Abstract
Background
The Covid-19 pandemic has affected all areas of society, including students. However, medical students have faced many challenges due to direct contact with patients. The present study was conducted with the aim of investigating and comparing the quality of life (QoL), anxiety and mindfulness between Iranian medical and non-medical students during the COVID-19 pandemic.
Method
Five hundred and six students (both medical and non-medical students) participated in the study from August to October 2022 with a convenience sampling method. The data were collected using an online questionnaire including a demographic form, the QoL Questionnaire (WHOQOL- BREF), the Generalized Anxiety Disorder 7-item survey (GAD‐7) and the Relaxation/Meditation/Mindfulness Tracker t-Persian version survey (RMMt-P). Pearson correlation and independent t-test and multivariate linear regression were used to determine the relationship between the study variables.
Results
The samples included 272 medical students and 234 non-medical students with a mean age of 21.99 ± 3.46 and 24.17 ± 6.54 years respectively. Most of the medical and non-medical students were female, single and had a bachelor’s degree. The mean scores of medical and non-medical students’ QoL during the COVID-19 pandemic were 57.86 ± 13.26 and 56.75 ± 14.42, respectively which indicates the higher quality of life of medical students. Anxiety and mindfulness predicted 29% of the variance of the QoL in the medical students, while anxiety and mindfulness and having a chronic disease predicted 30% of the variance of the QoL in the non-medical students. No significant difference existed in the QoL and its subscales during the COVID-19 pandemic between medical and non-medical students (p > 0.05). There was a significant difference in terms of anxiety (p = 0.02) and mindfulness (p = 0.03) between medical and non-medical students during the prevalence of COVID-19.
Discussion and conclusion
The findings of the present study indicated that medical students exhibited lower levels of anxiety and higher levels of mindfulness. Therefore, interventions aimed at reducing anxiety and increasing mindfulness among non-medical students are necessary. It is recommended that preventive approaches and psychological interventions to improve students’ quality of life become an integral part of crisis response during the COVID-19 pandemic. Additionally, reducing anxiety and enhancing mindfulness can improve the quality of education and professional performance of medical students, while also contributing to their mental well-being and effective clinical communication.
Keywords: COVID-19, Quality of life, Anxiety, Mindfulness, Students, Comparison
Background
The COVID-19 pandemic affected the entire world. Students, like other social groups, also faced the challenges of this pandemic, including its psychological consequences [1, 2]. According to existing literature, even before the pandemic, students were more vulnerable to mental health problems due to academic challenges and various personal and psychological stress [3]. Recent systematic reviews around the world emphasize the increase in psychological costs associated with the COVID-19 pandemic [4]. The Quality of life (QoL) is one of the variables related to mental health that has been investigated in various studies among students.
The QoL has been proposed as an important criterion in psychological research [5] and is a key element in monitoring public health. It is also considered as a valid criterion for identifying unmet needs and potential intervention consequences [6]. Since quarantine and social distancing became embedded in the daily life of students during the COVID-19 pandemic, this resulted in a significant decrease in student activities; which further led to a drop in students’ QoL [5]. The results of a further study showed that there was a strong correlation between the intensity of quarantine measures during the pandemic and the level of activity of students in public spaces, with a general drop in the QoL [7]. Another study on Greek students during the COVID-19 pandemic also showed that 55.8% had a lower score in the psychological domain of qoL questionnaire and 52.3% also had a lower score in the social area of the QoL [8]. Studies conducted in Iranian students have shown that stress [9] general health status and life satisfaction [10] smartphone addiction [11] are related to quality of life.
The changes related to the COVID-19 pandemic, including social distancing, led to a high prevalence of anxiety in students in addition to the decline in the QoL [12]. A meta-analysis study showed that the prevalence of anxiety, depression and stress in students was 29, 37 and 23%, respectively [13]. Another research showed that more than a third of students suffered from anxiety during the early stages of the COVID-19 pandemic. In addition, being female, living in rural areas, facing financial problems, working full-time, worrying about the infection of yourself and others, decreased sleep quality, and transitioning to online learning, were factors associated with increased anxiety during the height of the pandemic [3]. If anxiety is not identified and treated, it can cause confusion and a substantial level of difficulty in understanding the course material, and the higher the anxiety, the lower the academic performance. Therefore, it can be inferred that academic performance is negatively affected by anxiety [14]. Emerging research addressing the enduring impact of long-term stress, isolation, and educational disruptions on students’ psychological resilience and need for coping mechanisms [15, 16]. One of the characteristics related to mental health that can prevent the anxiety and psychological distress caused by social distancing and isolation during the COVID-19 pandemic is mindfulness [17–19]. The results of a study on Chinese students during the COVID-19 pandemic showed that those who had a higher level of mindfulness reported fewer mental health problems, including anxiety and depression [20].
