Exploring mental well-being among medical students in the Visegrad four: a cross-national analysis

Abstract

The mental health of medical students is a critical concern, as their well-being directly influences performance and the overall success of educational institutions. This research aimed to investigate the mental well-being of medical students across the Visegrad Four countries. A cross-sectional study with a sample of 1507 students (395 men) was conducted using an online questionnaire in English. Mental well-being was assessed with the Warwick-Edinburgh Mental Well-being Scale, coping strategies with the Brief COPE inventory, and somatic symptoms with the Patient Health Questionnaire-15. Sociodemographic, health-related data and satisfaction with the university were also measured. K-means cluster analysis was employed to classify students into distinct well-being groups: (1) ‘Stable group’ with high well-being, low somatic symptoms, and strong satisfaction, (2) a ‘Risk group’ with moderate well-being, moderate somatic symptoms, and minimal satisfaction, and (3) a ‘Worst condition group’ characterized by low well-being, high somatic symptoms, and high ratio of mental disorder diagnoses. Multinomial logistic regression indicated that the Stable group displayed higher adaptive coping, less avoidant coping, greater health control, more social support and health-promoting behaviours than the Worst condition group. These insights could inform targeted interventions to improve mental health support in medical education.

Introduction

In this study, we conceptualize well-being as a multidimensional construct encompassing emotional, psychological, and social functioning, consistent with the World Health Organization (WHO) framework and contemporary models. According to the WHO (2021), well-being is defined as a positive state experienced by individuals and societies. Similar to health, it is a resource for daily life and is supported by social, economic, and environmental conditions. Well-being encompasses quality of life and the ability of people and societies to contribute to the world with a sense of meaning and purpose. Focusing on well-being supports the tracking of the equitable distribution of resources, overall thriving, and sustainability [1].

Medical universities focus primarily on training medical professionals, but there is an increasing emphasis on health aspects related to coping with stress and maintaining well-being during both the study period and subsequent work in the medical sector [2,3,4]. Research shows that well-being among medical students tends to deteriorate over time which is linked to increased dropout rates, with students experiencing high levels of stress and burnout being more likely to disengage from their studies [5]. Addressing mental health proactively is essential not only for student well-being but also for retention in medical programs. At the beginning of their education, medical students typically report a similar level of well-being to students from other universities. However, as their studies progress, their well-being declines, and stress levels rise [6]. In fact, in Brazeau et al.‘s (2014) study, medical students reported lower levels of depression symptoms at the start of their education compared to other college graduates of similar age. However, by the first year, this trend reversed, with medical students reporting higher than average levels of these symptoms [7]. Consequently, they are more likely to experience negative affects in relation with a lower level of well-being. For example, Heinen et al.‘s study found that medical students reported higher levels of perceived stress, anxiety, and depression compared to reference samples, although no statistically significant differences were observed concerning gender, migrant background, or employment status [8]. Similarly, Boni et al.‘s (2018) study showed that more than half of medical students experienced high levels of emotional exhaustion even in the early years of their education [9]. Additionally, Zdun-Ryżewska et al. (2022) observed that medical university students were more exhausted and more convinced of their superiority compared to social science students [10]. Finally, Monrad et al. (2021) noted that about 50% of medical students exhibit signs of helplessness, disconnection, and burnout [11].

Given the growing evidence of declining well-being and rising psychological distress among medical students, it becomes increasingly important to explore the mechanisms through which they manage and cope with stress. Understanding the different coping styles students adopt in response to stress provides valuable insight into both the risks and protective factors associated with their mental well-being.

