Verslaafde Behav Rep. 2017 Jun; 5: 19–28.
Gepubliseer aanlyn 2017 Feb 7. doi: 10.1016 / j.abrep.2017.02.002
PMCID: PMC5800554
PMID: 29450224
Taal: Inglese | Duitse | Duitse
Rayna Sariyska,a,⁎ Bernd Lachmann,a Sebastian Markett,b,c Martin Reuter,b,c en Christelike Montaga,d
1. inleiding
Die internet het sy weg gevind in die daaglikse lewe van baie mense wêreldwyd, en bied 'n maklike manier om inligting in te samel en om vermaak te verbruik. Met die groeiende aantal internetgebruikers, wat tans byna 50% van die wêreldbevolking uitmaak (toegang op 07.09.16. http://www.internetlivestats.com/internet-users/), the number of reports on problematic Internet usage (PIU) is rising. In a representative study from Germany (N = 15,024 XNUMX deelnemers) Rumpf, Meyer, Kreuzer, John en Merkeek (2011) het voorkoms van 1.5% in internetverslawing getoon, met jonger gebruikers wat hoër proporsies toon (4% in die groep 14-16-jariges). Eerste pogings om PIU te definieer en te diagnoseer1 is gemaak deur Kimberly Young in die jaar 1998 (sien ook eerste gevalleverslag van Jong, 1996). Sedertdien is talle toetse en siftingsinstrumente ontwikkel (bv Young, 1998b, Jong, 1998a, Tao et al., 2010), ten einde voorkoms in verskillende populasies te kan bereken en pasiënte van effektiewe behandeling te voorsien. Daar is egter nog geen bestaande nosologiese klassifikasie van PIU nie. Die navorsing oor aanlyn-speletjieverslawing blyk 'n stap voor te wees, aangesien Internet Gaming Disorder (IGD) onlangs in Afdeling III van DSM-5 ingesluit is, wat sodoende verdere ondersoeke aanmoedig voordat dit as 'n formele afwyking beskou word (Amerikaanse Psigiatriese Vereniging). IGD word beskou as 'n spesifieke vorm van PIU, wat slegs in klein dele oorvleuel met die algemene vorm van PIU wat hierbo beskryf word (bv. Davis, 2001, Montag et al., 2015).
1.1. PIU en implisiete leer/besluitneming
Tekortkominge in besluitneming is getoon in talle studies wat pasiënte met substans- en gedragsverslawing ondersoek (bv. Bechara et al., 2001, Schoenbaum et al., 2006). As gevolg van ooreenkomste in die konseptualisering van PIU en gedrags-/middelverslawing (Jong, 1998a), is die onderwerp van besluitneming ook van hoë relevansie om die aard van oormatige internetgebruik beter te verstaan. By die beoordeling van besluitneming is 'n differensiasie gemaak tussen besluitneming onder dubbelsinnigheid en besluitneming onder risiko (Brand et al., 2006, Schiebener en Brand, 2015). Terwyl besluitneming onder dubbelsinnigheid die reëls vir winste en verliese en die waarskynlikhede van verskillende uitkomste nie eksplisiet verduidelik word nie (gemeet bv. met die (eerste proewe van die) IOWA Dobbeltaak of IGT), in besluitneming onder risiko eksplisiete inligting oor die potensiële gevolge, en die waarskynlikhede vir winste en verliese is beskikbaar of is berekenbaar (gemeet bv. met die Game of Dice Task of GDT) (Brand et al., 2006, Schiebener en Brand, 2015). Gebaseer op hierdie differensiasie en op die dubbelprosesmodelle van besluitneming (bv Epstein, 2003), Schiebener en Brand (2015) 'n teoretiese model voorgestel om besluitneming onder risiko te verduidelik. In hierdie model word die rol van uitvoerende funksies uitgelig as 'n sleutel van relevansie vir besluitneming onder risiko, maar nie besluitneming onder dubbelsinnigheid nie. Emosionele beloning en straf is veronderstel om beide vorme van besluitneming te vergesel. Dus kan beide reflektiewe prosesse (beheer deur kognisie), tesame met impulsiewe prosesse (geïnduseer deur die afwagting van emosionele beloning en straf) betrokke wees by besluitnemingsprosesse onder objektiewe risikotoestande (Schiebener & Brand, 2015). Daarbenewens is daar voorgestel dat faktore soos inligting oor die besluitsituasie, individuele eienskappe en situasie-geïnduseerde toestande en eksterne invloede modulerende effekte op besluitneming het (Schiebener & Brand, 2015).
Met betrekking tot internetverslawing is 'n nuwe teoretiese raamwerk voorgestel deur Brand, Young, Laier, Wölfling en Potenza (2016), genoem 'n interaksie van persoon-affekte-kognisie-uitvoering (I-PACE), waar 'n verswakking van uitvoerende funksies en inhiberende beheer ook uitgelig is as relevant vir die ontwikkeling van PIU. Volgens hierdie model lê die ontwikkeling en instandhouding van spesifieke internetgebruikafwykings onderliggend aan interaksies tussen predisponerende faktore (bv. persoonlikheid en psigopatologie), moderators (bv. disfunksionele hanteringstyl en internetverwagtinge), en bemiddelaars (bv. affektiewe en kognitiewe reaksies op situasionele leidrade). Hierdie komplekse interaksies, gekombineer met die ervaring van bevrediging en positiewe versterking, as gevolg van die gebruik van 'n sekere kenmerk van die internet, en met verminderde uitvoerende funksies en inhiberende beheer, kan 'n spesifieke internetgebruikversteuring tot gevolg hê.
Tot dusver is 'n paar empiriese studies uitgevoer in die konteks van PIU, inhiberende beheer en besluitneming. Die meeste van hulle is in ooreenstemming met die voorgenoemde teoretiese raamwerk deur Brand et al. (2016). Sun et al. (2009) het byvoorbeeld swakker prestasie in 'n dobbeltaak by oormatige internetgebruikers en stadiger keuse van 'n suksesvolle strategie gerapporteer in vergelyking met beheerdeelnemers. In 'n meer onlangse studie, Pawlikowski en Brand (2011) gerapporteer verminderde besluitnemingsvermoë onder risiko in die GDT in 'n groep oormatige World of Warcraft (WoW) spelers in vergelyking met kontrole deelnemers. Yao et al. (2015) het 'n gewysigde weergawe van die Go/NoGo-taak gebruik (waar spelverwante stimuli langs neutrale stimuli gebruik is) en vermindering in inhiberende beheer by deelnemers met IGD gerapporteer, in vergelyking met kontrole-deelnemers. Laier, Pawlikowski en Brand (2014) found similar results with a modified version of the IGT, when using pornographic and neutral pictures on the advantageous and/or disadvantageous card decks. Here, male participants showed deficient decision making in trials where the pornographic pictures were associated with disadvantageous card decks. However, also mixed results concerning decision making in the context of PIU or IGD were reported. In a study by Ko et al. (2010) byvoorbeeld internetverslaafde deelnemers het beter besluitneming getoon, gemeet met die IGT, in vergelyking met kontroledeelnemers. In die studie deur Yao et al. (2015) reeds hierbo aangehaal, kon geen verskil in besluitneming met behulp van die IGT gevind word tussen gesonde deelnemers en diegene met IGD nie. Om hierdie teenstrydige resultate uitmekaar te haal, is verdere studies, wat moontlike interfererende veranderlikes ondersoek, nodig. Een spesifieke veranderlike word later in die huidige studie beskryf.
