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Eigh ypes o ideo game expe ience
© 2024 The Au ho s. Published by Else ie B.V.
Published e sion
Vahlo, Jukka; Tuu i, Kai
Vahlo, J., & Tuu i, K. (2025). Eigh ypes o ideo game expe ience. En e ainmen Compu ing,
52, A icle 100882. h ps://doi.o g/10.1016/j.en com.2024.100882
2025
Con en s lis s a ailable a ScienceDi ec
En e ainmen Compu ing
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Eigh ypes o ideo game expe ience
Jukka Vahlo a,c,∗, Kai Tuu i b,c
aCen e o Collabo a i e Resea ch CCR, School o Economics, Uni e si y o Tu ku, Finland
bFacul y o Educa ion and Psychology, Uni e si y o Jy äskylä, Finland
cDepa men o Music, A and Cul u e S udies, Uni e si y o Jy äskylä, Finland
ARTICLE INFO
Keywo ds:
Game expe ience ypes
Su ey
La en class analysis
Game p e e ences
ABSTRACT
The s udy o game expe ience is a well-es ablished a ea wi hin game esea ch, suppo ed by nume ous
models. These models, while aluable, o en ocus on analyzing game expe iences wi hin speci ic con ex s
a he han acili a ing compa a i e analyses. Add essing his esea ch gap, ou s udy empi ically iden i ies
p e alen game expe ience ypes ha a e common ac oss a ious games. By analyzing 5,372 game expe ience
desc ip ions p o ided by 1,193 su ey esponden s, his esea ch employs a su ey design inspi ed by he
low o quali a i e in e iews, acili a ing a comp ehensi e unde s anding o he di e se ac o s shaping hese
expe iences. Th ough la en class analysis, we delinea e eigh dis inc game expe ience ypes: Compelling
Challenge, Imme si e Explo ing, C ea i e Ca ing, Ene ge ic Rushing, Compe i i e Shoo ing, Chee ul Bouncing,
S a egic Managemen , and Daily Dwelling. Each ype is analyzed in e ms o bo h he a iables om he la en
class analysis and addi ional su ey a iables, enhancing ou unde s anding o hei unique and compa a i e
cha ac e is ics. This app oach sheds ligh on he mul i ace ed na u e o game expe iences and b oadens ou
insigh s in o playe engagemen ac oss di e en game gen es, o e ing p ac ical implica ions o game design,
ma ke ing, and u u e esea ch.
1. In oduc ion
Game expe iences a e a widely s udied subjec , wi h nume ous
models and amewo ks de eloped by bo h businesses and esea che s.
In game esea ch and beyond, game expe ience models a e u ilized
o s udy how di e en ypes o playe s in e ac wi h games. Insigh s
om hese models help e ine heo ies abou game design and playe
engagemen , con ibu ing o he unde s anding o game expe ience as
a psychological, cul u al, and social phenomenon. Models ha classi y
game expe ience ypes also acili a e a mo e nuanced unde s anding o
how games a ec indi iduals and g oups, enhancing he capaci y o c e-
a e mo e engaging, pe sonalized, and e ec i e game-based applica ions
o ields including en e ainmen , educa ion and heal h.
Game expe ience models a e impo an o game businesses since by
classi ying di e en ypes o game expe iences, de elope s can ailo
game ea u es o sui a ious playe ypes, enhancing engagemen
and sa is ac ion. This can in ol e adjus ing di icul y le els, na a i e
elemen s, o in e ac i e componen s based on he playe ’s capabili ies
and p e e ences. Modeling game expe iences also help designe s by
p o iding a amewo k o in e p e ing and discussing playe eedback.
Knowing he ypes o expe iences playe s conside g a i ying also al-
lows companies o c a pe sonalized ma ke ing campaigns. This can
∗Co esponding au ho .
E-mail add esses: [email p o ec ed] (J. Vahlo), [email p o ec ed] (K. Tuu i).
inc ease he e ec i eness o ad e isemen s by a ge ing playe s wi h
con en ha aligns wi h hei in e es s.
Some game expe ience models ocus on analyzing game quali ies,
examining how speci ic elemen s like gameplay mechanics, aes he ics,
social ea u es, and na a i e design con ibu e o he o e all playe
expe ience. O he models build upon playe ai s and playe ypes,
explo ing how mo i es, p e e ences, and beha io s shape game expe i-
ences and p edic playe s’ choice o games and play s yles. While hese
exis ing models ha e p o ided aluable insigh s, hey ha e ce ain
limi a ions. Models ha ocus on analyzing game expe ience om he
pe spec i e o playe ai s may o e look he con ex ual and si ua ional
ac o s ha in luence game expe iences, ea ing hem as s a ic and
consis en ac oss di e en games and en i onmen s. On he o he hand,
models ha ocus on game quali ies may ha e o ea playe s as
implied [1], which is o say ha playe s’ a ied easons o play a e
o en le ou side o he main esea ch model. As a consequence, hese
models a e o en cons uc ed based on game designe s’ o ma ke e s’
expe ise on unde s anding he game expe ience wi hou co ela ing i
wi h ex ensi e empi ical da a on how playe s’ hemsel es expe ience
he game and i s elemen s.
This s udy aims o con ibu e o he exis ing body o knowledge
by add essing he limi a ions o cu en models and adop ing a mo e
h ps://doi.o g/10.1016/j.en com.2024.100882
Recei ed 24 Ap il 2024; Recei ed in e ised o m 20 Augus 2024; Accep ed 22 Augus 2024
En e ainmen Compu ing 52 (2025) 100882
A ailable online 30 Augus 2024
1875-9521/© 2024 The Au ho s. Published by Else ie B.V. This is an open access a icle unde he CC BY-NC license ( h p://c ea i ecommons.o g/licenses/by-
nc/4.0/ ).
J. Vahlo and K. Tuu i
phenomenologically comp ehensi e and con ex ualized app oach o
unde s anding di e en game expe iences, while s ill inco po a ing
empi ical s a is ical da a analysis. By emphasizing he subjec i e ex-
pe iences o playe s, ou goal is o cap u e bo h he mul idimensional
and dynamic na u e o game expe iences and he di e se ac o s ha
shape playe p e e ences. The e is a need o game expe ience models
g ounded in ex ensi e empi ical analysis o how playe s pe cei e g a -
i ying and memo able games. The p ima y objec i e o his s udy is o
cons uc such a playe da a-d i en model, one ha conside s a a ie y
o game elemen s and con ex ual ac o s c i ical o di e en ia ing one
game expe ience om ano he .
We begin he a icle by discussing p io esea ch on game expe i-
ences and he challenges associa ed wi h assessing hem. Nex we will
p esen he esea ch ques ions o he cu en s udy and ela e hem
o ea lie esea ch on game expe iences. We will hen desc ibe he
me hodology employed, which includes he design o a esea ch su ey
cap u ing mul iple ypes o alued game expe iences. Finally, we will
p esen he esul s and discuss he implica ions o game s udies and
playe esea ch.
2. Theo e ical backg ound
2.1. Con ex -speci ic and gene al models o game expe ience esea ch
The esea ch on game expe iences can be b oadly ca ego ized in o
wo app oaches: con ex -speci ic and gene al models. Con ex -speci ic
models analyze playe expe iences wi hin he speci ic con ex o playing
a pa icula game and in ela ion o he ea u es o ha game. This
in ol es examining ac o s such as gameplay mechanics, g aphics,
sound design, na a i e, le el design, playabili y, and o e all playe sa -
is ac ion. The e o e, he con ex -speci ic app oach closely aligns wi h
he p ima y objec i e o Games Use Resea ch (GUR), which is o
unde s and he indi idual playe ’s expe ience du ing and immedia ely
a e playing a speci ic game [2–7].
In con as o con ex -speci ic models, gene al models aim o un-
de s and he unde lying ac o s and mo i a ions behind why people
play games and seek game expe iences. These models del e in o he
psychological, social, and cul u al aspec s o gaming, wi h an objec i e
o iden i ying common psychosocial d i e s and he needs ul illed
h ough gaming. Gene al models ha e p ima ily been applied in he
h ee main a eas o esea ch: (1) playe p e e ences, which encom-
pass playe mo i es, p e e ed play s yles, and beha io al pa e ns
ac oss mul iple games [e.g., 8–13], (2) demog aphic ac o s ela ed o
playe s and hei a a a s [e.g., 14–16], and (3) playe cul u es and
communi ies [e.g., 17–19].
