Self-compassion as a well-being strategy against burnout among dentists: a controlled intervention study.

Self-compassion as a well-being strategy against burnout among dentists: a controlled intervention study - PMC Skip to main content An official website of the United States government Here's how you know Here's how you know Search Log in Primary site navigation Search Log in Search PMC Full-Text Archive Search in PMC Journal List User Guide As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health. Learn more: PMC Disclaimer | PMC Copyright Notice BMC Psychol . 2026 Apr 21;14:807. doi: 10.1186/s40359-026-04571-w Self-compassion as a well-being strategy against burnout among dentists: a controlled intervention study Onur Ucak Turer 1, ✉ , Mustafa Ozcan 1 , Bahar Alkaya 1 , Furkan Demirbilek 1 , H Gokhan Kayhan 1 , Gulcin Daglioglu 2 , Nazli Totik 3 , Gulsah Seydaoglu 3 , M Cenk Haytac 1 Author information Article notes Copyright and License information 1 Faculty of Dentistry, Department of Periodontology, Cukurova University, Adana, Turkey 2 Faculty of Medicine, Department of Medical Biochemistry, Cukurova University, Adana, Turkey 3 Faculty of Medicine, Department of Biostatistics, Cukurova University, Adana, Turkey ✉ Corresponding author. Received 2026 Feb 26; Accepted 2026 Apr 14; Collection date 2026. © The Author(s) 2026 Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ . PMC Copyright notice PMCID: PMC13227856  PMID: 42010743 Abstract Background The dental profession is inherently demanding, often leading to chronic stress and an increased risk of burnout among practitioners. Burnout has been associated with dysregulation of the hypothalamic-pituitary-adrenal axis, alterations in cortisol levels, and heightened inflammatory responses. Mindfulness-based self-compassion (MBCL) training has emerged as a promising approach for mitigating occupational stress and supporting well-being. Methods This controlled intervention study examined the associations between an 8-week MBCL program and biochemical markers (cortisol, interleukin-6, interleukin-1β, and oxytocin), as well as psychological outcomes (burnout, mindfulness awareness, self-compassion, and anxiety) in dentists. A total of 49 participants were allocated to either the MBCL training group or a control group. Results Following the intervention, participants in the MBCL group showed lower IL-6 and IL-1β levels, a more adaptive diurnal cortisol pattern, and higher oxytocin levels compared with controls. In addition, reductions in burnout and anxiety scores, as well as increases in self-compassion and mindfulness awareness, were observed in the MBCL group. Conclusions These findings suggest that MBCL training may be associated with improvements in psychological well-being and stress-related biochemical markers among dentists. However, given the non-randomized design and relatively small sample size, the results should be interpreted as preliminary and hypothesis-generating rather than causal. Trial registration ClinicalTrials.gov NCT06804720 registration date 20/01/2025. Supplementary Information The online version contains supplementary material available at 10.1186/s40359-026-04571-w. Keywords: Mindfulness, Self-compassion, Burnout, Dentistry, Cortisol, Interleukin-6, Interleukin-1β, Oxytocin Introduction The dental profession is highly demanding, characterized by high workload and sustained professional demands. Dentists are required to deliver high-quality care, where even minor errors may have significant consequences. This pressure to maintain high standards may contribute to increased anxiety and may affect their mental and emotional well-being. Numerous studies have investigated stress levels among dentists [ 1 – 4 ]. By definition, stress arises when an individual faces a perceived threat that exceeds their ability to cope effectively. In the context of dentistry, stress is often implicitly linked to emotions such as anxiety and worry [ 5 ]. Anxiety, which significantly influences both the performance and well-being of dentists, is a key component of the broader network involving stress and burnout [ 5 , 6 ]. According to a meta-analysis, there is a notable gap in the literature due to the lack of empirical evidence quantitatively demonstrating the impact of stress on dentists’ clinical performance [ 6 ]. To strengthen the physiological perspective, it is recommended that future research incorporates biomarkers useful in identifying stress and anxiety in dentists and dental students [ 6 ]. Additionally, the effects of rest and anxiety on dentists’ clinical performance remain underrepresented in the literature, despite being critically important areas. While current scientific evidence in this domain is still limited, it is steadily increasing. In this context, the relationship between dentists’ anxiety and their decision-making styles has been demonstrated and findings indicated that improving the ability to cope with challenging situations may enhance decision-making processes. Higher levels of anxiety in dentists may lead to decisions being based more on emotional states rather than objective clinical criteria [ 5 ]. Similarly, a study observed a significant deterioration in dentists’ diagnostic performance—particularly in sensitivity—when evaluating bitewing radiographs under time pressure. Diagnostic errors may compromise patient safety, especially when pathology is missed, and such errors also pose medicolegal risks for practicing dentists [ 7 ]. Supporting this, another study demonstrated that being a dental student has a notable impact on stress levels and a strong influence on executive functions such as decision-making and reasoning, which can be buffered by adequate rest [ 8 ]. Another important point to highlight is the bidirectional relationship between performance and perceived stress: as dentists’ performance declines due to stress or fatigue, their perception of stress intensifies, which in turn may further impair their performance [ 5 , 7 , 8 ]. In the presence of such anxiety, the need to balance technical precision with the interpersonal demands of patient care, while managing patient expectations and the inherent stress of the profession, often leads to heightened vulnerability to chronic stress and burnout. For many dental professionals, the weight of these responsibilities becomes an emotional burden, transforming what was once a passion for healing into an exhausting daily struggle. This emotional strain not only reflects the personal toll of sustained stress but also represents the early stages of a broader occupational hazard: burnout. Distinguishing between these emotional challenges and the clinical manifestation of burnout is important, as the former captures the subjective experience of distress while the latter defines a measurable syndrome. This reality highlights the importance of systematically examining the mental health risks within dentistry [ 9 – 15 ]. Empirical evidence indicates that the dental profession is inherently associated with high levels of stress, which substantially increases the risk of burnout [ 2 , 10 , 12 , 13 , 16 – 19 ]. The World Dental Federation (FDI) states that 32% to 51% of dentists across different countries exhibit symptoms of burnout [ 20 ]. Burnout syndrome manifests as a response to chronic occupational stress and is characterized by the triad of emotional exhaustion, depersonalization, and reduced personal accomplishment. Maslach and colleagues define burnout as the stage where work that was once important, meaningful, and stimulating turns into something unpleasant, unfulfilling, and devoid of meaning [ 21 ]. At this point, energy depletes into exhaustion, engagement shifts to cynicism, and effectiveness gives way to ineffectiveness [ 15 , 21 , 22 ]. While this description highlights the emotional and behavioral manifestations of burnout, a clearer understanding also requires distinguishing it from chronic stress, which, although related, represents a distinct process. For a better understanding of the processes within the body, it is crucial to clarify the relationship and differences between chronic stress and burnout. Although both chronic stress and burnout refer to psychological and emotional exhaustion, they involve distinct processes and effects. Chronic stress arises from long-term, continuous external factors that challenge the individual and is typically manifested through psychological and physiological symptoms such as anxiety, insomnia, and physical discomfort. Stress triggers biological responses by exceeding the individual’s capacity to adapt, mainly by exerting prolonged pressure on the hypothalamic-pituitary-adrenal (HPA) axis [ 23 , 24 ]. That is, when external or internal demands exceed homeostatic balance and effective coping capacity, the organism’s normal regulatory mechanisms become insufficient. Consequently, stress-response systems such as the hypothalamic-pituitary-adrenal (HPA) axis and the sympathetic nervous system are activated, resulting in physiological and psychological dysregulation. Burnout, by contrast, reflects emotional and psychological depletion within a specific domain, such as work. It is a process rather than a fixed outcome. Physiological markers can change over time, reflecting various stages of adaptation or dysregulation in response to chronic stress exposure. A review of the literature on burnout and related stress syndromes has led to the hypothesis that the fatigue symptoms in burnout are related to a state of hypocortisolism (abnormally low cortisol levels) and increased feedback sensitivity of the HPA axis [ 25 ]. Building on this distinction, evidence further suggests that burnout shares similarities with other stress-related conditions, potentially involving changes in the body’s stress response system, particularly in how the HPA axis regulates cortisol and responds to stress [ 26 – 28 ]. Under normal conditions, cortisol levels in plasma increase within 15 min following acute stress, but return to basal levels once effective coping is established. Permanent or repeated exposure to stressors with which one cannot adequately cope may contribute to a prolonged activation of the HPA axis, leading, in turn, to abnormal elevations in the levels of circulating glucocorticoids [ 29 – 31 ]. Over time, continued strain on the HPA axis due to chronic stress might lead to hypocortisolism, a condition characterized by abnormally low cortisol levels [ 25 , 26 , 32 ]. Psychological stress is generally associated with increased cortisol levels through activation of the HPA axis [ 23 ]. However, the relationship is not always linear; elevated cortisol cannot be interpreted as a definitive sign of stress, nor can low cortisol be assumed to indicate its absence. This complexity arises because cortisol secretion is influenced by multiple factors, including circadian rhythms, metabolic demands, and physical activity, in addition to psychological stress. As a result, individuals may display elevated cortisol levels even without perceived stress, whereas prolonged exposure to chronic stress may suppress HPA axis activity, leading to a blunted cortisol response [ 23 ]. Therefore, when relating cortisol levels to an individual’s stress state, it is essential to interpret the data within a broader physiological and contextual framework to ensure accurate representation. The diurnal cortisol slope (DCS) reflects the extent of change in cortisol levels from morning to evening [ 33 ]. In a healthy individual, cortisol levels peak in the early morning shortly after waking—this