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This paper analyzes how older people, living in Spain, use smartphones and smartphone applications. Using a mixed methods approach, we compare quantitative results obtained by tracking mobile app usage amongst different generational samples with qualitative, focus-group discussions with active smartphone users. A sample of Spanish smartphone users were tracked during one month in the winter of 2014 (238 individuals, aged 20 to 76 years-old). This was followed by three focus group sessions conducted in the spring of 2015, with 24 individuals aged 55 to 81. As we learned, WhatsApp is currently the most popular application used by people of all ages, including older adults. Smartphones increasingly are playing a central role in the life of older participants, although the frequency of app access is negatively correlated with age. On the other hand, as our data indicates, older adults also use a number of different types of apps that are distinct from that of younger users. Older participants access personal information manager apps (calendar, address book and notes) more often than other age groups. And comparatively, older participants use the smartphone less often in stable locations (home, office, relatives’ home) with Wifi than somewhere else and with mobile data. As we argue, differences in age seem to reflect the evolution in personal interests and communication patterns that change as we grow older. Our study captures new trends in smartphone usage amongst this cohort. It also indicates how a combination of methods may help to assess the validity of the log and qualitative data. We highlight the relevance of conducting careful generational studies in smartphone use and some of the potentials and limitations of making predictive studies of ICT use as we change throughout the life course. Finally, we assert the value of the inclusion of older representatives within research, which ultimately may influence public decisions and the design of new technologies.
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Abstract
This paper analyzes how older people, living in Spain, use smartphones and smartphone applications.
Using a mixed methods approach, we compare quantitative results obtained by tracking mobile app usage
amongst different generational samples with qualitative, focus-group discussions with active smartphone
users. A sample of Spanish smartphone users were tracked during one month in the winter of 2014 (238 in-
dividuals, aged 20 to 76 years-old). This was followed by three focus group sessions conducted in the spring
of 2015, with 24 individuals aged 55 to 81. As we learned, WhatsApp is currently the most popular applica-
tion used by people of all ages, including older adults. Smartphones increasingly are playing a central role
in the life of older participants, although the frequency of app access is negatively correlated with age. On
the other hand, as our data indicates, older adults also use a number of different types of apps that are dis-
tinct from that of younger users. Older participants access personal information manager apps (calendar, ad-
dress book and notes) more often than other age groups. And comparatively, older participants use the
smartphone less often in stable locations (home, office, relatives’ home) with Wifi than somewhere else and
with mobile data. As we argue, differences in age seem to reflect the evolution in personal interests and com-
munication patterns that change as we grow older. Our study captures new trends in smartphone usage
amongst this cohort. It also indicates how a combination of methods may help to assess the validity of the
log and qualitative data. We highlight the relevance of conducting careful generational studies in smartphone
use and some of the potentials and limitations of making predictive studies of ICT use as we change through-
out the life course. Finally, we assert the value of the inclusion of older representatives within research, which
ultimately may influence public decisions and the design of new technologies.
Keywords: smartphones; ageing; apps; use patterns; elders; focus groups; log data.
Introduction
Older adults are often portrayed as less avid users of information and communication tech-
nologies (ICT), as uninterested in ICTs, or of not being capable to use them properly. These
discourses find some support if one examines the existing available data (Eurostat, 2015).
Yet, this statistical picture is changing and one must also question how this data was collect-
ed and what it may include or include. For example, older adults show the highest growth rate
for mobile ICT adoption in developed contexts (Deloitte, 2014). An increasing amount of ev-
idence examines older individuals as active users of social network sites (SNS) such as Face-
Romanian Journal of Communication and Public Relations
vol. 18, no 1(37)/ April 2016, 27-47
ISSN: 1454-8100/ E-ISSN: 2344-5440
Andrea ROSALES*
Mireia FERNÁNDEZ-ARDÈVOL**
Beyond WhatsApp: Older people and smartphones
*Universitat Oberta de Catalunya, Spain, arosalescl@uoc.edu
** Universitat Oberta de Catalunya, Spain, mfernandezar@uoc.edu
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book (Choudrie & Vyas, 2014; Duggan, Ellison, Lampe, Lenhart, & Madden, 2015; Nef,
Ganea, Müri, & Mosimann, 2013), their use of virtual spaces for maintaining both weak and
strong ties (Hage & Noseleit, 2015; Khvorostianov, Elias, & Nimrod, 2012) or for develop-
ing personal interests (Nimrod, 2014). Closer to home, the pervasive use of instant messag-
ing (IM), notably WhatsApp in Spain (CIS, 2016), challenges an array of age stereotypes as
demonstrated by a casual observation in the city of Barcelona where people of any age – old-
er people included – are seen busily using their smartphones while on public transport. Such
stereotypes of the participation of older people in the world of ICTs are often built on em-
bedded prejudices that run contrary to available empirical evidence. More recent studies ad-
dress this stereotypical portrait of ICT use in the case of older people (Loos, 2011) and can
assist us to understand how research may be contributing to the perpetuation of an age-based
digital divide (Lagacé, Charmarkeh, Tanguay, & Annick, 2015).
Digital media use, as a part of the overall landscape of mediated communication, is wide-
ly studied with respect to children and youth, but is underdeveloped with respect to older
people (Colombo & Fortunati, 2011; Mihailidis, 2014; Silverstone & Haddon, 1996). Teenagers
and young people often constitute reference points for ICT studies because it is assumed that
they help identify the main trends of adoption and use (Castells, Fernández Ardèvol, Linchuan
Qiu, & Sey, 2006; Ito et al., 2010). Contributions that take the older population into account
are scarce in comparison, although there is a growing interest in how older adults engage
with Internet and ICTs in general (Colombo & Fortunati, 2011; Loos, Haddon, & Mante-Mei-
jer, 2012; Prendergast & Garattini, 2015) and in mobile communication in particular (Co-
munello, Mulargia, Belotti, & Fernández-Ardèvol, 2015; Fernández-Ardèvol, 2016; Nguyen,
Irizarry, Garrett, & Downing, 2015; Pang, Vu, Zhang, & Foo, 2015; Petrovèiè, Fortunati, Ve-
hovar, Kavèiè, & Dolnièar, 2015). There appear to be (non-explicit) normativities that per-
sistently frame the ideal patterns of use and adoption as those belonging to youth, although
this is changing.
Ageing and age are socially constructed phenomena and are ongoing processes. Ageing
in particular, and phases in the life course in general, shape and are shaped by broader rela-
tions of power as Calasannti & King have argued in a recent paper (2015). Being old often
has negative connotations (Garattini & Prendergast, 2015) because of prevailing age-related
norms that often portraying older people as limited individuals who are objects of others’ ac-
tions (Jolanki, 2009). Such norms limit the perceived agency of older people in different
ways. Yet as Ling has argued in 2008, intimate personal network can act either as a support-
ive mechanism or a limiting one (Ling, 2008). This set of conditions and context affects ICT
adoption in particular and perceptions of digital technologies in general (Buccoliero & Bel-
lio, 2014). As other research indicates, personal values and interests change over the lifetime
(B. L. Neugarten, 1996) and personal communication patterns and the use of media evolve
as we grow old, as Ling, Bertel, & Sundsoy (2012) have demonstrated in analyzing differ-
ences in SMS use between different age groups. Stereotypes surrounding ICT use may con-
tribute significantly to digital inequalities, as they deploy implicit modes of operation that may
shape social behaviors (Greenwald & Banaji, 1995), including ICT skills (Lagacé et al., 2015)
Studies that track online individual behavior have multiplied recently, and older people
have started to be included in such analyses (Azuddin, Malik, Abdullah, & Mahmud, 2014;
Pang et al., 2015). Tracking online activities offers new ways of achieving an accurate un-
derstanding of users’ behaviors (Gonçalves & Ramasco, 2009) that partially correlates with
reported use (Boase & Ling, 2013). However, these analyses tend to be ahistorical ((Up-
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richard, 2012), static or focused on very short-term observations (Thomas et al., 2013). De-
spite the obvious necessity to question the assumptions involved in the huge capacities that
big data bring to research(boyd & Crawford, 2012), few approaches try to understand the
meaning behind the existing databases, databases that reflect online activity in terms of indi-
viduals’ everyday life perspectives (DeLyser & Sui, 2013). In this regard, a key contribution
to our understanding of data is to compare and confront the results obtained with log-tracked
data with the opinions and perceptions of different groups, such as older people.
