Never Too Old to Play: The Appeal of Digital Games to an Older Audience
←
→
Page content transcription
If your browser does not render page correctly, please read the page content below
Games and Culture
6(2) 155-170
ª The Author(s) 2011
Never Too Old to Play: Reprints and permission:
sagepub.com/journalsPermissions.nav
The Appeal of Digital DOI: 10.1177/1555412010364978
http://gac.sagepub.com
Games to an Older
Audience
Bob De Schutter1
Abstract
This study aimed to explore the use of digital games among older adults and provide
a set of ‘‘benchmark data’’ with respect to the uses and gratifications of these play-
ers. To find out who these older players of digital games are, what games they prefer,
and what playing motives they have, an exploratory survey was administered among
124 individuals aged between 45 and 85 years old. The results of this survey confirm
that the majority of the older digital game audience exists of solitary players with a
particular fondness for casual PC games. The most popular playing motive among the
respondents was challenge, while social interaction proved to be the most important
predictor for the time that respondents invested in playing digital games.
Keywords
users and gratifications, older gamers, game studies, casual games
Since the turn of the millennium, the annual industry reports of the Electronic
Entertainment Software Association [ESA] indicate that digital games have become
an increasingly popular pastime for adult and elderly players. While the ESA’s 1999
study estimated that only 9% of the North American digital games audience was
older than 50 years, this percentage rose to 19% in their 2005 study, and was esti-
mated to be at 24% in their latest study (2007). Corresponding to ESA
1
Group T-International University College Leuven, Association K.U. Leuven, Belgium
Corresponding Author:
Bob De Schutter, Wilders 51, Geel 2440, Belgium
Email: b@bobdeschutter.be
155156 Games and Culture 6(2)
reports, other market studies (British Broadcasting Corporation, 2005; eMarketer,
2007; Entertainment and Leisure Software Publishers Association, 2004;
Nielsen-Netratings, 2004; Vance, 2004) have confirmed that the audience of digital
games has expanded beyond children, teens, and young adults.
Nevertheless, the focus of game studies has not expanded in a similar manner.
Studies with an emphasis on the older audience of digital games (Copier, 2002;
Pearce, 2008) are still rare. The first wave of publications on older players of digital
games was written from a gerontological perspective (Farris, Bates, Resnick, &
Stabler, 1994; Goldstein et al., 1997; Schueren, 1986; Whitcomb, 1990). These studies
evaluated the potential of digital games to improve the quality of life of the frail
elderly. More recently, however, research questions concerning older adults and
digital games have been posed in the field of interaction design (De Schutter &
Vanden Abeele, 2008; Gamberini, Alcaniz, Barresi, & Fabregat, 2006; Ijsselsteijn,
Nap, de Kort, & Poels, 2007; Khoo, Lee, Cheok, & Kodagoda, 2006; Vanden Abeele,
Husson, Vandeurzen, & Desmet, 2007), where researchers used ethnographic inquiry
and usability research to design games that meet the specific needs of the older player.
Although such studies offer insights into how digital play meets the needs of elderly
life, both the gerontological and design perspectives seem concerned with getting
older players to play, rather than with analyzing those who are already playing.
Unfortunately, research on the latter seems to be exceptionally rare, with the exception
of Copier’s (2002) qualitative inquiry into the playing habits of 12 elderly gamers and
Pearce’s (2008) exploration of the lifestyles of ‘‘Baby Boom Gamers.’’
The use of digital games by its older audience deserves similar commercial and
academic interest as the use of digital games by children or teens. First of all, the
phenomenon of older individuals playing digital games does not appear to be a fad.
The game industry has been successfully promoting products catering to the prefer-
ences of an older audience (Campbell, 2006) and the first generations that grew up
with the medium are aging but still playing (Morris, 2006). Consequently, this new-
found grey market for digital games will keep expanding, as Western society will be
aging rapidly in the near future (Pelfrene, 2005).
Aside from these emerging opportunities for the game industry, the new audience
of digital games also offers prospects to media scholars. It has been argued that the
social, psychological, and cognitive changes that accompany the shift to late adult-
hood are as far reaching as the process of growing up, which might indicate that both
life stages are equally susceptible to external (media) influences (Eggermont &
Vandebosch, 1999). Furthermore, developmental stages in the life of teens and ado-
lescents have been associated with different uses of digital games (Sherry, Desouza,
Greenberg, & Lachlan, 2003), which raises questions on how the use of digital
games (in terms of the amount of time spent on playing these games, playing prefer-
ences, and playing motives) should be conceptualized in the later stages of life.
These questions were the starting point of an exploratory study on the older
audience of digital games in Flanders.1 The topic was approached from a uses and
gratifications perspective (Rosengren, 1974; Rubin, 2002; Ruggiero, 2000; Sherry,
156De Schutter 157
Lucas, Greenberg, & Lachlan, 2006). Uses and gratifications theory has become an
influential paradigm in media research and ‘‘emphasizes the active role of the media
user, arguing that selecting and using media is a determined, goal-directed activity
that is largely determined by the individual’s motives’’ (Jansz & Tanis, 2007). It is
therefore considered a fitting perspective for investigating why audiences choose to
be exposed to different media.
