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Appendix A 15

Appendix A

AnAlytic strAtegy

o describe the psychometric properties o the

secondary and elementary school resilience and

youth development modules, this report examines

Te dimensionality o scales by using explor-

atory and conrmatory actor analysis models.

Measurement equivalence across demo-

graphic subgroups by estimating conrma-

tory actor analysis models with covariates

(such as multiple indicator, multiple cause

structural equation models).

Scale reliability by estimating internal consis-

tency and test-retest reliability coecients.

Construct validity by examining the relation-

ship o scales to other theoretically related

constructs and mean dierences across demo-

graphic subgroups.

Data

Statewide data rom the local administration o the

Healthy Kids Survey.Te data or the analyses inthis report are rom local administration o the

Healthy Kids Survey (HKS) in elementary, middle,

and high schools. Tese data were drawn rom a

database o all local HKS data processed between

1998 and spring 2005 by WestEds Health and

Human Development Program (approximately

2.1 million observations). Analyzing such a large

sample size would, however, make almost every

parameter estimate statistically signicant, would

inate chi-square values o model t, and would

make assessing substantive signicance moredicult. Tus, two mutually exclusive analytic

samples were used in the analyses: a main sample

and a validation sample. Te samples were drawn

rom the aggregate data le that included all HKS

data processed between the spring 2003 and the

spring 2005 administrations o the Healthy Kids

Survey. For the secondary school analysis, separate

samples were drawn or each grade (7, 9, and 11),

gender, and ethnicity (Chinese American, Arican

American, Mexican American, and white Euro-

pean American)with 500 respondents randomly

sampled per cell (12,000 total). Equal numbers

were used or each gender and ethnic group so

that models that do not adjust or gender and/orethnicity would not be aected by gender/ethnic

dierences in the sample.

Te elementary school Healthy Kids Survey is ad-

ministered only to fh graders and does not ask

students about their ethnic/racial group. Random

samples o 1,000 males and 1,000 emales (2,000

total) were drawn rom the aggregated HKS data

le. Tus, or the elementary school resilience and

youth development module, only gender dier-

ences in measurement structure were examined.Respondents with missing data on more than

hal the resilience items were excluded rom the

analysis. For estimating models with missing data,

maximum likelihood estimation with missing at

random (MAR) assumptions were used, which

assume that values are missing at random con-

ditional on the other observed items in the data

(Little & Rubin, 2002; Muthn & Muthn, 2006).

(See section on missing data patterns.)

Te same procedures were used to draw thevalidation samples or both the secondary school

and elementary school samplesexcept that

respondents included in the main sample were ex-

cluded rom the validation sample. Te data were

weighted by grade, race/ethnicity, and gender to

represent the characteristics o HKS respondents

surveyed rom spring 2003 to spring 2005.

Local evaluation HKS data.Statewide data was

supplemented with two sets o HKS data originally

collected or local evaluation. Data collected in2006 rom a large urban school district in South-

ern Caliornia were used to describe the temporal

stability o the derived scales (test-retest reliability).

Te elementary school Healthy Kids Survey and the

secondary school core module and resilience and

youth development module were administered two

times in two weeks to 132 fh-grade students and

90 ninth-grade students. Data collected in 2004/05


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16 MeAsuring resilience And youth developMent: the psychoMetric properties o the heAlthy Kids survey

rom students in a large county in Southern Cali-

ornia were used to examine the relationship be-

tween the RYDM constructs and standardized test

scores. Standardized test score and school/com-

munity asset data were available or 2,898 students,

while test score and home and internal asset datawere available or 651 students.6 English Language

Arts and Mathematics Caliornia Standards est

scale scores were used as criterion variables.

Missing data patterns. Approximately 0.5 percent

o respondents in the elementary and secondary

modules were excluded rom the sampling pool

because o missing data on more than hal the

resilience items (table A1). In the secondary school

samples, approximately 65 percent o respondents

provided answers to all the survey items in theresilience and youth development module; an ad-

ditional 18 percent had missing values on one or

two items; 8 percent had missing values on 3 to 10

items; and 8 percent had missing values on 11 or

more items. Respondents with missing values on

11 or more items had lower scores on about one-

quarter o the secondary RYDM itemsscoring

approximately 912 percent o a standard devia-

tion lower on these items. Tese results held or

both the main and validation samples. Dierences

in item means were diminished signicantly afercontrolling or one or two o the remaining items,

suggesting that the missing at random assumption

is reasonable.

Approximately 81 percent o elementary students

provided valid answers to all the RYDM items

and 15 percent answered all but one or two items.Respondents with missing values on two or more

items had lower scores on seven o the elementary

RYDM items (averaging 0.24 standard deviations).

Tese dierences were no longer apparent afer

controlling or any two o the remaining items,

again suggesting that maximum likelihood esti-

mation with missing at random assumptions will

yield unbiased parameter estimates.

Exploratory and conrmatory actor analyses

Analyses were conducted to test empirically

whether the actor structure o the resilience in-

strument is consistent with current usage and with

its underlying conceptual model. For each sample

and subsample (grade, gender, ethnicity), the mea-

surement structure o the resilience instrument

was established by tting a series o exploratory

and conrmatory actor analysis models. Explor-

atory actor analysis (EFA) models were estimated

to determine roughly the number o actors under-

lying the data and the measurement structure othe latent actors. A combination o actors was

tAble A1

M aa a o oa a ma am om

h a oh vom mo

nm

m

m

sa ema

Ma am vaa am Ma am vaa am

nm

p

nm

p

nm

p

nm

p

0 7,819 65.2 7,865 65.5 1,627 81.4 1,622 81.1

1 1,634 13.6 1,615 13.5 266 13.3 249 12.5

2 585 4.9 545 4.5 55 2.8 59 3.0

35 497 4.1 539 4.5 33 1.7 45 2.3

610 445 3.7 437 3.6 15 0.8 14 0.7

11 m 1,020 8.5 999 8.3 4 0.2 11 0.6

ta 12,000 100 12,000 100 2,000 100 2,000 100

Note: Analytic samples randomly drawn rom students surveyed between spring 2003 and spring 2005. Secondary school resilience and youth development

module has 51 survey items. The elementary school module has 21 survey items.


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Appendix A 17

used to determine the number o actors to retain

in the EFAs, including t indices, scree plots, the

number o eigenvalues greater than 1, conceptual

clarity, and simplicity. Models with the ewest

possible actors and models with no cross-loadings

were avored over more complex models.

Te results o the exploratory actor analysis mod-

els were then used as a starting point or a series o

nested conrmatory actor analysis (CFA) models.

Measures o model t, correlations among the

latent constructs (actors), and actor-loading pat-

terns were used to make decisions about models.

Tis process was replicated or each grade, gender,

and ethnic group, and or the main sample and the

validation sample.

o derive estimates or the EFA and CFA models,

Muthn and Muthns (2006)Mplus statistical

modeling program was used. Because all the items

used to measure resilience assets are ordinal,

Muthns (1984) approach to exploratory and

conrmatory actor analysis with ordinal indica-

tors was used.

In the general actor analysis model, the relation-

ship between the indicators (y*) and the under-

lying constructs () can be represented by:

(A1) y*= + +

where is a vector o measurement intercepts, is

a matrix o measurement slopes (actor loadings),

and is a matrix o residuals, assumed to be inde-

pendent o and with zero expectation. Te model

implies the ollowing covariance matrix oy*:

(A2) = +

where is the covariance matrix o and is the

covariance matrix o (see Long, 1983).

In general, the indicatorsy*are assumed to be

normally distributed, latent continuous variables.

A persons observed score on itemy depends on

her/his position ony*. I the observed item is con-

tinuous,y*is directly observed (y =y*). However,

i the observed item is dichotomous or ordinal, the

observed categorical variable (y) is linked to the

latent continuous variable (y*) in a nonlinear way

through a model o thresholds (see Muthn, 1984).

Te relationships between an observed ordinal or

dichotomous itemy with c categories to y* can beexpressed as:

(A3) y = c, ic


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emale to school meaningul participation indi-

cates that the means o the underlying construct

are allowed to be dierent or males and emales.

Te actor loadings are not allowed to be dier-

ent or males and emales, and there is no direct

eect o emale on the individual items. Te model

assumes that the items unction identically or

males and emales in measuring school meaning-

ul participation.8

Te measurement model in panel B allows or

emale/male nonequivalence in the measurement

intercept or item R14. Tat is, it allows or a direct

eect o emale on R14 that is not dependent on

the underlying construct. Tis is indicated by the

arrow going directly rom emale to R14. A sig-

nicant emale/male dierence in measurement

intercept indicates that the item unctions di-

erently or emales and males in measuring the

underlying construct. For example, i the measure-

ment intercept or R14 is 25 percent o a standard

deviation (emale R14) lower or emales than

males, then or a given level o school meaningulparticipation, emales score 25 percent o a standard

deviation lower on R14. In this example, a given

score on item R14 does not mean the same thing or

males and emalesat least not with reerence to

the school meaningul participation construct.

