Mapping Burnout in Medical Students: Interactions Between Learning Approaches and the Educational Environment

Mapping Burnout in Medical Students: Interactions Between Learning Approaches and the Educational Environment | 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 Mapping Burnout in Medical Students: Interactions Between Learning Approaches and the Educational Environment Lale Ozisik, Melih Elcin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8149384/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Burnout is a prevalent and growing issue among healthcare professionals, often emerging during medical education. Learning approaches and perceptions of the educational environment are key factors that may influence the development of burnout among medical students. This study aimed to explore the relationship between burnout levels, learning approaches, educational environment perceptions, and academic achievement in final-year medical students. Methods: A descriptive cross-sectional study was conducted among sixth-year students at Hacettepe University Faculty of Medicine, Türkiye. Data were collected electronically using a questionnaire including sociodemographic items, academic achievement, the Maslach Burnout Inventory (MBI), the Approaches and Study Skills Inventory for Students (ASSIST), and the Dundee Ready Education Environment Measure-Turkish version (DREEM-TR). Descriptive statistics, correlation analyses, and multivariate analyses were performed using SPSS 25, with p < 0.05 considered statistically significant. Results: A total of 241 students participated (95.25%). Mean scores on the MBI were: Emotional Exhaustion 17.54±6.63, Depersonalization 7.14±3.53, and Personal Accomplishment 12.95±4.40. The majority of students (74.7%) adopted a strategic learning approach. Students with higher academic performance demonstrated higher strategic and lower surface learning approach scores. Perceptions of the educational environment correlated negatively with all burnout dimensions and the surface learning approach, and positively with strategic and deep learning approaches. Conclusion: Medical students’ burnout is significantly related to their learning approaches and perceptions of the educational environment. Promoting supportive educational environments and fostering effective learning strategies may reduce burnout and enhance academic and professional development. Burnout medical students learning approaches educational environment DREEM ASSIST Figures Figure 1 Figure 2 Figure 3 Figure 4 BACKGROUND Healthcare workers are at risk of developing mental illness due to numerous factors such as chronic stress, large workloads and compassion fatigue [ 1 ]. Research shows that 39% of physicians have depression and this ratio is twice the general population. In the United States, approximately 400 doctors die each year due to suicide [ 2 ]. It has also been shown that physicians' burnout level is one of the most important factors leading to suicide [ 3 , 4 ]. According to Maslach, burnout is a syndrome characterized by emotional exhaustion, depersonalization, and reduced professional accomplishment, emerging in people who work intensively with others [ 5 ]. In the 11th revision of the International Classification of Diseases (ICD-11), burnout was defined as a professional phenomenon rather than a medical condition, manifested by feelings of exhaustion, increased mental distance to work or negativity, and decreased professional activity [ 6 ]. Burnout has reached epidemic levels worldwide, affecting 30% to 60% of physicians depending on specialty and measurement methods [ 7 ]. In the U.S., more than half of physicians report burnout, with rates rising from 44% in 2019 to 53% in 2023 after Covid-19 Pandemic [ 3 , 8 ]. Another survey in 2024 has shown that six in 10 physicians and residents, and seven in 10 medical students reported often experiencing burnout [ 9 ]. According to the UK House of Commons Health and Social Care Committee report (2021), work-related stress among NHS staff has been rising, with the NHS Staff Survey showing an increase from 40.3% in 2019 to 44% during the COVID-19 pandemic [ 10 ]. Physicians’ burnout syndrome is increasingly recognized as a public health crisis in many high-income countries. Young doctors were most at risk, followed by general practitioners. This situation not only affects physicians' personal lives and job satisfaction, but it also creates serious pressures on the entire health system, in other words, it threatens especially the care and safety of patients [ 6 ]. An increasing number of articles have been published in the last 15 years, indicating that the origins of burnout in physicians started in medical school [ 11 ]. Prevalence rates for professional burnout in medical students, ranges from 7.0% to 75.2%, depending on country-specific factors, applied instruments, cutoff-criteria for burnout symptomatology [ 12 ]. A 2019 meta-analysis indicate that burnout affects approximately 44% of medical students, with emotional exhaustion and depersonalization being the most common symptoms [ 13 ]. In a more recent systematic review, the prevalence of burnout ranged from 5.6% to 88% [ 14 ]. In addition, depression and suicidal thoughts were more common during medical school than physicians who started working [ 15 , 16 ]. Burnout among medical students has been linked to poorer academic performance, increased substance use, and impaired mental health, all of which may compromise future physicians’ ability to deliver high-quality, compassionate patient care [ 15 ]. It is also important to focus on the variety of learning and educational environments in the medical school that may be associated with burnout, as these can have either a positive or negative impact on burnout. Learning approach refers to the differentiation in goals and activities that can be chosen to fulfill a specific learning task [ 17 ]. There are three learning approaches defined in the literature: surface, deep and strategic approaches. It has been shown that the learning approach is the adoption of the way of dealing with the learning, depending on the individual's intention. It is not a permanent personality feature and it changes according to the environmental factors and personality characteristics [ 18 ]. Medical students’ learning approaches may also play a significant role in the development of burnout, Previous research has shown that strategic learners tend to experience lower levels of anxiety and burnout, whereas students who adopt a surface approach report poorer academic outcomes and higher stress levels [ 18 ]. Whereas, the causal direction may also operate in reverse; burnout and decreased personal accomplishment may lead students to rely more on surface learning [ 19 ]. The educational environment is defined as everything that happens in the classroom, department, faculty or university. The educational environment includes the culture of a school or class and its priorities and characteristics, such as physical environment, institutional policies, context, culture, interaction, peer support, and educational feedback. Educational environment of an institution is the environment experienced or perceived by students and teachers. Research shows that the educational environment affects students' success, happiness and motivation. The quality of the educational environment is an indicator of the effectiveness of a training program. The educational environment sub-scales are positively associated with academic achievement and satisfaction with educational programs. In the recent researches, a strong and consistent correlation was found between the perceived quality of the educational environment and burnout [ 20 – 22 ]. Some of the previous studies have explored the relationship between learning approaches and burnout individually [ 23 ], while others have examined the role of the educational environment [ 24 ].However, a few have evaluated these components together, and none have focused specifically on final-year medical students preparing for clinical practice [ 25 , 26 ]. Understanding these complex interactions is critical for designing interventions that promote effective learning and protect future physicians’ mental health. In this context, it is important for the future physicians to determine the levels of burnout, and to evaluate its relationship between their learning approaches, educational environments and academic achievement, to deal with burnout or prevent burnout. The aim of this study is to evaluate the relationship of burnout levels of the senior students of the medical faculty, with their learning approaches, educational environments and academic achievement. MATERIALS AND METHODS Study design and setting This single-center, descriptive cross-sectional study was conducted at Hacettepe University Faculty of Medicine, a large tertiary academic institution in Ankara, Türkiye. The study evaluated the relationship between burnout, learning approaches, perception of the educational environment, and academic achievement among final-year medical students. Participants and procedure The study population comprised all sixth-year medical students enrolled in both the Turkish and English programs during the 2019–2020 academic year. Data collection was conducted electronically between July and August 2019 using an online questionnaire. Participation was voluntary, and informed consent was obtained electronically at the beginning of the survey. Students who completed the questionnaire in full were included in the analysis. There were no exclusion criteria. Ethical approval Ethical approval for this study was obtained from the Hacettepe University Senate Ethics Commission (Application No: 670055). Data collection instruments Quantitative data were collected using a structured online questionnaire consisting of four sections. The study questionnaire was developed specifically for this research and consisted of demographic questions and validated Turkish versions of the MBI, ASSIST, and DREEM-TR instruments. An English version of the complete questionnaire is provided in Additional File 4 : 1. Sociodemographic and academic data: This section included questions about age, gender, motivation for choosing medical school, alcohol consumption, smoking status, drug or substance abuse and self-reported cumulative Grade Point Average (GPA). 2. Maslach Burnout Inventory (MBI): The MBI, a validated 22-item instrument, was used to assess burnout across three dimensions: Emotional Exhaustion (EE), Depersonalization (DP), and Personal Accomplishment (PA). The Turkish validated adaptation of the MBI, which uses a 5-point Likert scale, was utilized in this study [27]. For the subscale of emotional exhaustion and depersonalization, items are negative, and scored as “0: Never, 1: Very rare, 2: Sometimes, 3: Most of the time, 4: Always”. For personal accomplishment subscale the 8 items (4, 7, 9, 12, 17, 18, 19, 21) are positive, and reverse-scored. The highest scores that can be obtained from the scale are, 36 for EE, 20 for DP and 32 for PA. The lowest score that can be obtained from each subscale is zero. In this study, higher EE, DP and PA scores indicate higher levels of burnout. 3. Approaches and Study Skills Inventory for Students (ASSIST): The ASSIST was employed to assess students' predominant learning approaches, including deep, strategic, and surface learning approaches. The Turkish validated version of the scale with 67 items all of which are five-point Likert type was used in the study [28]. The first section of ASSIST (A) consists of 52 items related to three subscales, deep, strategic and surface learning approaches. Section B comprises six items designed to assess the meanings that students attribute to the concept of ‘learning.’ The final section (C) consists of nine items in which students are asked to indicate their preferences for different types of teaching [29]. Students respond to 1- 5 Likert type scale (5 high) items. Subscale scores are created by adding the answers given to the items in that subscale. The sum of items is generated by summing up the items and creating a new variable. The predominant learning approach was calculated using the subscale scores according to protocol. 4. Dundee Ready Education Environment Measure – Turkish version (DREEM-TR): The DREEM-TR was used to evaluate students’ perceptions of the educational environment, covering subscales related to perceptions of learning, perceptions of teachers, academic self-perceptions, perceptions of atmosphere, and social self-perceptions. A five-point Likert-type grading was used as 5: strongly agree, 4: agree, 3: undecided, 2: disagree and 1: strongly disagree. The scale comprises a five-dimensional structure with 43 items: 11 items assess students’ perceptions of teaching, 9 items evaluate perceptions of teachers, 8 items address perceptions of their own academic abilities, 11 items measure perceptions of the educational environment, and 4 items pertain to perceptions of the social environment. Items 4, 8, 9, 22, 31, 35, and 42 of the DREEM-TR are reverse-scored. The maximum achievable score on the scale is 215, while the minimum is 43 [30]. The Maslach Burnout Inventory (MBI), the Approaches and Study Skills Inventory for Students (ASSIST), and the Dundee Ready Education Environment Measure (DREEM-TR) — all of which have been previously adapted and validated in Turkish — were used with written permission from their respective copyright holders (Additional Files 1–3). Statistical analysis Data were analyzed using IBM Statistical Package for the Social Sciences version 25 (SPSS, IBM, Armonk, NY). In descriptive statistics, number and percentage (%) are specified for categorical variables. For continuous variables with normal distribution, mean and standard deviation (Standard Deviation, SD); for continuous variables that do not show normal distribution, the width between quarter values (Interquartile Range, IQR) and median were used. Pearson Chi-Square Test was used to evaluate categorical variables. The normality of variables was tested using visual (histogram and probability plots) and analytical methods (Kolmogorov-Smirnov / Shapiro-Wilk Test), and also the number of data, skewness kurtosis coefficients were checked. For the variables determined to conform to the normal distribution; for the statistical significance between the two independent groups, Student's t Test; for the variables that are found not to conform to the normal distribution, Mann-Whitney U Test, ANOVA among three independent groups or Kruskal Wallis Test were used as statistical method. The relationship between the variables was evaluated by Pearson Correlation Analysis. A multivariate analysis (MANOVA) was performed to assess the simultaneous effects of burnout and learning approaches on academic achievement and perception of the educational environment. Statistical significance level was accepted as p <0.05. While evaluating the correlation results, Karasar's criteria were taken into consideration [31]. RESULTS The questionnaire forms were sent electronically to the 6 th grade students of Hacettepe University Faculty of Medicine. 12 of the students did not agree to participate in the survey and 241 (response rate 95.25%) were provided consent and completed the survey. Sociodemographic data of 241 students are summarized in Table 1. Table 1 Sociodemographic characteristics of the students N= (241) Mean ± SD Min - Max Age 23,79 ± 1,13 min:22, max:31 n % Sex Male 142 58,9 Female 99 41,1 Alcohol consumption No Use 131 54,4 Use 110 45,6 Substance abuse No Use 230 95,4 Use 11 4,6 Smoking Smoker 46 19,1 Non-smoker 195 80,9 Academic grade point average 2 - 2,9 (low) 133 55,2 3,0 – 4 (high) 108 44,8 Choice of Profession Willingly 219 90,9 Unwillingly 22 9,1 Maslach Burnout Inventory The mean scores of the MBI subscales among the students were as follows: Emotional Exhaustion 17.54±6.63, Depersonalization 7.14±3.53 and Personal Accomplishment 12.95±4.40. (Table 2). Table 2 Maslach Burnout Inventory Scores Among Students Subscale Mean ± SD Emotional Exhaustion 17.54 ± 6.63 Depersonalization 7.14 ± 3.53 Personal Accomplishment 12.95 ± 4.40 A correlation analysis was conducted to evaluate the relationships among the subscales of the MBI. There was a moderate, positive, and statistically significant correlation between EE and DP (r=0.651, p<0.01) and between EE and PA (r=0.439, p<0.01). Additionally, a moderate, positive, and statistically significant correlation was observed between DP and PA (r=0.317, p<0.01). No significant differences were found in students’ MBI subscale scores based on gender, alcohol consumption, smoking status, or substance use. Although students with GPAs of 2.0–2.9 had higher EE and PA scores and slightly lower DP scores, neither of these differences were statistically significant when compared to students with GPAs of 3.0–4.0. When the burnout scores were compared according to students’ motivation underlying their choice of the medical profession (categorized in the survey as choosing medicine “willingly” vs. “unwillingly”), students with lower career-choice motivation exhibited higher EE, DP, and PA scores than those with higher motivation. However, only the difference in EE was statistically significant (20.64 vs. 17.22, p = 0.02). Learning Approaches and Study Skills Inventory for Students Students most frequently preferred the Strategic Approach, followed by the Deep Approach, while the Surface Approach was the least preferred among the three (Table 3). Table 3 Students’ Preference Levels for Learning Approaches Approach n Mean (X) SD Deep Approach 241 55.66 9.66 Strategic Approach 241 65.35 11.47 Surface Approach 241 50.22 9.92 Students were categorized based on the highest score they obtained among the three subscales of the ASSIST. Accordingly, 74.7% (n=180) of the students adopted the Strategic Approach, 13.7% (n=33) adopted the Surface Approach, and 11.6% (n=28) adopted the Deep Approach (Figure 1). No significant differences were found in students’ learning approach preferences based on gender, alcohol consumption, smoking status, or substance use. A statistically significant difference was found: F(3, 237) = 3.18, p = 0.05; Wilks’ Lambda = 0.96 in students’ learning approach preferences based on motivation for choosing the profession. When the dependent variables were examined individually, the students with lower career-choice motivation had significantly higher Surface Approach scores compared to those with higher motivation (p = 0.02). A statistically significant difference was found (F(3, 237) = 2.70, p = 0.001; Wilks’ Lambda = 0.93) in students’ learning approach preferences based on their academic achievement. When each learning approach was evaluated separately, students with higher academic GPAs (3.0–4.0) had significantly higher Strategic Approach scores and lower Surface Approach scores compared to those with lower GPAs (2.0–2.9) (p < 0.001, p = 0.05) Dundee Ready Education Environment Measure – Turkish (DREEM-TR) The mean total score obtained from the DREEM-TR scale was 128.91 ± 23.16. Subscale scores were standardized as percentages based on their different maximum scores. The highest percentage score was found in the “students’ academic self-perception” subscale (65.32%), and the lowest percentage score was in the “students’ perceptions of learning” subscale (56.18%) (Table 3). Table 3 Students' Perceptions of Educational Environment n Mean SS Percent Dreem Total 241 128,92 23,16 60,0% Self-perception of learning 241 30,90 6,30 56,2% Perception of Teachers 241 28,02 5,58 62,2% Academic Self-Perception 241 26,13 4,98 65,3% Social Self-Perception 241 12,19 2,57 61,0% Perception of Learning Climate 214 31,66 7,63 57,6% When the items with the lowest mean scores were examined, item 3 received the lowest average score (mean item score: 1.87). This item states, “There is a good support system for students who get stressed.” The item with the highest score was item 13, which reads, “I have good friends in this school,” with a mean score of 4.22. There were no significant differences in DREEM-TR scores based on gender, smoking, or alcohol use. However, a significant relationship was found between substance use and perceptions of the educational environment. Students who reported substance use had significantly lower DREEM-TR scores compared to those who did not use substances (mean: 115.36 vs. 129.56; p = 0.047). A significant relationship was also observed between academic achievement and DREEM-TR scores. Students with GPA between 3.0 and 4.0 had higher DREEM-TR scores than those with GPA between 2.0 and 2.9 (mean: 133.60 vs. 125.11; p = 0.004). The Relationship Between Students’ Preferred Learning Approaches and Burnout Subscales A moderate, statistically significant positive correlation was found between the surface approach and EE, DP and PA scores (r:0.590, 0.386, and 0.478 respectively, p<0.01). There was a statistically significant weak negative correlation between the strategic approach and EE scores (r:-0.182, p=0.005), and a moderate negative correlation between the strategic approach and PA scores (r:-0.433, p<0.01). Finally, a moderate, statistically significant negative correlation was observed between the deep approach and PA scores (r:-0.319, p<0.01). (Figure2) The Relationship Between Students’ Perceptions of the Educational Environment and Burnout Subscale Scores A moderate, statistically significant negative correlation was found between perceptions of the educational environment and EE and PA scores (r:-0.480 and -0.498 respectively, p<0.01). A weak but statistically significant negative correlation was also observed between perceptions of the educational environment and DP scores (r:-0.288, p<0.01). (Figure 3) The Relationship Between Students’ Perceptions of the Educational Environment and Their Preferred Learning Approaches A low, statistically significant positive correlation was found between students’ DREEM-TR total scores and deep approach scores (r:0.285, p<0.01). A moderate, statistically significant positive correlation was observed between perceptions of the educational environment and strategic approach scores (r:0.442, p<0.01). In contrast, a moderate, statistically significant negative correlation was found between perceptions of the educational environment and surface approach scores (r:-0.549, p<0.01). (Figure 4) DISCUSSION This study identified several important findings by examining the complex relationships among burnout, learning approaches, perceptions of the educational environment, and academic achievement in final-year medical students. Burnout levels did not differ across most sociodemographic variables; however, students who had chosen medicine with lower motivation had significantly higher emotional exhaustion, indicating that motivation may protect against burnout. Most students used a strategic learning approach, and higher academic performance correlated with greater use of strategic approaches and less use of surface approaches. The surface learning approach showed the strongest positive correlation with burnout across all subscales. Positive perceptions of the educational environment were linked to lower burnout and a preference for deep and strategic learning, while negative perceptions correlated with