The COVID-19 pandemic has had widespread and profound effects on the mental health of students [18]. Among these, university students have faced numerous challenges due to sudden changes in educational methods, social restrictions, and financial concerns. In this context, comparing the mental health of medical and non-medical students is particularly important, as both groups confront different challenges that can impact their mental health in various ways. Factors such as the distinct nature of medical education, exposure to illness, work-related stress, and social and occupational expectations have a more significant effect on the mental health of medical students [19]. Non-medical students may have faced more issues related to social isolation and restrictions on regular activities; however, medical students additionally encounter unique experiences such as anxiety about contracting illnesses in work environments and providing clinical care in critical situations.
Compared to other students, medical students experience special and stressful situations that can cause them negative feelings and anxiety. Risk perception and subsequent behavior in individuals during a pandemic is highly complex and influenced by multiple cultural and psychological factors [21]. Perception of risk as well as the fear of illness is strongly related to worry and causes thoughts that evoke negative emotions and high levels of anxiety and distress [22, 23]. A study showed that compared to medical students, non-medical students had a higher rate of moderate to severe anxiety symptoms and a low QoL [24].
Comparing the mental health of medical and non-medical students can help identify fundamental differences in their experiences, thereby facilitating the design of more specific and effective psychological support strategies for each group. In addition, few comparative studies were found on the examination of these variables between medical and non-medical students. It was thought that medical students are professionally trained and have more knowledge than others about the causes, prevention and treatment of diseases. However, it is unclear whether their medical knowledge and skills can manage their fear of infectious disease epidemics. Therefore, the present study was conducted with the aim of investigating and comparing the QoL, anxiety and mindfulness between Iranian medical and non-medical students during the COVID-19 pandemic.
The following specific objectives were considered: (a) assessing the quality of life in medical and non-medical students, (b) assessing anxiety levels in medical and non-medical students, (c) assessing mindfulness in medical and non-medical students, (d) examining the association between demographic characteristics and quality of life, (e) comparing quality of life, anxiety, and mindfulness between medical and non-medical students, and (f) assessing the associations of all important study variables with the quality of life of medical and non-medical students using multivariate linear regression.
Methods
Study design and participants
This cross-sectional study was conducted to compare the QoL, anxiety and mindfulness among medical and non-medical students during the outbreak of COVID-19. An online questionnaire was used for data collection. The questionnaire was distributed on social networks (WhatsApp and Telegram). The inclusion criteria were all Iranian students who were over 18 years of age who live in Iran and had no psychological disorder (self-reported) and had access to social networks. The exclusion criterion was any respondent who was eligible to participate but did not fill in the online questionnaire completely.
Sample size and sampling
The convenience sampling method was used to collect the samples. Cochran’s formula was used to calculate the sample size in this study. The required sample size for this research was calculated to be at least 385 respondents. Confidence factor = 95% p = q = 0.5, population proportion = 50%, population size (unlimited population size), (d = 0.05). However, room was left for a 10% probability of some dropping out of a target sample of 430 and considering 20% attrition rate, 462 sample size was found to be adequate. Eventually, of the numerous questionnaires that were distributed, 506 survey responses were overall usable in this research. To minimize bias, participants were randomly selected, and an anonymous survey was employed to encourage honest reporting.
Measure
Data were collected using four questionnaires including a demographic form, the QoL Questionnaire (WHOQOL-BREF), the Generalized Anxiety Disorder 7-item survey (GAD‐7) and the Relaxation/Meditation/Mindfulness Tracker t-Persian version survey (RMMt-P).
