The Design of a Gamified App for Supporting Undergraduates' Resilience

This paper presents the design and preliminary evaluation of a gamified, theory-based mobile application intended to support psychological resilience among undergraduate students in the post-pandemic "new normal." The authors motivate the work by noting that COVID-19 disrupted education for over 60% of students and was associated with elevated anxiety, and they argue that existing resilience apps largely target specific professional groups, are not gamified, lack solid theoretical grounding, and do not use Internet of Things (IoT) sensing or behavioral change techniques. The app proposed here is positioned as a prevention-oriented tool for a general, non-clinical student population.

The prototype lets users set one of three daily goals derived from World Health Organization mental health recommendations: studying, physical exercise, and socializing. Progress is tracked through a combination of self-report, via a short validated anxiety measure that is scored automatically, and objective phone-based sensor data, using the accelerometer for exercise goals and a noise sensor for socializing goals. Users earn points and badges, can compare themselves on a leaderboard, and can share achievements on social networks.

The feasibility and usability evaluations drew on two samples. In November 2021, 30 first-year undergraduates (mean age 18.41) tested the prototype face to face, rating feasibility at a mean of 3.34 out of 5 and usability at a System Usability Scale score of 70.3, which is described as satisfactory. An earlier April 2021 online study with 74 mostly third- and fourth-year students produced more favorable ratings (feasibility mean 3.77; SUS 72.5). Students in higher years rated feasibility significantly higher than first-year students, and age correlated moderately and positively with feasibility ratings. The authors conclude that the design offers practical lessons for gamified health apps, including using brief text, embedded automatically scored validated instruments, and IoT-generated routine data. Effectiveness testing in a quasi-experimental setting is identified as future work.