Clinical Psychological Science
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Novel Models for Delivering Mental Health Services and Reducing the Burdens of Mental Illness
Alan E. Kazdin and Sarah M. Rabbitt
Clinical Psychological Science 2013 1: 170 originally published online 23 January 2013
DOI: 10.1177/2167702612463566
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Review Article
Novel Models for Delivering Mental Health
Services and Reducing the Burdens of
Mental Illness
Clinical Psychological Science
1(2) 170­–191
© The Author(s) 2013
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DOI: 10.1177/2167702612463566
http://cpx.sagepub.com
Alan E. Kazdin and Sarah M. Rabbitt
Department of Psychology, Yale University
Abstract
Most individuals in both developing and developed countries who experience mental illness do not receive psychological
services. The dominant model of delivering services used in developed countries (individual therapy by a highly trained
mental health professional) can provide effective (i.e., evidence-based) treatments but is greatly limited as a means of
reaching the large swath of individuals in need. We highlight several models outside the mental health professions (e.g., public
health, medicine, business) that are more affordable and accessible and can be scaled up to reach many individuals in need.
These models include task shifting, disruptive innovations, interventions in everyday settings, best-buy interventions, lifestyle
changes, and social media. We convey their key characteristics and how they have been or can be applied to mental health.
We end by discussing challenges in applying the models, critical issues on which effective treatment delivery depends, and
paths to make progress.
Keywords
models of delivering treatment, reduce burdens of mental illness
Received 8/21/12; Revision accepted 8/31/12
The burdens of mental illness in terms of individual and
family suffering and financial costs in developed and
developing countries have been recognized for some time (see
Desjarlais, Eisenberg, Good, & Kleinman, 1995; Eaton et al.,
2011; World Health Organization [WHO], 2010). Attention to
the burdens has increased within the past decade in light of
converging influences, including improved data on the incidence and prevalence of dysfunction worldwide and on disparities of care within and among nations; recognition that
mental illness plays a critical role in physical health care and
economic development; and global attention to the impact of
natural (e.g., earthquakes, tsunamis) and human-caused (e.g.,
war, forced migrations and resettlement) disasters on both
physical and mental health. The mismatch between need and
provision of mental health services has become even more
salient with advances in pharmacological and psychological
treatments. Regarding the latter, for example, many evidencebased psychosocial interventions are available that can ameliorate a variety of dysfunctions in children, adolescents, and
adults (e.g., National Registry of Evidence-Based Programs
and Practices, 2012). If we could only deliver these interventions to reach those in need.
The importance of addressing mental illness has been well
recognized in its own right. Yet, accelerated attention emerged
from global health initiatives to treat physical disease (e.g.,
chronic, infectious; Institute of Medicine [IOM], 2010; WHO,
2011b). Initiatives to provide physical health care services
revealed gaps in mental health services. Moreover, as we note
later, it became clear that mental health and physical health are
inextricably intertwined, with bidirectional, reciprocal, and
comorbid relations. Reducing the burdens of physical health
could not neglect mental health, as reflected in the oft-cited
statement there is “no health without mental health” (Prince
et al., 2007, p. 859; WHO, 2005, p. 11).
Several models or strategies of delivering treatment and
preventive interventions emerged to address physical diseases.
Many barriers for delivering care for physical health care to
large swaths of individuals in need, particularly in developing
countries, were recognized to be similar to the barriers of providing mental health care (Lancet Global Mental Health Group
[LGMHG], 2007; Sharan et al., 2009). Consequently, models
for delivering treatment proved to be applicable to both mental
and physical health services.
Against this backdrop, new models emerged for delivering
both medical and psychological interventions. Model of
Corresponding Author:
Alan E. Kazdin, Department of Psychology, 2 Hillhouse Avenue,Yale
University, New Haven, CT 06520-8205
E-mail: [email protected]
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Novel Models for Delivering Mental Health Services
delivery refers to how the treatment is provided (i.e., by whom,
where, and in what context) and can be distinguished from the
treatment itself (e.g., one-time vaccination, weekly medication, surgery, cognitive behavior therapy). These models are
not in widespread use in the mental health professions (i.e.,
clinical psychology, psychiatry, social work) in part because
they emerged from other disciplines and professions (e.g.,
medicine, public health, business). We highlight several models of delivery to expand on those models currently in use in
the mental health professions and to reach more underserved
individuals. We focus on psychosocial interventions broadly
conceived as distinguished from more biologically based
interventions (e.g., medication, deep brain stimulation, diet).
We begin by highlighting the challenge of the burden to
clarify the impetus for the article and then discuss and illustrate several different models of delivering psychological services. In a prior article, we noted that a portfolio of models of
care is needed to address the burdens of mental illness (Kazdin
& Blase, 2011). This article brings together models from
diverse domains that can greatly expand the reach of psychosocial treatments and redress the mismatch between need for
and access to services.
The Challenges of Meeting the Need for
Mental Health Services
Impetus for considering, developing, and utilizing novel models of delivering psychological treatments stems from
increased recognition of the burden of mental illness (e.g.,
Reeves et al., 2011; WHO, 2011b). Worldwide approximately
30% of the population is estimated to have at least one mental
disorder within a 12-month period (LGMHG, 2007). In the
United States, approximately 25% (~79 million people) of the
population (~314 million) meets criteria in any given year
(Kessler et al., 2009; Kessler & Wang, 2008). Over the course
of a lifetime, approximately 50% of the U.S. population meets
criteria for at least one psychiatric disorder. In short, the number of individuals with a psychiatric disorder at any given
point in time is enormous and presents a major challenge for
providing care and services.
The monetary and personal costs of psychiatric disorders
are enormous as well. For example, substance use disorders,
the most prevalent mental disorders in the United States, affect
over 20 million Americans and cost approximately $500 billion annually (Jason & Ferrari, 2010). The main costs are for
medical and psychiatric treatment, criminal justice (for substance-related crimes), and loss of earnings. Reductions in
annual earnings on average in the United States are approximately $16,000 less for individuals with diagnosis of a mental
disorder, compared to their control counterparts. This results
in a total reduction of $193.2 billion in personal earnings
nationally in 1 year (Kessler et al., 2008). A single episode of
major depressive disorder is associated with an average of
over 5 weeks of lost productivity per worker, resulting in an
annual capital loss to employers of $36 billion (Kessler et al.,
2006). Costs extend to impairment in everyday situations.
Psychiatric disorders account for over 50% of the days that
individuals report that they could not perform their usual tasks
when queried about physical or mental health (Merikangas
et al., 2007).1
Mental disorders are more impairing than common chronic
medical disorders, with particularly greater impairment in the
domains of home, social, and close-relationship functioning
(Druss et al., 2009). As a dramatic illustration, in 2004 the
burden of depressive disorders (e.g., years of good health lost
because of disability) was ranked third among the list of mental and physical diseases (World Federation for Mental Health,
2011). By 2030, depression is projected to be the number one
cause of disability, ahead of cardiovascular disease, traffic
accidents, chronic pulmonary disease, and HIV/AIDS (WHO,
2008).
A critical aspect to reducing the burden of mental illness is
the ability of effective interventions to reach those in need of
services. Recent years have seen an increase in the proportion
of people in need who receive treatment in the United States,
with 20.3% of individuals suffering from a disorder between
1990 and 1992 and 32.9% receiving some form of treatment
(e.g., psychiatry services, complementary and alternative
medicine) between 2001 and 2003 (Kessler et al., 2005). This
leaves approximately 70% in need of services not receiving
them. Ethnic disparities with respect to access to mental health
care add important challenges of providing services. Ethnic
minority groups (e.g., African, Hispanic, and Native Americans) have much less access to care than do European Americans (e.g., McGuire & Miranda, 2008; Wells, Klap, Koike, &
Sherbourne, 2001). The lack of available services for most
people and systematic disparities among those services underlie the importance of delivering services in ways that can reach
many more people and target special groups.
Current Models of Delivering Psychological
Services
Psychosocial interventions refer here to the broad range of
psychotherapeutic services designed to treat or ameliorate
psychiatric disorders; social, emotional, cognitive, and behavioral problems; stress; and related sources of impairment.
These interventions draw on many conceptual views (e.g.,
cognitive, family, psychodynamic, humanistic), each with
multiple variations and in total comprising hundreds of specific treatment techniques (e.g., graduated exposure, interpersonal psychotherapy, multimodal psychotherapy). For this
article, our focus is on the model of delivery (i.e., how an
intervention is provided) rather than conceptual underpinnings
or techniques of specific treatments.
Dominant model of delivering services
The dominant model of delivery of the various therapy techniques is administration by a highly trained (e.g., master’s or
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Kazdin, Rabbitt
doctoral level) mental health professional in one-to-one,
in-person sessions with a client.2 Typically, clients visit a particular setting (e.g., clinic, private office, health care facility)
where the sessions are held. This model has historical connections to medicine and the “physician’s practice” model (C. M.
Christensen, Grossman, & Hwang, 2009). Indeed, many early
psychological techniques (e.g., Mesmerism, hypnosis, psychoanalysis) were provided by physicians (e.g., Anton Mesmer, James Braid, and Sigmund Freud, respectively) and
followed medical practice. Currently in the United States, the
majority of treatments are administered in the one-to-one,
in-person therapy model, and that applies to well-developed
evidence-based interventions as well as the much larger number of interventions yet to be evaluated empirically (e.g.,
Hersen, 2005; Kazdin, 2000). The one-to-one, in-person
model has been enduring, is in demand, and can deliver many
evidence-based interventions. Indeed, the now vast research
on evidence-based interventions supports not only scores of
specific interventions but, by implication, the dominant model
through which they are delivered. The focus of this article is
on reaching the majority of individuals who are in need of
treatment but are not being served by this model.
