Effectiveness of the KEEP foster parent intervention during an.docx

Effectiveness of the KEEP foster parent intervention during an
implementation trial
Joseph M. Price a,c,⁎, Scott C. Roesch a,c, Natalia Escobar
Walsh b,c
a Department of Psychology, San Diego State University, 5500
Campanile Drive, San Diego, CA 92182, United States
b SDSU/UCSD Joint Doctoral Program in Clinical Psychology,
6363 Alvarado, Ct., Suite 103, San Diego, CA, 92120, United
States
c Child and Adolescent Services Research Center, 3665 Kearny
Villa Rd., Suite 200, San Diego, CA 92123, United States
a b s t r a c ta r t i c l e i n f o
Article history:
Received 24 August 2012
Accepted 26 September 2012
Available online 2 October 2012
Keywords:
Intervention
Foster parents
Behavior problems
Externalizing behavior problems are highly prevalent among
children in foster care, placing them at risk for
placement disruptions and later personal and social
maladjustment. The KEEP foster parent intervention was
designed to equip foster parents and relative caregivers with the
parenting skills necessary for managing
challenging behavior problems. In prior research, the KEEP

intervention was found to be effective in reducing
child behavior problems. In the current study, the KEEP foster
parent intervention was implemented in San
Diego County during a three-year trial. The intervention was
delivered by paraprofessionals employed by a
local community agency (Social Advocates for Youth, San
Diego) to 181 foster parent and relative caregivers
of boys and girls between the ages of 5 and 12. The control
group from an earlier effectiveness study of the
KEEP intervention that was also conducted in San Diego
County was utilized as a historical comparison
group. Regression analyses were used to examine the effects of
the intervention on reducing levels of child
behavior problems at treatment termination. Consistent with the
findings from the previous KEEP effective-
ness study, the intervention was found to be effective in
reducing child behavior problems when delivered by
a community agency. Furthermore, the KEEP intervention was
found to be effective in reducing child behav-
ior problems among children displaying various levels of initial
behavior problems.
© 2012 Elsevier Ltd. All rights reserved.
1. Introduction
Children in foster care display emotion and behavior problems
re-
quiring mental health assessments and/or intervention at a rate
higher
than would be expected compared to normative samples or
community
studies (Landsverk & Garland, 1999; Landsverk, Garland, &
Leslie,
2002). Among the various problems evidenced by children in
foster

care, externalizing behavior problems (e.g., aggressive,
disruptive, de-
structive, and oppositional behaviors) are highly prevalent and
salient.
Data from the National Survey of Child and Adolescent
Wellbeing
(NSCAW) study revealed that a high proportion (43% based on
teacher
report, 50% based on parent report) of children in foster care
evidence
some form of externalizing behavior problems (National Survey
of
Child & Adolescent Well-being Research Group, 2003).
Findings from
other studies reveal that the levels of antisocial behavior for
children re-
ceiving child welfare services are statistically indistinguishable
from
children in intensive mental health treatment programs (Trupin,
Tarico, Low, Jemelka & McClellan, 1993). Similarly, in their
examination
of the mental health of Canadian children in foster care in
comparison to
community and clinical samples, Stein, Evans, Mazumdar, and
Rae-Grant (1996) found that both the foster and clinical samples
exhibited significantly more externalizing problems than the
children
in the community sample, with no differences between the
foster and
clinical groups. Adding to the degree of impact of these
findings is a
body of research indicating that the risk for lifetime problems
with an-
tisocial behavior is especially high for children with an early
onset of be-

havior problems (e.g., Patterson, DeBaryshe, & Ramsey, 1989).
Not
surprisingly, many youth in foster care develop serious conduct
prob-
lems, including being arrested for violent crimes (Maxfield &
Widom,
1996; Smith & Thornberry, 1995).
Within this population, externalizing behavior problems have
been
found to be linked to foster care placement instability. Not only
have ex-
ternalizing behavior problems been found to be predictive of
placement
disruptions and exits (Aarons et al., 2010; Chamberlain et al.,
2006;
Newton, Litrownik, & Landsverk, 2000), but placement
disruptions
have also been found to be predictive of increases in rates of
child be-
havior problems (Aarons et al., 2010; Newton et al., 2000).
Thus, chil-
dren who enter foster care displaying high levels of behavior
problems have an increased likelihood of experiencing a change
in
placement, which, in turn, further increases the risk for
continued and
even escalating behavior problems.
In response to the need for addressing the behavior problems of
chil-
dren in foster care and to reduce the number of changes of
placement, a
foster parent training intervention entitled KEEP (Keeping
Foster and
Kinship Parents Trained and Supported) was developed and

tested.
The primary goal of the current investigation was to determine
whether
the effectiveness of the KEEP intervention in reducing child
behavior
problems could be maintained when delivered by a community
agency
during an implementation trial conducted in San Diego County.
Children and Youth Services Review 34 (2012) 2487–2494
⁎ Corresponding author at: Department of Psychology, San
Diego State University,
5500 Campanile Drive, San Diego, CA 92182, United States.
0190-7409/$ – see front matter © 2012 Elsevier Ltd. All rights
reserved.
http://dx.doi.org/10.1016/j.childyouth.2012.09.010
Contents lists available at SciVerse ScienceDirect
Children and Youth Services Review
journal homepage: www.elsevier.com/locate/childyouth
http://www.sciencedirect.com/science/journal/01907409
1.1. Development of the KEEP intervention model
Based on the basic tenants of Parent Management Training
(Kazdin
& Wassell, 2000; Patterson, 2005), the KEEP intervention
represents a

modified version of Multidimensional Treatment Foster Care
(MTFC)
which was developed by Chamberlain and colleagues
(Chamberlain,
Leve, & DeGarmo, 2007; Chamberlain & Reid, 1991;
Chamberlain &
Reid, 1994; Eddy & Chamberlain, 2000; Leve & Chamberlain,
2004).
An earlier version of the KEEP intervention was tested in Lane
County,
Oregon (Chamberlain, Moreland, & Reid, 1992). In this study,
foster par-
ents with a new child placement were randomly assigned to one
of
three conditions: parenting training using Parent Management
Training
components, payment and assessments only, and assessments
only.
Compared to the payment only group and the control group,
parents
in the parent-training group evidenced significantly greater
decreases
in child behavior problems, had fewer failed placements due to
child be-
havior or emotional problems, and were significantly less likely
to quit
foster parenting.
The next step in this line of research involved the development
and
testing of the KEEP intervention in an effectiveness study in
San Diego
County. The intervention, which began in the fall of 2000 and
was com-
pleted in early 2006, provided parent training and support to
relative

and nonrelative caregivers of children between the ages of 5 and
12 in
regular foster care. Foster and kin caregivers in the intervention
group
completed a 16-week course of parenting training within the
context
of small facilitator-run groups. Caregivers in the control group
received
“services as usual,” which included yearly parenting classes and
support
groups for caregivers needing to meet state foster parent
licensing re-
quirements (i.e., licensed foster and kinship providers). The
results of
this study revealed that in comparison to the control group,
children
in the intervention group evidenced a significant decrease in
behavior
problems over the course of the 4-month intervention
(Chamberlain,
Price, Reid, et al., 2008). Moreover, the findings indicated that
the effects
of the intervention were maintained across developer-trained
and
non-developer-trained intervention staff (Chamberlain, Price,
Reid, et
al., 2008), suggesting that with appropriate training and
supervision,
the intervention remained effective as it moves away from the
interven-
tion developers. The intervention was also effective in
increasing paren-
tal use of targeted parenting strategies which, in turn, served to
mediate
the effects of the intervention on reductions in child behavior
problems,

especially for children displaying more than six behavior
problems per
day at baseline (Chamberlain, Price, Leve, et al., 2008). Finally,
the inter-
vention resulted in increasing the number of positive exits from
the
home (e.g., unification with biological parents, adoptions), and
mitigat-
ed the negative risk-enhancing effect of a history of multiple
place-
ments on negative exits (Price et al., 2008).
1.2. Implementation of KEEP in San Diego County
Following the completion of the original KEEP effectiveness
study
and publication of the initial findings, interest was generated
among
San Diego County Child Welfare leadership about how the
KEEP in-
tervention might be implemented into the regular in-service
train-
ing offered to foster and relative caregivers. As a result, a series
of
meetings took place between the Child and Adolescent Services
Research Center (CASRC), the Oregon Social Learning Center
(OSLC) re-
search partners, and the San Diego County Child Welfare
administrators
on how to proceed toward the implementation of the KEEP
intervention
in San Diego County. The focus of these discussions centered
on three
key issues: (a) identifying funding for the intervention; (b)
staffing fa-
cilitators for the parenting groups; and (c) maintaining

intervention fi-
delity. Child Welfare administrators were able to obtain
supplemental
funding from the State of California to conduct a pilot of the
implemen-
tation of the KEEP intervention in San Diego County. Due to
the work-
loads of caseworkers, it was determined that KEEP intervention
would
need to be delivered by a community-based mental health
service
contractor, one with a working relationship with the San Diego
Child
Welfare agency and currently delivering services in San Diego
County.
Social Advocates for Youth (SAY) San Diego, which served two
of the
six regions within the county, was contacted and expressed an
interest
in delivering the KEEP intervention. In order to maintain the
fidelity of
the intervention, OSLC-trained staff from the KEEP
effectiveness study
who were experienced in facilitating KEEP intervention groups
(25+)
and in supervising other KEEP group facilitators, provided
weekly su-
pervision of SAY San Diego group facilitators.
1.3. Cascading Dissemination Model
Moving the delivery of the KEEP intervention from research-
based organizations (OSLC and CASRC) to a community-based
provider
represents the next phase in the Cascading Dissemination Model