The goal of this paper is to understand the ways that older people appropriate smartphones
from a perspective that challenges ageist stereotypes. To do so, we create a dialogue between
the results of a generational log data study and the reported experiences of older smartphone
users. We first tracked the activity of 238 smartphone users aged between 18 and 76 years old
for one month. We then gathered reported experiences, related to the results of the first part of
the study, in three focus groups with 25 individuals aged between 55 and 81 years old. Our
analysis is oriented in two inter-related directions: the specific uses (what?) by older adults of
smartphones and the routines established by our older participants (where?). We explore the
specificities of smartphone use among older people, to better articulate the relevancy that the
smartphone, and smartphone applications (or apps) have for older individuals. The (new) per-
spective that log data brings to the study of digital devices allows for an increase in our over-
all knowledge on the current use of smartphones while our focus group research adds nuance
to these issues. With this in mind we look more closely at current research on smartphones.
Studying smartphone use
Smartphones have specific affordances and capabilities, different from computers or tablets.
The comparison of use patterns among136 smartphone users and 160 laptop users in the US,
including the analysis of log data gathered in 2009, shows that use sessions tend to be short-
er and more distributed through the day in smartphones than in laptops (Oulasvirta, Ratten-
bury, Ma, & Raita, 2012). One study, undertaken in Flanders, Belgium, analyzed news
consumption on mobile devices –smartphones and tablet computers combined interviews, di-
aries, and automated data logs of 30 participants tracked during one week (Van Damme, Cour-
tois, Verbrugge, & Marez, 2015). Researchers found that news media are consumed on different
screens, such as computers, laptops, television, or mobile devices. The authors also identi-
fied a noticeable shift towards news consumption on mobile devices, which is considered an
individual activity. Interestingly, the consumption of news on mobile devices is mostly non-
mobile, as the consultation of news when at home exceeded that during the rest of the day.
Indeed, the mobile phone tends to be used most (from stable locations, such as the home,
work, or school (Castells et al., 2006) than on the go. This is, perhaps, a reflection of the so-
cial dynamics that articulate everyday life (Giddens, 1987 ch. 6). For instance, the Spanish
population, aged 10 years old and over, spend most of the day at home (16:34 hours on av-
erage), while the second most common place for people to be is their place of work or school
(2:45 hours). In addition, people spend one hour a day on the street or in open spaces, and
1:08 hours on transportation.
Mobile phones constitute important everyday life tools that allow for permanent connec-
tion (Katz & Aakhus, 2002). Permanent connection means being able to reach others at any
moment, however this does not mean that individuals spend the whole day on their smart-
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phones. The consultation period on the device tend to be short. What one finds are brief us-
age sessions repeated over time, which represent an important part of smartphone use and con-
stitute one of its particular characteristics. Ørmen & Thorhauge (2015) term these
‘microroutines’, which are embedded into everyday life patterns. In the US, the 6-month
tracking of 25 users demonstrated that smartphones are in the idle state most of the time
(Shye, Scholbrock, Memik, & Dinda, 2010).
The design and goals of log data studies are diverse. In Finland, 20 smartphone users were
tracked during four weeks and interviewed to determine their social networking patterns
through a specific social network aggregator service, LinkedUI (Cui & Honkala, 2011). The
authors also observed that people form habits of checking their mobile devices at frequent
intervals. In South Korea, a national panel of 1646 users provided by a marketing research
company, were tracked during one month in 2011 to measure usage concentration of smart-
phone apps (Jung, Kim, & Chan-Olmsted, 2014). While panelists’ time was concentrated on
a few apps, the array of game apps used was diverse. That is, most people used the same few
apps but in the case of games the market was much more segmented. In addition, there seems
to be the conjoint use of apps, as a study in the USA showed. Based on data traffic and the
time access of apps collected from a set of 600.000 unique subscribers, gathered evidence sug-
gests that, for instance, weather and news apps are used together (Xu et al., 2011). Finally,
according to Barkhuus & Polichar (Barkhuus & Polichar, 2011), individuals use their smart-
phones in highly individual manners to suit their needs and lifestyle. For example many peo-
ple use mobile devices during parallel activities of personal interest, such as streaming music
while cycling or playing games while watching TV (Lord et al., 2015).
Smartphone logs to predict smartphone use
An array of studies have attempted to make predictions on different aspects of smartphone
use (Ørmen & Thorhauge, 2015). In 2004, the MIT Human Dynamics Laboratory conduct-
ed a pioneer study that gave rise to the reality mining dataset (Eagle & Pentland, 2006) by
tracking 100 smartphones to ”extract patterns that predict future human behavior”.1Within
the project, a classification of daily routines based on mobile phone data, which then encour-
aged researchers to make predictive statements on the routines in an individual’s everyday
life (Eagle & Pentland, 2009). Similarly, Nokia Research Center conducted the Lausanne da-
ta collection campaign in 2009-2010 (Kiukkonen, Blom, Dousse, Gatica-Perez, & Laurila,
2010). They analyzed smartphone log data together with self-reported information. This mixed
method was used to determine personality traits of mobile phone users that could feed ma-
chine learning methods (Chittaranjan, Jan, & Gatica-Perez, 2011).
A lack of generational perspective
Most papers analyzing smartphone use do not collect or report the age of participants, do
not include older people, or do not report the nuances of smartphone use depending on age
differences. Among this rising number of studies that track smartphone use, almost none fo-
cus on older people or make generational comparisons. One possible exception is a study on
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the excessive dependence on smartphones comparing ‘digital natives’ and ‘non natives’, where
(non) nativity was based on the participant’s age (Ahn & Jung, 2014). The majority of research
analyzes youth and adults together (Cui & Honkala, 2011; Eagle & Pentland, 2009; Oulasvir-
ta et al., 2012; Van Damme et al., 2015). There are also studies that look at a specific age group,
such as youth (Lee et al., 2014; Mihailidis, 2014; Pan, Chen, & Rau, 2013; Raento, Oulasvir-
ta, & Eagle, 2009) or adults (Barkhuus & Polichar, 2011; Kiukkonen et al., 2010). Jung et al.
(Jung et al., 2014) analyze a sample of individuals grouped by age from 10 years old to 50
years old and over, ignoring nuances for each generation. In Chittaranjan, Jan, & Gatica-
Perez (Chittaranjan et al., 2011), the sample ranges from 19 to 63 years old with no specific
analysis of the age dimension. Finally, some studies do not even mention the age of partici-
pants in the case study (Böhmer, Hecht, Schöning, Krüger, & Bauer, 2011), either because
authors do not consider it relevant for the topic of the study, or because it was not possible
to access that information (Lord et al., 2015; Shye et al., 2010; Xu et al., 2011). Given this
context, one of our goals is to contribute to a reflection on the current shortage of data on old-
er individuals in the study of smartphone by providing specific empirical evidence and by dis-
cussing its interpretation. The research question we have is: What are the specificities, if any,
in the use of smartphones by older adults?
