Designing an Anxiety Self-Monitoring Application for Health Sciences Students: An Early Design-Based Research Cycle with Proposed AI Functions
DOI:
https://doi.org/10.69569/jip.2026.495Keywords:
Anxiety self-monitoring, Design-based research, Human-centered AI, ISO/IEC 25010, Mobile mental healthAbstract
Anxiety is common among adolescents and young adults, and mobile applications are increasingly used to help them notice and track symptoms. Few app projects, however, document how user needs, expert judgment, and artificial intelligence (AI) features shape a design. This study reports an early design-based research (DBR) cycle for AniBuddy, an anxiety self-monitoring application prototype for health sciences students at a private institution in Cavite, Philippines. A biopsychosocial-spiritual survey of 325 students aged 15 to 24 measured somatic and psychological anxiety symptoms, perceived social support, and meaning in life. Three graphical user interface experts reviewed the evaluation instrument; student end users and three subject experts then rated the prototype's perceived quality on five ISO/IEC 25010 characteristics and commented on it. Psychological symptoms were reported most often (M = 4.63 on a 7-point scale), chiefly overthinking and anticipatory worry. Somatic symptoms (M = 4.22) and perceived support (M = 4.08) were moderate; students reported moderate presence of meaning (M = 3.68) and little search for it (M = 2.91). Students who could open the iOS prototype were very satisfied (n = 18, M = 4.55), subject experts were satisfied (M = 3.80), and both rated reliabilities lowest. Feedback was traced to design decisions across three refinement cycles. Three AI-enabled functions are proposed: a conversational agent and interest-based suggestions, both added after the evaluation, and a mood forecast whose predictive accuracy was never assessed. Each is paired with a risk-specific safeguard. The ratings reflect perceived rather than technically validated quality. The study contributes provisional design principles and a risk register for the next cycle, which must add clinical, privacy, and security review.
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