<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Archiving and Interchange DTD v1.0 20120330//EN" "JATS-archivearticle1.dtd">
<article xmlns:xlink="http://www.w3.org/1999/xlink">
  <front>
    <journal-meta />
    <article-meta>
      <title-group>
        <article-title>Do I Need IT? Russian Pensioners' Engagement with Information and Communication Technologies</article-title>
      </title-group>
      <contrib-group>
        <aff id="aff0">
          <label>0</label>
          <institution>Novosibirsk State Technical University</institution>
          ,
          <addr-line>Novosibirsk, Russia 20 Karl Marx pr., 630073, Novosibirsk</addr-line>
          ,
          <country country="RU">Russia</country>
        </aff>
      </contrib-group>
      <pub-date>
        <year>2020</year>
      </pub-date>
      <fpage>0000</fpage>
      <lpage>0002</lpage>
      <abstract>
        <p>Digitalization of industry and everyday life leads to the need for wider adoption of information and communication technology (ICT) skills. Although today's education does focus on IT competences, they were largely inaccessible for the people who are now nearing the retirement age or older. Correspondingly, only about 1/3 of people from this demographic group report the mastery of even basic IT skills, which suggests that the notorious age-related digital gap still persists. Meanwhile, competence in IT is required for both more successful and flexible employment (which is particularly important in the light of the pension reform ongoing in Russia) and for continuous usage of computerized cognitive training (CCT) programs. In our paper we study IT competences in pensioners and people approaching the retirement age and report the results of two surveys that we ran with a total of 295 elder participants. Our results suggest that in the socially active group of seniors the reported computer usage is comparable with more traditional household and dacha-related activities. In the general population, however, people aged 50 and over show relatively little interest towards improvement of their IT skills. We outline some measures for greater engagement of pensioners with ICT, which can ultimately contribute to long-term improvement of their cognitive functions and preventing age-related dementia.</p>
      </abstract>
      <kwd-group>
        <kwd>Human Resources</kwd>
        <kwd>Social-Economic Status</kwd>
        <kwd>Cognitive Status</kwd>
      </kwd-group>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>Introduction</title>
      <p>The gap between different generations’ knowledge and skills remains significant even
as the world is supposedly becoming “flat”. With age, it becomes more challenging
for people to accept novel things, to remain flexible, to reject methods and techniques
that used to be effective in the past. Meanwhile, the number of retired people in
Russia is increasing: prior to the pension reform in 2019, the average growth was 1% per
year and the total number was approaching 50 million people. Correspondingly, the
studies of employment and work activities in elder people are gaining extra
momentum in advanced countries, as life expectancy and the share of seniors in the
population are increasing in all of them.</p>
      <p>Copyright ©2020 for this paper by its authors.</p>
      <p>Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).</p>
      <p>
        Information and Communication Technologies (ICT) are widely recognized as
effective means for supporting physical well-being in elder people, but the cognitive
aspect should not be underestimated also. Some researchers see ICT as the instrument
for broadening the horizons, acquiring new skills and seeking new interests [
        <xref ref-type="bibr" rid="ref1 ref2">1, 2</xref>
        ].
The others emphasize the need in overcoming technical difficulties and accessibility
of various forms of network interaction (e.g. e-communication for medicine,
education, etc.) [
        <xref ref-type="bibr" rid="ref3 ref4">3, 4</xref>
        ]. There is actually ongoing discussion whether the impact of ICT on
elder people’s health is ultimately positive, as the negative effects include for instance
increased stress [
        <xref ref-type="bibr" rid="ref5 ref6">5-6</xref>
        ].
      </p>
      <p>
        In any case, the ubiquitous development of ICT led to the diffusion of the related
IT competences, in both work activities and at home. But age is generally negatively
correlated with ICT competence level, although the latter is also affected by the
culture, education, IT infrastructure, economic environment, and other factors. Greater
adaptation of elder people to the new technologies would let them maintain their work
abilities (which are increasingly vital in the light of the pension reform in Russia) and
improve the general quality of life. Moreover, computerized training can help in
saving cognitive functions and preventing age-related dementia: numerous data related to
the cognitive training of information selection speed, various components of attention,
memory, and their comprehensive enhancement programs suggest not only
shortterms effects of training, but also long-term improvements. The latter are
accompanied by the structural and functional changes in the cortex and hippocampus, as well
as changes in the activity of the mediator systems of the brain, which leads to
adjustments not only in the cognitive, but also in the emotional state [
        <xref ref-type="bibr" rid="ref7 ref8 ref9">7-9</xref>
        ]. The leading role
of behavioral and social factors is highlighted by the findings about positive effect of
cognitive training combined with aerobic training of physical activity [
        <xref ref-type="bibr" rid="ref10">10</xref>
        ]. The
protective effect of such training is also supported by the data of genetic, bio-chemical
and Magnetic Resonance Imaging analyses.
      </p>
      <p>
        Still, despite the noted positive effect of the computerized cognitive training
(CCT), only 10-12% of elder people are prone to systematically exercising its
program [
        <xref ref-type="bibr" rid="ref11 ref12">11, 12</xref>
        ]. It seems that the situation could be improved by changing the social
norms of prestigious behavior and development of web resources dedicated to
cognitive stimulation, customized for effectiveness for personal features of users of
different ages. So, our article is dedicated to the study of IT competences in pensioners and
people approaching the retirement age, with respect to the barriers for wider ICT
usage. This involves the following contributions (the sample in our studies were the
elder people residing in the Siberian Federal district, mostly in the city of
Novosibirsk):
• assessment of elder people’s adoption and interest towards IT-related skills and
activities;
• identification of elder people’s habits in personal usage of IT;
• identification of the relation between the level of IT competences adoption and
career history for pensioners and those who approach the retirement age;
• testing the hypothesis that self-satisfaction with IT skills is high in elder people.
      </p>
      <p>The rest of the paper is organized as follows. In Section 2 we overview existing
research works related to IT competences in general and how the elder people use or
can better use them for their benefit. In Section 3, we describe the methodology of
two surveys that we ran with a total of 295 Russian people of pre-retirement and
retirement age, while in Section 4 we present the surveys’ results. In the Conclusions
we summarize our findings and make proposals for the further work aimed on wider
engagement of elder people with today’s ubiquitous ICT.