higher burnout and more surface approaches. These findings highlight the interconnected roles of motivation, learning approaches, and the educational environment in shaping burnout risk in medical students. Burnout Level and Related Conditions in Students Among studies conducted in Türkiye, an unpublished study from Hacettepe University (May 2019) reported mean MBI scores for 365 next-grade students: EE 18.52, DP 7.72, and PA 14.27 [32]. In comparison, our subscale scores (MBI: EE 17.54, DP 7.14, PA 12.95) were slightly lower, which may be attributed to the fact that participants in the earlier study were in their final month, whereas our participants were only in their second month and may have been at different levels of burnout. Furthermore, a 2005 study of 276 final-year medical students in Ankara reported similar MBI means: EE 18.32, DP 7.57, PA 13.34 [33]. Likewise, Akdeniz University’s final-year students reported: EE 17.3, DP 6.3, PA 19.9 [34]. Overall, the timing within the academic year may explain observed differences between groups. In our study, students with lower motivation underlying their career choice had higher scores across all three burnout subscales; however, only the difference in EE scores (20.64 vs. 17.22) was statistically significant (p = 0.02). Similar findings have been reported in studies conducted among nurses in Türkiye, where burnout levels were higher among individuals whose motivation for choosing the profession was limited or externally driven [35, 36]. Another study examining burnout among surgical and internal medicine residents demonstrated that those with higher EE scores were more likely to have entered their specialties without strong initial motivation compared with intrinsically motivated residents [37]. These results suggest that the motivation underlying medical career choice may function as a protective factor against burnout. Students with a GPA of 2.0–2.9 had higher EE and PA scores than those with a GPA of 3.0–4.0, but these differences were not statistically significant. Burnout has been linked to lower academic performance among medical students, possibly due to reduced personal accomplishment, which lowers academic self-efficacy. It may also directly lead to reduced concentration, impaired motivation, or a shift toward surface learning strategies, which are commonly observed among students with burnout [38, 39]. Students’ Learning Approaches In our study, 74.7% of students adopted the strategic learning approach, 13.7% adopted the surface approach, and 28% adopted the deep learning approach. The highest mean score was observed in the strategic learning approach. Notably, students with higher academic performance had higher mean scores for the strategic learning approach and lower scores for the surface learning approach. These findings are consistent with other studies in medical schools, which have shown that strategic and deep learning approaches are positively associated with higher academic performance and are more frequently preferred by medical students, whereas the surface approach is negatively associated with academic performance [40-42]. In our study, students with lower motivation for choosing the medical profession had higher mean scores on the surface learning approach, suggesting a preference for surface learning due to lower engagement with the school. Although no previous studies have directly examined this association, strong intrinsic motivation to study medicine is generally understood to be linked to deeper learning approaches. Therefore, less motivated students may adopt surface strategies. The Relationship Between Learning Approaches and Burnout In our study. the students who adopted the surface approach had higher burnout levels. In contrast, students who adopted the strategic approach had lower EE and PA scores. Students who adopted the deep approach had lower PA scores. In a study conducted by Cipra and colleagues, medical students who adopted the strategic learning approach demonstrated higher academic performance and lower levels of anxiety and burnout. Conversely, students who adopted the surface learning approach were found to have the lowest grade point averages and higher levels of stress [43]. Students who are affected by anxiety and fear of failure may struggle to structure their study programs or focus on available learning materials, leading them to adopt a surface approach to learning. As a result, students who rely on surface learning may fail to integrate knowledge effectively, become easily discouraged, lose confidence, and thereby reinforce this negative learning pattern. However, the reverse causal direction is also plausible: adopting a surface learning approach, once its limitations and shortcomings are perceived, may itself become a source of anxiety and potentially lead to the development of burnout syndrome [19]. Students' Perceptions of Educational Environment Because the DREEM-TR includes 43 items rated on a 1–5 Likert scale, it was not possible to directly interpret it according to the guide developed by McAleer and Roff which provides cut-off interpretations based on raw scores for the 50-item 0–4 Likert version [44]. Therefore, total and subscale scores were first normalized as percentages of their respective maximum possible scores. Then verbal categories were derived from the original descriptors and adapted to the percentage scale, following approaches used in previous literature [45, 46]. Accordingly, the following verbal equivalents were used for percentage scores: 0–25% = very poor, 26–50% = problematic, 51–75% = more positive than negative, and 76–100% = excellent educational environment. According to this model our overall score would be roughly considered ‘more positive than negative’ perception of educational environment with a percentage score of (60%). This finding is consistent with previous research reporting overall DREEM percentage scores ranging between 58% and 65% in various medical schools worldwide. For example, studies from Nigeria [47], Iran [48] and China [49] all reported similar percentage scores within this range. As in many of these studies, “Students’ Academic Self-Perception” showed the highest subscale score (65.3%) in our cohort, whereas “Perceptions of Learning” (56.2%) and “Perceptions of Atmosphere” (57.6%) were more positive than negative. Notably, our students’ “Social Self-Perception” (61.0%) was higher than that reported in several comparable cohorts, suggesting a relatively supportive peer environment. This interpretation is further supported by the item-level result showing that “I have good friends in this school” received the highest mean score (4.22) among all items, reflecting strong interpersonal relationships and social cohesion among students. This finding may suggest that peer relationships serve as a protective factor against burnout, as poor interpersonal relationships in the workplace are known contributors to burnout [50]. Although a Turkish adaptation and validation of the DREEM scale (DREEM-TR) has been published [30], no previous study conducted among Turkish medical students has reported percentage-normalized scores or verbal category equivalents. Therefore, the present study fills an important gap in the national literature, providing the first example of a percentage-based interpretation of the DREEM-TR among Turkish medical students. Another important finding of our study was that the mean perception of the educational environment score of substance users was found to be lower than that of non-users. To our knowledge, this is the first study to explore the relationship between substance use and perceptions of the educational environment among medical students. One possible explanation for this finding is that students who use substances may experience higher levels of stress and reduced academic engagement, which could negatively influence their perceptions of the educational environment. Alternatively, perceiving the educational environment as less supportive may contribute to maladaptive coping behaviors, like substance use. Although the direction of this relationship cannot be determined in a cross-sectional design, the association suggests an important and previously unexplored interface between student well-being and perceptions of the educational climate. Students with higher academic performance had more positive perceptions of the educational environment in our study, consistent with prior research [20, 51]. Prior studies suggest that students’ perceptions of the educational environment influence their learning approaches, which in turn are associated with academic performance [52, 53]. For example, negative perceptions are associated with surface learning approaches [25], while positive perceptions are associated with deep learning approach [20]. Our results reinforce the idea that students with positive perceptions tend to adopt deep, strategic learning approaches, while those with less positive perceptions prefer surface approaches. Biggs describes the curriculum, teaching method, assessment and classroom climate as situational variables that affect the learning approaches, highlighting that both are modifiable and interact with one another [54]. Changes in the educational environment can influence students' preferred learning approaches. The educational environment appears especially useful in predicting learning approaches. If a student's perception of the educational environment is negative, this may negatively affect their learning approach and indirectly their academic achievement [55]. Importantly, the literature also shows that negative perceptions of the educational environment may contribute to higher levels of burnout, which in turn can further lead to surface learning approaches [21, 25]. The Relationship Between Educational Environment and Burnout In our study, students’ perceptions of the educational environment showed a negative correlation with all three burnout dimensions, indicating that students who perceive the educational environment negatively tend to have higher levels of burnout. This finding is consistent with previous studies reporting that unsatisfactory aspects of the medical school educational environment may be associated with burnout [21]. Conversely, a positive perception of educational environment has been shown to protect against burnout [22]. For medical students, the working environment is also the educational environment. Given that burnout is caused by the characteristics of the working environment rather than the individual, the epidemic-level prevalence of burnout among medical students highlights the importance of thoroughly evaluating the quality of the educational environment in medical schools. A closer examination of our findings further highlights this point. Notably, the item with the lowest score in the DREEM-TR was “There is a good support system for students who get stressed” (mean = 1.87), indicating a weakness in the existing educational environment. A perceived lack of institutional support system may undermine students’ ability to cope with burnout. Given that strong institutional and peer support systems are among the key protective factors against burnout in medical education, this result emphasizes the urgent need for medical education settings to prioritize and implement structured support opportunities for students. When we examine burnout syndrome and the educational environment from a quality perspective in the medical school context, we see that burnout also poses a threat to patient safety. Efforts to address burnout are now included in quality improvement. The Accreditation Council for Graduate Medical