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Record W4407983918 · doi:10.1177/30502225251319877

Cross-cultural Adaptation, Reliability and Validity Tests of Screen for Child Anxiety and Related Emotional Disorders (SCARED) Child Version and SCARED-5-items in Indonesian Adolescents

2025· article· en· W4407983918 on OpenAlexaff
Fransiska Kaligis, Inez Cassandra, Hervita Diatri, Tjhin Wiguna, Eva Suarthana

Bibliographic record

VenueSage Open Pediatrics · 2025
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersDirektorat Riset and Pengembangan, Universitas Indonesia
KeywordsCronbach's alphaIndonesianPsychologyContent validityAnxietyClinical psychologyReliability (semiconductor)ValidityPsychometricsPsychiatry

Abstract

fetched live from OpenAlex

Anxiety disorders are prevalent among adolescents and significantly impair social and academic functioning. It should be identified early to avoid detrimental effects. This study aimed to validate and assess the reliability of the Indonesian SCARED Child Version for detecting anxiety disorders in Indonesian adolescents. The SCARED Child Version was translated into an Indonesian version according to the standard cross-cultural adaptation method. Reliability was tested with internal consistency test on 123 adolescents aged 12 to 18 years old in Jakarta, which obtained Cronbach's alpha value for SCARED-41 items of .927, and .741 for SCARED-5 items. The content validity test was carried out through a qualitative relevance assessment involving 9 experts and the results showed an average Content-Validity-Index for items of 0.94, Content-Validity-Ratio of 0.88, and Validity-Index for scales of 0.94. The Indonesian version of the SCARED Child Version has good reliability and validity for the early detection of anxiety disorders among Indonesian adolescent.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.014
GPT teacher head0.302
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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