Running head: ACCESS TO HEALTHCARE

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Access to Healthcare Among Those Experiencing Homelessness: A depression Screening Project
Cinthia Arredondo Paramo BSN, RN
Arizona State University

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Abstract

Homeless individuals encounter barriers such as lack of health insurance, increased cost of care
and unavailability of resources. They have increased risk of comorbid physical disease and poor
mental health. Depression is a prevalent mental health disorder in the US linked to increased risk
of mortality. Literature suggests depression screening can identify high-risk individuals with
using the patient health questionnaire (PHQ-9). The objective of this project is to determine if
screening identifies depression in the homeless and how it impacts healthcare access. Setting is a
local organization in Phoenix offering shelter to homeless individuals. An evidence-based project
was implemented over two months in 2019 using convenience sampling. Intervention included
depression screening using the PHQ-9, referring to primary care and tracking appointment times.
IRB approval obtained from Arizona State University, privacy discussed, and consent obtained
prior to data collection. Participants were assigned a random number to protect privacy. A chart
audit tool was used to obtain sociodemographics and insurance status. Descriptive statistics used
and analyzed using Intellectus. Sample size was (n = 18), age (M = 35) most were White-nonHispanic, 44% had a high school diploma and 78% were insured. Mean score was 7.72, three
were previously diagnosed and not referred. Three were referred with a turnaround appointment
time of one, two and seven days respectively. No significant correlation found between age and
depression severity. A significant correlation found between previous diagnosis and depression
severity. Attention to PHQ-9 varied among providers and not always addressed. Future projects
should focus on improving collaboration between this facility and providers, increasing
screening and ensuring adequate follow up and treatment.
Keywords: Access to healthcare, homeless, depression, screening, PHQ-9

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Acknowledgements

The journey to obtaining a DNP has been full of challenges, discipline and perseverance.
I have grown personally and professionally, and I am grateful for all of you who helped me
throughout my journey. I would like to extend my sincere gratitude to all of you.
Arizona State University DNP faculty – Thank you for all of your hard work and efforts you
place on ensuring all of us get a valuable education and become well rounded nurse practitioners.
Dr. Charlotte Thrall – Thank you for your continued support, guidance and mentoring
throughout this program. Thank you for the learning opportunities you provided me as well as
the opportunity to get out of my comfort zone and give back to our community.
Dr. Nancy Denke – Thank you for being a great individual and for taking the time to
guide me, encourage me and provide me with learning opportunities to ensure my success in this
program. I am grateful to know and for all of your help.
Mom - Thank you for all of your encouragement and your support my entire life and the
past three years. You have taught me to be strong, courageous, independent and confident. I love
you and I am the person I am today because of your hard work and dedication.
Brother – Thank you for your support and encouragement throughout this program.
Thank you for listening to me, motivating me listening to my concerns. I am so lucky to be your
sister and I could have not done this without you. Love you!
Husband- Thank you for encouraging me to follow my dreams and being supportive
every step of the way. Thank you for keeping me sane and lifting my spirits this entire program. I
am grateful to have a loving, kind, husband like you by my side. Love you!

Thank you all!

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Access to Healthcare Among Those Experiencing Homelessness: A depression Screening Project
Homelessness has been recognized as a global phenomenon, affecting impoverished
populations in both developed and developing countries (Busch-Geertsema, Culhane &
Fitzpatrick, 2016). It can be described as an individual who is without a permanent, consistent,
and adequate residence, living in a shelter or place not designed for human habitation, including
those who are at imminent risk of housing loss and people escaping from domestic violence with
inadequate resources to obtain permanent housing (Baggett, 2018). These individuals are
affected by a variety of health disparities, limiting the amount and quality of health care services
they receive. Factors impacting health disparities include level of education, socioeconomic
status, health literacy, gender, race or ethnicity and geographic location. Access to essential
healthcare is an important aspect of everyday life and allows individuals to maintain health,
manage chronic conditions and prevent complications. Homelessness often leads to lack of
health insurance, decreased use of preventative health services, poor health outcomes and
increased disability and mortality.
Background and Significance
Individuals can experience homelessness in diverse forms, this could be transient,
intermittent or chronic. Initially considered to be primarily composed of men, the homeless
population today includes women, children and families (Katz, 2017). According to the United
States Department of Housing and Urban Development (HUD) (2019) 567,715 or 17 of out
every 10,000 individuals experienced homelessness in a single night in the year 2019. Seventy
percent were adults without children and 30% were individuals and their families (HUD, 2019).
Children comprised 19% or 107,069 individuals, eight percent were between 18 and 24 years of
age, and about 75% were over the age of 25 (HUD, 2019). Sixty one percent or 343,187 were

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men or boys, 39 % or 219,911 were women or girls, and less than one percent were transgender
(3,255) or gender non-conforming (1,362) (HUD, 2019).
HUD (2019) reports the total number of homeless individuals in the nation increased by
three percent or 14,885 individuals from the year 2018 and out of those 96,141 individuals
experienced chronic homelessness. The Arizona Department of Economic Security (DES) (2019)
reports in one single night there were 3,426 sheltered and 3,188 unsheltered individuals in
Maricopa county. There were 1,011 sheltered, 361 unsheltered individuals in Pima County and
1,039 sheltered and 983 unsheltered individuals in balance of state (BOS) or areas of Arizona
outside of the Maricopa and Pima counties (DES, 2019).
Problem Statement
Current literature demonstrates being homeless results from macro and micro-level
contributions (Barile, Pruitt & Parker, 2018). Macro-level influences include housing difficulties,
changes in social policy, reduction in public housing, income inequity, poverty and
unemployment (Barile et al., 2018). Micro-level influences include individual vulnerabilities
such as low income, dysfunctional family or changes in family dynamics, military veteran status,
increased debt, alcohol or substance abuse, lack of education, mental and physical disabilities
and lack of adequate social support (Barile et al., 2018).
A multidimensional approach must be applied to adequately treat the complex healthcare
needs of these individuals and reduce the associated morbidity and mortality of being homeless.
Primary care is thought to be essential healthcare that is practical, scientifically sound, includes
socially acceptable methods of technology, it is universally available and cost-effective to the
community and country (Campbell, O'Neill, Gibson & Thursto, 2015). Inadequate access to

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primary and preventative services leads to frequent misuse of emergency services and limited
continuing care for chronic disease and psychiatric illnesses for these vulnerable individuals.
Purpose and Rationale
Mental health encompasses emotional and psychological well-being and it is an
important part of being a healthy individual. Homelessness can leave an individual vulnerable to
mental and physical health problems, violence and substance abuse (Dai & Zhou, 2020).
Equally, evidence suggests that homelessness can be triggered or worsened by health issues,
particularly mental illness and learning disabilities (Dai & Zhou, 2020). Homeless individuals
experience health complications throughout their lifetime and thus seek medical services for a
variety of reasons. Unfortunately, access to quality healthcare is not always possible due to
compounding factors, most frequently lack of insurance coverage.
Depression is the most prevalent mental health disorder in the United States, with a
lifetime prevalence estimated to be 17% (Meyers, Groh, & Binienda, 2014). Approximately 17.3
million adults had at least one major depressive episode in the year 2017 (National Institute of
Mental Health, 2019). It is associated with high mortality and impaired ability to effectively
manage other chronic disease (Siu et al., 2016). The economic burden of depression in the
United States is estimated at $210 billion annually, and worldwide, depression is the leading
cause of disability (Schaeffer & Jolles, 2019). The goal of Healthy People 2020 (2019), is to
improve access to comprehensive, quality health services to promote and maintain health,
prevent and manage disease, reduce unnecessary disability and premature death, and achieve
health equity for all Americans. The purpose of this paper is to discuss vulnerable populations,
explore barriers to healthcare and determine how the utilization of valid and reliable screening
tools helps identify depression and impact on health and access to care.

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Epidemiological data
Being homeless is associated with poor health and premature mortality. Homeless
individuals are challenged with triple morbidity that encompasses physical illness, mental illness
and substance abuse leading to complications and complex healthcare needs (Elwell-Sutton,
Holland, Fok, Albanese & Mathie, 2017). These problems contribute to an increase in premature
mortality with an average life expectancy of 42 to 52 years of age (Bernstein, Meurer, Plumb &
Jackson, 2015). Additionally, deaths in this population are related to unintentional injuries,
suicide and homicide, mental disorders, communicable infectious disease and cardiovascular
disease (Slockers, Nusselder, Rietjens & Van Beeck, 2018). Furthermore, acute and chronic
respiratory, digestive and musculoskeletal disorders burden these individuals (Kaduszkiewicz,
Bochon, Van den Bussche, Hansmann-Wiest & Van der Leeden, 2017).
In addition to somatic complaints, they are also exposed to extreme heat, cold, poor diet
or insufficient food, and lack of personal hygiene leading to sustainability of infections and
parasitic infestations (Kaduszkiewicz et al., 2017). According to Kaduszkiewicz et al. (2017) of
the homeless individuals who accessed medical care, 75% had a mental disorder requiring
treatment and 74% had a concurrent substance induced disorder. However, their inability to
receive preventive health services or healthcare services in general leaves them vulnerable, and
to many of them the hospital becomes an important source of healthcare. They become
susceptible to unnecessary hospitalizations due to outpatient conditions that frequently go
unaddressed (White & Newman, 2015).
The high rates of acute care use including emergency room visits and inpatient
hospitalizations, has become a pattern seen in many countries and healthcare systems with and
without universal health insurance (Fazel, Geddes, & Kushel, 2014). Once admitted, these

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individuals are also responsible for longer hospitalizations of at least two days or more (Fazel,
Geddes, & Kushel, 2014). They are three times more likely to be admitted, and three times more
likely to stay hospitalized than the general population (Medcalf & Russell, 2014). Additionally,
individuals experiencing homelessness also have high readmission rates and longer
hospitalizations due to discharge delays (Shetler & Shepard, 2018). The consequences are
unforeseen secondary healthcare costs that are eight times higher than patients who are not
homeless (Medcalf & Russell, 2014).
A variety of interventions are presently being implemented to improve the access to
healthcare for vulnerable populations. A systematic review of interventions to improve access to
care listed the most common interventions as continuity of care via case management, formal
integration of services both medical and social, multidisciplinary clinical teams and institutional
incentives (Khanassov et al., 2016). Homeless individuals are faced with a diversity of social
determinants of health that impact their overall health. Social determinants of health are known
as conditions in which people are born, grow, live and interact on a daily basis. These include
education, race, ethnicity, sex, sexual orientation, and place of residence (Adler, Glymour &
Fielding, 2016). The incorporation of social determinants of health into clinical practice is also a
crucial approach to effectively manage the needs of vulnerable populations (O'Toole, Johnson,
Aiello, Kane & Pape, 2016).
Health screening is vital to maintain health and identify problems before they arise. It
allows health providers to assess an individual’s risk for the development of certain diseases.
Depression is a common and significant healthcare problem. The U.S. Preventive Services Task
Force (USPST) recommends routine screening for depression in the general adult population and
the development of adequate systems to ensure accurate diagnosis, treatment and follow up (Siu

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et al., 2016). Programs combining depression screening along with adequate support systems
improve clinical outcomes in adults and the prompt treatment of depression decreases clinical
morbidity (Siu et al., 2016).
Conclusion
Focus should be placed on improving the overall health of homeless individuals.
Emphasis needs to be placed on preventing communicable disease, adequate and continuing
treatment of mental health problems, substance abuse, chronic health conditions and increasing
preventative health screening. A multidimensional approach must be applied to adequately treat
these individuals and reduce morbidity and mortality associated with being homeless. Increasing
the availability of affordable primary care services is a desirable policy that would increase
primary care access (White & Newman, 2015). Additionally, health policy should focus on the
creation of primary care programs that are multidisciplinary and integrated with mental health
services, social and economic support, outreach strategies and focused on health promotion
(Jego, Abcaya, Ștefan, Calvet-Montredon & Gentile, 2018). Routine depression screening along
with collaborative approaches to interventions can help individuals be successful and healthy.
Internal evidence
A local non-profit organization located in the Phoenix metropolitan area, is dedicated to
help underserved individuals. Their goal is to provide Christ-centered programs and services to
help men, women, and children escape hunger and homelessness. This is possible through the
services provided, and their success is determined through recovered individuals and how well
they incorporate back into society with housing, jobs, and family reunification. This organization
is not a medical facility, therefore, their gap in care comes from the inability to provide medical
services directly to these individuals.

