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Record W2045789676 · doi:10.1016/j.rbr.2014.04.003

Tradução e validação do Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST 2.0) para o idioma português do Brasil

2014· article· pt· W2045789676 on OpenAlexaboutno aff
Karla Emanuelle Cotias de Carvalho, Miburge Bolívar Gois Júnior, Kátia Nunes Sá

Bibliographic record

VenueRevista Brasileira de Reumatologia · 2014
Typearticle
Languagept
FieldHealth Professions
TopicAssistive Technology in Communication and Mobility
Canadian institutionsnot available
Fundersnot available
KeywordsCronbach's alphaBrazilian PortugueseHumanitiesPortugueseMedicineClinical psychologyArtPhilosophy

Abstract

fetched live from OpenAlex

Traduzir e validar o Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST 2.0) para o idioma Português do Brasil. Tradutores juramentados traduziram e retrotraduziram o Quest. A validade do conteúdo (IVC) foi determinada por cinco especialistas e, após a versão final do B‐Quest, foi aplicado um pré‐teste a usuários de cadeiras de rodas manuais, andadores e muletas. As propriedades psicométricas foram testadas como garantia da validade dos itens, confiabilidade e estabilidade da escala. Foram obtidos dados de 121 usuários dos dispositivos mencionados. Nosso es‐tudo demonstrou um IVC de 91,66% e uma análise de fatores satisfatória com referência à estrutura bidimensional do instrumento, o que assegurou a representatividade dos itens. Os coeficientes alfa de Cronbach dos itens «dispositivo», «serviços» e «escore total» do B--Quest foram 0,862, 0,717 e 0,826, respectivamente. A estabilidade de teste‐reteste, reali‐zada após terem transcorrido dois meses, foi analisada com o uso do teste de correlação de Spearman, tendo sido demonstrada elevada correlação (ρ>0,6) para a maioria dos itens. Conclusão: O estudo sugere que o B‐Quest é um instrumento confiável, representativo e válido para a medição da satisfação de usuários de tecnologia assistiva no Brasil. To translate and validate the Quebec User Evaluation of Satisfaction with Assistive Technology (QUEST 2.0) into Brazilian Portuguese. Certified translators translated and back‐translated Quest. Content validity (CVI) was determined by 5 experts and, after the final version of B‐Quest, a pre‐test was applied to users of manual wheelchairs, walkers and crutches. The psychometric properties were tested to assure the validity of items and the reliability and stability of the scale. Data were obtained from 121 users of the above‐mentioned devices. Our study showed a CVI of 91.66% and a satisfactory factor analysis referent to the two‐dimensional structure of the instrument that ensured the representativeness of the items. The Cron‐bach's alpha of the items device, service and total score of B‐Quest were 0.862, 0.717 and 0.826, respectively. Test‐retest stability conducted after a time interval of 2 months was analyzed using Spearman's correlation test, which showed high correlation (ρ >0.6) for most items. The study suggests that the B‐Quest is a reliable, representative, and valid instrument to measure the satisfaction of users of assistive technology in Brazil.

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)0.009
metaresearch head score (Gemma)0.015
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.644
Threshold uncertainty score0.717

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.400
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 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
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".

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Citations73
Published2014
Admission routes1
Has abstractyes

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