1
1.1</p>
    </sec>
    <sec id="sec-2">
      <title>Related Work</title>
      <sec id="sec-2-1">
        <title>IT Competences in Digital Economy</title>
        <p>
          Our literature review of related works suggests high interests of researchers towards
the influence of digitalization on work career, employment and population’s health.
Joseph Quinn and his co-authors notice that the current demographic and economic
changes have significantly increased risks of the future pensioners that causes workers
in the USA to remain professionally employed until later age than before [
          <xref ref-type="bibr" rid="ref13">13</xref>
          ].
Berkelaar &amp; Buzzanell have introduced the generalizing concept of digital career capital,
which is implicitly monitored by employers and becomes progressively more
important in human capital in general [
          <xref ref-type="bibr" rid="ref14">14</xref>
          ]. About a decade ago yet another related term
was introduced (see e.g. in [
          <xref ref-type="bibr" rid="ref15">15</xref>
          ]): digital competence, which represents more broad
conception of knowledge and work skills. In its elementary level, modern workers
must be able to use computers, mobile devices, work with software and apps in their
professional domain, and use the Internet.
        </p>
        <p>
          Approaching from the other side, Frey &amp; Osborne considered how workplaces are
subject to computerization and forecasted its forthcoming impact on the labor market
in the USA [
          <xref ref-type="bibr" rid="ref16">16</xref>
          ]. Particularly they focused on the analysis of risk for the number of
jobs and the relation between probability of a job computerization, the wages, and the
education level. OECD’s publication “Skills for a Digital World” (2016) considers the
close interconnectedness of the processes in the digital economy, including in the
aspects of skills, training and labor. It was also repeatedly noted that the digital
environment and workplaces, which are not bound to a particular time and space, require
new competences and qualifications.
        </p>
        <p>
          At the same time, the digital environment becomes integral part of the developing
health care and social security. Thus, IT needs to be mastered by broad strata of future
workers of different professions, not just the ones related to the actual ICT domain.
According to the well-established approach by Jens Rasmussen (1983), the human
performance models can be divided into Skills, Rules and Knowledge, depending on if
routine or novel tasks are performed by workers [
          <xref ref-type="bibr" rid="ref17">17</xref>
          ]. The knowledge model is
recognized the most demanded in the context of the digitalization of economy and the
communications. Let us illustrate some professions in Russia that imply different levels
of mastery of ICT and the corresponding different performance models (Table 1).
Performance
models
Knowledge
Rules
Skills
        </p>
      </sec>
      <sec id="sec-2-2">
        <title>ICT and the Elder People</title>
        <p>
          The analysis of the age structure of ICT professionals in Russia in 2018 suggested
that among the high qualification specialists 7.0% were older than 50, and 0.8% were
aged 60-72. In the medium qualification level a) technicians: 11.8% were older than
50, and 1.6% were aged 60-72, b) electronics specialists: 30.2% older than 50, and
6.9% aged 60-72. Of the qualified ICT “blue collars”, 29.0% were older than 50,
while 6.1% were aged 60-72 [
          <xref ref-type="bibr" rid="ref18">18</xref>
          ].
        </p>
        <p>
          In today’s environment, mostly high level of IT competences is required to
implement the Knowledge performance model. This situation started in 2000s, while
previously the set of competences for the Knowledge model was different, and the model
itself was not in such high demand. Accordingly, people of pre-retirement and
retirement age who are still employed have difficulties in responding to the labor market
requirements and update their competences. The results of a study of Russian
researchers aged 50-70 by G.L. Volkova suggest that in this demographics the most
popular form of advanced trainings is specialty courses, while the second most
popular form is computer courses. For the researchers aged 30-49, computer courses were
already in the third place, while for the ones younger than 29 they were the least
popular form [
          <xref ref-type="bibr" rid="ref19">19</xref>
          ]. Thus the demand for updating computer skills and IT competences in
general is the highest in the people of pre-retirement and retirement age.
        </p>
        <p>
          In 2018, researchers from the Institute for Statistical Studies and Economics of
Knowledge of the HSE conducted a study of households with regard to the Internet
skills [
          <xref ref-type="bibr" rid="ref20">20</xref>
          ]. In it, they introduced an integrated indicator of various actions on the
network, which included:
1. Being a part of social networks
2. Sending/receiving emails
3. Phone and video chats online
4. Searching for information about goods and services
5. Uploading personal files to websites, social networks, cloud storages for public
access
6. Searching for information related to health or medical care services
7. Performing financial transactions
8. Buying/selling goods and services on the Internet
9. Downloading software
10. Online learning
With respect to the performed actions, four levels of Internet skills were identified:
basic (1-2 actions), intermediate (3-4 actions), high (5-6 actions) and advanced (7-10
actions). According to the survey (2018), 33% of the participants had basic level,
while 32% had intermediate level. The results that were obtained for the people of
pre-retirement age are presented in Fig. 1. For male participants the share was notably
higher, while with age it decreased, and on overall less than 36% possessed at least
basic skills among the pensioners.
The results of a somehow similar survey of pensioners in the USA suggest that the
age-related digital gap that persisted already a decade ago (see e.g. in [
          <xref ref-type="bibr" rid="ref21">21</xref>
          ]), still
endures. The level of ICT mastery was found to be affected by the levels of education,
income, and the social-economic status [
          <xref ref-type="bibr" rid="ref22">22</xref>
          ]. Meanwhile, ICT for the elder people
potentially imply the following benefits:
• Instrument for obtaining knowledge and learning new skills, which contribute to
better cognitive status and the quality of life,
• The means for barrier-free communication, both social and with various
organizations;
• The mechanism for maintaining and improving health status.
1.3
        </p>
      </sec>
      <sec id="sec-2-3">
        <title>Effect of Cognitive Training Programs in the Elderly</title>
        <p>
          Organizational difficulties and the increasing expenses associated with population
ageing in developed countries support the relevance of preventing age-related
development of cognitive dysfunctions [
          <xref ref-type="bibr" rid="ref23 ref24">23, 24</xref>
          ]. The use of internet technologies is
learning for children and young adults is a given and is beyond doubt, although some
problems related to computer addiction and the changes in the structure of thinking,
especially speech functions and social communication, are noted [
          <xref ref-type="bibr" rid="ref25">25</xref>
          ]. The effectiveness
of cognitive training for the elder people is still being discussed, particularly in the
aspect of transmission of the results to succeeding in everyday activities [
          <xref ref-type="bibr" rid="ref26 ref27">26, 27</xref>
          ].