While esea che s using bo h con ex -speci ic and gene al app oaches
equen ly employ su eys, in e iews, and psychophysiological expe -
imen s o s udy game expe iences, hese app oaches aim o add ess
only pa ially o e lapping esea ch ques ions. Fo example, a con ex -
speci ic app oach migh explo e which elemen s o a game a e pe -
cei ed as nos algic and how nos algia mo i a es con inued gameplay
o ha pa icula game, whe eas a s udy based on a gene al model o
game expe ience migh in es iga e he ex en o which playe s engage
wi h games o sa is y a desi e o nos algia. Bo h ypes o s udies ocus
on unde s anding game expe iences, albei om di e en pe spec i es.
Howe e , bo h con ex -speci ic and gene al app oaches sha e a simila
unde s anding o he elemen s and ac o s ha shape and con ibu e o
he game expe ience. In ou e o o iden i y di e en ypes o game
expe iences, i is c ucial o conside hese aspec s and hei implica ions
o he p esen esea ch.
In hei li e a u e e iew o 15 models o game expe ience e-
sea ch, Högbe g, Hama i, and Wäs lund [20] ha e iden i ied ele en
dimensions ha a e equen ly ega ded as c ucial componen s o he
game expe ience. Since hese dimensions we e iden i ied as based
on a li e a u e e iew on how he game expe ience has equen ly
been s udied and b oken down in o i s p e alen aspec s, he ele en
Fig. 1. A igu e summa izing how con ex -speci ic models and gene al models o game
expe ience esea ch ha e been applied o s udying mo i a ional ac o s and enjoymen
ac o s as desc ibed by C aw o d [34].
dimensions can be ega ded as pa amoun o any esea ch on he
game expe ience ega dless o whe he he esea ch ocuses on con ex -
speci ic o gene al app oach. The dimensions encompass play ulness,
enjoymen , a ec , low, imme sion, challenge, skill, compe i ion, social
expe ience, p esence, and senso y expe ience.
Play ulness is a b oad ca ego y ha in e sec s wi h se e al o he
o he en dimensions, as i encompasses quali ies like cu iosi y, c e-
a i i y, imagina ion, spon aneous lea ning, and a willingness o ex-
plo e [21–24]. Enjoymen and a ec bo h pe ain o he emo ional
s a es e oked by he game expe ience and how game design p ac ices
aim o c ea e engaging and cap i a ing expe iences [25,26]. Flow,
challenge, and skill a e in e connec ed concep s, as he s a e o au o elic
low is said o be a ainable when playe s’ skills and abili ies align
wi h he challenges p esen ed by he en i onmen [27,28]. Simila ly,
om he pe spec i e o E ing Go man’s [29] in luen ial analysis o
sel -expe ience and social in e ac ion, imme sion,p esence,social expe-
ience, and senso y expe ience a e closely in e wined. Bo h p esence
and imme sion a e desc ibed as he sensa ion o ‘‘being he e’’ and he
pe cep ion o di ec expe ience wi hou media ion [30]. In esea ch,
p esence has been desc ibed as consis ing o a leas wo dimensions:
spa ial p esence and social p esence. Spa ial p esence e e s o he
physical sensa ion o being anspo ed o ano he en i onmen , while
social p esence e e s o he pe cep ion o being in he p esence o
ano he au onomous being [29–33].
I would be bene icial in ela ion o unde s anding he dimensions
o game expe ience, i we can u he cla i y he concep ual dis inc ion
be ween he esea ch on gene al gameplay mo i a ion and he models
ha assess game-speci ic ea u es. To achie e his, i is help ul o e isi
he insigh s o game designe and esea che Ch is C aw o d [34], who
p oposed dis inguishing be ween he ques ion o ‘‘why do people play
games in gene al?’’ and he ques ion o ‘‘wha makes one game mo e
enjoyable han ano he ?’’ The o me ques ion ela es o mo i a ing
ac o s, while he la e ocuses on ac o s ha con ibu e o enjoymen
du ing gameplay. Mo i a ing ac o s encompass psychological needs and
explici sel -a ibu ed easons ha in luence indi iduals’ choices o en-
gage wi h games ins ead o pu suing o he leisu e ac i i ies. In con as
o his, enjoymen ac o s in luence an indi idual’s game choices and
ep esen he speci ic g a i ica ion o e ed by pa icula ideo games o
pa icula ype o ideo games [35,36].
2.2. Resea ch ques ions
In gene al models o he game expe ience esea ch, he analysis
p ima ily emphasizes mo i a ional ac o s, while enjoymen ac o s a e
only included as desc ip i e a iables (Fig. 1). On he o he hand,
En e ainmen Compu ing 52 (2025) 100882
2
J. Vahlo and K. Tuu i
in con ex -speci ic models, enjoymen ac o s a e ypically conside ed
only in ela ion o he pa icula game expe ience unde analysis.
The e exis s a gap in game expe ience esea ch ega ding models
ha ocus on game enjoymen ac o s in ways ha aim o b idge
con ex -speci ic and gene al app oaches: he empi ical iden i ica ion
o p e alen game expe ience ypes emains la gely unexplo ed. Mo e-
o e , unde s anding how playe s’ sus ained enjoymen ac o s, linked
o hei gen e p e e ences, may ela e o he game expe iences hey
alue he mos emains uncha ed. To add ess hese gaps, we ask
wha p e alen ypes o game expe iences can be empi ically iden i ied
when he esea ch ocus is se on playe s’ enjoymen ac o s o playing
pa icula games.
Mo e speci ically, he esea ch ques ions o he cu en s udy can be
o mula ed as:
RQ1: How can a esea ch su ey be designed o s a is ical analysis,
allowing esponden s o desc ibe mul iple ypes o hei a o ed game
expe iences in de ail, i espec i e o whe he hese expe iences a e
simila o signi ican ly di e en om each o he ?
RQ2: In a esea ch model ha enables playe s o conside bo h he
main elemen s o he games hey ha e played and aspec s o hei own
gaming expe ience wi h hese games, wha kind o o ms do playe s’
p e e ed ideo game expe iences ake?
RQ3: How a e playe s’ gene al enjoymen ac o s as gen e p e e -
ences associa ed wi h he ypes o game expe iences hey a o ?
3. Me hodology
3.1. Su ey me hodology
F om a me hodological pe spec i e, he o emos aim o his s udy is
o in es iga e how ecu en pa e ns in indi iduals’ a ied expe iences
o playing ideo games can be s udied using s uc u ed s a is ical
su eys in a way ha enables and encou ages pa icipan s o desc ibe
he pa icula i y o each o hei game expe iences (RQ1). To achie e
his, a sel - epo playe p e e ence su ey was designed, d awing some
inspi a ion om he s uc u al p inciples o quali a i e in e iews. The
objec i e is o collec sel - epo da a on playe s’ mul iple game expe i-
ences a he han jus one and hen iden i y ecu ing pa e ns in hese
indi idual desc ip ions, he eby enabling a mo e phenomenologically
inclined analysis o p e alen game expe ience ypes.
The decision o collec da a h ough a su ey, a he han h ough
di ec in e iews o obse a ional me hods, was d i en by he need o
ga he a la ge da ase capable o ep esen ing a wide ange o playe
expe iences ac oss di e se gaming con ex s. Su eys a e pa icula ly
adep a his, as hey allow o b oad pa icipa ion while main aining a
s uc u ed o ma ha can be s a is ically analyzed. The design o he
su ey was in en ionally eminiscen o in e iew echniques o ha ness
some o he ocus, dep h and de ail o en ound in quali a i e esea ch.
Wi h his app oach, we aimed o elici ich, desc ip i e da a ha goes
beyond su ace-le el p e e ences and aps in o he deepe emo ional
and cul u al engagemen s playe s ha e wi h games. This design choice
was c ucial no only o ga he ing de ailed da a bu also o aligning
he su ey’s s uc u e wi h ou analysis goals, which p io i ize unde -
s anding he essence o expe iences as hey a e pe cei ed by indi iduals
(RQ2). This alignmen ensu ed ha he me hodological app oach o
he cu en s udy was cohe en wi h i s analy ical objec i es, he eby
p o iding a holis ic iew o how game expe iences a e li ed h ough
and a icula ed by playe s.