An applied strategy was used to ascertain whether

group dierences in measurement intercepts have

implications or evaluation research. Recommen-

dations or item changes are made only when the

measurement intercepts are substantively dierentacross groups ( 0.20 standard deviations) in both

the main sample and the validation sample.

Fit indices

A mean- and variance-adjusted 2 test o model t

is obtained by multiplying the minimum unc-

tion by twice the total sample size and dividing by

a scaling correction actor (or more details, see

Muthn, 1984, 1987; Muthn & Muthn, 2006).

Afer adjusting or the scaling correction ac-tor (see Satorra, 2000; Satorra & Bentler, 1999;

Muthn & Muthn, 2006), the dierence in 2 tests

or two nested models ollows a 2 distribution

and can be used to test whether a model results

in a statistically signicant improvement in t.

However, 2 dierence tests are sensitive to sample

size and can be inuenced by substantively mean-

ingless parameter dierences in large samples.

For this reason, the analysis also relied on several

other indices o model t.

For EFA models, root mean square residual

(RMSR) and root mean square error o approxi-

mation (RMSEA) values were used to assess model

t (Hu & Bentler, 1999). RMSR is the square root

o the mean o the squared residuals and indexes

the dierence between the sample variance/covari-

ance matrix and the variance/covariance matrix

predicted by the model. Hu and Bentler (1999)

R12

R13

R14

School

meaningful

participation

Panel A MIMIC modelingno measurement invariance

Female

R12

R13

R14

School

meaningful

participation

Panel B MIMIC modelinghypothetical gender

measurement intercept invariance (differential item

functioning for R14)

Female

igure A1

Hoha am o MiMic aoah

o o mam qva

Note: MIMIC reers to multiple indicators multiple causes structuralequation models.


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Appendix A 19

suggest that RMSR values less than 0.05 indicate

good t. Te RMSEA is also based on dierences

between the observed and predicted variance/

covariance matrices, but penalizes or model com-

plexity. RMSEA is computed by:

(A5) RMSEA = 2

(n*df)1// ( )n

where 2 is the model chi-square value, n is the

total sample size, and dis the degrees o ree-

dom. RMSEA penalizes or model complexity

by dividing 2 by (n*d). Hu and Bentler (1999)

recommend RMSEA values o 0.06 or less as

the cut-o or good model t. Based on Hu and

Bentlers recommendations, more emphasis is

placed on RMSEA than on RMSR in EFA modelselection.

In addition to RMSEA, several additional t

indices were used to assess CFA models, includ-

ing Bentlers comparative t index (CFI), the

ucker-Lewis index (LI), and Muthn and

Muthns (2006) weighted root mean square

residual (WRMR). As implemented in Mplus, both

the CFI and LI compare estimated CFA models

to baseline models with uncorrelated variables

(independence model). CFI and LI are calculatedas ollows:

(A6) CFI =1max 2

Hodf

Ho, 0

max 2Ho

dfHo

, 2Bdf

B, 0

(A7)TLI =

2B

dfB

2Ho

dfHo

2B

dfB 1

where 2 and dHo denote the chi-squared value

and degrees o reedom o the estimated model

and 2 and dB denote the same or the baseline

model. Both CFI and LI are not appreciably

inuenced by sample size. By convention, CFI and

LI values greater than 0.95 indicate good t (Hu

& Bentler, 1999).

Yu and Muthn (2001) recently developed WRMR

to identiy good-tting models with categorical

outcomes. It is dened as ollows:

(A8) WRMR =e

(sr r)

vr

e

r

where sr is an element in the sample variance/

covariance (or probit threshold/polychoric cor-

relation) matrix, r is the element in the variance/

covariance matrix predicted by the model, r

is an estimate o the variance osr, and e is the

number o elements in the variance/covariance

matrix. According to Muthn, WRMR is suitable

or models where sample statistics have widely

varying variances, when sample statistics are on

dierent scales, and in models with categoricaloutcomes. Yu and Muthn (2001) suggest WRMR

values less than or equal to 1.00 or good models

with categorical outcomes. Because WRMR has

been tested or models with categorical outcomes,

greater weight is placed on this index in CFA

model selection.

Modication indices and 2 dierence testing

were also used to compare nested conrmatory

actor analyses models, particularly or testing

measurement intercept invariance.

Additional reliability and validity analyses

Internal consistency estimates o reliability o the

derived scales were calculated using Cronbachs

alpha or each grade, gender, and ethnic group in

both the main sample and the validation sample.

Nunnalys (1978) criterion o 0.70 was used as the

cuto or determining acceptable internal consis-

tency reliability or the secondary school survey.

Because o the notoriously low internal consis-tency evident in surveys o elementary school

students, this criterion was relaxed slightly to 0.60

or the elementary school resilience and youth

development module. o examine test-retest reli-

ability, RYDM survey data collected rom a small

sample o fh and ninth graders who took the

resilience and youth development module twice in

two weeks was used.


6/29


Dierences in resilience scale scores across the

demographic subgroups were also examined.

o make demographic dierences in the resil-

ience scales more interpretable, eect sizes were

calculated to represent the magnitude o such

dierences (Cohen, 1988). With two groups (male/emale), the dierence in scale means between

each group was divided by the pooled standard

deviation (Cohens d). Tus, the standardized

dierence represents the dierence between each

group in standard deviation units. With more

than two groups (race/ethnicity), the standard-

ized dierences were represented by multiplying

Cohensby 2which is roughly equivalent to the

standardized dierence calculated or two groups

when the number o observations in each cell is

equal (Cohen, 1988). Cohenswas calculated by

(A9) f=

(mim)2

kk

i=1

where mi represents the mean or each subgroup i,

m represents the population mean, k the number

o subgroups, and the pooled standard deviation.

Construct validity was assessed by examining

the relationship o the derived resilience scales toother theoretically related constructsincluding

substance use, school violence, school-related

behavior, and standardized test scores. o exam-

ine these relationships using a common metric,

correlations between resilience constructs and

criterion variables rom conrmatory actor analy-

sis models were estimated using the main and

validation samples. Latent constructs represent

continuous variables, while the criterion variables

are either dichotomous or ordinal. Tus, poly-

serial correlations are presented, which representthe correlation between a continuous variable and

a dichotomous or ordinal variable that reects

an underlying continuous variable (Bedrick &

Breslin, 1996).


7/29

Appendix b 21

Appendix B

results

Tis appendix presents the results o the analyses

conducted to evaluate the psychometric properties

o the resilience and youth development module.

Secondary school environmental resilience assets

Exploratory actor analysis results. EFA models were

estimated or each subpopulation and or the main

and validation samples to determine the number

o actors underlying the items. Te EFA models

suggested that the environmental resilience assets

items measure eight actors.9 Te actor pattern and

loadings or the main sample and cross-validation

sample are displayed in tables B1 and B2, respec-tively. Te 8-actor EFA solutions show conceptu-

ally clear actor-loading patterns that are mostly

consistent with the underlying theory guiding the

development o the instrument. Te pattern o ac-

tor loadings across all the demographic subgroups

is consistent with those displayed in tables B1 and

B2.10 Distinct actors are apparent or support and

meaningul participation in the school, community,

and home environments, as well as caring and pro-

social relationships in the peer environment.

However, the actor pattern evident in the 8-actor

solution is inconsistent with how the instrument

currently is being used in Caliornia because the

results suggest that caring relationships and high

expectations at school, in the home, and in the

community are notdistinct actors.

Confrmatory actor analysis results. A CFA model

equivalent to the 8-actor EFA models in tables

B1 and B2 was estimatedexcept that all but the

highest magnitude loadings rom the EFA modelwere constrained to be zero.11 Tat is, each item

was orced to load on only one actor. As with the

EFA models, the results were consistent across

each sample. Te CFA models indicated that item

R45 (My riends get into a lot o trouble) has a

relatively small actor loadingsuggesting that an

association with peers who get into a lot o trouble

is a less sensitive indicator o pro-social peers

than the other two items assessing this construct.

Moreover, there was a relatively high correlation

between home support and home meaningul

participation (0.78 and 0.79), which suggests that

these two constructs may not be distinct.

Te CFA models were re-estimated to include covari-

ates to detect dierences in measurement intercepts

across demographic subgroups. Several measure-

ment intercepts diered by demographic subgroup:

Te results or R23 (I help other people)

suggest that or a given level o community

meaningul participation, emale and Mexi-

can American youth report between one-fh

and one-third o a standard deviation higher

or helping other people. Te item thus has adierent meaning or these two populations.

