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Record W2036271982 · doi:10.5539/gjhs.v6n5p142

Assessing Whether Measurement Invariance of the KIDSCREEN-27 across Child-Parent Dyad Depends on the Child Gender: A Multiple Group Confirmatory Factor Analysis

2014· article· en· W2036271982 on OpenAlexvenueno aff
Zahra Bagheri, Peyman Jafari, Elahe Tashakor, Seyed Amin Kouhpayeh, Homan Riazi

Bibliographic record

VenueGlobal Journal of Health Science · 2014
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsnot available
FundersShiraz UniversityShiraz University of Medical Sciences
KeywordsDyadPsychologyMeasurement invarianceDevelopmental psychologyGirlConfirmatory factor analysisAutonomyStructural equation modeling

Abstract

fetched live from OpenAlex

This study aims to assess the measurement invariance (MI) of the KIDSCREEN-27 questionnaire across girl-parent and boy-parent dyad to clarify how child gender affects the agreement between children's and parents' perception of the meaning of the items in the questionnaire. The child self-reports and parent proxy-reports of the KIDSCREEN-27 were completed by 1061 child-parent dyad. Multiple group categorical confirmatory factor analysis (MGCCFA) was applied to assess MI. The non-invariant items across girl-parent dyad were mostly detected in the psychological well-being and the social support and peers domains. Moreover, the boys and their parents differed mainly in the autonomy and parent relation domain. Detecting different non-invariant items across the girl-parent dyad compared to the boy-parent dyad underlines the importance of taking the child's gender into account when assessing measurement invariance between children and their parents and consequently deciding about children's physical, psychological or social well-being from the parents' viewpoint.

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 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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.057
Threshold uncertainty score0.848

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.088
GPT teacher head0.366
Teacher spread0.277 · 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 teacher head, 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

Citations28
Published2014
Admission routes1
Has abstractyes

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