In s udies aiming o p o ide a comp ehensi e desc ip ion o expe-
ien ial ea u es, a quali a i e esea ch app oach is undoub edly mo e
sui able han a s a is ical app oach elying on sel - epo su eys and
psychome ically alida ed ins umen s. Howe e , he e a e ways o
inco po a e s a is ical analyses ei he in combina ion wi h quali a i e
me hods o independen ly, o b idge he gap be ween s a is ical and
quali a i e app oaches. Due o he alidi y o li ed expe ience [37,38],
i is necessa y ha such s a is ically o ien ed s udies do no equi e
in o man s o gene alize hei expe iences, bu a he ask hem o b ing
a pa icula o a pa icula kind o expe ience wi hin hem and con-
cen a e on he expe ience o an ex ended pe iod o ime. Rega dless
o he applied ques ion ypes, i is impo an o design a su ey ha
encou ages and suppo s su ey pa icipan s on ocusing on desc ibing
a pa icula expe ience unde analysis.
We designed a sel - epo su ey on alued game expe iences by
d awing some inspi a ion om he ways hema ic in e iews and elic-
i a ion in e iew echniques suppo he in e iewee in ocusing on
and desc ibing a pa icula expe ience. In gene al, hema ic in e iews
aim o explo e and unde s and he unde lying pa e ns and meanings
wi hin pa icipan s’ expe iences. They a e s uc u ed in o p ede ined
in e iew opics ha aim o co e an impo an aspec o in e iewee’s
meaning-making [e.g., 39]. Simila ly o his, we s uc u ed he su ey
using ocused lenses in a manne ha co esponds wi h he opics o
hema ic in e iews. Elici a ion in e iew he e e e s o speci ic ech-
niques in which he in o man s a e epea edly asked o ocus on he
same pa icula expe ience o hei pas . A he co e o his me hod is
a cyclic p ocess in which an e oca i e ocus on he a ge expe ience
is main ained while, h ough epea ed e-enac ions o he eminisced
li ed expe ience, he in e iewee is guided o un old desc ip ions o he
expe ience in a ying angles [38]. Following a simila idea, ou su ey
echnique was designed o e ain a sus ained ocus on expe iences
o a pa icula game. Hence, he ocused lenses o he su ey we e
designed and s uc u ed in a manne ha emb aced a ying desc ip i e
ocuses on he expe ience, g adually un olding di e en aspec s o
wha he expe ience is and how i could be desc ibed, and p e e ably
a oiding ques ions oo much equi ing gene aliza ions o easonings
om he in o man s. This kind o ocused echnique (see Fig. 2) was
used o un eil ex ensi e ye compa able laye s o desc ip ion on game
expe iences.
In a well-conduc ed in e iew, in e iewees a e able o exp ess
hei iewpoin s and expe iences eely, while he in e iewe ypically
also a en i ely engages wi h he esponses, encou aging u he elab-
o a ions and p obing o deepe insigh s [38–40]. O cou se, wi hin
su eys, such a ich in e ac ion be ween pe sons is no possible, as
hey a e mos ly ixed in hei low o ques ions. The aim wi h ou
ocused su ey echnique, howe e , is o somewha mimic he eel o
being p esen in a con e sa ion-like in o ma ion exchange be ween an
in e iewee and an in e iewe . This was implemen ed by p esen ing
ques ions p e e ably one a a ime o he esponden , and a o ding
s aigh o wa d-as-possible ways o answe he ques ion, o example
ia an a ay o checkbox i ems, mul iple-choice ields, o open an-
swe ing. Howe e , since ou goal is o s a is ically iden i y p e alen
and eoccu ing game expe ience ypes, we conside ed ha he su ey
should mainly consis o p e-s uc u ed a he han open-ended ques-
ions. Di e en ly pu , he su ey design was in luenced by in e iew
echniques ega ding he sha ed goal o (1) p o ide suppo o s udy
pa icipan s in ocusing on he game expe ience while (2) p o iding
a guided and e o less means o un old desc ip ions o he ocused
expe ience by esponding o checkbox op ions om a ying angles o
di e en hema ic lenses.
3.2. Su ey design and implemen a ion
The online su ey began by asking pa icipan s o men ion a ideo
game hey enjoyed playing o ha had become a signi ican pa o hei
daily li e. A e his, pa icipan s we e asked o speci y why hey chose
o men ion he game, wi h ou p ede ined easons p o ided: ‘‘Because
playing he game was e y enjoyable’’, ’’Because i has been meaning ul
o me,‘‘ ’’Because I had ond memo ies abou i ,‘‘ and ’’Because i has
g own o be a pa o my e e yday li e’’. Pa icipan s could choose
any combina ion o hese easons. Following his, pa icipan s we e
asked o indica e he p ima y de ice hey used o play he game and
he ypical du a ion o a play session. To s eamline he p ocess, we
implemen ed au ocomple e game lis s and au ocomple e game de ice
En e ainmen Compu ing 52 (2025) 100882
3
J. Vahlo and K. Tuu i
Fig. 2. An ins ance o expe ience- ocused su ey echnique, ini ialized wi h a Focused
Expe ience (𝐹 𝐸), ollowed by a se ies o Focused Lenses (𝐹 𝑙𝑛) ha e ain he ocus, and
inally ending he phase wi h a ese o ocus (e.g., o a new i e a ion wi h ano he
game expe ience).
lis s in he su ey. Pa icipan s could begin yping he name o he game
hey had in mind and selec he game i le om a pop-up menu ha
displayed close ma ches. The au ocomple e game lis consis ed o 3,386
popula games, and he game de ice lis had 181 p ede ined op ions.
I pa icipan s could no ind a ma ch in he au ocomple e lis s, hey
we e ins uc ed o manually en e he game and de ice names in he
sea ch box. The use o au ocomple e lis s se ed wo pu poses. Fi s ly,
i sa ed esponden s’ e o by acili a ing he iden i ica ion o co ec
game names. Secondly, i ensu ed cleane da a as game i les can be
challenging o emembe , and many pa icipan s end o use ac onyms
o sho ened e sions o game i les in hei communica ion.
In succession o he in oduc o y ques ions, an ini ial ocus on a
pa icula game expe ience was se and pa icipan s hen s a ed o
espond o a se ies o ocused lenses, which allowed hem o opically
desc ibe hei expe ience wi h he game in de ail (see Fig. 2). Each
lens included an a ay o checkbox op ions om which pa icipan s
selec ed he i ems ha bes desc ibed hei game expe ience in ocus.
Checkbox i ems we e he e conside ed o be he mos con enien way
o espond o he ques ion o a ocused lens. F om an a ay o checkbox
i ems, esponden s could easily and wi h only a ew clicks desc ibe he
mos p ominen aspec s in ela ion o he pe sonal game expe ience in
ques ion.
A e esponding o he lenses, he ocus was ese o ano he game
ha a pa icipan would like o men ion (see Fig. 2). In all, su ey
pa icipan s we e ins uc ed o men ion a minimum o h ee and a
maximum o i e games. A e pa icipan s men ioned h ee o i e
games and esponded o he ques ions o he co esponding lenses,
he expe ience- ocused phase was comple ed and he su ey mo ed o
adi ionally s uc u ed ques ions abou mo i a ional ac o s assessing
pa icipan s’ gene al gameplay p e e ences, gaming mo i es and o ien-
a ions, and game gen e play habi s. Towa ds he end o he su ey,
pa icipan s we e asked demog aphic ques ions, hei weekly play ime,
and hei mon hly expendi u e on ideo games.
4. Measu es and s udy pa icipan s
4.1. Measu es: The ocused lenses on game expe iences
The ocused lenses (see Fig. 2) and hei co esponding checkbox
ype ques ion op ions (see Tables 3 and A.7) we e designed based on
how ea lie esea ch had s udied a ied aspec s o he game expe ience.
We examined se e al su ey ins umen s speci ically designed o assess
di e en ace s o game expe ience, pa icula ly hose ela ing o enjoy-
men ac o s ha in luence an indi idual’s p e e ence o ce ain games
o e o he s.
