Personality and Gaming

In general, the preferred model for researching personality in gamers has been the Five Factor Model (FFM; ^{Costa & McCrae, 1985}). However, the results regarding FFM traits are highly heterogeneous and, in many cases, contradictory. A systematic review and meta-analysis conducted by ^{Akbari et al. (2021}), for instance, revealed a dispersion of results, with no clear pattern linking FFM traits to gaming. The only trait that showed some consistency across studies was conscientiousness, which was negatively associated with gaming. This variability may be due to various factors: measurement instruments are heterogeneous, samples are highly diverse, and gender and age variables are generally not statistically controlled. This last point is particularly important, as the state of the art suggests that both personality and gaming vary according to gender and age (e.g., ^{De la Iglesia, 2024}a; ^{Jeng & Teng, 2008}; Teng et al., 2012), meaning that these pre-existing differences could affect the observed results. Although some previous studies have focused on age and gender differences in relation to gaming and personality traits, the present work does not aim to analyse those differences. Instead, it seeks to statistically control for gender and age variables in order to explore the strength of the link between personality traits and gaming, beyond any pre-existing differences that may be associated with participants’ gender and age.

Based on these considerations, the aim of this study is to examine personality traits in gamers. Initially, the objective is to compare personality traits between gamers and non-gamers to determine whether differences exist between these two groups. In addition, the study seeks to explore the relationship between personality and several variables associated with gaming, such as hours of gameplay, preferred video game, self-perceived performance, interaction with other players, and gaming experiences.

The following section summarises the background related to FFM traits and variables associated with gaming.

Extraversion

Numerous studies have examined the relationship between extraversion and gaming. Some findings suggest that gamers exhibit higher levels of extraversion compared to non-gamers (^{Estalló Martí, 1994}; ^{McClure & Mears, 1986}; ^{Teng, 2008}). However, ^{Braun et al. (2016}) found that extraversion was higher in non-gamers and in moderate gamers compared to excessive gamers. Regarding the relationship between extraversion and hours of use, results are also mixed. Teng et al. (2012) found no association, ^{Potard et al. (2020}) observed that less extraverted individuals played less, and ^{Montag et al. (2021}) reported a negative association.

Problematic gaming (sometimes referred to as addiction, pathological use, or negative gaming experiences) generally shows a negative relationship with extraversion (^{Braun et al., 2016}; ^{Charlton & Danforth, 2010}; ^{Chew, 2022}; ^{Dieris-Hirchea et al., 2020}; ^{Jeong & Lee, 2015}; ^{López-Fernández et al., 2020}; ^{Medina-Valdivia & Ponce-Eguren, 2021}), although some studies report no association (^{Collins et al., 2012}; ^{Şalvarli & Griffiths, 2019}). Conversely, ^{Huh and Bowman (2008}) found a positive relationship.

In terms of motivations for play, extraverts are more inclined to seek socialisation, achievement (performance in the video game), teamwork, adventure, and relaxation, and are less likely to seek immersion (^{Jeng & Teng, 2008}; ^{Park et al., 2011}; ^{Winther, 2010}). Within games, extraverts tend to engage in social behaviours, help others, and display fandom for game content (^{Worth & Book, 2014}). In the context of World of Warcraft (WOW) ², ^{Yee et al. (2011}) observed that more extraverted gamers participated more in group activities (dungeons, guilds, or clans) and less in solitary activities (exploring, cooking, fishing). Regarding preferred genres, ^{Peever et al. (2012}) reported that extraverts prefer casual, party, music, and strategy games, while ^{López-Fernández et al. (2020}) found associations with hardcore genres such as action, shooters, and sports.

Neuroticism

In some research, no differences have been reported between gamers and non-gamers in neuroticism (^{Teng, 2008}). ^{Braun et al. (2016}), on the contrary, found that neuroticism was higher among non-gamers and those who played excessively in contrast to those who played moderately. Regarding gaming hours, positive associations with neuroticism have been found (Braun et al., 2016; ^{Jeong & Lee, 2015}; Teng et al., 2012), although ^{Collins et al. (2012}) reported no relationship. As for problematic use, there is a marked tendency to report positive associations with neuroticism (^{Akbari et al., 2021}; ^{Charlton & Danforth, 2010}; ^{Chew, 2022}; ^{Dieris-Hirchea et al., 2020}; ^{Gervasi et al., 2017}; ^{Huh & Bowman, 2008}; ^{Medina-Valdivia & Ponce-Eguren, 2021}; Şalvari & Griffiths, 2019) with isolated results reporting no relationship (Gervasi et al., 2017; ^{López-Fernández et al., 2020}; Şalvari & Griffiths, 2019).