According to Parker and Endler (1992) there are three primary stress-coping styles: a) Task-oriented style (this involves making an effort to solve the problem in the face of stress, either by changing the situation or through cognitive reappraisal; b) Emotion-oriented style (this style focuses on the individual’s emotions and reactions. If the strategies employed generate and sustain positive emotions, they can have a beneficial effect); and c) Avoidance-oriented style (this style involves avoiding thinking about the problem, often by diverting attention or seeking social support) [12]. Research suggests that active problem-solving is generally the most health-promoting approach, as it allows for the experience of positive emotions while addressing the stressful situation [13]. Conversely, maladaptive reactions such as venting anger and frustration on others and refusing to accept reality are potentially destructive reactions. Research by S. Moos and A. Schaefer (1993) has shown that individuals who use avoidance strategies achieve poorer adaptive outcomes than those who more frequently employ problem-solving strategies [14]. The way individuals perceive a stressful situation also influences their coping strategy: studies indicate that assessing a situation as changeable more often leads to the adoption of problem-focused strategies, while low perceived influence and personal control tend to direct individuals towards emotion-focused strategies [15]. In the context of medical education, the significance of coping styles becomes even more apparent. Students, as future health care workers, will be exposed to various stressful factors in their careers, such as high responsibility and risk of burnout. The extent to which these stressors impact their well-being largely depends on their ability to effectively regulate their emotions [16]. Other studies indicate a link between fatigue and reliance on avoidance-oriented coping activities [17]. These findings suggest that the way students cope with stress not only shapes their immediate psychological state but also influences their long-term mental well-being.

The mental well-being of medical students is a critical issue not only globally but also within the Visegrad region (V4), where addressing student mental health has become an essential priority for ensuring the sustainability and effectiveness of healthcare systems. Recent research among medical students in Poland reveals significant challenges related to mental well-being, life satisfaction, and academic motivation [18,19,20].A nationwide survey showed that only 20% rated their mental health as good, while 52% reported anxiety disorders, 75% suffered from sleep disorders, 46% experienced eating disorders, and 15% had been diagnosed with depression. Alarmingly, 73% did not seek medical help despite these issues [18]. Furthermore, in the Czech Republic, a study revealed that excessive stress among medical students significantly increases the risk of health problems, dropout, and opting out of clinical practice, threatening efforts to stabilise the healthcare system [21]. Additionally, in Slovakia, a cross-sectional study examined the prevalence of anxiety, depression, and hedonic capacity among both domestic and foreign medical students. The results revealed that 57% of domestic students and an alarming 74% of foreign students screened positive for either anxiety, depression, or a combination of both [22]. Finally, in Hungary, growing attention is being paid to the mental health of medical students, with recent studies highlighting both risk factors and possible institutional support measures [6, 23]. The authors emphasise that strengthening protective factors, such as effective coping strategies, social support and mental health services, is crucial in mitigating burnout and promoting student resilience and future professional performance.

To conclude, the assessment of well-being is increasingly being integrated into medical school curricula [24](. The evaluation of mental health aims to identify key risk factors and create conditions that promote mental well-being. However, there is a research gap in the Visegrad Region (V4) countries: the Czech Republic, Hungary, Poland, and Slovakia, indicating a lack of studies and integrated actions related to well-being. This study aims to explore the well-being of medical students within the Visegrad Group (V4) countries, focusing on their mental health, coping mechanisms, social support structures, and how it is connected to satisfaction with the learning environment. Specifically, we aim to identify the characteristics of a ‘vulnerable’ group to gain insights that could support the improvement of students’ well-being and thus lower the drop-out rates. While previous studies have documented the decline in well-being among medical students, few have explored the specific cultural and systemic factors in the V4 context that contribute to this trend. We hypothesise that maladaptive coping strategies, unhealthy behaviours and limited social support are associated with lower levels of well-being and satisfaction with the learning environment.

Methods

Participants

A total of 1842 individuals, medical school students in the Visegrad Region were recruited for the study and completed the questionnaires. Due to missing data and not fulfilling the inclusion criteria (see below), the data of 335 individuals had to be dropped. Thus, the final sample included data from 1507 students (395 men, 1092 women, 14 other and 6 reported that they do not want to answer), aged between 18 and 53 (M = 21.92, SD = 3.493) 43% (n = 648) of the students were from Hungarian universities (University of Pécs, University of Szeged, University of Debrecen, and Semmelweis University), 18.3% (n = 276) were from the Czech Republic (Charles University), 20.4% (n = 308) were from Poland (Gdansk University), and 18.3% (n = 275) were from Slovakia (Bratislava-Comenius University and Comenius University, Jessenius Faculty of Medicine in Martin). The mean time spent at the institution was 2.53 years (SD = 1.58).