Method
To answer this question, we have used a mixed methods approach. First, we tracked
users’ smartphone activity in a sample of 283 adults during a period of one month. Second,
we conducted three focus groups with older adults to have insight into the way they used
their smartphones.
Research based on the log data generated by smartphones have proliferated since the mid
2000s. Smartphones open the door, as do other on line digital media, to automated log data
which allow non-intrusive records of mundane everyday life activities and make possible
“augmented longitudinal, process, and context-sensitive investigations” (Raento et al., 2009).
Log data are used to obtain “real use” data not only in the field of the social sciences, but al-
so in computing sciences in general (Shye et al., 2010) and in human computer interaction in
particular (Cui & Honkala, 2011). However, “the log data per se cannot provide the most im-
portant insights, namely the context and purpose of use” (Ørmen & Thorhauge, 2015) and it
is necessary to keep in mind that not all data gathered on the device corresponds to the ac-
tivity of the user (Raento et al., 2009). Thus, a mixed methods approach (Creswell, 2003) is
used to complement the quantitative data from smartphone logs, with qualitative data from
focus groups. In what follows we detail these two very different yet related studies, one us-
ing mobile app tracking and one based on focus groups. Some details of the tracking are nec-
essary for an appropriate interpretation of results.
Mobile app tracking
As we are researchers who live and work in the context of Spain, we have used a market
research panel that focuses on the Spanish population to track the online activities of a set of
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panelists on their smartphones (from now on in this paper we will refer to them as panelists).
The panelists are active internet users, already registered in the panel when we started the study.
They installed an app on their device(s) to become part of the tracked panel and received
non-economic rewards for participating in the activities of the panel-mainly surveys and track-
ing. The dataset corresponds to one month of activity between 17 November and 16 Decem-
ber 2014. The software registers every time each user accesses an app, the date and time of
the access, the active length of the session, and the type of connection (Wi-Fi or mobile da-
ta). For example if a panelist opens a fitness app (i.e. Endomondo) to track their running, the
software counts one access when they activate it, and then logs the length of the session un-
til the panelist moves onto another app or their phone returns to the idle mode.
The sample within our study corresponds to 171.360 hours of smartphone activities. It
belongs to a wider log data collection which, in the same period, the tracked the activity of
455 panelists either on their computers or on their mobile devices. The selected sample re-
sembles the characteristics of the Spanish population who are active Internet users (INE,
2014). The oldest panelist was only 76, which is a reflection of (online) market research in-
terests, which do not consider older people as a prominent target (Sawchuk & Crow, 2011).
After filtering, the final sample of smartphone users was 238 panelists, which gave us access
to 242 devices, as four panelists participated with two smartphones. With 122 women (51,2%)
and 116 men (48,7%), age ranges from 20 to 76 years old: 36 panelists (15,1% of the sam-
ple) can be classified as young individuals – 20-24 years old; 94 (39,5%) as young adults –
25-39 years old; 91 (38,2%) as adults – 40-59 years old; and 17 (7,1%) as older individuals
– 60-76 years old.
Focus groups
25 participants—15 men and 10 women, aged 55 to 81, participated in the focus groups
(from now on in this paper we will refer to them as participants). When using quotations from
participants we will indicate their sex and age to guard their privacy. Participants were involved
in one two-hour session, divided in three groups of 8, 8 and 9 participants. All had different
levels of experience with smartphones, from four months to three years of use. All of them
are involved in a self-learning group on smartphones, showing their interest in the use of their
smartphones. Participants meet weekly at Àgora, a highly participatory, lifelong-learning
community, to share their knowledge about smartphones, to express their doubts and con-
cerns, and to learn new things from their others. Àgora is committed to strengthening the so-
cial inclusion of older people and immigrants in Barcelona (Catalonia, Spain) by providing
them with free courses on a wide range of areas, such as Internet and languages (Sanchez Aro-
ca, 1999).
Three researchers, two of them the authors of the paper, conducted the focus groups. To
answer the research question, the outline of the conversations included four issues: a) partic-
ipants’ history with smartphones, b) What do they use them for? c) Where do they use them?
and d) When do they use them? Focus groups were voice recorded for further transcription.
The authors listened to the audios, read the transcriptions, and discussed the more prominent
topics in order to make a thematic analysis (Braun & Clarke, 2006).
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Description of the data set
As we discovered, our participating panelists accessed 2247 different apps on their smart-
phones during the tracked month. We used OpenRefine to identify different versions of the same
app and group them under the same label, e.g. “Facebook” and “Facebook for HTC” were la-
beled as Facebook.2 In this paper we focus on the number of accesses, the time and day of ac-
cess, and the type of connection (Wi-Fi or mobile data) used when the app was accessed.
For analytical purposes we have categorized the mobile apps in the sample. To optimize
the research effort, we have reduced the number of apps to be categorized by applying three
non-exclusive criteria to select the most used apps, namely the number of users, the number
of access and the mean time of use during the tracked month. In each case we have included
the top 300 apps. In terms of users, the app in the 300th position had 4 users while the top app
had 233 (WhatsApp); in terms of accesses, the 300th app had 88 accesses while the top app
had 188.911 accesses (WhatsApp); and in terms of average length of session, the app in the
300th position accounted a mean time of 2:57 minutes of access and the app in the 1st posi-
tion accounted 60 minutes (Clean). The resulting set of apps represented 30% of the accessed
apps (675 out of 2.247) and accounted for 97% of accesses among the sample, and for 98%
of the time spent by the 238 panelists in their tracked devices.
Table 1 collates our classification of mutually exclusive categories. The 675 apps were cat-
egorized using an iterative and open form of thematic analysis (Braun & Clarke, 2006). Three
researchers participated in the three-iteration process that used the name of the app and its
description. For those apps related to more than one category we chose the most relevant cat-
egory to allow for a univocal taxonomy. While previous studies have used adaptations of the
app store taxonomy (Böhmer et al., 2011; Carrascal & Church, 2015; Xu et al., 2011) we cre-
ated an app taxonomy taking into account both the multimodal mass media and the interac-
tive, horizontal networks of communication built around the Internet and wireless
communication provided in the context of “mass self-communication” (Castells, 2009, p. 4).
For the analysis we focused on a selection of categories deemed relevant to the topic of
our study, a generational comparison of online activities. We did not include System and Mar-
ket research tools in our further analysis, as they mostly constitute activities the mobile de-
vice does by itself, or are not the users’ intended activity. For instance, launchers (part of the
system category) are accessed every time the user accesses the device, but usually the pur-
pose is to open another app. In addition, we excluded eBooks and Health & Fitness categories
due to their limited number of users.
Results
Given this data, we can now discuss how smartphone use is different – or not – for older
participants and why particular smartphone apps are relevant to the participants in the three
focus groups. We contrast most significant results of the generational tracking study, mainly
in terms of app access with the experiences reported in the focus groups, in terms of specif-
ic uses (what?) and routines (where?) participants use their smartphones in order to better
understand this data.
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Table 1. Categories of mobile apps and their description, by alphabetical order. Num ber
of users and number of apps in each category
34 Revista românã de comunicare ºi relaþii publice
Category Users Apps
Bank 72 9
Financial corporations’ apps.
Browsers & Searchers 208 10
Internet browsers and search engines.
Device Management 220 52
Tools for management, improvement, and optimization of the smartphone (antivirus, app managers, battery savers
and cleaning systems, amongst others).
eBooks 34 8
Apps to read and/or download eBooks.
Email 187 10
Apps to manage email, such as Gmail, email (for Android), or Yahoo.