Still, the positive effect of the training for mental health and functional status of the
brain has been proven in both psychometric and neurophysiological research works
(e.g. [
          <xref ref-type="bibr" rid="ref27 ref28">27, 28</xref>
          ]).
        </p>
        <p>
          ICT skills in elder age are prerequisite for using the computerized training of
attention and memory, which is lately extensively used for activating cognitive reserves of
the brain in the context of atrophy of neurons that grows with aging and the resulting
violation of the brain’s functional systems [
          <xref ref-type="bibr" rid="ref23 ref30 ref31 ref32 ref8">8, 23, 30-32</xref>
          ]. For that end, both dedicated
software and various types of computer games are employed. The systematic training
allows to improve the speed of motor reaction and visual discrimination, the functions
of working memory and attention, as well as to increase the efficiency of more
complex planning and strategic thinking operations [
          <xref ref-type="bibr" rid="ref33 ref34 ref35">33-35</xref>
          ]. Several hours of the training
have been found to improve the above indicators and even intelligence in general.
Neurophysiological research has shown the compensatory development of structures
and functions of different areas of the frontal cortex as a result of working memory
training [
          <xref ref-type="bibr" rid="ref36">36</xref>
          ]. It is noted that already 10-hours computerized training in thinking
flexibility for the people aged over 65 caused improvement in solving various cognitive
tasks, including ones that were not presented in the training, as well as prevented the
decrease in the quality of life 5 years later [
          <xref ref-type="bibr" rid="ref37">37</xref>
          ]. Still, better results are noted from
longer training [
          <xref ref-type="bibr" rid="ref38 ref39">38, 39</xref>
          ], for which both the trainee’s mastery of IT skills and interest
towards the training and the software’s usability are essential.
        </p>
        <p>
          However, despite the many psychometric and neurophysiologic proofs of the
cognitive training’s utility for recovering speed characteristics of mind and memory in
the older age, this technology so far does not see ubiquitous usage, due to several
psychological and organizational factors. For instance, we previously found in our
survey of elder women attending computer courses in People’s Faculty of
Novosibirsk State Technical University (NSTU) that the priority of cognitive activity was
low in the motivational inductors profile [
          <xref ref-type="bibr" rid="ref11">11</xref>
          ]. Only 20% of the elderly students took
part in the cognitive training program that we implemented in the dedicated online
software, and only 8% of the pensioners completed 20 sessions or more. Insufficiently
vigorous usage of the proposed online technology can be associated with age-related
weakening of the activity initiation functions due to age-related changes in brain
structures, especially the prefrontal areas of the cortex [
          <xref ref-type="bibr" rid="ref12 ref23 ref40 ref41">12, 23, 40, 41</xref>
          ], as well as with
low levels of IT skills that we also discovered in the survey with that group of older
students.
        </p>
        <p>So, a large body of inter-disciplinary research supports the increasing importance
of IT competences in shaping the digital career capital, in the usage of digital
environment, preservation of mental health and functional ability of the brain, which is
particularly important for elder people. However, our overview of the related data for
Russia suggests that people in pre-retirement and retirement age do not possess
sufficient knowledge and skills in IT. To analyze the degree of IT adoption for this
demographic group in the non-capital city of Novosibirsk, we ran two survey studies,
which we describe in the subsequent Section of our paper.
2</p>
      </sec>
    </sec>
    <sec id="sec-3">
      <title>The Surveys Methodology</title>
      <p>First of all, there is currently a certain controversy regarding retirement and
preretirement age in Russia. The pension reform has started in 2019 and is expected to be
implemented until 2028, gradually increasing the default retirement age as shown in
Table 2. The concept of pre-retirement age was officially introduced in the Federal
Law 350-FZ “On amendments to certain legislative acts of the Russian Federation
related to the appointment and payment of pensions” in 2018. Particularly, the
citizens who have reached the pre-retirement age are subject to certain tax exemptions
and social security measures. The planned dynamics of the pre-retirement age that
follows the changes in the retirement age in the period of the pension reform is also
presented in Table 2.</p>
      <p>Retirement
age:
females</p>
      <p>males
Preretirement
age:
females
males
In our surveys, we considered the participants who have reached the age of 55 to be of
retirement age, while the ones who have reached 50 to be of pre-retirement age. The
main method used in our work was a questionnaire, distributed personally or over
Internet.</p>
      <p>In the first survey, we studied activities in pensioners who were students of the
People’s Faculty of NSTU (which is also called “the third age college”) in 2018-2019.
The total number of the students taking part in the survey was 203 (184 females, 19
males), and their age ranged from 55 to 78 years (mean = 66, SD = 5.1).</p>
      <p>Our second survey studied IT skills and interest towards them in elder people and
was mostly distributed over the Internet in 2015-2019. The total number of
respondents was 92, all of them aged over 50 and residing in the Siberian Federal District of
Russian Federation. The self-reported age distribution of the participants is presented
in Table 4.</p>
    </sec>
    <sec id="sec-4">
      <title>Results</title>
      <sec id="sec-4-1">
        <title>Survey 1: The Pensioners’ Activities</title>
        <p>Of the participants that reported the demographics, 66% had higher education, 2%
had incomplete higher education, 5% had full secondary education and 27% had
secondary special education. Most of them had or used to have occupation as
administrative workers (32 people), engineers (27), economists and accountants (21), medical
workers (14), teachers (12). The rest 97 participants have self-specified various other
professions.</p>
        <p>
          Only 60 subjects turned in the fully completed questionnaires, with their
selfreported activities estimated on a scale from 1 (lowest degree) to 5 (highest degree).
The resulting data are presented in Table 3.
Presumably, high popularity of cooking and summer cottage (dacha) facilities and the
low ratings for fishing are due to the dominance of women in the sample and indicate
the preservation of stereotypical female roles among pensioners. Elsewhere, we can
note the overall balanced distribution in activities, which include work both at home
and at dacha, cognitive and physical activities.
The comparable ratings of reading, TV and computers suggest that most of the
pensioners had actually mastered the IT and use the resources of the Internet.
Correspondingly, CCT to support the cognitive functions and prevent age-related dementia
should be available for elder demographics. On the other hand, the sample in the
People’s Faculty is not representative of the whole population, since only socially active
pensioners seeking new information and new forms of communications enroll there.
