Ohlms, Ma ie Luise; Melche s, Klaus G.
A icle — Published Ve sion
A e Games Always Fun and Fai ? A Compa ison o
Reac ions o Di e en Game‐Based Assessmen s
In e na ional Jou nal o Selec ion and Assessmen
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John Wiley & Sons
Sugges ed Ci a ion: Ohlms, Ma ie Luise; Melche s, Klaus G. (2025) : A e Games Always Fun and Fai ?
A Compa ison o Reac ions o Di e en Game‐Based Assessmen s, In e na ional Jou nal o Selec ion
and Assessmen , ISSN 1468-2389, Wiley, Hoboken, NJ, Vol. 33, Iss. 1,
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In e na ional Jou nal o Selec ion and Assessmen
RESEARCH ARTICLE
A e Games Always Fun and Fai ? A Compa ison o
Reac ions o Di e en Game‐Based Assessmen s
Ma ie Luise Ohlms
1,2
| Klaus G. Melche s
1
1
Depa men o Wo k and O ganiza ional Psychology, Ins i u ü Psychologie und Pädagogik, Uni e si ä Ulm, Ulm, Ge many |
2
Depa men o Wo k and
O ganiza ional Psychology, Ins i u ü Psychologie, Albe ‐Ludwigs‐Uni e si ä F eibu g, F eibu g, Ge many
Co espondence: Ma ie Luise Ohlms ([email p o ec ed])
Recei ed: 27 Augus 2024 | Re ised: 19 Decembe 2024 | Accep ed: 6 Janua y 2025
Funding: The esea ch was suppo ed by a doc o al schola ship o he S udiens i ung des deu schen Volkes o he i s au ho .
Keywo ds: applican eac ions | game | game‐based assessmen | gami ica ion | indi idual di e ences | pe sonnel selec ion
ABSTRACT
Game‐based assessmen (GBA) has ga ne ed a en ion in he pe sonnel selec ion and assessmen con ex owing o i s pos ula ed
po en ial o imp o e applican eac ions. Howe e , GBAs can di e conside ably depending on hei speci ic design. The e o e,
we sough o de e mine whe he es ake eac ions o GBAs a y owing o he di e en mani es a ions ha GBAs may ake on,
and o es ake s' indi idual p e e ences o such assessmen s. In an expe imen al s udy, each o N= 147 pa icipan s was
shown six di e en GBAs and asked o a e se e al applican eac ion a iables conce ning hese assessmen s. We ound ha
eac ions o GBAs we e no inhe en ly posi i e e en hough GBAs we e gene ally pe cei ed as enjoyable. Howe e , pe cep ions
o ai ness and o ganiza ional a ac i eness a ied conside ably be ween GBAs. Pa icipan s' age and expe ience wi h ideo
games we e ela ed o eac ions bu had less impac han he di e en GBAs. Ou esul s sugges ha a echnology‐as‐designed
app oach, which conside s GBAs as a combina ion o mul iple componen s (e.g., game elemen s), is c ucial in GBA esea ch o
p o ide gene alizable esul s o heo y and p ac ice.
1 | In oduc ion
Comme cial ideo games ha e gained emendous popula i y
o e he pas decades, as hey o e playe s enjoymen , men al
s imula ion, and s ess elie , among o he bene i s (ESA 2022).
The in oduc ion o games in o nongame con ex s (De e ding
e al. 2011) has been an a emp o exploi he ad an ages o
ideo games o qui e some ime (e.g., Qian and Cla k 2016).
Acco dingly, his end has also ound i s way in o he pe -
sonnel selec ion and assessmen con ex whe e i is e e ed o
as game‐based assessmen (Lande s and Sanchez 2022).
One eason o he use o game‐based assessmen (GBA) is he
di icul y in a ac ing highly quali ied p o essionals o join an
o ganiza ion, which has become an inc easingly challenging
ask o many o ganiza ions amid he p e ailing skills sho age
(B unello and W uuck 2021). In ligh o his di icul y, GBA is
sugges ed as a way o suppo ec ui men and selec ion by
p o iding bo h a posi i e candida e expe ience and a alid
measu emen o applican s' ele an knowledge, skills, abili ies,
and o he a ibu es (KSAOs, Bha ia and Ryan 2018). Gi en
hei engaging and gami ied na u e (De e ding e al. 2011), a
possible ad an age o GBAs claimed in he li e a u e (e.g.,
Bha ia and Ryan 2018) is hei po en ial o e oke mo e posi i e
applican eac ions compa ed o adi ional alid assessmen
me hods. Howe e , GBAs can di e emendously, as hei
design o e s lexibili y owing o he a ie y o game elemen s,
1
such as s o ylines, le els, badges, a a a s, and gen es ha can
be chosen (Fe ze , McNama a, and Geime 2017; Ohlms 2024).
As a consequence o he conside able a iabili y in GBA
designs, wo ele an ques ions a ise: The i s is whe he
This is an open access a icle unde he e ms o he C ea i e Commons A ibu ion License, which pe mi s use, dis ibu ion and ep oduc ion in any medium, p o ided he o iginal wo k is p ope ly
ci ed.
© 2025 The Au ho (s). In e na ional Jou nal o Selec ion and Assessmen published by John Wiley & Sons L d.
1o 16In e na ional Jou nal o Selec ion and Assessmen , 2025; 33:e12520
h ps://doi.o g/10.1111/ijsa.12520
applican eac ions o a speci ic GBA a e compa able o
eac ions o ano he GBA? Second, one can ask whe he ce ain
indi iduals a e mo e o less likely o eac posi i ely o GBAs,
ha is, whe he he e a e indi idual cha ac e is ics associa ed
wi h eac ions o GBAs?
P e ious s udies o GBAs ha e been unable o answe hese
ques ions because hey ha e usually ollowed a echnology‐as‐
causal (i.e., ea ing GBAs as a single en i y) o a echnology‐
as‐ins umen al pa adigm (i.e., ea ing GBAs as a single en i y
bu conside ing po en ial in e ac ing e ec s wi h o he exo-
genous a iables, Lande s and Ma in 2021). These s udies
compa ed a gi en GBA o i s adi ional coun e pa (e.g.,
Lande s e al. 2022; Ohlms, Melche s, and Kanning 2024a),
some imes conside ing po en ial mode a o s o media o s
(e.g., Gko ezis e al. 2021), bu did no compa e di e en
GBAs. Gi en ha p e ious esea ch has yielded mixed esul s
ega ding applican eac ions o GBAs (e.g., Lande s e al.
2022; Ohlms, Melche s, and Kanning 2024a), he ques ion
a ises as o whe he a echnology‐as‐designed pe spec i e
(Lande s and Ma in 2021),whichdecomposesGBAsin o hei
speci ic design ea u es and examines hei in luence on ou -
comes while conside ing o he po en ially in luen ial exogen-
ous a iables, would be mo e app op ia e. Thus, om a
heo e ical pe spec i e, i is impo an o compa e he same
indi iduals' eac ions o di e en GBAs o see whe he
eac ions o GBAs a e simila ac oss di e en GBAs, sugges -
ing a echnology‐as‐causal pe spec i e, o whe he hey a y
ac oss di e en GBAs, sugges ing a echnology‐as‐designed
pe spec i e.
F om an applied pe spec i e, i would also be use ul o know
whe he applican eac ions a e always a ec ed in he same way
independen o he used GBA and whe he applican s' pe sonal
cha ac e is ics a e addi ionally associa ed wi h hei eac ions o
GBAs. Such knowledge would enable o ganiza ions o make
in o med decisions abou whe he and wha ype o GBAs o
employ o p omo e posi i e applican eac ions.