Demographic information
The demographic information of the participants included age, sex, marital status, education level, chronic diseases, addiction, past COVID-19 infection and COVID-19 vaccination status.
The quality of life questionnaire (WHOQOL-BREF)
The WHOQOL-BREF questionnaire with 26 questions, mainly within four domains, was used to check people’s QoL in this study, during the height of the COVID-19 pandemic. Of the 26 questions in total, the first two questions do not belong to any of the four domains. The WHOQOL-BREF evaluates the overall health status and QoL of respondents in terms of the following areas: (a) The physical health domain; (b) The psychological domain; (c) The social relationship domain and (d) The environmental domain. It is essential to note that questions 3, 4 and 25 were scored in reverse. To interpret the QoL scores, the short version should be converted to the long version, and then the amount in each domain is calculated from zero to 100. Iranian version of the WHOQOL-BREF (Nejat Safa et al. 2006) was shown Cronbach’s alpha coefficient of 0.77 in the physical health domain, 0.77 in the mental domain, 0.75 in the social relations domain, and 0.84 in the environmental health domain. The total Cronbach’s alpha coefficient was 0.78 [25].
The generalized anxiety disorder 7-item survey (GAD-7)
This scale was designed by Spitzer et al. to measure the generalized anxiety disorder using 7 questions. Also, in this scale, there is an additional question to measure the interference of the disorder in the person’s functioning. The questions are graded on a Likert scale from 0 to 3 and have a score between 0 and 21. The obtained scores are added together to obtain the total anxiety score for the scale. The psychometric characteristics of the scale, including its reliability and external validity coefficients, have been confirmed, and the Cronbach’s alpha coefficient of the scale is 0.92 [26]. In the study of Naeinian et al. (2010) in Iran, the validity and reliability of this tool was confirmed with Cronbach’s alpha of 0.74 [27]. In the study of Zakeri et al. (2021) in the outbreak of the COVID-19 disease in Iran, a Cronbach’s alpha of 0.88 was reported for this scale [28].
The Relaxation/Meditation/Mindfulness tracker t-Persian version survey
Relaxation/Meditation/Mindfulness (RMM) trackers contain 25 items used to assess the frequency of experiencing different RMM states. The trackers include a range of self-report inventories of RMM. The RMM Tracker t items are scored on a 13-point Likert scale. The scores of the items of each level are added together and divided by the number of items of that level. Higher scores indicate higher and more positive levels of each domain [29]. The Persian version of RMM t consists of 23 modes of RMM. There are 23 special RMM modes divided into three dynamic and interactive levels, namely, Level (1) conscious love, gratitude and transcendence (10 items); Level (2) states of relaxation (9 items); and Level (3) deepening of the conscious mind (4 items). In Iran, Malkoutikhah et al. (2021) confirmed the validity of the content and structure of the Persian version of the RMM t. The values of Cronbach’s alpha in the three levels were 0.93, 0.91 and 0.80 respectively [30].
Data collection
After obtaining the necessary permissions, the researcher distributed the online questionnaire via social networks. Student organizations and faculty members were contacted to disseminate the survey link. Additionally, participants were encouraged to take part in the study through engaging messages and sharing the link on social media platforms. The online questionnaire included demographic information questionnaires, the WHOQOL-BREF, the GAD-7, and the RMM Trackers. At first, a pilot study consisting of 50 respondents was conducted to identify any issues related to the online questionnaire. Feedback indicated that the online questionnaire was well-designed and effectively engaged participants. Each respondent could only answer the questions once. The researcher checked the questionnaires in terms of possible problems such as failure to implement, record and publish correctly. Data collection lasted from August to October 2022. A total of 543 online questionnaires were completed by the respondents, and after removing incomplete questionnaires, 506 questionnaires were included in the final analysis.
Data analysis
Descriptive and inferential statistical methods were used for data analysis using SPSS version 24 software. Descriptive statistics were used to describe the demographic characteristics and mean scores of the study variables, and to determine the relationship between the demographic variables and the QoL variables, ANOVA, independent t tests and Mann Whitney u test were used. Pearson’s correlation was used to determine the relationship between QoL, anxiety and mindfulness. Independent t tests were used to compare the QoL, anxiety and mindfulness between medical and non-medical students. Multi-variable linear regression regression was used to investigate the relationship between the variables of analysis and QoL of medical and non-medical students. To perform the regression, the variables that were less than 0.2 were included in the regression model. A significant level of 0.05 was considered.
