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Wageningen University - Department of Social Sciences
MSc Thesis Chair Group Strategic Communication
Acceptance of serious games by community-dwelling elderly
Serious games as possible intervention to improve older adults’ mood
July 2016
Applied Communication Science - Strategic Communication
Student: Eva Troost (920313-843-020)
Supervisors: Dr. Jorinde Spook
Prof. dr. ir. Lisette de Groot
Thesis code: CPT-81333
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Abstract Background The Dutch population is ageing which causes an increase in physical and mental health
problems. Elderly who suffer from chronic diseases are particularly vulnerable to depression.
Depression worsens the outcomes of diseases and increases mortality. It often goes unrecognized and
treatment is not always as effective as it should be. Therefore, the need for prevention programs aimed
at the risk indicators of depression is increasing. E-Health applications may be interesting as part of a
prevention program since ordinary interventions are often perceived as uninteresting, affecting
elderly’s motivation and commitment. This study assessed the acceptance of serious games, a form of
e-Health, by community-dwelling elderly.
Methods A total of 246 respondents completed a questionnaire. One respondent was excluded from
the study because he lived in a nursing home. The questionnaire assessed elderly’s game preferences,
their mood using the Positive Affect Negative Affect Schedule (PANAS) and the acceptance of
serious games using an adapted version of the Unified Theory of Acceptance and Use of Technology
(UTAUT). UTAUT was applied to the example of the serious game Wii Fit for Nintendo Wii.
Stepwise multiple regression analysis and a moderator analysis were conducted in order to find out to
what extend the model fit.
Results. The variables game expectancy and effort expectancy were significant predictors and
explained 71,3% of the variance in attitude. Attitude and social influence were significant predictors
for game intention and explained 36,8% of its variance. For mood and attitude, as well as for
facilitating conditions and game intention, no significant relations were found. The variable gender
moderated the relation between game expectancy and attitude slightly. Furthermore, the relation
between attitude and game intention was positively moderated by the age-related functional
limitations mobility restrictions and visual impairment.
Conclusions The model used in this study explains 36,8% of the variance in game intention while the
original UTAUT explains 70%. In this context, the theoretical framework used in this study cannot be
used to explain the acceptance of serious games by community-dwelling. For further research it is
recommended to use UTAUT2 as it includes more constructs that might explain elderly’s game
intention. Finally, it is recommended to study the acceptance of serious games in an experimental
design.
Keywords: Serious Games, Unified Theory of Acceptance and Use of Technology, Positive and
Negative Affect Schedule, Mood, Community-dwelling Elderly, Nintendo Wii
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Preface During my childhood, I was already fond of playing games. Playing games taught me to be
competitive, think strategic and play with others. However, most important to me at that time was that
games were fun. Although I must admit that there have also been occasions when game attributes were
thrown off the table whenever I lost a game. So yes, games also taught me how to cope with losing.
It was not until recently that I realized that I had my first experience with playing serious
games at the age of 5. I had some trouble with the pronunciation of certain words for which I needed
speech therapy. During the therapy I needed to do a lot of exercises, but luckily, the therapy always
ended with playing a game. However, there was something strange about these games, the rules
always included extra steps which forced me to practice my pronunciation even more!
While I was studying for my Bachelor Communication and Multimedia Design, my interest in
e-Health arose. This was also the first time that I learned about the concept serious games. During the
master Applied Communication Science at Wageningen University, my interest in serious games
grew. My internship at a hospital gave me the opportunity to talk to several caregivers about the
possible implications of e-Health and serious games. At that moment I decided that I wanted to do my
master thesis about serious games. Around the same time, Jorinde Spook published a thesis topic
regarding the acceptance of serious games by elderly on the website of Applied Communication
Science.
Jorinde Spook, my first supervisor, supported me during the process of my thesis by providing
me feedback via e-mail and in person. She also encouraged me to go out of my comfort zone and
conduct a quantitative research even though I had little experience with this. I enjoyed working with
her because of her knowledge on the subject and her confidence in my research skills. With my second
supervisor, Lisette de Groot, I mostly communicated at a distance. Her objective opinion on my work
enabled me to progress and make decisions regarding my research on crucial moments. Although I
conducted my thesis just partially at their department, Anne van de Wiel and Dione Bouchaut helped
me select participants for my thesis and sent out the questionnaires. Evert-Jan Bakker advised me on
which analyses to conduct on my data, which gave me guidance to carry out my measurements.
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Furthermore, I want to thank Robin Splithof for sharing his thoughts on the subject, his critical
view on my work and for inspiring me with his own thesis. Also, I want to thank Simone Leijdekkers
for our discussions, which could be serious at one moment and light-hearted the next moment. Last
but not least, I want to thank my family and friends for supporting and encouraging me during the
process.
Finally, I hope that the results from my thesis will add to the knowledge about elderly’s
acceptance of serious games and that further research will be conducted on whether serious games can
be used for the prevention of depression.
Eva Troost
Arnhem, July 2016
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Table of Contents
Abstract...........................................................................................................................................iPreface...........................................................................................................................................iiFigures and tables.........................................................................................................................vi
Abbreviations.....................................................................................................................................vi1. Introduction...............................................................................................................................1
1.1 Problem Statement........................................................................................................................11.2 State of the Art..............................................................................................................................3
1.2.1 Serious Games.......................................................................................................................31.2.2 Game Elements......................................................................................................................41.2.3 Unified Theory of Acceptance and Use of Technology (UTAUT)........................................5
1.3 Research Questions.......................................................................................................................62. Theoretical framework...............................................................................................................7
2.1 Attitude..........................................................................................................................................72.1.1 Hypotheses Attitude..............................................................................................................8
2.2 Game Intention.............................................................................................................................92.2.1 Hypotheses Game Intention...................................................................................................9
2.3 Moderators..................................................................................................................................102.3.1 Hypothesis Moderators........................................................................................................10
3. Methods....................................................................................................................................113.1 Sampling.....................................................................................................................................113.2 Research Design.........................................................................................................................113.3 Procedures..................................................................................................................................123.4 Measures.....................................................................................................................................12
3.4.1 Operationalization of Variables...........................................................................................123.4.2 Case Questionnaire: Wii Fit.................................................................................................143.4.3 Statistical Analysis..............................................................................................................14
4. Results......................................................................................................................................164.1 Descriptive Statistics...................................................................................................................164.2 Game Preferences.......................................................................................................................184.3 Univariate Analysis.....................................................................................................................194.4 Multivariate Analysis..................................................................................................................19
4.4.1 Correlation Analysis............................................................................................................194.4.2 Multiple Regression Analysis..............................................................................................204.4.3 Cross-validation of Stepwise Regression.............................................................................21
4.5 Moderator Analysis.....................................................................................................................224.5.1 Gender.................................................................................................................................224.5.2 Age-related Functional Limitations.....................................................................................234.5.3 Game Experience.................................................................................................................23
4.6 Expected Influence of Serious Games on Mood..........................................................................234.7 Model with Relations between Variables....................................................................................24
5. Discussion.................................................................................................................................255.1 Findings......................................................................................................................................255.2 Literature....................................................................................................................................25
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5.3 Implications................................................................................................................................285.4 Limitations..................................................................................................................................295.5 Recommendations for Future Research......................................................................................305.6 Conclusion..................................................................................................................................31
6. References................................................................................................................................327. Appendices...............................................................................................................................37
Appendix I – Game Elements............................................................................................................37Appendix II – Feedback Pre-test.......................................................................................................38Appendix III – Positive and Negative Affect Schedule......................................................................39Appendix IV – Establishment of Questions UTAUT..........................................................................40Appendix V – Questionnaire.............................................................................................................43
Onderdeel 1 – Algemene gegevens..............................................................................................43Onderdeel 2 – Digitale spellen.....................................................................................................45Onderdeel 3 – Spelen van een serious game.................................................................................48Onderdeel 4 – Stemming..............................................................................................................53Onderdeel 5 – Serious games en stemming..................................................................................54
Appendix VI – Results Open Questions.............................................................................................55
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Figures and tables Figure 1 – Theoretical framework for this research ................................................................................. 7 Figure 2 – UTAUT for acceptance of serious games by community-dwelling elderly. ........................ 24 Figure 3 - Game elements ...................................................................................................................... 37 Figure 4 - The PANAS. ......................................................................................................................... 39 Table 1 - Distribution of respondents' age categories ............................................................................ 11 Table 2 - Cross-tab to compare level of education with whether respondents play digital games ........ 17 Table 3 - Descriptives on respondents’ attitude towards using the device in their daily lives.. ............ 17 Table 4 - Type of games and the extent to which respondents like these games .................................. 18 Table 5 - Data description of variables of the theoretical framework ................................................... 19 Table 6 - Correlations between variables of the theoretical framework ................................................ 20 Table 7 – Unstandardized regression coefficients for attitude and the significance levels of the
independent variables .................................................................................................................... 21 Table 8 - Unstandardized coefficients for game intention and the significance levels of the dependent
variables ........................................................................................................................................ 21 Table 9 - Establishment of questions UTAUT ...................................................................................... 40 Table 10 - Digital games played by the respondents ............................................................................. 55 Table 11 - Other games respondents like that don't fit in game categories ........................................... 57 Table 12 - Elements a game should contain .......................................................................................... 58 Table 13 - Reasons to dislike a game ..................................................................................................... 59 Table 14 - Reasons why serious games might improve a person's mood .............................................. 60 Table 15 - Reasons why serious games could worsen a person's mood ................................................ 61 Abbreviations AT Attitude
CBS Central Bureau for Statistics
EE Effort Expectancy
FC Facilitating Conditions
GE Game Expectancy
GI Game Intention
PA Positive Affect
PANAS Positive and Negative Affect Schedule
PE Performance Expectancy
NA Negative Affect
SI Social Influence
UTAUT Unified Theory of Acceptance and Use of Technology
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1. Introduction
1.1 Problem Statement
The Dutch population is ageing: in 1990, 1,9 million persons in the Dutch population were
seniors (persons above the age of 65, from now on referred to as elderly or older adults) which equaled
12,8% of the population at the time (Central Bureau for Statistics, 2016). In 2015 the number of older
adults living in the Netherlands increased up to 3 million, which accounted for 17,7% of the Dutch
population (Central Bureau for Statistics, 2016). Reasons for the ageing of the population are that
fertility and mortality rates decline. This is caused by a decline in child mortality and a decrease of
mortality risks for elderly, resulting in an increase of life expectancy (United Nations, 2010).
As age increases, so will physical and mental health problems like visual impairments,
coronary heart diseases, osteoarthritis and diabetes mellitus (Honigh-Vlaming, 2013; Nationaal
Kompas Volksgezondheid, 2013). The average age when people in the Netherlands tend to get health
problems is 70 years (Polder, Wong & Wouterse, 2012). Although the life expectancy for women is
slightly higher than for men (82,7 years compared to 78,5 years), women spend most of these extra
years in poor health as women are facing health concerns for the last 13 years of their lives, whereas
men do so for 7 years (Polder et al., 2012). As the distribution of the major group of diseases is evenly
among men and women, the difference might be caused by different types of diseases within these
groups (Nationaal Kompas Volksgezondheid, 2013). When considering cancer as a group of diseases,
the type of cancer that causes the highest burden of disease for men is lung cancer, while for women
this is breast cancer (Nationaal Kompas Volksgezondheid, 2013). The increase in health problems at
higher age in part explains why healthcare costs for society increase with age.
