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Original Paper
The Effect of Information Communication Technology Interventions
on Reducing Social Isolation in the Elderly:A Systematic Review
Yi-Ru Regina Chen1, PhD; Peter J Schulz2, PhD
1Hong Kong Baptist University, Kowloon Tong, China (Hong Kong)
2University of Lugano, Lugano, Switzerland
Corresponding Author:
Yi-Ru Regina Chen, PhD
Hong Kong Baptist University
Department of Communication Studies
Hong Kong Baptist University
Kowloon Tong,
China (Hong Kong)
Phone: 852 3411 5057
Fax: 852 3411 7375
Email: yrchen@hkbu.edu.hk
Abstract
Background: The aging of the population is an inexorable change that challenges governments and societies in every developed
country. Based on clinical and empirical data, social isolation is found to be prevalent among elderly people, and it has negative
consequences on the elderly’s psychological and physical health. Targeting social isolation has become a focus area for policy
and practice. Evidence indicates that contemporary information and communication technologies (ICT) have the potential to
prevent or reduce the social isolation of elderly people via various mechanisms.
Objective: This systematic review explored the effects of ICT interventions on reducing social isolation of the elderly.
Methods: Relevant electronic databases (PsycINFO, PubMed, MEDLINE, EBSCO, SSCI, Communication Studies: a SAGE
Full-Text Collection, Communication & Mass Media Complete, Association for Computing Machinery (ACM) Digital Library,
and IEEE Xplore) were systematically searched using a unified strategy to identify quantitative and qualitative studies on the
effectiveness of ICT-mediated social isolation interventions for elderly people published in English between 2002 and 2015.
Narrative synthesis was performed to interpret the results of the identified studies, and their quality was also appraised.
Results: Twenty-five publications were included in the review. Four of them were evaluated as rigorous research. Most studies
measured the effectiveness of ICT by measuring specific dimensions rather than social isolation in general. ICT use was consistently
found to affect social support, social connectedness, and social isolation in general positively. The results for loneliness were
inconclusive. Even though most were positive, some studies found a nonsignificant or negative impact. More importantly, the
positive effect of ICT use on social connectedness and social support seemed to be short-term and did not last for more than six
months after the intervention. The results for self-esteem and control over one’s life were consistent but generally nonsignificant.
ICT was found to alleviate the elderly’s social isolation through four mechanisms: connecting to the outside world, gaining social
support, engaging in activities of interests, and boosting self-confidence.
Conclusions: More well-designed studies that contain a minimum risk of research bias are needed to draw conclusions on the
effectiveness of ICT interventions for elderly people in reducing their perceived social isolation as a multidimensional concept.
The results of this review suggest that ICT could be an effective tool to tackle social isolation among the elderly. However, it is
not suitable for every senior alike. Future research should identify who among elderly people can most benefit from ICT use in
reducing social isolation. Research on other types of ICT (eg, mobile phone–based instant messaging apps) should be conducted
to promote understanding and practice of ICT-based social-isolation interventions for elderly people.
(J Med Internet Res 2016;18(1):e18) doi:10.2196/jmir.4596
KEYWORDS
social isolation; elderly; ICT intervention
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Introduction
It is estimated that the proportion of the world population aged
60 years and older will reach 22% by 2050 [1]. Social isolation
among the elderly is therefore a growing concern. Depending
on the definition and measure, the prevalence of social isolation
among people aged 60 years and older is 7% to 24% [2-7]
compared to 7% in the general population [6]. In addition,
perceived social isolation is more severe among the older old
people (aged 75-85 years) than the younger old (aged 57-65
years) [8]. Most importantly, social isolation is a real threat to
the mental and physical health of the elderly population [7-11],
leading to depression [3,12], self-harming (eg, drug abuse,
alcoholism, suicide) [13-15] or self-neglecting behavior [16],
a higher level of cognitive and/or physical disability [17], and
increased mortality [8,18]. Consequently, preventing or
ameliorating social isolation in that age group is becoming a
top social topic and a priority in policy-making in many
countries [19-20].
Social isolation is a multidimensional concept that lacks a clear
and consistent definition in the literature [21-22]. Some scholars
see it as directly equivalent to loneliness and use the terms
interchangeably [20]; others perceive the two concepts as related
yet distinct. For example, social isolation has been defined as
the absence of contact with people who provide social support
[23]. Others have defined it as a 2-dimensional concept that
contains an objective absence of contacts or interactions with
the contacts and a subjective feeling of limited or lost
companionship or social support (ie, loneliness) resulting from
having limited contacts or interactions [8,21]. No matter which
definition one adopts, social isolation is considered a result of
the elderly population’s reduced social interactions—particularly
with family, friends, and community networks—caused by their
retirement, physical changes (cognitive and physical
disabilities), inevitable loss of spouse or friends (shrinking
network size), and/or living alone or in institutions [8].
Information and communication technology (ICT) may
overcome the social and spatial barriers of social interaction by
enabling easy, affordable communication and activities of
multiple forms (ie, textual, audio, and/or visual) between the
elderly (often with limited mobilization) and others anytime
and anywhere. Many researchers have therefore been
investigating its potential for alleviating social isolation in the
elderly.
A search of the literature identified 4 systematic reviews
[20-21,24-25] that synthesized the effects of social isolation
interventions. These reviews examined studies of various
designs, including randomized controlled trials (RCTs),
experiments, quasi-experimental studies, and before-and-after
(cohort) studies, published in the periods 1970 to 2002 [21,24],
1976 to 2009 [20], and 2000 to 2013 [25]. While 3 reviews
examined all forms of interventions for social isolation
[20-21,24], Morris and colleagues [25] focused only on the
interventions using smart technologies to synthesize the effect
of interventions on social connectedness of the elderly living
at home and found conflicting results.
The objective of our systematic review is to gain a synthesis of
the evident effects of ICT interventions on social isolation in
the elderly. Our review is timely and valuable for the following
reasons: (1) it reviews the effect of ICT interventions on the
elderly with various characteristics (eg, demographics, health
status, and living arrangements); (2) it covers the most recent
research, published between 2002 and 2015; and (3) in addition
to quantitative research, it includes studies that used qualitative
methods (ie, observations, in-depth interviews, and focus group
interviews) to offer insights into the mechanisms underpinning
the observed variations in ICT effectiveness.
Methods
Searching Strategy, Inclusion Criteria, and Study
Selection
Electronic searches for this systematic review were conducted
in July 2015 using PsycINFO, PubMed, MEDLINE, EBSCO,
SSCI, Communication Studies: a SAGE Full-Text Collection,
Communication & Mass Media Complete, Association for
Computing Machinery Digital Library, and IEEE Xplore. These
databases were used because they include research on subjects
such as health, aging, social science, digital technologies,
computer-mediated communication, and communication science.
