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Record W2064866540 · doi:10.3109/07434618.2011.653828

Using the WHO-ICF with Talking Mats to Enable Adults with Long-term Communication Difficulties to Participate in Goal Setting

2012· article· en· W2064866540 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAugmentative and Alternative Communication · 2012
Typearticle
Languageen
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsnot available
FundersCanadian Stroke Network
KeywordsInternational Classification of Functioning, Disability and HealthRehabilitationTerm (time)Process (computing)Augmentative and alternative communicationApplied psychologyPsychologyConjunction (astronomy)Health professionalsGoal settingTracking (education)Medical educationComputer scienceKnowledge managementNursingMedicineHealth carePedagogySocial psychologyPolitical sciencePsychiatry

Abstract

fetched live from OpenAlex

The World Health Organization International Classification of Functioning, Disability and Health (WHO-ICF) provides a framework that helps rehabilitation staff to take a holistic view of the patient. However, it is used predominantly by professionals rather than by active participation on behalf of the person with the disability. In addition, the language used within the framework can be difficult for patients to understand. In order to address these issues the Activities and Participation section of the ICF has been adapted by using graphic symbols. It has been used in conjunction with Talking Mats(™ 1 ), a low-tech communication framework, to help adults with long-term conditions participate in goal setting. This paper describes how this was done and provides examples from clinical practice. The paper discusses how this combined framework can empower people with communication difficulties and long-term conditions to become active participants in the rehabilitation process by identifying their own goals, indicating changing priorities and tracking their progress.

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.

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 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 score0.052
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.112
GPT teacher head0.457
Teacher spread0.346 · 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