Perhaps the dominant model of providing in-person treatment by a trained mental health professional would be more
viable if the person-power pool were greatly increased. The
estimated number of mental health professionals in the United
States who provide services (i.e., 700,000; Hoge et al., 2007)
is likely to be an underestimate given the range of providers
under different auspices (e.g., pastoral work, counselors who
use other names but still provide therapy). Thus, no single
number ought to be considered complete. Even so, it is difficult to envision that the number could help sufficiently if 25%
of the U.S. population in any given year meets criteria for a
psychiatric disorder. Characteristics of the geographical distribution, interests, and composition of the highly trained professional workforce convey why sheer numbers alone will not
mitigate the problem of reaching many unserved individuals
in need.
First, in the United States, mental health professionals are
concentrated in highly populated, affluent urban areas and in
cities with major universities (Health Resources and Services
Administration, 2010). Thus, their distribution limits reaching
large swaths of people in need (e.g., rural areas, small towns).
Second, the majority of mental health professionals do not
provide care to populations and clinical problems for which
there is a great (children, adolescents) and expanding (the
elderly) need (IOM, 2011a, 2012). Too few mental health professionals are trained to provide services to these groups.
Finally, disproportionately few mental health professionals
reflect the cultural and ethnic characteristics of those in need
of care. Also, too few of those who are trained are in neighborhoods where their services are needed. For these reasons,
expanding the workforce to deliver treatment with the usual
one-to-one, in-person model of care is not likely to have major
impact on the burdens of mental illness.
Expansion of delivery models
One-to-one, in-person therapy is referred to as the dominant
model because clinical practice, graduate training, clinical
program accreditation, pre- and postdoctoral internships, and
research on psychosocial interventions draw heavily on this
model. The need to move to additional models has been recognized for decades (e.g., A. Christensen, Miller, & Muñoz,
1978; Ryder, 1988), but converging influences mentioned earlier have increased the calls for other models. Moreover, concrete options are now available and viable (e.g., Bennett-Levy
et al., 2010; Harwood & L’Abate, 2010; L’Abate, 2007;
Rotheram-Borus, Swendeman, & Chorpita, 2012). We add to
these calls by drawing on initiatives that are outside the mental
health professions and that reflect multiple influences related
to physical and mental health care.
Within the mental health professions, the model of delivering psychosocial interventions is expanding. Many of these
involve the use of technology and online versions of treatment
that draw on the Internet and other media, including video,
phone, and application software (apps) for smartphones and
tablets. Broad areas such as telepsychiatry encompass many of
these applications when used over distances (e.g., Wooton,
2003). Impetus for telepsychiatry included some of the features that underlie models that we present, namely, a shortage
of highly trained personnel to provide in-person treatments
when needed.
Some uses of technology are variants of the dominant
model in the sense that they are one-to-one and face-to-face
(e.g., individual sessions by Webcam) but extended to places
where there may be no service or suitable facilities available.
Other extensions include self-help interventions and a vast
array of techniques (e.g., online interventions, expressive writing techniques) that are available 24/7 and require little or
no assistance from a trained professional (L’Abate, 2007).
Several Internet, computer-based, self-help, and low-cost psychological interventions are evidence based and achieve
effects (i.e., effect sizes) at least on par with the similar technique administered in person by a trained mental health professional and are high in client adherence to and satisfaction
with treatment (e.g., Andrews, Cuijpers, Craske, McEvoy, &
Titov, 2010; Cartreine, Ahern, & Locke, 2010; Harwood &
L’Abate, 2010).
We mention these expanded versions of delivering therapy
because they are extensions of the dominant model, broaden
the reach of therapy to many who otherwise might not receive
services, and play an important role in addressing the challenges we highlighted previously. We are not covering online,
self-help, and other emergent technologies within the mental
health professions, because they have been well covered elsewhere (e.g., Andrews et al., 2010; Barak, Hen, Boniel-Nissim,
& Shapira, 2008; Mohr, Vella, Hart, Heckman, & Simon,
2008). We focus on models that are not widely recognized
for their potential in contemporary clinical psychology, psychiatry, and social work. These interventions can add to the
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Novel Models for Delivering Mental Health Services
dominant and expanded models of delivery and perhaps scale
up interventions in ways that these other models may not be
able to achieve.
Novel Models and Their Application to
Mental Health Care
We refer to the models of delivery as novel in the context of
the dominant way in which psychological services are provided within the mental health professions currently in the
United States. We selected models that have a subset of
characteristics:
Reach: Capacity to reach individuals not usually served
or well served by traditional service delivery
models.
Scalability: Capacity to be applied on a large scale or
larger scale than traditional service delivery.
Affordability: Relatively low cost compared to that
of the usual model, which relies on individual treatment by highly trained (master’s, doctoral degree)
professionals.
Expansion of nonprofessional workforce: Increases the
number of providers who can deliver interventions.
Expansion of settings where interventions are provided:
Brings interventions to locales and everyday settings
where people in need are likely to participate or
attend already.
Feasibility and flexibility of intervention delivery:
Ensures that the interventions can be implemented
and adapted to varied local conditions to reach
diverse groups in need.
The models are not unified in the sense of emanating from
a single source (e.g., discipline, movement) or having an overarching principle that allows us to classify them crisply.
Indeed, the models have emerged from multiple contexts,
including public health, medicine, and business. We highlight
the individual models, convey their origins and use, and
describe how they have been or might be used to address the
burdens of mental illness.
Task shifting
Definition and background. Task shifting is a method of
strengthening and expanding the health care workforce by
redistributing the tasks of delivering services to a broad range
of individuals with less training and fewer qualifications than
traditional health care workers (e.g., doctors, nurses). This
redistribution allows an increase in the total number of health
workers (e.g., nonprofessionals, lay individuals) to scale up
the scope of providing services.3 The concept and practice of
task shifting are not new and currently are in place in many
developed countries (e.g., Australia, England, United States)
where nurses, nurse assistants, and pharmacologists provide
services once reserved for doctors. Also, community health
workers, a term defined long before task shifting was developed, have provided specific health services (e.g., birthing,
neonatal care, immunization) in developing and developed
countries and with demonstrated efficacy (e.g., Bang, Reddy,
Deshmukh, Baitule, & Bang, 2005; Greenwood et al., 1989).
These workers consisted of individuals trained outside of traditional medical training positions. Task shifting represents an
extension in which multiple tasks are shifted to different levels
(e.g., nurses and midwives taking on more roles restricted previously to doctors, lay individuals taking on roles restricted
previously to nurses, and patients helping out in their own care
and care of others).
Task shifting emerged from global health initiatives, particularly in developing countries. These initiatives focused on treating and preventing infectious (e.g., malaria, HIV/AIDS,
tuberculosis) and noncommunicable disease (e.g., cardiovascular disease, diabetes, cancer, respiratory disease) and improving
living conditions and education (e.g., IOM, 2010, 2011b; United
Nations, 2000; WHO, 1978, 2011a). These initiatives provide
an important context because they contended with key challenges of meeting health care needs in many cultures, under a
variety of conditions (e.g., enormous resource constraints, geographical obstacles), where people in need of services were not
likely to receive them. Key strategies to address the problems
included reorganizing and decentralizing health services to
accommodate the limited traditional resources and infrastructure (e.g., medical personnel, hospitals).
Task shifting began in earnest with specific attention to the
treatment of HIV/AIDS (WHO, 2008). The epidemic and
spread of HIV/AIDS heightened the need to increase quickly
the delivery of services to unserved individuals and to reduce
the burden of the epidemic. The need for services in many
developing countries was sharply contrasted with traditional
means of providing care. For example, approximately 95% of
individuals with HIV/AIDS reside in developing countries and
almost two thirds of them in Sub-Saharan Africa. Yet, SubSaharan Africa has only 3% of the world’s health workers and
provides less than 1% of the world’s health expenditures (WHO,
2008). Globally, an estimate of an additional 2.4 million doctors, nurses, and midwives would be needed to meet national
and international goals (WHO, 2006). The United Nations
agreed to work toward access to prevention, treatment, care,
and support programs universally by 2010. To that end, the
range of workers recruited for health care expanded and
included nurses, midwifes, community residents (some of
whom were individuals living with HIV/AIDS) who could
provide specific services, support of others, and help to overcome stigma and discrimination in their local communities.
The majority of task-shifting applications have focused on
physical health in developing countries (e.g., Ethiopia, Haiti,
Malawi, Namibia) where shortages of human resources and
the burden of illness (e.g., HIV/AIDS) are acute. Empirical
evaluations have shown task shifting to rapidly increase access
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Kazdin, Rabbitt
to services, reach large numbers of individuals in need, and
yield good health outcomes and high levels of patient and
counselor satisfaction (WHO, 2008). The utility and effectiveness of the procedure were shown in high-income as well as
resource-constrained countries. This evidence also controverted concerns that task shifting leads to low-quality care or
that lay counselors would be less effective than professional
workers in the outcomes they achieve.
Applications to mental health. As physical health initiatives
expanded globally, mental health received increased attention
and became the source of its own set of initiatives.4 For example, in 2007, an international group of health researchers noted
that the burden of mental illness worldwide, the enormous
proportion of individuals not receiving treatment, and the
availability of effective interventions were among the key reasons why expansion and scaling up of mental health services
were “urgently needed” (LGMHG, 2007, p. 1242). Also, several lines of work demonstrated that physical health and mental health are integrally related (e.g., Boehm & Kubzansky,
2012; LGMHG, 2007; O’Donohue & Cucciare, 2005; Prince
et al., 2007; Sharan et al., 2009)—for example,
•• substance use and abuse directly affect morbidity and
mortality from physical disease (e.g., cardiovascular disease) but also from injury and death from all
causes,
•• physical health problems (e.g., failing health, physical
disability, diabetes, cardiovascular disease) are linked
to later mental health problems (e.g., depression),
•• individuals with mental health problems have much
higher rates of utilizing medical care services (e.g.,
emergency room visits, self-referral for medical
treatment), and
•• delivering mental and physical health services shares
several common barriers.