A unified search term using Boolean operators was applied for
all databases: ((social isolation OR loneliness) AND elderly
AND (Internet OR social media OR information and
communication technology)). Next, to ensure a broad inclusion
of published studies relevant to our review topic, we adopted
the following criteria to select studies for the review: (1)
publications must be in English; (2) studies must empirically
investigate the effects of ICTs on one or more attributes of social
isolation among the elderly; and (3) study participants must be
aged 55 years or older.
The search yielded 424 publications, of which 51 duplicates
were removed. The first author then checked the remaining titles
and abstracts to determine their relevance. If the information
provided by a title or abstract was insufficient for determination,
the full paper was screened by 2 researchers who documented
the reasons leading to the exclusion of full texts. An additional
2 studies were found in the systematic review of studies on the
elderly population’s social connectedness and smart technologies
by Morris et al [25]. A total of 30 articles met the inclusion
criteria outlined in Figure 1 and were retained for this systematic
review. After carefully reading the full texts of the articles,
researchers excluded 5 more studies because of a lack of a
complete text (1 article), no examination of social isolation as
the outcome of ICT use (3 articles), and the participants being
aged younger than 55 years (1 article).
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Figure 1. An overview of the inclusion process.
Data Analysis and Synthesis
Data on study design, sample size and characteristics, types of
ICT applications, targets of elderly interaction via ICT
applications, comparison groups, and outcomes were extracted
from the selected studies and analyzed using a coding scheme.
For research quality assessment of quantitative research, the
Effective Public Health Practice Project (EPHPP) tool [26] was
used because of its suitability for assessing such research with
various study designs. The EPHPP tool evaluates 6 components
of a quantitative study: selection bias, study design, confounders,
blinding, data collection method, and withdrawals and dropouts.
Based on performance in each component, an overall rating (ie,
strong, moderate, or weak) of each study can be determined.
The criteria proposed by Salmon [27] were used to evaluate the
qualitative research: theoretical framework, value of study, data
collection, participant description, data analysis, and data
interpretations. For publications reporting more than one study,
each study was independently analyzed. Data coding and quality
appraisal were conducted by the first author and a research
assistant, reaching an intercoder reliability of .91. Any
inconsistencies between the reviewers were discussed between
the 2 authors to achieve agreement.
The included studies differed in their research designs, research
locations, participant characteristics, types and usage of
interventions, and outcome measures. In view of the studies’
heterogeneity, a narrative synthesis (instead of a meta-analysis)
was performed [28].
Results
Characteristics of Examined Studies
All projects were published between 2002 and 2015, with 11
dated before 2010 [29-39] and 14 dated in or after that year
[40-53]. They were conducted in 12 countries (Austria, Canada,
Finland, Israel, Netherlands, New Zealand, Norway, Slovenia,
Sweden, Taiwan, United Kingdom, and United States) with the
highest number coming from the United States (n=9). In the 25
projects, 30 studies were reported (5 projects reported 2 studies:
1 quantitative and 1 qualitative). RCTs comprised 6 studies
[36,39,43,47,51-52]; another 6 were cohort studies (2 with a
control group [30,35] and 4 without [31,38,41,44]). Of the
remaining studies, 4 were cross-sectional studies (surveys)
[32,37,40,46] and 14 were qualitative studies: 9 employing
in-depth interviews [29-31,34-35,42,45,48-49], 3 conducting
focus group interviews [33,38,53], and 2 applying participant
observations [39,50]. See Multimedia Appendix 1 for a complete
description of the characteristics of the 25 reviewed publications.
Most research used some form of Internet or Web-based apps
(eg, search, email, online chat rooms, videoconferencing, social
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networking apps, and Web-based telehealth systems) on
computers. Among those that did not, 1 study employed a
telephone befriending intervention, 1 used mobile phones
(smartphones), 1 focused on iPad use, 1 applied Nintendo Wii
(a video game system), and 1 used a visual pet companion app
that allowed the senior users to interact with a pet avatar in real
time through an android tablet. The ICT intervention in all but
2 studies was implemented in the regular living environments
of the participants, including private housing (n=13), assisted
and independent living communities (n=2), congregate housing
sites (n=1), retirement villages (n=2), nursing homes (n=4), day
care centers (n=1), and no specifics on where they resided (n=2).
The intervention was implemented in both settings for 3 projects
[35,39,41] that worked with participants from 2 selected
residential settings. The visual pet intervention [50] was mobile,
and the participants used it in their familiar surroundings not
bound by their living environment. The Finland study by Blažun
et al [41] had the intervention set up at a community college.
The ICT intervention in all but 2 studies aimed to facilitate
interaction with other people in general (the participants most
frequently contacted their family members, friends, significant
others, doctors, and acquaintances made through online chat
rooms). The other 2 studies [51-52] designed the intervention
for the older person’s interaction with family members only.
Characteristics of Participants
Sample size of the studies varied from 8 to 5203. The number
of participants in the RCT studies ranged from 22 to 205. The
sampling strategy of most studies (n=25) was convenience
sampling; 3 [36,40,46] used random sampling and 2 [43,48]
did not specify the sampling strategy.
Participants’average age ranged from 66 years (SD not given)
to 83 years (SD 1.4) with heterogeneity across demographics,
including age, gender, education, income, health status, mental
status, living arrangements, and nationalities. Of the chosen
studies, 1 [45] had equal numbers of male and female
participants and 1 [38] had more males (n=17) than females
(n=15). For the remaining studies, female participants often far
outnumbered males even though ICT use among the elderly is
highly associated with males [54]. There are two possible
explanations for this phenomenon: (1) women have longer life
expectancy across nations than men and (2) women are more
likely to feel lonely and communicate with others and are
therefore more likely to participate in such studies. Of the 25
projects, 2 [30,42] recruited living-alone elders only. In terms
of participant health characteristics, 4 projects [29,36,41,47]
targeted elderly people in generally good health and 5
[30-31,34,38,42,50] looked at those at high risk (lonely, frail,
or chronically ill or physically handicapped seniors, those having
dementia, and carers of spouses with dementia or after stroke).
The other studies did not use health status as a filtering criterion
for sampling. For other participant characteristics, 1 study [49]
examined elderly former Soviet Union immigrants in Israel with
financial difficulties and 1 [33] targeted elderly people interested
in computer use. See Multimedia Appendix 2 for details on
participant characteristics.
According to the EPHPP quality assessment tool, an attrition
rate of 40% or above indicates weak data collection for a study
[26]. Based on this standard, 3 studies [30-31,52] were assessed
to have a large number of dropouts. Fokkema and Kinpscheer
[30] targeted solitary, lonely seniors with chronic illness or
physical disability. The participants’physical and psychological
conditions might account for the high attrition rate (43%) even
considering the addition of 6 participants from the waiting list
to replace the first 8 dropouts. The other 2 studies [31,52] were
longitudinal projects lasting 12 months. The study duration
contributed to the high rate of participant attrition, especially
in a study targeted at the elderly in nursing homes [52]. Of the
participants in Mellor’s study [31], 60% were lost in the
follow-up. In the study by Tsai et al [52], 44% of the participants
in the control group did not complete the study. Of particular
concern was a study by Machesney el al [50] in which the
number of dropouts was unfortunately not specified but referred
to as “several.”
