Construct validity of informational skills for the application of Scientometrics

Introduction: Scientometrics, as a key discipline in the metric studies of information, requires specific informational skills for its effective application. This study focuses on validating the theoretical construct of informational skills for the application of scientometrics, aimed at tutors of the Health Information Systems career. Objective: to validate the theoretical construct of informational skills for the application of scientometrics. Method: A quantitative study was carried out with tutors from the Health Information Systems career where exploratory factor analysis (EFA) and confirmatory (CFA) techniques were used to evaluate the factor structure of the construct. The analyses were performed with IBM SPSS Statistics 25 and IBM AMOS 25. Results: The EFA revealed a two-factor structure with acceptable factor loads (values between 0.77 and 0.98). The TFA confirmed a two-factor model with an adequate fit (comparative fit index = 0.906, goodness of fit index = 0.844). Factor 1 grouped technical-operational skills (identification, collection, and presentation of data), while Factor 2 included critical-analytical skills (search strategies, quality assessment, analysis, and evaluation). Bartlett's sphericity test (p = 0.000) and the KMO index (0.709) supported the suitability of the data for factor analysis. Conclusions: The construct of informational skills for scientometrics is valid, with a two-factor structure that reflects operational and critical-analytical skills.