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Exploring the Use of Information and Communication Technology by People With Mood Disorder: A Systematic Review and Metasynthesis

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Background: There is a growing body of evidence relating to how information and communication technology (ICT) can be used to support people with physical health conditions. Less is known regarding mental health, and in particular, mood disorder. Objective: To conduct a metasynthesis of all qualitative studies exploring the use of ICTs by people with mood disorder. Methods: Searches were run in eight electronic databases using a systematic search strategy. Qualitative and mixed-method studies published in English between 2007 and 2014 were included. Thematic synthesis was used to interpret and synthesis the results of the included studies. Results: Thirty-four studies were included in the synthesis. The methodological design of the studies was qualitative or mixed-methods. A global assessment of study quality identified 22 studies as strong and 12 weak with most having a typology of findings either at topical or thematic survey levels of data transformation. A typology of ICT use by people with mood disorder was created as a result of synthesis. Conclusions: The systematic review and metasynthesis clearly identified a gap in the research literature as no studies were identified, which specifically researched how people with mood disorder use mobile ICT. Further qualitative research is recommended to understand the meaning this type of technology holds for people. Such research might provide valuable information on how people use mobile technology in their lives in general and also, more specifically, how they are being used to help with their mood disorders.
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Original Paper
Exploring the Use of Information and Communication Technology
by People With Mood Disorder: A Systematic Review and
Metasynthesis
Hamish Fulford1, MSc; Linda McSwiggan1, PhD; Thilo Kroll2, PhD; Stephen MacGillivray3, PhD
1School of Nursing and Health Sciences, University of Dundee, Dundee, United Kingdom
2Social Dimensions of Health Institute (SDHI), Universities of Dundee and St Andrews, Dundee, United Kingdom
3School of Nursing and Health Sciences, Centre for Health and Related Research, University of Dundee, Dundee, United Kingdom
Corresponding Author:
Stephen MacGillivray, PhD
School of Nursing and Health Sciences
Centre for Health and Related Research
University of Dundee
Airlie Place
Dundee,
United Kingdom
Phone: 44 01382388534
Fax: 44 01382388533
Email: s.a.macgillivray@dundee.ac.uk
Abstract
Background: There is a growing body of evidence relating to how information and communication technology (ICT) can be
used to support people with physical health conditions. Less is known regarding mental health, and in particular, mood disorder.
Objective: To conduct a metasynthesis of all qualitative studies exploring the use of ICTs by people with mood disorder.
Methods: Searches were run in eight electronic databases using a systematic search strategy. Qualitative and mixed-method
studies published in English between 2007 and 2014 were included. Thematic synthesis was used to interpret and synthesis the
results of the included studies.
Results: Thirty-four studies were included in the synthesis. The methodological design of the studies was qualitative or
mixed-methods. A global assessment of study quality identified 22 studies as strong and 12 weak with most having a typology
of findings either at topical or thematic survey levels of data transformation. A typology of ICT use by people with mood disorder
was created as a result of synthesis.
Conclusions: The systematic review and metasynthesis clearly identified a gap in the research literature as no studies were
identified, which specifically researched how people with mood disorder use mobile ICT. Further qualitative research is
recommended to understand the meaning this type of technology holds for people. Such research might provide valuable information
on how people use mobile technology in their lives in general and also, more specifically, how they are being used to help with
their mood disorders.
(JMIR Ment Health 2016;3(3):e30) doi:10.2196/mental.5966
KEYWORDS
information and communication technology; ICTs; mood disorder; metasynthesis; self-management
Introduction
Mood disorder is a diagnostic category containing, among
others, diagnoses such as major depression and bipolar
depression [1]. For some, having a mood disorder can be a
lifelong problem and the need to support people with such
long-term conditions is a major challenge facing health care
providers. In order to effectively manage their health and
wellbeing, people with a mood disorders may have to master a
range of skills and make lifestyle changes, either independently
or with the support of others, such as family, friends, third sector
services, and mental health and social care professionals [2].
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In mental health care systems designed primarily to treat acute
episodes of care, the rise in long-term conditions has threatened
the sustainability of services and ultimately failed to meet the
needs of patients with ongoing care management and the
delivery of psychosocial interventions [3]. Developments in
information and communication technology (ICT) (such as the
use of the Internet or computer technology and electronic
systems) have begun to provide new ways for people to manage
their health. ICT interventions have become affordable,
accessible, and versatile such as through the use of Web-based
self-help resources [4]. Psychological interventions have been
effectively delivered through ICTs [5] while having the ability
to reach rural areas within diverse populations and settings [6].
ICTs are increasingly being used for direct patient care [7].
eHealth is the umbrella term used for a broad range of health
informatics applications that facilitate the management and
delivery of health-related care, including the dissemination of
health-related information, storage, and exchange of clinical
data, interprofessional communication, computer-based support,
patient-provider interaction, education, health service
management, health communities, and telemedicine, among
other functions [8].
In mental health care, eHealth technologies can facilitate the
delivery of a wide range of effective treatments for a variety of
clinical problems. They have widened the choices available to
patients for selecting an approach best suited to manage their
long-term condition [7]. Such choices include: computerized
cognitive behavioral therapy (cCBT) [9]; computerized
bibliotherapy, and Web-based self-help resources/patient
information websites [10]; online counselling [11]; patient
forums, blogs, social media/social networking sites (SNSs) [12],
and online self-management groups [13].
More recently, a shift has occurred toward making technologies
more portable or mobile, evidenced by the recent rise in
smartphone and tablet ownership and usage [14]. Consequently,
mHealth has become important for the delivery of health and
health services. Improvements in reliability and broadband
coverage means greater and faster Internet access for these
mobile technologies. As a result, mobile devices have changed
the way that consumers manage their health and engage with
the health care system [15].
Evidence suggests that mHealth can facilitate the provision of
effective interventions and support the self-management of
long-term conditions [15]. Self-management is an interactive,
dynamic, and daily set of activities by which people manage
their long-term condition through overlapping skills, tasks, and
processes. [16].
However, despite its growing popularity over the last decade,
systematic research on the use of mHealth as a means of
improving health outcomes remains scarce [17,18]. Many
mHealth development studies to date, mostly outcome studies
and randomized control trials (RCT), have failed to include
patients or end users in a meaningful way or considered them
only in limited ways in the design process [5,14,19-22]. This
oversight has contributed to technology redundancy and
abandonment rates [23]. Qualitative research that provides a
more in-depth understanding of users’ views and experiences
of how eHealth and mHealth affects their lives [23,24] is of
vital importance if we are to understand how people use or
benefit from technology and what drives them to engage, or
not, with these technologies.
With the fast accumulation of qualitative studies in practice
disciplines that specifically reflect experiences and subjective
perspectives there is a need to bring together evidence from
these studies [25]. We therefore conducted a systematic review
in order to collect and synthesize all qualitative evidence
exploring the use of ICTs and/or mobile information and
communication technologies (mICTs) by people with mood
disorder. We sought to answer the following review questions:
1. Why do people with mood disorders use (m)ICTs?
2. What are (m)ICTs being used for by people with mood
disorders?
3. What are the perceived benefits and challenges of using
(m)ICTs by people with mood disorders?
4. In what ways are (m)ICTs being used for self-management
by people with mood disorders?