Dependent Variables and Outcome Measures
The outcome of ICT use was examined in 4 studies
[42,43,48,49] by exploring its effect on social isolation in
general, while the remaining studies assessed specific aspects
of social isolation only. Social isolation as an outcome indicator
was only quantitatively measured by Cotton et al [43] using a
self-developed scale that contained 3 items, asking how
frequently the participant was bothered by (1) not having a close
companion, (2) not having enough friends, and (3) not seeing
enough of people they feel close to. The other 3 qualitative
studies did not clearly define the term. Catton and colleagues
[42] seemed to regard social isolation as being forgotten and
not belonging. Kahlbaough et al [47] and Karimi and
Neustaedter [48] linked the concept to “not being connected
with family, friends, and existing contacts.” It should be noted
that researchers in the 3 qualitative studies perceived social
isolation and loneliness as highly interrelated, if not
interchangeable, while Cotton et al [43] analyzed social isolation
and loneliness as two separate outcomes of ICT use.
Studies that examined ICT impact on social isolation did so by
looking at its effect on 1 or more of the 7 single attributes of
social isolation: loneliness, social support, social contact,
number of confidants, social connectedness/social connectivity,
social networks, and social well-being. Among these, loneliness
was the most tested dependent variable (n=18). It was measured
by the University of California Los Angeles Loneliness Scale
in 20 of the 25 projects. Fokkema and Knipscheer [30] used de
Jong-Gierveld and Kamphuis’ loneliness scale [55] whereas
Aarts et al [40] used the scale’s short version of 6 items [56].
Heo et al [46] employed the social support scale by Schuster et
al [57] to assess loneliness while Sum et al [37] adopted the
Social and Emotional Loneliness Scale. Rather than using a
standardized scale, Blažun et al [41] used self-reported items
of loneliness by the elderly participants in their pre-intervention
survey to evaluate outcomes.
Social support was assessed by Tsai and colleagues [51-52]
using Hsiung’s Social Support Behaviors Scale, which includes
subscales regarding (1) number of social networks, (2) quantity
of social support behavior (emotional, informational,
instrumental, and appraisal support), and (3) satisfaction with
social support. The social support instrument used by Torp et
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al [38] was adopted from the scale developed by Russel and
colleagues [58]. Torp et al also examined social contact as
another outcome indicator, applying Andersson’s [59] Family
and Friendship Contacts Scale. Social well-being was
conceptualized as a multidimensional variable by Slegers et al
[36] and was measured using de Jong-Gierveld and Kamphuis’
loneliness scale and the number of social networks. Social
connectedness/social connectivity and social networks examined
in the reviewed qualitative studies were not clearly defined but
were related to the number of connections with others and/or
with society at large. Mellor et al [31], however, measured social
connectedness using Lee and Robin’s Social Connectedness
Scale [60] in their cohort study.
It is worth noting that even though depression is not a dimension
of social isolation, it is a related concept that attracts much
academic attention. Of the reviewed studies, 6 also examined
depression as an outcome variable [35,39,42,50-52]. This
research tendency reflects the previous findings that social
isolation leads to depression (a negative indicator of
psychological well-being) among the elderly. Self-esteem,
self-control, and quality of life were the other related outcomes
of ICT intervention tested in the studies.
Effects of ICT Interventions on Alleviating Social
Isolation
Of the studies addressing the relationship between ICT usage
and social isolation in general, 4 demonstrated a positive result:
the use of telephone befriending programs [42], computer and
Internet [43,49], and ICT in general [48] lessened social
isolation. The reported effect of ICT use on the individual
dimensions of social isolation was consistent across studies,
except for that on loneliness. ICT interventions significantly
fostered social support, social contacts, social
connectedness/social connectivity, and social networks among
the participants, but no effect was found on number of confidants
[39] or social well-being [36].
Of the studies examining loneliness, 15 of 18 revealed a
significant reduction of loneliness among the elderly using ICT.
Studies using communication programs (using landline phones,
smartphones, iPads, emailing, and online chat rooms or forums)
and high-technology apps (Wii, the TV gaming system, and
Gerijoy, a virtual pet companion) consistently reported a positive
effect on alleviating loneliness. The general use of computer
and Internet in an RCT design was assessed in 2
nonsignificant-result studies [36,39], with 1 [36] targeting
healthy elderly people living at home and the other [39] targeting
elderly people living in subsidized housing or nursing facilities.
The remaining non-significant study [40] examined the use of
social networking sites in particular. Considering that other
studies reporting a significant effect of such interventions also
used the RCT and survey design targeting the elderly with
different levels of health status and in various living situations,
it is evident that the effect of the computer and Internet and of
social networking sites on improving loneliness among the
elderly was inconclusive. Another inconclusive finding concerns
the effect of videoconferencing on loneliness reduction among
the elderly. Blažun and colleagues [41] found that Slovene
participants at nursing homes reported no change of loneliness
level after their use of Skype, while loneliness of Taiwanese
nursing home participants was significantly lessened after their
videoconferencing via Skype or Windows Live Messenger
[51-52].
Furthermore, Sum et al [37] found that computer and Internet
use functioned differently for various types of loneliness: social
loneliness, family loneliness, and romantic loneliness. Using
computers and the Internet to communicate with acquaintances
alleviated elderly people’s social loneliness, but heavy usage
(of long duration) was positively associated with social
loneliness. In addition, using the computer and Internet to make
new contacts resulted in family loneliness. The impact of
computer and Internet use on romantic loneliness was not
determined.
Internet use increased social support among the elderly in
general [46] and among those who were the main carers of their
spouses with dementia or after a stroke in particular [38]. In a
similar vein, Nahm’s [32] survey data revealed a positive
function of the elderly population’s Internet use in building
computer-mediated social networks, which led to social support.
Interview data from the study by Dhillon et al [45] suggested
that ICT (such as Facebook or networking games) fostered social
interaction and social support that further alleviated loneliness
among the elderly. Tsai et al [51] found that videoconferencing
chats between elderly people at nursing homes and family
members significantly increased emotional (ie, caring, empathy,
love, and trust) and appraisal (ie, communicating information
relevant to self-evaluation) support but not informational (ie,
communicating information for problem-solving assistance) or
instrumental (ie, tangible goods, services, and aid) support.