Procedure

Based on the characteristics of the exploratory research, we strived to have questionnaires filled out in a broader group of students, which is the reason we sent out the questionnaires to the students having active legal status, taking part in medical education in the four countries. The research was conducted with the help of the Medical School of University of Pécs, Jessenius Faculty of Medicine in Martin, Charles University, Faculty of Medicine in Hradec Králové, Medical University of Gdansk among medical schools’ students. Participants were recruited via institutional mailing lists and student organizations at participating universities. The data was collected using an online format in English language between September 10, 2023, and December 31, 2023. English was chosen as the survey language to ensure consistency across countries and to facilitate cross-national comparison. Filling out the online questionnaire took approximately 20 minutes. To ensure an appropriate level of English proficiency (participants genuinely understood the questions and were able to respond appropriately), two screening questions were used: one objective and one subjective. The first question was, ‘Indicate the highest level of English language exam you have obtained.’ The second question was, ‘Indicate how comfortable you feel when using the English language’, where participants responded using a 5-points Likert-scale (1 – ‘not at all/uncomfortable’, 5 – ‘comfortable’). Participants who indicated a proficiency level below B2 or a comfort level lower than ‘4’ were excluded from the data analysis. Out of the total raw sample of 1,842 participants a total of 154 individuals were excluded (121 female, 33 male; M = 21.97, SD = 4.58); 49 from Hungary, 41 from Poland, 51 from the Czech Republic, and 13 from Slovakia. The majority were in the first two years of university (n = 89). The minimal sample size was calculated using the RaoSoft® sample size calculator (available at www.raosoft.com/samplesize.html) based on the total number of medical students in the V4 Universities, including medical students, which was approximately 16000 during the data collection period. The sample size was determined with a 99% confidence level and a 5% margin of error. Based on these parameters, the minimal required sample size was calculated to be 638 participants.”

The research was approved by the Hungarian United Ethical Review Committee for Research in Psychology (EPKEB, Ref. No. 2023 − 131) and was carried out in accordance with the Code of Ethics of the World Medical Association (Declaration of Helsinki). Participation in the research was voluntary, and written and informed consent was obtained from all participants. Participants could interrupt the filling out of the questionnaire at any time without explanation and in such a case, the data collected about the participant was deleted. The data collected during the survey is stored on a secure computer with a code.

Measures

Socio-demographic and health-related general data such as education, age and gender were used in the analysis. Participants were also asked about any mental disorder diagnoses and their overall satisfaction with their current study program (‘In general, how satisfied are you with your study program?’ rated from 1 - not at all satisfied, to 5 - completely satisfied). Additionally, satisfaction with various aspects of university life was assessed through closed questions about ‘the learning load,’ ‘cleanliness,’ ‘the effectiveness of communication’, ‘other disease prevention activities carried out by the employer’. Further health-related questions were also assessed. In addition to eating habits and physical activity, two more questions focused on perceived and practised control: ‘How much can you do for your health?’ (rated from 1 – nothing at all, to 4 very much) and ‘How much do you do for your health?’(rated from 1 – nothing at all, to 4 great deal) Finally social support was also assessed by the further question: “In difficult life situations, how much help can you count on from the following people?” (0-there is no such a person/group in my life, 1- none, 2- little, 3- an average amount, 4- a lot).

Warwick-Edinburgh mental wellbeing scale

Warwick-Edinburgh Mental Wellbeing Scale (WEMWBS) was developed to enable the measuring of mental wellbeing in the general population and the evaluation of projects, programmes and policies which aim to improve mental wellbeing [25]. The 14-item scale WEMWBS has 5 response categories, summed to provide a single score. The items are all worded positively and cover both feeling and functioning aspects of mental wellbeing, thereby making the concept more accessible. The scale has been widely used nationally and internationally for monitoring, evaluating projects and programmes and investigating the determinants of mental wellbeing. Respondents are required to rate each item on a 5-point Likert-scale (1 refers to ‘none of them’, while 5 refers to ‘all of the time’). We used the English language version in our questionnaire. The total score of WEMWBS is from 14 to 70 a score of 41–44 is indicative of possible/mild depression; a score of < 41 is indicative of probable clinical depression. In our sample, the scale showed adequate reliability (based on Cronbach’s α values): 0.906.