File Management 206 20
Tools for managing files inside the smartphone or with other devices, such as Gallery or Dropbox.
Games 145 171
Games and gambling apps.
Health & Fitness 31 9
Tools to manage data related with health & fitness, such as sport trackers and calorie counters.
IM, Voice & Video Calls 237 20
Apps for instant messaging, phone calls, video calls, SMS or MMS.
Market Research Tools 9140
Apps to participate in surveys and market studies.
Mass Media On Demand 167 34
Mainstream audiovisual contents on demand, with the exception of appsincluded in the Radio & TV category.
Media Creator Tools 175 27
Tools for media creation including the camera, voice recorders and apps to edit pictures.
Personal Information Managers 205 28
Tools to manage personal information, namely calendars, contacts, notes, etc.
Personal Interest Content 125 43
Apps with personal interest contents including catalogues, loyalty programs and scoreboards.
Personal Tools 220 88
Utility tools of general interest including bar codes scanner, tools to download media, flashlights, GPS, educational
apps, maps and dictionaries.
Press & Weather 116 23
Mainstream press and weather apps.
Productivity Tools
Tools for professional performance, including Office Mobile or Polaris Office.
Radio & TV 68 12
Mainstream radio and TV channel apps.
Shopping 78 24
Apps mainly devoted to sales.
Social Network Sites (SNS) 225 25
It includes general and specialized social networks sites as well as social curator systems.
System 37 219
Launchers.
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Older panelists accessed less often their smartphones than the rest. However,
it is a central part of their lives.
Our panelists access their smartphones 100 times a day on average (outliers excluded).
While the number of accesses per day are negatively correlated with age; that is, the older
you are the less times you access your phone (r = -.148, p < .05, n=234, see Figure 1). How-
ever, the focus group participants demonstrat how embedded smartphones are in the every-
day lives of all of the panelists, and the central role they play, as comments from two of our
oldest participants illustrate: “Except for [cooking] fried eggs, I use it [the smartphone] for
everything” (Woman, 70). “I almost don’t use the computer now; I do everything in my smart-
phone” (Man, 78). Indeed this type of response is made by panelists who were initially re-
luctant to have a smartphone, or relayed a strong discourse against mobile phones overuse,
e.g. “The smartphone was a gift from my husband (Aged 60) who was tired of me not having
WhatsApp” (Woman, 60). She complains about his excessive smartphone use “Does it only
happen to me, that you are talking with somebody and then he gets distracted by his What-
sApp and you end up talking with nobody?” (same Woman, 60). So, while she is both a re-
luctant adopter, and is critical of the smartphone, she has become an active user who accepts
its centrality within her everyday routines and rituals: “You see, I have no problem if you
show me the picture of your grand children during a dinner with more friends” (same Woman,
60). The smartphone is also expressed as a central part of the everyday life of participants who
report turning off their device when they are at home (Man, 69). Even these participants pre-
fer to have it at hand and admit that they check it from time to time (Man, 75), or keep the
smartphone close to them so they could use it whenever it was needed (Woman, 81).
Figure 1. Mean accesses a day by age break. N=234 (4 outliers excluded).
Beyond WhatsApp: Older People and Smartphones 35
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Communicating and socializing via WhatsApp: what the panelists do on smartphones
According to the generational tracking, the three most accessed app categories are IM &
Calls (35,2 accesses per day on average for the whole panel sample, and 23,7 for the older
age group), SNS (10,9 and 9,0) and Browsers (9,8 and 5,8) - see Figure 2. WhatsApp is the
most accessed app (as discussed above), with an average of 26,4 accesses per day (16,9 among
the older panelists). This could be due, in part, because in Spain where this study took place,
it is common to have to pay extra for each text message, while having a small mobile data
package is cheaper. In this sense, WhatsApp is seen as a cheap communication service.
Figure 3 shows which app categories are comparatively more popular among the four age
cohorts. It gathers the age distribution of active users in each app category, measured in terms
of average accesses per user. We are able to identify statistically significant differences for
some categories of apps. On one side, there are three categories that show negative correla-
tion with age, meaning that accesses decrease with age: IM & calls, SNS and Mass media on
demand (r =- .243, p < .001; r = -.138, p < .05; and r =- .155, p < .05 respectively). On the oth-
er side, two apps categories show an increase of use with age: Press & Weather and Personal
Information Manager ( r = .189, p < .01; r = .112, p < .1 respectively). In addition, we observe
another app category that is comparatively more popular among panelists between 60-76 years
of age compared to young adults and adults (ANOVA test, p < .05 in both cases).
Figure 2. Mean accesses day by category. All panelists and Older panelists compared.
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Figure 3. Age distribution of active tracked panelists by app category, in terms of mean ac-
cesses by individuals. (Active panelists are those with one or more access to a given category.)
*Statistically significant differences among age groups.
Communicating and socializing within the budget: what is relevant,
according to focus group participants
WhatsApp is a very relevant app, as it is always associated to a flat rate bill, it has no lim-
itations and is cheaper than phone calls or text messages (SMS): “I use WhatsApp extensive-
ly, as I have a limited number of phone calls a month” (Man, 55). Indeed, participants report
that they tend to restrict heavy media consumption when using their mobile data plan in or-
der to control their budget. Otherwise they do not care about the use of other services with
mobile data if they are not that heavy in terms of data consumption. “I don’t watch YouTube
videos, because it consumes my data plan, unless I have Access to a Wi-Fi connection. If I
have Wi-Fi I watch YouTube videos” (Man, 68). Thus, the combined use of traditional voice
calls, with text messages and video calls, is influenced by flat rates and the relevance of each
communication interest. In fact, phone calls are mostly used to access close personal net-
works, which includes relatives and friends. “I have a family group in WhatsApp, but I pre-
fer to call my daughter when I want to talk with her” (Woman, 70).
In addition to being restricted to contacting those who are in a close personal network, voice
calls are used for urgent or relevant issues that require an immediate answer. “A WhatsApp is
not an important call” (Man, 55), while “[a] phone call urges more” (Woman, 76). Finally,
Skype and other video call systems are mostly used to talk with close relatives living abroad:
I use Skype to talk with my daughter who lives in Morocco, while my grandchild [who lives in the same city]
calls me through Hangout, I did not know Hangout, or how it works, but they manage to call me (Woman, 77).
WhatsApp is used to keep in touch either with close or extended personal networks, help-
ing to maintain and reinforce both strong and weak ties. WhatsApp groups play a role in these
dynamics. In this sense, groups with family, friends or peers are common, and they can be
either local or transnational. Groups allow participants to be in touch with relatives who are
far from distance; “We have a family group, and this way my son in Australia is up to date
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on the family issues, and I do not have to update him” (Woman, 70). Finally, it is also wide-
ly used for social entertainment:
I think it is a tool to bring joy to people [A woman interrupts to say “Yes, I know it”] to break monoto-
ny. Whenever I receive a nice WhatsApp, I forward it immediately, I want others to enjoy it. I do not want
to be the only one who can enjoy it (Woman, 81).
I have a lot of fun with WhatsApp (Woman, 76).
Personal and social concerns over time
Despite its pervasiveness, IM is not exempt from personal concerns or social controver-
sy. Participants report controlling their own access to WhatsApp. Participants speak of situ-
ations in which others either had limited face-to-face interaction because of the immediacy
of WhatsApp or that WhatsApp had become a distraction from more relevant things: “You
cannot be all the day in WhatsApp” (Woman, 76). “I’m in two groups and I receive too many
messages, my wife asks me every time if it’s from our daughters, I have to check it to confirm
that it’s not them” (Man, 72).