5. What role, if any, do (m)ICTs play in terms of social
relationships for people with mood disorders?
Methods
Rationale
A protocol for the review was published in PROSPERO
(ID=CRD42014008841). The systematic review and
metasynthesis drew on methods proposed by Sandelowski and
Barroso [26], Thomas and Harden [27], and Barnett-Page and
Thomas [28]. Qualitative research synthesis is an approach
developed to make use of this proliferation of qualitative
findings driven from the growth of empirical research and
evidence-based practice in the 1990s [26].
Search Strategy
Due to potential difficulties in finding qualitative research [27],
a sensitive systematic search strategy was created to maximize
the likelihood of finding all relevant studies. The strategy
consisted of two search strings combining thesaurus terms,
free-text terms, and broad-based terms: one for ICTs/mICTs
and one for qualitative methods (See Textbox 1 for an example
of a search). Initially there were also terms for mood disorders,
however, the pilot searches identified the inclusion of this string
as being too specific limiting the aggregative capabilities of the
search strategy. The systematic review would therefore
categorize and catalogue all qualitative health research related
to ICTs with mood disorder being the category focused upon
for synthesis.
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Textbox 1. Example search of Cumulative Index to Nursing and Allied Health.
1. (MH “World Wide Web Applications+”) (MH “Computers, Hand-Held”) (MH “Macintosh Microcomputers”) (MH “Multimedia”) OR (MH “Social
Media”) (MH “Telemedicine+”) OR (MH “Telepsychiatry”) OR (MH “Telehealth+”) (MH “Computers, Portable+”) (MH “Computer Input Devices+”)OR
TI App OR TX Mobile phone*OR TX Mobile Internet OR TX Sony OR TX HTC OR TX Nokia OR TX Samsung OR TX Wireless OR TI 5G OR
TI 4G OR TI 3G OR TX Touch screen OR TX Context-aware system* OR TX Cel* Phone* OR TX User-centered design OR TX Mobile app* OR
TX Internet treatment OR TX Virtual realit* OR TX Internet delivered OR TX Mobile technolog* OR TX Electronic health OR TX Mobile health
OR TX iPad* OR TI Apple OR TX mHealth OR TX eHealth OR TX Android OR TX Blackberry OR TX Windows mobile* OR TX Windows phone*
OR TX Smartphone* OR TX iPhone* OR TI Mobile*
2. (MH “Phenomenological Research”) OR (MH “Observational Methods+”) OR (MH “Patient Attitudes”) OR (MH “Ethnographic Research”) OR
(MH “Constant Comparative Method”) OR (MH “Purposive Sample”) OR (MH “Qualitative Studies+”) OR (MH “Focus Groups”) OR TX Theoretical
sample OR TX Qualitative research OR TX Theoretical saturation OR TX Mixed methodolog*
3. 1 AND 2
4. Limit 3 to published 2007-2014
Searches were run in eight electronic databases: Medline,
Embase, Cumulative Index to Nursing and Allied Health, the
psychological literature database, Applied Social Sciences Index
and Abstracts, British Nursing Index, Social Sciences Citation
Index, and Cochrane Library. The results from each database
were exported into Endnote X7 where duplicates were removed
electronically and manually. The title and abstracts of the
remaining articles were exported into a Microsoft Word
document and numbered ready for screening.
Additionally, to optimize qualitative article retrieval the
following methods were used: footnote searching; citation
searching; journal run; area scanning; and author searching. In
addition, experts and key authors were contacted to identify
unpublished and ongoing studies. Due to research on the mobile
aspect of ICTs being an emerging field, it was envisaged that
grey literature might be a valuable source of primary data. Grey
literature covers a wide range of material including: reports,
government publications, fact sheets, newsletters, conference
proceedings, policy documents, and protocols. We therefore
searched the following sources for grey literature: The New
York Academy of Medicine’s Grey Literature report and Open
Grey and Grey Source Index. The Journal of Medical Internet
Research and Biomedcentral Psychiatry were hand searched
from 2007 to present day.
Eligibility and Screening
One reviewer screened all of the titles and abstracts for inclusion
in accordance with the following inclusion criteria: study used
widely accepted qualitative methods to elicit in-depth
experiences with findings appearing well supported by raw data
(eg, participant quotes); study sample included people with
mood disorders; study sample included the use of (m)ICTs;
time period of 2007 to 2014 (2007 saw the release of the first
‘smartphone’, ie, Apple’s iPhone); and English language.
To optimize the validity of the search a systematic sampling
strategy was adopted, whereby 10% of results were coscreened
(HF & SM/LM) to facilitate consistency of approach [29]. All
questionable citations from the full search results were discussed
in order to reach consensus on disposal. Full texts were retrieved
for those publications that were deemed to meet inclusion
criteria and those that could not be adequately assessed for
inclusion with the information provided in the abstract. Two
authors independently assessed the full texts for inclusion and
then met to discuss their decisions. Where they could not come
to a consensus, a third author was consulted.
Quality Appraisal
There is a lack of agreement about the approach to quality
appraisal in qualitative research [26,30]. Therefore, due to the
scarcity of data on the topic being studied, papers were not
excluded based on quality, instead all papers were included and
their quality appraised. A global assessment of study quality
was undertaken assessing studies as being either strong or weak.
Strong studies would likely include elements of respondent
validation, triangulation of data, transparency, reflexivity, clear
descriptions of methodology, methods of data collection,
analysis, and an overall fit in regards to the research questions
and the design of the project [31]. Reports were both
individually and comparatively appraised. A typology designed
by Sandelowski and Barroso [32] for classifying findings was
used. Rather than comparing differences in quality between
studies the typology was used to identify the level of data
transformation.
Synthesis
The synthesis stage used thematic synthesis, an approach that
combines elements of meta-ethnography and grounded theory
providing the opportunity to synthesis methodologically
heterogeneous studies [27,28]. The thematic synthesis followed
a three-step process described in Textbox 2.
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Textbox 2. Thematic synthesis steps.
Step 1
Free sentence-by-sentence coding: the verbatim findings of each selected study were entered into NVivo 10. Codes were developed initially free from
hierarchical structure but as the translation of concepts developed from one study to another new codes were either added to existing ones or new
codes created.
Step2
Organization of free codes in hierarchical order under a range of descriptive themes: free codes were organized into related areas to create descriptive
themes; then similarities and differences between codes were studied, facilitating the organization of the codes into related groups and the formation
of a hierarchical tree structure of descriptive themes.
Step 3
Development of analytical themes: descriptive themes were analyzed and then organized into more abstract analytical themes, producing a synthesis
that went beyond the data in the original studies and addressed the research questions.
In order to keep the synthesis as close to the data as possible
the research questions were initially set to one side facilitating
an inductive process. Codes were applied as part of an iterative
process with constant comparison with other codes (Step 1).
This process was repeated for all the codes until higher order
categories were constructed and all codes accounted for (Step
2). The review questions were then brought to the fore and used
as a framework to guide the analytical process, which focused
and transformed the descriptive themes into the final synthesis
(Step 3). The categorization process was examined by the
reviewing team where, through discussion, changes, and
adaptions were made where necessary until consensus was
reached and no further changes were required. The reviewing
team scrutinized the synthesis at an analytical level through a
cyclical process until a final synthesis was achieved.