Task shifting was extended to mental health problems
because of its ability to be scaled up to provide services to
individuals who otherwise did not have access to care and its
adaptability to diverse countries, cultures, and local conditions. An exemplary application of task shifting to mental
health was a randomized controlled trial (RCT) of treatment of
anxiety and depression in India (Patel, Weiss, et al., 2010).
Twenty-four public and private facilities (including more than
2,700 individuals with depression or anxiety) received a
stepped-care intervention beginning with psychoeducation
and then interpersonal psychotherapy, as needed and as administered by lay counselors. The lay counselors had no health
background and underwent a structured 2-month training
course. Medication was available, as was specialist attention
(health professional) for suicidal patients. At 6 and 12 months
after treatment, the intervention group had higher rates of
recovery than did a “treatment-as-usual” control group administered by a primary healthcare worker, as well as lower
severity symptom scores, lower disability, fewer planned or
attempted suicides, and fewer days of lost work (Patel, Weiss,
et al., 2010, 2011). Overall, the study showed that lay counselors could be trained to administer interventions with fidelity
and that their interventions reduced prevalence of disorder in a
large sample.
This illustration conveys that task shifting, at least in developing countries, is beyond the stage of potential utility in
delivering mental health services for individuals meeting criteria for psychiatric disorder. Evidence from other studies conveys the impact on depression and schizophrenia (e.g., Balaji
et al., 2012; Rahman, Malik, Sikander, Roberts, & Creed,
2008). These demonstrations not only establish the clinical
utility of task shifting but add to the evidence that lay counselors can deliver effective treatment and that outcome effects are
not sacrificed in the process. Moreover, studies evaluated outcomes on a larger-than-usual scale for psychological intervention studies, evaluated and monitored treatment fidelity, and
included follow-up, among other features.
Key considerations. Task shifting has several features leading us to include it as model of delivery of psychological services. Table 1 summarizes these in relation to criteria we
mentioned previously. Task shifting has several additional
noteworthy features, including its applicability across countries (developed or developing) and across types of health care
needs (e.g., prevention, treatment; physical disease, mental illness). The approach emphasizes standardized treatments, a
decentralized delivery model, and simplified treatment protocols. Standardized training is provided to lay counselors, and
monitoring and evaluation are built into the system (e.g., to
ensure integrity of treatment, to evaluate outcomes). As a
model of delivery, task shifting is designed to provide interventions on a large scale and to reach individuals who otherwise would not receive services. These are key characteristics
needed for mental health services in both developed and
developing countries.
Task shifting is a multistage process that we have oversimplified to draw attention to the treatment delivery facet. The
process begins with consultation of experts, stakeholders (e.g.,
patient population) in a given location (e.g., country), national
endorsement by ruling political government, and attention to
regulatory requirements on a temporary and more permanent
basis that might preclude or limit delivery of treatment. In any
given application, task shifting requires coordination among
government agencies, nongovernment organizations, professional organizations, and local governments. This might make
task shifting more easily implemented in developing countries
where infrastructures (e.g., from local and national government, accrediting organizations) might be more amenable to
change or at least rapid change. Clearly, task shifting has its
own special challenges. In its favor is the demonstrated ability
of the model to deliver physical and mental health services, to
show positive outcomes on a large scale and in diverse circumstances, and to have an empirical base for guidelines about
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Novel Models for Delivering Mental Health Services
Table 1. Key Characteristics of Each Novel Model
Model
Task shifting
Disruptive innovation
Unconventional settings
Best-buy interventions
Lifestyle change
Social media
Reach
Scalability
Affordability
Expansion of
workforce
Expansion of
settings
Y
Y
Y
Y
Y
Y
Y
Y
Y
?
Y
Y
Y
?
?
Y
Y
?
Y
?
Y
?
?
?
Y
Y
Y
?
?
Y
Feasibility
and flexibility
Y
Y
Y
Y
Y
Y
Note: Y = yes, the model includes this characteristic; ? = the model may or may not include this characteristic. As conveyed in the text,
some models of delivery (e.g., best-buy, social media) have variants of how treatment is delivered and so our characterizations are broad
summaries.
implementing the model. There might well be special segments of the population (e.g., elderly) or segments of the country (e.g., rural areas) that are particularly underserved in the
United States as a point of departure to apply task shifting.
Disruptive innovations
Definition and background. Disruptive technology or disruptive innovations emerged from business rather than health
care (Bower & Christensen, 1995; C. M. Christensen, 2003;
C. M. Christensen et al., 2009). The concept pertains to a
change in a product or service that is not a linear, evolutionary,
or incremental step. Rather the product or service often provides a disruptive, disjunctive, or qualitative leap and develops or extends a market that is not otherwise being served.5
Disruptive innovation theory refers to the process by which
products or services that are complicated, expensive, and less
affordable move to novel delivery models and products that
change these characteristics.
The concept of disruptive innovation may not be familiar,
but the many innovative products and services that illustrate
its application are part of our routine daily life (C. M.
Christensen et al., 2009). For example, e-mail, free video conferencing, and text messaging are not mere extensions of earlier forms of communication (e.g., postal service, landline
phones) but a leap in new ways of staying in touch that are
rapid, very accessible, less costly, and with novel advantages
(e.g., rapid exchanges of text messages, photos, and video). As
a related example, the development of cell phones made phone
services available in many developing countries where service
was lacking or quite restricted because of the limited infrastructure and resources to install and maintain landlines. Cell
phone service “leapt over” the traditional barriers of providing
phone services in novel ways.
Disruptive innovations are evident in many domains,
including manufacturing (e.g., interchangeable parts, assembly line in car production), business (e.g., cell phone, smartphone, tablet), consumer purchasing (e.g., via credit cards,
smartphones, and PayPal), social networking (e.g., Facebook),
and health care (e.g., home pregnancy tests, medical robotics;
see C. M. Christensen et al., 2009). These innovations often
provide simpler, less expensive, or more convenient solutions
to problems and often can be scaled to reach people who
would not otherwise have access. Telemedicine, which refers
to the use of communication and information technology to
extend the reach of medical practice, is one example of a disruptive innovation that has changed how and where some
patients receive medical care (e.g., Roine, Ohinmaa, & Hailey,
2001). Other disruptive innovations in health care have utilized nonmedical settings, such as drug stores and shopping
malls, to provide a range of services to measure blood pressure
or cholesterol, treat various illnesses (e.g., allergies, pinkeye,
strep throat) and skin conditions (e.g., cold sores, minor burns,
wart removal), and provide vaccines. Patient referrals can be
can be made if the tests reveal the need for further diagnostic
work or intervention.
Direct preventive and treatment interventions can be provided to reach people more quickly than in traditional settings.
Providing flu shots at drug stores and grocery stores and at
schools (for children) is an illustration. A 2009 threatened epidemic (H1N1 [“swine flu”] virus) led to the U.S. government
urging expansion of settings to include retailers where the flu
shots could be administered (Centers for Disease Control and
Prevention, 2009). This was in recognition that the existing
infrastructure and means of providing inoculations would not
overcome the many barriers to reaching individuals in need
and achieving the necessary level of community immunization
(crowd or herd immunity) to protect the public.
Applications to mental health. Disruptive innovations
could provide more accessible ways of delivering mental
health interventions (see Rotheram-Borus et al., 2012). Many
interventions already have extended to mental health care
through the use of smartphones, tablets, the Internet, and video
conferencing (e.g., Backhaus et al., 2012; Barak et al., 2008;
Bennett-Levy, 2010). For example, smartphones and tablets
provide opportunities for assessing psychological states and
bringing interventions to individuals in their everyday lives.
The assessment can provide feedback in real time that can
activate treatment from one’s communication device. To
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illustrate, biofeedback (as an intervention for stress) in years
past required traveling to a facility (e.g., a lab) with the suitable equipment. Currently, many portable and affordable
devices (for measuring heart rate, blood pressure, blood glucose levels) are available for the public and can provide the
necessary feedback or periodic monitoring to extend biofeedback in everyday life (i.e., wherever the individual is at a given
point in time; e.g., Pallavicini, Algeri, Repetto, Gorini, &
Giuseppe Riva, 2009; Zhang, Wu, Wang, & Wang, 2010). Sensors that monitor heart or breathing rate and provide information immediately (e.g., in color or graphical display) can
prompt the use of relaxation and other self-management techniques (e.g., RelaxLine, 2010; StressEraser, 2012). Apps for
smartphones and tablets are constantly emerging and now will
allow assessment, feedback, and applications of interventions
that can change mental health care.
Online delivery of treatment is a disruptive intervention that
we already mentioned as an extension of the dominant model
of therapy. Multiple options are available online for the treatment of anxiety and depression. These programs often include
the same core cognitive behavioral treatment sessions as used
with in-person treatment (e.g., scheduling of positive activities,
identifying and challenging cognitive distortions) and are
divided into sessions (with video clips describing key information and assigned homework) that patients can complete from
home. There are now scores of other evidence-based self-help
psychosocial interventions for a range of psychological problems (Bennett-Levy et al., 2010; Harwood & L’Abate, 2010).
These interventions can leap over many of the usual barriers of
receiving treatment and expand on the dominant model of inperson, individual psychotherapy at a clinic.
When such disruptive innovations first emerge (e.g., personal computer, cell phone), they do not compete head-tohead with the traditional product (e.g., mainframe computer,
centralized computers in industry and on campuses, landline
phones, pay phones). Over time the innovation may begin to
compete and take over as the product develops and the use
expands. Perhaps innovative treatment delivery models that
are disruptive, such as computerized, online, and self-help
therapies, will have that same course.