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On admission to this organization, individuals answer a short health questionnaire. There
is no comprehensive health screening, allowing individuals to potential go undiagnosed. They
are quickly assisted in applying for government medical assistance. However, once approved,
medical care is provided by a third-party mobile clinic once a week. When medical concerns
arise, they must notify a member of the team. This sponsor contacts the only social worker at this
facility who triages the concern and prioritizes individual’s medical needs. The social worker
does not have any official medical training which could lead to delays in care and negative
patient outcomes if triaged incorrectly, making this an important safety concern.
PICOT Question
This inquiry has led to the PICOT question: In homeless adults, “how does using a valid
and reliable tool to screen for depression compared to the usual screening questions affect the
identification of depression and referrals over a period of two months?”
Literature Review and Search Strategy
An exhaustive search of the literature was conducted using the following databases
PubMed, CINAHL and PsychInfo. The first search was conducted through PubMed using the
terms ‘depression’, ‘screening’, and ‘adults’. This search yielded 74,466 results. This search was
then modified to the following terms: ‘depression’, ‘screening’ and ‘homeless’ yielding a search
result of 175 potential articles. This search was further modified to include publications within
the last five years (2014-2019) and only list articles written in the English language. This final
search resulted in a total of 48 potential articles.
A second search was conducted through CINAHL using the terms ‘depression’,
‘screening’ and ‘homeless’. This initial search only produced 23 results with dates ranging from
2001 to 2019. The search was modified with the additional following terms: ‘depression’,

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‘screening tool’ and ‘adults’ which yielded 553 results. This search was once again modified to
include publications ranging between 2014 and 2019, include ‘all adults’, ‘males’ and ‘English’
yielding a total of 153 results. Grey literature within this search yielded four dissertations.
A third search was conducted through PsychINFO. This advanced search included the
terms ‘patient health questionnaire’, ‘depression’ and ‘screening’. This search yielded 100 results
with publication dates ranging from 1976 to 2019. The search was again modified to include
publications between January 1st, 2014 to January 1st, 2019 yielding 99 results. Search was
modified to include ‘adulthood’ and males yielding again 99 results. Within these results grey
literature included two books and two dissertations. Local and national organizational
publications and relevant academic books were reviewed.
Critical Appraisal and Synthesis of Evidence
The Melnyk and Fineout-Overholt’s (2011) rapid critical appraisal tool was used to
validate the quality and strength of evidence of a variety of research studies. Ten final studies
were used for this review. The purpose of the studies, research questions, inclusion and exclusion
criteria were clearly identified (Appendix A). The studies were high level evidence including one
level I, nine level II, four randomized-controlled trials, one retrospective, one prospective
repeated-measures and three cross-sectional designs (Appendix B). Most of the studies were
conducted in the United States, one in Vietnam, one in Israel, one in Australia and one in India
(Appendix B).
Nine of the studies included funding, however, no conflict of interest or bias was stated
or identified (Appendix A). Seven of the studies were conducted in primary care settings and
three were held in community centers such as homeless shelters and community health fairs
(Appendix B). Sample sizes were adequate and dependent and independent variables were

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clearly stated and understood (Appendix B). Many studies included an interdisciplinary,
collaborative approach by incorporating education, counseling, exercise and medication
treatment for depression (Appendix A). However, the main independent variable in all studies
was depression screening and five studies included an additional psychosocial education variable
(Appendix B).
Primary outcomes included identifying depression and monitoring depression severity
(Appendix B). There was a significant amount of homogeneity with eight of the studies utilizing
the Patient Health Questionnaire 9-item (PHQ-9) to screen and monitor depression (Appendix
B). One study utilized both the Beck Depression Inventory (BDI) and Hamilton Depression
Rating Scale (HAM-D), and one other study used the Center for Epidemiologic Studies
Depression Scale (CES-D) (Appendix B). Other variables such as anxiety, substance abuse
including alcohol, opioids and illicit drugs, cognitive impairment, suicidal ideation and attempts
and quality of life were screened with various instruments. These instruments included the
Generalized Anxiety Disorder 7-item (GAD-7), Mini-Mental State Examination (MMSE), Drug
Abuse Screening Test 10-item (DAST-10), Short Michigan Alcoholism Screening Test (SMAST
13) and General Self-Efficacy (GSE) scale (Appendix A).
Although there was a degree of heterogeneity in the demographic characteristics, they
were also homogenous. All studies included adults over the age of 18 without cognitive
impairment or severe mental health (Appendix A). Their age ranged from 18 to 87 years old with
mean age ranging from 41 to 61 (Appendix B). The majority of the studies included both men
and women with the exception of one that was 100% male (Appendix B). All samples included a
diverse population of insured, uninsured, low levels of education, as well as some degree of
education and different ethnic and racial backgrounds (Appendix A). Only three studies included

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homelessness as part of their demographic data and 100% of the participants in one study were
currently homeless (Appendix B).
Foundation of the Project
The evidence suggests the prevalence of depression is high among individuals from
various racial and ethnic groups, social, economic and cultural backgrounds, as wells across the
lifespan. It also suggests depression does not always present as a single problem but can be
accompanied by other conditions such as anxiety and substance abuse, ultimately impacting
overall health. Primary practice and community centers are important settings in unique
situations to screen and identify individuals at risk with the utilization of efficient, cost-effective
tools such as the PHQ-9 questionnaire. Once identified, numerous interventions such as
education, counseling, exercise and medication can be implemented. This, along with a
collaborative approach, significantly reduces depressive symptoms and improves health and
overall quality of life. Based on the evidence an evidence-based practice (EBP) project was
designed to change practice and answer clinical questions.
Theoretical Framework
The Theory of Unpleasant Symptoms (TOUS) was developed in 1990 and it was
designed to integrate current knowledge about symptoms and highlight the commonalities and
dimensions that have the potential to be useful in nursing practice and research (Smith & Liehr,
2014). The theory consists of three major concepts; symptoms, influencing factors and
performance outcomes (Smith & Liehr, 2014). Symptoms are defined as unpleasant, occurring
either in isolation or accompanied by other symptoms, and thus seen as the central part of the
theory. Because they are often perception-based, this theory respectively focuses on individually
perceived symptoms rather than observable signs (Smith & Liehr, 2014).

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Influencing factors are identified as physiological, psychological and situational.
Physiological factors include anatomical, genetic, illness-related and treatment related variables
(Smith & Liehr, 2014). Psychological factors are more complex include affective and cognitive
variables such as mood and emotional response to illness (Smith & Liehr, 2014). Lastly,
situational factors include an individual’s environment both social and physical including
background, access to resources such as financial, emotional and instrumental help with
symptom management (Smith & Liehr, 2014).
The final concept of performance represents the consequences of the symptoms. The
experience of symptoms has an impact on the individual’s ability to function physically,
cognitively and in socially defined roles (Smith & Liehr, 2014). Symptoms are often indicators
that an existing pathology is improving or worsening, and it is thought that the combination of
multiple factors can significantly impact the symptom experience (Smith & Liehr, 2014). This
theory has been identified as the theoretical framework for this project because homeless
individuals often experience a variety of symptoms in relation to their medical and mental health.
They are often deprived of necessary resources to reach and maintain good health and their
outcomes often depend on their perception of symptoms, other physical conditions,
psychological health and situational challenges (Appendix C).
Evidence-Based Practice Model
The Iowa model of evidenced-based practice has been chosen as guide to the
implementation of this EBP project (Appendix D). The model contains six steps. The steps of
this model include: identifying the problem; 2) determine its priority to organization; 3) search
for evidence; 4) critically analyze and synthesize the evidence, determine its adequacy if not
conduct another search; 5) develop and implement an EBP standard; 6) evaluate and disseminate

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results to implement change (Brown, 2014). For this EBP project, inadequate health screening
and access to healthcare have already been identified as being a problem. This has been
acknowledged as a high priority for the organization with a need for change. An exhaustive
search, critical analysis and synthesis of evidence has been performed. The next step is to
conduct an EBP project which consists of piloting a screening intervention for depression,
collecting and analyzing the data and disseminate the results, specifically for changing practice
evidence by the adoption of the intervention by this organization.
Methods
Ethical considerations and human subject protection
Privacy and confidentiality. Prior to the implementation of this project, approval from
Arizona State University’s Institutional Review Board (IRB) was obtained to ensure human
subjects protection. Privacy and confidentiality rights were discussed with each participant
during the implementation. A written consent that explained the purpose of the project and their
right to decline was given to each individual prior to data collection. A random number was
given to each individual document in order to de-identify data and protect personal privacy. No
data was collected on individuals who declined to participate, and an X was written on their
paperwork simply to track how many individuals declined. All documents were stored in a
locked cabinet in her office to ensure confidentiality and as part of her daily routine. A deidentified master list was collected and stored electronically, and password protected to ensure
adequate data collection.
Description of population and setting. Project is taking place at a local non-profit
organization located in the Phoenix metropolitan area. This organization has both men, women
and children shelters; however, this intervention is only taking place at the men’s facility. The

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population mainly consists of homeless men from various ethnicities including Caucasian,
African American, Native and Hispanic men between the ages of 18 and 73 years old.
Participants will include all men seeking shelter in this organization and advancing to the
Foundations program.
Project description. The project took place over a period of two months, early October
until the end of November 2019. Convenience sampling was used, and sample size was
dependent on the number of individuals admitted to the program.
Instrumentation, data collection and data analysis. In order to evaluate depression rate
and severity, the PHQ-9 (Appendix E) will be the tool used. It is an instrument that can be used
to screen, diagnose and monitor depression severity. It incorporates Diagnostic and Statistical
Manual of Mental Disorders (DSM-IV) diagnostic criteria for major depressive disorder and can
also grade severity of depressive symptoms (Kroenke, Spitzer & Williams, 2001). It is selfadministered and consists of nine questions rating symptoms on a four-point Likert scale,
indicating frequency of symptom over the past two weeks as (0 = not at all, 1 = several days, 2 =
more than half the days, 3 = nearly every day) for a total maximum score of 27 (Kroenke, Spitzer
& Williams, 2001). Suicidal ideation and duration is assessed for in item number nine, and
counts regardless of duration (Kroenke, Spitzer & Williams, 2001). No depression is suggested
with a score of zero to four, five to nine indicates mild depression, ten to 14 moderate
depression, 15 to 19 moderately severe depression, 20 to 27 indicates severe depression
(Kroenke, Spitzer & Williams, 2001).
The PHQ-9 has been validated as a screening test in a variety of studies including the
general population, primary care settings and other specific disease populations (Shin, Lee, Han,
Yoon, & Han, 2019). The diagnostic validity of the PHQ-9 was established in a study involving

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eight primary care and seven obstetrical clinics (Kroenke, Spitzer & Williams, 2001). Scores
greater than ten had a sensitivity of 88% and a specificity of 88% to detect Major Depressive
Disorder (Kroenke, Spitzer & Williams, 2001). Reliability and validity of the tool have indicated
it has rigorous psychometric properties with an internal consistency (α = 0.89) in the primary
care group and (α = 0.86) Ob-Gyn group (Kroenke, Spitzer & Williams, 2001). Test-retest
reliability was excellent with a correlation between the PHQ-9 completed by the patient in the
clinic and the one administered telephonically within 48 hours at r = 0.84 (Kroenke, Spitzer &
Williams, 2001).
Chart audits are used as methods of data collection for a variety of different studies
regarding incidence, prevalence, clinical course, prognosis of conditions and outcomes of health
services (Uttam et al., 2018). They are often utilized to answer clinical questions, determine
adherence to guidelines or standards of practice (Uttam et al., 2018). It has become a wellaccepted method and applied in a variety of healthcare disciplines such as epidemiology, quality
assessment, professional education, residency training, inpatient care, clinical research and serve
a variety of purposes (Uttam et al., 2018). Data can be individualized in various ways and
directly linked to the electronical medical health record, making them a valuable tool for clinical
practice.
For the purpose of this project, a chart audit form was used to gather pertinent
information to measure outcomes (Appendix F). This form collected important
sociodemographic information such as age, gender, ethnicity, level of education and whether the
individual is insured or uninsured. To identify the referral timeframe, the date of initial PHQ-9
screening, date when social worker received and submitted referral to primary care practice, date
of scheduled appointment and whether depression was diagnosed by primary care provider was

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collected. Data analysis was used using Intellectus and descriptive and inferential statistics
performed.
Budget and funding. No funding was required or utilized for this project. Total expected
budget was estimated at $24,487.04 (Appendix G). This included the preparation stage included
designing education material, consent forms, project outline costs as well as equipment needed
for that such as the computer. A room will need to be used to meet with the team and discuss
project details and individual roles. During the delivery stage, a room will need to be utilized to
conduct the depression screening process. It will also include other indirect costs such as general
office supplies required to fill out questionnaires and keep track of information. Other costs such
as the salaries individuals directly involved in the project include the social worker who will be
coordinating referrals and keeping track of resident progress, intake staff who will be delivering
project information, consent forms and PHQ-9 questionnaires, as well as student time who will
be continuously monitoring project progress.
Utilizing student’s own laptop for project development removed equipment cost.
Utilizing the organization’s current building and rooms will also allow for indirect cost savings.
Making changes to the social worker and intake team’s workflow and allowing them to
incorporate screening tools and referrals into their daily routine will help deduct additional salary
costs. DNP student will be donating her time to the development of this project and throughout
the stages of preparation, delivery and evaluation which will allow for further cost savings.
Potential sources of funding could include writing a grant to help with overall costs of supplies
and equipment. However, this organization is willing to donate their time and resources for the
development of this project and overall improvement of health for their residents. This yielded a
final estimated budget of $1,187.04 (Appendix H).