Patient health questionnaire somatic symptom scale (PHQ-15)

The Patient Health Questionnaire Somatic Symptom Scale (PHQ-15) consists of 15 body-related symptoms derived from the Primary Care Evaluation of Mental Disorders (PRIME-MD), a questionnaire developed to assess mood, anxiety, somatoform, and alcohol-related disorders in primary care settings [26]. Symptoms include 14 of the 15 most prevalent DSM-IV somatization disorder somatic symptoms, such as headaches, dizziness, stomach pain, and fatigue. Each item is rated on a 3-point Likert scale, where 1 means ‘not bothered at all’, 2 means ‘bothered a little’, and 3 means ‘bothered a lot’. The total score of the PHQ-15 ranges between 0 and 30, with proposed cut-off points of 5, 10, and 15, indicating mild, moderate, and severe somatic symptom severity, respectively (Stauder et al., 2021). The Cronbach’s α value of PHQ-15 in our sample was 0.830.

Brief COPE

The Brief COPE is a widely used questionnaire designed to assess coping strategies individuals use in response to stress. The Brief COPE consists of 28 items, divided into 14 subscales, each representing different coping mechanisms. Specifically, the Brief COPE is a 28-item instrument with 2 items per subscale, and contains 14 subscales measuring active coping, planning, positive reframing, acceptance, humour, religion, using emotional support, using instrumental support, self-distraction, denial, venting, substance use, behavioural disengagement, and self-blame. These factors are based on the model of cope proposed by Lazarus and Folkman and the Brief COPE measure has been used in diverse contexts and populations [27]. Each item is rated on a 4-point Likert scale, where 1 means ‘I haven’t been doing this at all’ and 4 means ‘I’ve been doing this a lot’. The structure of the subscales may vary: some researchers propose two subscales, adaptive and maladaptive [28], while others suggest emotion-focused, problem-focused, and avoidant subscales [29]. The three subscales showed adequate reliability, Cronbach’s α values were as follows: Problem-focused (α = 0.760), Emotion-focused (α = 0.747) and Avoidant (α = 0.788).

Data analysis

Statistical analyses were performed using SPSS (version 28) and R (version 4.3.2.). Missing data were replaced using the series median. To reduce the dimensionality of the satisfaction and social support-related items and to prevent multicollinearity in subsequent regression models, separate Principal Component Analyses (PCA) with promax rotation were conducted using the ‘psych’ package [30]. PCA was applied instead of exploratory factor analysis because the main goal was to reduce dimensionality while retaining as much information about the original variables as possible. Prior to conducting PCA, the suitability of the data was confirmed with the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy and Bartlett’s test of sphericity. Both tests indicated that the data were appropriate for PCA in case of both sets of questions (see Results). The extracted factor scores representing satisfaction and social support were subsequently used as composite variables in regression analyses to reduce the risk of overfitting and to enhance the interpretability of the models. Linear regression analysis was conducted to explore the predictors of well-being among university students in two steps. The first model included predictors such as age, gender (dummy-coded), country of university (dummy-coded; Hungary as the reference category), mental disorder diagnosis (dummy-coded), PHQ-15 score, problem-focused coping, emotion-focused coping and avoidant coping. In the second model, additional predictors such as primary and secondary social support (see below), satisfaction, self-reported health-related behaviours such answers to the questions of how much one can do for health, how much one does for health, how involved one is currently in eating healthily, frequency of physical activity and time spent on physical activity weekly were included. For the country of university predictor, Hungary was selected as the reference category because it had the largest number of students.

Finally, K-means cluster analysis was conducted to identify subgroups based on the WEMWBS, PHQ-15, satisfaction, and mental disorder diagnosis. The optimal number of clusters was decided based on silhouette analysis using the ‘factoextra’ package [31]. A series of univariate analyses of variance (ANOVA) as well as chi-square tests were conducted to test whether the variables differed significantly across the identified clusters. Finally, multinomial logistic regression was used to identify the significant predictors of cluster membership. Two models were tested. The first model included the predictors age, gender (dummy coded), country of university (dummy-coded; Hungary as the reference category), problem-focused coping, emotion-focused coping and avoidant coping, primary and secondary social support. Beside all predictors included in the first model, answers to the questions of how much one can do for health, how much one does for health, how involved one is currently in eating healthily, frequency of physical activity and time spent on physical activity weekly were also added to the second model.

