicalgroup scored higher on Sense of Mastery, Sense of Relatedness, and the Resource


Table 2Means, Standard Deviations, and Cohen’s d for Nonclinical and Clinical

Samples on Resiliency Scales for Children and Adolescents Scale and IndexScores and Beck Youth Inventory–II (BYI-II) Scores

Scale Status M SD Difference t df Significance Cohen’s d

Mastery non 50.93 9.15 10.52 10.53 358 < .0001 1.11clin 40.41 9.82

Relatedness non 49.99 8.99 9.95 10.74 358 < .0001 1.12clin 40.04 10.26

Reactivity non 50.00 8.60 8.82 –10.62 357 < .0001 1.20clin 58.82 9.09

Resource non 50.00 8.96 10.31 11.38 358 < .0001 1.21clin 39.69 9.88

Vulnerability non 48.81 8.75 12.13 –13.11 357 < .0001 1.50clin 60.94 8.74

Anxiety non 48.55 7.26 –9.10 –9.99 358 < .0001 1.07clin 57.65 9.68

Depression non 48.70 7.12 –9.83 –11.05 358 < .0001 1.19clin 58.53 9.42

Anger non 48.56 7.64 –9.30 –10.24 358 < .0001 1.09clin 57.86 9.37

Disruptive Behavior non 49.18 8.83 –8.65 –7.57 358 < .0001 .82clin 57.83 12.32

Note: Nonclinical (non) n = 191; clinical (clin) n = 169. Nine clinical cases included in standardizationssample were eliminated for this comparison.



Index. The clinical sample scored higher on Emotional Reactivity, Vulnerability, andall four BYI-II scores. Affect sizes are large for all differences. The largest effect sizewas for the Vulnerability Index score (d = 1.50).

DFA was employed to identify variables that best discriminated the nonclinicalsample of adolescents from the clinical sample (see Table 3 [all]). DFA was used todetermine which variables discriminate between two categorical groups, which inturn can be used to determine which variables are the best predictors of group mem-bership. In DFA, the dependent variable consists of discrete groups, and the purposeof the statistical function is to maximize the distance between those groups, to comeup with a function that has strong discriminatory power among the groups.

Variables entered as the independent variable included the following: (a) parentlevel of education, (b) gender, (c) RSCA scores (Sense of Mastery T-score, Sense ofRelatedness T-score, and Emotional Reactivity T-score), Index scores (Vulnerabilityand Resource) and BYI-II scores for Anxiety, Depression, Anger, and DisruptiveBehavior. Groups to be discriminated were coded according to clinical status as 0(nonclinical) or 1 (clinical).

It was hypothesized that the Vulnerability Index would be the best discriminatorbetween cases that were clinical and those who were nonclinical. Tables 3a, 3b, and 3c


Table 3aDiscriminant Function Analysis of Variables Predicting Clinical Status

Wilks’s Lambda Exact F

Step Entered Statistic df1 df2 df3 Statistic df1 df2 Sig.

1 Vulnerability Index .675 1 2 357.00 171.900 1 357.000 .00012 Beck Youth .641 1 1 357.00 99.642 2 356.000 .0001

Inventory–II Anxiety

Note: At each step, the variable that minimizes the overall Wilks’s Lambda is entered. Maximum numberof steps is 14. Minimum partial F to enter is 3.84. Maximum partial F to remove is 2.71.

Table 3bStructure Matrix and Standardized Canonical Discriminant Function

Coefficients for Variables Retained in Discriminant Function

StandardizedCanonical Discriminant

Structure Matrix Function Coefficient

Vulnerability Index .927 .758Beck Youth Inventory, Anxiety .723 .410



display the results of the DFA using a stepwise method, displaying functions enteredand retained as significant: Wilks’s Lambda, F value, significance of F, and χ2. Thefirst function included the Vulnerability Index and yielded a Wilks’s Lambda of .675and an F of 171.9 with 357 degrees of freedom, which was significant atp < .0001. The second function entered included the BYI-II Anxiety score. Thisfunction yielded a Wilks’s Lambda of .641 and an F of 99.64 with 356 degrees offreedom and was significant at p < .0001. Tables 3c and 3d provide a summary ofDFA including structure matrix, standardized canonical coefficient, eigenvalues, andclassification results. The structure matrix displays a high loading for both theVulnerability Index and the BYI-II scores on the final discriminant function. Thestandardized canonical coefficients indicate that the Vulnerability Index contributesmore unique variance to the function than does the BYI-II Anxiety score. The canon-ical correlation for the function was .599, indicating that this function accounted for36% of the variance in clinical membership.


