Evaluating quality of life and well-being of university students, with the EQ5D-5L, the WHO-5 Well-Being Index, and the ICECAP-A questionnaires to gain baseline data

Abstract

Backgrounds

The study objective was to fill the gap in understanding of students’ quality of life and well-being by evaluating well-being from a traditional perspective with the World Health Organization’s General Well-being Scale and a capability perspective ICECAP-A (ICEpop CAPability measure for Adults); quality of life was assessed with the EQ-5D-5 L (EuroQol instrument) to gain norms for this population.

Methods

In our cross-sectional study, we applied the validated Hungarian version of internationally recognised instruments: WHO-5 Well-Being Index, ICECAP-A, and the EQ-5D-5 L. In total, 561 university students completed the online survey.

Results

The mean WHO-5 Well-Being Index was 42.62 (Std. Error 0.869) higher scores representing better well-being; ICECAP-A score was 0.441 (Std. Error 0.008) on a scale where 0 equals to „no-capability” and 1 corresponds to „full-capability”. The average EQ-5D-5 L index score was 0.846 (Std. Error 0.008) on a scale where 0 equals death and 1 corresponds to “perfect quality of life” should be repéased by: best possible health. The low/bad results gained in both aspects align with previous evidence coming from academically demanding fields. Chronic physical conditions showed minimal influence on outcomes.

Conclusion

The study presents a comprehensive baseline assessment to provide norms for university students of quality of life and well-being studying health and biomedical sciences. ICECAP-A provided a broader capability-based perspective, supporting its future use in economic evaluations of interventions. These baseline data support the need for targeted support strategies and can inform future evaluations of intervention cost-effectiveness and resource allocation in academic and public health contexts. Our results should have broader implications across academic settings.

Background

The answer to the question, “How are you?” is desirably: “I am fine thank you”; or “Very well, thank you“; this good state is wishfully kept lifelong. The condition of a person can be described by two concepts: by the quality of life of a person and the well-being of a person, which are closely related and overlapping, sharing quite some similarities. Since both have subjective perceptions and are multidimensional, both have external factors that play an important role in shaping them.

A person’s health status (including physical, mental, and social well-being) significantly affects quality of life, a concept that can be assessed through health-related quality of life (HrQoL). This refers specifically to how health impacts an individual’s quality of life and can be measured using both generic and disease-specific quality of life questionnaires [1]. Well-being encompasses various dimensions [2] of a person’s life, such as emotional, psychological, and social aspects. It is generally defined as the state of feeling good and functioning well; however, it also emphasizes mental health and emotional fulfillment [3, 4]. Well-being assessments are valuable tools designed to evaluate mental and emotional health by using standardized scales like the WHO-5 Well-Being Index. These tools can help individuals and organizations identify early signs of stress and burnout, which is especially common among healthcare professionals [5–7]. Capability measures have gained significant relevance in social care and economic assessments. The increasing use of capability questionnaires and the rise of related empirical studies show growing interest in this field. The ICEpop CAPability (ICECAP-A) instrument [8] assesses well-being and capabilities by focusing on broader aspects of life. It is explicitly based on Amartya Sen’s capability approach [9], a normative framework in welfare economics and development philosophy that emphasizes individuals’ real freedoms and opportunities to live the lives they value. This approach captures opportunities individuals wish to achieve, rather than just their current state. It is particularly useful for economic evaluations, including health technology assessments. Previous research has validated the ICECAP-A in various mental and physical health conditions [10–16]. A newer, similar instrument is the Oxford CAPabilities-Mental Health questionnaire, which aims to measure mental health-related capabilities [17, 18]. The advantage of this approach is that it respects individual differences since capability measures evaluate what people can do, considering personal traits, social context, and environmental constraints. It also allows for context-sensitive policy evaluation, recognizing that the same resource can produce different outcomes across individuals. Capability measures enable the calculation of Capability-Adjusted Life Years, which facilitate broader cost-effectiveness analyses that incorporate dignity, control, and independence [19].