To add ess hese gaps, and ollowing he call om a ecen
e iew by Ramos‐Villag asa, Fe nández‐Del‐Río and Cas o
(2022) o in es iga e ac o s ha impac applican eac ions o
GBAs, he p esen s udy ep esen s a i s s ep and employed a
wi hin‐subjec s design o di ec ly compa e a ious es ake
eac ions o six a he di e en GBAs. Addi ionally, we aimed o
examine how indi idual cha ac e is ics o po en ial applican s
ela e o hei eac ions o GBAs, building on Lande s and
Sanchez's (2022) p oposed ex ension o Hausknech , Day, and
Thomas's (2004) applican eac ion model. Finally, gi en exis -
ing e idence o gende and age di e ences in p e e ences o
comme cial ideo games (ESA 2019,2022), we aimed o
in es iga e whe he hese di e ences also exis in he con ex o
GBAs. Hence, he p esen s udy p o ides insigh s o GBA
esea ch and p ac ice by de e mining whe he es ake s eac
di e en ly o di e en GBAs. This would allow a es whe he a
echnology‐as‐causal o a echnology‐as‐designed pe spec i e is
mo e app op ia e when s udying GBAs, hus p o iding impo -
an a enues o u u e GBA esea ch.
2 | Game‐Based Assessmen and Game Elemen s
GBA e e s o he use o ( ideo‐)games as pe sonnel selec ion
ins umen s o measu e applican s' ele an KSAOs o a ce ain
posi ion (Lande s and Sanchez 2022). GBA se es as a s and‐
alone me hod, aiming o pu applican s in o a psychological
s a e o game ul expe ience (Lande s and Sanchez 2022). GBAs
a e designed h ough game de elopmen , which, owing o hei
o en complex, sophis ica ed, and mul imodal na u e, ypically
in ol es highe cos s han he de elopmen o mo e adi ional
assessmen me hods (Bha ia and Ryan 2018; Lande s and
Sanchez 2022). When c a ing such play ul assessmen s, one
can gene ally make use o any game elemen o any combina-
ion o di e en elemen s ha a e employed in comme cial
games such as leade boa ds (i.e., an indica ion abou how well
one pe o ms compa ed o o he s), poin s (i.e., ewa ds awa ded
o he success ul comple ion o speci ic asks o he accom-
plishmen o p ede ined a ge s), and/o a na a i e (i.e., he
s o yline o he game) o name jus a ew. In addi ion o a ious
game elemen s, he sphe e o game gen es also o e s ample
eedom in GBA de elopmen . A gen e ep esen s a way o
ca ego ize games based on hei game elemen s, s uc u e,
challenge, and in e ac i i y (Fe ze , McNama a, and Geime
2017). Despi e a ple ho a o di e en game gen e classi ica-
ions ha has eme ged o ca ego ize games o en e ainmen
pu poses (e.g., King and K zywinska 2002;Rollingsand
Adams 2003), in he pe sonnel selec ion con ex , six game
gen es a e p edominan ly used: ac ion, simula ion, ole‐
playing, ad en u e, mini‐game, and s a egy (see Table 1in
Fe ze , McNama a, and Geime 2017, o a de ini ion o he
GBA gen es).
The combina ion o di e en game cha ac e is ics (e.g., game
elemen s, game ic ion) ha de ine a game and con ibu e o
a play ul expe ience as well as o o he desi ed ou comes
(e.g., inc eased mo i a ion) is de ined di e en ly ac oss game
axonomies which a e p ima ily de e mined by a ia ions
in hei in ended ou comes (Lande s e al. 2018). Ye , game
axonomies speci ic o he pe sonnel selec ion and assess-
men con ex a e sca ce, wi h one excep ion being he p o-
posed GBA axonomy by Hawkes, Cek and Handle (2017).
This axonomy aims o ca ego ize GBAs based on se en
ca ego ies. These ca ego ies a e (1) ideli y (i.e., he deg ee o
Summa y
•This s udy examines whe he people a y in hei
eac ions o di e en game‐based assessmen s (GBAs),
explo ing compa abili y among hem.
•Resul s sugges ha po en ial applican s' eac ions can
di e conside ably ac oss di e en GBAs.
•Pa icipan s' age co ela ed nega i ely wi h eac ions o
GBAs, while expe ience wi h ideo games was posi i ely
associa ed wi h eac ions.
•Depending on hei age po en ial applican s di e ed in
hei p e e ences o ce ain GBAs.
•Va ying applican eac ions ac oss di e en GBAs s ess
he need o a hough ul choice o GBAs o pe sonnel
selec ion.
2o 16 In e na ional Jou nal o Selec ion and Assessmen , 2025
eedom when playing he GBA), (2) con lic ing demands
(i.e., he ex en o which a playe is con on ed wi h mul iple
demands simul aneously), (3) a iable pa h (i.e., he ex en o
which game p og ession is a ec ed by ac ions aken du ing
he GBA), (4) engagemen (i.e., he ex en o which he GBA
has elemen s ha use s ind enjoyable o ha p omo e
imme sion), (5) suspense ulness (i.e., he ex en o which a
desi ed ou come is likely o occu and how i can be in lu-
enced by he use 's ac ions), (6) game ulness (i.e., he ex en
o which he assessmen has elemen s and in e ac i i y yp-
ical o a game), and (7) ideli y (i.e., he ex en o which a
game is eali y‐based and job‐ ela ed). Thus, o example, one
could apply Hawkes e al.'s axonomy o a ligh simula o
GBA used o he selec ion o pilo s. Following he axonomy,
one would a e such a GBA high on all dimensions excep o
game ulness, as a ligh simula o ypically does no con ain
con en ional game elemen s (see also Hawkes, Cek, and
Handle 2017).
2.1 | Applican Reac ions o Game‐Based
Assessmen s
Gi en he highe de elopmen cos s and p og amming com-
plexi y o GBAs compa ed o adi ional selec ion me hods
(Lande s and Sanchez 2022), one migh ques ion why o gani-
za ions should incu hese expenses o in eg a e GBAs in o hei
selec ion p ocesses. Howe e , he e a e se e al bene i s o GBAs
ha a e pos ula ed in he li e a u e (e.g., Bha ia and Ryan 2018)
and by GBA endo s.
The main ad an age o his play ul me hod is claimed o lie
in imp o emen s o applican eac ions and candida e a -
ge ing h ough he en e aining and play ul na u e o hese
assessmen s (Bha ia and Ryan 2018). Wi h many o ganiza-
ions ha a e cu en ly s uggling o ind sui able alen o
join hei wo k o ce (B unello and W uuck 2021), hopes a e
high ha GBAs can imp o e he candida e expe ience, and
hus p o ide a s a egic ad an age as applican s' pe cep ions
o assessmen p ocedu es a e linked o hei a i udes o
he o ganiza ion and also o hei job o e accep ance
in en ions.
To examine whe he GBAs do indeed ha e he hoped‐ o
posi i e e ec s on applican eac ions compa ed o hei
adi ional coun e pa s and o o e gene alizable implica-
ions o GBA esea ch, esea che s mus be clea abou he
pa adigma ic app oach hey a e using o s udy GBAs, and
which app oach is app op ia e o s udy his echnology‐based
selec ion me hod
2
(Lande s and Ma in 2021). Looking a he
ini ial s udies ha ha e examined applican eac ions o
GBAs, i becomes clea ha hese s udies ha e ended o
adop a echnology‐as‐causal (e.g., Ohlms e al. 2024)o
echnology as‐ins umen al app oach (e.g., Gko ezis e al.
