Certified Peer Specialists’Perspective of the Barriers and Facilitators
to Mobile Health Engagement
Karen L. Fortuna
&Carly M. Goldstein
&Joseph E. Glass
&Jessica M. Brooks
Received: 13 November 2019 /Revised: 17 March 2020 /Accepted: 6 April 2020
#Springer Nature Switzerland AG 2020
This study examined certified peer specialists’perceptions of the barriers and facilitators to mobile health (mHealth) engagement.
A total of 267 certified peer specialists from 38 states completed an online survey. Of this sample, 74 certified peer specialists
completed open-ended questions. Data were analyzed from the 74 respondents who responded to open-ended questions.
Certified peer specialists identified previously unidentified facilitators including the augmented use of certified peer specialists
in combination with mHealth to improve engagement. One emerging theme identified was the belief that mHealth interventions
may promote social isolation if not designed appropriately. Certified peer specialists appear to prefer using tablets instead of
smartphones. Integrating certified peer specialists’perspectives of barriers and facilitators to mHealth engagement may promote
initial and sustained mHealth engagement among consumers with serious mental illness. Future research using implementation
science frameworks should examine these previously identified barriers and facilitators to mHealth engagement as correlates and/
or predictors of engagement among service users.
Keywords Serious mental illness .mHealth .Peer support .Implementation science
The use of mobile health (mHealth), such as smartphone-
based interventions, has modernized and innovated mental
health care and services for consumers with serious mental
illness (SMI) (i.e., people diagnosed with schizophrenia spec-
trum disorder, bipolar disorder, and persistent, refractory ma-
jor depressive disorder). Among people with SMI, mHealth
interventions have led to improved illness self-management,
relapse prevention, adherence to medications and/or
treatment, and provided psychoeducation, recovery support,
symptom monitoring, and promoted health and wellness
(Naslund et al. 2015). As the landscape of mental health ser-
vice delivery is transforming the way services are provided—
one constant remains the same—sustained mHealth engage-
ment among people with SMI is difficult (Naslund et al.
Research has examined engagement factors among people
with SMI by using both qualitative (Barnes et al. 2011;de
Leeuw et al. 2012;Deppetal.2010; Poole et al. 2012; Todd
et al. 2013; Proudfoot et al. 2007) and quantitative (Jain et al.
2015; Ben-Zeev et al. 2013) methods. This literature has de-
scribed distinctive barriers that adults with SMI encounter
when attempting to engage in mHealth interventions.
Barriers to device ownership have included affordability, lack
of interest, lack of necessity, inability to use a phone (Ben-
Zeev et al. 2013), and poor signal (Jain et al. 2015). Barriers to
device use that have been identified include environmental
barriers such as safety and privacy concerns (Barnes et al.
2011; de Leeuw et al. 2012; Poole et al. 2012; Anttila et al.
2012), physical barriers such as technical issues (Anttila et al.
2012; de Leeuw et al. 2012; Poole et al. 2012; Todd et al.
2013), psychosocial barriers such as the need for inclusion
of human support (Poole et al. 2012), concerns about the im-
pact of psychological state on mHealth intervention use
*Karen L. Fortuna
Geisel School of Medicine, Department of Psychiatry, Dartmouth
College, Lebanon, NH, USA
VISN 5 MIRECC Baltimore VA Medical Center Annex, 10 N
Greene St, Baltimore, MD 21201, USA
The Weight Control and Diabetes Research Center, The Miriam
Hospital, 196 Richmond St, Providence, RI, USA
DartmouthCenters for Health and Aging, 46 Centerra Parkway, Suite
200, Lebanon, NH 03766, USA
Kaiser Permanente Washington Health Research Institute, 1730
Minor Ave, Suite 1600, Seattle, WA 98101-1466, USA
Columbia University School of Nursing, 560 W 168th St, New
York, NY 10032, USA
Journal of Technology in Behavioral Science
(Barnes et al. 2011; Proudfoot et al. 2007;Toddetal.2013),
mobile phone literacy (Anttila et al. 2012; Poole et al. 2012),
and concerns about telling people what the smartphone was
used for (Depp et al. 2010).
