Skip to main content

ORIGINAL RESEARCH article

Front. Psychol., 09 May 2024
Sec. Addictive Behaviors

Emotional analysis of multiplayer online battle arena games addiction

  • 1School of Design, Fujian University of Technology, Fujian, China
  • 2Faculty of Innovation and Design, City University of Macau, Macau, Macao SAR, China
  • 3School of Humanities, Fujian University of Technology, Fujian, China

Introduction: Multiplayer Online Battle Arena (MOBA) games have garnered widespread popularity as a form of recreational activity. The launch of League of Legends (LoL), a prominent MOBA game, has captivated the enthusiastic pursuit of gamers in the MOBA community. The surge in MOBA game fervor, coupled with the influence of personal emotions, can result in excessive engagement, ultimately leading to addiction.

Objective: This study aimed to investigate the moderating effects of visceral perception, behavior, and reflection on game players’ addiction within the framework of Leisure Theory (LT), Uses and Gratification Theory (UGT), and Emotional Design Theory (EDT).

Methods: A hypothesized theoretical model was developed and empirically evaluated based on 236 self-reported validated responses from MOBA gamers. SPSS (version 26) was employed for demographic analysis and game duration analysis. The measurement model and structural model analyses were conducted in two stages using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4.1.0 to validate the nine theoretical hypotheses.

Results: It has been observed that personal emotions significantly contributes to MOBA game addiction during gamers’ leisure time or moments of gratification. Specifically, a noteworthy connection exists between two dimensions, namely gamers’ behavior and reflection, demonstrating a positive correlation with gaming addiction. Without taking entertainment as a motivating factor, there is no significant relationship between gamers’ leisure-time and visceral perception.

Conclusion: This study enhances the theoretical model of gamers’ behavioral motives in engaging with MOBA gaming and contributes to the expansion of research on game addiction theory. These findings offer valuable theoretical insights for emotional design in games and the design of mechanisms for preventing game addiction.

Introduction

Video gaming has emerged as one of the most popular recreational activities globally (Griffiths et al., 2012; Pornpongtechavanich et al., 2022). Initially perceived as a mild leisure pursuit, video games have been demonstrated to possess addictive features, particularly in strategy video games like multiplayer online battle arena (MOBA) (Nuyens et al., 2016; Han et al., 2020). MOBA games constitute a significant segment of the rapidly expanding and captivating eSports genre, closely intertwined with players’ social experiences (Wang et al., 2023). This connection has led to widespread criticism of the genre, citing perceived adverse effects on players’ physical and psychological well-being, lifestyle, and work-study balance (T’ng et al., 2023). However, recent pro-game research on the genre has challenged these assumptions, highlighting MOBA games for their potential to foster cultural inclusiveness, enhance social connectedness, alleviate stress, boost cognitive skills, and facilitate skill transferability (Mora-Cantallops and Sicilia, 2018; Wang et al., 2023).

In 2021, Tencent officially launched the League of Legends (LoL) MOBA game in China, generating significant excitement among Chinese gaming enthusiasts (Ye, 2021). The integration of MOBA games with LoL PC players led to a surge in the MOBA game industry, further fueled by LoL’s recognition as an official medal sport at the Asian Games Hangzhou in 2022 (see official website). However, these developments heightened concerns among parents and other stakeholders about potential issues arising from the escalating popularity of this gaming craze (Lieberoth and Fiskaali, 2021). Empirical studies have identified various factors contributing to gaming addiction (Nuyens et al., 2016; Xia et al., 2019; Lieberoth and Fiskaali, 2021; Wut et al., 2021). MOBA games, such as LoL and Honor of Kings (HOK) in China, in particular, have gained notoriety for their adverse effects on gamers, including user retention problems (Wang et al., 2023) and the promotion of gaming disorder through frustration-induced continuance (T’ng et al., 2023). To address and manage gaming disorder more effectively, researchers have proposed theoretical models based on diverse perspectives and measurement methods.

Many studies have explored the personality characteristics of MOBA game players, their post-game gratification behaviors, and motivations for continued gaming. One study, drawing on communication theory, posited that not all MOBA game behaviors are consciously motivated (LaRose and Eastin, 2004). Recurrent behavior in stable environments can lead to habit formation, reducing the cognitive load associated with decision-making, and transforming outcome expectations into habits (De Grove et al., 2016). Another study, utilizing the Five Factor Model, maintained that MOBA game players’ traits of extraversion, agreeableness, and openness interact with in-game performance, affecting player behavior (Matuszewski et al., 2020).

Based on the premise, the behavior of MOBA gamers appears to be related to their personality, manifesting as various individual characteristics that can influence thinking and behaviors rooted in attitude, motivation, needs, and emotions, thereby impacting their external or internal behaviors (Wang and Yu, 2017). Furthermore, the gratification of MOBA game players with their in-game performance can unveil the correlation between emotional needs and behavioral intentions (Wut et al., 2021). Experimental and self-report measures have indicated that players display impulsiveness during MOBA gameplay, and this impulsiveness serves as a crucial indicator for identifying excessive involvement in MOBA games (Nuyens et al., 2016).

However, in advancing a tentative theory regarding eSports skills, Larsen (2020) employed a three-pronged approach involving discussion, reflection, and evaluations of players who watched 100+ hours of eSports events on social media. This inferential theory not only guided and enhanced gamer skills at competitive levels but also solidified the argument that theoretical modeling, coupled with empirical research, can enhance gamers’ behavior in MOBA games. Analyzing data from game players of TI4 (The International Dota 2 Championships), Xia et al. (2019) found that tactical awareness had a greater influence than manipulation skills in team games, as evidenced by Brown-Mood tests (Brown and Mood, 1951). However, Xia and colleagues did not delve into the influence of intrinsic factors, such as tactical awareness, on individual players’ game reflection level, operational skills, and in-game performance in non-tournament MOBA games. Additionally, certain studies have highlighted indispensable influences of factors like emotion, external environment, and system. Conducting an assessment of game and players’ experience using multiple system, user, and context influence parameters, Suznjevic et al. (2019) provided references for future Quality of Experience (QoE) assessment tools to analyze reports on MOBA gamers’ self-evaluation. Building upon this assessment, Pornpongtechavanich et al. (2022) constructed a QoE model incorporating human, context, and system factors to explore the impact of MOBA game quality on players’ game perception. They scrutinized influential factors on game quality and audio-visual quality assessment, encompassing the player’s emotional state, physical and mental constitution, social background and perceptions; the external physical and social environment, service content and innovativeness; as well as the game system itself (Pornpongtechavanich et al., 2022). The model lays a theoretical foundation for further exploration of the affective analysis of MOBA game addiction.

This study contributes to the research on MOBA gaming addiction by investigating the moderating effects of visceral perception, behavior, and reflection on the variables of leisure and gratification. Furthermore, the study expands the theoretical model of game players’ behavioral motives by integrating the theories of leisure (LT), uses and gratification (UGT), and emotional design (EDT).