However, this positive effect on social support was not found
at the 6-month or 12-month stages of the intervention [52]. In
addition, videoconferencing chats gave lower perceived
instrumental support at the 6-month or 12-month stages while
the frequency of in-person visits was not changed. The
instrumental support finding may, as claimed by the researchers,
imply that video chats assisted the elderly in better adapting to
the living environment in the nursing home. Thus, their need
for tangible goods, services, or aid dropped as their length of
residence increased.
The relationship between ICT use and social connectivity/social
connectedness or social networks was tested in 6 projects, which
reported a generally consistent pattern. ICT in general (Internet,
mobile/smartphones, iPads, social networking sites, and
audio/video chat apps) served as an effective means for the
elderly to remain connected with others [31,35,44,48] and
expand their social networks [32,53]. It is important to note that
Mellor and colleagues [31] reported that elderly people’s use
of computer and Internet at home increased their social
connectedness at the 3-month stage of intervention but not at
the 6-month or 9-month stage.
In addition to the social-isolation dimensions, a few studies
explored the impact of ICT on related constructs, including
depression, anxiety, negative affect, cognition, physical
functioning (or daily activities), self-control (or perceived
control), self-esteem, and quality of life (or life satisfaction).
The results pertaining to the effect of ICT use on depression
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were consistent and generally positive with only 1 study [50]
reporting no clear information in the results section. While 2 of
the 3 studies concluded that ICT led to positive effects, 1 [31]
reported inconclusive results in this outcome. A favorable
influence of ICT on life satisfaction was revealed in 4 studies
[35,42,47,50], while 2 studies [31,39] found non-significant
change in life satisfaction after using ICT. Neither self-esteem
[31,39] nor control over life [36,39] was identified as a
significant outcome of ICT use. Perception of self-control was,
however, significantly increased after accessing ICT [35]. ICT
use was found to improve physical health in the elderly [42].
Its effect on increasing the physical activities was inconclusive
[36,47].
Lastly, a few studies assessed the effect of ICT use on the
quantity and quality of communication of the elderly with others,
and 3 studies [39,43,53] found a positive outcome. More elderly
participants from Clark’s study [29] stated that the Internet chat
environment did not confine their messages for communication
than said it did.
Quality Assessment of Examined Studies
While 4 quantitative studies were rated as moderate
[35,43,46,52] and 4 as strong [36,39,47,51], 8 were rated as
weak [30-32,37-38,40-41,44]. Among the 4 strong studies,
Slegers et al [36] stood out with its rigorously controlled,
randomized design. After randomizing twice, it compared the
long-term effect of computer and Internet use on loneliness
among the elderly in 4 conditions: training-intervention,
training-no intervention, no training-no intervention (people in
this condition had an interest in computer and Internet use), and
control group (people here were not at all interested in ICT use).
The majority of the studies used a convenience sample that
resulted in a high risk of selection bias. Consistent with the
evaluation results of Morris et al [25], all but 6 of the chosen
quantitative studies [36,40,44,49,51-52] failed to specify the
proportion of the source population participating or the
proportion of those who agreed to participate in the assigned
group. The lack of such information makes it hard to determine
the samples’representativeness. Of the 6 studies, 2 [40,44] had
a participation proportion of less than 60%. None of the studies
report any attempt to blind the participants from the intervention
outcomes being examined. Information about whether the
assessor (or caregiver) was aware of the intervention was very
limited. There were 2 studies [30,43] that did not examine the
possible differences between the experiment and control groups
prior to the intervention. Furthermore, 3 studies [36,43,50] did
not specify the duration of ICT intervention, and in 2 studies
[35,43] the format of ICT training (ie, individual or group
training) was not reported. Information about the training format
is necessary because the literature suggests a relationship
between the format and effectiveness of training for the elderly,
who are likely to be slow learners of ICTs [31,39].
Of the 16 quantitative studies, 7 controlled for confounding
factors in the analyses of effects of ICT interventions. Such
factors included number of friends and family [43],
physical/emotional/social limitations [43], number of children
[35], positive life events [35], personal motivations (ie, learning
new skills and gaining attention from others) [36], personality,
perceived psychological health [34], length of residency in
nursing homes [51-52], educational level [40], sex [40], and
age [40,51-52]. Of particular concern was the high percentage
of participants who dropped out over the course of the trial in
a few studies and the lack of power analysis conducted in all
but 1 [36] of the RCT studies.
Among the qualitative studies, 4 [30-31,35,38] were conducted
as a secondary analysis to provide further insights into the results
of a (randomized) quantitative study. The quality of most
qualitative studies was low because the authors failed to address
several key areas, as proposed by Salmon [27]. First, most such
studies (whether stand-alone or secondary) were descriptive or
exploratory without examining specified propositions derived
from the literature, while 3 studies [33,49,53] discussed the
findings based on theories. Second, the interviewee recruitment
processes were not clearly specified. Most studies reported the
sampling frame and characteristics of the interviewees but some
failed to provide information about the recruitment method (eg,
randomly, purposively, or conveniently recruited) and others
did not explain how a certain location, nursing home, or
community was selected and why. Additionally, even though
most studies reported the number of interviewees, none of them
mentioned whether the number was a result of theoretical
saturation. Without such information, readers are unable to
determine the appropriateness and richness of the data.
Furthermore, most studies [30-31,34-35,39,48,50] did not clearly
report how the data were collected and analyzed. They often
failed to report the interview protocol or the coding procedure
even though some did state how they identified the emerging
themes. This information is crucial because the researchers’
approach to the data directly determines what the findings are.
Lastly, a serious concern was that many authors reported the
data superficially without interpretation or implications.
Discussion
This systematic review is, to our knowledge, the first to address
the potential of ICT for preventing or reducing social isolation,
a state that implies the risk of deteriorating physical and
psychological well-being for the elderly. The results of this
systematic review provide emerging quantitative and qualitative
evidence to support the function of ICT in alleviating social
isolation (in general or in particular dimensions) among elderly
people. This review advances the mechanism of how ICT assists
the elderly in combating social isolation and provides insights
for policies and practices.
Social Isolation as an Untested Concept
Most studies of the review evaluated the effect of ICT use on
single social-isolation dimensions, including loneliness, social
support, and social connectedness. This pattern is consistent
with that revealed in the review of studies by Dickens and
colleagues [20] on social isolation interventions for the elderly,
where only 2 of the 32 studies used social isolation as an
outcome variable while the remaining studies mostly assessed
loneliness, social network size, and social support. These
findings suggest that social isolation of the elderly as a
multidimensional concept is largely understudied [20,22]. Even
though evidence shows that the use of ICT affects specific
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aspects of social isolation, its effect on the overall perception
of social isolation remains largely unknown. Therefore, more
research is needed to unlock the relationship between ICT
interventions and social isolation reduction.