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Results

A total of 31 individuals were asked to participate in this project. Final sample size was
(N = 18) and 100% were male. The most frequently observed category of race/ethnicity was
White Non-Hispanic (n = 6, 33%), followed by Hispanic (n = 4, 22%), American Indian (n = 2,
11%), Asian/ Pacific Islander (n = 2, 11%), Black non-Hispanic (n = 1, 6%), Hispanic/Pacific
Islander (n = 1, 6%) and those who failed to answer that question (n = 2, 11%). The most
frequently observed category of level of education was high school diploma (n = 8, 44%). This
was followed by less than high school (n = 4, 22%), some college (n = 3, 17%), bachelor’s (n =
1, 6%). Two individuals failed to answer this question (n = 2, 11%). The most frequently
observed category of insured was Yes (n = 14, 78%) and No (n = 4, 22%). The participants age
had an average of 35.50 (SD = 11.39, SEM = 2.69, Min = 21.00, Max = 62.00, Skewness = 0.87,
Kurtosis = 0.22).
When analyzing the questions of the PHQ-9, the most frequently observed category of
question 1; little interest or pleasure in doing things was not at all (n = 9, 50%). The most
frequently observed category of question 2; feeling down, depressed, or hopeless was not at all
(n = 9, 50%). The most frequently observed categories for question 3; trouble falling or staying
asleep or sleeping too much were nearly every day, not at all, and several days, each with an
observed frequency of 6 (33%). The most frequently observed category for question 4; feeling
tired or having little energy was not at all (n = 9, 50%). The most frequently observed category
for question 5; poor appetite or overeating was not at all (n = 10, 56%).
The most frequently observed category for question 6; feeling bad about yourself was
more than half the days (n = 6, 33%). The most frequently observed category for question 7;
trouble concentrating on things was not at all (n = 9, 50%). The most frequently observed

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category for question 8; moving or speaking so slowly that people could have noticed, or the
opposite was not at all (n = 10, 56%). The most frequently observed category for question 9;
thoughts that you would be better off dead was not at all (n = 10, 56%). The most frequently
observed category for question 10; if you checked off any problems how difficult have these
problems made it for you to work, take care of things at home or get along with other people
was, not difficult at all (n = 12, 67%). The observations for total score was an average of 7.72
(SD = 4.69, SEM = 1.10, Min = 1.00, Max = 16.00, Skewness = 0.30, Kurtosis = -1.07).
The most frequently observed category of severity was mild (n = 7, 39%). This was
followed by none – minimal (n = 5, 28%), moderate (n = 4, 22%) and moderately severe (n = 2,
11%). A Spearman correlation analysis was conducted between previously diagnosed and
depression severity. The correlations were examined based on an alpha value of 0.05 (p = 0.05).
A significant positive correlation was observed between previously diagnosed and depression
severity (rs = 0.63, p = .005). The correlation coefficient between previously diagnosed and
depression severity was 0.63, indicating a large effect size. This correlation indicates that as
individuals are previously diagnosed, depression severity tends to be increased. A Pearson
correlation analysis was conducted between total score and age. Cohen's standard was used to
evaluate the strength of the relationship. The correlations were examined based on an alpha value
of 0.05 (p = 0.05). There were no significant correlations between any of the variables (rp = 0.05,
p = .843) (For full list of tables and figures, see Appendix I).
Project Impact
Patient. The implementation of this project successfully identified individuals at risk for
depression as well as those already suffering with depression. This resulted in a faster referral to
primary care to address mental and physical needs.

ACCESS TO HEALTHCARE

21

Provider. This project focused on increasing the screening at this facility and did not
follow any providers.
System. Allowed this organization to implement an intervention that led to identification
of individuals with depression. Consequently, they were able to promptly refer individuals to
primary care, leading to faster access to healthcare.
Policy. Currently there no policy to routinely screen for depression at this facility.
Project sustainability. This project utilizes the PHQ-9 which is a free tool that can be
utilized to screen and monitor depression. The intervention was purposely implemented so that it
would not create additional work for current staff or cost to the organization. Routine screening
for depression can be sustained by making it a part of the intake process as individuals are
admitted to the Foundations program. Combining depression referrals with routine medical
referrals could be an efficient way sustain this intervention.
Discussion
According to the results, most individuals presented with an average score indicative of
mild depression. Some participants presented with moderate and moderately severe depression
scores. This is clinically significant because recommendations for mild depression scores include
monitoring and follow up. For those individuals with higher depression scores, follow up and
treatment must be implemented to promote better health outcomes. There was a significant
correlation between a previous diagnosis of depression and depression severity. This is important
because it corroborates the validity of the PHQ-9 and the reasoning for utilizing it for the
purpose of this project. An additional analysis was done to determine if depression severity was
more prevalent based on age. The results did not find a significant correlation meaning that

ACCESS TO HEALTHCARE

22

depression severity does not vary across ages and addressing depression and its symptoms is
important for all individuals.
Limitations
This project included several limitations. One limitation of the study included working
with a small staff team of two individuals, thus limiting the number of potential participants and
referrals. Additionally, these two individuals do not have a medical background leading to lack
of understanding regarding depression, screening and other helpful interventions. In addition,
individuals were only screened and referred if proposed criteria were met, leaving out
opportunities to reach other high-risk individuals. For those who met criteria, once referred, the
attention to PHQ-9 varied among providers and physical complaints were often prioritized.
Access to healthcare was limited to one particular organization, eliminating potential
collaboration with other clinics and expanded access to care.
Recommendations
The findings of this project correlate with current literature and demonstrate that using
valid and reliable tools such as the PHQ-9 can be an effective tool to identify depression in
adults. The implementation of routine screening in the homeless population can help identify the
rate of individuals suffering this condition and lead to prompt referrals. This can lead to faster
access to healthcare, prompt treatment, improved mental and physical health leading to overall
well-being and functioning. Depression screening in homeless shelters presents a unique
opportunity to identify high risk individual and the data can be valuable to further explore the
needs of this particular population.
Currently, there is not enough evidence regarding depression screening and outcomes
specifically in the homeless population. This could be due to inability to reach individuals who

ACCESS TO HEALTHCARE

23

are not in homeless shelters. This project can be of significance in understanding how depression
impacts those individuals experiencing homelessness. Future projects should focus on improving
collaboration between this facility and healthcare providers, increasing the screening and
ensuring timely referrals and appropriate follow up for those with positive symptoms of
depression.

ACCESS TO HEALTHCARE

24
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Appendix A

Table 1
Evaluation Table
Citation
Niemi et al.
(2016).
Communitybased
intervention for
depression
management at
the primary care
level in Ha Nam
Province,
Vietnam: a
clusterrandomized
controlled trial
Funding:
Swedish
International

Conceptual
Framework
Inferred
cognitive
behavioral
model

Design/Method

Sample/Setting

Design: CRCS
from 6-2013 to
1-2014, pre and
post-test
interventions.
IG: 11
communes
CG: 10
communes
4 groups:
MND, MID,
MOD, SED
Inclusion: pts
17 years and
older at BLDH
with somatic or
psychological
complaints.
District had to
adequately

N:1951
n: 1401 IG
n: 550 CG
n: 25 excluded
based on
incomplete PHQ9. 1.3% attrition
rate.
Setting: 21 CHC,
1 district hospital.
Demographics:
49.1% Females,
13 (38.2%) in IG,
11 (50.0%) in
CG. 50.9%
Males, 21
(61.8%) in IG, 11
(50.0%) in CG.

Variables
Studied
IV1:
psychoeducati
on counseling
for healthcare
staff.
IV2: Yoga
training for
nurses and
physicians.
DV:
depression
severity
YC: 8-week
workshop, one
session per
week.

Measurement
of Variables
PHQ-9
MINDI- Given
to all
individuals
scoring MOD
or SED for
official
diagnosis
according to
the DSM-IV
criteria

Data
Analysis
Linear
regression,
Pearson
chi-squares,
independent
sample ttests, Mann–
Whitney U
test
p = 0.05

Findings

Decision for Use

76.6% MDN
19% MID 2.9%
MOD 0.2%
SED
IG: 20.5% DEP,
CG: 26% DEP,
34 MOD in IG,
22 MOD in CG,
MA of DEP
64.5 years (SD
12.63), MA of
NDP 60.3 (SD
14.67),
DIA between
depressed and
NDP p < 0.001
IV2: Difference
of DEP between
IG and CG
P = 0.013

LOE: Level I
Strengths: PHQ-9
administered as an interview
in case individual was
illiterate. Prompt referral for
severely depressed
individuals.
Weaknesses: weakness of
the randomization
procedure,
resulting in unequal
amounts of patients in the
intervention and control
groups. Does not examine
long-term effects of
intervention.
Harm feasibility:
Intervention was not

 - Cronbach’s alpha value; AI: American Indian/Alaska Native; ANOVA: Analysis of variance; BD: Bipolar disorder; BLDH: Binh Luc district hospital; CCM: Chronic care
model; CCO: clinical cut-off point; CES-D: Center for Epidemiologic Studies Depression; CG: control group; CH: Currently homeless; CHC: community health centers; COL:
College; CRCS: Cluster-randomized controlled superiority trial; DAST-10: Drug Abuse Screening Test 10-item; DEP: depression; DIA: difference in age; DIG: difference in
gender; DSM-IV: Diagnostic and statistical manual of mental disorders; DV: dependent variable; DX: diagnosed/diagnosis; EMP: employed; FMHX: Family history of mental
health issues; G1: usual care; G2: UC and psychotherapy; G3: UC and education; G4: UC, psychotherapy, and education; GAD-7; Generalized Anxiety Disorder 7-item; GSE:
General Self-Efficacy scale; HIS: Hispanic/Latino; HS: high school or less; HTN: hypertension; HX: history; IG: intervention group; IV: independent variable; Key: AA:
African Americans; LOE: level of evidence; M: mean; MA: mean age; MDC: Medicaid; MED: median; MID: mildly depressed score 5-9; MIL: Military issue; MINDI: MiniInternational Neuropsychiatric Diagnostic Interview; MMSE: Mini mental state exam; MND: minimally depressed score less than 4; MOD: moderately depressed score 10-19;
NC: income; NDMD: non-depressed/minimally depressed; NDMHC: Never discussed mental health concerns with professional; NDP: non-depressed patients; NI: No insurance;
p: significance; PDMHWP: Previously discussed mental health care concerns with a professional; PHQ-9: Patient health questionnaire 9 item; PI: Private insurance; PRIMEMD: Primary Care Evaluation of Mental Disorders; RPA: receiving public assistance; RRD: Red river delta geographical area SD: standard deviation; SED: severely depressed
score greater than 20; SI: suicidal ideation; SMAST 13: Short Michigan Alcoholism Screening Test; TX: treatment; UC: Usual care; UMD: unipolar major depression; UNE:
unemployed; Vet: Veteran; YC: yoga course.

ACCESS TO HEALTHCARE
Citation

Conceptual
Framework

Development
Cooperation
Agency.
Bias: none
recognized
Country:
Vietnam

Citation

Conceptual
Framework

31
Design/Method

Sample/Setting

represent RRD
and have a
psychiatric
hospital in area.
Exclusion:
psychotic, active
infection,
impaired
consciousness
or emergency
cases.
Purpose:
evaluate the
effectiveness of
a collaborative
communitybased
intervention
including
psychoeducation
and yoga for
depression
management in
primary care.
Design/Method

Age: 17- 96 M
age of 61.3 years
(SD 14.27)

Sample/Setting

Variables
Studied

Variables
Studied

Measurement
of Variables

Measurement
of Variables

Data
Analysis

Data
Analysis

Findings

Decision for Use

difference in
PHQ-9 scores
after the 8th
week between
IG and CG
p < 0.001
DIA p=0.49,
DIG p=0.10
Med PHQ-9
before and after
intervention
12.5 and 4 in IG
p<0.001, CG
score decreased
2 points.

harmful to any individuals,
results improved depression
scores.
PICOT applicability:
Study conducted in a
community setting and can
be applicable to other
populations. It shows good
reliability of PHQ-9
screening tool in identifying
and managing patients with
depression. Demonstrates
added interventions to
standard care promote better
outcomes of depressive
symptoms.