Results

Results of PCA

The Kaiser-Meyer-Olkin (KMO) and Barlett’s tests both indicated that the social support-related questionnaire items were adequate for PCA (MSA = 0.817, X2(19) = 2915.756, p <.001). Parallel analysis revealed that the optimal number of components is two. The first component explained 31% of the variance and involved the items related to social support from upper-year students, student organisations, teachers, peers and teammates. This component was labelled ‘Secondary social support’. The second component explained 20.4% of the variance and involved the items related to social support from family, friends, and classmates. This component was labelled ‘Primary social support’. Together, the two components explained 51.4% of the variance.

According to KMO and Barlett’s tests, the satisfaction-related items were also adequate for PCA (MSA = 0.832, X2(21) = 3820.237, p <.001). Parallel analysis showed that the optimal number of components is one. This one component explained 50.8% of the variance and was labelled ‘Satisfaction’. The component included the items related to one’s satisfaction with catering, communication, food, prevention, recreation, time schedule and workload.

Predictors of student Well-being (WEMWBS)

Results of the analyses focusing on the prediction of WEMWBS are summarised in Table 1. Both regression models, Model 1 (F(13, 1493) = 81.530, adj. R2 = 0.410) and Model 2 (F(18, 1488) = 66.227, adj. R2 = 0.438), were significant and explained 41% and 43.8% of the variance, respectively. The comparison of the two models revealed that the additional predictors in Model 2 significantly improved the predictive power (F(5, 1488) = 15.877, ΔR2 = 0.030)). Having a mental disorder was a significant predictor in Model 2, while it was only marginally significant in Model 1, both suggesting that having a mental disorder was associated with lower levels of well-being. PHQ scores were also significant predictors of WEMWBS: higher levels of somatic symptom severity were associated with lower levels well-being. Two of the coping styles, problem-focused and emotion-focused coping were positively, while avoidant-coping was negatively associated with WEMWBS. These results suggest that engaging with stressors either through active problem solving or emotional processing may support psychological well-being, whereas avoiding stressors may undermine it. Both primary and secondary social support as well as satisfaction were positive predictors of WEMWBS scores. That is, having supportive relationships and feeling content with one’s learning environment appears to contribute significantly to psychological well-being. It has also been revealed that both the perceived and practised control over one’s health were positively associated with well-being suggesting that individuals who feel capable of managing their health and actively engage in health-promoting behaviors tend to experience greater psychological well-being. Related to this, eating healthy was also a positive predictor of well-being, whereas gender and physical activity were not significant predictors of well-being. The analysis revealed differences based on the location of the universities the respondents attended. Specifically, students studying at Slovakian universities scored lower on the WEMWBS than those studying at Hungarian universities. A similar pattern was observed for students at Czech universities; however, the association was only marginally significant and became non-significant in Model 2.

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Results of cluster analysis and multinomial regression

WEMWBS, PHQ-15, Mental disorder and Satisfaction were subjected to K-means clustering to identify subgroups within the sample. Based on the Silhouette analysis, the 3-class solution was supported (average Silhouette = 0.40). Cluster 1, termed as the ‘Risk group’, comprised 47.6% (n = 718; female = 47.6%; m = 22.09 year) of the sample and exhibited moderate scores on mental well-being (mean WEMWBS scores = 44.90) and somatic symptoms (PHQ-15 scores = 9.52), with minimal satisfaction (mean Satisfaction scores = 0.05). The proportion of participants with a mental disorder diagnosis was 7.5%. Cluster 2, identified as the ‘Stable group’, constituted 23.8% (n = 360; female = 64.4%; m = 21.89) of the sample, displaying higher mental well-being (mean WEMWBS scores = 56.29) and lower somatic symptoms (mean PHQ-15 scores = 6.67), along with higher satisfaction (mean Satisfaction scores = 0.52) with a low proportion of mental disorder diagnosis (3.9%). Conversely, Cluster 3, labelled as the ‘Worst condition group’, comprised 28.4% (n = 429; female = 79.5%; m = 21.67) of the sample and had the highest proportion of diagnosed mental disorders (18.9%). This group exhibited the lowest mental well-being (mean WEMWBS scores = 33.58), the highest somatic symptoms (PHQ-15 scores = 14.70), and notably negative satisfaction (mean Satisfaction scores = −0.52) (Fig. 1.). ANOVA tests confirmed significant differences between clusters across all variables: WEMWBS scores (F(2,1504) = 2546.18, p <.001), PHQ-15 scores (F(2,1504) = 292.78, p <.001), and Satisfaction scores (F(2,1504) = 134.55, p <.001). Additionally, Chi-square tests confirmed significant differences in the distribution of mental health statuses across clusters (X2(2) = 58, p <.001).

