Can Digital Games Help Seniors Improve their Quality of Life?
Louise Sauvé
1
, Lise Renaud
2
,
David Kaufman
3
and Emmanuel Duplàa
4
1
Département Éducation, Télé-université / SAVIE, 455 Rue du Parvis, GIK9H6, Québec, (Qc), Canada
2
Faculté de communication, UQAM, C.P. 8888, succ. Centre-ville, H3C3P8, Montréal, (Qc), Canada
3
Faculty of Education, Simon Fraser University, 8888 University Dr, V5A1S6, Burnaby, (BC), Canada
4
Faculty of Education, University of Ottawa, 145 Jean-Jacques Lussier St, K1N6N5, Ottawa, (ON), Canada
Keywords: Online Games, Seniors, Benefits, Quality of Life.
Abstract: A developmental research study aimed to design, publicize and evaluate an online educational game to
improve the quality of life for seniors 55 years and older. The game Live Well, Live Healthy!
(cvje2.savie.ca) is a Bingo game in which the learning content in the study was integrated into the
mechanism of the game. A "pre-test/post-test" single group methodology measured the impact of the game
in three dimensions of quality of life: psychological, physical and social. A total of 56 seniors played for a
week in the multiplayer mode (real-time interaction with at least two other participants). The results indicate
that the educational game improved the perception of seniors in a majority of the variables concerning the
three dimensions: physical (fatigue, sleep, eating habits); social well-being (building ties, social
connectedness, friendships) and psychological well-being (depression, difficulty doing activities, mood and
feeling of being loved). Some variables (sadness, isolation, proximity to family and physical habits)
generated a weak perception of positive benefits for these seniors.
1 INTRODUCTION
1.1 Background
The aging population represents a serious challenge
for healthcare systems and social insurance in the
21st century. These aging seniors are facing the
decline of their physical and cognitive abilities, loss
of long-term companions and social support,
changes in their familial or professional
environment, changing lifestyles and the increased
likelihood of developing chronic and disabling
diseases. But what are we doing to improve the
quality of life for seniors? Can online educational
games help them age better?
1.2 Purpose of the Study
Our study aims to measure the benefits of an online
educational game designed for seniors concerning
their quality of life.
1.3 Research Questions
• What is the impact of the educational game on the
perception of the seniors’ physical condition?
• What is the impact of the educational game on the
perception of the seniors’ psychological state?
• What is the impact of the educational game on the
perception of the seniors’ social environment?
2 LITERATURE REVIEW
An investigation by CEFRIO in Quebec indicated
that over a third of seniors aged 55 and over using
the internet to play digital games either alone or in
groups (Beaudoin et al., 2011). Given this interest,
we wondered whether the use of online educational
games for improving the quality of life of seniors
could be beneficial.
Quality of life is a global concept describing the
daily life of people, taking into account the
emotional and social functions as well as purely
physical conditions. Even though there does not
seem to be a consensual definition (Kuyken and
WHOQOL Group, 1995), the most widely used
definition comes from the World Health
Organization - WHO (1993). Quality of Life is
defined as ‘…individuals' perception of their
94
Sauvé, L., Renaud, L., Kaufman, D. and Duplàa, E.
Can Digital Games Help Seniors Improve their Quality of Life?.
In Proceedings of the 8th International Conference on Computer Supported Education (CSEDU 2016) - Volume 1, pages 94-102
ISBN: 978-989-758-179-3
Copyright
c
2016 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
position in life in the context of the culture and the
value systems in which they live and in relation to
their goals, expectations, standards and concerns. It
is a broad ranging concept affected in a complex
way by the person’s physical health, psychological
state, level of independence, social relationships,
personal beliefs and their relationship to salient
features of their environment.’’(WH0, 1997, p. 1).
This concept takes into account four dimensions:
physical (autonomy and physical abilities),
psychological (isolation, depression, emotion),
relational (family, social, professional), symptomatic
(impact of a disease and its treatment). Surveys
(Bowling and Dieppe, 2005; Chen et al., 2013)
reveal that a majority of seniors consider
psychological well-being, involvement in social
activities and physical health as conditions for
successfully aging. Finally, Turcotte and
Schellenberg (2006, p. 51) consider that "active
participation in society can also be compromised if a
person has difficulty hearing, seeing, walking,
climbing stairs, bending, learning or doing similar
activities. All these difficulties, if cumulative, can
greatly impair the quality of life of a person of any
age."