Findings

Decision for Use

Key: - Cronbach’s alpha value; AA: African Americans; AI: American Indian/Alaska Native; ANOVA: Analysis of variance; BD: Bipolar disorder; BLDH: Binh Luc hospital;
CCM: Chronic care model; CCO: clinical cut-off point; CES-D: Center for Epidemiologic Studies Depression; CG: control group; CH: Currently homeless; CHC: community
health centers; COL: College; CRCS: Cluster-randomized controlled superiority trial; DAST-10: Drug Abuse Screening Test 10-item; DEP: depression; DIA: difference in age;
DIG: difference in gender; DSM-IV: Diagnostic and statistical manual of mental disorders; DV: dependent variable; DX: diagnosed/diagnosis; EMP: employed; FMHX: Family
history of mental health issues; G1: usual care; G2: UC and psychotherapy; G3: UC and education; G4: UC, psychotherapy, and education; GAD-7; Generalized Anxiety
Disorder 7-item; GSE: General Self-Efficacy scale; HIS: Hispanic/Latino; HS: high school or less; HTN: hypertension; HX: history; IG: intervention group; IV: independent
variable; LOE: level of evidence; M: mean; MA: mean age; MDC: Medicaid; MED: median; MID: mildly depressed score 5-9; MIL: Military issue; MINDI: Mini-International
Neuropsychiatric Diagnostic Interview; MMSE: Mini mental state exam; MND: minimally depressed score less than 4; MOD: moderately depressed score 10-19; NC: income;
NDMD: non-depressed/minimally depressed; NDMHC: Never discussed mental health concerns with professional; NDP: non-depressed patients; NI: No insurance; p:
significance; PDMHWP: Previously discussed mental health care concerns with a professional; PHQ-9: Patient health questionnaire 9 item; PI: Private insurance; PRIME-MD:
Primary Care Evaluation of Mental Disorders; RPA: receiving public assistance; RRD: Red river delta geographical area SD: standard deviation; SED: severely depressed score
greater than 20; SI: suicidal ideation; SMAST 13: Short Michigan Alcoholism Screening Test; TX: treatment; UC: Usual care; UMD: unipolar major depression; UNE:
unemployed; Vet: Veteran; YC: yoga course.

ACCESS TO HEALTHCARE
Citation
Opperman et al.
(2017).
Depression
screening at a
community
health fair:
Descriptives and
treatment
linkage.
Funding: none
identified
Bias: none
stated or
identified
Country:
United States

Conceptual
Framework
Inferred
chronic care
model

32
Design/Method

Sample/Setting

Design:
retrospective
study
Inclusion: all
men in a
community
health fair
Exclusion: none
Purpose:
Explore
demographic
and depressive
symptom
associations with
participants, and
examine rates of
immediate
treatment
linkage with an
on-site clinician,
as well as
treatment
linkage to
follow-up
mental health
services.

N=261
Setting:
Men’s health fair
in a large city.
Demographics:
Males, 18-87
years of age,
M=51.23;
SD=13.18
n = 65 Caucasians
24.9%,
n = 169 AA
64.8%, n =1,
0.4% AI, n = 8,
3.1% Asian, n =
3, 1.1% other, n =
9, 3.4% mixed
HIS: n =6, 2.3%
Vet n = 47,
18.0%, NI n = 85,
32.6%, PI n =
118, 45.2%,
MDC n = 27,
10.3%, MIL n =
9, 3.4%, CH n =
14, 5.4%,

Variables
Studied
IV =
depression
screening,
DV=
depression

Measurement
of Variables
12-item
demographic
questionnaire
PHQ-9 (α=
0.87)

Data
Analysis
One-way
ANOVA,
Independent
groups ttests, chi
square

Findings

Decision for Use

n: 67 CCO 10
indicating
MOD, n=27
NDMHC, n: 24
met with
psychiatric
nurse, n=194
below CCO of
10. One-way
ANOVA no
significant
differences
between
demographic
variables and
depressive
symptoms.
CH p=0.02,
RPA p<0.001,
PDMHWP
p<0.001,
FMHX p<0.001
self-reported
greater severity
of depressive
symptoms

LOE: Level II
Strengths: Adequate
screening, onsite psychiatric
nurse, encouraged mental
health follow up.
Weaknesses: Patients did
not follow up with mental
health after six months.
Lack of control group. Low
applicability due to specific
low-income sample.
Harm feasibility:
individuals were not harmed
by the intervention, it was
non-invasive.
PICOT applicability:
Sample was representative
of low income, uninsured
ethnic groups and applicable
to selected population.

Key: - Cronbach’s alpha value; AA: African Americans; AI: American Indian/Alaska Native; ANOVA: Analysis of variance; BD: Bipolar disorder; BLDH: Binh Luc hospital;
CCM: Chronic care model; CCO: clinical cut-off point; CES-D: Center for Epidemiologic Studies Depression; CG: control group; CH: Currently homeless; CHC: community
health centers; COL: College; CRCS: Cluster-randomized controlled superiority trial; DAST-10: Drug Abuse Screening Test 10-item; DEP: depression; DIA: difference in age;
DIG: difference in gender; DSM-IV: Diagnostic and statistical manual of mental disorders; DV: dependent variable; DX: diagnosed/diagnosis; EMP: employed; FMHX: Family
history of mental health issues; G1: usual care; G2: UC and psychotherapy; G3: UC and education; G4: UC, psychotherapy, and education; GAD-7; Generalized Anxiety
Disorder 7-item; GSE: General Self-Efficacy scale; HIS: Hispanic/Latino; HS: high school or less; HTN: hypertension; HX: history; IG: intervention group; IV: independent
variable; LOE: level of evidence; M: mean; MA: mean age; MDC: Medicaid; MED: median; MID: mildly depressed score 5-9; MIL: Military issue; MINDI: Mini-International
Neuropsychiatric Diagnostic Interview; MMSE: Mini mental state exam; MND: minimally depressed score less than 4; MOD: moderately depressed score 10-19; NC: income;
NDMD: non-depressed/minimally depressed; NDMHC: Never discussed mental health concerns with professional; NDP: non-depressed patients; NI: No insurance; p:
significance; PDMHWP: Previously discussed mental health care concerns with a professional; PHQ-9: Patient health questionnaire 9 item; PI: Private insurance; PRIME-MD:
Primary Care Evaluation of Mental Disorders; RPA: receiving public assistance; RRD: Red river delta geographical area SD: standard deviation; SED: severely depressed score
greater than 20; SI: suicidal ideation; SMAST 13: Short Michigan Alcoholism Screening Test; TX: treatment; UC: Usual care; UMD: unipolar major depression; UNE:
unemployed; Vet: Veteran; YC: yoga course.

ACCESS TO HEALTHCARE
Citation

Citation
Meyers et al.
(2014).
Depression
screening and
treatment in
uninsured urban
patients

Conceptual
Framework

Conceptual
Framework
Inferred
Chronic Care
Model

33
Design/Method

Sample/Setting

Design/Method

NDMHC n = 163,
62.5%,
FMHX n = 95,
36.4%
Sample/Setting

Variables
Studied

Measurement
of Variables

Data
Analysis

Findings

Decision for Use

Variables
Studied
IV1:
Treatment
intervention
IV2: Time
DV: PHQ-9
depression
score

Measurement
of Variables
PRIME-MD
and PHQ-9

Data
Analysis
Test of
proportions,
repeatedmeasures
ANOVA, p
<0.05

Findings

Decision for Use

N: 674
N= 412 (61.1%) LOE: Level II
Design:
Prospective
n: 255 DEP
PHQ-9 score
repeatedn: 49 dropped
≥5, n = 255 dx
Strengths: Large sample
measures design, from study. 7.3%
with DEP.
size, PHQ-9 proved to be an
re-evaluated at
attrition.
IV2: All groups adequate tool to screen for
8,12 and 24
Setting: Primary
reduction in DV depression vs standard care.
weeks.
care clinic 8/2005
in 6 months
All groups regardless of
4 groups: G1,
to 8/2007 and
with mean score intervention had significant
G2, G3 and G4
2/2009 to 9/2010.
of 15 at
reduction in depressive
Funding:
partially funded
Demographics:
baseline to 8.3
symptoms after 24 weeks.
Inclusion:
by Blue Cross
patients
Age 18-64, n =
p<0.001. G2,
Blue Shield
previously
314 (31.8%) less
G2 and G4 did
Weaknesses: Study only
Foundation of
diagnosed with
than 45, 360
not show
followed short-term
Michigan
DEP and/or who (68.2%) greater
additional,
outcomes. Additional
were not
than 45.
significant
interventions such as
Bias: None
receiving any
n = 641 (95.1%)
reduction of
psychotherapy and
declared
form of
AA, n = 33
DV.
education were not
treatment for
(4.9%) other,
adequately measured. Not
DEP.
n = 448 (66.5%)
all patients took advantage
Country:
United States
F, n = 226
of free psychotherapy
Exclusion:
previously DX
(33.5%) male,
Key: - Cronbach’s alpha value; AA: African Americans; AI: American Indian/Alaska Native; ANOVA: Analysis of variance; BD: Bipolar disorder; BLDH: Binh Luc hospital;
CCM: Chronic care model; CCO: clinical cut-off point; CES-D: Center for Epidemiologic Studies Depression; CG: control group; CH: Currently homeless; CHC: community
health centers; COL: College; CRCS: Cluster-randomized controlled superiority trial; DAST-10: Drug Abuse Screening Test 10-item; DEP: depression; DIA: difference in age;
DIG: difference in gender; DSM-IV: Diagnostic and statistical manual of mental disorders; DV: dependent variable; DX: diagnosed/diagnosis; EMP: employed; FMHX: Family
history of mental health issues; G1: usual care; G2: UC and psychotherapy; G3: UC and education; G4: UC, psychotherapy, and education; GAD-7; Generalized Anxiety
Disorder 7-item; GSE: General Self-Efficacy scale; HIS: Hispanic/Latino; HS: high school or less; HTN: hypertension; HX: history; IG: intervention group; IV: independent
variable; LOE: level of evidence; M: mean; MA: mean age; MDC: Medicaid; MED: median; MID: mildly depressed score 5-9; MIL: Military issue; MINDI: Mini-International
Neuropsychiatric Diagnostic Interview; MMSE: Mini mental state exam; MND: minimally depressed score less than 4; MOD: moderately depressed score 10-19; NC: income;
NDMD: non-depressed/minimally depressed; NDMHC: Never discussed mental health concerns with professional; NDP: non-depressed patients; NI: No insurance; p:
significance; PDMHWP: Previously discussed mental health care concerns with a professional; PHQ-9: Patient health questionnaire 9 item; PI: Private insurance; PRIME-MD:
Primary Care Evaluation of Mental Disorders; RPA: receiving public assistance; RRD: Red river delta geographical area SD: standard deviation; SED: severely depressed score
greater than 20; SI: suicidal ideation; SMAST 13: Short Michigan Alcoholism Screening Test; TX: treatment; UC: Usual care; UMD: unipolar major depression; UNE:
unemployed; Vet: Veteran; YC: yoga course.

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Conceptual
Framework

34
Design/Method

Sample/Setting

with DEP and
receiving TX, hx
of mental illness
Purpose: To
determine if
formal screening
increases the
identification of
depression in
low-income
patients in
primary care
settings
determine if
identification
and treatment
lower depression
scores and to
determine the
most effective
depression
intervention for
low-income
patients in
primary care
settings

n = 432 (64%)
HS, n = 242
(35.9%) Col,
n = 594 (88.1%)
INC $20,000
n = 340 (50.4%)
UNE, n = 334
(49.6%) EMP.

Variables
Studied

Measurement
of Variables

Data
Analysis

Findings

Decision for Use
perhaps skewing the results.
No control group.
Harm feasibility:
individuals were not harmed
by the intervention, it was
non-invasive.
PICOT applicability: This
can be applicable to
homeless populations. PHQ9 is a reliable, cost-effective
tool for diagnosis of
depression in this
population. This study
shows the importance of
active screening and prompt
treatment to promote better
outcomes.

Key: - Cronbach’s alpha value; AA: African Americans; AI: American Indian/Alaska Native; ANOVA: Analysis of variance; BD: Bipolar disorder; BLDH: Binh Luc hospital;
CCM: Chronic care model; CCO: clinical cut-off point; CES-D: Center for Epidemiologic Studies Depression; CG: control group; CH: Currently homeless; CHC: community
health centers; COL: College; CRCS: Cluster-randomized controlled superiority trial; DAST-10: Drug Abuse Screening Test 10-item; DEP: depression; DIA: difference in age;
DIG: difference in gender; DSM-IV: Diagnostic and statistical manual of mental disorders; DV: dependent variable; DX: diagnosed/diagnosis; EMP: employed; FMHX: Family
history of mental health issues; G1: usual care; G2: UC and psychotherapy; G3: UC and education; G4: UC, psychotherapy, and education; GAD-7; Generalized Anxiety
Disorder 7-item; GSE: General Self-Efficacy scale; HIS: Hispanic/Latino; HS: high school or less; HTN: hypertension; HX: history; IG: intervention group; IV: independent
variable; LOE: level of evidence; M: mean; MA: mean age; MDC: Medicaid; MED: median; MID: mildly depressed score 5-9; MIL: Military issue; MINDI: Mini-International
Neuropsychiatric Diagnostic Interview; MMSE: Mini mental state exam; MND: minimally depressed score less than 4; MOD: moderately depressed score 10-19; NC: income;
NDMD: non-depressed/minimally depressed; NDMHC: Never discussed mental health concerns with professional; NDP: non-depressed patients; NI: No insurance; p:
significance; PDMHWP: Previously discussed mental health care concerns with a professional; PHQ-9: Patient health questionnaire 9 item; PI: Private insurance; PRIME-MD:
Primary Care Evaluation of Mental Disorders; RPA: receiving public assistance; RRD: Red river delta geographical area SD: standard deviation; SED: severely depressed score
greater than 20; SI: suicidal ideation; SMAST 13: Short Michigan Alcoholism Screening Test; TX: treatment; UC: Usual care; UMD: unipolar major depression; UNE:
unemployed; Vet: Veteran; YC: yoga course.

