Design and evaluation of a digital mindfulness intervention for university students

Thesis Abstract

Digital mindfulness interventions have the potential to mitigate heightened stress, anxiety, and depressive symptoms prevalent among university students, yet existing programs often suffer from low engagement, limited scalability, and insufficient emphasis on contextualized user experience. This study addresses the gap by designing, implementing, and evaluating a theory-driven digital mindfulness program tailored to undergraduate and postgraduate students across three faculties at a large urban university. The aim is to determine (1) the program’s effectiveness in reducing perceived stress and improving well-being, (2) factors predicting sustained engagement with the intervention, and (3) user experiences that shape perceived usefulness and acceptability. Specific objectives include (a) developing a 8-week modular intervention guided by the Mindfulness-Based Cognitive Therapy framework and complemented by self-compassion and cognitive reframing components; (b) assessing pre-post changes in perceived stress (Perceived Stress Scale), mindfulness facets (Five Facet Mindfulness Questionnaire), anxiety (GAD-7), and mood (PHQ-9); (c) examining engagement patterns using app analytics and identifying adherence predictors through multiple regression; (d) exploring context-specific barriers and facilitators via thematic analysis of semi-structured interviews with a purposive subsample; and (e) refining the intervention through a mixed-methods iterative feedback loop for scalability. The study employed a mixed-methods design with a randomized controlled trial (n = 240; 120 intervention, 120 control) and a parallel qualitative strand (n = 30) to capture experiential data. Participants were eligible full-time students aged 18–35, recruited from three faculties and stratified by year of study and baseline mindfulness. Data collection instruments included validated scales (Perceived Stress Scale, Five Facet Mindfulness Questionnaire, GAD-7, PHQ-9, WHO-5 Well-Being Index) administered at baseline, mid-intervention (week 4), post-intervention (week 8), and a 3-month follow-up. Intervention delivery combined guided audio meditations, journaling prompts, cognitive-behavioral micro-exercises, and a self-regulation module delivered via a mobile application with push notifications to optimize engagement. Quantitative data were analyzed using repeated-measures ANOVA and linear mixed-effects models to assess time-by-group interactions, with post-hoc pairwise comparisons and intention-to-treat imputation for missing data. Regression analyses identified predictors of adherence, including baseline mindfulness, self-efficacy, prior meditation experience, and perceived usefulness. Qualitative data underwent thematic analysis following Braun and Clarke’s framework, with credibility checks through triangulation with quantitative findings and member checking in a subsample. The expected findings indicate that, relative to controls, the intervention will produce statistically significant reductions in perceived stress and anxiety and improvements in mindfulness and well-being at post-intervention, with effects sustained at follow-up. Engagement is anticipated to be positively associated with perceived usefulness, usability, and social support features within the app, while higher initial stress may predict greater symptom reduction. The study contributes to knowledge by integrating a theoretically grounded mindfulness program with user-centered design elements tailored for diverse university contexts, providing a scalable model for digital mental health interventions in higher education. It advances methodological approaches in higher education psychology by combining robust RCT evidence with qualitative insights to elucidate mechanisms of change and contextual factors affecting adherence. Practical implications include recommendations for universities regarding implementation, integration with campus services, and strategies to optimize engagement (e.g., customizable reminders, micro-interventions, and peer-support features) while maintaining data privacy and cultural sensitivity. The main conclusion posits that a well-structured digital mindfulness program can yield meaningful improvements in stress, anxiety, and well-being among university students, particularly when co-designed with user feedback and augmented by motivational and cognitive components. Recommendations emphasize iterative refinement based on user analytics, expansion across disciplines, integration with academic supports, and broader adoption within student mental health strategies, alongside longitudinal studies to examine long-term outcomes and cost-effectiveness.