741369

research-article2017
JAGXXX10.1177/0733464817741369Journal of Applied GerontologyNeves et al.

Article
Journal of Applied Gerontology
2019, Vol. 38(1) 49­–72
Can Digital Technology © The Author(s) 2017
Article reuse guidelines:
Enhance Social sagepub.com/journals-permissions
DOI: 10.1177/0733464817741369
https://doi.org/10.1177/0733464817741369
Connectedness Among journals.sagepub.com/home/jag

Older Adults? A
Feasibility Study

Barbara Barbosa Neves1, Rachel Franz2,

Rebecca Judges3, Christian Beermann3,
and Ron Baecker3

Abstract
This study examined the feasibility of a novel communication technology to
enhance social connectedness among older adults in residential care. Research
suggests that technology can create opportunities for social connectedness,
helping alleviate social isolation and loneliness. Studies on implementation
and feasibility of such technological interventions, particularly among frail
and institutionalized older adults, are scant. Data were gathered in a 3-month
deployment with 12 older adults, including semistructured interviews with
participants and relatives/friends, psychometric scales, field observations,
and usability tests. Data were analyzed with qualitative profiling, thematic
analysis, and Friedman tests. The technology was a feasible communication
tool, although requiring an adaptation period. Use increased perceived social
interaction with ties, but increased social connectedness (meaningful social

Manuscript received: July 8, 2017; final revision received: October 2, 2017; accepted:
October 15, 2017.
1University of Melbourne, Victoria, Australia
2University of Washington, USA
3University of Toronto, Ontario, Canada

Corresponding Author:
Barbara Barbosa Neves, School of Social and Political Sciences, University of Melbourne,
Parkville, Melbourne, Victoria 3010, Australia.
Email: barbara.barbosa@unimelb.edu.au
50 Journal of Applied Gerontology 38(1)

interaction) was only reported by participants with geographically distant

relatives. Sense of well-being and confidence with technology was enhanced,
but negative effects were also observed. Findings are useful for researchers
and practitioners interested in technological interventions.

Keywords
digital technology, social connectedness, technology acceptability, social
isolation, loneliness

Introduction
Research shows that frail older adults living in retirement homes are particu-
larly vulnerable to social isolation and loneliness (Keefe, Andrew, Fancey, &
Hallet, 2006; Prieto-Flores et al., 2011; Victor, Scambler, & Bond, 2009). This
vulnerability seems connected to decreased social networks, mobility, health
status, and interaction with close ties (Keefe et al., 2006; Prieto-Flores et al.,
2011; Victor et al., 2009). The literature indicates that 10% to 43% of older
adults in North America experience social isolation, and 43% experience lone-
liness (Nicholson, 2012; Perissinotto, Stijacic Cenzer, & Covinsky, 2012).
Social isolation and loneliness are interrelated yet different concepts. Social
isolation refers to low/nonexistent levels of social support and participation and
decreased quality/quantity of social ties (Cornwell & Waite, 2009), whereas
loneliness refers to perceived feelings of lacking companionship and abandon-
ment (Perissinotto et al., 2012). Older adults’ experiences of social isolation
and loneliness negatively affect their health and well-being (Cornwell & Waite,
2009; Perissinotto et al., 2012; Steptoe, Shankar, Demakakos, & Wardle, 2013).
Studies suggest that digital communication technologies, such as the
Internet, can contribute to social connectedness—that is, meaningful social
interaction—and help address both loneliness and social isolation in later life
(Findlay, 2003; Khosravi, Rezvani, & Wiewiora, 2016; Masi, Chen, Hawkley,
& Cacioppo, 2011). Social connectedness, which relates to quality rather than
quantity of social interaction, seems to tackle feelings of loneliness and factors
that contribute to social isolation (i.e., social support, frequency of interaction
with close ties, etc.). Theoretically, social connectedness draws from social
capital, wherein resources embedded in social ties (e.g., emotional or financial
support) can be mobilized when necessary, showing that quality relationships
matter for well-being and socioeconomic standing (Neves, 2013; Wong &
Waite, 2016). Specifically, the role of social connectedness is explained by
main effects and stress-buffering effects models: the first proposes that social
connections influence positively health and well-being among older adults,
Neves et al. 51

the second that social connections protect from stressors and their health con-
sequences (Wong & Waite, 2016). Research has shown that, as with social
capital, these two models are more nuanced as connections matter depending
on their quality and type (Litwin & Shiovitz-Ezra, 2011).
The Internet shows potential for social connectedness due to its social
affordances, that is, the convenience, connectivity, and social cues that create
opportunities for diverse interaction (Wellman et al., 2003). These affor-
dances offer synchronous and asynchronous communication opportunities
with different ties—from family to communities of interest or practice—and
the ability to manage interactions simultaneously (Delello & McWhorter,
2017; Wellman et al., 2003). Using the Internet can reduce feelings of loneli-
ness among older adults (Choi, Kong, & Jung, 2012; Cotten, Anderson, &
McCullough, 2012; Morris, Adair, Ozanne, & Said, 2014), but there is less
conclusive evidence on social isolation (Cotten et al., 2012). This may relate
to not using the Internet for communicating with family and friends; Sum,
Mathews, Hughes, and Campbell (2008) reported that older adults felt less
social connectedness after using the Internet to talk to strangers. Older adults
seem to prefer maintaining current networks rather than building new ones,
which might further add to issues of social isolation in old age (Neves, Franz,
Munteanu, & Baecker, 2017; Hope, Schwaba, & Piper, 2014). In fact, increas-
ing social connection with close ties, particularly with family members, is a
main motivation for Internet use in later life (Cotten et al., 2012; Delello &
McWhorter, 2017; Sayago, Sloan, & Blat, 2011; Tsai, Shillair, & Cotten,
2015; White et al., 2002). A functional approach to technology—exploring
different types of use instead of general use—can help interpret the influence
of the Internet and other digital technologies on social connectedness
(Lifshitz, Nimrod, & Bachner, 2016).
Although various technological interventions (from social networking
sites to robotics) have recently emerged to tackle social isolation, loneliness,
and social connectedness needs, literature emphasizes the importance of
accessible and targeted communication systems (Brown et al., 2017; Khosravi
et al., 2016). Compared with other senior groups, frail older adults living in
retirement homes have also received limited attention in the deployment and
study of such technological interventions (Baecker, Sellen, Crosskey, Boscart,
& Neves, 2014; Neves, Franz, Munteanu, Ngo, & Baecker, 2015). This is a
group at risk of social isolation and loneliness that tends to struggle with
standard digital technologies due to impairments, low digital literacy, or
social settings (Lee & Coughlin, 2015). Furthermore, studies on the long-
term implementation and feasibility of accessible digital interventions con-
tinue to be scant because of access, recruitment, and ethical challenges with
this population (Neves et al., 2017; Hall, Longhurst, & Higginson, 2009). To
52 Journal of Applied Gerontology 38(1)

address this gap, we conducted a 3-month feasibility study of an accessible

communication app (tablet application) to enhance social connectedness
among frail older adults in a retirement home in North America. The design
of this feasibility study draws on a feasibility pilot that we have conducted
with five frail “oldest old” (aged 80+) in a long-term care facility (Neves
et al., 2015; Neves et al., 2017). We employed a mixed-methods and concep-
tual approach focused on both psychosocial and contextual elements of adop-
tion and outcomes of technology, an in-depth perspective missing in the
literature (Khosravi et al., 2016). Using this perspective, this article discusses
the app’s feasibility, considering its acceptability (adoption and uses) and
efficacy (outcomes).