For R54 (I do un things or go un places

with my parents), 11th graders report

substantially lower levels o participation in

un activities with parents or a given level o

home meaningul participation than do sev-

enth and ninth graders (0.29 to 0.33 standard

deviations). Tis represents a developmental

dierence in the appropriateness o this item.

Female and Chinese American youth report

lower requencies on R45 (My riends get into

a lot o trouble) or a given level o pro-social

peersreecting the dierent meaning at-

tached to this item by these populations.

Each o these measurement intercept dierences is

substantively signicant. Tat is, these particular

items assess the underlying constructs dierently

or demographic subgroups and thus should not be

used as indicators. Dropping these items, however,leaves three subscales with only two items, which is

ar rom ideal. able B3 presents revised CFA mod-

els afer dropping the items with non-invariant

measurement intercepts. able B4 reports latent

actor correlations.12 Note that the correlations

between home support and home meaningul par-

ticipation remain relatively high (0.73), indicating a

high degree o overlap between these two actors.


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tAble b1

soa hoo voma a oao ao

aa , ma am, 8-ao oo

oa

a

im im 1 2 3 4 5 6 7 8

r6 sca sa w a a a m. 0.75 0.08 0.02 0.02 0.07 0.03 0.06 0.01

r8 sca sa w w im . 0.79 0.02 0.01 0.03 0.03 0.04 0.04 0.06

r10 sca sa w m

w i a m . . . 0.86 0.02 0.01 0.01 0.02 0.04 0.02 0.00

r7 sh sa w m w i a j. 0.82 0.02 0.00 0.01 0.02 0.01 0.02 0.02

r9 sh sa w awa wa m m . 0.92 0.05 0.02 0.03 0.05 0.06 0.03 0.02

r11 sh sa w a i w a . 0.83 0.01 0.05 0.00 0.03 0.01 0.05 0.04

r12 spa si a. 0.08 0.57 0.01 0.19 0.08 0.06 0.01 0.01

r13 spa si k a a 0.02 0.91 0.02 0.09 0.01 0.02 0.00 0.00

r14 spa si a mak a . 0.04 0.79 0.04 0.01 0.02 0.05 0.00 0.04

r15 cmca cmma w a a a m. 0.04 0.05 0.95 0.03 0.04 0.04 0.02 0.00

r17 cmca cmma w w i am a . . . 0.02 0.03 0.90 0.05 0.01 0.07 0.05 0.04

r20 cmca cmma wm i . 0.02 0.04 0.82 0.02 0.03 0.08 0.00 0.00

r16 cmh cmma w m w i a j. 0.01 0.01 0.90 0.02 0.03 0.04 0.01 0.01

r18 cmh cmma w a i w a . 0.02 0.05 0.90 0.02 0.10 0.05 0.02 0.03

r19 cmh cmma w awa wa m m . 0.04 0.01 0.95 0.00 0.05 0.08 0.03 0.04

r21 cmpa i am a , am, /

m, . . . 0.03 0.06 0.02 0.82 0.01 0.03 0.04 0.03

r22 cmpa i am ak m, a, a . . . 0.02 0.07 0.03 0.97 0.00 0.01 0.01 0.06

r23 cmpa i . 0.05 0.10 0.09 0.46 0.09 0.19 0.08 0.07

r49 hmca hm a w m wk . 0.02 0.07 0.03 0.00 0.86 0.01 0.01 0.02

r51 hmca hma w ak w m a m m. 0.03 0.08 0.02 0.12 0.77 0.27 0.01 0.10r53 hmca hma w m

w i a m . . . 0.02 0.01 0.03 0.12 0.76 0.32 0.03 0.06

r48 hmh hma w m w . 0.01 0.02 0.01 0.13 0.76 0.18 0.06 0.09

r50 hmh hma w a i w a . 0.04 0.02 0.07 0.03 0.83 0.02 0.00 0.03

r52 hmh hma w awa wa m m . 0.03 0.08 0.05 0.09 0.89 0.08 0.01 0.06

r54 hmpa i a w

m a . . . 0.01 0.08 0.01 0.04 0.30 0.63 0.02 0.04

r55 hmpa i a m a mak a . 0.02 0.11 0.00 0.08 0.09 0.68 0.00 0.08

r56 hmpa i mak w m am. 0.03 0.02 0.02 0.01 0.23 0.70 0.03 0.01

r42 pca A w a a a m. 0.02 0.04 0.04 0.05 0.04 0.04 0.83 0.06

r43 pca A w ak w m a m m. 0.02 0.03 0.01 0.03 0.01 0.01 0.96 0.00

r44 pca A w m w im a a a m. 0.00 0.00 0.00 0.03 0.02 0.02 0.92 0.02

r45 ph M a . 0.05 0.05 0.03 0.03 0.01 0.01 0.02 0.45

r46 ph M wa . 0.02 0.02 0.02 0.07 0.03 0.05 0.04 0.92

r47 ph M w . 0.02 0.03 0.01 0.01 0.05 0.05 0.02 0.68

Note: Analytic samples consist o 12,000 7th-, 9th-, and 11th-grade respondents sampled rom surveys administered between spring 2003 and spring 2005.

Weighted data. Loadings with largest absolute values bolded.


9/29

Appendix b 23

tAble b2

soa hoo voma a oao ao

aa , vaao am, 8-ao oo

oa

a

im im 1 2 3 4 5 6 7 8

r6 sca sa w a a a m. 0.76 0.03 0.03 0.01 0.10 0.06 0.05 0.03

r8 sca sa w w im . 0.78 0.03 0.02 0.03 0.04 0.04 0.03 0.04

r10 sca sa w m

w i a m . . . 0.85 0.02 0.02 0.03 0.04 0.04 0.01 0.01

r7 sh sa w m w i a j. 0.82 0.02 0.01 0.01 0.01 0.01 0.01 0.02

r9 sh sa w awa wa m m . 0.90 0.07 0.01 0.03 0.05 0.05 0.04 0.01

r11 sh sa w a i w a . 0.84 0.07 0.01 0.03 0.06 0.05 0.01 0.02

r12 spa si a. 0.11 0.59 0.01 0.18 0.06 0.07 0.04 0.03

r13 spa si k a a 0.03 0.88 0.03 0.09 0.01 0.01 0.00 0.00

r14 spa si a mak a . 0.02 0.80 0.04 0.00 0.02 0.04 0.01 0.03

r15 cmca cmma w a a a m. 0.02 0.06 0.95 0.03 0.08 0.01 0.03 0.02

r17 cmca cmma w w i am a . . . 0.01 0.01 0.89 0.06 0.02 0.08 0.03 0.03

r20 cmca cmma wm i . 0.00 0.02 0.83 0.01 0.04 0.06 0.02 0.03

r16 cmh cmma w m w i a j. 0.03 0.01 0.89 0.02 0.01 0.07 0.00 0.01

r18 cmh cmma w a i w a . 0.02 0.08 0.89 0.02 0.11 0.07 0.01 0.00

r19 cmh cmma w awa wa m m . 0.04 0.02 0.95 0.01 0.07 0.12 0.03 0.01

r21 cmpa i am a , am, /

m, . . . 0.03 0.06 0.02 0.83 0.02 0.01 0.02 0.03

r22 cmpa i am ak m, a, a . . . 0.00 0.07 0.01 0.97 0.02 0.03 0.02 0.05

r23 cmpa i . 0.04 0.13 0.08 0.47 0.08 0.16 0.09 0.05

r49 hmca hm a w m wk . 0.03 0.05 0.03 0.03 0.85 0.03 0.01 0.00

r51 hmca hma w ak w m a m m. 0.05 0.08 0.04 0.12 0.74 0.30 0.02 0.09r53 hmca hma w m

w i a m . . . 0.02 0.03 0.06 0.12 0.73 0.32 0.02 0.07

r48 hmh hma w m w . 0.01 0.03 0.00 0.11 0.75 0.20 0.07 0.12

r50 hmh hma w a i w a . 0.06 0.02 0.07 0.03 0.81 0.04 0.01 0.03

r52 hmh hma w awa wa m m . 0.08 0.08 0.05 0.08 0.85 0.05 0.03 0.03

r54 hmpa i a w

m a . . . 0.04 0.07 0.01 0.05 0.23 0.67 0.06 0.06

r55 hmpa i a m a mak a . 0.03 0.15 0.03 0.10 0.06 0.68 0.04 0.05

r56 hmpa i mak w m am. 0.02 0.02 0.00 0.01 0.16 0.77 0.02 0.02

r42 pca A w a a a m. 0.04 0.05 0.04 0.04 0.03 0.02 0.83 0.05

r43 pca A w ak w m a m m. 0.02 0.03 0.02 0.03 0.00 0.02 0.96 0.01

r44 pca A w m w im a a a m. 0.01 0.01 0.01 0.03 0.03 0.01 0.91 0.03

r45 ph M a . 0.07 0.07 0.04 0.01 0.02 0.03 0.09 0.42

r46 ph M wa . 0.02 0.02 0.01 0.04 0.01 0.02 0.07 0.85

r47 ph M w . 0.01 0.04 0.04 0.05 0.02 0.05 0.01 0.77


Weighted data. Loadings with largest absolute values bolded.