The s uc u e o ocused lenses comp ised se en opics aligned wi h
speci ic expe ien ial ac o s o playing he speci ic game: gaming si u-
a ion (7 i ems), gameplay ac i i y ypes (26 i ems), gameplay challenges
(16 i ems), emo ions in gameplay (20 i ems), o e all game expe ience (13
i ems), game elemen app ecia ion (24 i ems), and o ien a ions o play he
game (9 i ems). The i ems o he se en lenses a e lis ed in Tables 3 and
A.7. Excep o he gaming si ua ion ques ion, pa icipan s we e asked
o choose one o ou op ions ha bes cap u ed hei game expe iences
in each opic. This was done, because limi ing he numbe o op ions
enables s a is ical analyses in a way in which he numbe o selec ed
op ions does no ha e unnecessa y s a is ical weigh . Ins ead, limi ing
he op ions o only a ew enables he esea che o ocus on he p o ile
o each game expe ience desc ip ion in which bo h he selec ed op ions
and he unselec ed op ions can be conside ed.
In he case o he gaming si ua ion lens (lens 1), we delinea ed se en
common si ua ions in which ideo games a e o en played (e.g. ‘‘A
home’’, ‘‘On a ip’’). The 26 i ems o he gameplay ac i i y ype
lens (lens 2) we e designed based on a psychome ically alida ed
ins umen ha assesses playe s’ p e e ences in i e ypes o game-
play ac i i ies: agg ession, explo a ion, managemen , coo dina e, and
ca e aking [11,35]. The ocused lens on game challenges (lens 3)
was inspi ed by he Videogame Challenge In en o y (CHA) [41] ha
measu es physical, analy ical, socioemo ional, and insigh ype o game
challenges [see also 42,43]. The lis o emo ions in game expe ience
lens (lens 4) was gene a ed on he basis o he empi ically ounded
model o 13 dis inc dimensions o subjec i e eelings associa ed wi h
music [44]. Se en addi ional emo ion ypes (awe, ca e ee, cu ios-
i y, empa hy, exci emen , lo e/a ac ion, nos algia) we e added o
complemen po en ially mo e gameplay-based emo ions. Fo designing
he ocused lens ha enabled pa icipan s o desc ibe o e all game
expe ience (lens 5), we d ew om a lis o gene al mo i es o play
ideo games. This was done as mo i e ac o s aim o po ay on a high
abs ac ion le el he main quali ies in ideo games ha unde sco e
playe s’ in e es and desi e o engage wi h his expe ience ype. A
lis o 13 i ems we e de eloped and hey co e ed expe ience ypes
and mo i e ca ego ies o compe i ion, achie emen , imme sion, un
and enjoymen , challenge and skill, sel -exp ession, bo edom, escapism,
social in e ac ion, play ulness, aes he ic expe iences, expe iences ha
s uc u e daily li e, and expe iences ha a e engaging also ou side
gaming sessions [see, e.g., 5,12,13].
Ou model o ocused lenses aligns wi h he ele en dimensions
iden i ied as cen al o game expe ience: play ulness, enjoymen , a ec ,
low, imme sion, challenge, skill, compe i ion, social expe ience, p es-
ence, and senso y expe ience [20]. Game challenges (lens 3) di ec ly
ela es o he dimensions o challenge and skill, highligh ing how
he alignmen o a playe ’s abili ies wi h he challenges p esen ed by
he game can acili a e he s a e o low, a co e componen o he
gaming expe ience. Emo ions in gameplay (lens 4) ies di ec ly in o
he dimensions o a ec , enjoymen , and senso y expe ience, e lec ing
he emo ional esponses ha games elici om playe s. These esponses
a e undamen al o unde s anding how games cap i a e and main ain
playe in e es .
The gameplay ac i i y ypes (lens 2) e lec he di e si y o in-
e ac ions ha games can o e , ela ing closely o he dimensions o
play ulness, imme sion, and social expe ience. This acknowledges he
a ie y o ways games can engage playe s, whe he h ough compe -
i i e play, coope a i e asks, o explo a ion, all o which con ibu e
o a game’s appeal and i s abili y o p o ide meaning ul expe iences.
The inclusion o gaming si ua ion (lens 1) aligns wi h he dimensions
o p esence and senso y expe ience, ecognizing he impo ance o
he physical and i ual con ex s in which gaming akes place. This
encompasses he imme si e quali ies o games, enhancing hei sense
o p esence wi hin he game en i onmen .
Finally, conside ing he mo i a ing game expe ience as a whole
(lens 5) allows us o encompass a b oad and mo e gene alized iew
o wha d i es playe s o engage wi h games, in eg a ing insigh s in o
how a ious aspec s o gameplay come oge he o ul ill psychological,
social, and cul u al needs. This holis ic app oach ensu es ha we
cap u e he complex in e play o ac o s ha con ibu e o he gaming
En e ainmen Compu ing 52 (2025) 100882
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J. Vahlo and K. Tuu i
expe ience, esona ing wi h he model p oposed by Högbe g, Hama i,
and Wäs lund and all o i s ele en dimensions [20].
In addi ion o he abo e i e lenses, a o al o 24 checkbox i ems
we e designed o enable esponden s o desc ibe he mos app eci-
a ed game elemen s (lens 6) in hei ocused gameplay expe ience.
Finally, o measu e gene al playe o ien a ion (lens 7) owa ds game
expe iences, we u ilized he 9-i em Hedonic and Eudaimonic Mo i es
o Ac i i ies (HEMA) scale [45] and adap ed i s Like - ype in en o y
i ems in o checkbox i ems. The lenses conce ning game elemen ap-
p ecia ion and o ien a ions owa d playing he men ioned game we e
conside ed mo e abs ac , e alua i e, and e lec i e laye s o desc ip-
ion. The e o e, hey ep esen a di e en kind o measu e compa ed
o he i s i e lenses. Hedonic and eudaimonic gaming o ien a ions
e e mo e o mo i a ional ac o s and playe disposi ions han o game
enjoymen ac o s, he la e o which a e he ocus o his esea ch.
The las wo lenses (6 and 7) we e included as auxilia y measu es o
in es iga ing he cons uc alidi y o he app oach.
In selec ing i ems o h ee o he se en lenses (2, 3, 7), we di ec ly
d ew om psychome ically alida ed su ey ins umen s and hei ac-
o s uc u es. In hese cases, he i ems included in hei co esponding
lenses we e selec ed based on ac o loadings hese i ems had shown
in alida ion s udies. In p inciple, we op ed o choose hose i ems ha
had shown he highes loadings o each o he iden i ied ac o s.
4.2. S udy pa icipan s and da a collec ion
The su ey da a1o 1,200 esponden s we e collec ed in he UK
(N=600) and in he US (N=600) ia online esea ch pla o m P oli ic.
Cu en ly P oli ic holds an online panel o o e 130,000 e ed pa ici-
pan s ac oss se e al coun ies, and i s da a se ices a e widely applied
by many esea ch o ganiza ions. P oli ic u ilizes a model in which a
co esponding esea che has a possibili y o e alua e each submission
be o e app o ing hem i a pa icipan iola es some o he basic
c i e ia o he su ey. Such a c i e ia can include esponding o each
ques ion wi h he same alue, submi ing an un inished su ey because
o echnical issues, o esponding oo quickly o he su ey. Because
o his p ocedu e, no la ge-scale addi ional da a cleaning p ocess was
no equi ed o ou da a. Howe e , we we e able o iden i y one
submission om he UK sample and six submissions om he US sample
who esponded o he ques ions by using a pa icula pa e n o alues
(e.g., 1, 2, 3, 1, 2, 3...o 2, 5, 2, 5...) ac oss se e al o he psychome ic
ins umen s. A e he cleaning p ocess, he inal sample consis ed o
(N=1,193).