On the other hand, those who score higher in neuroticism report playing to socialize and experience immersion (^{Winther, 2010}). Within the game, those with higher neuroticism exhibit more helping behaviors towards others and more fanaticism for game content (^{Worth & Book, 2014}). In the research by ^{Yee et al. (2011}) on WOW players, it was reported that those with higher neuroticism preferred more player versus player (PvP) activities. Regarding game genres, ^{Potard et al. (2020}) found that those who preferred action games showed higher neuroticism.

Conscientiousness

^{Teng (2008}) reported that gamers show more conscientiousness compared to non-gamers, and ^{Braun et al. (2016}) reported the opposite. On the other hand, this trait was found to be negatively associated with gaming hours (^{Montag et al., 2021}; ^{Potard et al., 2020}; Teng et al., 2012). Several studies found negative associations between conscientiousness scores and problematic use (^{Akbari et al., 2021}; Braun et al., 2016; ^{Chew, 2022}; ^{Dieris-Hirchea et al., 2020}; ^{López-Fernández et al., 2020}; ^{Medina-Valdivia & Ponce-Eguren, 2021}; ^{Wang et al., 2014}), while others found no relationship (^{Collins et al., 2012}; ^{Jeong & Lee, 2015}) or a positive one (^{Lehenbauer-Baum & Fohringer, 2015}).

^{Yee et al. (2011}) found that WOW players with higher conscientiousness tend to collect items, have more pets, cook more, fish more, and achieve more challenges. Those with low conscientiousness, in contrast, are more reckless and have a higher chance of their characters dying from falling from high places. Regarding game genres, those with higher conscientiousness tend to prefer racing, flying, and fighting games (^{Peever et al., 2012}).

Agreeableness

Agreeableness does not show differences between gamers and non-gamers (^{Teng, 2008}), and among gamers, a positive relationship was found with the number of hours played (Teng et al., 2012). Regarding problematic use, some studies found negative associations (^{Akbari et al., 2021}; ^{Charlton & Danforth, 2010}; ^{Chew, 2022}; ^{Collins et al., 2012}; ^{López-Fernández et al., 2020}; ^{Medina-Valdivia & Ponce-Eguren, 2021}; ^{Sánchez-Llorens et al., 2023}), while others found no relationship (^{Braun et al., 2016}; ^{Dieris-Hirchea et al., 2020}; ^{Jeong & Lee, 2015}).

Motives for play among those with high agreeableness are often socializing and adventure (^{Park et al., 2011}). Regarding performance-related motivation when playing, Park et al. (2011) reported a positive association with this trait, and ^{Winther (2010}) a negative one. Within the game, those with higher scores on this trait tended to help other players (^{Worth & Book, 2014}). Furthermore, WOW players who are highly agreeable prefer non-combative activities (exploring, crafting, events, cooking, fishing), and those with low agreeableness are more interested in killing, getting better equipment, and PvP activities (^{Yee et al., 2011}).

Openness to experience

Finally, ^{Teng (2008}) found that gamers show more openness to experience than non-gamers. ^{Braun et al. (2016}) found no differences between gamers and non-gamers in this trait. Some research found a positive association with the number of hours played (^{Teng et al., 2012}; ^{Witt et al., 2011}), and another found a negative one (^{Montag et al., 2021}). Regarding problematic use, no association was found with this trait (^{Dieris-Hirchea et al., 2020}; ^{Jeong & Lee, 2015}), or the association found was negative (^{Akbari et al., 2021}; ^{Braun et al., 2016}; ^{Wang et al., 2014}). ^{López-Fernández et al. (2020}) reported a positive association in the case of women.

In relation to motives for play, those with more openness to experience seek to experience immersion, discovery, role-playing, and socializing (^{Jeng & Teng, 2008}; ^{Winther, 2010}; ^{Worth & Brook, 2014}), and within the game, they tend to help other players (Worth & Book, 2014). WOW players with high openness to experience tend to have more characters, explore more, and participate in non-combative activities (^{Yee et al., 2011}). Regarding video game genres, those with more openness tend to prefer adventure, action, platform, logic, and social simulation games (^{López-Fernández et al., 2020}; ^{Peever et al., 2012}).