The share of such active group in the whole population of female pensioners in Russia
can be estimated as 13-30% [
          <xref ref-type="bibr" rid="ref20">20</xref>
          ].
3.2
        </p>
      </sec>
      <sec id="sec-4-2">
        <title>Survey 2: The Pensioners’ IT Skills</title>
        <p>The age distribution of the 92 participants who took part in the survey is presented in
Table 4. As for the education, in the group of pre-retirement age responders 19.7%
graduated in a major related to ICT (economic cybernetics, mathematics and
informatics, applied mathematics, computer operator, etc.). In the elder age group, this
share is lower (see in Table 5), since at the time of their study computer skills were
not so widely demanded and were not taught in the education system. Moreover,
those who had IT-related major did not always work in this field. On the other hand,
since at a certain moment the demand for ICT specialists significantly exceeded
supply, some respondents worked in this field despite having no formal specialized
education.
Of the 12 responders aged 50-60 who had ICT-related education, only 11 worked in
the related field, while 4 responders who did not have the education, did have
ICTrelated jobs in their career history. Of the responders aged 60-70, only 1 of the 2 who
graduated in ICT-related major had a corresponding job, while 4 responders reported
having worked in IT industry despite having no related education. In the age group
over 70, only 1 responder had a short experience of working as computer operator
(inputting data on received goods into information system), even though he did not
have a related education. The data presented in the above tables suggest that
nowadays the economy mostly demands highly educated employees who have medium or
high mastery of IT competences. The development of ICT leads to decreased
opportunities for non-specialists to get an IT-related job. This situation is notably different
from the period of 1980-2000 when due to the shortage of specialists the barriers for
employment in IT industry were rather low. It was then when some of the today’s
pensioners managed to obtain ICT-related work experience and the corresponding
competences.</p>
        <p>
          Further, we surveyed all the participants on the personal use of ICT – the resulting
data is presented in Table 6 (multiple options could be selected). The list of ICT uses
was composed according to [
          <xref ref-type="bibr" rid="ref20">20</xref>
          ]. The most popular uses that we found were:
engaging in social networks, searching for information, watching videos and reading news,
articles and books.
Interestingly, the responders’ satisfaction with their IT competence level was rather
high, particularly in the 50-60 age group. The responders aged over 60 reported that
they see little need in acquiring an IT competence.
4
        </p>
      </sec>
    </sec>
    <sec id="sec-5">
      <title>Discussion</title>
      <p>
        The results of our study of ICT effect in the work history correspond to the research
of the age structure in Russian IT specialists in [
        <xref ref-type="bibr" rid="ref18">18</xref>
        ] and confirm the shortage of the
industry-related professional skills in Russian elder people found in [
        <xref ref-type="bibr" rid="ref19">19</xref>
        ]. The
discovered personal uses of ICT (Table 6) are in line with the international trends found in
elder people, who have also moved from mostly reading e-mails and information
search [
        <xref ref-type="bibr" rid="ref42">42</xref>
        ] to communicating via messengers and social networks. In this, our results
is more consistent with [
        <xref ref-type="bibr" rid="ref43">43</xref>
        ] who found that the people over 80 are mostly interested
in online messaging and obtaining new information, and also that the ICT usage had
relation with psychological well-being of the oldest-old participants.
      </p>
      <p>
        The related research works studying the Russian pensioners are not entirely
consistent, which may be explained with varying samples. For instance, for the sample of
50 elder people in [
        <xref ref-type="bibr" rid="ref44">44</xref>
        ] they found that the most popular ICT uses were e-government
services, information search and online communication.
      </p>
      <p>
        In the study of 68 people in [
        <xref ref-type="bibr" rid="ref45">45</xref>
        ] they found that the communication and reading
news items were the most prominent. All in all, it seems that somehow different
concepts are used to describe more or less the same activities. Probably greater sample
sizes and consideration of the factors such as national culture, age, gender, education
level, family status, etc. would be needed to achieve better consistency.
      </p>
      <p>All in all, our research suggests that ICT usage for personal purposes by elder
people may allow developing their social relationships, decrease the perceived isolation,
provide mental stimulation beneficial for their overall health, broaden the worldview,
improve the set of skills and knowledge, and share the experience. As for the
generalizability of our study, we need to note that we only covered the subjects aged over 50
residing in the Siberian Federal district of Russia, who were mostly female (82.7%)
and had higher education (62.4%). This demographic is generally renowned for their
high level of mental and physical activity, the desire to obtain better competences, as
well as the balance between the household and outdoors tasks. Although they do not
show much use of online technologies, they are self-satisfied with it.</p>
    </sec>
    <sec id="sec-6">
      <title>Conclusions</title>
      <p>The global extension of IT usage, both in industrial context and at home, and the need
to maintain physical and psychological health of the ageing population call for wide
adoption of IT competences. However, their mastery in Russian citizens of
preretirement and retirement age remains moderate: only 36% of males and 30% of
females in this demographic group possess at least basic IT skills. At the same time,
learning IT skills nowadays remains one of the most popular forms of training and
continuing education.</p>
      <p>However, training in IT implies that elder people need to engage in relatively
atypical activities, and the previously formed social-cultural behavior stereotypes act as
barriers for that. This in particular limits their abilities in changing career tracks and
choosing new professions (Table 1), which is essential in the light of the ongoing
pension reform in Russia. At the same time our survey of the people aged over 50 in
the Siberian Federal District suggested low relation between the formal education in
IT and choosing career in this industry.</p>
      <p>
        Arguably even more severe effect of elder people’s low engagement with ICT is
neglect of computerized cognitive training, which proved to be effective in
maintaining mental health and preventing age-related dementia, as well as for improving
functions of attention, memory and flexibility of thinking [
        <xref ref-type="bibr" rid="ref46">46</xref>
        ]. Unfortunately, even such
socially active group of elderly as the students of People’s Faculty who self-reported
recurrent usage of computers comparable with the traditional household activities
(Table 3) showed little interest in continuous CCT.
      </p>
      <p>
        Overall, our results suggest that the age-related IT gap first noted some decades
ago still persists and that motivation in elder people remains the key barrier for
overcoming it (cf. [
        <xref ref-type="bibr" rid="ref21">21</xref>
        ]). To make broad strata of the elderly population engage with ICT
and CCT, more usable websites targeting this particular user group need to be
developed, taking into account the age-related differences in perception and memorizing
information, as well as individual variability in the dynamics of these processes.