So far, little is known about the two phenomena mentioned above, especially among young adults and university students, by whom we often take good mental health, well-being, and quality of life for granted. Concerns are rising about the prevalence of mental health issues among students in higher education. Many surveys are urging academic institutions to develop intervention strategies [20–23]. According to the Eurostudent-8 survey [24], about 50% of students aged 22–24 and half of those aged 25–29 report poor well-being, as measured by the WHO-5 index. In comparison, the rate of poor well-being is lower among students aged 30 and older, with only 39% experiencing poor well-being in this age group. Among the „Eurostudent countries,” Hungary ranks around the middle, with 47% of students indicating poor well-being. A significant factor might be that current students born between 1993 and 2012 show a higher prevalence of poor mental health compared to earlier student cohorts [25].

Unfortunately, limited data are available on the quality of life of university students. Measuring quality of life among young adults might seem unnecessary since chronic diseases are expected to be rare; however, even stress alone [26] has a significant impact on a person’s quality of life. Gaining better insight into the quality of life data for students and understanding how and to what extent quality of life instruments capture well-being in this young adult population would certainly be valuable. Quality of life data in the form of population norms provides [27–29] a comprehensive overview of society’s, primarily adults’ quality of life, assessed by a generic instrument; the most widely used is the EuroQoL instrument [30]. The importance of these evaluations lies in their role as baseline data, serving as benchmarks for assessing individuals’ or patients’ HRQoL compared to broader population standards.

The special position of students and their special circumstances highlight the importance of getting baseline data and an understanding of their QoL and well-being status; since the start of university life, new academic challenges, expectations for success, and the need to demonstrate strong performance contribute to stress. Experienced stress can consequently adversely affect overall well-being and negatively influence academic performance and might also impact future burnout rates after graduation while working already as healthcare professionals. This underlies the need for follow-up studies, starting while students are at universities and would follow them after qualification; well-being [31, 32], and quality of life [33] assessments could provide data for the development of tailored student support services.

In our previous study [20], the focus was primarily on evaluating well-being of university students studying at three, non-medical faculties of the Semmelweis University, to analyse impacting factors of well-being, by assessing the relationships between well-being, stress, emotional support, sleep patterns, sport, and further variables like smoking, consumption of sleeping pills, sedatives, psychoactive agents, energy drinks, and exam anxiety. The gained results show that most of the students experience low or very low levels of well-being, which vary throughout the study period; the most severe cases were observed during the first and last academic years. We found that students’ well-being is positively linked to emotional support, physical activity, and quality of sleep, while it is negatively affected by pre-exam anxiety. Our findings suggest that universities can and should enhance student well-being by promoting support: by offering stress management and providing guidance on effective learning strategies. Going forward, our objective was to explore overall well-being with two different measurement methods and the quality of life experienced by our students.

Methods

The study objective was to fill the gap in understanding of students’ quality of life and well-being; by evaluating students’ well-being, first from a traditional perspective and second via the capability perspective, as well as to assess their HrQoL, aiming to gain baseline data, norms for our university students’ population.

So, we wished to assess whether university students in health and biomedical sciences report significantly lower well-being and HrQoL scores compared to their peers from the literature. Does the ICECAP-A instrument capture impaired well-being cordially? Do and to what extent do chronic diseases have a detrimental effect on well-being and quality of life in our population?

Our survey was a non-interventional, cross-sectional online study; besides questions on demographics, questions on chronic diseases (sleep disorder, depression, allergic diseases, respiratory disease, or other) were asked too.

We used the validated Hungarian version of internationally recognised instruments, such as the WHO-5 Well-Being Index, ICECAP-A, and the EQ-5D-5 L. All instruments are easy to use, self-administered, and well accepted by respondents; furthermore, they are short, which is an advantage in minimizing or avoiding missing answers to questions. All the measures applied were validated for the Hungarian population.

