Cross-Cultural Validation of the Compulsive Internet Use Scale in Four Forms and Eight Languages
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The 14-item Compulsive Internet Use Scale (CIUS) is one of the most frequently internationally adapted psychometric instruments developed to assess generalized problematic Internet use. Multiple adaptations of this instrument have led to versions in different languages (e.g., Arabic and French), and different numbers of items (e.g., from 5 to 16 items instead of the original 14). However, to date, the CIUS has never been simultaneously compared and validated in several languages and different versions. Consequently, the present study tested the psychometric properties of four CIUS versions (i.e., CIUS-14, CIUS-9, CIUS-7, and CIUS-5) across eight languages (i.e., German, French, English, Finnish, Spanish, Italian, Polish, and Hungarian) to (a) examine their psychometric properties, and (b) test their measurement invariance. These analyses also identified the optimal versions of the CIUS. The data were collected via online surveys administered to 4,226 voluntary participants from 15 countries, aged at least 18 years, and recruited from academic environments. All brief versions of the CIUS in all eight languages were validated. Dimensional, configural, and metric invariance were established across all languages for the CIUS-5, CIUS-7, and CIUS-9, but the CIUS-5 and CIUS-7 were slightly more suitable because their model fitted the ordinal estimate better, while for cross-comparisons, the CIUS-9 was slightly better. The brief versions of the CIUS are therefore reliable and structurally stable instruments that can be used for cross-cultural research across adult populations.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it