The uses and gratifications approach has been applied to digital games since the
1980s, with a strong emphasis on teen and adolescent players. It has been successful
in explaining why people attend amusement arcades (Selnow, 1984; Wigand,
Borstelmann, & Boster, 1985), gather for LAN parties (Jansz & Martens, 2005),
or play certain game genres and games (Jansz, Avis, & Vosmeer, 2007; Jansz &
Tanis, 2007; Tanis & Jansz, 2008; Walma van der Molen & Jongbloed, 2007).
Although earlier studies have constructed instruments based on television uses
and gratifications research, recent studies have developed instruments specifically
for digital games. The most consistently used scale has been the Analysis of Video
Game Uses and Gratifications instrument (AVGUG) by Sherry, Lucas, et al. (2006).
Studies that did not use this instrument often surveyed similar playing motives, but it
remains difficult to compare these findings to those of studies that used the AVGUG
instrument. The results of both lines of research were considered relevant in the
context of this investigation.
First, there has been a consensus in uses and gratifications research that younger
and male respondents tend to report longer playing times (Jansz & Martens, 2005;
Jansz & Tanis, 2007; Lucas & Sherry, 2004; Sherry, Desouza, et al., 2003; Walma
van der Molen & Jongbloed, 2007). Second, playing motives—especially the social
interaction motive—were found to be sound predictors for playing time (Jansz &
Tanis, 2007; Sherry, Desouza, et al., 2003; Sherry, Lucas, et al., 2006;).
The challenge motive (i.e., playing to push oneself to beat the game or to get to
the next highest level) has generally been the most popular motive for studies using
the AVGUG instrument (Lucas & Sherry, 2004; Sherry, Desouza, et al., 2003;
Sherry, Lucas, et al., 2006; Walma van der Molen & Jongbloed, 2007). This finding
could be related to challenge being a motive that characterizes many types and gen-
res of games (Grodal, 2000). In contrast, uses and gratifications studies (Jansz et al.,
2007; Jansz & Tanis, 2007; Tanis & Jansz, 2008) that focused on players of specific
genres or games found that other motives than challenge were more popular among
their participants. Unfortunately, these studies did not use the AVGUG instrument,
thereby making a fair comparison impossible, and the challenge motive remains a
popular motive—albeit not the most popular motive—among them.
Next, uses and gratifications research has explained differences in game usage (in
terms of genre preferences and playing time) between preadolescents, adolescents,
and young adults (Sherry, Desouza, et al., 2003; Sherry, Lucas, et al., 2006). For
example, preadolescents prefer games that offer social and physical powers that they
lack in real life, whereas adolescents look toward games as a means of interacting
157158 Games and Culture 6(2) with their peers. Young adult players are troubled by the social unacceptability of games among their peers and therefore revert to the less social motives. Finally, Lucas and Sherry (2004) applied the uses and gratifications perspective alongside Fundamental Interpersonal Relationship Orientation theory2 (FIRO; Schutz, 1958) to explain gender differences in digital game play. Both authors argue that digital games are largely perceived as the domain of males and that female players are systematically placed at a disadvantage in terms of their ability to interact with the gaming environment. Therefore, digital games are less capable to gratify female players’ need for fundamental inclusion, affection, and control. Conse- quently, female players play less frequently than males and prefer games that offer challenges that better suit their skills. Based on the uses and gratifications studies cited above, some predictions can be made with respect to older players. As Copier (2002) indicated that digital games are not socially accepted among older players, it could be theorized that the social playing motives will be less popular. Furthermore, the concepts that explained sex differences in the study by Lucas and Sherry (2004) seem partly relevant to an older audience. Older players often find it difficult to overcome the challenges of new technologies. This, along with digital games being socially unaccepted entertain- ment for their age group, puts them in a similar position as female players in terms of games satisfying the need for inclusion, affection, and control. From this point of view, female and older players are alike as they are part of a demographic that was not targeted by the industry until recently. We therefore expect to find many ‘‘casual’’ gamers among older players, as market studies (Wallace & Robbins, 2006) have indicated that the audience of casual games gener- ally skews toward older people, with a slight demographic skew toward women. Such games are often purchased as downloadable content or played for free through an Internet browser. They are highly accessible and have short learning curves. Consequently, digital games should suit the needs of an older audience as well. In conclusion, we adopted the uses and gratifications perspective to provide benchmark data regarding the demographic context, playing time, genre and plat- form preferences, and playing motives of the older audience of digital games, with a special interest toward the genre of casual games. Method As no prior information was known about the size of the older audience of digital games in Flanders, we launched an online call for respondents on our personal Web site (Gameonderzoek.be), on two of the largest Flemish online forums dedicated to digital games (i.e., Telenet Games and Arena 51), and on the largest Flemish online community for older Internet users (i.e., Seniorennet.be). We also launched the same call through a real-life umbrella organization for elderly citizen’s communities of interests (i.e., Vlaams O.O.K.) and a full-page interview in two national newspapers (i.e., Het Volk and Het Nieuwsblad). Finally, we used the snowball technique by 158
De Schutter 159
contacting our own social network of gamers who shared our URL to their friends
and so on. The call for respondents contained the following criteria: (a) potential
participants should play digital games (whether it is Tetris, Solitaire, Chess, or
Half-Life 2) at least once a week, (b) they should at least be 45 years of age, and
(c) they should be willing to fill out a survey. As a result of these sampling tech-
niques, we constructed a database of 239 individuals who received access to an
online questionnaire on a secure server. All information was handled confidentially
and reported anonymously.