(Chamberlain, Price, Reid et al., 2008). In this model, the
delivery, man-
agement, and supervision of the intervention is moved away
from the
intervention developers at each iteration (in this case, OSLC)
and to-
ward the implementation of the intervention by individuals that
were
independent of its original developers. Phase 1 of the cascade is
repre-
sented by the initial development and testing of the intervention
in an
efficacy study that took place in three Oregon counties
(Chamberlain
et al., 1992). The parent training groups were conducted by an
experi-
enced foster parent who had extensive training in the OSLC
PMT
model and was supervised by the treatment developer. Phase 2
of the
cascade was implemented in San Diego County as the first part
of the
KEEP effectiveness study. In this phase, the intervention was
delivered
by paraprofessional staff hired by the Child and Adolescent
Services Re-
search Center (CASRC) research partners. These facilitators
were super-
vised by an OSLC-trained on-site supervisor and an experienced
OSLC
clinical consultant. During Phase 3, which was the second part
of the
KEEP effectiveness trial, the CASRC intervention staff trained
and super-
vised a second cohort of paraprofessional interventionists. The
OSLC

clinical consultant had no direct interaction with the group
facilitators
in this phase, but did consult with the CASRC interventionists
in their
supervision of this new group of facilitators. The current study
repre-
sents the next phase of the Cascading Dissemination Model
moving clos-
er to large scale implementation, with delivery of the
intervention
through a community agency with no particular ties to OSLC
and with
funding provided by a Child Welfare agency rather than a
research
entity.
The primary goal of this investigation was to examine the effec-
tiveness of the KEEP intervention in reducing child behavior
prob-
lems as it was being delivered by a community-based mental
health provider in San Diego County. Since the delivery of the
KEEP
intervention by SAY San Diego did not include any type of
control
group, data from the original KEEP effectiveness study was
utilized
to create a quasi-experimental design. In this design, the
baseline
and post-treatment data from the randomized effectiveness
study of
the KEEP intervention conducted in San Diego County (1999 to
2006)
was integrated and analyzed with the baseline and post-
treatment
data collected from the implementation trial of the KEEP
intervention

within San Diego Child Welfare Services (2005 to 2008). Data
from
both the intervention and control group from the KEEP
effectiveness
study were utilized to in order to integrate findings from the
effective-
ness study with the findings from the implementation trial.
Within this
design, the original control condition from the effectiveness
trial served
as the control group when comparisons were made with the
original
KEEP effectiveness study intervention group. This same control
group
also served as a historical comparison group (nonequivalent
control)
when comparisons were made with the KEEP implementation
trial
group. The use of a historical comparison group from earlier
clinical tri-
als has been used as a component of research designs to
examine the ef-
fectiveness of treatments delivered in a community setting (e.g.,
Costin
& Chambers, 2007). This type of research design illustrates how
re-
searchers might utilize data from prior clinical trials of an
intervention
2488 J.M. Price et al. / Children and Youth Services Review 34
(2012) 2487–2494
to examine the potential effectiveness of the intervention when
it is

implemented in a service setting without any type of control
group. It
is hypothesized that relative to the children in the control group
from
the KEEP effectiveness study, children in the community
agency admin-
istered KEEP SAY implementation trial group would also
demonstrate
greater reductions in child behavior problems over the course of
the
4-month period of the intervention.
An additional goal of this investigation was to determine
whether
the KEEP intervention was effective in reducing child behavior
prob-
lems at termination among children with various levels of
behavior
problems at baseline. That is, is the KEEP intervention effective
in reduc-
ing child behavior problems regardless of the initial level of
child behav-
ior problems observed at baseline? It was hypothesized that the
intervention would be effective in reducing child behavior
problems
at termination for children with behavior problems at or above
the
mean in baseline behavior problems. This hypothesis was
examined
using both the KEEP effectiveness study intervention group and
the
KEEP SAY implementation trial group.
2. Method
2.1. Participants

2.1.1. KEEP effectiveness study participants
These participants were randomly assigned to either the
interven-
tion (KEEP parent training) or to the control group in an earlier
effec-
tiveness trial of the KEEP foster parent intervention (see
Chamberlain,
Price, Reid et al., 2008). In this earlier study, eligible study
partici-
pants included all foster and relative caregivers with a child
between
the ages of 5 and 12 who was received from the San Diego
County
Health and Human Services Agency, Child Welfare services
sometime
between 1999 and 2004. Eligibility requirements were (a) the
child
was between the ages of 5 and 12, (b) the child had been in the
place-
ment for at least 30 days (in order to minimize selecting
children in
temporary shelters or emergency foster placements), and (c) the
child was not considered to be “medically fragile” (that is, not
severe-
ly physically or mentally handicapped — only one child met
this
criteria). The resulting sample was comprised of 700 foster
families
(34% kinship placements, 66% non-relative placements).
California
state law requires foster parents to participate in parent training
and support group each year in order to be licensed. The parents
in
the intervention group (n=359) were allowed to apply

participation
in the KEEP intervention group toward state licensing
requirements.
Parents in the control group (n=341) participated in routine
parent
training and support provided by San Diego County services.
Table 1
shows the baseline demographic characteristics of the
participants
from KEEP effectiveness study.
2.1.2. KEEP SAY implementation trial participants
Similar to the original KEEP effectiveness study, eligible
participants
included all foster and relative caregivers with a child between
the ages
of 5 and 12 who was received from San Diego County Child
Welfare Ser-
vices. In addition, because Social Advocates for Youth (SAY)
also ser-
viced relative substitute caregivers (e.g., grandparents, aunts,
and
uncles) who were not dependents under the care of the San
Diego
HHSA, participants were also recruited from eligible relative
caregivers
served by SAY San Diego. Similar to the KEEP effectiveness
study, eligi-
bility requirements included that (a) the child was between the
ages of
5 and 12, (b) the child had been in the placement for at least 30
days,
and (c) the child was not considered to be “medically fragile.”
Table 1
provides the demographic characteristics of the group of

participants
for whom background information was available (n=181),
although
the n's varied by demographic category. For those parents who
received
their children from San Diego County Child Welfare services,
participa-
tion in the KEEP intervention was allowed to fulfill yearly state
licensing
requirements. To examine potential differences between the
KEEP
effectiveness study participants and the KEEP SAY
implementation
trial group, ANOVA and Chi-Square analyses were employed.
The re-
sults of the ANOVA analyses on continuous background
variables re-
vealed significant differences between the two samples on the
following demographic variables: parent age, F(2,812)=6.96, p=
.001; age of the focal child, F(2,872)=12.5, p=.001; and
household in-
come level (1 to 10 rating scale, with 1=household income of
less than
$14,999 and 10=$95,000 and up), F(2,856)=4.33, p=.01 Chi
Square
analyses on dichotomous background variables revealed
significant
group differences on percentage of relative vs. non-relative
caregivers,
c2(4, N=859)=23.7, p=.001, and primary language of foster
parent,
c2(2, N=859)=47.3, p=.001. Chi Square analyses also revealed
signif-
icant group differences on percentage of ethic group
composition, c2

(10, N=854)=44.2, p.=.001. In particular, there was a higher
per-
centage of Latino caregivers in the KEEP SAY implementation
group
than in either of the KEEP effectiveness study groups.
2.2. Recruitment methods
For both sets of participants, recruitment was facilitated by the
use
of data systems from the San Diego County HHSA that were
reviewed
on a quarterly basis to identify eligible children and foster and
kinship
families. For the KEEP SAY implementation trial group, contact
informa-
tion on relative caregivers from SAY San Diego was also
utilized to iden-
tify eligible children and relative caregivers not served by the
San Diego
County Child Welfare Services. For both groups, similar
recruitment
procedures were used. First, eligible families were contacted by
phone
to determine their level of interest in the study. Next, interested
families
received a home visit, at which time a detailed project
description, con-
sent information and Institutional Review Board (IRB) approved
con-
sent form was provided. Those interested in participating
verified
their willingness to participate by signing the consent form. The
inves-
tigation was conducted in compliance with appropriate IRB (San

Diego
State University and the Oregon Social Learning Center for the
KEEP ef-
fectiveness study and from San Diego State University for the
KEEP SAY
implementation trial). Participation in both studies was
voluntary. In
addition, no solicitation or incentives were provided by San
Diego
County Child Welfare Services or Social Advocates for Youth
for families
Table 1
Demographic information on foster and kin parents by group.
Demographic information KEEP effectiveness study KEEP SAY
implementation
(n=181)
Intervention
(n=359)
Control
(n=341)
Parent gender
Female 94% 93% 98%
Male 6% 7% 2%
(n=117)
Mean parent age 49.86 (11.7) 47.29 (11.7) 51.28 (10.75)
Parent ethnicity (n=154)
African American 27% 24% 21%
Asian/Pacific Islander 4% 2% 2%
Caucasian 21% 34% 14%