2021; Ohlms, Melche s, and Kanning 2024a). Acco ding o
Lande s and Ma in, in a echnology‐as‐causal app oach, e-
sea che s examine he impac o a echnology (e.g., a GBA)
on an ou come o in e es (e.g., applican eac ions). Thus, in
such a echnology‐as‐causal pa adigma ic app oach, GBAs
a e ea ed as a single en i y wi hou ega d o po en ial di -
e ences in hei design. In a echnology‐as‐ins umen al
app oach, GBAs would s ill be conside ed as a uni o m en-
i y, bu his app oach conside s po en ial in e ac ing e ec s
wi h o he exogenous a iables (e.g., applican eac ions o
GBAs di e based on es ake s' ideo game expe ience,
Lande s and Ma in 2021).
Howe e , using a echnology‐as‐causal o echnology‐as‐
ins umen al app oach o examine he e ec s o GBAs on
ele an pe sonnel selec ion ou comes (e.g., applican
eac ions, alidi y, eliabili y) may comp omise he ex e nal
alidi y o such esea ch. This is because, as men ioned
abo e, GBAs can a y conside ably ega ding hei design
(i.e., game elemen s o game gen e) as well as he cons uc
(s) hey in end o measu e (Fe ze , McNama a, and Geime
2017). Gi en he di e se na u e o GBAs, ha dly any wo
GBAs a e alike. Consequen ly, i seems unlikely ha
eac ions o a speci ic GBA a e compa able o hose o
ano he GBA. Mo eo e , he use o a GBA may no inhe -
en ly esul in applican s pe cei ing he selec ion p ocess as
mo e enjoyable, en e aining, and ai compa ed o adi-
ional me hods. In ac , he a o able ou comes o applican
eac ions o a GBA a e likely dependen on an e ec i e
game de elopmen (Lande s and Sanchez 2022). Agains
his backg ound, i may be a gued ha a echnology‐
as‐designed app oach may be mo e app op ia e when
TABLE 1 | Game‐based assessmen gen es.
Gen e Desc ip ion
GBA used in he p esen
s udy
Ac ion Games demanding apid and p ecise playe eac ions o asks o s imuli US Ai Fo ce: Ai man Challenge
Simula ion Games ha emula e scena ios and asks o a (semi‐) ealis ic i ual
en i onmen
ReQiu: Wo kday simula ion
Role‐playing Games in which playe s command he ac ions o one o mo e cha ac e s
and pe o m asks on hei behal
LTP: Building Docks
Ad en u e Games in which playe s emba k on a ( i ual) ad en u e in which hey
ace challenges and in e ac wi h a a a s and/o objec s
Ohlms e al. (2024):
Minec a game
Mini‐game Games o sho du a ion, which can usually be sol ed wi hin 10 min and
a e ypically simple in hei objec i es
C i e ia Co p: Cogni y; Lande s
e al. (2022)
S a egy Games equi ing s a egic planning and p oblem‐sol ing skills o
accomplish speci ic asks in a i ual en i onmen
McKinsey Sol e: Ecosys em
C ea ion
3o 16
examining he e ec s o GBAs and aiming o d aw sound
conclusions o GBA esea ch and p ac ice.
So a , esea ch has no ye cla i ied which pa adigma ic
app oach is mo e app op ia e o s udying GBAs. I a
echnology‐as‐causal o echnology‐as‐ins umen al app oach is
su icien o in es iga ing GBAs, hen applican eac ions o
di e en GBAs should yield consis en esul s. This would allow
GBAs o be ea ed as a single en i y ha always p oduces
ce ain e ec s on ele an ou comes (i.e., applican eac ions)
and o gene alize om he esul s o one GBA o hose o
ano he . Howe e , i applican eac ions di e om GBA o
GBA, his would a gue o a echnology‐as‐designed app oach.
Tha is, looking a he e ec s o a GBA as a whole on applican
eac ions would be o limi ed alue and con ibu e li le o
heo y and p ac ice beyond a speci ic GBA.
To de e mine whe he applican eac ions o di e en GBAs a e
he same o di e en , i is necessa y o ha e pa icipan s e al-
ua e mul iple GBAs. Howe e , p e ious s udies ha e only ex-
amined a single GBA a a ime. Ne e heless, hese ini ial
s udies o es ake s' eac ions o GBAs a leas indi ec ly
suppo he no ion ha eac ions may di e be ween di e en
GBAs. Fo ins ance, Lande s e al. (2022) ound mo e posi i e
eac ions o he GBA Cogni y, which comp ises se e al mini‐
games, compa ed o a pape ‐pencil es measu ing simila
abili ies. Con e sely, Ohlms, Melche s and Kanning (2024a)
epo ed mo e nega i e eac ions o a GBA implemen ed in he
Minec a de elopmen en i onmen and ca ego ized in he
ad en u e gen e, compa ed o i s adi ional coun e pa . Sim-
ila ly, adding game elemen s o o he wise non‐gami ied es s
led o mo e posi i e eac ions in some s udies (e.g., Geo giou
and Nikolaou 2020) bu no in o he s (e.g., Ohlms e al. 2024).
These indings sugges ha a echnology‐as designed app oach
o s udying GBAs would be mos app op ia e.
Fu he mo e, Gilliland (1993) heo e ical model on applican
eac ions, as well as i s ex ensions by Hausknech , Day and
Thomas (2004) and Lande s and Sanchez (2022), may also
help o explain which pa adigma ic app oach may be
app op ia e o s udying GBAs. Speci ically, Hausknech
e al. posi a ious de e minan s (e.g., job o pe son cha -
ac e is ics) ha may a ec applican eac ions o he selec ion
p ocess (e.g., p ocedu al jus ice pe cep ions o es anxie y),
which, in u n, a e assumed o esul in indi idual and
o ganiza ional ou comes such as he pe cei ed o ganiza ional
a ac i eness o applican s' job o e accep ance in en ions.
Addi ionally, Hausknech e al.'s model sugges s se e al
mode a o s ha may in luence hese ela ionships.
In he con ex o GBAs, Lande s and Sanchez (2022)p oposed
an ex ension o Hausknech , Day, and Thomas's (2004)model
by adding game elemen s and game‐ ela ed mode a o s.
Speci ically, Lande s and Sanchez in oduced game elemen s
such as leade boa ds o s o ylines as an eceden s ha a e
in ended o in luence pe cei ed p ocedu al cha ac e is ics
(e.g., jus ice ules, i.e., aspec s ha a ec he pe cei ed ai -
ness o he selec ion p ocess and decision, such as he pe -
cei ed job‐ ela edness o applican s' oppo uni y o pe o m),
which, in u n, should in luence applican pe cep ions (e.g.,
pe cei ed ai ness) and ela ed ou comes (e.g., a i udes
owa d he o ganiza ion). Fu he mo e, in he con ex o
GBAs, Lande s and Sanchez ex ended Hausknech e al.'s
model by a se ies o game‐ ela edmode a o ssuchas he
e ec i eness o he GBA design. Thus, he ex ended model
explains how indi idual game elemen s and hei e ec i e
in eg a ion may in luence applican s' pe cep ions o he jus-
ice ules. Fo ins ance, applican s migh pe cei e a GBA
in which hey ha e o manage a ic ional o ganiza ion (e.g.,
Melche s and Basch 2022) as mo e job‐ ela ed han a adi-
ional cogni i e abili y es ha equi es hem o sol e
ma ices. Howe e , he opposi e migh be he case when
applican s ha e o comple e a GBA in which hey ha e o
sa e a cu sed coun y (e.g., Ohlms, Melche s, and Kanning
2024a). The e o e, i is easonable o assume ha applican
eac ions di e depending on he pa icula GBA.
