Running head: ADOLESCENT DEPRESSION

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Adolescent Depression: Integrating Behavioral Healthcare in a Pediatric Primary Care Setting
Tori Danae Huftalin, BSN, RN, CPN
Mentor: Diana Jacobson, PhD, RN, PPCNP-BC, PMHS, FAANP
Arizona State University

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Abstract

KEY WORDS: Adolescent depression, behavioral health, primary care, guideline
implementation
INTRODUCTION: Despite depression affecting one of every ten adolescents, primary care
providers struggle to detect depression in affected individuals. Unmanaged early onset
adolescent mood disorders have an increased potential to result in suicide, the second leading
cause of death in adolescents. Referring all patients with a positive depression screen to a mental
health specialist creates treatment delay and burdens already limited community resources.
OBJECTIVE: The objective of this primary care practice transformation was to improve
pediatric primary care provider confidence and behavior to support and deliver evidence-based
behavioral healthcare for adolescents with mild to moderate depression.
METHODS: An evidence-based adolescent depression education program was delivered to
pediatric primary care providers in a small community setting. The program’s components
included measures to identify and manage mild to moderate depression. Outcome measures
included: 1) provider knowledge, beliefs, and confidence measured pre- and post-intervention;
and 2) electronic health record documentation of provider adherence to guideline
recommendations one, two, and three months post-intervention.
RESULTS: Four providers participated in the intervention. The mean total score for the provider
beliefs and knowledge from a 5-point Likert scale demonstrated a positive increase after the
intervention (14.75 vs. 23.25, p = .068). The mean total provider confidence score achieved near
significance as well (12.25 vs. 21.75, p = .066). Resultant behavior change in the providers did
not reach statistical significance when the electronic health records of all adolescent well visits
over a three-month period were assessed. Screening for depression at adolescent well visits

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increased from 0% to 84-90% post-intervention. Setting treatment goals upon detection of
depression increased from 0% to 41% (p = .089). Providers appropriately administered active
support 67% of the time when a patient was identified with mild depressive symptomology postintervention. Providers complied with guideline recommendations with identified cases of
moderate and severe depression (n = 2).
CONCLUSIONS: Pediatric primary care providers demonstrated some positive behavioral
changes towards integrating behavioral healthcare into their practice after an educational session
on the guidelines for adolescent depression.

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Adolescent Depression: Integrating Behavioral Healthcare in a Pediatric Primary Care Setting
Adolescent mental health care is a challenge for many pediatric primary care providers
(PCPs). PCPs struggle to detect and diagnose adolescent depression (AD), leaving as many as
50-66% of these individuals without diagnosis or management. Of those diagnosed, only about
50% are appropriately treated (Wren, Foy, & Ibeziako, 2012; Zuckerbrot, Cheung, Jensen, Stein,
& Laraque, 2007). Resources are limited, and only 63% of counties in the United States (US)
have one or more mental health facilities that provide outpatient mental health treatment for
children and adolescents (Cummings, Wen, Druss, 2013). Even in commercially insured
adolescents with a positive depression screening, as few as 18% of those referred to a mental
health professional may attain a face-to-face appointment within 180 days (Hacker et al., 2014).
Background and Significance
A major depressive episode (MDE) affects approximately 11% of adolescents between
the ages of 12-17 (National Institute of Mental Health [NIMH], 2014; Substance Abuse and
Mental Health Administration [SAMHA], 2015). The twelve-month prevalence rate of major
depression is estimated to be 2.8 million adolescents in the US (NIMH, 2014). Approximately
three times as many females report depressive symptomology at rates of 12-16% versus 4-5% for
males (SAMHA, 2015). The rates of AD are highest between the ages of 15-17 years, which
corresponds to rates of 13.2-13.8% of the total adolescent population (NIMH, 2014). Major
depressive disorder (MDD) is characterized by a significant impairment in functioning for at
least two weeks with a depressed mood or loss of interest in pleasure in life activities (American
Psychiatric Association [APA], 2013). Adolescents with mental health disorders are more likely
to engage in early sexual activity and drug and alcohol use (Burnett-Zeiglar et al., 2012).
Additionally, they report poorer grades in school and poorer self-rated health status with

