Impact of digital stress and digital sensitivity on school connectedness among Pakistani adolescent students: the mediating role of AI motivation

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Purpose Adolescents' engagement with digital technologies and artificial intelligence (AI) is increasingly associated with psychological experiences and school-related outcomes, particularly in developing countries. This study examined the associations among digital sensitivity, digital stress, school connectedness and AI motivation among adolescents in Pakistan. It also explored the indirect association of digital sensitivity and digital stress with school connectedness through AI motivation and examined gender differences in digital sensitivity, digital stress and school connectedness. Design/methodology/approach A cross-sectional correlational design was employed with 290 secondary and high school students (ages 11–18) enrolled in private English-medium schools in Lahore, Pakistan. Standardized instruments were used to assess digital sensitivity, digital stress, school connectedness and AI motivation. Data were analyzed using correlation analyses, multiple regression, indirect effect analysis with bootstrapping and independent-sample t-tests. Findings Significant associations were observed among digital sensitivity, digital stress, AI motivation, and school connectedness. The regression model was statistically significant (F = 109.32), accounting for 60% of the variance in school connectedness (R2 = 0.60). Bootstrap analyses (5,000 samples) indicated a significant indirect statistical association through AI motivation compatible with a cross-sectional mediation model, B = −0.772, 95% CI [−1.095, −0.477]. Gender comparisons revealed that males reported higher levels of digital sensitivity, digital stress and AI motivation, whereas females reported stronger school connectedness. The findings are contextual, associational, and exploratory and that they require confirmation through longitudinal research and additional psychometric validation. Research limitations/implications Our findings highlight the importance of maintaining a balanced approach to digital integration that supports engagement with AI technologies while preserving students' sense of school connectedness. However, given that the present conclusions are based on context-specific data, which can be useful in the context of English medium private urban schools. Our results cautiously suggest several practical directions that may warrant attention in similar educational contexts, including monitoring digital fatigue, strengthening teacher support, encouraging more reflective and purposeful use of AI tools and safeguarding opportunities for face-to-face interaction within school environments. These implications should be interpreted as tentative and exploratory, particularly in resource-constrained educational settings. The present findings suggest the importance of examining educational digitalization and AI-related motivation in conjunction with broader indicators of adolescents' psychological and educational adjustment, including digital stress, well-being and school connectedness. Practical implications The findings suggest that digital experiences, AI motivation and school connectedness are interrelated among adolescents attending private English-medium schools in Pakistan. Given the cross-sectional nature of the study, the results should be interpreted as evidence of association rather than causation. The findings underscore the value of further research examining digital engagement, AI-related motivation and indicators of adolescents' educational and psychological adjustment, including school connectedness, well-being and digital stress. Future longitudinal and experimental studies are needed to clarify the direction and nature of these relationships across diverse educational contexts. Originality/value This study provides novel empirical evidence from a developing-country context by integrating digital sensitivity, digital stress, AI motivation and school connectedness within a unified framework. It extends prior research by identifying AI motivation as a mediating mechanism in adolescent digital and educational experiences.

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