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Certified Peer Specialists’ Perspective of the Barriers and Facilitators to Mobile Health Engagement

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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.
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Certified Peer SpecialistsPerspective of the Barriers and Facilitators
to Mobile Health Engagement
Karen L. Fortuna
1
&Anjana Muralidharan
2
&Carly M. Goldstein
3
&Maria Venegas
4
&Joseph E. Glass
5
&Jessica M. Brooks
6
Received: 13 November 2019 /Revised: 17 March 2020 /Accepted: 6 April 2020
#Springer Nature Switzerland AG 2020
Abstract
This study examined certified peer specialistsperceptions 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 specialistsperspectives 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 samesustained mHealth engage-
ment among people with SMI is difficult (Naslund et al.
2015).
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
Karen.L.Fortuna@Dartmouth.edu
1
Geisel School of Medicine, Department of Psychiatry, Dartmouth
College, Lebanon, NH, USA
2
VISN 5 MIRECC Baltimore VA Medical Center Annex, 10 N
Greene St, Baltimore, MD 21201, USA
3
The Weight Control and Diabetes Research Center, The Miriam
Hospital, 196 Richmond St, Providence, RI, USA
4
DartmouthCenters for Health and Aging, 46 Centerra Parkway, Suite
200, Lebanon, NH 03766, USA
5
Kaiser Permanente Washington Health Research Institute, 1730
Minor Ave, Suite 1600, Seattle, WA 98101-1466, USA
6
Columbia University School of Nursing, 560 W 168th St, New
York, NY 10032, USA
Journal of Technology in Behavioral Science
https://doi.org/10.1007/s41347-020-00138-7
(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
engagement.
Methods
An online survey was developed to assess certified peer spe-
cialistsperception 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 specialistsperception 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,”“Idont 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 themselveslike dieting and exercising?
Their responses to the three open-ended questions were sys-
tematically recorded and analyzed in the same form as quali-
tative interviews.
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
open-ended questions.
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 studys 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 Analysis
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.
Results
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-
trum disorder.
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 themselveslike 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 fitdomain.
See Table 2for selected quotes.
Intervention Characteristics
Affordability The most prevalent theme in this domain represent-
ed peer specialistsview that the cost of smartphones and data
plans deterred mHealth engagement. Affordabilitywas 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 participationand government subsidies
[are needed] for smartphonesnot flip phones.
Formal Training The second most prevalent theme within this
domain represented peer specialistsview 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 specialistsview 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-
ment)impacted engagement.
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)
Age, years
Mean (SD) 50.9 (12)
Range 2177
Sex, n(%)
Female 59 (80)
Race, n(%)
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 voicesor 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
smartphone(facilitators).
mHealth Interventions May Promote Social Isolation An
emerging theme identified included peersbelief 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
smartphones.
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 specialistsperspective of the barriers and facilitators to mobile health engagement (n=74)
Facilitators Barrier
Intervention characteristics
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
[TABLET];
(--) 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
mHealth engagement
(+) 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-
sons preference about including real person in interventions as
social challenges are current for some.
Characteristics of individuals
Physical and
psychological barriers
to mHealth
engageme nt
(-) phone so hard to navigate and seeand difficulty with the
strain on the eyes when using in low light conditions and
age-related [problems] seeing text and hearing voicesand
psychological barriers (i.e., [problems] hearing voices).
(-) some are fearful of internet risks such as Identity theftand
not believing the CIA and NSA has tapped their phone or
tablet.
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]
mHealth interventions
may promote social
isolation
(-) WHEN YOU USE AN APP, YOU ARE ***ALONE***.
Unless the app is purely to get people TOGETHER, it
ISOLATES.
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 tabletboth 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
reevaluated.
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
engagement.
An emerging theme identified included certified peer spe-
cialistsbelief 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 componentnot 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 SMIyet, 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 specialistsperspectives 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
NIMH (K01MH117496).
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.