The questionnaire began with demographic questions (age, gender, employment,
education, professional status, etc.). Next, a day-by-day scale was used to measure
the amount of time the respondents allocated to playing digital games (i.e., playing
time). A 5-point Likert-type scale ranging from ‘‘never’’ to ‘‘daily’’ was used to
measure the frequency of playing a certain genre, the frequency of playing on a
certain platform, and the frequency of playing with others. The scale for genre
preferences contained 16 genres and was based on Malliet’s instrument (2007), to
which we added the ‘‘adaptations of traditional games’’ genre. Every genre was
accompanied by three games that epitomized the genre. For the platforms, a list
of 13 popular consoles was used, along with PC, mobile phone, and PDA with the
option to write any console not included in the list. Aside from these scales, the sur-
vey also asked the respondents’ top three favorite games of all time. Considering that
this study targets players who might not have grown up with digital games and who
could be unaware of the gamer culture (Copier, 2002), we expected that many of our
respondents would not necessarily play a wide variety of genres.
In the analysis, the respondent’s three favorite games were used to divide the
sample in players with a preference for either ‘‘casual games’’ or ‘‘hardcore games.’’
We used the same definition as Reinecke and Trepte (2008), whose basis was a white
paper by the International Game Developers Association (Wallace & Robbins,
2006). In this respect, casual games are defined as downloadable computer games
with relatively small file size or browser-based Web games.3 Although we had some
concerns before operationalizing this description, it suited our sample well as none
of our respondents cited ambiguous cases or a combination of both casual and hard-
core games among their three favorite games. Furthermore, a lot of the games that
ended up being coded as casual games were free online browser-based games or
games that were actually listed in the white paper (e.g., games by Big Fish Games,
PopCap, etc.).
Finally, to measure our respondents’ motives for playing digital games, the
survey contained the AVGUG instrument (Sherry, Lucas, et al., 2006) translated into
Dutch. The principal components analysis (varimax rotation) resulted in six compo-
nents with eigenvalue greater than 1, explaining 80.4% of the total variance. The six
factors had satisfactory reliability: competition (i.e., to be the best player of the
game; Cronbach’s a ¼ .86), challenge (i.e., to push oneself to beat the game or to
get to the next highest level; a ¼ .89), social interaction (i.e., to play as a social
experience with friends; a ¼ .94), diversion (i.e., to pass time or to alleviate
159160 Games and Culture 6(2)
boredom; a ¼ .93), fantasy (i.e., to do things that you cannot do in real life such as
driving race cars or flying; a ¼ .94), and arousal (i.e., to play because the game is
exciting; a ¼ .87).
Results
A total of 239 individuals participated in the survey, 124 of whom completed the
entire questionnaire.4 Most of our respondents were female (57.9% of the sample)
with a mean age of 58.18 (SD ¼ 7.05). The oldest respondent was 85 years of age
(born in 1923) whereas the youngest respondents were 45 years old (born in
1957; n ¼ 4). The sample was divided into the following three age categories:
‘‘young medior’’ (33.1%, aged 45–54), ‘‘old medior’’ (50.8%, aged 55–64), and
‘‘senior’’ (16.1%, aged 65 and above). Because our sample contained only 8 respon-
dents above the age of 74, we decided not to split the ‘‘senior’’ category into ‘‘young
senior’’ and ‘‘old senior’’ subcategories. As a result, we had one group each in
middle adulthood, late adulthood, and the transition between both developmental
stages (Berk, 2003).
The sample contained a wide range of educational levels. The largest group
(34.7%) received education at the highest level (i.e., higher education), 31.5% was
trained at the middle level (i.e., higher secondary school) while 27.4% attended pro-
fessional training at a basic level (i.e., lower secondary school or less). With respect
to the professional status of our respondents, the largest group (38.5%) of the sample
held a job whereas 33.9% had retired. The remaining respondents consisted mainly
of housewives (12.8%) or people suffering from a temporary or permanent illness
that withheld them from work (9.2%). All respondents were living independently
(95.8%) or with family members (4.2%). No one reported to be living in a service
flat or a retirement home. The vast majority of the respondents (89.3%) were
engaged in a steady relationship and most of them (83.5% of the sample) were also
living with their partners. The greater part of the sample (59%) had one or more
grandchildren (M ¼ 2.16, SD ¼ 2.78). In terms of sampling methods, Seniorennet.be
was responsible for 64.5% of the sample. The other sampling methods (e.g., Telenet
Games, Arena 51, coverage in a national newspaper) did not have as much success as
we had hoped, resulting in a combined 6.4%. The remaining respondents indicated
that they could not remember how they found the site or that they found it by
coincidence.
Genre and Platform Preferences
The range of genres the respondents reported to play proved to be limited. While the
puzzle game genre (M ¼ 3.18, SD ¼ 1.37) and the genre of digital adaptations of
traditional games (M ¼ 3.36, SD ¼ 1.40) had a normal spread, the other genres were
never or seldom played, and none of them received a combined mean score over
1.5 on a 5-item scale (with 1 being ‘‘never’’ and 2 being ‘‘seldom’’). After
160De Schutter 161
qualitatively analyzing the top three favorite games of the respondents, we were able
to paint a more nuanced picture: exactly 80% of the respondents were identified as
casual gamers. The remaining 20% of the sample reported many different genres
among their favorite games, including shooting games (e.g., Call of Duty),
action–adventure games (e.g., Splinter Cell), simulation games (e.g., Simcity), plat-
form games (e.g., Jak and Daxter), racing games (e.g., Gran Turismo), sports games
(e.g., FIFA), massively multiplayer online games (e.g., World of Warcraft), role-
playing games (e.g., Oblivion), and adventure games (e.g., Myst).