The limited examination of the general concept of social
isolation as a multidimensional construct might be a result of
the lack of an appropriate scale. Sansoni et al [61] found the
following 4 instruments of social isolation to be the leading
ones in the literature: the Lubben Social Network Scale [62-64],
the de Jong-Gierveld Loneliness Scale [55-56], the Medical
Outcomes Study Social Support Survey [65], and the
Multidimensional Scale of Perceived Social Support [66]. These
instruments are clearly designed for measuring particular aspects
rather than the overall concept of social isolation. Future
research is required to develop a reliable scale of social isolation
as a multidimensional variable by first discovering the concept’s
underpinnings from the perspective of the elderly. For instance,
the comprehensive review of social isolation literature conducted
by Nicholson [22] identified 5 key attributes of social isolation:
(1) belonging, (2) social contacts, (3) quality of relationships,
(4) fulfilling relationships, and/or (5) engagement. When
investigating the complex relations between social isolation and
health, Cornwell and Waite [8] operationalized social isolation
as a variable of multiple components (ie, social contact
frequency, social network size, social activity, loneliness, and
social support) integrated into 2 forms: social disconnectedness
and isolation. Further evaluation should be performed to validate
the applicability of the instruments for measuring single aspects
of social isolation versus that of the instruments tapping social
isolation as a multidimensional construct. Even though some
dimensions of social isolation were addressed by the studies
included in this review, there are still some such as quality of
relationships and engagement that remain untested in relation
to the effect of ICT intervention. Researchers should explore
these dimensions in future studies to advance our understanding
of social isolation.
The Mechanism of ICT in Alleviating Social Isolation
ICT use consistently affected social isolation in general, social
support, and social connectedness positively, but the positive
ICT effect on social connectedness and social support rarely
lasted for more than 6 months after the intervention. The results
for loneliness were inconclusive. The results for self-esteem
and control over life were consistently nonsignificant.
After triangulating the quantitative and qualitative data of the
included studies in this review, it is suggested that the elderly’s
employment of ICT reduces their social isolation through the
following mechanisms: connecting to the outside world, gaining
social support, engaging in activities of interest, and boosting
self-confidence. ICT helps the elderly stay connected with their
family members (especially grandchildren), friends, former
colleagues, acquaintances, and new contacts of shared interests
or needs across temporal and geographical boundaries via digital
interactions. Connections lead to social inclusion and foster
social support. ICT also allows elderly people to renew their
hobbies or competence and participate in enjoyable activities
without the time constraint. Most importantly, ICT use boosts
self-confidence among the elderly by making them “connected
to information,” “feel young,” “become one of the modern
generation,” “overcome challenges,” “equip themselves with
new skills,” “stay socially active,” and “help others online.” It
is worth noting that providing advice to the younger generation
(acquainted or unknown) has a significant positive impact on
the elderly population’s self-confidence. The self-confidence
gained leads to self-efficacy that goes beyond the use of ICT
and participating in social activities. ICT use also empowers
the elderly by engaging them in critical thinking and
decision-making and providing access to information and
resources. Self-confidence and empowerment further trigger
their positive feelings toward themselves and their control over
life and/or life satisfaction. Thus, a further examination of
self-efficacy, mastery, and empowerment as outcomes should
be promising for theory building in the field of social isolation.
ICT Use Among the Elderly
The findings of this review suggest that the elderly can benefit
from ICT interventions and will use them (sometimes
frequently) after proper training. At the same time, the high
attrition rate of participants in the trials and the inconclusive
results of ICT impact on loneliness reduction imply that ICT is
not suitable for every senior. Spatial (eg, home-bound or
institutionalized) and social (eg, immigrants or spousal carers)
barriers to socialization, interest in ICT, motivations for ICT
use, cognitive capability, sufficient eyesight, and basic physical
ability to use the equipment (eg, figure or hand movement, skills
of using the touch pad) are possible predictors of the suitability
of ICT for the elderly. Furthermore, tailor-made training for the
elderly (in terms of its setting, procedure, materials, timing, and
instructor’s style and attitude) is necessary for a maximum
positive effect of the ICT on alleviating social isolation.
There are different mechanisms by which ICTs influence
different kinds of loneliness and social support among the
elderly [37,51-52]. The results reveal the interplay between the
ICT-mediated activity and the effect of such behavior on
particular types of loneliness and social support. Considering
that there were only 2 studies addressing the types of loneliness
and 2 examining types of social support, future research on
these topics should advance the understanding of ICT’s role in
alleviating social isolation. Results of such research can provide
insights into which individuals among the elderly can most
benefit from ICT to reduce their loneliness or increase their
social support in particular cases.
Future Development
The majority of the reviewed studies tested the ICT intervention
as a one-time trial among a small number of participants. Thus,
the generalizability of the results is limited. Further examination
is needed to test their applicability.
Most ICT interventions examined in this systematic review
involved the use of the computer and Internet. With the rapid
development of ICT, other types of interventions should be
explored. As stated by some interviewed participants of the
reviewed studies, the use of ICT allowed them to adjust to their
younger family members;#8217 communication style and
preferences. As a result, it enhanced the quantity and quality of
their intergenerational communication. Similarly, Clark [27]
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observed that use of a particular platform, if one has a sufficient
number of friends, lessens social isolation. ICT that is currently
prevalent—instant messaging (eg, WhatsApp, Line, Snapchat),
YouTube videos, and social networking sites (eg, Facebook,
Instagram)—should be further investigated for the potential in
reducing social isolation among the elderly. For example, Harley
and Fitzpatrick [67] found that YouTube allowed a senior user
to engage in communication beyond the family context with
younger YouTubers who shared his interests using self-made
videos (ie, videoblogging). Such behavior further fulfilled the
senior’s social and emotional needs and increased his
self-confidence. Also of interest for further research are mobile
phone apps, because elderly people demonstrate a fast-growing
rate of mobile phone-based ICT adoption across their age groups
in wealthy countries [68].
Additionally, the results of this review suggest that ICT use
does not guarantee quality of communication. For example,
when the ICT-mediated communication is not reciprocal, the
ICT use could increase social isolation among the elderly [48].
Consequently, examining how to use ICT for generating quality
communication between the elderly and others (eg, using
videoconferencing for the elderly to virtually join family
activities) can be a promising subject for future research on
social isolation and/or intergenerational communication.
Strengths and Weaknesses of the Review
This systematic review tackled an emerging trend of social
isolation research: ICT interventions for reducing social isolation
in the elderly. The comprehensive search strategy and the
inclusion of studies of all designs increased the likelihood of
including all relevant studies in the field. Presenting the results
of both randomized and nonrandomized research might be a
limitation of this study. However, this review decision
broadened our exploration of the available social-isolation
interventions and their effectiveness and helped to better achieve
the objective of this study.
The heterogeneity of studies included in this review limits the
comparability and generalizability of our results. Although
restricting the scope to studies published in English might
introduce bias, the reviewed studies were conducted in America,
Europe, and the Asia-Pacific region.