Key considerations. Table 1 summarizes key features of disruptive innovations as a broad model of delivery. There are
many individual innovations that fall within the model, but
there are general characteristics worth noting. Typically, disruptive innovations make a product or service more affordable
and accessible, and these are key reasons for presenting this as
model of delivery of psychological services. When diagnostic
procedures and interventions are first studied, they often
require special skills. As the procedures develop and effects
become reasonably predictable, their administration can be
turned over to others (less expensive caregivers) and provided
in settings (outside of hospitals and clinics) with equal or better
quality than the higher cost counterparts (C. M. Christensen
et al., 2009). Evidence-based treatments for anxiety (e.g., systematic desensitization, graduated exposure, cognitive behavior therapy) initially relied on a small group of researchers and
clinicians (with master’s and doctoral degrees) who could
implement the procedures. These are now well-established
interventions that can be administered as self-help interventions or by lay counselors supervised by more trained individuals with demonstrated effectiveness (e.g., Bennett-Levy et
al., 2010; Dombeck & Wells-Moran, 2006). Thus, affordability and accessibility have been reduced, although the scale of
these latter extensions has been restricted.
Disruptive interventions often (but not always) are brought
to people where they are. This is distinguished from the traditional model of therapy that tends to bring people to the treatment (e.g., clinic, agency, hospital). Technology and online
services have allowed individuals to access services (e.g.,
assessment, intervention) in convenient, user-friendly, and
immediate ways free from the usual barriers that can impede
seeking or participating in treatment and are disruptive in that
sense. The challenge in developing disruptive innovations
(e.g., in mental health services) is establishing that quality is
not sacrificed by making services more accessible, by delivering them with less experienced providers, or by bringing them
directly to the clients. Once quality is reliably established,
convenience is the next domain that is usually developed,
which further increases accessibility (Christiansen et al.,
2009).
Interventions in unconventional (everyday)
settings
Definition and background. This model focuses on expanding care beyond traditional locales for services (e.g., clinics,
hospitals, outpatient offices) and into everyday settings where
people regularly attend or spend time. In this way, individuals
who may need clinical services but are not receiving them
through traditional venues can gain access to care. Disruptive
innovations already mentioned often are in settings (e.g., pharmacies, shopping malls) that are part of everyday life. Yet, the
separate treatment of everyday settings as a model is warranted because interventions in such settings have emerged
from different traditions (e.g., community psychology, community mental health settings) and emphasize place (i.e., setting) rather than the nature of change (i.e., disruptive) in the
innovation itself. Perhaps better stated, all disruptive health
care innovations are not necessarily in natural everyday settings. Also, all interventions in everyday settings are not necessarily disruptive. As a model of delivery, interventions in
unconventional and everyday settings open multiple opportunities to reach people not otherwise served. The specific settings include schools, workplaces, homes, neighborhoods,
prisons and juvenile retention facilities, churches, hair salons,
and barber shops, to name a few (e.g., Jürgens, Ball, & Verster,
2009; Linnan et al., 2001; Luque et al., 2011).
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Novel Models for Delivering Mental Health Services
An example of a natural setting for physical health care is
the beauty salon. Salons are an ideal setting for health education and interventions because of the large number of people
who are regularly served there and because socialization and
discussion of topics related to health and beauty occur regularly (Linnan & Ferguson, 2007; Solomon et al., 2004). Moreover, many individuals see their stylists and cosmetologists as
trusted and supportive, making them a potential source for
important information (Cowen et al., 1979; Solomon et al.,
2004). Several types of health programs (e.g., mammography
for breast cancer screening, cardiovascular disease prevention,
education for sexually transmitted diseases) have been based
in salons to promote critical health messages, specifically to
the African American community (e.g., Linnan et al., 2001;
Wilson et al., 2008).6 Typically, salon employees (e.g., stylists,
cosmetologists, beauticians) provide the intervention directly
to clients after receiving focused training (e.g., Lewis, Shain,
Quinn, Turner, & Moore, 2002; Sadler, Thomas, Gebrekristos,
Dhanjal, & Mugo, 2000; Wilson et al., 2008).
As an illustration, a stroke education program for African
American women was run through beauty salons in two urban
areas. Beauticians attended a brief training (conducted at a
one-time luncheon) and were provided with materials (e.g.,
pamphlets) to provide to their clients. They then educated their
clients (during regular appointments) about stroke risks, warning signs, and appropriate responses to clinical scenarios.
Women who received the intervention showed improved
knowledge of the signs of stroke and appropriate responses
(i.e., calling 911; Kleindorfer et al., 2008). In a larger scale
example, the Healthy Hair Starts With a Healthy Body Program included 700 stylists and over 14,000 clients in eight
Michigan communities (Madigan, Smith-Wheelock, & Krein,
2007). Stylists attended two 4-hr training programs about kidney disease, diabetes, and hypertension and were trained to
conduct two “chats” with clients. Participants in the program
reported increased exercise, improved diet, and greater contact
with medical professionals about related health issues. These
and many other such demonstrations have shown impact of
laypersons in everyday settings administering health-related
interventions.
Applications to mental health. Mental health care has been
provided outside of traditional settings for many years, including correctional facilities, the workplace, and schools (e.g.,
Roman & Blum, 1996; Rones & Hoagwood, 2000; Smith,
Sawyer, & Way, 2002). Indeed, school-based preventive and
treatment interventions for children and adolescents are used
routinely to provide services that focus on diverse clinical
issues, including conduct problems, depression, stress, substance use, and suicidality. At this point, perhaps the use of
schools is sufficiently common for preventive interventions to
be considered a conventional rather than unconventional
setting.
We are advancing the model to look for opportunities in
less-well-used settings where underserved populations can be
reached. As an example of a setting in use that might be
expanded, emergency mental health services are provided
through mobile crisis units (e.g., Guo, Biegel, Johnsen, &
Dyches, 2001). This form of care may be adapted to provide
general, nonemergency care to individuals who can benefit
from clinical interventions outside the context of a psychiatric
emergency. For example, a family might call and schedule a
visit with a mobile mental health unit because of concerns
about behavioral problems at school; the unit could arrive at
the family’s home (or a different predetermined location) at a
scheduled time for a consultation session to address these
issues. Alternatively, the crisis units may be adapted to serve
mental health needs during natural disasters, similar in form
and function to how mobile medical care is provided to underserved populations during such emergencies (e.g., Krol,
Redlener, Shapiro, & Wajnberg, 2007). In this case, mobile
units could provide trauma screening (and, subsequently, helpful resources and referrals) and general crisis management
strategies to high-risk individuals. In either scenario, high-risk
and underserved populations can be targeted, and mental
health care can be brought directly to the individual in their
homes and neighborhoods.
The settings used in physical health care interventions discussed previously (i.e., beauty salons) provide a guide to some
of the settings that the mental health field might utilize and
where applications can be scaled up. Many of the characteristics that make such settings feasible for health prevention and
intervention also make them suitable for mental health interventions. In fact, an existing program trains hair stylists to
assess anxiety and depression symptoms and assists them in
providing appropriate referral information to clients (Hanlon,
2011). If such programs were extended to the many beauty
salons in the United States (estimated to exceed 300,000;
Rudner, 2003), the potential reach of treatment to people who
do not receive services would be a significant beginning.
Key considerations. Among the many benefits of treatment in
everyday settings (see Table 1), the possibility of reaching
people who are unlikely to seek services through conventional
resources and settings is worth underscoring. With disruptive
innovations, we noted that treatments are often brought to
individuals rather than bringing individuals to treatment (e.g.,
clinic, hospitals). Everyday settings might be conceived as a
compromise of sorts—people still have to go places (beauty
parlors, nail salons, parks, playgrounds, restaurants, coffee
shops, shopping malls, grocery stores), but they go there anyway for other reasons. Treatment is brought to these settings
and to the people, which could be especially useful for those
who are not seeking their primary care physicians for advice
and, of course, for those who do not have primary care physicians. Everyday settings could be used to target special populations based on the settings that different groups are more apt
to attend. As a model of care, everyday settings offer several
additional benefits. Among them is the use of lay providers
(e.g., hair stylists, teachers) instead of traditional mental health
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professionals. This reduces the costs associated with care and
increases the ability to scale up a workforce to reach people in
need, in keeping with the emphases of task shifting.
There are challenges in moving treatments to everyday settings, related to the settings themselves (e.g., some settings are
better suited to interventions than others) and to the interventions (e.g., some types of treatments may be more readily
administered in natural settings). Promising intervention settings might include repeated contacts or visits (e.g., a setting
that people go to on a regular basis so that services and some
follow-up can be included), reputable and reliable providers
(e.g., individuals that clients will trust and consider credible
sources), and suitable duration and privacy of the interaction.
In spite of the challenges, this model has special opportunities
to move treatments to people in novel ways and to target
unserved populations based on the settings selected.
Best-buy interventions
Definition and background. Economics of health care have
added to the impetus to identify novel models of providing
services. A survey of world business leaders by the World Economic Forum indicated that chronic disease (e.g., cardiovascular disease, cancer) is a major threat to economic growth
globally (Bloom et al., 2011; WHO, 2011b). Disability and
mortality exert great economic impact not only on individuals,
families, and households but also on industries and societies
through consumption of health care services, loss of income,
productivity, and capital expenditures that could otherwise
support public and private investment. Best-buy interventions
have emerged from this context to designate interventions for
physical illnesses, particularly the control of chronic diseases
globally (IOM, 2010).
Best buy refers to an intervention for which “there is compelling evidence that is not only highly cost effective, but is
also feasible, low-cost (affordable), and appropriate to implement within the constraints of a local health system” (WHO,
2011a, p. 2). Best buy also includes features such as appropriateness for the setting (e.g., culture, resources), capacity of the
health system to deliver a given intervention to the targeted
population, technical complexity of the intervention (e.g.,
level of training that might be required), and acceptability
based on cultural, religious, and social norms. Impetus for
delineating best-buy interventions was an effort to help countries and policymakers make difficult choices on how to allocate resources for health care (WHO, 2011a). In addition to
best buys, “good buys” are occasionally distinguished and
refer to interventions that do not meet all the criteria for feasibility of delivery and cost but represent an expanded set of
interventions that can be made available as resources allow.
