Latent class analysis of depression and anxiety among medical students during COVID-19 epidemic

Since December 2019, a novel coronavirus pneumonia (COVID-19) outbreak has persisted in Wuhan. The World Health Organization declared that the COVID-19 outbreak constitutes a public health emergency of international concern [1]. The outbreak of the COVID-19 has caused public panic and psychological pressure [2, 3]. In January 2020, the Ministry of Education issued a notice requiring colleges to appropriately postpone school opening time. To prevent the escalation of the epidemic, schools have taken measures such as extending holidays to ensure that the majority of students are isolated in their current residences and complete their school-related responsibilities remotely [4]. For college students, extended holidays, long-term stays at home, fewer trips out of the home, and an inability to attend school and participate in social activities, may affect their academic performance and lead to their anxiety and depression [5‐7].

In a recent study, the research team identified social networking as the strongest protective factor against depression and suggested that reducing sedentary activities, such as watching TV and daytime naps, could also help reduce the risk of depression [8]. This epidemic not only led to a risk of death from infection, but also led to unbearable psychological pressure. College students must reduce the frequency of their outings, resulting in their inability to participate in social activities, which may affect their learning progress and exacerbate their anxiety and depression. Therefore, the mental health status of medical students is of great concern to medical universities [9].

As a special group of future medical workers, medical students’ physical and mental development is not yet fully mature, and the healthy growth of these students can effectively promote the positive development of healthcare in the future [10]. Compared with their normal way of living and learning, staying at home was a major contrast. In fact, the epidemic has affected mental health among those in the medical industry than among those in the general public, and they must be treated correctly to adapt to this change [11]. Mental health problems may continue into adulthood if they are not detected or properly treated. For students in clinically related disciplines, these problems can lead to many undesirable personal and professional consequences [12, 13]. Therefore, it is necessary to pay attention to the mental health of medical students during the epidemic period and take targeted action to intervene with students with different characteristics.

In research on the mental health of medical students, the indirect measurement of the latent mental health can be obtained through observed and measurable behaviour. Previous studies generally used the total scores of the self-assessment scales as the standard for categorizing the mental health of medical students [14, 15]. The categorization standard was too simple to distinguish group characteristics. The application of latent class analysis (LCA) technology can solve this problem and provide more scientific methods for the classification of medical students’ mental health during epidemic. LCA is a more scientific and rigorous statistical method to classify the potential characteristics of a population based on the score probability of each item [16]. Using LCA to group depression and anxiety symptoms of medical students, considering both symptom profile and severity, is helpful to explore the potential mechanism of depression and anxiety, and to develop more targeted intervention measures.

At present, LCA has been widely used in sociology, psychology and disease classification or diagnosis [17, 18]. Current research on COVID-19 has focused on pathogenesis, epidemiology and clinical research [19‐22]. There is no latent category research on mental health during the COVID-19 epidemic. Therefore, this study intends to use LCA to explore the factors influencing medical students’ mental health during the COVID-19 to provide accurate decision-making references for relevant education departments.

In the current study, LCA was used to classify medical students’ depression and anxiety during the COVID-19 epidemic. LCA is an important research method in social science that assumes that individuals can be grouped into classes with similar patterns of some behaviours according to their response to a set of observed indicators [29]. Three interpretable subtypes of depression and anxiety based on LCA models were detected in the present analysis, and the entropy of the 3-class model (0.88) indicated excellent membership classification. This is consistent with previous reports involving LCA, which classified child mental health at the population level and determined the reliability of identified classes [30‐32]. Meanwhile, a number of researchers have published papers encouraging the use of LCA in the classification of mental health issues because it is well suited to addressing pertinent questions [33‐36]. For example, Essau CA encouraged the application of LCA for studying complex multidimensional phenomena, such as mental disorders, because multiple aspects of individual functioning can be studied holistically [37]. Other researchers have suggested that LCA is an important analytic tool for studying health risk behaviours in college students [38‐42]. Furthermore, it can also be used to examine the clustering of modifiable health risk behaviours and to explore the relationship between these identified clusters and mental health outcomes [43].