1.2. PIU, risikoneming en impulsiwiteit
Due to the initial characterization of PIU as an impulse control disorder, a number of studies were conducted to explore PIU in the context of impulsivity and risk-taking. Cao, Su, Liu en Gao (2007) en Lee et al. (2012) het getoon dat PIU positief geassosieer is met eienskapimpulsiwiteit, gemeet met die Barratt Impulsiveness Scale (BIS-11). Met betrekking tot die teoretiese raamwerk deur Brand et al. (2016), reeds hierbo bekendgestel, word impulsiwiteit onder die persoonlikheidsfaktore genoem, wat die mees stabiele assosiasies met PIU toon en word dus voorgestel om een van die faktore te wees wat die ontwikkeling en instandhouding daarvan beïnvloed. In die breë word impulsiwiteit gekenmerk as "'n geneigdheid tot vinnige, onbeplande reaksies op interne of eksterne stimuli, sonder inagneming van die negatiewe gevolge van hierdie reaksies op die impulsiewe individue of op ander" (Moeller, Barratt, Dougherty, Schmitz, & Swann, 2001; bl. 1784). Die verwante term van risikoneming word gedefinieer as "gedrag wat uitgevoer word onder onsekerheid, met of sonder inherente negatiewe gevolge, en sonder robuuste gebeurlikheidsbeplanning" (Kreek, Nielsen, Butelman, & LaForge, 2005; bl. 1453). Ko et al. (2010) het die ballon-analoge risiko-taak toegepas (Lejuez et al., 2002) om risiko-neming te meet, maar het geen beduidende verband met PIU gevind nie. In die huidige studie kyk ons weer na hierdie assosiasies deur beide selfrapportering toe te pas tesame met eksperimentele maatstawwe van impulsiwiteit/risiko-neming.
1.3. Die rol van geslag vir PIU/IGD
Nog 'n belangrike kwessie in die konteks van internetverslawing is die voorkeur van spesifieke kenmerke van die internet (bv. aanlyn inkopies, aanlyn speletjies), afhangende van geslag. 'n Verteenwoordigende studie van Duitsland het getoon dat 77.1% van internetverslaafde vroue op die ouderdom van 14–24 jaar sosiale netwerkwerwe gebruik in vergelyking met 64,8% mans op dieselfde ouderdom (Rumpf et al., 2011). In dieselfde studie het 7.2% van internetverslaafde vroue op die ouderdom tussen 14 en 24 jaar gerapporteer dat hulle die internet gebruik om aanlyn videospeletjies te speel, vergeleke met 33.6% van mans op dieselfde ouderdom (Rumpf et al., 2011). Dit blyk dus dat manlike deelnemers met betrekking tot IGD 'n groter voorkeur vir aanlyn-speletjies toon, in vergelyking met vroulike deelnemers en na berig is dat hulle 'n groter risiko loop om IGD te ontwikkel. Verder, Ko, Yen, Chen, Chen en Yen (2005) waargeneem dat ouer ouderdom, laer selfbeeld en laer daaglikse lewenstevredenheid geassosieer word met meer ernstige IGD onder mans, maar nie vroue nie. Ten spyte van hierdie resultate is daar nog net 'n paar studies wat die geslag van deelnemers sistematies as 'n moderator/bemiddelaar veranderlike in die konteks van PIU beskou. Dit is egter moontlik dat hierdie verskille 'n paar opponerende resultate in die veld verantwoord, en dus sal hulle in die volgende studies in ag geneem word.
The aim of our research project was to investigate the link between PIU, as well as IGD and implicit learning in a group of male participants with proneness to IGD (study 1). In study 2 we aimed at replicating these results, by comparing healthy participants and excessive WoW players under the consideration of gender. The purpose of study 3 was to explore the relationship between PIU, IGD and impulsivity/risk-taking (self-report and experimental data) in healthy participants.
Gebaseer op die voorgenoemde literatuur, het ons die volgende hipoteses geformuleer:
We expect negative associations between PIU/IGD and implicit learning abilities (study 1).
We expect negative associations between PIU/IGD and implicit learning abilities (study 2). We expect this negative association to be strongest in the group of male WoW players.
We expect positive associations between PIU/IGD and the self-report and experimental measures of impulsivity/risk-taking in healthy participants (study 3).
2. Study 1
2.1. metodes
2.1.1. deelnemers
N = 107 deelnemers (99 mans, 8 vroue, ouderdom M = 19.52, SD = 3.57) is gewerf by die "Gamescom 2013" in Duitsland, die wêreld se grootste speletjie-geleentheid. Maar omdat die baie lae aantal vroulike deelnemers in die huidige steekproef (n = 8) en die bogenoemde geslagsverskille in die konteks van IGD (bv Rumpf et al., 2011), het ons die vroulike deelnemers uitgesluit van die verdere ontledings van die studie. Nadat ook deelnemers met ontbrekende data uitgesluit is, het die steekproef tot gevolg gehad n = 79 manlike deelnemers (ouderdom M = 19.81, SD = 3.62). Wat hul opleiding betref, het 8.9% gerapporteer dat hulle 'n universiteits- of politegniese graad het, nog 40.5% het gerapporteer dat hulle 'n A-vlak- of beroepsbaccalaureaat-diploma het en 26.6% het gerapporteer dat hulle 'n sekondêre skoolverlaatsertifikaat of sekondêre moderne skoolkwalifikasie het, terwyl 24% het geen skooldiploma nie.