Education (ACGME) in the United States recommends providing an educational environment that prioritizes patient safety and quality of care. It specifically advises attention to workload and working conditions to reduce fatigue and burnout among residents [56]. Educators should first increase their awareness of burnout and gain a clear understanding of the factors that contribute to its development. In medical schools, it is especially important to identify aspects of the educational environment and students’ learning approaches that may lead to burnout. Gathering student feedback about their perceptions of the educational environment and using this information as a foundation for strategic planning can provide a valuable starting point for improvement. Our research findings should be interpreted in light of certain limitations. One major limitation is the participation rate, which may restrict the generalizability of the results to all final-year students. In addition, since the Turkish-adapted version of the Maslach Burnout Inventory (MBI) does not define cut-off points for its subscales, burnout levels could not be categorized in this study. This, in turn, limited our ability to make direct comparisons with the literature; instead, statistical analyses were conducted using mean scores to determine relationships between variables. Conclusion Addressing deficiencies in the educational environment is essential to ensure effective learning in medical schools, reduce burnout rates, and promote patient safety. In addition to designing and implementing interventions, it is necessary to maintain a supportive educational environment. Continuous improvement in the educational environment requires identifying its strengths and weaknesses; therefore, monitoring students’ perceptions of the educational environment at various stages of their training is critical. Further research is needed to statistically model the simultaneous relationship between the educational environment, learning approaches, and burnout. Given the lack of prior studies in medical education that examine these three components together, the present study is particularly significant. Furthermore, we believe the findings from this study can serve as a resource for developing interventions to improve the educational environment and support students in coping with burnout within medical schools. Abbreviations MBI Maslach Burnout Inventory ASSIST Approaches and Study Skills Inventory for Students DREEM-TR Dundee Ready Education Environment Measure – Turkish version ICD International Classification of Diseases GPA Grade Point Average EE Emotional Exhaustion DP Depersonalization PA Personal Accomplishment Declarations Ethics declarations Ethical approval and consent to participate Ethical approval for this study was obtained from the Hacettepe University Senate Ethics Commission (Application No: 670055). All procedures performed in this study were conducted with the principles of the Declaration of Helsinki. Participation was voluntary, and informed consent was obtained electronically from all participants before completing the survey. Consent for publication Not applicable. Availability of data and materials The anonymized dataset generated and analyzed during this study is not publicly archived but is available from the corresponding author upon reasonable request. Competing interests The authors declare no competing interests. Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Contributions Author Contributions: Conceptualization: [LO], [ME]; Methodology: [LO], [ME]; Data acquisition: [LO]; Formal analysis and investigation: [LO] ; Writing - original draft preparation: [LO]; Writing - review and editing: [LO], [ME]; Statistical Expertise: [LO] ; Supervision: [ME] Corresponding Author: Correspondance to Lale Ozisik Acknowledgements The authors thank all the students who participated in the survey. Authors and Affiliations Lale Ozisik: Department of Internal Medicine, Faculty of Medicine, Hacettepe University. Ankara, Türkiye Melih Elcin: Interprofessional Education (IPE), School of Health Sciences, Springfield College, Springfield, MA, USA References Agerbo E, Gunnell D, Bonde JP, Mortensen PB, Nordentoft M. 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Student Approaches to Learning and Studying: ERIC; 1987. Ramsden P. Learning from the student’s perspective. In: Learning to Teach in Higher Education. edn. Edited by Ramsden P. New York: RoutledgeFalmer; 2003: 62–84. Weiss KB, Wagner R, Nasca TJ. Development, Testing, and Implementation of the ACGME Clinical Learning Environment Review (CLER) Program. J Grad Med Educ. 2012;4(3):396–8. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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2","display":"","copyAsset":false,"role":"figure","size":1306670,"visible":true,"origin":"","legend":"\u003cp\u003eScatter plots illustrating the correlations between students’ MBI subscale scores and their preferred learning approaches\u003c/p\u003e","description":"","filename":"Figure2ScatterplotsillustratingthecorrelationsbetweenstudentsMBIsubscalescoresandtheirpreferredlearningapp.png","url":"https://assets-eu.researchsquare.com/files/rs-8149384/v1/51e7b787b0d8546595dc440b.png"},{"id":97469811,"identity":"bdd36d6a-4824-4a4b-802a-04bcf55261c9","added_by":"auto","created_at":"2025-12-04 17:24:00","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1039797,"visible":true,"origin":"","legend":"\u003cp\u003eScatter plots illustrating the correlations between students’ educational environment perceptions (DREEM-TR total score) and their MBI subscale scores\u003c/p\u003e","description":"","filename":"Figure3ScatterplotsillustratingthecorrelationsbetweenstudentseducationalenvironmentperceptionsDREEMTRtotalscoreandtheirMBIsubscalescores.png","url":"https://assets-eu.researchsquare.com/files/rs-8149384/v1/4949f5016452eea52802453f.png"},{"id":97469812,"identity":"dea0c5e8-6a55-4015-84bc-3035a8880580","added_by":"auto","created_at":"2025-12-04 17:24:00","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1045153,"visible":true,"origin":"","legend":"\u003cp\u003eScatter plots illustrating the correlations between students’ perceptions of the educational environment (DREEM-TR total score) and their preferred learning approaches\u003c/p\u003e","description":"","filename":"Figure4ScatterplotsillustratingthecorrelationsbetweenstudentsperceptionsoftheeducationalenvironmentDREEMTRtotalscoreandtheirpreferredlearningapproaches.png","url":"https://assets-eu.researchsquare.com/files/rs-8149384/v1/1e6e5101a25ce6c178484950.png"},{"id":99792176,"identity":"2f0ccd04-6f93-4cfe-9acc-13ada7ed8157","added_by":"auto","created_at":"2026-01-08 13:15:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3206203,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8149384/v1/e33b4edd-7f3c-42cb-a2f7-88e9bfa84324.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eMapping Burnout in Medical Students: Interactions Between Learning Approaches and the Educational Environment\u003c/p\u003e","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eHealthcare workers are at risk of developing mental illness due to numerous factors such as chronic stress, large workloads and compassion fatigue [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Research shows that 39% of physicians have depression and this ratio is twice the general population. In the United States, approximately 400 doctors die each year due to suicide [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. It has also been shown that physicians' burnout level is one of the most important factors leading to suicide [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAccording to Maslach, burnout is a syndrome characterized by emotional exhaustion, depersonalization, and reduced professional accomplishment, emerging in people who work intensively with others [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In the 11th revision of the International Classification of Diseases (ICD-11), burnout was defined as a professional phenomenon rather than a medical condition, manifested by feelings of exhaustion, increased mental distance to work or negativity, and decreased professional activity [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eBurnout has reached epidemic levels worldwide, affecting 30% to 60% of physicians depending on specialty and measurement methods [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In the U.S., more than half of physicians report burnout, with rates rising from 44% in 2019 to 53% in 2023 after Covid-19 Pandemic [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Another survey in 2024 has shown that six in 10 physicians and residents, and seven in 10 medical students reported often experiencing burnout [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. According to the UK House of Commons Health and Social Care Committee report (2021), work-related stress among NHS staff has been rising, with the NHS Staff Survey showing an increase from 40.3% in 2019 to 44% during the COVID-19 pandemic [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePhysicians\u0026rsquo; burnout syndrome is increasingly recognized as a public health crisis in many high-income countries. Young doctors were most at risk, followed by general practitioners. This situation not only affects physicians' personal lives and job satisfaction, but it also creates serious pressures on the entire health system, in other words, it threatens especially the care and safety of patients [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. An increasing number of articles have been published in the last 15 years, indicating that the origins of burnout in physicians started in medical school [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Prevalence rates for professional burnout in medical students, ranges from 7.0% to 75.2%, depending on country-specific factors, applied instruments, cutoff-criteria for burnout symptomatology [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. A 2019 meta-analysis indicate that burnout affects approximately 44% of medical students, with emotional exhaustion and depersonalization being the most common symptoms [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In a more recent systematic review, the prevalence of burnout ranged from 5.6% to 88% [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In addition, depression and suicidal thoughts were more common during medical school than physicians who started working [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eBurnout among medical students has been linked to poorer academic performance, increased substance use, and impaired mental health, all of which may compromise future physicians\u0026rsquo; ability to deliver high-quality, compassionate patient care [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. It is also important to focus on the variety of learning and educational environments in the medical school that may be associated with burnout, as these can have either a positive or negative impact on burnout.