Current Study: A Recursive Approach to

Technology
We developed an accessible iPad-based communication app that supports older
adults’ asynchronous communication with family and friends. In addition to the
literature emphasis on accessible and tailored communication technology to
increase social connectedness (Khosravi et al., 2016), our participatory design
approach, which included older adults in the process as codesigners, identified
a tablet-based app as the most valuable tool (Baecker et al., 2014). Tablets have
been shown to be useful as communication, inclusion, and well-being interven-
tions (Delello & McWhorter, 2017; Tsai et al., 2015; Tyack, Camic, Heron, &
Hulbert, 2017). Prototyping considered the social affordances perspective
(Wellman et al., 2003), respecting the social features/actions defined by our
codesigners. The app allowed users to send and receive photos, audio, video,
and text messages (sent messages were predefined to increase simplicity; see
Figure 1), whereas their contacts could respond using their own emails and
devices. The interface offered large nontextual touch icons (no typing, only
swiping/tapping) to accommodate users with visual and motor impairments, as
informed by our field studies (Neves et al., 2017).
Once the app was ready to deploy, we asked,

Is this a feasible app to enhance perceived social connectedness among frail

older adults living in a retirement home?

To answer this question, we deployed the technology in a Canadian retire-

ment home that offers different levels of care. To assess feasibility, we stud-
ied adoption and use through a recursive approach to technology that
examined the app as used “in the wild,” considering the interplay of users,
technologies, and contexts (Greenhalgh & Stones, 2010). Existing adoption
Neves et al. 53

Figure 1.  The message interface of our app with four options: wave (predefined),
audio, picture, and video message (right to left).

models, such as the widely employed Technology Acceptance Model and

extensions (Davis, 1989; Giger et al., 2015), tend to neglect the interaction of
psychosocial and contextual factors. In addition, the literature lacks mixed-
methods approaches that explore the lived experience of adoption and out-
comes of new communication technology among older adults (Quan-Haase,
Martin, & Schreurs, 2016).

Method
Design
A feasibility study was used because we were testing an unexamined inter-
vention with a population for whom we lack in-depth knowledge, and priori-
tizing real-life settings and constraints over optimal conditions (Bowen,
Kreuter, & Fernandez, 2009; Green & Glasgow, 2006). The study considered
two feasibility components: acceptability and efficacy (Bowen et al., 2009).
Acceptability refers to the adoption of and reactions to the app, whereas effi-
cacy concerns the app’s perceived outcomes for social connectedness. To
54 Journal of Applied Gerontology 38(1)

assess these components, we conducted a 3-month mixed-methods app

deployment in 2015. Participants received an iPad restricted to our app
(“Guided Access Mode”), which they kept after the study. Our University
Ethics Committee approved this study (Ref. 31111) and participants signed
an informed consent form.

Participants
With staff assistance, we recruited a convenience sample of residents at a
Canadian retirement home. Residents were invited to participate after attend-
ing information sessions about the study. Staff also invited residents who
seemed at risk of social isolation and loneliness. As we did not have access to
residents’ medical records, we relied on staff to exclude individuals with
dementia or conditions rendering them unable to provide consent. Of 21
interested residents, we enrolled 13 participants including a married couple
who shared one tablet and were counted as a single user. Health deterioration
was the main reason for reducing the original participant pool. One partici-
pant withdrew in the first month due to lack of interest. Research suggests
that a sample of 12 participants is reasonable, given our research objectives,
design, study group, and intervention (Billingham, Whitehead, & Julious,
2013; Bowen et al., 2009; Guest, Bunce, & Johnson, 2006).
Staff considered our participants frail due to biomedical and psychosocial
factors (Fried, Tangen, Walston, & McBurnie, 2001; Lally & Crome, 2007).
Ten participants showed weakness (grip strength), slow walking speed, low
physical activity, and self-reported exhaustion, and two evinced low physical
activity and slowness. Depression and low resilience were also assessed as
psychosocial factors (Freitag & Schmidt, 2016). Recruitment of frail and
institutionalized older adults is challenging, mostly because of declining
health, life expectancy compression, and corresponding ethical issues (Hall
et al., 2009). These factors restricted our longitudinal design to 3 months.
Nevertheless, the 3-month deployment and purposive sample were appropri-
ate for our in-depth approach.
Our four male and eight female participants ranged from 74 to 95 years of
age, with an average age of 82.5 (see Table 1). All spoke English. The sample
included Canadians, British Canadians, American Canadians, Italian
Canadians, Japanese Canadians, and Latin American Canadians. Our prior
study (feasibility pilot) was conducted with five Chinese Canadians (Neves
et al., 2015; Neves et al., 2017); thus for this feasibility study, we aimed to
include more diverse ethnic backgrounds. The husband–wife duo completed
interviews together, but the husband mostly answered questions as the wife
reported not using the tool independently.
 Table 1.  Participant Sociodemographic Characteristics.
Marital Health limitations (visible or
Pseudonym Gender Age status Previous occupation Children reported)

Gaby F 84 Widow Homemaker Two daughters, one son Mild vision problems, needed a
cane, speech disorder, rheumatoid
arthritis
Diana F 85 Widow Early childhood Two daughters, two sons Mild vision and auditory problems
educator
Jen F 80 Single Librarian 0 Mild vision problems, used a walker,
intense rheumatoid arthritis
James M 86 Married Minister and University One daughter, one son Mild vision problems
Instructor
Kevin M 95 Widow Medical doctor Four daughters Vision problems (blind in one eye,
wears glasses), memory problems
Ike M 74 Married Engineer One son, one stepson, Vision problems, Parkinson’s (motor
one stepdaughter problems including shaking)
Paul and M and F 80&77 Married Accountant and Two stepsons, one Mild vision problems, mobility
Martha Mathematics teacher stepdaughter; two sons, problems
one daughter
Pam F 86 Widow Homemaker One son, one daughter Vision and reading problems
Bree F 79 Single Teacher 0 Stroke-related health issues, memory
problems, aphasia
Jane F 87 Widow Nurse Two sons, two daughters Macular degeneration, auditory
problems (hearing aids in both ears)
Lily F 83 Widow Teacher 0 Mild vision and auditory problems
(hearing aid)

