In this study, we examine digital game preferences by identifying game dynamics, i.e. player-game interaction modes, of 700 contemporary digital games, and players' (N = 1717) desire to play games with specific types of dynamics. Based on statistical analysis of the data, 5 game dynamics preference categories ("assault," "manage," "journey," "care," and "coordinate") In this study, we aim to provide new knowledge on how players' gaming preferences and different types of digital games can be analyzed within a single research framework based on activity theoretical considerations and game design concepts. While earlier research has argued challenge and competition as the principal reasons to play digital games (Sherry et al., 2006) and social interaction, immersion, and achievement as the key human motivations to play online games (Yee, 2006), player preferences in specific types of games are still largely unknown. The approach presented in this study should not be equated to motivations to play studies (e.g. Yee, 2006;Sherry et al., 2006) or to the studies of player behavior types (e.g., Bartle, 2003) but rather taken as complementary work aimed at identifying player-game interaction preference types. The knowledge of what keeps players involved with gameplay is paramount for developing player-centric games with better market fit (see Adams, 2014).We start by discussing how our approach relates with prior studies on player typologies. We then set the analytical framework for our investigation by defining the theoretical concepts relevant to our study, and finally present our research questions of identifying (1) the core game dynamics of contemporary digital games; (2) players' game dynamics preferences; and (3) player types based on game dynamics preferences. The results are followed by a discussion that will bring our approach into dialogue with related prior research. Player Typologies and Preferences for Playing Digital GamesPrior player categorizations have focused on either motivations to play or behavioral dimensions of players' play styles (Hamari & Tuunanen, 2014, p. 34). Categorizations of players by play styles (e.g., Bartle, 2003;Mulligan & Patrovsky, 2003;Tseng, 2010) and motivations to play (e.g., Bateman, Lowenhaupt & Nacke, 2011;Przybylski, Rigby & Ryan, 2010;Sherry et al., 2006;Yee, 2006) have mostly analyzed gaming habits or players' personality traits instead of examining playing as a form of computer-mediated designed interaction. These categorizations also do not typically include different types of digital games in the analysis. Behavioral observations of players' play styles are usually based on only one game, most typically an online game, or at least on a set game genre, whereas studies on motivations to play aim to explore the reasons why people play, for example, mobile games, online multiplayer games, or digital games in general.In contrast, the shortcoming of genre categories as well as other design-oriented classifications, such as design patterns approach (Björk & Holopainen, 20...
In the present study, we validated Gameplay Activity Inventory (GAIN), a short and psychometrically sound instrument for measuring players' gameplay preferences and modeling player profiles. In Study 1, participants in Finland (N = 879) responded to a 52-item version of GAIN. An exploratory factor analysis was used to identify five latent factors of gameplay activity appreciation: Aggression, Management, Exploration, Coordination, and Caretaking. In Study 2, respondents in Canada (N = 1322) and Japan (N = 1178) responded to GAIN, and the factor structure of a 15-item version was examined using a Confirmatory Factor Analysis. The results showed that the short version of GAIN has good construct validity, convergent validity, and discriminant validity in Japan and in Canada. We demonstrated the usefulness of GAIN by conducting a cluster analysis to identify player types that differ in both demographics and game choice. GAIN can be used in research as a tool for investigating player profiles. Game companies, publishers and analysts can utilize GAIN in player-centric game development and targeted marketing and in generating personalized game recommendations.
In this study, we develop and validate Intrinsic Motivations to Gameplay (IMG) inventory. In Study 1, psychometric properties of a preliminary 10-item version of IMG were investigated by employing an online survey data collected among Finnish and Danish population (N = 2,205). In Study 2, a 23-item version of IMG was developed based on further interview data and survey data collected among Canadian population (N = 1,322). The 23-item version of IMG revealed five factors of intrinsic motivations for gameplay: Relatedness, Autonomy, Competence, Immersion, and Fun. In Study 3, a third survey was conducted among Finnish and Japanese participants (N = 2,057) to design a Self-Determination theory (SDT) informed confirmatory factor analysis (CFA). The CFA validated a 15-item version of IMG inventory, which can be utilized widely in studies on digital gaming and gamification to better understand player preferences.
The recent inclusion of gaming disorder in the ICD-11 as a mental disorder has further increased the importance of researching the health spectrum related to gaming. A critical area in this regard is the lack of clarity concerning the differences between gaming disorder and intensive play, the latter of which often involves several gaming hours per day without related health problems. In this study, we approached the above question by interpretive phenomenological analysis with interviews in two groups of highly involved videogame players: those who seek or have sought clinical help for their problems with gaming (n=6), and those who play esports more than 4 hours per day without self-reported related health problems (n=10). The interviews were carried out by using a new Phenomenology of Play (POP) interview frame. These data were contextualized with interviews of medical experts (n=6) who have experience of working with the former group. The findings imply that experiences of disorder derive from gaming interfering with what one wants to be, do, and have throughout life, whereas the experiences of intensive esport play derive from gaming being integrated into self throughout life. To our knowledge, this was the first registered report using qualitative phenomenological methods—we encourage researchers to explore the utility of registered reports with other qualitative methods to further optimize scientific progress.
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