2.1.2. maatreëls
Deelnemers het vrae oor hul ouderdom, geslag en opvoeding beantwoord, 'n kort weergawe van die internetverslawingtoets (s-IAT, Pawlikowski, Altstötter-Gleich, & Brand, 2013; Cronbach's Alpha in die huidige steekproef was 0.70), wat 12 Likert-skaal items bevat (1 = nooit tot 5 = baie dikwels nie) en die Online Game Addiction Scale (OGAS, 'n gewysigde weergawe van die Gaming Addiction Scale deur Lemmens, Valkenburg, & Peter, 2009, where the word “online” was added to every item; Cronbach’s Alpha in the present sample was 0.66), consisting of 7 items, ranging between 1 = never and 5 = very often. Additionally, participants rated their computer gaming experience (e.g. “For how many years have you been playing computer games?” or “How many hours on average per week do you play online computer games?”). A self-report measure of risk-taking was administered, including one item on overall risk-taking tendencies (“How would you describe yourself from 0 (not at all willing to take risks) to 10 (absolutely willing to take risks)?”); German Socio-Econimic Panel (SOEP; Siedler, Schupp, Spiess en Wagner, 2008). Ons het 'n effens aangepaste eksperimentele taak gebruik ("Duiwel se bors"), geïnkorporeer uit 'n studie deur Eisenegger et al. (2010), in order to measure implicit learning. On each of a total of 36 trials, we presented ten pictures of closed wooden boxes on the computer screen. The boxes were aligned in one row and participants had the opportunity to subsequently open a self-selected number of boxes, working from left to right. Participants were instructed that nine of the boxes contained a virtual monetary reward (5 cents) and one contained a “devil”. If participants opened only reward boxes on a given trial, they proceeded to the next trial by gaining the sum of the rewards. If they opened a box, containing the devil, among with the other boxes, they lost everything on the current trial. The upcoming position of the devil was randomized among the 36 trials, but appeared on each position from 2 to 102 presies vier keer. Alhoewel dit nie aan die deelnemers genoem is nie, kon deelnemers met hoër kognitiewe vaardighede 'n implisiete begrip vir hierdie reël uitgewerk het en kon geleer het om beter te presteer in die loop van die eksperiment. Die totaal van geldelike belonings teen die einde van die eksperiment word verder na verwys as "WINS" en sal gebruik word as 'n maatstaf van implisiete leer. Die eksperimentele opstelling word uitgebeeld in Fig 1.
Eksperimentele opstelling van die Duiwel se kis – die opening van die kis met die duiwel het gelei tot die verlies van alle versamelde munte van 'n gegewe verhoor.
2.1.3. prosedure
All questionnaires only available in English were translated into German by our own work group. The participants first filled in the questionnaires and then completed the Devil’s chest experiment. Please note, that participants in study 1 did not receive any monetary reward after completing the experiment and that they were informed about this fact prior to completing the experiment.
2.1.4. Statistiese ontledings
Vir die volgende ontledings is die normaliteit van die data ondersoek deur die duimreël toe te pas, voorgestel deur Miles en Shevlin (2001; bl. 74), considering the skewness of the investigated variables. Correlation analyses were computed with Pearson’s or Spearman’s correlations, depending on the distribution of the data, and bootstrap bias-corrected and accelerated confidence intervals (BCa 95% confidence intervals) were computed for every correlation coefficient to further test their significance. Repeated measures ANOVA was used to test for implicit learning effects, when comparing the gain in the first 18 trials with the gain in the last 18 trials of the experiment.
2.1.5. Etiek
Die navorsingsprojek (studies 1, 2 en 3) is goedgekeur deur die Plaaslike Etiese Komitee van die Universiteit van Bonn, Bonn, Duitsland. Alle proefpersone het ingeligte toestemming gegee voordat hulle die studie voltooi het.
2.2. Resultate
Gemiddeldes en standaardafwykings van die veranderlikes wat ondersoek word, word in Tabel 1.
Tabel 1
Gemiddelde, standaardafwyking (SD) en moontlike/werklike omvang vir die veranderlikes spelervaring (jare), aanlyn-speletjie-ure per week, s-IAT, OGAS, GAIN en risikoneming (selfverslag).
| beteken | SD | Moontlike omvang | Werklike omvang | |
|---|---|---|---|---|
| Spelkundigheid (jare) | 11.09 | 4.31 | - | 3-24 |
| Aanlyn speletjie-ure per week | 22.24 | 16.00 | - | 0-70 |
| s-IAT | 23.86 | 5.38 | 12-60 | 12-43 |
| OGAS | 14.75 | 4.36 | 7-35 | 7-26 |
| GAIN | 413.61 | 71.97 | 0-900a | 160-520 |
| Risiko neem (selfverslag) | 6.77 | 1.89 | 0-10 | 3-10 |
N = 79, risikoneming (self-rapportering) n = 64.
2.2.1. Korrelasie-ontledings
Slegs die veranderlike GAIN was nie normaal versprei nie. Die ouderdom van die deelnemers was positief gekorreleer met GAIN (ρ = 0.27, p < 0.05). Boonop het GAIN 'n negatiewe korrelasie met die s-IAT-telling getoon (ρ = − 0.26, p < 0.05). Daarbenewens het ons gedeeltelike korrelasies vir GAIN en die s-IAT-telling bereken om vir ouderdom te beheer. Die korrelasie het beduidend gebly (r = − 0.28, p < 0.05). Die negatiewe korrelasie tussen GAIN en die OGAS-telling het marginaal nie betekenisvolheid bereik nie (ρ = − 0.20, p = 0.073) en het nie-beduidend gebly na beheer vir ouderdom (r = − 0.12, p = 0.292). Alle betekenisvolle korrelasies het betekenisvol gebly na die inspeksie van die BCa 95% vertrouensintervalle. Sien asseblief Tabel 2 for an overview of the results.
Tabel 2
Korrelasies tussen WINS in die “Duiwel se bors”-eksperiment en die s-IAT, OGAS-telling en risikoneming (selfverslag).
| GAIN | s-IAT | OGAS | risiko neem (selfverslag) | |
|---|---|---|---|---|
| GAIN | 1 | |||
| s-IAT | − 0.264⁎ | 1 | ||
| OGAS | − 0.203 | 0.511⁎⁎ | 1 | |
| risiko neem (selfverslag) | 0.148 | 0.129 | 0.187 | 1 |
N = 79, neem risiko (selfverslag) n = 64; Spearman-korrelasies word uitgebeeld in Italic.
2.2.2. Manipulasiekontrole van die “Duiwel se bors”-eksperiment as 'n maatstaf van implisiete leer
Die resultate van die herhaalde maatreëls ANOVA het 'n beduidende gemiddelde verskil tussen die GAIN in die eerste 18 proewe van die eksperiment getoon, in vergelyking met die laaste 18 proewe (F(1,78) = 17.303, p < 0.01), wat wys dat deelnemers meer geld in die tweede deel van die eksperiment gewen het (M1 = 192.34 en M2 = 221.27 respectively) (see Fig 2).
Betekenis en die standaardfout vir die WINS in die eerste 18 proewe teenoor die WINS in die laaste 18 proewe van die "Duiwel se bors" eksperiment. MU = geldeenhede.