Conclusion
This systematic review has suggested a need for more
well-designed studies on the effect of ICT interventions on the
social isolation of elderly people. ICT in general is a promising
tool for tackling social isolation of the elderly, but it is not for
every senior. Research identifying who among the elderly can
most benefit from ICT use and how the training and
implementation of such intervention should be tailored to
maximize its effect offers great value for clinical practice. In
addition, with the rapid development of ICT, the effectiveness
of other types of interventions (eg, mobile phone-based instant
messaging apps and YouTube videos) in reducing social
isolation should be empirically examined. Results of such
research can facilitate innovative and effective practice of
ICT-based social isolation interventions for elderly people.
Conflicts of Interest
None declared.
Multimedia Appendix 1
Characteristics of the selected studies.
[PDF File (Adobe PDF File), 247KB - jmir_v18i1e18_app1.pdf ]
Multimedia Appendix 2
Participant characteristics of the selected studies.
[PDF File (Adobe PDF File), 160KB - jmir_v18i1e18_app2.pdf ]
References
1. World Population Ageing 2007. New York: United Nations; 2007. Magnitude and speed of population ageing URL: http:/
/www.un.org/en/development/desa/population/publications/pdf/ageing/WorldPopulationAgeingReport2007.pdf [accessed
2015-11-13] [WebCite Cache ID 6d0OGYWLn]
2. Victor C, Bowling A, Bond J, Scambler S. Loneliness, social isolation and living alone in later life. Sheffield, UK: University
of Sheffield: Economic and Social Research Council Growing Older Programme; 2003.
3. Iliffe S, Kharicha K, Harari D, Swift C, Gillmann G, Stuck AE. Health risk appraisal in older people 2: the implications
for clinicians and commissioners of social isolation risk in older people. Br J Gen Pract 2007 Apr;57(537):277-282 [FREE
Full text] [Medline: 17394730]
4. Tomaszewski W, Barnes M. Investigating the dynamics of social detachment in old age. In: Banks J, Breeze E, Lessof C,
Nazroo J. editors. Living in the 21st century: older people in England. The 2006 English Longitudinal Study of Ageing
(wave 3). London: Institute of Fiscal Studies; 2008:150-185.
5. Hawthorne G. Measuring Social Isolation in Older Adults: Development and Initial Validation of the Friendship Scale.
Soc Indic Res 2006 Feb 13;77(3):521-548. [doi: 10.1007/s11205-005-7746-y]
J Med Internet Res 2016 | vol. 18 | iss. 1 | e18 | p.8http://www.jmir.org/2016/1/e18/ (page number not for citation purposes)
Chen & SchulzJOURNAL OF MEDICAL INTERNET RESEARCH
XSL
•
FO
RenderX
6. Hawthorne G. Perceived social isolation in a community sample: its prevalence and correlates with aspects of peoples'
lives. Soc Psychiatry Psychiatr Epidemiol 2008 Feb;43(2):140-150. [doi: 10.1007/s00127-007-0279-8] [Medline: 17994175]
7. Saito M, Fujiwara Y, Kobayashi E, Fukaya T, Nishi M, Shinkai S. [Prevalence and characteristics of social isolation in the
elderly in a dormitory suburb according to household composition]. Nihon Koshu Eisei Zasshi 2010 Sep;57(9):785-795.
[Medline: 21061557]
8. Cornwell EY, Waite LJ. Social disconnectedness, perceived isolation, and health among older adults. J Health Soc Behav
2009 Mar;50(1):31-48 [FREE Full text] [Medline: 19413133]
9. Mulvaney-Day NE, Alegría M, Sribney W. Social cohesion, social support, and health among Latinos in the United States.
Soc Sci Med 2007 Jan;64(2):477-495 [FREE Full text] [doi: 10.1016/j.socscimed.2006.08.030] [Medline: 17049701]
10. Fiori KL, Smith J, Antonucci TC. Social network types among older adults: a multidimensional approach. J Gerontol B
Psychol Sci Soc Sci 2007 Nov;62(6):P322-P330. [Medline: 18079416]
11. Kharicha K, Iliffe S, Harari D, Swift C, Gillmann G, Stuck AE. Health risk appraisal in older people 1: are older people
living alone an “at-risk” group? Br J Gen Pract 2007 Apr;57(537):271-276 [FREE Full text] [Medline: 17394729]
12. Dorfman RA, Lubben JE, Mayer-Oakes A, Atchison K, Schweitzer SO, De Jong FJ, et al. Screening for depression among
a well elderly population. Soc Work 1995 May;40(3):295-304. [Medline: 7761915]
13. Hanson BS. Social network, social support and heavy drinking in elderly men--a population study of men born in 1914,
Malmö, Sweden. Addiction 1994 Jun;89(6):725-732. [Medline: 8069173]
14. Eng PM, Rimm EB, Fitzmaurice G, Kawachi I. Social ties and change in social ties in relation to subsequent total and
cause-specific mortality and coronary heart disease incidence in men. Am J Epidemiol 2002 Apr 15;155(8):700-709 [FREE
Full text] [Medline: 11943687]
15. Berkman LF, Glass T, Brissette I, Seeman TE. From social integration to health: Durkheim in the new millennium. Soc
Sci Med 2000 Sep;51(6):843-857. [Medline: 10972429]
16. Locher JL, Ritchie CS, Roth DL, Baker PS, Bodner EV, Allman RM. Social isolation, support, and capital and nutritional
risk in an older sample: ethnic and gender differences. Soc Sci Med 2005 Feb;60(4):747-761 [FREE Full text] [doi:
10.1016/j.socscimed.2004.06.023] [Medline: 15571893]
17. Havens B, Hall M. Social isolation, loneliness, and the health of older adults in Manitoba, Canada. Indian J Gerontol
2001;1(15):126-144.
18. Boden-Albala B, Litwak E, Elkind MSV, Rundek T, Sacco RL. Social isolation and outcomes post stroke. Neurology 2005
Jun 14;64(11):1888-1892. [doi: 10.1212/01.WNL.0000163510.79351.AF] [Medline: 15955939]
19. Sum S, Mathews MR, Pourghasem M, Hughes I. Internet technology and social capital: How the Internet affects seniors'
social capital and wellbing. J Comput Mediat Commun 2008;14(1):202-220. [doi: 10.1111/j.1083-6101.2008.01437.x]
20. Dickens AP, Richards SH, Greaves CJ, Campbell JL. Interventions targeting social isolation in older people: a systematic
review. BMC Public Health 2011;11:647 [FREE Full text] [doi: 10.1186/1471-2458-11-647] [Medline: 21843337]
21. Cattan M, White M, Bond J, Learmouth A. Preventing social isolation and loneliness among older people: a systematic
review of health promotion interventions. Ageing and Society 1999;25(1):41-67. [doi: 10.1017/S0144686X04002594]
22. Nicholson NR. Social isolation in older adults: an evolutionary concept analysis. J Adv Nurs 2009 Jun;65(6):1342-1352.