Acknowledgement. The reported study was funded by RFBR according to the research project
No. 19-29-01017.
      </p>
    </sec>
  </body>
  <back>
    <ref-list>
      <ref id="ref1">
        <mixed-citation>
          1.
          <string-name>
            <surname>Dhillon</surname>
            ,
            <given-names>S.K.</given-names>
          </string-name>
          :
          <article-title>ICT Evaluation for Knowledge Sharing among Senior Citizens Community</article-title>
          .
          <source>In International Conference on Software Engineering and Computer Systems</source>
          ,
          <volume>92</volume>
          -
          <fpage>103</fpage>
          (
          <year>2011</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref2">
        <mixed-citation>
          2.
          <string-name>
            <surname>Fernández</surname>
          </string-name>
          ,
          <string-name>
            <surname>M.D.M</surname>
          </string-name>
          . et al.:
          <article-title>Using communication and visualization technologies with senior citizens to facilitate cultural access and self-improvement</article-title>
          .
          <source>Computers in Human Behavior</source>
          ,
          <volume>66</volume>
          ,
          <fpage>329</fpage>
          -
          <lpage>344</lpage>
          (
          <year>2017</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref3">
        <mixed-citation>
          3.
          <string-name>
            <surname>Dascălu</surname>
            ,
            <given-names>M.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Rodideal</surname>
            ,
            <given-names>A.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Popa</surname>
            ,
            <given-names>L.</given-names>
          </string-name>
          : In Romania, Elderly People Who Most Need ICT Are Those Who Are Less Probable to Use It. Social Work Review/Revista de Asistenta Sociala,
          <volume>17</volume>
          (
          <issue>2</issue>
          ),
          <fpage>81</fpage>
          -
          <lpage>95</lpage>
          (
          <year>2018</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref4">
        <mixed-citation>
          4.
          <string-name>
            <surname>Etemad-Sajadi</surname>
            ,
            <given-names>R.</given-names>
          </string-name>
          ,
          <string-name>
            <given-names>Dos</given-names>
            <surname>Santos</surname>
          </string-name>
          ,
          <string-name>
            <surname>G.G.</surname>
          </string-name>
          :
          <article-title>Senior citizens' acceptance of connected health technologies in their homes</article-title>
          .
          <source>International Journal of Health Care Quality Assurance</source>
          ,
          <volume>32</volume>
          (
          <issue>8</issue>
          ),
          <fpage>1162</fpage>
          -
          <lpage>1174</lpage>
          (
          <year>2019</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref5">
        <mixed-citation>
          5.
          <string-name>
            <surname>Kovar</surname>
            ,
            <given-names>I.</given-names>
          </string-name>
          :
          <article-title>Use of virtual reality as a tool to overcome the post-traumatic stress disorder of pensioners</article-title>
          .
          <source>International Journal on Advanced Science, Engineering and Information Technology</source>
          ,
          <volume>9</volume>
          (
          <issue>3</issue>
          ),
          <fpage>841</fpage>
          -
          <lpage>848</lpage>
          (
          <year>2019</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref6">
        <mixed-citation>
          6.
          <string-name>
            <surname>Tams</surname>
            ,
            <given-names>S.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Hill</surname>
            ,
            <given-names>K.</given-names>
          </string-name>
          :
          <article-title>Helping an old workforce interact with modern IT: a NeuroIS approach to understanding technostress and technology use in older workers</article-title>
          .
          <source>In Information systems and neuroscience, Lecture Notes in Information Systems and Organisation</source>
          ,
          <volume>16</volume>
          , pp.
          <fpage>19</fpage>
          -
          <lpage>26</lpage>
          (
          <year>2017</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref7">
        <mixed-citation>
          7.
          <string-name>
            <surname>Castells-Sánchez</surname>
            ,
            <given-names>A.</given-names>
          </string-name>
          et al.:
          <article-title>Effects and Mechanisms of Cognitive, Aerobic Exercise and Combined Training on Cognition, Health and Brain Outcomes in Physically Inactive Older Adults: the Projecte Moviment Protocol</article-title>
          . Frontiers in aging neuroscience,
          <volume>11</volume>
          ,
          <issue>216</issue>
          (
          <year>2019</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref8">
        <mixed-citation>
          8.
          <string-name>
            <surname>Lisanne</surname>
            ,
            <given-names>F.</given-names>
          </string-name>
          , et al.:
          <article-title>Effects of computerized cognitive training on neuroimaging outcomes in older adults: a systematic review</article-title>
          .
          <source>BMC geriatrics</source>
          ,
          <volume>17</volume>
          (
          <issue>1</issue>
          ),
          <volume>139</volume>
          (
          <year>2017</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref9">
        <mixed-citation>
          9.
          <string-name>
            <surname>Turunen</surname>
            ,
            <given-names>M.</given-names>
          </string-name>
          et al.:
          <article-title>Computer-based cognitive training for older adults: Determinants of adherence</article-title>
          .
          <source>PloS one</source>
          ,
          <volume>14</volume>
          (
          <issue>7</issue>
          ) (
          <year>2019</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref10">
        <mixed-citation>
          10.
          <string-name>
            <surname>Anatürk</surname>
            ,
            <given-names>M.</given-names>
          </string-name>
          , et al.:
          <article-title>A systematic review and meta-analysis of structural magnetic resonance imaging studies investigating cognitive and social activity levels in older adults</article-title>
          .
          <source>Neuroscience &amp; Biobehavioral Reviews</source>
          ,
          <volume>93</volume>
          ,
          <fpage>71</fpage>
          -
          <lpage>84</lpage>
          (
          <year>2018</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref11">
        <mixed-citation>
          11.
          <string-name>
            <surname>Razumnikova</surname>
            <given-names>O.M.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Asanova</surname>
            <given-names>N.V.</given-names>
          </string-name>
          :
          <article-title>Motivational behavior inducers as reserves for successful aging</article-title>
          .
          <source>Uspekhi gerontologii</source>
          ,
          <volume>31</volume>
          (
          <issue>5</issue>
          ),
          <fpage>737</fpage>
          -
          <lpage>742</lpage>
          (
          <year>2018</year>
          ). - in
          <string-name>
            <surname>Russian</surname>
          </string-name>
          .
