College Student Perceptions of Using a Symptom-Based Algorithm to Enhance Vending Machine Over the Counter (OTC) Medication Use.

BACKGROUND: People use symptom checkers for clinical decision-making, including over the counter (OTC) product selection. Health and wellness vending machines (HWVM) that stock OTC medications are common on college campuses, including the University of Rhode Island (URI). No system integrates access to self-assessment health tools for OTC medication selection with HWVM. OBJECTIVE: The study objective is to assess college students' preferences for using a symptom checking algorithm, either on a kiosk adjacent to the vending machine or online. METHODS: Survey responses were collected via Qualtrics™ in the spring of 2025. Survey questions included demographic information, students' use of the HWVM, and whether a symptom algorithm could enhance their experience using the HWVM. RESULTS: 303 unique students participated in the survey. Among this sample, 17% (n=53) reported HWVM use. When students have new health issues, 64% (n=136) reported a preference for contacting a person, while 30% (n=64) prefer using an online source. Overall, 75% (n=145) of students reported that a symptom-based algorithm could enhance their experience using the HWVM. More students would access the algorithm via their phones (78%, n=145) versus a kiosk (57%, n=109). CONCLUSIONS: Only one in six respondents reported using the vending machine. While most students prefer talking to a person for health decision-making, most students would use a symptom-based algorithm prior to vending machine OTC medication selection. Future research should be performed to validate algorithms, compare their use with HWVM inventory trends, and document user satisfaction.