{"paper_id":"3a48a7f9-d61c-4388-b4f3-15b836c2ded7","body_text":"Analysis of University Students’ Perception of Mental Health | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Analysis of University Students’ Perception of Mental Health Iveta Vrabková, Ivana Vaňková This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6587591/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Nov, 2025 Read the published version in BMC Public Health → Version 1 posted 15 You are reading this latest preprint version Abstract Mental health of university students has become an increasingly important public health issue, especially following the COVID-19 pandemic. Despite the high prevalence of mental illness, there still lacks a deeper understanding of how students themselves perceive their mental health and what contextual and institutional factors influence this perception. This research focused on the perception of mental health among university students in the Czech Republic and analysed their attitudes towards the urban environment as well as the preferred forms of support. The cross-sectional questionnaire survey, conducted online, involved 767 students from five public universities. The fifteen questions covered the areas of internal experiences, social background, and institutional conditions. Data were analysed using the principal component analysis (PCA) and Welch’s t-test to compare gender differences. Analysis revealed three latent components shaping the perception of mental health: (1) subjective mental well-being (e.g., loneliness, self-assessment of the mental state); (2) contextual and interpersonal factors (e.g., feeling of security, family support); and (3) institutional determinants (e.g., availability of services, family background). Gender differences were statistically significant in the second and third components – women showed higher sensitivity to institutional and environmental factors. Social networks, study demands, and family relationships were perceived as the main stressors by the students, while cultural and educational possibilities of the cities were valued positively by them. Availability of services at the universities, prevention, and easier access to care were considered by them as the most suitable forms of support. The findings show that students’ perception of mental health is multilayered – influenced by individual, social, as well as institutional aspects. Efficient public health strategies should therefore not be limited to clinical intervention, but they should corroborate the university environment, reflect gender differences, and improve the systemic availability of support. mental health university students factor analysis gender urban environment prevention Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Background Mental health of young adults has become a major public health policy priority in the last decade, not only in the Czech Republic, but also globally. In the Czech Republic, this priority is reflected in the National Mental Health Action Plan 2020–2030, which accentuates the need for prevention, early intervention, and accessible care for vulnerable groups, among whom university students feature prominently (MoH CR, 2025) [ 1 ]. The period of university studies is characterised by increased psychosocial pressure – transition to independence, academic demands, and uncertainty about the future – which creates the conditions for mental health problems. Global reports, including the World Mental Health Report (WHO, 2022) [ 2 ], point to the growing crisis in the mental health of young people. The main risk factors include the increased digital burden, socioeconomic instability, and limited access to quality mental health services, a fact reflected in more than 25% increase in the prevalence of anxiety and depressive disorders after the COVID-19 pandemic – primarily among young adults and women. There is long-standing evidence that young people’s mental health is significantly influenced by social determinants (Anthony, W. A.) [ 3 ]. Tew et al. (2012) [ 4 ] identified the influence of socioeconomic uncertainty, temporary jobs, and loss of identity on psychological well-being. Stewart and Vigod (2016) [ 5 ] pointed out gender inequality where women face a higher burden due to the combination of care, work, and study. The environment in which young people live also plays an important role – according to Peen et al. (2010) [ 6 ], urban environment with a high density of inhabitants, anonymity, and noise is an independent risk factor for mental disorders. According to WHO (2017) [ 7 ], anxiety, depression, and sleep disorders are among the most common diagnoses in this age group, and they are the main causes of disability, comparable to chronic somatic diseases (Vigo et al., 2016) [ 8 ]. Despite the high prevalence of mental disorders, the rate of seeking professional help remains low, especially due to stigmatisation and low mental health literacy. Although there are already studies examining the individual determinants of mental health (Gatdula et al., 2022) [ 9 ], a deeper understanding of how university students subjectively perceive their mental health in the context of the urban environment and what forms of support they find most effective is still lacking. At the same time, it has not been sufficiently mapped whether and how these perceptions differ by gender. This article is divided into four parts. Methodology describes the research design, questionnaire design, and analytical approach including factor analysis. The part Results presents the main outputs including latent components and gender differences identified. Discussion interprets the results in the light of contemporary literature and proposes implications for the creation of mental health policies. The article concludes with a summary of key findings and recommendations for further research and intervention practice. Methodology The methodology was selected in order to achieve the research objective – to identify latent variables behind university students’ perception of mental health and to inquire into their perception of the urban environment and preferred interventions to support mental well-being. This objective is divided into two sub-objectives (SO), supplemented by research questions (RQ). SO1: Identify the main latent components of university students’ perception of mental health using the factor analysis. SO2: Evaluate how students reflect on the positive and negative dimensions of the urban environment in relation to mental health, and what types of intervention they perceive as the most beneficial to its promotion. RQ1: What major components shape students’ perception of mental health based on their attitudes and experiences? RQ2: How the main components identified (latent variables) reflect the general awareness and education about mental health? RQ3: How students perceive positive and negative aspects of the urban environment in relation to their mental health? RQ4: Does perception of factors affecting mental health differ by gender? RQ5: Which types of interventions do students find most effective in supporting their mental health? The research (including the questionnaire design) is based on the assumption of a two-factor model, meaning that the latent dimensions of the perception of mental health contain both the aspects of well-being (e.g., subjective state, support) and the threat factors (such as loneliness, unavailability of care). The two-factor model (Keyes, 2005, Zhou et al., 2020) [10, 11] construes mental health as two independent, but co-existing areas. The first area includes psychopathological symptoms and difficulties, the second includes psychological functioning and well-being. Similarly to Bernanke et al. (2017) [12], who used latent analysis of classes to identify groups of students with different mental health risks, this research also focuses on identifying hidden patterns in how students perceive their mental well-being. The methodological approach was also inspired by the study of Zhou et al. (2020) [11] that used latent profile analysis to identify different types of mental health among adolescents, thus supporting the suitability of person-centred approaches for revealing latent patterns in subjective perception. The research builds on the findings of previous secondary research, which shows that the prevalence of mental illnesses in the young population increases in time and is also influenced by socioeconomic factors like the urban and rural environment, availability of care, criminality, and the age of first-time mothers (Vrabková, Vaňková, 2024) [13]. Formulation of the questions was consulted with experts in psychological and psychiatric care and then tested in the pilot preliminary research in a group of 27 students (15 women and 12 men). The final set of 15 questions was distributed to students of the five largest universities in the Czech Republic in the form of an on-line questionnaire. The Ethics Committee of VSB – Technical University of Ostrava reviewed the questionnaire and the accompanying cover letter, which explained the scientific objectives of the survey to the participants. The review ensured that the research design met ethical standards for research involving human participants. Ethics approval was granted under the reference number VSB/25/044396. The study was conducted in accordance with the Declaration of Helsinki. Participation in the survey was fully voluntary and anonymous. Respondents were informed about the purpose of the research prior to participation and could withdraw at any time. No personal or sensitive data were collected, except for basic demographic characteristics (age and gender). Therefore, written informed consent was not required in accordance with national ethical guidelines and regulations. The questions included ordinal (O), nominal (N), and binary (B) types of variables (indicated by the letters in the table). The questions are introduced in Table 1 below. Table 1 Questions for the Quantitative Research Q Type of variable Q1 How would you rate your current mental state? O Q2 If you sought professional help for your mental health (e.g., psychologist, psychiatrist), how would you rate the quality of these services? O Q3 Do you think mental health care is easily accessible in your city/region? O Q4 Which factors do you think affect the mental health of young people aged 18–25 the most? (select the 3 most important) B Q5 Do you live in an urban or rural environment? N Q6 What benefits of living in the city do you think have a positive impact on mental health? (select the 3 most important) B Q7 What disadvantages of living in the city do you think deteriorate mental health? (select the 3 most important) B Q8 If you could choose, where would you prefer to live in terms of mental health? N Q9 How important is support from family and friends to you in dealing with mental health problems? O Q10 Do you think the age at which people enter parenthood can affect the mental health of their children? O Q11 How much of an impact do you think crime in your region has on your mental health? O Q12 Do you think the age of the first-time mother can affect her mental health? O Q13 How would you rate the level of general awareness and education about mental health in secondary schools and colleges? O Q14 Which of the following do you