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Record W2099267992 · doi:10.5014/ajot.2010.09072

Exploring the Effectiveness of Occupational Therapy Interventions, Other Than the Sensory Integration Approach, With Children and Adolescents Experiencing Difficulty Processing and Integrating Sensory Information

2010· review· en· W2099267992 on OpenAlexaff
Helene J. Polatajko, Noémi Cantin

Bibliographic record

VenueAmerican Journal of Occupational Therapy · 2010
Typereview
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOccupational therapyPsychological interventionSensory processingIntervention (counseling)Sensory systemInclusion (mineral)PsychologyHomogeneousClinical psychologyAssociation (psychology)MedicinePsychotherapistCognitive psychologyPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

This literature review was completed as part of the Evidence-Based Literature Review Project of the American Occupational Therapy Association to explore the effectiveness of occupational therapy interventions with children and adolescents experiencing difficulty processing and integrating sensory information. This part of the review focused on interventions other than the sensory integration approach. Twenty articles (reporting on 21 studies) met the inclusion criteria. This systematic review found that children with difficulty processing and integrating sensory information and difficulties with the performance of daily occupations can benefit from intervention. However, the great variability that characterizes this literature in terms of populations, interventions, and study quality precludes the formation of any firm conclusions regarding specific approaches. There is an urgent need for well-controlled studies examining the effectiveness of frequently used pediatric occupational therapy interventions with well-defined, homogeneous populations on outcomes that target participation in everyday life.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.984
Threshold uncertainty score0.798

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.110
GPT teacher head0.373
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations73
Published2010
Admission routes1
Has abstractyes

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