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Record W3146741004 · doi:10.21203/rs.3.rs-353852/v1

Cross-Cultural Validation of the Global Interprofessional Therapeutic Communication Scale© in the Korean context

2021· preprint· en· W3146741004 on OpenAlexaff
JuHee Lee, Suzanne Hetzel Campbell, Natália D. Aredes, Soomin Hong

Bibliographic record

VenueResearch Square · 2021
Typepreprint
Languageen
FieldHealth Professions
TopicInterprofessional Education and Collaboration
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCronbach's alphaConfirmatory factor analysisScale (ratio)PsychologyContext (archaeology)EmpathyHealth careReliability (semiconductor)Concurrent validityApplied psychologyNursingClinical psychologyPsychometricsSocial psychologyMedicineStructural equation modelingComputer scienceInternal consistency

Abstract

fetched live from OpenAlex

Abstract Background: Person-centered nursing is pivotal to the high-quality and safe practice of nursing, and therapeutic communication plays an essential role in this process. Therapeutic communication by healthcare professionals is vital in developing and maintaining constructive relationships with patients. The Global Interprofessional Therapeutic Communication Scale© (GITCS©) measures the therapeutic communication skills of healthcare providers. This scale is useful for assessing the verbal, non-verbal, and culturally sensitive therapeutic communication abilities of healthcare providers in various clinical situations. The purpose of this study was to evaluate the cross-cultural validity and reliability of the Korean version of the Global Interprofessional Therapeutic Communication Scale© (K-GITCS). Methods: A cross-cultural validation of a psychometric evaluation is conducted in the present study. The instrument was translated into Korean using the original developers’ translation process.A convenience sample of 300 registered nurses with more than one year of experience was recruited from a tertiary hospital. Validity was evaluated through a confirmatory factor analysis, and the instrument was tested for psychometric reliability.Results: The three-factor structure of the K-GITCS was validated. A confirmatory factor analysis of the K-GITCS was conducted, and the results satisfied the statistical criteria with a standardized root mean square residual of 0.06, a non-normed fit index of 0.88, a root mean square error of approximation of 0.07, and a comparative fit index of 0.82. The following factors were correlated: trust and rapport building, power-sharing, and empathy. Cronbach’s alpha was 0.94, indicating good internal consistency.Conclusions: Initial testing with experienced registered nurses in one institution indicated that the K-GITCS© instrument has adequate construct validity and reliability to identify therapeutic communication skills in this population. The K-GITCS can be used to assess registered nurses’ therapeutic communication. Further research using the GITCS is required to promote the communication skills of healthcare providers. Studies testing with nursing students and nurses in other institutions and interprofessional healthcare providers are also necessary. This instrument can offer valuable insights to guide its development and to devise tailored interventions considering the specific demands of registered nurses. It can be used in nursing education and clinical settings for evaluations of therapeutic communication skills.

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)0.010
metaresearch head score (Gemma)0.011
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 score0.010
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.136
GPT teacher head0.581
Teacher spread0.444 · 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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Citations0
Published2021
Admission routes1
Has abstractyes

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