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Cluster membership was then subjected to multinomial logistic regression with the third cluster (Worst condition group) being the reference category (see Table 2.). Both multinomial regression models were significant (Model 1: χ2(20) = 525.551, p <.001, McFadden R2 = 0.166; Model 2: χ2(30) = 654.585, p <.001, McFadden R2 = 0.206). The comparison of the two models showed that the full model (Model 2) fit the data significantly better than the reduced model (Model 1) (χ2(10) = 129.034, p <.001). This indicates that the additional variables included in Model 2 significantly improved the model’s explanatory power.

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The analysis revealed that individuals in the second cluster (Stable group) exhibited higher levels of adaptive coping (both problem-focused and emotion-focused) and received more social support. Additionally, this group had a higher sense of control over their health, actively engaged in health-promoting behaviours, and maintained healthier eating habits. They were also less likely to use avoidance as a coping strategy compared to individuals in the third cluster (Worst condition group). These findings suggest that individuals in the Stable group benefit from a broad range of protective psychosocial and behavioural factors or habits that may support resilience and well-being under stress. Among demographic variables, gender as well as the country of university were significant predictors in both models. Specifically, female students and students attending universities in Czechia and Slovakia were more likely to belong to the third cluster.

Similarly, individuals in the first cluster (Risk group) exhibited higher levels of problem-focused coping and were less likely to use avoidant coping strategies compared to the Worst condition group, while emotion-focused coping was not a significant predictor. It was also revealed that members of the first cluster were as unlikely to practise healthy eating habits as the reference group but were actively engaged in general health-promoting behaviours. They also had a higher sense of control over their health and received social support. These results suggest a rather mixed profile for the Risk group: while they display some adaptive characteristics such as active coping and perceived control over their own health, they may still be vulnerable due to suboptimal emotional coping and dietary behaviours, potentially placing them at risk for lower long-term well-being compared to the Stable group. For the demographic variables, the same pattern was observed as in the comparison between the second and third clusters (see the previous paragraph).

Discussion

This study sheds light on the mental well-being of medical students across the Four Visegrad countries, revealing critical insights into the factors that influence their psychological health. The findings highlight the importance of adaptive coping strategies, peer support, and a perceived sense of control over health in fostering mental well-being among medical students, while identifying the deleterious effects of maladaptive coping and the prevalence of physical symptoms associated with negative affect.

Adaptive coping strategies emerged as significant positive predictors of mental well-being. These strategies, including problem-oriented and emotion-focused coping, enable students to manage stress effectively, thereby mitigating the adverse impacts of academic pressures and emotional strain. The efficacy of these coping mechanisms aligns with previous research, which underscores the importance of proactive coping behaviours in reducing stress and enhancing psychological resilience among medical students [32]. Adaptive coping not only aids in immediate stress management but also contributes to long-term mental health benefits [33], creating a foundation for sustained well-being throughout one’s medical career.

Peer support and satisfaction with university experiences were also identified as factors associated with higher levels of mental well-being. The role of social support systems, particularly peer networks, in mitigating stress and enhancing emotional stability is well-documented. Peer interactions provide a platform for sharing experience, seeking advice, and fostering a sense of belonging, which are essential for coping with the rigorous demands of medical education [34]. Moreover, high levels of satisfaction with university life contribute to a positive academic environment, reinforcing students’ engagement and commitment to their studies.