The WHO-5 Well-Being Index: The World Health Organization’s General Well-being Scale (WHO-5-index) is one of the most widely used, easy-to-administer, and well-accepted measures of subjective well-being. Since it is widely used, data can be compared to published data in the literature.

It asks five questions about the respondent’s mental health. Responses are scaled on a 6-level scale, ranging from 0 to 5; the questionnaire is scored by summing the responses of five dimensions and multiplying the numbers by 4, providing an index with a range of 0 to 100. Higher scores indicate better well-being. A score over 51 indicates good well-being, and a score below 50 indicates poor well-being. The WHO-5 Well-Being Index is a validated measure for screening for mental disorders [34–36].

ICEpop CAPability measure for Adults (ICECAP-A) [8]: the instrument is fairly new; the characteristic features make ICECAP-A a unique tool for capturing broader aspects of well-being, as described previously. This holistic approach could ensure that all aspects of an individual’s life are considered in health planning and intervention design. It was created to measure well-being with an emphasis on capability; the ICECAP-A tool is designed for adults aged 18 years and above.

It measures the level of capabilities with five items reflecting different aspects of life, which are attachment, stability, achievement, enjoyment, and autonomy. Questions are framed to assess potential capabilities (e.g., “I am able to.“), distinguishing them from measures that assess current states or functioning. A 4-level scale is used for categorizing response options, ranging from 1, indicating no capability, to 4, representing full capability. Scores range from 0, which corresponds to „no capability” to 1, which corresponds to „full capability,” calculated from tariff sets for the instruments developed using best-worst scaling methods. The index score is derived by employing country-specific value sets, with the Hungarian tariffs [37, 38] utilized in our study.

The EuroQol -EQ5D-5L- questionnaire (EQ-5D-5L) [30, 39, 40] was developed to assess health-related quality of life (HrQoL); it is one of the most widely used generic preference-based, index-type measures, which summarizes quality of life with a single number, making comparisons easier. It includes five key domains/questions: mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. Respondents rate their level of impairment on a five-point Likert scale for each domain, from 1, indicating no problem, to 5, indicating a severe problem or inability to perform. The EQ-5D-5L index score is derived from the profile; in our study, the score was calculated using the country-specific value sets for Hungary [41].

The EQ-VAS, as an additional component of the questionnaire, evaluates self-perceived health status on a visual analog scale, which spans from 0 to 100, where 0 corresponds to the worst imaginable health, while 100 represents the best imaginable health.

In this paper, the term “quality-of-life” will be operationally defined as HrQoL.

Our survey was internet-based, carried out from February 1 to April 30. 2023. Participation was both voluntary and anonymous. Only Hungarian students from Semmelweis University were invited to participate in our online questionnaire survey; through an email invitation, sent by the dean’s office to all students enrolled at the faculties of the university for that spring term; within the study period, a reminder email was sent to reinforce participation rate. Responses were collected in a coded format for data analysis.

The first part of the questionnaire, besides demographics, also asked questions about whether the participant is suffering from a chronic condition. Participants could select from the following chronic diseases: sleep disorders, diagnosed depression, allergy, lung diseases, diabetes, hypertension, as well as other responses were possible to specify by the students. Multiple responses were permitted.

The Ethics Committee of Semmelweis University approved our survey (SE-RKEB 173/2022).

The primary aim of this study was to establish baseline normative data on the quality of life (HrQoL) and well-being of university students in health and biomedical sciences. This included assessing differences across key subgroups using both traditional (EQ-5D-5 L, WHO-5 index) and capability-based (ICECAP-A) instruments.

Data analysis was performed by using the Software Package for Statistical Analysis 30.0. (IBM SPSS). The 95% confidence interval was calculated to determine the strength of the association between values. We used a p-value of 0.05 or less as the cut-off for statistical significance.