Bo h o he samples we e collec ed by using he balanced sample
op ion o P oli ic ega ding gende s, and he su ey was a ge ed o
hose 18–70 aged P oli ic panel membe s who had epo ed o play
some ideo game a leas occasionally wi hin he pas 12 mon hs. A
he ime o collec ing he da a, o e 40,000 P oli ic panelis s i his
c i e ion. We did no u ilize any o he c i e ion o game play habi s as
we aimed o a sample ha would ep esen as many aspec s o game
expe ience p e e ences as possible. This was a conscious decision as he
main objec i e o his s udy was o iden i y p e alen game expe ience
ypes based on playe expe iences, and his goal is only achie able
i he da a would ep esen as many ypes o playe s as possible. In
he s udy desc ip ion on P oli ic’s panel se ice, we u he mo e no ed
ha i was equi ed o each su ey pa icipan o be able o name
a leas h ee ideo games hey had enjoyed o play o ha had been
an in eg al pa o hei e e yday li e. All pa icipan s p o ided hei
w i en in o med consen o pa icipa e in his s udy. The samples we e
collec ed be ween 5 h and 10 h o Oc obe 2022. The median ime a
use spen in aking he su ey in he UK sample was 22 min and in he
US sample 21 min. Desc ip i e s a is ics o he ull sample a e epo ed
in Table 1.
1The da a- ela ed p ocedu es used in his s udy adhe e o he ene s o
he Decla a ion o Helsinki. E hical e iew and app o al was no equi ed o
he s udy on human pa icipan s in acco dance wi h he local legisla ion and
ins i u ional equi emen s.
Table 1
Desc ip i e demog aphics o he esea ch
da a o he s udy.
UK USA To al
N 599 594 1193
Female 292 284 576
Male 296 292 588
Non-bina y 7 14 21
No disclosed 4 4 8
Mean age 36.7 32.9 34.8
Table 2
Mos played game gen es, epo ed as he pe cen age o he sample who epo ed o
play he men ioned gen e equen ly.
Game gen e % pa icipan s Game gen e % pa icipan s
Ad en u e 60% Pla o m 13%
Ac ion 55% MMORPGs 13%
Ac ion-Ad en u e 38% Ba le Royale 11%
Role-playing 38% Figh ing 10%
Puzzle 36% Pa y games 8%
Shoo e games 28% Visual no el 5%
S a egy 26% Collec ible Ca d Games 3%
Simula ion 25% Edu ainmen 3%
Racing 17% MOBA 3%
Spo s 14%
F om a p ede ined lis o 17 game gen es, he su ey pa icipan s
we e asked o selec 1–4 gen es ha hey had played he mos (
Table 2). Ad en u e games we e men ioned he mos as some 60%
o he whole sample epo ed o play games o his gen e. This was
ollowed by ac ion games (55%), ac ion-ad en u e games (38%), ole-
playing games (38%), puzzle games (36%), shoo e games (28%),
s a egy games (26%), and simula ions (25%). O e 77% o he sample
epo ed o be ac i e playe s o ideo games (N=922), o e 19% had
ac i ely played ideo games ea lie in hei li e (N=230), and 3% did
no conside hemsel es o be ac i e playe s o ideo games (N=41).
Rega ding game ypes, single-playe compu e o console games
we e he mos played ype (mean alue 3.6 on a 5-poin scale in which
1=No a all, 5=Ve y much), ollowed by mul i-playe compu e o
console games (mean alue 2.8), single-playe mobile games (mean
alue 2.8), mul iplaye mobile games (1.8), and inally espo s on any
pla o m (mean alue 1.8). Rega ding weekly play ime, 54% o he
esponden s epo ed o play compu e games weekly wi h he a e age
weekly play ime o 6.9 h, 53% epo ed o play console games weekly
wi h he a e age play ime o 6.3 h, and 49% epo ed o weekly play
mobile games wi h he a e age play ime o 4.1 h. In o al, 33% o
he sample epo ed ha hey did no play any ideo games weekly
(N=395), while he a e age play ime ac oss di e en gaming pla o ms
was 11.9 h o he 66% who did epo o play weekly (N=798). Taking
hese desc ip i e s a is ics in conside a ion, he esea ch sample can be
desc ibed o be ep esen a i e om he pe spec i e o a ied gaming
habi s and playe p e e ences al hough he sample was no demog aph-
ically ep esen a i e albei i was collec ed o be balanced be ween
gende s. The da a was analyzed by using S a a 17.1/SE so wa e.
4.3. La en class analysis
We used la en class analysis (LCA) o iden i ying he game expe i-
ence classes o ypes (RQ2). LCA was selec ed o e 𝑘-means clus e ing
as LCA is based on a p obabilis ic and model-based amewo k whe eas
𝑘-means is a dis ance-based algo i hm [46,47]. Since LCA allows o
he es ima ion o p obabili ies o obse a ions belonging o each la en
class, i p o ides a amewo k o a iche unde s anding o he unce -
ain y associa ed wi h class assignmen s han 𝑘-means clus e ing. LCA
is also pa icula ly well-sui ed o analyzing ca ego ical o bina y da a
which co esponds wi h he ype o da a analyzed in his s udy as he
ocused lenses consis ed o a la ge numbe o bina y checklis ques ions.
En e ainmen Compu ing 52 (2025) 100882
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J. Vahlo and K. Tuu i
Table 3
S a is ics o all he 82 i ems included in he LCA in ela ion o he eigh ypes o ideo game expe ience: Compelling Challenge (CHAL), Imme si e Explo ing (IMME), Ene ge ic
Rushing (RUSH), C ea i e Ca ing (CREA), Compe i i e Shoo ing (COMP), Chee ul Bouncing (BOUN), S a egic Managemen (STRA), Daily Dwelling (DWEL).
Type 1 Type 2 Type 3 Type 4 Type 5 Type 6 Type 7 Type 8
CHAL IMME RUSH CREA COMPE BOUN STRA DWEL
N856 840 670 691 637 1006 325 347
Lens 1: Gaming si ua ion
A home 100% ⇑100% ⇑96% ⇓99% 96% ⇓96% ⇓99% 98%
A someone else’s place 13% ⇓12% ⇓34% ⇑19% 28% ⇑16% ⇓10% ⇓51% ⇑
A wo k 0% ⇓1% ⇓1% ⇓4% 3% ↓2% ⇓3% 43% ⇑
A school 0% ⇓1% ⇓2% ↓5% ↑2% 1% ⇓2% 25% ⇑
Ou doo s (e.g. in a pa k) 0% ⇓1% ⇓0% ⇓6% ↑0% ⇓1% ⇓0% ⇓50% ⇑