10/29


tAble b3

Fa oa hoo voma a mo, ma am

im

oa

c a aa m

ema

a

saa

a

School support

r6 sca sa w a a a m. 1 0.80

r8 sca sa w w im . 0.98 0.79

r10 sca sa w m w i a m . . . 1.08 0.86

r7 sh sa w m w i a j. 1.05 0.84

r9 sh sa w awa wa m m . 1.09 0.87

r11 sh sa w a i w a . 1.10 0.88

School meaningul participation

r12 spa si a. 1 0.78

r13 spa si k a a . 0.98 0.77

r14 spa si a mak a . 1.12 0.88

Community supportr15 cmca cmma w a a a m. 1 0.92

r17 cmca cmma w w i am a . . . 0.99 0.91

r20 cmca cmma wm i . 0.97 0.88

r16 cmh cmma w m w i a j. 1.03 0.94

r18 cmh cmma w a i w a . 1.04 0.95

r19 cmh cmma w awa wa m m . 1.04 0.95

Community meaningul participation

r21 cmpa i am a , am, /m, . . . 1 0.88

r22 cmpa i am ak m, a, a . . . 0.97 0.86

Home support

r49 hmca hma w m wk. 1 0.84

r51 hmca hma w ak w m a m m. 1.03 0.87

r53 hmca hma w m w i a m . . . 1.05 0.89

r48 hmh hma w m w . 0.93 0.78

r50 hmh hma w a i w a . 1.10 0.92

r52 hmh hma w awa wa m m . 1.10 0.92

Home meaningul participation

r55 hmpa i a m a mak a . 1 0.85

r56 hmpa i mak w m am. 1.02 0.86

Peer caring relationships

r42 pca A w a a a m. 1 0.92

r43 pca A w ak w m a m m. 1.01 0.92

r44 pca A w m w im a a a m. 1.03 0.94

Pro-social peers

r46 ph M wa . 1 0.86

r47 ph M w . 0.91 0.78


Weighted data.


11/29

Appendix b 25

Elementary school environmental resilience assets

Exploratory actor analysis results. An identi-

cal strategy was used to analyze the elementary

school RYDM environmental resilience items.

EFA models suggested that a 4-actor model best

represents the environmental resilience items,

with distinct actors or school support (car-

ing relationships and high expectations), home

support, meaningul participation (in the school

and home domains), and pro-social peers (tables

B5 and B6). Tese results were ound or both the

main sample and the validation sample and or

both boys and girls.

tAble b4

coao amo oa hoo voma

a, a omao ao aa mo

a

Ma am (1) (2) (3) (4) (5) (6) (7) (8)

(1) s 1.00

(2) s ma aa 0.59 1.00

(3) cmm 0.54 0.42 1.00

(4) cmm ma aa 0.42 0.58 0.46 1.00

(5) hm 0.47 0.37 0.59 0.44 1.00

(6) hm ma aa 0.48 0.59 0.51 0.38 0.73 1.00

(7) p a a 0.41 0.35 0.46 0.34 0.46 0.44 1.00

(8) p-a 0.42 0.40 0.38 0.39 0.49 0.50 0.54 1.00


Weighted data.

tAble b5

ema hoo voma a oao ao

aa , ma am, 4-ao oo

im

oa

im 1 2 3 4

10 sca d a . . . a a a ? 0.74 0.05 0.01 0.01

13 sca ta . . . w . . . a m a? 0.62 0.07 0.00 0.05

11 sh ta . . . w a j? 0.56 0.02 0.17 0.07

14 sh ta . . . a a a j? 0.67 0.10 0.02 0.03

52 hmca pa . . . a a wk? 0.00 0.81 0.01 0.01

55 hmca pa . . . w a m a? 0.06 0.51 0.20 0.01

53 hmh pa . . . a a a j? 0.11 0.79 0.00 0.02

54 hmh pa . . . a m wa ? 0.10 0.77 0.03 0.00

9 spa d mak a / a ? 0.14 0.16 0.48 0.05

15 spa d a ? 0.16 0.11 0.50 0.15

56 hmpa d a m? 0.17 0.21 0.48 0.03

56 hmpa d mak a m? 0.10 0.05 0.37 0.03

50 ph d ? 0.03 0.01 0.07 0.63

51 ph d ? 0.02 0.04 0.18 0.68

Note: Analytic samples consist o 2,000 th-grade respondents sampled rom surveys administered between spring 2003 and spring 2005. Weighted data.

Loadings with largest absolute values bolded.


12/29


Confrmatory actor analysis results. Te CFA results

also supported the 4-actor model. Te analyses

o dierential item unctioning suggested that the

measurement intercepts or item 15 (Do you do

things to be helpul at school?) and item 51 (Do

your best riends try to do the right thing?) dieror boys and girls. For a given level o meaningul

participation, emales report between 20 and 36

percent o a standard deviation higher requen-

cies o doing things to be helpul at school or a

given level o meaningul participation. In addition,

emales are substantially less likely to report that

their best riends try to do the right thing (0.43

standard deviations). Because o the magnitude

o these measurement intercept dierences, these

items should not be used to measure the underlying

constructs. Because dropping item 51 means thatonly one item is lef to measure pro-social peers,

item 50 (Do your best riends get into trouble?)

should also be dropped. Te elementary school

module thus would not assess pro-social peer assets.

Afer dropping the pro-social peer items, a 3-actor

model is lefwith actors or school support,

home support, and meaningul participation.

Because meaningul participation is measured

with only three items, a 2-actor model was also

estimated by orcing the relevant meaningul

participation items to load on the school and home

actors. Te t o the 2-actor model is relatively

close to that o the 3-actor model, although thelatter resulted in a statistically signicant im-

provement in model t (see 2 values or Model

4 versus Model 3 in appendix C). Moreover, an

inspection o the standardized loadings in the

2-actor model or items 9, 56, and 57 indicates

that these meaningul participation items are only

weakly related to underlying school and home

actors (0.26, 0.37, and 0.24, respectively). Tus the

3-actor model has the most support.

able B7 presents the results or the nal CFAmodel. A look at the standardized actor loadings

reveals that the relationships between meaning-

ul participation and its items are still weak (0.40,

0.53, and 0.30 or items 9, 56, and 57, respectively),

suggesting that the items are insensitive indicators

o meaningul participation. Overall, however, the

results are consistent with those reported or the

secondary school resilience and youth development

tAble b6

ema hoo voma a oao ao

aa , vaao am, 4-ao oo

im

oa

im 1 2 3 4

10 sca d a . . . a a a ? 0.73 0.03 0.03 0.0113 sca ta . . . w . . . a m a? 0.65 0.02 0.03 0.01

11 sh ta . . . w a j? 0.51 0.05 0.18 0.02

14 sh ta . . . a a a j? 0.71 0.14 0.07 0.02

52 hmca pa . . . a a wk? 0.01 0.73 0.00 0.01

55 hmca pa . . . w a m a? 0.07 0.48 0.22 0.01

53 hmh pa . . . a a a j? 0.10 0.90 0.09 0.01

54 hmh pa . . . a m wa ? 0.07 0.81 0.01 0.04

9 spa d mak a / a ? 0.05 0.20 0.62 0.06

15 spa d a ? 0.10 0.05 0.50 0.18

56 hmpa d a m? 0.07 0.16 0.36 0.08

56 hmpa d mak a m? 0.16 0.16 0.38 0.0950 ph d ? 0.02 0.03 0.00 0.51

51 ph d ? 0.02 0.03 0.05 0.77



13/29

Appendix b 27

modulewith the exception that meaningul par-ticipation is global, rather than domain-specic,

or the elementary school items and that pro-social

peers cannot be measured adequately.

Secondary school internal resilience assets

Exploratory actor analysis results. Te EFA models

indicated that two o the three items used to assess

cooperation and communicationR36 (I enjoy

working together with other students my age)

and R37 (I stand up or mysel without puttingothers down)either load on more than one

actor or do not load signicantly on any actor.

For simplicity, these items were dropped rom the

analysis, and EFA and CFA models were estimated

on the remaining set o items. Te EFA results

suggested that ve actors underlie the observed

itemssel-ecacy, empathy, problem solving,

sel-awareness, and goals/aspirations (tables B8

and B9). Te 5-actor solution is conceptually clearand is consistent with how the instrument is cur-

rently used in Caliornia.

