Psychometric Properties of Screening Instruments for Social Network Use Disorder in Children and Adolescents
Bibliographic record
Abstract
Importance: Children and adolescents spend considerable time on the internet, which makes them a highly vulnerable group for the development of problematic usage patterns. A variety of screening methods have already been developed and validated for social network use disorder (SNUD); however, a systematic review of SNUD in younger age groups has not been performed. Objective: To review published reports on screening tools assessing SNUD in children and adolescents with a maximum mean age of 18.9 years. Evidence Review: To identify instruments for the assessment of SNUD, a systematic literature search was conducted in the databases PsycINFO, PubMed, Web of Science, PsycArticles, and Scopus. The final search took place on May 2, 2022. Psychometric properties of available tools were examined and evaluated to derive recommendations for suitable instruments for individuals up to 18 years of age. Findings: A total of 5746 publications were identified, of which 2155 were excluded as duplicates. Of the remaining 3591 nonredundant publications, 3411 studies were assessed as not relevant after title and abstract screening. A full-text analysis of 180 remaining studies classified as potentially eligible resulted in a final inclusion of 29 studies revealing validation evidence for a total of 19 tools. The study quality was mostly moderate. With regard to validation frequency, 3 tools exhibited the largest evidence base: Social Media Disorder Scale (SMDS), the short version of the Bergen Facebook Addiction Scale, and Bergen Social Media Addiction Scale-Short Form (BSMAS-SF). Among these, 1 study tested a parental version (SMDS-P) for its psychometric properties. Taking all criteria into account, the strongest recommendation was made for the SMDS and BSMAS-SF. Conclusions and Relevance: Results suggest that the SMDS-SF and BSMAS-SF were appropriate screening measures for SNUD. Advantages of the SMDS are the availability of a short version and the possibility of an external parental rating.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".