Digital games are becoming increasingly popular
with seniors (Diaz-Orueta et al., 2012; Nacke et al.,
2009). According to the World Health Organization
- WHO (2001), digital games can influence both the
health conditions of seniors (taking into
consideration health in a perspective that is both
broad and biopsychosocial) and their ability to
perform activities in their current environment.
What does the literature say concerning the
impact of digital games on the quality of life of
seniors as it pertains to the physical, psychological
and social aspects? Some studies on the impacts of
digital games on an active lifestyle (i.e., the ability
to maintain physical and functional independence)
have shown beneficial effects on the quality of life
of seniors (Figueira et al., 2008; Freitas et al., 2007;
Pernambuco et al. 2012). Other studies have
examined the contribution of games using the
Nintendo Wii game console on the performance of
physical and functional tasks. Studies from
Jorgensens et al. (2013), Maillot et al. (2012) and
Singh et al. (2013) conclude that improvements were
apparent; however, those of Bieryla and Dold (2013)
and Daniel (2012) do not find any improvements.
Social interaction and social support are
constantly identified as key aspects of quality of life
for seniors (Adams et al., 2011; Heylin, 2010;
Reichstadt et al., 2010; Theurer and Wister, 2010).
Seniors are already active users of interactive
technologies and they would be able to use digital
games and be able to easily learn (Pew Internet and
American Life Project, 2011). Studies are showing
increasingly that digital games are a means of social
interaction that may improve the quality of life of
seniors (De Schutter and Abeele 2010; De Schutter,
2011; Ijsselsteijn et al., 2007; Khoo and Cheok
2006; Khoo et al., 2009; Mahmud et al., 2008;
Stebbins 2007; Stowe and Cooney, 2015; Theng et
al., 2012;). Whitcomb (1990) found that games
develop a sense of well-being and social
relationships among seniors while providing an
enjoyable way to spend time. Astell (2013)
suggested that digital games and interactive
technologies (Skype, Facebook, etc.) offer social
connections, especially for elderly people suffering
from dementia.
Regarding physiological aspects, Allaire et al.
(2013) found a significant difference between
gaming (moderate and occasional) and non-gaming
seniors, concerning socio-affective dimensions such
as mood and depression. In addition, Wollersheim et
al. (2010) reported that digital games breakdown
isolation as well as decrease feelings of loneliness.
Despite these findings, few studies have
addressed the psychological aspects of quality of
life.
It is difficult to draw conclusions from current
empirical studies because there is little overlap in
these studies due to several factors:
the variation in the demographic data of the
participants; for example, the number (1-1000
respondents), age (45 to 87), educational level
(secondary to university);
the ratio of men vs. women (more women than
men participate in most studies);
the diversity of research methodologies;
the use of various measuring instruments (few
studies use the same instruments);
the choice of digital games, which are not always
developed for seniors.
What happens if we experiment on an
educational game with learning content dealing with
nutrition and prevention, in addition to the three
quality of life dimensions: physical (physical
activity benefits in the development of autonomy
and physical abilities), psychological (actions to take
to reduce anxiety, depression, emotions) and
relational (the contribution of the social environment
- family, social, professional - for the well-being of
seniors). Can such a game change the perceptions of
seniors towards the benefits that educational games
can bring by educating them about the actions they
can take to improve their quality of life?
Can Digital Games Help Seniors Improve their Quality of Life?
95
3 GAME DESCRIPTION
According to a survey of 932 Canadian seniors
(Kaufman et al., 2014), the Bingo game was found
to be the most frequently one mentioned by
respondents. Figure 1 represents the Live Well, Live
Healthy! game interface which is divided into three
parts: a) the Bingo card, rules and tutorial; b)
information on the game’s progress: the type of
game, randomly drawn ball, and the Bingo button
for ending the game; and c) information related to
the players’ actions: players' names and scores, as
well as the microphone and chat control buttons.
Figure 1: Live Well, Live Healthy!
The Live Well, Live Healthy! game was
developed using a generic shell for educational
games (http://cvje2concepteur.savie.ca). The game’s
educational objectives are the following: to increase
knowledge about nutrition and physical activities, to
decrease risk situations (or to improve prevention
situations) and to identify the importance of social
interactions with friends and family members.
