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Record W3007931994 · doi:10.1080/01942638.2020.1726551

Service Providers’ Perspectives on Using the ‘F-Words in Childhood Disability’: An International Survey

2020· article· en· W3007931994 on OpenAlexaff
Alice Kelen Soper, Andrea Cross, Peter Rosenbaum, Jan Willem Gorter

Bibliographic record

VenuePhysical & Occupational Therapy In Pediatrics · 2020
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsMcMaster University
Fundersnot available
KeywordsOperationalizationInternational Classification of Functioning, Disability and HealthService providerLikert scalePsychologyMedical educationService (business)Clinical PracticeMedicineNursingRehabilitationDevelopmental psychologyBusiness

Abstract

fetched live from OpenAlex

AIMS: The 'F-words in Childhood Disability' - operationalizing the International Classification of Functioning, Disability and Health Framework - have attracted great interest around the world. However, we have yet to learn how service providers (SPs) are using them. The aim of this study was to explore international SPs' attitudes toward and use of the 'F-words'. METHODS: A survey was administered, guided by the Theory of Planned Behavior, including Likert-scaled statements and an open-ended question. Ninety-one SPs working with children with impairments from 27 countries completed the survey. RESULTS: While 82 agreed the 'F-words' are good practice, only 60 are using the 'F-words'. Similarly, 52 SPs agreed that their colleagues approved of their use and 54 felt they were easy for families to use and understand. Respondents reported three main uses: (i) support of preexisting clinical approaches, (ii) direct integration into practice, and (iii) being taught in higher education. They also identified barriers to implementation (e.g., alternative clinical approaches and limited resources). CONCLUSIONS: Findings provide insights in how the 'F-words' are being used and the limitations thereof, which can inform future directions to support international implementation. With international SPs, we need to develop adapted dissemination tools to support uptake by individuals worldwide.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.489

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.079
GPT teacher head0.369
Teacher spread0.290 · 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 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

Citations16
Published2020
Admission routes1
Has abstractyes

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