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The Well-Being Index (WBI) for schools: A brief measure of adolescents' mental health

Article

The Well-Being Index (WBI) for schools: A brief measure of adolescents' mental health

Abstract

Schools are increasingly concerned with the well-being of the whole child - likely, more so since the COVID-19 pandemic - and goals here were to document the psychometric properties of a brief new measure of adolescent mental health, the Well-Being Index (WBI). The measure assesses 4 symptom areas, 2 each of internalizing and externalizing symptoms-Depression, Anxiety, Rule-Breaking, and Substance Use-and an optional scale on Isolation at School. A total of 2,444 students from 2 high schools completed the WBI, the Youth Self-Report (YSR), and other related measures. Alpha coefficients showed acceptable internal consistency, with values for the 5 WBI subscales at .83, .84, .78, .79, and .74, respectively. Both exploratory and confirmatory factor analyses demonstrated consistent factorial validity. Correlations with corresponding YSR subscales indicated good convergent and discriminant validity. The WBI Substance Use and Isolation at School subscales, similarly, had high correlations with subscales from preexisting measures. Criterion-related validity was indicated in significant correlations between WBI subscales and conceptually related dimensions of close relationships. Also examined was the percentage of youth falling above clinical cutoffs on both the WBI and YSR, and findings demonstrated high concurrent validity. Collectively, results suggest the promise of the WBI as a brief, psychometrically sound measure to assess the adjustment of adolescents, along with perceptions of school climate that can be modified toward fostering their overall well-being. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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The Well-Being Index (WBI) for Schools:
A Brief Measure of Adolescents’ Mental Health
Suniya S. Luthar 1,2
Ashley M. Ebbert 1.3
Nina L. Kumar 4
Prepublication version.
For published manuscript, please email NLKumar@AuthConn.com
1 Authentic Connections, Tempe, AZ
2 Columbia University’s Teachers College (Emerita)
3 Arizona State University, Department of Psychology, Tempe, AZ
4 Authentic Connections, Cambridge, MA
The authors gratefully acknowledge support provided by Authentic Connections.
Correspondence concerning this article or the Well-Being Index measure should be addressed to
Nina L. Kumar, 240 Sidney Street Unit 101, Cambridge, MA 02139.
Email: nlkumar@authconn.com
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Abstract
Schools are increasingly concerned with the well-being of the whole child – likely, more
so since the COVID-19 pandemic – and goals here were to document the psychometric
properties of a brief new measure of adolescent mental health, the Well-Being Index (WBI). The
measure assesses 4 symptom areas, 2 each of internalizing and externalizing symptoms—
Depression, Anxiety, Rule-Breaking, and Substance Use—and an optional scale on Isolation at
School. A total of 2,444 students from 2 high schools completed the WBI, the Youth Self-Report
(YSR), and other related measures. Alpha coefficients showed acceptable internal consistency,
with values for the 5 WBI subscales at .83, .84, .78, .79, and .74, respectively. Both exploratory
and confirmatory factor analyses demonstrated consistent factorial validity. Correlations with
corresponding YSR subscales indicated good convergent and discriminant validity. The WBI
Substance Use and Isolation at School subscales, similarly, had high correlations with subscales
from preexisting measures. Criterion-related validity was indicated in significant correlations
between WBI subscales and conceptually related dimensions of close relationships. Also
examined was the percentage of youth falling above clinical cutoffs on both the WBI and YSR,
and findings demonstrated high concurrent validity. Collectively, results suggest the promise of
the WBI as a brief, psychometrically sound measure to assess the adjustment of adolescents,
along with perceptions of school climate that can be modified toward fostering their overall well-
being.
Keywords: adolescents, symptoms, COVID-19, schools, well-being
Statement of Significance: This article establishes good psychometric properties of a
brief measure of common adolescent symptoms: depression, anxiety, rule-breaking, and
substance use. Its brevity allows for widespread administration in school-based
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assessments of mental health; these are especially important given documented increases
in (a) overall distress levels among teenagers over the years and (b) expectations that
schools must play a major role in monitoring and promoting youth well-being.
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The Well-Being Index (WBI) for Schools:
A Brief Measure of Adolescents’ Mental Health
Schools are increasingly concerned about the mental health of their students, given
reports of increases in anxiety, depression, rule-breaking behaviors, and substance use among
youth in recent years (see American Psychological Association (APA, 2018; Luthar, Kumar, &
Zillmer, 2019). However, measures used to assess adolescents’ mental health either take a
substantial amount of time to administer, or when brief, are narrow in scope. Additionally, there
is rarely consideration of students’ feelings of isolation at school: the degree to which they feel
alienated from others as opposed to connected. Our goal in this study was to assess a brief,
psychometrically sound measure that could capture overall mental health of students at the
school level, enabling comparisons across institutions as well as within them (with the latter
illuminating subgroups that might be especially vulnerable).
Schools’ Assessments of Students’ Mental Health
With the current generation of adolescents reporting higher levels of stress and
depression than those before them (APA, 2018; Twenge et al., 2019), schools today are
increasingly charged with helping ensure youths’ psychological well-being. In point of fact,
there is now a clearly articulated national emphasis on mental health literacy among teachers,
wherein they are charged with not only traditional teaching of academic subjects but also with
promoting their students’ good mental health (Lescheid, Saklofske, & Flett, 2018). Vigilance for
students’ mental health, in turn, requires regular assessments of adjustment levels in problem
areas that are common among teens, using measures that are psychometrically sound and yet
efficient to administer.
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Extant Measures of Youth Mental Health
Considering existing self-reported measures of symptoms across multiple domains, some
of the best, most widely used instruments are lengthy. For example, the Youth Self-Report,
generally considered to be the gold-standard assessment tool, has a total of 112 items, measuring
multiple symptoms in both the internalizing and externalizing categories, as well as social
competence (Achenbach & Rescorla, 2001). Similarly, the Behavior Assessment System for
Children has a total of 160 items and was designed to measure the behavior and self-perceptions
of children and adolescents between four and 18 years of age (Reynolds & Kamphaus, 1992).
The Beck Youth Inventories, second edition (BYI-II), is a set of norm-referenced diagnostic
scales designed to assess children and adolescents between the ages of seven and 18 in areas of
Depression, Anxiety, Anger, Disruptive Behavior, and Self Concept. Each inventory of the BYI-
II takes 5-10 minutes to administer, but the full “combination” inventory, spanning both
internalizing and externalizing symptoms, takes between 30 minutes and one hour (Beck et al.,
2005).
Whereas these comprehensive measurements are invaluable when evaluating youth in
clinical settings (e.g., in assessments for treatment goals in psychotherapy), they tend to be less
practical for use in school-based studies on students’ well-being. The latter typically involve
assessment not just of symptoms, but also of multiple risk and protective factors that might affect
students’ adjustment levels (e.g., see Luthar & Kumar, 2018). In general, schools are reluctant to
allow more than one 45-50 minute class period to administer surveys on students’ psychological
and behavioral adjustment.
Considering, on the other hand, existing measures of symptoms that have the advantage
of being brief and thus more feasible for school-wide assessments, these tend to focus on limited
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domains of youths’ maladjustment. To illustrate, the Center for Epidemiologic Studies
Depression Scale (CES-D; Radloff, 1977) is a 20-item scale designed to measure depressive
symptoms; this instrument, however, does not assess other areas that are important during
adolescence, including anxiety (APA, 2018), rule-breaking, and drugs and alcohol use (Moffitt,
2003). Similarly, there are several relatively brief measures that encompass only externalizing
problems. The Self-Report Delinquency Checklist (SRD; Huizinga & Elliot, 1986) contains 37
items assessing the seriousness of delinquent behaviors (including substance use), but no
internalizing symptoms. The widely used 53-item Youth Risk Behavior Survey (YRBS) was
designed to measure behaviors related to intentional and unintentional injury, tobacco use,
alcohol and other drug use, sexual activity, diet, and physical activity (Brener et al., 1995;
Centers for Disease Control, 1995). While the YRBS does measure substance use, it does not
have psychometrically validated subscales (with multiple, internally consistent items, as in the
YSR or BASC) that measure depression, anxiety, or rule-breaking.