On a ip o on he way (e.g. o wo k, o school) 0% ⇓4% ⇓1% ⇓12% ⇑0% ⇓2% ⇓2% ⇓74% ⇑
When wai ing (e.g. some hing o happen) 2% ⇓7% ⇓3% ⇓13% ⇈5% ⇓4% ⇓4% ⇓81% ⇑
Lens 2: Gameplay ac i i y ypes
Ba le 51% ⇑49% ⇑19% ⇓6% ⇓87% ⇑25% ⇓42% 38%
Ca e aking and nu u ing 0% ⇓1% ⇓0% ⇓37% ⇑0% ⇓1% ⇓6% 10% ⇈
Cha ac e de elopmen (e.g. de eloping skills o abili ies) 40% ⇑58% ⇑10% ⇓34% ⇈12% ⇓18% ⇓24% ↓26%
Choosing looks and cus omizing appea ances 10% ⇊11% ↓13% 43% ⇑14% 2% ⇓6% ⇓11%
Collec ing o loo ing (e.g. a e i ems, easu es, c ea u es) 34% ⇑38% ⇑5% ⇓30% ↑14% ⇓32% ⇑13% ⇓35% ⇑
Cons uc ion and de elopmen (e.g. ci ies o bases) 3% ⇓3% ⇓1% ⇓35% ⇑1% ⇓0% ⇓45% ⇑7%
Da ing 0% ⇓2% ↑0% ⇓7% ⇑0% ⇊0% ⇓1% 1%
Deco a ing 1% ⇓0% ⇓0% ⇓31% ⇑0% ⇓0% ⇓2% ↓3%
Doing ac oba ics 3% 1% ⇓5% ⇑0% ⇓2% 6% ⇑0% ⇊1% ↓
Exploding o des oying 15% ⇑4% ⇓2% ⇓2% ⇓25% ⇑13% ⇑2% ⇓7%
Explo ing he gamewo ld 50% ⇑71% ⇑4% ⇓28% ⇊9% ⇓33% 14% ⇓22% ⇓
Ga dening 0% ⇓0% ⇓0% ⇓15% ⇑0% ⇓0% ⇓1% 1%
In es iga ing he s o y 36% ⇑59% ⇑1% ⇓4% ⇓3% ⇓11% ⇓2% ⇓14% ↓
Making meaning ul choices 10% 21% ⇑4% ⇓8% ↓4% ⇓9% ⇓26% ⇑14% ↑
Managing and di ec ing (e.g. people o uni s) 1% ⇓1% ⇓2% ⇓5% 2% ⇓1% ⇓44% ⇑5%
Pe o ming in music (e.g. playing ins umen s, dancing) 1% 0% ⇊7% ⇑1% 0% ↓0% ⇓0% ↓1%
Pe o ming in spo s 0% ⇓0% ⇓37% ⇑0% ⇓0% ⇓0% ⇓9% ⇈2% ⇊
P oducing, c a ing o manu ac u ing 3% 1% ⇓0% ⇓17% ⇑1% ⇓0% ⇓8% ⇑5%
Racing 2% ⇓0% ⇓39% ⇑0% ⇓1% ⇓5% ↓0% ⇓3% ⇊
Resou ce managemen 5% ↓1% ⇓2% ⇓12% ⇑2% ⇓1% ⇓41% ⇑11% ⇑
Running o jumping on pla o ms 11% 3% ⇓7% ↓0% ⇓4% ⇓28% ⇑0% ⇓6%
Shoo ing 32% ⇑4% ⇓2% ⇓1% ⇓61% ⇑10% ⇓1% ⇓3% ⇓
Sneaking o hun ing 19% ⇑4% ↓0% ⇓1% ⇓12% ⇑3% ⇓0% ⇓3% ⇊
Sol ing puzzles 12% 19% ⇑3% ⇓3% ⇓1% ⇓27% ⇑5% ⇓38% ⇑
T ading (e.g. i ems, esou ces, weapons) 3% 2% 1% ⇊4% ⇈1% ↓0% ⇓10% ⇑3%
Wa a e 3% ⇓0% ⇓0% ⇓0% ⇑35% ⇑0% ⇓16% ⇑2% ⇊
Lens 3: Game challenge ypes
Ac ing unde a ime p essu e 35% 15% ⇓50% ⇑13% ⇓40% ⇑50% ⇑33% 37%
Dealing wi h us a ion o disappoin men 26% ⇑14% ⇓29% ⇑15% ⇓27% ⇈22% 26% 24%
Diplomacy o nego ia ion 4% ↓15% ⇑0% ⇓4% 0% ⇓2% ⇓22% ⇑2% ⇊
La e al hinking (e.g. c ea i i y o imp o isa ion) 11% ⇓24% ⇑7% ⇓45% ⇑7% ⇓9% ⇓18% 14%
Logical p oblem-sol ing 25% 40% ⇑5% ⇓23% 3% ⇓33% ⇑28% 38% ⇑
Mas e ing complex con ols 21% ⇑9% ↓21% ⇑5% ⇓12% 5% ⇓3% ⇓7% ↓
Mo al o e hical decision-making 9% 26% ⇑0% ⇓12% ⇑1% ⇓1% ⇓6% 1% ⇓
Op imizing ( inding ou he bes solu ion o combina ion) 14% ⇊28% ⇑6% ⇓25% ⇑9% ⇓7% ⇓35% ⇑30% ⇑
Pa ience o pe sis ence 31% ↑28% 17% ⇓48% ⇑11% ⇓28% 18% ⇓33% ↑
P ecision and accu acy 36% ⇑15% ⇓39% ⇑7% ⇓53% ⇑24% 6% ⇓23%
Quick e lexes and as eac ion 53% ⇑22% ⇓53% ⇑3% ⇓60% ⇑38% ↑6% ⇓24% ⇓
S a egy and s a egizing 24% ⇊38% ⇑13% ⇓19% ⇓34% ⇑17% ⇓76% ⇑39% ⇑
S ess ole ance 18% ⇑0% ⇓6% 3% ⇓8% ↑4% ⇊4% 5%
S ong ne es 16% ⇑1% ⇓5% 0% ⇓7% ⇑1% ⇓2% ↓2% ↓
Tac ical decision-making 17% 24% ⇑7% ⇓7% ⇓34% ⇑5% ⇓47% ⇑17%
Teamwo k 5% ⇓6% ⇓14% ⇈5% ⇓37% ⇑3% ⇓7% 8%
Lens 4: Emo ions in gameplay
Amusemen 39% ⇓45% ⇓64% ⇑58% 52% ↓77% ⇑50% ⇊68% ⇑
Annoying 7% ↓3% ⇓13% ⇑3% ⇓18% ⇑8% 16% ⇑13% ↑
Anxie y 27% ⇑4% ⇓14% 2% ⇓20% ⇑4% ⇓20% ⇑13%
Awe 16% ⇑24% ⇑3% ⇓6% ↓2% ⇓1% ⇓2% ⇓5% ↓
Beau y 9% 25% ⇑0% ⇓14% ⇑1% ⇓2% ⇓1% ⇓3% ⇊
Ca e ee 5% ⇓10% ⇓12% ↓46% ⇑7% ⇓20% ⇑4% ⇓19%
Cu iosi y 24% ⇑42% ⇑2% ⇓21% ⇈3% ⇓7% ⇓12% ↓20%
De ian /Bold 21% ⇑4% ⇓3% ⇓2% ⇓11% ⇑1% ⇓12% ⇑3% ⇊
D eaminess 2% ⇓15% ⇑1% ⇓17% ⇑0% ⇓3% ⇓2% ⇊3% ↓
Empa hy 3% 10% ⇑0% ⇓4% ⇈0% ⇓0% ⇓2% 1% ↓
Ene gy 31% ⇑10% ⇓43% ⇑4% ⇓48% ⇑16% ⇓19% 17% ⇊
E o ic/Desi ous 1% ⇈1% ↑0% 1% 0% 0% ⇊0% 0%
Exci emen 61% ⇑42% ⇊58% ⇑16% ⇓70% ⇑36% ⇓49% 44%
Joy ul/Chee ul 9% ⇓20% 26% ⇈35% ⇑16% ⇓25% ⇈14% ⇊28% ⇈
Lo e/A ac ion 1% ↓5% ⇑0% ⇓4% ⇑0% ⇊1% 0% ↓1%
Nos algia 17% ⇓29% ⇈18% ⇓23% 20% ⇊36% ⇑30% ↑26%
Sadness/Melancholy 7% ⇑13% ⇑0% ⇓1% ⇓0% ⇓0% ⇓2% 1% ⇊
(con inued on nex page)
En e ainmen Compu ing 52 (2025) 100882
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J. Vahlo and K. Tuu i
Table 3 (con inued).
Type 1 Type 2 Type 3 Type 4 Type 5 Type 6 Type 7 Type 8
CHAL IMME RUSH CREA COMPE BOUN STRA DWEL
N856 840 670 691 637 1006 325 347
Sca y/Fea 26% ⇑4% ⇊0% ⇓0% ⇓7% 0% ⇓0% ⇓0% ⇓
Se eni y/Calmness 3% ⇓16% ⇑1% ⇓35% ⇑1% ⇓5% ⇓13% 12%
T iumphan /he oic 29% ⇑16% 11% ⇓1% ⇓31% ⇑5% ⇓41% ⇑18%
Lens 5: Mo i a ing game expe ience as a whole
Aes he ic expe iences ha a e app ecia ed in i sel 40% ⇑57% ⇑15% ⇓40% ⇑13% ⇓27% ⇊16% ⇓18% ⇓
Compe i i e expe iences o playing agains o he s 9% ⇓1% ⇓55% ⇑4% ⇓66% ⇑5% ⇓16% 18%
Enjoyable expe iences ha a e en e aining, un and elaxing 30% ⇓49% 50% 66% ⇑34% ⇓58% ⇑44% 54% ↑
Expe iences o accomplishmen and achie emen 55% ⇑37% ⇓39% ⇊35% ⇓36% ⇓38% ⇓69% ⇑59% ⇑
Expe iences o making you own choices and o exp essing you sel 11% ↓27% ⇑4% ⇓34% ⇑5% ⇓3% ⇓17% 10% ↓
Expe iences o o e coming challenges and becoming mo e skill ul 49% ⇑21% ⇓20% ⇓9% ⇓33% ⇈21% ⇓42% ⇑36% ⇑
Expe iences ha ease bo edom and help you kill ime 17% ⇓12% ⇓21% 29% ⇑21% 29% ⇑23% 45% ⇑
Expe iences ha gi e s uc u e and hy hm o you e e yday li e 2% 2% 1% ⇊6% ⇑1% ⇊2% 2% 6% ⇑
Expe iences ha help you o o ge e e yday li e conce ns 18% 21% ⇈10% ⇓22% ⇑16% 14% ⇊14% 19%
Expe iences ha keep you engaged e en ou side gaming si ua ions 6% ⇑5% ⇑2% 1% ⇊3% 0% ⇓5% 3%
Imme si e expe iences o pu ing mysel in he game 32% ⇑38% ⇑6% ⇓8% ⇓12% ⇊3% ⇓14% 7% ⇓
Play ul expe iences o explo ing and disco e ing 24% ⇑41% ⇑4% ⇓18% 3% ⇓13% ⇓10% ⇓19%
Social expe iences o playing and communica ing wi h each o he 5% ⇓3% ⇓12% ⇑5% ⇊26% ⇑3% ⇓10% 7%
Highe alue ↑𝑝 < 0.05,⇈𝑝 < 0.01,⇑𝑝 < 0.001, Lowe alue ↓𝑝 < 0.05,⇊𝑝 < 0.01,⇓𝑝 < 0.001, in compa ison o he mean o o he se en classes (Pea son’s 𝜒2).