Delineating evidence-based best buys was conceived as an
economic tool to help countries assess how to achieve a given
amount of change, given the number of eligible individuals in
need of the intervention, the potential savings of those changes,
and the cost differences of alternative strategies, among other
variables (e.g., Chisholm, Lund, & Saxena, 2007; Chisholm &
Saxena, 2012; WHO, 2011b). The best-buy interventions can
vary for a given disorder and country because the cost of delivering a particular intervention in light of the health resources
and infrastructure will vary. However, best-buy interventions
have been delineated that are likely to have broad applicability
across countries.
For example, in one analysis four criteria (health impact,
cost-effectiveness, cost of implementation, and feasibility of
scaling up) were used to identify best-buy interventions that
would have significant public health impact on noncommunicable diseases, including cardiovascular disease, cancers, diabetes, and chronic lung disease (WHO, 2011a). Best buys for
cardiovascular disease and diabetes were counseling, multidrug therapy, and aspirin. These were selected in light of the
reduction of disease burden (e.g., DALYs, as defined in Footnote 1) and very low cost. A good-buy intervention was counseling for diabetes control for individuals over 30 whose risk
of fatal events was especially high. The intervention would be
quite cost-effective, but it has a higher cost (less affordable) to
deliver and is not feasible in many countries.
Applications to mental health. We mentioned previously
the intricate relations of mental and physical health. Several
best-buy interventions for physical diseases often focus on
domains of functioning that overlap with and are part of
behavior, lifestyle, and mental health. For example, reducing
tobacco and alcohol use and increasing healthy diets and physical activity are the foci of best-buy interventions for cardiovascular disease, cancer, diabetes, and chronic lung disease
(WHO, 2011a). For tobacco use, raising taxes, protecting people from tobacco smoke, warning about the dangers associated
with tobacco, and enforcing bans are estimated to save more
than 5 million deaths in 23 large low- and middle-income
countries over a 10-year period (see WHO, 2003). Similarly
for alcohol use, best-buy interventions included enhanced taxation of alcoholic beverages and comprehensive bans on
advertising and marketing, based on their favorable cost-effectiveness, affordability overall, and feasibility. Excessive alcohol use was identified for best buy for reducing the incidence
of cardiovascular diseases and cancers but extends to other
burdensome conditions (e.g., cirrhosis of the liver, depression,
traffic injuries and deaths; WHO, 2011a). It is likely that many
best buys for physical health will have added benefits and cost
savings in light of their favorable consequences for mental
health.
More explicit designations of best buys have been identified for select mental disorders. For example, for clinical
depression, generically produced antidepressant medication,
brief psychotherapy, and treating depression in primary care
qualified as best buys (Chisholm et al., 2007). For psychoses,
treating people with antipsychotic drugs and with psychosocial support is regarded as a best buy. Controlled trials of best
buys demonstrating their utility, scalability, and impact relative to treatments as usually conducted are not yet available
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Novel Models for Delivering Mental Health Services
from resources we could identify, and systematic research in
this area may yield surprising results about what interventions
actually warrant a best-buy designation.
Key considerations. As noted in Table 1, best-buy interventions emphasize cost-effectiveness, feasibility, affordability,
and scalability. Clearly, economic considerations play a central role. For example, in an evaluation from the United Kingdom, an expenditure of 1 British sterling (£; approximately
US$1.50) for intervention was estimated to save 5.0£ and 7.9£
(approximately US$7.50 and US$12.00) for early diagnosis
and treatment of depression and conduct disorder, respectively
(Knapp, McDaid, & Personage, 2011). Estimates such as these
are based on long-range benefits and savings (i.e., over the life
of the individual and for the period in which the intervention
will be administered to the population). Scalability and feasibility also raise economic considerations. Can the intervention
be delivered with available funding given the large swaths of
people in need and to the locales (e.g., rural areas, desert or
mountain regions) where delivery is needed?
Best-buy interventions are based on estimates of utilization
and impact. The importance of direct empirical tests is well
recognized once interventions are implemented. For example,
best-buy interventions administered on a large scale have been
used to improve health and educational performance in rural
China (Rural Education Action Project, 2012). Rural youth
have high rates of iron deficiency anemia, are nearsighted but
do not have glasses, and are infected with worms—all of
which have been associated with problems of concentration in
class and lower cognitive functioning, which limit educational
progress and contribute the continued cycle of poverty. A bestbuy intervention used lay individuals to counsel in nutrition
practices and provided eyeglasses, multivitamins with iron,
and deworming medication. RCTs (with wait-list controls)
revealed that the intended benefits were in fact achieved (e.g.,
Luo et al., 2011).
Direct tests are critical to ensure that well-intended, feasible, and scalable interventions yield the intended outcomes
and in fact are best or at least good buys. Also, as in any largescale intervention, sustaining the integrity of the intervention
can be a challenge. Interestingly, some of the best-buy interventions (e.g., selective taxes, bans on advertising for substance use and abuse) differ from the usual psychological
interventions and do not require individual compliance or
adherence to a regimen. We include best buy as a model from
which to select among evidence-based intervention options.
Lifestyle change
Definition and background. Lifestyle change or therapeutic
lifestyle change refers to intervention efforts that modify highrisk behaviors to reduce disease mortality and morbidity
(American College of Lifestyle Medicine, 2009; Egger, Binns,
& Rossner, 2008; National Center for Chronic Disease Prevention and Health Promotion, 2011). We use lifestyle change
broadly to include a range of behaviors in which individuals
can or do engage that positively affect health. Common exemplars are controlling diet, exercising, reducing or eliminating
consumption of alcohol and nicotine, and participating in
activities that can reduce stress, improve functioning, and alter
physical or mental health.
Lifestyle interventions have targeted behaviors, such as
smoking, alcohol consumption, diet, and exercise, in light of
their association with common chronic diseases and conditions, such as cardiovascular disease, diabetes, and obesity.
Yet diverse physical ailments benefit from lifestyle change:
cancer, chronic pain disorders, fibromyalgia, dyslipidemia,
multiple sclerosis, osteoarthritis, osteoporosis, and rheumatoid
arthritis (American College of Lifestyle Medicine, 2009).
Often lifestyle changes are part of a larger treatment regimen
(e.g., involving medication or surgery), or multiple lifestyle
changes are included as a package (e.g., improved diet, exercise, and weight management; National Center for Chronic
Disease Prevention and Health Promotion, 2011). However,
growing evidence suggests that lifestyle change alone can
have a remarkable impact on physical diseases. For example,
an RCT for men with early-stage prostate cancer (who had
chosen surveillance rather than conventional interventions)
found that individuals who engaged in a lifestyle change program that included changes in diet, exercise, and stress management were less likely to require conventional treatment
(e.g., prostatectomy, radiotherapy) than similar patients who
were receiving routine care (Frattaroli et al., 2008). These
results were obtained at both 1 and 2 years of follow-up, suggesting that conventional treatments (and the associated physical, psychological, and financial costs) can be significantly
delayed or avoided completely in some circumstances.
Applications to mental health. Lifestyle changes have
had favorable impact on symptoms of many psychological
disorders, including depression, anxiety, schizophrenia,
eating disorders, body dysmorphic disorder, substance use disorders, and cognitive dysfunction in physical disorders (e.g.,
Alzheimer’s disease; Ströhle, 2009; R. Walsh, 2011). The most
frequently used lifestyle changes are exercise and nutrition as
applied to physical health. Yet, lifestyle has been extended to
include a variety of other activities, such as spending time in
nature, engaging in recreational activities, being involved in
religious or spiritual activities, and volunteering and contributing to others, each with evidence on its behalf in relation to
improving physical and/or mental health (R. Walsh, 2011).
Depression provides an example of how lifestyle changes
can have significant impact on clinical dysfunction. For many
years, psychologists have incorporated some aspects of lifestyle change and various activities into treatment for depression (e.g., Dimidijian et al., 2006; Lewinsohn, 1975). The
specific activities are individualized but usually focus on exercise, social engagement, and recreational activities (e.g.,
Leahy, Holland, & McGinn, 2012). Lifestyle changes alone or
in combination with other interventions are effective for
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treating mild to moderate depression and similar in their
effects to medication and psychotherapy (e.g., Rimer et al.,
2012; Tkachuk & Martin, 1999). In fact, when compared to a
commonly used selective serotonin reuptake inhibitor, aerobic
exercise (40 min, three times a week) was associated with
lower rates of relapse at 6-month follow-up (Babyak et al.,
2000). Although much of this work has been conducted with
adults, applications have extended to children, adolescents,
postpartum adults, and the elderly (e.g., Hamer & Chida,
2008; Larun, Nordeim, Ekeland, Hagen, & Heian, 2006;
Sidhu, Vandana, & Balon, 2009).
Key considerations. Table 1 conveys key characteristics of
lifestyle changes in relation to other models we presented. One
of the most compelling advantages of lifestyle change is the
broad impact that such change can have. For example,
increased physical exercise can have multiple beneficial physical health outcomes (e.g., improved cardiovascular health,
reduced risk for obesity, metabolic disorders, and cancer) and
mental health outcomes (e.g., fewer depression symptoms,
reduced stress levels and anxiety, decreased substance use,
improved neurocognitive functioning; e.g., Brown et al., 2010;
Deslandes et al., 2009; Dunn, Trivedi, Kampert, Clark, &
Chambliss, 2005; McMorris, Tomporowski, & Audiffren,
2009). The broad effects on general well-being and physical
and mental health translate to reduced use of other health services and are likely to make lifestyle changes a best-buy
intervention.
Other noteworthy benefits of lifestyle changes are affordability (initial outlay of costs), cost-effectiveness (e.g., impact
in relation to few initial costs for many activities), flexibility
(e.g., lifestyle changes include multiple options that can be
selected for convenience and personal preferences), and wide
applicability (e.g., individuals with diagnosable or subclinical
psychological problems can benefit). Lifestyle changes may
also remove barriers to treatment (e.g., stigma, lack of nearby
services) for individuals seeking mental health services
(Corrigan, 2004; Pescosolido et al., 2010).