The Live Well, Live Healthy! game offers a
mechanism to display a question every time the
number of a randomly drawn ball is on one or more
of the players’ cards. If the player answers the
question correctly, a token appears in the box and
the player earns points (20 points for an easy
question, 30 points for an average question and 50
points for a difficult question). If the player does not
answer the question correctly, the token will not
appear in the box and the player loses half the points
allocated to the question. The 92 questions included
in the game are distributed as follows: physical state
(31 questions about nutrition, 24 about physical
activities), psychological aspect (18 questions) and
the social environment (19 questions).
The Live Well, Live Healthy! game provides
feedback to support the learning of the preset
content. Immediate feedback, related to each
learning task, allows the players to identify
successful activities and those they have failed.
Figure 2: Question Card.
The game incorporates mechanisms (Figure 2)
that: (1) highlight the results of each learning
activity (success or failure) through visual or audible
feedback (A) such as a smiling face or a sad one and
positive or negative tone (i.e a signal that indicates
whether the action in the game has been made
correctly or not by the player) and (2) the correct
and incorrect answers through textual, visual (B) or
audible (C) feedback on the content of the learning
activity or provide additional information to sustain
interest in the case of positive responses; and (3)
allow players to see what they have learned by
providing an overview of the results of the game’s
learning activities, together with teaching materials
to review subject matter that has not been learned.
For more details about this digital game and a
good preview, please read Sauvé et al. (2014). This
game (http://cvje2.savie.ca) will promote active
living and healthy eating habits among seniors as
well as giving them opportunities to interact with
others by illustrating these themes with good quality
images and animations.
4 METHODOLOGY
Opting for a single group pre- and post-test protocol,
our study leads us to measure the physical,
psychological and social dimensions of quality of
life. Remember that quality of life is a subjective
concept and the apprehension of the construct itself
is complex. The definition of quality of life being
adopted in this study specifies the items that the
study will retain to measure the impact of the game.
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Table 1: Quality of Life Dimensions.
Quality of Life
Dimensions
Items Measured
Physical State
Sleep
Tiredness
Eating habits
Physical activity habits
Psychological
Aspect
Depression
Isolation
Feeling loved
Mood
Sadness
Ease in doing activities
Social
Environment
Strengthening ties
Social connectedness
Friendship
Interactions with family
Interactions with friends
These items (Table 1) were subjected to Likert
scale to obtain the construct of the quality of life. To
facilitate data collection, we opted for a self-
administered questionnaire. It is therefore preferable
to use scales having a limited number of questions to
minimize the time it takes to fill out the
questionnaire.
4.1 Handing out the Pre/Post
Questionnaires
A questionnaire of 15 items was used for data
collection. The questions were formed as a Likert
scale with five levels (5 = strongly agree, 4 = agree,
3 = neutral, 2 = disagree and 1 = strongly disagree).
The questions were designed to determine the
perceptions of the participants towards the benefits
of playing online concerning physical, social and
psychological well-being. The reliability of the
instrument was determined to use the index of
internal consistency from Cronbach’s alpha (α =
0.87). The validity has been established by
calculating the Pearson correlation coefficient
between items belonging to the same dimension.
The four items in the "Physical state" dimension
showed significant correlations among them.
Similarly, the five items comprising the "Social
environment" dimension presented significant
correlations among all items. Finally, significant
correlations between the six items belonging to the
"Psychological aspect" dimension amounted to 66%.
The pretest was completed prior to the
participation of seniors in the Live Well, Live
Healthy! game. Seniors were invited to play at least
four games over a period of one month. Following
their participation, they had to complete the post-
test.
4.2 Sample
It is very difficult to find objective definitions of the
terms "senior" or "elderly". “The new definitions
proposed by experts are not getting consensual
approval yet" (Turcotte and Schellenberg, 2006,
p. 8). As part of our study, we selected two criteria:
minimum age of 55 and that of being retired in
establishing our sample of seniors.
Turcotte and Schellenberg (2006) identify two
types of seniors: those who are currently 65, the
threshold that delineates the elderly according to
Statistics Canada and those who are considered the
next generation of seniors, adults aged between 55
and 64. Beaudoin et al., (2011) also chose the age of
55 and over to designate seniors from generation A.
Given this trend, we chose to form two age groups:
55 to 64 and 64 years and older.
On the retirement aspect, Turcotte and
Schellenberg (2006) found that people aged 56 and
over who are retired have more time to devote to
their home computer. In a recent study in Australia
realized by Brand et al. (2014), nearly one player in
five is likely to be aged 51 and over. The reasons
and motivations why players choose to play vary by
age group, suggesting that the stages of life play an
important role in the act of playing games.