Ethical considerations
This study was conducted after the approval of the Ethics Committee of Rafsanjan University of Medical Sciences (IR.RUMS.REC.1401.096). On the first page of the online questionnaire, an informed consent form was designed and the respondents who met the inclusion criteria were asked to confirm their willingness to participate on this form. Participants were informed about the study’s purpose, their rights, and the voluntary nature of their participation. Informed consent was obtained electronically prior to participation, ensuring that participants understood they could withdraw at any time without any consequences. The authors did not have access to information that could identify participants during or after data collection. To maintain confidentiality, all survey responses were anonymous, and no identifying information was collected. Data were stored on a secure server with limited access to the research team. We employed encryption protocols during the data collection process.
Results
The samples in this study included 272 medical students and 234 non-medical students with a mean age of 21.99 ± 3.46 and 24.17 ± 6.54 years respectively. Most of the medical and non-medical students were female, single and had a bachelor’s degree (Table 1) (Fig. 1).
Table 1.
Demographic characteristics of the medical and non-medical students and their association with the quality of life during the prevalence of COVID-19 (n = 506)
| Variable | Frequency (valid percent) | Quality of life | |||||
|---|---|---|---|---|---|---|---|
| Medical students (n = 272) | Non-medical students (n = 234) | ||||||
| Frequency (%) | Mean (SD) | Statistic test (P value) |
Frequency (%) | Mean (SD) | Statistic test (P value) |
||
| Gender | |||||||
| Male | 178 (35.2) | 84 (30.9) | 57.44 (13.89) | t = -0.34 (0.73) | 94 (40.2) | 57.19 (14.06) | t = 0.38 (0.69) |
| Female | 328 (64.8) | 188 (69.1) | 58.04 (13.00) | 140 (59.8) | 56.45 (14.71) | ||
| Marital status* | |||||||
| Married | 89 (17.6) | 38 (14.2) | 58.99 (10.90) | t = 0.56 (0.57) | 51 (22.4) | 58.14 (13.51) | t = 0.80 (0.42) |
| Single | 407 (80.4) | 230 (85.8) | 57.67 (13.68) | 177 (77.6) | 56.28 (14.74) | ||
| Education level | |||||||
| Associate degree | 48 (9.5) | 12 (4.4) | 52.02 (12.73) | F = 1.24 (0.28) | 36 (15.4) | 57.68 (16.83) | F = 1.01 (0.36) |
| Bachelor’s degree | 376 (74.3) | 219 (80.5) | 58.04 (13.47) | 157 (67.1) | 55.86 (14.49) | ||
| Masters and Ph.D | 82 (16.2) | 41 (15.1) | 58.57 (12.12) | 41 (17.5) | 59.31 (11.58) | ||
| ‡ Having a chronic disease* | |||||||
| Yes | 20 (4.0) | 9 (3.4) | 48.50 (11.91) | t = -2.14 (0.03) | 11 (4.8) | 50.77 (15.89) | t = -1.43 (0.15) |
| No | 475 (96.0) | 258 (96.6) | 58.09 (13.22) | 217 (95.2) | 57.19 (14.40) | ||
| Drug addiction* | |||||||
| Yes | 10 (2.0) | 5 (1.9) | 59.80 (9.98) | Z = -0.40 (0.68) | 5 (2.2) | 59.75 (18.50) | Z = -0.19 (0.84) |
| No | 485 (98.0) | 264 (98.1) | 57.73 (13.36) | 221 (97.8) | 56.82 (14.50) | ||
| Infected with COVID-19 | |||||||
| Yes | 225 (44.5) | 116 (42.6) | 56.79 (12.42) | t = -1.14 (0.25) | 109 (46.6) | 57.38 (16.07) | t = 0.63 (0.52) |
| No | 281 (55.5) | 156 (57.4) | 58.65 (13.83) | 125 (53.4) | 56.19 (12.85) | ||
| COVID-19 vaccination | |||||||
| Yes | 488 (96.4) | 266 (97.8) | 58.02 (13.21) | t = 1.35 (0.17) | 222 (94.9) | 56.54 (14.41) | t = -0.94 (0.34) |
| No | 18 (3.6) | 6 (2.2) | 50.62 (14.52) | 12 (5.1) | 60.56 (14.75) | ||
∗Missing value, QoL: quality of life; SD = Standard Deviation, t = Independent t test, F = Analysis of variance, Z = Mann Whitney u test; ‡: hypertension, coronary heart disease (CHD), cancer, asthma and diabetes
Fig. 1.