As a consequence of this change in demographics and the related economic risks, the
European Commission (2007) states that policies should be aimed at increasing healthy life years
through healthy ageing and prevention policies. Elderly who suffer from chronic medical diseases and
cognitive impairment are especially vulnerable to depressions (Alexopoulos, 2005). “Depression is a
clinical term used to describe extreme negative mood characterized by persistent sadness and
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impairment in functioning” (Russoniello, O’Brien & Parks, 2009, p. 54). Clinical as well as
subclinical depression worsens the outcomes of diseases and increases mortality (Alexopoulos, 2005;
Penninx as cited in Bergh Jets, Timmermans, Hoeymans & Woittiez, 2004). Preventing depression
may therefore contribute to increasing healthy life years. Jongenelis, Pot, Eisses, Beekman, Kluiter
and Ribbe (2004) distinguish persons with minor depression, major depression and persons who have
significant depressive symptoms but cannot be diagnosed with depression according to research
criteria. The study by Jongenelis et al. (2004) shows that depression is especially prevalent among
elderly nursing home residents: the prevalence of elderly living in nursing homes who suffer from
some type of depression is 46,2%. This is about three to four times higher than the prevalence of
depression among community-dwelling elderly (Jongenelis et al., 2004). Depression among elderly
nursing-home residents is often not identified and undertreated (Jongenelis et al., 2004). Current
treatment methodologies avert just 13% of the burden of depression and 36% if the coverage of the
treatment would be optimal (Andrews, Sanderson, Corry & Lapsley, 2000). Cuijpers, Straten and Smit
(2005) and Veer-Tazelaar, Cuijpers and Beekman (2011) argue that the low effectiveness of the
treatment is another reason why the need for intervention programs for depression among elderly is
increasing.
The intervention program by Veer et al. (2011) aimed at preventing depression and anxiety
among community-dwelling elderly proved to be more effective than treatment: the incidence of
anxiety and depression decreased with 50% after one year and positive effects remained even the
second year after the intervention. Jongenelis et al. (2014) argue that interventions aimed at prevention
should be focused on the risk indicators of depression that can be influenced like: recent negative life
events, for example losing a loved one, and lack of social support caused by a shrinking social
network. Furthermore, loneliness and perceived inadequacy of care are modifiable factors (Jongenelis
et al., 2014).
According to Veer-Tazelaar et al. (2011) a lot of elderly suffer from depressive and anxiety
symptoms which are the most important risk factors for the development of depression and anxiety
disorders. As depression is a term to describe extreme negative mood, mood is perceived as risk
indicator of depression in this thesis (Russoniello et al., 2009). Depression is much less prevalent
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among community-dwelling elderly and as this thesis focuses on the prevention of depression, it is
targeted at community-dwelling elderly.
1.2 State of the Art
Current health interventions are not always perceived as motivating by elderly as they
frequently consist of repetitive activities (Marin, Navarro & Lawrence, 2011). A motivation-enhancing
opportunity is e-Health, referring to “all forms of electronic health care delivered over the internet,
ranging from informational, educational, and commercial ‘products’ to direct services offered by
professionals, non-professionals, businesses, or consumers themselves” (Maheu, Whitten & Allen,
2001, pp. 3-4.). E-Health interventions may enhance elderly’s motivation because it allows them to be
better in control of their own health (Timmer, 2010). According to Stroetmann, Hüsing, Kubitschke
and Stroetmann (2002), e-Health offers opportunities for elderly since older adults tend to live alone
without family members to look after them. In their research Stroetmann et al. (2002) found that older
adults (aged 50 to 80+) do have an interest in e-Health applications, especially when they have
experience and interest in information technology applications, but that this interest was considerably
less when age increased. Peek, Wouters, Luijkx and Vrijhoef (2016) found that acceptance of the
technology and the existence of favorable prerequisites for its use are essential for the successful
implementation of new technologies among elderly.
1.2.1 Serious Games
A form of e-Health are serious games (Krijgsman, 2014). Serious games are games with
another purpose than solely entertainment (Michael & Chen, as cited in Breuer & Bente, 2010). Abt
(1987): “We are concerned with serious games in the sense that they have an explicit and carefully
thought-out educational purpose and are not intended to be played primarily for amusement” (p. 9).
Learning aspects of serious games can be in a game’s design or be determined by its context (Abt, as
cited in Breuer & Bente, 2010). Serious games may be accepted by elderly as intervention technique
when the design is aimed at their needs and fun elements are implemented (Marin et al., 2011).
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DeSmet et al. (2014) state that serious games can have a small positive effect on a healthy
lifestyle and its determinants, especially for the person’s knowledge of the subject that the game is
aimed at. Knowledge is also the determinant in which long-term effects are maintained, while this is
not the case for behavior (DeSmet et al., 2014). Lee, Kim and Kim (2015) found similar results
regarding the effect of serious games in retaining or improving physical abilities. Although their
intervention was too short to find physical changes, their results are promising: “Highly positive
effects in perceived health beliefs and concerns, reliability, ease of use, and perceived behavioral
control were detected” (Lee et al., 2015, p. 181). Kahlbaugh, Sperandio, Carlson and Hauselt (2011)
found that playing sports games on the game console Nintendo Wii has a positive influence on
elderly’s well-being, especially on decreasing their loneliness and improving their mood.
1.2.2 Game Elements
Elderly’s technological experiences with games may be limited, as they lived most of their
lives without these technologies (Brox, Fernandex-Luque & Tøllefsen, 2011). In addition, older adults
might suffer from functional limitations, which makes usability an important aspect in designing
serious games for elderly (Brox et al., 2011; Marin et al., 2011; Carvalho & Ishitani, 2012). As such,
the interface should take age-related functional limitations like visual limitations, mobility restrictions
and the possible burden on memory, into account (Aoki, as cited in Brox et al., 2011).
Carvalho and Ishitani (2012) state that usability is indeed very important in game design since
it is an important reason why players like a game. However, according to their research, this is not
enough to motivate elderly to actually play the game. Nap, Kort and Ijsselstein (2009) found that
elderly gamers play digital games for fun and relaxation, but also to escape from reality (e.g. to escape
from the grieve of losing someone or to escape from daily activities), to stay in touch with society and
to give meaning to their day. The qualitative research by Nap et al. (2009) was conducted on a small-
scale. To improve the validity of these findings it is important to conduct a comparable study on the
factors that constitute elderly’s determinants or intention to play serious games using quantitative
methods.
5
To be able to comprehend how games are constructed, the analogy of games and their
elements by Järvinen (2008) is used as background information for this thesis. A description of
Järvinen’s (2008) analogy can be read in Appendix I – Game elements. Järvinen (2008) uses the
premise that a game is a system. This premise is also used in this thesis to set up a theoretical
framework.
Research thus far has focused mainly on usability aspects of serious games for elderly and the
impact of playing serious games on health. However, little research has focused on elderly’s
acceptance of serious games (Ibrahim & Jaafar, 2011). The main purpose of this thesis is therefore to
study the factors that constitute the acceptance of serious games by elderly in order to find out whether
serious games may be interesting as part of a prevention program for depression.
1.2.3 Unified Theory of Acceptance and Use of Technology (UTAUT)
This thesis uses a model which is based on the Unified Theory of Acceptance and Use of
Technology (UTAUT) by Venkatesh, Morris, Davis and Davis (2003) and it includes aspects of
UTAUT2 (Venkatesh, Thong & Xu, 2012).
UTAUT is a model that is derived from eight models and theories and assesses individual
acceptance of new technologies in organizations (Venkatesh et al., 2003). UTAUT consists of four
determinants of behavioral intention and usage of technology: Performance Expectancy (PE), Effort
Expectancy (EE), Social Influence (SI) and Facilitating Conditions (FC) (Venkatesh et al., 2003).
Venkatesh et al. (2003) also identified four moderators of the relations: gender, age, experience and
voluntariness of use. The model explains 70% of the variance in behavioral intention (Venkatesh,
2003). UTAUT2 is aimed at the acceptance of consumers and individuals and has three extra
constructs: hedonic motivation, price value and habit (Venkatesh et al., 2012). Based on these models
and the findings by Ibrahim and Jaafar (2011) stating that usability aspects, together with social factors
and facilitating conditions, influence user decisions about an information system, a theoretical
framework is developed as is described in chapter 2. As this thesis focuses on mood as risk-indicator
of depression, mood was added as construct to the framework.
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1.3 Research Questions
This thesis tested whether the theoretical framework can be applied to identify the factors that
constitute community-dwelling elderly’s acceptance of serious games.
Main research question
Can the adapted version of UTAUT be applied to explain the acceptance of serious games by
community-dwelling elderly?
Sub research questions
1. How does elderly’s mood affect their attitude towards serious games aimed at
preventing depression?
2. How do the different constructs on attitude towards serious games and game intention
relate to each other?
3. How do the variables gender, age-related functional limitations and game experience
moderate the relations between the constructs and attitude and game intention?
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2. Theoretical framework
The theoretical framework used in this thesis is visualized in Figure 1 and will be explained in
the following sections.
Figure 1 – Theoretical framework for this research. Adapted from “User Acceptance of Information Technology: Toward a Unified View,” by V. Venkatesh, M.G. Morris, G.B. Morris & F.D. Davis, 2003, MIS Quarterly, 27, p. 447. Copyright 2003 by MIS Quarterly.
2.1 Attitude
The theoretical framework of this thesis is based on UTAUT. In the original UTAUT Attitude
(AT) is left out because according to Venkatesh et al. (2003), the relation between attitude towards
technology and intentions arises from the effect of performance expectancy and effort expectancy.
However, Welmers (2005) argues that attitude consists of cognitive (beliefs and knowledge), affective
(feelings and emotions) and conative (actions or behavior) components. In UTAUT the variables
performance expectancy and effort expectancy make up the cognitive component of attitude and
intention is the conative component (Welmers, 2005). This means that when attitude is excluded, there
are no affective factors included in the model (Welmers, 2005). Therefore, attitude is added as variable
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in this framework. An additional reason for adding attitude is that games themselves influence the
affective component of attitude as well since they provide fun for players (Carvalho & Ishitani, 2012).
As mentioned in the previous chapter, this thesis focused on mood as determinant of
depression. Therefore, mood was added as the first construct of this model. Moods have a considerable
effect on attitudes: a positive mood leads to a higher likelihood of positive effects (George & Brief,
1992; Wegener, Petty & Klein, 1994). The mood scale Positive Affect and Negative Affect Schedule
(PANAS) is used to measure the participants’ mood (Watson, Clark & Tellegen, 1988).
The second construct is game expectancy (GE) (in the original UTAUT referred to as
performance expectancy): the extent to which elderly believe that they will learn something from
playing the serious game (Venkatesh et al., 2003).
Effort expectancy (EE), the third construct, is about the expected ease of use of the game
(Venkatesh et al., 2003). As in the original UTAUT, a positive relation between game expectancy and
attitude is expected as well as between effort expectancy and attitude.
2.1.1 Hypotheses Attitude
Below the hypotheses regarding attitude as dependent variable are stated. The first hypothesis
answers sub question 1, hypothesis 2 and 3 partially answer sub question 2.
• H1: Elderly’s mood is positively related to their attitude towards serious games.
• H2: Elderly’s game expectancy is positively related to their attitude towards serious games.
• H3: Elderly’s effort expectancy is positively related to their attitude towards serious games.