Theoretical framework

Emotional design

Understanding, expressing, and communicating emotions constitute fundamental human abilities. Integrating positive emotional elements into design significantly enhances users’ emotional experiences (Yoon et al., 2020). In his bestseller, “Emotional Design: Why We Love (or Hate) Everyday Things,” Norman (2004) introduced an innovative theory of emotional design (EDT), challenging the preceding practicality and usability paradigm. Norman hypothesized the heightened importance of the emotional aspect in design, proposing three interdependent design levels: visceral design, behavioral design, and reflective design (Norman, 2004). Norman (2004) elucidated these concepts as follows: Visceral design, preceding consciousness and cognition, lays the foundation for esthetics, appearances, and initial impressions encompassing visual and auditory senses. Behavioral design pertains to user experience, including functionality, performance, and usability, representing external expressions of user pleasure and utilitarian emotions. Reflective design involves consciousness, higher emotions, and perceptions, which vary across cultures, experiences, education, and individual differences. However, EDT elucidated the impact of emotions on responses to design objects (Zachry, 2005), spanning product, interior, and game design. Therefore, when considering emotional studies in design, the consequential themes are emotional effects on user behavior and reflection (Yoon et al., 2020), especially in the realm of human-computer interaction (Imbesi, 2010). The intricate relationship between emotional responses to design and users’ visceral, behavioral, and reflective reactions directly influences the gaming experience of MOBA players. Abbasi et al. (2023) found that visually appealing design and graphics may lead to a positive attitude toward games and the games’ visual and auditory aspects may create a sensory experience that is positively related with game engagement. Patzer et al. (2020) examined the potential for game involvement in terms of behavioral manifestations such as gamer motivation and intention. In addition, gamers’ imagination, emotions, and sensory experiences could trigger cognitive, emotional, and behavioral engagement with the game (Bojan et al., 2021). The above studies show that games are designed with cognitive and affective factors, but cognition is related to behaviors such as motivation.

Hence, this paper based on the correlation between visceral perception (e.g., visual, auditory, tactile, and other sensory variables), behavior (e.g., player skill level and actual combat experience), reflection (e.g., player acquisition of game culture and information), and game addiction, the following hypotheses are posited:

H1: Visceral perception is positively associated with MOBA game addiction.

H2: Behavior exhibits a positive association with MOBA game addiction.

H3: Reflection demonstrates a positive association with MOBA game addiction.

Leisure

Leisure is a distinct and subjective mental state, intricately linked to motivation and time (Voss, 1967). When an individual attains a specific psychological state of freedom outside of work, it is considered leisure time. In the early days of the Industrial Revolution, leisure was confined to the “idle class,” exempt from labor-related obligations (Carnevali and Strange, 2014). However, with technological advancements and increased productivity, employers reduced working hours, providing workers with more free time for leisure activities. The evolving work-leisure relationship prompted the study of Leisure Theory (LT) to adopt a multidisciplinary approach (Spracklen et al., 2017). While recent studies on leisure have embraced interdisciplinary fields such as sociology, geography, and culturology, scholars from each discipline have contributed varying definitions of leisure to conceptualize the concept and construct theoretical models. Despite increased scholarship to distinguish the relationship between leisure and other disciplines, this study introduces a theoretical model within leisure activities, specifically focusing on MOBA.

Digital technology has transformed the social dynamics of leisure activities, creating a leisure space intertwined with social attributes (Rojas de Francisco et al., 2016). Social media, recognized as a leisure activity by an increasing number of young people, plays a significant role in users’ lives (Andreassen, 2015; Kuss and Griffiths, 2017; Sharma et al., 2020). Authors have explored the impact of social media on individual users’ self-reflection and emotions within the framework of LT (Sharma et al., 2020). Variables such as age, education level, income, gender, occupation, and social class are commonly assessed for their influence on social media use (Whitfield et al., 2020). However, some studies emphasize social media’s role in enabling individuals to connect without constraints of time and space, contributing to social addiction (Kuss and Griffiths, 2017).

Gaming, identified as a new form of social media, serves as an entertainment platform abundant with leisure resources (Javier Cabeza-Ramirez et al., 2021), boasting an estimated two billion players globally (Matuszewski et al., 2020). In the virtual gaming world, individuals can momentarily escape reality, alleviating pressures from real life and making it a popular leisure activity for various age groups (Tobon et al., 2020). Consequently, studies on gaming culture have gained attention, highlighting the close relationship between leisure and social activities (Andreassen et al., 2017). Engaging in screen-based leisure is significantly linked to an individual’s physical activity, body mass index, social situation, and emotions (Li et al., 2020). Thus, this study investigates whether leisure influences gamers’ emotional experiences, potentially leading to addiction through leisure variables such as decompression, entertainment, and virtual engagement. The following hypotheses are posited:

H4a: Leisure is positively associated with gamers’ visceral perception of playing MOBA games.

H4b: Leisure is positively associated with gamers’ behavior while playing MOBA games.

H4c: Leisure is positively associated with gamers’ reflection on playing MOBA games.

Uses and gratification

User and Gratification Theory (UGT) is a mass communication theory employed to investigate societal behaviors and motives in the pursuit of specific media to fulfill their needs (Whiting and Williams, 2013). A multidimensional analysis often examines basic needs, individual differences, and cultural backgrounds to understand an individual’s interactions and intentions to use specific media (Rosengren, 1974). With the evolution of new and digital media, UGT is now applied to elucidate why and how individuals choose social media platforms like Instagram, Snapchat, Facebook, and Twitter (Sheldon and Bryant, 2016; Alhabash and Ma, 2017; Phua et al., 2017), games such as League of Legends (LOL) and Pokémon Go (Macedo and da Cunha, 2017; Hamari et al., 2019; Jang and Liu, 2019; Bueno et al., 2020), or video streaming sites like YouTube and Vimeo (Ruggiero, 2000; Khan, 2017; Golob et al., 2021). Not surprisingly, diverse outcomes are expected due to media use being based on individual differences (Greenberg et al., 2010).

UGT has recently been introduced to studies on game behavior and motivation, exploring factors that attract players to video games (Hamari et al., 2019; Jang and Liu, 2019; Bueno et al., 2020; Patzer et al., 2020). Previous research has established a connection between game gratification and motivation, as well as the intention of players’ sustained involvement in these games (Jang and Liu, 2019) and the level of satisfaction felt while playing (Phan et al., 2016). Using UGT, researchers have analyzed the relationship between player gratification and in-game consumption behavior (Ghazali et al., 2019; Hamari et al., 2019), in-game consumption behavior (Wang and Yu, 2017), as well as the connection between player viscosity and experience (Bueno et al., 2020).

If a player has a positive experience during the game, they will be focused, curious, interested, and willing to continue the gaming experience (Choi and Kim, 2004). This may lead to the possibility of further involvement and continuation in the game. Some researchers maintain there is a significant correlation between gratification and players’ motivation to continuously play these games (Abbasi et al., 2017). The motivation for game continuity and players’ long-term gratification experience with the game are the main reasons most players become addicted (Hamari and Keronen, 2017). A recent report by the World Health Organization highlighted the high risks of negative effects of game addiction on various aspects of players’ personal lives, including family, social, professional, and other related areas (Gros et al., 2020). Players’ curiosity about the game, their achievements, and gratification can influence their gaming experience, potentially leading to game addiction. Therefore, this study advances the following assumptions:

H5a: Gratification positively influences players’ visceral perception of playing MOBA games.

H5b: Gratification positively influences players’ behavior in playing MOBA games.

H5c: Gratification positively influences players’ reflection on playing MOBA games.

Building upon the review of these theoretical frameworks, it is proposed that leisure and gratification may exert a positive influence on the visceral perception, behavior, and reflection of MOBA game players. Furthermore, a consistently positive gaming experience is identified as the crucial factor in fostering prolonged engagement among MOBA game players. In light of the aforementioned assumptions, an exploratory research model (refer to Figure 1) for a emotional analysis of MOBA game addiction has been formulated.

Figure 1
www.frontiersin.org

Figure 1. The emotional MOBA game addiction model.