Results
Search findings
The search identified 12,926 titles; 67 publications were
retrieved in full (Figure 1). The methodological designs of the
studies were qualitative or mixed-methods using focus groups,
interviews, or forum/message boards as the methods for
generating data. Studies originated mainly from Europe, the
United States, or Australia and New Zealand.
Only one paper was identified from the systematic review of
qualitative papers and therefore, synthesis of mICTs and mood
disorders was not possible due to lack of data. However, the
review mapped and categorized all qualitative papers in the
domain of health and ICT research. This facilitated
methodological development in order to find a solution
regarding how to use imperfect data. Rather than lose the
potentially valuable qualitative data of relevance to the project,
the 67 full-text papers were rescreened. The aggregative and
sensitive systematic search strategy offered a flexible approach
toward the data. This provided the researchers with the ability
to use the existing data to explore how people with mood
disorders used ICTs ‘of relevance’ to mobile technology. This
would include, but not be limited to, ICTs such as websites,
online therapy, online support groups, forums, blogs, and so
on, essentially, ICTs that could be accessed from mICTs but
were not necessarily made explicit within the text. Thirty-four
studies were included in the synthesis after the full-text articles
had been rescreened; a summary of their results can be found
in Multimedia Appendix 1.
The results of the appraisal process are shown in Table 1 with
22 studies identified as being strong and 12 weak, with most
having a typology of findings either at the topical or thematic
survey levels of data transformation. Therefore, with over a
third of the studies being weak in quality, the appraised strength
of the studies weighed upon, in a measured manner, our
interpretation of the study findings.
The synthesis created three analytical themes and a number of
respective analytical subthemes to describe people’s use of
ICTs. This is presented as a typology of findings (Textbox 3).
The research questions were then used as a template, explicating
the typology of findings to understand how the descriptive
themes interrelated with their analytical themes, thus helping
to answer the questions asked of the data. The results are
presented below.
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Table 1. Appraisal of qualitative papers in metasynthesis.
n (%)Global assessment of study quality
12 (35)Weak
22 (65)Strong
Typology of findings
4 (12)No findings
11 (32)Topical survey
14 (41)Thematic survey
5 (15)Conceptual thematic description
0 (0)Interpretive explanation
34 (100)Total
Textbox 3. Typology of findings.
Movement and change
Change processes
Engagement
Motivational aspects of use
Recovery
Taking action
Values
Providing a source of community
Communication
Intrapersonal effects
Safe places
Sharing
Social aspects
The person and technology
Acceptance of technology
Design features
Functionality
Personal time
Safety
Technical mastery
Technical issues
Usability
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Figure 1. PRISMA diagram of screened articles of relevance to mood disorders and mICT .
Why do People With Mood Disorders use (Mobile)
Information and Communication Technologies?
Considerable overlap was found in terms of why people used
ICTs and the perceived benefits this technology gave them.
Two studies [33,34] provided data regarding motivation to use
ICTs. For those involved in Internet-based treatment, the
interactive nature of ICTs appeared to increase their motivation
to engage with treatment and, in so doing, possibly help in their
recovery [34].
Three studies showed how users of ICTs liked the option of
being able to choose where to use technology (ie, at work or in
the convenience of their own homes) [35-37]. Having easy
access to information from around the world, at any time in the
day, through use of the Internet was regarded as useful in
comparison to using books [37,38].
The use of websites to support relatives of people with
depression appeared to decrease feelings of stigma in both by
enabling people to draw strength from talking more openly
about their situation [37]. Young people were concerned about
feelings of embarrassment if other people realized they had
depression increasing a sense of helplessness [38-40]. Fear of
being judged by others due to having a mental health issue was
a particular problem faced by some young users of ICTs and it
became a specific reason for using the technology [39,41]. Fear
of school peers finding out and potential links to bullying opted
users to engage with ICTs in the privacy of their own homes
[41]. People who felt shame due to experiencing emotional
problems would put a lot of effort into hiding their symptoms
so having a website where people could discuss their emotional
problems anonymously was considered a good thing and often
would be the first time sharing their experiences [40]. The use
of websites to support relatives of people with depression
appeared to decrease feelings of stigma and support their mental
health [41]. Using Web-based assessment tools appeared to
facilitate dialogue between patients and clinicians. For instance,
patients felt it was easier to talk to their general practitioner as
they had thought about things beforehand and would be more
confident in receiving a diagnosis [36]. Of significant
importance to using ICTs was the concept of privacy [37,42-44].
Web-based programs were considered, by some, as providing
the most private way to seek help for psychological issues [35].
ICTs appeared to provide people with options regarding how
they used technology with choice over temporal, location,
treatment, privacy, and disclosure aspects of their care needs
[33,38,39,41,45]. The credibility of ICTs appeared an important
factor when deciding upon usage [35]. For example, having
testimonials from other users displayed on Web pages regarding
credibility, and knowledge that the ICT was designed on
research appeared to raise confidence in technology [35,46].
ICTs were also regarded as cost-effective solutions to
access-to-care problems faced by people living in remote
localities, by both patients and health professionals [47].
Participants reported being aware of long waiting times for
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specialist health services and, with the alternative being
expensive private treatment, the low cost nature of ICTs made
them attractive [34,37,42]. Modifying aspects of ICTs with a
user-centered design appeared to facilitate use to some extent
by reducing technical challenges and helped people feel more
competent and autonomous [48,49].
What are (Mobile) Information and Communication
Technologies Being Used for by People With Mood
Disorders?
The use and view of ICTs as a resource appeared to be an
important factor in people’s lives. ICTs could open up access
to information, support, and treatment in a highly accessible,
interactive, and instant way [37,38,42,50,51]. The Internet was
also considered empowering [45] and provided a resource for
learning [46,48,52]. Holding certain values appeared to suggest
people were going to commit to using and completing
therapeutic work via ICTs more than others, for example, having
a sense of what one should, or should not do, appeared to
influence some people’s commitment to complete Web-based
programs regardless of how tedious or frustrating they were
[53]. ICTs appeared to be used as a resource for people to
communicate and exchange information and stories with others
[38,43,45]. They appeared to facilitate disclosure of personal
information regarding people’s mental health [40], indicating
a need by people to talk about their issues [34].
What are the Perceived Benefits and Challenges of
Using (Mobile) Information and Communication
Technologies by People With Mood Disorders?
There was significant overlap in terms of why people use ICTs
and the benefits provided. As these benefits have already been
identified and discussed in the previous two sections, this section
focuses on the challenges of using technology. Certain forms
of technology and their functionalities produced usage
difficulties [42]. That is, people were put off using ICTs if
software was slow, had broken hyperlinks, was unnecessarily
complex or impersonal, and if use required additional software
[47,50,54]. For some people, there were concerns regarding the
safety of using ICTs for treatment purposes due to queries
regarding the levels of confidentiality the technology could
provide [47,52,55]. Being able to use ICTs anonymously
appeared to be an important aspect in managing confidentiality
and a factor when assessing the appropriateness of using a
Web-based intervention [37,40,43]. Indeed, there were people
who preferred not to share personal information unless it was
face-to-face due to the importance they placed on confidentiality
[38].
Some people made a conscious decision not to use ICTs.