A perceived sense of control over one’s health emerged as another significant factor associated with higher mental well-being. This sense of control may help students to feel empowered in managing their health and could be linked to reduced feelings of helplessness and stress [35]. Perceived control also buffers the impact of low socioeconomic status on cortisol levels and physical symptoms, highlighting its role in moderating the link between socioeconomic status and health outcomes [36]. Longitudinal studies emphasise the bidirectional relationship between perceived control and health outcomes, indicating that control beliefs impact subsequent changes in health, highlighting the importance of maintaining and promoting adaptive control beliefs throughout adulthood [37] and perceived sense of control positively affects not only mental, but also physical, behavioural and social well-being [38].

Healthy eating habits, as highlighted in the study, appear to be also associated with better mental health outcomes. Nutritional choices directly affect cognitive function and emotional regulation, underscoring the need for educational institutions to promote healthy lifestyle practices among students [39].

However, frequency and amount of physical activity were not significant predictors of cluster membership. Although we were not able to reproduce these findings in our study, several other studies [40, 41] highlight the critical role of physical activity in enhancing the overall well-being of university students, particularly those in demanding fields like medicine. Incorporating intense physical activity into their daily routines can significantly alleviate this stress, improve mental health, and boost overall well-being [42]. While not directly supported by our findings, these insights may still inform practical interventions; for example, universities may consider offering exercise programs, as prior studies suggest their potential benefit in supporting students’ mental health and academic success.

The current study also aimed to identify distinct subgroups of medical students based on their well-being, somatic symptoms, satisfaction, and mental disorder diagnoses. The analysis revealed three clusters, each representing unique profiles: the Risk group, the Stable group, and the Worst condition group. The Stable group demonstrated the highest levels of mental well-being and the lowest somatic symptoms, indicative of a relatively resilient subgroup of students. This group’s positive outcomes may be explained by their adaptive coping mechanisms, particularly their higher reliance on problem-focused and emotion-focused coping strategies. These students also exhibited higher levels of social support, both primary and secondary, which are known protective factors for mental health [43, 44], and it has been proven as a mediator between coping styles and mental health of medical students [45]. Conversely, the Worst condition group presented the most concerning profile, with the lowest mental well-being, the highest somatic symptoms, and the highest proportion of diagnosed mental disorders. The association between poor mental health and high somatic symptoms is well-documented [46], as somatic complaints often accompany anxiety, depression, and stress-related disorders [47]. This group’s predominant reliance on avoidant coping strategies likely exacerbates their condition, as avoidance is associated with poorer psychological outcomes and increased stress [48, 49]. The lack of sufficient social support further compounds their difficulties, highlighting the need for targeted mental health interventions to mitigate the risk of long-term psychological issues. The Risk group occupies an intermediate position between the other two clusters. While their mental well-being and somatic symptoms are moderate, their low satisfaction and relatively high use of problem-focused coping indicate potential for both resilience and vulnerability. Although this group does not exhibit the severe distress of the Worst condition group, their low satisfaction suggests that they may still be at risk for future deterioration in mental health, especially without appropriate support mechanisms.

A notable finding of this study is the variation in gender representation across the clusters. The Worst condition group had the highest proportion of female students (79.5%), while the Risk group was more evenly split (47.6% female), and the Stable group also had a relatively high proportion of women (64.4%). These differences in gender distribution raise important questions about the role of gender in mental health among medical students. It is known that the higher prevalence of problematic well-being among female medical students is influenced by a combination of behavioural, psychosocial, and systemic factors. Female medical students frequently report elevated levels of stress, anxiety, and depression, all of which are significant predictors of mental health challenges. One key factor contributing to this increased vulnerability is the prevalence of impostor syndrome among female students, where individuals doubt their abilities and feel fraudulent despite their achievements [50]. Furthermore, poor sleep quality is also strongly associated with mental health issues, including anxiety and depression, which are already more prevalent in females compared to males [51]. However, our results also show an increased representation of women in the Stable group, suggesting that gender alone is not a definitive predictor of low well-being. These findings highlight the need for further research to explore the nuanced ways in which gender interacts with other psychosocial factors in medical training. Moreover, it underscores the importance of considering gender when designing mental health support programs. Gender-sensitive interventions should be developed to address the specific needs and stressors faced by female students, while also recognizing that individual experiences vary. The results and significant differences between clusters suggest that a one-size-fits-all approach to mental health in medical education is insufficient. Instead, a targeted, evidence-based approach is required to support the diverse mental health needs of students in this high-pressure environment.

