Afonso Ana Paula, Fonseca Manuel J, Cardoso Joana, Vasquez Beltran
LASIGE, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal.
Department of Social and Behavioural Sciences, University of Maia, Maia, Portugal.
Front Sports Act Living. 2024 Aug 9;6:1407848. doi: 10.3389/fspor.2024.1407848. eCollection 2024.
Video games have become increasingly popular worldwide, attracting billions of gamers across diverse demographics. While studies have highlighted their potential benefits, concerns about problematic gaming behaviors have also emerged. Conditions such as Internet Gaming Disorder (IGD) have been recognized by major health organizations, necessitating accurate diagnostic tools. However, existing methods, primarily reliant on self-report questionnaires, face challenges in accuracy and consistency. This paper proposes a novel technological approach to provide gaming behavior indicators, aiming to offer precise insights into gamer behavior and emotion regulation.
To attain this objective, we investigate quantifiable gaming behavior metrics using automated, unobtrusive, and easily accessible methods. Our approach encompasses the analysis of behavioral telemetry data collected from online gaming platforms and incorporates automated extraction of gamer emotional states from face video recordings during gameplay. To illustrate the metrics and visualizations and demonstrate our method's application we collected data from two amateur and two professional gamers, all of whom played Counter-Strike2 on PC. Our approach offers objective insights into in-game gamer behavior, helping health professionals in the identification of patterns that may be difficult to discern through traditional assessment methods.
Preliminary assessments of the proposed methodology demonstrate its potential usefulness in providing valuable insights about gaming behavior and emotion regulation. By leveraging automated data collection and visualization analysis techniques, our approach offers a more comprehensive understanding of gamer behavior, which could enhance diagnostic accuracy and inform interventions for individuals at risk of problematic gaming behaviors.
Our findings demonstrate the valuable insights obtainable from a tool that collects telemetry data, emotion regulation metrics, and gaming patterns. This tool, utilizing specific indicators, can support healthcare professionals in diagnosing IGD and tracking therapeutic progress, potentially addressing challenges linked to conventional IGD assessment methods. Furthermore, this initial data can provide therapists with detailed information on each player's problematic behaviors and gaming habits, enabling the development of personalized treatments tailored to individual needs. Future research endeavors will focus on refining the methodology and extending its application in clinical settings to facilitate more comprehensive diagnostic practices and tailored interventions for individuals at risk of problematic gaming behaviors.
电子游戏在全球范围内越来越受欢迎，吸引了来自不同人口统计学群体的数十亿玩家。虽然研究强调了它们的潜在益处，但对问题游戏行为的担忧也随之出现。诸如网络游戏障碍（IGD）等情况已得到主要健康组织的认可，因此需要准确的诊断工具。然而，现有方法主要依赖自我报告问卷，在准确性和一致性方面面临挑战。本文提出了一种新颖的技术方法来提供游戏行为指标，旨在深入了解玩家行为和情绪调节。
为实现这一目标，我们使用自动化、不引人注意且易于获取的方法来研究可量化的游戏行为指标。我们的方法包括分析从在线游戏平台收集的行为遥测数据，并在游戏过程中从面部视频记录中自动提取玩家的情绪状态。为了说明这些指标和可视化，并展示我们方法的应用，我们从两名业余玩家和两名职业玩家那里收集了数据，他们都在个人电脑上玩《反恐精英2》。我们的方法为游戏内玩家行为提供了客观见解，有助于健康专业人员识别通过传统评估方法可能难以察觉的模式。
对所提出方法的初步评估表明，它在提供有关游戏行为和情绪调节的有价值见解方面具有潜在用途。通过利用自动化数据收集和可视化分析技术，我们的方法提供了对玩家行为更全面的理解，这可以提高诊断准确性，并为有问题游戏行为风险的个体的干预提供信息。
我们的研究结果表明，从一个收集遥测数据、情绪调节指标和游戏模式的工具中可以获得有价值的见解。这个工具利用特定指标，可以支持医疗保健专业人员诊断IGD并跟踪治疗进展， potentially addressing challenges linked to conventional IGD assessment methods.此外，这些初始数据可以为治疗师提供有关每个玩家问题行为和游戏习惯的详细信息，从而能够制定针对个体需求的个性化治疗方案。未来的研究将集中在完善该方法并将其应用扩展到临床环境中，以促进对有问题游戏行为风险个体的更全面诊断实践和个性化干预。
