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Record W2090469523 · doi:10.1080/10400435.2010.483645

Perceptions of Writing and Communication Aid Use Among Children with a Physical Disability

2010· article· en· W2090469523 on OpenAlexaff
Alysia Carpe, Katie Harder, Cynthia Tam, Denise Reid

Bibliographic record

VenueAssistive Technology · 2010
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsHolland Bloorview Kids Rehabilitation HospitalBridgepoint Active HealthcareUniversity of TorontoPublic Health Ontario
Fundersnot available
KeywordsPerceptionPsychologyAssistive technologyPhysical disabilityMedical educationApplied psychologyPhysical therapyEngineeringMedicineMultimediaPhysical medicine and rehabilitationComputer scienceHuman–computer interaction

Abstract

fetched live from OpenAlex

Children with physical disabilities (CPD) often experience decreased opportunities to participate in daily occupations. Occupational therapists (OTs) prescribe writing and communication aids; however, little is known about this population's perceptions of the technology. This qualitative study explored the perceptions that CPD had regarding their writing and communication aids. Children were interviewed; a focus group of one parent and two OTs provided context to the children's comments. Enablers and barriers to using communication aids were found. Participants reported a greater sense of pride, more self-confidence, and a greater sense of autonomy and productivity with the technology. Analysis of the interviews, focus group, and reflective notes resulted in a model showing how enablers and barriers of on-screen technology usage relates to occupational enhancement or occupational detriment. This study contributes to an understanding of the meaning that CPD associate with writing technology and the factors associated with usage.

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)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.384
Teacher spread0.357 · 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 designQualitative
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

Citations15
Published2010
Admission routes1
Has abstractyes

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