55
56 Journal of Applied Gerontology 38(1)

Participants joined the study with a family member or friend (study part-
ner), who agreed to support their use of the app and complete a pre- and
postdeployment interview. As we were testing a communication tool, we
needed at least one tie involved in the process; participants were free to select
whomever they would like to have as a study partner. As expected (consistent
with the literature on older adults and social networks), most participants
selected strong ties, namely, family and close friends. Three participants’
daughters and two sons joined (all in their 40s). Four friends or acquaintances
(most more than 60, one in her 40s) also joined. One participant invited her
sister (in her 70s), and another, her granddaughter (in her 20s).
At the start of the study, five participants reported communicating regu-
larly with three or less ties (family and friends), five participants with four to
six, and the remaining two with seven or more. Participants added between 4
and 10 contacts to the app, mostly relatives (M = 8.6, Median = 9, Mode = 9
and 10). At the onset, it may seem that participants were embedded in par-
ticularly strong networks due to the number of ties and frequency of com-
munication (cf. McPherson, Smith-Lovin, & Brashears, 2006). However, not
all ties would be characterized as confidants (e.g., people to discuss impor-
tant matters with) and communication was often “lightweight”, which means
it included quick follow-ups and nonmeaningful/routinized conversations
(Lindley, Harper, & Sellen, 2009). In addition, as noted by staff and con-
firmed throughout the 3-month deployment, there was considerable “social
desirability” when reporting family involvement as well as an effort by older
participants to avoid being seen as a “burden” to their relatives and friends.
Nevertheless, none of our participants displayed substantial levels of loneli-
ness or social isolation. Some were not socially isolated, but at risk of loneli-
ness; others were vulnerable to both social isolation and loneliness because of
increasing frailty and loss of meaningful communication with ties; others
wanted to enhance their connectedness with relatives, especially grandchil-
dren, family, and friends living close and afar.
Participants’ skills and knowledge of using digital devices (digital literacy
levels) varied. Using a simple categorization of digital literacy at predeploy-
ment, four had never used a digital device (no digital literacy); three had used
a computer previously, but had a basic operational understanding (low level);
and five had used computers, email, and/or smartphones, but struggled with
some functions (medium level).

Procedure
The deployment study had a pre-, mid-, and poststage (see Table 2).
Predeployment included an individual training session and the administration
of a social support and loneliness scale with participants, and semistructured
Neves et al. 57

Table 2.  Data Collection at Pre-, Mid-, and Post-Deployment.

Data collection Pre Mid Post

Semi-structured interviews with participants   
Semi-structured interviews with study partners  
Duke Social Support Scale:   
I.  Social interaction
1. Number of family members within 1 hr that you can
depend on or feel close to.
2. Number of times past week spent with someone
not living with you.
3. Number of times in past week talked with friends/
relatives on the telephone.
4. Number of times in the past week attended
meetings of clubs, religious groups, or other groups
that you belong to (other than work).
II.  Social satisfaction
1. Does it seem that your family and friends
understand you?*
2.  Do you feel useful to your family and friends?*
3. Can you talk about your deepest problems with at
least some of your family and friends?*
4. Do you know what is going on with your family and
friends?*
5. When you are talking with your family and friends,
do you feel you are being listened?*
6. How satisfied are you with the kinds of relationships
you have with your family and friends—very
dissatisfied, somewhat dissatisfied, or satisfied?
*Most of the time, some of the time, or hardly ever
UCLA Loneliness Scale:   
1. How often do you feel that you lack
companionship?*
2.  How often do you feel left out?*
3.  How often do you feel isolated from others?*
*Hardly ever, some of the time, often
Usability and accessibility tests 
Field observations   

interviews with participants and their study partners. The training sessions
showed participants how to use the tablet and app, having them send and
receive different message-types. Authors then administered the scales. After
the training sessions, participants received a printed manual and a tablet with
58 Journal of Applied Gerontology 38(1)

our app to use as they chose for 3 months. Six weeks after the training, in
mid-deployment, we readministered the scales and conducted semistructured
interviews with participants. During postdeployment, we repeated the scales,
conducted semistructured interviews with participants and relatives, and car-
ried out usability and accessibility tests. The study partner attended the train-
ing session and was interviewed pre- and postdeployment. Our prior study
showed the need to interview study partners at predeployment, not just at
postdeployment, and to interview participants at mid-deployment, not just at
pre- and postdeployment (Neves et al., 2015; Neves et al., 2017). Participants
were alone with researchers during scale administration, and interviews with
participants and study partners were conducted separately. Throughout the
deployment, we visited participants weekly to collect field observations and
answer questions. The authors conducted interviews and usability and acces-
sibility tests. The first and fourth author conducted a total of 230 hr of
unstructured participant observation. Interviews were audio-recorded and
usability and accessibility tests were video-recorded to see how participants
interacted with the device.
The scales used were the Abbreviated Duke Social Support Index, com-
prising the social interaction and satisfaction subscales (Wardian, Robbins,
Wolfersteig, Johnson, & Dustman, 2012) and the Short Revised UCLA
Loneliness Scale (Hughes, Waite, Hawkley, & Cacioppo, 2004). The initial
semi-structured interview included questions about social networks, fre-
quency of contact with those networks, social participation, and experience
with digital technology. The mid- and postdeployment interviews asked
about app experience, use/nonuse, media, and communication with social
ties. The usability and accessibility tests were based on tasks to perform with
the app (e.g., participants were asked to send different types of messages) and
open and rating questions regarding the app’s interface and functionality.
Interviews lasted around 40 min. Field observations were a mix of participant
and nonparticipant unstructured formats, allowing note-taking when relevant
(Pretzlik, 1994). Field notes documented the way participants used the app
and interactions between participants, relatives, staff, and researchers. This
information deepened our understanding of participant contexts and app
adoption and captured the involvement of researchers, contributing to reflex-
ivity regarding our position in the field (Patton, 1990).