The most popular hardcore games were Call of Duty and Half-Life, which were
both cited by three respondents as one of their favorite three games. While only three
other hardcore games (i.e., Counter-Strike, Medal of Honor, and Age of Empires)
were cited by more than one respondent, casual games were frequently cited. The
most popular5 of them all was Tetris, which was cited 17 times, followed by Spider
Solitaire (13 times) and Zuma (10 times).
Similar to genre preferences, the mean scores for platform preferences were
low. The respondents were avid PC users (M ¼ 4.13, SD ¼ 1.18) whereas only
a minority of the sample reported playing games on other platforms. The second
most played platform (and the only other platform other than PC with a mean
higher than 1.5) was the mobile phone (M ¼ 1.62, SD ¼ 1.07). Because the differ-
ent types of consoles all had low means below 1.23 (Playstation 2 scoring the high-
est), we grouped all consoles into one value. Nevertheless, consoles as a whole still
proved an unpopular gaming platform for the majority of the sample (M ¼ 1.52,
SD ¼ 0.94) as only 13.7% of the respondents reported playing more than once a
month on a console.
Thus, with regard to platform and genre preferences, we can conclude that the
respondents can mainly be classified as casual gamers who prefer the PC platform.
This was also evident in view of the purchase of digital games, where the sample
consisted predominantly of players who purchase no (58.1%) or less than three
games (31.5%) annually. Consequently, the majority of the sample reported that they
never (59.7%) or rarely (16.1%) play commercially available digital games. This
finding was also supported by the observation that only 12.1% of respondents con-
fessed to playing illegal copies of digital games.
The prevalence of casual players in the sample already indicated that casual play-
ers are older than hardcore6 players. A chi-square analysis (w2(2) ¼ 8.906; p < .05)
confirmed that the relationship between age and the casual game preference was sig-
nificant within the used sample. A significantly large number of the hardcore players
in the sample were members of the young medior group (61.9%), whereas only
27.4% of the casual players were young mediors. Gender was also significantly
related toward casual gaming (w2(2) ¼15.067; p < .001), as the majority (91.4%)
of the female players were coded as casual players. Of the male respondents, only
57.1% were classified as casual players. In conclusion, the hardcore players were
more likely to be male and part of the younger age groups in the sample.
161162 Games and Culture 6(2) Playing Time The next step in our exploration of respondents’ characteristics as players of digital games was to analyze the time spent playing digital games on a daily basis. After adding up the reported amounts of play time for the different days of the week, the mean playing time of the sample was computed at 1.45 hr a day (SD ¼ 1.14). To provide a clearer view of the playing time distribution, we divided the sample in the following three groups using the criteria of Jansz and Martens (2005; which were originally constructed for participants of a LAN event): ‘Heavy players’ (16.1%), who spend more than 2.5 hours a day playing digital games; ‘moderate players’ (39.5%), who play between 1 hour and 2.5 hours a day playing digi- tal games; and ‘light players’ (44.4%), whose reported amount of time playing fell below 1 hour each day. Correlational analysis uncovered a correlation (r ¼ .226, p < .05) between age and the playing time. This finding was supported by an analysis of variance (ANOVA) that indicated that our three age groups (i.e., young mediors, old mediors, and seniors) dif- fered significantly from each other in the time they spent playing digital games (F(2, 121) ¼ 3.685, p < .05). An LSD post hoc test revealed that the young mediors group (M ¼ 1.85, SD ¼ 1.34) played significantly more (p < .05) than both the seniors group (M ¼ 1.07, SD ¼ 0.65) and the old medior group (M ¼ 1.32, SD ¼ 1.06). These two last groups, however, did not differ significantly from each other. Retirement appeared to be related to a decrease in playing time (t(108) ¼ 2.223, p < .05) but the relationship between both variables failed to remain significant after entering age as a covariate. In view of the respondents’ education, playing time also differed significantly (F(2, 113) ¼ 3.598, p < .05). An ANOVA indicated that respondents with a higher education (M ¼ 1.09, SD ¼ 0.87) invested significantly less time into playing games than did respondents who were trained at the middle (M ¼ 1.69, SD ¼ 1.11; p < .05) and the basic level (M ¼ 1.56, SD ¼ 1.29; p < .05). In contrast to the studies cited above—those that were conducted with respect to younger audiences—male players (M ¼ 1.22, SD ¼ 1.14) within this sample reported to play less hours on average than female players (M ¼ 1.59, SD ¼ 1.12). This difference was only marginally significant (t(122) ¼ 1.771, p ¼ .079), however. After removing the hardcore players in the sample from the analysis, the difference between male players (M ¼ 1.06, SD ¼ 0.78) and female players (M ¼ 1.57, SD ¼ 1.04) did become significant (t(82) ¼ 2.032, p < .05). As such, this study confirms the finding that female casual players play longer than male casual players (Wallace & Robbins, 2006). No significant differences in playing time were found between hardcore and casual players (t(103) ¼ 1.448, p ¼ .151), which confirms the notion that 162
De Schutter 163
Table 1. Reported Means for Uses and Gratifications by Gender
Total Men Women F
Challenge 3.59 3.28 3.77 5.785*
Arousal 2.42 2.43 2.41 0.152
Diversion 2.41 2.01 2.66 6.191*
Fantasy 1.67 1.95 1.49 15.048***
Competition 1.47 1.61 1.38 3.998*
Social interaction 1.46 1.64 1.36 8.047**
Notes: F is the result of analysis of covariance (ANCOVA) with hours of game play per day as covariate.
