Assessing Nomophobia among University Students: A Confirmatory Factor Analysis of the NMP_Q in Pakistan

Abstract

This study presents a comprehensive Confirmatory Factor Analysis of the Nomophobia Questionnaire (NMP-Q), originally developed by Yildirim and Correia (2015), within the context of university students in Pakistan. Nomophobia, conceptualized as the anxiety and fear associated with being without a mobile phone, is a burgeoning area of research with significant implications for the psychological well-being of digital natives. While the NMP-Q is a widely recognized instrument, its reliability and validity necessitate confirmation within specific cultural and demographic contexts to ensure measurement precision. To this end, the present research undertook a rigorous methodological process to evaluate the instrument's internal consistency and construct validity. Reliability, assessed via Cronbach's alpha, demonstrated strong internal consistency for the full scale (α = .918). The four subscales— (1) unable to access information (NAI) (α = .730), (2) Giving up convenience (GUPC) (α = .704), (3) Unable to communicate (α = .743) (NBAC), and (4) Losing connectedness (LOFC) (α = .757)—all exhibited acceptable to high reliability, exceeding the conventional threshold. Furthermore, CFA was employed to verify the structure of four factors. The results confirmed that all 20 items loaded significantly (p < .05) on their respective constructs, with standardized factor loadings ranging from 0.55 to 0.67, all surpassing the recommended minimum value. The CFA findings provide strong evidence for the construct validity of NMP-Q, affirming its theoretical framework. In conclusion, this validation study confirms that the adapted NMP-Q is a psychometrically sound, valid, and reliable instrument for the assessment of the multifaceted nature of Nomophobia among university students in Pakistan. It is therefore recommended for use by researchers and practitioners seeking to understand and measure mobile phone-related anxiety in academic settings, ensuring that subsequent findings are based on a robust and validated metric.