Use of Digital Mental Health for Marginalized and Underserved Populations

Abstract

Purpose of review
Digital mental health (DMH) interventions provide opportunities to alleviate mental health disparities among marginalized populations by overcoming traditional barriers to care and putting quality mental health services in the palm of one’s hand. While progress has been made towards realizing this goal, the potential for impactful change has yet to be realized. This paper reviews current examples of DMH interventions for certain marginalized and underserved groups, namely, ethnic and racial minorities including Latinx and African-Americans, rural populations, individuals experiencing homelessness, and sexual and gender minorities.

Recent findings
Strengths and opportunities, along with the needs and considerations, of each group are discussed as they pertain to the development and dissemination of DMH interventions. Our review focuses on several DMH interventions that have been specifically designed for marginalized populations with a culturally sensitive approach along with other existing interventions that have been tailored to fit the needs of the target population. Overall, evidence is beginning to show promise for the feasibility and acceptability of DMH inter ventions for these groups, but large-scale efficacy testing and scaling potential are still lacking.

Summary
These examples of how DMH can potentially positively impact marginalized populations should motivate developers, researchers, and practitioners to work collaboratively with stakeholders to deliver DMH interventions to these underserved populations in need.

Full text

1 23
Current Treatment Options in
Psychiatry
e-ISSN 2196-3061
Curr Treat Options Psych
DOI 10.1007/s40501-019-00181-z
Use of Digital Mental Health for
Marginalized and Underserved Populations
Stephen M.Schueller, John F.Hunter,
Caroline Figueroa & Adrian Aguilera

1 23
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Curr Treat Options Psych
DOI 10.1007/s40501-019-00181-z
Technology and its Impact on Mental Health Care (J Torous and T Becker, Section Editors)
Use of Digital Mental Health
for Marginalized
and Underserved Populations
Stephen M. Schueller, PhD
1,*
John F. Hunter, PhD
1
Caroline Figueroa, MD, PhD
2
Adrian Aguilera, PhD
2,3
Address
*,1
Department of Psychological Science, School of Social Ecology, 4304 Social and
Behavioral Sciences Gateway, Irvine, CA, 92697-7085, USA
Email: s.schueller@uci.edu
2
School of Social Welfare, University of California, Berkeley, CA, USA
3
UCSF, Department of Psychiatry, Zuckerberg San Francisco General Hospital, San
Francisco, CA, USA
*Springer Nature Switzerland AG 2019
This article is part of the Topical Collection on Technology and its Impact on Mental Health Care
Keywords Technology IMental health IDisparities ImHealth ITreatment IHealth information technology
Abstract
Purpose of review Digital mental health (DMH) interventions provide opportunities to alleviate
mental health disparities among marginalized populations by overcoming traditional barriers to
care and putting quality mental health services in the palm of one’s hand. While progress has
been made towards realizing this goal, the potential for impactful change has yet to be realized.
This paper reviews current examples of DMH interventions for certain marginalized and under-
served groups, namely, ethnic and racial minorities including Latinx and African-Americans, rural
populations, individuals experiencing homelessness, and sexual and gender minorities.
Recent findings Strengths and opportunities, along with the needs and considerations, of each
group are discussed as they pertain to the development and dissemination of DMH interventions.
Our review focuses on several DMH interventions that have been specifically designed for
marginalized populations with a culturally sensitive approach along with other existing inter-
ventions that have been tailored to fit the needs of the target population. Overall, evidence is
beginning to show promise for the feasibility and acceptability of DMH inter ventions for these
groups, but large-scale efficacy testing and scaling potential are still lacking.
Summary These examples of how DMH can potentially positively impact marginalized popula-
tions should motivate developers, researchers, and practitioners to work collaboratively with
stakeholders to deliver DMH interventions to these underserved populations in need.
Author's personal copy

Introduction
Technology is regularly touted for its promise to over-
come health disparities, offering widely accessible, yet
low-cost resources that can transcend time, place, and
language. Technology, therefore, may play an especially
important role in mental health services. Minorities are
less likely to receive mental health services and when
they do are more likely to receive lower quality care [1,
2]. As such, digital mental health (DMH) tools might be
able to overcome several identified barriers to quality
care among marginalized and underserved populations
including access, cost, transportation, and stigma. DMH
tools can be tailored for different groups by adjusting
cultural and language aspects of DMH interventions that
might increase their appeal and uptake.