Research methodology

Participants

A total of 298 samples were systematically gathered using a non-probabilistic sampling approach from 24th Nov. 2021 to 24th Mar. 2022 in China. Inclusion criteria encompassed individuals expressing a willingness to volunteer and those engaged in playing MOBA games, specifically League of Legends (LOL) and Honor of Kings (HOK), recognized as the prevailing MOBA games in China (Wirtz, 2022). Additionally, respondents fell within the age bracket of 12 to 40. According to 2017 data from the Nielsen Company, two-thirds of the U.S. population aged 13 and above identified as game players. Notably, 62 participants did not partake in MOBA games and were consequently excluded from the study. The dissemination of online questionnaires transpired randomly through Wenjuanxing, a platform akin to Amazon Mechanical Turk. The conclusive analysis was based on 236 validated questionnaires, equating to a commendable 79.2% response rate among the entire sample pool. It is crucial to note that the act of agreeing to participate in the experiment inherently signified informed consent.

Questionnaire design

The questionnaire was structured into two sections. The initial segment gathered socio-demographic data, encompassing information such as respondents’ gender, age, education level, employment status, salary, gaming experience, and proficiency. The second section comprised 43 five-point Likert scales, ranging from 1 (totally disagree) to 5 (totally agree). For the emotional analysis of gamers’ addictive behavior, a validated scale for design, adjustment, modification, and optimization was employed. The scales developed by this study are attached in Supplementary Material.

In measuring the average weekly/daily MOBA gaming hours, survey items are adapted from “Usage (UG)” construct from Wu and Holsapple’s (2014) scale.

Visceral perception experience include visual experience and auditory experience. Therefore, survey items are adapted from the following studies: (1) survey items in “Sensory Experience” construct from Abbasi et al.’s (2019, 2021, 2023) measurement models are adapted; (2) survey items in “Sensory & imaginative Immersion” category from Phan et al.’s (2016) GUESS scale are adapted; (3) survey items from Tomlinson et al.’s (2018) BUZZ scale are adapted.

MOBA gamers’ behavioral performance involves both game skills and challenges. Therefore, survey items are adapted from the following studies: (1) survey items in “Behavioral intention to play (BI)” construct from Wu and Holsapple’s (2014) scale are adapted; (2) survey items concerning with skills and challenges from Phan et al.’s (2016) GUESS scale are adapted; (3) survey items in “Perceived behavioral control” construct from Hollebeek et al.’s (2022) measurement model are adapted; (4) survey items concerning with challenges from Bueno et al.’s (2020) scale are adapted.

Gamers’ reflection of the game include both perceptions of the game information and perceptions of the game culture. Therefore, regarding the measurement of gamers’ perception of information, the survey items are adapted from the following studies: (1) survey items in “Cognitive Engagement” construct from Abbasi et al.’s (2023) scale are adapted; (2) the item “I am likely to recommend this game to others.” from Phan et al.’s (2016) GUESS scale is adapted. For measuring cultural cognition, survey items are adapted from following studies: (1) survey items in “Cognitive Engagement” construct from Abbasi et al.’s (2023) scale are adapted; (2) survey items from the “Perceived behavioral control” construct from Hollebeek et al.’s (2022) measurement model are adapted; (3) survey items in “Game Knowledge” construct from Jang and Liu’s (2019) scale are adapted.

Playing games is one of the most popular forms of leisure activities Abbasi et al.’s (2021). Playing games can create escapism and relieve stress for gamers, and immerse themselves in the virtual worlds. A large number of gamers take games as a leisure activity to entertain themselves and spend their free time. Therefore, survey items are adapted from the following studies: (1) survey items concerning escapism and avatars from Abbasi et al.’s (2023) scale are adapted; (2) survey items in “Escapism” construct from Bueno et al.’s (2020) scale are adapted; (3) survey items concerning characters or avatars from Phan et al.’s (2016) GUESS and Segaran et al. (2021) scale are adapted.

Achievement and satisfaction are the two core factors that enhance MOBA gamers’ gratification. Therefore, regarding the measurement of satisfaction, survey items are adapted from the following studies: (1) survey items in “Enjoyment” construct from both Abbasi et al.’s (2023) and Hamari et al.’s (2019) scale are adapted; (2) survey items in “Entertainment” construct from Jang and Liu’s (2019) scale are adapted; (3) survey items in Patzer et al.’s (2020) GUESS Subscales are adapted.

For measurement of MOBA game addiction, survey items are adapted from the following studies: (1) survey items in “Continuance Intention (CI)” construct from Bueno et al.’s (2020) scale are adapted; (2) survey items in “Emotional involvement (EI)” construct from Wu and Holsapple’s (2014) scale are adapted; (3) survey items in “Continuance use intention (CUI)” construct from Jang and Liu’s (2019) scale are adapted.

In summary, addiction factors among MOBA gamers were analyzed in this study across six constructs: Leisure, Gratification, Visceral, Behavioral, Reflective, and Games Addiction. The construct of visceral include visual perception (VP) and auditory perception (AP). The construct of behavioral performance include skill (Sk) and challenge (Ch). The construct of reflective include sharing information (SI) and cultural (Cl) cognition. The construct of gratification include satisfaction (Sat) and achievement (Ach).

Procedure

The socio-demographic analysis in this study was conducted by Statistical Package for the Social Sciences (SPSS, Version 26). For model evaluation, the Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to assess the relationships between indicators and the measurement models, as well as the structural models. PLS-SEM, known for its capacity to manage complex models and maximize the variance in dependent variables, was selected for its suitability in conducting formative measures on latent variables and fitting the exploratory nature of this theoretical model analysis (Hair et al., 2017; 116). The analysis utilized SmartPLS 4.1.0, involving two key stages:

In Stage 1, four First-order models, Gratification, Reflective, Behavioral and Visceral, were evaluated for measuring structure modeling. As reviewed above, Gratification contains two First-order measurement models, Ac and Sat; Reflective contains two First-order measurement models, Cl and SI; Behavioral contains two First-order measurement models, Ch and Sk; and Visceral contains two First-order measurement models, VP and AP. Thus, in the First-order measurement structural model, we evaluated Factor Loading (FL), Cronbach’s Alpha (Cα), Composite Reliability (CR) value, Average Variance Extracted (AVE) value, and Variance Inflation Factor (VIF) value, intending to assess the reliability and convergent validity of First-order measurement structural models.

In Stage 2, this study constructed a Second-order structural model consisting of six constructs: Leisure, Gratification, Visceral, Behavioral, Reflective, and Games Addiction. First, the reliability and convergent validity of its measurement constructs were assessed by the same assessment method as in Stage 1. Second, the indirect and overall effects between each construct were evaluated, assessing reflective constructs to determine the significance of the relationships posited in the hypotheses.

Findings and results

Demographic analysis

Demographic analysis revealed seven key variables among the respondents: gender, age, education, financial status, employment status, MOBA gaming skills, and years of playing MOBA games. The distribution between male (46.2%) and female (53.8%) participants indicated a balanced gender representation in MOBA gaming. The age range of 18 to 30 years dominated the sample, comprising 80.9%, with no minors participating. This age distribution aligns with findings from the Pew Research Center (2018) and the Nielsen Company (2017), which highlighted a predominant young adult demographic in gaming, especially among the Z Generation and Millennials (Dimock, 2019; Lim and Parker, 2020). A significant majority of the respondents were unmarried (91.1%) and well-educated, with over 78.0% holding a bachelor’s degree. This educational status correlates with the high percentage of college students (64.0%) in the sample, who generally have more leisure time compared to high school students and working adults. Employees formed the second-largest group at 25.9%. In terms of gaming proficiency, 75% of respondents were high-level players, and a substantial 83.0% had over 3 years of gaming experience. These demographic details are further elaborated in Table 1.

Table 1
www.frontiersin.org

Table 1. Socio-demographic characteristics of MOBA gamers (N = 236).