is known as the cortisol awakening response. Throughout the day, cortisol levels gradually decline, reaching their lowest point at night to facilitate restful sleep. In cases of burnout, this natural rhythm can become disrupted. Individuals experiencing chronic stress may exhibit a flattened cortisol curve, where the difference between morning and evening cortisol levels is minimal [ 26 , 28 , 33 – 35 ]. Alternatively, some may have elevated cortisol levels throughout the day or an inverted curve with higher levels at night. These abnormalities indicate that the body’s stress response system is dysregulated. A flattened or altered cortisol curve in burnout suggests that the HPA axis is not functioning optimally. This dysregulation can lead to various symptoms associated with burnout, such as fatigue, sleep disturbances and cognitive impairments including memory impairments [ 36 ], attention deficits [ 37 ], executive functioning deficits [ 38 ]. Understanding the changes in the cortisol curve is crucial for identifying burnout and implementing effective interventions [ 26 , 28 , 33 – 35 ]. Although several studies have reported associations between inflammatory responses and psychological distress, most investigations have focused on clinical mood disorders or general affective symptoms rather than occupational burnout as a distinct construct. As a result, burnout-related immune and inflammatory mechanisms have often been addressed indirectly, and the specific biological correlates of burnout remain insufficiently characterized. Consequently, there is a limited number of studies directly examining the relationship between elevated inflammatory cytokines and burnout [ 39 , 40 ]. This highlights a significant gap in the literature and underscores the importance of research exploring the psychoneuroimmunological dimensions of burnout. Studies have demonstrated a positive association between inflammatory markers and burnout, suggesting that chronic stress and emotional exhaustion may contribute to increased levels of pro-inflammatory cytokines such as Interleukin-6 (IL-6) and Interleukin-1β (IL-1β) [ 41 – 43 ]. IL-6, a primarily pro-inflammatory cytokine, is responsive to mental stress [ 44 ] and has been consistently shown in meta-analyses to be elevated across various stress-related and affective conditions [ 45 , 46 ] although it may not be sufficiently sensitive to distinguish clinical states [ 47 – 49 ]. A recent meta-analysis revealed a significant reduction in IL-6 levels following mindfulness-based interventions (MBIs), and this finding has been associated with improvements in psychological well-being and reductions in stress levels [ 50 ]. Additionally, IL-6 is frequently utilized as a surrogate marker for biologically active IL-1β, given the significant association between IL-1β and stress [ 41 , 44 , 51 ]. These findings underscore the critical interplay between chronic stress, inflammatory pathways, and mental health, highlighting the potential of cytokines such as IL-6 and IL-1β as biomarkers for stress-related conditions. Similarly, oxytocin (OT) has been shown to mitigate stress responses and mental health by reducing cortisol levels and enhancing emotional resilience [ 52 – 55 ]. Studies conducted in humans support the idea that OT attenuates the activity of the HPA axis, resulting in lower levels of cortisol under acute stress [ 56 , 57 ]. Studies evaluating the relationship between OT levels and burnout highlight the regulatory effects of this neuropeptide on stress response systems [ 53 – 55 , 58 , 59 ]. Research suggests that OT levels are generally lower in individuals experiencing burnout, which may be linked to hyperactivation of the HPA axis [ 56 , 57 ]. Such findings emphasize the potential connection between burnout and OT and suggest that OT may play a protective role in coping with stress. Such physiological changes can influence cognitive and clinical performance, especially in high-stress professions like dentistry, where performance under pressure is critical but understudied. Stress and fatigue can negatively affect dentists’ decision-making processes, motor skills, and overall clinical performance. It is known that stress can lead to distraction, increased likelihood of errors, and reduced job satisfaction [ 24 ]. These physiological changes may influence dentists’ clinical abilities, as high cortisol levels under stress can impair cognitive functions such as attention, memory, and decision-making. According to the FDI, dentists face elevated risks of burnout and mental health challenges, which have been exacerbated by the COVID-19 pandemic. The FDI has called on dental associations to take proactive measures to address this crisis [ 20 , 60 , 61 ]. In addition, FDI recommends mindfulness-based relaxation techniques as an effective strategy for combating burnout in dentistry. These techniques have been shown to reduce the physiological impacts of stress and assist dental professionals in better managing the challenges they face in the workplace [ 62 – 64 ]. Regular practice of these techniques can enhance dental professionals’ ability to cope with stress and mitigate the risk of burnout. According to the American Psychological Association, mindfulness is defined as “a moment-to-moment awareness of one’s experience without judgment”. It encourages acceptance of the present moment without evaluation [ 65 ] and encompasses three core skills: focused attention, open monitoring and loving-kindness/compassion [ 66 ]. Focused attention calms the mind by anchoring attention during strong emotions, while open monitoring broadens awareness, helping individuals recognize when they are caught in narratives and release resistance to the present moment. Loving-kindness and compassion provide support in the face of difficult life experiences. Whereas mindfulness is directed toward the experience itself, compassion is directed toward the experiencer who is suffering [ 66 – 69 ]. Mindfulness-based self-compassion (MBCL) training builds upon this foundation by encouraging individuals to approach their emotions and experiences with kindness, while establishing a mindful connection to the present moment. Mindfulness asks, “What is happening right now?” while self-compassion asks, “How can I support myself within this moment?” [ 63 , 66 , 67 , 69 ]. In this context, MBCL appears to be a promising approach to supporting the emotional processes of healthcare professionals in high-stress environments [ 67 – 69 ]. Compassion consists of five elements: recognizing suffering, understanding the universality of human suffering, feeling for the person suffering, tolerating uncomfortable feelings, and motivation to act/acting to alleviate suffering [ 70 ]. Self-compassion is considered an inward form of the compassion that is usually directed towards others [ 63 , 67 ]. Self-compassion enables individuals to approach their own challenges and shortcomings with kindness and understanding [ 67 , 71 , 72 ]. Self-compassion training utilizes the foundational principles of mindfulness to foster greater openness, sensitivity, and self-acceptance in individuals [ 71 – 74 ]. Research indicates a bidirectional relationship between these constructs: mindfulness supports the development of self-compassion, while self-compassion deepens mindfulness practice, which helps individuals manage stress more effectively [ 71 – 74 ]. The development of self-compassion fosters a non-judgmental and supportive attitude toward both oneself and others, promoting more balanced and effective interpersonal interactions, which is of great importance in the healthcare field [ 66 , 69 , 70 , 75 ]. Self-compassion is significantly and independently linked to well-being among healthcare professionals [ 74 , 76 , 77 ]. International professional bodies highlight compassion as a core ethical value: In the US, compassion is enshrined in the American Medical Association’s Principles of Medical Ethics, with Item 1 stating that “A physician shall be dedicated to providing competent medical services with compassion and respect for human dignity”, while in the UK, compassion is one of the six core values of the NHS constitution (Department of Health; DoH, 2013) [ 70 ]. Without self-compassion or compassion, healthcare professionals may struggle to respond to themselves and others with understanding, patience, and emotional balance. This may increase their vulnerability to psychological difficulties, while also reducing their clinical effectiveness [ 74 , 76 , 77 ]. Conversely, cultivating self-compassion strengthens perceived social support [ 78 ], emotional resilience, and mitigates the effects of chronic stress. This, in turn, contributes to more sustainable professional practice and improved quality of care [ 66 , 69 , 70 , 75 ]. From a theoretical perspective, the effects of mindfulness- and compassion-based interventions can be understood within established psychological frameworks, particularly stress-coping models and self-regulation theories. According to stress-coping frameworks, individuals’ appraisal of stressors and their perceived coping capacity play a central role in determining psychological and physiological responses to stress. In high-demand professions such as dentistry, maladaptive appraisal processes and self-critical coping styles may exacerbate stress-related outcomes, including burnout. MBCL may influence these processes by promoting adaptive emotion regulation, reducing self-critical responses, and enhancing self-compassionate coping strategies. From a self-regulation perspective, MBCL can be conceptualized as strengthening individuals’ capacity to monitor internal states, tolerate distress, and respond to challenging experiences with greater psychological flexibility. Through these mechanisms, MBCL may support more balanced stress responses at both psychological and physiological levels. Beyond its clinical relevance, the present study aims to contribute to the psychological literature by integrating psychoneuroimmunological markers with established psychological constructs such as burnout, mindfulness, and self-compassion. While previous research has largely examined these constructs using self-report measures, the current study extends this approach by incorporating objective biological indicators of stress regulation. In doing so, this study provides a more integrative perspective on how psychological processes may be linked to physiological stress mechanisms in high-demand professional contexts. By examining both psychological and biological dimensions simultaneously, the findings may offer preliminary insights into the potential pathways through which mindfulness- and compassion-based interventions are associated with stress regulation and well-being. Although studies have highlighted associations between stress-related psychological symptoms and changes in biochemical parameters, to our knowledge, this is one of the first studies to concurrently evaluate biochemical stress markers and psychological outcomes in dentists in relation to a structured MBCL intervention. Moreover, the impact of mindfulness-based self-compassion training programs on these variables has yet to be explored. Within this context, although burnout represents a clinically relevant outcome in this study, the primary focus was on stress-related biochemical mechanisms, with psychological variables examined as complementary outcomes. To investigate these relationships, we conducted a controlled intervention study involving dentists enrolled in an 8-week MBCL program. This assessment