Following what these authors suggested, retired
people were more available and interested in
participating in the experiment.
The recruitment of our sample of seniors of 55
and over was carried out through elderly
associations and retirement homes. The experiments
were done on site during social activities organized
by the associations or in the residences’ living room
in which computer equipment is made available to
the participants. This project was approved by the
ethics committee at each of the authors’ universities.
All participants signed a consent form and were able
at any time to interrupt their participation without
any prejudice. A list of available human resources in
their region was provided to them if needed.
4.3 Analyses
The analysis comprised the calculation of
frequencies and percentages for each question. The
Fisher’s exact test was used to determine the
significance of the differences between the
responses of the pretest and post-test. Since the
variables were not normally distributed, the use of
Can Digital Games Help Seniors Improve their Quality of Life?
97
parametric tests such as the paired samples t-test was
discarded.
5 RESULTS
Of the 67 participants of the study, 56 (83%)
completed the pre- and post-test questionnaires in
their entirety, providing all the required information.
Table 2 shows the analysis of the 56 respondents.
Table 2: Sample characteristics (sex, age group and level
of online gaming skills (n = 56).
Age
Group
Level of
Online
Gaming
Skills
Men Women TOTAL
Between
55 and
64
Beginner 4 10 14
Intermediary 2 4 6
Subtotal 6 14 20
65 and
over
Beginner 8 18 26
Intermediary 1 9 10
Subtotal 9 27 36
TOTAL 15 41 56
The sample included 41 women and 15 men. 20
participants (36%) are aged 64 or under and 36
subjects (64%) are 65 or older. 40 players have
stated they are "beginners" in relation to their level
of online gaming skills, while 16 participants were
considered "intermediate" (Initially we presented
three skill levels. Two respondents were "experts".
Given the low numbers, we decided to integrate
them with the intermediate players).Note that the
initial trial period was one month and that seniors
were
the participants have little invited to play at
least one game per week for a minimum of four
games with two other participants. However, the
technological constraints of the locations for the
experiment (little or no computer equipment or
connectivity) reduced the experimental period for
one week. All seniors played at least one game, 79%
of them played two games and 21% of seniors
played four games.
In the following subsections we present the
perceptions of participants (n = 56) regarding the
effects of playing online on their quality of life.
These effects are grouped according to the
previously described dimensions: physical state,
psychological aspects and social environment. Table
3 shows the results related to these three dimensions.
Table 3: Results in connection with the three dimensions
regarding the quality of life (n = 56).
Items Physical State
x
̄
p
Pre Post
Fatigue
2.95 3.57 0.069
Sleep
3.44 3.80 0.031
Eating Habits
4.05 4.20 0.083
Physical Activity
Habits
2.18 2.53
0.462
Items Social Environment
x
̄
p
Pre Post
Strengthening
Ties
2.90 3.79
0.001
Social
Connectedness
3.32 3.44
0.056
Friendship
3.03 3.79
0.003
Interactions with
Family
3.72 3.95 0.621
Interactions with
Friends
3.69 4.13
0.064
Items Psychological Aspects
x
̄
p
Pre Post
Depression
3.76 4.21
0.022
Ease of Doing
Activities
3.55 4.00
0.156
Mood
3.84 4.33
0.011
Isolation
3.79 4.15
0.158
Sadness
3.86 4.23
0.167
5.1 Perceptions about the Effects of
Playing Online on Physical
Well-being
Regarding the effects of the game on the players’
physical state, the results show an increase in the
means of the four items on this dimension, resulting
in an improvement in participants' perceptions
towards physical well-being (Table 3).
Fatigue - The average of the pre-test (2.95)
showed a more neutral perception of the effects that
playing online has on fatigue while the post-test
average increased by 0.62 to place it in the
favourable range (strongly agree or agree). The
percentage of participants who thought that playing
online does not tire them after a few hours of
playing went from 43% in the pretest to 63% in the
post-test. These differences are significant (Fisher's
exact test, p = 0.069).
Sleep - The general assessment of the impact of
online games on sleep also improved. Generally,
participants believe that online play does not affect
their sleep. Although the pretest average (3.44)
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showed an already favourable position on this, it
strengthened and increased by 0.36 in the post-test.
This difference is significant (Fisher's exact test, p =
0.031).