[doi: 10.1111/j.1365-2648.2008.04959.x] [Medline: 19291185]
23. Wenger GC, Burholt V. Changes in levels of social isolation and loneliness among older people in a rural area: a twenty-year
longitudinal study. Can J Aging 2004;23(2):115-127. [Medline: 15334812]
24. Findley RA. Interventions to reduce social isolation amongst older people: where is the evidence? Ageing and Society
2003;23(5):647-658. [doi: 10.1017/S0144686X03001296]
25. Morris ME, Adair B, Ozanne E, Kurowski W, Miller KJ, Pearce AJ, et al. Smart technologies to enhance social connectedness
in older people who live at home. Australas J Ageing 2014 Sep;33(3):142-152. [doi: 10.1111/ajag.12154] [Medline:
24730370]
26. Quality Assessment Tool for Quantitative Studies: Effective Public Health Practice Project. 2009. URL: http://www.
ephpp.ca/PDF/Quality%20Assessment%20Tool_2010_2.pdf [accessed 2015-05-01] [WebCite Cache ID 6YCW3AIuz]
27. Salmon P. Assessing the quality of qualitative research. Patient Educ Couns 2013 Jan;90(1):1-3. [doi:
10.1016/j.pec.2012.11.018] [Medline: 23237574]
28. Lipsey MW, Wilson DB. Practical meta-analysis. Thousand Oaks, Calif: Sage; 2001.
29. Clark DJ. Older adults living through and with their computers. Comput Inform Nurs 2002;20(3):117-124. [Medline:
12021610]
30. Fokkema T, Knipscheer K. Escape loneliness by going digital: a quantitative and qualitative evaluation of a Dutch experiment
in using ECT to overcome loneliness among older adults. Aging Ment Health 2007 Sep;11(5):496-504. [doi:
10.1080/13607860701366129] [Medline: 17882587]
31. Mellor D, Firth L, Moore K. Can the Internet improve the well-being of the elderly? Ageing Int 2008 Feb 9;32(1):25-42.
[doi: 10.1007/s12126-008-9006-3]
32. Nahm ES, Resnick B, Mills ME. A model of computer-mediated social support among older adults. AMIA Annu Symp
Proc 2003:948 [FREE Full text] [Medline: 14728453]
J Med Internet Res 2016 | vol. 18 | iss. 1 | e18 | p.9http://www.jmir.org/2016/1/e18/ (page number not for citation purposes)
Chen & SchulzJOURNAL OF MEDICAL INTERNET RESEARCH
XSL
•
FO
RenderX
33. Richardson M, Weaver CK, Zorn Jr TE. 'Getting on': older New Zealanders' perceptions of computing. New Media &
Society 2005 Apr 01;7(2):219-245. [doi: 10.1177/1461444805050763]
34. Savolainen L, Hanson E, Magnusson L, Gustavsson T. An Internet-based videoconferencing system for supporting frail
elderly people and their carers. J Telemed Telecare 2008;14(2):79-82. [doi: 10.1258/jtt.2007.070601] [Medline: 18348753]
35. Shapira N, Barak A, Gal I. Promoting older adults' well-being through Internet training and use. Aging Ment Health 2007
Sep;11(5):477-484. [doi: 10.1080/13607860601086546] [Medline: 17882585]
36. Slegers K, van Boxtel MPJ, Jolles J. Effects of computer training and Internet usage on the well-being and quality of life
of older adults: a randomized, controlled study. J Gerontol B Psychol Sci Soc Sci 2008 May;63(3):P176-P184. [Medline:
18559683]
37. Sum S, Mathews RM, Hughes I, Campbell A. Internet use and loneliness in older adults. Cyberpsychol Behav 2008
Apr;11(2):208-211. [doi: 10.1089/cpb.2007.0010] [Medline: 18422415]
38. Torp S, Hanson E, Hauge S, Ulstein I, Magnusson L. A pilot study of how information and communication technology
may contribute to health promotion among elderly spousal carers in Norway. Health Soc Care Community 2008
Jan;16(1):75-85. [doi: 10.1111/j.1365-2524.2007.00725.x] [Medline: 18181817]
39. White H, McConnell E, Clipp E, Branch LG, Sloane R, Pieper C, et al. A randomized controlled trial of the psychosocial
impact of providing internet training and access to older adults. Aging Ment Health 2002 Aug;6(3):213-221. [doi:
10.1080/13607860220142422] [Medline: 12217089]
40. Aarts S, Peek STM, Wouters EJM. The relation between social network site usage and loneliness and mental health in
community-dwelling older adults. Int J Geriatr Psychiatry 2015 Sep;30(9):942-949. [doi: 10.1002/gps.4241] [Medline:
25503540]
41. Blažun H, Saranto K, Rissanen S. Impact of computer training courses on reduction of loneliness of older people in Finland
and Slovenia. Computers Hum Behav 2012 Jul;28(4):1202-1212. [doi: 10.1016/j.chb.2012.02.004]
42. Cattan M, Kime N, Bagnall A. The use of telephone befriending in low level support for socially isolated older people--an
evaluation. Health Soc Care Community 2011 Mar;19(2):198-206. [doi: 10.1111/j.1365-2524.2010.00967.x] [Medline:
21114564]
43. Cotten SR, Anderson WA, McCullough BM. Impact of internet use on loneliness and contact with others among older
adults: cross-sectional analysis. J Med Internet Res 2013;15(2):e39 [FREE Full text] [doi: 10.2196/jmir.2306] [Medline:
23448864]
44. Delello JA, McWhorter RR. Reducing the digital divide: Connecting older adults to iPad technology. J Appl Gerontol 2015
Jun 17:1-26. [doi: 10.1177/0733464815589985] [Medline: 26084479]
45. Dhillon JS, Ramos CR, Wunsche BC, Lutteroth C. Designing a Web-based telehealth system for elderly people: An interview
study in New Zealand. In: Proceedings of the 24th International Symposium on Computer-Based Medical Systems -- CBMS
2011 Bristol.: IEEE; 2011 Jun Presented at: the 24th International Symposium on Computer-Based Medical Systems; 27-30
June 2011; Bristol p. 1-6 URL: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5999157 [WebCite Cache] [doi:
10.1109/CBMS.2011.5999157]
46. Heo J, Chun S, Lee S, Lee KH, Kim J. Internet use and well-being in older adults. Cyberpsychol Behav Soc Netw 2015
May;18(5):268-272. [doi: 10.1089/cyber.2014.0549] [Medline: 25919967]
47. Kahlbaugh PE, Sperandio AJ, Carlson AL, Hauselt J. Effects of playing Wii on well-being in the elderly: Physical activity,
loneliness, and mood. Activities, Adaptation & Aging 2011 Oct;35(4):331-344. [doi: 10.1080/01924788.2011.625218]
48. Karimi A, Neustaedter C. From high connectivity to social isolation: communication practices of older adults in the digital
age. : Association for Computing Machinery; 2012 Presented at: Computer Supported Cooperative Work; February 11-15,
2012; Seattle WA.