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... In this instance, peers who are persons who identify as having a lived experience of a mental health challenge and/or trauma contribute to the research process. This partnership has led to a series of studies [5,[10][11][12]. The peer-academic partnership was used in both the development and implementation of this study by developing the research questions, recruitment, retention, and development of the interview guide (Multimedia Appendix 1); conducting focus groups; and interpreting study findings. ...
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Background: The United Nations has called for wide-scale community mental health psychoeducation; however, few programs currently exist. Emotional Connecting, Empowering, Revitalizing (eCPR) is a community education and training program developed by individuals with a lived experience of mental health challenges or trauma. It is designed to provide community members with skills and confidence to support someone experiencing mental health challenges. Objective: This qualitative study aimed to examine the user experiences of diverse community members engaged in eCPR training. This study reviewed their attitudes toward training and opportunities for improvement in future implementations of training. Methods: eCPR training participants (N=31) were invited to participate in virtual focus groups between June 2020 and July 2020. Data were analyzed using the rigorous and accelerated data reduction method, which converts raw textual data into concise data tables to develop a codebook, and thematic analysis was performed to identify common themes. Results: The themes identified when analyzing the data included emotional holding and containment, training feedback, principles and practices of eCPR, implementation, connection in a digital environment, skills practice, and shared experiences. Conclusions: eCPR may benefit individuals from multiple, diverse demographics. It can enhance their ability to connect with others to understand what it means to be with someone who is experiencing a mental health challenge or crisis, to accept their own emotions, and to be confident in being their most authentic self in both their work and personal lives. eCPR may answer the call of the United Nations by bringing opportunities for authenticity and healing to community settings. Exploring the effects of delivering eCPR in communities on individuals experiencing distress is an important next step. This study found that eCPR may be beneficial to many groups of trainees with varying backgrounds and experiences. These findings are important, as they speak to the potential for eCPR to be implemented in a variety of community settings with the intention of working to improve mental health in everyday settings.
... In addition, apps can facilitate communication between patients and health care professionals through automated data exchanges. Quantitative analysis revealed a positive correlation between adherence and level of personal support during the study period for all health domains, which was also confirmed by previous studies [20,128]. Consequently, it can be assumed that hybrid systems that combine automated app content with elements of human support achieve higher adherence rates than those achieved by interventions without human support. ...
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Background: Mobile health (mHealth) apps show vast potential in supporting patients and health care systems with the increasing prevalence and economic costs of noncommunicable diseases (NCDs) worldwide. However, despite the availability of evidence-based mHealth apps, a substantial proportion of users do not adhere to them as intended and may consequently not receive treatment. Therefore, understanding the factors that act as barriers to or facilitators of adherence is a fundamental concern in preventing intervention dropouts and increasing the effectiveness of digital health interventions. Objective: This review aimed to help stakeholders develop more effective digital health interventions by identifying factors influencing the continued use of mHealth apps targeting NCDs. We further derived quantified adherence scores for various health domains to validate the qualitative findings and explore adherence benchmarks. Methods: A comprehensive systematic literature search (January 2007 to December 2020) was conducted on MEDLINE, Embase, Web of Science, Scopus, and ACM Digital Library. Data on intended use, actual use, and factors influencing adherence were extracted. Intervention-related and patient-related factors with a positive or negative influence on adherence are presented separately for the health domains of NCD self-management, mental health, substance use, nutrition, physical activity, weight loss, multicomponent lifestyle interventions, mindfulness, and other NCDs. Quantified adherence measures, calculated as the ratio between the estimated intended use and actual use, were derived for each study and compared with the qualitative findings. Results: The literature search yielded 2862 potentially relevant articles, of which 99 (3.46%) were included as part of the inclusion criteria. A total of 4 intervention-related factors indicated positive effects on adherence across all health domains: personalization or tailoring of the content of mHealth apps to the individual needs of the user, reminders in the form of individualized push notifications, user-friendly and technically stable app design, and personal support complementary to the digital intervention. Social and gamification features were also identified as drivers of app adherence across several health domains. A wide variety of patient-related factors such as user characteristics or recruitment channels further affects adherence. The derived adherence scores of the included mHealth apps averaged 56.0% (SD 24.4%). Conclusions: This study contributes to the scarce scientific evidence on factors that positively or negatively influence adherence to mHealth apps and is the first to quantitatively compare adherence relative to the intended use of various health domains. As underlying studies mostly have a pilot character with short study durations, research on factors influencing adherence to mHealth apps is still limited. To facilitate future research on mHealth app adherence, researchers should clearly outline and justify the app’s intended use; report objective data on actual use relative to the intended use; and, ideally, provide long-term use and retention data.