Many distinct activities and practices are encompassed in
the term lifestyle change; many psychological and physical
health goals can be the targets of such changes; and individuals of different ages and stages (e.g., children, the elderly) can
benefit from them. That very diversity of activities and practices may make this especially important as a model of
addressing mental health and reducing the burdens of mental
illness. An advantage of lifestyle changes is the range of
options beyond the familiar focus on exercise, diet, and
reduced alcohol consumption and beyond what the public
knows or what businesses are likely to promote in their interests in controlling health care costs. Also, lifestyle activities
can be used where individuals are in their everyday lives (e.g.,
daily routine, no special facilities) or in facilities (e.g., gyms,
parks, churches) that do not have the barriers (perceived and
real) associated with seeking mental health treatment. Lifestyle interventions are offered in everyday settings (e.g.,
schools for children and adolescents, workplace for adults)
and might be the first line of larger scale interventions and as
self-help or minimal lay counselor–assisted interventions.
Many of the challenges are familiar, such as getting individuals to adopt and adhere to lifestyle changes (e.g., exercising regularly). Novel aids (e.g., apps that facilitate monitoring
activity in real time) may assist in providing feedback, encouragement, and records of accomplishment. Because lifestyle
changes are not routinely seen as mental health treatment, basic
questions of such treatments have few answers (e.g., what lifestyle changes, for what problems, in what doses). Nevertheless,
existing evidence conveys important mental health benefits,
including alleviation of clinical dysfunction. As such, lifestyle
changes could have a major impact on the burdens of mental
illness if they were systematically scaled up.
Social media
Definition and background. Social media refers to content
that is widely available to the public and includes, as primary
examples, Web logs (blogs), social networking Web sites (e.g.,
Facebook), collaborative projects (e.g., Wikipedia), usergenerated content communities (e.g., YouTube), virtual social
worlds (e.g., Second Life), and virtual games (Kaplan &
Haenlein, 2010). These media vary in social dimensions (e.g.,
the amount of personal information that a user can disclose)
and media richness (e.g., the type of media content allowed by
the application). We highlight Internet-based applications to
convey some of the possibilities from this large category. Yet,
social media have a broad range of options, and they continue
to proliferate (e.g., Bennett-Levy et al., 2010).
Advances in social and communication technology are
increasingly part of daily life in light of an array of devices
(e.g., smartphones, tablets), multiple options for communicating (e.g., texting, e-mail, Facebook), and software of all kinds
that bring immediate access to virtually every facet of human
functioning (e.g., health care, religion, entertainment, work,
news). These technological advances have fostered cultural
changes in ways of communicating, socializing, obtaining
information, and accessing resources (Campbell & Park, 2008;
Ling, 2004). For example, social networking Web sites bring
individuals into contact with one another in novel ways but also
change the frequency and intimacy of those contacts. One can
instantly share news, information, photos, and videos with
large groups of people all across the world and quickly receive
rich feedback on the shared materials. Meetings and connections are much more “person based,” as individuals are accessed
and engaged in interactions wherever they are (Campbell &
Park, 2008). This is distinguished from “placed based,” such as
meeting at one’s home, at a gathering, or at a restaurant.
In health care, social media are used in many ways.
For example, public health officials use social media (e.g.,
Twitter) to track flulike symptoms, predict patterns in influenza outbreaks, and use that information to respond to minimize danger (Schmidt, 2012; Signorini, Segre, & Polgreen,
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2011). In terms of direct patient care, social networking
sites have been used to create thousands of different support
groups for diverse physical health problems (e.g., breast cancer, colorectal cancer, and diabetes; Bender, Jimenez-Marroquin, & Jadad, 2011; De la Torre-Díez, Díaz-Pernas, &
Antón-Rodríguez, 2012). Users can share messages with one
another and increase awareness (e.g., prevention, early detection) of critical issues. The groups also provide access to support for individuals who might not otherwise have access to a
support network or whose access might be limited by personal
or geographical barriers.
Applications to mental health. Social media can provide
interventions at the intersection of technology and social interaction. For example, blogging (i.e., writing regularly on a
blog) might be viewed as another medium for delivering one
of the many evidence-based expressive writing interventions
(e.g., for trauma; Frattaroli, 2006; Pennebaker, Mehl, &
Niederhoffer, 2003). Individuals who maintain blogs report
having a large group of friends and high rates of perceived
psychological support (Baker & Moore, 2008). Among adolescents with social difficulties (e.g., problems with peer relationships, inadequate support from friends), regularly writing
on a blog for 10 weeks (compared with keeping a nonblog
computer journal or a no-treatment control group) improved
self-esteem, reduced social-emotional distress, and increased
engagement in social activities (Boniel-Nissam & Barak,
2011).
The very nature of social networking Web sites (e.g., sharing thoughts, feelings, information with others) can make it an
ideal forum for identifying high-risk individuals and those in
need of mental health resources. In Taiwan, a recently developed program used Facebook as a means of assessing suicidality risk in adolescents (Chiang et al., 2011). After authorizing
the program to access some of their personal information (e.g.,
location, age, gender, e-mail address), adolescents were
prompted to complete a brief (five-item) questionnaire about
suicidal feelings. This information was stored in a database,
and adolescents who were determined as being high risk were
contacted by mental health professionals and were provided
resources or ongoing services through the Internet. This use of
social networking can facilitate both screening mental health
problems and coordinating services for individuals who may
not otherwise have access to care.
A growing area of research focuses on the use of virtual
social worlds (e.g., Second Life) as a “setting” for psychological intervention and support (Gorini, Gaggioli, Vigba, & Riva,
2008).7 Some aspects of these treatment programs closely parallel in-person therapy. For example, a therapist and client can
“meet” regularly for sessions in a virtual social world, with the
client’s avatar and a therapist’s avatar interacting through such
meetings. This type of treatment offers some of the same benefits of other Internet-based treatments (e.g., increased accessibility to rural areas) as well as some unique benefits, such
opportunities to easily create a community of supports in the
virtual world. Outcome research, still relatively sparse, shows
that effect sizes of virtual therapy are similar to those obtained
in more well-studied person-based treatments (Yuen et al.,
2012). Access to extensive support services (through the
online community and not a mental health professional) is an
important feature of some forms of virtual therapy. In fact,
researchers are creating expanded support communities in virtual social worlds for patients with diagnoses (e.g., borderline
personality disorder) that have demonstrated significant benefits from support through a therapeutic community (Good,
Gnanayutham, Sambhanthan, & Panjganj, 2011).
Key considerations. Social media have several characteristics that make them a model of delivery worth highlighting
(see Table 1). Among their unique characteristics is the opportunity for rapid connectivity. Blogs, social networking sites,
and other uses of technology allow for information to travel
quickly and be easily accessible to users. For example, when
Facebook made it possible for users to easily see if other users
were organ donors and, if interested, to sign up to be donors,
the number of organ donors increased substantially (by 700%
in some states) within days (Goldman, 2012). One could envision how critical mental health information, such as depression screenings, might be made widely available through
social networking sites. Furthermore, because of the opportunities for self-disclosure and general sharing of information
and resources, several social media outlets provide opportunities to increase general public awareness about mental health
issues and may serve to destigmatize treatment seeking.
The social component can positively influence behavior.
Knowing that others can see and track one’s activities (and
seeking and tracking the activities of other people) can change
attitudes, influence behavior, and foster seeking and obtaining
support. For example, a Web-based health promotion program
focused on helping individuals make small positive changes to
improve their overall health (Poirier & Cobb, 2012). Users
could make social connections (through the Web site) with
other users. The individuals with more social ties were more
engaged in the intervention based on self-reported behavior
change and use of the Web site and its resources.
The pervasive use of social media and emerging technologies might make this model of treatment delivery rich in
options going forward. Technological advances bring familiar
and novel challenges. Among them are privacy protections
and encryption of material. These are significant challenges
outside the context of mental health and therapy, and these
latter uses give new meaning to “identity theft.” Technology
will continue to advance in these areas. Social media as a
model of delivery greatly expand the reach of psychological
interventions, and expanding on both the intervention technique options within this model of delivery and the client protections is critical.
Other models and variants within a model
We have identified several models of providing but also conceptualizing psychological services that are not part of
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mainstream delivery of services and that might be used to
reach those who are underserved. We selected models to illustrate a range of options but did not intend to present all possible models. Indeed, within the models that we did cover, we
could not begin to elaborate the options. For example, lifestyle
changes encompass many interventions (e.g., use of meditation, spirituality, volunteering to help others), some of which
include their own literatures and evidence as effective ways of
addressing mental health (see L’Abate, 2007; R. Walsh, 2011).
Similarly, everyday settings include a plethora of options for
individuals of different ages and with varied interests, and we
merely illustrated a couple of locales.
Apart from not elaborating all options within a given
model, other models on the horizon might have been included
too barring space considerations. For example, social robotics
refers to a growing interdisciplinary field that incorporates
aspects of traditional robotics, computer science, engineering,
communications, and psychology (Hegel, Muhl, Wrede,
Hielscher-Fastabend, & Sagerer, 2009). Social robots exhibit
human social characteristics, including emotional expression,
communication skills, and nonverbal cues, and are engineered
to follow social norms that facilitate engagement in human
interactions (Fong, Nourbakhsh, & Dautenhahn, 2003).