Development and Validation of the Well-Being Index
In view of the literature presented, goals of this study were to test the psychometric
promise of a new measure of adolescents’ mental health – the Well-Being Index (WBI; Kumar,
2019) -- that assesses both internalizing and externalizing symptoms and yet is brief. This
measure was developed for use in school-based assessments of students’ psychosocial and
behavioral adjustment, keeping in mind the problem areas most commonly seen among
adolescents. Within the internalizing domain, these include depression and anxiety, and within
the externalizing domain, included are rule-breaking and substance use (Achenbach & Rescorla,
2001). Thus, the WBI contains five items each to assess depression, anxiety, and rule-breaking,
to be completed on a five-point Likert scale (Kumar, 2019). To measure substance use, the WBI
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entails the use of five items, verbatim, from the publicly available Monitoring the Future Study
(Johnston, O’Malley, & Bachman, 2014).
With regard to procedures used to develop WBI items, the literature was reviewed to
identify symptoms that are (a) commonly reported among adolescents in distress (e.g., Hovens,
Cantwell, & Kiriakos, 1994; Roberts, Roberts, & Chan, 2007; Roberts, Roberts, & Xing, 2007),
and (b) are recurrently included in well-established measures of internalizing and externalizing
problems (Achenbach & Rescorla, 2001; Beck et al., 2005; Huizinga & Elliot, 1986; Radloff,
1977; Reynolds & Kamphaus, 1992). Examples of regularly referenced symptoms include
feelings of sadness, nervousness, and stealing, respectively, for depression, anxiety, and rule-
breaking, and drinking to intoxication for substance use. Having culled the symptoms most
commonly documented as signaling each of the four problem areas of interest for this new
measure, the top five were identified, and brief statements were composed to capture each (see
Methods for more details).
To document the psychometric properties of the WBI in this study, analyses were done
on both reliability as well as different types of validity. With regard to reliability, alpha
coefficients of internal consistency were examined for all subscale scores. These were computed
separately among boys and girls.
As a primary test of validity, subscale scores on the WBI were compared against those on
the YSR – which, as previously noted, is widely regarded as the gold standard of assessments of
adolescent symptoms. Simple correlations were examined to assess convergent and discriminant
validity, with expectations that WBI subscale scores would show strong links with the
conceptually parallel dimensions on the YSR, and lower correlations with those conceptually
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distinct (e.g., WBI Depression and Anxiety would both have stronger links with YSR Anxious-
depressed, than with YSR Rule-breaking).
In a second set of analyses on validity, associations were examined between WBI (and
YSR) subscales and other aspects of adolescents’ psychosocial adjustment with which
conceptually, they should be related; the hope was that the magnitude of associations for the
subscales of the WBI would be at least comparable to (if not greater than) those of the YSR. In
these analyses, the central focus here was on dimensions of relationships, which we know are
critical in relation to exacerbating both internalizing and externalizing symptoms (Luthar &
Eisenberg, 2017). Specifically, links were examined with feelings of alienation from both parents
as well as from teachers, feelings of being bullied or victimized at school, and overall
relationship stress; each of these is conceptually linked with both internalizing and externalizing
problems (for reviews, see Flett, 2018; NASEM, 2019a; 2019b). In addition, we examined teens’
reports of discipline at school, i.e., the degree to which they felt that students who broke rules
were treated fairly, with the assumption that those high on rule breaking (or other symptoms)
would be less likely to see school rules as generally fair and appropriate.
In a third set of validity analyses, the focus was on the degree to which the WBI and YSR
each classified youth as having symptom levels surpassing the normal range, i.e., greater than 2
SD’s and 1.5 SDs from the sample mean, respectively labelled “much above average” and
“above average” on the YSR. The goal here was to identify percentage of agreement across the
two measures, as well as the percentage of WBI “false positives” and “false negatives” vis-à-vis
classifications by the YSR. The percentage of “false positives” reflected situations in which the
WBI might classify a student as falling above cutoffs on symptoms, but the YSR did not.
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Conversely, the percentage of “false negatives” would reflect situations in which the WBI did not
classify a student as being above cutoffs, but the YSR did.
Isolation at School
As a further gauge of overall student well-being – apart from symptoms – the WBI
contains five items pertaining to students’ sense of alienation or rejection at school as opposed to
belonging and acceptance; information on this construct could also be valuable for school
administrators. As we now know well, resilience rests centrally on relationships (Luthar &
Eisenberg, 2019; NASEM, 2019a) and school-based relationships can strongly affect students’
well-being (e.g., Millings et al., 2014; Vaz et al., 2014). Just as the quality of relationships with
parents is critical in determining how well children negotiate the ongoing challenges of
adolescence, research has demonstrated the high the potential for relationships at school to move
adjustment trajectories toward more positive (or negative) directions (for a review, see
Domitrovich, Durlak, Staley, & Weissberg, 2017).
Another reason for school administrators to measure isolation at school would be to
evaluate the success of integrating new sets of students, especially at grade levels that represent
major transition points. For example, middle schools often bring together, in the 6th grade,
elementary school students from a number of feeder schools, leading to the formation of new
groups of friends and the possible isolation of some, as peer groups coalesce. Similarly, many
high schools include only grades 9 through 12; it can be helpful to keep track of the degree to
which incoming 9th graders feel a sense of belonging to the institution. Routine assessments at
such transitional points can also be critical for identifying any subgroups who might need
additional support integrating into the school, such as international students joining a new
school, even as they are transitioning to life in a new country.
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Along with the four symptom domains, therefore, this study also entailed examination of
the psychometric properties of the five-item WBI scale on Isolation at School. As with symptom
scales, alpha coefficients were computed separately for girls and boys to document internal
consistency. To assess validity of this scale, of central interest were associations with measures of
alienation from both adults and peers at school, i.e., teacher alienation and peer victimization.
Summary
To summarize, goals in this study were to examine the reliability and validity of the WBI
as a useful potential measure of well-being of students in school-wide assessments. Specific
goals were to (1) Evaluate the reliability or internal consistency of each subscale; two on
internalizing symptoms (Depression and Anxiety), two on externalizing symptoms (Rule-
breaking and Substance Use), and a separate scale on Isolation at School; (2) Validate the
internal structure of distinct symptom subscales, i.e., empirically demonstrating the
conceptualized four-factor structure of the two internalizing and two externalizing symptoms
assessed; (3) Examine the convergent and discriminant validity of WBI symptom subscale
scores, via correlations with YSR subscales; (4) Assess criterion-related validity by examining
associations of the WBI subscales with conceptually-related, established measures; and (5)
Measure concurrent validity, that is, concordance in the percentage of youth falling above
clinical cutoffs on the WBI and on the YSR.
Method
Participants and Procedures
Data were obtained from 2,444 high school adolescents, grades 9 (n = 628), 10 (n = 678),
11 (n = 635), and 12 (n = 486), and postgraduates (n = 17). Of the sample, 49.8% were male (n =
1217) and 50.2% were female (n = 1227). Participants were from two high school samples, one
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independent (which some refer to as ‘private’) and one public, respectively from the Northeast
and Southwest regions of the United States. Students described themselves as primarily
Caucasian (61.5%), with other ethnicities represented as follows: African American/Black
(4.4%), Latinx/Hispanic (15.5%), Asian/Asian American/Pacific Islander (8.2%), American
Indian/Native American (1.1%), Middle Eastern (0.6%), and Biracial/Multiracial/Other (9.8%).
Participants’ reports indicated that 72.8% of the parents were married, with about half having
graduated from college (53% of mothers and 50% of fathers) and a majority working full-time
jobs (61% of mothers and 83% of fathers).
As part of their ongoing work to foster positive youth development, school officials
administered a survey on well-being and adjustment in the Spring semester of 2019. Parents
were informed about the nature of the survey, given the option to decline their children’s
participation, and assured of the confidentiality and anonymity of the data. Adolescents
completed the questionnaires in their classrooms during regularly scheduled class time, using
computer-based surveys. Only 8% of the student body across both schools were either denied
parent consent to participate in the study or were absent on the day of data collection. A total of
2,546 students completed the survey with a rejection rate of 4% due to incomplete data, resulting
in a final sample of 2,444 adolescents. The present study was granted “exempt” status by the IRB
committee at Columbia University’s Teachers College, protocol number 20-161, as it involved
analyses of pre-existing, anonymous data.
Measures
Measures used in this study were part of a larger battery of instruments assessing
students’ well-being and the quality of their relationships with parents, peers, and adults at
school. The order of questionnaires was the same in all administrations, beginning with
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demographic data, and measures with a negative valence (e.g., symptoms or difficulties in
relationships) interspersed with those of a positive valence (e.g., perceived support across
different relationships). The measures were all psychometrically sound; alpha reliability
coefficients, shown in Table 1, indicated acceptable levels of internal consistency (e.g., α ≥ .70;
Nunnally & Bernstein, 1994).
