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Record W2135956618 · doi:10.3109/07434618.2012.704525

Family Impact of Assistive Technology Scale: Development of a Measurement Scale for Parents of Children with Complex Communication Needs

2012· article· en· W2135956618 on OpenAlexafffund
Elizabeth Delarosa, S HORNER, Casey Eisenberg, Laura J. Ball, Anne Marie Renzoni, Stephen E. Ryan

Bibliographic record

VenueAugmentative and Alternative Communication · 2012
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsHolland Bloorview Kids Rehabilitation HospitalUniversity of Toronto
FundersCanadian Institutes of Health ResearchHealth~HollandHolland Bloorview Kids Rehabilitation Hospital Foundation
KeywordsScale (ratio)Assistive technologyAugmentative and alternative communicationPsychologyDevelopmental psychologyComputer scienceHuman–computer interactionGeographyCartographyPsychiatry

Abstract

fetched live from OpenAlex

Young people use augmentative and alternative communication (AAC) systems to meet their everyday communication needs. However, the successful integration of an AAC system into a child's life requires strong commitment and continuous support from parents and other family members. This article describes the development and evaluation of the Family Impact of Assistive Technology Scale for AAC Systems - a parent-report questionnaire intended to detect the impact of AAC systems on the lives of children with complex communication needs and their families. The study involved 179 parents and clinical experts to test the content and face validities of the questionnaire, demonstrate its internal reliability and stability over time, and estimate its convergent construct validity when compared to a standardized measure of family impact.

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)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.168
GPT teacher head0.457
Teacher spread0.289 · 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 designObservational
Domainnot available
GenreMethods

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

Citations40
Published2012
Admission routes2
Has abstractyes

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