Reasons included having no interest in certain forms of
technology, not being technologically savvy, and being too
unwell to use technology (for example, reduced energy and
motivation due to an acute depressive phase) [38,41,56]. There
were also practical reasons for not using ICTs, such as, having
no need to use it, not identifying with content, inhibitive cost,
or having no Internet connection [42,48]. Users needed to
believe and trust in the ICTs they were using [48,52]. There
were concerns regarding information reliability and quality on
the Internet, and doubts as to whether people had the ability to
discriminate trustworthy information themselves [45]. Of note,
was the generally limited mention of negative outcomes in the
reviewed studies.
In What Ways are (Mobile) Information and
Communication Technologies Being Used for
Self-Management Purposes by People With Mood
Disorders?
The use of ICTs appeared to support people to acquire relevant
knowledge in regards to their mood problems providing a sense
of recognition in situations that might be difficult to accept or
unfamiliar, thus helping them feel supported [34]. ICTs were
used, by some, to acquire information about treatment, diseases,
drug information, and the experiences of others [44,45]. Some
people read information specifically targeted toward health
professionals as they deemed it to be the most comprehensive
and up-to-date sources of information [45]. Seeing relevance
in material appeared to be a factor in the process of acquiring
new self-knowledge. This was achieved through learning
together by reflecting and restructuring new knowledge to suit
one’s own needs [34]. ICTs appeared to be being used for
help-seeking through the acquirement of self-help information,
the development of skills, and also as a means to seek help
through online support groups and forums [38,40,45,57,58].
Sitting down at a computer at regular times working on a
self-help programs appeared to be of benefit; people reported
experiencing an empowering effect, a change of perspective,
increased personal agency, and a way of keeping new learning
at the forefront of their minds [46]. A programs to help monitor
depression (on a mobile phone) appeared to hold potential as a
motivational tool to support people to look after themselves
[42]. Self-help books were viewed as having a number of
disadvantages such as being hard to read, noninteractive, and
difficult to engage with; where available, people preferred
Web-based versions [50,59]. ICTs appeared to provide people
with informational support and the ability to delve as deeply as
they wished into certain topics, such as medication management,
counselling services, negative thinking, and poor concentration
[40,52]. The Internet appeared to be considered a key component
in providing greater access to health information by patients
and receiving benefits from engaging in self-help
[34,40,45,46,52].
ICTs appeared to help provide a sense of control in people’s
lives by providing them with the opportunity to find information
about where to find help, assisted them with understanding
when to seek help, and what support was available to them
[38,52]. They helped prepare for meetings with health
professionals, thus making treatment more collaborative [45].
Support from online forums was flexible and inexpensive [60].
Maintaining contact with friends and family was also feasible
through diverse Web-based platforms [39].
Receiving support through ICTs appeared to be of benefit by
people with mood disorders [49]. People required support in
maintaining relationships and dealing with broken relationships
while recovering from a mood disorder [50]. Methods of
support, in preference to telephone calls or home visits by
professionals, included the use of emails due to their unintrusive
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nature [49,50]. People also appeared to benefit from support
from friends, family members, and significant others to
encourage and help them persist with using ICTs for their
recovery [48]. Web-based programs potentially offered a means
to lessen stigma toward mental health and encourage acceptance
of conditions such as Bipolar Disorder [35,37,52,61]. Web-based
programs supported people to feel validated and empowered
increasing feelings of confidence and self-worth [36,46,57].
Learning time management techniques facilitated people to
organize their time better helping them meet deadlines and
prepare for exams [35,48]. Time was required to be set aside to
use ICTs and having personal time in a private space was
appreciated [37]. People taking responsibility for their treatment,
had a sense of determination, curiosity, and attributed success
to their own endeavors appeared to benefit more from treatment
delivered through ICTs [53,62]. People were able to use ICTs
to contact health professionals and source health information
for themselves, which appeared to help them manage their own
problems moving from a position of passivity to one of activity
[34,38,53,62]. Being aware of one’s motivational levels and
having responsibility for maintaining motivation to use
interventions delivered through ICTs appeared helpful [33].
Holding certain values would help people to complete
Web-based programs and others found their own way of working
with material to face and overcome challenges and seeing
difficulties as potentially valuable lessons to be learned [53,62].
People’s awareness sometimes appeared to change when using
ICTs. For instance, becoming aware of holding high
expectations toward technology and feeling disappointment if
programs did not meet all their needs fostered a sense of
consideration to revisit and work with material to see if it would
be of benefit [62,63]. Web-based programs held the potential
to help people become more aware of their negative thinking
habits, promoting reflection, and challenging of thoughts moving
people in a more positive direction toward self-acceptance
[34,37,50,64]. Participant feedback in the design process of
ICTs potentially influenced the goals of particular programs
centering on raising awareness regarding the importance of
managing depressive symptoms among their users [65]. The
use of ICTs to access information and seek other people’s
opinions through online forums for example offered different
viewpoints and helped people understand more about the
difficulties they faced [37].
What Role, if any, do (Mobile) Information and
Communication Technologies Play in Terms of Social
Relationships for People With Mood Disorders?
Using ICTs for social support appeared to be of benefit to people
and one of the predominant reasons for using the technology
on a daily basis [42]. Meeting similar people in virtual
environments created a sense of acknowledgement and
recognition decreasing feelings of social isolation, loneliness,
and alienation [37,48,52]. People could use ICTs as an
opportunity for sharing their feelings, emotions, and personal
stories [40]. The exchange of experiences and knowledge in a
supportive environment appeared to help people; narrate their
experiences, gain a sense of community, share tips, and provide
a sense of comfort, strength, and hope in people [37,42-45].
Using ICTs made some users less inhibited, in terms of the
personal information they shared, because they felt more secure
about privacy being maintained and, therefore, found ICTs less
discomforting than face-to-face interactions [37,38,40].
ICTs provided people with the capacity to use online social
networks in order to communicate with people experiencing
similar issues, to ask advice or discuss certain topics in a
convenient and accessible manner [37,38,42]. ICTs also
provided people with the opportunity to receive and give peer
support [37,44,50,66]. Peer support appeared to help people
engage with Web-based interventions, overcome procrastination
and motivational issues, and helped them to understand their
own problems in a way that gave potential for behavior change
[44,50].
Discussion
Principal Findings
The aim of the study was to conduct a metasynthesis of all
qualitative studies exploring the use of ICTs by people with
mood disorder. The resultant metasynthesis created an analytical
typology of findings and a descriptively themed framework,
which conceptualized how people with mood disorder use and
relate to their ICTs, and in so doing, answered the specific
review questions. The metasynthesis identified that people with
mood disorders use ICTs in similar ways and face similar
technological paradoxes as other users [67]. However, the
metasynthesis developed the understanding further, suggesting
a continuum of use, in this instance, by people with mood
disorder. How ICTs of relevance to mobile technology are used
and harnessed by this particular client group are discussed
below.
