# Predictors of Smartphone Usage Addiction among Health Sciences Students in Selected Universities in Kampala, Uganda

## TL;DR

This study found that over half of health science students in Ugandan universities are addicted to smartphones, with daily usage time and early onset being key predictors.

## Contribution

The study identifies specific predictors of smartphone addiction among Ugandan health science students, offering insights for targeted interventions.

## Key findings

- The prevalence of smartphone addiction was 53.9% among health sciences students in Kampala.
- Daily smartphone usage time and early onset of use were significant predictors of addiction.
- Most affected students were female and unmarried, with an average addiction score of 16.13.

## Abstract

Globally, smartphone use among university students is expanding at an exponential rate, and its lingering addiction has now become a global issue, causing some emotional comprehension issues that can lead to significant consequences. Hence, this study aimed to assess the magnitude of smartphone addiction (overuse) and its predictors among health sciences students at selected universities in Kampala, Uganda.

An online-based descriptive cross-sectional study design was employed for this study among 308 students of health sciences in Ugandan universities. A three-sectioned, pretested, and validated questionnaire was used to capture data on socio-demographic attributes and smartphone use habits from the respondents. The data were analysed using IBM SPSS version 26. The outcome variable (i.e., smartphone addiction) was transformed into a weighted aggregate score prior to dichotomisation. Analysis of variance, chi-square test of independence, and binary logistic regression analysis were employed for the study hypotheses, and the significance level was set at P ≤.05.

The prevalence of smartphone addiction was found to be 53.9%. Female respondents were predominant, 179 (58.1%), and relatively three-quarters of the respondents, 237 (76.9%), were unmarried. The smartphone addiction score among the respondents was 16.13 (95% confidence interval [CI], 15.49 to 16.78) on a maximum reference scale of 30. At the multivariable model, daily time spent using a smartphone (AOR 0.40; 95% CI, 0.23 to 0.69) and the onset of smartphone use (AOR 0.55, 95% CI, 0.31 to 0.97) were identified as the significant independent predictors of smartphone addiction.

This study reported a high prevalence of smartphone addiction among the sampled health sciences students in Ugandan universities. The most significant predictors of smartphone addiction include the number of hours spent on a smartphone daily and the onset of smartphone use. Given the negative health outcomes that this problem may evoke, this study calls for targeted health education intervention to enhance self-control skills, and to effectively tackle smartphone addiction among university students in Uganda.