Table 3cSummary of Canonical Discriminant Function Analysis

Eigenvalue

Function Eigenvalue % of Variance Cumulative % Canonical Correlation

1 .560 100 1 .599

Wilks’s Lambda

Test of Function(s) Wilks’s Lambda χ2 df Sig.

1 .641 158.260 2 .0001

Note: The second canonical discriminant function was used in the analysis.

Table 3dClassification Results for Discriminant Function Analysis

Classification Results

Predicted Group Membership

Clinical Status Nonclinical Clinical Total

Original Count Nonclinical 155 36 191Clinical 46 122 166

% Nonclinical 81.2 18.8 100Clinical 27.4 72.6 100

Note: 77.2% of original grouped cases correctly classified; 73% sensitivity; 81% specificity.



Sensitivity, Specificity, and Rate of Accurate Classification

Using the discriminant function predictive equation described above, the per-centage of original cases accurately classified was 77.2%. Sensitivity or percentageof actual clinical cases accurately predicted was 73%, and specificity or percentageof nonclinical cases accurately predicted was 81%. Stated differently, this predictiveequation yielded 19% false positives, or nonclinical cases that were misclassified asclinical. False negative percentage was 27%, meaning that this percentage of theclinical cases was missed using this equation. Positive predictive value refers to thechance that a positive test result will be correct. Negative predictive value refers tothe chance that a negative test result will be correct. The above analysis producedboth positive and negative predictive values of 77%.

When the Vulnerability Index was entered alone into the discriminant function(table not shown), sensitivity was 79% and specificity was 78%. The percentage oforiginal cases accurately classified was 78.6%. Therefore, removing the BYI-IIscores from the discriminant function decreased specificity but increased sensitivityby 6%, or 11 clinical cases. Examination of the Vulnerability Index score alone asan indicator suggests that in a nonclinical sample, a cut score of T = 55 optimizessensitivity. This cut score corresponds to the above-average range indicated in theRSCA manual (Prince-Embury, 2007). Other discriminant function analyses (tablenot presented) indicated that other combinations of variables accurately predictedclinical status to the same degree. For example, with the Vulnerability Indexremoved, the Resource Index was the primary predictor supplemented by the BYI-II Anxiety score and the RSCA Emotional Reactivity scale score.

Discussion

The analyses and results above present preliminary evidence to support the use ofthe RSCA in preventive screening for psychological vulnerability. Three interrelatedanalyses consistently provided support: simple correlation analysis, comparison ofmean scores of clinical and nonclinical samples, and DFA.

Significant correlations were found between the BYI-II scores and all of theRSCA scale and index scores for the normative sample. These findings provide evi-dence for the hypothesized positive associations between self-reported psychologi-cal symptoms and psychological vulnerability assessed by the RSCA VulnerabilityIndex and Emotional Reactivity scale scores. Evidence was also provided for thehypothesized negative associations between psychological symptoms and personalresources of adolescents assessed by the RSCA Resource Index and Sense ofMastery and Sense of Relatedness scale scores.

The strongest correlations were found between the BYI-II scores and the RSCAVulnerability Index and Emotional Reactivity scale scores. The Emotional Reactivityscore accounted for most of the variance of the Vulnerability Index in predictingsymptom severity in the nonclinical sample.




In summary, this study of associations among variables supports anticipated pos-itive associations between self-reported symptoms and the Emotional Reactivityscale score and Vulnerability Index score and negative associations between self-reported symptoms and the Resource Index, Sense of Mastery score, and Sense ofRelatedness score in a normative sample. These findings suggest that psychologicalvulnerability, particularly emotional reactivity, was more strongly related to self-reported symptoms than were personal resources such as sense of mastery and senseof relatedness for the normative group as a whole.

Findings regarding Emotional Reactivity as a source of psychological vulnerabil-ity are consistent with previous research of psychopathology that has found that achild’s development of pathology in the presence of adversity is related in some wayto the child’s emotional reactivity and his or her ability to modulate and regulate thisreactivity. Strong emotional reactivity and associated difficulty with self-regulationhas been associated with behavioral difficulty and vulnerability to pathology. Thepractical implications of these findings are that preventive interventions thatdecrease emotional reactivity with respect to sensitivity, difficulty recovering fromupset, and impairment of functioning because of upset may prevent or reduce vul-nerability to psychological symptoms. Additional longitudinal research is needed tosubstantiate these implications.

