In recent years, different studies have proposed and validated user models (e.g., Bartle, BrainHex, and Hexad) to represent the different user profiles in games and gamified settings. However, the results of applying these user models in practice (e.g., to personalize gamified systems) are still contradictory. One of the hypotheses for these results is that the user types can change over time (i.e., user types are dynamic). To start to understand whether user types can change over time, we conducted an exploratory study analyzing data from 74 participants to identify if their user type (Achiever, Philanthropist, Socialiser, Free Spirit, Player, and Disruptor) had changed over time (six months). The results indicate that there is a change in the dominant user type of the participants, as well as the average scores in the Hexad sub-scales. These results imply that all the scores should be considered when defining the Hexad's user type and that the user types are dynamic. Our results contribute with practical implications, indicating that the personalization currently made (generally static) may be insufficient to improve the users' experience, requiring user types to be analyzed continuously and personalization to be done dynamically.

翻译：近年来,不同研究提出并验证了用户模型(如巴托、伯恩赫克斯和六十六),以在游戏和合成的设置中代表不同的用户概况;然而,实际应用这些用户模型(如个性化合成系统)的结果仍然自相矛盾。这些结果的一个假设是,用户类型可以随时间变化(即用户类型是动态的)。为了开始了解用户类型是否可以随时间变化,我们进行了一项探索性研究,分析74名参与者的数据,以确定用户类型(亚齐华、慈善家、社会学、自由精神、玩家和破坏者)是否随着时间的推移(6个月)发生变化。结果显示,参与者的主要用户类型以及Hexad子尺度的平均分数发生了变化。这些结果意味着,在界定 Hexad 的用户类型时,所有得分都应考虑在内,用户类型是动态的。我们的结果有助于产生实际影响,表明个人化(一般静止的)目前的用户类型可能不足以不断改进用户的类型。这些个人化(一般是静态的)可能不足以进行个人化分析,从而改进用户的类别。