* p < .05.
** p < .01.
*** p < .001.
casual players are not necessarily less dedicated players with regard to playing time
(Wallace & Robbins, 2006).
Playing Motives
The respondents generally reported low scores for the playing motives. The most
popular motive (and the only one that managed to achieve a higher mean score than
a neutral 3 on the 5-item Likert-type scale) was the challenge motive (M ¼ 3.59,
SD ¼ 1.00). The other challenges were ranked from best to worst: arousal (M ¼
2.42, SD ¼ 0.98), diversion (M ¼ 2.41, SD ¼ 1.28), fantasy (M ¼ 1.67, SD ¼ 0.94),
competition (M ¼ 1.47, SD ¼ 0.69), and social interaction (M ¼ 1.46, SD ¼ 0.89).
The last three motives have extremely low means, which can be explained in
terms of the social context of the older audience. As most players (84.7%) reported
that they are solitary players who never or seldom play with others, it could be
expected that the social motives (i.e., competition and social interaction) would
receive low mean scores. This assumption was affirmed by the three t tests. In
comparison with respondents who played with others at least once a month, soli-
tary players reported significantly lower means for social interaction (t(19.536) ¼
4.552, p < .001), competition (t(122) ¼ 2.515, p< .05), and fantasy (t(20.974) ¼
2.809, p< .05).
An exploration was made on the relation between playing time and playing motives
using linear regression analysis with playing time as the dependent variable. The
motives were entered as predictors and explained 26% of the variance in the playing
time variable (F(3, 120) ¼ 14.362, p < .001). The strongest predictor was social inter-
action (b ¼ .331, p < .001), followed by fantasy (b ¼ .221, p < .05) and challenge (b ¼
.164, p < .05), respectively. Competition, diversion, and arousal could not be used as
significant predictors of the time invested in playing digital games.
Earlier research revealed that playing motives were significantly related to differ-
ent developmental stages (Sherry, Desouza, et al., 2003) and gender (Lucas &
163164 Games and Culture 6(2) Sherry, 2004) and the relationship between age, gender, and the playing motives was explored. Correlation analysis revealed that the age of the respondents was signifi- cantly related to challenge (r ¼ .189, p < .05), social interaction (r ¼ .189, p < .05), and diversion (r ¼ .208, p < .05; Table 1). For gender, an analysis of covariance (ANCOVA) with hours of playing time per day as covariate revealed that five of the six motives were significantly different. The results for fantasy (F(1, 121) ¼ 15.048, p < .001), competition (F(1, 121) ¼ 3.998, p < .05), and social interaction (F(1, 121) ¼ 8.047, p < .01) were in line with Lucas and Sherry (2004), while the other three motives were not: men and women did not differ significantly on the arousal motive, and women scored significantly higher than men on diversion (F(1, 121) ¼ 6.191, p < .05) and challenge (F(1, 121) ¼ 5.785, p < .05). After controlling for genre preferences (casual or hard- core), the difference between men and women on diversion (F(1, 101) ¼ 3.166, p ¼ n.s.) became insignificant but the difference on challenge remained significant (F(1,101) ¼ 5.327, p < .05). Lucas and Sherry (2004) pointed out that a male bias in game design leads to female players having to overcome a bigger challenge than male players, which could be a tentative explanation for our female respondents scor- ing significantly higher means on the challenge motive than the male respondents. Finally, we explored the statement of Wallace and Robbins (2006) that casual games might relate to playing motives that differ from motives related to hardcore players. This claim was supported in two of the four motives, as casual players dif- fered significantly from hardcore players on the fantasy (t(25.320) ¼ 2.445, p < .05) and the arousal (t(103) ¼ 2.187, p < .05) motives. The casual group scored significantly lower on the fantasy motive (M ¼ 1.51, SD ¼ 0.77) than their counter- parts (M ¼ 2.12, SD ¼ 1.08). The same was true for the arousal motive where casual players reported a mean score of 2.31 (SD ¼ 0.90) opposed to a mean score of 2.80 (SD ¼ 1.07) reported by the hardcore players. Discussion This exploratory survey identified the older audience of digital games in Flanders as mainly PC users, who like to play casual games for the challenge. The sample contained individuals with broad educational and professional backgrounds and almost all respon- dents were living on their own. Our sample consisted of more females than males, which corresponds to the large representation of casual players in the sample (Nielsen- Netratings, 2004; Tinney, 2005; Wallace & Robbins, 2006). Aside from the casual play- ers, a minority of hardcore players could be identified as well. The latter were skewed toward the younger age groups but did not necessarily play longer than their casual counterparts, which corresponds with findings of previous research into casual games (Wallace & Robbins, 2006). Furthermore, while the casual players were more often than not female, the opposite was true for the hardcore players in the sample. Results on the subject of casual players confirmed most findings of market report on casual players (Nielsen-Netratings, 2004; Tinney, 2005; Wallace & Robbins, 164
De Schutter 165
2006), although most of our respondents could also be identified as an older audi-
ence against casual gaming norms.7 We have already argued that the popularity
of these types of games is not surprising in view of an aging audience. Uses and grat-
ifications research (Sherry, Desouza, et al., 2003) has indicated that many young
adults already demonstrate a tendency toward digital adaptations of traditional
games and more strategically oriented games, a linear trend that apparently contin-
ues in later adult stages. Furthermore, casual games are much more suited than hard-
core games to meet the needs of an ageing audience (De Schutter & Vanden Abeele,
2008; Ijsselsteijn et al., 2007) in terms of content and interaction.