... In addition, apps can facilitate communication between patients and healthcare professionals through automated data exchange. Quantitative analysis revealed a positive correlation between adherence and the level of personal support during the study period for all health domains, which is also confirmed by previous studies [117,121]. Consequently, it can be assumed that hybrid systems which combine automated app content with elements of human support achieve higher adherence rates than interventions without human support. While the ideal ratio between human-computer interactions and sole human interactions in mHealth app interventions remains to be explored, new technologies such as conversational agents show promising results in simulating personal support without the need for human support and may enable increased levels of automation [122][123][124][125]. ...
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BACKGROUND Mobile health applications show vast potential in supporting patients and health care systems with the globally increasing prevalence and economic costs of non-communicable diseases. However, despite the availability of evidence-based mHealth apps, a substantial proportion of users does not adhere to them as intended and may consequently not receive treatment. Therefore, understanding factors that act as barriers or facilitators to adherence is a fundamental concern to prevent intervention dropouts and increase the effectiveness of digital health interventions. OBJECTIVE This review aims to identify intervention- and patient-related factors influencing the continued use of mHealth applications targeting non-communicable diseases (NCDs). We further derive quantified adherence scores for different health domains, which may help stakeholders plan, develop, and evaluate mHealth apps. METHODS A comprehensive systematic literature search (January 2007- December 2020) was conducted in MEDLINE, Embase, Web of Science, Scopus, and ACM Digital Library. Data on intended use, actual use, and factors influencing adherence were extracted. Intervention-related and patient-related factors with a positive or negative influence on adherence are presented separately for the health domains NCD-Self-Management, Mental Health, Substance Use, Nutrition, Physical Activity, Weight Loss, Multicomponent Lifestyle Interventions, Mindfulness, and other NCDs. Quantified adherence measures, calculated as the ratio between estimated intended and actual use, were derived for each study and compared with qualitative findings. RESULTS The literature search yielded 2862 potentially relevant articles, of which 99 were included as part of the inclusion criteria. Four intervention-related factors indicated positive effects on adherence across all health domains: (1) personalization or tailoring the content of the mHealth app to the individual needs of the user, (2) reminders in the form of individualized push notifications, (3) a user-friendly and technically stable app design, and (4) personal support complementary to the digital intervention. Social and gamification features were also identified as drivers of app adherence across several health domains. A wide variety of patient-related factors like user characteristics or user recruitment channels further affects adherence. Derived adherence scores of included mHealth apps averaged 56.0%. CONCLUSIONS This study contributes to the scarce scientific evidence on factors positively or negatively influencing adherence to mHealth apps and is the first to compare adherence relative to the intended use of various health domains quantitatively. As underlying studies mostly have a pilot character with short study durations, research on factors influencing adherence to mHealth apps is still limited. To facilitate future research on mHealth app adherence, researchers should clearly outline and justify the app's intended use, report objective data on actual use relative to the intended use, and ideally, provide long-term usage and retention data.
... Authors initially developed the first version of the decision-support items, which were based on digital peer support competencies that have been documented in Collins-Pisano and Fortuna (under review) and barriers and facilitators to using technologies as identified by service users and peer support specialists. 30 The initial decision-support tool included the following domains: security/privacy, costs, usability, accessibility, and recovery. ...