Our metasynthesis identified the factors influencing why people
with mood disorders chose to use ICTs such as affordability,
accessibility, and versatility. These factors align closely with
previous studies on the delivery of health-related products
evidenced through increasing Web-based self-help resources
[4], effective delivery of psychological interventions [68], and
their ability to reach rural areas within diverse populations and
settings [6]. The body of eHealth research is expanding with
studies across different patient groups, using different
technologies/interventions, and focusing on different outcomes
[69-73]. In their interpretive review of the literature on consumer
eHealth, Hordern et al [74] identified five broad usage themes:
(1) peer-to-peer online support groups and health-related virtual
communities, (2) self-management/self-monitoring applications,
(3) decision aids, (4) the personal health record, and (5) Internet
use. The results of our metasynthesis reflected these uses but
also highlight a number of intrinsic factors affecting people’s
use of ICTs. People were motivated to use ICTs to aid recovery,
associated with the convenience afforded to them through using
the technology. The privacy and choice of communication
methods of ICTs were seen as facilitative and credible options
often wrapped-up in cost-effective and user-center designed
products. Seen as a resource, ICT use was empowering,
facilitating people to self-care or self-manage. The Internet was
considered a key component in providing greater access to health
information by patients and for them to receive benefits from
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engaging in self-help [34,40,45,46,52]. ICTs helped provide a
sense of control in people’s lives by providing them with the
opportunity to access information to help themselves, bettered
their understanding about when to seek help, and increased
awareness of what help was available [38,52]. They facilitated
people to prepare for meetings with their health professionals
making treatment more collaborative. Receiving support through
ICTs was seen to be of benefit by people with mood disorders
[49]. ICTs potentially facilitated people to take the first step in
managing their recovery after years of deliberation [34]. ICTs
supported people to stay in contact with health professionals
involved in their care and establish therapeutic relationships
despite being separated by distance [38,47,49]. People were
able to use ICTs to contact health professionals and source
health information for themselves in order to manage their
problems by converting intentions into actions [34,38,53,62].
People who took responsibility for their treatment, had a sense
of determination, curiosity, and attributed success to their own
endeavors appeared to benefit more from treatment delivered
through ICTs [53,62]. ICTs that were stimulating to use and
interacted well with peoples' senses and cognitive abilities
enhanced engagement [46]; this was deemed vital in the context
of online depression therapy [34]. With engagement came an
enhanced sense of personal agency from interacting with ICTs
and the completion of Web-based activities offered a sense of
empowerment [37,46]. The functionality of ICTs was an
important factor in their adoption and use [42]. For example,
having functions to compare information from day-to-day to
week-to-week, track information, format content, use Web-based
diaries, forums, bookmarks, blogs, messages, control privacy
settings, invitation functions, e-reminders, and options to reply
directly to clinicians were important usage features
[37,42-44,49,50]. ICTs with increased usability were desirable
[38,42]. For example, having a user-interface that could be
personally controlled, with an array of images, colors,
information, and music options, could help engage the user [46].
In addition, being able to use ICTs in different locations (such
as, work, home, or on public transport) appeared important
factors when assessing usability by the user [37,42].
When designing ICTs and Web-based interventions importance
was placed upon managing depressive symptoms in order to
support people, through evidence-based interventions, with their
practical and interpersonal issues caused by their conditions.
[50,65]. Web-based programs supported users to work on
solving problems through taking a structured approach using
manageable steps [46,57]. If people focused on achieving
manageable goals then it provided them with a sense of
completion [50,53]. Web-based programs supported people to
cognitively restructure, facilitating them to rethink stressful
situations that challenged their negative thought patterns.
Web-based programs also facilitated behavioral changes by
breaking negative cycles of inactivity, self-incrimination, and
withdrawal, which lead to secondary benefits as people become
closer to those around them [34,35]. Peer support accessed
through ICTs helped people to feel more positive and understand
themselves better leading to behavior change and the confidence
to negotiate changes in treatment [44]. Accessing Web-based
medication information through ICT use prompted some people
to request additional drug information from their prescriber
regarding risks and benefits of antidepressants and conversely,
made others change the dose of drug or discontinue the
prescription without seeking professional guidance first [45].
Having a sense of curiosity toward ICTs and a will to learn
self-management techniques and, if an improvement in their
health was noticed through using ICTs, then they were more
likely to persist with an intervention [48,53]. ICTs supported
people to stay in contact with health professionals involved in
their care and to establish therapeutic relationships despite being
separated by distance [38,47,49]. However, ICTs can be viewed
to have paradoxical elements to them; social and economic
paradoxes, which challenged people in their social and
individual lives [67].
The findings of our metasynthesis indicate that usage difficulties
were a key factor in reducing people’s motivation to use ICTs.
This aligns well with the findings of others, including Bessel
et al [75] who identified that computer-based interventions have
limitations, such as the reliance on users having access to
computers at scheduled times and restricted and unreliable
Internet access in remote and rural areas. Safety was a key
concern raised from the synthesis with the concept of
confidentiality and data security being paramount. This is clearly
associated with the disadvantages of ICTs such as software
errors, unreliable information, problems with privacy and
unreliability, lack of regulation, social isolation, and in some
forms of technology, the loss of vocal intonation and nonverbal
communication [75]. Internet-delivered treatment programs
such as open access websites are characterized by poor
adherence with an average dropout rate of 31% [76,77].
There are many advantages for patients when using ICTs, such
as being able to get in contact with health professionals quickly
and easily, a reduction in travel and waiting times for
face-to-face appointments, convenience, and affordability. The
technology provides a medium for communication between
health professionals and patients where information about the
patients’ disease, treatment, and therapeutic interventions can
be discussed [7]. This is of particular importance for those with
long-term conditions and our metasynthesis reinforces this point.
In contrast to other forms of patient contact, ICTs provide the
opportunity for asynchronous communication. eHealth holds
the potential to enable patients to better manage their long-term
health conditions through the use of technology [7].
Our metasynthesis identified that people used ICTs to acquire
relevant knowledge in regards to their mental health issues. This
can be linked to an increasing trend in society to adopt
self-service models of interaction. There have been promising
results for using computers to deliver self-management programs
to patients with long-term conditions in health-supported settings
showing potential for changing health behavior and improving
clinical outcomes [78]. Since 2005, interest in the Internet as a
vehicle to disseminate interventions designed to treat and
prevent mental disorders, including those targeted at depression,
has been increasing [11]. Passive psychoeducational information
might be an effective intervention for depression when employed
with reminders and involving minimal information [11]. In their
systematic review, Griffiths et al [11] identified that the Internet
was highly effective and facilitative when used to deliver mental
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health interventions with or without practitioner guidance.
Web-based CBT has also been shown to provide small benefits
when used to help manage chronic pain [79]. However, in a
recent meta-analysis of computerized cognitive behavioral
therapy (cCBT) by So et al [9] only short-term reductions in
symptoms were noted, long-term follow-up and functional
improvement were not significant and there was a
recommendation that the clinical usefulness of cCBT should
be reconsidered downward in terms of methodological validity
and practical implementation [9]. Therefore, further research is
required to help understand peoples’ self-service approach to
accessing Web-based health information and their acceptability
and use of Web-based therapeutic interventions [80].
Outcome data from RCTs and meta-analyses have identified
the cost-effectiveness and clinical efficacy of mental health
programs delivered via ICTs with comparable effect sizes to
face-to-face treatment [14,81]. Web-based interventions have
also highlighted positive effects on patient empowerment and
self-efficacy including people with physical health conditions
such as cancer [82,83]. Our metasynthesis suggests similar
outcomes for people with mood disorder and that ICTs can
provide opportunities for help seeking and support for such
people. Yet, evidence points to the variable quality of
information and apps available on the Internet [7,84-87]. There
appear to be numerous health-related websites with limited
availability of help, containing information that can be difficult
to read and incomplete [85,86].