Already social robots have been applied to health care, as in
the case of Autom, a robot that serves as a weight-loss coach
and provides feedback about health, tracks weight loss, and
engages in small talk and conversations that can be individualized (Ackerman, 2011; Kidd & Breazeal, 2008). In mental
health care, applications with autism spectrum disorder take
advantage of the social robot’s ability to interact with a child,
to engage in joint attention tasks, and to model as well as
respond to social cues (e.g., Atherton & Goodrich, 2011; Ricks
& Colton, 2010; Scassellati, 2005). Mounting evidence suggests that social robots, most often in the form of a pet (e.g.,
robotic dog) or another animal (e.g., seal [sans water]), can
indeed be useful therapeutic tools by reducing loneliness and
depression, increasing observed social interaction, and altering stress hormone levels (Banks, Willoughby, & Banks, 2008;
Wada & Shibata, 2007; Wada, Shibata, Saito, Sakamoto, &
Tanie, 2005). Social robotics is a fast-developing area and no
doubt will make mental and physical health services available
in novel ways.
Yet, another model on the horizon derives from contemporary research on social networking and contagion. Considerable research has linked physical and mental health problems
(e.g., obesity, substance abuse) to social groups, contagion,
and peers (Christakis & Fowler, 2007; Valente, 2003). Interventions are emerging that use networks strategically for therapeutic ends and diffuse intervention effects (e.g., lifestyle
changes) at a group level (i.e., network) rather than an individual level (see Valente, 2012). The novelty of social networks will be to intervene at the level of peer groups (e.g.,
schools, communities) and in ways that could be used for
treatment and prevention. Social robotics and social networking add to options that might extend the reach of mental health
interventions. For this article, we could not cover all options to
extend models of delivery. We selected a sample already in use
in health care and provide options that could reduce the burden
of mental illness if added to the dominant models of delivery
within the mental health professions.
General comments
Four points are important to underscore about the models we
presented. First, the models derive from different disciplines
and historical contexts but have overlapping features. For
example, task shifting, best buys, and treatment in everyday
settings often rely on lay caretakers and deliver the interventions where people function in their daily lives. These commonalities might be viewed and further developed as
components of models, in the same way that components or
common elements of evidence-based treatments have been
culled from multiple treatment techniques (e.g., Belkin et al.,
2011; Chorpita & Daleiden, 2009). These commonalities
might be considered as a template to which effective interventions might be added.
Second, the models that we presented might be dismissed
as nothing new or newsworthy and in that sense not “novel” at
all. Task shifting and disruptive innovations, for example,
have a history going back decades. Certainly, using lay counselors or paraprofessionals in the community (e.g., community
psychology) has an extensive history as well (e.g., Sarason,
1974). Yet, the models have evolved, and their methods of
delivery have taken on new urgency in light of global priorities in addressing the burdens of physical and mental illness
and greater recognition of their connection. Also, the models
rely increasingly on evidence-based interventions in the context of both physical and mental health care (e.g., treatments
for HIV, cognitive therapy for depression). By and large, the
models we discussed have received little attention in delivery
of psychological services from the mental health professions.
The models highlight new opportunities and treatment delivery options that can greatly extend the ways of providing
services.
Third, we are not advocating or dismissing any particular
model. We believe that a portfolio of models is needed (i.e.,
several models with overlapping reach that can cover the
swaths of individuals in need services) as noted elsewhere
(Kazdin & Blase, 2011). The dominant model of one-to-one,
in-person treatment has established itself as able to deliver
effective, evidence-based treatment but unable or less able, at
least so far, to reach most individuals in need. Other models
are needed to improve coverage of large swaths of unserved
individuals.
Fourth, we limited our discussion to the presentation of
models and omitted critical topics, such as how they might be
deployed. The sequencing or delivery order of interventions
and, perhaps, the models of delivery as well are very important. That is, what are the first lines of intervention or model of
delivery? We would like to provide a lower cost, easily
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Novel Models for Delivering Mental Health Services
accessible, and highly scalable intervention first, then proceed
to a more effortful, costly, and difficult-to-administer intervention only when needed. The notion of stepped care reflects this
sequencing and has been discussed frequently (e.g., Haaga,
2000; L’Abate, 2012; O’Donohue & Draper, 2011). Deciding
the sequencing of models of delivering treatment and the specific techniques is no less important than the models
themselves.
There has been such excellent progress in identifying
evidence-based psychosocial treatments. We extend the
empirical approach and spirit of that progress by advocating
for evidence-based models of delivery. Each model will raise
its own challenges and barriers, but that variation among models will allow multiple options for delivering and receiving
treatment and for making psychosocial interventions accessible. Moreover, many of the challenges and barriers of the
models we highlight already have the benefit of experience
and evidence-based guidelines for implementation (Patel,
Chowdhary, Rahman, & Verdeli, 2011; WHO, 2008).
Challenges in Moving Toward Novel Models
We focused on opportunities for expanding models of treatment delivery to showcase several options. We do not wish to
imply that the model of treatment delivery is the sole challenge for improving mental health in the United States.
Communication and mental health literacy
Utilization of services, no matter what the model of delivery,
will require better public understanding of the need for, benefits of, and access points to these services, a domain referred to
as health literacy (IOM, 2004). Generally, the public is more
aware of early signs of physical maladies (e.g., HIV, cigarette
smoking) and their consequences and options for prevention
and treatment than they are of signs of mental illness. Mental
health literacy refers to a broad area of the public’s knowledge
and beliefs about mental illnesses, including signs, characteristics, and methods of treating or preventing them (Jorm,
2012).
Failure to recognize the presence of a disorder or, if recognized, to identify options for intervention is an obvious impediment to delivering services. For example, among people who
seek treatment for anxiety or depression, considerable time
elapses (mean = 6.9 years) to recognize that the disorder is
present and additional time (mean = 1.3 years) to seek treatment (Thompson, Issakidis, & Hunt, 2008). Multiple surveys
show that the majority of the public does not recognize various
psychiatric disorders (see Jorm, 2012, for a review). Accurate
information about disorders and intervention options is related
to help seeking. Among the challenges in promoting new models of treatment delivery is to help the public understand mental illness, the early signs, and what can be done to prevent,
treat, and mitigate sources of dysfunction. The models of
delivery that we discussed can make treatment much more
accessible to more people in need of services. Yet, accessible
treatments will have impact only if they are accessed.
Efforts to improve mental health literacy have been effective. For example, at different levels (e.g., country-wide, single or multiple cities; Australia, Germany, and Norway,
respectively), efforts have included intensive information
campaigns and have improved literacy about disorders and
help seeking, but impact on actual help seeking is less clear
(Jorm, 2012). Communication efforts may require reaching
many members of a community so that individuals are influenced by a social network (e.g., neighbors) with others who
know and discuss available interventions (cf. Valente, 2012).
Also, communication campaigns may act synergistically with
other influences, including the availability of more accessible
interventions, and in that way contribute to enhanced access to
care (IOM, 2010). Much has been learned about strategies,
dose-response effects of varied communication strategies, and
how they exert impact (see IOM, 2010; Hernandez & Landi,
2011).
Novel models of treatment delivery will require continued
efforts to increase mental health literacy. The use of multiple
models of delivery can make the task more challenging
because more options are available for receiving psychosocial
interventions. Yet, those same models may make treatments
more accessible directly by fostering communication among
peers (e.g., neighbors, lay health care workers) and providing
intervention in settings with which potential consumers are
already familiar. Some of the models we highlighted (task
shifting, disruptive innovation, treatment in everyday settings)
bring treatment to where the people are, and those same models may enhance efforts at improving mental health literacy.
Assessment and monitoring
Initiatives in global health have underscored the pivotal role of
assessment of clinical dysfunction in effective treatment and
prevention (e.g., National Health Information System; WHO,
2004). Among the reasons, assessment is designed to help
policymakers make informed decisions about services that
could affect large swaths of individuals as interventions are
scaled up. Whether incidence and prevalence are reduced and
whether daily functioning is improved are empirical questions
and presumably apply to any model of delivering preventive
or treatment services.
In some of the models highlighted earlier, the strong assessment component was not described. For example, in best-buy
interventions, the process begins assessing the needs (e.g.,
scope of clinical dysfunction) and capacity of the setting (e.g.,
infrastructure and resources that might be used). Interventions
then are designed that are identified as likely best buys (IOM,
2011b). Assessment continues by monitoring costs, fidelity of
implementation, and clinical outcomes to confirm, among
other things, that the desired outcomes are achieved and ultimately whether best buys in fact are best buys. Similarly, in
task shifting, well-developed methods evaluate the effects of
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training lay caregivers, the fidelity of treatment delivery, and
impact on disorder (WHO, 2008).
Achieving the goals of reaching more people in need and
reducing the burden of mental illness would profit from, if not
require, national monitoring and surveillance on a regular
basis. Several models of large-scale assessment models are
already in place in the United States and illustrate possibilities
on which to build (e.g., Centers for Disease Control and Prevention, http://www.cdc.gov/yrbs; National Comorbidity
Study, http://www.hcp.med.harvard.edu/ncs/; Institute for
Health Metrics and Evaluation [Murray & Frank, 2008]). The
required step is to integrate assessment with models of treatment delivery. We mention assessment because of its central
role to achieving the aims toward which this article was
directed, namely reducing the burdens of mental illness. More
models and different models of delivery are needed, but the
data on impact are the arbiter of the value of these models in
both reaching individuals who are not otherwise served and
achieving impact on critical outcomes.
Moving forward to expand models of delivery
Applying novel models has multiple challenges, and describing viable options does not imply that adoption could begin
now. Among the weighty issues that govern treatment delivery
are financing of health care, legislation, social policy, and regulations and oversight at multiple levels (e.g., federal and state
regulations; professional organizations). These issues and barriers in delivering and receiving services are beyond the goals
of the present article. Considerable work has been done in
identifying such challenges and setting priorities.8 Here we
take up one question briefly: How do we move “here” (dominance of a treatment delivery model that serves as the foci of
training, research, and clinical practice) to “there” (expansion
of multiple models of delivery that are not covered, included,
or advocated in training or research)? For example, in clinical
psychology, accredited doctoral programs provide clinical
training in psychotherapy (individual, family, group) administered in person and require a year of internship where such
experience continues. The model of delivery has continued for
decades and continues as part of training and licensing. How
might changes come about to expand the range of models for
delivering treatment?