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Peer support specialists (i.e., lay interventionists representing one of the fastest-growing mental health workforce) are increasingly using technologies to support individuals with mental health challenges between clinical encounters. The use of technology by peers has been significantly increased During COVID-19. Despite the wide array of technologies available, there is no framework designed specifically for peer support specialists and service users to select technologies to support their personal recovery. The objective of the study was to develop a Decision-Support Tool for Peer Support Specialists and Service Users to facilitate shared decision-making when choosing technologies to support personal recovery. The study used an iterative co-production process, including item formulation and a series of group cognitive interviews with peer support specialists and service users (n=9; n=9, n=4). The total sample included 22 participants: peer support specialists (n=18, 81.8%) and service users (n=4, 18.2%). The final version of the Decision-Support Tool for Peer Support Specialists and Service Users (D-SPSS), includes 8 domains: (1) privacy and security; (2) cost; (3) usability; (4) accessibility; (5) inclusion and equity; (6) recovery principles; (7) personalized for service users’ needs; and (8) device set-up. Our study found that involving peer support specialists and service users in the design and co-production phase of a decision-support tool is feasible and has the potential to empower both peer support specialists and service users, and potentially increase engagement in the use of technologies that support individuals’ recovery from traditional clinical encounters. Experience Framework This article is associated with the Innovation & Technology lens of The Beryl Institute Experience Framework (https://www.theberylinstitute.org/ExperienceFramework). Access other PXJ articles related to this lens. Access other resources related to this lens
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Background: As digital peer support is quickly expanding across the globe in wake of the COVID-19 pandemic, standardization in the training and delivery of digital peer support can advance the professionalism of this field. While telehealth competencies exist for other fields of mental health practice such as social work, psychiatry, and psychology, limited research has been done to develop and promote digital peer support competencies. Objective: The goal of this manuscript is to introduce the co-production of core-competencies which can guide digital peer-support. Peer support specialists were recruited through an international listserv and participated in a 1-hour virtual focus group. Methods: A total of four focus groups were conducted with 59 peer support specialists from 11 states and 3 countries. Results: Analysis was conducted using RADar, and ten themes were identified: (1) protecting the rights of service users; (2) technical knowledge and skill in the practice of digital peer support; (3) available technologies; (4) equity of access; (5) digital communication skills; (6) performance-based training; (7) self-care; (8) monitoring digital peer support and addressing digital crisis; (9) peer support competencies; and (10) health literacy (emerging). The authors present recommendations based on these themes. Conclusions: The introduction of digital peer support core competencies is an initial first step to promote the standardization of best practices in digital peer support. The established competencies can potentially act as a guide for training and skill development to be integrated into state peer support specialist competencies and enhance competencies endorsed by the Substance Abuse for Mental Health Services Administration. Clinicaltrial:
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The novel coronavirus has thrown large sections of our healthcare system into disarray, with providers overburdened by record breaking number of hospitalizations and deaths. The U.S., in particular, has remained the nation with one of the fastest growing case counts in the world. As a consequence, many other critical healthcare needs have not received the necessary resources or consideration. This commentary draws attention to substance use and opioid access during the ongoing crisis, given the potential for breakdowns in treatment access for addiction, the growing concern of mental health comorbidities, and the lack of access for those who require opioids for adequate pain management. Further, the commentary will offer policy and practice recommendations that may be implemented to provide more equitable distribution of care.