This study found that the mental health of medical students had obvious grouping characteristics during the COVID-19 pandemic, and the statistical indicators supported three latent classifications, namely, the ‘low symptoms group’, the ‘mild mental health group’ and the ‘poor mental health group’. Most medical students in this study belonged to the ‘low symptoms group’, and they had low probability scores for each factor of depression and anxiety, which showed that most medical students had strong psychological adjustment ability and adaptability in isolation at home during the epidemic period. Through the probability score plot, it can be seen that all the medical students had a lower probability of scoring on suicidal ideation. It is possible that the students were in a sensitive period of youth and had more or fewer psychological problems, but they did not have ideas of self-harm or suicide.

In the poor mental health group, the probability score plot showed that the mental health problems of medical students occur in clusters rather than independently. The poor mental health group had a higher probability of scoring on all other factors except suicidal ideation, which can partly be attributed to the stressful training experience [44], such as the long length of schooling, academic pressure, and the stress of clinical practice [45]. This subtype of students may have multidimensional psychological problems, with long-term consequences on well-being and professional relationships. This is in accordance with previous studies showing that most of the students with depression symptoms were also diagnosed with generalized anxiety symptoms [46, 47]. The cause of co-existence was related to sharing the same risk factors and symptoms [48‐50]. The symptoms of depression and anxiety in medical students may include slowness of thought, decreased energy, low self-worth, disturbed sleep, and difficulty concentrating, which have been known to jeopardize academic development [51, 52]. To prevent their behaviour from becoming extreme, these students urgently need corresponding psychological treatment measures and should be the focus of prevention and treatment. Computer-delivered cognitive behavior therapy (CCBT), which has become widely used for the growth of the internet and smartphones, can be considered [53, 54].

Multinomial logistic regression analysis showed that compared with the ‘low symptoms group’, there were more females in the ‘poor mental health group’ and the ‘mild mental health group’. In particular, the risk of female students entering the ‘poor mental health group’ was 1.732 times higher than that of male students, indicating that the mental health problems of female students were more prominent, which may be due to the different hormones and stressor events. Consistent with previous studies, gender differences have always existed in the mental health of medical students [55‐57]. In an investigation of the effects of different educational levels, it is found that the higher one’s educational level is, the higher the risk of entering the ‘poor mental health group’ and ‘mild mental health group’. Medical students with many years of education are more likely to have psychological problems, which may be related to the higher pressure from scientific research and work [58]. Similarly, medical students with drinking habits also have a higher risk of psychological problems, which was in accordance with the findings of previous studies [59, 60]. Compared with the low symptoms group, medical students in the high-risk group with individual or family psychiatric disorders had a higher risk of mental health problems than did students without psychiatric disorders. A history of psychiatric disorders was consistently found to be significant correlate of depression and anxiety [61, 62].

Apart from traditional factors, epidemic-related factors were also observed in our study. Compared with the low symptoms group, the higher the awareness of COVID-19, the lower the risk of psychological problems for medical students in the poor mental health group and mild mental health group. This phenomenon elucidated that the better understanding of preventive measures about COVID-19 for medical students, the more active they are in coping with the epidemic situation. Therefore, improving medical students’ cognition of COVID-19 is beneficial to their mental health. Government departments and universities should make use of social platforms, social software and other new media to attract medical students to consciously receive health education on epidemic prevention measures and related knowledge in COVID-19. Similarly, compared to the low symptoms group, the risk of mental health problems in the poor mental health group with fear of being infected with COVID-19 was three times higher than that in students without this fear. These results indicated that the outbreak of COVID-19 might have a significant effect on the risk of mental health in medical students. This was consistent with previous studies conducted in Guangzhou, which suggested that psychological consequences of the COVID-19 could be serious in college students [63]. Under the stress of the COVID-19 epidemic, the mental health status of medical students had clustering characteristics. It is urgent to implement targeted psychological interventions and health education measures according to the latent group.

Nevertheless, the present study had several potential limitations. First, this was a cross-sectional study, thereby precluding conclusions on causality and weakening the dynamic analysis of mental health problems in medical students. Second, the instruments measuring the mental health used in our study were all conducted using self-rating scales, which may influence the accuracy of the results. Third, the medical students’ mental health problems included not only depression and anxiety, but also other psychological problems that were not taken into consideration in our study. This may lead to underestimation of medical students’ psychological problems.

In conclusion, this is the first study using LCA to explore mental health subgroups of medical students during the COVID-19 epidemic. LCA is a useful tool for studying and classifying mental health at the population level. It was found that the mental health status of medical students had clustering characteristics. The results will be highly relevant to medical education and could be a very important reminder of the current mental health status of medical students.