Game duration analysis

The statistics of gamers’ weekly or daily engagement in MOBA games are shown in Figure 2. This study measured the length of time related to gaming activities in gamers’ daily lives from four aspects: (1) the length of time that gamers spend on games per day on weekends; (2) the length of time that gamers spend on games per day on weekdays; (3) the length of time that gamers spend on watching videos related to MOBA games per day; and (4) the days that gamers spend on games every week.

Figure 2
www.frontiersin.org

Figure 2. Comparative analysis of MOBA gamers’ game duration (N = 236).

Table 2 shows that among 236 samples, the proportion of gamers playing MOBA games for more than 2 h (2 ~ 3 h, 3 ~ 4 h, >5 h) on weekends (27.54, 16.95, 15.25%) is higher than that on weekdays (13.14, 2.54, 4.66%), with a distinct increase on weekends. The proportion of gamers playing MOBA games for less than 2 h (<1 h, 1-2 h) on weekends (13.56, 26.69%) is smaller than that on weekdays (44.92, 34.75%). It indicates that gamers are more likely to get engaged in MOBA games with longer leisure time on weekends.

Table 2
www.frontiersin.org

Table 2. Statistical analysis of MOBA gamers’ game duration (N = 236).

Second, the average length of time gamers spend on watching MOBA online game videos in their daily life is around 1 ~ 2 h (Mean = 1.44, see Table 2), of which 89.83% of gamers watch MOBA online game videos for 0 ~ 2 h per day. It indicates that gamers also spend their leisure time watching MOBA online game videos when they are not engaged in MOBA games.

Third, as shown in Table 2, 58.90% of gamers spend 3 days in average playing MOBA games per week (Mean = 3.12). 80.30% of the gamers spend up to 3 h per day (Mean = 2.41) in playing MOBA games, indicating that gamers have developed the habit of playing MOBA games to some extent. This finding is consistent with the study by De Grove et al. (2016), who found that gamers’ behavior of repeated engagement in games contributed to the development of personal habits.

Stage 1: first-order reflective models analysis

The convergence effectiveness of the conceptual model was evaluated using CR, Cα, AVE, and VIF. Abbasi et al. (2021) and Hair et al. (2019) established that for the structural model to pass reliability and validity tests, Cα, Rho A, and CR values should exceed 0.70, AVE should be greater than 0.50, while VIF should be lower than 5. As shown in Table 3, survey items (15 items) with FL value lower than 0.70 are deleted, leaving a total of 28 question items in the four First-order reflective models of Gratification, Reflective, Behavioral and Visceral with FL value (0.707 ~ 0.954) greater than 0.70.

Table 3
www.frontiersin.org

Table 3. Reliability and validity test of the first-order reflective models (N = 236).

With 15 survey items deleted, the Cα value (0.787 ~ 0.928) and CR value (0.794 ~ 0.928) of the eight constructs (AC, Sat, Cl, SI, AP, VP, Ch and Sk) were greater than 0.70, and the VIF value (1.504 ~ 4.964) was less than 5, which indicated that survey items in each First-order model had good reliability. Second, the AVE value (0.612 ~ 0.874) of each construct, which is greater than 0.50, indicates that these survey items and constructs have good convergent validity. Third, the Cα (0.885 ~ 0.891), AVE (0.557 ~ 0.653) and CR (0.869 ~ 0.891) values of the four constructs Gratification, Reflective, Behavioral and Visceral passed the test and the p values was less than 0.001, indicating that these four First-order models passed the reliability test.

In terms of differential validity assessment, Henseler et al. (2015) proposed a new assessment method, heterotrait-monotrait (HTMT), to measure the correlation between different constructs and thus assess the differential validity between each construct. In this case, an HTMT ratio below 0.85 indicates good discriminant validity between the constructs (Hair et al., 2019). In this study, the four First-order models are tested for differential validity separately, and the results are shown in Table 4, where the HTMT ratios between the constructs are significantly lower than 0.85, indicating that the four reflective First-order models of Gratification, Reflective, Behavioral and Visceral all have good differential validity.

Table 4
www.frontiersin.org

Table 4. Heterotrait-montrait (N = 236).

Stage 2: second-order reflective models analysis

In the Second-order reflective models analysis, the Partial Least Squares (PLS) algorithm was employed to assess the structural model’s reliability and validity. The maximum sub-sample size was set at 5000, and confidence intervals (CI) were calculated using the Percentile Bootstrapping method. The testing was conducted using a two-tailed approach, with a significance level set at p < 0.05. Table 5 displays FL and VIF value for each item, and constructs FL, mean, standard STDEV, t-values, p-values, CR, Cα, and AVE values for Leisure, Gratification, Visceral, Behavioral, Reflective and Games addiction.

Table 5
www.frontiersin.org

Table 5. Reliability and validity test of second-order measurement model.

The findings indicate that I-FL values (0.853–0.949) for each item are greater than 0.70, and VIF values (1.324–3.501) are less than 5, indicating good reliability of the measurement constructs. C-FL (0.744–0.895), CR (0.853–0.945), and Cα (0.662–0.895) values are greater than 0.70 for each of the six constructs. AVE values (0.744–0.895) greater than the minimum threshold of 0.50 and the p-values are less than 0.001. These findings confirm that the Second-order structural model successfully meet the criteria for reliability and validity testing.

The model’s uniqueness was affirmed through a discriminant validity test, an essential criterion for verifying reflective structural models as noted by Hair et al. (2017). Latent variable correlation (Fornell-Larker, F-L) is another way to test the discriminant validity, where the value of the square root of AVE should be greater than the correlation coefficient between each constructs (Hair et al., 2017, 2019, 2022). In other words, the explanation of observed variables by latent variables should be better than the explanation of other latent variables in order to pass the discriminant validity test.

The findings, presented in Table 6, show that HTMT value of Gratification <− > Behavioral, Reflective <− > Behavioral, and Reflective <− > Gratification are 0.937, 0.955, and 0.904, respectively, which are all greater than 0.85, indicating that internal correlation exist among constructs of Behavioral, Gratification and Reflective. The HTMT values of the other constructs are less than 0.85, indicating that certain internal correlation exist among some constructs in the model. Therefore, this study is further tested by F-L. It is also found that the value of the square root of AVE between each construct is greater than the correlation coefficient between each construct, which passed differential validity. It indicates differential validity is supported, displaying good internal consistency between each constructs in the model of this study.

Table 6
www.frontiersin.org

Table 6. Discriminant validity Fornell-Larcker and HTMT values.

In the structural model and hypothesis testing, this study utilized the Partial Least Squares (PLS) automatic estimation method for measuring structural models and verifying hypotheses. The final verification model is depicted in Figure 3, and the total effects are detailed in Table 7. The t-values for H1, H2, and H3 were 3.391, 2.415, and 3.541, respectively, with corresponding p-values of <0.01, < 0.05, and < 0.001, respectively, and positive path coefficients. These results support H1, H2, and H3, indicating that visceral, behavioral, and reflective aspects positively influence over-engagement in MOBA games by gamers.

Figure 3
www.frontiersin.org

Figure 3. Validation model of the study model.

Table 7
www.frontiersin.org

Table 7. Total effect of the verification model of the hypotheses.

The t-values for H4a is 1.876, with p-value of 0.061, greater than a 0.05 threshold. This leads to the rejection of H4a, suggesting that leisure does not significantly influence gamers’ visceral perception in MOBA games. However, H4b and H4c, with t-values of 8.471 and 6.569 respectively, and p-values were less than 0.05 and 0.001 respectively, are supported, indicating a significant influence of leisure on gamers’ behavioral and reflective states. Additionally, the indirect effect of leisure on MOBA game engagement, with a t-value of 7.735 and a p-value less than 0.001, suggests a significant overall impact of leisure on game engagement.