Our metasynthesis identified that people with mood disorder
were using ICTs to give and receive social support. This
corresponds with evidence from SNS use and associated indices
of psychological well-being relating to a persons’ sense of
self-worth, self-esteem, satisfaction with life, and other
psychological development measures [88]. The metasynthesis
identified that people with mood disorder where using social
networks in a similar way as suggested by Cohen [89] by
providing platforms to give and receive social support in the
form of informational support, instrumental support, and
emotional support. The metasynthesis highlighted how ICTs
facilitate people with mood disorder to communicate with others,
corresponding to previous work undertaken regarding
Web-based disinhibition. Suler [90] suggests that a number of
factors can loosen psychological barriers allowing for inhibition
to become reduced when on the Internet: invisibility, dissociative
anonymity, synchronicity, dissociative imagination, solipsistic
introjections, and minimizing authority. People use social
networking sites (SNSs) for their sociability function to maintain
relationships with on and offline friends over varying distances
[91] attending to extended social networks and relationships
[92,93]. Before the development of popular Web-based SNSs
such as Facebook, Skinner and Zack [94] had already identified
that barriers to communication were being overcome through
using the Internet and as a result people were getting help in
ways convenient to them.
Of particular importance was the lack of qualitative research
being undertaken in this field as evidenced by only one paper
retrieved specifically reporting on mICTs. To date, patients or
end uses have not been sufficiently included in the design of
software applications. The same applies to the selection of
relevant and appropriate outcome measures in effectiveness
studies such as RCTs. These omissions have contributed to
redundancy and the abandonment of technology. n fact, there
has been a presumption that those designing technology and
undertaking research already know what the user wants in terms
of software and hardware. Designers have, jumped ahead, and
designed apps and websites, without first talking to end users
about how they use and fit technology into both their existing
lives and what would help them manage their lives. Qualitative
research, which provides a more in-depth understanding of
users’views and experiences is of vital importance if we are to
understand how people use or benefit from technology and what
drives them to engage, or not, with these technologies.
Recommendations
Research: research relating to how people with mood disorder
used ICTs was lacking and in particular, their use of mICTs,
not as participants in research studies, but as ubiquitous
technology in their everyday lives. Qualitative research is
required to help understand how mICTs fit into people’s lives
both in general but also more specifically in relation to their
mood disorders.
Practice: clinical practice could be supported through
understanding how people with mood disorder use mICTs to
look after themselves providing clinicians with valuable
information to help harness peoples’ mICTs for use in their
recovery and inform the future design of technology.
Strengths and Limitations
The review relied exclusively upon English language
publications, which may not adequately reflect the user
experiences and perceptions that were gathered in non-English
speaking contexts. Another issue may relate to the quality of
primary data sources and the quality of existing quality appraisal
tools for metasyntheses. The researcher’s stance was clearly set
out in the study providing rationales for the choice of
methodology and methods used. Transparency was achieved
by clearly detailing the synthesis process and checks and
balances were used to ensure rigor throughout. The study
originally set out to synthesis all qualitative articles regarding
people with mood disorder and mICT. Unfortunately, as only
one article met the original inclusion criteria for mobile
technology a synthesis of this material was not possible.
However, our novel approach toward the search and retrieval
of data allowed us to catalogue all qualitative data related to
health and ICTs including data of relevance to mICTs. This
process provided us with the opportunity to restructure our
inclusion criteria and make use of the data that would have
otherwise been neglected in other systematic reviews and
metasyntheses.
Conclusion
The metasynthesis of people with mood disorders and their use
of ICTs has provided a tentative understanding into their uses,
challenges, and gratifications spanning the intrapersonal,
interpersonal, and through into wider society. The typology of
findings and analytical framework highlights the connections
and interrelationships between analytical themes and
subcategories; the intrinsic and extrinsic nature of use and the
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embedded characteristics of the technology. Our metasynthesis
has identified that people can use ICTs in novel ways to help
them manage their lives and health. People use ICTs to support
motivation, for their convenience, to help decrease feelings of
stigma, their facilitative capabilities, enhance privacy,
credibility, and cost effectiveness. ICTs support people to access
the Internet to get what they need in a way that fits into their
lives. ICTs are a resource for communication and promote user
engagement. However, they are not without issue, with particular
challenges of trust and confidentially requiring to be negotiated.
That being said, when the challenges are navigated successfully,
people are able access opportunities to manage their mood
disorder by acquiring relevant knowledge, engage in
help-seeking behavior, receive support, gain a sense of control,
learn time management techniques, take responsibility, and
increase their awareness. ICTs also allow access to Web-based
social networks where sharing with others can facilitate social
support. Our typology of findings creates an empirical basis to
help guide and harness the potential of (m)ICTs to support
self-management, facilitate collaborative, person-centered care,
and support the person actively recover from their mood
disorder. Importantly, our metasynthesis has highlighted a gap
in the evidence base, as no research has focused specifically on
mICT use by people with mood disorder.
Authors' Contributions
H. Fulford undertook the metasynthesis and manuscript preparation with principal supervision from S. MacGillivray and additional
supervision from L. McSwiggan and T. Kroll.
Conflicts of Interest
None declared.
Multimedia Appendix 1
Summary of results
[PDF File (Adobe PDF File), 65KB - mental_v3i3e30_app1.pdf ]
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Abbreviations
cCBT: computerized cognitive behavioral therapy
BD: bipolar disorder
GP: general practitioner
mICTs: mobile information and communication technologies
ICTs: information and communication technologies
RCT: randomized control trials
SNS: social networking site
Edited by J Prescott; submitted 10.05.16; peer-reviewed by B Lai, D Moore; comments to author 01.06.16; revised version received
05.06.16; accepted 06.06.16; published 01.07.16
Please cite as:
Fulford H, McSwiggan L, Kroll T, MacGillivray S
Exploring the Use of Information and Communication Technology by People With Mood Disorder: A Systematic Review and
Metasynthesis
JMIR Ment Health 2016;3(3):e30
URL: http://mental.jmir.org/2016/3/e30/
doi:10.2196/mental.5966
PMID:27370327
©Hamish Fulford, Linda McSwiggan, Thilo Kroll, Stephen MacGillivray. Originally published in JMIR Mental Health
(http://mental.jmir.org), 01.07.2016. This is an open-access article distributed under the terms of the Creative Commons Attribution
License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any
medium, provided the original work, first published in JMIR Mental Health, is properly cited. The complete bibliographic
information, a link to the original publication on http://mental.jmir.org/, as well as this copyright and license information must
be included.
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... Mobile technologies may mitigate access challenges in relation to receiving timely and appropriate mental health care in that they can connect the user to information and support resources (Tomlinson et al. 2013). However, it is not well understood if and how people with mood disorders use mobile technologies in their daily lives and what their applicability may be for managing health and well-being (Fulford et al. 2016). This information is vital to reduce technological attrition and redundancy (Poole 2013). ...