At the same time, however, technology has yet to
realize this potential. Health disparities still exist. The
barriers associated with technology ownership and use
may differ from those present in health care, and thus,
unique considerations might need to be taken into ac-
count for the development and deployment of digital
tools. Such barriers include lack of access or different
access to technology infrastructure including desktop
computers, mobile phones, and high-speed and wireless
Internet. For example, a recent study evaluating the use
of mobile health apps among diverse patients illustrated
challenges completing even the core functions of those
apps [3]. As such, if marginalized and underserved pop-
ulations are not considered during the development and
evaluation of DMH, these technologies might serve to
further entrench, rather than overcome, existing
disparities.
The goals of this paper are to review the current
examples of the use of DMH interventions for margin-
alized and underserved populations, to distill common-
alities among this work, and to identify considerations
and priorities for future development and research.
Defining marginalized and underserved populations
We draw our definition of marginalized and underserved populations from the
National Institute of Minority Health and Health Disparities which focuses on
producing equal opportunity for health for all populations [4]. This definition
is broader than racial and ethnic minorities and includes underserved rural
populations, those with fewer economic resources (e.g., individuals experienc-
ing homelessness), and sexual and gender minorities [5]. These populations
face discrimination and social disadvantages presenting challenges in many
areas of their life including access to mental health care. In addition to being
barriers to receiving care, discrimination and social disadvantages contribute to
stress and the development of mental health issues [6]. We consider a few
populations that fall under this broader definition as they provide good ex-
amples of the existing work on DMH interventions for marginalized and
underserved populations. This include ethnic and racial minorities including
Latinx and African-Americans, rural populations, individuals experiencing
homelessness, and sexual and gender minorities.
Ethnic and racial minorities
In this section, we will discuss interventions that have been deployed for
various racial and ethnic groups. Although work has investigated the use of
DMH for a multitude of racial and ethnic groups, here we highlight work
conducted in the USA within two groups specifically—Latinx and African-
Americans, because the work in these groups illustrates key points that
encompass strengths and issues involved in DMH deployment.
Technology and its Impact on Mental Health Care (J Torous and T Becker, Section Editors)
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In the USA, Latinx individuals own smartphones at the same rates as whites
(both 77%) [7]. This high ownership of smartphones among Latinx popula-
tions provides an opportunity for DMH interventions to be disseminated
among this population that has historically underutilized traditional mental
health services [8]. However, Latinxs are more likely to be “smartphone de-
pendent”compared with Whites, that is to own smartphones but lack broad-
band Internet access at home [7]. In addition, they are more likely than other
groups to interact via text messaging or mobile messaging platforms such as
WhatsApp. Glimpses into their specific use of these devices, such as messaging
platforms, might also speak to the forms and content of interventions that
might be relevant.
Despite low utilization of standard services, there appears to be an interest in
digital health among the Latinx population. In a survey of primary care Latinx
patients, 86% stated an interest in utilizing a health app and 40% expressed
motivation to use such apps daily [9]. Latinx smartphone users also report
being 20% more likely than whites to use a health app [10]. However, many
studies of digital health interventions do not include or have low rates of Latinx/
Hispanic participants. While there is more to be done, some researchers have
begun to target Latinx populations in their DMH interventions.
Digital and mobile health apps targeting Latinx populations have often
targeted depression [11,12,13••], among other mental health concerns such
as alcohol abuse [14] and disordered eating [15]. In a fully remote mobile app
intervention for depression, Latinxs responded equally well to the intervention
but dropped out earlier on average [13••]. In targeting this population, it is
important to incorporate culturally relevant themes. One example of cultural
differences within digital health experience is a finding that Spanish-speaking
Latinxs focused on the role of interventions in helping them feel cared for and
supported, while English speakers (which included one Latina, but the rest
white or African-American) emphasized the introspective and self-reflective
nature of the depression intervention [16]. Thus, tailoring DMH interventions
to focus on the provision of support and care may be particularly apt for
targeting Latinx populations.
While cultural tailoring and adaptation takes more time and effort, particu-
larly given the diversity of Latinx subgroups, one straightforward improvement
in this field would be to offer existing mental health apps in Spanish (and other
languages). Aguilera et al. [11] found that using automated text messaging as an
adjunct to group cognitive behavioral therapy (CBT) for depression in Spanish
resulted in significantly increased engagement, as evidenced by patients at-
tending more sessions and staying in treatment longer. These studies have all
reported generally positive qualitative feedback regarding the use of technolo-
gies to support therapeutic interactions. While translation does not always
ensure cultural relevance, it is an initial step in widening access to digital mental
health tools. Overall, researchers and developers have not taken enough ad-
vantage of developing digital health interventions for this engaged and high
need group.