Compared with other uses and gratifications research on digital games using the
same instrument (Lucas & Sherry, 2004; Sherry, Desouza, et al., 2003; Sherry, Lucas,
et al., 2006), most playing motives seemed to score lower than anticipated. This may
be explained to some extent by the fact that the individuals in our sample were mostly
solitary players, while some of the motives defined by Sherry, Lucas, et al. (2006)
were related to the social characteristics of digital gaming. The emphasis on challenge
and the lower score of diversion seem to theoretically relate directly to the need of
individuals in late adulthood to cultivate themselves (Copier, 2002; De Schutter &
Vanden Abeele, 2008), whereas the lack of interest for the arousal motive might be
related to the preference for casual games (which have less an audiovisual impact than
hardcore games). Furthermore, the results of this study also confirm that social inter-
action is the most important predictor for longer playing time, a finding that was pre-
viously established in studies by Sherry et al. and Jansz and Tanis (2007).
In terms of genre preferences and playing motives, our respondents were similar
to the female sample used in the communication-based explanation of Lucas and
Sherry (2004) for gender differences in digital gaming. The players of both samples
report a preference for traditional and puzzle games. Playing motives were ranked in
the same order for both samples with the challenge motive being the only one obtain-
ing a higher score than the neutral answer. We therefore argue that the combination
of uses and gratifications theory and the FIRO theory is useful to explain the differ-
ences between younger and older players.
As with Pearce’s (2008) study on ‘‘baby boomer gamers,’’ we found several simi-
larities in our Flemish audience of digital games: our respondents were predomi-
nantly females, they preferred the PCs as their platform, and they expressed a
fondness for the intellectual challenge of puzzle games. Some of our results, how-
ever, also contradict Pearce’s findings, as only a few of our respondents reported
to enjoy adventures, role-playing games, or shooters. The fantasy motives received
a low mean score, whereas the ‘‘baby boom gamers’’ in Pearce’s study love games
that allow players to visit another world. Finally, the ‘‘baby boom gamers’’ are social
gamers and seem to be slightly heavier players. We argue that these dissimilarities
could be attributed to Pearce’s sampling method that focused on users of sites where
older gamers explicitly seek people to play and discuss their games with (such as
TheOlderGamers.com) and sites that are oriented specifically toward adventures
(such as AdventureGamers.com).
165166 Games and Culture 6(2) Finally, we acknowledge that the study has some flaws owing to a small sample size and the issues concerning Internet sampling and self-selection. We argue that the older audience of digital games is a difficult audience to study because digital games are not always socially accepted in the context of older players, which may make the threshold of participating in a research project a big one (Copier, 2002). Furthermore, there are no known methods to find large groups of older players and we were unsuccessful in our attempt to find respondents by means of snowballing, the print media, or organizations for individuals in middle and late adulthood. Still, we argue that these results are an interesting first step in portraying older players of digital games and comparing them with younger players. This study therefore raises many questions for future research. First of all, the social acceptance of digital games among older individuals remains an interesting subject. What are the reasons for the solitary play of the majority of older players? Copier (2002) and Sherry, Desouza, et al. (2003) already indicated that this may be due to digital games being socially unacceptable or being perceived as childish or a waste of time. However, maybe they are just looking for mature playing partners (Pearce, 2008)? Or maybe multiplayer games do not offer the type of challenge they are looking for? Future research on the topic of social acceptance should also inves- tigate the differences, if any, between players who have discovered games in later stages of adult life and gamers who have kept playing digital games since they were young. Older individuals who have always identified themselves as gamers might not feel as marginalized as those who have just discovered the medium, which could theoretically affect their uses and gratifications. Next, there are opportunities for longitudinal research designs in the light of the FIRO-based explanation for the differences between younger and older play- ers and the similarities between the female and older audiences of digital games. As older players and woman gamers keep playing, they could become better at controlling games and they could receive more social gratifications from them. Both audiences are currently relatively new to gaming, so it will be interesting to see whether these changes will influence their playing motives and prefer- ences. This is especially relevant since the games industry has begun to aggres- sively target both audiences with specific content. We also argue that current uses and gratifications research on digital games could benefit from more detailed studies. Studies that target the use of a specific genre or even a game (Jansz et al., 2007) could offer a deeper understanding of why certain types of players play certain games. Finally, future quantitative research should continue solving sampling issues or look for deviating cases. We have yet to find players of the Nintendo DS, the Nintendo Wii, or other consoles, for example. There are also opportunities for qualitative research, which will be addressed in a follow-up study. In view of the low scores of the playing motives, it seems plausible that the AVGUG instrument (Sherry, Lucas, et al., 2006) is missing certain motives that cater specifically to the ageing individual, such as playing games ‘‘to train one’s memory or dexterity,’’ ‘‘to keep up with the changing times,’’ or 166
De Schutter 167
‘‘to learn about modern technology.’’ Vandebosh and Eggermont (2002) have argued
that age and its influences on media use should be studied in a wider context, with
attention to the physical, psychological, cognitive, social, and economic situations of
each individual, as well as his or her cultural, historical, and social identity. Certainly,
this should not be different for digital games.