Well-Being Index (WBI)
The WBI was developed by the third author, drawing upon her background in psychology
and expertise with school-based assessments (Kumar, 2019; Luthar & Kumar, 2018; Luthar,
Kumar, & Zillmer, 2019; 2020). Three 5-item subscales were drafted to capture problem areas
common among adolescents (depression, anxiety, and rule-breaking; see below for details), plus
one subscale that would assess feelings of isolation at school. As is common for the creation of
new measures in psychology (see DeVellis, 2016), items were created by first generating
statements that paraphrased each category of symptoms to be captured, relying on existing,
relevant theoretical and empirical literatures. After refining the items to reflect specific and age-
appropriate wording, the initial pool of items was reviewed by other experts as is recommended
(DeVellis, 2016); each expert had experience in developmental psychopathology research and
clinical practice with adolescents (the first and second authors). Collectively, this team then
finalized WBI subscale items, with a goal of balancing both thoroughness and brevity in
representing distinct, yet conceptually related symptoms, and ensuring face validity.
The three newly created symptom subscales included Depression (e.g., “I am sad or
depressed”), Anxiety (e.g., “I worry or obsess”) and Rule-breaking (e.g., “I cheat on exams or
tests”). For each of these, subjects were asked to indicate the extent to which the items were true
for them within the past 6 months on a 5-point scale (0 = never, 1 = rarely, 2 = sometimes, 3 =
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often, and 4 = very often). To assess the fourth mental health dimension, Substance Use,
questions from the Monitoring the Future (MTF) study (Johnston, O’Malley, & Bachman, 2014)
asked about substance use behaviors most common among youth – drinking alcohol, getting
drunk, using marijuana, smoking cigarettes, and vaping. The stem for these questions was,
“During the last 30 days, on how many occasions (if any) have you...” and sample items include
“Smoked cigarettes” and “Drank alcohol (including beer, wine, and liquor) -- more than just a
few sips”. Ratings were rescaled from a 7-point to 5-point scale (0 = never and 4 = 40 or more
times) to match the other WBI subscales. The reliability and validity of this type of self-report on
substance use have been amply documented (Johnston, Bachman, & O’Malley, 2014; Wallace &
Bachman, 1991). Finally, the supplementary Isolation at School subscale also contained five
items (e.g., “At my school, I feel isolated or like I don’t belong”). These items too were rated on
how true they were for the individual within the past 6 months, on a 5-point scale (0 = never, 1 =
rarely, 2 = sometimes, 3 = often, and 4 = very often).
Alpha coefficients of all WBI subscales are shown in Table 1. Among boys and girls
respectively, values were as follows: Depression, .82 and .84; Anxiety, .82 and .82; Rule-
breaking, .78 and .78, Substance Use, .83 and .76; and Isolation at School, .74 and .73.
(Note: When the WBI was administered within the school-based assessment battery, the five
subscales were presented in the same order that they are described here, and the order of all items
was fixed, as is true when administering the Youth Self Report described in the section that
follows.)
Measures Used to Validate the WBI Subscales
Symptoms: The Youth Self-Report (YSR)
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The YSR (Achenbach & Rescorla, 2001) is a 112-item index designed to measure
internalizing and externalizing symptoms across several subscales. Participants are asked to
indicate frequencies of experiencing these within the past six months on a 3-point scale (0 =
never, 1 = sometimes, 2 = often). Although the entire YSR was included with standard
administration, in this study, we examined data on two internalizing subscales directly relevant to
WBI subscales, i.e., Anxious-depressed and Somatic Complaints, and one externalizing subscale,
Rule-breaking. The Anxious-depressed scale consists of 13 items, which describe symptoms of
feeling anxious (e.g., “I worry a lot”’) and depressed (e.g., “I feel worthless or inferior”). The
Somatic Complaints scale consists of 10 items, which describe physical symptoms of anxiety or
depression (e.g., “I feel overtired without good reason”). Finally, the Rule-breaking subscale
consists of 15 items, which describe delinquent behaviors (e.g., “I break rules at home, school,
and elsewhere”). In the present study, reliability coefficients among boys and girls respectively
were as follows: Anxious-depressed, .95 and .94; Somatic Complaints, .82 and .94; and Rule-
breaking: .95 and .95 (see Table 1).
Conceptually Related Constructs
Adolescents’ feelings of alienation from mothers and fathers were assessed with the
Alienation subscale of the Short Form of the Inventory of Parent and Peer Attachment (IPPA;
Armsden & Greenberg, 1987). The IPPA Short Form consisted of 24 items with 12 pertaining to
each parent, each rated on a 5-point scale from 1 (almost never or never true) to 5 (almost
always or always true). The Alienation scale consisted of 8 items (4 for each parent) that
assessed the youth’s feelings of anger, isolation, and mistrust in relating to each parent (e.g.,
“Talking over my problems with my mother/father makes me feel ashamed or foolish,” “I feel
angry with my mother/father”), with reliability coefficients ranging from .77 to .82.
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Also considered were dimensions from the School Climate and Connectedness Survey
(SCCS; American Institutes for Research, 2011), which evaluates student attitudes toward their
school and dimensions of connectedness. The following two school climate subscales were
included with three items each: Fairness of Discipline, e.g., “When students break rules, they are
treated fairly,” and Teacher Alienation, e.g., “My teacher has made me feel inadequate or inferior
to others.” For each dimension of school climate assessed, participants responded to items on a
5-point scale from 1 (strongly disagree) to 5 (strongly agree). In the present study, internal
consistencies were well above 0.70, ranging from .79 to .94 (see Table 1).
Peer victimization was measured by the Revised Peer Experiences Questionnaire (RPEQ)
(Prinstein, Boergers, & Vernberg, 2001) which taps into overt, relational, and reputational
victimization rated on a 5-point scale from 1 (never) to 5 (a few times a week). The RPEQ has
demonstrated good validity and reliability (Prinstein et al., 2001), and in this sample, alpha
coefficients ranged from .86 to .92. Finally, students were assessed on overall stress from
relationships, responding to this prompt: “Please indicate how much stress the people in the
following relationships cause you (e.g., parents, teachers, coaches, friends in general, friends due
to competition, and significant others). For each relationship, students rated their response on a
5-point scale from 1 (not at all) to 5 (a great deal) with alpha coefficients ranging from .73 to .
81.
Statistical Analyses
Analyses for this study were conducted using SPSS software (IBM SPSS Statistics,
Version 25.0), Mplus (Muthén & Muthén, Version 7.11). To test the equality of correlation
coefficients specifically, an interactive, online calculator was used (Lee & Preacher, 2013).
Results
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Descriptive Data
Table 1 presents means and standard deviations on all variables in this study, separately
for boys and girls. As would be expected, girls had significantly higher levels of both WBI
internalizing symptoms, whereas boys had substantially higher externalizing problems, and
slightly higher substance use. Similar patterns were seen on YSR subscales. On all the validating
indices – negative aspects of relationships – girls reported higher levels than boys.
Internal Structure: Factorial Validity of WBI Symptom Subscales
After randomly splitting the sample in half, an Exploratory Factor Analysis (EFA) was
conducted on one half of the data to identify the underlying factor structure of items in the two
sets each of internalizing versus externalizing domains, Depression and Anxiety, versus Rule-
breaking and Substance Use. Analyses used maximum likelihood (ML), a common model-fitting
method that estimates factor loadings and unique variances, and CF-Quartimax rotation (i.e., an
oblique rotation method that uses the overall variance of the squared factor structure, based on
the assumption that the subscales are correlated). Results of the EFA model indicated the four
conceptually distinct subscales of symptoms (see Table 2); these findings provided the basis for
specifying a Confirmatory Factor Analysis (CFA) model that was fit to the other half of the data.
Evaluating Model Fit
In order to determine whether the specifications of the estimated CFA model were
consistent with the data, the goodness of fit of the model was evaluated. Using combinational
rules based on a two-index presentation strategy (Hu & Bentler, 1999), the standardized root
mean square residual (SRMSR) and the root mean square error of approximation (RMSEA;
Steiger, 1990) were considered. A model with relatively good fit would be evidenced by a SRMR
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value of close to .08 (or less) and a RMSEA value of close to .06 (or less) (Hu & Bentler, 1999).