Furthermore, it is expected that playing serious games might have a positive influence on
elderly’s mood since fun elements and social connections are included (Russoniello et al., 2009;
Kahlbaugh et al., 2011). However, measuring the actual impact of gaming on mood is beyond the
scope of this research. Therefore, only the extent to which elderly think playing serious games could
improve their mood is included to get an indication for the relevance of further research.
9
2.2 Game Intention
Attitude, social influence (SI) and facilitating conditions (FC) are the constructs that determine
behavioral intention, in this thesis referred to as game intention (GI). Social influence is about the
extent to which a person perceives that others think he or she should play the game (Venkatesh et al.,
2003). It is determined by a person’s subjective norm, social factors and image and influences
behavioral intention through compliance, internalization and identification (Venkatesh et al., 2003).
Facilitating conditions can be described as the extent to which a person believes to have the
infrastructure to play a serious game (Venkatesh et al., 2003). In UTAUT, facilitating conditions only
influence the actual usage of a system. However, in UTAUT2 it is described that as consumers’
contexts vary, facilitating conditions act more like perceived behavioral control in the Theory of
Planned Behavior and therefore does have a direct influence on intention (Ajzen, as cited in Venkatesh
et al., 2012). This is also the case in this research, so therefore a direct link between facilitating
conditions and game intention is expected.
2.2.1 Hypotheses Game Intention
The hypotheses below partially answer sub question 2.
• H4: There is a positive relation between elderly’s attitude towards serious games and their
intention to play serious games (game intention).
• H5: There is a positive relation between social influence and elderly’s game intention.
• H6: There is a positive relation between facilitating conditions and elderly’s game intention.
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2.3 Moderators
Next to the different constructs there are some moderators in UTAUT of which the following
are important for this study: gender and (game) experience. The variable age as moderator is in this
model replaced by age-related functional limitations as these are strongly related to age and may
influence elderly’s perception of usability (Carvalho & Ishitani, 2012). IJsselstein, Nap, Kort and
Poels (2007) mention three physical age-related functional limitations which are important for digital
game design for elderly: visual impairment, hearing impairment and mobility restrictions.
2.3.1 Hypothesis Moderators
The hypothesis regarding the moderators answers sub question 3.
• H7: The associations between the different variables in the model are positively moderated by
the variables gender, game experience, and negatively moderated by age-related functional
limitations. The effect of the associations between the variables will be stronger for women
who have digital game experience and don’t suffer from age-related functional limitations.
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3. Methods
3.1 Sampling
The population of interest were male and female community-dwelling elderly above the age of
65. The participants were recruited from an existing database of the Division Human Nutrition with
elderly who are willing to participate in research. The participants were approached via e-mail.
A questionnaire was set up using the software Limesurvey and was sent out to 1230 eligible
participants. In total the questionnaire was completed by 246 respondents, indicating a response rate of
20,5%.
The male-female ratio was fairly even: 122 respondents were male, which equaled 49,6%, and
124 respondents, 50,4%, were female. The age distribution of the respondents is shown in table 1.
Table 1 - Distribution of respondents' age categories
Age category Number Percent Cumulative percent 65 – 70 118 48,0 48,0 70 – 75 91 37,0 85,0 75 – 80 26 10,6 95,5 80 - 85 7 2,8 98,4 > 85 4 1,6 100,0 Total 246 100,0
Furthermore, most participants (98,9%) lived independently, one person lived in a service flat
and one other person lived in a care home. The person living in a care home is left out of further
analysis since this research targeted community-dwelling elderly.
3.2 Research Design
The research had a cross-sectional design and was aimed at explaining the factors that
determine elderly’s acceptance of serious games (Vaus, 2001). A quantitative questionnaire was used
to test the hypotheses.
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3.3 Procedures
Before the questionnaire was sent to the target population, it was pre-tested on a small scale.
This was done to find out whether the questionnaire contained mistakes and if the questions were
understood by the participants. The feedback of the pre-test is in Dutch and can be read in Appendix II
- Feedback Pre-test. The results were used to make some small adjustments to the questions.
All participants received an email with an invitation for the questionnaire once. The
questionnaire started with an introduction text explaining the research and instructions on how the
participants should fill in the survey. Completing the survey took about 20 minutes of the participants’
time. The first part of the questionnaire consisted of general questions to gather demographics. The
second part contained questions regarding digital games and participants’ game preferences. For the
third part of the survey, elderly were asked to self-assess their mood using the PANAS. After this,
elderly’s acceptance of serious games and modern technology was measured using the adapted
UTAUT model. The final part of the survey consisted of questions about the extent to which elderly
think that playing serious games might help to improve their mood.
3.4 Measures
The different constructs of the model used were described in Chapter 2. This paragraph
presents how the constructs have been operationalized and how the statistical analyses were
conducted.
3.4.1 Operationalization of Variables
Mood was measured using the PANAS (Watson et al., 1988). The PANAS is a 20-item scale
in which persons self-assess their emotional experience (Lim, Yu, Kim & Kim, 2010; see Appendix
III – Positive Affect Negative Affect Schedule). It is a brief and reliable method that is closely related
to the Tripartite Model, which is used to explain anxiety and depression, by Clark and Watson
(Crawford & Henry, 2004). The scale consisted of 10 items to measure Positive Affect (PA) and 10
items to measure Negative Affect (NA), using a five-point Likert scale (1= Very Slightly or Not at All,
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2= A Little, 3= Moderately, 4= Quite a Bit, 5= Extremely). Depression is characterized by a high NA
and a low PA (Watson et al., 1988). Long-term instructions were included in PANAS to decrease the
influence of fluctuations in mood (Watson et al., 1988). Thus, for the PANAS, participants were asked
to rate to what extent they experience a certain emotion (e.g. interested, distressed, excited) in general.
The outcomes of the PANAS were compared to a reference population, which was the mean outcome
of the population: 35.0 for PA (standard deviation of 6.4) and 18.1 for NA (SD= of 5.9) (Watson et al.,
1988). A factor analysis was conducted to check whether the various items load on the same factor.
After this, the reliability was calculated using Cronbach’s alpha, which was .86 for both PA and NA.
The operationalization of game experience, effort expectancy, attitude, social influence,
facilitating conditions and game intention was similar to that of the original UTAUT. Each variable
contained three or four items which were rated by the respondents using a unipolar 5-item Likert scale
(1= Completely Disagree, 2= Disagree, 3= Don’t Disagree, Don’t Agree, 4= Agree, 5= Completely
Agree). Items from UTAUT and UTAUT2 were converted to fit this example, as can be read in
Appendix IV - Establishment Questions UTAUT. An example of a statement for game expectancy is:
“Playing Wii Fit will help me increase my chances to improve my health” and an example of social
influence is: “People who influence my behavior think I should play Wii Fit”. In total the respondents
rated 24 statements. The choice for a 5-item scale was made because this is less exhausting for
participants and 5-items scales are equally reliable as 7-item scales (Dawes, 2008). A factor analysis
was conducted. To increase the reliability and validity, item EE5r “I think the functional limitations I
suffer from, will hinder me in playing Wii Fit” from the construct effort expectancy was deleted.
Cronbach’s alpha for the constructs were: GE= .94, EE= .92, AT= .95, SI= .95, FC= .85, GI= .98.
Next to measuring the different constructs, also three moderators were measured. The
moderators gender and game experience were dichotomous variables. The moderator age-related
functional limitations was a categorical variable. This variable was operationalized into the categories
no limitations, visual impairment, hearing impairment, mobility restrictions and the option prefer not
to say. (IJsselstein et al., 2007). The complete questionnaire is in Dutch and can be read in Appendix
V - Questionnaire.
14
3.4.2 Case Questionnaire: Wii Fit
This section elaborates on the operationalization of the theoretical framework by describing
Wii Fit, which is used as a case in the questionnaire. Wii Fit is an example of a serious game. The
choice for Wii Fit as case was made as Kahlbaugh et al. (2011) found that playing a Wii game resulted
in a greater positive mood among community-dwelling elderly. Wii Fit is a game for the game console
Nintendo Wii, a game console that can be connected to a TV. It has a remote control that detects the
player’s movements and position.
The game Wii Fit is a health and fitness game that can be played on Nintendo Wii. It provides
various exercises to do fitness like yoga, muscle trainings, aerobics exercises and balance games. The
game is provided with a balance board with an integrated scale. The use of the balance board enables
the Nintendo Wii to know the player’s position and posture. Thus to play Wii Fit, the player uses the
remote control and stands on the balance board. Before the game, the player can decide what his
health goal is and the number of calories he wants to burn. After this the player chooses which game
he wants to play.
In the questionnaire respondents could read a similar description of the game Wii Fit.
Additionally, two pictures of persons playing the game were added, as well as a link to a video in
which the game was explained.
3.4.3 Statistical Analysis
Descriptive statistics were used to summarize the demographics and elderly’s game
preferences. Elderly’s mood was assessed by comparing the outcome of the PANAS mood scale to the
reference population.
For the construct mood, the mean and standard deviation (SD) of PA and NA were calculated.
For each of the other variables (GE, EE, AT, SI, FC and GI) the mean outcome and SD were
calculated as well. Thus the outcomes of the independent and dependent variables were continuous
variables.
15
Univariate analysis was conducted to provide an overview of the means and standard
deviations of the different constructs. The hypotheses were tested using two stepwise multiple
regression analyses. In the first regression analysis the independent variables were mood (PA and
NA), game expectancy and effort expectancy. The outcome variable was attitude (AT). In the second
multiple regression analysis, AT acted as one of the dependent variables, together with social
influence and facilitating conditions. The outcome variable in this analysis was game intention. The
stepwise regression analyses were cross-validated in a random 75% sample of the complete
population.
The effect of the moderators was tested by the conduction of a moderator analysis. Interaction
terms for the dependents variables and the moderators were created. The moderator analysis tested the
effect of each moderator separately on the different relations between each independent variable on the
corresponding dependent variable. If a relation was significant, the dependent variable was stratified
by the different groups to compare the means.
16
4. Results
4.1 Descriptive Statistics
As described in the previous chapter, 245 respondents were included in this study. The mood of the
respondents was assessed using the PANAS mood-scale. The mean Positive Affect (PA) of the respondents
is 36,6 (SD= 4,6) and the mean Negative Affect (NA) is 21,9 (SD= 4,6). The average for the population,
which was used as reference population, for PA is 35,0 (SD= 6,4) and for NA 18,1 (SD= 5,9).
Most participants (75,1%) do not suffer from age-related functional limitations. From the
participants that do suffer from age-related functional limitations, 14,9% is hard hearing, 3,2% is visually
impaired and 5,6% suffer from mobility restrictions. The majority of the participants have children and/or
grandchildren (86,1%) and 61,6% of them sees their children or grandchildren at least weekly.
More than half of the respondents (56,7%) reported that they play digital games: 61,2% of them
plays digital games daily. The most important reasons to play digital games are for fun (66,9% of the cases)
and to relax (48,9% of the cases). Tablet/iPad (41,3%) and computer/laptop (38,6%) are the most
commonly used devices to play digital games, followed by smartphones (16,9%). Mobile phones without
internet and game consoles are barely used for digital gaming by the respondents (both 1,6%).
For the respondents who don’t play digital games (43,3%), the most frequently reported reasons
for not playing these games was that they don’t feel the need to play (65,1%), because they wouldn’t like
digital games (12,4%) and because they have never played digital games (10,9%).
