Objective To investigate the current situation and related influencing factors of internet addiction among medical students. Methods From October 11 to November 7， 2021， a total of 7 201 undergraduate medical students from sophomores to seniors at Hebei Medical University were selected as the research subjects. A self-made general situation questionnaire was used to collect general information， and the Chinese version of the Internet Addiction Scale （IAT）， Pittsburgh Sleep Quality Index （PSQI）， Self-Rating Anxiety Scale （SAS）， and Self-Rating Depression Scale （SDS） were used to evaluate the internet addiction status， sleep quality， anxiety， and depressive mood of medical students. Medical students with IAT scores of 20-39 were included in the non-internet addiction group， 40-69 in the suspected addiction group， and 70- 100 in the addiction group. The influencing factors of internet addiction among medical students were analyzed by multiple Logistic regression analyses. Results A total of 24.8% （1 788/7 201） of medical students had internet usage issues （IAT ≥ 40 points）， with suspected addicts accounting for 23.9% （1 721/7 201） and addicts accounting for 0.9% （67/7 201）. There was a statistically significant difference in gender， personality， relationship， family upbringing style， campus bullying experience， alcohol consumption， daily physical exercise， learning pressure， interpersonal relationship pressure， sleep quality， anxiety， and depression among three groups of medical students （P＜0.05）. Multiple Logistic regression analysis showed that anxiety （OR=4.866， 95%CI=2.067-3.779）， depression （OR=6.038， 95%CI=3.278-11.121）， poor interpersonal relationship （OR=4.023， 95%CI=1.259-3.733）， doting family （OR=3.147， 95%CI=1.150-8.606）， poor sleep quality （OR=2.168， 95%CI=1.259-3.733）， school bullying （OR=1.938， 95%CI=1.059-3.548）， daily physical exercise （OR=0.386， 95%CI=0.220-0.678） were influencing factors of internet addiction （P＜ 0.05）. Conclusions The issue of internet use among medical students cannot be ignored， and anxiety and depression are the main risk factors for their internet addiction.