Currently, research on understanding mHealth engagement
has been conducted with consumers with SMI (Barnes et al.
2011;Ben-Zeevetal.2013;Jainetal.2015; Poole et al. 2012;
Proudfoot et al. 2007;Toddetal.2013), nurses (Anttila et al.
2012), and formal and informal caregivers (de Leeuw et al.
2012). Emerging mHealth interventions are incorporating cer-
tified peer specialists as interventionists in service delivery
(Fortuna et al. in press; Fortuna et al. 2017). However, to
our knowledge, few studies have considered the perception
of certified peer specialists in understanding mHealth and
may be asked to use mHealth interventions for their own care
and the care of others.
Certified peer specialists are individuals who have both a
mental health diagnosis, are in recovery, and are trained and
accredited by a state or accrediting organization to provide
Medicaid reimbursable services (Solomon 2004). Certified
peer specialists as both consumers of mental health services
and an emerging workforce of mHealth interventionists
(Fortuna et al. 2017;2018a,b,c,d) would be particularly
skilled at articulating and understanding factors that impact
engagement in mHealth interventions in their dual expert-
consumer role. This study examined certified peer specialists’
perceptions of the barriers and facilitators to mHealth
An online survey was developed to assess certified peer spe-
cialists’perception of the barriers and facilitators of mHealth
engagement among adults with SMI. The survey was devel-
oped with input from certified peer specialists. For the pur-
poses of this study, we defined mHealth as tablets and
smartphone applications. A total of 12 survey items were de-
signed to assess certified peer specialists’perception of what
makes a smartphone or tablet difficult to use. Examples of
possible non-mutually exclusive answers included “cost of
the smartphone,”“reading is hard to do on a smartphone,”
“typing on a smartphone is hard,”“I would lose my
smartphone,”“Idon’t understand how to use a smartphone,”
and “I am not interested in a smartphone.”Possible responses
included “yes,”“no,”or “not sure.”
Qualitative data was organized around three follow-up,
open-ended questions: “does anything make using a
smartphone hard?”and “does anything make using a tablet
hard?”Finally, certified peer specialists were asked a final
open-ended question, “what would encourage consumers
you work with to use a smartphone App daily to practice
taking care of themselves—like dieting and exercising?”
Their responses to the three open-ended questions were sys-
tematically recorded and analyzed in the same form as quali-
To be eligible for the study, respondents needed to (1) have
finished a state-accredited training program and received a
peer support certification, (2) be a US resident, and (3) be at
least 18 years or older. From February 2018 to April 2018,
respondents were recruited and invited to participate in the
online survey through announcements posted on websites,
email lists, and newsletters affiliated with certified peer spe-
cialist organizations. At the time of survey closure, 289 par-
ticipants started the survey. However, a total of 22respondents
(< 10%) were excluded from the final dataset due to missing
data, resulting in a sample size of 267 participants. A total of
267 respondents completed the survey questions. Of these
individuals, 74 responded to the open-ended questions. Data
were analyzed from the 74 respondents who responded to
Upon receiving exemption status and approval from the
(blinded for review) Institutional Review Board to conduct
this study, respondents were recruited to participate in the
online survey. Prior to starting the survey on Qualtrics, respon-
dents read an informed consent statement that provided details
on the study’s purpose and assurance that any level of partic-
ipation was voluntary in nature. Respondents were informed
that the data collected would be confidential and anonymous
(i.e., we did not require the reporting of any personally iden-
tifiable or sensitive information). Finally, respondents were
told that the survey would require about 20 min to complete
before deciding whether to provide their consent.
Respondents were not compensated for participation.
Data analyses were performed using the Statistical Package
for the Social Sciences, version 22 (IBM Corp. 2015).
Descriptive statistics (i.e., frequencies and percentages) were
used to describe the demographic characteristics of the re-
spondents (Table 1).