2.3. bespreking
Om op te som, soos voorgestel in ons hipoteses, in studie 1 is internetverslawing geassosieer met gebrekkige implisiete leervermoëns. Hierdie resultaat lewer verdere bewyse vir die rol van swak besluitneming in die konteks van PIU (bv Brand et al., 2016). Die assosiasie met IGD was in dieselfde rigting, maar het nie betekenis bereik nie. Dit kan verklaar word deur die relatief klein steekproefgrootte en/of die relatief lae interne konsekwentheid (0.66) van die OGAS-skaal in hierdie studie. Ten einde hierdie verhoudings verder te ondersoek en die resultate tussen manlike en vroulike deelnemers en tussen spelers en nie-spelers te vergelyk, is studie 2 uitgevoer.
3. Study 2
Die doel van die tweede studie was om die resultate van studie 1 te herhaal, deur gebruik te maak van 'n steekproef van World of Warcraft (WoW) spelers en kontrole deelnemers, wat naïef was vir WoW. Aangesien die verband tussen die s-IAT en GAIN as 'n maatstaf van implisiete leer waargeneem kan word by manlike deelnemers met geneigdheid tot IGD, was ons geïnteresseerd om replikasie van studie 1 se resultate te sien, veral by manlike WoW-spelers.
3.1. metodes
3.1.1. deelnemers
WoW players and control participants, took part in the study. The WoW players were recruited, using following criteria: WoW gaming experience for a minimum of two years. An exclusion criteria was playing other games than WoW for > 7 h per week, however, participants with no experience in other games were preferably recruited. Control persons needed to be WoW naïve, hence had no experience of playing this game before. Exclusion criteria for both groups of participants were visual impairment, difficulties in reading and writing, dyschromatopsia, concussion, long-term medication, neurological and psychiatric diseases, hearing disability and high substance use. After a thorough inspection of the sample we excluded one participant due to an eating disorder and daily cannabis consumption, one participants due to neurological and psychiatric disorders and one participant from the control group due to extreme values in sIAT and OGAS, and participants with missing data, which resulted in n = 77 kontrole deelnemers (39 mans) en n = 44 WoW-spelers (28 mans). 6.5% (n = 5) of control participants reported casual usage of online role-playing games (< 3 h gaming per week) and 23.4% (n = 18) het toevallige gebruik van Ego-shooter-speletjies aangemeld (< 1 uur speletjies per week). Die gemiddelde ouderdom van die totale steekproef was M = 23.70 (SD = 3.93). Regarding their education 10.7% reported having a university degree, another 85.9% reported having A-level or vocational baccalaureate diploma and 2.5% reported having secondary school leaving certificate or secondary modern school qualification. One person (0.9%) did not answer the items regarding education.
3.1.2. maatreëls
Hier weer die s-IAT (Pawlikowski et al., 2013; Cronbach's Alpha in die huidige steekproef was 0.76), OGAS ('n wysiging van die GAS deur Lemmens et al., 2009; Cronbach's Alpha in die huidige steekproef was 0.88) en die rekenaarspeletjie-ervaring is geassesseer. Boonop is die World of Warcraft Spesifieke Problematiese Gebruik-Engagement-vraelys (WoW-SPUQ), bestaande uit 27 items, gegradeer op 'n skaal van 1 = "stem heeltemal nie saam" tot 7 = "stem heeltemal saam" (Peters & Malesky, 2008; Cronbach's Alpha in die huidige steekproef was 0.89) is slegs deur die WoW-groep ingevul. Verder, die Barratt Impulsivity Scale (BIS-11; Patton & Stanford, 1995; Cronbach’s Alpha in the present sample was 0.85) was administrated as a measure of impulsivity (30 items are scored on a scale, ranging from 1 = “rarely/never” to 4 = “almost always/always”). With this scale, three second order factors can be assessed: attentional impulsivity is defined as an inability to focus attention or concentrate; motor impulsiveness involves acting without thinking, while non-planning impulsiveness involves a lack of “futuring” or forethought (Stanford et al., 2009). Interne konsekwenthede vir die subskale in die huidige studie was onderskeidelik 0.73, 0.69 en 0.69.
3.1.3. prosedure
Die deelnemers het aan 'n groot longitudinale studie deelgeneem om biologiese faktore naas sielkundige veranderlikes en hul rol vir IGD te ondersoek. Vir die huidige studie is slegs die data van die eerste meetpunt gebruik om die bevindinge van studie 1 te toets en te herhaal (om die Duiwel se bors-eksperiment vir 'n tweede keer te voltooi (T2) is duidelik nie vergelykbaar met om naïef daarmee te wees soos in studie 1 ). Die vraelyste en die eksperiment is in dieselfde volgorde as in studie 1 voltooi. In vergelyking met studie 1 is deelnemers in studie 2 egter die bedrag geld betaal wat hulle in die “Duiwel se bors”-eksperiment gewen het en hulle is oor hierdie feit ingelig. voor die voltooiing van die eksperiment.
3.1.4. Statistiese ontledings
Die data-assessering is analoog aan studie 1 uitgevoer.
3.2. Resultate
Die OGAS-telling en die aanlyn-speletjie-ure per week was nie-normaal versprei in die groepe manlike en vroulike kontroledeelnemers. Verder was die s-IAT telling en ouderdom nie-normaal versprei in die groep vroulike kontrole deelnemers. Die korrelasie tussen GAIN en die s-IAT-telling in die groep manlike WoW-spelers is eensydig getoets, gebaseer op die bevindinge in studie 1.
Beskrywende statistieke vir beheerdeelnemers en WoW-spelers word in Tabel 3. Here male and female control participants had significantly lower gaming experience, online gaming hours per week, and OGAS scores, compared to male and female WoW players (see Tabel 3). Verder het vroulike WoW-spelers aansienlik hoër tellings op die s-IAT getoon, in vergelyking met vroulike kontrole deelnemers. Alle ander veranderlikes het nie betekenisvol verskil tussen kontroledeelnemers en die WoW-spelers nie.