As our data indicates, WhatsApp is both one of the main motivations for our participants
to get a smartphone and, at the same time, is the most polemic app. Yet, even highly reluc-
tant smartphone users admit that they end up using it:
I was initially reluctant to have a smartphone (…) I only use the smartphone when needed, and to check
all the rubbish people send through WhatsApp. (Man, 69 – ironic comment)
You know, I am anti WhatsApp but I see no problem to see somebody else’s grandchildren pictures in
the smartphone. (Woman, 60)
While participants described their experiences and enthusiasm for WhatsApp, they did
not have the same experience or opinions about Facebook. Most of participants report using
this Social Networking Software on their smartphones but only a few of them had experiences
to share during focus groups. One woman reports that Facebook allows her to “get back in
touch with old friends from Colombia” (Woman, 69). Another male participant is dissatisfied
with the use of his image on Facebook “I have seen pictures of myself in Facebook, and I
don’t agree with it” (Man, 78). Other participants did not report using other SNS in their
smartphones, even though some of them use Moovit – a public transportation SNS. They do
not use the social features of this app or Endomondo.
This disparity between the number of accesses of these apps and the short-lived enthusi-
asm that the participants in our focus group had for these particular apps could be because
the tracking of panelists and the focus group selection involved a different cohort of individ-
uals. However, in the focus groups, participants expressed an ambivalence that is worth not-
ing. While they have and may use the Facebook app on their smartphones, they are not
necessarily enthusiastic about its presence on their phones or in their lives.. It is possible that
for these participants, Facebook’s novelty has passed, it is already integrated in the everyday
routine, and other tools are more central. In a discussion of the novelty-factor of WhatsApp,
one participant reports “In the beginning you laugh a lot, then you get used to that and you
can’t be hooked all day” (Man, 55).
A similar ambivalence for the use of particular apps on the smartphone surfaces in dis-
cussions of email, an app that all of the participants have on their smartphones. On the one
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hand, participants appreciate the possibility of receiving and reading emails at any time; on
the other hand, most of them wait to answer emails at home as the computer’s keyboard and
the screen are more comfortable. While some report their efforts in dealing with uninterest-
ing emails, such as junk mail, others report using email to send “interesting” contents to their
friends, such as PowerPoint presentations with pictures or jokes (Man, 76a). Another partic-
ipant uses his Gmail account on the smartphone as Gmail is used by his inner circle. This tac-
tic allows him to automatically avoid receiving irrelevant or uninteresting emails on the device
(Man, 76b). Finally, another participant reports using her smartphone to filter uninteresting
emails before moving to the computer to go further with the interesting ones (Man, 64).
Calendar, Weather and Games. Other smartphone uses
The tracking study indicates that Personal Information Management apps are used more
frequently as we age. Similarly, focus group participants report the extensive use of notes
and calendars as memory aids. Some participants use reminders on the smartphone. The man-
agement of doctor’s appointments by those following a strictly controlled medical program
surface in the focus groups as do other uses of notes and calendars as a part of daily or week-
ly routines: “I use the calendar to remember medications, and doctor appointments with
notes” (Man, 55). “I do the shopping list [in the smartphone” (Woman, 77). The specific
app used to remember things is a personal choice for the execution of everyday activities.
Amongst participants who rely on mobile apps, some prefer the calendar to remember an ap-
pointment while others prefer notes: “I don’t use the calendar, I use notes to remember ap-
pointments and other things” (Man, 69). Finally, others reported that they prefer to use a
paper-based calendar, or – for medical appointments – to rely on the doctor to call you the
day before (Woman, 76). Some describe the use of such apps as a challenge they want to ad-
dress, even if they do not need reminders or they are not going to use them for relevant things.
In other words, we find that Personal Information Management tools are important to some
older participants as they assist them in remembering dates, tasks and other items “to-do” ,
while for others, these tools symbolize the fun of learning something new, even when “tra-
ditional” systems are positively evaluated. As one participant put it: “I don’t use the calen-
dar, I trust this [putting his forefinger in his head]” (Man, 73).
While Device Management apps are not particularly relevant for older panelists, partici-
pants in our focus groups report the frequent use of these apps. These apps are particularly
important for those possessing phones with limited storage space or battery issues. The use
of these apps is mainly pushed to the user by notification systems. The cleaning systems, par-
ticularly Clean Master, were appropriated by participants who identify it by way of the broom
metaphor, the icon that identifies the app: “I use the broom every day” (Woman, 81). “I use
it when there is a notification about it” (Man, 55). The use of this app is influenced by the
learning community to which these participants belong, as they had discussed this topic to-
gether shortly before the focus groups. Although participants rarely report using browsers di-
rectly, some of them use the phone to search and their use of apps related to their personal
interests, such as recipes, poetry, history: any topic inciting curiosity.
I use it for inquires while reading, I like Spanish history so I see videos in the smartphone. Then, I like
poetry and in the smartphone you can see the meter in a verse. (Man, 78)
I use it to follow the football match abroad (…), and I use the app Seient Lliure [to manage his football
season ticket]. (Man, 76b)
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I check the movie listings. (Woman, 70)
In line with the tracking study, where News & Weather apps are more popular as age in-
creases, weather apps are popular among participants. One participant, who is very reluctant
to have a smartphone, uses a weather widget in his device (Man, 69). Yet, few participants
read the news on their smartphones: “In the morning I read the newspaper, Sports, and El
Periódico” (Man, 76b). “I use it to read the headlines in ‘El País’ and other newspapers”
(Woman, 70).
Finally, games on the smartphone are not that popular among the participants, although
those who do play games are quite active. Instead of playing games on the smartphone, most
participants play games on the computer, or the tablet because of the bigger screen. Partici-
pants describe how playing games on different devices are a part of their routine: “I play
Rummikub on the tablet; whenever I can’t play I log in the app [at least] to obtain the daily
credits” (Woman, 77). Beyond the mere fun of the activity, games on the phone are useful in
alleviating boring situations and periods of waiting: “You can spend half an hour in the doc-
tor’s waiting room, and it is a pastime” (Woman, 55). Games are described as a way to build
links with grandchildren: “My grandchild asked me to download a game, War of clash, and
then I was hooked because it is addictive, we also exchange things in the game, with my
grandchild” (Man, 68).
Different routines amongst older participants
In the focus groups we asked participants to reflect on how they use their smartphones and
how they manage their device’s connection. The initial discussion tended to focus on the use
of the smartphone outside the home, in the streets, when some information was needed, such
as getting in touch with somebody or for practical purposes such as looking for an address:
“I use it outside, when looking for a place, and this way I don’t get lost” (Woman, 76).
While this would explain the extended use of Personal Information Management apps,
Media Creator tools, and Health and Fitness apps through mobile data access, this discussion
ignores many of the above-described uses of smartphones, which include entertainment, emo-
tional support, social interaction with an extended social network, expressive uses, or its use
for non-urgent matters connected to daily life. In the focus groups, it was commonplace to
talk about using the phone outside of the home. We needed to prompt further conversation
around other locations of use and whether the use of these locations was habitual or not. For
example, some participants did not take their mobile phones out when going to a social event,
or when going to the cinema, the theatre or other events. In contrast, others turn their phones
on silent when they arrived home. Still others explain using the phone when needed, which
means having it close to them all the time so that they are able to receive notifications. Oth-
ers discuss having the device accessible to check notifications, regardless of whether they are
at home or outside, with Wi-Fi or with mobile data:
I use it more at home, because of WhatsApp, and because of having the family abroad. (Man, 64)
I use it when I need it. (Man, 78a)
I have it always with me. (Man, 76a)
At home I always leave the phone on a table; from time to time I check it, because I can’t hear it. (Man, 75)
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This became an important insight into a key difference between difference age groups:
where data is accessed and how it is accessed. Smartphones work with two different types of
internet connection: Wi-Fi and mobile data. Significantly, amongst all panelists with Wi-Fi
and Mobile data connection, Wi-Fi is more commonly used to access apps than mobile data
connection (56,3% of accesses, ahead of 43,6%).3However, older panelists (60 to 76 years
old) rely more on mobile data. This cohort use more mobile data than other age group (50,1%
vs. 43,6%) and use mobile data as much as Wi-Fi (50,1% vs. 49,9%). The question is why.
