MétaCan
Menu
Back to cohort
Record W3191474664

Does knowledge about attention-deficit/hyperactivity disorder impact teachers' reported behaviors and perceptions?

2008· article· en· W3191474664 on OpenAlexaff
Jeneva L. Ohan, Nicole Cormier, Shellane L. Hepp, Troy A. W. Visser, Melanie C. Strain

Bibliographic record

VenueUWA Profiles and Research Repository (University of Western Australia) · 2008
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsPsychologyPerceptionAttention deficit hyperactivity disorderStrengths and weaknessesAttention deficitDevelopmental psychologyGeneral knowledgeKnowledge levelClinical psychologySocial psychologyMathematics education
DOInot available

Abstract

fetched live from OpenAlex

This study surveyed elementary school teachers in Melbourne, Australia to investigate their knowledge about attention-deficit/hyperactivity disorder (ADHD) and its impact on their reported behavior toward and perceptions of children with ADHD. Consistent with previous international findings, teachers demonstrated good overall knowledge about ADHD, with strengths in knowledge of symptoms/diagnosis and weaknesses in knowledge of causes and treatments. To investigate how knowledge impacted reported behaviors and perceptions, teachers also read vignettes of children with ADHD symptoms and rated their reactions to these children. In general, teachers with high, and to some extent average, knowledge about ADHD reported more helpful behaviors (e.g., help-seeking for their students) and perceptions (e.g., perceive the benefit of behavioral and educational treatments). However, teachers with high and average knowledge also predicted that these children would be more disruptive in the classroom, and reported having less confidence in their ability to manage these children. Implications and need for future research are discussed.

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)0.000
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 score0.054
Threshold uncertainty score0.732

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 studies0.0010.001
Scholarly communication0.0000.001
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 head0.081
GPT teacher head0.382
Teacher spread0.301 · 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

Citations8
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueUWA Profiles and Research Repository (University of Western Australia)Same topicAttention Deficit Hyperactivity DisorderFrench-language works237,207