... This study identified that participants with mood disorders both sought and received support through their use of mICTs, often facilitating their first steps towards managing their recovery after periods of deliberation; however, user-related, health-related, and technology-related barriers are still required to navigated and negotiated (Simblett et al. 2019). Whilst the CGT approach conceptualized similar influencing factors as Fulford et al. (2016) in terms of why people with mood disorders chose to use ICTs such as their affordability, accessibility, and versatility; it also theorized new ones, such as power (facilitate choice and control), safety (sense of attachment), and fulfilment (informational needs met). ...
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Information and communication technologies (ICTs) have become increasingly integrated into how care is delivered and received. However, no research has yet explored how people with mood disorders use mobile information and communication technologies (mICTs) in their everyday lives and, more specifically, how they might use mICTs to look after themselves. An exploratory qualitative study, within secondary and specialist mental health Services, was undertaken. Data generation involved in‐depth, semi‐structured interviews with 26 people with mood disorders. Participants’ data sets were analysed using constructivist grounded theory (CGT). The resultant theory explains how mICTs were used in daily life, and also, more specifically, how they were used to manage recovery from mood disorders. The findings reveal that people with mood disorders used their mICTs to centralize themselves within their on‐ and offline worlds and their importance of attachment were central in their continued use. These findings have the potential to inform and encourage the further incorporation of mICTs into the health and social care settings; spanning the therapeutic to systemic levels so that the full potential of these ubiquitous technologies can be harnessed to improve care and care delivery. Yet, without adequate resource and support, health and social care professionals’ efforts will be hampered, contributing to technology redundancy and high attrition rates in the use of this type of technology.
... If V * and V are equal, the user authentication is successful, and a request is sent to the terminal node [26]. e client of the system is a program that provides local services for customers. ...
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Left-behind children, as a special phenomenon group stationed in rural areas, lack parents’ education and care for a long time and shoulder the burden of life early. Moreover, in rural areas with relatively closed information, their communication with their parents only relies on short-term telephone contact. If things go on like this, it may lead to mental health problems in children. In recent years, the group of left-behind children began to get the attention of the society. The social people want to help the left-behind children mainly through the information provided by the school, which cannot actually understand the real situation of the left-behind children, and the help to the left-behind children is only a drop in the bucket. Therefore, it is necessary to use the internet as a convenient and fast platform to build a mobile information system for the mental health of rural left-behind children, input the mental health of left-behind children, and pay attention to and track the left-behind children. This paper mainly studies the construction of the rural left-behind children’s mental health mobile information system based on the Internet of Things. This paper expounds the related concepts of the Internet of Things, which has a good connection effect on the construction of the left-behind children’s mental health mobile information system. Then, it analyzes the functional requirements of the rural left-behind children’s mental health mobile information system, in terms of design, the C/S model is used, the database in the data server is designed to analyze the mental health information management needs of left-behind children, and the data model is established by defining the key domains in the system. This paper also collects and sorts out the left-behind children’s mental health data through data mining technology, studies the factors affecting the left-behind children’s mental health, and clarifies the necessity of constructing the rural left-behind children’s mental health mobile information system and focuses on the observation objects. The results show that the evaluation factors of left-behind children’s mental health are significantly higher than those of non-left-behind children, and their mental health needs attention because left-behind children lack the care of their parents for a long time. The mental health status of left-behind children aged 7–12 is the most worrying, which is significantly different from other age groups in obsessive-compulsive disorder, interpersonal sensitivity, anxiety, hostility, paranoia, and mental illness. It may be because left-behind children aged 7–12 are in the development stage, they are not as ignorant as left-behind children aged 1–6, and they are not as mature as left-behind children aged 13–17. 1. Introduction With the continuous development of urbanization, there is a lack of a large number of labor forces in urban construction, and many rural surplus labor forces turn to urban migrant workers. Because the migrant workers’ knowledge level is not high, their work is relatively difficult, and their living environment is not ideal, the migrant workers leave their children in grandparents or other relatives’ homes, and the group these children refer to is left-behind children [1, 2]. The reason why rural left-behind children are prone to mental health problems is the lack of care and love of their parents. Parents go out to work for a long time, have no time to communicate with their children, do not understand their children’s inner feelings, and do not have the habit of paying attention to their children’s mental health growth in rural areas [3, 4]. In this case, the left-behind children who live in other people’s homes lack attention and care, and they are forced to be sensible since childhood. Their physical and psychological development is unbalanced, and their values are vague, which easily leads to their mental health and going astray [5, 6]. Groups and caring people from all walks of life in the society want to understand and help the left-behind children, but they have no time to deeply understand the family situation of each left-behind child and conduct a field investigation. They can only go to the local education department or the working committee of customs and other institutions, and these institutions choose schools to recommend students for help [7, 8]. We establish an information management system for rural left-behind children to facilitate relevant departments to pay attention to and track left-behind children so that parents of migrant students can understand their children’s situation through this information platform. Through this system, caring people from all walks of life can grasp the current situation of left-behind children and provide them with the help they need as much as possible, care and concern about their study and life, and promote their psychological, ideological, and other aspects of healthy development, so that they can grow up happily in the childhood when their parents are not around [9, 10]. We establish a rural left-behind children information management system [11]. By collecting detailed information of left-behind children and entering this system database, on the one hand, it is convenient for relevant departments to pay attention to and track these children, and it can also grasp the direction and number of the floating population [12, 13]. Through this information platform, parents of students who are migrant workers can easily understand the learning and living conditions of their children in their hometowns. In addition, caring people and social groups from all walks of life can inquire and understand related information about left-behind children through this system and use this information to grasp the status quo of left-behind children as much as possible to provide them with the help they need, caring and paying attention to their study and life [14]. This paper mainly studies the construction of the rural left-behind children’s mental health mobile information system based on the Internet of Things. This paper expounds on the related concepts of the Internet of Things, and its network information collection and other integrated information networks have a good connection function for the construction of the left-behind children’s mental health mobile information system. Then, this paper analyzes the functional needs of the rural left-behind children’s mental health mobile information system and summarizes some corresponding functional needs by considering the group objects. The design of the mobile information system for the mental health of rural left-behind children is relatively simple, using C/S mode, and there are only two layers in the architecture, namely, client and data server. The database design of the data server is to analyze the left-behind children’s mental health information management needs and to establish the data model by defining the key fields in the system. This paper also collects and sorts out the left-behind children’s mental health data through data mining technology, studies the factors affecting the left-behind children’s mental health, and clarifies the necessity of constructing the rural left-behind children’s mental health mobile information system and focuses on the observation objects. 2. Research on the Mobile Information System of Mental Health of Rural Left-Behind Children Based on Internet of Things 2.1. Related Concepts of Internet of Things The Internet of Things refers to the integration of intelligent perception and identification technology and pervasive computing ubiquitous network, which is known as the third wave of the development of the world information industry after the computer Internet. Specifically, the Internet of Things connects objects to the Internet through various information sensing technologies and various communication technologies, so as to realize the integrated network of identification, tracking, management, and control of things [15, 16]. The Internet of Things is a global open-loop ubiquitous network system, which is the extension and expansion of the Internet. It extends the original communication between people to the information interaction between people and things and between things. Its network structure is shown in Figure 1. One can see from the flow chart that the low layer of the network is the sensing layer. Information sensing and communication are the purpose of converging things and the basis of IoT applications. There is an important role played by radio sensor networks in this layer. It is through the wireless network that sensor nodes transmit the sensed information to the aggregating nodes and establish a direct connection into the IoT [17]. Using the Internet of Things to build a rural left-behind children’s mental health mobile information system, we can realize rapid information exchange, timely feedback the actual situation of left-behind children to parents, guardians, and support personnel, and can pay attention to the changes in the mental health of left-behind children in real time.