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increased use of emergency services (Burnett-Zeiglar et al., 2012). MDD can have hindering
long-term implications, as depression is considered the second leading cause of years lived with
disability worldwide (Ferrari et al., 2013). Considering the economic burden of adults with MDD
which is estimated to be $210.5 billion in 2010 in the US (Greenberg, Fournier, Sisitsky, Pike, &
Kessler, 2015), successful treatment outcomes of adolescent depression demonstrate significant
value. Additionally, integrated behavioral and medical care alleviates some of the burden and
expense of referrals to specialist care. Finally, depression places an adolescent at an increased
risk of suicide, which is the third leading cause of death in young adults (Forman-Hoffman et al.,
2016; Wren et al., 2012). Ultimately, early depression recognition and management may play a
role in preventing the desperation that leads to suicide (Neves & Leanza, 2014).
Exhaustive Search Strategy
An exhaustive literature search was employed to answer the clinically relevant PICO
question, “In adolescents ages 11-18 with a positive depression screening at a primary care visit,
how does early treatment using integrated mental healthcare in the primary care setting
compared to usual care affect their outcomes on a follow up depression screening?” The
Cochrane Database of Systematic Reviews, PubMed, PyscINFO, and CINAHL databases were
utilized for the search using the following similar search terms: adolescent depression, primary
care, youth depression, child depression, primary care management, early management, early
intervention, early recognition, integrated behavioral-medical care, integrated care,
collaborative care, active support, active monitoring, usual care, referral, selective serotonin
reuptake inhibitor, and outcomes. Limits were applied to include evidence from 2010 to present,
peer reviewed articles, clinical trials, systematic reviews, and meta-analyses. The final numbers
of reviewed evidence from each database are as follows: Cochrane Database of Systematic

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Reviews (38), PubMed (37), PsycINFO (34), and CINAHL (74). Additionally, the National
Guideline Clearinghouse was searched using the term adolescent depression (AD) with a yield of
99 results. Manual review produced one additional guideline for consideration.
Critical Appraisal and Synthesis
The ten studies included for evidence synthesis were selected based on critical evaluation
for relevance and quality. The evidence synthesis included five systematic reviews (SRs)
(Chueng et al., 2007; Dolle & Schulte-Körne, 2013; Foreman-Hoffman et al., 2016; McDermott
et al., 2011; Zuckerbrot et al., 2007), three meta-analyses (MAs) (Cox et al., 2014; Ma et al,
2014; Richardson et al, 2014), one randomized control trial (RCT) (Asarnow et al., 2015), and
one case-control cohort study (CCC) (Wells et al., 2012).
The results of the critical appraisal of the selected studies revealed that active support
should be considered as first-line treatment for mild depression with follow-up at 1-2 week
intervals (Chueng et al., 2007; Dolle & Schulte-Körne, 2013; Foreman-Hoffman et al., 2016;
McDermott et al., 2011; Zuckerbrot et al., 2007). Cognitive Behavioral Therapy (CBT) should be
first-line therapy for moderate MDD (Dolle & Schulte-Körne, 2013; McDermott et al., 2011);
however, selective serotonin reuptake inhibitor (SSRI) or combination therapy of SSRI and
psychotherapy also may be considered first-line therapy (Chueng et al., 2007; Foreman-Hoffman
et al., 2016). While one MA, including 21 RCTs, considered Fluoxetine superior to CBT alone
(Ma et al., 2014), another MA, including 11 RCTs, did not reach the same conclusion (Cox et al.,
2014). However, both MAs concluded that combination treatment for best for efficacy and
safety. A CCC, RCT, and MA all demonstrated both statistical and clinical significance to
support the integration of mental health into PC through guideline-based care and collaboration
(Asarnow et al., 2015; Richardson et al., 2014; Wells et al., 2012).