All participants in our focus groups have a mobile data plan, and all but one participant
has Wi-Fi at home. Those who have it at home always use their Wi-Fi connection when at
home, and most of them use Wi-Fi in places they visit frequently, such as their children’s
house, where they know how to connect and they are sure that it is reliable: “I use Wi-Fi in
my everyday places, where I already have the password and it connects automatically, oth-
erwise I use the mobile data” (Man, 76a). “For the half hour you are going to be in a bar
there is no need (to connect to the bar’s Wi-Fi)” (Man, 69). Joining any and all networks, just
to connect for a short or temporary period of time, is not perceived as a desirable option. Pub-
lic Wi-Fi accesses, however, is relevant when on a trip abroad or for accessing public Wi-Fi
while travelling. However, in Barcelona the use of public WiFi connections are not a com-
mon practice for the following reasons:
I use Wi-Fi at home, in my son’s house, in hotels and abroad in some airports where you can find free
Wi-Fi. (Man, 76b).
I don’t even try to connect to public Wi-Fi accesses, except when I’m on vacations. (Man, 73).
Here [municipality’s open public] Wi-Fi is that slow, I prefer not to use it. (Man, 76b).
In summary, participants use Wi-Fi at home, while visiting familiar locations, or during
longer vacation-style trips. Otherwise, this group of over-seventies report that they prefer to
use their mobile data connection in other places, while commuting, in non-habitual places,
or in habitual places where they do not find it worthwhile to make the effort of accessing the
Wi-Fi because it is for too short a period of time or is likely to be too slow.
Discussion
To return to our main research question: What are the specificities, if any, in the use of
smartphones by older adults? We have discussed how, in this case study, a combination of
qualitative and quantitative data may contribute to a nuanced generational analysis of how
changes in interests throughout the life course influence and impact the communication prac-
tices and use of mobile media technologies, such as smart phones, amongst older users. We
now return to these findings.
Validity of quantitative and qualitative results
Similar to previous results (Böhmer et al., 2011) our data indicates that IM & calls are the
most accessed apps with a lower use among the older panelists (60-76). Even though it is al-
so the most accessed app for all age groups, an easy conclusion would be that for older pan-
elists, IM & Calls is comparatively less important than for younger generations. If we accept
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this reasoning, we tacitly are assuming a common normativity: the higher the use of a given
technology or service, the better. Yet, discussion groups allow us to understand how impor-
tant WhatsApp is for participants, who describe both (micro) coordination and expressive us-
es. They also explain non-dependent uses of the phone and describe a set of issues around
the inappropriateness of using WhatsApp e.g. at some hours of the day or to send some type
of contents.
We find an important disparity between the number of accesses to some apps, most no-
tably social networking apps, in the tracking and the descriptions by participants in the focus
groups of their sense of the importance of these apps. Consistent with older peoples’ interest
in social networks (Righi, Sayago, & Blat, 2012), it is not surprising that these were the sec-
ond most often accessed app category, in general for all panelists, and more specifically for
older panelists. However, despite their frequency of occurrence in the log data, participants
do not report using them with enthusiasm, have few experiences to share and convey little
explicit interest in learning more about them. Despite the frequency of appearance of social
networking apps, when we probed further, these apps are less important that we initially
thought. Beyond the concerns of older people about social network sites (ibid), it seems that
the social network sites they use are not a novelty anymore. Even though all participants use
them, they do not constitute a topic of conversation. When an ICT becomes a part of every-
day life, there might not be that many new anecdotes to put on the table. Conversely, What-
sApp could be seen as a trending topic with more issues to discuss and resolve, such as
use-norms. Therefore, it seems that conversations might focus primarily on specific ICTs but
not on all of the ICT individuals use in their daily lives.
Beyond age stereotypes, personal interest change throughout the life course
The generational analysis of the data indicates how smartphone use changes throughout
the entire life course and how this might influence the results of studies that do not consider
the age of participants. Similar to previous studies (Nylander, Lundquist, & Brännström,
2009), our data suggest that users make more application accesses at stable locations with Wi-
Fi (56,6% of accesses) than in other places with mobile data (43,6% of accesses), similar to
previous findings by Castells et al., 2006. However, given the slight differences between WiFi
and mobile data accesses, and the time spent by people at a stable location or somewhere else
(Giddens, 1987) it is striking that proportionally, our panelists use the smartphone more out-
side of their stable locations than we anticipated, and that older panelists use mobile data on
the smartphone when they are outside of the home, more than they used a WiFi connection.
In addition to the greater use of mobile data among older panelists than the rest of the
panelists, participants often reported their preference for using alternative devices, such as a
tablet, computer, TV or fixed phone when possible. The screen size of tablets, the comfort of
personal computers, and the ubiquity of smartphones are some of the arguments supporting
a position that encourages a wider ecology of media (Hearn & Foth, 2007) at home. As well,
specific content might be available only on one of the devices. In other words, making less
application accesses on the smartphone does not mean that older adults use ICTs less often,
but that they prioritize ergonomics when choosing the ICTs to be used at home.
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Conclusion
The aim of this paper has been to analyze the use of smartphones by older adults by put-
ting quantitative and qualitative data on smartphone usage into conversation: log data that in-
dicates general patterns of usage and focus group data that helps to understand usage patterns
from the perspective of the users’ reported experience. While this approach is not new, the
novelty of our study lies in our addition of an age-related dimension to the research. We high-
light the relevance of generational studies, showing some of the nuances of smartphone use
by different age groups. Without a generational analysis, smartphone use-studies and predic-
tive systems miss the particular interests of older people potentially excluding them from fu-
ture technology developments.
The paper has examined two dimensions of smartphone use, namely specific uses (what)
and routines (where). First, in terms of specific uses we observe that Instant Messaging (IM),
particularly WhatsApp, is one of the most prominent services being used by our older pan-
elists. These older panelists access personal information manager apps (calendar, address
book and notes) more often than other age groups. Second, regarding routines, focus group
participants explain how location shapes their connection decisions – Wi-Fi or mobile data –
and the ways that they try to make the most of their data plan. Older participants’ discourses
highlight the practical uses they make of the mobile phone in public places and the confine-
ment of social network sites, gaming and media consumption to private spheres and, there-
fore, to the use of a Wi-Fi connection.
From a generational perspective, we find differences in smartphone use-patterns in terms
of specific uses and places of use. Such differences seem to reflect the evolution of personal
interests and communication patterns as we grow older (B. L. Neugarten, 1996). Empirical
evidence emerges from the basic analysis of tracked data while the discussion groups bring
insights on these results. In this, the combination of methods helps to assess the validity of
the log data. The dialogue between quantitative results and qualitative discourses we have pro-
posed in this paper clearly enriches the interpretation of tracked data and also the interpreta-
tion of qualitative data. In addition, we adopt a special focus on older people and a generational
approach, that includes generational recruitment and analysis. Empirical evidence on the prac-
tices of older people in this area are in need to contest the stereotypes and ageist attitudes that
are commonplace.