Our findings support the growing recognition that medical education should not only focus on clinical knowledge and technical skills, but also on preparing students to maintain their own mental well-being throughout their careers [52]. Medical students - who are future healthcare providers - need to develop coping strategies, emotional self-regulation, and a sense of professional identity to navigate the demands of both training and practice. To address this, we recommend that medical curricula include curricular or extracurricular opportunities for students to learn about stress management, mental health, and self-care. Such initiatives would not only help students manage current challenges but also contribute to long-term resilience and professional development. In addition, institutions could invest in support systems that are easily accessible and tailored to students’ needs. These might include mental health counselling services, mentoring activities, peer support groups, and targeted programs that promote the soft-skills essential for well-being. The results of this study underscore the importance of pedagogical approaches in medical education, as well. As noted by Varga et al. (2020), the lack of pedagogical training for medical teachers can hinder effective teaching and contribute to student burnout [53]. By implementing training programs that focus on pedagogical skills, medical schools can enhance academic engagement and potentially reduce dropout rates. Future research should consider exploring these challenges to gain a more comprehensive understanding of the mental health experiences of medical students, ultimately informing more effective support interventions.

This study has several limitations that should be acknowledged. First, the cross-sectional design limits the ability to draw causal inferences about the relationships between well-being, coping strategies, and social support. While the findings provide a snapshot of the mental health landscape among medical students, longitudinal studies would be beneficial to examine how these variables interact over time. Second, although the study includes participants from four Visegrad countries, the sample may not fully represent all medical students in these countries. Third, the online format of the study may have introduced self-selection bias, as students experiencing higher or lower levels of well-being might have been more or less likely to participate, or as students might underreport negative feelings or behaviours due to social desirability. Incorporating objective measures of well-being and coping strategies could enhance the validity of the findings. Furthermore, although English proficiency was screened, potential disparities in language comprehension and cultural interpretations of mental health and well-being across the Visegrad countries may have influenced responses. It should also be noted that participants with insufficient English proficiency were excluded from the analyses, which led to an overrepresentation of students from the Czech Republic and Poland among those excluded. While this may introduce a degree of sampling bias, it was necessary to ensure the reliability and validity of the responses In addition to this, the use of several single-item, self-developed questions (e.g., health control, satisfaction) represents a limitation, as these items lack full psychometric validation and may not capture the complexity of the underlying constructs. Finally, while the study controlled for various factors, other confounding variables, such as socioeconomic status or academic pressure may not have been accounted for, potentially influencing the outcomes. Moreover, although country-level differences may exist, the primary aim of the study was to examine patterns across the V4 region as a whole; therefore, country-specific comparisons were beyond the scope of this analysis.

Conclusion

The findings underscore the significant role of adaptive coping strategies, social support, and a perceived sense of control over health in fostering mental well-being. The findings suggest that adaptive coping mechanisms, particularly problem-focused and emotion-focused strategies, may play a role in managing stress and mitigating the adverse effects of academic pressures. Furthermore, the identification of three distinct clusters ‘Risk group’, ‘Stable group’ and ‘Worst condition group’ highlights the variability in mental health outcomes among students. The study identified a higher proportion of students in the ‘Worst condition group’ exhibiting concerning mental health outcomes. While the well-being of the majority of medical students is high, providing support to the ‘Risk group’ is crucial to reduce the likelihood of poorer outcomes. Ultimately, this research advocates for a nuanced, evidence-based approach to mental health support in medical education. It calls for educational institutions to implement programs that promote adaptive coping strategies, facilitate peer support, and encourage healthy behaviours, including balanced nutrition. By fostering a supportive environment that addresses the diverse mental health needs of students, universities can play a crucial role in enhancing the well-being and resilience of future healthcare professionals.

Data availability

The data that support the findings of this study are openly available here: https://osf.io/6mf9j/?view_only=6c34b87a061743a69888b8977dd8f3d8.

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