For H5a-c, the t-values were 6.569, 12.747, and 7.928, respectively, with all p-values <0.001 and positive path coefficients, validating these hypotheses. These findings indicate that gratification significantly influences gamers’ visceral perception, behavior, and reflection. Moreover, the t-value for the indirect effect of gratification on MOBA game engagement was 4.364, with a p-value <0.001, demonstrating a substantial overall impact of gratification on engagement in MOBA games.

Model quality assessment

PLS-SEM model quality assessment includes the coefficient of determination (R2), which is used to evaluate the explanatory and predictive power of the model. The value of R2 ranges from 0 to 1, with higher values indicating greater explanatory power. The criteria for assessing the R2 value are inconsistent across different disciplines and research areas (Hair et al., 2022).

The R2 of the theoretical model of MOBA addiction was assessed by SmartPLS 4.1.0 based on Bootstrapping algorithm. The results are shown in Table 8. The effects of Leisure and Gratification on Visceral (T = 4.258, p < 0.001), Behavioral (T = 9.133, p < 0.001), and Reflective (T = 11.550, p < 0.001) constructs were 26.8, 47.5, and 55.9%, respectively. The explanatory power of Visceral, Behavioral, and Reflective for Games Addiction was 32.0%. It shows that the theoretical model of this study has good quality.

Table 8
www.frontiersin.org

Table 8. R2 quality assessment.

Discussion

This study aimed to explore the moderating roles of visceral perception, behavior, and reflection in MOBA gamers, relating to the LT, UGT, and EDT frameworks, and to identify factors contributing to game addiction. Although nine hypotheses were formulated to develop a theoretical model, not all received empirical support.

In Stage 1 the First-order reflective models analysis revealed that MOBA gamers’ visual and audio-visual experiences elicit strong emotional responses, significantly influencing their excessive game involvement. Nuyens et al. (2016) suggested that impulsive and stress reactions from intense game participation might be key psychological factors. Enhanced accessibility of games via smartphones (Chamarro et al., 2020) provides increased playing opportunities, but the MOBA interface’s limited size on mobile devices might diminish sensory experiences. The PLS-SEM model’s validity test showed tactile perception’s dimension load coefficient below 0.70, similarly affected by the screen’s size in some visual perception constructs. However, gamers reported that sound effects and background music in MOBA games greatly enhance the experience. They agreed that muted sound effects would render the game uninteresting. Consequently, all auditory perception dimensions’ load coefficients aligned with reliability and validity standards. Thus, auditory experience emerged as a primary factor in gamers’ MOBA addiction, followed by visual and tactile experiences. Abbasi et al. (2017) corroborated that MOBA games’ audio-visual feedback and stimulation intensify gamers’ sensory experiences, bolstering their intention to continue playing. Mason (2017) previously demonstrated how audio-visual and tactile elements could enhance the gaming experience and promote gamers’ continued engagement.

Secondly, gamers’ proficiency in MOBA control skills and resulting behaviors contributed to their excessive involvement, partly due to the challenge of increasing game difficulty, aligning with findings from Ghazali et al. (2019) and Merikivi et al. (2017). Furthermore, gamers’ deep understanding of characters’ personalities, stories, and design inspirations, alongside cognitive activities like sharing battle experiences and staying updated with game developments, significantly drove their over-engagement. This behavioral and cultural reflection in gaming, a novel finding in the field, was positively correlated with excessive game involvement. Most gamers preferred playing with friends, demonstrating effective socialization skills during gameplay (Chamarro et al., 2020). They also actively engaged with the game’s backstory and character lore, and eagerly gathered the latest game strategies and updates (Wang et al., 2023), indicating a significant and positive relationship between game-related gratification and gamers’ active information-seeking behavior.

Thirdly, emotional involvement in an activity intensifies and prolongs behavior (Mudie, 2003; Ghazali et al., 2019), a concept validated by our findings. Visceral perception, behavior, and reflection all positively influenced gamers’ excessive involvement in MOBA games. MOBA’s visual, auditory, and tactile elements stimulate gamers’ senses, with emotional feedback like rewards and punishments after game outcomes significantly affecting their neurological and physiological responses (Arbeau et al., 2020). This not only heightened gamers’ involvement but also extended their playing time and frequency. Leisure and gratification were identified as key factors promoting gamers’ sensory engagement and gameplay behavior.

Fourthly, while leisure activities did not significantly influence gamers’ visceral perception, they impacted their behavior and reflection on the game. The influence of leisure on gaming behavior is supported by relevant studies. Király et al. (2017, 2022) argued that leisure activities played a beneficial role for gamers’ escapist motivations behaviors. Van Rooij and Nijkamp (2018) employed leisure-time use/diary analysis to understand gamers behavior within the virtual context. He also believed problematic gaming behavior did not happen in a vacuum; in other words, gaming always displaces other activities. Leisure activities contribute to people’s basic needs and growth needs (Joseph Sirgy et al., 2018). Growth needs include cognition on symbolism, esthetics, and morality. This finding supports the conclusion that leisure has a positive effect on gamers’ cognition in this study. In addition, the overall effect mentioned above indicate that leisure is positively correlated with their intention to continue playing. Furthermore, the sense of gratification obtained from playing MOBA games positively correlated with their intention to continue playing.

Conclusion and limitation

Drawing on UGT, LT, and EDT, this paper proposes a theoretical model for understanding engagement in MOBA games. It synthesizes existing literature, focusing on the nexus between gamers’ emotions and behaviors (Fikkers et al., 2016) and the interplay between emotional drivers and excessive involvement in MOBA games (Nuyens et al., 2016). The model examines how leisure, uses and gratifications, and players’ emotional experiences-encompassing visceral perception, behavior, and reflection-influence their propensity for over-engagement in MOBA games. This research extends the range of variables known to impact MOBA game engagement and underscores the comprehensive nature of the proposed model.

The emotional MOBA game addiction model underwent rigorous evaluation, successfully meeting criteria for reliability and validity, including CR, Cα, Rho A, and AVE measures. Additionally, it passed the HTMT test for discriminant validity, affirming its structural distinctiveness and overall effect. The analysis revealed a positive correlation between personal visceral perceptions and reflections with over-engagement in MOBA games. While personal behaviors had an ambiguous effect on over-engagement, leisure and gratification significantly increased the likelihood of excessive involvement. Notably, the correlation between leisure and players’ reflection was insignificant, predominantly reflected in the behavior of experienced players engaging in MOBA games primarily for leisure and entertainment. These findings suggest that players often engage in games during their busiest times, contradicting the notion of idle gaming.

In summary, this study expands upon existing theoretical frameworks that address MOBA game motivation and addiction, guided by emotional, leisure, and uses and gratification theories. It also offers a theoretical foundation for future research on game reflection, behavior, and over-engagement in MOBA games. Considering the proliferation of mobile technologies like smartphones and smartwatches, further research is warranted to explore their impact on MOBA gaming addiction. Moreover, reconceptualizing gaming as more than a leisure pursuit warrants additional investigation in academic discourse. The theoretical model provides certain theoretical references for further exploration of addition to online video games as well as online electronic devices, etc., and has certain applicability to the research in the field of related areas as Internet Addiction.