        </mixed-citation>
      </ref>
      <ref id="ref12">
        <mixed-citation>
          12.
          <string-name>
            <surname>Turner</surname>
            ,
            <given-names>G.R.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Spreng</surname>
            ,
            <given-names>R.N.</given-names>
          </string-name>
          :
          <article-title>Executive functions and neurocognitive aging: dissociable patterns of brain activity</article-title>
          .
          <source>Neurobiology of aging</source>
          ,
          <volume>33</volume>
          (
          <issue>4</issue>
          ),
          <fpage>826</fpage>
          -
          <lpage>e1</lpage>
          (
          <year>2012</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref13">
        <mixed-citation>
          13.
          <string-name>
            <surname>Cahill</surname>
            ,
            <given-names>K.E.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Giandrea</surname>
            ,
            <given-names>M.D.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Quinn</surname>
            ,
            <given-names>J.F.</given-names>
          </string-name>
          :
          <article-title>Retirement patterns and the macroeconomy,</article-title>
          <year>1992</year>
          -
          <fpage>2010</fpage>
          :
          <article-title>The prevalence and determinants of bridge jobs, phased retirement, and reentry among three recent cohorts of older Americans</article-title>
          .
          <source>The Gerontologist</source>
          ,
          <volume>55</volume>
          (
          <issue>3</issue>
          ),
          <fpage>384</fpage>
          -
          <lpage>403</lpage>
          (
          <year>2015</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref14">
        <mixed-citation>
          14.
          <string-name>
            <surname>Berkelaar</surname>
            ,
            <given-names>B.L.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Buzzanell</surname>
            ,
            <given-names>P.M.:</given-names>
          </string-name>
          <article-title>Online employment screening and digital career capital: Exploring employers' use of online information for personnel selection</article-title>
          .
          <source>Management Communication Quarterly</source>
          ,
          <volume>29</volume>
          (
          <issue>1</issue>
          ),
          <fpage>84</fpage>
          -
          <lpage>113</lpage>
          (
          <year>2015</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref15">
        <mixed-citation>
          15.
          <string-name>
            <surname>Ilomäki</surname>
            ,
            <given-names>L.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Kantosalo</surname>
            ,
            <given-names>A.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Lakkala</surname>
            ,
            <given-names>M.</given-names>
          </string-name>
          :
          <article-title>What is digital competence</article-title>
          .
          <source>Linked portal. Brussels: European Schoolnet (EUN)</source>
          ,
          <fpage>1</fpage>
          -
          <lpage>12</lpage>
          (
          <year>2011</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref16">
        <mixed-citation>
          16.
          <string-name>
            <surname>Frey</surname>
            ,
            <given-names>C.B.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Osborne</surname>
            ,
            <given-names>M.A.</given-names>
          </string-name>
          :
          <article-title>The future of employment: how susceptible are jobs to computerisation?</article-title>
          .
          <source>Technological forecasting and social change</source>
          ,
          <volume>114</volume>
          ,
          <fpage>254</fpage>
          -
          <lpage>280</lpage>
          (
          <year>2017</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref17">
        <mixed-citation>
          17.
          <string-name>
            <surname>Rasmussen</surname>
          </string-name>
          , J.:
          <article-title>Skills, rules, and knowledge; signals, signs, and symbols, and other distinctions in human performance models</article-title>
          .
          <source>IEEE transactions on systems, man, and cybernetics</source>
          , (
          <volume>3</volume>
          ),
          <fpage>257</fpage>
          -
          <lpage>266</lpage>
          (
          <year>1983</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref18">
        <mixed-citation>
          18.
          <string-name>
            <surname>Abdarakhmanova</surname>
            ,
            <given-names>G.I.</given-names>
          </string-name>
          et al.:
          <article-title>Indexes of the digital economy: 2019, statistical volume</article-title>
          .
          <source>HSE</source>
          , Moscow (
          <year>2019</year>
          ). - in
          <string-name>
            <surname>Russian</surname>
          </string-name>
          .
        </mixed-citation>
      </ref>
      <ref id="ref19">
        <mixed-citation>
          19.
          <string-name>
            <surname>Volkova</surname>
            ,
            <given-names>G.L.</given-names>
          </string-name>
          :
          <article-title>Life-long learning: how the Russian researchers obtain further education</article-title>
          .
          <source>Nauka. Tekhnologiya. Innovatsii</source>
          ,
          <volume>1</volume>
          -
          <fpage>3</fpage>
          (
          <year>2019</year>
          ). - in
          <string-name>
            <surname>Russian</surname>
          </string-name>
          .
        </mixed-citation>
      </ref>
      <ref id="ref20">
        <mixed-citation>
          20.
          <string-name>
            <surname>Nefedova</surname>
            ,
            <given-names>A.I.</given-names>
          </string-name>
          :
          <article-title>Online practice of the Russians</article-title>
          .
          <source>Digital Economy</source>
          ,
          <fpage>1</fpage>
          -
          <lpage>2</lpage>
          (
          <year>2019</year>
          ). - in
          <string-name>
            <surname>Russian</surname>
          </string-name>
          .
        </mixed-citation>
      </ref>
      <ref id="ref21">
        <mixed-citation>
          21.
          <string-name>
            <surname>Bakaev</surname>
            ,
            <given-names>M.</given-names>
          </string-name>
          et al.:
          <article-title>E-learning and elder people: Barriers and benefits</article-title>
          .
          <source>In 2008 IEEE Region 8 International Conference on Computational Technologies in Electrical and Electronics Engineering</source>
          , pp.
          <fpage>110</fpage>
          -
          <lpage>113</lpage>
          (
          <year>2008</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref22">
        <mixed-citation>
          22.
          <string-name>
            <surname>Hargittai</surname>
            ,
            <given-names>E.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Dobransky</surname>
            ,
            <given-names>K.</given-names>
          </string-name>
          <article-title>Old dogs, new clicks: Digital inequality in skills and uses among older adults</article-title>
          .
          <source>Canadian Journal of Communication</source>
          ,
          <volume>42</volume>
          (
          <issue>2</issue>
          ) (
          <year>2017</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref23">
        <mixed-citation>
          23.