Over 50% of the respondents is highly educated (university of applied sciences or higher). In table
2 a cross-tabulation is conducted to compare participants’ level of education with whether or not
participants play digital games.
17
Table 2 - Cross-tabulation to compare level of education with whether respondents play digital games
Percentage of respondents
play digital games
Total Yes No
Education
• Other
• Primary
• Lower pre-vocational
• Lower general secondary
education
• Intermediate vocational education
• Higher general secondary
education
• Higher vocational education
• University
0,9
2,8
3,8
13,2
7,5
8,5
41,5
21,7
0,7
0,0
7,9
18,7
16,5
12,9
30,2
12,9
0,8
1,2
6,1
16,3
12,7
11,0
35,1
16,7
Total 100,0 100,0 100,0
Although not all participants reported to play digital games, the respondents perceive the use
of some digital devices in their daily lives a good idea. The respondents could rate each of the digital
devices on a scale from 1 (‘A very bad idea’) to 5 (‘A very good idea’). The table below shows the
mean and standard deviation for each of the digital devices.
Table 3 - Descriptives on respondents’ attitude towards using the device in their daily lives (Using the device in my daily live is: 1= a very bad idea, 2= a bad idea, 3= neutral, 4= a good idea, 5= a very good idea)
Device Mean S.D.
Computer/laptop 4,30 0,72
Mobile phone (without internet) 3,38 1,02
Smartphone 3,57 1,05
iPad/tablet 3,94 0,92
Game console (Xbox, Playstation, Nintendo Wii) 2,22 0,96
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4.2 Game Preferences
For the development of a serious game for community-dwelling elderly, it is useful to know
the type of games they like and dislike. Respondents rated each game type on a scale from 1 (‘don’t
like the type of game at all’) to 5 (‘like the type of game very much’) or 6: ‘I’ve never played this type
of game’, this last option was coded as missing value. Table 4 sums up the different types of games
and the extent to which the respondents enjoy playing these games.
In an open question, respondents mentioned some other games which they like and that,
according to them, don’t fit the categories above. The most frequent games that were reported are
Scrabble, Wordfeud and Rummikub.
Two open questions were added to find out what elements elderly like and dislike in games.
The answers were categorized to be able to count the frequencies as can be read in Appendix XI –
Results Open Questions. Frequently mentioned game elements that make a game pleasurable
according to the respondents are that a game should be sociable (reported 69 out of 349 times), require
intelligence (37 out of 349 times) and must be challenging (32 out of 349 times). Elements that the
Table 4 - Type of games and the extent to which respondents like these games (1= don't like it at all, 2= don’t like it, 3= neutral, 4= like it, 5= like it very much)
Type of game N valid N missing Mean S.D.
Board games 219 26 3,53 1,00
Strategy games 188 57 3,08 1,09
Dice games 208 37 3,38 1,15
Card games 228 17 3,62 1,18
Puzzle games 229 16 3,99 1,16
Action games 183 62 1,67 0,99
Trading card games 114 131 1,82 0,89
Slots 157 88 1,75 1,02
Racing games 141 104 1,65 0,95
Sports games 152 93 2,28 1,17
Virtual life games 122 123 1,60 0,86
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respondents mentioned as unappealing are aggression and violence (reported 61 out of 288 times),
games in which speed is very important (30 out of 288 times) and games that are too complicated (30
out of 288 times).
4.3 Univariate Analysis
In table 5 an overview of the results from the different constructs is provided. The constructs
were measured using a 5-point Likert scale.
Table 5 - Data description of variables of the theoretical framework (for PA and NA 1= very slightly or not at all and 5= Extremely, for the other constructs 1= completely disagree and 5= completely agree)
Construct Mean S.D.
Positive Affect (PA) 3,66 0,46
Negative Affect (NA) 2,19 0,46
Game Expectancy (GE) 2,73 0,96
Effort Expectancy (EE) 3,14 0,85
Attitude (AT) 2,73 0,95
Social Influence (SI) 2,29 0,87
Facilitating Conditions (FC) 3,03 0,93
Game Intention (GI) 1,77 0,88
4.4 Multivariate Analysis
4.4.1 Correlation Analysis
In table 6 the correlations between the variables are shown. The table shows an important
reason why there is little concern for multicollinearity as the correlations between the different
independent variables among each other is below .7. The table also shows that game expectancy and
effort expectancy are significantly correlated to the dependent variable attitude. Attitude in its turn, is,
together with social influence and facilitating conditions, significantly correlated to the dependent
variable game intention.
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Table 6 - Correlations between variables of the theoretical framework (*p<.05, ** p <.001). PA= Positive Affect, NA= Negative Affect, GE= Game Expectancy, EE= Effort Expectancy, AT= Attitude, SI= Social Influence, FC= Facilitating Condition
Construct PA NA GE EE AT SI FC GI
PA 1
NA -.05 1
GE -.04 .09 1
EE .12 -.08 .55** 1
AT -.03 .08 .84** .53** 1
SI -.10 -.01 .58** .33** .61** 1
FC .11 -.05 .36** .57** .40** .35** 1
GI -.05 -.00 .50** .31** .58** .52** .31** 1
4.4.2 Multiple Regression Analysis
The model was tested using two stepwise multiple regression analyses. In the first analysis
attitude was the dependent variable and in the second analysis this was game intention. Table 7 shows
that only game expectancy and effort expectancy are significant predictors of attitude and therefore
positive affect and negative affect are left out of the model. The model that includes both game
expectancy and effort expectancy correlates slightly better with attitude (R= .85 and adjusted R2= .71)
than the model that only includes game expectancy (R= .84 and adjusted R2= .70) Thus, the model
with game expectancy and effort expectancy as predictors explains 71% (71,3% to be exact) of the
variance in attitude. Next to the significance level, table 7 shows the unstandardized regression
coefficient B, which shows how much attitude increases or decreases when an independent variables
increases. The formula to predict attitude is: AT = .26 + (.78*GE) + (.11*EE).
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Table 7 – Unstandardized regression coefficients for attitude and the significance levels of the independent variables
Dependent variable Unstandardized B Significance
(Constant) .26
Game Expectancy .78 .000
Effort Expectancy .11 .02
Positive Affect -.01 .80
Negative Affect .02 .60
The stepwise multiple regression analysis with game intention as dependent variable excluded
the independent variable facilitating conditions from the model since this variable was not significant.
The model that includes the two independent variables attitude and social influence, correlates slightly
better with game intention than the model that only includes attitude: R= .61 and adjusted R2=. 37
compared to R= .58 R2= .33. The model including these two predictors explains 37% (or 36,8% to be
exact) of the variance in game intention. The formula to predict game intentions is: GI= .11 +
(.39*AT) + (.26*SI).
Table 8 - Unstandardized coefficients for game intention and the significance levels of the dependent variables
Dependent variable Unstandardized B Significance
(Constant) .11
Attitude .39 .000
Social Influence .26 .000
Facilitating conditions .06 .28
4.4.3 Cross-validation of Stepwise Regression
The stepwise regression was validated by comparing the full sample to random 75% of the
sample. The result for the regression analysis with attitude as dependent variable shows that the same
variables are included in the model as for the analysis on the full sample size (game expectancy and
effort expectancy). The original stepwise regression analysis explains 71,3% of the variance in attitude
(GE: B=.78 and EE: B= .11). In the analysis with 75% of the sample, this is 75,4% (GE: B= .81, EE:
22
B= .11). Comparing the adjusted R2 from the complete sample to that of 75% of the sample shows a
difference of 4,1%, which is explained by a higher GE in the sample with 75% of the population. This
difference shows that the model cannot be generalized completely.
The same comparison was made for the stepwise analysis with game intention as dependent
variable. In the analysis with 75% of the sample the variables attitude and social influence are
included in the model, which is in accordance with the stepwise regression analysis on the full sample.
The analysis using the full sample explains 36,8% of the variance in game intention (AT: B= .39, SI:
B= .26) while the analysis on 75% of the sample explains 35,5% of the variance (AT: B= .39, SI: B=
.23). Comparing the values of R2 and B of the two samples, it shows that the second part of the model
generalizes very well.
4.5 Moderator Analysis
The moderators in the model are gender, age-related functional limitations and game
experience. The effect of each moderator was tested on the significant associations between each
independent variable and the corresponding dependent variable.
4.5.1 Gender
For the first part of the model, two interaction terms were created: one for GE and gender and
the second for EE and gender. The analysis showed that only the interaction between GE and gender is
significant (p= .03), causing a very small change in R2 of .006. This equals an increase of .6% of
variance in attitude for women. Even though the difference was very small, when the data is stratified
by gender, it is confirmed that men have a lower AT (2,57) than women (2,89).
The same moderator analysis for gender was conducted on the regression analysis with GI as
dependent variable and AT and SI as independent variables. Results from this analysis show that
neither the interaction between AT and gender, nor the interaction between SI and gender are
statistically significant.
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4.5.2 Age-related Functional Limitations
The moderator age-related functional limitations is categorical and consist of the categories:
no limitations, hearing impairment, visual limitations, mobility restrictions and prefer not to say. For
this moderator different dummy variables were created. Additionally, the interaction terms between
these dummies and the dependent variables were created.
The functional limitations are not significant moderators for the relation between GE and AT,
nor for the relation between EE and AT.
However, the age-related functional limitations are a statistically significant moderator for the
relation between AT and GI (p= .001). The moderator explains a change of 4,8% of the variance in GI.
The interaction terms between AT and visual limitations and between AT and mobility restrictions
show a significant, positive relation. This means that respondents that suffer from visual limitations
and/or mobility restrictions have a higher game intention. The mean GI for the entire population is
1,77, while this is 2,03 for respondents with visual limitations and 1,78 for respondents with mobility
restrictions.
4.5.3 Game Experience
Including game experience and interaction terms to the regression analysis with attitude as
dependent variable showed no significant results. The same applied to the regression analysis with
game intention as dependent variable.
4.6 Expected Influence of Serious Games on Mood
As actually playing a serious game was not included in this research, the extent to which
elderly think playing a serious game could improve their mood was included in the questionnaire.
Three statements on this topic were included which could be rated from 1 (completely disagree) to 5
(completely agree). The three statements were very similar, the first statement is: ‘Playing a serious
game would have a positive influence on my mood’, the other two statements included the aspect of
(2) playing a game with friends/family or (3) as competition with friends or family. The means of
24
statements are: (1) 2,67 (SD= 0,97), (2) 2,76 (SD= 0,99) and (3) 2,64 (SD= 0,99). Additionally, two
open questions were included to assess why respondents think that playing a serious game might
improve or worsen their mood. These open questions were not mandatory and the majority of the
respondents didn’t answer the questions. Reasons why respondents think that playing a serious game
could improve their mood are if the game includes social contact (reported 12 out of 60 times) and if it
helps improve their health (reported 10 times). Playing a serious game could worsen a person’s mood,
according to the respondents, if the game is too difficult (reported 6 out of 47 times). A complete
overview of the results can be read in Appendix XI – Results Open Questions.
4.7 Model with Relations between Variables
Figure 2 shows the relations of the stepwise regression analyses. The significant relations are
bold. For the non-significant relations, the arrow in the model is grey. The variance in the dependent
variables, which is explained by the corresponding independent variables, is in red.
Figure 2 – UTAUT for acceptance of serious games by community-dwelling elderly.
