Gaming & Well-being Dataset
NLP / Natural Language Processing
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About
This dataset explores the intricate relationships between online gaming, anxiety levels, life satisfaction, and social phobia. It comprises survey responses from gamers globally, featuring questions commonly employed by psychologists to assess individuals susceptible to anxiety, social phobia, and diminished life satisfaction. The original data was meticulously collated by Marian Sauter and Dejan Draschkow, offering a valuable resource for psychological and social studies [1].
Columns
- S. No.: A serial number for each record [2].
- Timestamp: The exact time a participant completed the questionnaire after its launch [3].
- GAD1 through GAD7: Responses to individual questions (1 to 7) related to Generalised Anxiety Disorder (GAD), typically rated on a scale [4-8].
- GADE: Describes the perceived affect or impact of gaming on a participant's work life, categorised into responses like 'Not difficult at all', 'Somewhat difficult', or 'Other' [8].
- SWL1 through SWL5: Responses to individual questions (1 to 5) from the Satisfaction With Life (SWL) scale, typically rated on a scale [8-11].
- Game: The name of the game primarily played by the participant, with 'League of Legends' being the most common [11].
- Platform: The mode of game playing, such as PC, Console (PS, Xbox, etc.), or Mobile [11].
- Hours: The number of hours per week a participant dedicates to gaming [12].
- earnings: Information regarding any earnings derived from gaming, including options like 'I play for fun' or 'I play mostly for fun but earn a little on the side' [12].
- whyplay: The participant's primary reason for playing games, such as 'having fun' or 'improving' [13].
- League: The participant's current gaming league or ranking [13].
- highestleague: The highest league or ranking a participant has ever achieved [13].
- streams: The reported number of online streams of the game [14].
- SPIN1 through SPIN17: Responses to individual questions (1 to 17) from the Social Phobia Inventory (SPIN) scale, typically rated on a scale [14-18].
- Narcissism: Indicates the participant's interest scale in the game, rated from 1 to 5 [18].
- Gender: The self-identified gender of the gamer who completed the questionnaire, predominantly Male [19].
- Age: The self-reported age of the gamer [19, 20].
- Work: The work status of the gamer, such as 'Student at college / university' or 'Employed' [20].
- Degree: The highest educational degree attained by the participant, with 'High school diploma (or equivalent)' being most common [20, 21].
- Birthplace: The country or region where the gamer was born, with USA and Germany being frequently cited [21].
- Residence: The country or region where the gamer currently resides, also with USA and Germany as common entries [21].
- Reference: The source or reference through which the questionnaire was discovered, predominantly 'Reddit' [21, 22].
- Playstyle: Describes the participant's preferred gaming style (e.g., 'Multiplayer - online - with real life friends', 'Multiplayer - online - with strangers', 'single player') [22].
- accept: Indicates whether the participant accepted the terms and conditions of the survey [22].
- GAD_T: The calculated total score for Generalised Anxiety Disorder [23].
- SWL_T: The calculated total score for Satisfaction With Life [24].
- SPIN_T: The calculated total score for Social Phobia Inventory [25].
- Residence_ISO3: The ISO3 code for the participant's current country of residence [25].
- Birthplace_ISO3: The ISO3 code for the participant's country of birthplace [25].
Distribution
The dataset is provided in a CSV file format, specifically named
GamingStudy_data.csv
. It has a file size of 4.26 MB and contains 55 columns. The dataset includes 13.5k valid records across all columns, with no mismatched or missing values reported [2]. While the exact number of rows is not specified, the "13.5k Valid" records indicate a substantial number of entries.Usage
This dataset is ideally suited for academic research and psychological studies. It can be used to:
- Investigate correlations between gaming habits and psychological well-being [1].
- Analyse the impact of specific game types or platforms on anxiety and social phobia [1, 11].
- Examine demographic factors influencing mental health outcomes in gamer populations [19, 20].
- Develop models to predict levels of anxiety or life satisfaction based on gaming behaviour [1].
- Study variations in gaming motivations and their psychological associations [13].
Coverage
The dataset's geographic scope is worldwide, as it consists of data collected from a survey among gamers globally. However, the most frequently reported birthplaces and residences are the USA and Germany, with a diverse representation from 125 and 108 unique countries respectively, indicating broad but possibly concentrated participation [1, 21, 25]. The demographic scope includes self-reported gender, age (ranging from 18 to 63, with a mean of 20.9), work status, and highest degree attained [19, 20]. The time range for data collection is not specified by exact dates, but the presence of a 'Timestamp' column indicates that records capture when participants took the questionnaire [3].
License
Attribution 4.0 International (CC BY 4.0)
Who Can Use It
- Psychologists and Researchers: For studying the psychological impacts of gaming, particularly concerning anxiety, social phobia, and life satisfaction [1].
- Game Developers: To understand player demographics and potential mental health implications related to gaming experiences [19, 20].
- Academics and Students: For educational purposes, data analysis projects, and thesis research on human behaviour, mental health, and digital culture [1].
- Public Health Organisations: To inform strategies and interventions related to digital well-being and responsible gaming [1].
Dataset Name Suggestions
- Global Gamer Mental Health Survey
- Gaming & Well-being Dataset
- Anxiety, Satisfaction, and Phobia in Gaming
- Psychological Impact of Online Gaming Data
- Gamer Mental Health Insights
Attributes
Original Data Source: Gaming & Well-being Dataset