... The literature is sparse on publications that address information seeking by patients with bipolar disorder [21]. Therefore, we aimed to fill this knowledge gap. ...
Full-text available
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Background: Patient education has taken center stage in successfully shared decision making between patients and health care providers. However, little is known about how patients with bipolar disorder typically obtain information on their illness and the treatment options available to them. Objective: This study aimed to obtain the perspectives of patients with bipolar disorder and their family members on the preferred and most effectively used information channels on bipolar disorder and the available treatment options. Methods: We conducted nine focus groups in Montana, New Mexico, and California, in which we surveyed 84 individuals including patients with bipolar disorder and family members of patients with bipolar disorder. The participants were recruited using National Alliance on Mental Illness mailing lists and websites. Written verbatim responses to semistructured questionnaires were analyzed using summative content analysis based on grounded theory. Two annotators coded and analyzed the data on the sentence or phrase level to create themes. Relationships between demographics and information channel were also examined using the Chi-square and Fisher exact tests. Results: The focus group participants mentioned a broad range of information channels that were successfully used in the past and could be recommended for future information dissemination. The majority of participants used providers (74%) and internet-based resources (75%) as their main information sources. There was no association between internet use and basic demographics such as age or geographical region of the focus groups. Patients considered time constraints and the fast pace in which an overwhelming amount of information is often presented by the provider as major barriers to successful provider-patient interactions. If Web-based channels were used, the participants perceived information obtained through Web-based channels as more helpful than information received in the provider's office (P<.05). Conclusions: Web-based resources are increasingly used by patients with bipolar disorder and their family members to educate themselves about the disease and its treatment. Although provider-patient interactions are frequently perceived to be burdened with time constraints, Web-based information sources are considered reliable and helpful. Future research should explore how high-quality websites could be used to empower patients and improve provider-patient interactions with the goal of enhancing shared decision making between patients and providers.
... The literature is sparse on publications that address information seeking by patients with bipolar disorder [21]. Therefore, we aimed to fill this knowledge gap. ...
Full-text available
Preprint
BACKGROUND Patient education has taken center stage in successfully shared decision-making between patients and health care providers; however, very little is known about how patients typically obtain information on their illness, especially as it relates to the treatment of bipolar disorder and what methods of information sharing are preferred. OBJECTIVE To obtain patients’ perspectives on the most effective information channels through which they educate themselves about the treatment of bipolar disorder. METHODS We conducted three focus groups in Montana, New Mexico, and California in which we enrolled 36 individuals with bipolar disorder and family members of patients with bipolar disorder. A mixed methods approach was utilized to analyze data collected through semi-structured questionnaires based on grounded theory and summative content analysis. RESULTS Participants preferred to receive information through a broad range of channels, with health care professionals, peers, and patient advocacy groups leading the list. The preferences of the participants mostly reflected information sources successfully used by them in the past, but problems with traditional approaches were also pointed out. Internet-based resources surpassed doctors as a successfully used source of information, while failed communication between patient and doctor was perceived as a leading barrier to successful outcomes. Regional differences in resources and culture strongly influenced the utilization of information channels. Most participants emphasized the importance of non-traditional ways of providing information on disease and disease management to support informed health care decision-making. CONCLUSIONS Patients use a variety of channels to educate themselves about their disease. While regional and social differences in resource use were apparent, failed doctor-patient communication was universally perceived as a barrier to successful treatment outcomes. It should be further explored how improving patient education and patient-doctor communication might increase patient engagement and could lead to better outcomes in care. CLINICALTRIAL ClinicalTrials.gov identifier: NCT02893371
... Finally, the interventions delivered through the apps need to be topically relevant, and acceptable to the patient and caregivers, thereby rendering such apps to be locally effective rather than universally usable. It is therefore of vital importance to understand the factors, which drive engagement and disengagement of end-users with mHealth technologies [33]. In India, mental health resources for psychosocial interventions are meager [34], and greater than 80% of patients suffering from SMIs fail to receive minimally adequate treatment for their illness [35,36], creating a mental health treatment gap of more than 80%. ...
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... People are motivated to use ICTs because of their affordability, accessibility (especially for those living in remote or rural areas), versatility and functionality. Of utmost importance is, moreover, the privacy and anonymity, the decrease of feelings of stigma and, in terms of social relationships, the fact that they facilitate dialogue, collaboration and opportunities for feelings and experiences exchange [10]. ...
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The anonymity of the Internet may provide depression information to Asian Americans who often associate depression with shame and stigma beliefs and avoid treatment. We interviewed 20 Asian Americans regarding reasons for Internet depression information use, non-use, and relevant Web site topics. Thematic analysis was used to analyze the qualitative responses. Reasons for Internet use included difficulty talking face-to-face, confidential, useful information, and convenience. Reasons for non-Internet use included "not a good source" and denial concerning depression. The Internet can allow for depression information tailored to Asian Americans and this study suggests topics of interest to include on such a Web site.
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Introduction A smart phone application (app) for patients with inflammatory bowel Disease (IBD), was introduced in April 2013 for IBD patients. Patients were requested to record symptoms daily on the app which were then sent behind the NHS firewall and were then available, via a dashboard system. The aim of this study was to perform qualitative analysis of patient focus groups formed for the study. Method Two focus groups were arranged after the app had been in use for three months. One of the focus groups was with participating clinicians in the unit, and one with a sample of participating patients. Both were conducted by an external qualitative researcher (DH). Interviews were recorded with participants’ permission, coded and analysed in Nvivo using a framework approach. 40 patients were recruited, and of these a purposive sample of 10 consented to participate in the focus group. Results A framework analysis of the recordings revealed distinct themes. Technical features of the app – Patients felt the app easy to use despite some teething issues around connectivity. There were issues depending on the type of phone the patient was using. All patients had experienced some issues, but accepted this at this stage because the app was being tested, Some patients reported that they liked the fact they were all collecting the same information. Patients expressed few, if any, concerns about the security of information being recorded. Use of the app – All patients reported using the app every day with only some minor exceptions. This was because the data they were collecting was of real importance to them. There was genuine enthusiasm and support for this innovation. Patients felt self monitoring had begun to transform subsequent clinical encounters. Patients felt reassured that their symptoms were monitored by a specialist Nurse. Features of success – The ability of patients to transmit data directly to the clinical team was seen as critical by patients. The integration of the application into the healthcare delivery is another key feature. Patients who had not collected structured information about themselves before, reported that they were better able to think about their disease. Conclusion Whilst it is still too early to ascertain whether this innovation is sustained and becomes normalised into everyday practice, the results from this study suggest it will. The ability for patients to send data directly to clinicians was seen as a key attribute of this development. Patients who had had a clinic visit since using the app felt it had made a significant impact on the consultation. This app fitted into patients lives and was tailored to their needs, and was a successful first step in releasing the potential that technology provides for this patient group. Disclosure of interest None Declared.