Comparison of gender and education level percentage of medical and non-medical students
The present study showed that there is a significant positive relationship between the QoL and mindfulness among medical students (r = 0.48; p < 0.001) and non-medical students (r = 0.46; p < 0.001). A negative significant correlation was found between the QoL and anxiety among medical students (r = -0.36; p < 0.001) and non-medical (r = -0.42; p < 0.001) students. Also, as indicated in Table 2 below, a negative significant correlation was found between mindfulness and anxiety among medical students (r = -0.21; p < 0.001) and non-medical (r = -0.31; p < 0.001) students. In terms of the demographic variables, only those medical students living with a chronic disease (P = 0.03) showed a significant relationship with QoL.
Table 2.
The correlation between the quality of life, anxiety and mindfulness among medical and non-medical students during the prevalence of COVID-19
| Variable | Pearson’s correlation coefficient (P value) | |||||
|---|---|---|---|---|---|---|
| Medical students (n = 272) | Non-medical students (n = 234) | |||||
| Anxiety | Mindfulness | QoL | Anxiety | Mindfulness | QoL | |
| Anxiety | 1 | 1 | ||||
| Mindfulness | -0.21 (< 0.001) | 1 | -0.31 (< 0.001) | 1 | ||
| QoL | -0.36 (< 0.001) | 0.48 (< 0.001) | 1 | -0.42 (< 0.001) |
0.46 (< 0.001) |
1 |
QoL: Quality of life
The mean scores of medical and non-medical students’ QoL during the height of the COVID-19 were 57.86 ± 13.26 and 56.75 ± 14.42, respectively. The mean scores of medical and non-medical student anxiety during the COVID-19 pandemic were 6.09 ± 4.24 and 7.01 ± 4.60, respectively. The mean scores of medical and non-medical students’ mindfulness were 7.09 ± 1.40 and 6.82 ± 1.42 respectively during the COVID-19 pandemic (Fig. 2). Anxiety (p = 0.02) and mindfulness (p = 0.03) between medical and non-medical students were significantly different during the prevalence of COVID-19. We found no significant difference in QoL and subscales between medical and non-medical students during the COVID-19 pandemic (p = 0.36) (Table 3).
Fig. 2.
Comparison of the mean of quality of life, anxiety and mindfulness between medical and non-medical students
Table 3.
Comparing the quality of life, anxiety and mindfulness between medical and non-medical students during the prevalence of COVID-19 (n = 506)
| Group/Variables | Medical students (n = 272) |
Non-medical students (n = 234) | Independent t test | P value | ||
|---|---|---|---|---|---|---|
| Mean | Standard Deviation | Mean | Standard Deviation | |||
| QOL | 57.86 | 13.26 | 56.75 | 14.42 | 0.90 | 0.36 |
| Physical Health | 62.71 | 15.47 | 60.14 | 16.29 | 1.81 | 0.07 |
| Psychological | 58.87 | 15.97 | 57.18 | 16.41 | 1.16 | 0.24 |
| Social relationship | 53.13 | 16.35 | 53.07 | 19.98 | 0.03 | 0.97 |
| Environmental | 56.58 | 15.47 | 56.58 | 16.21 | 0.09 | 0.92 |
| Anxiety | 6.09 | 4.24 | 7.01 | 4.60 | -2.32 | 0.02 |
| Mindfulness | 7.09 | 1.40 | 6.82 | 1.42 | 2.14 | 0.03 |
| Mindful Love/ Thankfulness/Transcendence | 7.52 | 1.52 | 7.33 | 1.57 | 1.32 | 0.18 |
| Relaxation | 7.24 | 1.61 | 6.97 | 1.76 | 1.84 | 0.06 |
| Mindful Deepening | 6.52 | 1.82 | 6.17 | 1.99 | 2.06 | 0.04 |
QOL: quality of life;
We used multiple regression with backward method for further analysis and included all variables with p-value < 0.2 in the multivariate regression model. The results indicated a relationship between anxiety, mindfulness and the QoL in the medical students, as well as between anxiety, mindfulness and QoL in non-medical students. As shown in Table 4, anxiety (B = -0.83; 95% confidence intervals (CI): -1.16_ -0.51) and mindfulness (B = 3.95; CI: 2.97_ 4.93) predicted 29% of the variance of QoL in the medical students. Anxiety (B = -1.02; CI: -1.37 _ -0.66) and mindfulness (B = 3.71; CI: 2.53 _ 4.89) and having a chronic disease (B = 8.12; CI: 0.76 _ 15.47) predicted 30% of the variance of the QoL in the non-medical students. In medical and non-medical students, mindfulness was the best predictor of the QoL (p < 0.001) (Table 4).