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Purpose

The purpose of this Doctor of Nursing Practice (DNP) project was to positively impact
pediatric primary care provider confidence and behavior to support the integration of guidelinebased mental healthcare into their practice for adolescents with depressive symptomology who
screen positive for depression in the primary care setting. This practice change supports earlier
intervention and evidence-based care for patients who are identified with AD in PC.
Model and Framework
In order to guide project execution, an evidence-implementation framework suitable for
modest-sized practice was selected. The Promoting Action on Research Implementation in
Health Services (PARIHS) framework includes elements of evidence, context, and facilitation
(Rycroft-Malone, 2004). Best achievement of evidence-based practice occurs when those
elements are functioning at the highest end of their spectrums. Implementation of this framework
included appraised research, transformational leadership, empowerment of staff and families,
adult learning approaches, and assignment of meaning to practice change.
In order to promote provider confidence and, ultimately, encourage practice change to
incorporate depression screening and treatment into primary care, Bandura’s Social Cognitive
Theory (SCT) guided the project (Bandura, 1986). SCT posits that environment, personal, and
behavioral factors interplay and impact future behavior; therefore, success is more likely if
individuals are able to regulate their own motivation and behavior (Bandura, 1986). In order to
support this project, alternative practice habits and decision support was built into the electronic
health record (EHR), which assigned value to depression care in each healthcare provider’s
personal delivery of healthcare. This decision support was instituted in order to promote
sustainable change.

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Methods

Approval for the project was obtained from the Arizona State University Institutional
Review Board. A small pediatric primary care office with five pediatric providers in a major
metropolitan area in the Southwestern US was actively seeking improvement in their care for
adolescents with depression and agreed to participate in the project. The project intervention
included provider education as well as the development of a clinical decision-making support
tool. Provider education encompassed screening, diagnosis, and initial management of mild to
moderate AD. The education provided foundational knowledge concerning active support and
monitoring, medication dosage/indications/side effects, and a process for direct referral for
patients to receive services such as CBT from a mental health provider. An algorithm describing
the interventions for patients who scored positively on the screening tool (Patient Health
Questionnaire-9) was built into the EHR to provide decision support for the providers in the
practice. The algorithm included information for all patients with depression symptoms as well
as for each level of depression documented (i.e., mild, moderate, and severe). However, the
providers were not obligated to use this tool and could easily choose to continue to document as
they did pre-intervention.
Outcome Measures
Provider knowledge, beliefs, and confidence. One outcome measure for this project
included provider knowledge, beliefs, and confidence, which was measured pre- and postintervention. In order to assess provider knowledge, beliefs, and confidence, a 5-point Likert
scale tool was created with the assistance of a field expert after an extensive review of the
literature demonstrated no existing tool had been developed to capture this information. The
assessment tool included seven questions each on both knowledge and confidence in relation to

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guideline-based care for adolescent depression. This outcome was measured pre-intervention and
one week post-intervention.
Behavior change. The second outcome assessed for behavior change following the
intervention using electronic health record (EHR) documentation of provider adherence to
guideline recommendations one, two, and three months post-intervention. To assess for the
provider adherence to the guidelines over the course of three months post-intervention, all well
child visits were assessed in the EHR from 9/1/2016 to 12/1/2016 to capture all screening
attempts for AD. A tool was created with a field expert and included an assessment of the exact
guideline recommendations for each level of depression. Data from the previous year regarding
the well visits (9/1/2015 to 12/1/2015) was collected for comparative analysis.
Statistical Tests
In order to assess for a difference in the mean total score from the provider surveys, a
Wilcoxon Signed-Rank Test was used. EHR data was analyzed using frequencies and crosstabulation. When it was appropriate, a Fisher exact test was used to assess for statistically
significant differences between the two independent samples in basic depression intervention for
any level of depression pre-intervention and post-intervention.
Results
Provider Knowledge, Confidence, and Beliefs
A total of four providers participated in the intervention. Provider experience as a
pediatric healthcare provider ranged from 2 to 24 years. The mean total score for the provider
beliefs and knowledge demonstrated a positive increase after the intervention (14.75 vs. 23.25, p
= .068). The mean total provider confidence score also improved, but did not attain statistical
significance (12.25 vs. 21.75, p = .066). While statistical significance was not achieved with such