Confrmatory actor analysis results. CFA models

consistent with the 5-actor EFA model were esti-

mated, with all but the highest loadings rom the

EFA models constrained to be zero. Several consis-

tent, substantively signicant dierences in mea-

surement intercepts across racial/ethnic groups

were evident when covariates were included:

Female youth are between 0.22 and 0.34 o a

standard deviation less likely to endorse item

R27 (I know where to go or help with a prob-

lem) or a given level o problem solving.

Arican American and Mexican American

youth report higher levels o having goals

and plans or the uture (R24) than white

tAble b7

Fa ma hoo voma a mo, ma am

im

oa

c a aa m

ema

a

saa

a

School support

10 sca d a . . . a a a ? 1 0.76

13 sca ta . . . w a m a? 0.90 0.68

11 sh d a . . . w a j? 0.79 0.60

14 sh d a . . . a a a j? 0.95 0.72

Home support

52 hmca d a a . . . a a wk? 1 0.78

55 hmca d a a . . . w a m a? 0.89 0.69

53 hmh d a a . . . a a a j? 1.11 0.86

54 hmh d a a . . . a m wa ? 1.01 0.79

Meaningul participation

9 spa d mak a a ? 1 0.4056 hmpa d a m? 1.36 0.53

57 hmpa d mak a m? 0.77 0.30

la a a

(1) (2) (3)

(1) s 1.00

(2) hm 0.64 1.00

(3) Ma aa 0.48 0.62 1.00



14/29


European American and Chinese American

youth, even afer accounting or ethnic groupdierences in the latent construct.

Chinese American youth report substantially

lower levels o having goals and plans or the

uture than the other ethnic groups or a given

score on the underlying construct. In addition,

Chinese American youth also are about 2530

percent o a standard deviation less likely to

report that they plan to go to college afer high

school (R26) or a given level on goals.

With such pronounced racial/ethnic group mea-

surement intercept dierences, items R24 and R26

should be dropped, and so goals would not be as-

sessed on the secondary school module. Item R27

should not be used to assess problem solving.

able B10 shows the nal recommended CFA

model or the secondary school internal resilience

items afer dropping items R24, R25, R26, and R27

rom the analysis. Overall, the latent constructsare consistent with current usage o the RYDM,

except that the communication and cooperation

construct is dropped because two o the items or

this scale did not uniquely load on one actor, the

goals construct is dropped because o measure-

ment slope invariance, and the problem-solving

construct is measured with just two items.

Elementary school internal resilience assets

Exploratory actor analysis results. Te elementaryschool resilience and youth development module

was designed to measure three internal resilience

traitsempathy, problem solving, and goals and

aspirationswith seven items. Although explor-

atory actor analyses o these items suggest that

a 2-actor solution was appropriate or both the

main and validation samples, the actor patterns

were dierent or the two samples as well as or

tAble b8

soa hoo a a oao ao aa , ma am, 4-ao mo

im

oa

im

a

1 2 3 4

r31 c i a wk w m w a a m. 0.39 0.16 0.08 0.23

r36 c i j wk w m a.im a -a

r37 c i a m w w.

r29 se i a wk m m. 0.66 0.09 0.15 0.11

r30 se i a m i . 0.50 0.11 0.16 0.35

r32 se t a ma a i w. 0.32 0.02 0.21 0.37

r33 ema i a w m . 0.06 0.71 0.02 0.15

r34 ema i a wa . 0.02 0.88 0.02 0.09

r38 ema i a wa a k. 0.11 0.70 0.12 0.03

r35 ps W i i m ak w. 0.64 0.33 0.07 0.18

r27 ps i kw w w a m. 0.68 0.01 0.07 0.11

r28 ps i wk m ak w a m. 0.80 0.24 0.14 0.12

r39 sAwa t a m . 0.12 0.06 0.46 0.28r40 sAwa i a m m a . 0.01 0.05 0.91 0.07

r41 sAwa i a w i wa i . 0.01 0.03 0.86 0.04

r24 ga i a a a a . 0.11 0.02 0.10 0.64

r25 ga i a aa m . 0.09 0.07 0.02 0.98

r26 ga i a m a . 0.01 0.09 0.11 0.88


Weighted data.


15/29

Appendix b 29

males and emales. Te items measure empathy

and goals/aspirations, but item 40 (Do you tryto work out your problems by talking or writing

about them?) either cross-loads or does not load

signicantly on the two actors, depending on the

analytic sample (see tables E124aE132). Te EFA

actor patterns were still ambiguous afer drop-

ping item 40, most likely because so ew items re-

mained to be analyzed (tables B11 and B12). Afer

moving to a CFA ramework, two nested models

were estimateda 1-actor model measuring over-

all internal assets and a 2-actor model measuring

empathy and goals/aspirations.

Confrmatory actor analysis results. Te 2-actor

CFA modelwhich includes distinct actors or

empathy and goals/aspirationsexhibited a sig-

nicantly better t to the observed data than the

1-actor model. able B13 presents the actor load-

ings and actor correlations or this CFA model

based on the main sample. An examination o the

standardized item loadings or goals/aspirations

indicates that two o the our items are weakly as-sociated with the underlying construct. Although

goals/aspirations is poorly measured by the in-

cluded items, this scale should be retained so that

its reliability and relationship to other constructs

can be urther investigated.

Reliability o the secondary and elementary school scales

Internal consistency.Te internal consistency o

the RYDM scales was estimated using Cronbachs

alpha coecient or the main sample, the valida-tion sample, and each demographic subsample

(tables B14 and B15). Te secondary school RYDM

scales (table B14) demonstrate acceptable levels o

reliability, with all scales exhibiting reliabilities

greater than 0.70, and 11 o 13 scales demonstrat-

ing reliabilities greater than 0.75. Te school

support, community support, and peer caring

relationships scales exhibit the highest internal

tAble b9

soa hoo a a oao ao aa , vaao am, 4-ao mo

im

oa

im

a

1 2 3 4

r31 c i a wk w m w a a m. 0.45 0.11 0.06 0.22

r36 c i j wk w m a.im a -a

r37 c i a m w w.

r29 se i a wk m m. 0.65 0.06 0.13 0.12

r30 se i a m i . 0.55 0.10 0.10 0.36

r32 se t a ma a i w. 0.46 0.10 0.16 0.36

r33 ema i a w m . 0.12 0.68 0.03 0.14

r34 ema i a wa . 0.02 0.84 0.03 0.11

r38 ema i a wa a k. 0.09 0.70 0.12 0.09

r35 ps W i i m ak w. 0.63 0.31 0.10 0.21

r27 ps i kw w w a m. 0.66 0.02 0.09 0.07

r28 ps i wk m ak w a m. 0.81 0.26 0.15 0.14

r39 sAwa t a m . 0.17 0.05 0.45 0.27r40 sAwa i a m m a . 0.02 0.07 0.94 0.07

r41 sAwa i a w i wa i . 0.09 0.01 0.79 0.01

r24 ga i a a a a . 0.11 0.04 0.10 0.63

r25 ga i a aa m . 0.09 0.11 0.03 0.97

r26 ga i a m a . 0.01 0.11 0.08 0.85


Weighted data.


16/29


consistency, with alphas all exceeding 0.90. Te

problem-solving (alpha = 0.73) and pro-social

peers (alpha = 0.74) scales exhibit moderate but

acceptable levels o internal consistency, especially

considering that the scales have only two items.

Internal consistency does not dier markedly by

student grade, gender, or race/ethnicity. However,

the problem-solving scale shows lower reliability

tAble b10

Fa oa hoo a a mo, ma am

im

oa

c a aa m

ema

a

saa

a

Sel-efcacy

r31 c i a wk w m w a . . . 1.00 0.77r29 se i a wk m m. 1.04 0.80

r30 se i a m i . 1.09 0.84

r32 se t a ma a i w. 1.04 0.80

Empathy

r33 ema i a w m . 1.00 0.82

r34 ema i a wa . 1.11 0.91

r38 ema i a wa a k. 1.09 0.90

Problem solving

r35 ps W i i m ak w. 1.00 0.85

r28 ps i wk m ak/w a m. 0.94 0.80

Sel-awarenessr39 sAwa t a m . 1.00 0.84

r40 sAwa i a m m a . 1.02 0.86

r41 sAwa i a w i wa i . 0.99 0.83

la a a

(1) (2) (3) (4)

(1) s-fa 1.00

(2) ema 0.73 1.00

(3) pm 0.78 0.82 1.00

(4) s-awa 0.82 0.69 0.62 1.00


Weighted data.

tAble b11

ema hoo a a oao ao aa , ma am, 2-ao mo

im

oa

im

a

1 2

37 ema d a w ? 0.70 0.04

38 ema d a w m ? 0.73 0.03

39 ps d kw w w a m? 0.06 0.63

40 ps d wk m ak/w . . . ? 0.31 0.36

41 ga/A d ? 0.17 0.52

42 ga/A d a a a a ? 0.03 0.38

16 ga/A d a . . . a ? 0.07 0.34



17/29

Appendix b 31

or Arican American students than or other

ethnic groups.