Table 4.
The multiple regression analysis summary for the quality of life in medical and non-medical students during the prevalence of COVID-19
| Variable | B | SE‡ | Βeta | T | P | 95% Confidence interval for B | Adjusted R2 | ||
|---|---|---|---|---|---|---|---|---|---|
| QoL | Medical students | (Constant) | 22.23 | 8.29 | - | 2.68 | 0.008 | 5.89 _ 38.56 | 29% |
| Mindfulness | 3.95 | 0.49 | 0.41 | 7.93 | < 0.001 | 2.97_ 4.93 | |||
| Anxiety | -0.83 | 0.16 | -0.26 | -5.10 | < 0.001 | -1.16_ -0.51 | |||
| Having a chronic disease‡ | 6.41 | 3.78 | 0.08 | 1.69 | 0.091 | -1.03 _ 13.86 | |||
| Non-medical students | (Constant) | 22.82 | 8.78 | - | 2.60 | 0.010 | 5.52 _ 40.13 | 30% | |
| Mindfulness | 3.71 | 0.59 | 0.36 | 6.21 | < 0.001 | 2.53 _ 4.89 | |||
| Anxiety | -1.02 | 0.18 | -0.32 | -5.59 | < 0.001 | -1.37 _ -0.66 | |||
| Having a chronic disease‡ | 8.12 | 3.73 | 0.12 | 2.17 | 0.031 | 0.76 _ 15.47 | |||
‡: Standard error; QoL: quality of life; ‡: hypertension, coronary heart disease (CHD), cancer, asthma and diabetes
Discussion
The present study was conducted with the aim of comparing the QoL, anxiety and mindfulness between Iranian medical and non-medical students during the COVID-19 pandemic. The study showed that during the outbreak of COVID-19, there was no significant difference in QoL between medical and non-medical students. Contrary to this finding, Yang et al.‘s (2022) study showed that non-medical students had a lower QoL compared to medical students during the waning phase of the COVID-19 pandemic in China [24]. Since the present study was conducted during the fifth peak of the disease in Iran, this may justify the difference between the findings. In addition, the data collection tool about the QoL in this study is different from Yang et al.‘s (2022) study. These methodological differences between the non-medical groups represented in the two studies can also be useful in explaining this difference.
Anxiety was significantly different between medical and non-medical students as medical students experienced less anxiety. This was consistent with the results of the studies of Saddik et al. (2020) comparing Emirati medical and dental students [31] and Yang et al. (2022) comparing Chinese medical and non-medical students [24] during the COVID-19 pandemic. Xiong et al. (2022) revealed that non-medical students reported higher prevalence of moderate to severe levels of depression, anxiety, and stress symptoms than medical students [32]. These results imply that medical students may have been less affected by this pandemic or may have recovered from anxiety faster than non-medical students. Furthermore, this finding could be explained by more knowledge and experience of the medical students about the COVID-19 pandemic and managing the disease comparing non-medical students. A study showed that medical knowledge had a protective effect on medical students’ psychological distress during the COVID-19 period. Also, in the present study, the average anxiety score of all students showing mild anxiety in students implies that psychological support appropriate to the needs of students is necessary. Additionally, regular screening of university students with instruments such as the GAD-7 can help professors to detect anxiety among students in its early stages and direct them to receive targeted psychological interventions, including individual counseling. Transactional Model of Stress and Coping can be applied to explain how medical students, through their training, may appraise stressful events as less threatening [33]. The coping strategies they learn, such as problem-solving and emotional regulation, can help reduce anxiety.
