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Record W4387047975 · doi:10.1186/s12909-023-04675-6

Adaptation of the professionalism mini-evaluation exercise instrument into Turkish: a validity and reliability study

2023· article· en· W4387047975 on OpenAlexaboutno aff
Ali İhsan Taşçı, Esra Akdenız, Mehmet Ali Gülpınar, Yavuz Onur Danacıoğlu, Emine Ergül Sarı, Levent Yaşar, Faruk Karandere, Sina Ferahman

Bibliographic record

VenueBMC Medical Education · 2023
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsnot available
Fundersnot available
KeywordsCronbach's alphaConfirmatory factor analysisConstruct validityTurkishReliability (semiconductor)Scale (ratio)Structural equation modelingMedical educationValidityPsychologyMedicineApplied psychologyAdaptation (eye)Content validityClinical psychologyPsychometricsStatistics

Abstract

fetched live from OpenAlex

BACKGROUND: There is an ongoing search for standardized scales appropriate for each culture to evaluate professionalism, which is one of the basic competencies of a physician. The Professionalism Mini-evaluation Exercise (P-MEX) instrument was originally developed in Canada to meet this need. In this study, it was aimed to adapt the P-MEX to Turkish and to evaluate the validity and reliability of the Turkish version. METHODS: A total of 58 residents at Bakirkoy Dr. Sadi Konuk Training and Research Hospital were assessed with the Turkish version of P-MEX by 24 raters consisting of faculty members, attending physicians, peer residents, and nurses during patient room visits, outpatient clinic and group practices. For construct validity, the confirmatory factor analysis was performed. For reliability, Cronbach's alpha scores were calculated. Generalizibility and decision studies were undertaken to predict the reliability of the validated tool under different conditions. After the administration of P-MEX was completed, the participants were asked to provide feedback on the acceptability, feasibility, and educational impact of the instrument. RESULTS: A total of 696 forms were obtained from the administration of P-MEX. The content validity of P-MEX was found to be appropriate by the faculty members. In the confirmatory factor analysis of the original structure of the 24-item Turkish scale, the goodness-of-fit parameters were calculated as follows: CFI = 0.675, TLI = 0.604, and RMSEA = 0.089. In the second stage, the factors on which the items loaded were changed without removing any item, and the model was modified. For the modified model, the CFI, TLI, and RMSEA values were calculated as 0.857, 0.834, and 0.057, respectively. The decision study on the results obtained from the use of P-MEX in a Turkish population revealed the necessity to perform this evaluation 18 times to correctly evaluate professionalism with this instrument. Cronbach's alpha score was 0.844. All the faculty members provided positive feedback on the acceptability, feasibility, and educational impact of the adapted P-MEX. CONCLUSION: The findings of this study showed that the Turkish version of P-MEX had sufficient validity and reliability in assessing professionalism among residents. Similarly, the acceptability and feasibility of the instrument were found to be high, and it had a positive impact on education. TRIAL REGISTRATION: 2020/249, Bakirkoy Dr. Sadi Konuk Training and Research Hospital.

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)0.007
metaresearch head score (Gemma)0.014
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 score0.007
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.098
GPT teacher head0.427
Teacher spread0.329 · 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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Citations6
Published2023
Admission routes1
Has abstractyes

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