Wearable, Smartphone and mHealth Approaches to Academic Stress in University Students: A Narrative Review

AbstractAcademic stress is common among university students and is linked to poorer mental health andacademic outcomes. Traditional measurement relies on retrospective questionnaires such as thePerceived Stress Scale (PSS), which miss day-to-day changes. This narrative review summarizes howthree technologies have been used to measure or reduce stress in students: wearable physiologicalsensors, smartphone-based digital phenotyping, and mobile health (mHealth) interventions. It coversnine key empirical studies and reviews, with every reported figure checked against the originalpublication.In controlled laboratory protocols, multimodal chest-worn sensors reached binary stress-detectionaccuracy of about 93% (WESAD, N = 15). Performance was lower in daily life: the cStress modelpredicted field self-reports with 72% accuracy, and a context-aware wrist model detected 70% of reallife stress events at 95% precision. Over a 30-day study of 201 students, wearable features classifiedhigh versus low perceived stress with 78.3% accuracy, outperforming phone-usage and behavioralfeatures. Smartphone sensing showed that conversation, sleep, and activity fall as workload rises acrossa term. For interventions, one randomized trial of a mindfulness app (N = 88 analyzed) reported a largereduction in PSS scores versus a wait-list control, while a systematic review of 89 digital interventionsfound that most were effective or partially effective but carried moderate-to-severe risk of bias.The main gaps are the difference between laboratory and field performance, the inability ofphysiological signals to separate distress from positive arousal, small and homogeneous samples, andlow long-term engagement. Future work should test closed-loop just-in-time adaptive interventions withmicro-randomized trials, personalize models to each student, and include students outside NorthAmerica and Europe