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Record W2001485016 · doi:10.3109/01942631003761554

Exploring the Use of Cognitive Intervention for Children with Acquired Brain Injury

2010· article· en· W2001485016 on OpenAlexaff
Cheryl Missiuna, Carol DeMatteo, Steven Hanna, Angela Mandich, Mary Law, William J. Mahoney, L Zuckerman Scott

Bibliographic record

VenuePhysical & Occupational Therapy In Pediatrics · 2010
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsAcquired brain injuryCognitionPsychologyOccupational therapyIntervention (counseling)PsychosocialAffect (linguistics)PopulationActivities of daily livingClinical psychologyDevelopmental psychologyRehabilitationMedicinePsychiatry

Abstract

fetched live from OpenAlex

INTRODUCTION: Children with acquired brain injury (ABI) often experience cognitive, motor, and psychosocial deficits that affect participation in everyday activities. Cognitive Orientation to Daily Occupational Performance (CO-OP) is an individualized treatment that teaches cognitive strategies necessary to support successful performance. OBJECTIVE: This study explores the use of CO-OP with children with ABI. METHOD: Children with ABI, experiencing school and self-care difficulties, were identified from a previous study. Six children, aged 6-15 years, completed 10 weekly intervention sessions with occupational therapists. Children and parents rated the child's performance of challenging everyday tasks and their satisfaction with this performance. Task performance was also evaluated objectively through videotape analysis. RESULTS: Participants showed significant improvement in their ability to perform child-chosen tasks and maintained this performance 4 months later. However, they had difficulty applying the executive problem-solving strategy and discovering cognitive strategies on their own. Issues related to the use of CO-OP with this population 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)0.001
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 score0.264
Threshold uncertainty score0.341

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
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 head0.242
GPT teacher head0.414
Teacher spread0.171 · 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

Citations49
Published2010
Admission routes1
Has abstractyes

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