Latino 41% 33% 59%
Native American 1% 1% 1%
Mixed ethnicity 6% 6% 3%
Parent preferred language (n=159)
English 67% 79% 49%
Spanish 33% 21% 51%
Mean household income 2.3 (1.3) 2.3 (1.3) 2.0 (1.4)
Relationship to child (n=159)
Kinship caregiver 32% 36% 53.8%
Non-Kinship caregiver 66% 64% 46.3%
Child gender (n=175)
Female 50% 54% 46%
Male 50% 46% 54%
Mean age of focal child 8.8 (2.2) 8.7 (2.3) 7.9 (2.3)
Mean number of children
in home
3.5 (1.8) 3.5 (2.0) 3.2 (1.8)
2489J.M. Price et al. / Children and Youth Services Review 34
(2012) 2487–2494
to participate in either of these groups. However, participants in
the
KEEP effectiveness study were provided incentives by the
research pro-
ject for completing baseline and termination assessments.
However,
participants in the KEEP SAY implementation trial were not

provided
incentives for completing any assessments.
2.3. Intervention model
Similar to parents in the KEEP effectiveness study, parents in
the
KEEP SAY implementation trial participated in parenting
groups of 3
to 10 individuals led by a trained facilitator. Parents received
16 weeks of parent training, supervision, and support in
behavior man-
agement methods. The primary focus of the KEEP intervention
was on
increasing use of positive reinforcement, consistent use of non-
harsh
discipline methods, such as brief time-outs or privilege removal
over
short time spans (e.g., no playing video games for one hour, no
bicycle
riding until after dinner), and teaching parents the importance
of
close monitoring of the youngster's whereabouts and peer
associations.
In addition, strategies for avoiding power struggles, managing
peer re-
lationships, and improving success at school were also included.
Ses-
sions were structured so that the curriculum content was
integrated
into group discussions and primary concepts were illustrated via
role-plays and videotaped recordings. Home practice
assignments
were given that related to the topics covered during sessions in
order
to assist parents in implementing the behavioral procedures

taught in
the group meeting. If foster parents missed a parent-training
session,
the material was delivered during a home visit. Such home
visits have
been found to be an effective means of increasing the dosage of
the in-
tervention for families who miss interventions sessions (Reid &
Eddy,
1997).
Parenting groups were formed based on parent schedule,
language
preference (English or Spanish), and location. Parenting groups
were
conducted in community recreation centers, churches, or SAY
facilities.
Several strategies were used to maintain parent involvement,
including
(a) provision of childcare, using qualified and licensed
individuals so
that parents could bring younger children and know that they
were
being given adequate care, (b) credit was given for the yearly
licensing
requirement for foster care (HHSA foster parents, only), (c)
parents
were reimbursed $15.00 per session for traveling expenses, and
(d) re-
freshments were provided. Group session attendance/completion
rates
(including make-up sessions for absences) were high, with 92%
of par-
ents completing at least 14 sessions. The language of the
materials (En-
glish or Spanish) was determined by the language used in

parenting
groups.
As was the case with the KEEP effectiveness study, during the
KEEP SAY implementation trial, the intervention was delivered
by
paraprofessionals. At least one of the group facilitators was
bilingual
in English and Spanish. Experience with group settings,
interpersonal
skills, and experience with diverse populations were given high
priority
in selecting interventionists. Interventionists were then trained
over
several weeks through a series of phases involving (a) viewing
video re-
cords of prior sessions run by experienced facilitators from the
original
KEEP effectiveness study, (b) role playing in mock group
sessions, with
the trainee as a group facilitator, (c) and co-facilitating group
sessions
with an experienced facilitator. The KEEP SAY personnel-led
interven-
tion groups were supervised on a weekly basis by an
experienced
KEEP facilitator from the KEEP effectiveness study.
Supervisors
reviewed video records of group sessions and met with group
facilita-
tors on a weekly basis to provide feedback. Consultation was
also pro-
vided by the Oregon Social Learning Center.
2.4. Measures

2.4.1. Child and parent characteristics
Foster and kin parent-report of child and family characteristics
and
demographics was assessed at study entry (baseline) via phone
interviews. Caregivers had known the target child for at least 30
days
prior to the baseline assessment. Interviews were conducted in
either
English or Spanish, depending on the preference of the parents.
2.4.2. Child behavior problems
The Parent Daily Report Checklist (PDR: Chamberlain & Reid,
1987)
was used to assess child behavior problems at baseline and four
months
later at termination in both groups. The PDR is a 30-item
measure of
child behavior problems administered via telephone to parents
on a se-
ries of consecutive or closely spaced days (approximately 1 to 3
days
apart). During each call, a trained interviewer asked the
foster/kinship
parent the following question, “Thinking about (child's name),
during
the past 24 h, did any of the following behaviors occur?”
Parents were
then read the list of 30 behaviors and asked to indicate either
“yes” or
“no” as to whether the behavior had occurred in the last 24 h.
Consis-
tent with the KEEP effectiveness study, three PDR calls were
adminis-

tered at baseline (prior to the intervention) and at termination
(following completion of the intervention) on different
occasions across
a two-week period. The PDR is structured so that parents focus
on
recalling only the past 24 h, thus avoiding aggregate recall or
estimates
of frequency thought to bias estimates (Stone, Broderick, Kaell,
DelesPaul, & Porter, 2000). The PDR has been used in several
previous
outcome studies, including those with families referred because
of
child conduct problems (e.g., Kazdin & Wassell, 2000;
McClowry,
Snow, & Tamis-LeMonda, 2005) and families with children in
regular
foster care (Chamberlain, Price, Reid et al., 2008; Chamberlain,
et al.,
1992). The concurrent validity of the PDR has been
demonstrated in
connection with measures of child and family functioning,
including
live observations of family interactions in the home (Forgatch &
Toobert, 1979; Patterson, 1976) and parents' ratings of child
behavior
(i.e.., Becker Adjective Checklist; Becker, Madsen, Arnold, &
Thomas,
1967). Scores representing levels of child behavior problems
were cal-
culated for each child at baseline and termination by summing
the
number of behaviors reported per day on the PDR (out of the
possible
30) divided by the number of calls made at each assessment
period
(typically three calls). Means and standard deviations for

baseline and
termination child behavior problems by intervention and control
groups are provided in Table 2.
3. Results
3.1. Determination of covariates
As reported earlier, analyses to examine potential differences
be-
tween the KEEP effectiveness study groups and the KEEP SAY
imple-
mentation trial group on demographic variables revealed
significant
group differences on several continuous variables, including the
age of
the focal child, age of the primary caregiver, and income level.
To deter-
mine potential covariates for regression analyses, these
variables were
examined in relation to child behavior problems at termination
using
correlational analyses. The correlations between these variables
and
child behavior problems at termination were: r=−.093 (p=.013),
.005 (ns), and .014 (ns), respectively. Prior analyses of the
demographic
data also revealed significant group differences on several
categorical
Table 2
Means and Standard deviations of Baseline and Termination
Behavior Problems by
Group.
Group Variable Baseline Child

Behaviors
Termination
child behaviors
M SD M SD
KEEP effectiveness Study
Intervention (n=356) 5.92 4.26 4.37 3.91
Control (n=341) 5.77 3.93 5.44 4.15
KEEP SAY implementation (n=159) 4.83 3.93 2.46 3.15
(2012) 2487–2494
and group status for those at the mean level of baseline behavior
problems, b=− .24, p=. 001. In addition, there was a statistically
significant and negative simple slope between the number of
termi-
nation behavior problems and group status for those at one
standard
deviation above the mean, b=−.36, p=.001, those at two
standard
deviations above the mean, b=− .49, p=.001, and those at three
standard deviations above the mean, b=− .61, p=.001. In each
case, relative to the control group, there was a significant
reduction
in termination behavior problems for children in the
intervention
group. Thus, as the number of baseline behaviors increased
there

was a greater reduction in the behavior problems in the
intervention
group in contrast to the control group. Fig. 1 depicts the
differences
between the control and intervention groups for the number of
ter-
mination behavior problems at a specific value (e.g., 1 SD
above the
mean) for baseline behavior problems.
Next, simple regression lines were computed for the relation be-
tween number of termination behavior problems and group
status 2
(KEEP SAY implementation trial group vs. KEEP effectiveness
study
control group) at specific values of number of baseline behavior
problems: one standard deviation below the mean, at the mean,
one standard deviation above the mean, and two standard
deviations
above the mean, and 3 standard deviations above the mean. The
sim-
ple slope between number of termination behavior problems and
group status at one standard deviation below the mean, b=−.31,
was statistically significant, p=.004. A statistically significant
and
negative simple slope was also found between number of
termination
behavior problems and group status for those at the mean level
of base-
line behavior problems, b=−.60, p=. 001. In addition, there was
a sta-
tistically significant and negative simple slope between the
number of
termination behavior problems and group status for those at one
stan-
dard deviation above the mean, b=−.89, p=.001, those at two