Statistical analyses were designed to address the following research questions:

• What are the baseline levels of HrQoL and well-being among students in health and biomedical sciences? Descriptive statistics (means, standard errors) were calculated for all outcome measures (EQ-5D-5 L index, EQ-VAS, WHO-5 index scores, ICECAP-A).

• Are there significant differences in relation to HrQoL and well-being across known subgroups (faculties, presence of chronic conditions)? One-way ANOVA was used to compare well-being and quality of life data across multiple independent groups. (across academic years 1–2-3–4, subgroups vs. total sample, between faculties, and years of 1to 4 years of study). Distribution normality was tested using diagnostic plots.

• Does the WHO-5 index and ICECAP-A capture well-being adequately? Pearson Correlation analysis was used.

• What proportion of students score below the WHO-5 index < 28, indicating risk of depression?

Results

The study involved 561 responses, with an average age of 23.88 ± 6.29 years. A notable majority, 87.7%, were female, highlighting a gender imbalance among participants, although this reflects the gender distribution within the faculties. A summary of the sociodemographic characteristics of the sample can be found in Table 1.

Table 1.

Sociodemographic characteristics of the participants

	The total sample	Faculty of pharmacy	Pető András Faculty	Faculty of Health Sciences
Number of participants	561	155	60	346
Gender (%)
Male	12.3	29.7	0.0	12.3
Female	87.7	70.3	100.0	87.7
Average age: years "+" should be +- SD	23.88 + +-6.29	21.95 + +-2.35	21.08 + +-1.49	25.22 + +-7.51
Number of students studying at the faculty		589	312	4190
Length of studies at the different Faculties (academic years)		5	4	4

The number of participants reflects the size of these faculties. The Faculty of Pharmacy offers an undergraduate program for pharmacists. The Faculty of András Pető specializes in conductive education, training graduates to work as conductors with disabled children. The Faculty of Health Sciences provides a wide range of courses, including dietetics, physiotherapy, nursing, and midwifery.

In our study, the mean WHO-5 Well-Being Index (presented in Table 2) was 42.62 on a scale ranging from 0 to 100, where a score of 51 and over indicates good well-being, that was represented in 36.4% cases, a score between 29 and 50 indicates poor well-being, that was found to be in 35% and in case of 30.1% of the students we identified a score below 28, that indicates potential depression, warranting further medical evaluation to diagnose the existence of depression; unsurprisingly, the instrument is a validated tool to screen mental disorders [34] (Table 3). The mean ICECAP-A score was 0.441 on a scale where 0 equals „no capability” and to 1 to „full capability”; a score much lower than expected.

Table 2.

Scores of the WHO-5 Well-Being Index, ICECAP-A, and EQ5D-5 L, EQ-VAS of the students at the different faculties

	Total sample mean (Std. Error)	Faculty of Pharmacy mean (Std. Error)	Pető András Faculty mean (Std. Error)	Faculty of Health Sciences mean (Std. Error)
WHO-5 index	42.62 (0.869)	38.29 (1.805)	45.47 (2.746)	44.03 (1.041)
ICECAP-A	0.441 (0.008)	0.444 (0.017)	0.426 (0.027)	0.447 (0.011)
EQ-5D-5 L index	0.846 (0.008)	0.822 (0.018)	0.820 (0.024)	0.862 (0.009)
EQ-VAS	69.322 (0.789)	66.838 (1.674)	64.500 (2.358)	71.271 (0.941)

Table 3.

Participants (%) scores of the WHO-5 Well-being index

	Total sample	Faculty of Pharmacy	Pető András Faculty	Faculty of Health Sciences
WHO-5 index: 0–28: indicates depression	30%	43%	26%	25%
WHO-5 index: 29–50: refers to poor well-being	33%	29%	24%	37%
WHO-5 index: 51 and over: refers to good well-being	37%	28%	50%	38%

Tables 2 and 3 provides an overview of the results of the quality of life and well-being scores of our participants studying at the three faculties.

