0% Complete
English
صفحه اصلی
/
چهاردهمین کنفرانس بین المللی فناوری اطلاعات و دانش
Exploring the Relationship Between Gameplay Log Data and Depression & Anxiety
نویسندگان :
Soroush Elyasi
1
Arya Varasteh Nezhad
2
Fattaneh Taghiyareh
3
1- دانشگاه تهران
2- دانشگاه تهران
3- دانشگاه تهران
کلمات کلیدی :
Data Analytics،Behavioral Analysis،Human-Computer Interaction،Mental Health Assessment،Serious Game،Depression and Anxiety
چکیده :
Depression and Anxiety are prevalent mental health disorders affecting millions worldwide. Identifying these disorders accurately and promptly is crucial to ensure that individuals can receive appropriate treatment. To address this issue, this paper proposes using a game to identify behavioral patterns that indicate depression and anxiety. Our study involved 56 university students. In this paper, we used statistical tools such as calculating Correlation, Linear Regression, Kolmogorov–Smirnov, ANOVA, and Mann–Whitney U test to analyze our data. For this research, we designed a shooter and a memory-based game that can challenge disorders by creating exciting and stressful moments. Using serious games offers several advantages over traditional methods, like increasing accuracy and reducing bias by removing self-reports and sampling with monitoring player behaviors for extended periods. Our results indicate that several parameters are significantly related to depression and anxiety. These parameters include the number of guesses and surrendering in memory games, manner of movements, losing perks, losing lives, number of enemies colliding with the player, and number of playing to win in shooter games. We also found that log size and skipping game tutorials in each game were related to depression and anxiety. Lastly, age and getting help from others were identified as significant factors. Overall, our research highlights the potential of games as an alternative tool for assessing and understanding depression and anxiety disorders. By leveraging the interactive nature of games, researchers and clinicians can gain valuable insights into individuals' mental health conditions, leading to improved identification and treatment outcomes.
لیست مقالات
لیست مقالات بایگانی شده
AI-based Secure Intrusion Detection Framework for Digital Twin-enabled Critical Infrastructure
Tanisha Patel - Nilesh Kumar Jadav - Tejal Rathod - Sudeep Tanwar - Deepak Garg - Hossein Shahinzadeh
تحلیل سازههای موثر بر پذیرش فناوری بلاکچین و استفاده از آن در صنعت بیمه ایران با استفاده از تکنیک معادلات ساختاری (مطالعه موردی: شرکت کارگزاری رسمی بیمه زندگی خوب)
احسان هنری - آفرین اخوان
Customer Churn Prediction Using Data Mining Techniques for an Iranian Payment Application
Olya Rezaeian - Dr ُSeyedhamidreza Shahabi Haghighi - Dr Jamal Shahrabi
شبکههای نرمافزار محور در کلان داده: مطالعهی راهکارهای امنیتی و چالشها
احسان سلیمانی دهکردی - محمدرضا ملاخلیلی میبدی
استخراج ویژگی مجموعه دادههای پزشکی دارای ابعاد بالا با استفاده از برنامه نویسی ژنتیک چند منظوره
سحر فقیهی راد - دکتر سیده نفیسه آل محمد سحر فقیهی راد - سیده نفیسه آل محمد -
ارائه مدل یادگیری ماشین برای پیشبینی سریزمانی باینری از دیدگاه مسئلههای دستهبندی با کاربرد در پیشبینی نتهای موسیقی
نیلوفر ع��دلخانی - حسام عمرانپور
Integration of Electric Vehicles in Smart Grid using Deep Reinforcement Learning
Farkhondeh Kiaee
Designing an AI-assisted toolbox for fitness activity recognition based on deep CNN
Ali Bidaran - Dr Saeed Sharifian
ML-based Optical Fibre Fault Detection in Smart Surveillance and Traffic Systems
Rushil Patel - Sana Narmawala - Nikunjkumar Mahida - Rajesh Gupta - Sudeep Tanwar - Hossein Shahinzadeh
توسعه ی کارآفرینی دیجیتال در بخش کشاورزی
شایان مظاهری - فاطمه قربانی پیرعلیدهی - فاطمه رزاقی بورخانی
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 40.3.1