stan-
dard deviations above the mean, b=−1.18, p=.001, and those at
three standard deviations above the mean, b=−1.47, p=.001. In
each case, relative to the control group, there was a significant
reduction
in termination behavior problems for children in the
intervention
group. Thus, as the number of baseline behaviors increased
there was
a greater reduction in the behavior problems in the intervention
group in contrast to the control group. Fig. 2 depicts the
differences be-
tween the comparison and intervention groups for the number of
ter-
mination behavior problems at a specific value (e.g., 1 SD
above the
mean) for baseline behavior problems.
4. Discussion
The primary goal of the current investigation was to examine
the
effectiveness of the KEEP intervention in reducing child
behavior
problems as it was being delivered by a community-based
mental
health provider during an implementation trial in San Diego
County. A
secondary goal was to determine whether the intervention was
effec-
tive in reducing child behavior problems at various levels as
presented
at baseline. The results from regression analyses replicated the
findings
of the KEEP effectiveness study in demonstrating that the KEEP
inter-

vention was effective in reducing child behavior problems in the
KEEP
effectiveness study intervention group (Chamberlain, Price,
Leve, et
al., 2008; Chamberlain, Price, Reid, et al., 2008). Furthermore,
the find-
ings from the same analyses revealed that the KEEP
intervention was
also effective in reducing child behavior problems when it was
implemented in San Diego County by a community service
provider
rather than a research-based entity. This pattern of findings
suggests
that as the KEEP intervention moves away from the intervention
devel-
opers and into real world service settings the effectiveness of
the inter-
vention can be maintained. Moreover, not only was the
effectiveness of
the intervention maintained as it was adopted within a child
welfare
setting, but it was also found to be effective with a different
composition
of substitute caregivers. Whereas in the original KEEP
effectiveness
study 34% of caregivers were relatives (e.g., grandparents,
aunts and un-
cles), in the KEEP SAY implementation trial, 53.8% of the
caregivers
were relatives. Despite these differences, the cumulative
findings from
the current investigation and the original KEEP effectiveness
study
(Chamberlain, Price, Reid, et al., 2008) indicate that the KEEP
foster par-
ent intervention is effective in reducing child behavior

problems, re-
gardless of the type of caregiver relationship.
An additional goal of this investigation was to determine
whether
the KEEP intervention was effective in reducing child behavior
prob-
lems based on various levels of initial baseline behavior
problems.
That is, is the KEEP intervention effective in reducing child
behavior
problems, regardless of the initial level of child behavior
problems
observed at baseline? It was hypothesized that the KEEP
interven-
tion, as delivered during both the effectiveness study and during
the implementation trial, would be effective in reducing child
behav-
ior problems at termination for children with behavior problems
at
or above the mean in baseline behavior problems as assessed by
the PDR. The results of the regression analyses revealed
significant
effects for the interactions between group status (intervention
vs.
control/comparison) and baseline behavior problems. Follow-up
-0.75
-0.25
0.25
0.75
1.25

1.75
2.25
1 2
-1 SD Mean 1 SD
2 SD 3 SD
Control KEEP
Intervention
-0.25
0.25
0.75
1.25
1.75
2.25
1 2
-1 SD Mean 1 SD
2 SD 3 SD
Control
Fig. 1. Differences between KEEP effectiveness study control
and intervention groups for
the number of termination behavior problems at a specific value
for baseline behavior

problems.
-1
-0.5
0
0.5
1
1.5
2
2.5
1 2
Comparison KEEP SAY
Intervention
-1 SD Mean 1 SD
2 SD 3 SD
-1 SD Mean 1 SD
2 SD 3 SD
Fig. 2. Differences between comparison (KEEP effectiveness
study control) and KEEP SAY
implementation groups for the number of termination behavior
problems at a specific
value for baseline behavior problems.
(2012) 2487–2494

simple slope analyses, one set of analyses for the effectiveness
study
comparisons and one set for the implementation trial
comparisons,
revealed that the KEEP intervention was effective in reducing
chil-
dren behavior problems at various levels of baseline behavior
prob-
lems, including at the mean level of baseline behavior problems
(5.92 for the intervention group in the KEEP effectiveness study
and 4.85 for the KEEP implementation study) and continuing up
through levels of behavior problems as high as three standard
devi-
ations above the mean. During the implementation trial the
inter-
vention was also effective in reducing child behavior problems
at
levels as low as one standard deviation below the mean at
baseline.
The particular relevance of the findings from the simple slope
analy-
ses is that they demonstrate that the KEEP intervention is
effective in
reducing behavior problems at the levels that place children at
risk
for placement disruptions. Using data from the control group of
the
KEEP effectiveness study, Chamberlain et al. (2006) found that
for
each behavior above 6 behavior problems there was a 25%
increased
risk for a negative placement disruption (e.g., foster parent
initiates

request for change of placement because of child behavior
problems
or caseworker determines that the placement is no longer a good
fit).
Thus, by helping foster parents and relative caregivers to
manage the
behavior problems of the children in their care, the KEEP foster
par-
ent intervention has the potential to reduce the risk for negative
placement disruptions and reduce the personal and economic
bur-
dens that result from placement disruptions.
4.1. Study limitations
One of the limitations of the current investigation was the
demo-
graphic differences between the participants in the KEEP
effectiveness
study and those who took part in the implementation trial. Even
though the participants in both groups were from the same
geographic
regions within San Diego County, the samples differed in
several ways
(e.g.., proportion of foster parent vs. relative caregivers,
proportion
of English vs. Spanish speakers, ethnic composition, and age of
the
children). As noted earlier, group differences on relative
proportion of
type of caregiver (foster vs. relative) was attributable to the fact
that
the community agency delivering the KEEP intervention in this
study
(SAY San Diego) serviced relative substitute caregivers caring
for chil-

dren who were not dependents of San Diego County Child
Welfare
Services. Thus, in addition to recruiting caregivers with
children who
were dependents of child welfare, eligible relative caregivers
served
by SAY San Diego with children who were not dependents were
also
recruited into the intervention during implementation.
Consequently,
a higher proportion of relative caregivers were recruited into the
KEEP
intervention during implementation. In contrast, in the original
KEEP
effectiveness study only families (both nonrelative and relative)
who
were caring for child welfare dependents were recruited into the
study. It is possible that the inclusion of the relative givers
served by
SAY San Diego to the KEEP SAY implementation trial
contributed to
the demographic differences between the samples.
Another limitation of the current study was the internal validity
threat of history (Cook & Campbell, 1979), in particular local
history,
in contributing to differences between the historical comparison
group (KEEP effectiveness study control group) and the KEEP
imple-
mentation trial group. It is possible that foster and kinship
caregivers
who participated in the KEEP intervention following
implementa-
tion received services unavailable to the foster and kinship care-
givers who participated in the earlier KEEP effectiveness study,
such as expanded pre-service or in-service training. However,

regu-
lar communications with our contacts at San Diego Child
Welfare
Services over the period of KEEP effectiveness study (1999 to
2006)
and the implementation trial (2005–2008) did not reveal any
sub-
stantial changes to basic pre-service or in-service training for
foster
parents.
4.2. Conclusions
First, within the context of the Cascading Dissemination Model,
the
results of this investigation suggest that as the KEEP
intervention
moves away from the intervention developers, paraprofessionals
from
a community agency that are given adequate training and
supervision
can deliver the intervention to foster and relative caregivers in a
man-
ner that is effective in reducing behavior problems of children
in foster
care,. As mentioned earlier, the group facilitators hired by SAY
San
Diego received extensive training in the KEEP intervention
model, the
curriculum, and the management of group processes. This
training
was conducted by personnel trained by the intervention
developers
and took place over several weeks prior to start of the first
parenting
groups. In addition, all group sessions were video recorded and

reviewed by the group facilitator and the clinical supervisor.
Also,
group facilitators contacted the parents in their group each week
to as-
sess levels of child behavior problems (via the Parent Daily
Report —
PDR) and to discuss application of session material. Group
facilitators
and the clinical supervisor met each week to discuss parents'
progress
in managing child behavior problems, the delivery of session
material,
and group processes during the prior session. It is within this
context
that the KEEP intervention was found to be effective in
reducing child
behavior problems, and at various levels of initial behavior
problems.
The training and supervision procedures were not burdensome
for the
group facilitators and likely contributed to the effectiveness of
the inter-
vention. The results of the implementation trial suggest that it is
feasible
to have the KEEP intervention delivered by a community mental
health
provider within a child welfare system of care and that it can be
deliv-
ered in a manner that leads to reductions in levels of children's
external-
izing behavior problems. Such reductions are likely to decrease
the risk
for unwanted placement changes in foster care (Chamberlain et
al.,
2006; Newton et al., 2000).