However, this study still has certain limitations. From theoretical perspective, this study does not consider the impact of negative behaviors such as the impact on gamers’ emotion brought by aggressive language when exploring the impact of MOBA games on gamers’ behaviors. Previous studies on the influence of leisure activities on gamers’ behavior can support the conclusions of this study. However, the influence of leisure on gamers’ cognition lacks supporting evidence. Secondly, when measuring MOBA gamers’ addiction, we only take the influence of continuance intention on gamers’ addiction into consideration, and experimental studies such as brain stimulation are not taken into account. Therefore, certain limitations still exist. In future studies, the effects of gamers’ negative behavior and the effects of brain stimulation on gamers’ addiction will be fully investigated, and the relationship between leisure and gamers’ cognition will be further explored in order to improve the theoretical model of this study.

Data availability statement

The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.

Ethics statement

The studies involving humans were approved by the Academic and Ethics Committee of the School of Design, Fujian University of Technology. The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent for participation in this study was provided by the participants' legal guardians/next of kin.

Author contributions

EH: Conceptualization, Data curation, Formal analysis, Funding acquisition, Methodology, Project administration, Writing – original draft. YX: Conceptualization, Formal analysis, Supervision, Writing – review & editing. XS: Formal analysis, Methodology, Resources, Writing – review & editing.

Funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This work was supported by Fujian Provincial Social Science Fund 2024 (NO. FJ2024BF028).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2024.1347949/full#supplementary-material

References

Abbasi, A. Z., Alqahtani, N., Tsiotsou, R. H., Rehman, U., and Hooi Ting, D. (2023). Esports as playful consumption experiences: examining the antecedents and consequences of game engagement. Telematics Inform. 77:101937. doi: 10.1016/j.tele.2023.101937

Crossref Full Text | Google Scholar

Abbasi, A. Z., Rehman, U., Fayyaz, M. S., Ting, D. H., Shah, M. U., and Fatima, R. (2021). Using the playful consumption experience model to uncover behavioral intention to play multiplayer online Battle arena (MOBA) games. Data Technol. Appl. 56, 223–246. doi: 10.1108/DTA-02-2021-0055

Crossref Full Text | Google Scholar

Abbasi, A. Z., Ting, D. H., and Hlavacs, H. (2017). “Playful-consumption experience in digital game playing: a scale development” in Entertainment computing – ICEC 2017. eds. N. Munekata, I. Kunita, and J. Hoshino (Cham: Springer), 290–296.

Google Scholar

Abbasi, A. Z., Ting, D. H., Hlavacs, H., Costa, L. V., and Veloso, A. I. (2019). An empirical validation of consumer video game engagement: a playful-consumption experience approach. Entertain. Comput. 29, 43–55. doi: 10.1016/j.entcom.2018.12.002

Crossref Full Text | Google Scholar

Alhabash, S., and Ma, M. (2017). A tale of four platforms: motivations and uses of Facebook, twitter, Instagram, and snapchat among college students? Soc. Media Soc. 3:2056305117691540. doi: 10.1177/2056305117691544

Crossref Full Text | Google Scholar

Andreassen, C. S. (2015). Online social network site addiction: a comprehensive review. Curr. Addict. Rep. 2, 175–184. doi: 10.1007/s40429-015-0056-9

Crossref Full Text | Google Scholar

Andreassen, C. S., Pallesen, S., and Griffiths, M. D. (2017). The relationship between addictive use of social media, narcissism, and self-esteem: findings from a large national survey. Addict. Behav. 64, 287–293. doi: 10.1016/j.addbeh.2016.03.006

PubMed Abstract | Crossref Full Text | Google Scholar

Arbeau, K., Thorpe, C., Stinson, M., Budlong, B., and Wolff, J. (2020). The meaning of the experience of being an online video game player. Comput. Hum. Behav. Rep. 2:100013. doi: 10.1016/j.chbr.2020.100013

Crossref Full Text | Google Scholar

Bojan, K., Stavropoulos, T. G., Lazarou, I., Nikolopoulos, S., Kompatsiaris, I., Tsolaki, M., et al. (2021). The effects of playing the COSMA cognitive games in dementia. Int. J. Serious Games 8, 45–58. doi: 10.17083/ijsg.v8i1.412

Crossref Full Text | Google Scholar

Brown, G. W., and Mood, A. M. (1951). On median tests for linear hypotheses. In Proceedings of the Second Berkeley Symposium on Mathematical Statistics and Probability. Berkeley: University of California Press.

Google Scholar

Bueno, S., Dolores Gallego, M., and Noyes, J. (2020). Uses and gratifications on augmented reality games: an examination of Pokemon go. App. Sci. 10:1644. doi: 10.3390/app10051644

Crossref Full Text | Google Scholar

Carnevali, F., and Strange, J.-M. (2014). 20th century Britain economic, cultural and social change. New York: Routledge.

Google Scholar

Chamarro, A., Oberst, U., Cladellas, R., and Fuster, H. (2020). Effect of the frustration of psychological needs on addictive behaviors in mobile videogamers—the media ting role of use expectancies and time spent gaming. Int. J. Environ. Res. Public Health 17:6429. doi: 10.3390/ijerph17176429

PubMed Abstract | Crossref Full Text | Google Scholar

Choi, D., and Kim, J. (2004). Why people continue to play online games: in search of critical design factors to increase customer loyalty to online contents. Cyberpsychol. Behav. 7, 11–24. doi: 10.1089/109493104322820066

Crossref Full Text | Google Scholar

De Grove, F., Cauberghe, V., and Van Looy, J. (2016). Development and validation of an instrument for measuring individual motives for playing digital games. Media Psychol. 19, 101–125. doi: 10.1080/15213269.2014.902318

Crossref Full Text | Google Scholar

Dimock, M. (2019). Defining generations: where millennials end and generation Z begins. Available at:https://www.pewresearch.org/short-reads/2019/01/17/where-millennials-end-and-generation-z-begins/

Google Scholar

Fikkers, K. M., Piotrowski, J. T., and Valkenburg, P. M. (2016). Beyond the lab: Inves tigating early adolescents’ cognitive, emotional, and arousal responses to violent g Ames. Comput. Hum. Behav. 60, 542–549. doi: 10.1016/j.chb.2016.02.055

Crossref Full Text | Google Scholar

Ghazali, E., Mutum, D. S., and Woon, M.-Y. (2019). Exploring player behavior and motivations to continue playing Pokemon GO. Inf. Technol. People 32, 646–667. doi: 10.1108/ITP-07-2017-0216

Crossref Full Text | Google Scholar

Golob, U., Krasevec, M., and Crnic, T. O. (2021). Video gaming spectatorship: what drives gameplay watching on youtube? Media Stud. 12, 40–56. doi: 10.20901/ms.12.23.3

Crossref Full Text | Google Scholar

Greenberg, B. S., Sherry, J., Lachlan, K., Lucas, K., and Holmstrom, A. (2010). Orientations to video games among gender and age groups. Simul. Gaming 41, 238–259. doi: 10.1177/1046878108319930

Crossref Full Text | Google Scholar

Griffiths, M. D., Kuss, D. J., and King, D. L. (2012). Video game addiction: past, present and future. Curr. Psychiatr. Rev. 8, 308–318. doi: 10.2174/157340012803520414

Crossref Full Text | Google Scholar

Gros, L., Debue, N., Lete, J., and van de Leemput, C. (2020). Video game addiction and emotional states: possible confusion between pleasure and happiness? Front. Psychol. 10:2894. doi: 10.3389/fpsyg.2019.02894

PubMed Abstract | Crossref Full Text | Google Scholar

Hair, J. F., Hult, G. T. M., Ringle, C. M., and Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM). Thousand Oaks: SAGE.

Google Scholar

Hair, J. F., Hult, G. T. M., Ringle, C. M., and Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM). Thousand Oaks: SAGE Publications.