included daily cortisol curves, as well as salivary IL-6, IL-1β, and OT levels. Additionally, we measured burnout, self-compassion, and mindfulness awareness before and after the training. In this study, we hypothesized that, compared to the control group, the test group would exhibit lower IL-1β, IL-6, and cortisol levels, along with higher OT levels. Furthermore, as our secondary hypotheses, we anticipated that the test group would demonstrate increased self-compassion and mindfulness awareness, accompanied by reductions in burnout scores and trait anxiety. Methods Ethics approval and consent to participate The study protocol was approved by the Cukurova University, Faculty of Medicine Institutional Ethics Committee (03/06/2022; 123/53). For transparency purposes, the study was prospectively registered in a public clinical trial registry (ClinicalTrials.gov; NCT06804720 ; registration date: 20/01/2025). All procedures were performed in accordance with relevant guidelines and regulations and adhered to the Declaration of Helsinki. Prior to participation, all participants received comprehensive oral and written information about the study’s purpose, and written informed consent was obtained. Study design This study employed a non-randomized controlled intervention design with two parallel groups and was conducted at the Faculty of Dentistry, Çukurova University (Adana, Turkey) between March and December 2024. Due to the behavioral and educational nature of the MBCL intervention, blinding of participants and the instructor was not feasible. Accordingly, the study followed a non-randomized controlled intervention design without participant or instructor blinding. To mitigate potential sources of bias, objective biochemical outcome measures were included, saliva sampling procedures were standardized across groups, and laboratory analyses were conducted by trained personnel following standardized ELISA procedures, while statistical analyses were conducted using predefined statistical methods, as described in the Methods section. Study participants Participants were recruited on a voluntary basis from resident dentists in their final year of specialty training (3 to 4 years of experience in dentistry) at the Faculty of Dentistry, Çukurova University. A total of 49 volunteers participated in the study and were allocated to either the MBCL training group (test group, n = 25) or the control group ( n = 24) using a non-randomized parallel group design. No random allocation sequence was generated; group assignment was based on participants’ availability and the scheduling of the MBCL training. The sample size was determined by feasibility, reflecting the number of eligible resident dentists available during the study period at this single-center institution. As no formal a priori power calculation was conducted, the study was considered exploratory and aimed to generate preliminary effect size estimates to inform future larger-scale trials; accordingly, the findings should be interpreted as preliminary rather than confirmatory. Participants in the test group attended scheduled training sessions (2 h per week for 8 weeks). In contrast, the control group did not receive any intervention during the study period; however, they provided saliva samples at the same time intervals and completed the same questionnaires as the test group. Considering that prior mindfulness training experience could influence the study outcomes, attention was paid to ensure that participants had similar levels of mindful awareness (assessed by The Mindful Attention Awareness Scale, MAAS) before joining the study. In this study, the MAAS was used to index participants’ baseline levels of mindful awareness. The purpose of using the MAAS was to assess the degree of mindfulness awareness present in participants at the start of the intervention, ensuring that all participants had a comparable level of mindful awareness before the training. This allowed us to examine the effects of the mindfulness-based intervention (MBCL) on psychological and physiological outcomes, taking into account participants’ initial mindfulness awareness levels. However, it is important to note that while the MAAS provides a measure of mindful awareness, it does not directly reflect the full range of individual mindfulness experiences, which may differ based on personal practice and context. The inclusion criteria were as follows: ability to provide written informed consent, willingness to adhere to the study protocol. The individuals who received a diagnosis of mood disorders based on Diagnostic and Statistical Manual of Mental Disorders-DSM-5 criteria following a standard diagnostic assessment conducted by psychiatrists from the Department of Psychiatry at Cukurova University Faculty of Medicine were excluded from the study. In addition, the other exclusion criteria included: diabetes mellitus, pregnancy, obesity, cardiovascular diseases, a history of psychiatric disorders, use of medications affecting cortisol levels and heart rate variability, alcohol consumption, and non-compliance with the study protocol. Intervention All participants in the test group completed the 8-week training, consisting of 2-hour sessions per week, in accordance with the MBCL training protocol [ 68 ]. Training was conducted by one expert periodontist who is also an internationally certified MBCL instructor (O.U.T.). Each session included guided meditation practices, group discussions, and experiential exercises. Participants were encouraged to engage in daily home practice. The MBCL program content is summarized as follows [ 68 ]: Week 1: how we evolved; threat, impulse, and soothing systems Introduction to the evolutionary basis of emotional regulation, focusing on the threat, drive, and soothing systems. Week 2: building a compassionate relationship with resistance Exploration of resistance and avoidance patterns, with practices aimed at developing a compassionate stance toward difficult internal experiences. Week 3: habits, desire and patterns Identification of habitual behavioral and emotional patterns, and increasing awareness of automatic reactions. Week 4: internalizing compassion Practices designed to cultivate and internalize self-compassion as a stable inner resource. Week 5: self and others Examination of the relationship between self-compassion and compassion for others, and their role in interpersonal functioning. Week 6: cultivating happiness Development of positive affect and well-being through practices that enhance appreciation and emotional balance. Week 7: wisdom and compassion Integration of insight and compassion in responding to challenging experiences with greater psychological flexibility. Week 8: living with the heart Consolidation of skills learned throughout the program and their application in daily life and professional contexts. Data collection and outcome measures The primary outcomes of the study were biochemical markers of stress, including cortisol, IL-6, IL-1β, and oxytocin. Secondary outcomes included psychological measures, namely burnout (MBI-HSS), self-compassion (SCS/OSCS), mindfulness awareness (MAAS), and trait anxiety (STAI-T). Laboratory analyses Saliva sampling Saliva samples were obtained using the Salivette system (Sarstedt Co., Nümbrecht, Germany). All participants were informed about the procedures for saliva collection and the precautions to be taken during the process. As instructed, participants were asked to place the cotton swab from the tube under their tongue for 4 min to collect the sample. To prevent contamination of saliva with blood, participants were advised not to brush their teeth prior to sample collection and to rinse their mouths with plain water only. They were also instructed to handle the collected saliva samples with care and ensure proper adherence to the cold chain before delivering them to the researchers. The collected saliva samples were transported under cold chain conditions and stored at − 80 °C until biochemical analyses were conducted. Detailed procedural steps and sampling protocols are provided to ensure reproducibility; additional technical details regarding saliva collection and laboratory procedures are provided in the Supplementary Material. Saliva sample analysis To clarify the sampling design, saliva samples were collected for two distinct analytical purposes: (1) assessment of diurnal cortisol patterns (daily cortisol curve) and (2) evaluation of inflammatory and stress-related biomarkers. For the assessment of diurnal cortisol rhythm, saliva samples were collected at five time points throughout a single day (30 min after waking, 10:00 AM, 12:00 PM, 5:00 PM, and 10:00 PM). This sampling procedure was performed at two time points: one day before the start of the 8-week intervention and one day after its completion, allowing for the comparison of pre- and post-intervention diurnal cortisol profiles [ 79 ]. Salivary cortisol was estimated by solid phase enzyme-linked immunosorbent assay (ELISA) (DiaMetra, Boldon, UK) in ng/ml. The procedure was performed according to the manufacturer’s guidelines on saliva samples. Daily salivary cortisol measurements included the slope of the diurnal cortisol rhythm from wake-up to bedtime (calculated by subtracting the bedtime cortisol level from the wake-up level and dividing by the total time awake) and the average cortisol level (calculated as the area under the curve encompassing all cortisol data points throughout the day, divided by the total time awake). Cortisol measurements were performed as single assays for each sample, and repeated measurements (e.g., duplicate or triplicate assays) were not conducted. For the assessment of real-time cortisol (C-rt), IL-1β, IL-6, and OT, an additional saliva sample was collected one day before the commencement of MBCL training (T1) and one day after its completion (T2). To ensure consistency, both pre- and post-training saliva samples were collected on the same day of the week and at the same time of the day (2:30 PM) during the participants’ active clinical workweek. This sampling protocol was applied consistently across both the intervention and control groups. This sampling protocol is illustrated in Fig. 1 to facilitate understanding of the sampling timeline. Fig. 1. Open in a new tab A flow diagram showing the enrollment, allocation, analysis and follow-up of subjects involved in the study Salivary levels of the pro-inflammatory cytokines IL-1β (Coonkoon Biotechnology Co., China), IL-6 (DIAsource ImmunoAssays S.A., Belgium) and OT (Coonkoon Biotechnology Co., China) levels were measured in pg/ml via ELISA according to the instructions of the producer. Psychological assessment All psychological scales used in this study are standardized instruments with established validity and reliability. Psychological assessments were administered in the test group one day before (T1) and one day after the MBCL training (T2), and at corresponding time intervals in the control group to match those of the test group. Self-Compassion Scale (SCS) The SCS (developed by Neff) was created to assess the trait of self-compassion and consists of 26 items measuring the six components of self-compassion: Self-kindness, common humanity, mindfulness, self-judgement, isolation and overidentification [ 63 ]. The SCS used a 5-point Likert response scale from (1) almost never, not very often, sometimes, very often to (5) almost always. The self-judgement, isolation, and over-identification subscales are reverse scored. Overall SCS scores (OSCS) range from low (1.0–2.49) and moderate (2.5–3.5) to