Internal consistency reliabilities or the elemen-

tary school RYDM scales are noticeably lowerthan those or the secondary school instrument

(see table B15). Tese low reliabilities are typical

o instruments administered to elementary school

students. Te school support, home support, and

empathy subscales demonstrate adequate reliabil-

itywith alphas ranging rom 0.63 to 0.65 or em-

pathy to 0.70 to 0.72 or school and home support.

Te elementary school meaningul participation

and goals/aspirations scales exhibit low levels

o reliability. Tese scales should not be used in

research or local evaluation activities requiring

precise measurement.

Stability.ables B16 and B17 show construct- and

item-level test-retest stability coecients or the

secondary school RYDM asset measures. Unlike the

internal consistency estimates, the resilience scales

evidence airly low levels o stability, with 8 o the 12

scales exhibiting pre-post correlations o less than

0.60. Only the community meaningul participa-

tion, home support, peer caring relationships, and

tAble b13

Fa ma hoo a a mo, ma am

im

oa

c a aa m

ema

a

saa

a

Empathy

37 ema d a w ? 1 0.71

38 ema d a w m ? 1.07 0.76

Goals/aspirations

39 ps d kw w w a m? 1 0.50

41 ga/A d ? 1.56 0.78

42 ga/A d a a a a ? 0.69 0.35

16 ga/A d a . . . a ? 0.50 0.25

la a a(1) (2)

(1) ema 1.00

(2) ga/aa 0.64 1.00


tAble b12

ema hoo a a oao ao aa , vaao am, 2-ao mo

im

oa

im

a

1 2

37 ema d a w ? 0.80 0.13

38 ema d a w m ? 0.80 0.06

39 ps d kw w w a m? 0.20 0.42

40 ps d wk m ak/w . . . ? 0.38 0.22

41 ga/A d ? 0.34 0.36

42 ga/A d a a a a ? 0.17 0.76

16 ga/A d a . . . a ? 0.08 0.56



18/29


sel-awareness scales demonstrate adequate stabil-ity. In the context o relatively high levels o internal

consistency, these comparatively low levels o stabil-

ity suggest that the resilience assets assessed by the

secondary school module demonstrate adequate

reliability at a single point in time.

A look at the item-specic stability coecients

in tables B16 and B17 shows the variation across

items. Although several are particularly unstable,the individual item test-retest reliabilities have

a negligible impact on the total scale test-retest

reliabilities. For example, the pre-post correlation

o item R8 (Tere is a teacher or some other adult

who notices when I am not there) is only 0.29.

However, dropping this item rom the school sup-

port scale does not markedly improve the stability

o the scale score (0.54 versus. 0.55).

tAble b14

soa hoo a o ab of b moah bo

ga g ra/

A 7 9 11 Ma ma

Aa

Ama

c

Ama

Ma

Ama W

Environmental resilience assets

s 0.90 0.89 0.91 0.92 0.90 0.91 0.89 0.90 0.90 0.91

s ma aa 0.78 0.76 0.77 0.80 0.77 0.78 0.74 0.79 0.78 0.79

cmm 0.95 0.94 0.95 0.95 0.95 0.95 0.95 0.95 0.95 0.95

cmm ma aa 0.75 0.73 0.76 0.77 0.76 0.75 0.76 0.72 0.77 0.73

hm 0.89 0.89 0.89 0.88 0.89 0.88 0.90 0.86 0.90 0.88

hm ma aa 0.78 0.76 0.78 0.79 0.78 0.78 0.75 0.79 0.77 0.79

p a a 0.90 0.88 0.90 0.92 0.89 0.90 0.89 0.90 0.91 0.89

p-a 0.74 0.73 0.75 0.74 0.72 0.74 0.72 0.71 0.75 0.73

Internal resilience assets

s-fa 0.82 0.81 0.82 0.82 0.83 0.80 0.82 0.82 0.82 0.81ema 0.85 0.86 0.85 0.85 0.85 0.83 0.84 0.85 0.85 0.86

pm 0.73 0.73 0.73 0.72 0.73 0.69 0.68 0.74 0.73 0.76

s-awa 0.81 0.80 0.81 0.82 0.82 0.80 0.81 0.82 0.80 0.81


Results are based on main sample. Cronbachs alpha coecients were almost identical in the validation sample.

tAble b15

ema hoo a o ab of b

Ma am vaa am

A Ma ma A Ma maEnvironmental resilience assets

s 0.71 0.70 0.72 0.70 0.71 0.69

hm 0.71 0.70 0.71 0.72 0.71 0.73

Ma aa 0.34 0.32 0.35 0.32 0.30 0.34


ema 0.63 0.64 0.57 0.65 0.63 0.64

ga/aa 0.36 0.41 0.27 0.39 0.43 0.33



19/29

Appendix b 33

tAble b16

t- ab o oa hoo voma a o a m

im

oa

c a aa m

sa

f ()

School support 0.54

r6 sca sa w a a a m. 0.50

r8 sca sa w w im . 0.29

r10 sca sa w m w i a m . . . 0.51

r7 sh sa w m w i a j. 0.43

r9 sh sa w awa wa m m . 0.47

r11 sh sa w a i w a . 0.46

School meaningul participation 0.53

r12 spa si a. 0.33

r13 spa si k a a . 0.56

r14 spa si a mak a . 0.37

Community support 0.44r15 cmca cmma w a a a m. 0.33

r17 cmca cmma w w i am a . . . 0.41

r20 cmca cmma wm i . 0.53

r16 cmh cmma w m w i a j. 0.44

r18 cmh cmma w a i w a . 0.39

r19 cmh cmma w awa wa m m . 0.46

Community meaningul participation 0.82

r21 cmpa i am a , am, /m, . . . 0.83

r22 cmpa i am ak m, a, a . . . 0.64

Home support 0.68

r49 hmca hma w m wk. 0.57

r51 hmca hma w ak w m a m m. 0.62

r53 hmca hma w m w i a m . . . 0.60

r48 hmh hma w m w . 0.53

r50 hmh hma w a i w a . 0.52

r52 hmh hma w awa wa m m . 0.63

Home meaningul participation 0.49

r55 hmpa i a m a mak a . 0.52

r56 hmpa i mak w m am. 0.43

Peer caring relationships 0.73

r42 pca A w a a a m. 0.52

r43 pca A w ak w m a m m. 0.62

r44 pca A w m w im a a a m. 0.76

Pro-social peers 0.51

r46 ph M wa . 0.51

r47 ph M w . 0.46

Note: Results are based on a sample o 90 ninth-grade respondents rom seven classrooms in two schools in a large urban school district. Two weeks sepa-

rated the rst and second administrations o the survey instruments.


20/29


Te elementary school RYDM scales exhibit

higher stability than the secondary school scales

(table B18). Only two o the ve elementary school

scales exhibit pre-post correlations below 0.60.

Te stability coecients in table B18 are similaror higher than the internal consistency reliability

estimates presented in table B15 or elementary

school students.

Validity o the secondary and elementary school scales

Scale means.o assess construct validity, demo-

graphic dierences in resilience scale scores were

examined across grade, gender, and racial/ethnic

groups. Secondary school RYDM scale means,

standard deviations, and standardized dierencesacross groups are presented in table B19. With the

exception o caring relationships with peers, 9th and

11th graders report marginally lower environmen-

tal resilience assets than seventh graders. Caring

relationships with peers increases with school grade,

consistent with the notion that adolescents become

more involved with peers (although not necessar-

ily pro-social ones) as they age. Student internal

resilience asset scores do not dier markedly by

grade, although empathy increases with school

grade, and sel-awareness declines with grade.

Gender dierences in resilience assets gener-ally avor emales, who report marginally higher

school and community support and substantially

higher peer caring relationships and exposure to

pro-social peers. Females also report considerably

higher levels o empathy and problem solving.

Tese dierences are consistent with expecta-

tionsgirls ofen have more extensive social

support resources than boys (Colarossi & Eccles,

2000; Crosnoe, Johnson, & Elder, 2004; Frey &

Rthlisberger, 1996) and evidence higher empathy

(Eisenberg & Lennon, 1983).