Notes
1. We refer to the Dutch-speaking parts of Belgium by referring to the geographical region of
Flanders. This regional restriction was imperative for practical reasons: the quantitative
study that will be presented in this article will be followed up in the near future using a
qualitative approach based on observations and face-to-face interviews.
2. Fundamental Interpersonal Relationship Orientation (FIRO) theory states that individu-
als are driven by three interpersonal needs: inclusion (i.e., the desire to interact with oth-
ers and belong to a group), affection (i.e., the desire to experience closeness and
interpersonal warmth), and control (i.e., the desire to have power over an individual’s
environment).
3. In terms of genre, casual games can be described as puzzle games, Mahjong games, word
games, card games, board games, and simple action or light management games (such as
Diner Dash, Cake Mania, and Feeding Frenzy).
4. We only used the completed questionnaires during analysis. In terms of gender and age, the
distribution of the removed entries and the remaining sample were similar.
5. The most popular game did not equate to the most popular response. When asked what
their three favorite games were, many respondents answered with a genre instead of a
game title. The overall most popular response, for example, was ‘‘Mahjong games’’
(cited 20 times), which could refer to a plethora of games that can be played with
Mahjong tiles. Our respondents did, however, refer to card games using regular play-
ing cards by responding with a specific variation’s name (e.g., Spider Solitaire [13
times], Hearts [9 times], and FreeCell [6 times]).
6. The term ‘‘hardcore gamer’’ is often used in the dedicated game press and industry to jux-
tapose the term ‘‘casual gamer.’’ Therefore, we use this term to describe respondents
whose favorite games could not be coded as a puzzle game, an adaptation of a traditional
game, or an arcade action game.
7. Even though casual players are perceived as older than hardcore players, the
vast majority of the casual audience is estimated much younger than 55 (Nielsen-
Netratings, 2004).
Declaration of Conflicting Interests
The authors declared no conflicts of interest with respect to the authorship and/or
publication of this article.
Funding
The authors received no financial support for the research and/or authorship of this
article.
167168 Games and Culture 6(2)
References
Berk, L. E. (2003). Development through the lifespan. Boston: Allyn & Bacon.
British Broadcasting Corporation. (2005). Gamers in the UK: Digital play, digital lifestyles.
Available from http://open.bbc.co.uk/newmediaresearch/files/BBC_UK_Games_Research_
2005.pdf
Campbell, C. (2006). Iwata: Wii is like selling make-up to men. Available from www.
next-gen.biz/index.php?option¼com_content&task¼view&id¼3833&Itemid¼2
Copier, M. (2002). Ouderen & games: Een kwalitatief onderzoek naar ouderen die digitale
spellen spelen. Heerlen, Maastricht: International Institute of Infonomics, Centrum voor
Gender en Diversiteit in Maastricht.
De Schutter, B., & Vanden Abeele, V. (2008). Meaningful play in elderly life. Communicating
for Social Impact, the 58th Annual Conference of the International Communication
Association. Le Centre Sheraton Hotel, Montreal, Quebec, Canada.
Eggermont, S., & Vandebosch, H. (1999). Televisie in het leven van ouderen. Communicatie,
28, 2-19.
eMarketer. (2007). Gamer demographic spreads out. Available from www.emarketer.com/
Article.aspx?id¼1004798
Entertainment and Leisure Software Publishers Association. (2004). Chicks and joysticks: An
exploration of woman and gaming. Available from www.elspa.com/assets/files/c/
chicksandjoysticksanexplorationofwomenandgaming_176.pdf
Entertainment Software Association. (2007). Essential facts about the computer and video
game industry. Available from www.theESA.com
Farris, M., Bates, R., Resnick, H., & Stabler, N. (1994). Evaluation of computer games’
impact upon cognitively impaired frail elderly. Computers in Human Services, 11,
219-228.
Gamberini, L., Alcaniz, M., Barresi, G., & Fabregat, M. (2006). Cognition, technology and
games for the elderly: An introduction to ELDERGAMES Project. PsychNology Journal,
4, 285.
Goldstein, J., Cajko, L., Oosterbroek, M., Michielsen, M., van Houten, O., & Salverda, F.
(1997). Videogames and the elderly. Social Behavior and Personality, 25(4), 345-352.
Grodal, T. (2000). Video games and the pleasure of control. In D. Zillman, & P. Vorderer,
(Eds.), Media entertainment: The psychology of its appeal (pp. 197-223). Mahwah, NJ:
Lawrence Erlbaum.
Ijsselsteijn, W., Nap, H. H., de Kort, Y., & Poels, K. (2007). Digital game design for
elderly users. Proceedings of the 2007 conference on Future Play, (pp. 17-22). Toronto,
Canada.
Jansz, J., Avis, C., & Vosmeer, M. (2007). Playing the Sims2: An exploratory survey among
female and male gamers. Paper presented at the annual conference of the International
Communication Association, San Francisco, USA.
Jansz, J., & Martens, L. (2005). Gaming at a LAN Event: The social context of playing video
games. New Media & Society, 7, 333-355.
168De Schutter 169
Jansz, J., & Tanis, M. (2007). Appeal of playing online first person shooter games.