Argentine Gamers

In Argentina, research on the psychological aspects linked to gaming is in an early stage of development, which includes the validation of scales to assess gaming experiences and video game addiction, as well as the study of gaming variables according to sociodemographic characteristics and the link between gaming and mental health (e.g., ^{De la Iglesia, 2024}a, ²⁰²⁴b; ^{González-Caino et al., 2022}; ^{Jordan-Muiños & Simkin, 2022}). Locally, the international trend is replicated, with reports indicating that 18.5 million Argentines play video games (approximately 40 % of the population) and that the size of the video game industry is valued at USD 72 million (^{Gilbert, 2021}). These statistics describe a scene in which video games appear to constitute an aspect of daily life for almost half of the population. Therefore, their study is relevant both locally, for the generation of regional knowledge, and internationally, to contrast and deepen global understanding. According to the objectives expressed at the beginning of the introduction and the background research presented, the following hypotheses are proposed:

Procedure

The research employed a non-experimental, cross-sectional design, and data were collected through a non-probabilistic snowball sampling method via an online survey distributed through social networks, emails, and digital platforms. Participants had to meet the following inclusion criteria: (1) reside in Argentina, (2) be 18 years of age or older, and (3) play video games at least once a month -based on the suggestion by ^{Eklund (2016}) and ^{Kaye (2019)} regarding the use of sufficiently broad criteria that allow capturing the diversity of gamers and increasing the representativeness of those who play video games in the general population. In the case of the non-gamer sample, the inclusion criteria were the same except for criterion 3, as the aim was to include individuals who did not play video games. The non-gamer sample was only analysed for the first objective of differences between groups. Furthermore, all participants had to provide their informed consent to participate in the study, where information was given about the study's objectives, the possibility of refusing or interrupting their participation at any time, and the confidential treatment of the information. No incentives were provided for participation. All procedures respected the ethical guidelines and standards of the 1964 Declaration of Helsinki and its subsequent amendments, and of the National Council for Scientific and Technical Research (CONICET). The project was evaluated and approved by the Ethics Committee of the University of Palermo.

Participants

Sample consisted of 197 adults from the general population who indicated playing video games. The average age was 30.2 years (SD = 9.34; Min = 18; Max = 70), with 64.97 % identifying as male, 32.99 % as female, 1.52 % as non-binary, and 0.5 % preferring not to report their gender. Regarding gaming hours, the average was 13.3 hours per week (SD = 13.5). According to ^{Przybylski's (2014}) classification, 47.6 % were typical gamers, 37 % moderate gamers, and the remaining 15.3 % were heavy gamers. In 75.3 % of cases, the preferred video game was categorized as hardcore, with the remaining being casual video games. Regarding gaming performance, 29.1 % perceived it as low, 37.6 % as standard, and 33.3 % as high. As for online interaction with other players, 40.7 % reported not interacting, 21.2 % interacting a little, 17.5 % interacting quite a bit, and 20.6 % reported interacting a lot. For the first two analyses conducted, an additional sample of 91 non-gamers was evaluated (M _age= 33.4 years; SD = 11.1; Min = 19; Max = 66; 87.91 % female).

Materials

Sociodemographic Survey (ad hoc). Developed specifically for this study to gather basic sociodemographic information from participants, such as age, gender, and place of residence.

Gaming Survey (ad hoc). A survey was created with questions about the number of weekly gaming hours, preferred video game (categorized as casual or hardcore), self-perceived performance (a single six-option performance scale: 1: I'm very bad at playing to 6: I play spectacularly), and frequency of interaction with other players (no, a little, quite a bit, and a lot).

Gaming Experiences Scale (^{De la Iglesia, 2024}a). This instrument is a short and locally adapted version for the Argentine population of the Online Gaming Survey (^{Snodgrass et al., 2017}). It consists of 18 items answered on a six-option Likert scale (0: does not represent me at all to 5: completely represents me). It assesses positive experiences (strengthening bonds and increasing one's own skills, the possibility of achieving personal growth, and gamer identity as a way of life) and negative experiences (feeling of loss of control, social isolation, obsession, negative affectivity, withdrawal, problems in other areas of personal life, and exhaustion). Its psychometric analyses provided evidence of validity (exploratory and confirmatory factor analyses, convergent validity studies) and reliability (internal consistency analyses) that demonstrated the appropriateness of its composite scores. In the sample analysed here, the internal consistency was ω = .88 for positive experiences and ω = .85 for negative experiences.