Significant differences were found when comparing the faculties, between the Faculty of Pharmacy and the Faculty of Health Sciences in the case of the WHO-5 index p=0.007, EQ-5D-5 L index p=0.003 and the EQ-VAS p=0.000; whereas there were no significant differences regarding the ICECAP-A. The fact that we could not find significant differences with the Pethő Faculty could be due to the low number of participating students from that faculty.

The relationship between the WHO-5 index and ICECAP-A was analysed by determining the correlation rate, which was r=−0.594 with a p=0.001 value.

Figures 1 and 2 summarise the instrument scores of students studying in the different academic years. It is important to note that Pharmacy studies in total cover 5 academic years, whereas students at the two other faculties finish with their training in 4 years.

Fig. 1.

Scores of the ICECAP-A and EQ-5D-5 L index of students studying in different academic years

Fig. 2.

Scores of the WHO-5 Well-Being Index of students studying in different academic years

The EQ-5D-5 L index score does not show major variability throughout the various years, as opposed to the WHO-5 Well-Being Index results. However, regarding the results of the different instrument scores, there were no significant differences (p-values were over 0.05) between the academic years (1–2-3 and 4).

The average quality of life score, the EQ-5D-5 L index, was 0.846, as presented in Table 3, on a scale where 0 equals death and 1 corresponds to the best possible health (no problems in any of the five dimensions). The average EQ-VAS was 69.322, showing that when students had to assess their quality of life between the worst imaginable health and the best imaginable health (on a scale between 0 and 100), their self-assessment was worse than the one calculated by the EQ-5D-5 L index. It was interesting to see that Pharmacy Students have the lowest scores in all areas except in the case of quality of life.

The answers to the domains of the EQ-5D-5 L questionnaire were also analysed, by calculating the percentage of problem severity in the five domains of the questionnaire; as expected, participants reported in almost all cases “no problems” or “slight problems” in the mobility and self-care domains. Figure 3 summarises the questionnaire responses across the five dimensions of the EQ-5D-5 L.

Fig. 3.

Levels of problem severity (%) in the EuroQoL questionnaire

The answers show that student in the majority of cases have no or little problem with mobility, self-care and usual activities. As opposed to that quite diverse answers were given in case of the “pain/discomfort domain”, and “anxiety/depression domain”, where only about 69% of students reported with no or slight problems.

Subgroup analysis: (i) of the “WHO-5 index equal or lower than 28” and (ii) the subgroup of chronically ill students

(i) the subgroup of “WHO-5 index equal or lower than 28”

As we wrote before, a WHO-5 index score of 28 or below indicates potential depression; furthermore, the instrument is a validated tool to screen for mental disorders [34]. However, a medical diagnosis is still required to diagnose a person with depression. The average scores of this subgroup are presented in Table 4.

Table 4.

The instrument scores of the subgroup “WHO-5 index equal or lower than 28”

	Average score (Std. Error)
WHO-5-index	18.13 (0.602)
ICECAP-A	0.590 (0.014)
EQ-5D-5 L index	0.727 (0.214)
EQ-VAS	58.461 (1.399)

Students in this subgroup (n=169, 30.1%) represent about one-third of the study participants. The WHO-5 index of these students indicates quite impaired well-being as well as a quality of life status.

Figure 4 summarises the questionnaire responses of the “WHO-5 index equal or lower than 28” subgroup across the five dimensions of the EQ-5D-5 L, with answers that indicate areas even more impacted by problems across the five dimensions, underlying the need for increased attention in case of this subgroup to improve their quality of life.

Fig. 4.

The “WHO-5 index equal or lower 28” subgroup and its problem severity (%) in the domains of the EuroQoL questionnaire

No statistically significant differences could be observed in the response profiles to the EQ-5D-5 L domains between the two subgroups, nor when each was compared to the full sample (p >0.05).

The fact that respondents did admit having problems with anxiety/depression (domain-5 of EQ-5D), could serve as a useful indicator tool for identifying students who may need specialized intervention. This approach could be particularly beneficial when students complete only a quality of life questionnaire.