Fu he mo e, LCA classes a e mo e obus han 𝑘-means clus e s as he
la e a e based on andomly ini ializing he ini ial clus e cen e and
hen i e a i ely upda ing hem un il con e gence [48,49].
P io o making he clus e ing, he da a was edi ed in o a o m ha
enabled app oaching he game expe ience desc ip ions as he uni o
analysis ins ead o ocusing p ima ily on he su ey pa icipan le el
da a. Thus, we eshaped he da a om a pa icipan -based wide o ma
in o game expe ience based long o ma .
I was manda o y o a pa icipan o name a leas h ee ideo
games and answe o he se en ocused lenses o each o hese games.
Naming he ou h and he i h game and answe ing o hei co e-
sponding lenses was olun a y and su ey pa icipan s did no ecei e
any kind o addi ional compensa ion o naming mo e han h ee
games. A o al o 266 su ey pa icipan s men ioned exac ly h ee ideo
games and eplied o he se o expe ience- ocused ques ions he e o e
also h ice. Six y pa icipan s men ioned ou games, whe eas 866
pa icipan s men ioned he maximum numbe o i e games and also
answe ed he expe ience- ocused ques ions o each o hose games.
Al oge he , he 1,193 su ey pa icipan s men ioned 5,372 ideo games
and esponded co espondingly o he same numbe o he ocused
ques ion s uc u es, making he da a o 5,372 ideo game expe ience
desc ip ions he main da ase o he clus e ing analysis o he s udy. In
o al, 1,605 indi idual game i les we e men ioned in he su ey da a.
Minec a had he mos men ions (n=106), ollowed by FIFA 22 (n=87),
G and The Au o V (n=68), Fo ni e (n=67), and he Sims 4 (n=63).
App oxima ely 57 pe cen o men ioned games we e men ioned only
once.
To iden i y p e alen o ms o ideo game expe ience, we included
he i e game expe ience lenses (lenses om 1 o 5) as clus e ing
in en o ies and conside ed he wo emaining lenses desc ip i e in en-
o ies. The in en o ies applied o iden i ying he clus e s o classes
we e Gaming si ua ion, Gameplay ac i i y ypes, Game challenge ypes,
Emo ions in gameplay, and Game expe ience as a whole. These i e
lenses we e included in he LCA p ocess.
The numbe o classes was iden i ied by combining h ee s a is ical
es s and c i e ia. Fi s , we u ilized he Bayesian In o ma ion C i e ion
(BIC), which is widely u ilized in LCA s udies as i conside s he log-
likelihood and he numbe o pa ame e s, penalizing mo e complex
models [50,51]. Second, we examined sc ee plo s c ea ed om he
wi hin-clus e sum o squa es (WSS) and i s loga i hm [log(𝑊 𝑆𝑆)]
o all possible clus e solu ions anging om 2 o 20 clus e s [52].
The es s suppo ed a solu ion o eigh game expe ience ypes, which
we hen p oceeded o gene a e using an LCA wi h he cloud-based
s a is ical analysis so wa e, DisplayR. As he hi d c i e ion, we applied
an app oach o domain use ulness, he eby accep ing only models in
which all classes had mo e han 6 pe cen o he sample [53]. The
solu ion o eigh game expe ience ypes ul illed his c i e ion. Table 3
epo s he p e alences o each o he 82 bina y clus e ing a iables o
he eigh expe ience ypes and how hese alues di e om he sample
mean in a s a is ically signi ican way.
5. Resul s: The eigh game expe ience classes
In his sec ion, we will analyze he eigh game expe ience classes.
The i s subsec ion ocuses on iden i ying hese classes by analyzing
he a iables included in he La en Class Analysis (LCA) p ocedu e
(Table 3). We will examine how he classes di e om each o he
based on hese a iables, p o iding a s a is ical ounda ion o hei
dis inc ions. In he second subsec ion, we will u he cha ac e ize
hese expe ience classes. This in ol es an in-dep h e iew o addi ional
and auxilia y a iables om he su ey ha we e no included in
he ini ial LCA bu con ibu e o a iche unde s anding o each class
(Table A.7 in Appendix). Addi ionally, we will conduc compa a i e
analyses o classes ha appea mos simila o each o he , highligh ing
sub le nuances and signi ican con as s o be e delinea e hei unique
cha ac e is ics.
5.1. Iden i ying he LCA-based game expe ience classes
Below, we ou line he eigh game expe ience ypes, sugges ing
names o hese expe ience ypes based on a iables included in he
LCA p ocess ha showed bo h absolu ely and ela i ely highes alues
on hem (Table 3). We also iden i ied games cha ac e izing each expe i-
ence ype based on h ee c i e ia: s a is ical p e alence wi hin he ype
in compa ison o he mean o o he se en classes (𝑝 < 0.001), he e-
quency o men ions in he da ase , and he pe cen age ep esen a ion in
he da ase . Fo ins ance, he no a ion ‘‘Elden Ring (n=26, 76%)’’ would
signi y ha Elden Ring had signi ican ly highe p e alence wi hin he
desc ibed game expe ience ype (𝑝 < 0.001), ha i was men ioned 26
imes in he analyzed game expe ience ype, and accoun ed o 76% o
all men ions in he da a.
The i s game expe ience ype consis ed o 856 game expe ience
desc ip ions. This game expe ience ype had no ably mo e sneaking and
hun ing ype o gameplay han he o he ypes. Seen h ough he lens
o game challenges, his game expe ience ype equi ed mo e s ess ol-
e ance and s onge ne es han any o he o he ypes. Highe le els o
de iance, boldness, ea , and anxie y we e he emo ions ha sepa a ed
his game expe ience ype om he o he s, and a he o e all le el
o he game expe ience, his ype was cha ac e ized by o e coming
di icul challenges by becoming mo e skill ul. These expe iences we e
En e ainmen Compu ing 52 (2025) 100882
7
J. Vahlo and K. Tuu i
also imme si e and some hing ha kep playe s engaged wi h hem also
beyond ac ual gaming si ua ions. Fu he mo e, his expe ience ype had
no ably low alues o amusemen , joy, and nos algia as well as o
enjoymen and elaxa ion. The mos no ewo hy games o he his game
expe ience ype we e: Da k Souls (n=9, 100%), The Las o Us (n=26,
87%), Bloodbo ne (n=8, 89%), Elden Ring (n=26, 76%), and Ho izon
Ze o Dawn (n=7, 100%). We name he game expe ience ype Compelling
Challenge.