RMSEA values close to .08 indicate fair fit (Browne & Cudek, 1993).
In the present study, a review of the related goodness-of-fit indexes revealed relatively
good-fitting EFA models as indicated by the following evaluative criteria for boys: SRMR = .04;
and RMSEA = .08. For girls, another good-fitting model was indicated by the following
evaluative criteria: SRMR = .04; and RMSEA = .07. Additionally, combinational rules based on
SRMR and RMSEA fit indexes revealed relatively good-fitting CFA models as indicated by the
following evaluative criteria for boys and girls, respectively: SRMR = .07 and .06; and RMSEA
= .08 and .07. CFA factor loadings are shown in Table 2.
Convergent, Discriminant, and Criterion-related Validity
Table 3 presents simple correlations across all variables in the study and shows that WBI
scores were significantly related to conceptually related YSR variables. Coefficients for the WBI
Depression in relation to YSR Anxious-depressed were .43 and .60 for boys and girls,
respectively, and those for the WBI Anxiety and YSR Anxious-depressed were .43 and .56.
Correlations between WBI Rule-breaking and the YSR Rule-breaking were .36 and .40 for boys
and girls, respectively. The WBI Isolation at School subscale was significantly related to school
climate subscales from pre-existing measures. Correlations among girls ranged from .22 to .44,
and those for boys ranged from .20 to .40 (please see Table 3 for more details).
Table 3 also shows expected associations between WBI subscales and conceptually
related constructs. WBI Depression and Anxiety subscales were significantly correlated with
alienation from mothers, with coefficients of .38 and .33, respectively, for boys, and .45 and .34
for girls. Parallel values for alienation from fathers were .36 and .33 for boys and .43 and .33 for
girls. Similarly, correlations with relationship stress were significant; for boys and girls,
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respectively, values for WBI Depression were .36 and .41 and for WBI Anxiety, .34 and .37. In
relation to peer victimization, the values for the two internalizing subscales, respectively, were .
35 and .29 for boys, and .39 and .35 for girls. Finally, WBI Rule-breaking had pronounced
associations with substance use, with correlation coefficients of .42 and .41 for boys and girls,
respectively; it was also significantly related to all relationship variables.
To examine convergent and discriminant validity in greater depth, we compared the
magnitude of coefficients where the WBI subscale was conceptually (a) similar to the YSR
subscale vs. (b) dissimilar, using asymptotic z tests (Lee & Preacher, 2013; Steiger, 1980).
Results are shown in Table 4, with values involving conceptually similar pairs shown first in
boldface, followed by those involving dissimilar pairs. For example, coefficients for WBI
Depression and YSR Anxious-depressed / YSR-Rule-breaking were .43 / .28 and .60 / .31, for
boys and girls, respectively. As shown in Table 4, all six comparisons showed that the
coefficients for WBI scores in relation to similar YSR ones were significantly higher than values
involving conceptually dissimilar ones, at p < .001.
WBI versus YSR Symptom Subscales in Relation to Validating Predictors
Correlation Coefficients
Table 5 shows associations between all validating predictor variables and (a) the three
WBI symptom subscales versus (b) the parallel YSR subscales. Again, the pairs of correlation
coefficients were compared to determine if they differed in magnitude. For example, in relation
to Mom Alienation, correlations compared included WBI Depression vs. YSR Anxious-
depressed, which were .38 vs. .31 for boys, and .45 vs. .33 for girls.
Results collectively indicated that despite the relative brevity of WBI subscales, this had
not led to lower overall magnitude of correlations, relative to those of the YSR, with validating
19
THE WELL-BEING INDEX
predictors. In fact, the magnitude of associations was generally comparable and, in some
instances, larger for the WBI. As shown in Table 5, of the 36 comparisons (18 x 2, for boys and
girls), 23 of them (64%) showed that correlations for WBI subscales were significantly larger, in
the expected direction, than those for their YSR analogues. In an additional 9 cases, WBI values
were higher, but these differences were not statistically significant. There were only 4 instances
where the coefficients for WBI were lower than those for YSR, with differences statistically
significant in just one of the cases. It should be noted that in the cases involving perceived
Fairness of Discipline, which conceptually, should be inversely correlated with adolescents’
symptoms, two correlation coefficients for WBI were lower than those for YSR in absolute value
(see Footnote in Table 5). At the same time, the valence of these associations was in the
expected negative direction for WBI but not the YSR, which is why these comparisons were
counted as favorable for the former.
R2 Values in Regressions
As another simple gauge of overall validity as symptom measures, regression analyses
were conducted using all six of the conceptually related validating variables as predictors, to
ascertain the total variance explained in the symptom subscale scores. Results of these
regressions, again, yielded no evidence that any of the brief WBI subscales had lower magnitude
of associations with predictors collectively as compared to the longer YSR subscales; in fact,
variance accounted for was greater in predicting to WBI subscales. Specifically, total R2 values
were as follows for pairs of outcome variables from the two measures: WBI Depression versus
YSR Anxious-depressed, R2 .25 and .21 (boys), .36 and .21 (girls); WBI Anxiety versus YSR
Anxious-depressed, R2 .23 and .21 (boys), .25 and .21 (girls); WBI Rule-breaking versus YSR-
Rule-breaking, .22 and .13 (boys), .23 and .13 (girls).
20
THE WELL-BEING INDEX
To ascertain whether the magnitudes of variance explained (R2) were significantly
different when outcome variables were based on the WBI versus the YSR measures, a repeated
measures model (GLM procedure) was used (see Wheeler, 2017). For example, the first pair of
R2 values compared, with WBI Depression versus YSR Anxious-depressed as outcomes, was .25
vs. .21 for boys. Across all six pairs of R2 coefficient delineated in the previous paragraph,
values were significantly higher for outcomes involving the WBI, at p < .001.
Concurrent Validity: Classification of Youth Above Clinical Cutoffs
The percentage of students falling above clinical cutoffs on the WBI and on the YSR each
were examined, using gender-specific norms for each; results are presented in Table 6. When the
WBI Depression classifications were compared with those on the YSR Anxious-depressed scale,
instances where both measures classified students in the clinically significant range (over 2 SD’s
from the mean), were 69% and 72% for boys and girls respectively. Parallel values in classifying
students in the range of borderline significance (above 1.5 SD’s from the mean) were 67% and
65% for boys and girls respectively. Similarly, when WBI Anxiety and YSR Anxious-depressed
classifications were compared, agreement above 2 SDs was 70% for both genders, while
agreement on being above 1.5 SDs was 66% and 63% for boys and girls respectively. For Rule-
breaking, the four values for matching classifications were 70% and 74% versus 68% and 73%.
Disagreements in classification occurred almost entirely because the YSR identified more
students as being above clinical cutoffs than did the WBI, rather than the reverse. In classifying
both clinically significant and borderline scores, between 23% and 36% of instances involved a
negative classification by the WBI but a positive one by the YSR. By contrast, “false positives”
based on the WBI (not indicated by the YSR) were very rare, ranging from 1-4%.
Discussion
21
THE WELL-BEING INDEX
The present results \provide evidence for the promise of a brief measure for school-based
assessments of youth mental health, the Well-Being Index (WBI; Kumar, 2019). The measure is
applicable to teens from various sociodemographic backgrounds, as it captures major
internalizing and externalizing symptoms that generally occur during the adolescent years.
Examination of psychometric properties showed good internal consistency of all scales as well as
high levels of validity. From a pragmatic standpoint, given an administration time of
approximately ten minutes, the WBI can be administered even on a monthly basis (e.g., when a
school may have experienced a traumatic event, or to periodically track the value of a given
intervention program for targeted subgroups). At a more macro level, annual administration of
this short measure would allow administrators to keep track of the overall well-being of their
students, much as they keep track of scores on standardized tests or passing percentages on
achievement tests. In discussions that follow, major findings on the WBI’s psychometric
properties are summarized first, followed by an appraisal of its applications in school-based
assessments tied to prevention efforts.
WBI as a Measure of Symptoms: Psychometric Properties
Results of this study indicated good psychometric properties of the WBI as a measure of
adolescents’ internalizing and externalizing symptoms. With regard to reliability, internal
consistency of the four symptom subscales – Depression, Anxiety, Rule-breaking and Substance
Use – was acceptable among both boys and girls. The eight values ranged from .72 to .84, with a
median of .82; these values fall well above the range that is considered satisfactory (α ≥ .70;
Nunnally & Bernstein, 1994).