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Citation
Kilbourne et al.
(2019).
Randomized
controlled trial
of a
collaborative
care intervention
for mood
disorders by a
national
commercial
health plan.

Conceptual
Framework
Conceptual
Framework
Collaborative
Chronic Care
Model

35
Design/Method

Sample/Setting

Design/Method

Sample/Setting

Variables
Studied
Variables
Studied
IV:
Depression
symptoms
IV2: Mentalhealth quality
of life
CCM:
contacts and
psychosocial
intervention
(10 selfmanagement
sessions,
ongoing care
management).

Measurement
of Variables
Measurement
of Variables
Patient Health
Questionnaire
(PHQ-9), 12item ShortForm (SF-12)
Health-Related
Quality of
Life Survey

Data
Analysis
Data
Analysis
Mixed
effects
models,
multivariabl
e logistic
regression,
Cohen’s d,

Findings

Decision for Use

Findings

Decision for Use

Design: singleN: 238 n:115
N73: Final,
LOE: Level II
blind,
CCM, n:123 UC.
n:165 dropped
Strengths: Effective in
randomized
Setting: Primary
out 69%
reducing depressive
controlled trial.
care clinics and
attrition. Mean symptoms and improving
2 groups: CCM, remote care via
differences 27% health-related quality of life
PHQ-9
UC.
telephone calls.
for individuals with mood
(Cohen’s
disorders.
Inclusion:
Demographics:
d=.25), 19% for Weaknesses: Only a small
Aetna patients,
MA of 41.36
SF-12 MCS
21 and older,
31.1; were mostly
number of eligible patients
(Cohen’s
hospitalized 6
female (66%),
enrolled, possibly due to
d=.20).
months prior
white (81%), and
hesitance of a program
Adjusted mean
with UMD or
employed
offered by an insurer instead
PHQ-9 scores
BD (bipolar
(58%);
of care provider. Post
were lower by
Funding: New
manic or
randomization drop out was
2.34
Harbinger
depressed state)
great due to losing Aetna
points (95%
Publishing and
Exclusion: no
coverage. Case manager
confidence
Springer.
longer enrolled
was not present and unable
level
Bias: None
in Aetna health
to address pharmacotherapy
[CL]=24.18 to – concerns.
stated or
plan, deceased,
0.50, p=0.01),
identified.
or unable to
Harm Feasibility:
indicating
provide
Individuals were not
improved
informed
harmed; study was
Country:
symptoms, and
United States.
consent due to
noninvasive and promoted
mean SF-12
an unstable
better health outcomes.
mental health
condition,
Key: - Cronbach’s alpha value; AA: African Americans; AI: American Indian/Alaska Native; ANOVA: Analysis of variance; BD: Bipolar disorder; BLDH: Binh Luc hospital;
CCM: Chronic care model; CCO: clinical cut-off point; CES-D: Center for Epidemiologic Studies Depression; CG: control group; CH: Currently homeless; CHC: community
health centers; COL: College; CRCS: Cluster-randomized controlled superiority trial; DAST-10: Drug Abuse Screening Test 10-item; DEP: depression; DIA: difference in age;
DIG: difference in gender; DSM-IV: Diagnostic and statistical manual of mental disorders; DV: dependent variable; DX: diagnosed/diagnosis; EMP: employed; FMHX: Family
history of mental health issues; G1: usual care; G2: UC and psychotherapy; G3: UC and education; G4: UC, psychotherapy, and education; GAD-7; Generalized Anxiety
Disorder 7-item; GSE: General Self-Efficacy scale; HIS: Hispanic/Latino; HS: high school or less; HTN: hypertension; HX: history; IG: intervention group; IV: independent
variable; LOE: level of evidence; M: mean; MA: mean age; MDC: Medicaid; MED: median; MID: mildly depressed score 5-9; MIL: Military issue; MINDI: Mini-International
Neuropsychiatric Diagnostic Interview; MMSE: Mini mental state exam; MND: minimally depressed score less than 4; MOD: moderately depressed score 10-19; NC: income;
NDMD: non-depressed/minimally depressed; NDMHC: Never discussed mental health concerns with professional; NDP: non-depressed patients; NI: No insurance; p:
significance; PDMHWP: Previously discussed mental health care concerns with a professional; PHQ-9: Patient health questionnaire 9 item; PI: Private insurance; PRIME-MD:
Primary Care Evaluation of Mental Disorders; RPA: receiving public assistance; RRD: Red river delta geographical area SD: standard deviation; SED: severely depressed score
greater than 20; SI: suicidal ideation; SMAST 13: Short Michigan Alcoholism Screening Test; TX: treatment; UC: Usual care; UMD: unipolar major depression; UNE:
unemployed; Vet: Veteran; YC: yoga course.

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Citation

Conceptual
Framework

36
Design/Method

Sample/Setting

inpatient status,
or inability to
speak English.
Purpose: To
determine if a
CCM in a U.S.
health plan
improved 12month outcomes
among those
with mood
disorders
compared with
usual care.
Citation

Conceptual
Framework
Inferred
Cognitive
Behavioral
Model

Design/Method

Sample/Setting

Variables
Studied

Measurement
of Variables

Data
Analysis

Findings

Decision for Use

scores were
higher by 3.21
points (CL= –
.97 to 7.38,
p=0.10),
indicating better
quality of life,
among
participants
receiving CCM
versus usual
care.

PICOT applicability:
Study can be applicable to
homeless population
utilizing the same tool. It
shows the importance of
integrated collaborative care
and how it can be more
successful than standard
care alone for treatment of
depression and other mental
health problems. It showed
potential for cost-efficient
approach to providing
evidence-based care
remotely to patients.
Decision for Use

Variables
Measurement Data
Findings
Studied
of Variables
Analysis
2 questions:
Lee et al. (2017).
Design: CrossN: 156
DV: Measure
IBM SPSS,
41% had
LOE: Level II
Have you
Mental health,
sectional,
Setting: homeless the suicidal
univariate
suicidal
Strengths: Good sample
ever thought of descriptive
substance abuse,
purposive and
adults in 7
ideation and
thoughts and
size. Adequate
committing
and suicide
convenience
shelters in Kansas suicide
Statistics,
21.6%
randomization. Good
suicide? and (2) correlation
among homeless
sampling
attempts of
previously
information regarding the
Demographics:
Have you ever
adults.
Inclusion: Age
19 to 72 years if
homeless
matrix,
attempted
importance of mental health
attempted to
18 or over in
age with a
individuals.
logistic
suicide. Drug
in regard to anxiety,
commit
homeless
MA 41 years;
regression
abusers likely
depression and substance
Funding:
IV1:
suicide?
supported by the
shelters, willing
66% male, 61.9% Depressive
vs non-drug
abuse.
U.S. Agency for
to participate
of the respondents symptoms
abusers to have
Key: - Cronbach’s alpha value; AA: African Americans; AI: American Indian/Alaska Native; ANOVA: Analysis of variance; BD: Bipolar disorder; BLDH: Binh Luc hospital;
CCM: Chronic care model; CCO: clinical cut-off point; CES-D: Center for Epidemiologic Studies Depression; CG: control group; CH: Currently homeless; CHC: community
health centers; COL: College; CRCS: Cluster-randomized controlled superiority trial; DAST-10: Drug Abuse Screening Test 10-item; DEP: depression; DIA: difference in age;
DIG: difference in gender; DSM-IV: Diagnostic and statistical manual of mental disorders; DV: dependent variable; DX: diagnosed/diagnosis; EMP: employed; FMHX: Family
history of mental health issues; G1: usual care; G2: UC and psychotherapy; G3: UC and education; G4: UC, psychotherapy, and education; GAD-7; Generalized Anxiety
Disorder 7-item; GSE: General Self-Efficacy scale; HIS: Hispanic/Latino; HS: high school or less; HTN: hypertension; HX: history; IG: intervention group; IV: independent
variable; LOE: level of evidence; M: mean; MA: mean age; MDC: Medicaid; MED: median; MID: mildly depressed score 5-9; MIL: Military issue; MINDI: Mini-International
Neuropsychiatric Diagnostic Interview; MMSE: Mini mental state exam; MND: minimally depressed score less than 4; MOD: moderately depressed score 10-19; NC: income;
NDMD: non-depressed/minimally depressed; NDMHC: Never discussed mental health concerns with professional; NDP: non-depressed patients; NI: No insurance; p:
significance; PDMHWP: Previously discussed mental health care concerns with a professional; PHQ-9: Patient health questionnaire 9 item; PI: Private insurance; PRIME-MD:
Primary Care Evaluation of Mental Disorders; RPA: receiving public assistance; RRD: Red river delta geographical area SD: standard deviation; SED: severely depressed score
greater than 20; SI: suicidal ideation; SMAST 13: Short Michigan Alcoholism Screening Test; TX: treatment; UC: Usual care; UMD: unipolar major depression; UNE:
unemployed; Vet: Veteran; YC: yoga course.

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Healthcare
Research
and Quality
(AHRQ) (R18
HS 21425).
Bias: none
identified
Country:
United States

Conceptual
Framework

37
Design/Method

Sample/Setting

and no known
severe cognitive
impairment
Exclusion: no
exclusion
criteria
specified.
Purpose: To
explore the
roles of mental
health and
substance abuse
problems on
suicidal ideation
and suicide
attempts
among this
population

were Caucasian,
17.4% AA.
17.8% employed.
29.2%
sexual/physical
abuse.

Variables
Studied
IV2: anxiety
IV3: Drug
abuse
IV4: alcohol
abuse
IV5: sociopsychological
and
demographic
variable.

Measurement
of Variables
CES-D scale,
GAD-7,
DAST-10,
SMAST-13,

GSE

Data
Analysis

Findings

Decision for Use

SI (B = .217, p
≤ .05, Odds
Ratio = 1.243).
Anxiety were
more likely vs
non-anxiety to
have SI (B =
.153, p ≤ .05,
Odds Ratio =
1.165) and
suicide attempts
(B = .274, p ≤
.001, Odds
Ratio = 1.316).
Employed less
likely to have
SI (B = –1.734,
p ≤ .05, Odds
Ratio = .177).
Hx of sexual
abuse (B =

Weakness: use of nonprobability sampling. Did
not study long term effects
of the impact of mental
health problems and
substance abuse on suicidal
ideation and suicide
attempts among homeless
people.
Harm Feasibility:
Individuals were not
harmed; study was
noninvasive and promoted
better health outcomes.
PICOT applicability:
Study explores the
importance of screening for
depression in the homeless
population. It adequately
links depression and anxiety
with substance abuse and
socio-psychological effects
such as suicide ideation and
attempts.

1.288, p ≤ .05,
Odds Ratio =
3.626) and
suicide
attempts

Key: - Cronbach’s alpha value; AA: African Americans; AI: American Indian/Alaska Native; ANOVA: Analysis of variance; BD: Bipolar disorder; BLDH: Binh Luc hospital;
CCM: Chronic care model; CCO: clinical cut-off point; CES-D: Center for Epidemiologic Studies Depression; CG: control group; CH: Currently homeless; CHC: community
health centers; COL: College; CRCS: Cluster-randomized controlled superiority trial; DAST-10: Drug Abuse Screening Test 10-item; DEP: depression; DIA: difference in age;
DIG: difference in gender; DSM-IV: Diagnostic and statistical manual of mental disorders; DV: dependent variable; DX: diagnosed/diagnosis; EMP: employed; FMHX: Family
history of mental health issues; G1: usual care; G2: UC and psychotherapy; G3: UC and education; G4: UC, psychotherapy, and education; GAD-7; Generalized Anxiety
Disorder 7-item; GSE: General Self-Efficacy scale; HIS: Hispanic/Latino; HS: high school or less; HTN: hypertension; HX: history; IG: intervention group; IV: independent
variable; LOE: level of evidence; M: mean; MA: mean age; MDC: Medicaid; MED: median; MID: mildly depressed score 5-9; MIL: Military issue; MINDI: Mini-International
Neuropsychiatric Diagnostic Interview; MMSE: Mini mental state exam; MND: minimally depressed score less than 4; MOD: moderately depressed score 10-19; NC: income;
NDMD: non-depressed/minimally depressed; NDMHC: Never discussed mental health concerns with professional; NDP: non-depressed patients; NI: No insurance; p:
significance; PDMHWP: Previously discussed mental health care concerns with a professional; PHQ-9: Patient health questionnaire 9 item; PI: Private insurance; PRIME-MD:
Primary Care Evaluation of Mental Disorders; RPA: receiving public assistance; RRD: Red river delta geographical area SD: standard deviation; SED: severely depressed score
greater than 20; SI: suicidal ideation; SMAST 13: Short Michigan Alcoholism Screening Test; TX: treatment; UC: Usual care; UMD: unipolar major depression; UNE:
unemployed; Vet: Veteran; YC: yoga course.