The combination of substantial African-American health disparities coupled
with their high rate of smartphone ownership should situate them as an ideal
population for DMH interventions. Similarly to Latinxs, African-Americans
own smartphones at similar rates to whites (75% vs. 77%) but are much more
likely to be smartphone dependent. Far fewer studies, however, have focused
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specifically on DMH interventions for African-American populations, and the
potential to expand access for African-Americans through technologies has not
been realized. One impediment is the extremely low rate of African-American
recruitment in mobile health intervention studies [17]. For the most part,
researchers are not going beyond the one-size-fits-all approach for designing
DMH interventions and recruiting African-Americans into their studies. This
lack of involvement is compounded by the fact that to our knowledge, there are
no DMH interventions that have been specifically designed for African-
American populations.
Although no DMH interventions have been specifically designed and
evaluated for African-American populations, there are some examples of
DMH interventions successfully aiding in mental health management for
samples that are mainly comprised of African-American individuals. In each
of these examples, the DMH intervention used an adjunct to standard
treatment that was meant to enhance the available options for therapeutic
benefits. In one small study, a telemedicine intervention aimed at managing
PTSD symptoms for combat veterans helped to reduce symptoms and was
rated as preferable than face-to-face therapy [18]. In another illustration of
DMH being utilized by a primary African-American population, a digital
biofeedback tool was used to help women veterans reduce depression
symptoms associated with trauma [19]. Finally, a more comprehensive and
multimodal intervention called FOCUS produced significant and sustained
reductions in depression for a majority African-American sample of partic-
ipants [20]. These examples demonstrate that DMH interventions have the
potential to help African-Americans with mental health issues. However,
the lack of culturally appropriate tailoring, stakeholder input, and effective
recruiting efforts limits the effectiveness of these interventions for alleviat-
ing health disparities for this population. To better serve the African-
American population, more attention should be paid to their unique needs
and DMH interventions should be better designed and disseminated with
those needs in mind.
Rural populations
Mental health services are overrepresented in urban areas, making it chal-
lenging to receive appropriate and effective services in rural areas. Indeed,
the population is similarly skewed with 80% of the population living in 3%
of the US land mass, which presents additional challenges with reaching the
remaining 20% of the US population [21]. Telephones and video confer-
encing software have been used for years to connect those in need in these
rural areas to providers from other areas [22]. These technologies allow for
synchronous communication between a provider and client and help
overcome barriers of geography and transportation. However, such tech-
nologies still require providers who are available with expertise in the issues
that might arise in rural populations. In light of this, a few DMH interven-
tions have been developed and evaluatedwithaneyetowardsexpanding
effective treatment options in rural settings.
Unlike racial and ethnic minorities, technology access is much lower in rural
populations. For example, smartphone ownership is only 65% compared with
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83% in urban populations and broadband internet access is much lower as only
61% of people in rural areas can get access to broadband internet compared
with 96% in urban areas [23]. Therefore, although DMH interventions in rural
populations address a clear need, there remain infrastructural issues to over-
come to ensure that such interventions can be useful. Therefore, the type of
technology utilized may be an important concern in rural populations. DMH
interventions in rural populations might require preferencing more established
and available technologies that have less intensive data demands.
Early work in rural settings has mostly focused on understanding the
feasibility and acceptability of DMH interventions. As such, this work tends
to use small samples and evaluate metrics of engagement and satisfaction.
For example, one study explored Text4Strength, an interactive text messag-
ing intervention designed for students in rural communities [24]. Most
students (91%) engaged with at least one interaction, but that percentage
dropped considerably (52%) when examining those who engaged in at least
three interactions. Nevertheless, over 70% of the students found this inter-
vention helpful. Another series of studies described the development and
early evaluation of the SPIRIT app, a mobile health system to facilitate a
collaborative care treatment model for patients with post-traumatic stress or
bipolar disorders [25,26••]. Similar to Text4Strength, this app was evalu-
ated with a small group of individuals but showed some early promise with
high rates of usability and engagement. Another output stemming from
Bauer and colleagues [25] work in developing the SPIRIT app was the
discovery of unique principles of development that should be considered
when designing mental health technologies. These principles extended nine
previous principles for digital development with five additional principles:
(1) design for public health impact, (2) add value for all users, (3) test the
product and the process, (4) acknowledge disruption, and (5) anticipate
variability. These five additional principles align with other work that has
expanded participatory design and research principles for underserved
populations [e.g., 27]. As such, it is worth noting that although developing
DMH interventions should follow methodologies from broader technology
development, it requires a consideration of principles that might be unique
to the space. Overall, it seems that despite some additional considerations,
such as technology infrastructure, that must be addressed in these settings,
DMH holds promise for rural populations. More work needs to explore the
scalability of such interventions and whether scaling identifies additional
challenges that need to be overcome.