In terms of the distinctiveness of the symptom areas measured, factor analyses supported
a four-factor model. As they had been conceptualized, the 20 items did map on the two
22
THE WELL-BEING INDEX
internalizing subscales of Depression and Anxiety and two externalizing subscales of Rule-
breaking and Substance Use. An evaluation of the goodness of fit model revealed an
exceptionally well-fitting model.
WBI subscales also showed strong levels of convergent and discriminant validity. With
regard to the former, one would expect stronger links between WBI subscales of internalizing
symptoms with YSR scores also of internalizing problems, as opposed to YSR externalizing
scores. In fact, correlations for both WBI Depression and WBI Anxiety with the YSR Anxious-
depressed subscale were higher than coefficients of each of these with YSR Rule-breaking (1.5 –
2 times as high). All comparisons were statistically significant.
Similarly, when considering the magnitude of correlations with conceptually linked
constructs – aspects of relationships with parents, peers, and teachers – WBI subscales’
correlations were clearly at least equivalent to those for YSR subscales, if not slightly higher, on
the whole. Specifically, of 36 comparisons conducted, differences were significantly higher for
the WBI in 64% of cases, and for the YSR in less than 3%. Furthermore, when all sets of
predictors were entered into regression analyses, the total variance explained was significantly
greater when outcomes were symptoms measured by the WBI, as opposed to based on the YSR.
In sum, despite the brevity of WBI subscales relative to YSR (five items each as opposed to 10-
15 items), findings of this study did not suggest any relative deficits in validity of measurement.
There was also generally good agreement in classifying youth as showing clinically
significant levels of symptoms, as measured by the WBI versus the YSR; this was true even
though descriptors of symptoms were similar but not identical. In these analyses, classification
based on the WBI Depression and Anxiety subscales were each compared against classification
via the single YSR subscale that subsumed both these dimensions, Anxious-depressed. Similarly,
23
THE WELL-BEING INDEX
the WBI separately measures Rule-breaking and Substance Use whereas the YSR Rule-breaking
subscale includes acts related to conduct disturbances as well as to substance use. These caveats
notwithstanding, levels of agreement in classifying youth in the clinically significant range
(“Much above average” or 2 SDs from the mean) ranged from 69% to 74%, with a median of
70%.
Discrepancies in classifying students above clinical cutoffs almost all occurred because of
“false negative”, wherein analyses using the YSR classified more students at the extremes than
did analyses using the WBI. One potential explanation for the difference in classification might
be that levels of clinically significant symptoms have shifted over the last couple of decades in
the United States. Norms on the YSR are based in assessments done around the year 2000
(Achenbach & Rescorla, 2001), before the creation of social media and tragedies such as 9/11,
and multiple reports have shown overall increases in adolescent distress over time (APA, 2018;
NASEM, 2019; Twenge et al., 2019). To the degree that teens as a group are more troubled
overall, this would imply a higher overall mean on any given scale and commensurately, smaller
numbers of youth falling under the “extremes” of +2 SDs. To illustrate, if the population mean of
adolescents’ symptoms on a given measure increased from 50 to 60 over the decades with SDs of
10 in both cases, individuals with scores of 79 would be below clinical cutoffs using 2019 norms
on this measure, but well above clinical cutoffs using norms from the past. This suggestion is in
fact supported by findings, in this study, of mean T scores all greater than 60 among both boys
and girls and across all three YSR subscales assessed. (In essence, this implies that a
standardized score of 75 would connote approximately +1.5 SD’s on the WBI (this sample’s
means of about 60 and SDs of 15), but equivalent to a YSR T score of +2 SD’s, given YSR’s
mean T score of 50 and SD of 10).
24
THE WELL-BEING INDEX
An additional possibility that must be considered, in relation to inferences about false
negative classifications on the WBI versus YSR, is that there were differences in samples that
were used in defining normative values on the measures. The original YSR norms were based on
non-referred youth (Achenbach & Rescorla, 2001). By contrast, norms created for the WBI were
based on all students at the schools sampled, which presumably included some children who had
been referred for professional help.
In future research, administration of the WBI to additional samples of students will be
critical in indicating values that truly approximate the current “population” means and standard
deviations. By the end of 2019, WBI data had been obtained from almost 15,000 youth across the
United States (these additional samples were not assessed on the YSR, however, so are not
discussed in the present paper). Examination of the larger samples will also permit more fine-
grained analyses of clinical cutoffs separately by gender, grade level, and ethnicity. However,
before moving to any such large scale administration of the WBI, a critical prerequisite has to be
work such as that reported on in this study: Establishing good psychometric properties of this as
a stand-alone instrument, validated against the widely used, gold standard measure (the YSR),
and documenting strong relationships with other conceptually linked measures.
Applying the WBI Toward Prevention of Youth Psychopathology
Just as nations have a simple “happiness index,” we believe that it is critical that schools
have a simple well-being index of their overall student body. As noted earlier, adolescents are
increasingly experiencing mental health difficulties (APA, 2018). Today’s youth who are in the
range of 15-21 years, called Gen Z, are significantly more likely than prior generations to report
that their mental health is fair or poor, with 27 percent indicating this is true for them. By
25
THE WELL-BEING INDEX
contrast, ratings of fair or poor mental health were given by 15 percent of Millennials and 13
percent of Gen Xers, and only seven and five percent, respectively, of Boomers and older adults.
From a prevention standpoint, these data indicate that it would be useful to schools to be
able to regularly track where their student bodies stand on psychosocial adjustment, just as they
do with standardized test scores. In addition, administering the WBI measure could allow
administrators to see which symptom areas might need enhanced attention within their own
schools, as impressionistic evidence is not always borne out by the data. High school teachers are
often more aware of externalizing, acting-out behaviors, for example, than of students’
depression or anxiety; the latter problems are more covert in nature and can go undetected even
when at seriously high levels (Flett, Hewitt, Nepon, & Zaki-Azat, 2018; Luthar et al., 2020).
Additionally, the WBI can help identify subgroups of youth who are particularly
struggling in a given school. Students with symptoms falling in the troubling “red zone” can vary
across institutions, for example, by grade level (with freshmen standing out in some cases or in
others, juniors immersed in college applications), as well as across different demographic
subgroups (e.g., with distress elevated among particular sexual or ethnic minorities or
international students). In turn, identifying vulnerable subgroups can help target mental health
resources to where they are most needed. This can be particularly helpful in low-income schools,
where resources for mental health in are typically scant (Hoagwood et al. 2018), necessitating
efficient, targeted programs rather than “universal” interventions for all students.
There can also be much value in administering the WBI routinely in relatively well-
resourced schools, characterized by high levels of achievement; in fact, these students report
symptom levels commensurate with if not greater than those of their counterparts in poverty
(Luthar et al., 2019; NASEM, 2019). From the perspective of prospective parents, it could be
26
THE WELL-BEING INDEX
valuable to have a gauge of whether schools truly are invested in fostering the development of
the “whole child” (Luthar et al., 2019; Wilson & Marshall, 2019). In all likelihood, many
parents would appreciate having information on the students’ overall mental health across critical
domains of adolescent adjustment, in addition to stellar records on academics and extracurricular
activities.
Besides measuring adolescents’ symptoms in critical mental health domains, another
potentially useful application of the WBI lies the use of the scale capturing feelings of isolation
at school. Decades of research on resilience have shown that relationships are fundamental to
doing well in despite stress (Luthar, Crossman, & Small, 2015; NASEM, 2019a). Additionally,
negative relationship indices tend to be more powerful than positive ones in affecting one’s well-
being (i.e., “bad is stronger than good”; Baumeister, Bratslavsky, Finkenauer, & Vohs, 2001).
Thus, feeling alienated by adults and peers at school, or simply dreading being at school, can
make a substantial difference in affecting students overall, including their academic performance
(Lescheid et al., 2018). This said, to our knowledge, there exists no brief measure capturing these
sentiments; the WBI subscale examined and validated here could help fill this gap.