Comparing medical and non-medical students, the results of the present study showed that there was a significant difference between the mindfulness of the two groups, with medical students experiencing higher mindfulness compared to non-medical students. Based on the literature reviewed, the present study is the first study that compares mindfulness between medical and non-medical students during the height of the COVID-19 pandemic. Mindfulness includes paying attention to the present moment with an open and curious attitude, which helps people understand stress better and respond to it more effectively. In fact, mindfulness is an ability that can be especially useful in stressful situations such as the COVID-19 pandemic. People who can achieve this state of mind are more aware of their feelings and can change and manage them better. Such people experience less anxiety [34]. Medical students may experience lower anxiety and higher mindfulness due to the nature of their training. Medical education emphasizes the development of skills such as resilience, coping mechanisms, and emotional regulation, which are essential for managing stress [15]. Medical students are often exposed to clinical environments where patient care is prioritized, potentially fostering self-efficacy, which can contribute to reduced anxiety.
The results of the present study showed that in medical students, anxiety and mindfulness variables predicted 29% of QoL variance. Also, in non-medical students, anxiety, mindfulness and having specific disease variables predicted 30% of QoL variance. In line with the results of this study, the study of Gan and Ling Yuen (2019) on medical students in Malaysia showed that the higher the anxiety, the lower the QoL, and in fact there is a significant negative correlation between anxiety and the QoL [35]. Also, confirming the findings of this study, Dafaalla et al.‘s (2016) study on medical students in Sudan showed that one of the variables that significantly predicts the QoL is anxiety [36]. Another study on non-medical students in the UK also showed that there was a significant inverse relationship between anxiety and the QoL [37].
Upon reviewing the literature, no study was found that investigated the level of mindfulness and the QoL in students, hence the present study investigated the impact of mindfulness training and its impact on the QoL. Therefore, part of the findings of this study could not be compared with similar studies conducted on students. Studies on other populations, such as patients with ulcerative colitis [38] and middle-aged women [39], in line with the findings of the present study, showed that there was a significant positive correlation between mindfulness and the QoL. In explaining the observed relationship between mindfulness and the QoL in the present study, it can be said that mindfulness frees a person from incompatible cognitive habits. Mindfulness also reduces maladaptive reactions in a person by removing depressive schemas such as helplessness. In addition, mindfulness can increase the QoL by reducing stress [39]. More research on mindfulness among clinicians/non-students is needed to gain a better understanding of the effects of mindfulness. Mindfulness interventions, such as mindfulness-based stress reduction (MBSR) or cognitive-behavioral stress management, can increase self-awareness, helping to protect against anxiety and reduce psychological burden [40, 41]. Lower anxiety and improved mindfulness are associated with better focus, higher academic performance, and increased productivity. These interventions also provide long-term mental health benefits, such as reduced burnout risk and enhanced coping strategies.
Many students are exposed to high levels of stress that reduce their quality of life and possibly affect their academic performance and overall educational experience. Students have distinct views depending on their fields of study and knowledge, yet they experience severe distress in crises. Students who choose different courses as their future career paths are significantly different from each other in terms of personality traits [42]. This study highlights the critical importance of mental health education for students who come through difficult periods who often experience distress and need to be taught effective coping strategies. Second, attention to mindfulness among young adults can also be beneficial for their mental quality of life [43]. In addition, it is necessary to encourage students to deal with stress by methods including: listening to music, prayer, yoga meditation, pursuing their hobbies, or exercising [44]. Providing financial security, educational and research requirements can also help students in reducing stress and preventing future mental illnesses in crises. In addition, to reduce complications caused by crises, it seems necessary to establish university psychology centers or cooperate with foreign units providing these services. Universities should integrate mindfulness training and mental health education into both medical and non-medical curricula. These programs can enhance students’ psychological resilience during crises. Educational institutions and universities may face financial barriers in implementing large-scale mental health programs. Additionally, some students may be reluctant to participate in mindfulness programs due to the stigma surrounding mental health or a lack of awareness. Offering mindfulness education as part of the curriculum and leveraging the expertise of mental health professionals, along with online platforms, can increase student participation.