Big Five Inventory (BFI; ^{John et al., 1991}). This 44-item instrument assesses the five major personality traits: extraversion (i.e., "...who is sociable"), agreeableness (i.e., "...who likes to cooperate with others"), conscientiousness (i.e., "...who does things efficiently"), neuroticism (i.e., "...who is depressive/sad"), openness to experience (i.e., "...who is curious about things"). It uses a five-point Likert scale of agreement (0: completely disagree to 4: completely agree). Studies conducted in Argentina verified the factorial validity for adolescent and adult non-clinical and military populations (^{Castro Solano & Casullo, 2001}). For this sample, adequate internal consistency values were obtained: extraversion ω = .78; agreeableness ω = .69; conscientiousness ω = .81; neuroticism ω = .82; openness to experience ω = .81.

Data Analysis

The analyses were performed with the original group sizes, without prior matching. The groups differed in size and gender composition due to the expected characteristics of the study population (^{Eklund, 2016}; ^{Vermeulen et al., 2011}). Given that these differences could influence the analyses, age and gender were included as covariates in all statistical models to control for their impact. In the case of the gender variable, it was dummy-coded representing the probability of being female. According to the number of weekly gaming hours, gamers were classified into typical (less than seven hours per week), moderate (between 8 and 21 hours per week), and heavy (more than 21 hours per week; ^{Przybylski, 2014}). Furthermore, the genre and characteristics of the video games preferred by each participant were identified, classifying them as hardcore (e.g., shooters, fighting games, action/adventure, survival, or strategy), that is, games with more content, with deeper and more detailed themes and narratives, requiring a greater amount of playing time both to learn and to play them, or casual (e.g., puzzles, word games), which are generally easier to play, with lighter content, and can be played intermittently without needing to invest a large and uninterrupted amount of playing time. This categorization follows the definitions proposed in previous studies (^{De Grove et al., 2015}; ^{Eklund, 2016}; ^{Kaye, 2019}). Self-perceived gaming performance was recategorized into three levels: low performance ("I'm very bad at playing," "I play quite badly," "I play ok"), standard performance ("I play well"), and high performance ("I play very well," "I play spectacularly"). Regarding gaming experiences, they were analyzed according to the two categories (positive and negative experiences) of the Gamer Experience Scale (^{De la Iglesia, 2024}a).

The statistical analyses used were Pearson's r, Student's t-test, one-way ANOVAs, and hierarchical multiple regressions. Multicollinearity was assessed using the Variance Inflation Factor (VIF). The obtained values were below 5, indicating a significant absence of collinearity among the predictors (^{Hair et al., 2010}). In addition, partial Pearson's r correlations and ANCOVAs were calculated to statistically control for the age and gender variables, which were introduced as covariates (^{De la Iglesia, 2024}a). The statistical software Jamovi version 2.2.5 (^{Jamovi, 2022}) was used.

Limitations and Future Lines of Research

This research presents some limitations that should be taken into account when considering the reported results. Firstly, the analysed sample is limited and non-probabilistic, which impacts the generalizability of the findings. Regarding the sample, the disparity in gender distribution between the gamer sample (largely composed of men) and the non-gamer sample (overrepresentation of women) could also be considered. However, it is important to note that the predominance of males in gamer samples and females in non-gamer samples is common when the gamers being studied are characterized by playing hardcore video games, as is the case with the majority of gamers in this sample (^{Eklund, 2016}; ^{Vermeulen et al., 2011}). To mitigate the possible impact of this disparity, gender was included as a covariate in all statistical analyses performed. Also, the measures of in-game performance and interaction were self-reports and may not accurately reflect actual achievements and interactions. Likewise, the absence of significant results when comparing gamers who preferred hardcore or casual video games could be due to the fact that this classification is too general. This could be addressed with genre classifications or scales that assess this aspect more specifically. Future lines of research could overcome these limitations with more representative randomized sampling and with measurements obtained directly from gameplay that are more precise. Additionally, more complex analyses could be tested, such as the study of personality profiles and explanatory models that posit mediating or moderating variables to explain the phenomenon, such as the models analysed by ^{López-Fernandez et al. (2021}). This research focused on normal personality traits, leaving the study of gaming and its relationship with pathological and positive personality traits pending.