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a small sample size, the positive change in the mean total scores reflects encouraging clinical
significance.
Behavior Change in Providers
A total of 237 charts were reviewed to assess for depression screening and intervention at
well visits. A total of 90 charts comprised the pre-intervention data collection while the
remaining 147 charts reviewed comprised post-intervention data collection. In the pediatric
primary care practice, screening for depression in the practice for adolescents 11 to 17 years of
age increased significantly from 0% at pre-intervention to 88%, 90%, and 84% at one, two, and
three months post-intervention, respectively. During the project, it was determined that
adolescents attended well visits with decreasing frequency as they became older; 21.9% of the
well visits were 11 year olds with a steady decline in percentage to 9.3% noted at 17 years of
age. Of the EHR reviewed well visits, females composed a higher percentage of visits at 56.5%.
In this patient population, adolescents were supported by private insurance 68.8% of the visits
while 29.5% had Medicaid or public insurance.
In the pre-intervention data (n = 90 charts), depression was listed on the problem list of
eight adolescents. Post-intervention (n = 147 charts) screening for adolescent depression using
the PHQ-9 identified nine adolescents (6.1%) with mild depression, one adolescent (0.68%) with
moderate depression, and one adolescent (0.68%) with severe depression. Three (2%) of the
adolescents who screened positive post-intervention already had the diagnosis of depression
listed on their problem list from a prior office visit. There were a total of twelve adolescents with
documented depression in the post-intervention EHR chart review data collection. Screening did
not seem to impact the level of depression detected in this patient population, as depression had

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been identified in 8.8% of the individuals pre-intervention and 8.1% of the individuals postintervention.
Application of basic AD guideline recommendations for all levels of depression did not
demonstrate statistical significance in the analyses of the providers’ documentation as noted on
EHR data collection at one, two, or three months post-intervention. However, setting treatment
goals with depressed adolescents neared statistical significance (p = .089). The results of a Fisher
exact test indicate that providers discussed the limits of confidentiality more post-intervention (n
= 2) versus pre-intervention (n = 0) (p = .385). Treatment goals were set at a higher rate postintervention (n = 5) than pre-intervention (n = 0) (p = .089). Assessment of personal strengths
occurred more often after the intervention (3 versus 0 occasions, p = .237). Review of some type
of depressive symptomology occurred on seven occasions post-intervention and four times preintervention (p = .590). Discussion of thoughts of harm to self or others or creation of a safety
plan occurred only six times post-intervention and four times pre-intervention (p = .568).
Nine adolescents were identified with mild depression in the post-intervention data. Of
these nine adolescents, two received no guideline-based intervention for mild depression from
the PCP. Active support was documented for 67% of the adolescents with mild depression (n =
6). Weekly or bi-weekly follow-up was recommended only 22% of the time (n = 2).
Additionally, counseling was recommended for 22% of the adolescents with mild depression (n
= 2). For the one adolescent identified as moderately depressed, the provider complied with the
appropriate recommendations of setting treatment goals, reviewing depressive symptomology,
creating a safety plan, and discussing and initiating an appropriate evidence-based interventions
for moderate depression. For the adolescent identified as severely depressed, the provider