Second, this study illustrates a research strategy for examining
the
effectiveness of an evidence-based practice as it is implemented
in a
child welfare service setting by utilizing a research design that
inte-
grates data from a prior effectiveness study of the intervention
and
the data collected during the implementation of the intervention.
With this design, the control group from an earlier efficacy or
effective-
ness study can provide a ready comparison group when it may
not be
possible to obtain a control or comparison group during the
implemen-
tation of an intervention. Researchers and service providers
might even
consider collaborating in conducting a randomized effectiveness
trial in
conjunction with a non-randomized implementation of an
intervention
in a community setting. The data from this research could be
analyzed
together to provide results on the effectiveness of the
intervention
under two types of conditions; (a) one with the delivery and
moni-
toring of the intervention carried out by researchers, and (b) the
other with delivery and monitoring carried out by the
community
providers and/or the service agency personnel who are
considering
adopting the intervention. The findings generated from this type
of
design would address the effectiveness of the intervention and
pro-

vide valuable information on the potential challenges and
barriers
to large scale implementation of the intervention.
Acknowledgments
Support for the KEEP effectiveness trial was provided by Grant
No.
MH 60195 from the Child and Adolescent Treatment and
Preventive
Intervention Research Branch awarded to Dr. Patti Chamberlain.
Sup-
port for the KEEP SAY implementation trial was provided by a
grant
from the State of California awarded to San Diego County Child
Wel-
fare Services. The authors would like to thank San Diego
County Child
Welfare Services Directors: Yvonne Campbell, Mary Harris, and
Debra
Zonders-Willis; Deputy Directors: Patty Rahiser, Renee Smiley,
and
Roseann Myers; Social Advocates for Youth Supervisor:
Shannon
Throop; Research Project Directors: Courtenay Paulic, Jan
Price, and
2493J.M. Price et al. / Children and Youth Services Review 34
(2012) 2487–2494
Norma Talamantes; OSLC consultant JP Davis; lead
interventionists
Norma Talamantes, Melissa Woods, Moniesha Cole, and Sonia
Miramontes; and the foster and relative caregivers who

participated
in these studies.
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(2012) 2487–2494
Effectiveness of the KEEP foster parent intervention during an
implementation trial1. Introduction1.1. Development of the
KEEP intervention model1.2. Implementation of KEEP in San
Diego County1.3. Cascading Dissemination Model2. Method2.1.
Participants2.1.1. KEEP effectiveness study participants2.1.2.
KEEP SAY implementation trial participants2.2. Recruitment
methods2.3. Intervention model2.4. Measures2.4.1. Child and
parent characteristics2.4.2. Child behavior problems3.
Results3.1. Determination of covariates3.2. Regression
analyses3.2.1. Hierarchical regression analyses3.2.2. Simple
slope analyses4. Discussion4.1. Study limitations4.2.
ConclusionsAcknowledgmentsReferences
Race and Poverty: prompt
This assignment is a sincere reflection on issues of race/racism,
poverty, and their nexus. This reflection will involve your
position (not only as conscious/aware being, but also as
positioned bodily creature conditioned by your context: class,

gender, geography, race, etc…) as it engages and takes the
authors we’ve read and experiences of others seriously. This
assignment can be broken down into two parts, these two parts
are conceptual and not chronological: the first asks you to
investigate your identity as it is shaped by social realities like:
race, white, non-white, colonization, imperialism, immigrant,
colonized, white supremacy, non-white suffering, stereo-typing,
prejudice, racism; and other most significant abstractions:
religion, gender, sexuality, geography, etc… (according to
readings below, select some aspects to write). The second asks
you to do the first, investigate your identity, by engaging with,
scholars who investigate, and write about these subjects (i.e. the
readings below), and, the experiences of other communities,
identities, etc…
This does not mean that write like part1….and
part2….separately. This is the whole essay, so connect these
two parts as a normal essay which can be divided into several
paragraphs.
3-4 pages, three sources taken from reading below (no sources
outside), any type of citation allowed, 12 font, double spaced.
Reading:
1. Tim Wise: Imagine If the Tea Party Was Black
http://www.alternet.org/story/146616/what_if_the_tea_party_we
re_black
2. Gobineau's Inequality of the Human Races
https://books.google.com/books?id=JeM_1BCeffAC&printsec=f
rontcover&source=gbs_ge_summary_r&cad=0#v=onepage&q&f
=false
3. RACE, ETHNICITY, AND SEXUALITY: INTIMATE
INTERSECTIONS, FORBIDDEN FRONTIERS Nagel, Joane.,
2003.
(If u can find this book and read it, that will be perfect. But if u
cannot find it to read, there is the website which has the
description about this book for u to consult

http://www.cjsonline.ca/reviews/racethsex.html )
Comorbidity of Anxiety and Depression in Youth:
Implications for Treatment and Prevention
Judy Garber, Vanderbilt University
V. Robin Weersing, SDSU ⁄UCSD Joint Doctoral Program in
Clinical Psychology
The high level of concurrent and sequential comorbidity
between anxiety and depression in children and adoles-
cents may result from (a) substantial overlap in both
the symptoms and items used to assess these putatively
different disorders, (b) common etiologic factors (e.g.,
familial risk, negative affectivity, information-processing
biases, neural substrates) implicated in the develop-
ment of each condition, and (c) negative sequelae of
anxiety conferring increased risk for the development of
depression. Basic research on their various common and
unique etiologic mechanisms has guided the develop-
ment of efficacious treatments for anxiety and depres-

sive disorders in youth. Potential processes through
which the successful treatment of childhood anxiety
might prevent subsequent depression are described.
Key words: anxiety, depression, prevention, treat-
ment. [Clin Psychol Sci Prac 17: 293–306, 2010]
Anxiety and depression frequently co-occur both con-
currently and sequentially in children and adolescents,
and one often increases the risk of the other over time.
The most common anxiety diagnoses in youth are sep-
aration anxiety disorder (SAD), social anxiety disorder
(SOC), generalized anxiety disorder (GAD), and spe-
cific phobia (SP); depression diagnoses include major
depressive disorder (MDD) and dysthymic disorder
(DD). These various anxiety and depressive disorders
appear together across generations, clustering strongly
within families. Unpacking the whole of the internaliz-
ing comorbidity literature is beyond the scope of
this article (see Axelson & Birmaher, 2001; Brady &

Kendall, 1992; Seligman & Ollendick, 1998). Rather,
we address several key questions regarding comorbid
anxiety and depression in youth. What is the extent of
their concurrent and sequential overlap? What may
account for the observed patterns of comorbidity
between these disorders? What are the implications of
their comorbidity for the treatment and prevention of
anxiety and depression?
EXTENT OF CONCURRENT AND SEQUENTIAL
COMORBIDITY
Anxiety and mood symptoms and disorders in youth
are distressing, impairing, and prevalent (e.g., Costello,
Mustillo, Erkanli, Keeler, & Angold, 2003), interfere
with interpersonal relationships and academic achieve-
ment, and increase the risk of suicide and other
psychopathology (e.g., Gould et al., 1998; Rohde,
Lewinsohn, & Seeley, 1994). Moreover, such negative
effects may propagate forward into adulthood (Rohde
et al., 1994; Weissman et al., 1999). The prognosis for

comorbid anxiety and depression is worse than either
condition alone, with higher risk of recurrence, longer
duration, increased suicide attempts, greater impair-
ment, less favorable response to treatment, and greater
utilization of mental health services (Birmaher et al.,
1996; Ezpeleta, Domenech, & Angold, 2006).
An estimated 15–20% of youth in the United
States meet criteria for any anxiety disorder (i.e., SAD:
2.8–8%, SP: 10%, SOC: 7%, panic disorder: 1–3%,
GAD: 4.3%; Beesdo, Knappe, & Pine, 2009), and
Address correspondence to Judy Garber, Vanderbilt University,
Psychology and Human Development, 0552 GPC, 230 Apple-
ton Place, Nashville, TN 37203-5721. E-mail: [email protected]
vanderbilt.edu.
! 2010 American Psychological Association. Published by Wiley
Periodicals, Inc., on behalf of the American Psychological
Association.
All rights reserved. For permissions, please email:
[email protected] 293

approximately one in five youth will have an episode
of MDD by age 18 (Lewinsohn, Hops, Roberts,
Seeley, & Andrews, 1993). The level of comorbidity
between these common problems is substantial, as evi-
denced by both high correlations between dimensional
measures of anxious and depressive symptoms (e.g.,
Cole, Peeke, Martin, Truglio, & Seroczynski, 1997;
Stark & Laurent, 2001) and diagnostic comorbidity
rates as high as 75% in some clinical samples (Sorensen,
Nissen, Mors, & Thomsen, 2005; Weersing, Gonzalez,
Campo, & Lucas, 2008).
Interestingly, this high degree of comorbidity does
not appear to be symmetrical. In community samples,
25–50% of youth with depression also meet criteria for
an anxiety disorder, whereas only 10–15% of those
with a primary anxiety disorder have a concurrent
depressive disorder (Angold, Costello, & Erkanli, 1999;
Axelson & Birmaher, 2001; Costello et al., 2003).