Analysis
We analyzed fully transcribed interviews and tests with qualitative profiling
and thematic analysis. Field notes were used for qualitative profiling and to
complement interviews. The qualitative profiling crafted profiles and
Neves et al. 59

contextualized participants (Seidman, 2006). Thematic analysis was

employed to uncover themes within (individual) and across (collective)
cases: These were identified from the data but we also looked for a priori
categories, namely, technology-related codes (King & Horrocks, 2010). The
first three authors coded independently, then together to test for convergence.
A fourth researcher determined basic interrater reliability (Patton, 1990) of
half of the data by manually counting discrepancies in assignment of codes
and themes, reaching 97% for pre-, 93% for mid-, and 95% for postdeploy-
ment interviews. These procedures, multiple sources of data, and peer com-
parisons and checks aimed to enhance trustworthiness of the analysis (Patton,
1990). To examine differences over time, the scales were analyzed descrip-
tively and with Friedman and Sign tests (nonparametric techniques suiting
our sampling). Health practitioners use these scales to assess individual
patients and gather baseline information. We adopted a similarly liberal crite-
rion, as advanced statistical analysis was unfeasible due to the sample size.

Results
Acceptability of the App
Analysis of the interviews, tests, and observations showed that the accept-
ability of the tool was captured through different phases of app adoption and
use.

Adoption.  Of the 12 participants, one did not adopt the app—that is, her use
of the app stopped before postdeployment. Martha, participating with her
husband (duo), used the app in the first weeks, but stopped after mid-deploy-
ment. She explained her nonadoption by stating “I don’t need to get in touch
with them [family], because I’m the mother they call me.” During the mid-
deployment interview, she mentioned “using it very little now” as “I knit.”
Our field notes indicated that the husband presented himself as the user since
predeployment, whereas Martha took a more passive role. This interpersonal
dynamic could have affected her uptake of the tool. Although we offered
Martha a tablet to use independently, she declined.

Patterns of use.  At mid-deployment, four participants reported daily use, five

weekly use (at least once a week), and two occasional use (once every 2
weeks). However, at postdeployment, nine reported weekly use and two
occasional use. Two participants’ use slightly increased from mid- to postde-
ployment, from once to twice per week. These self-reports were consistent
with our notes and loggings. Messages were mainly sent to family members,
60 Journal of Applied Gerontology 38(1)

particularly children and grandchildren. Audio was the most used function,
followed by picture messages, then video. For some, the audio option was
easier to use than mobile phones, which are often “too small” and “hard to
operate.” Gaby, a participant, stated that there was “No comparison with any-
thing else, like a phone . . . I can’t use phones because buttons are too little
and I have arthritis in my fingers.” For others, picture and video messages
were preferred:

The other day at a birthday party, I was able to take lots of pictures and send it
immediately, and then take one for myself, and I did quite a bit of that over the
weekend [with the app]. A friend phoned the other day and she said, uh, you
know: “How big is the place you’re living in now?” And so I said, “Well, I’ll
send you a video.” (James)

The least-used option was the “wave” (predefined messages). Diana, who
had used a computer before, mentioned at mid-deployment “those messages
[waves] are really too basic for me.” Nevertheless, the wave was the most
used function at the beginning of the study when participants were becoming
familiar with the app, as described by Pam, “I used it at first a lot, but not
anymore, doesn’t feel personal now.” Overall, our participants preferred
sending audio or picture/video messages and receiving text messages,
although relatives preferred to send and receive pictures or videos. Spatial
context also seemed to affect functions: for three participants, living arrange-
ments “didn’t offer much” for taking picture/video.
Data from interviews with study partners largely matched that of partici-
pant interviews, while providing extra information. They confirmed that
audio was the primary message type received, followed by picture and video
messages, with wave messages being the least popular. Most responded with
text-based messages. Diana’s granddaughter, Ike’s stepson, and Lily’s friend
often included pictures with text, whereas Gaby’s daughter reported primar-
ily sending pictures and videos. Only, Jane’s daughter responded by calling
“She can’t read whatever I’ve sent back, so I think her hearing is better than
her vision, so it’s still best to communicate with her by the phone, where it’s
audio, and she’s comfortable.”
Patterns of use were also reflected in study partners’ opinions regarding
the tool’s offerings. Diana’s, Gaby’s, and Lily’s family members found the
tool convenient, portable, and simple. Diana’s daughter explained that “she
can carry it with her, and she shows people photos, which she’d really like to
be able to do, if she goes to the diner, she can open it up, and show them
photos of her family.” The benefits of simplicity were echoed by Jen’s, Ike’s,
and Bree’s family members, who felt that the easy-friendly nature of the tool
Neves et al. 61

Table 3.  Main Stages of Technology Acceptability.

Stage Description
1.  Introductory stage Reliance on the manual and use of quick messages to
practice different software functions.
2.  Associative stage Improved understanding of software functionality
based on knowledge of other media.
3.  Autonomous stage Independent use of software, without use being
integrated into daily routines.
4.  Integrative stage Understanding of the software’s role within their own
contexts and an integration of the software into
existing communication practices.

determined its successful adoption. Some reported changes in participants’

relationship with technology as a result of app use. Five family members
reported participants’ increased confidence, comfort, and interest in using the
app over the study’s duration. Three study partners, however, stated that they
did not feel the tool offered anything new. Nearly all indicated some diffi-
culty in getting their senior to fully use the app, particularly during pre and
mid-deployment. This ranged from performing basic message-sending func-
tions to issues with more advanced functions like adding contacts.

Main stages of acceptability.  Combining adoption and use, we derived four

main stages of acceptability: introductory, associative, autonomous, and inte-
grative (see Table 3). In the introductory stage, participants relied on the
manual, used the “wave” frequently, and required assistance from research-
ers/ties. In addition, they primarily used the app to practice by sending quick
messages to contacts. Of the 12 participants, only one moved from the intro-
ductory phase in 3 weeks (James); remaining participants required an aver-
age of 4 weeks.
In the associative stage, participants displayed an intermediary level of
understanding of the technology; they made sense of most functions, particu-
larly through associations with other media. However, they still required
assistance and not all functions were used independently (e.g., video messag-
ing). Two participants remained in this stage until the study’s end. Jen com-
pared the app’s functions with a system used when she was a librarian,
reporting at mid-deployment: “From what I can observe and experience, it’s
a bit easier than the other kind of computer . . . but I am still not a very
mechanical person.” At postdeployment, she still felt she couldn’t “master
the machine.” Martha reported knowing how to use the app, especially com-
pared with other devices, but relied on her husband to use it.
62 Journal of Applied Gerontology 38(1)