Finally, there are three issues worth noting with regard to the use of the moniker “Well-
Being Index” for this measure that in fact encompasses adjustment problems. First, in
developmental research that is described as covering children’s “well-being” or “health”,
outcomes in fact commonly include symptoms such as depression, anxiety, and substance use, as
well as dimensions of social exclusion (Best, Manktelow, & Taylor, 2014; Patton et al., 2016;
Sieving et al., 2001; Vanassche, Sodermans, Matthijs, & Swicegood, 2013). Second, in
contemporary school-based surveys of students’ psychological or behavioral difficulties,
instruments often reference health rather than illness, e.g., the Global School-based Student
27
THE WELL-BEING INDEX
Health Survey (Center for Disease and Prevention, 2020) and the Independent School Health
Check (2020). Third, in the world of practice within K-12 education, enhancing overall “well-
being” of students is typically viewed as implying low levels of symptoms. To illustrate, Wilson
and Marshall (2019) exhort schools to appraise how they “conceptualize and adopt a definition
of health and wellness… and how they use it to inform their approaches to very real problems—
student suicide, depression, anxiety, self-harm, peer-to-peer sexual assault, self-medication/drug
and alcohol abuse.”
Limitations and Future Directions
Among the limitations of this study, the first is that the present sample included only high
school students (grades 9 to Postgrad), although the assessment tool is intended for use with
youth from grade 6 through grade 12. In the future, the WBI should be tested with middle
schoolers as well, aged 11-14 years. Second, data were only collected with students in two areas
of the country, Northeast and Southwest; the measure should be validated in different parts of the
country and with demographically heterogenous samples. With regard to psychometric
properties, future studies should also consider test-retest coefficients as indices of reliability, in
addition to levels of internal consistency.
There are several limitations associated with the sole reliance on one informant in this
study; scores on both the WBI and YSR were based in self-reports (as are many adolescent
symptom scales described at the outset of this article). The mono-method, mono-informant
approach could have led to under-reporting on some scales more so than others, with lower
acknowledgement of externalizing behaviors, for example, than internalizing symptoms.
Additionally, it could have led to some inflations in associations among measures. With regard
to the latter issue, it should be reiterated that in fact, of central interest in validating WBI
28
THE WELL-BEING INDEX
subscales are links between students’ subjective experiences of their own distress and the quality
of salient relationships in their lives, also as perceived by the teens themselves. This said, future
studies might usefully examine the degree to which assessments based on the WBI converge
with or differ from those based on reports from other informants, such as parents or teachers
(these adults’ ratings were not available here as the schools administered surveys anonymously,
allowing no identifiers for individuals’ data).
Summary and Conclusions
In conclusion, data presented here suggest the validity of the WBI as a brief, scientifically
sound measure to assess the adjustment of adolescents. Its use in school-based assessments can
help fill a critical need: Early and expedient detection of mental health issues, so that
interventions can be targeted to students who most need them, and in areas within which they are
most vulnerable (Leschied et al., 2018). The central role of mental health promotion in schools,
in fact, is now explicitly emphasized by researchers as well as practitioners. In their introduction
to the Handbook of School-Based Mental Health Promotion, the editors emphasized,
“(The) challenges and problems on the mental health front have become urgent enough
that . . . a focus on mental health promotion in children and adolescents must become part
of the regular school day, and this is just as important as the more traditional educational
learning that takes place in our schools. (Leschied et al., 2018, p. 1; see also Offner,
2018).
Similarly, in their report on the foundations of student success, Wilson and Marshall (2019)
noted that whereas schools’ central focus is on academics, students’ “current and long-term
mental, emotional, and physical well-being strongly contribute to their ultimate success in life”.
Thus, there is a critical need to carefully measure critical mental health indices and track these
29
THE WELL-BEING INDEX
over time (needless to say, such ongoing assessments could be still more useful in wake of
pandemic-related disruptions across schools). It is our hope that given the documented
psychometric properties and ease of administration given its brevity, the WBI can be applied in
future school-based assessments toward maximizing the wellness of a generation of highly
stressed youth.
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Table 1
Descriptive Statistics and Psychometric Properties of Study Variables
Boys Girls Boys Girls
WBI Subscales
 
Mean SD Mean SD F gender Eta
sq
Depression .82 .84 5.60 4.33 7.50 4.48 113.75*** .05
Anxiety .82 .82 5.85 4.33 8.95 4.71 288.23*** .11
Rule-breaking .78 .78 4.04 3.66 3.35 3.30 24.17*** .01
Substance Use .83 .76 1.56 3.29 1.30 2.63 4.47*0
37
THE WELL-BEING INDEX
Isolation at School .74 .73 3.98 4.01 5.39 4.19 72.29*** .03
YSR Subscales a
 
Mean SD Mean SD
Anxious-depressed Raw score .95 .94 8.06 7.97 10.77 8.26 66.79*** .03
Anxious-depressed T score - - 63.43 14.91 64.72 15.28
Somatic Complaints Raw score .94 .92 5.69 5.80 7.32 5.98 45.76*** .02
Somatic Complaints T score - - 63.32 14.40 63.55 14.08
Rule-breaking Raw score .95 .95 8.85 8.11 8.03 7.57 6.49*0
Rule-breaking T score - - 62.96 13.79 61.66 12.51
Validating Variables
Mom Alienation .77 .77 8.21 3.62 8.76 3.74 12.82*** .01
Dad Alienation .80 .82 8.33 3.84 8.90 4.07 11.65** .01
School – Fairness of Discipline .86 .79 2.87 1.04 3.02 0.87 12.81*** .01
School – Teacher Alienation .92 .92 1.83 1.02 1.97 1.03 10.87** .01
Peer Victimization .92 .86 4.50 2.17 4.59 1.72 1.29 0
Relationship Stress .81 .73 1.91 0.84 2.14 0.79 43.44*** .02
Note. n = 1217 for boys and 1227 for girls.
a For the YSR, values are reported for both raw and T scores (boldface); the latter indicate that this 2019 sample
had higher mean T scores and SDs (T > 60; SDs > 12) than in 2001 norms (T = 50; SD = 10).
38
THE WELL-BEING INDEX
Table 2
Exploratory and Confirmatory Factor Analyses Using Maximum Likelihood Estimation and CF-Quartimax Rotation
EFA CFA
Factor 1 Factor 2 Factor 3 Factor 4
WBI Subscales Depression Anxiety Rule-breaking Substance Use Factor Loadings
Boys Girls Boys Girls Boys Girls Boys Girls Boys Girls
Low life enjoyment .69 .74 .08 -.02 -.01 .06 0 -.05 .73 .75
Low self-worth .43 .59 .37 .24 -.01 .05 0 -.08 .75 .70
Suicidal ideation .79 .81 -.09 -.13 .07 .01 .01 .07 .69 .70
Sad .71 .72 .18 .19 -.02 -.05 .04 .05 .86 .85
Tired .39 .28 .25 .28 .06 .16 .03 -.03 .56 .61
Anxious .03 .03 .86 .85 -.03 -.07 .03 .07 .83 .85
Nervous .04 -.02 .80 .82 .02 .04 -.06 -.05 .81 .82
Worry .01 .05 .68 .63 .11 .12 .02 -.02 .70 .72
Headaches .24 .14 .27 .28 .05 .14 .09 .04 .44 .48
Nausea .23 .13 .36 .45 .18 .11 .05 .06 .64 .65
Breaks school rules -.09 -.01 .06 -.01 .72 .62 .06 .08 .65 .72
Breaks parents’ rules .00 .02 .00 -.02 .74 .72 .09 .06 .81 .82
Cheats .08 -.05 -.11 -.01 .52 .60 -.05 -.03 .59 .55
Lies -.01 .04 .08 .09 .71 .63 -.06 -.08 .64 .70
Steals .18 .07 -.08 0 .56 .45 -.07 .11 .51 .54
Cigarettes .07 -.04 .02 .11 .06 -.02 .29 .38 .47 .42
Alcohol -.02 -.06 .02 0 .02 .11 .80 .74 .80 .83
Drunk -.05 0 .03 .03 -.02 -.07 .91 .90 .87 .89
Marijuana .14 .10 -.07 -.05 .02 .05 .63 .62 .64 .65
Vaping .20 .05 -.13 0 .13 .10 .47 .58 .66 .59
Note. n = 604 males and 617 females for EFA Sample; n = 623 males and 610 females for CFA Sample.
Shading indicates items loading onto the designated factor.