Charting how such changes often come about has been
articulated and illustrated in the context of disruptive innovations (C. M. Christensen et al., 2009) and other areas where
research moves from developing effective interventions to
their larger scale application (e.g., agriculture, health, manufacturing and business, technology; Rogers, 2003). The usual
path is change from without (i.e., noncompetitive services or
products emerge that are outside the system), examples of
which we gave earlier. Over time, as they become more convenient and accessible, they are applied more widely and cause
change in traditional views of how things are effectively done.
Some of this already is evident in mental health services.
Online and self-control therapies, many with a strong evidence
base, are still not competing with local therapists in town, and
we are not advocating that they ought to. Yet, as the evidence
base of such interventions is more widely discussed and developed, presumably treatment techniques and the models
through which they are delivered will be extended and eventually incorporated more often into training and services.
Conclusions
The article focuses on models of treatment delivery directed
toward reducing the burdens of mental illness and related conditions. The models are designed to provide affordable and
accessible interventions to reach the large swaths of individuals in need of psychological services but who do not receive
them. Inability of the dominant model to reach most individuals in need, systematic disparities in who is served by this
model, and soaring health care costs are among the reasons to
expand the models of delivery. Indeed, novel approaches to
treatment (e.g., peer based, use of lay workers, Internet and
phone based) increasingly are advocated precisely with these
reasons in mind (e.g., Heisler, 2006; Muñoz, 2010; RotheramBorus et al., 2012; Sarasohn-Kahn, 2012). Models we highlighted build on this larger movement to expand the reach of
psychological interventions.
We reviewed models that have as their point of departure
the goal of scaling up interventions so they can reach many
people in need, expanding the workforce as needed to permit
that, and bringing interventions to individuals. Applications in
physical health care have shown the viability of diverse models in situations where many individuals with a particular clinical problem cannot receive the traditional model of delivery
(e.g., coming to a clinic where a highly trained professional
provides care). The models we reviewed address many of the
delivery challenges surrounding physical health care and have
begun to be extended to mental health care (e.g., Belkin et al.,
2011; Patel et al., 2010; Patel et al., 2011). These applications
convey that the use of the models is not wishful or wistful
thinking. In addition, many of the issues for applying models
(e.g., training; supervision; ensuring fidelity of treatment
delivery; sustaining a lay workforce; integrating culture, ethnicity, and diversity into delivery) have empirical literatures
on which we could draw to move forward.
There are broader advantages to extending the reach of
mental health services. We focused on reducing the burdens of
mental illness broadly conceived. The statistics we cited (e.g.,
25% of the U.S. population meets criteria for at least one psychiatric disorder in a given year) might well be considered an
underestimate of the scope of dysfunction. We did not consider “subclinical” dysfunction for which impairment and
symptoms fall below a diagnostic threshold. These dysfunctions might be more readily addressed if there were low-cost,
highly accessible interventions that could be scaled to reach
large numbers. Indeed, a recent demonstration with subclinical depression using e-mail-based self-help indicates the
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Novel Models for Delivering Mental Health Services
effectiveness of such an intervention (Morgan, Jorm, &
Mackinnon, 2012). Treating subclinical or subthreshold dysfunction might have preventive benefits too because subclinical symptoms are a risk factor for onset of dysfunction.
Apart from subclinical dysfunction, we know from recent
national survey data that most individuals in the United States
experience moderate to high levels of stress (American Psychological Association, 2012). In addition, various other psychological conditions, experiences, or states (e.g., social
isolation and loneliness) are not diagnosable but take their toll
on both subjective well-being and physical health (e.g.,
Cacioppo & Patrick, 2008). More accessible and affordable
interventions brought to individuals in more convenient ways
might help psychological functioning among a variety of individuals who would profit from but not otherwise seek intervention. Impetus for the article was considering models of
treatment delivery that would help reduce the burdens of mental illness, but those models might reduce some of the burdens
of the periodic challenges that many—most of us—experience
even though our reactions may not rise to the level of a diagnosable disorder.
We did not discuss the benefits of extending mental health
services on physical health. Reducing the burden of physical
illness requires attention to and depends on the reduction of
mental illness and vice versa (Prince et al., 2007). Recently,
for example, addressing mental disorders has been regarded as
“the missing link” to effective HIV prevention, care, and treatment (National Institute of Mental Health, 2012). Psychiatric
impairment, particularly depression, is prevalent among individuals living with HIV (30%–50% of the people), and mental
illness influences access to care, seeking treatment, treatment
adherence, untoward levels of disease markers, and higher
mortality rates. Our article has argued for the need of novel
models of delivery to reduce the burdens of mental illness, but
reducing those burdens and some of the models we have discussed can have important implications for the burdens of
physical illness as well.
We know now from improved and more comprehensive
epidemiological research that the burdens of mental illness are
enormous, that our well-developed evidence-based treatments
are not reaching individuals in need, and that merely extending our evidence-based treatments to clinical practice with the
dominant model currently in use will not have the needed
impact. It is not the treatment techniques per se that are the
main issue but rather their use in a model that is not accessible
or affordable and cannot be easily scaled up to reach people in
need. Multiple models of delivery, some already shown to be
scalable, to reach large swaths of individuals in need are available. If we begin with the goal of reducing the burdens of mental illness, we include individual psychotherapy and new
variants (e.g., delivered online, delivered via self-help). But
we attend to other models too and evaluate our progress on
prevalence and incidence of dysfunction and daily functioning
on a national scale and ultimately across many nations. The
goal of this article was to foster consideration of novel models
that could make a difference in mental health; some of these
models already have in other contexts with similar barriers in
delivering health care.
Acknowledgments
This article was guest edited by Luciano L’Abate, Georgia State
University.
Declaration of Conflicting Interests
The authors declared that they had no conflicts of interest with
respect to their authorship or the publication of this article.
Notes
1. Disability-adjusted life year (DALY) is a measure of disease burden reflected by the estimated number of years lost owing to ill
health, disability, or premature death. One DALY = 1 year of health
life that is lost based on life expectancy. This is a measure used to
provide a single estimate of the burden by combining both morbidity
and mortality (see World Bank, 1993, for details).
2. Not all therapies focus on the individual. Group (e.g., 8–10 individuals), family, and couples therapies, for example, involve more
than one individual. These slightly expanded foci share the one-toone (unit rather than person) treatment delivered by a trained mental
health professional and are in keeping with the dominant model.
Adding a small number of individuals does not achieve objectives
toward which this article is directed (i.e., novel models to reach the
large swaths of individuals who are in need of services but do not
receive them).
3. Task sharing is a related term that is sometimes used interchangeably with, but occasionally distinguished from, task shifting. Sharing,
when distinguished, can mean lesser trained individuals working
with professionals (e.g., A. Walsh, Ndubani, Simbaya, Dicker, &
Brugha1, 2010), but the distinction is not consistently made or
required for this article.
4. Several such initiatives that focused on mental health include
Grand Challenges in Global Mental Health Millennium Villages
Program, Integrated Innovations for Global Mental Health,
Collaborative Hubs for International Research on Mental Health in
Low- and Middle-Income Countries, Program for Improving Mental
Health Care, among others (see Belkin et al., 2011; Patel, Chowdhary,
Rahman, & Verdeli, 2011; http://grandchallengesgmh.nimh.nih.gov/
about.shtml).
5. The term disruptive innovation is based on the fact that the new
product or service “disrupts” an existing market by changing who is
served and how the service is provided. The disruption makes things
simpler and more affordable. The disruption might not be to consumers but rather to established companies or markets. For example,
digital cameras and photography “disrupted” the market for, and the
business based on, film (chemical) photography. The former has not
eliminated the use of film, which is not the issue in disrupting the
market, but it has clearly led to a qualitative change in how most
people take photos. Technology was the initial term used, but it gave
way to innovation. As illustrated with further examples, innovation
better captures the breadth products and services, some of which do
not require a change in technology.
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Kazdin, Rabbitt
6. The unique and important role of beauty salons in the African
American community has been well documented (e.g., Gill, 2010).
Salons have been centers of economic, social, and political change,
and beauticians were catalysts for social activism. For example, during the civil rights movement, beauticians registered their customers
to vote and spread information about political rallies and demonstrations. This rich historical context has left the African American
beautician or stylist in a valued leadership role and as an ideal messenger of critical information about a variety of topics, including
health (Linnan & Ferguson, 2007).
7. This is distinct from virtual reality and virtual reality exposure
therapy, which use a variety of sensory cues and specialized equipment, such as head-mounted displays, to create a believable simulation of reality and a personalized setting for therapy (Bohil, Alicea,
& Biocca, 2011). Much of the work in virtual reality–based interventions has focused on anxiety (e.g., Riva, 2005) and traumatic experiences (e.g., Rizzo et al., 2010). Because many of these treatments
include a therapist (to assist in creating personalized experiences and
to help patients process those experiences), these forms of virtual
therapy are not included here.
8. The challenges for delivering mental health services have been
systematically identified by the Grand Challenges in Global Mental
Health Initiative, the National Institutes of Health, and the Global
Alliance for Chronic Disease (http://grandchallengeesmh.nimh.nih
.gov/). Several constituencies were involved (consortium of researchers, advocates, and clinicians from over 60 countries). From that,
1,565 challenges were identified for progress in mental health. This
was pared down to 154 challenges, then the top 40, and then 25 by
the final expert panel (Collins et al., 2011). The top 5 challenges for
reducing the burdens of mental illness included (a) integrate screening and services into routine primary care, (b) reduce cost and
improve supply of effective medication, (c) improve children’s
access to evidence-based care, (d) provide effective and affordable
and community-based care, and (e) strengthen the mental health
component in the training of all health personnel (Collins et al.,
2011).
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