As a gued abo e, o d aw meaning ul and gene alizable
conclusions o GBA esea ch and p ac ice, i is necessa y o
de e mine whe he a echnology‐as‐causal/ echnology‐as‐
ins umen al o a echnology‐as‐design app oach should be
aken o s udy GBAs, as his has undamen al implica ions
o s udy designs and esea ch di ec ions. To answe his
ques ion, we will compa e applican eac ions o di e en
GBAs and o examine he ollowing esea ch ques ion:
Resea ch Ques ion 1 (RQ 1). Does he speci ic GBA
in luence applican s' eac ions owa d i ?
3
2.2 | Indi idual Di e ences and Applican
Reac ions o Game‐Based Assessmen s
No only migh he GBA ype in luence applican eac ions, bu
also indi idual di e ences in p e e ences o games. Lande s
and Sanchez's (2022) ex ended applican eac ions model
in oduced he idea ha applican s' skills and p io expe ience
wi h game elemen s ac as game‐ ela ed mode a o s o in lu-
ence hei eac ions o GBAs. Thus, indi iduals who ha e mo e
expe ience wi h ideo games and echnical sys ems (e.g., com-
pu e s) migh ha e a highe compu e sel ‐e icacy in dealing
wi h compu e ‐based games and migh eac mo e posi i ely o
compu e ‐based GBAs, because hey a e al eady amilia wi h
games om hei leisu e ime. In line wi h his, p e ious
esea ch ound ha echnology sel ‐e icacy and ideo game
expe ience we e posi i ely associa ed wi h es ake s' eac ions
o GBAs (Ellison e al. 2020; Gko ezis e al. 2021; Ohlms,
Melche s, and Kanning 2024a). Likewise, s udies examining
applican eac ions o echnology‐based selec ion ins umen s
in gene al ound ha expe ience wi h compu e s we e associ-
a ed posi i ely wi h applican eac ions o echnology‐based
selec ion p ocedu es (Wiechmann and Ryan 2003). In addi ion,
compu e sel ‐e icacy appea s o ha e a posi i e associa ion
wi h he pe cei ed ease o use o digi al sys ems (e.g., Oos om
e al. 2013). Thus, we hypo hesize:
Hypo hesis 1. Video game expe ience is posi i ely associa ed
wi h applican eac ions o GBAs.
Hypo hesis 2. Compu e sel ‐e icacy is posi i ely associa ed
wi h applican eac ions o GBAs.
4o 16 In e na ional Jou nal o Selec ion and Assessmen , 2025
Assuming ha ideo game expe ience and compu e sel ‐
e icacy in luence eac ions o GBAs, i seems ele an o con-
side how hese explana o y a iables a e ela ed o gende and
age. Fo comme cial ideo games, di e ences in p e e ences o
ideo games in gene al, as well as o ce ain ypes o games in
pa icula , we e ound based on gende and age. Speci ically,
women gene ally end o spend less ime playing games and
demons a e lowe mo i a ion owa d gaming ac i i ies (e.g.,
González‐González e al. 2022; Ha mann and Klimm 2006;Lucas
and She y 2004). Mo eo e , he e a e gende di e ences in p e -
e ences o di e en game gen es and elemen s (e.g., Lucas and
She y 2004) so ha men engage mo e wi h shoo e , spo s, and
ac ion games han women do, who ins ead end o play mo e
casualgameslikepuzzleandca dgames handomen(ESA2019).
Resea ch u he indica es ha women pa icula ly end o ejec
agg essi e and iolen con en , sexualized po ayals o emale
cha ac e s in ideo games as well as a lack o social in e ac ion
(e.g., wi h a a a s, Ha mann and Klimm 2006). Addi ionally,
women a e less a ac ed o compe i i e game elemen s in ideo
games han men a e (Ha mann and Klimm 2006). Ini ial s udies
in he con ex o GBAs also indica ed ha applican eac ions o
GBAs a y based on applican s' gende . Hence, women end o
eac less posi i ely o GBAs compa ed o men (Ellison e al. 2020;
Ohlms, Melche s, and Kanning 2024a).
In e ms o age, i may be assumed ha es ake s' age may be
ela ed o mo e nega i e eac ions o GBAs owing o lowe
compu e sel ‐e icacy and less ideo game expe ience among
olde indi iduals (Reed, Do y, and May 2005; Williams, Yee, and
Caplan 2008). Rega ding comme cial ideo games, a ep esen -
a i e su ey by he En e ainmen So wa e Associa ion (ESA
2022) e ealed ha he majo i y o playe s (60%) a e below he
age o 35. Con e sely, only 9% a e be ween 55 and 64 yea s old,
and a me e 4% a e olde han 65 yea s, sugges ing ha olde
people gene ally enjoy ideo games less han younge in-
di iduals. Fu he mo e, age is associa ed wi h game gen e p e -
e ences, wi h indi iduals aged 18 o 34 ending o p e e ac ion,
shoo e , and puzzle games, while hose o e 65 yea s ending o
p e e puzzle as well as skill and chance games (ESA 2022).
Based on he desc ibed indings, we aim o examine he
ollowing hypo heses:
Hypo hesis 3. Men show mo e posi i e eac ions o GBAs
han women.
Hypo hesis 4. Age is nega i ely associa ed wi h applican
eac ions o GBAs.
Hypo hesis 5. GBA ype mode a es (a) he ela ionship
be ween gende and applican eac ions and (b) he ela ionship
be ween age and applican eac ions.
3 | Me hods
3.1 | S imulus Ma e ial
The selec ion o he six di e en GBAs ha pa icipan s had o
e alua e wi hin he s udy was based on a comp ehensi e sea ch
o GBAs de eloped o bo h comme cial and esea ch pu poses.
To iden i y hese GBAs, we conduc ed an ex ensi e sea ch
ac oss mul iple sou ces. Speci ically, we conduc ed an online
sea ch o iden i y comme cially a ailable GBAs, such as hose
o e ed by assessmen p o ide s (e.g., C i e ia Co p, Aon). In
addi ion o comme cial and publicly a ailable GBAs, we e iewed
he scien i ic li e a u e on gami ica ion and GBAs o u he
iden i y GBAs de eloped o esea ch pu poses. This sea ch led o
he iden i ica ion o 78 di e en play ul assessmen s (when a
ce ain assessmen consis ed o se e al mini‐games/subgames hey
we ecoun edasmul iplesepa a eGBAs,e.g., hesixmini‐games
o he GBA Cogni iy [www.c i e iaco p.com]we econside edas
indi idual GBAs). To iden i y po en ial di e ences be ween he
play ul assessmen s ound du ing ou sea ch, all assessmen s we e
coded by wo independen code s (a Mas e le el and a PhD s u-
den specializing in wo k and o ganiza ional psychology) based on
wo c i e ia. On he one hand, he code s assessed which game
gen e a pa icula p ocedu e could be assigned o. The ca ego i-
za ion o gen e was based on Fe ze e al.'s (2017) classi ica ion,
hus he play ul p ocedu es could be assigned o one o six di -
e en gen es (ac ion, ad en u e, ole‐playing, simula ion, s a egy,
mini‐game). On he o he hand, o u he classi y he di e ences
be ween iden i ied p ocedu esbeyondgen e,weusedHawkes
e al.'s (2017) axonomy o GBAs. As men ioned abo e, his ax-
onomy comp ises se en cha ac e is ics ha can be used o ca e-
go ize play ul p ocedu es. Fo example, acco ding o Hawkes
e al.'s axonomy, a GBA in which es ake s can mo e eely in a
i ual game en i onmen using he con ol keys would be a ed
high on he dimension eedom o ac ion. In con as , a mul iple‐
choice ques ionnai e would ep esen a low le el on his dimen-
sion. To e eal ine di e ences be ween GBAs, we used a 5‐poin
scale om 1 = low le el (wi h a speci ic example o a low le el o
each dimension) o 5 = high le el (wi h a speci ic example o a low
le el o each dimension).