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Conceptual
Framework

38
Design/Method

Sample/Setting

Variables
Studied

Measurement
of Variables

Data
Analysis

Findings

Decision for Use

(B=1.554, p ≤
.05, Odds
Ratio = 4.726).
Citation
McClintock et
al. (2017).
Incorporating
patients’ social
determinants of
health into
hypertension and
depression care:
A pilot
randomized
controlled trial.
Funding:
Agency for
Healthcare
Research and
Quality (Grant
No. K18 HS23445).

Conceptual
Framework
Inferred
Chronic Care
Model

Design/Method

Sample/Setting

Design:
two phases: a 2week run-in
phase and a
randomized
controlled trial
phase.
Inclusion:18
and older,
diagnosis of
HTN and, a
current
prescription
for an
antihypertensive.
Exclusion:
Inability to give
informed
consent,
significant
cognitive

N: 54
N:1 person
dropped
Setting: three
primary care
practices
Demographics:
MA 60, Basic
intervention AA
13 (52%),
Caucasian 9
(12%), depression
SD 6.3. Enhanced
intervention AA
19 (65.5%),
Caucasian 7
(24.1%),
depression SD 6.9

Variables
Studied
DV1: Blood
pressure
DV2:
Depressive
symptoms
IV1:
Enhanced
interventionBasic plus PPP
IV2: Basic
interventionindividualized
program to
improve
adherence to
antihypertensi
ves and
integration of
depression
treatment

Measurement
of Variables
Electronic
monitor, PHQ9, MMSE

Data
Analysis
t test and
Fisher’s
exact test,
variance–
covariance
matrix,
standard
deviation.

Findings

Decision for Use

1V1:
significantly
improved
systolic and
diastolic BP
mean from
baseline
vs pts in IV2
12 weeks (IV1:
−11.96 vs. IV2:
6.08; p =
0.003), (IV1:
−4.79 vs. IV2:
4.12; p =
0.019). IV1:
significantly
improved PHQ9 from baseline
vs IV2 at 12
weeks (IV1:
−2.75 vs. IV2

LOE: Level II
Strengths: Randomized.
Effectively explored social
determinants of health into
HTN and depression
management.
Weaknesses: Sample may
not be truly representative
due to only including three
primary care clinics. Small
sample size.
Harm Feasibility: Study
was non-invasive, no
individuals were harmed
during this study.
PICOT Applicability:
Homeless individuals
struggle with a variety of
social difficulties. Not many

Bias: The
authors deny any
conflict of
interest.
Key: - Cronbach’s alpha value; AA: African Americans; AI: American Indian/Alaska Native; ANOVA: Analysis of variance; BD: Bipolar disorder; BLDH: Binh Luc hospital;
CCM: Chronic care model; CCO: clinical cut-off point; CES-D: Center for Epidemiologic Studies Depression; CG: control group; CH: Currently homeless; CHC: community
health centers; COL: College; CRCS: Cluster-randomized controlled superiority trial; DAST-10: Drug Abuse Screening Test 10-item; DEP: depression; DIA: difference in age;
DIG: difference in gender; DSM-IV: Diagnostic and statistical manual of mental disorders; DV: dependent variable; DX: diagnosed/diagnosis; EMP: employed; FMHX: Family
history of mental health issues; G1: usual care; G2: UC and psychotherapy; G3: UC and education; G4: UC, psychotherapy, and education; GAD-7; Generalized Anxiety
Disorder 7-item; GSE: General Self-Efficacy scale; HIS: Hispanic/Latino; HS: high school or less; HTN: hypertension; HX: history; IG: intervention group; IV: independent
variable; LOE: level of evidence; M: mean; MA: mean age; MDC: Medicaid; MED: median; MID: mildly depressed score 5-9; MIL: Military issue; MINDI: Mini-International
Neuropsychiatric Diagnostic Interview; MMSE: Mini mental state exam; MND: minimally depressed score less than 4; MOD: moderately depressed score 10-19; NC: income;
NDMD: non-depressed/minimally depressed; NDMHC: Never discussed mental health concerns with professional; NDP: non-depressed patients; NI: No insurance; p:
significance; PDMHWP: Previously discussed mental health care concerns with a professional; PHQ-9: Patient health questionnaire 9 item; PI: Private insurance; PRIME-MD:
Primary Care Evaluation of Mental Disorders; RPA: receiving public assistance; RRD: Red river delta geographical area SD: standard deviation; SED: severely depressed score
greater than 20; SI: suicidal ideation; SMAST 13: Short Michigan Alcoholism Screening Test; TX: treatment; UC: Usual care; UMD: unipolar major depression; UNE:
unemployed; Vet: Veteran; YC: yoga course.

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Citation

Conceptual
Framework

Country:
United States

Citation

Conceptual
Framework
Inferred
Cognitive
Behavioral

39
Design/Method
impairment at
baseline
(MMSE) < 21),
residing in a
care facility.
Purpose: test
the effectiveness
of an integrated
intervention for
HTN and
depression
incorporating
social
determinants of
health.
Design/Method

Sample/Setting

Sample/Setting

Variables
Studied
with HTN
management.

Measurement
of Variables

Data
Analysis

Findings

Decision for Use

0.40; p =
0.024).

studies have explored how
social determinants of
health impact individual
health. This study is
important in exploring not
only depression, but the
overall management of
chronic health conditions in
this population.

Variables
Measurement Data
Findings
Decision for Use
Studied
of Variables
Analysis
Feingold et al.
N= 554
DV1: opioid
multinomial Individuals with LOE: Level II
Design:
(2018). The
Cross-sectional
misuse
Selfregression,
DEP, were at
association
study
Setting: 2 large
DV2: mild
administered
Independent increased risk t
Strengths: Good sample
between severity
Purpose: To
clinics in Israel
questionnaire:
sample
for opioid
size. Showed a direct link
DV3:
of depression
explore rates of
participants were
moderate
sociot-tests,
misuse (AOR)
between depression and risk
and prescription
PO misuse
recruited over a
demographic,
multiple
=3.63; 95%
of opioid abuse in
DV4:
opioid misuse
among chronic
6-month period.
moderatesubstance use,
logistic
(CI)=1.71–7.7)
individuals with chronic
among chronic
pain patients
severe
pain indices
regression
vs those without pain.
pain patients
with DEP and
DV5: severe
(0-10 scale),
analyses,
DEP. Severity
Demographics:
with and without
Females in Mild
depression
of DEP was
Key: - Cronbach’s alpha value; AA: African Americans; AI: American Indian/Alaska Native; ANOVA: Analysis of variance; BD: Bipolar disorder; BLDH: Binh Luc hospital;
CCM: Chronic care model; CCO: clinical cut-off point; CES-D: Center for Epidemiologic Studies Depression; CG: control group; CH: Currently homeless; CHC: community
health centers; COL: College; CRCS: Cluster-randomized controlled superiority trial; DAST-10: Drug Abuse Screening Test 10-item; DEP: depression; DIA: difference in age;
DIG: difference in gender; DSM-IV: Diagnostic and statistical manual of mental disorders; DV: dependent variable; DX: diagnosed/diagnosis; EMP: employed; FMHX: Family
history of mental health issues; G1: usual care; G2: UC and psychotherapy; G3: UC and education; G4: UC, psychotherapy, and education; GAD-7; Generalized Anxiety
Disorder 7-item; GSE: General Self-Efficacy scale; HIS: Hispanic/Latino; HS: high school or less; HTN: hypertension; HX: history; IG: intervention group; IV: independent
variable; LOE: level of evidence; M: mean; MA: mean age; MDC: Medicaid; MED: median; MID: mildly depressed score 5-9; MIL: Military issue; MINDI: Mini-International
Neuropsychiatric Diagnostic Interview; MMSE: Mini mental state exam; MND: minimally depressed score less than 4; MOD: moderately depressed score 10-19; NC: income;
NDMD: non-depressed/minimally depressed; NDMHC: Never discussed mental health concerns with professional; NDP: non-depressed patients; NI: No insurance; p:
significance; PDMHWP: Previously discussed mental health care concerns with a professional; PHQ-9: Patient health questionnaire 9 item; PI: Private insurance; PRIME-MD:
Primary Care Evaluation of Mental Disorders; RPA: receiving public assistance; RRD: Red river delta geographical area SD: standard deviation; SED: severely depressed score
greater than 20; SI: suicidal ideation; SMAST 13: Short Michigan Alcoholism Screening Test; TX: treatment; UC: Usual care; UMD: unipolar major depression; UNE:
unemployed; Vet: Veteran; YC: yoga course.

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Conceptual
Framework

anxiety: A crosssectional study
Funding:
Indivior
Pharmaceuticals
Bias: Two of the
authors declared
no conflict of
interest. Two
authors
disclosed
receiving prior
speaking fees
from Indivior
Pharmaceuticals.
Country: Israel

Citation

40
Design/Method

Sample/Setting

according to
level of
severity.

DEP 74 (52%),
MOD 52 (51%),
DEP mod-severe
60 (55%), severe
43 (46.2). Males
mild DEP 69
(48.3%), MOD
DEP 50 (49%),
Mod-severe 49
(45%), severe 50
(53.8%).

Inclusion: 18
and older,
diagnosed with
chronic
and currently
prescribed POs.

Variables
Studied

Measurement
of Variables
COMM, PHQ9, GAD-7.

Data
Analysis

Exclusion: not
prescribed POs,
cognitive
impairment or
language
difficulties.

Conceptual
Framework

Design/Method

Sample/Setting

Variables
Studied

Measurement
of Variables

Data
Analysis

Findings

Decision for Use

strongly
associated with
increased risk
for opioid
misuse for
moderate
(AOR=3.71;
95% CI=1.01–
13.76),
moderatesevere
(AOR=6.28;
95% CI=1.6–
24.57)
and severe
(AOR=14.66;
95% CI=3.28–
65.52) DEP, but
those positive
for mild DEP
(AOR=1.49;
95% CI=0.39–
5.68).
Findings

Weaknesses: Study did not
use a standardized tool to
screen for other substance
abuse. It did not explore the
amount and frequency of
opioid abuse.
Harm Feasibility: No
individuals were harmed
PICOT Applicability:
Homeless individuals deal
with a variety of chronic
conditions, including pain.
This study can be used to
explore how severity of
depression impacts
substance misuse and
overall health outcomes in
this population.

Decision for Use

Key: - Cronbach’s alpha value; AA: African Americans; AI: American Indian/Alaska Native; ANOVA: Analysis of variance; BD: Bipolar disorder; BLDH: Binh Luc hospital;
CCM: Chronic care model; CCO: clinical cut-off point; CES-D: Center for Epidemiologic Studies Depression; CG: control group; CH: Currently homeless; CHC: community
health centers; COL: College; CRCS: Cluster-randomized controlled superiority trial; DAST-10: Drug Abuse Screening Test 10-item; DEP: depression; DIA: difference in age;
DIG: difference in gender; DSM-IV: Diagnostic and statistical manual of mental disorders; DV: dependent variable; DX: diagnosed/diagnosis; EMP: employed; FMHX: Family
history of mental health issues; G1: usual care; G2: UC and psychotherapy; G3: UC and education; G4: UC, psychotherapy, and education; GAD-7; Generalized Anxiety
Disorder 7-item; GSE: General Self-Efficacy scale; HIS: Hispanic/Latino; HS: high school or less; HTN: hypertension; HX: history; IG: intervention group; IV: independent
variable; LOE: level of evidence; M: mean; MA: mean age; MDC: Medicaid; MED: median; MID: mildly depressed score 5-9; MIL: Military issue; MINDI: Mini-International
Neuropsychiatric Diagnostic Interview; MMSE: Mini mental state exam; MND: minimally depressed score less than 4; MOD: moderately depressed score 10-19; NC: income;
NDMD: non-depressed/minimally depressed; NDMHC: Never discussed mental health concerns with professional; NDP: non-depressed patients; NI: No insurance; p:
significance; PDMHWP: Previously discussed mental health care concerns with a professional; PHQ-9: Patient health questionnaire 9 item; PI: Private insurance; PRIME-MD:
Primary Care Evaluation of Mental Disorders; RPA: receiving public assistance; RRD: Red river delta geographical area SD: standard deviation; SED: severely depressed score
greater than 20; SI: suicidal ideation; SMAST 13: Short Michigan Alcoholism Screening Test; TX: treatment; UC: Usual care; UMD: unipolar major depression; UNE:
unemployed; Vet: Veteran; YC: yoga course.

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Carey et al.
(2014).
Comparison of a
single selfassessment item
with the PHQ-9
for detecting
depression in
general practice.
Funding:
Beyond blue
and the National
Heart
Foundation of
Australia
Bias: Authors
deny conflict of
interest
Country:
Australia

Conceptual
Framework
Inferred
Cognitive
Behavioral

41
Design/Method

Sample/Setting

Design: Crosssectional survey
presented on a
touchscreen
computer.
Purpose:
explore the
utility of a single
self-assessment
item vs Patient
Health
Questionnaire
(PHQ-9) at
different
thresholds.
Inclusion: 18
and older,
understood
English, and
presented to the
doctor.
Exclusion:
Unable to give
informed
consent.

