Digital Literacy and Career Intention among Nursing Students: Evidence from Indonesian Nursing Education - Zahra Athina Deapriandita; Wastu Adi Mulyono; Hasby Pri Choiruna (Fakultas Ilmu-ilmu Kesehatan Universitas Jenderal Soedirman, 2026)
Background Digital transformation in healthcare and nursing education increases the need for nursing graduates who are digitally capable and work-ready, making digital literacy a foundational competency that should be deliberately developed rather than assumed. At the same time, nursing students’ career intentions are shaped by educational and contextual influences, and intention-related patterns are relevant to workforce sustainability, including in Indonesia where nursing students may consider varied career trajectories. Students’ perceptions of digital health technologies also suggest that digitalization can shape how they imagine their future nursing roles, reinforcing the educational importance of digital competence development. Objective To examine whether digital literacy significantly predicts intention to become a nurse among Indonesian undergraduate nursing students, controlling for age, sex, PKK training/competence, and cohort. Methods A cross-sectional survey was conducted among undergraduate nursing students at Jenderal Soedirman University, Indonesia (n = 282). Digital literacy was measured using an 11-item instrument (α = 0.87), and intention to become a nurse was measured using a 4-item instrument (CVI = 0.93; α = 0.78). Multiple linear regression tested whether digital literacy predicted intention to become a nurse after adjusting for covariates. The use of cross-sectional survey designs and regression modeling aligns with common approaches in nursing education research examining digital literacy-related competencies and career intention outcomes. Results Participants were predominantly female (84.4%) with mean age 19.4 ± 1.6 years. Mean digital literacy score was 45.54 ± 5.54 (range 23–55), and mean intention to become a nurse was 16.37 ± 2.73 (range 6–20). Digital literacy significantly predicted intention to become a nurse (B = 0.187, SE = 0.026, t = 7.08, p < 0.001), controlling for age, sex, PKK, and cohort. The model was significant (F (8, 273) = 10.97, p < 0.001) with R² = 0.243 (adjusted R² = 0.221). Cohort was significant for Batch 2022 (p = 0.018), Batch 2023 (p = 0.050), and Batch 2025 (p = 0.042). Conclusion Higher digital literacy is associated with stronger intention to become a nurse among Indonesian nursing students, independent of demographic factors and educational cohort. These findings support curricular strategies that assess and strengthen nursing students’ digital literacy as part of developing digitally fluent, work-ready graduates, consistent with broader calls to embed digital capability development within nursing education.