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Background: Peer support is recognized globally as an essential recovery service for people with mental health conditions. With the influx of digital mental health services changing the way mental health care is delivered, peer supporters are increasingly using technology to deliver peer support. In light of these technological advances, there is a need to review and synthesize the emergent evidence for peer-supported digital health interventions for adults with mental health conditions. Objective: The aim of this study was to identify and review the evidence of digital peer support interventions for people with a lived experience of a serious mental illness. Methods: This systematic review was conducted using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) procedures. The PubMed, Embase, Web of Science, Cochrane Central, CINAHL, and PsycINFO databases were searched for peer-reviewed articles published between 1946 and December 2018 that examined digital peer support interventions for people with a lived experience of a serious mental illness. Additional articles were found by searching the reference lists from the 27 articles that met the inclusion criteria and a Google Scholar search in June 2019. Participants, interventions, comparisons, outcomes, and study design (PICOS) criteria were used to assess study eligibility. Two authors independently screened titles and abstracts, and reviewed all full-text articles meeting the inclusion criteria. Discrepancies were discussed and resolved. All included studies were assessed for methodological quality using the Methodological Quality Rating Scale. Results: A total of 30 studies (11 randomized controlled trials, 2 quasiexperimental, 15 pre-post designs, and 2 qualitative studies) were included that reported on 24 interventions. Most of the studies demonstrated feasibility, acceptability, and preliminary effectiveness of peer-to-peer networks, peer-delivered interventions supported with technology, and use of asynchronous and synchronous technologies. Conclusions: Digital peer support interventions appear to be feasible and acceptable, with strong potential for clinical effectiveness. However, the field is in the early stages of development and requires well-powered efficacy and clinical effectiveness trials. Trial registration: PROSPERO CRD42020139037; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID= 139037.
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We explored the perspectives of certified peer specialists and older adults with serious mental illness on the impact of a peer-delivered medical and psychiatric self-management intervention, "PeerTECH." Transcripts from interviews with consumers with serious mental illness and a focus group with certified peer specialists who were engaged in PeerTECH were analyzed. Consumer participants (n = 8) had a mean age of 68.8 years (SD = 4.9) and included individuals diagnosed with major depressive disorder (five people), schizophrenia spectrum disorders (two people), and bipolar disorder (one person). Certified peer specialists (n = 3) were aged 55 years or more. Themes included internal and external forces of accountability, confidence, internal and external locus of hope, human bonding, and peer support. This exploratory qualitative study found that human support from peers can potentially influence health behavioral change in a combined peer and technology-based medical and psychiatric illness self-management intervention.
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Assess certified peer specialists' smartphone ownership, use, and willingness to use smartphones to provide peer-delivered services. Certified peer specialist from 38 states completed an online survey. The final sample of 267 certified peer specialists included respondents from 38 states. The majority of certified peer specialists were female (73%; n = 195) and Caucasian (79.8%; n = 213), with an average age of 50.9 (SD = 12) years, range from 21 to 77 years. More than half of the certified peer specialists (82.1%; n = 184) were currently working in peer support positions. Of those who reported their mental health diagnoses, 11% reported their diagnosis as schizophrenia spectrum disorder, 22% of respondents reported bipolar disorder, and 23% reported persistent major depressive disorder. Nearly all respondents owned a smartphone (94.8%; n = 253), and everyone indicated that smartphones and tablets could enhance the services they deliver. Certified peer specialists reported substantial ownership and use of smartphones, comparable to existing national data. They are willing to deliver smartphone interventions for mental health and physical health self-management, suggesting that smartphones may be an increasingly useful tool for offering evidence-based care. Without Medicaid mandate, certified peer specialists are naturally trying to enhance peer delivered services with technology. Peer support could act as a mechanism to promote consumer engagement in a smartphone-based intervention. Certified peer specialist own and utilize smartphones, and the majority are willing to deliver technology-based and technology-enhanced interventions using these devices to address medical and psychiatric self-management.