Individuals experiencing homelessness
Technology access among individuals experiencing homelessness is not as low
as some might believe. Data from adults experiencing homeless suggest that
most own mobile phones (93%) and many own smartphones (58%) [28].
Youth and young adults experiencing homelessness have even higher rates of
smartphone ownership, sometimes even as high as their housed peers [29,
30••]. However, individuals experiencing homelessness face other barriers to
using technology including keeping consistent phones phone numbers and
charging devices to keep them operational. They are also more likely to use
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older and cheaper models. Other considerations exist as well, as 86% of adults
experiencing homelessness were found to use Android devices [28], although
use of Android devices in the USA among the general population is only slightly
greater than half. Internet connectivity for individuals experiencing homeless-
ness is an important way to maintain continuity and connection in their life and
to seek housing and employment. As such, it may be a useful pathway to engage
individuals experiencing homelessness in mental health services.
Indeed, some early work has started to examine DMH interventions
oriented towards individuals experiencing homelessness. Homelessness
often consists of a complex array of challenges, including housing and
employment, which must be addressed when designing mental health
services. An overview of this early work illustrates some key points in
developing and deploying effective digital interventions for this population.
First, technology can serve as an important bridge to accessing a wealth of
resources. For example, the StreetConnect app provides a broad range of
referral resources intended to address the various needs of those experienc-
ing homelessness [31]. Second, for service providers working with individ-
uals experiencing homelessness requiresanappreciationofhowtoreach
them physically and digitally. Common platforms, such as social media,
might be a particularly effective way to stay connected, especially among
youth populations, and can be an effective tool for introducing interven-
tions [32]. Lastly, although early work has demonstrated that DMH inter-
ventions are liked and used, they have failed to establish clinical effective-
ness [30••]. Further work should establish that not only do homeless
populations like and use DMH intervention but that these interventions
produce a beneficial impact on their lives. Similar to work in rural popu-
lations, DMH for individuals experiencing homelessness shows promise as
technology appears to be a useful way to establish and maintain connec-
tions with this group. More work needs to determine, however, what goals
technology is most effective at achieving, for example, connection to ser-
vices, strengthened relationships, improved self-efficacy, and evaluating
DMH interventions in light of those goals. Such constructs might be the
precursors to changes in clinical symptoms. Additionally, when working
with individuals experiencing homelessness, one also needs to consider
broader factors that can promote better mental health such as housing,
employment, and social support.
Sexual orientation—LGBTQ
Sexual and gender minorities are faced with a unique set of challenges (e.g., social
ostracism) that can impact mental health [33]. LGBTQ individuals are signifi-
cantly more likely to have depressive symptoms than their heterosexual coun-
terparts but have difficulty accessing psychological services, likely due to the
challenges of finding a therapist who can specifically address issues relevant to
this population [34].Atthesametime,ratesoftechnologyownershipamong
LGBTQ individuals are comparable with their heterosexual peers [35]. LGBTQ
individuals are also very likely to seek support through digital means. At
CrisisTextLine, a text message-based crisis support service, 44% of the people who
text are LGBTQ [36] and gender and sexual identity issues account for 1.8% of the
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conversations [37]. The Trevor Project [38] is a support source providing crisis
interventions and suicide prevention services to LGTBQ youth (including a
partnership with CrisisTextLine) and provides supports in online spaces. Thus,
DMH appears particularly well suited to provide services to this population.
One of the earliest forms of DMH interventions, computerized cognitive
behavioral therapy (cCBT) provides a promising opportunity to assist LGBTQ
individuals because it can be tailored to specifically target the needs of this group
and deliver private assistance that might not be associated with of visiting a mental
health provider. For example, cCBT can include content that addresses heterosex-
ism, homophobia, lack of family support, social judgment, and issues about
Table 1. Summary of DMH considerations for each group
Group Ownership and use Strengths and
opportunities
Needs and considerations
Latinx 77% own a smartphone, and
20% own a cellphone but not
asmartphone[7].
Messaging platforms like
WhatsApp show higher rates
of adoption and use [51].