Eating Habits - Both before and after playing
online, the widespread opinion was that this activity
does not encourage participants to skip meals. This
perception was strengthened in participants (average
rose from 4.05 to 4.20). The proportion of participants
who were of the opinion that online gaming had no
effect on feeding habits has gone from 84% in the
pretest to 93% in the post-test. These differences are
significant (Fisher's exact test, p = 0.083).
Physical Activity Habits - The perception of a
positive effect from the game on physical activity
was rather low. Before playing, only 12% of
participants were of the opinion that online gaming
encourages them to be more active. Although this
proportion increased to 27% in the post-test, the
average remains in the negative range (2.18 in the
pre-test and 2.53 in the post-test). The result of
Fisher's exact test shows that these differences are
not significant (p = 0.462).
5.2 Perceptions about the Effects of
Playing Online on Social
Well-being
In regard to the effects of gaming on the social
environment of the participants, the responses show
an improvement in perception in this regard. Indeed,
there was an increase in the averages of the five
items included in this dimension (Table 3).
Strengthening Ties - With 36% in the pre-test to
75% in the post-test, the rate of participants who
agreed with the idea that the game allows them to
strengthen their ties increased significantly (p =
0.001). The average had an increase of 0.89. In other
words, the perception of the game as a means of
strengthening social ties has changed favourably.
Perception of Social Connectedness - Online
gaming promotes a social connectedness with others.
The pretest average (3.32) and post-test (3.44)
support this assertion. The proportion of participants
in agreement was 52% before playing and 66%
thereafter. These differences are significant (Fisher's
exact test, p = 0.056).
Friendship - In connection with the two
preceding items, the rate of participants who were of
the opinion that online play allows them to have
friends has increased significantly (from 40% in the
pretest to 73% in the post-test). The average
increased by 0.76 and answers converged more
around the average. These differences are significant
(Fisher's exact test, p = 0.003).
Interactions with Family - The perception towards
interactions with family remains in the positive range.
The average pretest was 3.72 and had an increase of
0.23. However, the Fisher exact test does not
conclude that these differences are significant (p =
0.621). If NSP is considered (42 in the pretest and 29
in the post-test), the significance improves, but
remains slightly nonsignificant (p = 0.139> 0.100).
Interactions with Friends - In the same vein, the
results suggest that there has been a consolidation of
the perception of interactions with friends. In the
pretest, 74% of participants found this perception
favourable. The percentage increased to 88% in the
post-test. These differences are significant (Fisher's
exact test, p = 0.064).
5.3 Perceptions about the Effects of
Playing Online on Psychological
Well-being
Regarding the effects of the game on psychological
well-being, although three of the six items that make
up this dimension do not show significant
differences, we see significant increases in the
averages as shown in Table 2.
Depression - According to participants'
responses before they used the game, 74% of
participants indicated they did not feel depressed in
the current week. In contrast, 17% said they felt
depressed. These proportions changed significantly
after using the game. The percentage of participants
who expressed not being depressed increased to 88%
while only one participant responded unfavourably.
These differences are significant (Fisher's exact test,
p = 0.022).
Ease of Doing Activities – The day after the
experiment, participants did not think that their daily
activities required an effort, and this was found both
in the pre-test (average of 3.55) and in the post-test
(4.00). Although there was an increase of 0.45 in the
average, the Fisher exact test does not confirm
significant differences (p = 0.15683). Yet it should
be noted that the NSP increased from 7 in the pretest
to 15 in the post-test, which had an impact on the
significance of the differences (If NSP is included,
the Fisher exact test p = 0.069 is less than 0.100,
then the differences may be considered significant).
Mood - The responses suggest that the game had
a positive effect on the moods of participants. The
rate of participants who expressed feeling in a good
mood had a significant increase (0.012). It rose from
77% to 88%. These differences are significant
(Fisher's exact test, p = 0.012).
Can Digital Games Help Seniors Improve their Quality of Life?
99
Isolation - The percentage of participants who
indicated they do not feel alone rose from 74% in
the pretest to 90% in the post-test. In the same vein,
the average was 3.79 and increased to 4.15.
Nevertheless, these differences cannot be considered
significant (p = 0.158> 0.100).
Sadness - Similar to the previous item, the
percentage of participants who said they did not feel
sadness has gone from 81% in the pretest to 88% in
the post-test. Similarly, the average was 3.86 and
went up to 4.23 for an increase 0.37. However, the
Fisher exact test showed no significant difference (p
= 0.167.).