(ii) the subgroup of students with chronic conditions

Young adults, university students, are generally considered to be healthy; nevertheless, we aimed to determine the proportion of chronic conditions within this population.

Among the participants, 81.4% reported no chronic diseases, while 18.6% indicated the presence of one or more chronic conditions. Among the 104 chronically ill students, 95 were female and 9 were male; the average age was 24.94+7.216 years.

Participants suffered from the following chronic diseases: sleep disorders (10.56%), diagnosed depression (18.27%), allergy (26.92%), lung diseases (13.46%), diabetes 6.73%), hypertension (5.76%), as well as other responses were possible (7.8%). The quality of life and well-being results of this subgroup are provided in Table 5.

Table 5.

Scores of the WHO-5 Well-Being Index, ICECAP-A, and EQ-5D-5 L in the subgroups of students with no chronic and chronic conditions

	Subgroup NO-chronic condition average (Std. Error)	Subgroup of students WITH chronic conditions (Std. Error)
WHO-5-index	43.26 (0.957)	39.69 (2.207)
ICECAP-A	0.430 (0.009)	0.489 (0.019)
EQ-5D-5 L index	0.854 (0.008)	0.816 (0.019)
EQ-VAS	70.175 (0.873)	65.865 (1.815)

We expected that students suffering from chronic conditions would have much worse scores, measured with the different instruments, compared to their peers among the participants with no chronic conditions in our study. We could not find any significant difference between the two groups (p>0.099).

Discussion

This study, according to our knowledge, offers the first comprehensive evaluation to gain population norms, baseline data of university students’ quality of life and well-being at a health/biomedical science-focused institution, utilising three internationally validated instruments, the EQ-5D-5 L, WHO-5 Well-Being Index, and ICECAP-A.

The two different approaches used to assess well-being (ICECAP-A and the WHO-5 Well-Being Index) are both appropriate for evaluating university students. The WHO-5-index identified that only 36.4% of students reported good well-being, while regrettably, 30.1% scored below 28, indicating the potential presence of depression. The mean 0.441 ICECAP-A score in our sample was much lower than expected.

The EQ-5D-5 L questionnaire demonstrated sensitivity in capturing quality of life impairment among students, revealing substantially lower scores of students studying health/biomedical sciences compared to the data of the general population of the same age group from the literature, calling for further evaluations to gain detailed understanding of the reasons, impacting factors.

Subgroup analyses showed that students with a low (28 or below) WHO-5 index could have a depression diagnosis (pending doctor confirmation), experienced significantly worse well-being and quality of life scores across all instruments. Interestingly, having chronic conditions did not significantly worsen scores, indicating that other factors and stressors likely play a more important role [20] in students’ well-being than physical health alone; however, it is important to note that the small number of students in this subgroup may have also influenced these results.

Comparison with general population literature data and published studies

Our results, measured using the WHO-5 Well-Being Index, align with previous research on student well-being. They refer to, that university students, especially those in demanding academic fields such as health and biomedical sciences, face higher risks of poor mental health and reduced well-being. This highlights the significant impact of stress, academic pressure, and social factors, as reported by the WHO - World Mental Health Surveys International College Student Project [42] and a Romanian cross-sectional study of dental students [43]. In our study, the average WHO-5 Well-Being Index score was 42.62, which is notably lower than the scores reported in a previous Hungarian study by Nguyen et al. In that study, participants aged 18−24 had a WHO-5 index of 47 and 50, indicating better well-being than our sample. Nguyen et al.‘s findings were based on a large cross-sectional internet survey with 2001 participants, including a subgroup of 192 individuals aged 18–24 years, who presented a WHO-5 index of 48 [44].