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Objective: To identify the strategies peer specialists use to provide illness self-management support for older adults with serious mental illness (SMI) through text messaging. Method: Transcripts of text message exchanges between 8 older adult participants with SMI who completed the PeerTECH intervention and 3 older adult certified peer specialists who delivered the 12-week program were analyzed. Text message analyses explored themes relevant to peer support and health behavior change. Quantitative data comprised frequency of text messages by either the peer or consumer. Results: Consumers (N = 8) had a mean age of 68.8 years (SD = 4.9) and were mainly women (88%), White (100%), and married (75%). Certified peer specialists (N = 3) were all 55 or older; 100% were female, 66% identified as White, and 33% identified as African American. Overall, peers sent 215 text messages whereas consumers sent 141 text messages. In the peer specialist-consumer text message exchanges, we identified 4 themes on different aspects of illness self-management, including health behavior change, self-management therapeutic techniques, engagement in health technology, and peer support. Conclusions and implications for practice: This exploratory qualitative study offers preliminary support that peers are able to use text messages to support the delivery of a peer-delivered home-based medical and psychiatric self-management intervention. Certified peer specialists can potentially provide a range of illness self-management support to older adults with SMI via text messaging. These findings will inform the development of standardized peer text-messaging services to augment evidence-based illness self-management interventions for older adults with SMI. (PsycINFO Database Record
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Description of certified peer specialists integration of peer philosophy into the delivery of a self-management intervention enhanced with mobile health. Qualitative examination of peer case notes that were routinely entered on a peer care management electronic dashboard. This study included consumers with serious mental illness (N = 8) with a mean age of 68.8 years (SD = 4.9). Certified peer specialists (N = 3) were all female and aged 55 years or older. Peers entered 146 case notes on the peer care management notes dashboard. Five themes emerged including encouragement of self-determination, bio-psychosocial-spiritual framework guides practice, sharing lived experience to teach self-management skills, personalized text messages to reinforce self-management skill development, and identifying unmet needs and advocating for human rights. Peers unique perspectives and expertise was complemented with the standardized delivery of evidence-based intervention enhanced with mobile health.
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To assess the feasibility, acceptability, and preliminary effectiveness of a peer-delivered and technology supported integrated medical and psychiatric self-management intervention for older adults with serious mental illness. Ten older adults with serious mental illness (i.e., schizophrenia, schizoaffective disorder, bipolar disorder, or major depressive disorder) and medical comorbidity (i.e., cardiovascular disease, obesity, diabetes, chronic obstructive pulmonary disease, hypertension, and/or high cholesterol) aged 60 years and older received the PeerTECH intervention in their homes. Three certified peer specialists were trained to deliver PeerTECH. Data were collected at baseline, one-month, and three-month. The pilot study demonstrated that a three-month, peer-delivered and technology-supported integrated medical and psychiatric self-management intervention (“PeerTECH”) was experienced by peer specialists and participants as feasible and acceptable. PeerTECH was associated with statistically significant improvements in psychiatric self-management. In addition, pre/post, non-statistically significant improvements were observed in self-efficacy for managing chronic health conditions, hope, quality of life, medical self-management skills, and empowerment. This pre/post pilot study demonstrated it is possible to train peers to use technology to deliver an integrated psychiatric and medical self-management intervention in a home-based setting to older adults with serious mental illness with fidelity. These findings provide preliminary evidence that a peer-delivered and technology-supported intervention designed to improve medical and psychiatric self-management is feasible, acceptable, and is potentially associated with improvements in psychiatric self-management, self-efficacy for managing chronic health conditions, hope, quality of life, medical self-management skills, and empowerment with older adults with serious mental illness and chronic health conditions.
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Grounded theory is an inductive, theory discovery methodology that allows the researcher to develop a theoretical account of the general features of a topic while simultaneously grounding the account in empirical observations or data (Glaser & Strauss, 1967). This article explicates the utility of a grounded theory approach to research on work organizations. Following a general introduction to the grounded theory method, the authors'review of the organizational literature using grounded theory illustrates the variety of issues and topics studied through this approach. The authors describe and explain specific strategies for conducting grounded theory research in and on organizations, including note taking and note writing, concept discovery, and concept definition and preliminary elaboration of theory. Throughout the article emphasis is placed on grounded theory's ability to facilitate understanding and to identify desirable improvements in work contexts.