Based on he gen e classi ica ions and a ings, we selec ed six
di e en GBAs o ou s udy. When choosing he GBAs, we
aimed o selec p ocedu es ha di e ed in e ms o bo h hei
gen es and hei classi ica ion acco ding o Hawkes e al.'s (2017)
axonomy. Thus, om each o he six gen es we picked one GBA,
which u he di e ed in e ms o Hawkes e al.'s classi ica ion
(see Table 2 o he coding acco ding o gen e and Hawkes e al.'s
axonomy). The aim was o b ing oge he a di e se ange o
GBAs o ou s udy. These GBAs (see below o mo e in o ma-
ion) we e he (1) Ai man Challenge, (2) Wo kday simula ion,
(3) Building Docks, (4) Minec a game, (5) G id Lock, and (6)
McKinsey's Ecosys em C ea ion. Fo each o he GBAs, we w o e
a ex ‐based desc ip ion wi h he goal, s o yline, indi idual asks,
game elemen s, and basic ules o he game. In addi ion, an
exce p o each game was shown in sho (app ox. 2‐min) ideos
o gi e pa icipan s a ealis ic imp ession o he game. These
ideos we e edi ed om open‐access sou ces (e.g., YouTube o
companies' websi e) and accompanied by a sel ‐ eco ded audio
sequence ha explained he GBA's unique ea u es in de ail.
3.1.1 | Ai man Challenge
The ai man challenge alls unde he ac ion gen e and is used by
he US Ai Fo ce (h ps://www.ai o ce.com/ai manchallenge/)
5o 16
as pa o hei ec ui men p ocess. In he ai man challenge,
applican s ha e o comple e a ious missions a ound he wo ld,
aking on di e en oles wi hin a ious ai o ce job p o iles. The
goal o he game is o success ully comple e as many missions as
possible o gain anks, badges, and achie emen s. Wi hin each
mission, se e al asks ha e o be sol ed. The eby, playe s ha e o
slip in o di e en ai o ce job p o iles and mas e hei indi-
idual asks.
3.1.2 | Wo kday Simula ion
The Wo kday simula ion, de eloped by ReQiu (h ps:// eqiu.
eu) belongs o he simula ion gen e, simula ing a ial day
wi hin he company ReQiu, du ing which es ake s encoun e
a ious wo k‐ ela ed challenges. These asks ha e o be com-
ple ed and sol ed wi hin a simula ed o ice. Fo ins ance, one
ask in ol es scheduling wo kdays wi h he goal o scheduling
as many wo kdays as possible.
3.1.3 | Building Docks
Building Docks is ca ego ized wi hin he ole‐playing gen e.
Applican s ake on he ole o a po owne and oge he wi h
h ee o he (compu e ‐con olled) cha ac e s ha e o u n a
newly opened po p o i able wi hin a yea . In doing so, hey
ha e o nego ia e wi h a ious s akeholde s (see Ba ends, De
V ies, and Van Vug 2022, o a comp ehensi e desc ip ion).
3.1.4 | Minec a Game
The Minec a game, de eloped by Ohlms, Melche s and
Kanning (2024a), is om he ad en u e gen e. In his GBA,
applican s ha e o escue a cu sed coun y by comple ing a -
ious cogni i e asks, such as sol ing ma ices (see Ohlms,
Melche s, and Kanning 2024a, o de ails).
3.1.5 | G id Lock
G id Lock is one o se e al mini‐games om he GBA Cogni y,
de eloped by C i e ia Co p (h ps://www.c i e iaco p.com).
In G id Lock, applican s ha e o inse a ious puzzle pieces
in o a gi en shape as quickly as possible (see Lande s e al.
2022, o a comp ehensi e desc ip ion).
3.1.6 | Ecosys em C ea ion
McKinsey's Ecosys em C ea ion game, called Sol e (h ps://
www.mckinsey.com), ep esen s a s a egy game. The goal o
his GBA is o build a sus ainable ecosys em in a co al ee . The
main ask is o es ablish a ood chain wi h eigh plan and
animal species, in which each species inds enough ood and
sui able li ing condi ions. Wi hin he GBA, es ake s ecei e a
a ie y o in o ma ion abou di e en plan and animal species,
om which hey ha e o choose eigh species and selec he
app op ia e habi a o hem.
TABLE 2 | Coding o he six GBAs acco ding o Hawkes (2017) GBA axonomy.
GBA used in he p esen
s udy Gen e
GBA cha ac e is ics acco ding o Hawke's GBA axonomy
F eedom o
ac ion
Con lic ing
demands
Va iable
pa hs Engagemen Suspense ulness Game ulness Fideli y
Ai man Challenge Ac ion 5.0 3.0 4.5 5.0 4.5 5.0 4.5
Wo kday simula ion Simula ion 4.5 2.0 3.5 4.5 4.0 4.5 4.0
Building Docks Role‐playing 3.5 3.0 4.5 4.0 5.0 4.5 2.0
Minec a game Ad en u e 4.5 2.5 3.0 4.5 3.0 5.0 1.0
Cogni y: G id Lock Mini‐game 2.5 1.0 1.5 3.0 2.5 3.0 1.0
Ecosys em C ea ion S a egy 4.5 5.0 5.0 4.5 5.0 5.0 1.0
No e: GBA cha ac e is ics we e a ed on a i e‐poin a ing scale anging om 1 = e y low o 5 = e y high. Values ep esen he mean a ing o he wo independen a e s.
6o 16 In e na ional Jou nal o Selec ion and Assessmen , 2025
3.2 | P ocedu e and Sample
The s udy used an expe imen al wi hin‐subjec s design. Thus,
wi hin he s udy, each pa icipan a ed all GBAs on six eac ion
a iables (see below). We ec ui ed Ge man speaking pa ici-
pan s ia di ec con ac s (e.g., wo d o mou h, Wha sApp,
e‐mail), social media (e.g., LinkedIn), and a depa men al pa -
icipan pool. Inclusion c i e ion o pa icipa ion was co ec ly
answe ing an a en ion check i em (see below).
