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Record W2340215435 · doi:10.1093/jpepsy/jsv116

Positive Illusions? The Accuracy of Academic Self-Appraisals in Adolescents With ADHD

2015· article· en· W2340215435 on OpenAlexaff
Todd Chan, Rhonda Martinussen

Bibliographic record

VenueJournal of Pediatric Psychology · 2015
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsLockheed Martin (Canada)University of Toronto
Fundersnot available
KeywordsPsychologyAttention deficit hyperactivity disorderDevelopmental psychologyClinical psychology

Abstract

fetched live from OpenAlex

OBJECTIVE: Children with attention deficit/hyperactivity disorder (ADHD) overestimate their academic competencies (AC) relative to performance and informant indicators (i.e., positive illusory bias; PIB). Do adolescents with ADHD exhibit this PIB and does it render self-views inaccurate? We examined the magnitude of the AC-PIB in adolescents with and without ADHD, the predictive accuracy of parent and adolescent AC ratings, and whether executive functions (EF) predict the AC-PIB. METHOD: Adolescents (49 ADHD; 47 typically developing) completed math and EF tests, and self-rated their AC. Parents rated their adolescents' AC and EF. RESULTS: Adolescents with ADHD performed more poorly on the math task (vs. comparison group) but had a larger AC-PIB relative to parents' ratings. EFs predicted the PIB within the full sample. Adolescents' AC ratings, regardless of ADHD status, were more predictive of math performance than their parents' AC ratings. CONCLUSION: Adolescents with ADHD appear self-aware in their AC despite a modest PIB; nuanced self-appraisals may depend on EFs.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.007
Threshold uncertainty score0.441

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.071
GPT teacher head0.411
Teacher spread0.340 · 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

Citations25
Published2015
Admission routes1
Has abstractyes

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