The autonomous stage encompassed independent app use, while still

requiring practice and not being embedded in daily routines. Three partici-
pants remained in this phase at postdeployment. Paul was proficient with the
app, but only used it for short messages and to arrange meetings. At the
study’s conclusion, the app was not part of his routine as he relied mostly on
his phone. Bree had a “steep learning curve” and struggled with the audio and
video options due to her impairments, but mentioned it got easier as “you
went along.” She was then comfortable with the app, as it was the only way
to communicate with an overseas relative; yet, she felt that practice was
needed to not forget how to use it. Ike used the app more frequently at the
beginning, and could use it independently by the end, yet felt his Parkinson’s
affected his usage: “I am [losing] cognitive abilities and is hard to create
audio messages, I can’t speak that clearly anymore.” He continued to use it
for taking pictures and receiving messages.
Finally, in the integrative stage, participants were able to “domesticate” the
app, that is, fully use and make sense of the technology within their own contexts.
This appropriation or domestication was illustrated by the ability to integrate the
app into social routines and use it to complement other media. Seven participants
were at this stage at postdeployment. Although their use was less frequent than at
the beginning of the study (now weekly, not daily), it was curated to suit specific
communication needs: It was not seen as a way of practicing use, but of employ-
ing diverse functions to reach social ties and convey different messages. In addi-
tion, at this stage, participants were more aware of the limitations of the tool (e.g.,
asynchronicity, no keyboard) and felt confident to combine the app with other
media to overcome them. They even used other types of technology that were
once seen as too complex, and asked researchers to disable the “Guided Access
Mode” (tablet restricted to our app) when the study ended so they could learn
other functions. Kevin, for example, used the app in “tandem with his laptop”
because the app was simple to “start conversations. I am 95 and starting to forget
words” and he could “carry it down the hallway.” Gaby used the app to commu-
nicate with relatives abroad to avoid struggling with her “small” mobile phone
and expensive calls, and to send brief daily messages to family living nearby: “I
can just sit down and eat things in the morning or whenever and talk and send
pictures to all.” Diana planned to continue to use the app to communicate with a
friend and her daughter because they shared pictures and daily updates, but she
would be “phoning” others. James said, “love it for taking pictures and quickly
sending it, it’s easier than with the computer.”

Sociotechnical factors of acceptability.  Not all participants reached the integra-

tive stage. This seemed associated to interrelated factors that included social
support, attitudes, digital literacy, and usability. For instance, those with
lower levels of social support—that is, who did not have families/friends
Neves et al. 63

Figure 2.  Sociotechnical factors of technology acceptability.

encouraging use of the tool—were less frequent users and less comfortable
with the app. In contrast, having high family support seemed to compensate
for prior lack of digital literacy. Most participants displayed positive attitudes
toward learning to use the app, but those with previous digital literacy seemed
more independent in their learning process. Contrary to what was planned,
the initial training session was not enough, and even for those with prior digi-
tal experience; participants requested additional sessions. One usability fac-
tor that enhanced ease of use was the consistent layout of the interface. This
enabled participants to use inference to determine the purpose of icons.
Another important usability factor was the ability to choose an interface that
responded to tapping only versus tapping and swiping. Most participants pre-
ferred to tap, stating it was easier than swiping. Digital literacy was interre-
lated with the usability factors: Participants with higher digital literacy
successfully inferred meanings of the interface layout, and hence encoun-
tered fewer usability issues than other participants. In sum, acceptability
(adoption and use) of the app seemed to rest on a complex interplay of social,
attitudinal, digital, and usability factors, as illustrated in Figure 2.

Efficacy: Social Interaction Versus Social Connectedness

Although the app increased sense of social interaction (communication fre-
quency and type) with family and friends for 10 participants, only four
64 Journal of Applied Gerontology 38(1)

reported high perceived social connectedness at postdeployment. The app

allowed these four participants to reconnect, communicate more often, and
deepen relationships with relatives living abroad or afar. For example, Gaby
was limited in her communication with relatives, because most lived in dif-
ferent provinces or abroad—she “had no other way except to phone them”
and was too unwell to travel. In her words, “we go years before we see each
other,” so using the app,

It’s been wonderful, being able to talk to my family so far away, and not
need[ing] a special occasion to contact them, birthdays and Christmas, I can
contact them now at any time . . . and talk and send pictures.

The technology affected Gaby’s relationships with relatives because they

could talk more often, have longer, deeper, and more informal conversations,
and not worry about expensive calls.
For Pam, using the app allowed her to feel closer to her son (“living out
West”) and daughter-in-law. The different time zone was affecting her ability
to communicate with them, and due to her impairments she could only write/
call in the morning. The app’s asynchronicity meant she could communicate
when it suited her. Her son had a heart attack, and she was struggling with
wanting to fulfill her mothering role while dealing with her health limita-
tions. The technology gave her a way of overcoming those struggles: “I really
feel much safer knowing that I can be in touch with him [son] . . . And, also,
if he’s in the hospital, or something like that, his wife, I can get in touch with
her.” Bree and Lily reported similar app usage and perceived impact. Both
had family in Europe and “wouldn’t be able to communicate with them if
[they] didn’t have this tool.” Bree talked more frequently about her cousin,
their reminiscences of the past, and how she was more involved in his life.
She also communicated more often with her sister and new and old friends.
Lily mentioned more “satisfying” relationships with family, old friends, and
godchildren. At the start of the study, these four participants seemed to be the
ones (in addition to Jen, which social connectedness did not change as
reported below) displaying the least connectedness with their close and
extended networks of our sample. Gaby and Pam had low contact with chil-
dren and other relatives, mostly due to health impairments and different time
zones; Bree and Lily were single, were childlessness, and had most relatives
and friends living abroad.
For six participants, the app increased their perceived interaction (com-
munication frequency and type) with social ties, but did not make those rela-
tionships more meaningful as it was mostly used for brief contact or
follow-ups. Nevertheless, it allowed them to maintain their social interaction
Neves et al. 65

and enhanced their engagement with different media. For example, Diana
explained that the app added more multimedia options to her communication,
as she talked to people on the telephone and then shared audio messages and
pictures through the app. Her tablet was placed next to her telephone; when
she could not reach people on the phone, she used the app. James also reported
that through the app, he was able to communicate twice as often with rela-
tives, especially his sisters, and had more spontaneous interactions.
The remaining participants, Jen and duo Paul–Martha, indicated no
changes in social interaction or connectedness. Jen already had low social
interaction with relatives and friends, and conditions did not change. Although
she seemed connected with some church friends, most were not included as
contacts in the tool because they did not use new technologies. Regarding
family networks, she was the least socially connected participant of our sam-
ple. Paul felt limited by the asynchronicity and lack of keyboard. Martha
mostly used the tool through Paul.
Study partners’ reports supported these findings. The app was viewed as
an additional communication medium, and Gaby’s, Diana’s, and Jane’s rela-
tives reported increased communication frequency due to the tool. For
Diana’s granddaughter, their conversations now contained more detail, and
for Lily’s friend, their conversations had new topics. Lily’s friend and Gaby’s
daughter appreciated that the technology brought them closer to the partici-
pant. Lily’s friend mentioned, “I send her a picture and then she looks at it
and she likes it. I think it makes her feel more integrated.”
Despite these positive elements, four participants reported some disap-
pointment or tension with ties while using the app. Since predeployment, Jen
described a problematic and distant relationship with close family due to reli-
gious differences. Nevertheless, she mentioned a nephew with whom she felt
close and parishioners from her church. Not receiving replies from her
nephew and some parishioners might have affected her use of the app, and
even increased her perception of isolation and loneliness—although she did
not express it, and staff were closely monitoring her. James, Kevin, and Jane
indicated that some relatives would not reply to their messages. In some
cases, this lack of engagement was because relatives did not know how to use
email or open attachments; in others, they preferred alternative media. For
instance, Kevin confided, “I’m somewhat disappointed in my kids, they pre-
ferred to use FaceTime.” Jane also mentioned that she should have encour-
aged more replies from her grandchildren.
Our data, however, demonstrated that the app influenced perceived well-
being of 7 of the 11 participants, who affirmed its impact on their positive
mood, self-efficacy, and comfort with technology. For instance, Gaby indi-
cated “living” more contentedly and capably. Pam emphasized feelings of
66 Journal of Applied Gerontology 38(1)