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5. Discussion
This main purpose of this thesis was to find out whether the adapted version of UTAUT can
be used to assess the acceptance of serious games by community-dwelling elderly. Additionally, it was
assessed whether community-dwelling elderly are an appropriate target group for a prevention
program aimed at preventing depression and if elderly think that playing serious games could
contribute to improving their mood.
5.1 Findings
The model used in this thesis explains 36,8% of the variance in elderly’s game intention.
Game expectancy and effort expectancy were found to be significant predictors of attitude and attitude
and social influence are significant predictors of game intention. The relation between attitude and
game intention was moderated by the variables visual limitations and mobility restrictions.
Furthermore, the study’s population in general does not suffer from depression which could
make them an appropriate target group for an intervention program aimed at preventing depression.
However, the respondents don’t think that a serious game can contribute to improving their mood.
5.2 Literature
In this thesis elderly’s game intention, and thus their acceptance of the serious game Wii Fit,
was rather low. An interesting contradiction is that more than half of the respondents (56,7%) play
digital games and that 92,2% of these digital gamers play games at least once a week. Peek et al.
(2016) state that, for implementation of new technologies, the technology should be accepted by
elderly and favorable prerequisites for its use should exist. The low game intention in this study might
be explained by the fact that the game Wii Fit doesn’t meet the respondents’ prerequisites on two
points. The first point is that the type of game doesn’t fit the respondents’ game preferences. Wii Fit is
a sports game, which is not a popular type of game among the respondents: it was rated with a mean of
2,28 on a scale of 1 to 5. Secondly, Wii Fit is played on Nintendo Wii, which is a type of game
console. From the respondents that play digital games, solely 1,6% reported they play games on a
26
game console. Furthermore, respondents’ attitude towards using a game console in their daily lives
was rated rather low: 2,22 on a scale of 1 to 5. An explanation for this attitude towards game consoles
is that elderly have little to no experience in using them. Other devices like computers, iPads and
smartphones, are perceived as more useful as they can also be used for other purposes than solely for
playing games.
Another explanation of the low outcome of game intention and of the other variables, is the
simple fact that the respondents have not played the game. Lee et al. (2015) found that playing serious
games results in a significant increase in health beliefs and concerns, ease of use and perceived
behavioral control at post-test compared to a pre-test. When comparing this study to the study of Lee
et al. (2015), the questionnaire might be perceived as a sort of pre-test, meaning that respondents’
game intention would be more positive after playing a serious game. In addition, their perception on
the impact of playing serious games on their mood might also be more positive after they have
experienced this. The research by Kahlbaugh et al. (2011) supports this as they found that playing
sports games on Nintendo Wii contributes to achieving a greater positive mood. Another
substantiation is the fact that the participants who have experience in playing digital games state that
reasons to play digital games are for fun (66,9% of the cases) and to relax (48,9% of the cases). This
implies that playing digital games contributes to improving elderly’s mood. If the elements that make
a digital game fun and relaxing for elderly are integrated in a serious game, the serious game might
contribute to improving their mood as well.
Three hypotheses from the theoretical framework are rejected. The first hypothesis concerns
the association between mood and attitude towards serious games. A significant positive relation was
hypothesized. Wegener et al. (1994) state that a positive mood, compared to a negative mood, leads to
a more positive attitude towards something, especially when a message is framed positively. It could
be that the rather objective description of the game Wii Fit in the questionnaire lead to a lack of
association between mood and attitude. The second hypothesis that is rejected concerns the association
between facilitating conditions and game intention. Like in UTAUT2, it was expected that, as
consumers’ contexts vary, facilitating conditions would act like the variable perceived behavioral
control in the Theory of Planned Behavior (Venkatesh et al., 2012). In this study the respondents were
27
treated like consumers in the sense that the facilitating conditions were not provided to them. It was
expected that this aspect would therefore be perceived as an obstacle towards playing serious games.
However, in this study no significant relation between facilitating conditions and game intention was
found. The reason for the absence of this direct link did not become clear from the results. It is
possible that if the actual usage of the game was measured, a direct link between facilitating
conditions and gaming would have been present. In that case, the variable facilitating conditions
would have acted like facilitating conditions in the original UTAUT and perceived behavioral control
would have worked via game expectancy and effort expectancy. The final hypothesis that is partially
rejected is hypothesis 7. The age-related functional limitations visual limitations and mobility
restrictions turned out to have a positive moderating effect on the relation between attitude and game
intention instead of a negative effect. Although the number of respondents suffering from these
limitations was very small (8 respondents reported to have visual limitations and 14 respondents have
mobility restrictions), this finding is the opposite of what was expected after studying the literature.
Since usability issues are very important in designing serious games for elderly, it seemed plausible
that suffering from functional limitations would negatively affect elderly’s game intention. An
explanation for this opposite result might be that elderly who are visually impaired or have mobility
restrictions, have positive expectations of playing a serious game. For people with visual limitations
these expectations might include the ability to adjust the settings of the game’s visual to their
preferences. People who suffer from mobility restrictions might believe that playing a serious game,
especially one that is aimed at physical activity, could help decrease their symptoms or at least prevent
their restrictions from progressing. Another aspect of this hypothesis, regarding the moderator game
experience, is rejected as well. It was expected that the presence of digital game experience would
increase the effect of the associations. However, no significant association was found. Plausible
explanations for this could be the fact that the game Wii Fit doesn’t meet the respondents’ game
preferences or that the case description made playing the game feel obligatory.
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5.3 Implications
As stated in the previous section, adding the elements that make elderly enjoy digital games
may improve their game intention and also the perceived effect of gaming on elderly’s mood. An
implication for the development of a serious game for community-dwelling elderly is to use a device
they are familiar with and which they prefer to use for playing digital games. This could be a
tablet/iPad and a computer/laptop. Regarding the type of game, it is recommended to develop a puzzle,
board, dice or card game, since these were rated rather positive in this research. According to the
respondents a game should contain a competition element and it should be challenging and sociable
(or in Dutch: ‘gezellig’). However, from the answers it did not become clear whether they meant that
the other players need to be physically present while playing the game or if playing at a distance, like
in digital games, is also considered sociable. Next to that, although it seems contradictory, it should
also be possible for elderly to play the game alone. Furthermore, nice lay-out and graphics were
considered important elements. A game for elderly should not be aggressive or contain violence. Also,
games that are too complicated and in which speed is very important are considered a letdown. This
corresponds to literature, which states that this is caused by elderly’s lack of experience with
technology and possible age-related functional limitations.
Something else which was outstanding is how busy the respondents’ lives are. A frequently
reported response to the question about why elderly don’t play digital games, but also to the other
open questions regarding game preferences, was that they didn’t have time to play games since they
have other obligations or activities. This indicates that a serious game that contains short levels or
which can be paused at any given moment may suit community-dwelling elderly better than games
with a long duration. Furthermore, it is important that playing the game doesn’t feel obligatory to the
participants as this will decrease their pleasure in playing the game. To find out whether a serious
game meets elderly’s game preferences and integrates learning aspects properly, it is important that it
is tested among elderly during various phases of the development.
29
5.4 Limitations
A threat to the validity of this research is that the questionnaire was distributed via email
among people who were registered in an existing database. This means that community-dwelling
elderly who don’t use internet were excluded from this study. However, although exact numbers
cannot be found, the Central Bureau for Statistics (as cited in NOS, 2015) states that 75% of the Dutch
elderly uses the internet daily and that this number is still growing. This means that the group of
community-dwelling elderly that can be reached via e-mail is also expanding. Still, this limitation
probably has the greatest impact on the results of this research. The results from this study may
therefore be used as starting point for further research, but cannot be generalized over the entire
population of community-dwelling elderly in the Netherlands.
Another threat regarding the validity is the fact that the response rate of the questionnaire was
quite low: 20,5%. The questionnaire was distributed via a database from which the respondents
receive requests to participate in researches frequently. It could be that, because of this, participants
are more selective in choosing the researches they participate in. Furthermore, it is known that a
number of mail addresses from the database are incorrect. However, the low response rate is still a
threat for nonresponse bias. No data were gathered from the non-respondents, so no concrete
conclusion can be drawn regarding the the representation of this research for the complete population
of elderly participants in the database.
A weakness of this research is the way the theoretical framework was operationalized to the
case of the Wii Fit. Respondents were asked to pretend to play Wii Fit to achieve a certain health goal.
It could be that this scenario was too hypothetical or that they didn’t answer the questions with this
goal in mind. Therefore, the items, especially those regarding game intention (e.g. ‘I intend to buy a
Nintedo Wii’ and ‘I’ll try to play Wii Fit in my daily life’), might have been illogical or even foolish
to them. It is also plausible that responses would have been completely different when a case about
another serious game would have been presented.
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5.5 Recommendations for Future Research
For future research it is recommended to conduct a similar study using UTAUT2. UTAUT2
contains three additional variables (hedonic motivation, price value and habit) which may provide a
more elaborate explanation on the outcome of game intention. In a future questionnaire, it is advisable
to provide an example of a serious game that suits elderly’s game and device preferences better. For
the target group it is recommended to also include community-dwelling elderly who don’t use modern
devices. Identifying the differences between those elderly and elderly who do have experience with
modern devices enables the possibility to prevent a gap between the groups when a serious game is
developed. Furthermore, it is recommended that future research elaborates on the effect of age-related
functional limitations on game intention. This research found a significant positive effect, however,
the sample was very small and it remained unclear why this effect was positive instead of negative.
In previous sections it was argued that a significant increase in the acceptance of serious
games might occur after elderly have actually played the game. Therefore, it is advised to conduct an
experiment in which elderly play a serious game as intervention. This intervention could be part of a
two-group experimental design with a test group that plays the serious game and a control group that
receives a more classical intervention. As part of the pre-test and posttest, a questionnaire similar to
the one conducted in this study may be used. An experimental research like this can also be used to
test whether playing a serious game influences elderly’s mood.
To conclude it would be valuable to conduct a research aimed at the development a serious
game for community-dwelling elderly while involving them in the design process. Organizing focus
groups with the elderly and other stakeholders might be a valuable way to start this process. Results
from this questionnaire regarding elderly’s game preferences may be used to structure the discussions
of these focus groups.
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5.6 Conclusion
The first sub research question concerns the effect of elderly’s mood on attitude, a positive
relation was hypothesized. However, no significant relation between positive affect and attitude or
between negative affect and attitude was found.
The second sub question is about the relations between the independent variables and the
corresponding dependent variable. Game expectancy and effort expectancy were the two significant
and positively related variables for attitude. Attitude and social influence were the significant positive
predictors for game intention. The relation between facilitating conditions and game intention was not
significant.
The final sub question concerns the moderators of the theoretical framework. The moderator
gender was significant for the relation between game experience and attitude, indicating a slightly
more positive effect on attitude for women. However, this effect was very small. Furthermore, in
contrast to what was hypothesized, this study found a positive moderation of the age-related functional
limitations visual impairment and mobility restrictions on the relation between attitude and game
intention.
The main research question concerns whether this adapted version of UTAUT can be used to
explain the acceptance of serious games by community-dwelling elderly. As stated before, the model
explains 36,8% of the variance in game intention. The original UTAUT, tested by Venkastesh et al.
(2003), explains 70% of the variance. Thus, although the theoretical framework used in this research
explains part of elderly’s acceptance of serious games, it explains considerably less than the original
model. Furthermore, not all variables show a significant relation in this research. This means that in
this context, the theoretical framework cannot be used to explain the acceptance of serious games by
community-dwelling elderly.