Thus, youth with primary depressive disorders tend to
have comorbid anxiety more often than do those with
primary anxiety disorders have comorbid depression
(Merikangas & Avenevoli, 2002; Ollendick, Shortt, &
Sander, 2005).
Several factors might explain this apparent imbal-
ance. First, subsyndromal levels of symptoms often
have not been assessed in studies of comorbidity. That
is, children diagnosed with anxiety disorders may have
concurrent depressive symptoms even if they do not
meet full criteria for a depressive diagnosis, and these
co-occurring, subthreshold symptoms may account for
the apparent link between anxiety and subsequent
depressive disorder in adolescence. Indeed, sub-
diagnostic depressive symptoms have been found to be
a more reliable predictor of subsequent depressive
disorders than symptoms of either separation or social
anxiety (Keenan, Feng, Hipwell, & Klostermann,

2009).
Second, anxiety disorders are quite heterogeneous;
the extent of comorbidity with depression depends on
which anxiety symptoms and disorders are assessed
(Avenevoli, Stolar, Li, Dierker, & Merikangas, 2001;
Chaplin, Gillham, & Seligman, 2009; Moffitt et al.,
2007). For example, whereas panic disorder does not
consistently predict subsequent depression, SOC and
GAD in childhood tend to be associated with depres-
sion during adolescence (Bittner et al., 2007; Keenan
et al., 2009). Thus, although there is considerable
comorbidity among anxiety disorders (Angold et al.,
1999), combining anxiety disorders together likely
distorts the apparent strength and direction of the
relation between particular anxiety disorders and
depression.
Third, the degree of comorbidity varies by age and
developmental period. Whereas anxiety is more preva-

lent during childhood, depression increases during ado-
lescence (e.g., Cohen, Cohen, & Brook, 1993;
Woodward & Fergusson, 2001). Youth with comorbid
anxiety and depression tend to be older than those
with either disorder alone (Brady & Kendall, 1992;
Merikangas & Avenevoli, 2002). This may be due, in
part, to differences in the structure and differentiation
of affect across development. For example, in young
children (third graders), anxiety and depression form a
unified, indistinguishable construct, whereas in older
children (sixth graders), a dual-factor or tripartite model
is more common (Cole, Truglio, & Peeke, 1997).
Thus, higher rates of comorbid anxiety and depressive
disorders tend to be found in adolescents than children
(Ollendick et al., 2005).
Finally, whereas concurrent comorbidity of anxiety
and depressive disorders is substantial and relatively
undisputed (Brady & Kendall, 1992), less clear is the

extent and direction of ‘‘sequential comorbidity,’’ that
is, when one disorder reliably precedes the other (An-
gold et al., 1999). Comorbid anxiety and depression
may have strong effects on one another such that the
presence of anxiety symptoms may lead to an increase
in depressive symptoms and vice versa (Bittner et al.,
2007; Goodwin, Fergusson, & Horwood, 2004); most
studies of sequential comorbidity have focused on anxi-
ety as the predictor and depression as the outcome,
rather than the reverse. In general, evidence indicates
that anxiety symptoms and disorders in childhood often
precede the onset of depressive disorders in adolescence
and young adulthood (Chorpita & Daleiden, 2002;
Pine, Cohen, Gurley, Brook, & Ma, 1998), particularly
for girls (Breslau, Schultz, & Peterson, 1995; Chaplin
et al., 2009; Keenan & Hipwell, 2005), and may con-
tribute to the increased risk of depression in females
(Bittner et al., 2004).

Less evidence exists of depression preceding anxiety,
however (e.g., Axelson & Birmaher, 2001; Orvaschel,
CLINICAL PSYCHOLOGY: SCIENCE AND PRACTICE • V17
N4, DECEMBER 2010 294
Lewinsohn, & Seeley, 1995). Only a few balanced
investigations have been conducted in which individu-
als with mood disorders are followed longitudinally to
assess the onset of an anxiety disorder as well as the
reverse (Gallerani, Garber, & Martin, 2010; Keenan
et al., 2009; Pine et al., 1998). For example, Pine et al.
(1998) reported that MDD during adolescence signifi-
cantly predicted a fivefold increased risk of GAD in
young adulthood.
WHAT ACCOUNTS FOR COMORBIDITY BETWEEN
ANXIETY AND
DEPRESSION
Several nonmutually exclusive explanations for the
observed comorbidity between anxiety and depression

have been suggested, some of which are methodologi-
cal and others more substantive. We highlight here
some of the most frequently suggested reasons for such
comorbidity and later discuss their implications for
intervention.
Item and Symptom Overlap
One methodological explanation for the high correla-
tion between self-report measures of anxiety and
depression is that the items on these scales are quite
similar or even identical. Investigations that have
excluded all overlapping items, however, have found
that the correlations of the abbreviated measures were
still significant (r = 0.34; Stark & Laurent, 2001) and
that such modified versions of the self-report measures
only reduced the shared variance (52–72%) in trait con-
structs by about 13% (Cole, Truglio, & Peeke, 1997).
A related, but more complex, reason for the
observed comorbidity between anxiety and depression

is that the symptoms that define these disorders are
similar. For example, social avoidance can characterize
both SOC and MDD, although the underlying reason
for and function of the avoidance may differ. The
clearest example of symptom overlap is between GAD
and MDD, both of which include fatigue, sleep distur-
bance, concentration difficulties, and irritability (in
children). The proposed revision for DSM-V eliminates
these specific symptoms from the criteria that define
GAD, which may be one way to reduce comorbidity.
The validity of these new symptom criteria for
GAD remains to be demonstrated in adults as well as
children.
Underlying Negative Affectivity
An important substantive explanation for the associa-
tion between anxiety and depression is that they have
shared etiologic influences. In particular, some of the
overlap between anxious and depressive symptoms

likely is because of a common underlying latent risk
factor of general negative affectivity (NA) or negative
emotionality (Barlow, 2000; Clark & Watson, 1991),
which is related to the personality construct of neuroti-
cism (Watson, 2000). NA represents the extent to
which an individual feels distress (e.g., upset, sad,
angry, guilty, worried) and not calm, relaxed, or peace-
ful. According to the tripartite model (Clark &
Watson, 1991), high NA characterizes both anxiety
and depression, whereas low positive affect (PA) and
loss of interest or pleasure are unique to depression,
and somatic tension and physiological hyperarousal
(PH) are distinct features of anxiety. Removing vari-
ance attributable to general NA reduces the correlation
between anxiety and depression and facilitates their dis-
crimination on the remaining unique features (i.e., PA,
PH).
Support for the tripartite model has been found in

clinical and nonclinical samples of children and adoles-
cents (Laurent & Ettelson, 2001). Particularly robust is
the finding that general NA accounts for much of the
variance shared by depression and anxiety in youth
(Chorpita, Daleiden, Moffitt, Yim, & Umemoto, 2000;
Tully, Zajac, & Venning, 2009). Evidence for the
physiologic arousal component has been more mixed,
however (e.g., Chorpita, 2002; Jacques & Mash, 2004;
Lonigan, Hooe, David, & Kistner, 1999). Watson
(2005) proposed a reconfiguration of mood and anxiety
disorders into ‘‘distress’’ and ‘‘fear’’ factors, which
together comprise a higher-order internalizing factor
(Slade & Watson, 2006). Accordingly, GAD, MDD,
DD, and posttraumatic stress disorder cluster with the
distress disorders, whereas panic disorder, SOC, and
SPs comprise the fear disorders. Some evidence that
GAD is more closely linked with depression when
compared to anxiety has been found in children

(Higa-McMillan, Smith, Chorpita, & Hayashi, 2008;
Lahey et al., 2008), although evidence that GAD is
more closely aligned with other anxiety disorders than
to depression also has been reported (e.g., Beesdo,
Pine, Lieb, & Wittchen, 2010).
COMORBID ANXIETY AND DEPRESSION ! GARBER &
WEERSING 295
Shared Familial Risk
Family studies consistently reveal that offspring of
depressed parents are at high risk for developing early-
onset anxiety disorders as well as depression, and
offspring of anxious parents are at risk to develop
early-onset depression (Warner, Mufson, & Weissman,
1995; Weissman, Warner, Wickramaratne, Moreau, &
Olfson, 1997). Familial risk may be a marker for
genetic or shared environmental mechanisms or both.
Twin studies indicate that a common genetic influ-
ence likely accounts for some of the covariation

between anxious and depressive symptoms (Hudziak,
Rudiger, Neale, Heath, & Todd, 2000; Thapar &
McGuffin, 1997). An endophenotype common to both
pediatric anxiety and depression may be ‘‘tempera-
ment’’ such as negative affectivity (as discussed
earlier), stress reactivity, affect dysregulation, behavioral
inhibition, and harm avoidance (e.g., Caspi, Moffitt,
Newman, & Silva, 1996; Kelvin, Goodyer, & Altham,
1996). Moreover, consistent with the notion of hetero-
typic continuity, the shared genetic liability may be dif-
ferentially expressed as anxiety earlier and depression
later in development (Eaves, Silberg, & Erkanli, 2003).
In particular, the common genetic ⁄biologic diathesis
may result in anxiety or depression depending on the
timing of the environmental events. In genetically
vulnerable children, stressors that occur in childhood
may produce anxiety, whereas those occurring during
adolescence may lead to depression. The developmental

progression from anxiety to depression may reflect a
‘‘readiness’’ (Kovacs & Devlin, 1998, p. 54) to show
certain physiologic aspects of anxiety (e.g., agitation,
hyperarousal) earlier in development, and certain other
physiologic (e.g., vegetative symptoms) and cognitive
(e.g., rumination) aspects of depression later.
Although genes likely play a significant role in the
etiology and comorbidity of anxiety and depression,
copious evidence also implicates parenting behaviors in
the intergenerational transmission of anxiety and
depression (e.g., McLeod, Weisz, & Wood, 2007;
McLeod, Wood, & Weisz, 2007). For example, paren-
tal rejection and control are positively correlated
with both anxiety and depression in children, with
rejection being more strongly associated with depres-
sion and control more associated with anxiety (Rapee,
1997). Such parenting behaviors have been found to
characterize both anxious and depressed mothers who

tend to exhibit less warmth and more controlling
behaviors toward their children (e.g., Lovejoy,
Graczyk, O’Hare, & Neuman, 2000; Whaley, Pinto, &
Sigman, 1999). In addition, insecure attachment early
in childhood has been linked with both anxiety and
depression later (Davila, Ramsay, Stroud, & Steinberg,
2005).
Similar Information-Processing Biases and Neural Substrates
Negative cognitions and information-processing errors
such as catastrophizing, rumination, and worry charac-
terize both anxiety and depression (Dozois & Beck,
2008; Martin & Tesser, 1996). Maladaptive interpreta-
tions of negative social events in particular are cogni-
tive biases associated with both social anxiety and
depression (Wilson & Rapee, 2005). Similar to
depressed individuals, people high in social anxiety
tend to make internal, stable, and global attributions for
failures in interpersonal situations (Alfano, Joiner, &

