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Record W3202643583 · doi:10.1080/07853890.2021.1896840

Translation of professionalism in physical therapy questionnaire for Portuguese of Portugal: Core values

2021· article· en· W3202643583 on OpenAlexaboutno aff
Mariana Ferreira Alves de Carvalho, Sofia Mateus, Fábio Pinto, I Corro Ramos, Sónia Vicente, Ângela Maria Pereira

Bibliographic record

VenueAnnals of Medicine · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDelphi Technique in Research
Canadian institutionsnot available
Fundersnot available
KeywordsExcellenceDutyCurriculumDelphi methodMedical educationMedicinePsychologyPedagogyPolitical scienceArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

Introduction Physiotherapists play a key role in today’s healthcare and are recognised as the professionals in charge of rehabilitation, prevention and risk reduction [1 Jensen GM, Hack LM, Nordstrom T, et al. National study of excellence and innovation in physical therapist education: part 2 – a call to reform. Physical Therapy. 2017;97(9):875–888.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]]. Professionalism is interconnected and inherent with the profession; physiotherapists have the duty to act in an ethically correct way and for this must be governed by certain ethical principles [2 Bialocerkowski A, Johnson A, Allan T, et al. Development of physiotherapy inherent requirement statements – an Australian experience. BMC Med Educ. 2013;13(54):1–13.[PubMed] , [Google Scholar]]. The evaluation of professionalism is difficult to achieve because of various qualities that should be present, and also because it is needed to use several measurement methods, particularly in complex real world contexts [3 Hodges BD, Ginsburg S, Cruess R, et al. Assessment of professionalism: recommendations from the Ottawa 2010 Conference. Med Teach. 2011;33(5):354–363.[Taylor & Francis Online] , [Google Scholar]]. The linguistic adaptation of an instrument is carried out using the Delphi Method, which brings a group of experts where a series of rounds is conducted until consensus of the translation is reached [4 Green AR. The Delphi technique in educational research. SAGE Open. 2014;4(2):215824401452977–215824401452978.[Crossref] , [Google Scholar]]. The aim of the study is the translation of the instrument Professionalism in Physical Therapy: Core Values, of the American Physical Therapy Association (APTA), with the intention to be used by physiotherapists in Portugal.Materials and methods The translation/back-translation was made by the Delphi Method with three rounds which were performed until de adaptation of the instrument to the Portuguese culture was achieved. A group of five experts, all with master and PhD academic degree, all with more than 25 years as Physiotherapist and Portuguese as their first language were selected.Results In order to reach consensus on the translation of the instrument, 3 rounds were carried out using the Delphi method, thus allowing linguistic equivalence to be obtained. In the 1st round of the process regarding the physical therapist's part, a 92 questions questionnaire was sent to the experts. In the 2nd round 42 questions were held and in the 3rd and final round, 5 questions were translated. Regarding the patient's part of the questionnaire, in the 1st round 18 questions were sent and in the 2nd round the number decreased to 9 questions. Consensus was achieved at 2nd round. The level of minimum agreement in each item was set to 80%, ensuring good translation and adaptation for Portuguese culture.Discussion and conclusions The aim of the study was achieved, and the linguistic translation was completed. As next step, it is needed to conduct validation of the instrument for Portuguese culture by performing a pre-test. The results of this content validation by experts will be useful to improve the standard of care, teaching and research in physiotherapy, based on a standardised instrument which allow to measure Portuguese Physiotherapists professionalism, and perform international benchmark as well.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.664
Threshold uncertainty score0.213

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.473
GPT teacher head0.579
Teacher spread0.106 · 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 designOther design
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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Citations1
Published2021
Admission routes1
Has abstractyes

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