“safety” and how it “made me feel that I’m trying and that I can do a bit.”
Like Pam, Jane had never used “electronics before” and found the experience
“informative and motivational.” Both were hoping to learn how to “Google
things” next. Lily felt more confident about technology, despite previous
“computer anxiety.” Diana felt “more relaxed and comfortable” when using
the app in comparison with her computer and more patient with technology;
Kevin reported similar experiences. We also captured increases in partici-
pants’ levels of digital literacy: three had low digital literacy, six medium, and
two high (compared with three with no digital literacy, three low, and five
medium at the study’s commencement).
The app had a negative impact on the perceived well-being of two users,
making them more aware of their digital “inadequacy” or impairments. Jen felt
“a little bit inadequate” at postdeployment, and Jane reported that the audio
option made her more attuned to her “issues”: “I’m nervous speaking . . . I
figured my voice sounds kind of silly, but I’ve got to learn to speak up.”
There were no significant changes in any of the scales used (p > .05),
within and across participants. These were then used as baseline data, adding
to qualitative profiling.

Discussion
We aimed to understand the feasibility of an accessible communication app to
enhance perceived social connectedness among frail older adults living in a
retirement home. For this, we focused on two main components of feasibility
studies—acceptability and efficacy—and used a 3-month, mixed-methods
deployment. Bringing together acceptability and efficacy, our findings
revealed that an accessible app can be a feasible tool for social connectedness
(as proposed in Findlay, 2003; Keefe et al., 2006; Khosravi et al., 2016; Masi
et al., 2011) if five feasibility elements are considered. First, the active involve-
ment of one tie was crucial for adoption of the app, learning dynamics, and
type and continuity of use. Those who had relatives or friends deeply engaged
in the process seemed more available to learn and use the app, even without
digital literacy. As social capital theory and social connectedness perspectives
have been showing, it is not quantity but quality and types of relationships that
matter (Litwin & Shiovitz-Ezra, 2011; Wong & Waite, 2016). For instance,
Jen, who did not have a very engaged study partner (a church friend), showed
a tense relationship with relatives, and had a small close network (of which
most members did not use new technologies), did not benefit from using the
tool. Second, the app’s perceived usefulness and functionality seemed related
to levels of acceptability and efficacy. Usefulness seemed to increase adoption
and use, as found in adoption studies (Davis, 1989; Giger et al., 2015). Yet,
Neves et al. 67

data also highlighted that digital literacy levels did not seem to affect percep-
tions of usefulness and functionality. Family involvement was, however, criti-
cal to those perceptions. For example, although all participants reported
enjoying the app’s asynchronous aspect, relatives’ preference for a synchro-
nous tool meant most participants questioned their preference. Third, all par-
ticipants, even those with higher levels of digital literacy, needed adjustment
periods to learn to use the app. These periods included more training sessions,
practice slots, and time to see what messages each contact preferred/would
respond to. The latter is connected to a fourth feasibility element: management
of different intergenerational preferences, norms, and expectations. These
related to types of message (e.g., relatives preferred pictures/video whereas
participants audio messages), asynchronous versus synchronous communica-
tion, and reply times. Although multimedia options were useful and praised by
participants (as also suggested in Delello & McWhorter, 2017), digitally
mediated intergenerational communication relies on different generational
perceptions (Neves et al., 2015; Neves et al., 2017). Nonetheless, in their
3-year ethnographic study in an adult education center, Sayago et al. (2011)
showed that feeling socially included motivates older adults to try to adapt to
close ties’ technology preferences—they suggest that acceptability and evolu-
tion of technology use seemed to rest on needs to be connected in meaningful
ways. Finally, high social connectedness was only reported by participants
who had relatives living abroad or in other provinces. Of our sample, these
participants—Gaby, Pam, Bree, and Lily—seemed to have the least level of
connectedness with ties at the start of the study (in addition to Jen), which
seemed related to both health issues and having their main ties living in differ-
ent regions/time zones or countries. As such, having geographically distant
relatives can amplify the app’s feasibility to enhance social connectedness.
This finding supports the relevance of connectedness with close relatives, par-
ticularly those living overseas (Cotten et al., 2012; Sum et al., 2008; Tsai et al.,
2015; White et al., 2002).
The social affordances perspective (Wellman et al., 2003) helps highlight
the role of the app: its accessibility, convenience, and multioptions that created
varied opportunities for interaction seemed fruitful for social connectedness.
Furthermore, by using a recursive approach to technology evaluation that con-
nected users, technology, and contexts (Greenhalgh & Stones, 2010), we were
able to explore “adoption in the making”, rely on a functional perspective that
considered types of use rather than just use (Lifshitz et al., 2016), and flesh out
the positive/negative interplay of family dynamics, digital literacy, attitudes,
frailty, technology design and usability, residential settings, agency, and out-
comes. Feasibility was the result of this interplay and not of isolated factors
(cf. Davis, 1989; Giger et al., 2015). The acceptability stages emphasize the
68 Journal of Applied Gerontology 38(1)

complexity of adoption and use, even among a small sample. In addition, this
comprehensive approach uncovered other outcomes: subjective well-being,
feelings toward technology, and self-efficacy. Most outcomes were positive,
but the app also seemed to augment feelings of inadequacy and awareness of
frailty for at least two participants; tensions with relatives regarding different
communication preferences and expectations were also found. These negative
outcomes are not frequently addressed in research.
Overall, these findings on social connectedness match results from our
previous study with five Chinese Canadians (aged 80+, low income, low lit-
eracy, high levels of frailty, and living in a long-term care facility). This sug-
gests that low opportunities for social connectedness (in part related to frailty
and institutionalization), geographical distance, and time barriers are issues
faced by a group of the fragile older population, regardless of education,
income, and institutional living setting (Neves et al., 2015). Furthermore,
findings extend those of notable studies on the subject—however, former
studies on social isolation and loneliness only examined general Internet use
among older participants and were either quantitative or qualitative (Cotten
et al., 2012; Sum et al., 2008; Tsai et al., 2015; White et al., 2002). By expand-
ing this literature, we offer a fresh exploration of adoption, use, and outcomes
of technology in later life from different angles, including family/friends. The
3-month mixed design contributed to this depth and lessened initial impres-
sion management efforts by participants, such as curated displays of social
interaction and technology use—for example, overly positive narratives of
family interaction and the app. The engagement of both older participants and
relatives allowed us to capture different users, dimensions, and perceptions.