\u003c/p\u003e\u003cp\u003eLearning approach refers to the differentiation in goals and activities that can be chosen to fulfill a specific learning task [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. There are three learning approaches defined in the literature: surface, deep and strategic approaches. It has been shown that the learning approach is the adoption of the way of dealing with the learning, depending on the individual's intention. It is not a permanent personality feature and it changes according to the environmental factors and personality characteristics [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Medical students\u0026rsquo; learning approaches may also play a significant role in the development of burnout, Previous research has shown that strategic learners tend to experience lower levels of anxiety and burnout, whereas students who adopt a surface approach report poorer academic outcomes and higher stress levels [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Whereas, the causal direction may also operate in reverse; burnout and decreased personal accomplishment may lead students to rely more on surface learning [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe educational environment is defined as everything that happens in the classroom, department, faculty or university. The educational environment includes the culture of a school or class and its priorities and characteristics, such as physical environment, institutional policies, context, culture, interaction, peer support, and educational feedback. Educational environment of an institution is the environment experienced or perceived by students and teachers. Research shows that the educational environment affects students' success, happiness and motivation. The quality of the educational environment is an indicator of the effectiveness of a training program. The educational environment sub-scales are positively associated with academic achievement and satisfaction with educational programs. In the recent researches, a strong and consistent correlation was found between the perceived quality of the educational environment and burnout [\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSome of the previous studies have explored the relationship between learning approaches and burnout individually [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], while others have examined the role of the educational environment [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].However, a few have evaluated these components together, and none have focused specifically on final-year medical students preparing for clinical practice [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Understanding these complex interactions is critical for designing interventions that promote effective learning and protect future physicians\u0026rsquo; mental health.\u003c/p\u003e\u003cp\u003eIn this context, it is important for the future physicians to determine the levels of burnout, and to evaluate its relationship between their learning approaches, educational environments and academic achievement, to deal with burnout or prevent burnout. The aim of this study is to evaluate the relationship of burnout levels of the senior students of the medical faculty, with their learning approaches, educational environments and academic achievement.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cp\u003e\u003cstrong\u003eStudy design and setting\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis single-center, descriptive cross-sectional study was conducted at Hacettepe University Faculty of Medicine, a large tertiary academic institution in Ankara, Türkiye. The study evaluated the relationship between burnout, learning approaches, perception of the educational environment, and academic achievement among final-year medical students.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParticipants and procedure\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study population comprised all sixth-year medical students enrolled in both the Turkish and English programs during the 2019–2020 academic year. Data collection was conducted electronically between July and August 2019 using an online questionnaire. Participation was voluntary, and informed consent was obtained electronically at the beginning of the survey. Students who completed the questionnaire in full were included in the analysis. There were no exclusion criteria.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval for this study was obtained from the Hacettepe University Senate Ethics Commission (Application No: 670055).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData collection instruments \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQuantitative data were collected using a structured online questionnaire consisting of four sections. The study questionnaire was developed specifically for this research and consisted of demographic questions and validated Turkish versions of the MBI, ASSIST, and DREEM-TR instruments. An English version of the complete questionnaire is provided in \u003cstrong\u003eAdditional File 4\u003c/strong\u003e:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e1. Sociodemographic and academic data:\u0026nbsp;\u003c/em\u003eThis section included questions about age, gender, motivation for choosing medical school, alcohol consumption, smoking status, drug or substance abuse and self-reported cumulative Grade Point Average (GPA).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e2. Maslach Burnout Inventory (MBI):\u003c/em\u003e The MBI, a validated 22-item instrument, was used to assess burnout across three dimensions: Emotional Exhaustion (EE), Depersonalization (DP), and Personal Accomplishment (PA). The Turkish validated adaptation of the MBI, which uses a 5-point Likert scale, was utilized in this study [27]. For the subscale of emotional exhaustion and depersonalization, items are negative, and scored as “0: Never, 1: Very rare, 2: Sometimes, 3: Most of the time, 4: Always”. For personal accomplishment subscale the 8 items (4, 7, 9, 12, 17, 18, 19, 21) are positive, and reverse-scored. The highest scores that can be obtained from the scale are, 36 for EE, 20 for DP and 32 for PA. The lowest score that can be obtained from each subscale is zero. In this study, higher EE, DP and PA scores indicate higher levels of burnout.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e3. Approaches and Study Skills Inventory for Students (ASSIST):\u003c/em\u003e The ASSIST was employed to assess students' predominant learning approaches, including deep, strategic, and surface learning approaches. The Turkish validated version of the scale with 67 items all of which are five-point Likert type was used in the study [28]. The first section of ASSIST (A) consists of 52 items related to three subscales, deep, strategic and surface learning approaches. Section B comprises six items designed to assess the meanings that students attribute to the concept of ‘learning.’ The final section (C) consists of nine items in which students are asked to indicate their preferences for different types of teaching [29]. Students respond to 1- 5 Likert type scale (5 high) items. Subscale scores are created by adding the answers given to the items in that subscale. The sum of items is generated by summing up the items and creating a new variable. The predominant learning approach was calculated using the subscale scores according to protocol.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e4. Dundee Ready Education Environment Measure – Turkish version (DREEM-TR):\u003c/em\u003e The DREEM-TR was used to evaluate students’ perceptions of the educational environment, covering subscales related to perceptions of learning, perceptions of teachers, academic self-perceptions, perceptions of atmosphere, and social self-perceptions. A five-point Likert-type grading was used as 5: strongly agree, 4: agree, 3: undecided, 2: disagree and 1: strongly disagree. The scale comprises a five-dimensional structure with 43 items: 11 items assess students’ perceptions of teaching, 9 items evaluate perceptions of teachers, 8 items address perceptions of their own academic abilities, 11 items measure perceptions of the educational environment, and 4 items pertain to perceptions of the social environment. Items 4, 8, 9, 22, 31, 35, and 42 of the DREEM-TR are reverse-scored. The maximum achievable score on the scale is 215, while the minimum is 43 [30].\u003c/p\u003e\n\u003cp\u003eThe Maslach Burnout Inventory (MBI), the Approaches and Study Skills Inventory for Students (ASSIST), and the Dundee Ready Education Environment Measure (DREEM-TR) — all of which have been previously adapted and validated in Turkish — were used with written permission from their respective copyright holders \u003cstrong\u003e(Additional Files 1–3).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData were analyzed using IBM Statistical Package for the Social Sciences version 25 (SPSS, IBM, Armonk, NY). In descriptive statistics, number and percentage (%) are specified for categorical variables. For continuous variables with normal distribution, mean and standard deviation (Standard Deviation, SD); for continuous variables that do not show normal distribution, the width between quarter values (Interquartile Range, IQR) and median were used. Pearson Chi-Square Test was used to evaluate categorical variables. The normality of variables was tested using visual (histogram and probability plots) and analytical methods (Kolmogorov-Smirnov / Shapiro-Wilk Test), and also the number of data, skewness kurtosis coefficients were checked. For the variables determined to conform to the normal distribution; for the statistical significance between the two independent groups, Student's t Test; for the variables that are found not to conform to the normal distribution, Mann-Whitney U Test, ANOVA among three independent groups or Kruskal Wallis Test were used as statistical method. The relationship between the variables was evaluated by Pearson Correlation Analysis. A multivariate analysis (MANOVA) was performed to assess the simultaneous effects of burnout and learning approaches on academic achievement and perception of the educational environment. Statistical significance level was accepted as p \u0026lt;0.05. While evaluating the correlation results, Karasar's criteria were taken into consideration [31].\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eThe questionnaire forms were sent electronically to the 6\u003csup\u003eth\u003c/sup\u003e grade students of Hacettepe University Faculty of Medicine. 12 of the students did not agree to participate in the survey and 241 (response rate 95.25%) were provided consent and completed the survey. Sociodemographic data of 241 students are summarized in Table 1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 1 Sociodemographic characteristics of the students\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"519\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eN= (241)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean ± SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMin - Max\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e23,79 ± 1,13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003emin:22, max:31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003en\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e58,9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e41,1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlcohol consumption\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNo Use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e54,4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eUse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e45,6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSubstance abuse\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNo Use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e230\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e95,4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eUse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4,6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSmoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e19,1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNon-smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e80,9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eAcademic grade point average\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2 - 2,9 (low)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e55,2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e3,0 – 4 (high)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e44,8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eChoice of Profession\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eWillingly\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e219\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e90,9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eUnwillingly\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9,1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eMaslach Burnout Inventory\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe mean scores of the MBI subscales among the students were as follows: Emotional Exhaustion 17.54±6.63, Depersonalization 7.14±3.53 and Personal Accomplishment 12.95±4.40.