Using thematic analysis, we organized and analyzed the
qualitative, open-ended data responses. The first two authors
developed a codebook that included a priori researcher-driven
codes (Martin and Turner 1986). Barriers to and facilitators of
engagement in mHealth interventions were organized into two
broad themes “intervention characteristics”(i.e., features of
the intervention that may impact engagement such as the per-
ceived benefit of the intervention and cost of the intervention)
and “characteristics of individuals”(i.e., characteristics of in-
dividuals that may impact engagement such as beliefs about
the mHealth intervention).
In order to include diverse perspectives in the process, the
codes were first discussed among the group of researchers and
then additional codes and operational definitions were added
J. technol. behav. sci.
to the codebook (Martin and Turner 1986). The final codes
were applied to all qualitative data responses, and the first two
authors sorted the codes and clustered the codes intooverarch-
ing themes. Based on thematic analysis, the first and second
author summarized these themes that were representative of
the different codes (Braun and Clarke 2006). Within-group
consensus or disagreements were assessed to check for reli-
ability and validity.
A total of 267 respondents completed quantitative survey ques-
tions. Of these individuals, 74 responded to the open-ended ques-
tions. Data were analyzed from the 74 respondents from 18 states
who responded to open-ended questions. The mean age of re-
spondents included in the data analysis was 50.9 years (SD =
12 years), with a range of 21 to 77 years. Most of the respondents
were identified as female (80%; n= 59) and Caucasian (77%;
n= 57); the majority (66%; n= 49) were currently employed at
least part-time or full-time as a certified peer specialist. Of those
who felt comfortable disclosing their mental health diagnoses
(N= 43), 30.2% of respondents reported a diagnosis of major
depressive disorder, 25.5% reported bipolar disorder, 20.9% re-
ported post-traumatic stress disorder, 9.3% reported alcohol/
substance use disorder, and 13.9% reported schizophrenia spec-
There were a total of 96 non-mutually exclusive open-ended
responses. Specifically, 70 responded to “does anything make
using a smartphone or tablet hard?,”66 responded to “does any-
thing make using a tablet hard?,”and 30 responded to “what
would encourage consumers you work with to use a smartphone
App daily to practice taking care of themselves—like dieting and
exercising?”Of these, 16 responses were excluded for being
irrelevant. A total of 80 open-ended responses were analyzed
from 74 certified peer specialists from 18 states.
We identified seven final codes relating to the overarching
themes on barriers to and facilitators of mHealth engagement.
Each of the seven codes was classified into one of the two
themes. The themes included intervention characteristics (i.e.,
affordability; formal training; connectivity; peer support
[emerging]) and characteristics of individuals (i.e., physical
and psychological barriers to mHealth engagement, beliefs,
and preferences; mHealth interventions may promote social
isolation [emerging theme]). Although data could be classified
into more than one domain, we opted to assign qualitative text
to the “best fit”domain.
See Table 2for selected quotes.
Affordability The most prevalent theme in this domain represent-
ed peer specialists’view that the cost of smartphones and data
plans deterred mHealth engagement. “Affordability”was defined
as the ability to purchase smartphones and data plans, either
through government subside or personal income. For example,
certified peer specialists stated that “lower costs of smartphones
[would] encourage participation”and “government subsidies
[are needed] for smartphones—not flip phones.”
Formal Training The second most prevalent theme within this
domain represented peer specialists’view on the issue that
formal training would promote mHealth engagement.
Certified peer specialists offered distinct mHealth training
topics. For example, certified peer specialists recommended
“education on how to get an email address password and use
email and texts contacts.”
Connectivity The third most prevalent theme within this do-
main represented peer specialists’view on the issue of Internet
connectivity as a barrier to engagement in mHealth. Certified
peer specialists suggested that location impacted connectivity.