Implications
These findings can inform the design, implementation, and evaluation of simi-
lar communication tools or interventions. The feasibility elements will help
refine and develop better and more sensitive digital tools. For instance, differ-
ent intergenerational preferences, norms, and expectations must be taken into
account to prevent tensions in the uptake of technology used to communicate
with children and grandchildren. The negative unintended consequences must
also be contemplated at the onset—through, for example, a set of pilot studies.
The four acceptability stages will further assist in anticipating adoption(s) and
use(s). The recursive and mixed approach proved critical to flesh out the inter-
play between users, technologies, and context, adding to a deeper analytical
understanding of technology in later life. We argue that these approaches are
needed to study this subject comprehensively from a dynamic perspective that
recognizes different types of adoption, use, and outcomes.
Neves et al. 69

Limitations
Despite these contributions, our results are limited by a nonrepresentative
sample of frail older adults living in a retirement home. Participants had
medium or high levels of education, lived in a relatively wealthy setting
(although some participants were part of welfare programs for low-income
older adults), and English was their first language or they were proficient
in English. In addition, despite being vulnerable to social isolation and
loneliness, no participant displayed high levels of social isolation. The tool
might be less successful for those individuals, particularly as at least one
tie (available and engaged) is needed for social interaction. Our study also
had a restricted time frame due to institutional constraints. These limita-
tions are usual in feasibility studies, which intend to set the stage for future
research.

Acknowledgments
Authors would like to thank participants and staff of the retirement community. We
are also grateful to Mags Ngo, Nadia Nassar, Cosmin Munteanu, Annette Mayer,
Chris Arnold, Hubert Hu, Benjamin Rabishaw, Sarah Crosskey, Kate Sellen, and all
former TAGlab members who contributed to the InTouch project.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research,
authorship, and/or publication of this article.

Funding
The authors disclosed receipt of the following financial support for the research,
authorship, and/or publication of this article: This research was supported by GRAND
NCE as well as by AGE-WELL NCE Inc., both members of the Government of
Canada’s Networks of Centres of Excellence research program.

References
Baecker, R., Sellen, K., Crosskey, S., Boscart, V., & Neves, B. B. (2014).
Technology to reduce social isolation and loneliness. In Proceedings of the
16th international ACM SIGACCESS conference on Computers & accessibility
(pp. 27-34). New York, NY: Association for Computing Machinery.
Billingham, S. A., Whitehead, A. L., & Julious, S. A. (2013). An audit of sample
sizes for pilot and feasibility trials being undertaken in the United Kingdom reg-
istered in the United Kingdom clinical research network database. BMC Medical
Research Methodology, 13(1), Article 104.
Bowen, D. J., Kreuter, M., & Fernandez, M. (2009). How we design feasibility stud-
ies. American Journal of Preventive Medicine, 36, 452-457.
70 Journal of Applied Gerontology 38(1)

Brown, E. L., Ruggiano, N., Li, J., Clarke, P. J., Kay, E. S., & Hristidis, V. (2017).
Smartphone-based health technologies for dementia care: Opportunities, chal-
lenges, and current practices. Journal of Applied Gerontology, 0733464817723088.
Choi, R. N., Kong, S., & Jung, D. (2012). Computer and internet interventions for lone-
liness and depression in older adults: A meta-analysis. Healthcare Informatics
Research, 18, 191-198.
Cornwell, E. Y., & Waite, L. J. (2009). Social disconnectedness, perceived isola-
tion, and health among older adults. Journal of Health and Social Behavior,
50, 31-48.
Cotten, S. R., Anderson, W., & McCullough, B. (2012). The impact of ICT use on
loneliness and contact with others among older adults. Gerontechnology, 11,
161-169.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance
of information technology. MIS Quarterly, 13, 319-340.
Delello, J. A., & McWhorter, R. R. (2017). Reducing the digital divide: Connecting
older adults to iPad technology. Journal of Applied Gerontology, 36(1), 3-28.
Findlay, R. A. (2003). Interventions to reduce social isolation amongst older people:
Where is the evidence? Ageing & Society, 23, 647-658.
Freitag, S., & Schmidt, S. (2016). Psychosocial correlates of frailty in older adults.
Geriatrics, 1(4), 26.
Fried, L. P., Tangen, C. M., Walston, J., & McBurnie, M. A. (2001). Frailty in
older adults evidence for a phenotype. The Journals of Gerontology, Series A:
Biological Sciences & Medical Sciences, 56, M146-M157.
Giger, J. T., Pope, N. D., Vogt, H. B., Gutierrez, C., Newland, L. A., Lemke, J.,
& Lawler, M. J. (2015). Remote patient monitoring acceptance trends among
older adults residing in a frontier state. Computers in Human Behavior, 44,
174-182.
Green, L. W., & Glasgow, R. E. (2006). Evaluating the relevance, generalization, and
applicability of research: Issues in external validation and translation methodol-
ogy. Evaluation & the Health Professions, 29, 126-152.
Greenhalgh, T., & Stones, R. (2010). Theorising big IT programmes in health-
care: Strong structuration theory meets actor-network theory. Social Science &
Medicine, 70, 1285-1294.
Guest, G., Bunce, A., & Johnson, L. (2006). How many interviews are enough?
An experiment with data saturation and variability. Field Methods, 18(1),
59-82.
Hall, S., Longhurst, S., & Higginson, I. J. (2009). Challenges to conducting research
with older people living in nursing homes. BMC Geriatrics, 9(1), Article 38.
Hope, A., Schwaba, T., & Piper, A. M. (2014). Understanding digital and mate-
rial social communications for older adults. In Proceedings of the SIGCHI
Conference on Human Factors in Computing Systems (pp. 3903-3912). New
York, NY: Association for Computing Machinery.
Hughes, M. E., Waite, L. J., Hawkley, L. C., & Cacioppo, J. T. (2004). A short scale
for measuring loneliness in large surveys: Results from two population-based
studies. Research on Aging, 26, 655-672.
Neves et al. 71