high (3.51–5.0) [ 63 , 74 ]. The calculation of the OSCS score was performed by reverse-scoring the negative subscale items (i.e., self-judgement, isolation, and over-identification) using the following scale: 1 = 5, 2 = 4, 3 = 3, 4 = 2, 5 = 1. A total mean score was then calculated by averaging all subscale scores. The Maslach Burnout Inventory-Human Services Survey (MBI-HSS) The MBI-HSS (developed by Maslach and Jackson) was used in this study [ 80 ]. The MBI-HSS is a 22-item instrument measuring three dimensions of burnout: Emotional Exhaustion, Depersonalization, and Personal Accomplishment. Participants rate the frequency of symptoms on a 7-point Likert scale ranging from 0 (Never) to 6 (Every day). Scoring is based on these three subscales as defined by the scale developer. The Mindful Attention Awareness Scale (MAAS) The MAAS (developed by Brown and Ryan) (mindful awareness) is a 15-item instrument measuring the general tendency to be attentive to and aware of present-moment experience in daily life. It has a single factor structure and yields a single total score [ 65 ]. Using a 6- point Likert-type scale (almost always to almost never), respondents’ rate how often they have experiences of acting on automatic pilot, being preoccupied, and not paying attention to the present moment. Anxiety The validated Turkish version of State-Trait Anxiety Inventory (STAI-T) form [ 81 ] was used to assess the self-reported anxiety levels [ 82 ]. The STAI-T (developed by Spielberger [ 82 ]) scale consists of 20 statements that ask people to describe how they generally feel. Each question is rated on a 4-point scale (not at all, somewhat, moderately so, very much so). The range of possible scores is between 20 and 80. STAI-T scores were interpreted using commonly accepted thresholds: 20–37: No or low anxiety 38–44: Moderate anxiety 45–80: High anxiety All psychological assessment instruments (MBI-HSS and STAI-T) are copyrighted measures and were administered with formal authorization from their respective rights holders. No scale items are reproduced in this manuscript. Statistical analysis Variables were summarized as mean ± standard deviation or median (25th–75th percentiles), as appropriate. Normality was assessed using the Shapiro-Wilk test. For comparisons of continuous variables between two independent groups, the Student’s t-test or Mann-Whitney U test was used according to data distribution. Paired comparisons within groups were performed using the paired samples t-test or Wilcoxon signed-rank test, as appropriate. Changes over time were evaluated using repeated measures ANOVA for normally distributed variables or the Friedman test for non-parametric data. When overall differences were significant, Bonferroni-adjusted post hoc comparisons were applied. Group, time, and group×time interaction effects were analyzed using repeated measures ANOVA or the F1-LD-F1 nonparametric model. The assumption of sphericity was assessed using Mauchly’s test; when violated, Greenhouse-Geisser or Huynh–Feldt corrections were applied (Greenhouse–Geisser for ε < 0.75; Huynh-Feldt for ε ≥ 0.75)86. Pearson correlation coefficients were calculated to evaluate relationships among normally distributed variables, while Spearman’s rank correlation was used for non-parametric data when necessary. In addition to the primary outcome analyses, an exploratory mediation analysis was conducted to examine whether oxytocin (OT) mediated the association between mindfulness awareness (MAAS; predictor) and self-compassion (OSCS; outcome). The “a” path (MAAS→OT), “b” path (OT→OSCS), and “c” path (MAAS→OSCS) were evaluated using linear regression models, and the significance of the indirect effect was assessed using the Sobel test. This mediation analysis was exploratory and hypothesis-generating in nature; therefore, the findings should be interpreted with caution. Statistical analyses were performed using IBM SPSS Statistics 20 (IBM Corp., Armonk, NY, USA) and RStudio (RStudio Team, 2020). The F1-LD-F1 model was implemented in R using the nparLD package. A two-tailed p value < 0.05 was considered statistically significant. To control for multiple comparisons across biochemical and psychological outcomes, Bonferroni-adjusted post hoc analyses were applied where appropriate, and the findings should be interpreted with consideration of potential type I error inflation. Results A total of 54 participants were screened and 49 eligible participants were scheduled for the study (Fig. 1 ). Twenty-five participants were assigned to the test group (13 female, 12 male) and twenty-four participants to the control group (12 female, 12 male). The mean age of the test group was 27.3 ± 2.2 for the test group and 27.0 ± 2.1 for the controls. Tables 1 and 2 present the differences in biochemical and psychological variables between the test and control groups at each time point. This analysis included both the assessment of variables and the calculation of changes between T1 and T2. Additionally, the group effect on changes over time was evaluated. Table 1. The differences OT, IL-1β, IL-6, daily cortisol and C-rt variables between the test and control groups at each time point Variable Time Group p p Test Control OT (pg/ml) T1 31.2 ± 3.4 31.3(29.6–33.3) 30.2 ± 3.8 31.5(28.9–33.3) 0.471 < 0.001 (Time*Group) < 0.001 (Time) T2 41.5 ± 3.8 39.5(39.0-45.3) 29.1 ± 3.0 30.0(27.3–31.2) < 0.001 p < 0.001 0.010 IL-1β (pg/ml) T1 148.6 ± 58.6 146.1(113.4-174.5) 149.8 ± 59.8 153.2(94.4-189.5) 0.826 < 0.001 (Time*Group) < 0.001(Time) T2 21.5 ± 16.4 13.1(11.6–19.5) 147.2 ± 42.2 152.8(104.6-178.2) < 0.001 p < 0.001 0.886 IL-6 (pg/ml) T1 6.5 ± 1.8 6.2(5.2–7.9) 6.6 ± 1.7 6.6(5.1–7.9) 0.897 < 0.001 (Time*Group) < 0.001(Time) T2 2.1 ± 0.9 1.7(1.5–2.6) 6.4 ± 1.8 5.9(5.0-7.9) < 0.001 p < 0.001 0.841 Cortisol T1 30 min 5.9 ± 0.8 5.9(5.5–6.5) 5.9 ± 1.1 6.1(5.0–7.0) 0.818 0.045 (Time*Group) < 0.001(Time) 10am 3.2 ± 0.5 Ϯ 3.2(2.9–3.6) 3.0 ± 0.7 Ϯ 3.2(2.5–3.5) 0.603 12pm 2.2 ± 0.5 Ϯ,φ 2.2(1.8–2.4) 2.4 ± 0.3 Ϯ,φ 2.3(2.1–2.5) 0.072 17pm 2.3 ± 0.4 Ϯ,φ 2.4(2.0-2.6) 2.4 ± 0.3 Ϯ,φ 2.4(2.1–2.6) 0.697 22pm 2.5 ± 0.5 Ϯ,φ 2.5(2.1–2.8) 2.3 ± 0.4 Ϯ,φ 2.2(2.0-2.5) 0.110 p < 0.001 < 0.001 Cortisol T2 30 min 9.2 ± 0.6 9.3(8.9–9.7) 5.9 ± 0.9 6.0(5.4–6.4) < 0.001 < 0.001 (Time*Group) < 0.001(Time) 10am 4.3 ± 0.5 4.3(4.0-4.8) 3.1 ± 0.5 3.3(2.8–3.5) < 0.001 12pm 3.9 ± 0.3 Ϯ 3.9(3.6–4.1) 2.3 ± 0.4 Ϯ,φ 2.2(2.1–2.5) < 0.001 17pm 2.1 ± 0.4 Ϯ,φ 1.9(1.8–2.5) 2.2 ± 0.3 Ϯ,φ 2.1(2.0-2.4) 0.043 22pm 0.8 ± 0.2 Ϯ,φ,ϒ 0.8(0.6-1.0) 2.2 ± 0.3 Ϯ,φ 2.2(2.1–2.4) < 0.001 p < 0.001 < 0.001 C-rt T1 24.2 ± 6.5 23.8(18.4–30.9) 24.0 ± 6.0 22.0(19.3–28.3) 0.984 < 0.001 (Time*Group) < 0.001(Time) T2 12.0 ± 1.6 12.1(10.5–13.7) 22.8 ± 7.0 23.8(15.5–28.9) < 0.001 p < 0.001 0.241 Open in a new tab Data was expressed as mean±standard deviation, median(IQR 25−75 ) Ϯ p < 0.05 between 30 min φ p < 0.05 between 10am ϒ p < 0.05 between 12pm Table 2. The differences MAAS, OSCS and STAI variables between the test and control groups at each time point Variable Time Group p p Test Control MAAS T1 3.4 ± 0.4 3.4(3.2–3.7) 3.5 ± 0.3 3.5(3.3–3.8) 0.229 < 0.001 (Time*Group) < 0.001(Time) T2 4.3 ± 0.3 4.3(4.1–4.5) 3.5 ± 0.3 3.5(3.2–3.7) < 0.001 p < 0.001 0.127 Maslach-emotion T1 3.7 ± 0.6 3.9(3.1–4.1) 3.6 ± 0.8 3.9(2.9–4.3) 0.793 < 0.001 (Time*Group) < 0.001(Time) T2 1.4 ± 0.1 1.3(1.3–1.6) 3.6 ± 0.7 3.4(3.0-4.1) < 0.001 p < 0.001 0.418 Maslach-depersonalization T1 1.9 ± 0.3 1.9(1.7–2.3) 2.0 ± 0.3 2.1(1.7-0.22) 0.926 < 0.001 (Time*Group) < 0.001(Time) T2 0.5 ± 0.2 0.4(0.3–0.7) 2.0 ± 0.3 2.1(1.7–2.2) < 0.001 p < 0.001 0.820 Maslach-success T1 3.2 ± 0.5 3.0(2.9–3.6) 3.3 ± 0.5 3.4(2.9–3.6) 0.635 < 0.001 (Time*Group) < 0.001(Time) T2 5.1 ± 0.4 5.1(4.7–5.6) 3.3 ± 0.4 3.5(3.0-3.7) < 0.001 p < 0.001 0.194 OSCS T1 2.2 ± 0.1 2.2(2.1–2.2) 2.0 ± 0.1 2.1(1.9–2.1) 0.001 < 0.001 (Time*Group) < 0.001(Time) T2 3.8 ± 0.1 3.9(3.8–3.9) 2.0 ± 0.2 2.0(1.9–2.1) < 0.001 p < 0.001 0.584 Self-kindness T1 1.8 ± 0.3 1.7(1.6–2.2) 1.8 ± 0.4 1.7(1.5–2.2) 0.960 < 0.001 (Time*Group) < 0.001(Time) T2 3.6 ± 0.4 3.6(3.4–3.8) 2.0 ± 0.4 2.1(1.5–2.4) < 0.001 p < 0.001 0.247 Self-judgment ψ T1 2.2 ± 0.4 2.2(2.0-2.4) 2.3 ± 0.4 2.1(1.9–2.4) 0.826 < 0.001 (Time*Group) < 0.001(Time) T2 4.2 ± 0.4 4.2(3.9–4.5) 2.0 ± 0.3 2.1(1.7–2.2) < 0.001 p < 0.001 0.009 Common humanity T1 1.8 ± 0.1 1.8(1.7–1.8) 1.7 ± 0.1 1.8(1.7–1.8) 0.545 < 0.001 (Time*Group) < 0.001(Time) T2 3.5 ± 0.3 3.4(3.2–3.7) 1.8 ± 0.1 1.8(1.7–1.8) < 0.001 p < 0.001 0.026 Isolation ψ T1 2.2 ± 0.4 2.3(2.1–2.6) 2.1 ± 0.4 2.1(1.9–2.1) 0.084 < 0.001 (Time*Group) < 0.001(Time) T2 4.0 ± 0.2 4.1(4.1–4.1) 2.0 ± 0.2 1.9(1.9–2.1) < 0.001 p < 0.001 0.187 Mindfulness T1 2.2 ± 0.3 2.2(1.9–2.4) 2.2 ± 0.3 2.2(1.8–2.5) 0.794 < 0.001 (Time*Group) < 0.001(Time) T2 3.7 ± 0.3 3.8(3.6–3.9) 2.2 ± 0.3 2.4(1.8–2.5) < 0.001 p < 0.001 0.866 Over-identification ψ T1 2.4 ± 0.2 2.5(2.3–2.6) 2.2 ± 0.4 2.2(2.0-2.7) 0.071 < 0.001 (Time*Group) < 0.001(Time) T2 4.0 ± 0.3 4.1(3.9–4.2) 2.2 ± 0.6 2.0(1.9–2.7) < 0.001 p < 0.001 0.268 STAI T1 51.6 ± 5.4 51 (48–56) 50.8 ± 5.6 51(47–55) 0.590 < 0.001 (Time*Group) < 0.001(Time) T2 25.3 ± 4.0 24(23–28) 51.4 ± 4.6 51(47–55) < 0.001 p < 0.001 0.446 Open in a new tab Data was expressed as mean±standard deviation, median (IQR 25−75 ) MAAS The Mindful Attention Awareness Scale, MBI Maslach Burnout Inventory, STAI State-Trait Anxiety Inventory, OSCS Overall Self-Compassion ψ Reverse scored subscale. Within-group effects (Time): p -values test the change from T1 to T2. Between-group effects (Group): p -values compare the test versus control group at each time point Although OT, IL-6, IL-1β, and C-rt levels were comparable between the test and control groups at T1, statistically significant between-group differences were observed at T2 ( p < 0.001 for all parameters), with higher changes observed in the test group (Table 1 ). Correlations between percentage changes from T1 to T2 were significant for cortisol and IL-6 ( r = 0.70) and for cortisol and IL-1β ( r = 0.72) ( p < 0.001 for both), indicating a strong association between these variables. Although the mean change in oxytocin levels in the control group appears small, the observed statistical significance reflects consistent within-subject directional changes rather than large between-subject differences. Similarly, the self-reported psychological variables, including SCS, MAAS, MBI, and STAI, were similar at baseline (T1) in both groups. The comparability and similarity of the MAAS scores were confirmed by the absence of a statistically significant difference between groups at baseline (T1), indicating that participants commenced the study with comparable levels of mindful awareness. However, at (T2), there was a significant decrease in MBI, and STAI scores, as well as a significant increase in OSCS, and MAAS in the test group, with no changes observed in the control group ( p < 0.001) (Table 2 ). The OSCS scores are presented in detail in Supplementary Table 1. The changes in daily cortisol levels and the distribution between groups over time are presented in Fig. 2 . Fig. 2. Open in a new tab Distribution of daily cortisol levels (diurnal cortisol slope) among groups (Group 1 = Test group; Group 2 = Control group) across five time points during the day (30 min after waking, 10:00 AM, 12:00 PM, 5:00 PM, and 10:00 PM). The first panel represents the diurnal cortisol curve obtained before the intervention, and the second panel represents the curve obtained after the intervention Exploratory analysis An additional mediation analysis was conducted to explore potential pathways linking mindfulness (MAAS) and oxytocin (OT), given