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Record W2166175177 · doi:10.1177/1087054710392541

The Relationship Between ADHD Symptoms and Competence as Reported by Both Self and Others

2011· article· en· W2166175177 on OpenAlexafffund
Yuanyuan Jiang, Charlotte Johnston

Bibliographic record

VenueJournal of Attention Disorders · 2011
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsUniversity of British Columbia
FundersCanadian Institutes of Health ResearchMichael Smith Health Research BC
KeywordsPsychologyCompetence (human resources)Clinical psychologyInter-rater reliabilityDevelopmental psychologyRating scaleSocial psychology

Abstract

fetched live from OpenAlex

OBJECTIVE: This study examines the relative relationships of self- and other-reports of adult ADHD symptoms to important life competencies, and also investigates whether self- and other-reports of ADHD symptoms are differentially associated with interrater differences in reports of competence. METHOD: A total of 91 women completed a self-perception questionnaire assessing competence. Other individuals who knew the women well completed the same questionnaire with regard to the women. The women's ADHD symptoms were also rated by themselves and others. RESULTS: Regressions of self- and other-reports of ADHD symptoms on competence scores suggest that other-reports of ADHD symptoms are more valid than self-reports. Also, correlations between reports of ADHD symptoms and interrater differences in rated competence were consistent with a positive illusory bias among women with high ADHD symptoms. CONCLUSION: Other-reports of ADHD symptoms may be better associated with an individual's competence than self-reports.

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)0.002
metaresearch head score (Gemma)0.022
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 score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
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 head0.056
GPT teacher head0.318
Teacher spread0.262 · 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

Citations30
Published2011
Admission routes2
Has abstractyes

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