Replication and Extension of Video Game Demand Scale with a Turkish-Speaking Gamer Population

Title of the Paper

Replication and Extension of Video Game Demand Scale with a Turkish-Speaking Gamer Population

Bibliographic Information

• Field of Study: Human-Computer Interaction (HCI), User Experience, Video Game Demand Assessment
• Keywords: Video games, interactivity, demand, scale development, user experience

Research Background and Problem Statement

• Identified Problems or Challenges:

  • How the interactive dimensions of video games can be described through the Video Game Demand Scale (VGDS), encompassing cognitive, emotional, social, and physical aspects. These dimensions are related to game characteristics and player experiences but have not been widely validated in non-English language contexts.
  • Current research in the video game domain heavily relies on English or Western samples ("WEIRD" populations, i.e., Western, Educated, Industrialized, Rich, and Democratic), with limited validation for other cultural contexts.
  • Turkey is considered one of the fastest-growing global gaming markets, yet its gaming culture and linguistic environment have not been sufficiently integrated into existing research.

• Significance:

  • VGDS can measure players' perceptions of various game demands, aiding game developers and researchers in understanding player user experiences.
  • Validating VGDS in non-English language contexts, particularly for Turkish-speaking players, provides an important case study for global gaming market research.

• Research Motivation and Related Work:

  • VGDS has undergone preliminary validation in German and Mandarin-speaking contexts but has not been tested among Turkish-speaking gamers.
  • There is a growing call within the gaming and HCI research communities to expand sample diversity and cultural applicability. This study aims to address this research gap.

Solution

• Research Methods and Solutions:

  • Translate and apply the English VGDS into Turkish (VGDS-T).
  • Collect data from 184 Turkish-speaking gamers through an online survey and use Confirmatory Factor Analysis (CFA) to validate the five-factor model of VGDS-T (cognitive, emotional, control, physical, and social demands).
  • Test VGDS-T's convergent validity, predictive validity, and concurrent validity.
  • Compare the 22-item and 26-item versions of the scale to analyze VGDS performance across different language contexts.

• Innovations:

  • Validate VGDS in a Turkish-speaking context, addressing the gap in cultural and linguistic applicability in global video game research.
  • Extend VGDS to non-"WEIRD" populations (e.g., Turkey), laying the groundwork for future cross-cultural studies.

• Implementation Steps and Techniques:

  1. Use translation/back-translation methods to translate VGDS into Turkish.
  2. Recruit participants via social media and forums and distribute online surveys.
  3. Perform data cleaning and Confirmatory Factor Analysis (CFA) to test the fit of the five-factor structure.
  4. Use Structural Equation Modeling (SEM) to validate VGDS-T's predictive, convergent, and concurrent validity.

Research Outcomes

• Specific Results:

  • The VGDS-T five-factor model (cognitive, emotional, control, physical, and social demands) was validated among Turkish-speaking gamers.
  • The 22-item version of the five-factor model showed slightly better fit than the original 26-item version.
  • Validity tests confirmed that VGDS-T dimensions were associated with corresponding game experience measures, such as cognitive demands correlating with task load perception and emotional demands positively correlating with game enjoyment.

• Comparative Advantages Over Existing Solutions:

  • VGDS-T is the first validated scale introducing VGDS into the Turkish-speaking context.
  • Results demonstrate that VGDS's five-factor model has broad applicability and commonality across different cultural and linguistic backgrounds.
  • Provides a tool to support research on Turkey's rapidly growing gaming market.

• Experimental or Evaluation Results:

  • Participants evaluated their demand perceptions across 119 different video games, showcasing diversity.
  • Confirmatory Factor Analysis (CFA) indicated that the 22-item version model had an RMSEA of 0.069 and a CFI of 0.926, outperforming the 26-item version.
  • Validity tests showed significant associations between VGDS-T individual demands (e.g., cognitive demands) and corresponding effort types (e.g., mental effort).

• Limitations and Future Directions:

  1. Sample Bias: The sample consisted of 89% male participants, which does not represent the broader Turkish-speaking gamer population. Future studies should focus on gender and cultural diversity.
  2. Data Collection Methods: Recruitment via social media (e.g., Reddit) may have limitations; alternative sampling scenarios such as campuses or gaming expos could be considered.
  3. Game Feature Analysis: This study did not deeply connect individual game demand characteristics with research results. Future studies could use real-game experiments for further validation.
  4. Cultural Context Integration: The study primarily focused on the five-factor model; future research could incorporate local gaming culture for deeper comparative analysis.

Conclusion

This study validated the VGDS five-factor model among Turkish-speaking gamers, extending VGDS's cross-language applicability and providing tool support for the growing non-"WEIRD" cultural gaming market. Future research could expand on larger, more diverse samples, integrating local culture and game characteristics to enrich the global perspective of video game research.