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THE WELL-BEING INDEX
Table 3
Correlations Among Well-Being Index, YSR, and Validating variables, and Results of Regressions with Symptoms Predicted by Validators
Variable 1 2 3 4 5 6 7 8 9 10 11 12 13 14
1. WBI Depression - .73** .41** .21** .67** .60** .51** .31** .45** .43** -.21** .28** .39**
.41**
2. WBI Anxiety .71** - .33** .17** .64** .56** .54** .24** .34** .33** -.15** .30** .35**
.37**
3. WBI Rule-breaking .42** .37** - .41** .37** .24** .26** .40** .38** .31** -.23** .21** .27**
.32**
4. WBI Substance Use .24** .15** .42** - .20** .11** .19** .37** .22** .20** -.15** .10** .27**
.20**
5. WBI Isolation at School .66** .59** .42** .10** - .52** .41** .26** .34** .31** -.22** .39** .44**
.41**
6. YSR Anxious-depressed .43** .43** .14** .20** .38** - .82** .75** .33** .28** 0 .16** .28**
.38**
7. YSR Somatic .34** .38** .16** .24** .26** .86** - .81** .27** .23** -.03 .16** .29**
.37**
8. YSR Rule-breaking .28** .23** .36** .44** .23** .80** .76** - .25** .20** -.02 .06*.24**
.31**
9. Mom Alienation .38** .33** .27** .18** .34** .31** .26** .25** - .44** -.14** .22** .27** .38**
10. Dad Alienation .36** .33** .32** .23** .35** .28** .25** .26** .51** - -.23** .21** .27** .35**
11. School–Fairness Discipline -.10** -.01 -.25** -.19** -.20** .06*.04 -.03 -.12** -.12** - -.25** -.19** -.17**
12. School–Teacher Alienation .28** .25** .28** .23** .35** .16** .17** .17** .22** .26** -.15** - .39** .34**
13. Peer Victimization .35** .29** .29** .27** .40** .31** .27** .26** .30** .27** -.12** .52** - .41**
14. Relationship Stress .36** .34** .22** .21** .37** .35** .29** .29** .32** .34** -.05 .37** .50** -
Note. Correlation coefficients for girls are in the top right of diagonal; those for boys are in the bottom left of the diagonal.
Dark and light shaded cells indicate WBI and YSR subscales, respectively, correlated with conceptually related constructs.
Table 4
Comparisons of Correlation Coefficients: WBI Subscales in Relation to Conceptually Similar/ Not Similar YSR Subscales
WBI Subscales WBI Subscale / YSR Subscale Conceptually similar / Not similar subscales
Boys rGirls r
Depression Anxious-depressed / Rule-breaking .43 / .28 *** .60 / .31 ***
Anxiety Anxious-depressed / Rule-breaking .43 / .23 *** .56 / .24 ***
Rule-breaking Rule-breaking / Anxious-depressed .36 / .14 *** .40 / .24 ***
Note. ***p < .001.
40
THE WELL-BEING INDEX
Table 5
Comparisons of Correlation Coefficients: Predictors in Relation to Conceptually Similar WBI / YSR Subscales
Predictors Correlations between WBI / YSR WBI / YSR
WBI subscale YSR subscale Boys rGirls r
Mom Alienation Depression / Anxious-depressed .38 / .31 ** .45 / .33 ***
Dad Alienation Depression / Anxious-depressed .36 / .28 ** .43 / .28 ***
Teacher Alienation Depression / Anxious-depressed .28 / .16 *** .28 / .16 ***
Fairness Discipline Depression / Anxious-depressed -.10a / .06 *** -.21a / .00 ***
Peer Victimization Depression / Anxious-depressed .35 / .31 .39 / .28 ***
Relationship Stress Depression / Anxious-depressed .36 / .35 .41 / .38
Mom Alienation Anxiety / Anxious-depressed .33 / .31 .34 / .33
Dad Alienation Anxiety / Anxious-depressed .33 / .28 *.33 / .28 *
Fairness Discipline Anxiety / Anxious-depressed -.01a / .06 ** -.15a / .00 ***
Teacher Alienation Anxiety / Anxious-depressed .25 / .16 ** .30 / .16 ***
Peer Victimization Anxiety / Anxious-depressed .29 / .31 .35 / .28 **
Relationship Stress Anxiety / Anxious-depressed .34 / .35 .37 / .38
Mom Alienation Rule-breaking / Rule-breaking .27 / .25 .38 / .25 ***
Dad Alienation Rule-breaking / Rule-breaking .32 / .26 ** .31 / .20 ***
Fairness Discipline Rule-breaking / Rule-breaking -.25 / -.03 *** -.23a / -.02 ***
Teacher Alienation Rule-breaking / Rule-breaking .28 / .17 *** .21 / .06 ***
Peer Victimization Rule-breaking / Rule-breaking .29 / .26 .27 / .24
Relationship Stress Rule-breaking / Rule-breaking .22 / .29 *.32 / .31
Note. *p < .05, **p < .01, ***p < .001. Instances where r for WBI subscale < r for YSR subscale are shown in
grey. a As perceived Fairness of Discipline is conceptually expected to be inversely correlated with symptoms,
these comparisons were favorable for WBI subscales.
Table 6
Concordance Among Well-Being Index and YSR Subscales Using WBI Normative Sample Cutoffs
YSR Anxious-depressed
Clinically significant or
“Much Above Average” (2 SD)
Borderline or
“Above Average” (1.5 SD)
WBI Depression Boys Girls Boys Girls
Agreement on Both 69% 72% 67% 65%
WBI No / YSR Yes 30% 27% 31% 34%
WBI Yes / YSR No 1% 1% 2% 1%
YSR Anxious-depressed
Clinically significant or
“Much Above Average” (2 SD)
Borderline or
“Above Average” (1.5 SD)
WBI Anxiety Boys Girls Boys Girls
Agreement on Both 70% 70% 66% 63%
WBI No / YSR Yes 29% 30% 33% 36%
WBI Yes / YSR No 1% 0% 1% 1%
YSR Rule-breaking
Clinically significant or
“Much Above Average” (2 SD)
Borderline or
“Above Average” (1.5 SD)
WBI Rule-breaking Boys Girls Boys Girls
Agreement on Both 70% 74% 68% 73%
WBI No / YSR Yes 27% 23% 28% 25%
WBI Yes / YSR No 3% 3% 4% 2%
Note. n = 1217 for boys and 1227 for girls. Cutoffs of 2 and 1.5 SDs for the YSR were based on published norms;
for the WBI, these two cutoffs were based on means and standard deviations within this sample. Bolded values
indicate the percentage of agreement between the YSR and WBI on classification of clinically significant and
borderline.
... Luthar 24 To examine the reliability and validity of the Well-Being Index as a useful potential measure of wellbeing of students in school-wide assessments. ...
... Three studies did not provide ethical approvement. 19,24,41 Rigorous data analysis was clearly presented in all but two studies. 21,37 The research value was adequately discussed in most studies. ...
... 12,14,28,38,44 The remaining were gathered person to person (12.1%). 24,25,37,43 The response rate varied from 25% to 100%. ...
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... All five schools were in the South, all were relatively high-achieving, and all had moved fully to distance learning during the first 8 weeks of school closures (Luthar et al., 2020a). The presence of clinically significant depression and anxiety was assessed by the Well-Being Index (WBI; Luthar et al., 2020b), a measure that has been well-validated against the "gold standard" of youth symptom assessments, the Youth Self-Report (YSR; Achenbach & Rescorla, 2001), in determining cutoffs for levels of symptoms that warrant clinical attention. ...
... Measures: Components of the SRS Depression and anxiety. The SRS included the two internalizing subscales, Depression and Anxiety, of the WBI, a psychometrically-validated measure (Luthar et al., 2020a(Luthar et al., , 2020b with each symptom measured by five items, each rated on a 5-point scale reflecting frequency of experience (0 = never, 4 = very often). Among schools assessed here, Depression alpha (α) reliability coefficients were 0.81 and 0.84 respectively for males and females, and for Anxiety, values were 0.84 and 0.86, respectively. ...
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Le criticità potrebbero essere trasformate in opportunità, progettando o rafforzando interventi psicosociali e formativi. Le ricerche (psicologiche, psicosociali, statistiche ecc…) fonti della mia tesi, sono ovviamente, quasi tutte recentissime, tutte le riviste hanno predisposto hub dedicati al COVID-19, e sono in continua evoluzione e aggiornamento. Altre fonti sono i documenti di varie organizzazioni, dal CENSIS al WHO all’OECD, ai documenti governativi italiani e non. Personalmente ho vissuto la DAD, quale docente di un istituto professionale.
