The Dutch residency educational climate test: construct and concurrent validation in Spanish language

Abstract

ObjectivesTo translate the 35-item version of the Dutch Residency Educational Climate Test (D-RECT), and assess its reliability, construct validity and concurrent validity in the Spanish language. MethodsFor this validation study, the D-RECT was translated using international recommendations. A total of 220 paper-based resident evaluations covering two Colombian universities were cross-sectionally collected in 2015. A Confirmatory Factor Analysis (CFA) was used to assess the internal validity of the instrument using the Comparative fit index (CFI), Tucker-Lewis index (TLI), Standardized root mean square residual (SRMSR), and Root mean square error of approximation (RMSA). Cronbach’s α was used to assess reliability. The concurrent validity was investigated through Pearson correlations with the Spanish version of the Postgraduate Hospital Educational Environment Measure (PHEEM). ResultsThe original 9-factor structure showed an appropriate fit for the Spanish version of the instrument (CFI = 0.84, TLI = 0.82, SRMSR = 0.06, and RMSA = 0.06). The reliability coefficients were satisfactory (>0.70). The mean total scores of the D-RECT and the PHEEM showed a significant correlation (r = 0.7, p<0.01). ConclusionsThis study confirms the validity and reliability of the Spanish version of the Dutch Residency Educational Climate Test, indicating that the instrument is suitable for the evaluation of departments’ learning climate in the Spanish context. Future research is needed to confirm these findings in other Spanish speaking countries.

Validation of the French translation of the Dutch Residency Educational Climate Test

“…As for the other studies [24,25,27], the scores obtained varied between 0.7 and 0.91, indicating a good internal consistency of the French version. Temporal stability indices were evaluated by asking subjects to ll the instrument twice.…”

“…RMSEA (root mean square error of approximation) is a parsimony correction Indice that tests the extent to which the model fits reasonably well in the population [32,33]. We found that the SRMR (0.058) had a good t (<0.06), and RMSEA (0.07) had an acceptable t (<0.10), indicating that the tested model ts well to the data [24]. Both comparative t indices, CFI (0.88) and TLI (0.87) were close to the 0.90 threshold, indicating a limited improvement of the tested model relative to a restricted, nested baseline model [32,33].…”

“…It is important to note that these are not rigid guidelines, and Brown comments that his use of "close to" for threshold values is intentional [32]. The most used indices of goodness of t are SRMR, RMSEA, CFI and TLI [24,27,43,44]. The SRMR (Standardized Root Mean Square Residual) is an absolute t index that is based on the discrepancy between the correlations in the input matrix and the correlations predicted by the model [32,33].…”

“…Based on Brown's recommendations, two indicators, SRMR (0.058) and RMSEA (0.07) had satisfactory results and two indicators, CFI (0.88) and TLI (0.87) had a result slightly below the recommended threshold. Table 3 also shows comparison of CFA results with all other studies that validated the revisited DRECT [24,25,27]. For convergent validity, factor loadings ranged between 0.48 and 0.93 (supplementary material 2).…”

“…Columbia [24,25]. In order to be accepted, the validation of the psychometric properties of a translated version must follow a rigorous process, especially when translating instruments from different countries and cultures.…”