This study is admittedly a historical one (Uprichard, 2012) and it has limitations. Indeed,
both the tracking data and the focus groups include older active users of smartphones, which
does not represent the majority of the older Spanish population. There is a clear auto-selec-
tion bias as a consequence of volunteering to participate in the two studies. However, partic-
ipants in the focus groups means that the sample includes old and new smartphone users,
those who chose to have a smartphone or who were given one as a gift, and users who range
from engaged users to reluctant users with different levels of appropriation and uses of their
smartphones in their everyday life. In addition there are not any panelists aged over 76 or fo-
cus group participants aged over 81, who have contributed to this study. Similarly, the track-
ing sample of older people is too small to perform some statistical tests. As well, these results
might be influenced by the fact that tracked individuals belong to a market research panel,
and that focus group participants take part in an educational group on smartphones. Diverg-
ing from other studies, our case study involves different participants in the tracking and in
the focus groups. While this can be seen as a limitation, we consider the discussion with old-
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er people and the results of the generational tracking relevant as they provide rich and in-depth
insights for future research.
Acknowledgments
We thank the participants in the focus groups for their invaluable contribution. Lluís Teix-
idó Seix contributed in different stages of data processing, in the construction of the taxonomy
of apps, and gave support during qualitative fieldwork. Daniel Blanche conducted one focus group
and helped in transcriptions. The authors are indebted to all participants who took part in the
studies and acknowledge the support from the ACT Project 895-2013-1018, funded by the So-
cial Sciences and Humanities Research Council of Canada, which partially funded this project.
Notes
1http://realitycommons.media.mit.edu/realitymining.html (accessed 06/06/2015).
2https://en.wikipedia.org/wiki/OpenRefine (last accessed 15/06/2015).
3Average accesses per day ascends to 64,1 (SD=2,9) for Wi-Fi, versus 49,6 (SD=3,3) for mobile data
(t(202) = 3,364, p < ,005).
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... Evaluating the impact of the peer-to-peer digital education course on smartphone using patterns To evaluate changes in smartphone usage patterns, we employ digital methods to collect data from participants' phone activities. Specifically, we will assess the actual use of the smartphone (Boase and Ling, 2013;Rosales and Fernández-Ardèvol, 2016;Kreuter et al., 2020;Stier et al., 2020), collecting smartphone usage data for about 4 months: (1 month) before the start of the course, during the course attendance, and (1 month) after the course has ended. Our aim is to empirically compare course participant usage patterns before and after the intervention, monitoring the advancements achieved in the meanwhile. ...
... As previously mentioned, such information will provide objective evidence on smartphones' use by participants, as shown in several studies (Boase and Ling, 2013;Rosales and Fernández-Ardèvol, 2016;Kreuter et al., 2020;Stier et al., 2020). It is important to clarify that by no chance it will be possible to access the content of the activities performed on the apps' categories. ...
... The https://sensortower.com/ app usually is used by users as a self-monitoring tool for measuring own activities on devices and improving self-management. As happened in other contributions (Rosales and Fernández-Ardèvol, 2016), we have repurposed the affordances of the app for academic research purposes. The data will be supplied to us by the company at three different moments: midway through the course, at the conclusion of the course, and 1 month after its completion. ...
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The digital transition poses relevant challenges and opportunities for older adults in aging European societies. To unleash the potential of the digital transition in old age and avoid the risk of exclusion, digital education for older adults seems to be a valuable solution. One of the most suitable approaches to digital education for older adults appears to be the peer-to-peer approach. However, not much literature is available on this topic. Within the ACTIVE-IT project, we aimed to design, implement, and evaluate a digital peer education course for older adults, focusing specifically on the use of smartphones and daily utility apps, such as mailing, e-Gov, and e-commerce. The purpose of this contribution is to document the protocol adopted to evaluate the course. The course involved 32 participants aged 65 or older, who, between March 2024 and June 2024, divided into three groups, attended a 10-lesson weekly course taught by a peer. We aim to measure the effect of the course on participants' digital skills and their perceived wellbeing. To do so, we will adopt a mixed methods approach, employing: digital methods by collecting and analyzing data on participants' smartphone use (i.e., log data on smartphone use before/during/after the intervention); a quasi-experiment, collecting information on course participants' wellbeing before/after the course attendance using a questionnaire survey; ethnographic observation conducted during the course, observing interactions between subjects during the course. The study has been approved by the Ethic Committee of the University of Milano Bicocca (prot.nr. 167541/2024).
... In other countries, Rosales found in Spain that WhatsApp is currently the most popular application used by people of all ages, including older adults [42]. Hämmerle conducted a qualitative study with 30 older adults (65+) in Switzerland, that already use WhatsApp in the last 3 months. ...
... Despite the fact that the use of e-commerce chatbots are associated with the young people use with the most cited literature concentrating solely on youth as the only study group [20,35,43], or hypotheses showing that there is greater risk in the use of e-commerce chatbots by users with low experience in using mobile shopping applications [25]. The results of this paper suggested that a WhatsApp e-commerce channel reinforces conversion rate among adults and older adults connecting with this demographic group as other channels of the same product cannot achieve, this results had already been obtained in academia for WhatsApp use [29,42]. ...
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This study examines the effectiveness of a WhatsApp e-commerce chatbot, integrated with agent support, implemented for The Coca-Cola Company (TCCC) in the Mexican market. The engineering process, chatbot design, development , and the expansion of this concept to a global chatbot orchestrator are discussed. Using Google Analytics, data from 2022 is analyzed, focusing on specific demographic segments and comparing the chatbot's performance with its web-based counterpart. Findings reveal a counterintuitive result: the WhatsApp e-commerce chatbot appeals to adults-older adults (+45 years) and females consumers for FMCG, Food and Beverages category, leading to higher conversion rates than the conventional web channel for this groups. Results suggest that managing a botview and web channel independently allows for tailored optimization strategies for each demographic segment. Chatbot surpassed its web-based counterpart in e-commerce total revenue contribution in 2022, in the market with the highest penetration of the Coca-Cola brand globally, becoming the primary reference channel for consumers. This study proposes that WhatsApp chatbots have the potential to become an established om-nichannel reference for e-commerce.
... As of September 2022, WhatsApp had over 2.4 billion users globally (Iqbal, 2024), outpacing instant messengers like iMessage, WeChat, Telegram, Viber, LINE, Signal, and others. Malaysian (Kamal et al., 2014), Italian, Slovenian (Taipale, 2019), Finnish (Hänninen et al., 2021;Taipale, 2019), Spanish (Rosales & Fern andez-Ardèvol, 2016) and Swedish (Eklund & Sadowski, 2023) users, older and younger, reported that their participation in a WhatsApp family group helped them to bridge distances, reconnect, and maintain intergenerational closeness, and to refresh and reactivate family relationships. In this paper, we present the Israeli Jewish family members' experiences and practices of maintaining a three-generation WhatsApp family group (WFG) by defining boundaries, using communication rules, and assigning roles. ...
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Objective This qualitative study analyzes communication practices, roles, and rules developed by family members while participating in a three‐generation WhatsApp family group (WFG). Background Although instant messaging applications such as WhatsApp have become increasingly popular with families worldwide, study findings of the digital family formation process, roles, rules, and family communication styles have remained fragmented. Combining the rich familism ideology with technological skills makes the Israel digital family a good study case. Method We conducted 43 semistructured interviews with WFG participants representing three generations of Jewish Israeli families. Results All WFGs were organized in the form of a three‐generation family tree, including one or a couple of older people in the core and a significant number of their younger relatives in the upper tree levels, where WFG membership was used as a marker of family belonging. WFG members played roles of kinkeepers, flickerers (rarely commenting participants), and silent warm experts. WFGs used two rules for communication—problematic discourse avoidance and exaggerated writing style—and two strategies for enforcing those rules—temporarily excluding rule breakers from the general group or ignoring messages of offending participant(s). Conclusion Maintaining the WFG is not a single initiative but a collective, well‐coordinated endeavor of all family generations, which helps to include grandparents in the digital family, gives WFG participants a sense of family belonging, and reproduces the image of the untroubled family. Implications The research findings can be helpful for educators, family therapists, social workers, and social policy professionals. Moreover, the study's results can benefit families who want to open WhatsApp family groups.