CyberPsychology & Behavior, 10, 135-138.
Khoo, E. T., Lee, S. P., Cheok, A. D., & Kodagoda, S. (2006). Age invaders: Social and
physical inter-generational family entertainment. Conference on Human Factors in
Computing Systems (CHI). Montreal, Canada.
Lucas, K., & Sherry, J. (2004). Sex differences in video game play: A communication-based
explanation. Communication Research, 31, 499-523.
Malliet, S. (2007). The challenge of video games to media effect theory (PhD Thesis, Catholic
University of Louvain).
Morris, C. (2006). Whither the grey gamer: While game players get older, the industry ignores
a potentially lucrative demographic. Available from money.cnn.com/2006/02/09/
commentary/game_over/column_gaming/
Nielsen-Netratings. (2004). Online games claim stickiest web sites. Available from www.
nielsen-netratings.com/pr/pr_040616.pdf
Pearce, C. (2008). The truth about baby boomer gamers: A study of over-forty computer game
players. Games and Culture, 3, 142-174.
Pelfrene, E. (2005). Ontgroening en vergrijzing in Vlaanderen 1990-2050: Verkenningen op
basis van de NIS-bevolkingsvooruitzichten. Available from publicaties.vlaanderen.be/
docfolder/2263/Ontgroening_en_vergrijzing_Vlaanderen_1990_2050.pdf
Reinecke, L., & Trepte, S. (2008). The effects of mood management processes on subsequent
cognitive performance. Journal of Media Psychology, 20, 3-14.
Rosengren, K. E. (1974). Uses and gratifications: A paradigm outlined. In J. G. Blumler &
E. Katz (Eds.), The uses of mass communications: Current perspectives of gratifications
research. Beverly Hills, CA: SAGE.
Rubin, A. M. (2002). The uses and gratifications perspective of media effects. In J. Bryant &
D. Zillman (Eds.), Media effects: Advances in theory and research (pp. 525-548).
Mahwah, NJ: Lawrence Erlbaum.
Ruggiero, T. E. (2000). Uses and gratifications theory in the 21st century. Mass Communica-
tion & Society, 3, 3-37.
Schueren, B. (1986). Video games: An exploration of their potential as recreational activity
programs in nursing homes. Activities, Adaptation & Aging, 8, 49-57.
Schutz, W. C. (1958). FIRO: A three-dimensional theory of interpersonal behavior.
New York: Rinehart and Company.
Selnow, G. W. (1984). Playing videogames: The electronic friend. Journal of Communication,
34, 148-156.
Sherry, J., Desouza, R., Greenberg, B., & Lachlan, K. (2003). Relationship between develop-
mental stages and video game uses and gratifications, game preference and amount of
time spent in play. Paper presented at the annual meeting of the International Communi-
cation Association, Marriott Hotel, San Diego, CA.
Sherry, J. L., Lucas, K., Greenberg, B. S., & Lachlan, K. (2006). Video game uses and grat-
ifications as predictors of use and game preferences. In P. Vorderer & J. Bryant (Eds.),
Playing video games: Motives, responses & consequences (2nd ed. pp. 525-548). Mahwah,
NJ: Lawrence Erlbaum Associates.
169170 Games and Culture 6(2) Tanis, M., & Jansz, J. (2008). Gaming for different reasons: What motivates people to play a specific video game? Paper presented at the annual conference of the ICA, Montreal, Canada. Tinney W. (ed.) (2005). The demographic issue, understanding the casual gamer. Online Games Quarterly, 1(2), Available at http://www.igda.org/online/quarterly/1_2/online_ quarterly_1_2.pdf. Vanden Abeele, V., Husson, J., Vandeurzen, L., & Desmet, S. (2007). A Soft Approach to Computer Science: Designing & Developing Games for and with Senior Citizens. Inter- national Journal of Game Development, 2(2), 41-62. Vance, M. (2004). Casual online gamer study. Lewisville, TX: Digital Marketing Services for AOL. Private industry report (Summarized in Pearce, 2008). Vandebosch, H., & Eggermont, S. (2002). Elderly people’s media use: At the crossroads of personal at societal developments. Communications, 27, 437-455. Vanden Abeele, V., Husson, J., Vandeurzen, L., & Desmet, S. (2007). A soft approach to com- puter science: Designing & developing games for and with senior citizens. International Journal of Game Development, 2. Wallace, M., & Robbins, B. (2006). casual games white paper. International Game Developers Association. Available from www.igda.org/casual/IGDA_CasualGames_Whitepaper_ 2006.pdf Walma van der Molen, J. H., & Jongbloed, W. (2007). An exploratory uses and gratifications study of free games on the Internet. Paper presented at the 57th conference of the Interna- tional Communication Association, San Francisco. Whitcomb, R. G. (1990). Computer games for the elderly. ACM SIGCAS Computers and Society. Proceedings of the conference on Computers and the quality of life, 20. Wigand, R. T., Borstelmann, S. E., & Boster, F. J. (1985). Electronic leisure: Video game usage and the communication climate of video arcades. Communication Yearbook, 9, 275-293. Bio Bob De Schutter is a PhD candidate at the Centre for Media Culture and Communication Technology of the Catholic University of Louvain. His doctoral dissertation explores the use of digital games by an older audience in Flanders. He also teaches game design at the Group T Engineering University of Louvain, where he is involved in various research projects that approach the development of serious games from a user-centered design perspective. 170
You can also read
