Evaluation of psychometric properties of the Arabic version of the Internet Disorder Scale (IDS-15)
Bibliographic record
Abstract
The internet in modern society has impacted individuals of all ages, especially youth. Over the past 25 years, internet has become increasingly accessible, affordable, and available to a large proportion of individuals worldwide. Despite the clear advantages the internet has brought, adverse effects including potential disordered internet use have been noted among a minority of users. This has led to an increase in the development of screening instruments and numerous validation studies in many countries. Although Arabic is spoken in 25 countries worldwide, little research has been carried out, probably because there is a lack of Arabic instruments assessing problematic internet use. The present study evaluated the psychometric properties of the Arabic version of the 15-item Internet Disorder Scale (IDS-15). A cross-sectional study was conducted among 327 active internet users (35.5 % male; mean age = 21.49 years [SD = 3.06]) using a pen-and-paper-based survey. All participants completed the IDS-15, Bergen Social Media Addiction Scale (BSMAS), and Satisfaction with Life Scale (SWLS). The concurrent validity of the Arabic IDS-15 was satisfactory as its total score was significantly correlated with scores on the BSMAS (standardized coefficient [β] = 0.382), time spent online (β = 0.310), time spent on social media (β = 0.368), time spent on sleep (β = -0.176), and SWLS score (β = -0.281). The internal consistency indicated good internal reliability. Confirmatory factor analysis supported the factor structure of the IDS-15. The Arabic version IDS-15 is a psychometrically sound and robust instrument for assessing internet disorder due to its excellent concurrent validity, good reliability, and satisfactory construct validity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".