Potential for inclusions of
social aspects, as feeling
cared or supported [16].
Language considerations for
Latinx population who is
monolingual Spanish (or
might prefer Spanish for
some interactions). Higher
prevalence of mobile-only
Internet access.
African-American 75% own a smartphone, and
23% own a cellphone but not
asmartphone[7].
Opportunities to recruit into
clinical research where
typically underrepresented
[17]. Mobilize community
connection and support.
Higher prevalence of
mobile-only Internet access.
Low rates of inclusion in
clinical research. Low rates of
stakeholder involvement in
development process.
Rural populations 65% own a smartphone [21],
low rate of broadband
internet access at 61% [23].
Potential to transcend
geographic space and allow
remote visits and
appointments.
DMH interventions need to
consider infrastructure
challenges such as
bandwidth, access, and data.
Homeless
individuals
Estimates of smartphone
ownership range across
different methods of
surveying. One study found
58% of adults [28].
Ownership rates similar to
housed peers in some
subgroups (i.e., youth) [29].
Tendency to use Internet to stay
connected and seek services.
24/7 access to resources
might be beneficial to
address structural barriers to
access.
Access to technology might
overlook other challenges
such as keeping phones
charged, maintaining phone
numbers, and service plans.
Higher prevalence of
mobile-only Internet access.
LGBTQ Smartphone ownership does not
differ by sexual orientation
[35].
Higher rates of seeking mental
health information or
resources online. Digital
spaces allow potential to
connect LGBTQ individuals
who might lack strong
communities or support
where they live.
Initial pilot studies show
acceptability and feasibility
of tailored tools.
Culturally sensitive, stigma-free
content is important.
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coming out in a supportive and personalized fashion [39]. Unfortunately, few
DMH interventions include these elements [33] even though LGBTQ individuals
have expressed favorable views towards the integration of technological tools in
their treatment [40]. Despite these challenges—adaptability, mobility,
privacy—DMH interventions present an opportunity to overcome some of the
barriers of treatment by providing supportive mental health resources to this
population [34].
One way in which DMH can potentially impact the mental health of LGTBQ
individuals is through the adaptation of currently available DMH technology to
more specifically target their needs. One DMH depression intervention, SPARX,
was altered by researchers to Rainbow SPARX which contains specific elements
that made the services more appropriate for the LGBTQ population struggling
with symptoms of depression [41]. For example, the rainbow version includes
multiple culturally sensitive script changes to the intervention modules, avatars
that can be customized without strict gender norms, and content addressing
specific challenges among this population (e.g., coming out, getting bullied). In
a qualitative assessment of the application, participants strongly endorsed the
effectiveness and acceptability of Rainbow SPARX for treating their depression
[41]. In addition, the use of Rainbow SPARX has been shown to significantly
reduce symptoms of depression and anxiety, and these effects were maintained
at a 3-month follow-up [41]. The successful adaptation of SPARX into a
LGBTQ-specific intervention demonstrates that digital self-help resources can
be a valuable adjunct to face-to-face therapy for this population.
Tailoring an existing application for use by LGBTQ individuals is one route
for providing DMH services;however, it may be evenmore efficacious todesign
a novel application that specifically targets LGBTQ issues. Burns and colleagues
[42] sought the input of sexual minority men to inform the culturally appro-
priate design of an application that assists with the management of generalized
anxiety disorder and major depression. The end-product of this systematic
development process was the application TODAY!, which provides a range of
tools that received positive feedback from users [43•]. This ground-up approach
ensures stakeholder involvement and allows the DMH to specifically address
the issues that are most important to this LGBTQ population.
Research in this area is still in its infancy, and only a few instances
of specific DMH interventions for LGBTQ populations exist. However,
there is great potential for a positive impact on LGBTQ mental health
through digital means. LGBTQ individuals seem to be connecting online
and are overrepresented when looking at digital service seekers. Given
their tendency to seek resources online, designing culturally appropriate
interventions or adapting currently available interventions might meet
the unique needs of this group. Future studies should work to test the
efficacy of these potential interventions and establish guidelines for the
successful development and implementation of DMH for LGBTQ
individuals.