think would be most helpful in improving mental health care for young people in your region? (select up to 2 options) B Q15 How often do you feel you have to look after your mental health on your own, without the help of professionals or family? O Identification of latent dimensions in the perception of mental health was performed using the principal component analysis (PCA), designed to reduce the data set dimension and reveal hidden structures in the data. PCA transforms the original variables X₁, X₂, ..., Xₚ into new, orthogonal components Zₖ, which maximise variance on data (1): Zₖ = aₖ₁X₁ + aₖ₂X₂ + ... + aₖₚXₚ = aₖᵗX (1) where aₖ is the eigenvector of correlation matrix Σ. The components are independent of each other and maintain order according to the explained variance. To increase factor interpretability, the varimax rotation was used, which maximises high loadings and minimises low loadings. The number of components was determined by Kaiser criterion (eigenvalue higher than 1) and scree plot. Comparative analysis of factor scores was used to analyse differences in the perception of mental health among students. The factor scores for the individual components were calculated as a weighted average of items included in the given latent variable, while the weights corresponded to the sizes of factor loadings. The subsequent testing of gender differences was performed using Welch’s t-test for independent selections, suitable in case of possible inequalities in variance between groups. This test was applied to the scores of the individual components, for which the respective items were available. Calculations were performed in IBM SPSS Statistics (Version 29). Results of the Questionnaire Survey The number of respondents of the on-line questionnaire aged 18–26 years was 767 (N = 767). The most numerous were respondents aged 20 (20.7%), 22 (19.8%), and 21 years (18.4%). The sample included 60.5% of women and 39.5% of men. The respondent structure according to the place of residence shows that almost a half of the respondents come from the urban environment (46.2%), a third live in areas with combined features of urban and rural environments (29.9%), and a quarter of respondents indicated that they lived in rural areas (24.0%). Latent Variables: Principal Component Analysis The principal component analysis (PCA) identified three components with latent values (eigenvalues) higher than 1, which corresponds to the classic Kaiser criterion (see Table 2 and Figure 1). These three components combined explain 46.93% of the total variance in data. The first component has the eigenvalue of 1.438 and explains 17.98% of the total variance. The second component with the value of 1.285 contributes 16.07% of variance, thus the cumulative variability explained reaches 34.04%. The third component has the eigenvalue of 1.030, adding further 12.88%, which leads to the cumulative share of 46.93% of variance explained. Table 2 Total Variance Explained Component Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance Cumulative % 1 1.438 17.975 17.975 1.438 17.975 17.975 1.428 17.855 17.855 2 1.285 16.069 34.044 1.285 16.069 34.044 1.181 14.761 32.616 3 1.030 12.881 46.925 1.030 12.881 46.925 1.145 14.309 46.925 4 0.996 12.453 59.378 5 0.930 11.627 71.005 6 0.882 11.030 82.035 7 0.750 9.380 91.415 8 0.687 8.585 100.000 Extraction Method: Principal Component Analysis, SPSS. The scree plot in Figure 1 visualises the distribution of eigenvalues across the eight components. The decline following the third component, clearly shows that the first three factors are of greatest importance. The red line shows the limit of the Kaiser criterion (eigenvalue = 1), separating the components with higher values. The varimax rotation (Table 2) caused a slight redistribution of the variance explained among these three components, but the cumulative total remained unchanged. The first component continues to have the largest share (17.86%), followed by the second (14.76%) and third (14.31%) components. The rotation ensures a more precise definition of the factor structure, as it highlights the dominant loadings of the variables to the individual components (latent variables). The loadings are illustrated by the factor loadings heat map, which shows how each manifest variable (Q1–Q15) contributes to the individual components, see Figure 2. Red shades indicate stronger positive loadings, grey shades weaker or no loadings. Component 1: Subjective perspective on mental well-being. This component comprises items related to personal experience of mental health – especially the feeling of loneliness in caring for mental health (0.750), evaluation of one’s own mental state (0.693), and perception of mental health awareness in the school environment (0.590). This dimension may be interpreted as self-perception and awareness of one’s own mental health. Component 2: Contextual factors and interpersonal support. The second component captures the impact of crime in the area (0.750) and the importance of support from family and friends (0.730). It is a dimension that reflects the external context and availability of social support in coping with mental health problems. Component 3: Social and institutional determinants of mental health. The third component includes items focusing on institutional approaches and broader social context: influence of parent’s age on the mental health of children (0.736), preferences for a place to live in terms of mental health (0.528), and availability of mental health care (0.508). This dimension can be perceived as institutional and community context of mental health. These three components together explain approximately 47% of the total variance (see Table 2 Total Variance Explained). The results indicate that attitudes towards mental health are not uniform, but rather structured in different, yet interconnected dimensions. Factor scores were calculated as a weighted average of items using the factor loadings. This was followed by the Welch’s t-test for independent samples that takes into account possible unequal variances. In terms of gender perception, the results showed that in Component PC1, the differences between men and women were not statistically significant ( t = –1.31; p = 0.192). In the component reflecting contextual factors and interpersonal support (PC2), comprising support from family and friends and perception of crime in the area, statistically significant gender differences were found ( t = –5.57; p < 0.001). Women had higher scores (F = 3.25) than men (M = 2.92), suggesting greater sensitivity to these external factors in relation to mental health. Significant gender differences ( t = –3.49; p < 0.001) were found in Component PC3, where women had a higher average score (F = 1.65) than men (M = 1.49). This may suggest that women are more sensitive to the effects of community and institutional environments on their mental health and attach higher importance to the availability of car and suitable environment. Results of the Perception of Mental Health Influences and Interventions Which factors do you think affect the mental health of young people aged 18-25 the most? Chart in Figure 3 shows the distribution of perception of external factors that affect mental health, broken down by gender (women N = 464, men N = 303; overall data set N = 767). Respondents had the opportunity to select 3 of the 7 predefined factors, which in their opinion negatively affect mental health. The most common determinant was the workload associated with study or employment, identified as a significant factor by 78.5% of respondents. This area was more strongly emphasised among women. Social media and technology ranked seconds (66.6%) and family relationships ranked third (61.0%) – here too, the response rate was higher for women than for men. Loneliness and social isolation were relevant for 57.4% of the respondents, again more common among women. Approximately a half of the respondents (52.3%), with no significant gender differences, indicated economic conditions as a potential stressor. In contrast, factors like crime and feeling unsafe (4.3%) and lack of access to healthcare (3.9%) were entirely marginal, a fact that may reflect their lower subjective relevance in relation to mental well-being. In summary, the perception of mental health determinants shows a gender-specific pattern where women more frequently identify stressors associated with the social environment, interpersonal relations, and digital technologies. Chart in Figure 4 shows the frequency of occurrence of positively rated aspects of the urban environment in relation to their perceived impact on mental health. Respondents had the opportunity to select 3 of the 6 predefined factors, which in their opinion most strongly represent the supportive or beneficial dimensions of urban life. The most significant factor was the greater social and cultural offer, identified by 81.1% of the respondents, a fact that underlines the importance of urban environment as a place of cultural stimulation and social engagement. The second most frequently cited area was access to employment and education (64.8%), which reflects the importance of the city as an area of socio-economic opportunity. The possibility to establish wider social contacts (42.1%) and better accessibility of public transport (42.4%) were assessed as positive benefits to a comparable extent, with only minor difference between women and men. Easier access to medical and mental healthcare (37.5%) was slightly more often reported by women, which probably reflects their higher sensitivity to the institutional infrastructure of care. In contrast, greater anonymity and privacy was identified as an advantage by mere 24.5% of the respondents, possibly indicating a lower importance of individualisation of the environment in relation to the perception of mental health. Overall, urban environment is primarily perceived as a space of cultural, educational, and employment opportunities, while the aspects of privacy, anonymity, and access to healthcare play a minor role in the respondents’ perception. Chart in Figure 5 shows the perception of negatively rated aspects of the urban environment that may adversely impact mental health. Respondents had the opportunity to select 3 of the 6 predefined factors, which in their opinion represent the main burdens of urban life. The most frequently cited problem was increased stress levels and fast pace of life, identified by 74.2% of respondents, while women reflected this fact more strongly women. Almost the same percentage of respondents (72.9%) pointed out the lack of natural environment and quiet areas, which confirms the importance of the natural environment for perceived psychological well-being. The third most common area was noise and pollution (62.3%), again more accentuated by women. In contrast, less prevalent, but not insignificant factors included higher crime rate (26.1%), more competitive working environment (30.8%), and anonymity associated with feelings of loneliness (23.5%). These aspects were less frequent in the answers, yet can significantly affect mental health in certain populations. It is arguable that negative aspects of the urban environment are perceived by the respondents primarily in connection with stress, lack of natural environment, and sensory overload, while fear