Tabel 3
Gemiddelde, standaardafwykings (SD), moontlike/werklike omvang, t-/U value and significance (p) for differences in means between the control participants and WoW group for the variables gaming experience (years), online gaming hours per week, GAIN, s-IAT, OGAS, WoW-SPUQ and BIS-11.
| Kontrole groep | WoW spelers | Moontlike omvang | Werklike omvang | t-/U waarde | p | |||
|---|---|---|---|---|---|---|---|---|
| beteken | SD | beteken | SD | |||||
| Manlike deelnemers | ||||||||
| Spelkundigheid (jare) | 9.49 | 6.81 | 14.29 | 4.85 | - | 0-22 / 6-25 | − 3.369 | 0.001 |
| Aanlyn speletjie-ure per week | 1.18 | 2.11 | 19.71 | 11.44 | - | 0-9 / 0-50 | 30.0 | <0.001 |
| GAIN | 450.77 | 39.10 | 443.04 | 54.30 | 0-900 | 370-510 / 305-525 | 0.678 | 0.500 |
| s-IAT | 21.67 | 6.53 | 23.79 | 6.90 | 12-60 | 12-42 / 14-41 | − 1.280 | 0.205 |
| OGAS | 8.67 | 2.39 | 15.79 | 5.85 | 7-35 | 7-17 / 9-29 | 94.5 | <0.001 |
| WoW-SPUQ | - | - | 87.57 | 23.26 | 27-189 | –/53–134 | - | - |
| BIS-11 totaal | 65.00 | 13.39 | 64.63 | 8.94 | 30-120 | 40-99 / 53-90 | 0.125 | 0.901 |
| BIS-11 aandagtig | 17.13 | 4.95 | 16.57 | 2.85 | 8-32 | 8-30 / 12-21 | 0.579 | 0.565 |
| BIS-11 motor | 23.16 | 4.81 | 22.43 | 3.66 | 11-44 | 14-35 / 16-33 | 0.671 | 0.504 |
| BIS-11 nie-beplanning | 24.71 | 5.32 | 25.74 | 4.77 | 11-44 | 14-40 / 16-40 | − 0.803 | 0.425 |
| Vroulike deelnemers | ||||||||
| Spelkundigheid (jare) | 3.86 | 5.76 | 11.50 | 5.29 | - | 0-15 / 1-20 | − 4.557 | <0.001 |
| Aanlyn speletjie-ure per week | 0.09 | 0.43 | 17.56 | 9.06 | - | 0-2.5 / 1-37.5 | 1.5 | <0.001 |
| GAIN | 429.74 | 39.98 | 439.06 | 58.72 | 0-900 | 330-510 / 295-510 | − 0.678 | 0.501 |
| s-IAT | 18.58 | 4.99 | 21.44 | 5.24 | 12-60 | 13-36 / 14-30 | 199.5 | 0.047 |
| OGAS | 7.11 | 0.51 | 13.50 | 3.69 | 7-35 | 7-10 / 9-21 | 4.0 | <0.001 |
| WoW-SPUQ | - | - | 81.63 | 22.42 | 27-189 | −/50–119 | - | - |
| BIS-11 totaal | 61.25 | 9.14 | 61.73 | 6.16 | 30-120 | 37-87 / 53-77 | − 0.187 | 0.852 |
| BIS-11 aandagtig | 16.61 | 3.55 | 17.06 | 3.38 | 8-32 | 10-25 / 10-22 | − 0.438 | 0.663 |
| BIS-11 motor | 21.08 | 3.93 | 21.80 | 3.97 | 11-44 | 12-31 / 17-29 | − 0.592 | 0.557 |
| BIS-11 nie-beplanning | 23.97 | 4.16 | 23.31 | 2.70 | 11-44 | 13-35 / 17-27 | 0.584 | 0.562 |
Note: Mann-Whitney-U-Test was conducted for comparing the means of non-normally distributed variables. Results are depicted in italics in the table.
3.2.1. Korrelasie-ontledings
Vir die groepe manlike of vroulike kontrole deelnemers was ouderdom van deelnemers nie betekenisvol gekorreleer met GAIN, s-IAT of die OGAS telling nie. Alle ander korrelasies word in Tabel 4. Here, GAIN was not significantly linked neither to the s-IAT nor to the OGAS score for male and female participants. Furthermore, the s-IAT score was positively linked to the BIS-11 subscale attentional impulsiveness in male control participants. All significant correlations in Tabel 4 remained significant after the inspection of the BCa 95% confidence intervals.
Tabel 4
Spearman and Pearson correlations for the variables GAIN, s-IAT, OGAS and BIS-11 for the group of control participants, splitted in males and females.
| GAIN | s-IAT | OGAS | BIS-11 totaal | BIS-11 aandagtig | BIS-11 motor | |
|---|---|---|---|---|---|---|
| Manlike deelnemers | ||||||
| GAIN | 1 | |||||
| s-IAT | − 0.053 | 1 | ||||
| OGAS | 0.238 | 0.139 | 1 | |||
| BIS-11 totaal | 0.020 | 0.248 | 0.349⁎ | 1 | ||
| BIS-11 aandagtig | 0.109 | 0.426⁎⁎ | 0.301 | 0.866⁎⁎ | 1 | |
| BIS-11 motor | − 0.064 | 0.094 | 0.338⁎ | 0.843⁎⁎ | 0.612⁎⁎ | 1 |
| BIS-11 nie-beplanning | 0.095 | 0.143 | 0.198 | 0.906⁎⁎ | 0.707⁎⁎ | 0.660⁎⁎ |
| Vroulike deelnemers | ||||||
| GAIN | 1 | |||||
| s-IAT | 0.118 | 1 | ||||
| OGAS | − 0.088 | 0.257 | 1 | |||
| BIS-11 totaal | − 0.139 | 0.232 | 0.156 | 1 | ||
| BIS-11 aandagtig | 0.161 | 0.282 | − 0.022 | 0.749⁎⁎ | 1 | |
| BIS-11 motor | − 0.219 | 0.201 | 0.292 | 0.764⁎⁎ | 0.312 | 1 |
| BIS-11 nie-beplanning | − 0.138 | 0.118 | − 0.119 | 0.868⁎⁎ | 0.531⁎⁎ | 0.478⁎⁎ |
Spearman-korrelasies word uitgebeeld in Italic.
n(mannetjies) = 39, n(mannetjies, BIS-11) = 38, n(vroue) = 38, n(vroue, BIS-11) = 36.
Vir die groep manlike en vroulike WoW-spelers was ouderdom nie betekenisvol gekorreleer met GAIN, s-IAT, OGAS of die WoW-SPUQ-telling nie. Alle ander korrelasies word in Tabel 5. Hier was GAIN negatief geassosieer met die s-IAT, asook die WoW-SPUQ-telling slegs in die groep manlike WoW-spelers. Hierdie korrelasies het egter slegs 'n neiging na betekenis getoon (r = − 0.30, p = 0.063, eensydige toets en r = − 0.313, p = 0.104, tweesterttoets). Alle betekenisvolle korrelasies het betekenisvol gebly na die inspeksie van die BCa 95% vertrouensintervalle.
