Future of Medical Education Journal

Future of Medical Education Journal

The Psychometrics properties of the Iranian Smartphone Application for midwifery education based on Rodger’s theory innovation: A Confirmatory Factor Analysis Study

Document Type : Original Article

Authors
1 Department of Midwifery, Ne.C., Islamic Azad University, Neyshabur, Iran
2 Department of Nursing and Midwifery, MMS.C., Islamic Azad University, Mashhad, Iran
3 Medical Education Department, Virtual Center, Jahrom Unversity of Medical Sciences, Jahrom, Iran
4 Department of Medical Education, Smart University of Medical Sciences, Tehran, Iran
10.22038/fmej.2026.94348.1724
Abstract
Background: The rapid growth of smartphone use has encouraged the adoption of innovative approaches in medical education. The aim of this study was to design and psychometrically validate a measurement model for the Smart Screening System “Screen App” based on the constructs of Rogers’ Diffusion of Innovation Theory using confirmatory factor analysis (CFA) among midwifery students.
Methods: This cross-sectional study was conducted among undergraduate Midwifery students of Islamic Azad University of Mashhad in 2023-2024. Data were collected using a researcher-made questionnaire designed based on the five constructs of Rogers’ diffusion of innovation theory. The content validity of the instrument was confirmed by 13 medical education experts and four Midwifery students. Students received detailed instructions and a 3–7 day familiarization period before completing the questionnaire.
Results: Quantitative face validity was evaluated using the Item Impact Score. The results indicated that no items required removal at this stage. Subsequently, content validity was assessed using the Content Validity Ratio (CVR) and the Content Validity Index (CVI). The minimum acceptable values for CVR and CVI were set at 0.54 and 0.70, respectively. CFA confirmed the good fit of the five-construct model includes the Chi-square/degrees of freedom ratio (χ²/df = 1.49), Comparative Fit Index (CFI = 0.93), Tucker-Lewis Index (TLI = 0.92), Incremental Fit Index (IFI = 0.94) and Root Mean Square Error of Approximation (RMSEA = 0.06) within the Intelligent Screening Application (ISA) system, supporting the theoretical structure.
Conclusions: “The Screen App”, as an innovative educational tool, may facilitate deeper learning and exert a significant educational impact on students, by incorporating the essential characteristics of innovation.
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