Perry, 1994; Hope, Gansler, & Heimberg, 1989),
although negative inferential style interacts with stress
to specifically predict depression and not anxiety in
adolescents (Hankin, 2008).
Data from performance-based studies indicate that
anxious and depressed youth also share information-
processing biases in attention toward threat and interpre-
tation of ambiguous situations as negative or threatening
(e.g., Bogels & Zigterman, 2000; Ladouceur et al.,
2005). The cognitive processes of individuals with anxi-
ety and depression tend to be primed to attend more
quickly and readily to threat (Coles, Heimberg, &
Schofield, 2008; Gotlib, Krasnoperova, Neubauer Yue,
& Joorman, 2004). Attention toward and interpretation
of threat is assumed to worsen symptoms of internalizing
psychopathology (Dalgleish et al., 2003; Lonigan, Vasey,
Phillips, & Hazen, 2004), and in turn, cognitive symp-
toms of anxiety and depression presumably then worsen

attention to and interpretation of negative stimuli
(Brozovich & Heimberg, 2008).
Finally, similar neural-circuitry dysfunction related to
emotional modulation of perception and behavior has
been found in individuals with either anxiety or depres-
sive disorders (e.g., Phillips, Drevets, Rauch, & Lane,
2003; Thomas et al., 2001). For example, adolescents
with anxiety or mood disorders have been found to
exhibit both common and distinct functional neural
correlates (i.e., amygdala responses) during face process-
ing, depending on the specific attention and emotion
states engaged (Beesdo, Knappe, & Pine, 2009; Beesdo,
Lau, et al., 2009). In particular, Beesdo, Lau, and
colleagues (2009) reported that both anxious and
depressed youth showed greater amygdala activation
than healthy controls when viewing fearful faces,

whereas disorder specificity emerged during passive
viewing of emotional stimuli. Thus, anxiety and
depressive disorders in youth involve many complex
commonalities, as well as distinguishable amygdala-
related biases, information-processing patterns, temper-
aments, family environments, and genetic vulnerabili-
ties.
Anxiety as a Risk for Depression
As noted earlier, anxiety and depression show substan-
tial sequential comorbidity, with anxiety symptoms and
disorders often preceding the onset of mood disorders
(e.g., Avenevoli et al., 2001; Kim-Cohen et al., 2003;
Pine et al., 1998). Accordingly, anxiety itself may be a
causal risk factor (Kraemer et al., 1997) for the devel-
opment of depression (Bittner et al., 2004; Wittchen,
Beesdo, Bittner, & Goodwin, 2003), and the experi-
ence of childhood anxiety may be both the source of
high sequential comorbidity over development and of

elevated rates of concurrent anxiety and depression in
adolescence.
Childhood anxiety may have depressogenic effects
through a variety of mechanisms. For example, social
anxiety might increase individuals’ affiliative behaviors
as well as their attempts to avoid negative evaluations
from others (e.g., Alden & Taylor, 2004; Leary &
Kowalski, 1995). This may result in dysfunctional social
behaviors that are intended to be protective, but actu-
ally end up increasing the likelihood of the very rejec-
tion they are trying to avoid. Anxiety-driven social
withdrawal and isolation can intensify peer rejection,
resulting in feelings of loneliness, low self-worth, and
sadness (Gazelle & Ladd, 2003), particularly for girls for
whom interpersonal relationships are especially impor-
tant (Rose & Rudolph, 2006). Similarly, avoidance of
expressing emotions because of fears of rejection and
humiliation has been found to mediate the relation

between social anxiety and changes in depressive symp-
toms (Grant, Beck, Farrow, & Davila, 2007). Socially
anxious individuals who inhibit their expression of
negative emotions may feel devalued, sad, and resent-
ful, and over time, become depressed. Furthermore,
individuals with social anxiety tend to make negative
inferences about the meaning of adverse social events
for their future and self-worth (Stopa & Clark, 2000),
which have been identified as cognitive vulnerabilities
to depression (Abramson, Metalsky, & Alloy, 1989).
Summary
The high level of comorbidity between anxiety and
depression in youth may be the result of three nonex-
clusive factors: (a) substantial overlap in both the
symptoms and items used to assess these putatively dif-
ferent disorders, (b) common etiologic factors impli-
cated in the development of each condition, and (c)
negative sequelae of anxiety conferring increased risk

for the development of depression. The first explana-
tion has important implications for the nosology of
disorders, the creation of valid assessments, and the
design and conduct of research with internalizing
youth. The second and third explanations may guide
the development of treatments for youth with internal-
izing problems and the prevention of depression in
adolescents and adults.
IMPLICATIONS FOR INTERVENTION
Treatment
Evidence-based treatments are typically designed to
target the precipitating and maintaining factors of
disorders to bring about symptom remission and func-
tional improvement. To the extent that anxiety and
depression in youth share common etiologic underpin-
nings, the efficacious treatments developed for these
disorders likely share common features and mechanisms
of action. Examination of the intervention literature

indicates that this is largely what appears to have tran-
spired. For both depression and anxiety, the best
practice pharmacotherapy is with selective serotonin
reuptake inhibitors (SSRIs; e.g., TADS, 2004; Walkup
et al., 2008). Generally, higher doses of SSRIs are
required for therapeutic effects on depression than
anxiety (with the notable exception of dosing for
obsessive-compulsive disorder). The same agents, how-
ever, appear to have similar benefits and adverse event
WEERSING 297
profiles across youth with anxiety or depression
(Bridge et al., 2007).
The primary psychosocial intervention for both anx-
iety and depression is cognitive-behavioral therapy
(CBT; see Compton et al., 2004), with positive effects
for CBT reported across the anxiety disorders and for

mild to moderate levels of depressive disorder (for
severe depression, the combination of CBT and SSRI
may be warranted; see Brent et al., 2008). The CBT
interventions that treat these conditions contain similar
elements, although the programs differ in their com-
plexity and number of strategies employed. For exam-
ple, various CBT manuals for anxiety and depression
include problem solving, assertiveness training, cogni-
tive restructuring, family communication skills training,
relaxation, exposure, pleasant activity scheduling, and
behavioral activation (Weersing, 2004). Across all these
techniques, the different CBT manuals share a core
focus on (a) the interplay between thoughts, feelings,
and behaviors and (b) within this framework, teaching
adaptive responses to stress and coping with negative
emotionality.
In addition to the surface similarity of effective
interventions for anxious and depressed youth, inter-

ventions for one condition may have beneficial spill-
over effects on comorbid symptoms of the other disor-
der. Several randomized controlled trials examining the
effects of individual, group, and family CBT and expo-
sure-based treatments for anxiety disorders in children
have found significant reductions in self-reported
depressive symptoms as well (Barrett, Dadds, & Rapee,
1996; Kendall, Flannery-Schroeder, Panichelli-Mindel,
& Southam-Gerow, 1997; Kendall, Hudson, Gosch,
Flannery-Schroeder, & Suveg, 2008; Kendall, Safford,
Flannery-Schroeder, & Webb, 2004; Manassis et al.,
2002; Silverman et al., 1999). A comprehensive meta-
analysis of the effects of psychological therapy for
depression in children and adolescents examined
whether such treatments affected other conditions also
(Weisz, McCarty, & Valeri, 2006). To examine this
specificity question, Weisz and colleagues compared
the effect sizes (ES) for measures of depression with

those for anxiety symptoms across ten studies that had
assessed both. They found that depression treatments
produced a significant reduction in anxiety symptoms
(ES = 0.39) that was only marginally lower than that
found for depressive symptoms (ES = 0.57). Thus,
finding that anxiety treatments reduce depressive symp-
toms and depression treatments beneficially affect anxi-
ety is consistent with the view that anxiety and
depression in youth are closely associated empirically
(e.g., Achenbach & Rescorla, 2001) and likely share
common risk factors such as negative affectivity (e.g.,
Clark & Watson, 1991; Laurent & Ettelson, 2001).
The presence of one disorder, however, sometimes
reduces the efficacy of the treatment of the other. If
they were essentially the same condition, then why
wouldn’t the interventions affect the comorbid disorder
as well? Some depression treatment studies have found
that comorbid anxiety predicts a worse outcome

