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Record W2168896345 · doi:10.1037/a0026001

A web-based intervention for elementary school teachers of students with attention-deficit/hyperactivity disorder (ADHD).

2011· article· en· W2168896345 on OpenAlexafffundabout
Brittany Barnett, Penny Corkum, Nezihe Elik

Bibliographic record

VenuePsychological Services · 2011
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsDalhousie University
FundersNova Scotia Health Research Foundation
KeywordsAttention deficit hyperactivity disorderPsychologyCompetence (human resources)Intervention (counseling)School teachersClinical psychologyKnowledge translationDevelopmental psychologyMedical educationPsychiatryMedicineMathematics educationSocial psychologyComputer science

Abstract

fetched live from OpenAlex

The goal of the present study was to determine whether a web-based medium is an effective tool for supporting knowledge, attitude, and behavior change in teachers of elementary school children with attention-deficit/hyperactivity disorder (ADHD). Nineteen teachers from Nova Scotia, Canada completed a 7-week intervention that consisted of presentations, web links, and discussion board activities related to different aspects of ADHD. Teachers' knowledge positively changed from pre- to post-intervention (p = .03), as did teachers' attitudes related to perceived control in their classrooms (p = .001) and competence in teaching (p < .0001). The study demonstrated that a web-based medium is a useful tool for knowledge creation and translation and has potential as a means of providing professional development to teachers about 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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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 science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.051
GPT teacher head0.372
Teacher spread0.321 · 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 designNon-randomized trial
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

Citations38
Published2011
Admission routes3
Has abstractyes

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