of crime and social isolation are less frequent. Chart in Figure 6 shows preferred areas of improvement in mental health care as perceived by the respondents, who had the opportunity to select from five possible interventions. The most commonly stated priority was strengthening the support in schools and universities (57.2%), a fact that points out the perceived significance of prevention and intervention within educational institutions as key points for early detection of psychological problems. This factor was more strongly accentuated by women. The second most frequently cited area was ensuring a better preventive care system (44.6%), indicating the respondents’ emphasis on early intervention and better systemic readiness of healthcare services. This was followed by improved availability of specialist care (44.5%), more often accentuated by women. Key areas identified by relatively fewer respondents were the increased access to care in terms of financial demands (40.7%) and awareness campaigns (39.2%). Still, these areas remain relevant components of the comprehensive strategy to improve mental health care. In general, respondents prefer systemic changes focusing on prevention, university environment, and availability of specialised care, while gender differences remain relatively consistent across all the categories. Discussion This study was aimed at identifying latent variables that shape the perception of mental health of university students and understanding their attitudes towards urban environment and preferred interventions. The results yielded several important findings, which correspond to the research questions. RQ1 and RQ2: Three key latent components were identified using the factor analysis – subjective perspective on mental well-being, contextual factors and interpersonal support, and institutional determinants. These dimensions show that perception of mental health is not a matter of individual experience, but is rather shaped by a broader social and environmental context. Especially significant was the component reflecting subjective perception and independence in taking care of one’s own mental health, suggesting a certain level of individualisation of experience and coping with mental health problems. RQ3: Relationship between the urban environment and mental well-being was evaluated ambivalently by the respondents. Cultural and educational opportunities were perceived positively by them, while the most common negative factors cited were stress, noise, and lack of natural environment. These results confirm that city can be both a source of support and a risky environment, which is consistent with previous findings (e.g., Peen et al., 2010; Srivarathan et al., 2023) [ 6 , 14 ]. RQ4: Gender differences observed indicate that women perceive mental health more comprehensively in relation to the institutional and community factors, while men had higher scores in the area of subjective assessment of mental well-being. This supports earlier findings regarding higher sensitivity in women towards social stressors (Stewart & Vigod, 2016) [ 5 ] and indicates the need for gender-sensitive interventions. RQ5: Preferred forms of support most commonly indicated by the students included strengthening mental health within educational institutions, including psychological services at universities, prevention, and psychoeducation. These findings show the potential of university environments as key points of early detection of mental problems. In terms of practical implications for mental health in general, it is important that interventions are not only focused on acute problems, but also on supporting students’ psychological resilience and overall well-being. It is therefore recommended to improve and expand the system of support at universities by preventive programmes. However, this research has, logically, several limitations due to the questionnaire survey in the form of voluntary participation, as this is likely to create selection bias – especially in terms of higher representation of women. Data were collected at a single point in time, which does not allow for causal relationships to be observed. Last, but not least, the research did not involve the entire diversity of university population, such as students with migration background or from marginalised communities. At the same time, we highlight the methodological limitations of quantitative approaches – as shown by Laidlaw et al. (2016) [ 15 ], students can perceive the terms “mental health” and “mental well-being” differently and this may influence interpretation of the answers. An issue to be addressed is to what extent efficiency of preventive programmes can be influenced by this different understanding. It also seems valid to ask if and how the urban environment can be transformed to minimise stressors and corroborate mental health resilience of university students. Results of this study, supplemented by the findings of Srivarathan et al. (2023) [ 14 ], indicate that stability of social ties, availability of green zones, and community support seem to be key factors in mental comfort of young population living in cities. Future research should take these limitations into consideration and combine quantitative approaches with qualitative methods that would allow deeper understanding of subjective implications associated with mental health. Conclusion The aim of the research was to identify latent variables that shape the perception of mental health of university students and understanding their attitudes towards urban environment and preferred interventions. Three components were found using the factor analysis: subjective perspective on mental well-being, contextual factors and interpersonal support, and social and institutional determinants of mental health. These dimensions show that perception of mental health is not reducible to individual symptoms, but is rather shaped by a social support, environment, and institutional framework. The results also showed that students reflect the urban environment ambivalently – they value its cultural and economic opportunities, but at the same time point to stress, absence of nature, and sensory overload. Preferred interventions thus include available, prevention-oriented, and community-based care, with an emphasis on the university environment as a key place of support. Gender differences ascertained indicate that women perceive external factors (such as crime rate, institutional availability of care) as being more significant, while men reach higher scores in subjective assessment of mental health. These differences should be taken into account when designing targeted interventions and preventive programmes. The results of this study can serve as a basis for targeted interventions and systemic changes in educational and medical institutions to better meet the needs of young people in the changing social and urban context. Declarations Acknowledgements This paper was supported by project NO. SP2024/077 „Approximation of exogenous and endogenous factors of effective allocation of public resources to support the implementation of digital and technological innovations in the public sector, VSB – Technical University of Ostrava and it has been produced whith the financial support of the European Union under the REFRESH – Research Excellence For Region Sustainability and High-tech Industries project number CZ.10.03.01/00/22_003/0000048 via the Operational Programme Just Transition. Funding The authors declare that there was no funding. Availability of data and materials All data generated or analyzed during this study are included in this article. Ethics aproval and consent to participate Not applicable. Consent for publication. Not applicable. Competing interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Author details Authors and Affiliations Department of Management, VSB – Technical University of Ostrava, 17. listopadu St. 2172/15, 708 00, Ostrava-Poruba, Czech Republic References Ministry of Health Czech Republic. National Action Plan for Mental Health 2020-2030. https://mzd.gov.cz/narodni-akcni-plan-pro-dusevni-zdravi-2020-2030/. Accessed 10 Jan 2025. World mental health report: Transforming mental health for all. (2022). https://www.who.int/publications/i/item/9789240049338. Accessed 5 Feb 2025. Anthony, W.A. (1993). Recovery from mental illness: the guiding vision of the mental health service system in the 1990s . Psychosocial Rehabilitation Journal, 16(4), pp.11–23. https://doi.org/10.1037/h0095655. Tew, J., Ramon, S., Slade, M., Bird, V., Melton, J. and Le Boutillier, C. (2012). Social factors and recovery from mental health difficulties: a review of the evidence . British Journal of Social Work, 42(3), pp.443–460. https://doi.org/10.1093/bjsw/bcr076. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-6587591\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":463189132,\"identity\":\"d7769bb2-1d08-4bf0-a8fe-1de056d333b1\",\"order_by\":0,\"name\":\"Iveta Vrabková\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIie3QMQuCQBTA8SeBLUetF4R+hSdOgfRZFMHG1oYGQ7hJmgWHvkIfQRFsiVoFHYTWllvCISIpiGo4GxvuP73lx3t3ADLZH6a+JvoYrXboJor/RrxuAl8k6yYD6u7qBrL5MGbOiSyPzib2Fd6IDqOeswohm0RVnpkkL51tlfSoaJNK9oZPwEMoZmwUqaWJ1FYBheTIV9eW6A9yO5h61BJbRPqhEhCwEAsvp5wlGhQtSYSEGfEYLTSq3EW+djWs0mDkC4ge9Gp+XlDUSmbU9mVK9DhIhT/27PO1imiHTCaTyX7pDlJBSP6R/CE3AAAAAElFTkSuQmCC\",\"orcid\":\"\",\"institution\":\"Technical University of Ostrava\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Iveta\",\"middleName\":\"\",\"lastName\":\"Vrabková\",\"suffix\":\"\"},{\"id\":463189133,\"identity\":\"9f6dc68d-843c-468f-a4f6-dcd0335bf892\",\"order_by\":1,\"name\":\"Ivana Vaňková\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Technical University of Ostrava\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Ivana\",\"middleName\":\"\",\"lastName\":\"Vaňková\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2025-05-04 09:08:14\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-6587591/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-6587591/v1\",\"draftVersion\":[],\"editorialEvents\":[{\"content\":\"https://doi.org/10.1186/s12889-025-25213-7\",\"type\":\"published\",\"date\":\"2025-11-10T15:58:31+00:00\"}],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":83672318,\"identity\":\"0eca8eb1-8037-4e7f-9f4a-97f878f25d50\",\"added_by\":\"auto\",\"created_at\":\"2025-05-30 13:39:37\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":47890,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eScree Plot PCA\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6587591/v1/9863409d5874d5aebdfab131.png\"},{\"id\":83673117,\"identity\":\"44f31e77-c1f1-448a-bebf-9bfcbd7949c9\",\"added_by\":\"auto\",\"created_at\":\"2025-05-30 13:55:37\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":43739,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eFactor Loadings Heat Map\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6587591/v1/4f1d7c4be9afdcecc70247d6.png\"},{\"id\":83672320,\"identity\":\"104aa4e6-a238-4503-bdb6-2472758d402f\",\"added_by\":\"auto\",\"created_at\":\"2025-05-30 13:39:37\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":31902,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eFactors Affecting University Students’ Mental Health\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6587591/v1/690a55af8bce5340ce46c24c.png\"},{\"id\":83672582,\"identity\":\"f968092b-b568-4041-8d63-6230ebfa0b56\",\"added_by\":\"auto\",\"created_at\":\"2025-05-30 13:47:37\",\"extension\":\"png\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":36587,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003ePositive Factors City Life on Mental Health\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"4.