White students generally report the highest envi-

ronmental assets in each area except or pro-social

peers. Chinese American students report the highest

aliation with pro-social peers. Mexican American

students report the lowest environmental resilience

assets in the school and peer domains and the low-

est meaningul participation in the community.

tAble b17

t- ab o oa hoo a a o a m

im c a aa m

sa

f ()

Sel-efcacy 0.58

r31 i a wk w m w a . . . 0.36r29 i a wk m m. 0.58

r30 i a m i . 0.37

r32 t a ma a i w. 0.50

Empathy 0.57

r33 i a w m . 0.44

r34 i a wa . 0.45

r38 i a wa a k. 0.45

Problem solving 0.52

r35 W i i m ak w. 0.48

r28 i wk m ak/w a m. 0.66

Sel-awareness 0.71r39 t a m . 0.59

r40 i a m m a . 0.48

r41 i a w i wa i . 0.66

Note: Results are based on a sample o 90 ninth-grade respondents rom seven classrooms in two schools in a large urban school district. Two weeks sepa-



21/29

Appendix b 35

Chinese American students exhibit the lowest envi-

ronmental resilience assets in the home domain and

the lowest reported community support.

White students also report the highest level o

internal assets in sel-ecacy, empathy, andproblem solving. Mexican American and Chinese

American students report the lowest sel-ecacy,

Arican American students exhibit the lowest

empathy scores.

able B20 presents elementary school RYDM scale

means or males and emales. Overall, the gender

dierences or elementary school students are

consistent with those or secondary school students.

Compared with boys, girls report marginally higher

school support, meaningul participation, and

goals/aspirations and substantially higher empathy.

Relationships with other constructs.o urtherassess construct validity, the relationship o each

resilience asset construct to other theoretically

related constructs assessed on the Healthy Kids

Survey was examinedincluding substance

use, violence, harassment, depression, and sel-

reported school grades and truancy. Te relation-

ships o resilience assets to Caliornia Standard-

ized English Language Arts and Mathematics

tAble b18

t- ab o ma hoo a o a m

im c a aa m

sa

f ()


School support

10 d a . . . a a a ? 0.53

13 d a . . . w a m a? 0.52

11 d a . . . w a j? 0.38

14 d a . . . a a a j? 0.39

Home support 0.70

52 d a a . . . a a wk? 0.56

55 d a a . . . w a m a? 0.65

53 d a a . . . a a a j? 0.53

54 d a a . . . a m wa ? 0.29

Meaningul participation 0.57 9 d mak a a ? 0.39

56 d a m? 0.34

57 d mak a m? 0.44


Empathy 0.70

37 d a w ? 0.55

38 d a w m ? 0.56

Goals/aspirations 0.41

39 d kw w w a m? 0.30

41 d ? 0.49

42 d a a a a ? 0.04

16 d a . . . a ? 0.03

Note: Results are based on a sample o 136 th-grade respondents rom eight classrooms in three schools in a large urban school district. Two weeks sepa-



22/29


test scores were examined using data previouslycollected by WestEd.

able B21 shows the relationships between envi-

ronmental resilience assets and theoretically re-

lated constructs or secondary school students. All

but one o the assessed dimensions o environmen-

tal assets are correlated with student substance use.

Students who report high environmental resilience

assets are less likely to report that they engage insubstance use. Te exception is peer caring rela-

tionships, which is weakly correlated with most o

the substance use indicators except substance use

on school property.

Environmental resilience assets are also nega-

tively associated with student depression and

truancy, and positively associated with students

tAble b19

soa hoo ba ma b moah bo

Grade Standardized

diferencea Male Female

Standardized

diferenceaArican

American

Chinese

American

Mexican

American White

Standardized

diferencea7 9 11


s 2.91

(0.80)

2.74

(0.82)

2.83

(0.81)

0.17 2.77

(0.83)

2.89

(0.80)

0.14 2.84

(0.85)

2.79

(0.76)

2.74

(0.82)

2.96

(0.80)

0.20

s

ma

aa

2.32

(0.86)

2.20

(0.84)

2.21

(0.87)

0.12 2.24

(0.85)

2.26

(0.85)

0.02 2.28

(0.88)

2.22

(0.81)

2.13

(0.84)

2.36

(0.86)

0.20

cmm

3.24

(0.92)

3.15

(0.94)

3.17

(0.95)

0.08 3.11

(0.96)

3.26

(0.90)

0.16 3.19

(0.97)

3.00

(0.96)

3.12

(0.95)

3.44

(0.81)

0.34

cmm

ma

aa

2.93

(1.10)

2.81

(1.12)

2.81

(1.12)

0.11 2.86

(1.11)

2.82

(1.12)

0.05 2.84

(1.13)

2.89

(1.05)

2.51

(1.16)

3.16

(1.01)

0.42

hm 3.45

(0.71)

3.36

(0.74)

3.33

(0.74)

0.14 3.35

(0.76)

3.40

(0.71)

0.07 3.35

(0.80)

3.27

(0.70)

3.34

(0.75)

3.55

(0.64)

0.28

hmma

aa

2.88(0.94)

2.72(0.94)

2.71(0.94)

0.17 2.73(0.96)

2.81(0.93)

0.09 2.76(0.98)

2.65(0.93)

2.72(0.95)

2.94(0.91)

0.23

p a

a

3.10

(0.93)

3.17

(0.91)

3.26

(0.89)

0.15 2.92

(0.96)

3.44

(0.78)

0.58 3.13

(0.95)

3.15

(0.87)

3.07

(0.96)

3.37

(0.84)

0.25

p-a 3.05

(0.85)

2.95

(0.82)

2.96

(0.78)

0.11 2.84

(0.83)

3.13

(0.77)

0.35 2.89

(0.85)

3.18

(0.73)

2.83

(0.84)

3.04

(0.79)

0.33


s-fa 3.24

(0.72)

3.18

(0.72)

3.22

(0.72)

0.08 3.19

(0.74)

3.23

(0.67)

0.06 3.22

(0.76)

3.15

(0.68)

3.12

(0.73)

3.36

(0.64)

0.25

ema 3.10

(0.87)

3.17

(0.82)

3.23

(0.78)

0.13 2.97

(0.88)

3.36

(0.71)

0.46 3.03

(0.90)

3.22

(0.74)

3.10

(0.85)

3.31

(0.77)

0.26

pm 2.87

(0.99)

2.85

(0.96)

2.87

(0.95)

0.02 2.64

(1.00)

3.08

(0.88)

0.45 2.82

(1.00)

2.82

(0.93)

2.81

(0.99)

2.99

(0.94)

0.15

s-awa 3.31

(0.78)

3.21

(0.80)

3.21

(0.79)

0.12 3.22

(0.82)

3.27

(0.76)

0.06 3.27

(0.83)

3.16

(0.78)

3.23

(0.79)

3.32

(0.76)

0.14

a. Standardized diference represents the diference between groups divided by the pooled standard deviation (Cohens d). With more than two groups,

the standardized diference is represented by multiplying Cohens by 2which is generally equivalent to the standardized diference calculated or two

groups (see appendix A).

ns = not statistically signicant rom 0 (p < .05)

Note: Standard deviations in parentheses. Analytic samples consist o 12,000 7th-, 9th-, and 11th-grade respondents sampled rom surveys administered

between spring 2003 and spring 2005.


23/29

Appendix b 37

sel-reported school connectedness and grades.

Te environmental resilience asset scales are less

consistently related to indicators o violence, ha-

rassment, and perceptions o school saety.

Te criterion variablesCaliornia Standards est

(CS) English Language Arts and Mathematics test

scoresare associated with school and communityassets, as well as home support. Te associations

are weak, however, with school support showing

the strongest relationship to test scores. est scores

are not signicantly associated with meaningul

participation in the home environment, peer car-

ing relationships, and pro-social peers.

able B21 suggests that the secondary school RYDM

instrument provides a valid assessment o environ-

mental resilience assets because these constructs

are associated with student substance use, depres-sion, sel-reported grades, truancy, and test scores

in expected ways. Although the correlations with

school connectedness and sel-reported grades are

moderate and have medium eect sizes, the correla-

tions or most o the criterion variables are small.

able B22 shows correlations between internal

resilience assets and the criterion variables or

secondary school students. Te results are similar

to those or environmental assets. With the excep-

tion o standardized test scores, each dimension

o internal resiliencesel-ecacy, empathy,

problem solving, and sel-awarenessis correlated

with most o the considered criterion variables,

which supports construct validity.

able B23 presents correlations between the el-

ementary school resilience assets and the criterion

variables o substance use, aggression, perceived

saety, and sel-reported academic perormance.

Both the environmental resilience and internal

resilience scales are positively associated with most

o the criterion variables, which supports construct

validity. Although the criterion variables are dier-

ent in the two samples, the correlations are stron-

ger or the elementary school resilience instrument

than or the secondary school instrument.