For example, certified peer specialists indicated that “poor
signal in many areas (rural areas, my office is in the base-
Peer Support (Emerging) Peer specialists reported that the
inclusion of certified peer specialists may promote a human
connection in a mHealth intervention and promote engage-
ment. Certified peer specialists offered ideas on how to
Table 1 Sociodemographic characteristics of study participants whom
completed qualitative responses (N=74)
Characteristic n(%) or M(SD)
Mean (SD) 50.9 (12)
Female 59 (80)
Caucasian 57 (77)
Black/African-American 8 (10.8)
Hispanic or Latino 4 (5.4)
Asian 2 (2.7)
Other 3 (4.1)
Primary mental health disorder, N=43n(%)
Major depressive disorder 13 (30.2)
Schizophrenia spectrum disorders 6 (13.9)
Bipolar disorder 11 (25.5)
Post-Traumatic stress disorder 9 (20.9)
Alcohol/substance use 4 (9.3)
Personality disorder 2 (1)
Other 12 (5.8)
J. technol. behav. sci.
include peers in mHealth interventions. For example, certified
peer specialists recommended “peer support text messages for
those with mental health and physical health issues.”
Characteristics of Individuals
Physical and Psychological Barriers to mHealth Engagement
The most prevalent theme within this domain was physical
and psychological barriers to mHealth engagement, presented
as two subcategories including physical barriers (e.g., “phone
so hard to navigate and see”) and psychological barriers (i.e.,
“[problems] hearing voices”or “an actual and symptomatic-
driven fear of data breach”).
Beliefs and Preferences The second most prevalent theme
within this domain was beliefs and preferences that act bar-
riers or facilitators to mHealth engagement. For example, a
respondent reported that “I am change averse - using a flip
phone”(barrier) and “I much prefer using a tablet than a
mHealth Interventions May Promote Social Isolation An
emerging theme identified included peers’belief that
mHealth interventions could potentially exacerbate social
isolation if not engineered thoughtfully. For example, a re-
spondent reported that “when you use an app, you are alone
unless the app is purely to get people together, it isolates.”
Conclusions and Implications for Practice
This study examined the perceptions of certified peer special-
ists regarding barriers to and facilitators of mHealth engage-
ment. The most frequently reported barrier to engagement was
the affordability of the phone and the data plan. Certified peer
specialists identified previously unknown facilitators includ-
ing mHealth interventions designed for people with SMI
could improve engagement by including certified peer spe-
cialists in combination with mHealth. One emerging theme
identified was the belief that mHealth interventions may pro-
mote social isolation if not designed appropriately. Certified
peer specialists appear to prefer using tablets instead of
Despite government programs offering free phones and
data plans and the rising use of smartphones among people
with SMI (Glick et al. 2016), affordability is still an issue.
Advances for how Medicaid and Medicare reimburse clini-
cians for mHealth are vital to scale engagement in mHealth.
Table 2 Certified peer specialists’perspective of the barriers and facilitators to mobile health engagement (n=74)
Affordability (+) “lower costs of smartphones [would] encourage participation”
and “government subsidizes [are needed] for smartphones—
not flip phones.”
(-) “Limited data due to cost”;“cost”;
“monthly expense with the use of the phone”
Formal training (+) “clear short courses on using a smartphone,”“classes to help
them fix things as they come up,”and “education on how to get
an email address password and use email and texts contacts etc.
must show mental health consumers exactly how smartphone
will benefit them. They also must understand what they
CANNOT use the smartphone for.”
(-) “I need help keeping up with technolo gy”;“The smart phone is
so powerful, but I am old school and have not learned to take
advantage of it.”
Connectivity (--) “Poor signal in many areas (rural areas,
my office is in the basement)”;
(--) “Not as fast as other methods of accessing the internet
(--) “Internet connection”;
(--) “The one I have is very slow and now it is not
connected to my mobile phone so I cannot use it. [TABLET]”
Peer support: A human
factor to promote
(+) “peer support text messages for those with mental health and
physical health issues,”“real connection--- The older the peer,
the more need for a real person connection,”and “assess per-
son’s preference about including real person in interventions as
social challenges are current for some.”
Characteristics of individuals
(-) “phone so hard to navigate and see”and “difficulty with the
strain on the eyes when using in low light conditions and
age-related [problems] seeing text and hearing voices”and
psychological barriers (i.e., [problems] hearing voices”).