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6587591/v1/57c7fd359758d2d272edcb84.png\"},{\"id\":83672584,\"identity\":\"3edcfcc5-31ba-450c-a247-f76eaddc530b\",\"added_by\":\"auto\",\"created_at\":\"2025-05-30 13:47:37\",\"extension\":\"png\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":32449,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eNegative Impact of Life in the City on Mental Health\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"5.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6587591/v1/c045e8a961804123cb10e5ec.png\"},{\"id\":83672322,\"identity\":\"7cbdfb24-22ed-4659-8fff-95e3f128ec9b\",\"added_by\":\"auto\",\"created_at\":\"2025-05-30 13:39:37\",\"extension\":\"png\",\"order_by\":6,\"title\":\"Figure 6\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":31583,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eWhat Can Improve Mental Health of Young People?\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"6.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6587591/v1/3919bae5c1f641ebe2fcdc03.png\"},{\"id\":96105829,\"identity\":\"f9ae88f5-2bf2-4f03-821c-879f810ccf0d\",\"added_by\":\"auto\",\"created_at\":\"2025-11-17 16:11:53\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":740918,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-6587591/v1/85b4de49-79ea-4573-9bca-a2fd41bbe4ae.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Analysis of University Students’ Perception of Mental Health\",\"fulltext\":[{\"header\":\"Background\",\"content\":\"\\u003cp\\u003eMental health of young adults has become a major public health policy priority in the last decade, not only in the Czech Republic, but also globally. In the Czech Republic, this priority is reflected in the National Mental Health Action Plan 2020\\u0026ndash;2030, which accentuates the need for prevention, early intervention, and accessible care for vulnerable groups, among whom university students feature prominently (MoH CR, 2025) [\\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e1\\u003c/span\\u003e]. The period of university studies is characterised by increased psychosocial pressure \\u0026ndash; transition to independence, academic demands, and uncertainty about the future \\u0026ndash; which creates the conditions for mental health problems.\\u003c/p\\u003e \\u003cp\\u003eGlobal reports, including the World Mental Health Report (WHO, 2022) [\\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2\\u003c/span\\u003e], point to the growing crisis in the mental health of young people. The main risk factors include the increased digital burden, socioeconomic instability, and limited access to quality mental health services, a fact reflected in more than 25% increase in the prevalence of anxiety and depressive disorders after the COVID-19 pandemic \\u0026ndash; primarily among young adults and women.\\u003c/p\\u003e \\u003cp\\u003eThere is long-standing evidence that young people\\u0026rsquo;s mental health is significantly influenced by social determinants (Anthony, W. A.) [\\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e3\\u003c/span\\u003e]. Tew et al. (2012) [\\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e4\\u003c/span\\u003e] identified the influence of socioeconomic uncertainty, temporary jobs, and loss of identity on psychological well-being. Stewart and Vigod (2016) [\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e] pointed out gender inequality where women face a higher burden due to the combination of care, work, and study. The environment in which young people live also plays an important role \\u0026ndash; according to Peen et al. (2010) [\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e], urban environment with a high density of inhabitants, anonymity, and noise is an independent risk factor for mental disorders.\\u003c/p\\u003e \\u003cp\\u003eAccording to WHO (2017) [\\u003cspan citationid=\\\"CR7\\\" class=\\\"CitationRef\\\"\\u003e7\\u003c/span\\u003e], anxiety, depression, and sleep disorders are among the most common diagnoses in this age group, and they are the main causes of disability, comparable to chronic somatic diseases (Vigo et al., 2016) [\\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e8\\u003c/span\\u003e]. Despite the high prevalence of mental disorders, the rate of seeking professional help remains low, especially due to stigmatisation and low mental health literacy.\\u003c/p\\u003e \\u003cp\\u003eAlthough there are already studies examining the individual determinants of mental health (Gatdula et al., 2022) [\\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e9\\u003c/span\\u003e], a deeper understanding of how university students subjectively perceive their mental health in the context of the urban environment and what forms of support they find most effective is still lacking. At the same time, it has not been sufficiently mapped whether and how these perceptions differ by gender.\\u003c/p\\u003e \\u003cp\\u003eThis article is divided into four parts. Methodology describes the research design, questionnaire design, and analytical approach including factor analysis. The part Results presents the main outputs including latent components and gender differences identified. Discussion interprets the results in the light of contemporary literature and proposes implications for the creation of mental health policies. The article concludes with a summary of key findings and recommendations for further research and intervention practice.\\u003c/p\\u003e\"},{\"header\":\"Methodology\",\"content\":\"\\u003cp\\u003eThe methodology was selected in order to achieve the research objective \\u0026ndash; to identify latent variables behind university students\\u0026rsquo; perception of mental health and to inquire into their perception of the urban environment and preferred interventions to support mental well-being. This objective is divided into two sub-objectives (SO), supplemented by research questions (RQ).\\u003c/p\\u003e\\n\\u003cp\\u003eSO1: Identify the main latent components of university students\\u0026rsquo; perception of mental health using the factor analysis.\\u003c/p\\u003e\\n\\u003cp\\u003eSO2: Evaluate how students reflect on the positive and negative dimensions of the urban environment in relation to mental health, and what types of intervention they perceive as the most beneficial to its promotion.\\u003c/p\\u003e\\n\\u003cp\\u003eRQ1: What major components shape students\\u0026rsquo; perception of mental health based on their attitudes and experiences?\\u003c/p\\u003e\\n\\u003cp\\u003eRQ2: How the main components identified (latent variables) reflect the general awareness and education about mental health?\\u003c/p\\u003e\\n\\u003cp\\u003eRQ3: How students perceive positive and negative aspects of the urban environment in relation to their mental health?\\u003c/p\\u003e\\n\\u003cp\\u003eRQ4: Does perception of factors affecting mental health differ by gender?\\u003c/p\\u003e\\n\\u003cp\\u003eRQ5: Which types of interventions do students find most effective in supporting their mental health?\\u003c/p\\u003e\\n\\u003cp\\u003eThe research (including the questionnaire design) is based on the assumption of a two-factor model, meaning that the latent dimensions of the perception of mental health contain both the aspects of well-being (e.g., subjective state, support) and the threat factors (such as loneliness, unavailability of care). The two-factor model (Keyes, 2005, Zhou et al., 2020) [10, 11] construes mental health as two independent, but co-existing areas. The first area includes psychopathological symptoms and difficulties, the second includes psychological functioning and well-being. Similarly to Bernanke et al. (2017) [12], who used latent analysis of classes to identify groups of students with different mental health risks, this research also focuses on identifying hidden patterns in how students perceive their mental well-being. The methodological approach was also inspired by the study of Zhou et al. (2020) [11] that used latent profile analysis to identify different types of mental health among adolescents, thus supporting the suitability of person-centred approaches for revealing latent patterns in subjective perception.\\u003c/p\\u003e\\n\\u003cp\\u003eThe research builds on the findings of previous secondary research, which shows that the prevalence of mental illnesses in the young population increases in time and is also influenced by socioeconomic factors like the urban and rural environment, availability of care, criminality, and the age of first-time mothers (Vrabkov\\u0026aacute;, Vaňkov\\u0026aacute;, 2024) [13].\\u003c/p\\u003e\\n\\u003cp\\u003eFormulation of the questions was consulted with experts in psychological and psychiatric care and then tested in the pilot preliminary research in a group of 27 students (15 women and 12 men). The final set of 15 questions was distributed to students of the five largest universities in the Czech Republic in the form of an on-line questionnaire.\\u0026nbsp;The Ethics Committee of VSB \\u0026ndash; Technical University of Ostrava reviewed the questionnaire and the accompanying cover letter, which explained the scientific objectives of the survey to the participants. The review ensured that the research design met ethical standards for research involving human participants. Ethics approval was granted under the reference number VSB/25/044396. The study was conducted in accordance with the Declaration of Helsinki.\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003eParticipation in the survey was fully voluntary and anonymous. Respondents were informed about the purpose of the research prior to participation and could withdraw at any time. No personal or sensitive data were collected, except for basic demographic characteristics (age and gender). Therefore, written informed consent was not required in accordance with national ethical guidelines and regulations.\\u003c/p\\u003e\\n\\u003cp\\u003eThe questions included ordinal (O), nominal (N), and binary (B) types of variables (indicated by the letters in the table). The questions are introduced in Table 1 below. \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eTable 1 Questions for the Quantitative Research \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;\\u0026nbsp;\\u003c/p\\u003e\\n\\u003ctable border=\\\"1\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"616\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 40px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 489px;\\\"\\u003e\\n \\u003cp\\u003eQ \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003eType of variable\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd style=\\\"width: 6px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 40px;\\\"\\u003e\\n \\u003cp\\u003eQ1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 494px;\\\"\\u003e\\n \\u003cp\\u003eHow would you rate your current mental state?