32
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37
7. Appendices
Appendix I – Game Elements
Järvinen (2008) treats games as systems. This enabled the possibility to create an analogy of
games and their elements. Järvinen (2008) proposes nine classes of game elements which are divided
in three categories. The first category is systemic elements and holds the classes components and
environment, where components are “the resources for play; what is being moved or modified in the
game” (Järvinen, 2007, p. 135) and the environment is “the space for play – board, grids, mazes,
levels, worlds” (Järvinen, 2007, p. 135). The second category, compound elements, are the game’s
ruleset (the procedures a player must follow), game mechanics (the actions the player performs as
means to achieve the game’s goal), theme (which functions as metaphor for the game and the rules),
interface and information (what the player and game need to know) (Järvinen, 2008). The behavioral
elements are in the third category which holds the players and the contexts: the players being the ones
who perform the game mechanics and the contexts explaining where, when and why the game takes
place including the physical location, players’ histories and other aspects that may influence how the
game is played (Järvinen, 2007; Järvinen 2008; Spook et al., 2015).
Figure 3 - Game elements. Retrieved from “Games without Frontiers: Theories and Methods for Game Studies and Design,” by A. Järvinen, 2007, Doctoral dissertation study for Media Culture University of Tampere, Finland.
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Appendix II – Feedback Pre-test
The questionnaire was pre-tested on three persons. Their feedback is in Dutch and is described
in this section.
Respondent 1 (behoort tot beoogde doelgroep, heeft vragenlijst ingevuld in Word):
• Ik heb filmpje bekeken, dus ik heb er langer dan 15 minuten overgedaan: 20 minuten. Ik vind het filmpje wel lang: misschien inkorten tot de kern van de informatie die je wilt.
• Vragen waren duidelijk. Niet te lang. • Vraag 7: ik speel geen sudoku maar wel graag kruiswoordpuzzels. Splitsen dat alternatief. • En als de respondent helemaal geen idee heeft – ondanks de goed uitleg vraag 10 / 11 - wat
Nintendo Wii is? (denk aan de leeftijd respondenten)
Respondent 2 (behoort bijna tot beoogde doelgroep, vragenlijst ingevuld in Limesurvey):
• Toevoegen: aan het eind van het filmpje of wanneer u voldoende begrijpt, kunt u het scherm afsluiten om terug te gaan naar de vragenlijst.
• Soorten spellen: bij beoordelen of een iemand een spel leuk vindt of leuk lijkt graag optie ‘ik heb zo’n soort spel nog nooit gespeeld’
• Of Nintendo Wii gebruikt kan worden naast andere apparaten: weet ik niet. • Consequentie in vragen UTAUT: ik zou vinden.. etc. • Dik drukken van intro-tekst in vragenlijst • Leuk om vragenlijst in te vullen
Respondent 3 (behoort niet tot beoogde doelgroep, vragenlijst ingevoerd in Limesurvey):
• Bij uitleg digitale apparaten zeggen dat Playstation etc. voorbeelden van spelcomputers zijn • Toelichten wat bedoeld wordt met ontsnappen uit realiteit (vraag over redenen dat mensen
digitale games spelen) • De optie ‘spel nog nooit gespeeld’ bij vraag over verschillende categorieën spellen links zetten
en niet rechts. • Goed dat het onderdeel over de mening van digitale apparaten in het dagelijks leven is
toegevoegd. • Bij het voorbeeld van Wii Fit iets duidelijker vermelden wat mensen daadwerkelijk moeten
doen, dus het uitvoeren van de oefeningen. • Subvragen links uitlijnen bij de vragen die in de tabel staan. • De subvragen over attitude ten opzichte van games lijken erg op elkaar.
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Appendix III – Positive and Negative Affect Schedule
An example of the PANAS is shown in figure 4. For this research the Dutch version of the
PANAS-scale from Peeters, Ponds and Vermeeren (1996) is used.
Figure 4 - The PANAS. Reprinted from “Development and Validation of Brief Measures of Positive and Negative Affect: The PANAS Scales,” by D. Watson, L.A. Clark & A. Tellegen, 1988, Journal of Personality and Social Psychology, 54, p. 1070. Copyright 1988 by the American Psychological Association, Inc.
The list of PA-items are: “. . . attentive, interested, alert, excited, enthusiastic, inspired, proud,
determined, strong and active” (Watson et al., 1988, p. 1064). The 10-item list for NA consists of: “. . .
2 terms from each of the five triads: distressed, upset (distressed); hostile, irritable (angry); scared,
afraid (fearful); ashamed, guilty (guilty); and nervous, jittery (jittery)” (Watson et al., 1988, p. 1064).
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Appendix IV – Establishment of Questions UTAUT
The items in this table are combined from the UTAUT and UTAUT2 (Venkatesh et al., 2003, p. 460, Venkatesh et al., 2012, p. 178). To be able to use
the items for this research, it was necessary to adapt them so they could be applied to the adoption of serious games by community-dwelling elderly.
Furthermore, the word system is replaced by serious games, as this research approaches serious games as systems.
Table 9 - Establishment of questions UTAUT (adapted from Venkatesh et al., 2003; Venkatesh et al., 2012)
Construct UTAUT Items Variables/elements Items for this survey Translation Performance Expectancy PE1: I find mobile Internet
useful in my daily life. Usefulness I would find the game Wii
Fit useful in my daily life. Ik zou het spel Wii Fit nuttig vinden in mijn dagelijks leven.
PE2: Using mobile Internet increases my chances of achieving things that are important to me.
Chances of achievement Playing Wii Fit will help me increase my chances to improve my health
Door het spelen van Wii Fit zullen mijn kansen om mijn gezondheid te verbeteren vergroot worden.
PE3: Using mobile Internet helps me accomplish things more quickly.
Accomplish goal more quickly
Playing Wii Fit will help me to improve my health more quickly
Het spelen van Wii Fit zal me helpen om mijn gezondheid sneller te verbeteren.
PE4: Using mobile Internet increases my productivity.
Increasing productivity Playing Wii Fit will increase my productivity
Het spelen van Wii Fit zal mijn productiviteit verhogen.
Effort expectancy EE1: Learning how to use mobile Internet is easy for me.
Learning to use the system Learning how to play Wii Fit is easy for me.
Leren hoe ik Wii Fit moet spelen zou makkelijk voor mij zijn.
EE2: My interaction with mobile Internet is clear and understandable.
Interaction clear and understandable
My interaction with Wii Fit is clear and understandable
Mijn interactie met Wii Fit zal duidelijk en begrijpelijk zijn.
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EE3: I find mobile Internet easy to use.
Easy to use I would find Wii Fit easy to play.
Ik zou Wii Fit makkelijk vinden om te spelen.
EE4: It is easy for me to become skillful at using mobile Internet.
Easy to become skillful It is easy for me to become skillful at playing Wii Fit.
Ik zou het makkelijk vinden om behendig te worden in het spelen van Wii Fit.
Additional question Age-related functional limitations
I think the functional limitations I suffer from, will hinder me in playing Wii Fit (reversed question)
Ik denk dat beperkingen die ik heb (bijv. slechter zicht of verminderde motoriek) mij zullen belemmeren in het spelen van Wii Fit.
Attitude A1: Using the system is a bad/good idea.
Good idea to use the system Playing Wii Fit is a good idea.
Het spelen van Wii Fit is een goed idee.
AF1: The system makes my work more interesting.
Interesting Playing Wii Fit makes achieving my health goals more interesting.
Het spelen van Wii Fit zou het behalen van mijn gezondheidsdoelen interessanter maken.
AF2: Working with the system is fun.
Fun Playing Wii Fit is fun. Ik zou plezier beleven aan het spelen van Wii Fit.
Affect1: I like working with the system.
Like working with the system
I like using the Nintendo Wii.
Ik zou het prettig vinden om oefeningen te doen met Wii Fit.
Social Influence SI1: People who are important to me think I should use mobile Internet
People who are important to me
People who are important to me think I should play Wii Fit.
Mensen die belangrijk voor mij zijn, zouden vinden dat ik Wii Fit moet spelen.
SI2: People who influence my behavior think I should use mobile Internet.
People who influence my behavior
People who influence my behavior think I should play Wii Fit.
Mensen die mijn gedrag beïnvloeden zouden vinden dat ik Wii Fit moet spelen.
SI3: People whose opinions that I value prefer I use mobile Internet.
People whose opinions I value
People whose opinions I value prefer I play Wii Fit.
Mensen van wie ik de mening waardeer, zouden graag hebben dat ik Wii Fit speel.
Facilitating conditions FC1: I have the resources necessary to use the system.
Necessary resources I have a TV to which I can connect the Nintendo Wii.
Ik heb een tv waarop ik de Nintendo Wii kan aansluiten.
FC2: I have the knowledge Necessary knowledge I have the knowledge Ik heb de benodigde kennis
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necessary to use mobile Internet.
necessary to play Wii Fit. om Wii Fit te spelen.
FC3: Mobile Internet is compatible with other technologies that I use.
Compatible with other technologies
Nintendo Wii is compatible with other technologies that I use.
De Nintento Wii kan gebruikt worden naast andere technologieën die ik gebruik (bijvoorbeeld een DVD-speler of een andere spelcomputer).
FC4: I can get help from others when I have difficulties using mobile Internet.
Help from others I can get help from others when I have difficulties using the Nintendo Wii/playing Wii Fit
Ik kan hulp van andere mensen krijgen wanneer ik problemen heb met het gebruiken van de Nintendo Wii of het spelen van Wii Fit.
Behavioral Intention to use the system
BI1: I intend to continue using mobile Internet in the future.
Use system in the future I intend to buy/play Wii Fit in the future.
1. Ik ben van plan om in de toekomst een Nintendo Wii te gaan aanschaffen.
2. Ik ben van plan om Wii Fit in de toekomst te gaan spelen.
BI2: I will always try to use mobile Internet in my daily life.
Try to use in daily life I will always try to play Wii Fit in my daily life.
Ik zal proberen om Wii Fit te spelen in mijn dagelijks leven.
BI3: I plan to use mobile Internet frequently.
Plan to use frequently I plan to play Wii Fit frequently.
Ik ben van plan om Wii Fit vaak te spelen.
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Appendix V – Questionnaire
Hartelijk dank dat u de tijd wilt nemen om deze vragenlijst in te vullen. Deze vragenlijst maakt
onderdeel uit van mijn afstudeeronderzoek bij de afdeling Strategische Communicatie van
Wageningen Universiteit, in samenwerking met de afdeling Humane Voeding. De vragenlijst gaat
over het spelen van (digitale) spellen.
De vragenlijst bestaat uit vijf onderdelen en zal ongeveer 20 minuten in beslag nemen.
Onderdeel 1 – Algemene gegevens In dit onderdeel wordt een aantal algemene vragen aan u gesteld.