          <string-name>
            <surname>Razumnikova O.M.</surname>
          </string-name>
          <article-title>: Patterns of the brain ageing and the means for activating its compensatory resources</article-title>
          .
          <source>Uspekhi fiziologicheskih nauk</source>
          ,
          <volume>46</volume>
          (
          <issue>2</issue>
          ),
          <fpage>3</fpage>
          -
          <lpage>16</lpage>
          (
          <year>2015</year>
          ). - in
          <string-name>
            <surname>Russian</surname>
          </string-name>
          .
        </mixed-citation>
      </ref>
      <ref id="ref24">
        <mixed-citation>
          24.
          <string-name>
            <surname>Razumnikova</surname>
            ,
            <given-names>O.</given-names>
          </string-name>
          et al.:
          <article-title>A computerized cognitive test battery Individual differences in cognitive characteristics: Measuring and dynamic of training</article-title>
          .
          <source>In Proceedings of IFOST2016</source>
          , pp.
          <fpage>256</fpage>
          -
          <lpage>258</lpage>
          (
          <year>2016</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref25">
        <mixed-citation>
          25.
          <string-name>
            <surname>Bavelier</surname>
            ,
            <given-names>D.</given-names>
          </string-name>
          et al.:
          <article-title>Removing brakes on adult brain plasticity: from molecular to behavioral interventions</article-title>
          .
          <source>Journal of Neuroscience</source>
          ,
          <volume>30</volume>
          (
          <issue>45</issue>
          ),
          <fpage>14964</fpage>
          -
          <lpage>14971</lpage>
          (
          <year>2010</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref26">
        <mixed-citation>
          26.
          <string-name>
            <surname>Goghari</surname>
            ,
            <given-names>V. M.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Lawlor-Savage</surname>
            ,
            <given-names>L.</given-names>
          </string-name>
          :
          <article-title>Comparison of cognitive change after working memory training and logic and planning training in healthy older adults</article-title>
          .
          <source>Frontiers in aging neuroscience</source>
          ,
          <volume>9</volume>
          ,
          <issue>39</issue>
          (
          <year>2017</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref27">
        <mixed-citation>
          27.
          <string-name>
            <surname>Greenwood</surname>
            ,
            <given-names>P. M.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Parasuraman</surname>
            ,
            <given-names>R.:</given-names>
          </string-name>
          <article-title>The mechanisms of far transfer from cognitive training: Review and hypothesis</article-title>
          .
          <source>Neuropsychology</source>
          ,
          <volume>30</volume>
          (
          <issue>6</issue>
          ),
          <volume>742</volume>
          (
          <year>2016</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref28">
        <mixed-citation>
          28.
          <string-name>
            <surname>Buitenweg</surname>
            ,
            <given-names>J.I.</given-names>
          </string-name>
          et al.:
          <article-title>Cognitive flexibility training: A large-scale multimodal adaptive active-control intervention study in healthy older adults</article-title>
          .
          <source>Frontiers in human neuroscience</source>
          ,
          <volume>11</volume>
          ,
          <issue>529</issue>
          (
          <year>2017</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref29">
        <mixed-citation>
          29.
          <string-name>
            <surname>Jaeggi</surname>
            ,
            <given-names>S.M.</given-names>
          </string-name>
          et al.:
          <article-title>The role of individual differences in cognitive training and transfer</article-title>
          .
          <source>Memory &amp; cognition</source>
          ,
          <volume>42</volume>
          (
          <issue>3</issue>
          ),
          <fpage>464</fpage>
          -
          <lpage>480</lpage>
          (
          <year>2014</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref30">
        <mixed-citation>
          30.
          <string-name>
            <surname>Lojo-Seoane</surname>
            ,
            <given-names>C.</given-names>
          </string-name>
          et al.:
          <article-title>Effects of cognitive reserve on cognitive performance in a followup study in older adults with subjective cognitive complaints. The role of working memory</article-title>
          .
          <source>Frontiers in aging neuroscience</source>
          ,
          <volume>10</volume>
          ,
          <issue>189</issue>
          (
          <year>2018</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref31">
        <mixed-citation>
          31.
          <string-name>
            <surname>Salthouse</surname>
            ,
            <given-names>T.A.</given-names>
          </string-name>
          :
          <article-title>Selective review of cognitive aging</article-title>
          .
          <source>Journal of the International neuropsychological Society</source>
          ,
          <volume>16</volume>
          (
          <issue>5</issue>
          ),
          <fpage>754</fpage>
          -
          <lpage>760</lpage>
          (
          <year>2010</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref32">
        <mixed-citation>
          32.
          <string-name>
            <surname>West</surname>
            ,
            <given-names>R. L.:</given-names>
          </string-name>
          <article-title>An application of prefrontal cortex function theory to cognitive aging</article-title>
          .
          <source>Psychological bulletin</source>
          ,
          <volume>120</volume>
          (
          <issue>2</issue>
          ),
          <volume>272</volume>
          (
          <year>1996</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref33">
        <mixed-citation>
          33.
          <string-name>
            <surname>Jaeggi</surname>
            ,
            <given-names>S.M.</given-names>
          </string-name>
          et al.:
          <article-title>Short-and long-term benefits of cognitive training</article-title>
          .
          <source>Proceedings of the National Academy of Sciences</source>
          ,
          <volume>108</volume>
          (
          <issue>25</issue>
          ),
          <fpage>10081</fpage>
          -
          <lpage>10086</lpage>
          (
          <year>2011</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref34">
        <mixed-citation>
          34.
          <string-name>
            <surname>Owen</surname>
            ,
            <given-names>A.M.</given-names>
          </string-name>
          et al.:
          <article-title>Putting brain training to the test</article-title>
          .
          <source>Nature</source>
          ,
          <volume>465</volume>
          (
          <issue>7299</issue>
          ),
          <fpage>775</fpage>
          -
          <lpage>778</lpage>
          (
          <year>2010</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref35">
        <mixed-citation>
          35.
          <string-name>
            <surname>Stern</surname>
            ,
            <given-names>Y.</given-names>
          </string-name>
          et al.:
          <article-title>Space Fortress game training and executive control in older adults: a pilot intervention</article-title>
          . Aging, Neuropsychology, and Cognition,
          <volume>18</volume>
          (
          <issue>6</issue>
          ),
          <fpage>653</fpage>
          -
          <lpage>677</lpage>
          (
          <year>2011</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref36">
        <mixed-citation>
          36.