Tabel 5
Spearman and Pearson correlations for the variables GAIN, s-IAT, OGAS, the WoW-SPUQ score and BIS-11 for the group of WoW players, splitted in males and females.
| GAIN | s-IAT | OGAS | WoW- SPUQ | BIS-11 totaal | BIS-11 aandagtig | BIS-11 motor | |
|---|---|---|---|---|---|---|---|
| Manlike deelnemers | |||||||
| GAIN | 1 | ||||||
| s-IAT | − 0.296 | 1 | |||||
| OGAS | − 0.105 | 0.776⁎⁎ | 1 | ||||
| WoW-SPUQ | − 0.313 | 0.688⁎⁎ | 0.742⁎⁎ | ||||
| BIS-11 totaal | 0.025 | 0.197 | 0.284 | 0.023 | 1 | ||
| BIS-11 aandagtig | 0.054 | − 0.011 | 0.019 | − 0.219 | 0.658⁎⁎ | 1 | |
| BIS-11 motor | − 0.038 | 0.170 | 0.231 | 0.187 | 0.761⁎⁎ | 0.218 | 1 |
| BIS-11 nie-beplanning | 0.033 | 0.220 | 0.312 | 0.027 | 0.892⁎⁎ | 0.451⁎ | 0.521⁎⁎ |
| Vroulike deelnemers | |||||||
| GAIN | 1 | ||||||
| s-IAT | 0.026 | 1 | |||||
| OGAS | − 0.024 | − 0.067 | 1 | ||||
| WoW-SPUQ | − 0.199 | 0.144 | 0.676⁎⁎ | ||||
| BIS-11 totaal | 0.048 | 0.080 | − 0.614⁎ | − 0.157 | 1 | ||
| BIS-11 aandagtig | − 0.139 | 0.194 | − 0.260 | 0.054 | 0.504 | 1 | |
| BIS-11 motor | 0.266 | − 0.013 | − 0.676⁎⁎ | − 0.305 | 0.845⁎⁎ | 0.170 | 1 |
| BIS-11 nie-beplanning | 0.012 | − 0.166 | 0.057 | 0.256 | 0.420 | − 0.222 | 0.250 |
For male participants, the correlation between the GAIN in the experiment and the s-IAT score was tested one-sided.
n(mannetjies) = 28, n(mannetjies, BIS-11) = 27, n(vroue) = 16, n(vroue, BIS-11) = 15.
3.2.2. Manipulasiekontrole van die “Duiwel se bors”-eksperiment as 'n maatstaf van implisiete leer
Die resultate van die herhaalde maatreëls ANOVA het nie 'n betekenisvolle gemiddelde verskil tussen die GAIN tydens die eerste 18 en die laaste 18 proewe van die "Duiwel se bors"-eksperiment in die groep mans getoon nie (F(1, 38) = 1.949, p = 0.171; M1 = 232.56 en M2 = 218.21) en vroulik (F(1, 37) = 0.594, p = 0.446; M1 = 221.18 and M2 = 209.87) control participants. For the whole sample of control participants the results remained non-significant (F(1,76) = 2.102, p = 0.151), whereas in the whole sample of WoW players the results gained significance (F(1,43) = 4.298, p = 0.044) (see Fig 3). For the group of male WoW players, the difference between trials 1–18 and 19–36 reached significance (F(1,27) = 5.377, p = 0.028, M1 = 235.54 and M2 = 205.54; hence with a lower outcome in M2 compared to M1), whereas for female WoW players it was non-significant (F(1,15) = 0.295, p = 0.595, M1 = 225.31 en M2 = 213.75).
Betekenis en die standaardfout vir die GAIN tydens die eerste 18 vs. die laaste 18 proewe van die “Duiwel se bors” eksperiment, vir kontrole deelnemers (linker grafiek) en WoW-spelers (regter grafiek). MU = geldeenhede.
3.3. bespreking
The aim of study 2 was to replicate the results of study one, by comparing WoW players and control participants. The negative correlations between GAIN and s-IAT and WoW-SPUQ scores showed a trend towards significance only in the group of male WoW players. However, the very small sample of male WoW players (n = 28) might deliver an explanation for the weaker effects. The manipulation check only showed a significant difference between the GAIN in the first and last 18 trials in the group of male WoW players, where participants showed lower gains in the second part of the experiment compared to the first part. We would like to remind the reader that participants in study 2 were paid the amount of money, which they won during the experiment and that they were aware of this fact before starting the experiment. Thus, in this case the extrinsic motivation of the participants might have been higher, compared to study 1. In fact, comparing the means of the GAIN between the Gamescom participants and the male WoW players, it is obvious that even though WoW-players did worse in the second part of the experiment, compared to the first part of the experiment, they still won more in total than male Gamescom participants (see Tabel 1, Tabel 3: M = 413.61 for Gamescom participants and M = 443.04 for male WoW players). Thus, in order to control for a potential interfering effect of motivation, we conducted an additional analysis, using the Unified-Motive-Scale-10 (UMS-10; Schönbrodt & Gerstenberg, 2012). The USM-10 data was available as a part of the bigger longitudinal study.
3.3.1. Additional analyses
In particular, we conducted a partial correlation with the variable achievement motivation (UMS-10; Schönbrodt & Gerstenberg, 2012, Cronbach’s Alpha in the present study was 0.89), the s-IAT, WoW-SPUQ scores and the GAIN in study 2. The association between s-IAT and GAIN increased from r = − 0.296, p = 0.063 (see Tabel 5; one-tailed test) to r = − 0.322, p = 0.054 (one-tailed test). The association between WoW-SPUQ and GAIN also increased from r = − 0.313, p = 0.104 (see Tabel 5; two-tailed test) to r = − 0.354, p = 0.082 (two-tailed test). With respect to female WoW players and control participants, the correlations between the s-IAT, WoW-SPUQ score and GAIN remained non-significant after controlling for motivation.
4. Study 3
The focus of study 3 was to test the association between PIU, IGD and impulsivity/risk-taking by using both experimental and self-report measures.
4.1. metodes
4.1.1. deelnemers
After the exclusion of five participants with missing data and one participant due to responses out of the range (e.g. 200 h of computer gaming per week) the sample for the current study resulted in N = 94 participants (33 males). Most of them were psychology students at Ulm University, Ulm, Germany. The mean age of the total sample was M = 23.48 (SD = 3.55). Regarding their education, 27% reported having university or polytechnic degree, another 67% reported having A-level or vocational baccalaureate diploma, 6% of participants (n = 6) did not answer questions on their education.