emerging evidence suggesting a relationship between mindfulness-related processes and oxytocin-mediated stress regulation. This analysis was considered exploratory and hypothesis-generating and should therefore be interpreted with caution. Prior to the mediation analysis, Pearson correlation analyses were conducted among the relevant variables. Significant correlations were observed between OT and MAAS ( r = 0.67), OT and OSCS ( r = 0.87), and MAAS and OSCS ( r = 0.79) (all p < 0.001). Mediation analysis revealed a significant total effect of MAAS on OSCS (β = 0.69, p < 0.001). The path from MAAS to OT was significant (β = 9.62, p < 0.001), as was the path from OT to OSCS (β = 0.08, p < 0.001). After including OT in the model, the direct effect of MAAS on OSCS remained statistically significant (β = 1.468, p < 0.001), indicating a partial mediation effect. Unstandardized regression coefficients are reported (Fig. 3 ). Fig. 3. Open in a new tab Mediation model illustrating the relationship between mindful awareness (MAAS), oxytocin (OT), and overall self-compassion (OSCS). ⁕ p < 0.001. MAAS: Mindful Attention Awareness Scale; OT: Oxytocin; OSCS: Overall Self-Compassion Scale. Note: The self-judgment , isolation , and over-identification subscales are reverse-scored when calculating OSCS , so that higher scores reflect greater overall self-compassion Path a (MAAS ➜ Oxytocin): The estimated coefficient for the direct effect of MAAS on OT is 9.62 (CI 95%: 6.67–12.58) ( p < 0.001). This finding suggests that, on average, a one-unit increase in MAAS is associated with a 9.62 unit increase in OT, assuming a linear relationship. The standardized coefficient is 0.674, which indicates a moderate positive relationship between MAAS and OT. Path b (Oxytocin ➜ OSCS): The estimated coefficient for the direct effect of OT on OSCS is 0.081 (95% CI:0.06–0.10) ( p < 0.001). This suggesting that, on average, a one-unit increase in OT is associated with a 0.081 unit increase in OSCS, assuming a linear relationship. The standardized coefficient is 0.620, which indicates a moderate positive relationship between OT and OSCS. Path c (MAAS ➜ OSCS): The estimated coefficient for the direct effect of MAAS on OSCS without considering the mediation effect is 0.692 (95% CI:0.41–0.98) ( p < 0.001). This suggests that, on average, a one-unit increase in MAAS is associated with a 0.692 unit increase in OSCS, assuming a linear relationship. The standardized coefficient is 0.372, indicating a weak to moderate positive relationship between MAAS and OSCS. Indirect effect (a*b): The estimated indirect effect of MAAS on OSCS through OT is 0.776 (95% CI: 0.47–1.08) ( p < 0.001). In other words, OT significantly mediated the relationship between MAAS and OSCS. This suggests that, on average, a one-unit increase in MAAS results in a 0.776 unit increase in OSCS indirectly through its effect on OT. The standardized indirect effect is 0.418, which indicates a moderate positive relationship. Total effect (c + a*b): The estimated total effect of MAAS on OSCS, considering both the direct and indirect effects, is 1.468 (95% CI:1.15–1.79) ( p < 0.001). This suggests that, on average, a one-unit increase in MAAS is associated with a 1.468 unit increase in OSCS when considering both the direct and indirect effects. The standardized total effect is 0.790, which indicates a moderate positive relationship. The hypothesis concerning the presence of a mediating effect was confirmed through the implementation of a Sobel test. The result of this test was a Sobel value of 4.83 and a p -value of less than 0.001. This outcome indicates that a mediating effect is indeed present. Mediation analysis was conducted without a strong theoretical framework and should therefore be regarded as exploratory. The findings highlight potential associations rather than definitive causal pathways. Discussion Dentistry is a high-demand profession associated with elevated levels of stress, anxiety, and burnout. In this study, we investigated the associations between an 8-week MBCL intervention and both psychological outcomes and stress-related biochemical markers in dentists. At the end of the intervention, no changes were observed in the control group, whereas significant changes in both psychological and biochemical measures were observed in the intervention group. To our knowledge, this is one of the first studies to prospectively evaluate both inflammatory and stress-related biomarkers alongside psychological outcomes in dentists in relation to a structured MBCL intervention. Although previous studies have investigated the relationship between burnout and cortisol levels, the findings have been inconsistent [ 27 , 83 – 85 ]. In the present study, both groups showed similar post-awakening cortisol levels at baseline; however, following MBCL training, the intervention group demonstrated a significant increase compared to the control group. Although this finding may initially appear counterintuitive, it is more plausibly interpreted as reflecting a normalization of the cortisol awakening response and a rebalancing of the HPA axis rather than heightened stress. This interpretation is consistent with evidence suggesting that mindfulness-based interventions may enhance adaptive physiological regulation and HPA axis functioning. A potential explanation involves a dissociation between the phasic and tonic components of the sympathetic stress response. Supporting this interpretation, Queirolo et al. [ 86 ] demonstrated that even brief interventions can reduce phasic, reactive stress responses while enhancing tonic, more stable autonomic regulation. Within this framework, the observed increase in cortisol may reflect not stress exacerbation but a shift toward more adaptive and regulated physiological functioning, consistent with the psychological improvements observed in the intervention group. Consistent with this interpretation, the diurnal cortisol slope (DCS) improved in the intervention group following training, whereas flatter patterns were observed in the control group. Flattened diurnal cortisol rhythms have been associated with poorer mental and physical health outcomes [ 87 – 91 ]. Despite inconsistencies in the literature due to methodological variability, including variations in study populations, differences and imprecision in DCS measurement and modeling strategies, and uncertainties in the assessment of health outcomes [ 92 ], the observed improvement in DCS in the intervention group may indicate more adaptive stress regulation. To minimize potential metabolic confounding effects on cortisol measurements, standardized sampling procedures were implemented in accordance with established guidelines [ 79 ]. In addition to cortisol dynamics, reductions in IL-6 and IL-1β levels were observed in the intervention group following MBCL training. Although baseline salivary IL-6 and IL-1β levels were similar between groups, post-intervention measurements revealed significant decreases in both cytokines in the intervention group. These changes were accompanied by improvements in psychological measures observed following MBCL training. These findings are consistent with previous research indicating that psychological stress is associated with increased inflammatory activity, and that stress-reduction interventions may promote more balanced inflammatory responses [ 46 , 93 – 96 ]. Furthermore, the observed reductions in IL-6 and IL-1β alongside a more balanced cortisol pattern support the interplay between cortisol and pro-inflammatory cytokines in stress regulation and immune function [ 41 , 50 , 51 , 97 – 100 ]. Oxytocin (OT) has been implicated in the modulation of stress-related responses and the regulation of emotional and physiological processes [ 96 , 101 ]. In the present study, participants in the intervention group demonstrated increased salivary OT levels following MBCL training, whereas lower levels were observed in the control group. These changes, together with improvements in self-compassion and mindfulness, suggest a potential association between compassion-based processes and neuroendocrine regulation. Mechanistically, OT is known to suppress HPA axis activity under stress, thereby reducing cortisol release, whereas chronic stress may impair this system by suppressing OT production and reducing receptor sensitivity [ 53 , 102 ]. In addition, OT has been linked to the regulation of inflammatory processes, including associations with lower IL-6 levels [ 98 – 100 ]. Psychosocial interventions, particularly mindfulness- and compassion-based practices, have been associated with increased OT levels and reduced inflammatory activity [ 102 , 103 ]. Furthermore, self-compassion, conceptualized as a form of self-directed support, has been suggested to stimulate OT release [ 103 , 104 ]. Through mechanisms such as mindfulness and self-kindness, individuals may become more aware of their emotional states and respond with greater internal support [ 66 , 75 ]. In addition, self-compassion has been suggested to act as a protective factor against inflammatory responses and to be linked to more favorable long-term health outcomes [ 104 – 108 ]. Taken together, these findings suggest a potential role of OT as a link between psychological processes and stress-related physiological regulation. The psychological findings of this study are consistent with existing literature demonstrating that mindfulness-based interventions can reduce anxiety and burnout while enhancing self-compassion and mindfulness awareness in healthcare professionals. In the present study, significant reductions in anxiety and burnout scores were observed alongside increases in self-compassion and mindfulness levels in the intervention group. Importantly, the integration of both subjective (self-report scales) and objective (biochemical markers) measures provides a more comprehensive understanding of the potential effects of MBCL interventions. Mindfulness-based interventions are widely recognized for their effectiveness in improving psychological well-being in both clinical and non-clinical populations [ 108 , 109 ]. The findings of the present study align with previous research demonstrating that MBIs reduce psychological distress and enhance emotional well-being in healthcare professionals [ 105 – 107 , 110 ]. Importantly, unlike many prior studies relying primarily on self-report measures, the present study integrates both psychological and biological markers, providing a more comprehensive perspective on stress regulation in high-demand professional contexts such as dentistry. In addition, workplace factors such as perceived social support may influence stress regulation among healthcare professionals. Within this context, MBIs may represent a practical and adaptable approach that can be integrated into clinical routines, potentially contributing to more sustainable stress management strategies in demanding work environments [ 111 , 112 ]. Furthermore, self-compassion may contribute to patient-centered care by supporting more balanced and effective clinician–patient interactions. By enhancing emotional regulation and self-awareness, self-compassion may help improve both interpersonal communication and overall treatment experiences [ 113 ]. Taken together, these findings suggest that MBCL training may be associated with improvements in both psychological well-being and physiological stress regulation in dentists. The integration of psychological and biological markers underscores the potential of mindfulness- and compassion-based interventions as a