N =1004
Setting: 12
general practices
in 3 urban
regions, from two
states within
Australia.
Demographics:
Female 616
(61%), insured
197 (20%), 1–2
chronic diseases
407 (41%)

Variables
Studied
Depression

Measurement
of Variables
PHQ-9, singleitem
questionnaire

Data
Analysis
STATA
11.0,
Frequencies,
percentages,
sensitivity,
specificity,
positive
predictive
value (PPV)
and negative
predictive
value
(NPV),
Clopper–
Pearson
method and
post-hoc
tests.

Findings

Decision for Use

N = 1004 (61%
female, 48%
aged 55 years
or older). With
threshold of
mild depression
or greater,
single item had
adequate
specificity
(76%, 95% CI:
71–80%), 76
out 100 people
non-depressed
by the PHQ-9
were also not
depressed by
the single
item. Sensitivity
was high (91%,
95% CI: 84–
95%), with the
single item
identifying 91
out of every

LOE: II
Strengths: Large sample
size. Self-administered tests
to minimize bias or cueing
of patient’s depressive
symptoms
Weaknesses: Study did not
involve a more structured
interview. It only compared
the effectiveness of two
different screening tools for
depression and not the
condition itself.
Harm Feasibility: None
PICOT Applicability: This
study shows that although a
single-item approach may
provide a quicker method of
identifying individuals with
possible depression, it is
important to do a second
assessment of depression to
establish a diagnosis,
identify false positives and
to explore patient views.

Key: - Cronbach’s alpha value; AA: African Americans; AI: American Indian/Alaska Native; ANOVA: Analysis of variance; BD: Bipolar disorder; BLDH: Binh Luc hospital;
CCM: Chronic care model; CCO: clinical cut-off point; CES-D: Center for Epidemiologic Studies Depression; CG: control group; CH: Currently homeless; CHC: community
health centers; COL: College; CRCS: Cluster-randomized controlled superiority trial; DAST-10: Drug Abuse Screening Test 10-item; DEP: depression; DIA: difference in age;
DIG: difference in gender; DSM-IV: Diagnostic and statistical manual of mental disorders; DV: dependent variable; DX: diagnosed/diagnosis; EMP: employed; FMHX: Family
history of mental health issues; G1: usual care; G2: UC and psychotherapy; G3: UC and education; G4: UC, psychotherapy, and education; GAD-7; Generalized Anxiety
Disorder 7-item; GSE: General Self-Efficacy scale; HIS: Hispanic/Latino; HS: high school or less; HTN: hypertension; HX: history; IG: intervention group; IV: independent
variable; LOE: level of evidence; M: mean; MA: mean age; MDC: Medicaid; MED: median; MID: mildly depressed score 5-9; MIL: Military issue; MINDI: Mini-International
Neuropsychiatric Diagnostic Interview; MMSE: Mini mental state exam; MND: minimally depressed score less than 4; MOD: moderately depressed score 10-19; NC: income;
NDMD: non-depressed/minimally depressed; NDMHC: Never discussed mental health concerns with professional; NDP: non-depressed patients; NI: No insurance; p:
significance; PDMHWP: Previously discussed mental health care concerns with a professional; PHQ-9: Patient health questionnaire 9 item; PI: Private insurance; PRIME-MD:
Primary Care Evaluation of Mental Disorders; RPA: receiving public assistance; RRD: Red river delta geographical area SD: standard deviation; SED: severely depressed score
greater than 20; SI: suicidal ideation; SMAST 13: Short Michigan Alcoholism Screening Test; TX: treatment; UC: Usual care; UMD: unipolar major depression; UNE:
unemployed; Vet: Veteran; YC: yoga course.

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Citation

Conceptual
Framework

Conceptual
Framework
Inferred
Cognitive
Behavioral

42
Design/Method

Design/Method

Sample/Setting

Sample/Setting

Variables
Studied

Measurement
of Variables

Data
Analysis

Findings
100 true cases
(as defined by
the PHQ-9).
Findings

Decision for Use

Variables
Measurement Data
Decision for Use
Studied
of Variables
Analysis
Weobong et al.
Design: parallel- N = 495
BDI-II, PHQ-9 Linear
HAP
LOE: Level II
DV1:
(2017).
arm, randomized n=248 EUC
Depression
regression,
maintained
Sustained
controlled trial
n= 245 to HAP
severity, DV2:
logistic
improved
Strengths: Large sample
effectiveness
plus EUC.
depression
regression,
scores at 12
size. Randomized trial.
Purpose:
and cost
Evaluate the
n=2 lost to
remission.
marginal
mons
effectiveness of
sustained
attrition (0.4%)
IV1: EUC
standardizati (difference in
Weaknesses: Limited
the Healthy
effectiveness
Setting: 10
routine consult
on, repeated mean= −0.34;
checkpoints to assess
Activity
and the cost
primary health
with physician,
measures
95% CI −2.37,
possible remission or
Programme, a
effectiveness of
centers India.
PHQ-9 results
analysis,
1.69; p = 0.74), relapses. Patients were not
brief
HAP over 12
copies of a
receiver
lower scores vs diagnosed with PHQ-9 at
Demographics:
psychological
months and to
EUC group: MA
contextualized
operated
EUC alone
baseline, it was only used to
treatment
assess whether
42.6, females 191 version of the
characteristi (−4.45; 95% CI assess symptoms severity.
for depression
behavioral
(77%), no
WHO Mental
c, p-values,
−7.26, −1.63; p Harm Feasibility: No
delivered by lay
activation
education 55
Health Gap
adjusted
= 0.002) and
individuals were harm
counsellors in
reported by
(22%),
Action
prevalence
higher rates of
during this study.
primary care:
patients at 3
unemployed 140
Programme
ratio.
remission (aPR
12-month
months mediated (56%).
(mhGAP) and
= 1.36; 95% CI PICOT applicability: This
follow-up of a
the effects of the EUC plus HAP:
information on
1.15, 1.61; p <
study shows the importance
randomised
intervention on
MA 42.4, females when and
0.009).
of collaborative, integrated
controlled trial
depression
188 (76%), no
where to refer
Economic
programs in the
at 12 months.
education 75
for psychiatric
analyses
management of depression.
Funding:
Wellcome
(31%),
care.
indicated that
It also showed that
Key: - Cronbach’s alpha value; AA: African Americans; AI: American Indian/Alaska Native; ANOVA: Analysis of variance; BD: Bipolar disorder; BLDH: Binh Luc hospital;
CCM: Chronic care model; CCO: clinical cut-off point; CES-D: Center for Epidemiologic Studies Depression; CG: control group; CH: Currently homeless; CHC: community
health centers; COL: College; CRCS: Cluster-randomized controlled superiority trial; DAST-10: Drug Abuse Screening Test 10-item; DEP: depression; DIA: difference in age;
DIG: difference in gender; DSM-IV: Diagnostic and statistical manual of mental disorders; DV: dependent variable; DX: diagnosed/diagnosis; EMP: employed; FMHX: Family
history of mental health issues; G1: usual care; G2: UC and psychotherapy; G3: UC and education; G4: UC, psychotherapy, and education; GAD-7; Generalized Anxiety
Disorder 7-item; GSE: General Self-Efficacy scale; HIS: Hispanic/Latino; HS: high school or less; HTN: hypertension; HX: history; IG: intervention group; IV: independent
variable; LOE: level of evidence; M: mean; MA: mean age; MDC: Medicaid; MED: median; MID: mildly depressed score 5-9; MIL: Military issue; MINDI: Mini-International
Neuropsychiatric Diagnostic Interview; MMSE: Mini mental state exam; MND: minimally depressed score less than 4; MOD: moderately depressed score 10-19; NC: income;
NDMD: non-depressed/minimally depressed; NDMHC: Never discussed mental health concerns with professional; NDP: non-depressed patients; NI: No insurance; p:
significance; PDMHWP: Previously discussed mental health care concerns with a professional; PHQ-9: Patient health questionnaire 9 item; PI: Private insurance; PRIME-MD:
Primary Care Evaluation of Mental Disorders; RPA: receiving public assistance; RRD: Red river delta geographical area SD: standard deviation; SED: severely depressed score
greater than 20; SI: suicidal ideation; SMAST 13: Short Michigan Alcoholism Screening Test; TX: treatment; UC: Usual care; UMD: unipolar major depression; UNE:
unemployed; Vet: Veteran; YC: yoga course.

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Trust Senior
Research
Fellowship grant
Bias: DM has
received money
for lectures not
related to this
work. CGF
holds a Principal
Research
Fellowship from
the Wellcome
Trust (046386).
VP member of
the Editorial
Board of PLOS
Medicine. All
other authors
declare no
competing
interests.
Country: India
Citation

Conceptual
Framework

Conceptual
Framework

43
Design/Method

Sample/Setting

Inclusion: 18–
65 years with a
probable
diagnosis of
moderately
severe to severe
DEP.
Exclusion:
Pregnant
women, severe
medical
conditions,
hearing/speech
difficulties.

unemployed 152
(62%).

Design/Method

Sample/Setting

Variables
Studied
IV2: EUC plus
HAP
behavioral
program, 6–8
sessions,
30–40 minutes
each.

Measurement
of Variables

Data
Analysis

Findings

Decision for Use

HAP plus EUC
was dominant
over EUC
alone, lower
costs and better
outcomes.

implemented interventions
delivered by individuals
other than physicians are
effective and cost effective.
In the homeless population,
screening and utilizing
community health workers
can be an effective way to
improve outcomes.

Variables
Measurement Data
Findings
Decision for Use
Studied
of Variables
Analysis
Grelotti et al.
N= 250
IG: daily
17-item
Mixed
Fluoxetine
LOE: Level II
Design:
(2017). Does
randomized
20mg daily
Hamilton
effects linear treatment on
Setting:
substance use
controlled trial
Homeless
fluoxetine for
Rating Scale
regression,
Strengths: Large
Key: - Cronbach’s alpha value; AA: African Americans; AI: American Indian/Alaska Native; ANOVA: Analysis of variance; BD: Bipolar disorder; BLDH: Binh Luc hospital;
CCM: Chronic care model; CCO: clinical cut-off point; CES-D: Center for Epidemiologic Studies Depression; CG: control group; CH: Currently homeless; CHC: community
health centers; COL: College; CRCS: Cluster-randomized controlled superiority trial; DAST-10: Drug Abuse Screening Test 10-item; DEP: depression; DIA: difference in age;
DIG: difference in gender; DSM-IV: Diagnostic and statistical manual of mental disorders; DV: dependent variable; DX: diagnosed/diagnosis; EMP: employed; FMHX: Family
history of mental health issues; G1: usual care; G2: UC and psychotherapy; G3: UC and education; G4: UC, psychotherapy, and education; GAD-7; Generalized Anxiety
Disorder 7-item; GSE: General Self-Efficacy scale; HIS: Hispanic/Latino; HS: high school or less; HTN: hypertension; HX: history; IG: intervention group; IV: independent
variable; LOE: level of evidence; M: mean; MA: mean age; MDC: Medicaid; MED: median; MID: mildly depressed score 5-9; MIL: Military issue; MINDI: Mini-International
Neuropsychiatric Diagnostic Interview; MMSE: Mini mental state exam; MND: minimally depressed score less than 4; MOD: moderately depressed score 10-19; NC: income;
NDMD: non-depressed/minimally depressed; NDMHC: Never discussed mental health concerns with professional; NDP: non-depressed patients; NI: No insurance; p:
significance; PDMHWP: Previously discussed mental health care concerns with a professional; PHQ-9: Patient health questionnaire 9 item; PI: Private insurance; PRIME-MD:
Primary Care Evaluation of Mental Disorders; RPA: receiving public assistance; RRD: Red river delta geographical area SD: standard deviation; SED: severely depressed score
greater than 20; SI: suicidal ideation; SMAST 13: Short Michigan Alcoholism Screening Test; TX: treatment; UC: Usual care; UMD: unipolar major depression; UNE:
unemployed; Vet: Veteran; YC: yoga course.

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compromise
depression
treatment in
persons with
HIV? Findings
from a
randomized
controlled trial.
Funding: U.S.
National
Institutes of
Health
R01MH063011
Bias: Authors
deny any
conflict of
interest.
Country:
United States

Conceptual
Framework

44
Design/Method

Sample/Setting

Purpose:
Identify use of
antidepressant
treatment in
depression with
HIV and active
substance abuse.
Inclusion:
Englishspeaking 18 and
older, infected
with HIV, living
in San
Francisco, CA,
Major
Depressive
Disorder, Minor
Depressive
Disorder, or
Dysthymia.
Exclusion: On
psychiatric meds
within 3 months
prior, receiving
psychiatric care
within 6 months
prior, bipolar,

shelters, free
lunch programs,
low-income
single-roomoccupancy hotels,
public HIV
clinics, and social
service agencies.
Demographics:
IG: MA 44.2 (SD
= 9.09), female 6
(9.1%), homeless
45 (72.6%),
alcohol use 33
(50%). Control:
MA 42.8 (SD=
8.44), female 8
(11.3%),
homeless 45
(64.5%), alcohol
use 38 (54%).