\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003eO\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 40px;\\\"\\u003e\\n \\u003cp\\u003eQ2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 494px;\\\"\\u003e\\n \\u003cp\\u003eIf you sought professional help for your mental health (e.g., psychologist, psychiatrist), how would you rate the quality of these services?\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003eO\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 40px;\\\"\\u003e\\n \\u003cp\\u003eQ3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 494px;\\\"\\u003e\\n \\u003cp\\u003eDo you think mental health care is easily accessible in your city/region?\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003eO\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 40px;\\\"\\u003e\\n \\u003cp\\u003eQ4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 494px;\\\"\\u003e\\n \\u003cp\\u003eWhich factors do you think affect the mental health of young people aged 18\\u0026ndash;25 the most? (select the 3 most important)\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003eB\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 40px;\\\"\\u003e\\n \\u003cp\\u003eQ5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 494px;\\\"\\u003e\\n \\u003cp\\u003eDo you live in an urban or rural environment?\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003eN\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 40px;\\\"\\u003e\\n \\u003cp\\u003eQ6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 494px;\\\"\\u003e\\n \\u003cp\\u003eWhat benefits of living in the city do you think have a positive impact on mental health? (select the 3 most important)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003eB\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 40px;\\\"\\u003e\\n \\u003cp\\u003eQ7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 494px;\\\"\\u003e\\n \\u003cp\\u003eWhat disadvantages of living in the city do you think deteriorate mental health? (select the 3 most important)\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003eB\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 40px;\\\"\\u003e\\n \\u003cp\\u003eQ8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 494px;\\\"\\u003e\\n \\u003cp\\u003eIf you could choose, where would you prefer to live in terms of mental health?\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003eN\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 40px;\\\"\\u003e\\n \\u003cp\\u003eQ9\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 494px;\\\"\\u003e\\n \\u003cp\\u003eHow important is support from family and friends to you in dealing with mental health problems?\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003eO\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 40px;\\\"\\u003e\\n \\u003cp\\u003eQ10\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 494px;\\\"\\u003e\\n \\u003cp\\u003eDo you think the age at which people enter parenthood can affect the mental health of their children?\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003eO\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 40px;\\\"\\u003e\\n \\u003cp\\u003eQ11\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 494px;\\\"\\u003e\\n \\u003cp\\u003eHow much of an impact do you think crime in your region has on your mental health?\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003eO\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 40px;\\\"\\u003e\\n \\u003cp\\u003eQ12\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 494px;\\\"\\u003e\\n \\u003cp\\u003eDo you think the age of the first-time mother can affect her mental health?\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003eO\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 40px;\\\"\\u003e\\n \\u003cp\\u003eQ13\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 494px;\\\"\\u003e\\n \\u003cp\\u003eHow would you rate the level of general awareness and education about mental health in secondary schools and colleges?\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003eO\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 40px;\\\"\\u003e\\n \\u003cp\\u003eQ14\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 494px;\\\"\\u003e\\n \\u003cp\\u003eWhich of the following do you think would be most helpful in improving mental health care for young people in your region? (select up to 2 options)\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003eB\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 40px;\\\"\\u003e\\n \\u003cp\\u003eQ15\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 494px;\\\"\\u003e\\n \\u003cp\\u003eHow often do you feel you have to look after your mental health on your own, without the help of professionals or family?\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 82px;\\\"\\u003e\\n \\u003cp\\u003eO\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp\\u003eIdentification of latent dimensions in the perception of mental health was performed using the principal component analysis (PCA), designed to reduce the data set dimension and reveal hidden structures in the data. PCA transforms the original variables \\u003cem\\u003eX₁, X₂, ..., Xₚ\\u0026nbsp;\\u003c/em\\u003einto new, orthogonal components \\u003cem\\u003eZₖ,\\u003c/em\\u003e which maximise variance on data (1):\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eZₖ = aₖ₁X₁ + aₖ₂X₂ + ... + aₖₚXₚ = aₖᵗX\\u003c/em\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;(1)\\u003c/p\\u003e\\n\\u003cp\\u003ewhere \\u003cem\\u003eaₖ\\u003c/em\\u003e is the eigenvector of correlation matrix \\u0026Sigma;. The components are independent of each other and maintain order according to the explained variance.\\u003c/p\\u003e\\n\\u003cp\\u003eTo increase factor interpretability, the varimax rotation was used, which maximises high loadings and minimises low loadings. The number of components was determined by Kaiser criterion (eigenvalue higher than 1) and scree plot. Comparative analysis of factor scores was used to analyse differences in the perception of mental health among students. The factor scores for the individual components were calculated as a weighted average of items included in the given latent variable, while the weights corresponded to the sizes of factor loadings. The subsequent testing of gender differences was performed using Welch\\u0026rsquo;s t-test for independent selections, suitable in case of possible inequalities in variance between groups. This test was applied to the scores of the individual components, for which the respective items were available.\\u003c/p\\u003e\\n\\u003cp\\u003eCalculations were performed in IBM SPSS Statistics (Version 29).\\u003c/p\\u003e\"},{\"header\":\"Results of the Questionnaire Survey\",\"content\":\"\\u003cp\\u003eThe number of respondents of the on-line questionnaire aged 18\\u0026ndash;26 years was 767 (N = 767). The most numerous were respondents aged 20 (20.7%), 22 (19.8%), and 21 years (18.4%). The sample included 60.5% of women and 39.5% of men. The respondent structure according to the place of residence shows that almost a half of the respondents come from the urban environment (46.2%), a third live in areas with combined features of urban and rural environments (29.9%), and a quarter of respondents indicated that they lived in rural areas (24.0%).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eLatent Variables: Principal Component Analysis\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe principal component analysis (PCA) identified three components with latent values (eigenvalues) higher than 1, which corresponds to the classic Kaiser criterion (see Table 2 and Figure 1). These three components combined explain 46.93% of the total variance in data. The first component has the eigenvalue of 1.438 and explains 17.98% of the total variance. The second component with the value of 1.285 contributes 16.07% of variance, thus the cumulative variability explained reaches 34.04%. The third component has the eigenvalue of 1.030, adding further 12.88%, which leads to the cumulative share of 46.93% of variance explained.\\u003c/p\\u003e\\n\\u003cp\\u003eTable 2 Total Variance Explained\\u003c/p\\u003e\\n\\u003ctable border=\\\"0\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\" width=\\\"597\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 83px;\\\"\\u003e\\n \\u003cp\\u003eComponent\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"2\\\" valign=\\\"top\\\" style=\\\"width: 110px;\\\"\\u003e\\n \\u003cp\\u003eInitial Eigenvalues\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 70px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd colspan=\\\"3\\\" valign=\\\"top\\\" style=\\\"width: 167px;\\\"\\u003e\\n \\u003cp\\u003eExtraction Sums of Squared Loadings\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd colspan=\\\"3\\\" valign=\\\"top\\\" style=\\\"width: 167px;\\\"\\u003e\\n \\u003cp\\u003eRotation Sums of Squared Loadings\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 83px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 54px;\\\"\\u003e\\n \\u003cp\\u003eTotal\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 56px;\\\"\\u003e\\n \\u003cp\\u003e% of Variance\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 70px;\\\"\\u003e\\n \\u003cp\\u003eCumulative %\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41px;\\\"\\u003e\\n \\u003cp\\u003eTotal\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 56px;\\\"\\u003e\\n \\u003cp\\u003e% of Variance\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 70px;\\\"\\u003e\\n \\u003cp\\u003eCumulative %\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41px;\\\"\\u003e\\n \\u003cp\\u003eTotal\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 56px;\\\"\\u003e\\n \\u003cp\\u003e% of Variance\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 70px;\\\"\\u003e\\n \\u003cp\\u003eCumulative %\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 83px;\\\"\\u003e\\n \\u003cp\\u003e1\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 54px;\\\"\\u003e\\n \\u003cp\\u003e1.438\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 56px;\\\"\\u003e\\n \\u003cp\\u003e17.975\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 70px;\\\"\\u003e\\n \\u003cp\\u003e17.975\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41px;\\\"\\u003e\\n \\u003cp\\u003e1.438\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 56px;\\\"\\u003e\\n \\u003cp\\u003e17.975\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 70px;\\\"\\u003e\\n \\u003cp\\u003e17.975\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41px;\\\"\\u003e\\n \\u003cp\\u003e1.428\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 56px;\\\"\\u003e\\n \\u003cp\\u003e17.855\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 70px;\\\"\\u003e\\n \\u003cp\\u003e17.855\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 83px;\\\"\\u003e\\n \\u003cp\\u003e2\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 54px;\\\"\\u003e\\n \\u003cp\\u003e1.285\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 56px;\\\"\\u003e\\n \\u003cp\\u003e16.069\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 70px;\\\"\\u003e\\n \\u003cp\\u003e34.044\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41px;\\\"\\u003e\\n \\u003cp\\u003e1.285\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 56px;\\\"\\u003e\\n \\u003cp\\u003e16.069\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 70px;\\\"\\u003e\\n \\u003cp\\u003e34.044\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41px;\\\"\\u003e\\n \\u003cp\\u003e1.181\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 56px;\\\"\\u003e\\n \\u003cp\\u003e14.761\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 70px;\\\"\\u003e\\n \\u003cp\\u003e32.616\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 83px;\\\"\\u003e\\n \\u003cp\\u003e3\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 54px;\\\"\\u003e\\n \\u003cp\\u003e1.030\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 56px;\\\"\\u003e\\n \\u003cp\\u003e12.881\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 70px;\\\"\\u003e\\n \\u003cp\\u003e46.925\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41px;\\\"\\u003e\\n \\u003cp\\u003e1.030\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 56px;\\\"\\u003e\\n \\u003cp\\u003e12.881\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 70px;\\\"\\u003e\\n \\u003cp\\u003e46.925\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41px;\\\"\\u003e\\n \\u003cp\\u003e1.145\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 56px;\\\"\\u003e\\n \\u003cp\\u003e14.309\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 70px;\\\"\\u003e\\n \\u003cp\\u003e46.925\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 83px;\\\"\\u003e\\n \\u003cp\\u003e4\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 54px;\\\"\\u003e\\n \\u003cp\\u003e0.996\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 56px;\\\"\\u003e\\n \\u003cp\\u003e12.453\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 70px;\\\"\\u003e\\n \\u003cp\\u003e59.378\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 56px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 70px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 56px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 70px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 83px;\\\"\\u003e\\n \\u003cp\\u003e5\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 54px;\\\"\\u003e\\n \\u003cp\\u003e0.930\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 56px;\\\"\\u003e\\n \\u003cp\\u003e11.627\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 70px;\\\"\\u003e\\n \\u003cp\\u003e71.005\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 56px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 70px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 56px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 70px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 83px;\\\"\\u003e\\n \\u003cp\\u003e6\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 54px;\\\"\\u003e\\n \\u003cp\\u003e0.882\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 56px;\\\"\\u003e\\n \\u003cp\\u003e11.030\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 70px;\\\"\\u003e\\n \\u003cp\\u003e82.035\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 56px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 70px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 56px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 70px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 83px;\\\"\\u003e\\n \\u003cp\\u003e7\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 54px;\\\"\\u003e\\n \\u003cp\\u003e0.750\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 56px;\\\"\\u003e\\n \\u003cp\\u003e9.380\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 70px;\\\"\\u003e\\n \\u003cp\\u003e91.415\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 56px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 70px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 56px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 70px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 83px;\\\"\\u003e\\n \\u003cp\\u003e8\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 54px;\\\"\\u003e\\n \\u003cp\\u003e0.687\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 56px;\\\"\\u003e\\n \\u003cp\\u003e8.585\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 70px;\\\"\\u003e\\n \\u003cp\\u003e100.000\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 56px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 70px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 41px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 56px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 70px;\\\"\\u003e\\u003cbr\\u003e\\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp\\u003eExtraction Method: Principal Component Analysis, SPSS. \\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eThe scree plot in Figure 1 visualises the distribution of eigenvalues across the eight components. The decline following the third component, clearly shows that the first three factors are of greatest importance. The red line shows the limit of the Kaiser criterion (eigenvalue = 1), separating the components with higher values.\\u003c/p\\u003e\\n\\u003cp\\u003eThe varimax rotation (Table 2) caused a slight redistribution of the variance explained among these three components, but the cumulative total remained unchanged. The first component continues to have the largest share (17.86%), followed by the second (14.76%) and third (14.31%) components. The rotation ensures a more precise definition of the factor structure, as it highlights the dominant loadings of the variables to the individual components (latent variables). The loadings are illustrated by the factor loadings heat map, which shows how each manifest variable (Q1\\u0026ndash;Q15) contributes to the individual components, see Figure 2. Red shades indicate stronger positive loadings, grey shades weaker or no loadings.\\u003c/p\\u003e\\n\\u003cp\\u003eComponent 1: Subjective perspective on mental well-being. This component comprises items related to personal experience of mental health \\u0026ndash; especially the feeling of loneliness in caring for mental health (0.750), evaluation of one\\u0026rsquo;s own mental state (0.693), and perception of mental health awareness in the school environment (0.590). This dimension may be interpreted as self-perception and awareness of one\\u0026rsquo;s own mental health.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eComponent 2: Contextual factors and interpersonal support. The second component captures the impact of crime in the area (0.750) and the importance of support from family and friends (0.730). It is a dimension that reflects the external context and availability of social support in coping with mental health problems.\\u003c/p\\u003e\\n\\u003cp\\u003eComponent 3: Social and institutional determinants of mental health. The third component includes items focusing on institutional approaches and broader social context: influence of parent\\u0026rsquo;s age on the mental health of children (0.736), preferences for a place to live in terms of mental health (0.528), and availability of mental health care (0.508). This dimension can be perceived as institutional and community context of mental health.\\u003c/p\\u003e\\n\\u003cp\\u003eThese three components together explain approximately 47% of the total variance (see Table 2 Total Variance Explained). The results indicate that attitudes towards mental health are not uniform, but rather structured in different, yet interconnected dimensions.\\u003c/p\\u003e\\n\\u003cp\\u003eFactor scores were calculated as a weighted average of items using the factor loadings. This was followed by the Welch\\u0026rsquo;s t-test for independent samples that takes into account possible unequal variances.\\u003c/p\\u003e\\n\\u003cp\\u003eIn terms of gender perception, the results showed that in Component PC1, the differences between men and women were not statistically significant (\\u003cem\\u003et\\u003c/em\\u003e = \\u0026ndash;1.31; \\u003cem\\u003ep\\u003c/em\\u003e = 0.192). In the component reflecting contextual factors and interpersonal support (PC2), comprising support from family and friends and perception of crime in the area, statistically significant gender differences were found (\\u003cem\\u003et\\u003c/em\\u003e = \\u0026ndash;5.57; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u003cem\\u003ep\\u003c/em\\u003e \\u0026lt; 0.001). Women had higher scores (F = 3.25) than men (M = 2.92), suggesting greater sensitivity to these external factors in relation to mental health. Significant gender differences (\\u003cem\\u003et\\u003c/em\\u003e = \\u0026ndash;3.49; \\u003cem\\u003ep\\u003c/em\\u003e \\u0026lt; 0.001) were found in Component PC3, where women had a higher average score (F = 1.65) than men (M = 1.49). This may suggest that women are more sensitive to the effects of community and institutional environments on their mental health and attach higher importance to the availability of car and suitable environment.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eResults of the Perception of Mental Health Influences and Interventions\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eWhich factors do you think affect the mental health of young people aged 18-25 the most?\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eChart in Figure 3 shows the distribution of perception of external factors that affect mental health, broken down by gender (women N = 464, men N = 303; overall data set N = 767). Respondents had the opportunity to select 3 of the 7 predefined factors, which in their opinion negatively affect mental health.\\u003c/p\\u003e\\n\\u003cp\\u003eThe most common determinant was the workload associated with study or employment, identified as \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;a significant factor by 78.5% of respondents. This area was more strongly emphasised among women. Social media and technology ranked seconds (66.6%) and family relationships ranked third (61.0%) \\u0026ndash; here too, the response rate was higher for women than for men.\\u003c/p\\u003e\\n\\u003cp\\u003eLoneliness and social isolation were relevant for 57.4% of the respondents, again more common among women. Approximately a half of the respondents (52.3%), with no significant gender differences, indicated economic conditions as a potential stressor.\\u003c/p\\u003e\\n\\u003cp\\u003eIn contrast, factors like crime and feeling unsafe (4.3%) and lack of access to healthcare (3.9%) were entirely marginal, a fact that may reflect their lower subjective relevance in relation to mental well-being.\\u003c/p\\u003e\\n\\u003cp\\u003eIn summary, the perception of mental health determinants shows a gender-specific pattern where women more frequently identify stressors associated with the social environment, interpersonal relations, and digital technologies.\\u003c/p\\u003e\\n\\u003cp\\u003eChart in Figure 4 shows the frequency of occurrence of positively rated aspects of the urban environment in relation to their perceived impact on mental health. Respondents had the opportunity to select 3 of the 6 predefined factors, which in their opinion most strongly represent the supportive or beneficial dimensions of urban life.