Comparison o current and recommended

measures o resilience assets

ables B24B27 compare the current use o items

to measure resilience assets among secondary

and elementary students with this studys recom-

mended use.

tAble b20

ema hoo ba ma b

A Ma ma

saaz

a


s 3.32(0.61)

3.28(0.62)

3.37(0.59)

0.15

hm 3.72

(0.44)

3.70

(0.46)

3.74

(0.42)

0.07

Ma aa 2.50

(0.60)

2.46

(0.60)

2.54

(0.60)

0.12


ema 3.01

(0.79)

2.84

(0.84)

3.18

(0.71)

0.42

ga/aa 2.24

(0.35)

2.21

(0.39)

2.26

(0.31)

0.15

a. Standardized diference represents the diference between groups divided by the pooled standard deviation (Cohens d).


Note: Standard deviations in parentheses. Analytic samples consist o 2,000 th-grade respondents sampled rom surveys administered between spring

2003 and spring 2005. Weighted data.


24/29


tAble b21

coao bw oa hoo voma a a o vaab

s

s

ma

aa

cmm

cmm

ma

aa

hm

hm

ma

aa

p a

a

p-a

Substance uselm a 0.17 0.20 0.14 0.25 0.21 0.20 0.02 0.30

30-a a 0.17 0.18 0.15 0.27 0.24 0.23 0.02 0.33

ta a 0.18 0.23 0.25 0.26 0.33 0.29 0.16 0.37

lm a 0.16 0.15 0.07 0.16 0.20 0.20 0.03 0.28

30-a a 0.16 0.14 0.06 0.17 0.20 0.20 0.03 0.28

30-a k 0.13 0.14 0.05 0.16 0.19 0.18 0.03 0.29

A a 0.16 0.10 0.14 0.18 0.23 0.21 0.11 0.27

lm majaa 0.16 0.16 0.08 0.19 0.18 0.19 0.00 0.29

30-a majaa 0.20 0.19 0.10 0.22 0.20 0.20 0.04 0.32

Majaa a 0.19 0.18 0.13 0.22 0.20 0.24 0.14 0.33

Violence

b , , . 0.10 0.06 0.08 0.04 0.09 0.08 0.14 0.15

Aa a 0.08 0.08 0.06 0.08 0.10 0.08 0.07 0.08

pa 0.14 0.07 0.10 0.09 0.14 0.12 0.16 0.26

Ma m a 0.04 0.00 0.02 0.00 0.10 0.09 0.06 0.11

sa jk, mm 0.04 0.03 0.01 0.00 0.10 0.11 0.09 0.14

ha 0.06 0.02 0.06 0.02 0.09 0.07 0.07 0.11

o 0.12 0.10 0.05 0.10 0.16 0.17 0.00 0.33

dama 0.18 0.08 0.14 0.09 0.22 0.17 0.12 0.29

a a 0.12 0.00 0.09 0.01 0.15 0.12 0.09 0.21

Psychological well-being

d 0.16 0.16 0.10 0.15 0.21 0.23 0.05 0.17

School-related actors

s 0.49 0.38 0.30 0.26 0.32 0.29 0.28 0.30

s a (-) 0.24 0.26 0.13 0.29 0.20 0.19 0.13 0.29

ta 0.15 0.15 0.08 0.15 0.23 0.22 0.01 0.27

Standardized test scoresa

cst e laa A 0.15 0.04 0.12 0.12 0.12 0.00 0.02 0.02

cst Mama 0.11 0.04 0.09 0.10 0.09 0.03 0.02 0.01

a. Analytic sample or standardized test score results based on local evaluation data obtained rom a large county in Southern Caliornia. Standardized test

score and school/community asset data were available or 2,898 students, while test score and home and internal asset data were available or 651 students.CST = Caliornia Standards Test


Note: Analytic sample or substance use, violence, psychological well-being, and school-related actors based on 12,000 7th-, 9th-, and 11th-grade respon-

dents sampled rom HKS surveys administered between spring 2003 and spring 2005.


25/29

Appendix b 39

tAble b22

coao bw oa hoo a a a o vaab

s-fa ema pm s-awa

Substance use

lm a 0.22 0.14 0.17 0.24

30-a a 0.19 0.11 0.14 0.22

ta a 0.20 0.13 0.17 0.21

lm a 0.20 0.14 0.16 0.22

30-a a 0.20 0.13 0.12 0.20

30-a k 0.17 0.17 0.14 0.18

A a 0.22 0.20 0.22 0.25

lm majaa 0.29 0.23 0.14 0.19

30-a majaa 0.20 0.16 0.08 0.14

Majaa a 0.25 0.23 0.20 0.21

Violence

b , , . 0.13 0.14 0.12 0.11

Aa a 0.12 0.01 0.02 0.10

pa 0.16 0.25 0.22 0.13

Ma m a 0.11 0.03 0.02 0.12

sa jk, mm 0.09 0.04 0.01 0.15

ha 0.11 0.05 0.08 0.15

o 0.19 0.14 0.16 0.22

dama 0.23 0.26 0.26 0.23

a a 0.25 0.17 0.21 0.24

Psychological well-being

d 0.26 0.02 0.11 0.30

School-related actors

s 0.33 0.29 0.28 0.32

s a (-) 0.29 0.22 0.21 0.20

ta 0.20 0.15 0.17 0.19

Standardized test scoresa

cst e laa A 0.05 0.09 0.03 0.02

cst Mama 0.05 0.05 0.05 0.02

a. Analytic sample or standardized test score results based on local evaluation data obtained rom a large county in Southern Caliornia. Standardized test

score and school/community asset data were available or 2,898 students, while test score and home and internal asset data were available or 651 students.

CST = Caliornia Standards Test


Note: Analytic sample or substance use, violence, psychological well-being, and school-related actors based on 12,000 7th-, 9th-, and 11th-grade respon-

dents sampled rom HKS surveys administered between spring 2003 and spring 2005.


26/29


tAble b23

coao bw ma hoo a a o vaab

ema a ia a

s

hm

Ma

aa ema

ga a

aa

Substance use

lm a 0.25 0.31 0.20 0.20 0.28

lm a 0.26 0.21 0.23 0.18 0.28

lm majaa 0.12 0.15 0.13 0.01 0.14

Aggression victimization

b , , . 0.17 0.12 0.07 0.07 0.14

Ma m a 0.10 0.13 0.12 0.05 0.14

b a a 0.10 0.13 0.12 0.02 0.06

Aggression perpetration

p, , 0.28 0.23 0.22 0.33 0.34

sa ma m 0.22 0.21 0.12 0.22 0.31Perceived saety

a a 0.48 0.30 0.14 0.19 0.41

a a a 0.20 0.20 0.11 0.01 0.25

Academic perormance

s ma 0.17 0.20 0.14 0.09 0.25




27/29


28/29


tAbleb25

currentandreommendedmeasuresofinternalresilienea

ssetsamongseondaryshoolstu

dents

cunuoonayoom

rom

mnuoonayoom

conu

im

conu

im

cooaonan

ommunaon

I

standupormyselwithoutputtingothersdown.

cooaonan

ommunaona

Itemdroppedcross-loadings

I

enjoyworkingtogetherwithotherstud

entsmyage.

Itemdroppedcross-loadings

i

anwokwomonwoa

nononanmn.

s-fay

ianwokwomonwoa

nononanmn.

s-fay

i

anwokoumyom.

ianwokoumyom.

i

anomoniy.

ianomoniy.

t

amanynaiow.

tamanynaiow.

emay

i

awnomonn

u.

emay

iawnomonnu.

i

younanwaooo

ou.

iyounanwaoooou.

i

younanwaoo

annk.

iyounanwaooannk.

pomovn

I

knowwheretogoorhelpwithaproblem.

pomovn

Itemdropped

unctionsdiferently

oremalesandmales

W

nininomonoakw

.

Wnininomonoakw.

i

yowokouomyakn

o

wnaoum.

iyowokouomyakn

ownaoum.

s-awan

t

auoomy.

s-awan

tauoomy.

i

unanmymooann.

iunanmymooann.

i

unanwyiowaio.

iunanwyiowaio.

goaanaaon

I

havegoalsandplansortheuture.

goaanaaona

Itemdropped

unctionsdiferentlyor

AricanAmericans/MexicanAmericans

I

plantograduateromhighschool.

Itemdroppedonlyoneitem

lettomeasureconstruct

I

plantogotocollegeorsomeother

s

choolaterhighschool.

Itemdropped

unctionsdiferently

orChineseAmericans

a.

Constructdroppedbecauseoins

ucientnumberoitems.

Note:Greenitemsdroppedrom

therecommendedmodelbecauseodiferentialit

em

unctioning,

inconsistentloadingpatterns,or

cross-loadingsorbecauseonlyasingleitem

remainstomeasure

construct.


29/29

description: tags: rel 2007034 appab

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