\u0026nbsp;(Table 2).\u003c/p\u003e\n\u003cp\u003eTable 2 Maslach Burnout Inventory Scores Among Students\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSubscale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean ± SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmotional Exhaustion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17.54 ± 6.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDepersonalization\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.14 ± 3.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePersonal Accomplishment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12.95 ± 4.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eA correlation analysis was conducted to evaluate the relationships among the subscales of the MBI. There was a moderate, positive, and statistically significant correlation between EE and DP (r=0.651, p\u0026lt;0.01) and between EE and PA (r=0.439, p\u0026lt;0.01). Additionally, a moderate, positive, and statistically significant correlation was observed between DP and PA (r=0.317, p\u0026lt;0.01).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNo significant differences were found in students’ MBI subscale scores based on gender, alcohol consumption, smoking status, or substance use. Although students with GPAs of 2.0–2.9 had higher EE and PA scores and slightly lower DP scores, neither of these differences were statistically significant when compared to students with GPAs of 3.0–4.0.\u003c/p\u003e\n\u003cp\u003eWhen the burnout scores were compared according to students’ motivation underlying their choice of the medical profession (categorized in the survey as choosing medicine “willingly” vs. “unwillingly”), students with lower career-choice motivation exhibited higher EE, DP, and PA scores than those with higher motivation. However, only the difference in EE was statistically significant (20.64 vs. 17.22, p = 0.02).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLearning Approaches and Study Skills Inventory for Students\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudents most frequently preferred the Strategic Approach, followed by the Deep Approach, while the Surface Approach was the least preferred among the three (Table 3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3 Students’ Preference Levels for Learning Approaches\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eApproach\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003en\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean (X)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDeep Approach\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e241\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e55.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eStrategic Approach\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e241\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e65.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurface Approach\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e241\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e50.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eStudents were categorized based on the highest score they obtained among the three subscales of the ASSIST. Accordingly, 74.7% (n=180) of the students adopted the Strategic Approach, 13.7% (n=33) adopted the Surface Approach, and 11.6% (n=28) adopted the Deep Approach (Figure 1). \u0026nbsp;\u003c/p\u003e\u003cp\u003eNo significant differences were found in students’ learning approach preferences based on gender, alcohol consumption, smoking status, or substance use.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA statistically significant difference was found: F(3, 237) = 3.18, p = 0.05; Wilks’ Lambda = 0.96 in students’ learning approach preferences based on motivation for choosing the profession. When the dependent variables were examined individually, the students with lower career-choice motivation had significantly higher Surface Approach scores compared to those with higher motivation (p = 0.02).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA statistically significant difference was found (F(3, 237) = 2.70, p = 0.001; Wilks’ Lambda = 0.93) in students’ learning approach preferences based on their academic achievement. When each learning approach was evaluated separately, students with higher academic GPAs (3.0–4.0) had significantly higher Strategic Approach scores and lower Surface Approach scores compared to those with lower GPAs (2.0–2.9) (p \u0026lt; 0.001, p = 0.05)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDundee Ready Education Environment Measure – Turkish (DREEM-TR)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe mean total score obtained from the DREEM-TR scale was 128.91 ± 23.16. Subscale scores were standardized as percentages based on their different maximum scores. The highest percentage score was found in the “students’ academic self-perception” subscale (65.32%), and the lowest percentage score was in the “students’ perceptions of learning” subscale (56.18%) (Table 3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003cstrong\u003eStudents' Perceptions of Educational Environment\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003en\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePercent\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDreem Total\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e241\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e128,92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23,16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e60,0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSelf-perception of learning\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e241\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e30,90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6,30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e56,2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePerception of Teachers\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e241\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28,02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5,58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e62,2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAcademic Self-Perception\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e241\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e26,13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4,98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e65,3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSocial Self-Perception\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e241\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12,19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2,57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e61,0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePerception of Learning Climate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e214\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e31,66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7,63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e57,6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eWhen the items with the lowest mean scores were examined, item 3 received the lowest average score (mean item score: 1.87). This item states, “There is a good support system for students who get stressed.” The item with the highest score was item 13, which reads, “I have good friends in this school,” with a mean score of 4.22.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThere were no significant differences in DREEM-TR scores based on gender, smoking, or alcohol use. However, a significant relationship was found between substance use and perceptions of the educational environment. Students who reported substance use had significantly lower DREEM-TR scores compared to those who did not use substances (mean: 115.36 vs. 129.56; p = 0.047). A significant relationship was also observed between academic achievement and DREEM-TR scores. Students with GPA between 3.0 and 4.0 had higher DREEM-TR scores than those with GPA between 2.0 and 2.9 (mean: 133.60 vs. 125.11; p = 0.004). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe Relationship Between Students’ Preferred Learning Approaches and Burnout Subscales\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA moderate, statistically significant positive correlation was found between the surface approach and EE, DP and PA scores (r:0.590, 0.386, and 0.478 respectively, p\u0026lt;0.01). There was a statistically significant weak negative correlation between the strategic approach and EE scores (r:-0.182, p=0.005), and a moderate negative correlation between the strategic approach and PA scores (r:-0.433, p\u0026lt;0.01). Finally, a moderate, statistically significant negative correlation was observed between the deep approach and PA scores (r:-0.319, p\u0026lt;0.01). (Figure2)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe Relationship Between Students\u0026rsquo; Perceptions of the Educational Environment and Burnout Subscale Scores\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA moderate, statistically significant negative correlation was found between perceptions of the educational environment and EE and PA scores (r:-0.480 and -0.498 respectively, p\u0026lt;0.01). A weak but statistically significant negative correlation was also observed between perceptions of the educational environment and DP scores (r:-0.288, p\u0026lt;0.01). (Figure 3)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe Relationship Between Students\u0026rsquo; Perceptions of the Educational Environment and Their Preferred Learning Approaches\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA low, statistically significant positive correlation was found between students\u0026rsquo; DREEM-TR total scores and deep approach scores (r:0.285, p\u0026lt;0.01). A moderate, statistically significant positive correlation was observed between perceptions of the educational environment and strategic approach scores (r:0.442, p\u0026lt;0.01). In contrast, a moderate, statistically significant negative correlation was found between perceptions of the educational environment and surface approach scores (r:-0.549, p\u0026lt;0.01). (Figure 4)\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study identified several important findings by examining the complex relationships among burnout, learning approaches, perceptions of the educational environment, and academic achievement in final-year medical students. Burnout levels did not differ across most sociodemographic variables; however, students who had chosen medicine with lower motivation had significantly higher emotional exhaustion, indicating that motivation may protect against burnout. Most students used a strategic learning approach, and higher academic performance correlated with greater use of strategic approaches and less use of surface approaches. The surface learning approach showed the strongest positive correlation with burnout across all subscales. Positive perceptions of the educational environment were linked to lower burnout and a preference for deep and strategic learning, while negative perceptions correlated with higher burnout and more surface approaches. These findings highlight the interconnected roles of motivation, learning approaches, and the educational environment in shaping burnout risk in medical students.