\\u003c/p\\u003e\\n\\u003cp\\u003eThe most significant factor was the greater social and cultural offer, identified by 81.1% of the respondents, a fact that underlines the importance of urban environment as a place of cultural stimulation and social engagement. The second most frequently cited area was access to employment and education (64.8%), which reflects the importance of the city as an area of socio-economic opportunity.\\u003c/p\\u003e\\n\\u003cp\\u003eThe possibility to establish wider social contacts (42.1%) and better accessibility of public transport (42.4%) were assessed as positive benefits to a comparable extent, with only minor difference between women and men. Easier access to medical and mental healthcare (37.5%) was slightly more often reported by women, which probably reflects their higher sensitivity to the institutional infrastructure of care.\\u003c/p\\u003e\\n\\u003cp\\u003eIn contrast, greater anonymity and privacy was identified as an advantage by mere 24.5% of the respondents, possibly indicating a lower importance of individualisation of the environment in relation to the perception of mental health.\\u003c/p\\u003e\\n\\u003cp\\u003eOverall, urban environment is primarily perceived as a space of cultural, educational, and employment opportunities, while the aspects of privacy, anonymity, and access to healthcare play a minor role in the respondents\\u0026rsquo; perception.\\u003c/p\\u003e\\n\\u003cp\\u003eChart in Figure 5 shows the perception of negatively rated aspects of the urban environment that may adversely impact mental health. Respondents had the opportunity to select 3 of the 6 predefined factors, which in their opinion represent the main burdens of urban life.\\u003c/p\\u003e\\n\\u003cp\\u003eThe most frequently cited problem was increased stress levels and fast pace of life, identified by 74.2% of respondents, while women reflected this fact more strongly women. Almost the same percentage of respondents (72.9%) pointed out the lack of natural environment and quiet areas, which confirms the importance of the natural environment for perceived psychological well-being. The third most common area was noise and pollution (62.3%), again more accentuated by women.\\u003c/p\\u003e\\n\\u003cp\\u003eIn contrast, less prevalent, but not insignificant factors included higher crime rate (26.1%), more competitive working environment (30.8%), and anonymity associated with feelings of loneliness (23.5%). These aspects were less frequent in the answers, yet can significantly affect mental health in certain populations.\\u003c/p\\u003e\\n\\u003cp\\u003eIt is arguable that negative aspects of the urban environment are perceived by the respondents primarily in connection with stress, lack of natural environment, and sensory overload, while fear of crime and social isolation are less frequent.\\u003c/p\\u003e\\n\\u003cp\\u003eChart in Figure 6 shows preferred areas of improvement in mental health care as perceived by the respondents, who had the opportunity to select from five possible interventions.\\u003c/p\\u003e\\n\\u003cp\\u003eThe most commonly stated priority was strengthening the support in schools and universities (57.2%), a fact that points out the perceived significance of prevention and intervention within educational institutions as key points for early detection of psychological problems. This factor was more strongly accentuated by women.\\u003c/p\\u003e\\n\\u003cp\\u003eThe second most frequently cited area was ensuring a better preventive care system (44.6%), indicating the respondents\\u0026rsquo; emphasis on early intervention and better systemic readiness of healthcare services. This was followed by improved availability of specialist care (44.5%), more often accentuated by women.\\u003c/p\\u003e\\n\\u003cp\\u003eKey areas identified by relatively fewer respondents were the increased access to care in terms of financial demands (40.7%) and awareness campaigns (39.2%). Still, these areas remain relevant components of the comprehensive strategy to improve mental health care.\\u003c/p\\u003e\\n\\u003cp\\u003eIn general, respondents prefer systemic changes focusing on prevention, university environment, and availability of specialised care, while gender differences remain relatively consistent across all the categories.\\u003c/p\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eThis study was aimed at identifying latent variables that shape the perception of mental health of university students and understanding their attitudes towards urban environment and preferred interventions. The results yielded several important findings, which correspond to the research questions.\\u003c/p\\u003e \\u003cp\\u003eRQ1 and RQ2: Three key latent components were identified using the factor analysis \\u0026ndash; subjective perspective on mental well-being, contextual factors and interpersonal support, and institutional determinants. These dimensions show that perception of mental health is not a matter of individual experience, but is rather shaped by a broader social and environmental context. Especially significant was the component reflecting subjective perception and independence in taking care of one\\u0026rsquo;s own mental health, suggesting a certain level of individualisation of experience and coping with mental health problems.\\u003c/p\\u003e \\u003cp\\u003eRQ3: Relationship between the urban environment and mental well-being was evaluated ambivalently by the respondents. Cultural and educational opportunities were perceived positively by them, while the most common negative factors cited were stress, noise, and lack of natural environment. These results confirm that city can be both a source of support and a risky environment, which is consistent with previous findings (e.g., Peen et al., 2010; Srivarathan et al., 2023) [\\u003cspan citationid=\\\"CR6\\\" class=\\\"CitationRef\\\"\\u003e6\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e].\\u003c/p\\u003e \\u003cp\\u003eRQ4: Gender differences observed indicate that women perceive mental health more comprehensively in relation to the institutional and community factors, while men had higher scores in the area of subjective assessment of mental well-being. This supports earlier findings regarding higher sensitivity in women towards social stressors (Stewart \\u0026amp; Vigod, 2016) [\\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e5\\u003c/span\\u003e] and indicates the need for gender-sensitive interventions.\\u003c/p\\u003e \\u003cp\\u003eRQ5: Preferred forms of support most commonly indicated by the students included strengthening mental health within educational institutions, including psychological services at universities, prevention, and psychoeducation. These findings show the potential of university environments as key points of early detection of mental problems.\\u003c/p\\u003e \\u003cp\\u003eIn terms of practical implications for mental health in general, it is important that interventions are not only focused on acute problems, but also on supporting students\\u0026rsquo; psychological resilience and overall well-being. It is therefore recommended to improve and expand the system of support at universities by preventive programmes.\\u003c/p\\u003e \\u003cp\\u003eHowever, this research has, logically, several limitations due to the questionnaire survey in the form of voluntary participation, as this is likely to create selection bias \\u0026ndash; especially in terms of higher representation of women. Data were collected at a single point in time, which does not allow for causal relationships to be observed. Last, but not least, the research did not involve the entire diversity of university population, such as students with migration background or from marginalised communities.\\u003c/p\\u003e \\u003cp\\u003eAt the same time, we highlight the methodological limitations of quantitative approaches \\u0026ndash; as shown by Laidlaw et al. (2016) [\\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e15\\u003c/span\\u003e], students can perceive the terms \\u0026ldquo;mental health\\u0026rdquo; and \\u0026ldquo;mental well-being\\u0026rdquo; differently and this may influence interpretation of the answers. An issue to be addressed is to what extent efficiency of preventive programmes can be influenced by this different understanding. It also seems valid to ask if and how the urban environment can be transformed to minimise stressors and corroborate mental health resilience of university students. Results of this study, supplemented by the findings of Srivarathan et al. (2023) [\\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e14\\u003c/span\\u003e], indicate that stability of social ties, availability of green zones, and community support seem to be key factors in mental comfort of young population living in cities.\\u003c/p\\u003e \\u003cp\\u003eFuture research should take these limitations into consideration and combine quantitative approaches with qualitative methods that would allow deeper understanding of subjective implications associated with mental health.\\u003c/p\\u003e\"},{\"header\":\"Conclusion\",\"content\":\"\\u003cp\\u003eThe aim of the research was to identify latent variables that shape the perception of mental health of university students and understanding their attitudes towards urban environment and preferred interventions. Three components were found using the factor analysis: subjective perspective on mental well-being, contextual factors and interpersonal support, and social and institutional determinants of mental health. These dimensions show that perception of mental health is not reducible to individual symptoms, but is rather shaped by a social support, environment, and institutional framework.\\u003c/p\\u003e \\u003cp\\u003eThe results also showed that students reflect the urban environment ambivalently \\u0026ndash; they value its cultural and economic opportunities, but at the same time point to stress, absence of nature, and sensory overload. Preferred interventions thus include available, prevention-oriented, and community-based care, with an emphasis on the university environment as a key place of support.\\u003c/p\\u003e \\u003cp\\u003eGender differences ascertained indicate that women perceive external factors (such as crime rate, institutional availability of care) as being more significant, while men reach higher scores in subjective assessment of mental health. These differences should be taken into account when designing targeted interventions and preventive programmes.\\u003c/p\\u003e \\u003cp\\u003eThe results of this study can serve as a basis for targeted interventions and systemic changes in educational and medical institutions to better meet the needs of young people in the changing social and urban context.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgements\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis paper was supported by project NO. SP2024/077 \\u0026bdquo;Approximation of exogenous and endogenous factors of effective allocation of public resources to support the implementation of digital and technological innovations in the public sector, VSB \\u0026ndash; Technical University of Ostrava and it has been produced whith the financial support of the European Union under the REFRESH \\u0026ndash; Research Excellence For Region Sustainability and High-tech Industries project number CZ.10.03.01/00/22_003/0000048 via the Operational Programme Just Transition.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors declare that there was no funding.