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Record W2739380536 · doi:10.5014/ajot.2017.022053

Impact of the Cognitive–Functional (Cog–Fun) Intervention on Executive Functions and Participation Among Children With Attention Deficit Hyperactivity Disorder: A Randomized Controlled Trial

2017· article· en· W2739380536 on OpenAlexaboutno aff
Jeri Hahn‐Markowitz, Itai Berger, Iris Manor, Adina Maeir

Bibliographic record

VenueAmerican Journal of Occupational Therapy · 2017
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsnot available
Fundersnot available
KeywordsExecutive functionsCogIntervention (counseling)Randomized controlled trialAttention deficit hyperactivity disorderCognitionPsychologyCrossover studyClinical psychologyOccupational therapyExecutive dysfunctionPhysical therapyPsychiatryMedicineNeuropsychologyAlternative medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: We examined the effect of the Cognitive-Functional (Cog-Fun) occupational therapy intervention on executive functions and participation among children with attention deficit hyperactivity disorder (ADHD). METHOD: We used a randomized, controlled study with a crossover design. One hundred and seven children age 7-10 yr diagnosed with ADHD were allocated to treatment or wait-list control group. The control group received treatment after a 3-mo wait. Outcome measures included the Behavior Rating Inventory of Executive Function (BRIEF) and the Canadian Occupational Performance Measure (COPM). RESULTS: Significant improvements were found on both the BRIEF and COPM after intervention with large treatment effects. Before crossover, significant Time × Group interactions were found on the BRIEF. CONCLUSION: This study supports the effectiveness of the Cog-Fun intervention in improving executive functions and participation among children 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 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)0.001
metaresearch head score (Gemma)0.001
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 score0.090
Threshold uncertainty score0.541

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.044
GPT teacher head0.375
Teacher spread0.331 · 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

Citations33
Published2017
Admission routes1
Has abstractyes

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