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Este é o quarto volume de uma coletânea produzida por um grupo de professores e alunos do Programa de PósGraduação em Ensino de Ciências e Matemática (PPGECIM) da Universidade Luterana do Brasil (ULBRA). A obra, intitulada Ensino e Aprendizagem em Ciências e Matemática: referenciais, práticas e perspectivas, apresenta resultados das investigações, discussões e reflexões à luz dos referenciais teóricos adotados nos trabalhos de pesquisa que têm sido desenvolvidos, aos quais se procura dar destaque. Está organizada em nove capítulos articulados, considerando as linhas de pesquisa do Programa: Ensino e Aprendizagem em Ensino de Ciências e Matemática, Tecnologias no Ensino de Ciências e Matemática, Inclusão e Formação de Professores, sendo que, o último capítulo, destaca aspectos metodológicos de processos de investigação. O primeiro capítulo trata das competências profissionais de um professor de Matemática, com foco na competência de Observar com Sentido, considerando-a fundamental para o exercício da profissão de professor. Salienta a importância da escolha de tarefas matemáticas para um planejamento didático de qualidade e como meio para o desenvolvimento da competência de Observar com Sentido, apresentando o exemplo de uma investigação com a temática Equações nos anos finais do Ensino Fundamental. As contribuições dos constructos da Etnomatemática e da Teoria Socioepistemológica da Matemática Educativa-TSME, as quais colocam em evidência o papel da Matemática e do seu ensino, na busca e consolidação de uma educação que valorize as manifestações sociais, culturais e produtivas de diferentes grupos de indivíduos são apresentadas no segundo capítulo, a partir da investigação produzida junto a uma comunidade indígena do Estado de Roraima. No capítulo três, é proposta uma reflexão sobre a importância da Educação Financeira, no currículo escolar, na perspectiva da Educação Matemática Crítica, partindo do entendimento que o currículo de Matemática deve abordar temáticas relevantes para a vida em sociedade, a formação do estudante e o desenvolvimento dos objetos do conhecimento. Destaca três pesquisas de Mestrado, as quais têm a Educação Matemática Crítica como pressuposto teórico. O capítulo quatro apresenta e discute os pressupostos teóricos relacionados com a metacognição, autorregulação e corregulação, bem como, suas implicações para o ensino de Ciências. A discussão aborda os principais aspectos conceituais da metacognição e autorregulação, o processo de corregulação colaborativa, revisão de estudos empíricos sobre a temática e apontamentos a respeito da metacognição e autorregulação no ensino de Ciências. A Cultura Digital e a Aprendizagem Criativa, no contexto do Ensino de Ciências, são caracterizadas no capítulo cinco, considerando que a inclusão de Tecnologias Digitais no ensino é uma possibilidade de transformar, qualitativamente, o processo educacional, tornando essas tecnologias potenciais para diminuir as desigualdades sociais. O foco da discussão é fomentar propostas educacionais para a formação da cidadania para a era digital. O capítulo seis aborda o que pode representar um desafio para os docentes no contexto de sala de aula, trazendo um olhar voltado não apenas à discussão das mudanças pelas quais a sociedade passa e como as novas tecnologias são incorporadas, mas, também, pontuando questões voltadas a conflitos de geração que tecem, certamente, novos caminhos que forneçam reflexões para a Formação de Professores para o século XXI. Uma reflexão sobre a formação do professor de Matemática para a Educação Básica, no cenário nacional, é o tema abordado no capítulo sete. Nele, são destacadas as implicações do percurso profissional (ciclo de vida profissional) no desenvolvimento docente e na construção de uma identidade profissional pautada em saberes que oportunizem a consolidação da autonomia necessária para enfrentar as exigências da profissão. O capítulo oito destaca a importância da adaptação curricular, no ensino de Ciências e Matemática, como estratégia para que os estudantes de inclusão tenham acesso aos conteúdos referentes ao ano escolar que frequentam, visando à sua compreensão, mas respeitando suas peculiaridades. São discutidos aspectos teóricos que envolvem a questão, sendo apresentados exemplos de adaptações curriculares já realizadas. Por fim, o último capítulo aborda o desenvolvimento de pesquisas com a utilização de imagens, escores e suas diferentes possibilidades, na metodologia denominada de S.I.M., Magnitude de Imagens por Escores (Magnitude of Images by Scores), dentro da perspectiva da Pesquisa com Métodos Mistos. O texto trata da construção da metodologia a partir do contínuo repensar de sua utilização, harmonizando percepções, concepções e mensurações com base em investigações produzidas no âmbito do PPGECIM. Carmen Teresa Kaiber Claudia Lisete Oliveira Groenwald Organizadoras
Article
Background Hand and foot eczema is a frequent chronic dermatological condition. The persistent itching, pain, and blistering can impair hand and foot function, leading to difficulties in performing tasks requiring fine motor skills. In addition, the impact on the quality of life for affected patients is significant, as the symptoms can be extremely uncomfortable and disruptive to daily activities. By incorporating digital health apps and educational programs into the management of hand and foot eczema, patients may receive ongoing support, optimize their clinical outcomes, and ultimately enhance their overall quality of life. Objective The purpose of this study was to evaluate the effect of a smartphone app combined with educational training on the clinical outcomes and mental health of patients with chronic hand and foot eczema during a 60-week study period. Methods Patients in the intervention group participated in an educational program focused on chronic hand and foot eczema at baseline and had in-person visits at weeks 0, 12, 24, 36, and 60, as well as access to our study smartphone app. The app allowed patients to upload pictures of their hands and feet and answer questions about pain severity, itching, mood, and quality of life. A chat function was also available for patients to contact their dermatologist. The control group received only the in-person study visits described above. Results A total of 87 patients were included in the study and randomized to the intervention (n=43) or control (n=44) groups. In total, 23 patients from the intervention group and 34 patients from the control group completed the study. Throughout the 60-week study period, a significant reduction in Hand Eczema Severity Index (HECSI) was consistently observed in all patients (week 60: linear regression coefficient [Coef]=–1.108; P≤.001). A trend toward a greater improvement of the HECSI in the intervention group compared to the control group was noticed (week 60: Coef=0.597; P=.05). Subgroup analysis revealed that patients who used the app with a usage frequency of less than 20% demonstrated a significant reduction in the HECSI from week 0 to week 60 (week 60: Coef=–1.275; P=.04) and a significant reduction in the Dermatology Life Quality Index (week 60: Coef=–1.246; P=.04) compared to the control group. We were able to demonstrate a significant correlation between the HECSI calculated based on pictures uploaded by patients through the app and the HECSI assessed during personal visits (ρ=0.885; P<.001), despite the potentially lower image quality of the pictures uploaded through the app. Conclusions This study provides further evidence that digital health apps can provide valuable support in improving patient clinical outcomes and management, especially as the app-based assessment of hand and feed images appears to be reliable. Trial Registration Deutsches Register Klinischer Studien DRKS00020963; https://drks.de/search/de/trial/DRKS00020963
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