Cultural differences in coping strategies, access to resources, and support systems can significantly influence students’ quality of life, anxiety levels, and mindfulness in various ways. Cultures vary in their approaches to stress management [15, 45]. In collectivist cultures, there is a greater reliance on social support from family and the community, while in individualistic cultures, self-reliance is emphasized [46]. Access to mental health services, educational support, and financial aid can vary widely across countries and cultures, which may affect students’ ability to seek care when needed. Social support networks also differ across cultures. Cultural expectations regarding seeking help from family, friends, or professionals can influence how students manage stress and anxiety [47]. These cultural variations in coping mechanisms, access to resources, and support systems lead to different mental health outcomes for students, impacting their stress management and psychological well-being.
Limitations
Examining the differences in quality of life, anxiety and mindfulness in two groups of medical and non-medical students in an infectious crisis is one of the strengths of the present study, which can show a broader insight into the crisis conditions of different groups of students. The cross-sectional design of this study was considered a limitation because no change over time, either before or until the end of the pandemic, could be evaluated. It is difficult to determine whether lower anxiety and higher mindfulness among medical students were pre-existing conditions or developed during the pandemic. The sampling method may have introduced selection bias, as participants were likely those with internet access and the motivation to participate in an online survey. This limits the generalizability of the results to a broader student population. Also, the causal relationship between the variables could not be evaluated in this design. In addition, this study was conducted in the fifth peak of the COVID-19 pandemic, and caution should be exercised in generalizing the findings to other peaks or stages of the pandemic. Also, self-report questionnaires were used to collect data, therefore, the data is somewhat subjective in nature, and it is suggested that objective methods for data collection should be used in future studies. The non-probability sampling technique was one of the other limitations that should be taken into account when interpreting the results. Due to the online survey, there is participation/selection bias, so caution should be used in interpreting the results. Tracking students over time would allow researchers to assess how anxiety and mindfulness evolve throughout their academic careers and during different stages of the pandemic. This could clarify the directionality of the relationship between medical education and mental health outcomes. Using probability-based sampling or recruiting participants from a wider range of institutions and regions could reduce selection bias. To reduce participation bias, researchers provided explanations about the study’s objectives to encourage greater student participation.
Conclusion
The findings of the present study showed that there was no significant difference between the QoL of medical and non-medical students. Compared to non-medical students, medical students experienced significantly lower anxiety and higher mindfulness. Also, two variables that were significantly and jointly predicting students’ QoL included anxiety and mindfulness. Therefore, based on the findings, it is suggested that mindfulness training programs as well as psychological and counseling interventions should be employed to improve the QoL and reduce the anxiety of students, especially non-medical students, during crises such as the COVID-19 pandemic.
Acknowledgements
We would thank the authorities of the Social Determinants of Health Research Centre and Clinical Research Development Unit, Ali-Ibn Abi-Talib Hospital, Rafsanjan University of Medical Sciences, Rafsanjan, Iran. Researchers also thank all the students who participated in the study across Iran. The study was supported by Fujian Province Education System Philosophy and Social Science Research Project, China (No.: JAS22126).
Author contributions
MAZ and MD develop the study idea and protocol. MAZ and MD supervised the study sampling and analyzed the data. YS, SP and MK did the sampling. MAZ, MS, FG-H, and HF wrote the first draft of the manuscript. JS, MAZ, AHH and DA wrote the final version of the manuscript. All authors read and confirmed the final version of the manuscript.
Funding
This research did not receive any specific grant from funding agencies in the public, commercial or not-for-profit sectors.
Data availability
The data that support the findings of this study are available from the corresponding author (Mohammad Ali Zakeri; Email: mazakeri@rums.ac.ir) upon reasonable request.
Declarations
Ethics approval and consent to participate
The studies involving human participants were reviewed and approved by Rafsanjan University of Medical Sciences. The patients/participants provided their written informed consent to participate in this study.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author (Mohammad Ali Zakeri; Email: mazakeri@rums.ac.ir) upon reasonable request.