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBurnout Level and Related Conditions in Students\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong studies conducted in T\u0026uuml;rkiye, an unpublished study from Hacettepe University (May 2019) reported mean MBI scores for 365 next-grade students: EE 18.52, DP 7.72, and PA 14.27 [32]. In comparison, our subscale scores (MBI: EE 17.54, DP 7.14, PA 12.95) were slightly lower, which may be attributed to the fact that participants in the earlier study were in their final month, whereas our participants were only in their second month and may have been at different levels of burnout. Furthermore, a 2005 study of 276 final-year medical students in Ankara reported similar MBI means: EE 18.32, DP 7.57, PA 13.34 [33]. Likewise, Akdeniz University\u0026rsquo;s final-year students reported: EE 17.3, DP 6.3, PA 19.9 [34]. Overall, the timing within the academic year may explain observed differences between groups.\u003c/p\u003e\n\u003cp\u003eIn our study, students with lower motivation underlying their career choice had higher scores across all three burnout subscales; however, only the difference in EE scores (20.64 vs. 17.22) was statistically significant (p = 0.02). Similar findings have been reported in studies conducted among nurses in T\u0026uuml;rkiye, where burnout levels were higher among individuals whose motivation for choosing the profession was limited or externally driven [35, 36]. Another study examining burnout among surgical and internal medicine residents demonstrated that those with higher EE scores were more likely to have entered their specialties without strong initial motivation compared with intrinsically motivated residents [37]. These results suggest that the motivation underlying medical career choice may function as a protective factor against burnout.\u003c/p\u003e\n\u003cp\u003eStudents with a GPA of 2.0\u0026ndash;2.9 had higher EE and PA scores than those with a GPA of 3.0\u0026ndash;4.0, but these differences were not statistically significant. Burnout has been linked to lower academic performance among medical students, possibly due to reduced personal accomplishment, which lowers academic self-efficacy. It may also directly lead to reduced concentration, impaired motivation, or a shift toward surface learning strategies, which are commonly observed among students with burnout [38, 39].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudents\u0026rsquo; Learning Approaches\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn our study, 74.7% of students adopted the strategic learning approach, 13.7% adopted the surface approach, and 28% adopted the deep learning approach. The highest mean score was observed in the strategic learning approach. Notably, students with higher academic performance had higher mean scores for the strategic learning approach and lower scores for the surface learning approach. These findings are consistent with other studies in medical schools, which have shown that strategic and deep learning approaches are positively associated with higher academic performance and are more frequently preferred by medical students, whereas the surface approach is negatively associated with academic performance [40-42].\u003c/p\u003e\n\u003cp\u003eIn our study, students with lower motivation for choosing the medical profession had higher mean scores on the surface learning approach, suggesting a preference for surface learning due to lower engagement with the school. Although no previous studies have directly examined this association, strong intrinsic motivation to study medicine is generally understood to be linked to deeper learning approaches. Therefore, less motivated students may adopt surface strategies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe Relationship Between Learning Approaches and Burnout\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn our study. the students who adopted the surface approach had higher burnout levels. In contrast, students who adopted the strategic approach had lower EE and PA scores. Students who adopted the deep approach had lower PA scores. In a study conducted by Cipra and colleagues, medical students who adopted the strategic learning approach demonstrated higher academic performance and lower levels of anxiety and burnout. Conversely, students who adopted the surface learning approach were found to have the lowest grade point averages and higher levels of stress [43]. Students who are affected by anxiety and fear of failure may struggle to structure their study programs or focus on available learning materials, leading them to adopt a surface approach to learning. As a result, students who rely on surface learning may fail to integrate knowledge effectively, become easily discouraged, lose confidence, and thereby reinforce this negative learning pattern. However, the reverse causal direction is also plausible: adopting a surface learning approach, once its limitations and shortcomings are perceived, may itself become a source of anxiety and potentially lead to the development of burnout syndrome [19].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudents\u0026apos; Perceptions of Educational Environment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBecause the DREEM-TR includes 43 items rated on a 1\u0026ndash;5 Likert scale, it was not possible to directly interpret it according to the guide developed by McAleer and Roff which provides cut-off interpretations based on raw scores for the 50-item 0\u0026ndash;4 Likert version [44]. Therefore, total and subscale scores were first normalized as percentages of their respective maximum possible scores. Then verbal categories were derived from the original descriptors and adapted to the percentage scale, following approaches used in previous literature [45, 46]. Accordingly, the following verbal equivalents were used for percentage scores: 0\u0026ndash;25% = very poor, 26\u0026ndash;50% = problematic, 51\u0026ndash;75% = more positive than negative, and 76\u0026ndash;100% = excellent educational environment.\u003c/p\u003e\n\u003cp\u003eAccording to this model our overall score would be roughly considered \u0026lsquo;more positive than negative\u0026rsquo; perception of educational environment with a percentage score of (60%). This finding is consistent with previous research reporting overall DREEM percentage scores ranging between 58% and 65% in various medical schools worldwide. For example, studies from Nigeria [47], Iran [48] and China [49] all reported similar percentage scores within this range. As in many of these studies, \u0026ldquo;Students\u0026rsquo; Academic Self-Perception\u0026rdquo; showed the highest subscale score (65.3%) in our cohort, whereas \u0026ldquo;Perceptions of Learning\u0026rdquo; (56.2%) and \u0026ldquo;Perceptions of Atmosphere\u0026rdquo; (57.6%) were more positive than negative. Notably, our students\u0026rsquo; \u0026ldquo;Social Self-Perception\u0026rdquo; (61.0%) was higher than that reported in several comparable cohorts, suggesting a relatively supportive peer environment. This interpretation is further supported by the item-level result showing that \u003cem\u003e\u0026ldquo;I have good friends in this school\u0026rdquo;\u003c/em\u003e received the highest mean score (4.22) among all items, reflecting strong interpersonal relationships and social cohesion among students. This finding may suggest that peer relationships serve as a protective factor against burnout, as poor interpersonal relationships in the workplace are known contributors to burnout [50].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAlthough a Turkish adaptation and validation of the DREEM scale (DREEM-TR) has been published [30], no previous study conducted among Turkish medical students has reported percentage-normalized scores or verbal category equivalents. Therefore, the present study fills an important gap in the national literature, providing the first example of a percentage-based interpretation of the DREEM-TR among Turkish medical students.\u003c/p\u003e\n\u003cp\u003eAnother important finding of our study was that the mean perception of the educational environment score of substance users was found to be lower than that of non-users. \u0026nbsp;To our knowledge, this is the first study to explore the relationship between substance use and perceptions of the educational environment among medical students. One possible explanation for this finding is that students who use substances may experience higher levels of stress and reduced academic engagement, which could negatively influence their perceptions of the educational environment. Alternatively, perceiving the educational environment as less supportive may contribute to maladaptive coping behaviors, like substance use. Although the direction of this relationship cannot be determined in a cross-sectional design, the association suggests an important and previously unexplored interface between student well-being and perceptions of the educational climate.\u003c/p\u003e\n\u003cp\u003eStudents with higher academic performance had more positive perceptions of the educational environment in our study, consistent with prior research [20, 51]. Prior studies suggest that students\u0026rsquo; perceptions of the educational environment influence their learning approaches, which in turn are associated with academic performance [52, 53]. For example, negative perceptions are associated with surface learning approaches [25], while positive perceptions are associated with deep learning approach [20].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur results reinforce the idea that students with positive perceptions tend to adopt deep, strategic learning approaches, while those with less positive perceptions prefer surface approaches. Biggs describes the curriculum, teaching method, assessment and classroom climate as situational variables that affect the learning approaches, highlighting that both are modifiable and interact with one another [54]. Changes in the educational environment can influence students\u0026apos; preferred learning approaches. The educational environment appears especially useful in predicting learning approaches. If a student\u0026apos;s perception of the educational environment is negative, this may negatively affect their learning approach and indirectly their academic achievement [55].\u003c/p\u003e\n\u003cp\u003eImportantly, the literature also shows that negative perceptions of the educational environment may contribute to higher levels of burnout, which in turn can further lead to surface learning approaches [21, 25].