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The purpose of this study is to describe in depth the eudaimonic happiness of al-Qur’an students in the Covid 19 pandemic era. This study uses a qualitative interpretive approach. The research design used a phenomenological research design. The subjects of this study were students of the Qur’an who live in the city of Yogyakarta. Data collection tools in this study were in-depth interviews and qualitative questionnaires. The data analysis technique in this research is thematic analysis technique. The method of validating the initial results of the preliminary research was carried out through the data triangulation process. The results showed that the eudaimonic happiness of the students of the Islamic scriptures was strong, as was the self-development of the students and their contribution to the welfare of others and the wider community. Keywords: happiness, eudaimonics, al quran students, covid pandemic era 19
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When children are exposed to serious life adversities, Ed Zigler believed that developmental scientists must expediently strive to illuminate the most critical directions for beneficial interventions. In this paper, we present a new study on risk and resilience on adolescents during COVID-19, bookended - in introductory and concluding discussions - by descriptions of programmatic work anchored in lessons learned from Zigler. The new study was conducted during the first two months of the pandemic, using a mixed-methods approach with a sample of over 2,000 students across five high schools. Overall, rates of clinically significant symptoms were generally lower as compared to norms documented in 2019. Multivariate regressions showed that the most robust, unique associations with teens' distress were with feelings of stress around parents and support received from them. Open ended responses to three questions highlighted concerns about schoolwork and college, but equally, emphasized worries about families' well-being, and positive outreach from school adults. The findings have recurred across subsequent school assessments, and strongly resonate with contemporary perspectives on resilience in science and policy. If serious distress is to be averted among youth under high stress, interventions must attend not just to the children's mental health but that of salient caregiving adults at home and school. The article concludes with some specific recommendations for community-based initiatives to address mental health through continued uncertainties of the pandemic.
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Youth in high achieving schools (HAS) are at elevated risk for serious adjustment problems—including internalizing and externalizing symptoms and substance use—given unrelenting pressures to be “the best.” For resilience researchers, successful risk evasion in these high-pressure settings should, arguably, be defined in terms of the absence of serious symptoms plus behaviorally manifested integrity and altruism. Future interventions should target that which is the fundamental basis of resilience: Dependable, supportive relationships in everyday settings. These must be promoted between adults and children and among them, toward enhancing positive development among youth and families in these high stress environments.
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In this chapter, we review evidence on a group recently identified as "at-risk", that is, youth growing up in the context of high achieving schools (HAS), predominated by well-educated, white collar professional families. Though these youngsters are thought of as "having it all", they are statistically more likely than normative samples to show serious disturbances across several domains including drug and alcohol use, as well as internalizing and externalizing problems. We review data on these problems with attention to gender-specific patterns, presenting quantitative developmental research findings along with relevant evidence across other disciplines. In considering possible reasons for elevated maladjustment, we appraise multiple pathways including aspects of family dynamics, peer norms, and pressures at schools. All of these pathways are considered within the context of broad, exosystemic mores: the pervasive emphasis, in contemporary American culture, on maximizing personal status, and how this can threaten the well-being of individuals and of communities. The chapter concludes with ideas for future interventions, with discussions on how research-based assessments of schools can best be used to reduce pressures, and to maximize positive adaptation, among youth in highly competitive, pressured school environments.
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Social-emotional competence is a critical factor to target with universal preventive interventions that are conducted in schools because the construct (a) associates with social, behavioral, and academic outcomes that are important for healthy development; (b) predicts important life outcomes in adulthood; (c) can be improved with feasible and cost-effective interventions; and (d) plays a critical role in the behavior change process. This article reviews this research and what is known about effective intervention approaches. Based on that, an intervention model is proposed for how schools should enhance the social and emotional learning of students in order to promote resilience. Suggestions are also offered for how to support implementation of this intervention model at scale.
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Compiled in this Special Section are recommendations from multiple experts on how to maximize resilience among children at risk for maladjustment. Contributors delineated processes with relatively strong effects and modifiable by behavioral interventions. Commonly highlighted was fostering the well-being of caregivers via regular support, reduction of maltreatment while promoting positive parenting, and strengthening emotional self-regulation of caregivers and children. In future work, there must be more attention to developing and testing interventions within real-world settings (not just in laboratories) and to ensuring feasibility in procedures, costs, and assessments involved. Such movement will require shifts in funding priorities—currently focused largely on biological processes—toward maximizing the benefits from large-scale, empirically supported intervention programs for today's at-risk youth and families.
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Teachers in the US are now considered integral to promoting students’ mental health; here we report on two major challenges for educators in high achieving schools (HAS). The first involves high adjustment disturbances among students. We present data on nine HAS cohorts showing elevated rates of clinically significant symptoms relative to norms; rates of anxious-depressed symptoms, in particular, were six to seven times those in national norms on average. As high achieving youth often keep internalizing symptoms hidden, their teachers will need help in understanding how to identify early signs of these types of distress, and to ensure appropriate, timely interventions. The second challenge we consider has to do with relationships between service providers and parents. Data obtained from the former showed that they tend to perceive relatively wealthy parents more negatively, and as more likely to threaten litigation, compared to parents from middle- or low-income backgrounds. We discuss the importance of proactively addressing such potentially adversarial relationships for the success of both the early detection of HAS students’ adjustment problems, and appropriate interventions for them. Next, we appraise how the aforementioned challenges can greatly exacerbate risks for burnout among educators in HAS settings, and how this might be alleviated via evidence-based, institutional-level interventions. Schools must ensure ongoing support for educators who carry the weighty, dual charge of tending to the emotional needs of a group of highly stressed students, in addition to ensuring their continued, exemplary levels of educational accomplishments.
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Excessive pressures to excel, generally in affluent contexts, are now listed among the top 4 "high risk" factors for adolescents' mental health, along with exposure to poverty, trauma, and discrimination. Multiple studies of high-achieving school (HAS) cohorts have shown elevated rates of serious symptoms relative to norms, with corroborating evidence from other research using diverse designs. Grounded in theories on resilience and ecological influences in development, a conceptual model is presented here on major risk and protective processes implicated in unrelenting achievement pressures facing HAS youth. These include forces at the macrolevel, including economic and technological changes that have led to the "middle class squeeze," and proximal influences involving the family, peers, schools, and communities. Also considered are potential directions for future interventions, with precautions about some practices that are currently widespread in HAS contexts. In the years ahead, any meaningful reductions in the high distress of HAS youth will require collaborations among all stakeholders, with parents and educators targeting the specific areas that must be prioritized in their own communities. Leaders in higher education and social policy could also help in beginning to curtail this problem, which is truly becoming an epidemic among today's youth. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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Drawing from the National Survey on Drug Use and Health (NSDUH; N = 611,880), a nationally representative survey of U.S. adolescents and adults, we assess age, period, and cohort trends in mood disorders and suicide-related outcomes since the mid-2000s. Rates of major depressive episode in the last year increased 52% 2005-2017 (from 8.7% to 13.2%) among adolescents aged 12 to 17 and 63% 2009-2017 (from 8.1% to 13.2%) among young adults 18-25. Serious psychological distress in the last month and suicide-related outcomes (suicidal ideation, plans, attempts, and deaths by suicide) in the last year also increased among young adults 18-25 from 2008-2017 (with a 71% increase in serious psychological distress), with less consistent and weaker increases among adults ages 26 and over. Hierarchical linear modeling analyses separating the effects of age, period, and birth cohort suggest the trends among adults are primarily due to cohort, with a steady rise in mood disorder and suicide-related outcomes between cohorts born from the early 1980s (Millennials) to the late 1990s (iGen). Cultural trends contributing to an increase in mood disorders and suicidal thoughts and behaviors since the mid-2000s, including the rise of electronic communication and digital media and declines in sleep duration, may have had a larger impact on younger people, creating a cohort effect. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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This chapter is about two interconnected main premises that follow from acknowledging the presence of young people who suffer in silence. First, the prevalence of anxiety and depression and other mental health problems among adolescents is not only large and growing, but it is also very much underestimated; that is, we are facing a much bigger problem than most people realize. Second, many young people are hiding their problems behind a façade, and they never seek help or even confide in friends or family members. In essence, they are “flying under the radar,” and the people in their lives are largely unaware of this hidden psychological pain. This chapter examines this hidden psychological pain and the reasons for it. While our focus is primarily on depression and anxiety, it is acknowledged that secret mental health issues can take many forms, including secret acts of intentional self-harm and eating behavior (e.g., bulimia). It is also likely that some of the experiences that potentiate the false self are kept hidden due to the anticipated reactions of other people (e.g., the feelings of loneliness that often accompany depression and social anxiety).