Although the focus of this article is on potential use of the RSCA for potentialscreening in a normative sample, one might ask whether these relationships hold upin a clinical sample. Correlation analyses were conducted also for the clinical sam-ple (table not reported). All correlations were significant and in the predicted direc-tion. Correlations were lower in the clinical sample than in the normative samplebecause of a more restricted range of scores both in RSCA scores and in BYI-IIscores in the clinical sample. However, relative salience of the Vulnerability Indexwas supported for the clinical sample. The Vulnerability Index was positively corre-lated with BYI-II Anger (.65), Depression (.60), and Disruptive Behavior andAnxiety (.46) for the clinical sample. The Emotional Reactivity scale score was pos-itively correlated with BYI-II scores for the clinical sample. Correlations rangedfrom .48 with the Disruptive Behavior score to .62 with the Anger score. However,it is likely that correlations across clinical samples would vary depending on the clin-ical composition of the group and would probably be most meaningful studied forspecific diagnostic groups. Future research examining correlations for specific diag-nostic groups of sufficient size would expand on these findings.

DFA using gender, parent education level, RSCA and index scores, and BYI-IInegative affect and behavior scores to predict membership in the clinical versus non-clinical sample indicated the Vulnerability Index as the best predictor, followed bythe BYI-II Anxiety score accurately predicting 77.2% of cases. Separate discrimi-nant function analyses for females and males (table not reported) yielded very sim-ilar results, with the Vulnerability Index indicated as the best predictor for both.




Neither parent education level nor gender was indicated as a significant variable inthis analysis.

DFA predicting clinical status was also conducted without the four BYI-II scores:Anxiety, Depression, Anger, and Disruptive Behavior (table not presented). TheVulnerability Index was the major variable entered into this equation as well. Thisanalysis yielded 79.1% accurately classified cases without the inclusion of the BYI-II scores. Another DFA conducted with the Vulnerability Index removed indicatedthat the Resource Index was the best predictor, supplemented by the BYI-II Anxietyscore and the Emotional Reactivity scale score.

These findings provide preliminary support for the use of the RSCA in screeningnormative samples of adolescents for psychological vulnerability to the developmentof psychopathology. The Vulnerability Index was found to be the best single RSCAscreening score in that it accurately identified 77% to 79% of cases depending onwhat variables are entered into the regression equation. However, other combina-tions of scores were predictive as well. The advantage of using the RSCA in screen-ing adolescents is that once an initial group is identified as vulnerable with theVulnerability Index, the RSCA Resiliency Profile of these individuals may be fur-ther examined. For example, the examiner can determine the extent to which theyouth’s vulnerability is because of high emotional reactivity or low resources.

The prevention implications of these findings are that the RSCA index, scale, andsubscale scores may be further examined to suggest intervention strategies for youthwho have been identified as psychologically vulnerable. For example, high vulnera-bility because of high emotional reactivity may be dealt with by teaching relaxationor stress management techniques. On the other hand, high vulnerability because oflow resources can be followed up by interventions that enhance sense of mastery orsense of relatedness. In addition, the RSCA may be used to assess the impact ofthese interventions on youth using pre-post intervention measurement.

Limitations and Suggestions for Future Research

It is recognized that this study was preliminary, and findings should be explored inadditional research. The sample sizes were relatively small; therefore, findings shouldbe replicated using larger samples. Further research with larger clinical samplesshould compare how these variables function within specific disorder groups. It mustbe kept in mind that these findings provided validity support for the RSCA scores asassociated with psychological symptoms and clinical status but did not provide evi-dence that these scores predict the development of psychopathology. Longitudinalstudies would be needed to explore this process. In addition, findings do not suggestthat the RSCA should be used alone as a diagnostic indicator. These findings relate togeneral psychological vulnerability that may or may not be associated with psycho-logical symptoms. In fact, as discussed above, the value of a preventive screener




would be enhanced by an ability to identify youth who are vulnerable but who maynot yet have developed psychological symptoms. Additional studies could examinethe impact of interventions on the reduction of psychological symptoms as mediatedby emotional reactivity, sense of mastery, and sense of relatedness.

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Sandra Prince-Embury, PhD, is a clinical psychologist and family therapist and author of the ResiliencyScales for Children and Adolescents and the Family Health Tree. Her research has included the psycho-logical impact of technological disaster. Currently, she provides therapy services for youth and familiesas well as consultation and training through the Resiliency Institute of Allenhurst LLC.




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Resiliency Scales