49. Khvorostianov N, Elias N, Nimrod G. 'Without it I am nothing': The internet in the lives of older immigrants. New Media
& Society 2011 Nov 11;14(4):583-599. [doi: 10.1177/1461444811421599]
50. Machesney D, Wexler SS, Chen T, Coppola JF. Gerontechnology Companion: Virutal pets for dementia patients. : IEEE;
2014 Presented at: Systems, Applications and Technology Conference (LISAT), 2014 IEEE Long Island; 2-2 May 2014;
New York p. 1-3. [doi: 10.1109/LISAT.2014.6845226]
51. Tsai HH, Tsai YF, Wang HH, Chang YC, Chu HH. Videoconference program enhances social support, loneliness, and
depressive status of elderly nursing home residents. Aging Ment Health 2010 Nov;14(8):947-954. [doi:
10.1080/13607863.2010.501057] [Medline: 21069600]
52. Tsai HH, Tsai YF. Changes in depressive symptoms, social support, and loneliness over 1 year after a minimum 3-month
videoconference program for older nursing home residents. J Med Internet Res 2011;13(4):e93 [FREE Full text] [doi:
10.2196/jmir.1678] [Medline: 22086660]
53. Winstead V, Anderson WA, Yost EA, Cotten SR, Warr A, Berkowsky RW. You can teach an old dog new tricks: a qualitative
analysis of how residents of senior living communities may use the web to overcome spatial and social barriers. J Appl
Gerontol 2013 Aug;32(5):540-560. [doi: 10.1177/0733464811431824] [Medline: 25474761]
54. Helsper EJ, Eynon R. Distinct skill pathways to digital engagement. European Journal of Communication 2013 Sep
16;28(6):696-713. [doi: 10.1177/0267323113499113]
J Med Internet Res 2016 | vol. 18 | iss. 1 | e18 | p.10http://www.jmir.org/2016/1/e18/ (page number not for citation purposes)
Chen & SchulzJOURNAL OF MEDICAL INTERNET RESEARCH
XSL
•
FO
RenderX
55. de Jong-Gierveld J, Kamphuls F. The development of a Rasch-type loneliness scale. Applied Psychological Measurement
1985 Sep 01;9(3):289-299. [doi: 10.1177/014662168500900307]
56. de Jong-Gierveld J, van Tilburg T. A 6-item scale for overall, emotional, and social loneliness confirmatory tests on survey
data. Res Aging 2006;28(5):582-598.
57. Schuster TL, Kessler RC, Aseltine RH. Supportive interactions, negative interactions, and depressed mood. Am J Community
Psychol 1990 Jun;18(3):423-438. [Medline: 2264558]
58. Russell D, Peplau LA, Cutrona CE. The revised UCLA Loneliness Scale: concurrent and discriminant validity evidence.
J Pers Soc Psychol 1980 Sep;39(3):472-480. [Medline: 7431205]
59. Andersson L. Intervention against loneliness in a group of elderly women: A process evaluation. Human Relations 1984
Apr 01;37(4):295-310. [doi: 10.1177/001872678403700402]
60. Lubben J, Blozik E, Gillmann G, Iliffe S, von Renteln Kruse W, Beck JC, et al. Performance of an abbreviated version of
the Lubben Social Network Scale among three European community-dwelling older adult populations. Gerontologist 2006
Aug;46(4):503-513. [Medline: 16921004]
61. Sansoni J, Marosszeky N, Sansoni E, Fleming G. Final report: Effective assessment of social isolation.: Centre for Health
Service Development, University of Wollongong; 2010 Jan 1. URL: http://www.adhc.nsw.gov.au/__data/assets/file/0007/
236329/24_Social_Isolation_Report.pdf [accessed 2015-05-01] [WebCite Cache ID 6YCWVY6DJ]
62. Lubben JE, Gironda M. Centrality of social ties to the health and well-being of older adults. In: Berkman B, Harooytoan
LK, editors. Social Work and Health Care in an Aging World. New York: Springer; 2003:319-350.
63. Lubben J, Gironda M. Measuring social networks and assessing their benefits. In: Phillipson C, Allan G, Morgan D, editors.
Social Networks and Social Exclusion: Sociological and Policy Perspectives. Burlington, VT: Ashgate Publishing Company;
2004:20-34.
64. Lubben J, Blozik E, Gillmann G, Iliffe S, von Renteln Kruse W, Beck JC, et al. Performance of an abbreviated version of
the Lubben Social Network Scale among three European community-dwelling older adult populations. Gerontologist 2006
Aug;46(4):503-513. [Medline: 16921004]
65. Sherbourne CD, Stewart AL. The MOS social support survey. Soc Sci Med 1991;32(6):705-714. [Medline: 2035047]
66. Zimet GD, Powell SS, Farley GK, Werkman S, Berkoff KA. Psychometric characteristics of the Multidimensional Scale
of Perceived Social Support. J Pers Assess 1990;55(3-4):610-617. [doi: 10.1080/00223891.1990.9674095] [Medline:
2280326]
67. Harley D, Fitzpatrick G. YouTube and intergenerational communication: the case of Geriatric1927. Univ Access Inf Soc
2008 May 29;8(1):5-20. [doi: 10.1007/s10209-008-0127-y]
68. Nielsen J. Seniors as Web users.: Nielsen Norman Group; 2013. URL: http://www.nngroup.com/articles/
usability-for-senior-citizens/ [accessed 2015-05-01] [WebCite Cache ID 6YCW89Kk4]
Abbreviations
EPHPP: Effective Public Health Practice Project
ICT: information and communication technology
RCT: randomized controlled trial
Edited by G Eysenbach; submitted 01.05.15; peer-reviewed by N Diviani, J Clemensen; comments to author 09.07.15; revised version
received 03.09.15; accepted 07.10.15; published 28.01.16
Please cite as:
Chen YRR, Schulz PJ
The Effect of Information Communication Technology Interventions on Reducing Social Isolation in the Elderly: A Systematic Review
J Med Internet Res 2016;18(1):e18
URL: http://www.jmir.org/2016/1/e18/
doi:10.2196/jmir.4596
PMID:26822073
©Yi-Ru Regina Chen, Peter J Schulz. Originally published in the Journal of Medical Internet Research (http://www.jmir.org),
28.01.2016. 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 the Journal of Medical Internet Research, is properly cited. The complete bibliographic
information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be
included.
J Med Internet Res 2016 | vol. 18 | iss. 1 | e18 | p.11http://www.jmir.org/2016/1/e18/ (page number not for citation purposes)
Chen & SchulzJOURNAL OF MEDICAL INTERNET RESEARCH
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