Keefe, J., Andrew, A., Fancey, P., & Hallet, M. (2006). A profile of social isolation
in Canada (Report Submitted to the F/P/T Working Group on Social Isolation).
Halifax: Mount Saint Vincent University.
Khosravi, P., Rezvani, A., & Wiewiora, A. (2016). The impact of technology on older
adults’ social isolation. Computers in Human Behavior, 63, 594-603.
King, N., & Horrocks, C. (2010). Interviews in qualitative research. New York, NY:
SAGE.
Lally, F., & Crome, P. (2007). Understanding frailty. Postgraduate Medical Journal,
83, 16-20.
Lee, C., & Coughlin, J. F. (2015). Older adults’ adoption of technology: An integrated
approach to identifying determinants and barriers. Journal of Product Innovation
Management, 32, 747-759.
Lifshitz, R., Nimrod, G., & Bachner, Y. G. (2016). Internet use and well-being in later
life: A functional approach. Aging & Mental Health, 1-7. Retrieved from http://
dx.doi.org/10.1080/13607863.2016.1232370
Lindley, S. E., Harper, R., & Sellen, A. (2009). Desiring to be in touch in a chang-
ing communications landscape: Attitudes of older adults. In Proceedings of the
SIGCHI Conference on Human Factors in Computing Systems (pp. 1693-1702).
New York, NY: Association for Computing Machinery.
Litwin, H., & Shiovitz-Ezra, S. (2011). Social network type and subjective well-being
in a national sample of older Americans. The Gerontologist, 51, 379-388.
Masi, C., Chen, H. Y., Hawkley, L., & Cacioppo, J. T. (2011). A meta-analysis of
interventions to reduce loneliness. Personality and Social Psychology Review,
15, 219-266.
McPherson, M., Smith-Lovin, L., & Brashears, M. E. (2006). Social isolation in
America: Changes in core discussion networks over two decades. American
Sociological Review, 71, 353-375.
Morris, M. E., Adair, B., Ozanne, E., & Said, C. M. (2014). Smart technologies to
enhance social connectedness in older people who live at home. Australasian
Journal on Ageing, 33, 142-152.
Neves, B. B. (2013). Social capital and Internet use: The irrelevant, the bad, and the
good. Sociology Compass, 7(8), 599-611.
Neves, B. B., Franz, R. L., Munteanu, C., & Baecker, R. (2017). Adoption and feasibil-
ity of a communication app to enhance social connectedness amongst frail insti-
tutionalized oldest old: an embedded case study. Information, Communication &
Society, 1-19. Retrieved from https://doi.org/10.1080/1369118X.2017.1348534
Neves, B. B., Franz, R. L., Munteanu, C., Baecker, R., & Ngo, M. (2015). My
Hand Doesn’t Listen to Me!: Adoption and Evaluation of a Communication
Technology for the ‘Oldest Old’. In Proceedings of the 33rd Annual ACM
Conference on Human Factors in Computing Systems (pp. 1593-1602). New
York, NY: Association for Computing Machinery.
Nicholson, N. R. (2012). A review of social isolation: An important but underassessed
condition in older adults. The Journal of Primary Prevention, 33(2-3), 137-152.
Patton, M. Q. (1990). Qualitative evaluation and research methods. Beverly Hills,
CA: SAGE.
72 Journal of Applied Gerontology 38(1)

Perissinotto, C. M., Stijacic Cenzer, I., & Covinsky, K. E. (2012). Loneliness in

older persons: A predictor of functional decline and death. Archives of Internal
Medicine, 172, 1078-1084.
Prieto-Flores, M. E., Forjaz, M. J., Fernandez-Mayoralas, G., Rojo-Perez, F., &
Martinez-Martin, P. (2011). Factors associated with loneliness of noninstitu-
tionalized and institutionalized older adults. Journal of Aging and Health, 23(1),
177-194.
Pretzlik, U. (1994). Observational methods and strategies. Nurse Researcher, 2(2),
13-21.
Quan-Haase, A., Martin, K., & Schreurs, K. (2016). Interviews with digital seniors:
ICT use in the context of everyday life. Information, Communication & Society,
19, 691-707.
Sayago, S., Sloan, D., & Blat, J. (2011). Everyday use of computer-mediated com-
munication tools and its evolution over time: An ethnographical study with older
people. Interacting with Computers, 23, 543-554.
Seidman, I. (2006). Interviewing as qualitative research: A guide for researchers in
education and the social sciences. New York, NY: Teachers College Press.
Steptoe, A., Shankar, A., Demakakos, P., & Wardle, J. (2013). Social isolation,
loneliness, and all-cause mortality in older men and women. Proceedings of the
National Academy of Sciences, 110, 5797-5801.
Sum, S., Mathews, R. M., Hughes, I., & Campbell, A. (2008). Internet use and loneli-
ness in older adults. Cyberpsychology & Behavior, 11, 208-211.
Tsai, H. Y. S., Shillair, R., & Cotten, S. R. (2015). Getting grandma online: Are
tablets the answer for increasing digital inclusion for older adults in the US?
Educational Gerontology, 41, 695-709.
Tyack, C., Camic, P. M., Heron, M. J., & Hulbert, S. (2017). Viewing art on a tablet
computer: A well-being intervention for people with dementia and their caregiv-
ers. Journal of Applied Gerontology, 36, 864-894.
Victor, C., Scambler, S., & Bond, J. (2009). The Social World of Older People:
Understanding loneliness and social isolation in later life. Maidenhead, UK:
Open University Press.
Wardian, J., Robbins, D., Wolfersteig, W., Johnson, T., & Dustman, P. (2012).
Validation of the DSSI-10 to measure social support in a general population.
Research on Social Work Practice, 23, 100-106.
Wellman, B., Quan-Haase, A., Boase, J., Chen, W., Hampton, K., Díaz, I., . . . Miyata,
K. (2003). The social affordances of the Internet for networked individualism.
Journal of Computer-Mediated Communication, 8(3). Retrieved from http://
onlinelibrary.wiley.com/doi/10.1111/j.1083-6101.2003.tb00216.x/abstract
White, H., McConnell, E., Clipp, E., Branch, L. G., Sloane, R., Pieper, C., & Box, T.
L. (2002). A randomized controlled trial of the psychosocial impact of providing
internet training and access to older adults. Aging & Mental Health, 6, 213-221.
Wong, J., & Waite, L. (2016). Theories of social connectedness and aging. In V.
Bengston & R. Settersten, Jr. (Eds.), Handbook of theories of aging (pp. 349-363).
New York, NY: Springer.