Future directions
The state of the evidence and development of DMH interventions for under-
served and marginalized populations mirrors themes that are present in DMH
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interventions more generally. Work has largely consisted of small pilot studies,
many which have demonstrated feasibility and acceptability, but few which
have demonstrated large-scale efficacy or scaling. For instance, a 2018 system-
atic review identified a number of pilot studies for digital interventions in
underserved groups, but noted that these interventions usually did not follow-
up with an implementation component [44•]. On one hand, this is not
surprising, given that focus on underserved and marginalized populations often
follows development of more general interventions as demonstrated by our
examples of tailoring or augmenting interventions for a specific population. On
the other hand, this is extremely disappointing given the discrepancy between
the need and supply of available mental health services for these populations
and the fact that following initial attempts provides the exciting potential to
build and expand. Thus, we offer a few suggestions that might help accelerate
and improve work that can increase the impact of DMH among underserved
and marginalized populations.
One possibility for the future of DMH is to develop tools that do not
require adaptation on the part of the developer to be relevant and
appropriate for different populations. This could include language ag-
nostic tools that leverage technology to create interactions based on
clinical science that do not have to be conveyed verbally. For example,
work has translated therapeutic evaluative condition [45] and attention-
bias modification [46] into mobile apps for widespread deployment. It is
worth considering how much can be developed that does not require
language especially when using digital media. Another possibility, how-
ever, would be to allow users of the DMH interventions to contribute to
the intervention themselves. Some DMH interventions have leveraged
peer involvement [i.e., 47,48], and peers from different populations
could assist in the delivery of content tailored to language or other
differences on these general use platforms.
Another important step is increasing the transparency within DMH
intervention as to whether individuals from different subpopulations
have used that intervention and whether it has worked for them. The
question most relevant to any potential user is not whether that inter-
vention has an impact on average but whether that intervention will
likely help him or her. Issues of the generalizability of benefits of DMH
across diverse groups is key. Some of the work described in this paper,
such as determining if DMH interventions contain content relevant for
specific groups or having people from groups use an intervention to
provide user feedback, is an important first step. But ultimately those
responsible for reporting outcomes on the impact of DMH interventions
should highlight this information.
Lastly, we offer a word of caution for the advancement of DMH. One area of
growth has been the use of artificial intelligence (AI) and machine learning to
provide deeply personalized interactions based on individualized understand-
ing. Such methods typically use historically collected data to make predictions
about new data being introduced to the model. Concerns have been raised
regarding the unwanted introduction of biases by AI and machine learning
models [49]. One example of potential problems in such interventions would
be an algorithm that can detect depressive symptoms based on automatic
recognition of voice in English-speaking patients not being applicable to
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Spanish-speaking patients. Furthermore, a smartphone application that
adapts a behavioral activation intervention according to emotional state
might suggest that the patient can engage in activities such as going to the
movies or spending an evening with friends. However, low-income indi-
viduals might experience financial and structural barriers that restrict
them from engaging in certain types of activities [50•]. For marginalized
populations, these biases may result in incorrect predictions or with-
holding of resources. Ways of overcoming machine bias include using
training data of diverse patient populations, ensuring that no group is
underrepresented, comparing model accuracy for different demographic
and social groups, and acquiring more diverse teams of programmers and
researchers, including different academic disciplines, to study the design
of fair and ethical models [49]. All of these suggestions align with the
broader need for inclusion of diverse populations early and often to
ensure broad benefit of DMH interventions. Otherwise, we run the risk of
further increasing existing health disparities (Table 1).
Conclusions
It is exciting to think that technologies can help overcome disparities in
mental health services and expand access and improve relevance for un-
derserved and marginalized populations. Table 1summarizes some of the
key points synthesized from the various populations we have discussed in
this paper. These populations have all been addressed in pioneering work
that has illustrated different ways in which technologies might overcome
disparities. Despite this initial progress, much work still needs to be done.
Pursuing thoughtful use of technology to address mental health needs
among underserved and marginalized populations requires an appreciation
of the strengths and needs within each group, the technological availability
and use of that group, and the interaction of these aspects to appreciate the
unique affordances of technology. Evidence is starting to show promise for
doing so, but large-scale efficacy, effectiveness, and implementation studies
are still lacking. As it stands, DMH interventions still hold a lot of potential
to help diverse groups, but now, that potential needs to be translated into
reality and action.
Compliance with ethical standards
Conflict of interest
Stephen M. Schueller declares that he has no conflict of interest. John F. Hunter declares that he has no conflict of
interest. Caroline Figueroa declares that she has no conflict of interest.
Adrian Aguilera reports personal fees from Care Message.
Human and animal rights and informed consent
This article does not contain any studies with human or animal subjects performed by any of the authors.
Technology and its Impact on Mental Health Care (J Torous and T Becker, Section Editors)
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