A e ob aining pa icipan s' in o med consen , hey we e old
o imagine ha hey we e sea ching o a new job and had
applied o an o ice posi ion a six di e en o ganiza ions,
which we e all equally a ac i e o hem in e ms o paymen
and job asks. Fu he mo e, pa icipan s we e old ha hey had
been in i ed o ake an online assessmen a each o he six
o ganiza ions. Subsequen ly, pa icipan s we e p esen ed wi h
he six di e en online assessmen s (i.e., GBAs) in andomized
o de . Pa icipan s did no play he GBAs hemsel es bu we e
p o ided wi h a ex ‐based explana ion as well as wi h a ideo o
each GBA. Wi hin each explana ion ex and ideo, he goal,
s a ing si ua ion, indi idual asks, game elemen s, and basic
ules o he speci ic GBA we e desc ibed in de ail. Addi ionally,
each ideo aimed o p o ide pa icipan s wi h a comp ehensi e
unde s anding ega ding he isual ep esen a ion o a pa ic-
ula GBA and i s associa ed game elemen s. A e each
espec i e GBA was desc ibed using a ideo and explana ion
ex , pa icipan s e alua ed six di e en applican eac ion
a iables conce ning his speci ic GBA. Pa icipan s' demo-
g aphic da a as well as hei compu e sel ‐e icacy, and ideo
game expe ience we e measu ed a he end o he su ey.
To de e mine he equi ed sample size o es ou esea ch
ques ion wi h a powe o 0.80, we conduc ed an a p io i powe
analysis using G*Powe (Faul e al. 2007). To be able o de ec a
small e ec o = 0.10 (co esponding o a do 0.20) o a one‐
way mul i a ia e analysis o a iance wi h epea ed measu es
(MANOVA; numbe o measu emen s = 6; assumed co ela ion
among epea ed measu es = 0.50), his analysis e ealed a
equi ed sample size o N= 114. Hypo heses 1 o 5we e ana-
lyzed using mul ile el modeling, o which he conce n abou
he su icien sample size gene ally e e s o he highe le el
(i.e., in ou analyses o he numbe o pa icipan s). Wi h a
minimum sample size o 120 pa icipan s (i.e., a Le el 2), we
could expec su icien powe o ou mul ile el model (Maas
and Hox 2005). Acco dingly, we aimed o collec da a om a
leas 120 pa icipan s.
The ini ial sample e en consis ed o 160 pa icipan s. Ye , be o e
he da a analysis, we excluded 13 pa icipan s who ailed he
a en ion check, which led o a inal sample o N=147. In his
sample, 56.46% sel ‐ epo ed as emale, 42.86% as male,
and 0.68% as di e se. Pa icipan s' mean age was 30.24 yea s
(SD = 10.46) and 2.04% epo ed a seconda y school ce i ica e as
hei highes educa ional deg ee, 7.48% an in e media e school‐
lea ing ce i ica e, 24.49% a gene al quali ica ion o uni e si y
en ance (i.e., Ge man Abi u ), 43.54% a bachelo 's deg ee,
21.77% a mas e 's deg ee, and 0.68% a PhD. O he pa icipan s,
44.90% we e employed a he ime o s udy (including 0.68% who
we e sel employed). 44.90% we e employed a he ime o he
s udy.
3.3 | Measu es
All i ems we e measu ed using a i e‐poin Like scales anging
om 1 = s ongly disag ee o 5 = s ongly ag ee. Suppo ing
In o ma ion Table S1 in he online supplemen lis s all i ems o
he di e en scales and he espec i e i em sou ces.
3.3.1 | Applican Reac ion Va iables
The di e en applican eac ion a iables o a gi en GBAs
we e adminis e ed immedia ely a e he GBA was p e-
sen ed. We measu ed pe cei ed job‐ ela edness ( wo i ems;
mean α= 0.91), p ocedu al ai ness ( h ee i ems; mean
α= 0.92), and oppo uni y o pe o m ( ou i ems; mean
α= 0.91) wi h h ee subscales o he Selec ion P ocedu al
Jus ice Scale (Baue e al. 2001) in he Ge man ansla ion by
Manzey and Gu k (2005). Face alidi y (mean α=0.85)was
assessed using a h ee‐i em scale om Oos om e al. (2013)
using he Ge man ansla ion by Ohlms, Melche s and
Kanning (2024a). To measu e o ganiza ional a ac i eness
(mean α= 0.91), we used i e i ems om Highhouse, Lie ens
and Sina (2003) in he Ge man ansla ion by Basch,
Melche s and Bü ne (2022). Finally, enjoymen o he
assessmen (mean α= 0.92) was cap u ed wi h h ee i ems
om Wilde e al. (2009) using he Ge man ansla ion by
Ohlms, Melche s and Kanning (2024a).
To assess whe he he six eac ion a iables indeed com-
p ised sepa able cons uc s, we conduc ed a con i ma o y
ac o analysis (CFA) wi h six co ela ed ac o s. This
CFA showed an adequa e i ac oss he di e en GBAs,
mean χ
2
(155) = 295.06, p<0.001;meanCFI=0.95;mean
SRMR = 0.06; mean RMSEA = 0.08. In con as , a single‐
ac o model had a poo i , mean χ
2
(170) = 1060.14,
p< 0.001; mean CFI = 0.68; mean SRMR = 0.10, mean
RMSEA = 0.19. In addi ion, he six‐ ac o model i ed sig-
ni ican ly be e han he single‐ ac o model, all Δχ
2
s
(15) > 598.00, all ps < 0.001.
3.3.2 | Indi idual Di e ence Va iables
In addi ion o he demog aphic a iables, we used i e i ems
(α= 0.93) om Bou gonjon e al. (2010) o measu e pa ici-
pan s' ideo game expe ience. Fu he mo e, we used eigh i ems
om Wiechmann and Ryan (2003) o assess compu e sel ‐
e icacy (α= 0.85).
3.3.3 | A en ion Check
To assess whe he pa icipan s conscien iously comple ed he
su ey, we inse ed an a en ion check i em in be ween he
applican eac ion i ems: “This is a es o you a en ion.
The e o e, please ick ‘s ongly ag ee’ o show ha you ha e
ead e e y hing ca e ully.”As no ed abo e, pa icipan s who
ailed o answe his i em co ec ly we e excluded om all
analyses (i.e., 13 pa icipan s).
7o 16
4 | Resul s
Means, s anda d de ia ions, and in e co ela ions be ween
a iables a e p esen ed in Table 3. Consis en wi h p e ious
esea ch (e.g., Gko ezis e al. 2021), age was nega i ely associ-
a ed wi h ideo game expe ience ( =−0.18, p= 0.03). Fu -
he mo e, as in p e ious s udies, men sco ed highe on ideo
game expe ience ( = 0.43, p< 0.001) and compu e sel ‐e icacy
( = 0.31, p< 0.001) han did women (e.g., Gko ezis e al. 2021).
4.1 | Reac ions o he Di e en GBAs
Ou i s objec i e was o assess whe he he di e en GBAs
e oked di e en eac ions in es ake s (RQ 1). To examine his
esea ch ques ion, we conduc ed a se ies o one‐way analyses o
a iance (ANOVAs) wi h epea ed measu es. The independen
a iable was he GBA and he dependen a iables we e he six
applican eac ion a iables.
