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Record W3003663977 · doi:10.1177/0308022619897877

The occupational repertoires of children with mobility difficulties: The child’s perspective

2020· article· en· W3003663977 on OpenAlexaff
Tatiana Barcelos Pontes, Katie Mah, Adrianne K Arnold, Helene J. Polatajko, Jane A. Davis

Bibliographic record

VenueBritish Journal of Occupational Therapy · 2020
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsToronto Rehabilitation InstituteUniversity of Toronto
Fundersnot available
KeywordsOccupational therapyPerspective (graphical)PsychologyOccupational mobilityPsychological interventionDevelopmental psychologyOccupational sciencePsychiatry

Abstract

fetched live from OpenAlex

Introduction Children with mobility difficulties are thought to share similar participation repertoires due to the impact of their physical impairments. However, with these children, as with all others, individual differences and contexts should mediate occupational repertoires and experiences, resulting in participation differences, at least in part. This study aimed to explore the occupational repertoires of children with mobility difficulties and their view of their occupational participation. Methods Five children with mobility difficulties were assessed using the paediatric activity card sort, to establish their occupational repertoires. Semi-structured interviews were used to understand the children’s occupational participation. Findings Our findings suggest that children with mobility issues are more likely to participate in quiet occupations, but not exclusively. The children defined participation in their own way. Conclusion The knowledge about how children with mobility difficulties understand participation in occupation can help occupational therapists to establish goals with their clients and personalise interventions.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.161
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.115
GPT teacher head0.436
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 teacher head, not a consensus.

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

Citations7
Published2020
Admission routes1
Has abstractyes

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