Psychometric evaluation of the Persian version of the Invisible Violence Against Women Questionnaire - Masoumeh Rostami; Abbas Ebadi; Hamid Sharif-Nia; Fidan Shabani; Reza Ghanei Gheshlagh (Journal of Research Development in Nursing and Midwifery)
Background: Some men use a nuanced set of attitudes, behaviors, and beliefs referred to as “invisible violence” to exert control over women. Although these behaviors are culturally accepted, they remain risk factors for intimate partner violence. Early detection of invisible violence can prevent domestic violence and its negative consequences. Therefore, this study aimed to evaluate the psychometric properties of the Persian version of the Questionnaire for the Invisible Violence Against Women (Q-IVAW). Methods: This cross-sectional study was conducted on 520 married women who were referred to health centers in Western Iran (Asadabad) in 2023. Sampling was performed using a convenience sampling method. After forward-backward translation, face, content, and construct validity (through exploratory and confirmatory factor analysis) were conducted. Internal consistency was assessed using Cronbach's alpha and McDonald's omega coefficients and stability was assessed using a test-retest. The data were analyzed using SPSS version 16 and Amos version 26 software. Results: In the exploratory factor analysis, four factors, including ‘utilitarian-benevolent sexist behaviors’, ‘crisis sexist behaviors’, ‘coercive sexist behaviors’, and ‘ambivalent sexist behaviors’, were extracted using the maximum likelihood method and Promax rotation. Cronbach's alpha for the four factors was 0.803, 0.724, 0.733, and 0.704, respectively. These factors account for 47.17% of the total variance. In confirmatory factor analysis, the final model demonstrated a good fit (CMIN/DF = 2.140, GFI = 0.952, AGFI = 0.932, NFI = 0.924, IFI = 0.958, CFI = 0.958, RMSEA = 0.047). Conclusion: The Persian version of the Q-IVAW has acceptable psychometric properties and can be used to measure invisible violence in Iranian women.