Meslekler Arası Ekip İş Birliğinin Değerlendirilmesi Ölçeğinin Türkçeye Uyarlanması: Geçerlilik ve Güvenilirlik Çalışması (T-AITCS-II)
Bibliographic record
Abstract
The purpose of this study was to adapt the Assessment of Interprofessional Team Collaboration Scale (AITCS-II), which was developed in 2012 by Orchard, King, Khalili, Bezzina-revised in 2018 by Orchard, Pedersen, Read, Mahler, Laschinger- into Turkish, and to examine the psychometric properties. The scale is a five-point Likert-type scale in its original form; it consists of 3 dimensions and 23 items. Explanatory and confirmatory factor analysis was performed to ensure construct validity. Explanatory factor analysis results revealed that the scale explained a total of 60,725% variance in three dimensions. The model fit of the three-dimensional structure was tested by confirmatory factor analysis. In confirmatory factor analysis, it was determined that the scale was classified into three sub-dimensions, as in the original. It was concluded that the model fit indices were at a good level with χ2/df=2.280, RMSEA=0.054, GFI=0.91, CFI=0.99. It was concluded that the CR values of the factor dimensions were higher than 0.70 and the AVE values were higher than 0.50. It has been determined that the diagonal elements of the matrices belonging to the square roots of the AVE values (√AVE) are larger than the correlation coefficients, which is the off-diagonal element of the matrix. It was determined that the factor structure of the scale was appropriate with the data obtained. Factor Cronbach's Alpha values for internal consistency were between 0.877 and 0.915, and the overall internal consistency value of the scale was found to be 0.945. As a result, it has been determined that the Turkish version of Assessment of Interprofessional Team Collaboration Scale is a valid and reliable measurement tool that can be used to determine the level of interprofessional team collaboration.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".