Feeling Loved - Participants in the study felt
loved. The answers show that this perception was
positive both before and after the use of the game.
This is confirmed by the averages of the pretest
(4.24) and the post-test (4.37) and by the
participant’s rate of agreement (95% in the pretest
and 90% in the post-test). These differences are
significant (Fisher's exact test, p = 0.016).
6 DISCUSSION
We recall that the content of the Live Well, Live
Healthy! game addresses the three dimensions of the
quality of life in the form of closed questions: the
physical state, the psychological aspect and the
social environment.
Overall, the results showed significant
differences in a majority of the variables that were
analyzed. Playing the Live Well, Live Healthy!
game online resulted in the participants improved
perception of their quality of life concerning their
psychological, physical and social states. So our
hypothesis that digital games improve seniors'
quality of life was confirmed through the physical,
social and psychological aspects. Digital game
development aimed at seniors is promising.
However, certain items seem questionable. What
about the non-significant variables?
The respondents reported that playing online
gave them no incentive to be more active. It is true
that most online games, individual or in group, are
not combined with physical devices such as
Nintendo Wii and Microsoft Kinect Xbox 360 from
which according to Daniel (2012) and Singh et al.
(2013), promote improvement in physical
conditioning. The interactions in the Live Well, Live
Healthy! game are done using a touch-screen or
mouse. The content of the game covers how to adopt
good physical habits. It seems that this way of
educating seniors, that is, by offering models of
good physical habits without putting them into
action from within the game, maintains their
perceptions that online games do not encourage
them to be more active.
As for their psychological state, playing online
for a limited period does not seem to change the
perception of seniors who feel isolated and sad. It is
interesting to note that participants who reported
feeling in a better mood after playing an educational
game, which was linked to the enjoyment in playing
the game according to Rosenberg et al. (2010),
should have normally felt less sad as well but this
was not the case. We would hypothesize that the
source of their sadness is more due to their social
isolation caused by lack of contact with friends
and/or family (Wollersheim et al., 2010) and that
their gameplay did not change this situation during
the period of our intervention.
Despite the interaction of respondents with
others (who were not family members) during the
game, it seems that those who had this perception
before the game did not change as a result of their
participation in the Live Well, Live Healthy! game.
These results lead us to question the time allowed to
seniors for playing. Given the technological
constraints that the participants had little or no
computer equipment nor sufficient connectivity at
their disposal particularly in their seniors residences,
we limited the playing time to one week in order to
move the equipment to the different locations. This
may explain the results that were obtained? Most
studies done with seniors that have obtained positive
results on the cognitive, social, psychological or
physical level (Sauvé et al., 2015) experimented on
the games for a period of at least three weeks. Only
the study done by Seçer and Satyen (2014) obtained
no significant difference when they experimented on
their game over a period of two to three weeks.
In terms of the social environment, playing
online maintained their perception towards the
proximity of the family but nothing more. However,
during the testing of the game, few seniors played
with their families; they mostly experimented with
friends and people around them at the residence. Can
the context of the experiment explain the
participants’ unchanging perception of this aspect?
This is a question for further research.
7 CONCLUSIONS
The results of our study indicate that educational
games among seniors, lead to an improved
perception of their quality of life encompassing the
CSEDU 2016 - 8th International Conference on Computer Supported Education
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following aspects: physical state (fatigue, sleep,
eating habits); social well-being (strengthening ties,
social connectedness, friendship and interaction with
friends) and psychological well-being (depression,
ease of doing activities, mood and feeling loved). As
for sadness, isolation, interactions with family and
physical habits, the perception of a positive effect
remains weak among seniors.
While showing very positive results regarding
the three dimensions of the study, several limitations
have nuanced our findings: the small number of
respondents (n = 56), the experimental time (one
week), the limited number of games in which
respondents participated (between one and four
games). Similarly, the use of a board game designed
with learning objectives and offered online limits the
generalizability of our results for the same type of
games.
Further studies should be made to overcome
these limitations and consider the impact of online
educational games on seniors.
ACKNOWLEDGEMENTS
We would like to thank the research assistants
involved with this study: Samuel Venière for
recruitment and data collection in the field, Aurélie
Faticati for the literature review and Gustavo Adolfo
Angulo Mendoza for the statistical analysis of the
data of the study.
We also thank the SSHRC for their financial
support to conduct this study.
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