The second game expe ience ype was based on 840 game expe i-
ence desc ip ions. This expe ience ype was cha ac e ized by gameplay
ac i i ies o cha ac e de elopmen , explo ing he gamewo ld, and
in es iga ing he s o y. F om game challenges, his game expe ience
ype had no ably mo e mo al o e hical decision-making han he o he
ypes. Awe, beau y, cu iosi y, empa hy, lo e, and melancholy we e
emo ions and eelings ha we e associa ed wi h his game expe ience
ype, and he game expe ience as a whole was desc ibed o en as
aes he ic, imme si e, and play ul expe ience o explo ing and disco -
e ing. This expe ience ype had e y low alues o ac ing unde ime
p essu e, dealing wi h us a ion, s ess ole ance, annoyance, and
playing ou o bo edom. The mos p e alen games men ioned in his
expe ience ype we e: The Wi che 3: Wild Hun (n=27, 82%), Final
Fan asy VII (n=19, 76%), Pe sona 5 Royal (n=11, 85%), D agon Age:
Inquisi ion (n=8, 100%), and Mass E ec (n=8, 100%). We call his
ype Imme si e Explo ing.
The hi d game expe ience ype consis ed o 670 game desc ip ions.
This ype di e ed om he o he ypes by i s highe alue o gameplay
ac i i ies o pe o ming in spo s, acing, and pe o ming in music
(e.g., playing ins umen s o dancing). F om he game challenge ypes
i had as high a alue o mas e ing complex con ols as he Compelling
Challenges ype. I had he second highes alue o ene gy as a eeling
o emo ion, and also he second highes alue o he compe i ion as
an expe ience desc ip ion. When compa ed o all expe ience ypes, i
had he lowes alue o i em collec ing o loo ing and gamewo ld
explo a ion, and also ela i ely low alue o logical p oblem-sol ing,
op imizing, s a egy, cu iosi y, calmness, and he escapis game expe-
ience. No ewo hy games in his game expe ience ype we e: Gui a
He o (n=8, 100%), Ma io Ka 64 (n=26, 96%), Rocke League (n=25,
96%), Ma io Ka 8 Deluxe (n=19, 86%), Fall Guys (n=19, 95%), NBA
2K22 (n=14, 93%), and G an Tu ismo (n=12, 92%). We name his
game expe ience ype Ene ge ic Rushing.
The ou h game expe ience class had 691 game men ions. This ex-
pe ience ype had a high alue o he gameplay ac i i ies o nu u ing
and ca e aking, cus omiza ion, deco a ing, and ga dening. I s challenge
ypes equi ed pa ience and pe sis ence and included challenges o c e-
a i i y and imp o isa ion. Se eni y, calmness, ca e ee, and d eaminess
we e associa ed wi h i s gameplay, and i was some hing ha p o ided
aid o e e yday li e conce ns as i ga e a sense o s uc u e and hy hm
o daily li e, and enabled enjoyable and elaxing sel -exp ession. I had
a low alue o ba le, and o he challenge ypes o ac ing unde ime
p essu e, dealing wi h disappoin men , quick e lexes and as eac ion.
I also was less exci ing and he oic as an emo ional expe ience as he
o he classes. On a whole, his expe ience ype was no skill-based
simila ly o o he ypes as i did no ha e di icul challenges. Games
o his class included i les such as: Animal C ossing: New Ho izons
(n=93, 96%), The Sims 4 (n=57, 92%), S a dew Valley (n=50, 91%),
The Sims (n=31, 91%), and Minec a (n=79, 75%). We label his game
expe ience ype C ea i e Ca ing.
Gameplay ac i i y ypes o ba le, exploding and des oying, shoo -
ing, and wa a e all we e clea ly o e - ep esen ed in he i h game
expe ience ype ha had 637 game expe ience desc ip ions. F om he
pe spec i e o game challenges, i was bes desc ibed by eamwo k-
based challenges ha equi e p ecision, accu acy, and as eac ion
ime. In compa ison o he o he game expe ience ypes, hese game
expe iences we e commonly desc ibed as exci ing, ene ge ic, compe -
i i e, and social. The desc ip ions did no include much cha ac e
de elopmen , meaning ul choice-making, puzzle-sol ing, o collec ing
and loo ing. Also pa ience and logical p oblem-sol ing had ela i ely
low alues o his game expe ience ype alongside he eelings o cu-
iosi y, calmness, empa hy, and awe. The mos p e alen games o his
class included: Team Fo ess (n=10, 100%), Call o Du y 4: Mode n
Wa a e (n=43, 86%), O e wa ch (n=37, 82%), League o Legends
(n=19, 73%), and Coun e -S ike: Global O ensi e (n=9, 90%). We call
his game expe ience ype Compe i i e Shoo ing.
The six h game expe ience ype was he la ges wi h 1,006 game
desc ip ions. This class had a high alue o unning and jumping
on pla o ms, ac ing unde ime p essu e, amusemen , and nos algia.
The expe ience ype did no ypically include cha ac e cus omiza ion,
cons uc ion and de elopmen , esou ce managemen , o ading. I
also did no usually include challenges o op imizing, s a egy, o
ac ical decision-making. On he le el o whole game expe ience, his
ype usually did no keep playe s engaged ou side gaming si ua ions.
The mos no able games o his class we e: Sonic he Hedgehog (n=40,
95%), Supe Ma io B os. (n=14, 88%), Supe Ma io Wo ld (n=13,
87%), C ash Bandicoo (n=34, 81%), and Spy o Reigni ed T ilogy (n=9,
100%). We name his clus e Chee ul Bouncing.
The se en h ype o game expe ience was he smalles wi h 325 de-
sc ip ions. I had highe alues han he o he clus e s o cons uc ion
and de elopmen , managing and di ec ing, esou ce managemen , and
ading. S a egy, ac ical decision-making, op imizing, and diplomacy
we e all no able challenge ypes o his class, whe eas he oic and
iumphan eelings we e clea ly associa ed wi h i as an emo ional
expe ience. On he le el o he whole game expe ience, playing games
o his class we e desc ibed as some hing ha el like ue accom-
plishmen and achie emen . This game expe ience ype did no equi e
mas e ing complex con ols, as eac ions, o p ecision and accu acy.
The games ha bes desc ibe his class included: Ci iliza ion V (n=10,
100%), Age o Empi es II (n=8, 100%), RimWo ld (n=9, 90%), Ci i-
liza ion VI (n=12, 92%), and Foo ball Manage 2022 (n=12, 75%). This
game expe ience class was named S a egic Managemen .
The eigh h and inal game expe ience class included 347 game
desc ip ions. I di e ed d as ically om all o he game expe ience
ypes as hese games we e e y commonly played ou doo s, when
wai ing o someone, and a someone else’s place in addi ion o playing
hem a home. F om he gameplay ac i i y ypes his clus e had a
high alue o sol ing puzzles, and he expe ience o playing hese
games was equen ly desc ibed as some hing ha eases bo edom, gi es
s uc u e and hy hm o e e yday li e, and eels like accomplishmen
and achie emen . This inal game expe ience ype included games such
as: Pokémon GO (n=8, 80%), Candy C ush Saga (n=17, 55%), Wo ds
wi h F iends (n=6, 86%), and Candy C ush F iends Saga (n=9, 53%).
We call his game expe ience ype Daily Dwelling, as i emphasizes he
pe meable ela ionships be ween gameplay and e e yday li e.
We can no e om Table 3 ha all i ems included in he LCA had
s a is ically signi ican di e ences be ween he eigh game expe ience
ypes. We can also no e ha some o he i ems we e p e alen o all
o he game expe ience ypes whe eas o he s we e nea non-exis ing.
Fo ins ance, playing a home had a alue o e 95% o e e y class
which indica es ha is a e y common p ac ice o play all kinds o
ideo games a home. I can also be summa ized ha emo ions such
as amusemen and exci emen and expe iences ha can be desc ibed
as enjoyable and en e aining and illed wi h accomplishmen and
achie emen a e equen o all kinds o gaming. Simila ly should
be obse ed ha eeling e o ic and desi ous eelings a e e y a e o
games ha playe s alue, o a leas ha hese eelings a e no among
he op cha ac e is ics ha make a game g a i ying and enjoyable o
playe s.
5.2. Fu he desc ip ions he game expe ience classes
Abo e we ha e iden i ied he eigh game expe ience classes based
on he a iables and ocused lenses included in he LCA p ocedu e. In
his subsec ion, we will p o ide addi ional desc ip ions o he classes
En e ainmen Compu ing 52 (2025) 100882
8
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