1. Wat is uw geslacht? � Man � Vrouw
2. Wat is uw burgerlijke staat? � Alleenstaand � Ongehuwd � Ongehuwd maar met partner � Gehuwd � Gescheiden � Weduwe/weduwnaar � Zeg ik liever niet
3. Wat is uw hoogst afgeronde opleidingsniveau? � Geen opleiding (lager onderwijs niet afgemaakt) � Lager onderwijs (basisschool, speciaal basisonderwijs) � Lager of voorbereidend beroepsonderwijs (zoals LTS, LEAO, LHNO, VMBO) � Middelbaar algemeen voortgezet onderwijs (zoals MAVO, (M)ULO, MBO-kort,
VMBO-t) � Middelbaar beroepsonderwijs en beroepsbegeleidend onderwijs (zoals MBO-lang,
MTS, MEAO, BOL, BBL, INAS) � Hoger algemeen en voorbereidend wetenschappelijk onderwijs (zoals HAVO, VWO
Atheneum, Gymnasium, HBS, MMS) � Hoger Beroepsonderwijs (zoals HBO, HTS, HEAO, HBO-V, kandidaats
wetenschappelijk onderwijs) � Wetenschappelijk onderwijs (universiteit) � Anders, namelijk:
…………………………………………………………………………
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4. Tot welke leeftijdscategorie behoort u? � 65 – 70 jaar � 70 – 75 jaar � 75 – 80 jaar � 80 – 85 jaar � > 85 jaar
5. Heeft u last van een van onderstaande beperkingen? � Slechthorend � Slechtziend � Mobiliteitsbeperkingen (problemen met bewegen en vervoer) � Ik heb geen last van beperkingen � Zeg ik liever niet
Slechthorend, slechtziend & mobiliteitsproblemen à vraag 6 Geen beperkingen of zeg ik liever niet à vraag 7
6. Ondervindt u door uw beperking hinder in het dagelijks leven? � Nooit � Zelden � Soms � Vaak � Heel vaak � Zeg ik liever niet
7. Wat is uw woonsituatie? � Zelfstandig � Serviceflat � Verzorgingshuis � Verpleeghuis � Aanleunwoning � Anders, namelijk:
………………………………………………………………………… � Zeg ik liever niet
8. Heeft u kinderen en/of kleinkinderen? � Ja � Nee � Zeg ik liever niet
Ja à vraag 9 Nee/zeg ik liever niet à vraag 10
45
9. Hoe vaak ziet u uw (klein)kinderen? � Dagelijks � Wekelijks � Maandelijks � Jaarlijks � Zeg ik liever niet
Onderdeel 2 – Digitale spellen Dit onderdeel gaat over spellen en digitale spellen. Met een digitaal spel wordt een spel bedoeld dat u speelt op een digitaal apparaat. Voorbeelden van digitale apparaten zijn:
• Computer of laptop • Mobiele telefoon • Smartphone (een mobiele telefoon met internet) • Tablet/iPad • Spelcomputer zoals PlayStation, Nintendo, Xbox of GameCube
10. Speelt u weleens digitale spellen?
a. Nee à Ga door naar vraag 15 b. Ja
11. Welke digitale spellen speelt u zoal? ………………………………………………………………………………………………
12. Hoe vaak speelt u digitale spellen? � Iedere dag � Minstens 1 keer per week � Minstens 1 keer per maand � Minstens 1 keer per jaar � Minder dan 1 keer per jaar
13. Om welke reden speelt u digitale spellen? *Meerdere antwoorden zijn mogelijk � Voor de lol � Om te ontspannen � Om te ontsnappen uit de realiteit (bijvoorbeeld van alledaagse activiteiten of na een
vervelende gebeurtenis) � Om in contact te blijven met andere mensen � Om betekenis aan de dag te geven � Anders, namelijk:
…………………………………………………………………………
46
14. Op welke apparaten speelt u digitale spellen? *Meerdere antwoorden zijn mogelijk � Computer of laptop � Mobiele telefoon zonder internet � Smartphone � Tablet of iPad � Een spelcomputer die aangesloten is op de tv zoals: Playstation, Nintendo, GameCube
of Xbox Ga na het beantwoorden van deze vraag naar vraag 16.
15. Om welke reden speelt u geen digitale spellen? *Meerdere antwoorden zijn mogelijk � Ik heb hier geen behoefte aan � Ik heb dit nog nooit gedaan � Ik heb geen toegang tot digitale spellen � Dit lijkt me niet leuk � Ik denk dat ik dat niet kan � Anders, namelijk:
………………………………………………………………………… De volgende vragen gaan over verschillende soorten spellen. U kunt deze vragen dus ook invullen als u in de vragen hiervoor heeft aangegeven dat u geen digitale spellen speelt.
16. Geef bij ieder type spel aan hoe leuk u dit vindt.
Helemaal niet leuk
Niet leuk
Neutraal Leuk Heel leuk
Nog nooit gespeeld
a) Bordspellen (zoals schaken, ganzenborden of Risk)
b) Strategiespellen (zoals Stratego)
c) Dobbelspellen (zoals Yatzee)
d) Kaartspellen (zoals bridge, poker en patience)
e) Puzzelspellen (zoals Sudoku en kruiswoordpuzzels)
f) Actiespellen (zoals schietspellen en
47
vechtspellen)
g) Ruilkaartspellen (zoals Yu-Gi-Oh en Magic: The Gathering)
h) Speelautomaten
i) Racespellen
j) Sportspellen
k) Virtual Life spellen (spellen waarin je een leven naspeelt, zoals de Sims)
17. Zijn er nog andere soorten spellen die u leuk vindt om te spelen? *Vul deze vraag alleen in als
uw antwoord niet bij een van de categorieën uit de vorige vraag past …………………….…………………….…………………….…………………….…………………….…………………….………….………….…………………….…………………...
18. Wat moet een spel bevatten zodat u het leuk vindt om dit spel te spelen? Denk hierbij bijvoorbeeld aan: hoe ziet het spel eruit, wat moet je doen in het spel en speelt u het spel alleen of met andere mensen, enzovoorts. …………………….…………………….…………………….…………………….…………………….…………………….………….………….…………………….…………………….…………………….…………………….…………………….…………………….…………………….…………………….…………………….…………………….…………………….…………………….………….
19. Om welke redenen vindt u een spel niet leuk om te spelen? Denk hierbij bijvoorbeeld aan: het spel gaat te snel/is te moeilijk, het thema spreekt niet aan, enzovoorts. …………………….…………………….…………………….…………………….…………………….…………………….………….………….…………………….…………………….…………………….…………………….…………………….…………………….…………………….…………………….…………………….…………………….…………………….…………………….………….
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Onderdeel 3 – Spelen van een serious game Dit onderdeel gaat over digitale spellen die als doel hebben om iemand op speelse wijze nieuwe kennis of vaardigheden te leren. Deze digitale spellen worden ook wel serious games genoemd. Voorbeelden hiervan zijn spellen die als doel hebben om het geheugen te trainen, taal- of rekenvaardigheden te verbeteren of spellen die u stimuleren om gezonder te leven. In andere woorden: serious games zijn educatieve spellen of spellen met een serieus doel. Tegenwoordig worden steeds vaker digitale apparaten gebruikt voor het spelen van serious games.
20. U mag eerst uw mening geven over digitale apparaten. Geef voor de apparaten hieronder aan in hoeverre u het een goed idee vindt om deze in uw dagelijks leven te gebruiken.
Heel slecht idee
Slecht idee Neutraal Goed idee Heel goed idee
a) Computer/laptop
b) Mobiele telefoon zonder internet
c) Smartphone (mobiele telefoon met internet)
d) Tablet of iPad
e) Spelcomputer zoals PlayStation, Nintendo, Xbox of GameCube
Hieronder volgt een voorbeeld van een serious game. Voor dit voorbeeld gebruiken we een spel voor de spelcomputer Nintendo Wii die aangesloten kan worden op een TV. De Nintendo Wii heeft een afstandsbediening die gevoelig is voor beweging en positie. De Nintendo Wii weet dus waar de afstandsbediening zicht bevindt en hoe hij vastgehouden wordt. Het spel Wii Fit is een gezondheids- en fitness spel dat gespeeld kan worden op de Nintendo Wii. Het bevat verschillende oefeningen om thuis fitness oefeningen te doen zoals yoga, spiertrainingen, aerobicsoefeningen en balansspellen. Bij het spel krijgt u een balansbord met ingebouwde weegschaal waar u op kan staan zodat de spelcomputer ook weet wat uw positie en lichaamshouding is. Om het spel te spelen gebruikt u dus de afstandsbediening (controller) en staat u op het balansbord. Voor u begint aan het spel kunt u zelf uw doel bepalen en het aantal calorieën dat u met de oefening wilt verbranden. Vervolgens kiest u welke fitnessoefeningen u gaat doen.
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Klik hier als u een filmpje wilt bekijken waarin het spel Wii Fit uitgebreider wordt uitgelegd. Aan het eind van het filmpje, of wanneer u voldoende gezien heeft, kan u het scherm afsluiten om terug te keren naar de vragenlijst.
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21. Voor de vragen in dit onderdeel mag u doen alsof u het spel Wii Fit op de Nintendo Wii gaat spelen. Uw doel is om uw gezondheid te verbeteren door het uitvoeren van de fysieke oefeningen.
Helemaal oneens
Oneens Niet oneens – niet eens
Eens Helemaal eens
a) Ik zou het spel Wii Fit nuttig vinden in mijn dagelijks leven.
b) Door het spelen van Wii Fit zullen mijn kansen om mijn gezondheid te verbeteren vergroot worden.
c) Het spelen van Wii Fit zal me helpen om mijn gezondheid sneller te verbeteren.
d) Het spelen van Wii Fit zal mijn productiviteit verhogen.
e) Leren hoe ik Wii Fit moet spelen zou makkelijk voor mij zijn.
f) Mijn interactie met Wii Fit zal duidelijk en begrijpelijk zijn.
g) Ik zou Wii Fit makkelijk vinden om te spelen.
h) Ik zou het makkelijk vinden om behendig te worden in het spelen van Wii Fit.
i) Ik denk dat beperkingen die ik heb (bijv. slechter zicht of verminderde motoriek) mij zullen belemmeren in het spelen van Wii Fit. (reversed question)
j) Het spelen van Wii Fit is
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een goed idee.
k) Het spelen van Wii Fit zou het behalen van mijn gezondheidsdoelen interessanter maken.
l) Ik zou plezier beleven aan het spelen van Wii Fit.
m) Ik zou het prettig vinden om oefeningen te doen met Wii Fit.
n) Mensen die belangrijk voor mij zijn, zouden vinden dat ik Wii Fit moet spelen.
o) Mensen die mijn gedrag beïnvloeden zouden vinden dat ik Wii Fit moet spelen.
p) Mensen van wie ik de mening waardeer, zouden graag hebben dat ik Wii Fit speel.
q) Ik heb een tv waarop ik de Nintendo Wii kan aansluiten.
r) Ik heb de benodigde kennis om Wii Fit te spelen.
s) De Nintento Wii kan gebruikt worden naast andere apparaten die ik gebruik (bijvoorbeeld een DVD-speler of een andere spelcomputer).
t) Als ik een Nintendo Wii zou gebruiken dan zou ik hulp van anderen kunnen krijgen wanneer ik problemen heb met het gebruik van de Nintendo
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Wii of met het spelen van Wii Fit.
u) Ik ben van plan om in de toekomst een Nintendo Wii te gaan aanschaffen.
v) Ik ben van plan om in de toekomst Wii Fit te gaan spelen.
w) Ik zal proberen om Wii Fit te spelen in mijn dagelijks leven.
x) Ik ben van plan om Wii Fit vaak te spelen.
22. Heeft u het filmpje over de Wii Fit bekeken voordat u de vragen hierover heeft beantwoord?
� Ja � Nee
23. Heeft u weleens een spel op de Nintendo Wii gespeeld? � Ja � Nee � Weet ik niet
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Onderdeel 4 – Stemming Dit onderdeel van de vragenlijst gaat over uw stemming op dit moment.