          <string-name>
            <surname>Lustig</surname>
            ,
            <given-names>C.</given-names>
          </string-name>
          et al.:
          <article-title>Aging, training, and the brain: a review and future directions</article-title>
          .
          <source>Neuropsychology review</source>
          ,
          <volume>19</volume>
          (
          <issue>4</issue>
          ),
          <fpage>504</fpage>
          -
          <lpage>522</lpage>
          (
          <year>2009</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref37">
        <mixed-citation>
          37.
          <string-name>
            <surname>Kalmar</surname>
            ,
            <given-names>J.H.</given-names>
          </string-name>
          et al.:
          <article-title>The relationship between cognitive deficits and everyday functional activities in multiple sclerosis</article-title>
          .
          <source>Neuropsychology</source>
          ,
          <volume>22</volume>
          (
          <issue>4</issue>
          ),
          <volume>442</volume>
          (
          <year>2008</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref38">
        <mixed-citation>
          38.
          <string-name>
            <surname>Gajewski</surname>
            ,
            <given-names>P.D.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Falkenstein</surname>
            ,
            <given-names>M.</given-names>
          </string-name>
          :
          <article-title>Training-induced improvement of response selection and error detection in aging assessed by task switching: effects of cognitive, physical, and relaxation training</article-title>
          .
          <source>Frontiers in human neuroscience</source>
          ,
          <volume>6</volume>
          ,
          <issue>130</issue>
          (
          <year>2012</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref39">
        <mixed-citation>
          39.
          <string-name>
            <surname>Forte</surname>
            ,
            <given-names>R.</given-names>
          </string-name>
          et al.:
          <article-title>Enhancing cognitive functioning in the elderly: multicomponent vs resistance training</article-title>
          .
          <source>Clinical interventions in aging, 8</source>
          ,
          <issue>19</issue>
          (
          <year>2013</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref40">
        <mixed-citation>
          40.
          <string-name>
            <surname>Acosta</surname>
            ,
            <given-names>L.Y.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Goodman</surname>
            ,
            <given-names>I.J.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Heilman</surname>
            ,
            <given-names>K.M.</given-names>
          </string-name>
          :
          <string-name>
            <given-names>Unilateral</given-names>
            <surname>Perseverationnnn</surname>
          </string-name>
          .
          <source>Cognitive and Behavioral Neurology</source>
          ,
          <volume>26</volume>
          (
          <issue>4</issue>
          ),
          <fpage>181</fpage>
          -
          <lpage>188</lpage>
          (
          <year>2013</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref41">
        <mixed-citation>
          41.
          <string-name>
            <surname>Reuter-Lorenz</surname>
            ,
            <given-names>P.A.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Cappell</surname>
            ,
            <given-names>K.A.</given-names>
          </string-name>
          :
          <article-title>Neurocognitive aging and the compensation hypothesis</article-title>
          .
          <source>Current directions in psychological science</source>
          ,
          <volume>17</volume>
          (
          <issue>3</issue>
          ),
          <fpage>177</fpage>
          -
          <lpage>182</lpage>
          (
          <year>2008</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref42">
        <mixed-citation>
          42.
          <string-name>
            <surname>Morris</surname>
            <given-names>A.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Goodman</surname>
            <given-names>J.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Brading</surname>
            <given-names>H.</given-names>
          </string-name>
          :
          <article-title>Internet use and non-use: views of older users</article-title>
          .
          <source>Universal access in the information society</source>
          ,
          <volume>6</volume>
          (
          <issue>1</issue>
          ),
          <fpage>43</fpage>
          -
          <lpage>57</lpage>
          (
          <year>2007</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref43">
        <mixed-citation>
          43.
          <string-name>
            <surname>Sims</surname>
            <given-names>T.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Reed</surname>
            <given-names>A.E.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Carr</surname>
            <given-names>D.C.</given-names>
          </string-name>
          :
          <article-title>Information and communication technology use is related to higher well-being among the oldest-old</article-title>
          .
          <source>The Journals of Gerontology: Series B</source>
          ,
          <volume>72</volume>
          (
          <issue>5</issue>
          ),
          <fpage>761</fpage>
          -
          <lpage>770</lpage>
          (
          <year>2017</year>
          ).
        </mixed-citation>
      </ref>
      <ref id="ref44">
        <mixed-citation>
          44.
          <string-name>
            <surname>Rossoshanskaya</surname>
            <given-names>A.Y.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Yashina</surname>
            <given-names>V.S.:</given-names>
          </string-name>
          <article-title>Computer literacy as the indicator of information culture in elder people</article-title>
          .
          <source>The Bulleting of Medical Internet Conferences</source>
          ,
          <volume>7</volume>
          (
          <issue>6</issue>
          ),
          <fpage>937</fpage>
          -
          <lpage>940</lpage>
          (
          <year>2017</year>
          ). [In Russian].
        </mixed-citation>
      </ref>
      <ref id="ref45">
        <mixed-citation>
          45.
          <string-name>
            <surname>Darinskaya</surname>
            <given-names>L.A.</given-names>
          </string-name>
          ,
          <string-name>
            <surname>Moskvicheva</surname>
            <given-names>N.L.</given-names>
          </string-name>
          :
          <article-title>The potential of interaction between generations in engaging elder people into digital environment</article-title>
          .
          <source>The Psychological Journal of St. Petersburg</source>
          ,
          <volume>20</volume>
          ,
          <fpage>43</fpage>
          -
          <lpage>65</lpage>
          (
          <year>2017</year>
          ). [In Russian].
        </mixed-citation>
      </ref>
      <ref id="ref46">
        <mixed-citation>
          46.
          <string-name>
            <surname>Au</surname>
            ,
            <given-names>J.</given-names>
          </string-name>
          et al.:
          <article-title>Improving fluid intelligence with training on working memory: a metaanalysis</article-title>
          .
          <source>Psychonomic bulletin &amp; review</source>
          ,
          <volume>22</volume>
          (
          <issue>2</issue>
          ),
          <fpage>366</fpage>
          -
          <lpage>377</lpage>
          (
          <year>2015</year>
          ).
        </mixed-citation>
      </ref>
    </ref-list>
  </back>
</article>