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appropriately assessed for self-harm, created a safety plan, and immediately referred the patient
to a mental health specialist in a proper timeframe.
Discussion
While the practice transformation DNP project did not have statistical significance on any
measured outcome, many barriers and influencing factors in the design and delivery of the
project were identified. One of the providers who participated in the intervention left the practice
two weeks after the intervention was delivered. Two providers employed by the practice over the
course of EHR data collection did not attend the intervention session due to illness or
employment initiation after the intervention delivery. In consideration of the small sample size,
no identifying measures were obtained on any provider in order to maintain participant
confidentiality. This consideration impacts the chart review data as two providers did not receive
the intervention yet are still included in the post-intervention chart review. Of those that the
providers serve, privately insured children are a high percentage of the patient population.
Additionally, well visits for adolescents 11-14 years of age composed 73% of the EHR data at
this practice, while the national data demonstrates that the occurrence of AD is highest in
individuals 15-17 years of age (NIMH, 2014). Adolescents who received well care during the
data collection period of the project that could not be screened due to documented barriers (e.g.,
blindness, severe mental or behavioral issues) were included in the EHR data collection and
analysis to remain compliant with the IRB-approved protocol. Finally, documentation of
measures provided in a visit may not always be complete. Guideline recommendations that may
have been followed may not be documented as instructed in the educational intervention. Based
on the wording of the documentation in the chart reviews, it became apparent that some
providers chose not to use the algorithm and documentation tool built into the EHR.

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The results of the project demonstrate that provider behavior change can be difficult to
obtain when instituting new practice measures because providers need to adapt to a higher
workload, increase their knowledge of depression and treatment, and develop new behavioral
skills. Because there was no identifying provider data obtained, the results are impacted to an
unknown extent secondary to two providers not receiving the educational intervention before
implementation. However, it is important to note that both patients with moderate and severe
levels of depression screened and identified post-intervention received appropriate guidelinebased care. Although the project focus was to increase the rates of PC management of mild to
moderate depression, the results of the DNP project indicated that many of the adolescents with
mild depression did not receive full guideline-based recommended care post-implementation.
Nevertheless, the initiation of active support in 67% of the cases of mild depression is a
clinically significant advancement in integrating behavioral healthcare in this pediatric PC
setting.
In this DNP project, screening identified additional adolescents with depression postintervention that did not have previously documented depression in their medical history. The
total percentage of adolescents identified with depression pre- to post-intervention remained the
same (8% versus 8%). It is difficult to ascertain whether adolescents with a positive depression
screening would have been identified in another way at some point regardless of the
implementation of this practice change of routinely screening for depression.
Significance and Impact
The objective of the practice transformation was to support providers’ knowledge and
confidence to integrate higher levels of evidence-based mental healthcare into their practice. In
one particular witnessed case during the course of the project, the knowledge of the guidelines

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empowered a provider to successfully manage an adolescent who failed outside treatment
through the use of medication and active support measures in the PC setting. After the
intervention, PCPs had the tools they needed to practice to their fullest scope in screening and
managing mild to moderate adolescent depression. Long term, this might help alleviate the
burden of referrals to mental health specialists in the community and enable those adolescents
struggling with more severe mental or behavioral issues to see the specialist sooner. The clinical
decision support tool built into the EHR supports project sustainability and encourages PCPs at
this practice to provide evidence-based behavioral healthcare for adolescents screening positive
for depression. Ultimately, to some extent, this DNP project increased comprehensive care in the
PC setting for adolescents.
Implications and Conclusion
Improving providers’ knowledge, confidence and beliefs about their ability to assess and
manage AD according to current guidelines can have a positive impact on practice and behavior
change. In future practice transformations, it would be helpful to create a protocol to establish a
follow-up office visit for a positive depression screen in addition to addressing the concern in the
well visit. Additionally, future practice improvement projects should examine how a depression
screening intervention for healthcare providers can simplify practice for providers, facilitating
sustainability, supporting engagement, and incentivizing participation.
If practice change occurs through the integration of behavioral healthcare into primary
care for adolescents with depression, there is potential for improved mental, physical, and social
health with early depression recognition and management (Richardson et al., 2014). Adolescent
behavioral healthcare suffers in light of the shortage of behavioral health specialist providers.
This shortage can be buffered through the inclusion of trained PCPs to use evidence-based

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treatment modalities to address depression (Cheung et al., 2007; Zuckerbrot et al., 2007). For the
PCPs, following guideline recommendations can expand their scope of practice to address a
diagnosis that is widely neglected, filling a significant gap in practice. For patients, the
implication of proper recognition and management of their depressive symptoms could lead to
improved physical health and school performance and decreased drug, alcohol, and early sexual
activity (Burnett-Zeiglar et al., 2012).

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