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe Relationship Between Educational Environment and Burnout\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn our study, students\u0026rsquo; perceptions of the educational environment showed a negative correlation with all three burnout dimensions, indicating that students who perceive the educational environment negatively tend to have higher levels of burnout. This finding is consistent with previous studies reporting that unsatisfactory aspects of the medical school educational environment may be associated with burnout [21]. Conversely, a positive perception of educational environment has been shown to protect against burnout [22].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; For medical students, the working environment is also the educational environment. Given that burnout is caused by the characteristics of the working environment rather than the individual, the epidemic-level prevalence of burnout among medical students highlights the importance of thoroughly evaluating the quality of the educational environment in medical schools. A closer examination of our findings further highlights this point.\u003c/p\u003e\n\u003cp\u003eNotably, the item with the lowest score in the DREEM-TR was \u003cem\u003e\u0026ldquo;There is a good support system for students who get stressed\u0026rdquo;\u003c/em\u003e (mean = 1.87), indicating a weakness in the existing educational environment. A perceived lack of institutional support system may undermine students\u0026rsquo; ability to cope with burnout. Given that strong institutional and peer support systems are among the key protective factors against burnout in medical education, this result emphasizes the urgent need for medical education settings to prioritize and implement structured support opportunities for students.\u003c/p\u003e\n\u003cp\u003eWhen we examine burnout syndrome and the educational environment from a quality perspective in the medical school context, we see that burnout also poses a threat to patient safety. Efforts to address burnout are now included in quality improvement. The Accreditation Council for Graduate Medical Education (ACGME) in the United States recommends providing an educational environment that prioritizes patient safety and quality of care. It specifically advises attention to workload and working conditions to reduce fatigue and burnout among residents\u0026nbsp;[56].\u003c/p\u003e\n\u003cp\u003eEducators should first increase their awareness of burnout and gain a clear understanding of the factors that contribute to its development. In medical schools, it is especially important to identify aspects of the educational environment and students\u0026rsquo; learning approaches that may lead to burnout. Gathering student feedback about their perceptions of the educational environment and using this information as a foundation for strategic planning can provide a valuable starting point for improvement. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur research findings should be interpreted in light of certain limitations. One major limitation is the participation rate, which may restrict the generalizability of the results to all final-year students. In addition, since the Turkish-adapted version of the Maslach Burnout Inventory (MBI) does not define cut-off points for its subscales, burnout levels could not be categorized in this study. This, in turn, limited our ability to make direct comparisons with the literature; instead, statistical analyses were conducted using mean scores to determine relationships between variables.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eAddressing deficiencies in the educational environment is essential to ensure effective learning in medical schools, reduce burnout rates, and promote patient safety. In addition to designing and implementing interventions, it is necessary to maintain a supportive educational environment. Continuous improvement in the educational environment requires identifying its strengths and weaknesses; therefore, monitoring students\u0026rsquo; perceptions of the educational environment at various stages of their training is critical.\u003c/p\u003e\n\u003cp\u003eFurther research is needed to statistically model the simultaneous relationship between the educational environment, learning approaches, and burnout. Given the lack of prior studies in medical education that examine these three components together, the present study is particularly significant. Furthermore, we believe the findings from this study can serve as a resource for developing interventions to improve the educational environment and support students in coping with burnout within medical schools.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eMBI\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eMaslach Burnout Inventory\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eASSIST\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eApproaches and Study Skills Inventory for Students\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eDREEM-TR\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eDundee Ready Education Environment Measure \u0026ndash; Turkish version\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eICD\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eInternational Classification of Diseases\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eGPA\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eGrade Point Average\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eEE\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEmotional Exhaustion\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eDP\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eDepersonalization\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003ePA\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePersonal Accomplishment\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval for this study was obtained from the Hacettepe University Senate Ethics Commission (Application No: 670055). All procedures performed in this study were conducted with the principles of the Declaration of Helsinki. Participation was voluntary, and informed consent was obtained electronically from all participants before completing the survey.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe anonymized dataset generated and analyzed during this study is not publicly archived but is available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthor Contributions: Conceptualization: [LO], [ME]; Methodology: [LO], [ME]; Data acquisition: [LO]; Formal analysis and investigation: [LO] ; Writing - original draft preparation: [LO]; Writing - review and editing: [LO], [ME]; Statistical Expertise: [LO] ; Supervision: [ME]\u003c/p\u003e\n\u003cp\u003eCorresponding Author: Correspondance to Lale Ozisik\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank all the students who participated in the survey.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors and Affiliations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLale Ozisik: Department of Internal Medicine, Faculty of Medicine, Hacettepe University. Ankara, Türkiye\u003c/p\u003e\n\u003cp\u003eMelih Elcin: Interprofessional Education (IPE), School of Health Sciences, Springfield College, Springfield, MA, USA\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAgerbo E, Gunnell D, Bonde JP, Mortensen PB, Nordentoft M. Suicide and occupation: the impact of socio-economic, demographic and psychiatric differences. Psychol Med. 2007;37(8):1131\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCollier R. Physician suicide too often brushed under the rug. 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Prediction of academic achievement based on learning strategies and outcome expectations among medical students. BMC Med Educ. 2019;19(1):99.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eI J: REVIEW OF RESEARCH IN LEARNING ENVIRONMENT. J Health Translational Med 2008(1):7\u0026ndash;V1111.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBiggs JB. Study Process Questionnaire Manual. Student Approaches to Learning and Studying: ERIC; 1987.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRamsden P. Learning from the student\u0026rsquo;s perspective. In: \u003cem\u003eLearning to Teach in Higher Education.\u003c/em\u003e edn. Edited by Ramsden P. New York: RoutledgeFalmer; 2003: 62\u0026ndash;84.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWeiss KB, Wagner R, Nasca TJ. Development, Testing, and Implementation of the ACGME Clinical Learning Environment Review (CLER) Program. J Grad Med Educ. 2012;4(3):396\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Burnout, medical students, learning approaches, educational environment, DREEM, ASSIST","lastPublishedDoi":"10.21203/rs.3.rs-8149384/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8149384/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e\u003cbr\u003e\nBurnout is a prevalent and growing issue among healthcare professionals, often emerging during medical education. Learning approaches and perceptions of the educational environment are key factors that may influence the development of burnout among medical students. This study aimed to explore the relationship between burnout levels, learning approaches, educational environment perceptions, and academic achievement in final-year medical students.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e\u003cbr\u003e\nA descriptive cross-sectional study was conducted among sixth-year students at Hacettepe University Faculty of Medicine, Türkiye. Data were collected electronically using a questionnaire including sociodemographic items, academic achievement, the Maslach Burnout Inventory (MBI), the Approaches and Study Skills Inventory for Students (ASSIST), and the Dundee Ready Education Environment Measure-Turkish version (DREEM-TR). Descriptive statistics, correlation analyses, and multivariate analyses were performed using SPSS 25, with p \u0026lt; 0.05 considered statistically significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u003cbr\u003e\nA total of 241 students participated (95.25%). Mean scores on the MBI were: Emotional Exhaustion 17.54±6.63, Depersonalization 7.14±3.53, and Personal Accomplishment 12.95±4.40. The majority of students (74.7%) adopted a strategic learning approach. Students with higher academic performance demonstrated higher strategic and lower surface learning approach scores. Perceptions of the educational environment correlated negatively with all burnout dimensions and the surface learning approach, and positively with strategic and deep learning approaches.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e\u003cbr\u003e\nMedical students’ burnout is significantly related to their learning approaches and perceptions of the educational environment. Promoting supportive educational environments and fostering effective learning strategies may reduce burnout and enhance academic and professional development.\u003c/p\u003e","manuscriptTitle":"Mapping Burnout in Medical Students: Interactions Between Learning Approaches and the Educational Environment","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-04 17:23:55","doi":"10.21203/rs.3.rs-8149384/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"114507aa-8e23-44a1-838e-cb142afce00d","owner":[],"postedDate":"December 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-06T05:39:34+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-04 17:23:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8149384","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8149384","identity":"rs-8149384","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}