4.1.2. maatreëls
The s-IAT (Pawlikowski et al., 2013; Cronbach’s Alpha in the present sample was 0.81), the OGAS (modified version of the GAS by Lemmens et al., 2009; Cronbach’s Alpha in the present sample was 0.81), BIS-11 (Patton & Stanford, 1995; Cronbach’s Alpha in the present sample was 0.80) and the overall risk-taking (The German Socio-Economic Panel, SOEP; Siedler et al., 2008) were assessed. The internal consistencies for the BIS-11 subscales were as follows: attentional impulsiveness 0.70, motor impulsiveness 0.70 and non-planning impulsiveness 0.39. Furthermore, the “Devil’s chest” experiment was slightly adjusted to measure impulsivity/risk-taking (compared to studies 1 and 2, here, the position of the “devil” was completely randomized among all of the trials, thus, learning was not possible). Here, the mean number of voluntarily opened boxes per trial (MNOB) was used as a measure of impulsivity/risk-taking. This is in line with the study by Eisenegger et al. (2010).
4.1.3. prosedure
The questionnaires and the experiment were completed in the same order as in studies 1 and 2, however, here participants filled in the questionnaires on a computer screen. In this study participants received compensation (Amazon voucher or course credits) for their participation in the study, but they were not paid the particular amount of money, that they won in the computer experiment. Participants were informed about this procedure prior to completing the experiment.
4.1.4. Statistiese ontledings
The statistical analyses were conducted analogously to studies 1 and 2.
4.2. Resultate
Of note, the variables online gaming hours per week and the OGAS score were not normally distributed. Descriptive statistics are reported in Tabel 6. Participants had some expertise in gaming in terms of gaming expertise in years, but the actual time spent on online gaming is very low. Analog to study 2, here we compared, if male and female participants differed regarding the variables, depicted in Tabel 6. Significant differences were observed with the variables gaming expertise (years) (U(33,61) = 385.0, p < 0.001), online gaming hours per week (U(33,61) = 663.5, p < 0.001), risk-taking (self-report) (U(33,61) = 732.0, p < 0.05) and OGAS (U(33,61) = 562.5, p < 0.001), where male participants scored higher than female participants.
Tabel 6
Means, standard deviations (SD) and possible/actual range for the variables gaming experience (years), hours gaming per week, risk taking (self-report), s-IAT, OGAS, BIS-11 and MNOB.
| beteken | SD | Moontlike omvang | Werklike omvang | |
|---|---|---|---|---|
| Spelkundigheid (jare) | 6.31 | 6.51 | - | 0-21 |
| Aanlyn speletjie-ure per week | 0.56 | 1.86 | - | 0-15 |
| Risiko neem (selfverslag) | 5.10 | 1.82 | 0-10 | 1-9 |
| s-IAT | 22.99 | 5.71 | 12-60 | 12-42 |
| OGAS | 8.00 | 2.05 | 7-35 | 7-18 |
| BIS-11 totaal | 61.37 | 9.17 | 30-120 | 44-84 |
| BIS-11 aandagtig | 16.54 | 3.47 | 8-32 | 10-28 |
| BIS-11 motor | 21.68 | 4.33 | 11-44 | 14-35 |
| BIS-11 nie-beplanning | 23.15 | 3.45 | 11-44 | 17-32 |
| MNOB | 4.90 | 0.79 | 0-10 | 3.22-7.5 |
4.2.1. Korrelasie-ontledings
Age was correlated with the OGAS score (ρ = 0.24, p < 0.05). The correlation between MNOB with the OGAS score also reached significance (ρ = 0.21, p < 0.05). After controlling for age, the correlation between MNOB and the OGAS score increased to r = 0.37, p < 0.01 (r = 0.45, p < 0.05 in males and r = 0.28, p < 0.05 in females). All other correlations are presented in Tabel 7.
Tabel 7
Spearman and Pearson correlations for the variables MNOB, risk taking (self-report), s-IAT, OGAS and BIS-11.
| MNOB | Risiko neem (selfverslag) | s-IAT | OGAS | BIS-11 totaal | BIS-11 aandagtig | BIS-11 motor | |
|---|---|---|---|---|---|---|---|
| MNOB | 1 | ||||||
| risiko neem (selfverslag) | 0.086 | 1 | |||||
| s-IAT | 0.115 | − 0.124 | 1 | ||||
| OGAS | 0.209⁎ | 0.092 | 0.235⁎ | 1 | |||
| BIS-11 totaal | 0.316⁎⁎ | 0.458⁎⁎ | 0.150 | 0.283⁎⁎ | 1 | ||
| BIS-11 aandagtig | 0.284⁎⁎ | 0.196 | 0.345⁎⁎ | 0.296⁎⁎ | 0.770⁎⁎ | 1 | |
| BIS-11 motor | 0.236⁎ | 0.576⁎⁎ | − 0.018 | 0.261⁎ | 0.847⁎⁎ | 0.443⁎⁎ | 1 |
| BIS-11 nie-beplanning | 0.257⁎ | 0.299⁎⁎ | 0.075 | 0.148 | 0.821⁎⁎ | 0.487⁎⁎ | 0.551⁎⁎ |
Note: Spearman correlations are depicted in italics.
4.2.2. Manipulation check of the “Devil’s chest” experiment as a measure of impulsivity/risk-taking:
MNOB was positively correlated to the BIS-11 score of the participants (see Tabel 7), therefore the current measure is clearly associated with impulsive behavior. There was no significant correlation between MNOB and the self-report measure of overall risk-taking (see Tabel 7). Analogously to studies 1 and 2, we compared the GAIN in the first and last 18 trials to rule out the role of learning effects. No significant differences could be found for male (F(1,32) = 2.365, p = 0.134, M1 = 219.24 and M2 = 235.61) or female participants (F(1,60) = 0.155, p = 0.695, M1 = 224.02 and M2 = 220.57). The results for the whole sample also did not gain significance (F(1,93) = .265, p = 0.608) (see Fig 4).
Betekenis en die standaardfout vir die WINS in die eerste 18 proewe teenoor die WINS in die laaste 18 proewe van die "Duiwel se bors" eksperiment. MU = geldeenhede.
5. General discussion
In the following, a summary of the results of studies 1, 2 and 3 is provided along with a discussion on their contribution to the field.
In study 1, higher s-IAT scores were associated with worse performance on the implicit learning task among male participants, with a proneness to IGD. The OGAS score of the participants, however, was not significantly associated with the variable GAIN (although there was a trend towards significance). In study 2 we aimed at replication of results of study 1 in a group of WoW players and control participants. Here, the gender of the participants was also taken into consideration. High s-IAT scores, as well as high WoW-SPUQ scores showed a trend towards low GAIN in the experiment only in the group of male WoW gamers (r = − 0.322, p = 0.054, eensydige toets en r = − 0.354, p = 0.082, two-tailed test, respectively). The OGAS score was again not linked to GAIN in neither of the groups. In study 3, in a student sample, the experimental measure of risk taking, MNOB, was positively linked to the OGAS score, but not the s-IAT score, after controlling for age.
