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Record W4385768483 · doi:10.22235/cp.v17i2.2700

Escala de Desregulação Emocional Infantojuvenil (EDEIJ): evidências de validade

2023· article· pt· W4385768483 on OpenAlexaff
Makilim Nunes Baptista, Ana Paula Porto Noronha, Bruno Bonfá-Araújo

Bibliographic record

VenueCiencias Psicológicas · 2023
Typearticle
Languagept
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsWestern University
Fundersnot available
KeywordsPsychologyHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

A autorregulação emocional frente a eventos tristes é essencial nas diferentes fases do desenvolvimento humano, principalmente ao tratar-se de crianças e adolescentes, uma vez que diferentes estratégias de autorregulação podem ser fatores protetivos a transtornos mentais como a depressão. Dado a existência da Escala de Autorregulação Emocional-Infantojuvenil (EARE-IJ) para mensurar tais eventos, este artigo tem como objetivo apresentar a versão revisada do instrumento, com o intuito de aprimorá-la, buscar evidências de validade baseadas na estrutura interna e índices de fidedignidade. Responderam ao instrumento 299 crianças e adolescentes, com idades de 10 até 16 anos (M = 12,20; DP = 1,36), de modo que foram testados diferentes modelos de análise fatorial confirmatória, coeficientes de confiabilidade e um modelo de invariância para a variável sexo. Os resultados acumulam evidências favoráveis para o instrumento em sua nova versão, passando a ser conhecida como Escala de Desregulação Emocional Infantojuvenil (EDEIJ). Além de indicarem que o instrumento é capaz de avaliar crianças e adolescentes com diferentes níveis de desregulação emocional, bem como possui invariância configural e métrica. Conclui-se que a ferramenta é eficiente para realizar o rastreio de estratégias de autorregulação emocional em crianças e adolescentes.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.699
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.007

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 head0.051
GPT teacher head0.335
Teacher spread0.284 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2023
Admission routes1
Has abstractyes

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