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Updated: Jan 23, 2026

Cross-Modal Multivariate Pattern Analysis
Published on: November 9, 2011
The impact of mobile internet usage patterns on employment intentions of medical students: A cross-sectional study
Jiajing Hu1, Nan Zhang1, Limin Duan1
1Inner Mongolia Medical University, Hohhot, China.
Background:
China's healthcare system is undergoing major transformations, with urbanization worsening the unequal distribution of medical resources and primary healthcare institutions facing persistent workforce shortages. Meanwhile, medical students must choose between further education and entering the workforce. The widespread use of mobile internet has reshaped career decision-making, yet its impact on medical students' employment intentions (EI) and primary care employment intentions (PCEI) remains unclear. Previous studies have focused on traditional factors, such as sociodemographic characteristics and academic experiences, but research on how mobile internet usage intensity and types influence career choices is limited. This study examines the relationship between mobile internet use and EI/PCEI, providing empirical insights into the role of digital engagement in career decisions.
Methods:
A cross-sectional survey was conducted among undergraduate medical students at Inner Mongolia Medical University in May-June 2024. Data were collected via an online questionnaire assessing sociodemographic factors, mobile internet usage intensity and type, and EI. Multiple linear regression models were used to analyze associations between mobile internet use and EI, adjusting for sociodemographic variables.
Results:
A total of 4,494 valid responses were analyzed. Higher mobile internet usage intensity was significantly associated with lower employment intention (EI) and primary care employment intention (PCEI). Compared with students using mobile internet for less than 1 hour per day, those using it for 1-3 hours showed significantly lower EI (β = -0.80, OR = 0.45) and PCEI (β = -0.75, OR = 0.47), with the strongest negative associations observed among students using mobile internet for more than 5 hours per day. Regarding usage type, students primarily engaged in leisure and entertainment or social networking reported significantly lower EI and PCEI than those using mobile internet mainly for academic and professional development, whereas e-commerce and lifestyle services showed no significant associations. Rural background was positively associated with PCEI, while higher academic year was associated with lower EI and PCEI.
Conclusions:
Higher mobile internet usage intensity and non-academic usage patterns are associated with lower employment intention, particularly reduced willingness to enter primary care. These findings highlight the need for policy and practice-oriented interventions, including integrating digital self-regulation and critical digital literacy into medical education, as well as strengthening positive digital representations of primary care careers. Such measures may support more informed career decision-making and contribute to workforce planning in underserved regions.
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