ASSESSING WELL-BEING AND READINESS FOR AI-DRIVEN INTERVENTIONS: A CROSS-SECTIONAL SURVEY OF ALLIED HEALTH SCIENCES STUDENTS IN KARACHI

Syed Abdul Aleem Shah; Ambreen Sarim; Atta Ullah Khan; Muhammad Danial Khan; Yasir Noman; Siddiqa Bashir

Authors

Syed Abdul Aleem Shah Author
Ambreen Sarim Author
Atta Ullah Khan Author
Muhammad Danial Khan Author
Yasir Noman Author
Siddiqa Bashir Author

Keywords:

Burnout; Allied Health Sciences; Data Sharing; Artificial Intelligence; Student Well-being; Academic Stress; Pakistan; Personalized Intervention

Abstract

This cross-sectional study investigated the prevalence of stress and burnout among final-year Allied Health Sciences students in Karachi and assessed their readiness for a data-driven, AI-enabled well-being intervention. Data from 306 students revealed that a significant majority (60%) experienced high academic burnout, confirming the first hypothesis. Analysis of data-sharing preferences showed students were significantly more willing to share anonymized wearable data than academic performance data, supporting the second hypothesis. A positive correlation was also found between exhaustion levels and willingness to adopt a personalized AI intervention, confirming the third hypothesis. The findings illuminate a critical public health issue within this demographic and provide essential empirical evidence for developing ethically-designed, student-approved support systems. This study establishes a crucial baseline for future interventions aimed at mitigating burnout through personalized, technology-augmented approaches in health sciences education.