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Evaluates the psychometric properties of the PPCS-6 in university students, indicating its validity for assessing problematic pornography use.
Introduction/Objective The Problematic Pornography Consumption Scale – Short Version (PPCS-6) is a brief, theory-driven instrument developed to assess core dimensions of problematic pornography use. This study aimed to evaluate its psychometric properties in a Brazilian sample of university students. This is one of the first studies to examine the PPCS-6 in the Brazilian context. Materials and Methods Data were collected from 687 cisgender medical students (M = 23.6; SD = 5.5) at three institutions. Participants completed a printed questionnaire including the PPCS-6, rated on a 7-point Likert scale. Confirmatory factor analysis (WLSMV estimator) tested the unidimensional model. Internal consistency was assessed using Cronbach’s alpha and Composite Reliability (CR), and convergent validity was evaluated through Pearson’s correlations with PPCS-18 scores. Group comparisons used Welch’s ANOVA and t-tests with Cohen’s d. The study was approved by the Research Ethics Committee (CAAE 47236221.9.0000.5415). Results The PPCS-6 showed excellent fit: χ2(9) = 31.12, CFI = 0.999, TLI = 0.998, RMSEA = 0.030, SRMR = 0.029. Loadings ranged from 0.795 to 0.871. Internal consistency was good (α = 0.82; CR = 0.86), with item-total correlations from 0.55 to 0.72. Significant differences were found among groups who answered “yes,” “no,” or “I don’t know” to whether they considered themselves addicted (p < .001), and between those using one or multiple devices (p = .042). Strong correlations with the PPCS-18 total score (r = 0.952) and non-overlapping items (r = 0.883) supported convergent validity. Conclusions The Brazilian PPCS-6 demonstrates strong psychometric performance and is a valid, efficient tool for assessing problematic pornography use. It may aid early identification of at-risk individuals in various settings. Future studies should test its application in diverse and clinical samples and investigate predictive validity using longitudinal designs. Financing CAPES.
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Perissini et al. (2026) studied this question.
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