comprehensive approach to stress regulation in high-demand professional settings. Limitations This study has several limitations. First, the absence of participant and provider blinding may have introduced expectation or performance bias. Second, the current study does not incorporate autonomic nervous system measures, such as heart rate variability or electrodermal activity, which are increasingly recognized as objective markers of stress and resilience [ 83 – 85 ]. Third, participants were self-selected on a voluntary basis, which may have resulted in a sample composed of highly motivated individuals who could be more likely to report favorable intervention outcomes. In addition, psychological outcomes were assessed using self-report instruments, which may be subject to response bias and social desirability effects, and therefore should be interpreted with caution. Fourth, the follow-up period was limited to the duration of the training, which restricts the ability to evaluate the long-term sustainability of the observed effects. An additional limitation is that diurnal cortisol profiles were obtained from a single day at each time point. Given that intra-individual variability in cortisol levels can be substantial due to various confounding factors, single-day measurements may not fully capture stable cortisol patterns. This should be considered when interpreting the findings, in line with expert consensus recommendations (e.g., Stalder et al.) [ 79 ]. A further important limitation is the non-randomized design of the study, which may introduce allocation bias and limit the strength of causal inference. Accordingly, causal inferences cannot be established, and the observed associations should be interpreted as preliminary. Although baseline characteristics between groups were comparable, future studies should employ randomized allocation procedures in larger and more diverse samples of dentists, taking into account variations in age, gender, and professional experience. Additionally, the relatively small sample size, determined by feasibility rather than formal power analysis, may limit the detection of smaller effects and the generalizability of the findings. Incorporating a broader range of physiological biomarkers alongside extended follow-up periods would further strengthen the evidence base and help clarify the sustained psychophysiological effects of mindfulness-based interventions. Finally, while the mediation analysis offers noteworthy insights, the findings should be interpreted with caution. In the absence of a strong theoretical framework supporting the tested pathways, the analysis should be considered exploratory, providing preliminary indications of potential associations rather than definitive causal mechanisms. Future research with larger samples and more robust theoretical models will be essential to further elucidate and validate these relationships. Taken together, these limitations underscore the need for cautious interpretation of the findings and highlight the importance of future randomized and longitudinal studies to confirm and extend the present results. Clinical Implications When these findings are considered together, it may be suggested that dentists with higher levels of self-compassion may be less vulnerable to increased inflammation following occupational stress and may be associated with more favorable psychological outcomes, such as reduced burnout, and anxiety. On the other hand, dentists with lower levels of SC may be particularly vulnerable to the adverse effects of stress. Similar to practicing dentists, perceived stress among dental students is also notably high and tends to increase progressively throughout their academic journey, peaking during the clinical years. Reducing this stress requires the development of effective management strategies and a re-evaluation of educational programs to foster more supportive learning environments. In this context, the implementation of MBI training during the dental education period may constitute a valuable preventive strategy, with the potential to yield long-term benefits for psychological resilience and professional well-being [ 114 ]. MBIs, by cultivating self-compassion, may offer not only practical tools for stress management but also a deeper psychological grounding for both practicing dentists and those still in training [ 115 ]. Programs such as MBCL can be recommended as an effective approach to strengthen psychological resilience and enable dentists to cope with workload more effectively [ 111 ]. The field of objective stress evaluation in dentistry is still in its infancy and there is a growing need for evidence-based interventions aimed at prevention and support. Our findings contribute to this emerging area, but more comprehensive, multi-modal approaches including physiological, psychological, and behavioral assessments are needed [ 12 ]. Conclusion In conclusion, the psychological and biochemical effects of MBCL training on supporting the mental health of dentists were evaluated in this study. Post-intervention, the test group showed improvements in stress-related, anxiety, and burnout scores, as well as increases in self-compassion. These findings were accompanied by changes in DCS patterns, reductions in IL-1β and IL-6 levels, and increased OT levels [ 116 , 117 ]. Given the non-randomized design and relatively small sample size, these findings should be interpreted as preliminary and hypothesis-generating rather than causal. Supplementary Information Supplementary Material 1. (16.5KB, docx) Supplementary Material 2. (15.3KB, docx) Acknowledgements The authors thank Emir Ozcelik for his valuable help during study. Abbreviations MBCL Mindfulness-Based Compassionate Living MBI-HSS Maslach Burnout Inventory – Human Services Survey MAAS Mindful Attention Awareness Scale STAI-T State-Trait Anxiety Inventory – Trait form SCS Self-Compassion Scale OSCS Overall Self-Compassion Score IL-6 Interleukin-6 IL-1β Interleukin-1 beta OT Oxytocin HPA axis Hypothalamic–Pituitary–Adrenal axis DCS Diurnal Cortisol Slope Authors’ contributions O.U.T., M.O. and M.C.H. developed the concept of the study. B.A., F.D. and H.G.K. followed the sample population and collected the questionnaires. O.U.T. performed mindfulness-based compassion living training for the study population. G.D. performed biochemical analysis. N.T. and G.S. were performed the statistical analysis. All authors reviewed the final manuscript. Funding This study was funded by the Çukurova University Scientific Research Projects Committee (Project No: TSA-2024-16877). Data availability The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Declarations Ethics approval and consent to participate The study protocol was approved by the Ethics Committee of Cukurova University Faculty of Medicine (Approval No: 123/53; Date: 03/06/2022). For transparency, the study was prospectively registered in a public clinical trial registry (ClinicalTrials.gov; NCT06804720 ; registration date: 20/01/2025). All procedures were performed in accordance with relevant guidelines and regulations and adhered to the Declaration of Helsinki. Prior to participation, all participants received comprehensive oral and written information about the study’s purpose, and written informed consent was obtained. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Footnotes Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. References 1. Cooper CL, Hingley P. Occupational stress among general practitioners. J Manage Med. 1988;3(2):96–106. [ Google Scholar ] 2. Denton D, Newton J, Bower E. Occupational burnout and work engagement: a national survey of dentists in the United Kingdom. Br Dent J. 2008;205(7):E13–13. [ DOI ] [ PubMed ] [ Google Scholar ] 3. Möller A, Spangenberg J. Stress and coping amongst South African dentists in private practice. J Dent Association South Afr = Die Tydskrif van die Tandheelkundige Vereniging van Suid-Afrika. 1996;51(6):347–57. [ PubMed ] [ Google Scholar ] 4. Osborne D, Croucher R. Levels of burnout in general dental practitioners in the south-east of England. Br Dent J. 1994;177(10):372–7. [ DOI ] [ PubMed ] [ Google Scholar ] 5. Chipchase SY, Chapman HR, Bretherton R. A study to explore if dentists’ anxiety affects their clinical decision-making. Br Dent J. 2017;222(4):277–90. [ DOI ] [ PubMed ] [ Google Scholar ] 6. Plessas A, Delgado MB, Nasser M, Hanoch Y, Moles DR. Impact of stress on dentists’ clinical performance. A systematic review. Community Dent Health. 2018;35(01):9–15. [ DOI ] [ PubMed ] [ Google Scholar ] 7. Plessas A, Nasser M, Hanoch Y, O’Brien T, Delgado MB, Moles D. Impact of time pressure on dentists’ diagnostic performance. J Dent. 2019;82:38–44. [ DOI ] [ PubMed ] [ Google Scholar ] 8. Queirolo L, Roccon A, Piovan S, Ludovichetti FS, Bacci C, Zanette G. Psychophysiological wellbeing in a class of dental students attending dental school: anxiety, burnout, post work executive performance and a 24 hours physiological investigation during a working day. Front Psychol. 2024;15:1344970. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 9. Collin V, Toon M, O’Selmo E, Reynolds L, Whitehead P. A survey of stress, burnout and well-being in UK dentists. Br Dent J. 2019;226(1):40–9. [ DOI ] [ PubMed ] [ Google Scholar ] 10. da Silva Moro J, Soares JP, Massignan C, Oliveira LB, Ribeiro DM, Cardoso M, de Luca Canto G, Bolan M. Burnout syndrome among dentists: A systematic review and meta-analysis. J Evidence-Based Dent Pract. 2022;22(3):101724. [ DOI ] [ PubMed ] [ Google Scholar ] 11. Moore R, Brødsgaard I. Dentists’ perceived stress and its relation to perceptions about anxious patients. Commun Dent Oral Epidemiol. 2001;29(1):73–80. [ PubMed ] [ Google Scholar ] 12. Plessas A, Witton R, Paisi M, Ellwood F, McColl E. Using the Mental Health Wellness Framework in dental practice. Bdj Team. 2022;9(10):10–2. [ Google Scholar ] 13. Sabitova A, McGranahan R, Altamore F, Jovanovic N, Windle E, Priebe S. Indicators associated with job morale among physicians and dentists in low-income and middle-income countries: a systematic review and meta-analysis. JAMA Netw open. 2020;3(1):e1913202–1913202. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 14. Singh P, Aulak D, Mangat S, Aulak M. Systematic review: factors contributing to burnout in dentistry. Occup Med. 2016;66(1):27–31. [ DOI ] [ PubMed ] [ Google Scholar ] 15. Søvold LE, Naslund JA, Kousoulis AA, Saxena S, Qoronfleh MW, Grobler C, Münter L. Prioritizing the mental health and well-being of healthcare workers: an urgent global public health priority. Front public health. 2021;9:679397. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 16. Gorter RC, Freeman R. Burnout and engagement in relation with job demands and resources among dental staff in Northern Ireland. Commun Dent Oral Epidemiol. 2011;39(1):87–95. [ DOI ] [ PubMed ] [ Google Scholar ] 17. Lee S, Oguienko O, Song B, Sunderji S, Wong J, Zhao X, Versloo J, Azarpazhoo A. Risk Factors for Burnout among Dentists: An Evidence-Based Study of the Literature. Dentistry. 2011. Toronto: University of Toronto Faculty of Dentistry. https://www.dentistry.utoronto.ca/system/files/y3_2011.pdf 18. Lovas JG, Lovas DA, Lovas PM. Mindfulness and professionalism in dentistry. J Dent Educ. 2008;72(9):998–1009. [ PubMed ] [ Google Scholar ] 19. Negucioiu M, Buduru S, Ghiz S, Kui A, Șoicu S, Buduru R, Sava S. Prevalence and Management of Burnout Among Dental Professionals Before, During, and After the COVID-19 Pandemic: A Systematic Review. In: Healthcare: 2024;12(23):2366–85. [ DOI ] [ PMC free article ] [ PubMed ] 20. Federation FWD. Mental health and well-being for oral health professionals and dental students. Int Dent J. 2024;74(1):159. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 21. Maslach C, Schaufeli WB, Leiter MP. Job burnout. Ann Rev Psychol. 2001;52(1):397–422. [ DOI ] [ PubMed ] [ Google Scholar ] 22. Hill AP, Curran T. Multidimensional perfectionism and burnout: A meta-analysis. Personality social Psychol Rev. 2016;20(3):269–88. [ DOI ] [ PubMed ] [ Google Scholar ] 23. Boucher P, Plusquellec P. Acute stress assessment from excess cortisol secretion: Fundamentals and perspectives. Front Endocrinol. 2019;10:749. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 24. Chrousos GP. Stress and disorders of the stress system. Nat reviews Endocrinol. 2009;5(7):374–81. [ DOI ] [ PubMed ] [ Google Scholar ] 25. Heim C, Ehlert U, Hellhammer DH. The potential role of hypocortisolism in the pathophysiology of stress-related bodily disorders. Psychoneuroendocrinology. 2000;25(1):1–35. [ DOI ] [ PubMed ] [ Google Scholar ] 26. Jonsdottir IH, Sjörs Dahlman A. Mechanisms in endocrinology: Endocrine and immunological aspects of burnout: a narrative review. Eur J Endocrinol. 2019;180(3):R147–58. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 27. Mommersteeg PM, Heijnen CJ, Kavelaars A, van Doornen LJ. The HPA-axis and immune function in burnout. Prog Brain Res. 2007;167:281–5. [ DOI ] [ PubMed ] [ Google Scholar ] 28. Pilger A, Haslacher H, Meyer BM, Lackner A, Nassan-Agha S, Nistler S, Stangelmaier C, Endler G, Mikulits A, Priemer I. Midday and nadir salivary cortisol appear superior to cortisol awakening response in burnout assessment and monitoring. Sci Rep. 2018;8(1):9151. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 29. Grossi G, Perski A, Ekstedt M, Johansson T, Lindström M, Holm K. The morning salivary cortisol response in burnout. J Psychosom Res. 2005;59(2):103–11. [ DOI ] [ PubMed ] [ Google Scholar ] 30. Henry JP. Biological basis of the stress response. Physiology. 1993;8(2):69–73. [ Google Scholar ] 31. Lundberg U, Frankenhaeuser M. Pituitary-adrenal and sympathetic-adrenal correlates of distress and effort. J Psychosom Res. 1980;24(3–4):125–30. [ DOI ] [ PubMed ] [ Google Scholar ] 32. McEwen BS. Adrenal steroid actions on brain: Dissecting the fine line between protection and damage. 1995. 33. Adam EK, Kumari M. Assessing salivary cortisol in large-scale, epidemiological research. Psychoneuroendocrinology. 2009;34(10):1423–36. [ DOI ] [ PubMed ] [ Google Scholar ] 34. Abelson JL, Sánchez BN, Mayer SE, Briggs H, Liberzon I, Rajaram N. Do diurnal salivary cortisol curves carry meaningful information about the regulatory biology of the HPA axis in healthy humans? Psychoneuroendocrinology. 2023;150:106031. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 35. Adam EK, Doane LD, Zinbarg RE, Mineka S, Craske MG, Griffith JW. Prospective prediction of major depressive disorder from cortisol awakening responses in adolescence. Psychoneuroendocrinology. 2010;35(6):921–31. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 36. Kramer JH, Yaffe K, Lengenfelder J, Delis DC. Age and gender interactions on verbal memory performance. J Int Neuropsychol Soc. 2003;9(1):97–102. [ DOI ] [ PubMed ] [ Google Scholar ] 37. Barkley RA, Barkley RA. Attention-deficit hyperactivity disorder: A handbook for diagnosis and treatment, (2nd ed.).New York : Guilford Press. 1998. 38. Stuss DT. Functions of the frontal lobes: relation to executive functions. J Int Neuropsychol Soc. 2011;17(5):759–65. [ DOI ] [ PubMed ] [ Google Scholar ] 39. Ciobanu AM, Damian AC, Neagu C. Association between burnout and immunological and endocrine alterations. Rom J Morphol Embryol. 2021;62(1):13. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 40. von Känel R, Bellingrath S, Kudielka BM. Association between burnout and circulating levels of pro-and anti-inflammatory cytokines in schoolteachers. J Psychosom Res. 2008;65(1):51–9. [ DOI ] [ PubMed ] [ Google Scholar ] 41. La Fratta I, Tatangelo R, Campagna G, Rizzuto A, Franceschelli S, Ferrone A, Patruno A, Speranza L, De Lutiis M, Felaco M. The plasmatic and salivary levels of IL-1β, IL-18 and IL-6 are associated to emotional difference during stress in young male. Sci Rep. 2018;8(1):3031. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 42. Santoft F, Hedman-Lagerlöf E, Salomonsson S, Lindsäter E, Ljótsson B, Kecklund G, Lekander M, Andreasson A. Inflammatory cytokines in patients with common mental disorders treated with cognitive behavior therapy. Volume 3. Behavior, & Immunity-Health: Brain; 2020. p. 100045. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 43. Tian R, Hou G, Li D, Yuan T-F. A possible change process of inflammatory cytokines in the prolonged chronic stress and its ultimate implications for health. Sci World J. 2014;2014(1):780616. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 44. Lester SR, Brown JR, Aycock JE, Grubbs SL, Johnson RB. Use of saliva for assessment of stress and its effect on the immune system prior to gross anatomy practical examinations. Anat Sci Educ. 2010;3(4):160–7. [ DOI ] [ PubMed ] [ Google Scholar ] 45. Steptoe A, Hamer M, Chida Y. The effects of acute psychological stress on circulating inflammatory factors in humans: a review and meta-analysis. Brain Behav Immun. 2007;21(7):901–12. [ DOI ] [ PubMed ] [ Google Scholar ] 46. Marsland AL, Walsh C, Lockwood K, John-Henderson NA. The effects of acute psychological stress on circulating and stimulated inflammatory markers: a systematic review and meta-analysis. Brain Behav Immun. 2017;64:208–19. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 47. Man IS, Shao R, Hou WK, Li SX, Liu FY, Lee M, Wing YK, Yau S-y, Lee TM. Multi-systemic evaluation of biological and emotional responses to the Trier Social Stress Test: A meta-analysis and systematic review. Front Neuroendocr. 2023;68:101050. [ DOI ] [ PubMed ] [ Google Scholar ] 48. Petakh P, Oksenych V, Kamyshna I, Boisak I, Lyubomirskaya K, Kamyshnyi O. Exploring the interplay between posttraumatic stress disorder, gut microbiota, and inflammatory biomarkers: a comprehensive meta-analysis. Front Immunol. 2024;15:1349883. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 49. Zhang Y, Wang J, Ye Y, Zou Y, Chen W, Wang Z, Zou Z. Peripheral cytokine levels across psychiatric disorders: A systematic review and network meta-analysis. Prog Neuropsychopharmacol Biol Psychiatry. 2023;125:110740. [ DOI ] [ PubMed ] [ Google Scholar ] 50. Sanada K, Montero-Marin J, Barceló-Soler A, Ikuse D, Ota M, Hirata A, Yoshizawa A, Hatanaka R, Valero MS, Demarzo M. Effects of mindfulness-based interventions on biomarkers and low-grade inflammation in patients with psychiatric disorders: a meta-analytic review. Int J Mol Sci. 2020;21(7):2484. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 51. Brydon L, Edwards S, Jia H, Mohamed-Ali V, Zachary I, Martin JF, Steptoe A. Psychological stress activates interleukin-1β gene expression in human mononuclear cells. Brain Behav Immun. 2005;19(6):540–6. [ DOI ] [ PubMed ] [ Google Scholar ] 52. Gimpl G, Fahrenholz F. The oxytocin receptor system: structure, function, and regulation. Physiol Rev. 2001;81(2):629–83. [ DOI ] [ PubMed ] [ Google Scholar ] 53. Jurek B, Neumann ID. The oxytocin receptor: from intracellular signaling to behavior. Physiol Rev. 2018;98(3):1805–908. [ DOI ] [ PubMed ] [ Google Scholar ] 54. La Fratta I, Franceschelli S, Speranza L, Patruno A, Michetti C, D’Ercole P, Ballerini P, Grilli A, Pesce M. Salivary oxytocin, cognitive anxiety and self-confidence in pre-competition athletes. Sci Rep. 2021;11(1):16877. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 55. Neumann ID, Landgraf R. Balance of brain oxytocin and vasopressin: implications for anxiety, depression, and social behaviors. Trends Neurosci. 2012;35(11):649–59. [ DOI ] [ PubMed ] [ Google Scholar ] 56. Cardoso C, Kingdon D, Ellenbogen MA. A meta-analytic review of the impact of intranasal oxytocin administration on cortisol concentrations during laboratory tasks: moderation by method and mental health. Psychoneuroendocrinology. 2014;49:161–70. [ DOI ] [ PubMed ] [ Google Scholar ] 57. Smith AS, Wang Z. Hypothalamic oxytocin mediates social buffering of the stress response. Biol Psychiatry. 2014;76(4):281–8. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 58. Olff M, Frijling JL, Kubzansky LD, Bradley B, Ellenbogen MA, Cardoso C, Bartz JA, Yee JR, Van Zuiden M. The role of oxytocin in social bonding, stress regulation and mental health: an update on the moderating effects of context and interindividual differences. Psychoneuroendocrinology. 2013;38(9):1883–94. [ DOI ] [ PubMed ] [ Google Scholar ] 59. Tawfik DS, Rovnaghi C, Profit J, Cornell TT, Anand KJ. Prevalence of burnout and its relation to the neuroendocrine system among pediatric residents during the early Covid-19 pandemic: a pilot feasibility study. Compr Psychoneuroendocrinology. 2023;14:100174. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 60. Castro MS, Meira GF, Mendes RGF, Castilho AVSS, Trench LA, Segalla CR, Vettore MV. Sales-Peres SHdC: The relationship between professional variables and burnout syndrome in Brazilian dentists during the COVID-19 pandemic. Int J Environ Res Public Health. 2024;21(4):435. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 61. Takefuji Y. Worldwide burnout in dentists. Br Dent J. 2024;236(11):857–857. [ DOI ] [ PubMed ] [ Google Scholar ] 62. Bluth K, Blanton PW. Mindfulness and self-compassion: Exploring pathways to adolescent emotional well-being. J Child Fam stud. 2014;23:1298–309. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 63. Neff KD. The development and validation of a scale to measure self-compassion. Self identity. 2003;2(3):223–50. [ Google Scholar ] 64. Neff KD, Knox MC, Long P, Gregory K. Caring for others without losing yourself: An adaptation of the Mindful Self-Compassion Program for Healthcare Communities. J Clin Psychol. 2020;76(9):1543–62. [ DOI ] [ PubMed ] [ Google Scholar ] 65. Brown KW, Ryan RM. The benefits of being present: mindfulness and its role in psychological well-being. J Personal Soc Psychol. 2003;84(4):822. [ DOI ] [ PubMed ] [ Google Scholar ] 66. Singer T, Bolz M. (Eds.) Compassion: Bridging practice and science. Max Planck Institute for Human Cognitive and Brain Sciences; 2013. http://www.compassion-training.org 67. Neff KD. Self-compassion: Theory, method, research, and intervention. Ann Rev Psychol. 2023;74(1):193–218. [ DOI ] [ PubMed ] [ Google Scholar ] 68. Van den Brink E, Koster F. Mindfulness-based compassionate living (MBCL). Handbook of mindfulness based Programmes. Mindfulness interventions from education to health and therapy. London: Routhledge; 2019. 10.4324/9781315265438. 69. Neff KD, Dahm KA. Self-compassion: What it is, what it does, and how it relates to mindfulness. Handbook of mindfulness and self-regulation. 2015. p. 121–137. 70. Strauss C, Taylor BL, Gu J, Kuyken W, Baer R, Jones F, Cavanagh K. What is compassion and how can we measure it? A review of definitions and measures. Clin Psychol Rev. 2016;47:15–27. [ DOI ] [ PubMed ] [ Google Scholar ] 71. Germer C.K. The mindful path to self-compassion: Freeing yourself from destructive thoughts and emotions. The Guilford Press; 2009. 72. Neff KD, Beretvas SN. The role of self-compassion in romantic relationships. Self identity. 2013;12(1):78–98. [ Google Scholar ] 73. Keng S-L, Smoski MJ, Robins CJ. Effects of mindfulness on psychological health: A review of empirical studies. Clin Psychol Rev. 2011;31(6):1041–56. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 74. Laliberte M, Boyd LD, Perry KR, Vineyard J. The role of self-compassion in mediating the effect of perfectionism on personal growth initiative in dental hygienists. Int J Dental Hygiene. 2024;22(2):284–93. [ DOI ] [ PubMed ] [ Google Scholar ] 75. Neff KD, Germer CK. A pilot study and randomized controlled trial of the mindful self-compassion program. J Clin Psychol. 2013;69(1):28–44. [ DOI ] [ PubMed ] [ Google Scholar ] 76. Zeny HAE, Rafat Abdel-Fattah H, Ragab El Sebaie N, Farid Ali Mohamed S. Perfectionism, self-compassion and depressive symptoms among nursing students. Egypt J Health Care. 2019;10(4):245–60. [ Google Scholar ] 77. Linnett RJ, Kibowski F. A multidimensional approach to perfectionism and self-compassion. Self Identity. 2020;19(7):757–83. [ Google Scholar ] 78. Uvnäs-Moberg K. Oxytocin may mediate the benefits of positive social interaction and emotions. Psychoneuroendocrinology. 1998;23(8):819–35. [ DOI ] [ PubMed ] [ Google Scholar ] 79. Stalder T, Kirschbaum C, Kudielka BM, Adam EK, Pruessner JC, Wüst S, Dockray S, Smyth N, Evans P, Hellhammer DH. Assessment of the cortisol awakening response: Expert consensus guidelines. Psychoneuroendocrinology. 2016;63:414–32. [ DOI ] [ PubMed ] [ Google Scholar ] 80. Maslach C, Jackson SE. The measurement of experienced burnout. J organizational Behav. 1981;2(2):99–113. [ Google Scholar ] 81. Öner N, Le Compte A. Süreksiz Durumluk/Sürekli Anksiyete Envanteri El Kitabı. 1 BaskI. İstanbul: Boğaziçi Üniversitesi Yayınları; 1983. p. 1–26. 82. Spielberger C. State-trait anxiety inventory for adults. Mind Garden; 1983. 10.1037/t06496-000 83. Beauchaine TP, Thayer JF. Heart rate variability as a transdiagnostic biomarker of psychopathology. Int J Psychophysiol. 2015;98(2):338–50. [ DOI ] [ PubMed ] [ Google Scholar ] 84. Markiewicz R, Markiewicz-Gospodarek A, Dobrowolska B. Galvanic skin response features in psychiatry and mental disorders: A narrative review. Int J Environ Res Public Health. 2022;19(20):13428. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 85. Queirolo L, Bacci C, Roccon A, Zanette G, Mucignat C. Anxiety in a regular day of work: A 24 hour psychophysiological investigation in young dentists with gender comparison. Front Psychol. 2023;14:1045974. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 86. Queirolo L, Facco E, Roccon A, Pistollato E, Di Fiore A, Fazia T, Bacci C, Zanette G. De-stress your physiological activation by compressing your imagination: a brief session of hypnosis decreases sympathetic stress response in moderately stressed dentists. Front Psychol. 2025;16:1577325. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 87. Bower JE, Ganz PA, Dickerson SS, Petersen L, Aziz N, Fahey JL. Diurnal cortisol rhythm and fatigue in breast cancer survivors. Psychoneuroendocrinology. 2005;30(1):92–100. [ DOI ] [ PubMed ] [ Google Scholar ] 88. Doane LD, Mineka S, Zinbarg RE, Craske M, Griffith JW, Adam EK. Are flatter diurnal cortisol rhythms associated with major depression and anxiety disorders in late adolescence? The role of life stress and daily negative emotion. Dev Psychopathol. 2013;25(3):629–42. [ DOI ] [ PubMed ] [ Google Scholar ] 89. Kumari M, Badrick E, Chandola T, Adam EK, Stafford M, Marmot MG, Kirschbaum C, Kivimaki M. Cortisol secretion and fatigue: associations in a community based cohort. Psychoneuroendocrinology. 2009;34(10):1476–85. [ DOI ] [ PubMed ] [ Google Scholar ] 90. Matthews K, Schwartz J, Cohen S, Seeman T. Diurnal cortisol decline is related to coronary calcification: CARDIA study. Psychosom Med. 2006;68(5):657–61. [ DOI ] [ PubMed ] [ Google Scholar ] 91. Sephton S, Spiegel D. Circadian disruption in cancer: a neuroendocrine-immune pathway from stress to disease? Brain Behav Immun. 2003;17(5):321–8. [ DOI ] [ PubMed ] [ Google Scholar ] 92. Adam EK, Quinn ME, Tavernier R, McQuillan MT, Dahlke KA, Gilbert KE. Diurnal cortisol slopes and mental and physical health outcomes: A systematic review and meta-analysis. Psychoneuroendocrinology. 2017;83:25–41. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 93. Chrousos GP. The hypothalamic–pituitary–adrenal axis and immune-mediated inflammation. N Engl J Med. 1995;332(20):1351–63. [ DOI ] [ PubMed ] [ Google Scholar ] 94. Mommersteeg PM, Heijnen CJ, Kavelaars A, Van Doornen LJ. Immune and endocrine function in burnout syndrome. Psychosom Med. 2006;68(6):879–86. [ DOI ] [ PubMed ] [ Google Scholar ] 95. Oosterholt BG, Maes JH, Van der Linden D, Verbraak MJ, Kompier MA. Burnout and cortisol: evidence for a lower cortisol awakening response in both clinical and non-clinical burnout. J Psychosom Res. 2015;78(5):445–51. [ DOI ] [ PubMed ] [ Google Scholar ] 96. Silverman MN, Sternberg EM. Glucocorticoid regulation of inflammation and its functional correlates: from HPA axis to glucocorticoid receptor dysfunction. Ann N Y Acad Sci. 2012;1261(1):55–63. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 97. Arch JJ, Brown KW, Dean DJ, Landy LN, Brown KD, Laudenslager ML. Self-compassion training modulates alpha-amylase, heart rate variability, and subjective responses to social evaluative threat in women. Psychoneuroendocrinology. 2014;42:49–58. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 98. Amasi-Hartoonian N, Sforzini L, Cattaneo A, Pariante CM. Cause or consequence? Understanding the role of cortisol in the increased inflammation observed in depression. Curr Opin Endocr metabolic Res. 2022;24:100356. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 99. Dowlati Y, Herrmann N, Swardfager W, Liu H, Sham L, Reim EK, Lanctôt KL. A meta-analysis of cytokines in major depression. Biol Psychiatry. 2010;67(5):446–57. [ DOI ] [ PubMed ] [ Google Scholar ] 100. Yui S, Sasayama D, Yamaguchi M, Washizuka S. Altered levels of salivary cytokines in patients with major depressive disorder. Clin Neurol Neurosurg. 2022;221:107390. [ DOI ] [ PubMed ] [ Google Scholar ] 101. McEwen BS. Physiology and neurobiology of stress and adaptation: central role of the brain. Physiol Rev. 2007;87(3):873–904. [ DOI ] [ PubMed ] [ Google Scholar ] 102. Heinrichs M, Domes G. Neuropeptides and social behaviour: effects of oxytocin and vasopressin in humans. Prog Brain Res. 2008;170:337–50. [ DOI ] [ PubMed ] [ Google Scholar ] 103. Gilbert P, Procter S. Compassionate mind training for people with high shame and self-criticism: Overview and pilot study of a group therapy approach. Clin Psychol Psychotherapy: Int J Theory Pract. 2006;13(6):353–79. [ Google Scholar ] 104. Breines JG, Thoma MV, Gianferante D, Hanlin L, Chen X, Rohleder N. Self-compassion as a predictor of interleukin-6 response to acute psychosocial stress. Brain Behav Immun. 2014;37:109–14. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 105. Danesh J, Kaptoge S, Mann AG, Sarwar N, Wood A, Angleman SB, Wensley F, Higgins JPT, Lennon L, Eiriksdottir G. Long-term interleukin-6 levels and subsequent risk of coronary heart disease: two new prospective studies and a systematic review. PLoS Med. 2008;5(4):e78. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 106. Ershler WB, Keller ET. Age-associated increased interleukin-6 gene expression, late-life diseases, and frailty. Annu Rev Med. 2000;51(1):245–70. [ DOI ] [ PubMed ] [ Google Scholar ] 107. Heinrichs M, Baumgartner T, Kirschbaum C, Ehlert U. Social support and oxytocin interact to suppress cortisol and subjective responses to psychosocial stress. Biol Psychiatry. 2003;54(12):1389–98. [ DOI ] [ PubMed ] [ Google Scholar ] 108. Hoge EA, Bui E, Palitz SA, Schwarz NR, Owens ME, Johnston JM, Pollack MH, Simon NM. The effect of mindfulness meditation training on biological acute stress responses in generalized anxiety disorder. Psychiatry Res. 2018;262:328–32. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 109. Jiang J, Yang M, Tian M, Chen Z, Xiao L, Gong Y. Intertwined associations between oxytocin, immune system and major depressive disorder. Biomed Pharmacother. 2023;163:114852. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 110. Galante J, Friedrich C, Dalgleish T, Jones PB, White IR. Systematic review and individual participant data meta-analysis of randomized controlled trials assessing mindfulness-based programs for mental health promotion. Nat mental health. 2023;1(7):462–76. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 111. Burton A, Burgess C, Dean S, Koutsopoulou GZ, Hugh-Jones S. How effective are mindfulness‐based interventions for reducing stress among healthcare professionals? A systematic review and meta‐analysis. Stress Health. 2017;33(1):3–13. [ DOI ] [ PubMed ] [ Google Scholar ] 112. Smith SA. Mindfulness-based stress reduction: An intervention to enhance the effectiveness of nurses’ coping with work‐related stress. Int J Nurs Knowl. 2014;25(2):119–30. [ DOI ] [ PubMed ] [ Google Scholar ] 113. Lomas T, Medina JC, Ivtzan I, Rupprecht S, Eiroa-Orosa FJ. The impact of mindfulness on the wellbeing and performance of educators: A systematic review of the empirical literature. Teach Teacher Educ. 2017;61:132–41. [ Google Scholar ] 114. Amran AG, Halboub E, Al-Sosowa AA, Al‐Maweri AA, Al‐Maweri SA, Alhajj MN. Stress Dynamics in Future Dentists: Insights From a 5‐Year Cohort Study. Eur J Dent Educ. 2025;30(2):418–26. [ DOI ] [ PubMed ] 115. Irving JA, Dobkin PL, Park J. Cultivating mindfulness in health care professionals: A review of empirical studies of mindfulness-based stress reduction (MBSR). Complement Ther Clin Pract. 2009;15(2):61–6. [ DOI ] [ PubMed ] [ Google Scholar ] 116. Hwang Y-G, Pae C, Song CR, Kim H-J, Bang M, Park CI, Choi TK, Kim M-K, Lee S-H. Self-compassion is associated with the superior longitudinal fasciculus in the mirroring network in healthy individuals. Sci Rep. 2023;13(1):12264. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 117. Kim JJ, Parker SL, Doty JR, Cunnington R, Gilbert P, Kirby JN. Neurophysiological and behavioural markers of compassion. Sci Rep. 2020;10(1):6789. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] Associated Data This section collects any data citations, data availability statements, or supplementary materials included in this article. Supplementary Materials Supplementary Material 1. (16.5KB, docx) Supplementary Material 2. (15.3KB, docx) Data Availability Statement The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Articles from BMC Psychology are provided here courtesy of BMC ACTIONS View on publisher site PDF (2.3 MB) Cite Collections Permalink RESOURCES Similar articles Cited by other articles Links to NCBI Databases Follow NCBI NCBI on X (formerly known as Twitter) NCBI on Facebook NCBI on LinkedIn NCBI on GitHub NCBI RSS feed Connect with NLM NLM on X (formerly known as Twitter) NLM on Facebook NLM on YouTube National Library of Medicine 8600 Rockville Pike Bethesda, MD 20894 Web Policies FOIA HHS Vulnerability Disclosure Help Accessibility Careers NLM NIH HHS USA.gov Back to Top

Related documents

• Organizational Compassion in Health Care Settings: A Mixed-Methods Systematic Review of Employee Experiences and Outcomes and Contributing Organizational Traits.#219168
• Examination of a Self-Compassion Course for Healthcare Providers Working With People With Multiple Sclerosis#1007065
• Nursing in unprecedented times : wellbeing, excellence and the power of research#278141
• From 'Little Things' to 'Seagulls': A Mixed Methods Exploration of Patients' Experiences of Person-Centred Compassionate Care in General Medical and Surgical Wards.#631097
• Burnout in healthcare: risk factors and solutions: Guidelines Series#1110940