24. De tabel hieronder bestaat uit woorden die verschillende gevoelens en emoties beschrijven. Geef voor ieder van de onderstaande emoties aan in welke mate u ze over het algemeen ervaart.
Nooit Zelden Soms Vaak Heel vaak
a) Geïnteresseerd
b) Overstuur
c) Uitgelaten
d) Van streek
e) Sterk
f) Schuldig
g) Angstig
h) Vijandig
i) Enthousiast
j) Trots
k) Prikkelbaar
l) Alert
m) Beschaamd
l) Geïnspireerd
m) Nerveus
n) Vastberaden
o) Aandachtig
p) Rusteloos
q) Actief
r) Bang
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Onderdeel 5 – Serious games en stemming Dit is het laatste onderdeel van de vragenlijst. Het spelen van serious games zou kunnen bijdragen aan het verbeteren van uw stemming. Dit kan door sociale aspecten die serious games soms hebben. Een voorbeeld hiervan is dat u het spel samen of tegen elkaar speelt, zoals bij de Wii Fit. Een andere manier is dat u virtueel samen met vrienden of kennissen speelt. U hoeft dan niet in dezelfde ruimte te zijn en u hoeft ook niet per se op hetzelfde moment het spel te spelen. Ook kan een serious game uw stemming verbeteren omdat u het spelen van het spel leuk vindt.
25. De vragen in dit onderdeel gaan over de mate waarin u verwacht dat het spelen van een serious game uw stemming kan verbeteren.
Helemaal oneens
Oneens Niet eens – niet oneens
Eens Helemaal eens
a) Het spelen van een serious game zou een positieve invloed op mijn stemming hebben.
b) Het spelen van een serious game samen met vrienden of familie zou een positieve invloed op mijn stemming hebben.
c) Het spelen van een serious game als een competitie met vrienden of familie zou een positieve invloed op mijn stemming hebben.
26. Zijn er nog andere redenen waarom u denkt dat het spelen van een serious game kan bijdragen
aan het verbeteren van uw stemming? …………………….…………………….…………………….…………………….…………………….…………………….………….………….…………………….…………………….
27. Zijn er reden waarom u denkt dat het spelen van een serious game juist niet bijdraagt aan het verbeteren van uw stemming? …………………….…………………….…………………….…………………….…………………….…………………….………….………….…………………….…………………….
Dit is het einde van de vragenlijst. Hartelijk bedankt voor uw medewerking!
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Appendix VI – Results Open Questions
In total, 6 open questions were included in the questionnaire. This appendix describes the
results of these questions.
Which digital games do you play?
This question was only proposed to respondents who reported that they play digital games. To
categorize the respondents’ answers, a combination of the lists of game genres reported in the game
genre framework by Järvinen (2007) was used. Especially the genres from the chapter on game genres
in popular discourse were used, as these genres are also used in video game journalism.
Table 10 - Digital games played by the respondents
Game category Type of game Frequency Puzzle Sudoku 8
Jigsaw 4 Crossword 1 Monument (maze game) 1 1010 2 ‘Patronen zoeken’ 1 Binary puzzle 2 Square puzzle beakout 1 Unblock me 1 Puzzles Juf Jansen 1 Tetris 2 Tasty Tale 1 Pet rescue saga 1 Magic puzzles 1 Cosmobots 1 Merged 1 Angry Birds 2 Detective games 1 Rummikub 6 Unspecified 2
Action game Call of Duty 1 Tile matching game
Bubble Shooter/game/up 5 Three in a row 1 Zuma 1 Mahjong 13 Candy Crush 15 Marble Magic 1 Luxor 1 Cookie Jam 1 Juicy Jam 1 Triominos 1 Boardrush 1 Dragon gem 1 Mexican Train 1
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Card game Bridge 13 Patience 24 Spider Solitaire 16 Free Cell 14 ‘Vlinders’ 1 Unspecified 10 Hearts 2 Belote 2 House of cards 1
Simulation game Township 1 Hay Day 4 ‘Landleven’ 2 Pearl’s Peril 1 Farm Heroes 2 Castle Ville 1 Farm Heroes 1 Farm games 1 Dragon Story 1 Toca Boca 1
Quiz Trivia Crack 4 4 pics, 1 word 1 Unspecified 1 Quiz Battle Lifestyle 1
Wordplay Wordfeud 35 Word 1 WordOn HD 4 Spelling games 1 Ruzzle 6 Woordjacht 1 Scrabble 2
RPG (Role Playing Game)
Sherlock Holmes 1 Pearl’s Peril 1 Unspecified 1 Pou 1
Strategy game Boom Beach 1 Stratego 1 Chess 5 ‘Mens erger je niet’ 1 Pac-xon 1
Dice game Sevens 1 Yahtzee 1
Brain Trainer Cognito 1 Lumosity 1
Driving game Unspecified 1 Sports game Boxing 1
Balance game 1 Arcade game Coin dozer 1
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Which other games do enjoy? *only answer this question when the games don’t belong to the categories mentioned in the previous question Table11-Othergamesrespondentslikethatdon'tfitingamecategories
Game Frequency Scrabble 14 Rummikub 10 Wordfeud 6 Shuffleboard 5 Dams 4 Monopoly 4 Triominus 4 Jigsaw 3 Keezen 3 Mahjong 3 ‘Mens erger je niet’ 3 Children’s games with children
3
Quizzes 3 Ruzzle 2 Candy Crush Soda/saga
2
Trivia Crack 3 Domino 2 Sudoku 1 ‘Spel van draken en winden’
1
Pingpong 1 Three in a row 1 Pet Rescue Saga 1
Alpha Betty 1 ‘Kolonisten van Catan’ 1 RPGs (role-playing games)
1
Mastermind 1 Bingo 1 ‘Levensweg’ 1 Memory 1 Spider Solitaire 2 Tetris 1 Adventure 1 Fantasy 1 Flight simulator 1 ‘Teken het maar’ 1 Backgammon 1 Bridge 1 Maze 1 Games without time limit
1
Mexican train (sort of domino)
1
Trivial Pursuit 1 Fly catcher game 1 Soccer 1 Pim Pat Pet 1 Tiddly-winks (vlooienspel)
1
Word games 1
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What elements should a game contain for you in order to be able to enjoy the game?
The intention was to categorize the answers to this question according to Järvinen’s (2007)
analogy of game elements. However, it turned out that the answers to this question didn’t fit the
analogy. Therefore, motivational determinants and elements described by Nap et al. (2009) were used.
Answers that could not be categorized using literature were categorized according to the frequency.
Table 12 - Elements a game should contain
Element Frequency With/against others/sociable (‘gezelligheid’)
69
Intelligence game/mind game/use or train your brain
37
Challenges/ game should not be too easy
32
Needs to look nice/nice graphics, colors/interface/lay-out etc.
18
Ability to play alone 18 Competition element 17 Excitement 15 Not too long 12 Strategy 11 Not too complicated 10 Different levels/ability to get high scores
9
Play for relaxation 8 Play game for fun 6 Able to play with grandchildren 6 Surprising elements/variation 6 Easy to understand/play 5 Speed is subordinate/decide own speed/not too fast
5
Speed 5 Luck 4 Games that require agility 4 Instructive/learn something 4 Family game/parlor game 3 Game needs to be free 3 Knowledge game 3 Possible to pause game 3 Find a solution 2 Requires tactics 2
Action-reaction 2 Able to combine playing game with chatting
2
Adventure 2 Story 2 Realistic 2 Needs to include physical activity
2
Not too violent 2 Puzzle elements 2 No competition 1 Test skills 1 Attention/focusing 1 If it’s not addictive 1 Develop yourself 1 Simple 1 Easy to operate 1 Possibility to have a good result 1 Think logical 1 Random opponent 1 Clear rules 1 Easy to start and to finish 1 Interaction 1 Independent/no team 1 Total 347 Unanswered/not interested in gaming
11
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What are reasons for you to dislike a game?
Table 13 - Reasons to dislike a game
Reasons Frequency Shooting/fighting/blood/war/ violence
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Theme doesn’t appeal 32 Game is too fast /time pressure
30
Too difficult 25 Too long 18 Winning by luck/coincidences 15 Racing games 8 Boring games 6 Too many rules 6 Gambling games 5 Competition 5 Too slow 4 Games is unclear/too chaotic 4 Virtual reality games 4 Too much strategy needed to play game
4
Don’t like losing games 3 Too easy 3 Unattractive design 2 Addictive games 2 Too little variation 2 Too much thinking required 2 Too much skills required 2 Digital games are often too fast
2
Sports 2 You don’t learn anything from games
2
Playing with others 2 No affinity with the game 1 It should appeal to me 1
No fun when someone is eliminated, prefer a positive approach which is focused on achieving a better achievement
1
If I can’t play it with my grandchildren
1
If others are too fanatical 1 Too much patience is needed 1 Requires too much concentration
1
Need to remember a lot 1 Opponent is too good 1 Playing with other people 1 Being too dependent of others 1 If you’re not allowed to talk 1 Mobility restrictions 1 Little experience in playing games
1
If game is too big; too much levels/options
1
Too noisy 1 Waiting too long for your turn
1
Games that are predictable 1 Boys’ games 1 Too dumb 1 Pictures are too little 1 Unrealistic 1 If I have to play alone 1 If the game is unknown 1 Too tired to play 1 Sitting for a long time 1 Total 281 Unanswered 27
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Are there any reasons why you think that playing a serious game could contribute to improving your mood? Table 14 - Reasons why serious games might improve a person's mood
Reasons Frequency Social contact/ ‘gezelligheid’
12
Improving health/condition/physical activity/losing weight improves mood
10
Playing a distraction 6 It’s fun 4 Relaxation 3 Competition 2 If it’s educational 2 Nice to see your progress 1 Reactions/feedback 1 Maintaining interest in daily life
1
Interest in others 1 Exercising/moving is always fun, but even better in a group
1
Developing yourself 1 Messaging with others 1 Could be useful if you’re older
1
If it’s challenging 1 Cooperation 1 If I would be disabled, it would be useful
1
Depends on current mood 1 Challenging 1 Play whenever you want to
1
Total 54 No/Unanswered 195
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Are there any reasons why you think that playing a serious game could worsen your mood?
Table 15 - Reasons why serious games could worsen a person's mood
Reasons Frequency Mood may worsen if you’re not good at the game/if it’s too difficult
6
Direct contact with others is missing (which is important for improving each others’ mood)
4
Shouldn’t feel obligatory 4 It’s unreal 4 Don’t like computer games 3 Have never experienced playing a serious game
2
Don’t like the competition elements
2
Visual impairment, so reading from a screen is too intense
2
It’s distracting 2 It takes too much effort to learn how a game works
1
Don’t like doing sports at home
1
Too much effort to play on a Wii Fit: too little space, TV is not suitable
1
Lack of discipline to do exercises regularly
1
Takes too much time 1 If you don’t feel like playing, it doesn’t help improve your mood
1
If it’s boring 1 I might not like it 1 Unrealistic that it works 1 Probably addictive 1 Major barrier to start playing games
1
It’s unsocial to be in front of a TV-screen
1
I don’t have a TV 1 If rules are taken too serious
1
Don’t want to be dependent on a game
1
Total 44 No/unanswered 204
