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Record W2898962588 · doi:10.1186/s40359-018-0262-z

Validation of a cross-cultural instrument for child behavior problems: the Disruptive Behavior International Scale – Nepal version

2018· article· en· W2898962588 on OpenAlex
Matthew D. Burkey, Ramesh P. Adhikari, Lajina Ghimire, Brandon A. Kohrt, Lawrence S. Wissow, Nagendra P. Luitel, Emily E. Haroz, Mark J. D. Jordans

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBMC Psychology · 2018
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of British Columbia
FundersNational Institutes of HealthNational Center for Advancing Translational SciencesNational Institute of Mental HealthJohns Hopkins UniversityAmerican Academy of Child and Adolescent Psychiatry
KeywordsScale (ratio)PsychologyCross-culturalCross-cultural studiesPsychological researchApplied psychologySocial psychologySociologyAnthropologyGeography

Abstract

fetched live from OpenAlex

BACKGROUND: Obtaining accurate and valid measurements of disruptive behavior disorders remains a challenge in non-Western settings due to variability in societal norms for child behavior and a lack of tools developed outside of Western contexts. This paper assesses the reliability and construct validity of the Disruptive Behavior International Scale - Nepal version (DBIS-N)-a scale developed using ethnographic research in Nepal-and compares it with a widely used Western-derived scale in assessing locally defined child behavior problems. METHODS: We assessed a population-based sample of 268 children ages 5-15 years old in Nepal for behavior problems with a pool of candidate items developed from ethnographic research. We selected final items for the DBIS-N using exploratory factor analysis in a randomly selected half of the sample and then evaluated the model fit using confirmatory factor analysis in the remaining half. We compared the classification accuracy and incremental validity of the DBIS-N and Eyberg Child Behavior Inventory (ECBI) using local defined behavior problems as criteria. Local criteria were assessed via parent report using: 1) local behavior problem terms, and 2) a locally developed vignette-based assessment. RESULTS: Ten items were selected for the final scale. The DBIS-N had good internal consistency (Cronbach's α: 0.84) and excellent test-retest reliability (intraclass correlation 0.93, r = .93). Classification accuracy and area under the curve (AUC) were similar and high for both the ECBI (AUC: 0.83 and 0.85) and DBIS-N (AUC: 0.83 and 0.85) on both local criteria. The DBIS-N added predictive value above the ECBI in logistic regression models, supporting its incremental validity. CONCLUSIONS: While both the DBIS-N and the ECBI had high classification accuracy for local idioms for behavior problems, the DBIS-N had a more coherent factor structure and added predictive value above the ECBI. Items from the DBIS-N were more consistent with cultural themes identified in qualitative research, whereas multiple items in the ECBI that did not fit with these themes performed poorly in factor analysis. In conjunction with practical considerations such as price and scale length, our results lend support for the utility of the DBIS-N for the assessment of locally prioritized behavior problems in Nepal.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.050
GPT teacher head0.389
Teacher spread0.339 · 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