Reliability and Validity of the Arabic Version of the Game Experience Questionnaire: Pilot Questionnaire Study
Bibliographic record
Abstract
Background Nowadays, digital gaming occupies a central position in the entertainment industry where it has developed into a cherished kind of entertainment in markets all over the world. In addition, it provides other sectors with various social and economic benefits. The Game Experience Questionnaire (GEQ) is a free, quantitative, and comprehensive self-report measure that was developed to assess the player game experience. Despite having been widely used by many research projects in the past, it has not been adapted into Arabic. Furthermore, several components of the scale proved problematic from a psychometric point of view. Therefore, a modified version of the scale is needed to measure the gaming experience of the Arab population. Objective The aim of this study was to validate and examine the psychometrics of an adapted Arabic version of the GEQ in Tunisia. Methods A total of 771 volunteer participants completed an online survey, which included an Arabic version of the GEQ, gaming data, and a sociodemographic questionnaire. Subjects were randomized in order to complete two phases of the study: exploratory and confirmatory. The exploratory data were acquired from 360 respondents whose mean age was 23.89 (SD 2.29) years. Out of 360 respondents, 111 (30.8%) were female and 249 (69.2%) were male. Confirmatory data were obtained from the remaining 411 subjects whose mean age was 21.94 (SD 1.80) years. Out of 411 subjects, 169 (41.1%) were female and 242 (58.9%) were male. Results After the elimination of two items, the exploratory and the confirmatory factor analyses provided an adequate factor structure of the Arabic version of the GEQ. In addition, the internal consistency coefficients suggested the reliability of the instrument. Significant differences were revealed for three subcomponents: flow by age (η2=0.013, P=.002), gender (η2=0.007, P=.02), and game type (η2=0.03, P<.001). For competence (η2=0.01, P=.03) and immersion (η2=0.02, P=.01), significant differences were highlighted by the type of game. The discriminant and convergent validities of the instrument were supported by calculating the average variance extracted (AVE) and comparing the square roots of the AVE values to the correlation coefficients, respectively. Conclusions The Arabic adapted version of the GEQ is valid and reliable and can be administered to measure the game experience in Arab countries.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".