As can be seen in Table 4, in all ANOVAs he GBAs had a
signi ican e ec on each o he six applican eac ion a iables,
all Fs > 5.22, all ps < 0.05. Fu he mo e, as can be seen in
Figu e 1, wi h he excep ion o enjoymen , he gene al pa e n
o esul s was simila o all he o he applican eac ion a i-
ables. Fo hese o he a iables, he co esponding η²s in
Table 4also sugges ha he e ec s o he GBAs we e la ge, and
subsequen pos ‐hoc es s using he Bon e oni p ocedu e
e ealed a ious signi ican di e ences. Speci ically, he same
pa e n o esul s was ound o p ocedu al ai ness, pe cei ed
job‐ ela edness, oppo uni y o pe o m, and ace alidi y: The
Wo kday simula ion and Building Docks we e a ed mos pos-
i i ely and signi ican ly highe han he Ecosys em C ea ion,
which was a ed signi ican ly highe han he Ai man Chal-
lenge, he Minec a game, and G id Lock. A simila pa e n o
esul s eme ged o o ganiza ional a ac i eness, wi h he only
di e ence being ha a ings o he Ecosys em C ea ion and
Minec a game did no di e signi ican ly. In pa icula , o all
hese applican eac ion a iables he e we e medium o
la ge di e ences be ween he Wo kday simula ion on he one
hand and he Ai man Challenge (d= 0.77 o 1.12), Minec a
(d= 0.77 o 1.37), and G id Lock (d= 0.62 o 1.41) on he o he
hand. Simila ly, we ound medium o la ge di e ences be ween
Building Docks on he one hand and he Ai man Challenge
(d= 0.72 o 1.06), Minec a (d= 0.66 o 1.31), and G id Lock
(d= 0.65 o 1.35) on he o he hand.
In con as o all he p e ious applican eac ion a iables, he e
we e smalle di e ences be ween he di e en GBAs wi h
ega d o he pe cei ed enjoymen o he GBAs. Speci ically, all
GBAs we e a ed posi i ely (i.e., had a mean > 3) on his
eac ion a iable and only e y ew GBAs di e ed signi ican ly
acco ding o he pos ‐hoc es s (see Table 3and Figu e 1).
Howe e , he e we e signi ican di e ences in enjoymen a -
ings be ween Building Docks and he Ai man Challenge
(d= 0.28), Building Docks and G id Lock (d= 0.46), as well as
he Minec a game and G id Lock (d= 0.31).
Taken oge he , ou esul s sugges ha po en ial applican s
pe cei ed he di e en GBAs as ela i ely enjoyable. In con as
TABLE 3 | Desc ip i e in o ma ion and co ela ions o age, gende , ideo game expe ience, and compu e sel ‐e icacy.
Va iable MSDSD
wi hin
123456789
1. P ocedu al ai ness 2.96 0.69 0.73 0.70*** 0.69*** 0.69*** 0.68*** 0.37***
2. Job‐ ela edness 2.57 0.61 0.86 0.76*** 0.82*** 0.80*** 0.72*** 0.40***
3. Oppo uni y o pe o m 2.60 0.61 0.76 0.64*** 0.81*** 0.78*** 0.75*** 0.51***
4. Face alidi y 2.72 0.55 0.93 0.59*** 0.76*** 0.70*** 0.73*** 0.40***
5. O ganiza ional a ac i eness 2.95 0.64 0.71 0.73*** 0.74*** 0.67*** 0.62*** 0.59***
6. Enjoymen 3.50 0.77 0.77 0.56*** 0.50*** 0.53*** 0.40*** 0.73***
7. Age 30.24 10.46 −0.31*** −0.08 −0.11 −0.06 −0.19*−0.28***
8. Gende
a
0.43 0.50 0.02 −0.02 −0.02 −0.08 −0.04 0.02 0.10
9. Video game expe ience 2.13 1.08 0.13 0.12 0.20*0.17*0.18*0.26** −0.18*0.43***
10. Compu e sel ‐e icacy 4.40 0.53 −0.06 −0.14 −0.14 −0.14 −0.03 0.15 −0.11 0.31*** 0.12
No e: Co ela ions below he diagonal a e pe son‐le el co ela ions. To calcula e hese pe son‐le el co ela ions, GBA‐le el da a below he diagonal we e a e aged ac oss GBA (N= 147). Co ela ions abo e he diagonal a e GBA‐le el
co ela ions (N= 882). Abo e he diagonal, GBA‐le el da a we e cen e ed a ound he espec i e pe son mean. Gende is coded 0 = emale, 1 = male.
a
n= 146.
*p< 0.05; **p< 0.01; ***p< 0.001.
8o 16 In e na ional Jou nal o Selec ion and Assessmen , 2025
Gko ezis, P., K. Geo giou, I. Nikolaou, and A. Ky iaza i. 2021. “Gami-
ied o T adi ional Si ua ional Judgemen Tes ? A Mode a ed Media ion
Model o Recommenda ion In en ions ia O ganiza ional A ac i e-
ness.”Eu opean Jou nal o Wo k and O ganiza ional Psychology 30,
no. 2: 240–250. h ps://doi.o g/10.1080/1359432X.2020.1746827.
González‐González, C. S., P. A. Toledo‐Delgado, V. Muñoz‐C uz, and
J. A nedo‐Mo eno. 2022. “Gende and Age Di e ences in P e e ences
on Game Elemen s and Pla o ms.”Senso s 22, no. 9: 3567. h ps://doi.
o g/10.3390/s22093567.
Ha mann, T., and C. Klimm . 2006. “Gende and Compu e Games:
Explo ing Females' Dislikes.”Jou nal o Compu e ‐Media ed
Communica ion 11, no. 4: 910–931. h ps://doi.o g/10.1111/j.1083-
6101.2006.00301.x.
Hausknech , J. P., D. V. Day, and S. C. Thomas. 2004. “Applican
Reac ions o Selec ion P ocedu es: An Upda ed Model and Me a‐
Analysis.”Pe sonnel Psychology 57, no. 3: 639–683. h ps://doi.o g/10.
1111/j.1744-6570.2004.00003.x.
Hawkes, B., I. Cek, and C. Handle . 2017. “Nex Gene a ion
Technology‐enhanced Assessmen .”In The Gami ica ion o Employee
Selec ion Tools, edi ed by J. C. Sco , D. Ba am, and D. H. Reynolds,
288–314. Be lin: Camb idge Uni e si y P ess. h ps://doi.o g/10.1017/
9781316407547.013.
Highhouse, S., F. Lie ens, and E. F. Sina . 2003. “Measu ing A ac-
ion o O ganiza ions.”Educa ional and Psychological Measu emen
63, no. 6: 986–1001. h ps://doi.o g/10.1177/0013164403258403.
Hox, J., and L. Wijngaa ds‐de Meij. 2015. “The Mul ile el Reg ession
Model.”In The Sage Handbook o Reg ession Analysis and Causal
In e ence, edi ed by H. Bes and C. Wol , 133–152. Sage.
King, G., and T. K zywinska. 2002. Sc eenPlay: Cinema/Videogames/
In e aces. New Yo k, NY: Wall lowe P ess.
Lande s, R. N., M. B. A ms ong, A. B. Collmus, S. Mujcic, and J. Blaik.
2022. “Theo y‐D i en Game‐Based Assessmen o Gene al Cogni i e
Abili y: Design Theo y, Measu emen , P edic ion o Pe o mance, and
Tes Fai ness.”Jou nal o Applied Psychology 107, no. 10: 1655–1677.
h ps://doi.o g/10.1037/apl0000954.
Lande s, R. N., E. M. Aue , A. B. Collmus, and M. B. A ms ong. 2018.
“Gami ica ion Science, i s His o y and Fu u e: De ini ions and a
Resea ch Agenda.”Simula ion & Gaming 49, no. 3: 315–337. h ps://doi.
o g/10.1177/1046878118774385.