Google Scholar

Hair, J. F., Risher, J. J., Sarstedt, M., and Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. Eur. Bus. Rev. 31, 2–24. doi: 10.1108/EBR-11-2018-0203

Crossref Full Text | Google Scholar

Hamari, J., and Keronen, L. (2017). Why do people play games? A meta-analysis. Int. J. Inf. Manag. 37, 125–141. doi: 10.1016/j.ijinfomgt.2017.01.006

Crossref Full Text | Google Scholar

Hamari, J., Malik, A., Koski, J., and Johri, A. (2019). Uses and gratifications of Pokemon go: why do people play Mobile location-based augmented reality games? Int. J. Hum.-Comput. Int. 35, 804–819. doi: 10.1080/10447318.2018.1497115

Crossref Full Text | Google Scholar

Han, H., Jeong, H., Jo, S. J., Son, H. J., and Yim, H. W. (2020). Relationship between the experience of online game genre and high risk of internet gaming disorder i n Korean adolescents. Epidemiol. Health 42:e2020016. doi: 10.4178/epih.e2020016

PubMed Abstract | Crossref Full Text | Google Scholar

Henseler, J., Ringle, C. M., and Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. J. Acad. Mark. Sci. 43, 115–135. doi: 10.1007/s11747-014-0403-8

Crossref Full Text | Google Scholar

Hollebeek, L. D., Abbasi, A. Z., Schultz, C. D., Ting, D. H., and Sigurdsson, V. (2022). Hedonic consumption experience in videogaming: a multidimensional perspective. J. Retail. Consum. Serv. 65:102892. doi: 10.1016/j.jretconser.2021.102892

Crossref Full Text | Google Scholar

Imbesi, L. (2010). Technology, crisis, and interaction design: a conversation with Bruce Sterling, Donald Norman, and Derrick De Kerckhove. MediaTropes 2, 128–135,

Google Scholar

Jang, S., and Liu, Y. (2019). Continuance use intention with mobile augmented reality games overall and multigroup analyses on Pokemon go. Inf. Technol. People 33, 37–55. doi: 10.1108/ITP-05-2018-0221

Crossref Full Text | Google Scholar

Javier Cabeza-Ramirez, L., Fuentes-Garcia, F. J., and Munoz-Fernandez, G. A. (2021). Exploring the emerging domain of research on video game live streaming in web of science: state of the art, changes and trends. Int. J. Environ. Res. Public Health 18:2917. doi: 10.3390/ijerph18062917

PubMed Abstract | Crossref Full Text | Google Scholar

Joseph Sirgy, M., Uysal, M., and Kruger, S. (2018). “A benefits theory of leisure well-being” in Handbook of leisure, physical activity, sports, recreation and quality of life. eds. L. Rodriguez De La Vega and W. N. Toscano (Cham: Springer International Publishing), 3–18.

Google Scholar

Khan, M. L. (2017). Social media engagement: What motivates user participation and consumption on YouTube? Comput. Hum. Behav. 66, 236–247. doi: 10.1016/j.chb.2016.09.024

Crossref Full Text | Google Scholar

Király, O., Billieux, J., King, D. L., Urbán, R., Koncz, P., Polgár, E., et al. (2022). A comprehensive model to understand and assess the motivational background of video game use: the gaming motivation inventory (GMI). J. Behav. Addict. 11, 796–819. doi: 10.1556/2006.2022.00048

PubMed Abstract | Crossref Full Text | Google Scholar

Király, O., Griffiths, M. D., King, D. L., Lee, H.-K., Lee, S.-Y., Bányai, F., et al. (2017). Policy responses to problematic video game use: a systematic review of current measures and future possibilities. J. Behav. Addict. 7, 503–517. doi: 10.1556/2006.6.2017.050

Crossref Full Text | Google Scholar

Kuss, D. J., and Griffiths, M. D. (2017). Social networking sites and addiction: ten lessons learned. Int. J. Environ. Res. Public Health 14:311. doi: 10.3390/ijerph14030311

Crossref Full Text | Google Scholar

LaRose, R., and Eastin, M. S. (2004). A social cognitive theory of internet uses and gratifications: toward a new model of media attendance. J. Broadcast. Electron. Media 48, 358–377. doi: 10.1207/s15506878jobem4803_2

Crossref Full Text | Google Scholar

Larsen, L. J. (2020). The play of champions: toward a theory of skill in eSport. Sport Ethics Philos. 16, 130–152. doi: 10.1080/17511321.2020.1827453

Crossref Full Text | Google Scholar

Li, Y., Wang, C., and Liu, J. (2020). A systematic review of literature on user behavior in video game live streaming. Int. J. Environ. Res. Public Health 17:3328. doi: 10.3390/ijerph17093328

PubMed Abstract | Crossref Full Text | Google Scholar

Lieberoth, A., and Fiskaali, A. (2021). Can worried parents predict effects of video games on their children? A case-control study of cognitive abilities, addiction indicators and wellbeing. Front. Psychol. 11:586699. doi: 10.3389/fpsyg.2020.586699

PubMed Abstract | Crossref Full Text | Google Scholar

Lim, P., and Parker, A. (2020). Mentoring millennials in an Asian context: talent Mana gement insights from Singapore. Wagon Lane, Bingley: Emerald Publishing Limited.

Google Scholar

Macedo, T., and da Cunha, E. (2017). When the fan-garners activism comes into play: participation, resistances and practices of the league of legends fandom in Brazil. Conexao 16, 21–50. doi: 10.18226/21782687.v16.n32.01

Crossref Full Text | Google Scholar

Mason, P. (2017). Medical neurobiology. Oxford: Oxford University Press.

Google Scholar

Matuszewski, P., Dobrowolski, P., and Zawadzki, B. (2020). The association between personality traits and eSports performance. Front. Psychol. 11:1490. doi: 10.3389/fpsyg.2020.01490

PubMed Abstract | Crossref Full Text | Google Scholar

Merikivi, J., Tuunainen, V., and Nguyen, D. (2017). What makes continued mobile gaming enjoyable? Comput. Hum. Behav. 68, 411–421. doi: 10.1016/j.chb.2016.11.070

Crossref Full Text | Google Scholar

Mora-Cantallops, M., and Sicilia, M. Á. (2018). MOBA games: a literature review. Entertain. Comput. 26, 128–138. doi: 10.1016/j.entcom.2018.02.005

Crossref Full Text | Google Scholar

Mudie, P. (2003). Internal customer: by design or by default. Eur. J. Mark. 37, 1261–1276. doi: 10.1108/03090560310486988

Crossref Full Text | Google Scholar

Norman, D. A. (2004). Emotional design why we love (or hate) everyday things. New York: Basic Books.