Variables
Studied
2 weeks,
followed by
once-weekly
22 weeks, selfadministered
once-weekly
for another 3
months.
CG:
Psychiatric
care and
possible
medication
regimen.

Measurement
of Variables
for Depression
(HAMD) and
Beck
Depression
Inventory
(BDI), selfreport of any
alcohol, crack,
cocaine,
heroin, or
methampheta
mine.

Data
Analysis
mixedeffects
Poisson
regression,
standard
deviation.

Findings
DEP severity
relative to
community
referral was
statistically
significant
irrespective of
alcohol use.
Effect size
1.76/5.4
= 0.33 for
alcohol and
2.34/5.4 =
0.43 for those
who did not use
alcohol. BDI,
the effect sizes
larger: 3.95/9.7
= 0.41 alcohol
and 6.45/9.7 =
0.66 no alcohol.
Alcohol use
days was 0.56
(95% CI: 0.20
to 1.58; p =
.276). Incident
rate ratio for

Decision for Use

Weaknesses: Study was not
a blinded randomized trial.
Study did not evaluate the
effect of specific drugs in
relation to depression. Study
was focused on depression
rather than substance abuse;
therefore, it did not assess
the extent of illicit drug use
on depression.
Harm Feasibility: None
PICOT Applicability:
Study focuses largely on
individuals with depression
and homelessness. This
shows the importance that
untreated depression can
have on chronic disease and
overall health outcomes.

Key: - Cronbach’s alpha value; AA: African Americans; AI: American Indian/Alaska Native; ANOVA: Analysis of variance; BD: Bipolar disorder; BLDH: Binh Luc hospital;
CCM: Chronic care model; CCO: clinical cut-off point; CES-D: Center for Epidemiologic Studies Depression; CG: control group; CH: Currently homeless; CHC: community
health centers; COL: College; CRCS: Cluster-randomized controlled superiority trial; DAST-10: Drug Abuse Screening Test 10-item; DEP: depression; DIA: difference in age;
DIG: difference in gender; DSM-IV: Diagnostic and statistical manual of mental disorders; DV: dependent variable; DX: diagnosed/diagnosis; EMP: employed; FMHX: Family
history of mental health issues; G1: usual care; G2: UC and psychotherapy; G3: UC and education; G4: UC, psychotherapy, and education; GAD-7; Generalized Anxiety
Disorder 7-item; GSE: General Self-Efficacy scale; HIS: Hispanic/Latino; HS: high school or less; HTN: hypertension; HX: history; IG: intervention group; IV: independent
variable; LOE: level of evidence; M: mean; MA: mean age; MDC: Medicaid; MED: median; MID: mildly depressed score 5-9; MIL: Military issue; MINDI: Mini-International
Neuropsychiatric Diagnostic Interview; MMSE: Mini mental state exam; MND: minimally depressed score less than 4; MOD: moderately depressed score 10-19; NC: income;
NDMD: non-depressed/minimally depressed; NDMHC: Never discussed mental health concerns with professional; NDP: non-depressed patients; NI: No insurance; p:
significance; PDMHWP: Previously discussed mental health care concerns with a professional; PHQ-9: Patient health questionnaire 9 item; PI: Private insurance; PRIME-MD:
Primary Care Evaluation of Mental Disorders; RPA: receiving public assistance; RRD: Red river delta geographical area SD: standard deviation; SED: severely depressed score
greater than 20; SI: suicidal ideation; SMAST 13: Short Michigan Alcoholism Screening Test; TX: treatment; UC: Usual care; UMD: unipolar major depression; UNE:
unemployed; Vet: Veteran; YC: yoga course.

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Conceptual
Framework

45
Design/Method
psychotic
disorder, or
dementia,
substance use or
suicidal ideation.

Sample/Setting

Variables
Studied

Measurement
of Variables

Data
Analysis

Findings

Decision for Use

illicit drug use
days was 0.66
(95% CI: 0.17
to 2.60; p =
.548).

Key: - Cronbach’s alpha value; AA: African Americans; AI: American Indian/Alaska Native; ANOVA: Analysis of variance; BD: Bipolar disorder; BLDH: Binh Luc hospital;
CCM: Chronic care model; CCO: clinical cut-off point; CES-D: Center for Epidemiologic Studies Depression; CG: control group; CH: Currently homeless; CHC: community
health centers; COL: College; CRCS: Cluster-randomized controlled superiority trial; DAST-10: Drug Abuse Screening Test 10-item; DEP: depression; DIA: difference in age;
DIG: difference in gender; DSM-IV: Diagnostic and statistical manual of mental disorders; DV: dependent variable; DX: diagnosed/diagnosis; EMP: employed; FMHX: Family
history of mental health issues; G1: usual care; G2: UC and psychotherapy; G3: UC and education; G4: UC, psychotherapy, and education; GAD-7; Generalized Anxiety
Disorder 7-item; GSE: General Self-Efficacy scale; HIS: Hispanic/Latino; HS: high school or less; HTN: hypertension; HX: history; IG: intervention group; IV: independent
variable; LOE: level of evidence; M: mean; MA: mean age; MDC: Medicaid; MED: median; MID: mildly depressed score 5-9; MIL: Military issue; MINDI: Mini-International
Neuropsychiatric Diagnostic Interview; MMSE: Mini mental state exam; MND: minimally depressed score less than 4; MOD: moderately depressed score 10-19; NC: income;
NDMD: non-depressed/minimally depressed; NDMHC: Never discussed mental health concerns with professional; NDP: non-depressed patients; NI: No insurance; p:
significance; PDMHWP: Previously discussed mental health care concerns with a professional; PHQ-9: Patient health questionnaire 9 item; PI: Private insurance; PRIME-MD:
Primary Care Evaluation of Mental Disorders; RPA: receiving public assistance; RRD: Red river delta geographical area SD: standard deviation; SED: severely depressed score
greater than 20; SI: suicidal ideation; SMAST 13: Short Michigan Alcoholism Screening Test; TX: treatment; UC: Usual care; UMD: unipolar major depression; UNE:
unemployed; Vet: Veteran; YC: yoga course.

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46
Appendix B

Table 2
Synthesis Table
Author

Carey et
al.

Feingold et
al.

Grelotti et
al.

Kilbourne et
al.

Lee et al.

McClintock
et al.

Meyers et al.

Niemi et
al.

Opperman et
al.

Weobong et
al.

Year
Country
Level of
significance

2014
Australia
II

2018
Israel
II

2017
US
II

2019
US
II

2017
US
II

2017
US
II

2014
US
II

2016
Vietnam
I

2016
US
II

2017
India
II

Design

Crosssectional
1004

Crosssectional
554

RCT

Single blind
RCT
238

Crosssectional
156
Setting

RCT

Prospective

CRCS

Retrospective

RCT

54

674

1951

261

495

Primary Care
Community

X

X

X

X

X

DS
Education

X

X

X
X

DSEV

X

X

X

PHQ-9
BDI
HAM-D
CES-D

X

X

Sample size

Males
Females
Homeless
Mean Age
ID depression

250

X
X

X
Independent variables
X
X
X
Dependent variables
X
X
Instruments
X

X
X

X

X
X

X
X

X

X
X

X

X

X

X

X

X

X

X

X

X
X

60%
40%
NA
61

33.5%
66.5%
NA
44

50.9%
49.1%
NA
61

100%
0
5.4%
51

24%
76%
NA
NA

X

X

X

X

X

X
X

39%
61%
NA
55

52%
48%
NA
NA

79.6%
20.4%
67%
43

44%
66%
NA
41

X

X

X

X

X
Demographics
44%
66%
100%
41
Findings
X

Key: BDI: Beck depression inventory; CES-D: Center for epidemiologic studies depression scale; CRCS: Cluster-randomized controlled superiority trial; DS: Depression
Screening; DSev: Depression severity; HAM-D: Hamilton depression rating scale; ID: Identify; NA: Not measured/ Not Applicable; PHQ-9: Patient health questionnaire 9-item;
RCT: Randomized controlled trial.

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Appendix C

Figure 1. Theory of Unpleasant Symptoms. Adapted from Middle range theory for nursing
(170), by M. J. Smith & P. R. Lier. 2014, New York, NY: Springer Publishing Company.

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Appendix D

Figure 2. Iowa Model of Evidence-Based Practice. Adapted from “Perioperative nursing leaders
implement clinical practice guidelines using the Iowa Model of Evidence‐Based
Practice,” by S. White, AORN Journal, 102(1), 50-59.

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Appendix E

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Appendix F

Demographic Form

Demographic Form
ID Number

Age

Gender

Race/Ethnicity
• Black non-Hispanic
• American Indian
• Hispanic
• Asian/Pacific Islander
White non-Hispanic

Level of Education
•
•
•
•
•

Less than high
school
high school diploma
Some college
Bachelors
Graduate

Insured
YES
NO

PHQ-9 Completion
Date

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Appendix G

Expected Budget

Phase

Activities

Design and print 2 recruitment
letters and 2 letters of support
(direct)
Design and print 200
demographic worksheets, 200
consent forms and 200 PHQ-9
questionnaires (direct)
Design and print 30 step-byPreparation step process of how project will
run, available mental health
resources (numbers, addresses)
and individual responsibilities
(direct)
Laptop computer for education
development (direct)
Room rental for project
planning and education of staff
(indirect)
Room rental for intake use and
depression screening process
(indirect)
General cost of utilities for
rental rooms (indirect)
Delivery
General office supplies (pens,
pencils, highlighters,
clipboards) (indirect)
Social worker time (indirect)
Intake team staff time (4
people) (indirect)
DNP student time (indirect)
Evaluation

Review and analyze DNP
project results (indirect)

Cost

subtotal

$0.56 each

$2.24

$0.28 each

$168.00

$0.56 each

$16.80

$1200

$1200

$1000
per month

$1000
for 1month

$1000
per month

$4000
For 4
months
$800
For 4
months
$200
For 4
months
$1,500
60 hours
$4,800
60 hours
each
$10,000
250 hours
$800
20 hours

$200
Per month
$50
Per month
$25 per
hour
$20 per
hour
$40 per
hour
$40 per
hour

Total

$24,487.04

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Appendix H

Cost Savings

Total Expected Budget

Cost Savings

Final Expected Budget

$24,487.04
Laptop computer for education
development (direct)

-

$1,200

Room rental for project planning and
education of staff (indirect)

-

$1,000

Room rental for intake use and
depression screening (indirect)

-

$4,000

Social worker time (indirect)

-

$1,500

Intake team staff time (4 people)
(indirect)

-

$4,800

DNP student time (indirect)

-

$10,000

Review and analyze DNP project
results (indirect)

-

$800

-

$22,900

$1,187.04

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Appendix I

Analysis Tables
Table 1
Frequency Table for Nominal Variables
Variable
Gender
M
Missing
Race/Ethnicity
American Indian
Asian/ Pacific Islander
Black non-Hispanic
Hispanic
Hispanic/ Pacific Islander
White Non-Hispanic
Missing
Level of Education
Bachelors
high school diploma
Less than high school
some college
Missing
Insured
No
Yes
Missing
Note. Due to rounding errors, percentages may not equal 100%.

n

%

18
0

100
0

2
2
1
4
1
6
2

11.11
11.11
5.56
22.22
5.56
33.33
11.11

1
8
4
3
2

5.56
44.44
22.22
16.67
11.11

4
14
0

22.22
77.78
0

Table 2
Summary Statistics Table for Interval and Ratio Variables
Variable
M
SD
n
SEM
Min
Max
Age
35.50
11.39 18
2.69
21.00
62.00
Note. '-' denotes the sample size is too small to calculate statistic.

Skewness
0.87

Kurtosis
0.22

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Table 3
Frequency Table for Nominal and Ordinal Variables
Variable
Severity
Mild
Moderate
Moderately Severe
None - Minimal
Missing
Note. Due to rounding errors, percentages may not equal 100%.

n

%

7
4
2
5
0

38.89
22.22
11.11
27.78
0

Table 4
Summary Statistics Table for Interval and Ratio Variables
Variable
M
SD
n
SEM
Min
Max
Total Score
7.72
4.69 18
1.10
1.00
16.00
Note. '-' denotes the sample size is too small to calculate statistic.

Skewness
0.30

Kurtosis
-1.07

Figure 5
Scatterplots between each variable with the regression line added

Table 6
Spearman Correlation Results Between Previously diagnosed and Severity
Combination
rs
Lower
Previously diagnosed - Severity
0.63
0.23
Note. The confidence intervals were computed using α = 0.05; n = 18

Upper
0.85

p
.005

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Figure 7
Scatterplots between each variable with the regression line added

Table 8
Pearson Correlation Results Between Total Score and Age
Combination
rp
Lower
Total Score -Age
0.05
-0.43
Note. The confidence intervals were computed using α = 0.05; n = 18

Upper
0.51

p
.843