Our sample’s mean ICECAP-A score of 0.441 was significantly lower than anticipated and lower compared to the general population of a similar age group. Specifically, Baji et al. [38] reported a score of 0.92 in their cross-sectional study involving 2023 participants across the population, of whom 208 individuals were aged 18–24 years. These findings highlight the increased vulnerability of university students. While ICECAP-A emphasizes capabilities of the well-being concept and so offers a broader perspective, it has also been validated for use with adults experiencing depression, as shown in a study by Mitchell et al., presenting the ability to measure well-being comprehensively [45]. Having baseline data, future research could benefit from the use of ICECAP-A by delivering valuable information for decision-makers, as ICECAP-A offers practical advantages for assessing net-benefit and cost-effectiveness analyses of interventional programmes that wish to improve well-being, as the instrument assigns monetary values to different well-being states [46–48].

Our study’s “QoL” replace with “quality of life” results, reflected by an average EQ-5D-5L index of 0.84, are notably lower than those reported during the COVID-19 pandemic; a cross-sectional online survey [49] conducted in November 2020 among a representative sample of the Hungarian population (total n=1631, with 141 aged 18–24) found an EQ-5D-5L index of 0.936 in this age group. Another Hungarian research based on analysing a polled database (n=10324) of 8 studies conducted between 2018 and 2021 found that the population score for 18–24-year-olds was approximately 0.95 [50].

Limitations

The study’s cross-sectional design and reliance on self-reported, online questionnaires introduce potential recall bias. We certainly face Selection Bias, as our survey was not representative of the target population due to the circumstances of including students in the study. Specifically, we did not invite students in a predetermined manner, which means that among respondents, there may have been students who are more conscious of their well-being and health. Consequently, the results may be overestimated; furthermore, the generalizability of our study findings is limited.

The low response rate, especially in relation to the students of the Faculty of Health Sciences, could have reduced representativeness, which could have weakened the reliability of the findings; the results may be skewed, either overstating or understating prevalent issues. Results must be interpreted with caution, and further efforts are warranted to attain more representative datasets before making faculty-level decisions or recommendations.

Conclusion

This study provides the first comprehensive baseline data on the quality of life and well-being of university students in health/biomedical sciences, using the EQ-5D-5 L, WHO-5 Well-Being Index, and ICECAP-A instruments. Results show notably lower well-being and quality of life scores compared to general population norms from the literature; findings are consistent with prior research highlighting elevated mental health risks among students in demanding academic fields. Approximately 30% of students scored in a range indicating potential depression. The ICECAP-A offered a broader capability perspective and could be valuable for future economic evaluations of interventions. Students suffering from chronic diseases did not have significantly lower scores. The findings call for targeted support; our baseline results offer the potential for comparison in future evaluations to assess the cost-effectiveness of potential support services and enable evidence-based allocation of resources, as well as to highlight the significance, added value of targeted interventions by universities, society, and public health. Our results might have broader implications across academic settings.

Abbreviations

COVID

CoronaVirus Disease of 2019, a disease caused by the SARS-CoV-2 virus

EQ-5D-5L

EuroQol questionnaire, the five level

EQ-VAS

EuroQol questionnaire visual analog scale

HRQoL

Health-related Quality of Life

ICECAP-A

ICEpop CAPability measure for Adults

SE-RKEB

Semmelweis Ethical Committee

SD

Standard Deviation

Std. Error

Standard Error

HrQoL

Health related quality of life

WHO-5 index

World Health Organization's General Well-being Scale or WHO-5 Well-Being Index

Authors’ contributions

The authors equally contributed to the study conception and design, and material preparation, data collection and analysis were performed by both AM and OSz.AM prepared the initial draft of the manuscript, and all authors provided feedback. Every author reviewed and gave their approval for the final version.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Data availability

All data is available in the paper. The row datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of the Semmelweis University (SE-RKEB 173/2022).

Informed consent was obtained from all individual participants included in the study.

Consent for publication

Not Applicable. The manuscript does not contain any individual person’s data.

Competing interests

The authors declare no competing interests.