Google Scholar

Nuyens, F., Deleuze, J., Maurage, P., Griffiths, M. D., Kuss, D. J., and Billieux, J. (2016). Impulsivity in multiplayer online Battle arena gamers: preliminary results on experimental and self-report measures. J. Behav. Addict. 5, 351–356. doi: 10.1556/2006.5.2016.028

PubMed Abstract | Crossref Full Text | Google Scholar

Patzer, B., Chaparro, B., and Keebler, J. R. (2020). Developing a model of video game play: motivations, satisfactions, and continuance intentions. Simul. Gaming 51, 287–309. doi: 10.1177/1046878120903352

Crossref Full Text | Google Scholar

Phan, M. H., Keebler, J. R., and Chaparro, B. S. (2016). The development and validation of the game user experience satisfaction scale (GUESS). Hum. Factors 58, 1217–1247. doi: 10.1177/0018720816669646

PubMed Abstract | Crossref Full Text | Google Scholar

Phua, J., Jin, S. V., and Kim, J. J. (2017). Uses and gratifications of social networking sites for bridging and bonding social capital: a comparison of Facebook, twitter, Instagram, and snapchat. Comput. Hum. Behav. 72, 115–122. doi: 10.1016/j.chb.2017.02.041

Crossref Full Text | Google Scholar

Pornpongtechavanich, P., Wuttidittachotti, P., and Daengsi, T. (2022). QoE modeling for audiovisual associated with MOBA game using subjective approach. Multimed. Tools Appl. 81, 37763–37779. doi: 10.1007/s11042-022-12807-1

PubMed Abstract | Crossref Full Text | Google Scholar

Rojas de Francisco, L., Lopez-Sintas, J., and Garcia-Alvarez, E. (2016). Social leisure in the digital age. Soc. Leis. 39, 258–273. doi: 10.1080/07053436.2016.1198598

Crossref Full Text | Google Scholar

Rosengren, K. E. (1974). “Uses and gratifications: a paradigm outlined” in the uses of mass communications: current perspectives on gratifications research. Eds. Jay G. Blumler and E. Katz (Beverly Hills: Sage Publications), 269–286.

Google Scholar

Ruggiero, T. E. (2000). Uses and gratifications theory in the 21st century. Mass Commun. Soc. 3, 3–37. doi: 10.1207/S15327825MCS0301_02

Crossref Full Text | Google Scholar

Segaran, K., Ali, A. Z. M., and Hoe, T. W. (2021). Does avatar design in educational games promote a positive emotional experience among learners? E-Learning Digital M. 18, 422–440. doi: 10.1177/2042753021994337

Crossref Full Text | Google Scholar

Sharma, M. K., John, N., and Sahu, M. (2020). Influence of social media on mental health: a systematic review. Curr. Opin. Psychiatry 33, 467–475. doi: 10.1097/YCO.0000000000000631

Crossref Full Text | Google Scholar

Sheldon, P., and Bryant, K. (2016). Instagram: motives for its use and relationship to narcissism and contextual age. Comput. Hum. Behav. 58, 89–97. doi: 10.1016/j.chb.2015.12.059

Crossref Full Text | Google Scholar

Spracklen, K., Lashua, B., Sharpe, E., and Swain, S. (2017). The Palgrave handbook of leisure theory. London: Palgrave Macmillan.

Google Scholar

Suznjevic, M., Skorin-Kapov, L., Cerekovic, A., and Matijasevic, M. (2019). How to measure and model QoE for networked games? A case study of world of Warcraft. Multimed. Syst. 25, 395–420. doi: 10.1007/s00530-019-00615-x

Crossref Full Text | Google Scholar

T’ng, S. T., Ho, K. H., and Pau, K. (2023). Need frustration, gaming motives, and internet gaming disorder in Mobile multiplayer online Battle arena (MOBA) games: through the Lens of self-determination theory. Int. J. Ment. Health Addict. 21, 3821–3841. doi: 10.1007/s11469-022-00825-x

PubMed Abstract | Crossref Full Text | Google Scholar

Tobon, S., Ruiz-Alba, J. L., and Garcia-Madariaga, J. (2020). Gamification and online consumer decisions: is the game over? Decis. Support. Syst. 128:113167. doi: 10.1016/j.dss.2019.113167

Crossref Full Text | Google Scholar

Tomlinson, B. J., Noah, B. E., and Walker, B. N. (2018). BUZZ: an auditory Interface user experience scale. Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems, Association for Computing Machinery. New York

Google Scholar

Van Rooij, A. J., and Nijkamp, L. M. (2018). Addressing problematic video game use: a multimethod, dual-context perspective on leisure-time use. J. Behav. Addict. 7, 526–530. doi: 10.1556/2006.7.2018.62

PubMed Abstract | Crossref Full Text | Google Scholar

Voss, J. (1967). The definition of leisure. J. Econ. Issues 1, 91–106. doi: 10.1080/00213624.1967.11502742

Crossref Full Text | Google Scholar

Wang, Y., Dai, Y., Chen, S., Wang, L., and Hoorn, J. F. (2023). Multiplayer online battle arena (MOBA) games: improving negative atmosphere with social robots and AI teammates. Systems, 11:425. doi: 10.3390/systems11080425

Crossref Full Text | Google Scholar

Wang, C., and Yu, G. (2017). The relationship between Player’s value systems and their in-game behavior in a massively multiplayer online role-playing game. Int. J. Comput. Games Technol. 2017, 1–10. doi: 10.1155/2017/6531404

Crossref Full Text | Google Scholar

Whitfield, G. P., Ussery, E. N., and Carlson, S. A. (2020). Combining data from assessments of leisure, occupational, household, and transportation physical activity among US adults, NHANES 2011-2016. Prev. Chronic Dis. 17:200137. doi: 10.5888/pcd17.200137

PubMed Abstract | Crossref Full Text | Google Scholar

Whiting, A., and Williams, D. (2013). Why people use social media: a uses and gratifications approach. Qual. Mark. Res. 16, 362–369. doi: 10.1108/QMR-06-2013-0041

Crossref Full Text | Google Scholar

Wirtz, B . (2022). The most popular MOBA games right now. Available at: https://www.gamedesigning.org/gaming/moba/

Google Scholar

Wu, J., and Holsapple, C. (2014). Imaginal and emotional experiences in pleasure-oriented IT usage: a hedonic consumption perspective. Inf. Manag. 51, 80–92. doi: 10.1016/j.im.2013.09.003

Crossref Full Text | Google Scholar

Wut, E., Ng, P., Leung, K. S. W., and Lee, D. (2021). Do gamified elements affect young people’s use behaviour on consumption-related mobile applications? Young Consum. 22, 368–386. doi: 10.1108/YC-10-2020-1218

Crossref Full Text | Google Scholar

Xia, B., Wang, H., and Zhou, R. (2019). What contributes to success in MOBA games? An empirical study of defense of the ancients 2. Games Cult. 14, 498–522. doi: 10.1177/1555412017710599

Crossref Full Text | Google Scholar

Ye, J. (2021). Tencent releases long-awaited league of legends mobile game in China following Beijing’s crackdown on the industry | South China Morning Post. Available at:https://www.scmp.com/tech/big-tech/article/3151691/tencent-releases-long-awaited-league-legends-mobile-game-china

Google Scholar

Yoon, J., Pohlmeyer, A. E., Desmet, P. M. A., and Kim, C. (2020). Designing for positive emotions: issues and emerging research directions. Des. J. 24, 167–187. doi: 10.1080/14606925.2020.1845434

Crossref Full Text | Google Scholar

Zachry, M. (2005). An interview with Donald a. Norman. Tech. Commun. Q. 14, 469–487. doi: 10.1207/s15427625tcq1404_5

Crossref Full Text | Google Scholar

Keywords: games addiction, PLS-SEM, MOBA games, emotional design, leisure theory, uses and gratification

Citation: Huang E, Xing Y and Song X (2024) Emotional analysis of multiplayer online battle arena games addiction. Front. Psychol. 15:1347949. doi: 10.3389/fpsyg.2024.1347949

Received: 01 December 2023; Accepted: 18 April 2024;
Published: 09 May 2024.

Edited by:

Jian-Hong Ye, Beijing Normal University, China

Reviewed by:

Vita Camellia, University of North Sumatra, Indonesia
Weiguaju Nong, Guangxi University of Foreign Languages, China
Bo-Ching Chen, CTBC Financial Management College, Taiwan

Copyright © 2024 Huang, Xing and Song. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Yalong Xing, eGluZ3lhbG9uZ0BjaXR5dS5lZHUubW8=

ORCID: Xiaozhou Song, https://orcid.org/0009-0001-3086-8172

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.