To sum up, it seems, that excessive use of the Internet is associated with deficiencies in implicit learning abilities. This association was observed with the s-IAT scores and the WoW-SPUQ score, but not OGAS scores in the current study. Existing literature delivers results supporting both: deficits in decision-making among problematic Internet users (e.g. Sun et al., 2009), as well as among excessive online gamers (e.g. Yao et al., 2014). Moreover, recently a new theoretical model I-PACE (Interaction of Person-Affect-Cognition-Execution) was proposed by Brand et al. (2016), which highlights the role of reduced executive functioning and impaired decision making for the development of specific PIU. The stronger effect found for the WoW-SPUQ score, compared to the OGAS score might reflect the choice of a more specific measurement to assess WOW addiction. However, further investigations are needed.
The fact that the association between PIU and reduced implicit learning ability in the present study was found only in the group of male participants with (proneness to) IGD (study 1 and 2) might further help explain the in part conflicting results on the relation between decision making and PIU in the literature (e.g. Ko et al., 2010, Sun et al., 2009). This association, however, seems plausible as studies suggest that IGD is primarily a male kind of addiction (e.g. Rumpf et al., 2011).
Met inagneming van Hipotese 3, some significant associations could be found between impulsivity, measured with BIS-11, and PIU/IGD (studies 2 and 3), which is consistent with findings in the literature (e.g. Lee et al., 2012). Whereas the self-report measure of risk-taking (SOEP) was not linked to PIU/IGD in neither of the studies, the experimental measure of risk-taking/impulsivity was associated with the OGAS score (study 3), but not with the s-IAT score. This particular difference might be due to issues, concerning the reliability of the measures. While self-reported risk-taking was assessed with a single item, the experimental measure of risk-taking is expected to deliver objective and reliable data. With regard to the association between MNOB and the OGAS score, the Devil’s chest experiment (version 2, where the boxes were completely randomized over the 36 trials) might cover a more specific side of impulsivity (like risk-taking), which better characterizes IGD than generalized PIU. However, Ko et al. (2010) showed no difference in risk-taking (measured with the BART) between Internet addicted subjects with a tendency towards IGD and control participants. Thus, this association needs further investigation.
The manipulation check of the “Devil’s chest” experiment to measure implicit learning was successful in study 1, thus, we assume that participants could implicitly extract and learn strategies to gain more money throughout the experiment. However, in study 2 no significant difference could be observed between the gain in trials 1–18 and 19–36 with the exception of the group of male WoW players, where participants showed lower gains in the second part of the experiment. Here, we showed in additional analyses that after controlling for achievement motivation, the negative association between GAIN and the s-IAT/WOW-SPUQ score got stronger. Hence, we suggest that in study 2 the implicit learning effect was overshadowed by the effects of achievement motivation, since participants were payed the amount of money that they won in the experiment. At this point, it needs to be noted that UMS-10 measures trait achievement motivation, thus, the tendency to be motivated towards bigger achievements in general, and not a state, thus, the motivation to win more in this particular experiment. However, by controlling for UMS-10 achievement motivation, we considered the role of individual differences in trait motivation for the performance in the Devil’s chest task within the sample.
The validation of the second version of the “Devil’s chest” experiment to measure risk taking/impulsivity, showed that the mean number of voluntarily opened boxes (MNOB) was not significantly linked to the self-report measure of risk-taking. This might be due to the fact that the SOEP assesses general risk taking with only one item, which in turn might have a negative influence on its reliability. However, MNOB was associated with the total BIS-11 score, as well as the subscales attentional, motor and non-planning impulsivity. These results are consistent with validation studies on similar behavioral measures of risk-taking like the BART (Lejuez et al., 2002).
In the following, some of the strengths and limitation of the presented research will be discussed. One strength of the present investigation is that the role of gender was taken into consideration. Even though gender differences have been described in the context of IGD and PIU (Rumpf et al., 2011), not many investigations have particularly assessed the role of gender when examining the association between PIU/IGD and implicit learning/risk taking, as in the present study. Moreover, in study 2 the group of WoW players was recruited, using strict criteria, and not by simply applying a cut-off value in a self-report questionnaire such as the OGAS. The use of a cut-off value is problematic, since many of the cut-offs, used in studies, are sometimes arbitrarily chosen and have not been appropriately validated in a clinical setting. Last, in studies 1 to 3 we assessed both PIU and IGD, which allows to further examining the similarities and unique characteristics of both disorders.
Limitations include the low number of participants per group, especially in study 2, and participants’ low age. Thus, future studies should examine more representative samples. Second, a comparison group of excessive Internet users, who were non-WoW players, was not included. Furthermore, the results of the study are based on correlational analyses, thus, no interpretations about causality are possible.
6. Gevolgtrekking
In sum, we were able to show that PIU is robustly associated with poor implicit learning abilities in male (WoW) gamers. This finding could be observed in two independent samples in the present study. Furthermore, a little bit weaker association between WOW-SPUQ and deficient implicit learning could be observed in the group of male WoW players. Moreover, higher scores on the OGAS were associated with higher tendencies for risk-taking behavior in study 3. The gender specific effect in studies 1 and 2 were further discussed in the study.
Rol van befondsingsbronne
Christian Montag is awarded a Heisenberg-grant by the German Research Foundation (MO 2363/3-1). Furthermore, the present study is funded by a research grant on Internet and computer gaming addiction awarded to Christian Montag by the German Research Foundation (MO 2363/2-1). The German Research Foundation had no role in the study design, collection, analysis or interpretation of the data, writing the manuscript, or the decision to submit the paper for publication.
bydraers
CM and RS designed the study. RS, BL and CM recruited and tested the participants. RS conducted the analyses and wrote the manuscript. BL double checked the statistical analyses and reviewed the manuscript. SM programmed the experimental tasks (versions 1 and 2) and gave a thorough feedback on the manuscript, after reviewing it. MR reviewed the manuscripts critically. All authors contributed to and have approved the final manuscript.
Bedankings
We thank Ralf Reichert from Turtle Entertainment for giving us the chance to conduct our experiment at the GamesCom 2013. However, Turtle Entertainment did not make any profit or have an influence on the execution of the study.
We also would like to thank Maximilian Sieber and Otilia Pasnicu, who recruited and tested the participants for study 3 as part of their Bachelor theses.
voetnote
1Throughout the present paper we will be using the term Problematic Internet Use (PIU) as a substitute for Internet addiction, as there is currently no existing official diagnosis in DSM-5 and ICD 10. As Internet Gaming Disorder (IGD) was included in the Appendix of DSM-5, this term will be used as a synonym of Online Gaming addiction. Please note that not every study, that we cite in the present article, investigated IGD, using the criteria suggested in DSM-5.
2Of note, the “devil” box was not programmed to appear in position 1, because this would have terminated the current trial without giving participants the opportunity to choose if they wanted to proceed by opening another box.
Verwysings
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