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Serious mental illness (SMI) is one of the leading causes of disability worldwide. Emerging mobile health (mHealth) and eHealth interventions may afford opportunities for reaching this at-risk group. To review the evidence on using emerging mHealth and eHealth technologies among people with SMI. We searched MEDLINE, PsychINFO, CINAHL, Scopus, Cochrane Central, and Web of Science through July 2014. Only studies which reported outcomes for mHealth or eHealth interventions, defined as remotely delivered using mobile, online, or other devices, targeting people with schizophrenia, schizoaffective disorder, or bipolar disorder, were included. Forty-six studies spanning 12 countries were included. Interventions were grouped into four categories: (1) illness self-management and relapse prevention; (2) promoting adherence to medications and/or treatment; (3) psychoeducation, supporting recovery, and promoting health and wellness; and (4) symptom monitoring. The interventions were consistently found to be highly feasible and acceptable, though clinical outcomes were variable but offered insight regarding potential effectiveness. Our findings confirm the feasibility and acceptability of emerging mHealth and eHealth interventions among people with SMI; however, it is not possible to draw conclusions regarding effectiveness. Further rigorous investigation is warranted to establish effectiveness and cost benefit in this population.
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Background: Loneliness involves subjective, rather than objective, social isolation and has a range of negative effects on mental and physical functioning. The purpose of this study was to examine the prevalence of loneliness in psychotic disorders and its association with symptoms and cognitive performance. Method: Data were drawn from the second Australian National Survey of Psychosis and comprised responses from 1642 participants with an International Classification of Diseases 10 diagnosis of psychotic disorder who had completed a semi-structured interview of symptoms and social functioning (including loneliness), along with standardized assessments of current (digit symbol coding; DSC) and premorbid (National Adult Reading Test) cognitive ability. We examined the prevalence of loneliness across the diagnostic categories of psychosis, and its association with psychotic and non-psychotic symptoms and digit symbol coding scores. Results: The prevalence of loneliness was high, ranging from 74.75% in participants with delusional disorders to 93.8% in depressive psychosis, and was significantly higher than in the general population. Loneliness was also significantly associated with anhedonia and subjective thought disorder. Participants feeling socially isolated/lonely for company had significantly lower DSC scores than those who only felt lonely occasionally. Unexpectedly, participants who reported not feeling lonely had the lowest DSC scores. Conclusions: Loneliness is common across all psychotic disorders, particularly in depressive psychosis. It is specifically associated with ongoing loss of pleasure and disordered thoughts as well as impairment in current cognitive functioning. However, poor cognitive functioning is not inevitably associated with loneliness. Implications for personalized treatment of psychosis are discussed.
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Introduction: mHealth holds promise in transforming care for people with serious mental illness (SMI) and other disadvantaged populations. However, information about the rates of smartphone ownership and usage of mobile health apps among people with SMI is limited. The objective of this research is to examine the current ownership, usage patterns, and existing barriers to mobile health interventions for people with SMI treated in a public sector community mental health setting and to compare the findings with national usage patterns from the general population. Methods: A survey was conducted to determine rates of ownership of smartphone devices among people with SMI. Surveys were administered to 100 patients with SMI at an outpatient psychiatric clinic. Results were compared with respondents to the 2012 Pew Survey of mobile phone usage. Results: A total of 85% of participants reported that they owned a cell phone; of those, 37% reported that they owned a smartphone, as compared with 53% of respondents to the Pew Survey and 44% of socioeconomically disadvantaged respondents to the Pew Survey. Discussion: While cell phone ownership is common among people with SMI, their adoption of smartphone technology lags behind that of the general population primarily due to cost barriers. Efforts to use mHealth in these populations need to recognize current mobile ownership patterns while planning for anticipated expansion of new technologies to poor populations as cost barriers are reduced in the coming years.