Development and validation of the Self-Administered Internet Addiction Scale (SAIAS-10)
Bibliographic record
Abstract
The number of people using the internet has skyrocketed during the past two decades, making screen addiction a threat greater than substance addiction. Clinical instances of screen addiction symptoms have emerged in the midst of the rising social media popularity. The existing scales for assessing screen addiction are dated and are lengthy, hence our primary objective was to develop a novel brief self-diagnostic scale that can detect internet addiction disorder. Our secondary objective is to conduct psychometric evaluations of this scale. The scale was administered to a total of 1057 participants (493 males, 564 females) with ages ranging from 14-24 years of age. Face and content validity, reliability, and internal consistency were assessed. Participants did not report any difficulty in understanding the questions. The final version of the scale comprises 10 items. A content validity index of 1, a Pearson correlation value of 0.98, and a Cronbach’s alpha of 0.923 were obtained. Findings suggest the SAIAS-10 is a reliable and valid tool for screening screen addiction and may aid in the clinical evaluation of symptomology and research.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".