(Curry et al., 2006; Emslie et al., 1998; Vostanis,
Feehan, & Grattan, 1998), although other studies have
shown that the presence of anxiety predicted a more
positive outcome of CBT for depression (Brent et al.,
1998; Rohde, Clarke, Lewinsohn, Seeley, & Kaufman,
2001). Results of investigations of whether depression
reduces the efficacy of anxiety treatments also have
been mixed. A significant relation between depressive
symptoms and a less favorable response to anxiety treat-
ment has been found in some studies (e.g., Berman,
Weems, Silverman, & Kurtines, 2000), but not others
(Southam-Gerow, Kendall, & Weersing, 2001). Thus,
interventions targeting one disorder will not necessarily
successfully treat the other comorbid condition, even if
similar treatments are effective for each diagnosis on its
own.
Taken together, these results have led to the devel-
opment of interventions designed to treat comorbid

anxiety and depression or, more ambitiously, to suc-
cessfully target anxiety, depression, or comorbid anxi-
ety and depression within a single treatment protocol.
Such work is still in the pilot stage of implementation
and testing, but two approaches have emerged. One
program with youth stems from adult work developing
a unified theory of emotional disorders (Barlow, Allen,
& Choate, 2004) and emphasizes the core cognitive
biases and avoidance of negative emotions common to
both anxiety and depression (Ehrenreich, Goldstein,
Wright, & Barlow, 2009). A second approach is a
more behavioral intervention focusing on graded
engagement in activities designed to increase positive
affect and reduce the functional impairment associated
with internalizing symptoms in youth (Weersing et al.,
2008). The technique of ‘‘graded engagement’’ com-

bines aspects of behavioral activation for depression,
exposure techniques for anxiety, and problem-solving
skills to target the maladaptive responses to stress and
negative emotions seen across anxiety and depression.
Notably, this intervention targets both threshold and
subthreshold levels of comorbidity between anxiety and
depression, and the functional impact that these symp-
toms have on each other. For example, depressed
youth may have difficulty developing rewarding and
mood-enhancing relationships if they also have a
history of social anxiety. Thus, although similar inter-
ventions are efficacious with both anxiety and depres-
sive disorders, treatments need to address their unique
features as well.
Prevention
Whereas treatment aims to reduce existing symptoms
and disorders, the goal of prevention is to decrease the
likelihood of the onset of a disorder or a worsening of

symptoms, particularly among individuals at risk based
on their having current subsyndromal symptoms (i.e.,
indicated prevention) or other risk factors such as
parental psychopathology or exposure to stress (i.e.,
selective prevention). Although less extensive, research
on the prevention of anxiety or depression parallels the
treatment literature in several ways (for reviews, see
Horowitz & Garber, 2006; Neil & Christensen, 2009;
Stice, Shaw, Bohon, Marti, & Rohde, 2009). First,
interventions aimed at preventing anxiety and depres-
sion use many of the same procedures. For example,
some depression prevention programs explicitly include
anxiety-reducing techniques such as relaxation, anxiety
management, and stress inoculation (e.g., Clarke, Haw-
kins, Murphy, & Sheeber, 1993; Hains & Ellman,
1994). Second, the presence of one disorder sometimes
moderates the effect of the preventive intervention on
the other. For instance, some depression prevention

programs have been found to be better for children
with higher baseline levels of emotional arousal (Hains
& Ellman, 1994) or clinical anxiety (Lowry-Webster,
Barrett, & Dadds, 2001; Lowry-Webster, Barrett, &
Lock, 2003).
Third, interventions aimed at preventing one disor-
der sometimes affect the other as well. For example,
the effects of the Penn Prevention program have been
found to be as strong or even stronger in reducing
anxious when compared to depressive symptoms
(Gillham et al., 2006; Roberts, Kane, Thomson,
Bishop, & Hart, 2003). Gillham and colleagues sug-
gested that the stronger effects on anxiety may have
been because the antianxiety skills were easier to learn
compared to the skills that more directly targeted
depression. It also is possible that including strategies
aimed at reducing anxiety dilutes the effects of the
overall intervention on depression.

In contrast, anxiety prevention programs have been
found to have only modest effects on depressive symp-
toms. For instance, the FRIENDS program, a universal
school-based intervention designed to prevent internal-
izing problems through enhancing problem-solving and
coping skills, has been found to significantly reduce
anxiety. A reduction in depressive symptoms, however,
was found only at the 12-month evaluation and not at
24 or 36 months (Barrett, Farrell, Ollendick, & Dadds,
2006; Lock & Barrett, 2003; Lowry-Webster et al.,
2001).
TREATING ANXIETY TO PREVENT DEPRESSION
Given that childhood anxiety often precedes and is
a risk factor for depression (Costello et al., 2003;
Wittchen et al., 2003), a potentially useful intervention
strategy may be to treat anxiety as a means of prevent-
ing subsequent depression (Bienvenu & Ginsburg,
2007; Flannery-Schroeder, 2006). Although some treat-

ments for anxiety also produce significant decreases in
depressive symptoms (e.g., Barrett et al., 1996; Kendall
et al., 2004; Manassis et al., 2002), the strategy of pre-
venting depression by successfully treating anxiety in
youth has yet to be tested in a way that disentangles
the baseline levels of both anxiety and depression. Sev-
eral important questions remain regarding the treatment
and prevention of anxiety and depression, respectively.
Do treatments for anxiety disorders prevent the onset
of subsequent depressive disorders in addition to reduc-
ing concurrent depressive symptoms? If successful treat-
ment of anxiety prevents subsequent depression, how
enduring are these effects? For whom does the treat-
ment of anxiety prevent depression? What are the
optimal implementation parameters, such as dose and
timing? Finally, what accounts for the depression
WEERSING 299

prevention effects of treatments for anxiety in children?
That is, through what mechanisms do these significant
effects occur?
Table 1 outlines several ways that treating anxiety
might be sufficient to prevent depression without
directly implementing depression prevention strategies.
If successful, then treating anxiety could be an effi-
cient and cost-effective way to prevent depression, at
least among anxious children. We suggest at least four
different ways this might occur: (a) Anxiety is a
probabilistic risk factor for the development of
depression. Removing anxiety may eliminate this risk,
although the underlying processes are not specified.
(b) The therapeutic activities that target anxiety (e.g.,
cognitive reappraisal, coping) may generalize to
depression. Children might learn to apply the skills
acquired for dealing with their anxiety to other situa-

tions and emotions, without necessarily being explic-
itly taught to do so. The extent to which such
transfer of learning occurs will partially depend on
the child’s level of cognitive development. (c) If anx-
iety is a causal risk factor for depression, then reduc-
ing anxiety should affect the processes (e.g.,
avoidance) that account for this link, thereby prevent-
ing depression. For example, anxiety leads some
children to avoid social situations and hence miss out
on positively reinforcing activities, thereby increasing
their chances of depression. Similarly, anxiety may
produce awkward social behaviors that result in
rejection and subsequent depression. If treatment
directly eliminates such anxiety and the associated
mediating pathways, then depression might be pre-
vented. (d) If anxiety and depression share common
mechanism(s) such as negative affectivity, then treat-
ments for anxiety that reduce the common risk fac-

tor(s) might prevent depression as well.
Finally, if treating anxiety is not sufficient to prevent
depression, then it may be necessary to supplement
anxiety treatments with intervention techniques specifi-
cally aimed at preventing depression. Although several
successful depression prevention programs exist (see
Brunwasser, Gillham, & Kim, 2009; Horowitz &
Garber, 2006; Stice et al., 2009, for reviews), studies
are needed that explicitly test the efficacy of combining
depression prevention strategies, either simultaneously
or sequentially, with treatments for anxiety (see bottom
of Table 1).
RESEARCH RECOMMENDATIONS
1. Determine what are the most efficacious and cost-
effective ways of providing interventions that treat
and prevent both anxiety and depression.
2. Conduct randomized clinical trials with sufficiently
long follow-up intervals to determine if treating

anxiety significantly decreases the likelihood of
subsequent depression.
3. Identify specific mechanisms that link the different
anxiety disorders to depression and test inter-
ventions that directly target these mechanisms.
Table 1. Treating anxiety to prevent depression
Type Description Processes
Sufficient If treating anxiety is sufficient to prevent depression:
Unspecified risk factor Simply removing anxiety is sufficient to
prevent depression.
Treatment does not explicitly involve treating or preventing
depression directly.
Remove anxiety; processes unspecified (could be biology,
cognitions, etc.)
Generalization Treatment for anxiety generalizes, so skills
learned serve to
prevent later depression
Coping, cognitive restructuring, exposure
Causal risk factor Treating anxiety directly addresses
mechanism(s) that lead to
depression
Avoidance, social skills. Anxiety as a causal risk factor for
depression.

Common mechanism(s) Treatment of anxiety directly addresses
common mechanism(s) Reducing the common factor such as NA
eliminates both
Not sufficient If treating anxiety is not sufficient to prevent
depression: Need to add depression prevention
Simultaneous Treat anxiety and add intervention techniques
specific to
preventing depression
Sequential Treat anxiety first, then add specific depression
prevention
techniques
4. Conduct treatment-dismantling studies to identify
the specific components of the treatments that con-
tribute to symptom reduction and improved func-
tioning.
ACKNOWLEDGMENTS
This work was supported in part by grants from
NIMH (R01MH064735; R01MH064503) and the
William T. Grant Foundation.

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