Cross‐national validation of the social media disorder scale: findings from adolescents from 44 countries
Bibliographic record
Abstract
Abstract Background and aims There is currently no cross‐national validation of a scale that measures problematic social media use (SMU). The present study investigated and compared the psychometric properties of the social media disorder (SMD) scale among young adolescents from different countries. Design Validation study. Setting and participants Data came from 222 532 adolescents from 44 countries participating in the health behaviour in school‐aged children (HBSC) survey (2017/2018). The HBSC survey was conducted in the European region and Canada. Participants were on average aged 13.54 years (standard deviation = 1.63) and 51.24% were girls. Measurement Problematic SMU was measured using the nine‐item SMD scale with dichotomous response options. Findings Confirmatory factor analyses (CFA) showed good model fit for a one‐factor model across all countries (minimum comparative fit index (CFI) and Tucker–Lewis index (TLI) = 0.963 and 0.951, maximum root mean square error of approximation (RMSEA) and standardized root mean square residual (SRMR) = 0.057 and 0.060), confirming structural validity. The internal consistency of the items was adequate in all countries (minimum alpha = 0.840), indicating that the scale provides reliable scores. Multi‐group CFA showed that the factor structure was measurement invariant across countries (ΔCFI = −0.010, ΔRMSEA = 0.003), suggesting that adolescents’ level of problematic SMU can be reliably compared cross‐nationally. In all countries, gender and socio‐economic invariance was established, and age invariance was found in 43 of 44 countries. In line with prior research, in almost all countries, problematic SMU related to poorer mental wellbeing (range β STDY = 0.193–0.924, P < 0.05) and higher intensity of online communication (range β STDY = 0.163–0.635, P < 0.05), confirming appropriate criterion validity. Conclusions The social media disorder scale appears to be suitable for measuring and comparing problematic social media use among young adolescents across many national contexts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".