(-) “some are fearful of internet risks such as Identity theft”and
“not believing the CIA and NSA has tapped their phone or
Beliefs and preferences (+) “I much prefer using a tablet than a smartphone”;
(+) “laptop and smart phone enough [TABLET]”;
(+) “at times it is not necessary [TABLET]”
(-) “I am change averse - using a flip phone”;
(-) “Size not as convenient as smartphone size [TABLET]”
may promote social
(-) “WHEN YOU USE AN APP, YOU ARE ***ALONE***.
Unless the app is purely to get people TOGETHER, it
J. technol. behav. sci.
One popular program is SafeLink, which is a government
program that offers phones and wireless services free of cost
for eligible Medicaid recipients. Potentially, certified peer spe-
cialists, mental health providers, and consumers are not aware
of these programs or there are other barriers to accessing
SafeLink. For example, income restrictions, state reimburse-
ment restrictions, or poor connectivity may influence accessi-
bility. Researchers and clinicians can potentially access
SafeLink services for eligible consumers to facilitate research
studies or evidence-based mHealth-delivered clinical care. As
consumers may have an mHealth delivery preference—
smartphone or tablet—both options should be available
through government programs. As Medicaid and Medicare
continue to reimburse for a larger number of mHealth services
annually, specific barriers to accessing programs like SafeLink
for consumers should be identified, addressed, and
mHealth interventions designed for people with SMI could
improve engagement by including certified peer specialists in
combination with mHealth. This is consistent with the find-
ings suggesting that peer support might be a human factor that
promotes the use of smartphone-based interventions among
consumers with SMI (Fortuna et al. 2018c). Peer support
could be embedded into the mHealth intervention such as
interventions like PeerTECH (Fortuna et al. 2017). Another
option would be for interventions to integrate peer support
with a sequential, multiple assignment, randomized trial de-
sign to evaluate a stepped care model for mHealth interven-
tions. For example, consumers who show early warning signs
of suboptimal engagement can be re-randomized to receive
peer support in an effort to make the mHealth intervention
more effective and engaging for them. Exploring the role of
peer support in combination with future mHealth interven-
tions can elucidate the impact of peer support on mHealth
An emerging theme identified included certified peer spe-
cialists’belief that mHealth interventions may promote social
isolation. A higher proportion of people with SMI report feel-
ing socially isolated compared with people without SMI
(Adams et al. 2004; Badcock et al. 2015; Cacioppo et al.
2006), which in turn is linked to an increased risk of mental
and physical health issues (Shankar et al. 2011). Consistent
with the goal of community integration for people with SMI,
we posit mHealth interventions could potentially act as an
augmented intervention component—not the primary services
for people with SMI whom are at risk for social isolation and
loneliness. As this was identified as an emerging theme, ex-
ploring reports of social isolation among consumers involved
in mHealth interventions is needed to explain this perspective.
Several limitations should be considered when interpreting
the results of the current study. First, because of the use of an
online survey in which only people with Internet access could
complete the survey, the generalizability of the study is
restricted. The respondents who visited the survey website
may be more comfortable with technology, more financially
stable, and/or more educated. Second, the self-reported nature
of an online survey may lead to reporting bias. However, in
order to collect data from a large sample of certified peer
specialists, prior research has used online surveys to obtain a
represented sample (Fortuna et al. 2018a; Salzer et al. 2010).
Third, we are not able to report an accurate recruitment rate
because the online survey was sent to approximately 1500
certified peer specialists and we do not know how many po-
tential participants read the advertisements for the study. In
addition, the majority of the respondents in this study were
female certified peer specialists, with males markedly under-
represented. This is not the typical composition of a sample of
individuals with SMI—yet, this is the demographic composi-
tion of certified peer specialists. Fourth, we used a three-item
Likert scale “yes,”“no,”or “not sure.”While this is an im-
provement over a dichotomous scale, this three-item scale
may not fully represent the range of responses. Finally, con-
textual environmental of our findings is not known. Thus, for
implementation purposes, generalizing findings to specific or-
ganizations is not possible. However, these findings can be
used for pre-implementation in developing mHealth interven-
tions and designing for engagement.