Lande s, R. N., and S. Ma in. 2021. “Theo y and Technology in O ga-
niza ional Psychology: A Re iew o Technology In eg a ion Pa adigms
and Thei E ec s on he Validi y o Theo y.”Annual Re iew o
O ganiza ional Psychology and O ganiza ional Beha io 8: 235–258.
h ps://doi.o g/10.1146/annu e -o gpsych-012420-060843.
Lande s, R. N., and D. R. Sanchez. 2022. “Game‐Based, Gami ied, and
Game ully Designed Assessmen s o Employee Selec ion: De ini ions,
Dis inc ions, Design, and Valida ion.”In e na ional Jou nal o Selec ion
and Assessmen 30, no. 1: 1–13. h ps://doi.o g/10.1111/ijsa.12376.
Lie ens, F., and P. R. Sacke . 2017. “The E ec s o P edic o Me hod
Fac o s on Selec ion Ou comes: A Modula App oach o Pe sonnel
Selec ion P ocedu es.”Jou nal o Applied Psychology 102, no. 1: 43–66.
h ps://doi.o g/10.1037/apl0000160.
Lucas, K., and J. L. She y. 2004. “Sex Di e ences in Video Game Play:
A Communica ion Based Explana ion.”Communica ion Resea ch 31,
no. 5: 499–523. h ps://doi.o g/10.1177/0093650204267.
Maas, C. J. M., and J. J. Hox. 2005. “Su icien Sample Sizes o Mul-
ile el Modeling.”Me hodology 1, no. 3: 86–92. h ps://doi.o g/10.1027/
1614-2241.1.3.86.
Manzey, D., and S. Gu k. 2005. P ozedu ale Ge ech igkei on Pe so-
nalauswahlmaßnahmen: Un e suchungen zu eine Deu schen Ve sion
de Selec ion P ocedu al Jus ice Scale (SPJS) on Baue e al. (2001).
[P ocedu al Jus ice o Pe sonnel Selec ion Me hods: In es iga ions o a
Ge man e sion o he Selec ion P ocedu al Jus ice Scale (SPJS) by
Baue e al. (2001)] [Pape p esen a ion]. Bonn, Ge many: 4 h Annual
Con e ence o he Ge man Socie y o Wo k and O ganiza ional
Psychology.
Melche s, K. G., and J. M. Basch. 2022. “Fai Play? Sex‐,Age‐,and
Job‐Rela ed Co ela es o Pe o mance in a Compu e ‐Based Simu-
la ion Game.”In e na ional Jou nal o Selec ion and Assessmen 30,
no. 1: 48–61. h ps://doi.o g/10.1111/ijsa.12337.
Ohlms, M. L. 2024. “Gami izie ung und Game-based Assessmen
[Gami ica ion and Game-Based Assessmen ].”In Digi ale Pe sona-
lauswahl und Eignungsdiagnos ik, edi ed by U. P. Kanning and M. L.
Ohlms, 127–154. Sp inge . h ps://doi.o g/10.1007/978-3-662-68211-1.
Ohlms, M. L., K. G. Melche s, and U. P. Kanning. 2024a. “Can We
Play ully Measu e Cogni i e Abili y? Cons uc ‐Rela ed Validi y and
Applican Reac ions.”In e na ional Jou nal o Selec ion and Assessmen
32, no. 1: 91–107. h ps://doi.o g/10.1111/ijsa.12450.
Ohlms, M. L., K. G. Melche s, and U. P. Kanning. 2024b. “Play ul
Pe sonnel Selec ion: The Use o T adi ional s. Game‐Rela ed Pe sonnel
Selec ion Me hods and Thei Pe cep ion F om he Rec ui e s' and Ap-
plican s' Pe spec i es.”In e na ional Jou nal o Selec ion and
Assessmen 32, no. 3: 381–398. h ps://doi.o g/10.1111/ijsa.12466.
Ohlms, M. L., K. G. Melche s, and F. Lie ens. 2025. “I 's Jus a Game!
E ec s o Fan asy in a S o i ied Tes on Applican Reac ions.”Applied
Psychology: An In e na ional Re iew 74, no. 1: e12569. h ps://doi.o g/
10.1111/apps.12569.
Ohlms, M. L., E. Voig lände , K. G. Melche s, and U. P. Kanning. 2024.
“Is Gami ica ion a Sui able Means o Imp o e Applican Reac ions and
Con ey In o ma ion Du ing an Online Tes ?”Jou nal o Pe sonnel
Psychology 23, no. 4: 169–178. h ps://doi.o g/10.1027/1866-5888/
a000343.
Oos om, J. K., D. Van De Linden, M. P. Bo n, and
H. T. Van De Molen. 2013. “New Technology in Pe sonnel Selec ion:
How Rec ui e Cha ac e is ics A ec he Adop ion o New Selec ion
Technology.”Compu e s in Human Beha io 29, no. 6: 2404–2415.
h ps://doi.o g/10.1016/j.chb.2013.05.025.
Qian, M., and K. R. Cla k. 2016. “Game‐Based Lea ning and 21s
Cen u y Skills: A Re iew o Recen Resea ch.”Compu e s in Human
Beha io 63: 50–58. h ps://doi.o g/10.1016/j.chb.2016.05.023.
Ramos‐Villag asa, P. J., E. Fe nández‐Del‐Río, and Á. Cas o. 2022.
“Game‐Rela ed Assessmen s o Pe sonnel Selec ion: A Sys ema ic
Re iew.”F on ie s in Psychology 13: 952002. h ps://doi.o g/10.3389/
psyg.2022.952002.
Reed, K., D. H. Do y, and D. R. May. 2005. “The Impac o Aging on
Sel ‐E icacy and Compu e Skill Acquisi ion.”Jou nal o Manage ial
Issues 17, no. 2: 212–228.
Rollings, A., and E. Adams. 2003. And ew Rollings and E nes Adams on
Game Design. Indianapolis, IN: New Ride s.
We bach, K., D. Hun e , and W. Dixon. 2012. Fo he Win: How Game
Thinking Can Re olu ionize You Business. Philadelphia, Pennsyl ania:
Wha on Digi al P ess.
Wiechmann, D., and A. M. Ryan. 2003. “Reac ions o Compu e ized
Tes ing in Selec ion Con ex s.”In e na ional Jou nal o Selec ion and
Assessmen 11, no. 2–3: 215–229. h ps://doi.o g/10.1111/1468-2389.
00245.
Wilde, M., K. Bä z, A. Ko ale a, and D. U hahne. 2009. “Übe p ü ung
Eine Ku zskala In insische Mo i a ion [Valida ion o a Sho Scale o
In insic Mo i a ion].”Zei sch i ü Didak ik de Na u wissenscha en
15: 31–45. h ps://pub.uni-biele eld.de/ eco d/2404161.
Williams, D., N. Yee, and S. E. Caplan. 2008. “Who Plays, How Much,
and Why? Debunking he S e eo ypical Game P o ile.”Jou nal o
Compu e ‐Media ed Communica ion 13, no. 4: 993–1018. h ps://doi.
o g/10.1111/j.1083-6101.2008.00428.x.
15 o 16
Woods, S. A., S. Ahmed, I. Nikolaou, A. C. Cos a, and N. R. Ande son.
2020. “Pe sonnel Selec ion in he Digi al Age: A Re iew o Validi y and
Applican Reac ions, and Fu u e Resea ch Challenges.”Eu opean
Jou nal o Wo k and O ganiza ional Psychology 29, no. 1: 64–77.
h ps://doi.o g/10.1080/1359432X.2019.1681401.
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