Assessing the influence of digital technologies in healthcare on self-medication among students at Makerere University: examining the associated factors and prevalence

Abstract

Self-medication is widely practiced among university students and is increasingly influenced by digital health technologies. While these platforms provide convenience and access to medical information, they may also contribute to inappropriate self-treatment, particularly in settings with limited regulatory oversight. To determine the prevalence of self-medication and examine factors associated with the use of digital technologies for self-medication among students at Makerere University. A descriptive cross-sectional study was conducted among 303 undergraduate students selected through stratified random sampling across colleges. Data were collected using a semi-structured questionnaire and analyzed using IBM SPSS version 26. Descriptive statistics summarized participant characteristics, while bivariate and multivariable logistic regression analyses identified factors associated with selfmedication. Of the 303 respondents, 230 students (75.9%) reported practicing selfmedication in the past six months. Among them, 198 students (86.1%) reported using one or more digital platforms to guide their decisions. The most commonly used platforms were health-related websites (65.3%), mobile health apps (42.2%), and social media health groups (38.6%). On-campus residence was significantly associated with self-medication (AOR = 1.89; 95% CI: 1.06–3.38). Students who used digital platforms more frequently also reported higher trust in these tools. However, no significant associations were found between self-medication and gender, age, or year of study. Digital technologies play a significant role in shaping self-medication behaviors among Makerere University students, with high reliance observed across platforms. These findings highlight the need to promote digital health literacy and ensure access to accurate, regulated online health information to minimize risks associated with unsupervised medication use.