In conclusion, this study advances our current knowledge
of barriers and facilitators that may impact mHealth engage-
ment. Certified peer specialists identified previously unidenti-
fied facilitators including the augmented use of certified peer
specialists in combination with mHealth to improve engage-
ment, personal beliefs, and preferences, and mHealth inter-
ventions may promote social isolation. Integrating certified
peer specialists’perspectives of barriers and facilitators to
mHealth engagement may promote initial and sustained
mHealth engagement of consumers with SMI. Future research
using implementation science frameworks should examine
these previously identified barriers and facilitators to
mHealth engagement as correlates and/or predictors of en-
gagement among service users.
Funding Information This study was funded by the Health Promotion
Research Center at Dartmouth, funded by a grant from the United States
Centers for Disease Control and Prevention (Cooperative Agreement U48
DP005018). Additional funding was received from the National Institutes
of Mental Health (T32 MH073553-11). Dr. Fortuna was supported by
Compliance with Ethical Standards
Conflict of Interest The authors declare that they have no conflict of interest.
Research Involving Human Participants and/or Animals All procedures
performed in studies involving human participants were in accordance
with the ethical standards of the institutional and/or national research
committee and with the 1964 Helsinki declaration and its later amend-
ments or comparable ethical standards.
J. technol. behav. sci.
Informed Consent Informed consent was obtained from all individual
participants included in the study.
Adams, K. B., Sanders, S., & Auth, E. (2004). Loneliness and depression
in independent living retirement communities: risk and resilience
factors. Aging & Mental Health, 8,475–485.
Anttila, M., Välimäki, M., Hätönen, H., Luukkaala, T., & Kaila, M.
(2012). Use of web-based patient education sessions on psychiatric
wards. International Journal of Medical Informatics, 81,424–433.
Badcock, J. C., Shah, S., Mackinnon, A., Stain, H. J., Galletly, C.,
Jablensky, A., & Morgan, V. A. (2015). Loneliness in psychotic
disorders and its association with cognitive function and symptom
profile. Schizophrenia Research, 169,268–273. https://doi.org/10.
Barnes, E., Simpson, S., Griffiths, E., Hood, K., Craddock, N., & Smith,
D. (2011). Developing an online psychoeducation package for bi-
polar disorder. JournalofMentalHealth,20,21–31. https://doi.org/
Ben-Zeev, D., Davis, K., Kaiser, S., Krzsos, I., & Drake, R. (2013).
Mobile technologies among people with serious mental illness: op-
portunities for future services. Administration and Policy in Mental
Health and Mental Health Services, 40(4), 340–343. https://doi.org/
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology.
Qualitative Research in Psychology, 3,77–101.
Cacioppo, J. T., Hughes, M. E., Waite, L. J., Hawkley, L. C., & Thisted,
R. A. (2006). Loneliness as a specific risk factor for depressive
symptoms: cross-sectional and longitudinal analyses. Psychology
and Aging, 21,140–151.
de Leeuw, R. J., Splunteren,P., & Boerema, I. (2012). Personal control in
rehabilitation: an internet platform for patients with schizophrenia
and their caregivers. Open Journal of Psychiatry, 2, 355–361.
Depp, C. A., Mausbach, B., Granholm, E., Cardenas, V., Ben-Zeev, D.,
Patterson, T. L., Lebowitz, B. D., & Jeste, D. V. (2010). Mobile
interventions for severe mental illness: design and preliminary data
from three approaches. Journal of Nervous and Mental Disease,
Fortuna, K., DiMilia, P., Lohman, M., Bruce, M., Zubritsky, C., Halaby,
M., Walker, R., Brooks, J., & Bartels, S. J. (2017). Feasibility, ac-
ceptability, and preliminary effectiveness of a peer-delivered and
technology supported self-management intervention for older adults
with serious mental illness. Psychiatric Quarterly, 89, 293–305.
