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Record W3174375172 · doi:10.1177/10870547211025629

Are There Resilient Children with ADHD?

2021· article· en· W3174375172 on OpenAlex
Elizabeth Chan, Nicole B. Groves, Carolyn L. Marsh, C. Miller, Kijana P. Richmond, Michael Kofler

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

VenueJournal of Attention Disorders · 2021
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Mental Health
KeywordsPsychologyFlourishingComorbidityPsychological resilienceAttention deficit hyperactivity disorderClinical psychologyDevelopmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: The adverse outcomes associated with ADHD are well known, but less is known about the minority of children with ADHD who may be flourishing despite this neurodevelopmental risk. The present multi-informant study is an initial step in this direction with the basic but unanswered question: METHOD: Reliable change analysis of the BASC-3 Resiliency subscale for a clinically evaluated sample of 206 children with and without ADHD (ages 8-13; 81 girls; 66.5% White/Non-Hispanic). RESULTS: Most children with ADHD are perceived by their parents and teachers as resilient (52.8%-59.2%), with rates that did not differ from the comorbidity-matched Non-ADHD sample. CONCLUSION: Exploratory analyses highlighted the importance of identifying factors that promote resilience for children with ADHD specifically, such that some child characteristics were promotive (associated with resilience for both groups), some were protective (associated with resilience only for children with ADHD), and some were beneficial only for children without ADHD.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.970

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 head0.022
GPT teacher head0.297
Teacher spread0.275 · 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