MétaCan
Menu
Back to cohort
Record W4362732583 · doi:10.1177/10870547231167512

“I’m Doing Okay”: Strengths and Resilience of Children With and Without ADHD

2023· article· en· W4362732583 on OpenAlexafffund
Emma Charabin, Emma A. Climie, Courtney Miller, Kristina Jelinkova, Jessica Wilkins

Bibliographic record

VenueJournal of Attention Disorders · 2023
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsUniversity of Calgary
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyPsychological resilienceDevelopmental psychologyPerspective (graphical)Resilience (materials science)Strengths and Difficulties QuestionnaireClinical psychologyPopulationAttention deficit hyperactivity disorderPsychiatryMental healthSocial psychologyMedicineEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: The body of research directed at understanding the strengths and resilience of this population is growing. Research has indicated there are strengths for individuals with ADHD, and found factors important for promoting good outcomes. This study investigates positive qualities by examining the strengths and resilience of children with and without ADHD. METHODS: = 18). RESULTS: Children in both groups tended to report average levels of strengths and resilience except for school functioning, where significant differences were found between groups. Significant correlations between strengths and resilience for both groups were found. Only family involvement was not significantly correlated with resilience for the without ADHD group. CONCLUSIONS: Results from this study emphasize the importance of taking a strength-based perspective when working with children diagnosed with 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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.310
Teacher spread0.297 · 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 source (direct Gemma or distilled Codex), 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

Citations23
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Attention DisordersSame topicAttention Deficit Hyperactivity DisorderFrench-language works237,207