Fortuna, K., Aschbrenner, KA., Lohman, MC., Brooks, J., Salzer, M.,
Walker, R., St George, L., & Bartels ,SJ. (2018a). Smartphone own-
ership, use, and willingness to use smartphones to provide peer-
delivered services: results from a national online survey.
Psychiatric Quarterly,89, 947–956. doi: https://doi.org/10.1007/
Fortuna, K., Naslund, JA., Aschbrenner, KA., Lohman, MC., Storm, M.,
Batsis, JA., & Bartels, SJ. (2018b). Text message exchanges be-
tween older adults with serious mental illness and older certified
peer specialists in a smartphone-supported self-management inter-
Fortuna, K., Storm, M., Naslund, J. A., Chow, P., Aschbrenner, K. A.,
Lohman, M. C., & Bartels, S. J. (2018c). Certified peer specialists
and older adults with serious mental illness’perspectives of the
impact of a peer-delivered and technology-supported self-manage-
ment intervention. Journal of Nervous and Mental Disease, 206,
Fortuna, K. L., Storm, M., Aschbrenner, K., & Bartels, S. J. (2018d).
Integration of peer philosophy into a standardized self-
management mobile health intervention. Psychiatric Quarterly, 89,
Fortuna, K. L., Naslund, J. A., LaCroix, J. M., Bianco, C. L., Brooks, J.
M., Zisman-Ilani, Y., Muralidharan, A., & Deegan, P. (in press).
Systematic review of peer-supported digital mental health interven-
tions for people with a lived experience of a serious mental illness.
JMIR: Mental Health.
IBM Corp. Released 2015. IBM SPSS Statistics for Windows, Version
23.0. Armonk, NY: IBM Corp.
Glick, G., Druss, B., Pina, J., Lally, C., & Conde, M. (2016). Use of
mobile technology in a community mental health setting. Journal
of Telemedicine and Telecare, 22,430–435. https://doi.org/10.1177/
Jain, N., Singh, H., Koolwal, G. D., Kumar, S., & Gupta, A. (2015).
Opportunities and barriers in service delivery through mobile
phones (mHealth) for severe mental illnesses in Rajasthan, India: a
multi-site study. Asian Journal of Psychiatry, 14,31–35. https://doi.
Martin, P., & Turner, B. (1986). Grounded theory and organizational
research. The Journal of Applied Behavioural Science, 22,141–157.
Naslund, J., Marsch, L., McHugo, G., & Bartels, S. (2015). Emerging
mHealth and eHealth interventions for serious mental illness: a re-
view of the literature. Journal of Mental Health, 24,321–332.
Poole, R., Simpson, S. A., & Smith, D. (2012). Internet-based
psychoeducation for bipolar disorder: a qualitative analysis of feasi-
bility, acceptability and impact. BMC Psychiatry, 12,139.https://
Proudfoot, J., Parker, G., Hyett, M., Manicavasagar, V., Smith, M.,
Grdovic, S., & Greenfield, L. (2007). Next generation of self-
management education: web-based bipolar disorder program.
Australian & New Zealand Journal of Psychiatry, 41,903–909.
Salzer, M. S., Schwenk, E., & Brusilovskiy, E. (2010). Certified peer special-
ists roles and activities: results from a national survey. Psychiatric
Services, 61,520–523. https://doi.org/10.1176/appi.ps.61.5.520.
Shankar, A., McMunn, A., Banks, J., & Steptoe, A. (2011). Loneliness,
social isolation, and behavioral and biological health indicators in
older adults. Health Psychology, 30, 377–385. https://doi.org/10.
Solomon, P. (2004). Peer support/peer provided services underlying pro-
cesses, benefits, and critical ingredients. Psychiatric Rehabilitation
Todd, N. J., Jones, S. H., & Lobban, F. A. (2013). What do service users
with bipolar disorder want from a web-based self-management in-
tervention? A qualitative focus group study. Clinical Psychology &
Psychotherapy, 20,531–543. https://doi.org/10.1002/cpp.1804.
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