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAvailability of data and materials\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAll data generated or analyzed during this study are included in this article.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eEthics aproval and consent to participate\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent for publication.\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCompeting interests\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthor details\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthors and Affiliations\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eDepartment of Management, VSB \\u0026ndash; Technical University of Ostrava, 17. listopadu St. 2172/15, 708 00, Ostrava-Poruba, Czech Republic\\u0026nbsp;\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eMinistry of Health Czech Republic. National Action Plan for Mental Health 2020-2030. https://mzd.gov.cz/narodni-akcni-plan-pro-dusevni-zdravi-2020-2030/. Accessed 10 Jan 2025.\\u003c/li\\u003e\\n\\u003cli\\u003eWorld mental health report: Transforming mental health for all. (2022). https://www.who.int/publications/i/item/9789240049338. Accessed 5 Feb 2025.\\u003c/li\\u003e\\n\\u003cli\\u003eAnthony, W.A. (1993). \\u003cem\\u003eRecovery from mental illness: the guiding vision of the mental health service system in the 1990s\\u003c/em\\u003e. Psychosocial Rehabilitation Journal, 16(4), pp.11\\u0026ndash;23. https://doi.org/10.1037/h0095655.\\u003c/li\\u003e\\n\\u003cli\\u003eTew, J., Ramon, S., Slade, M., Bird, V., Melton, J. and Le Boutillier, C. (2012). \\u003cem\\u003eSocial factors and recovery from mental health difficulties: a review of the evidence\\u003c/em\\u003e. British Journal of Social Work, 42(3), pp.443\\u0026ndash;460. https://doi.org/10.1093/bjsw/bcr076.\\u003c/li\\u003e\\n\\u003cli\\u003eStewart, D.E. and Vigod, S.N. (2016). \\u003cem\\u003eDeveloping a gender-sensitive women\\u0026rsquo;s mental health policy: lessons from Canada\\u003c/em\\u003e. Health Care for Women International, 37(2), pp.134\\u0026ndash;148. https://doi.org/10.1080/07399332.2015.1085312.\\u003c/li\\u003e\\n\\u003cli\\u003ePeen, J., Schoevers, R.A., Beekman, A.T.F. and Dekker, J. (2010). \\u003cem\\u003eThe current status of urban-rural differences in psychiatric disorders\\u003c/em\\u003e. Acta Psychiatrica Scandinavica, 121(2), pp.84\\u0026ndash;93. https://doi.org/10.1111/j.1600-0447.2009.01438.x.5.\\u003c/li\\u003e\\n\\u003cli\\u003eWorld Health Organization (WHO). (2017). \\u003cem\\u003eDepression and Other Common Mental Disorders: Global Health Estimates\\u003c/em\\u003e. Geneva: World Health Organization. https://apps.who.int/iris/handle/10665/254610. Accessed 10 Jan 2025.\\u003c/li\\u003e\\n\\u003cli\\u003eVigo, D., Thornicroft, G. and Atun, R. (2016). \\u003cem\\u003eEstimating the true global burden of mental illness\\u003c/em\\u003e. The Lancet Psychiatry, 3(2), pp.171\\u0026ndash;178. https://doi.org/10.1016/S2215-0366(15)00505-2.\\u003c/li\\u003e\\n\\u003cli\\u003eGatdula, N., Costa, C. B., Rasc\\u0026oacute;n, M. S., Deckers, C. M., \\u0026amp; Bird, M. (2022). College students\\u0026rsquo; perceptions of telemental health to address their mental health needs. Journal of American College Health, 72(2), 515\\u0026ndash;521. https://doi.org/10.1080/07448481.2022.2047697.\\u003c/li\\u003e\\n\\u003cli\\u003eKeyes, C. L. M. (2005). Mental Illness and/or Mental Health? Investigating Axioms of the Complete State Model of Health. \\u003cem\\u003eJournal of Consulting and Clinical Psychology, 73\\u003c/em\\u003e(3), 539\\u0026ndash;548. https://doi.org/10.1037/0022-006X.73.3.539.\\u003c/li\\u003e\\n\\u003cli\\u003eZhou, J., Jiang, S., Zhu, X. \\u003cem\\u003eet al.\\u003c/em\\u003e Profiles and Transitions of Dual-Factor Mental Health among Chinese Early Adolescents: The Predictive Roles of Perceived Psychological Need Satisfaction and Stress in School. \\u003cem\\u003eJ Youth Adolescence\\u003c/em\\u003e 49, 2090\\u0026ndash;2108 (2020). https://doi.org/10.1007/s10964-020-01253-7.\\u003c/li\\u003e\\n\\u003cli\\u003eBernanke, J., Stanley, B., Oquendo, M., \\u0026amp; Posner, J. (2017). Toward fine-grained phenotyping of suicidal behavior: The role of suicidal subtypes. \\u003cem\\u003eMolecular Psychiatry, 22\\u003c/em\\u003e(8), 1080\\u0026ndash;1081. DOI: https://doi.org/10.1038/mp.2017.123.\\u003c/li\\u003e\\n\\u003cli\\u003eVrabkov\\u0026aacute;, I., Vaňkov\\u0026aacute;, I. (2024). Socioeconomic Factors in the Prevalence of Mental Disorders in the Population Aged 0\\u0026ndash;25 Years: Regions in the Czech Republic. Preprint, https://www.researchsquare.com/article/rs-5349124/v1.\\u003c/li\\u003e\\n\\u003cli\\u003eSrivarathan, A., J\\u0026oslash;rgensen, T. S. H., Lund, R., Nygaard, S. S., and Kristiansen, M. (2023). They are breaking us into pieces: A longitudinal multi-method study on urban regeneration and place-based social relations among social housing residents in Denmark. Health \\u0026amp; Place, 79, 102965. https://doi.org/10.1016/j.healthplace.2023.102965.\\u003c/li\\u003e\\n\\u003cli\\u003eLaidlaw, P., McLellan, A. and Ozakinci, G. (2016). Understanding undergraduate student perceptions of mental health, mental well-being and help-seeking behaviour. \\u003cem\\u003eStudies in Higher Education\\u003c/em\\u003e, 41(12), pp.2156\\u0026ndash;2168. https://doi.org/10.1080/03075079.2015.1026890\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-public-health\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"pubh\",\"sideBox\":\"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/pubh/default.aspx\",\"title\":\"BMC Public Health\",\"twitterHandle\":\"@BMC_series\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"mental health, university students, factor analysis, gender, urban environment, prevention\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-6587591/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-6587591/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eMental health of university students has become an increasingly important public health issue, especially following the COVID-19 pandemic. Despite the high prevalence of mental illness, there still lacks a deeper understanding of how students themselves perceive their mental health and what contextual and institutional factors influence this perception. This research focused on the perception of mental health among university students in the Czech Republic and analysed their attitudes towards the urban environment as well as the preferred forms of support.\\u003c/p\\u003e \\u003cp\\u003eThe cross-sectional questionnaire survey, conducted online, involved 767 students from five public universities. The fifteen questions covered the areas of internal experiences, social background, and institutional conditions. Data were analysed using the principal component analysis (PCA) and Welch\\u0026rsquo;s t-test to compare gender differences.\\u003c/p\\u003e \\u003cp\\u003eAnalysis revealed three latent components shaping the perception of mental health: (1) subjective mental well-being (e.g., loneliness, self-assessment of the mental state); (2) contextual and interpersonal factors (e.g., feeling of security, family support); and (3) institutional determinants (e.g., availability of services, family background). Gender differences were statistically significant in the second and third components \\u0026ndash; women showed higher sensitivity to institutional and environmental factors. Social networks, study demands, and family relationships were perceived as the main stressors by the students, while cultural and educational possibilities of the cities were valued positively by them. Availability of services at the universities, prevention, and easier access to care were considered by them as the most suitable forms of support.\\u003c/p\\u003e \\u003cp\\u003eThe findings show that students\\u0026rsquo; perception of mental health is multilayered \\u0026ndash; influenced by individual, social, as well as institutional aspects. Efficient public health strategies should therefore not be limited to clinical intervention, but they should corroborate the university environment, reflect gender differences, and improve the systemic availability of support.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Analysis of University Students’ Perception of Mental Health\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2025-05-30 13:39:32\",\"doi\":\"10.21203/rs.3.rs-6587591/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"decision\",\"content\":\"Revision requested\",\"date\":\"2025-07-28T08:19:43+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"23756837684069324796828030467435804294\",\"date\":\"2025-07-28T06:19:12+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-07-27T16:58:55+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"168837782113777631522382840803987453282\",\"date\":\"2025-07-23T08:39:30+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"333936549391104766817315732955097595485\",\"date\":\"2025-07-22T18:18:56+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"editorInvited\",\"content\":\"\",\"date\":\"2025-06-30T13:22:36+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-06-15T15:15:40+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"12374884814870941614018910015243086117\",\"date\":\"2025-06-14T18:37:00+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2025-06-14T14:59:25+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"118208312048893889538813224127483723780\",\"date\":\"2025-06-13T16:45:14+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"163320022141565445163747775642150642316\",\"date\":\"2025-06-01T04:00:40+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2025-05-28T09:39:41+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2025-05-16T08:28:00+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2025-05-15T12:07:28+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"BMC Public Health\",\"date\":\"2025-05-15T12:06:18+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-public-health\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"pubh\",\"sideBox\":\"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/pubh/default.aspx\",\"title\":\"BMC Public Health\",\"twitterHandle\":\"@BMC_series\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"47cbad5a-2c9d-4a70-b62b-12438860b119\",\"owner\":[],\"postedDate\":\"May 30th, 2025\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"published-in-journal\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2025-11-17T16:08:57+00:00\",\"versionOfRecord\":{\"articleIdentity\":\"rs-6587591\",\"link\":\"https://doi.org/10.1186/s12889-025-25213-7\",\"journal\":{\"identity\":\"bmc-public-health\",\"isVorOnly\":false,\"title\":\"BMC Public Health\"},\"publishedOn\":\"2025-11-10 15:58:31\",\"publishedOnDateReadable\":\"November 10th, 2025\"},\"versionCreatedAt\":\"2025-05-30 13:39:32\",\"video\":\"\",\"vorDoi\":\"10.1186/s12889-025-25213-7\",\"vorDoiUrl\":\"https://doi.org/10.1186/s12889-025-25213-7\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-6587591\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-6587591\",\"identity\":\"rs-6587591\",\"version\":[\"v1\"]},\"buildId\":\"8U1c8b4HqxoKbykW_rLl7\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}