Problematic Internet Use among Adults: A Cross-Cultural Study in 15 Countries
Bibliographic record
Abstract
BACKGROUND: The present study compared adult usage patterns of online activities, the frequency rate of problematic internet use (PIU), and risk factors (including the psychopathology associated with PIU, i.e., distress and impulsivity) among adults in 15 countries from Europe, America, and Asia. METHODS: A total of 5130 adults from Belgium, Finland, Germany, Italy, Spain, France, Switzerland, Hungary, Poland, UK, Norway, Peru, Canada, US, and Indonesia completed an online survey assessing PIU and a number of psychological variables (i.e., depression, anxiety, stress, and impulsivity). The sample included more females, with a mean age of 24.71 years (SD = 8.70). RESULTS: PIU was slightly lower in European countries (rates ranged from 1.1% in Finland to 10.1% in the UK, compared to 2.9% in Canada and 10.4% in the US). There were differences in specific PIU rates (e.g., problematic gaming ranged from 0.4% in Poland to 4.7% in Indonesia). Regression analyses showed that PIU was predicted by problematic social networking and gaming, lack of perseverance, positive urgency, and depression. CONCLUSIONS: The differences in PIU between countries were significant for those between continental regions (Europe versus non-European countries). One of the most interesting findings is that the specific PIU risks were generally low compared to contemporary literature. However, higher levels of PIU were present in countries outside of Europe, although intra-European differences existed.
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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 | 0.009 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".