1. Background
Occupational stress and burnout among dentists are significant concerns, as various studies have highlighted the prevalence and impact of these issues within the profession. The nature of dental practice, characterized by long working hours, high patient expectations, and challenging work environments, contributes to elevated stress levels and burnout among dental practitioners. One of the primary sources of occupational stress for dentists is patient-related stressors (1-6). A study conducted in Hong Kong identified these stressors as the most significant contributors to occupational stress, leading to a notable incidence of burnout among dentists in the region (7). Similarly, newly graduated dentists have been found to experience higher levels of professional burnout, anxiety, and depression, primarily due to the demanding nature of their work. For instance, a study among Palestinian dentists revealed that various work stressors, including workload and patient interactions, were linked to increased burnout (8).
According to Maslach et al.'s definition, job burnout is a process of physical and psychological exhaustion that occurs as a result of constant and repetitive emotional pressures from long-term involvement (9). Job burnout is a psychological syndrome consisting of three dimensions: (a) Emotional exhaustion, which is the feeling of being under pressure and depleted of internal resources, leading to mental or emotional fatigue (10); (b) depersonalization, which is a negative and indifferent response towards individuals in positions of receiving services and care; and (c) reduced personal accomplishment, which is a decrease in the sense of competence, a feeling of not being successful, and a sense of not fulfilling personal responsibilities (5). Job burnout is more common among professions with a higher rate of job-related interactions with individuals in need, such as nurses, teachers, doctors, and company managers. There is a close relationship between job burnout and stress, and this type of exhaustion occurs as a result of constant stressors (11-13).
Dentists are prone to experiencing job burnout due to the long hours and high energy required to provide services to patients. Job factors such as the need for high precision during work, treating specific groups such as children, mentally disabled individuals, and the elderly, exposure to multiple harmful factors such as loud noises, chemicals, working under physically inappropriate conditions for long hours, and contact with infectious agents, put additional pressure on dentists, resulting in a decline in the quantity and quality of services provided (14). The exact contributing factors that enable some dentists to handle stress and avoid burnout more successfully than others are unknown at this time. Some researchers have identified two categories of factors that contribute to job burnout: One related to the work environment and the other related to individual characteristics and acquired traits (9).
Among the variables believed to be related to job stress and coping mechanisms are mental health and emotional intelligence variables (15, 16). Emotional intelligence (EI) is defined as the ability of individuals to evaluate and express their own and others' emotions, regulate their own and others' emotions, and use it effectively and efficiently to guide and control their thoughts and actions and solve problems (17). According to these definitions, emotional intelligence can be considered a supportive factor against work pressures (18). Overall, an individual's ability to manage emotions can positively impact relationships with colleagues and clients (19, 20).
2. Objectives
There is insufficient data to determine whether stress and burnout levels and emotional intelligence (EI) levels are correlated. The present study aimed to investigate the relationship between emotional intelligence, stress levels, and burnout levels among dentists in Kermanshah city.
3. Methods
The present study used a descriptive-analytical design. Participants were drawn from private and dental clinical practices with a convenience sampling technique.
Based on the correlation coefficient (r) of 0.26 for the relationship between stress and burnout, and the correlation coefficient of -0.38 for the relationship between emotional intelligence and burnout, as reported in a previous study (21), with a power of 80% (β) and a significance level of 5% (α), the required sample size for evaluating the relationship between stress and burnout was determined to be 114 individuals. Being an active dentist and having satisfaction were the criteria for participating in the study. The inclusion criteria were: Dentists who have worked minimum of one year and have agreed to participate in the study. The study excluded dentists who experiencing grief or separation from a spouse in the past year, having a psychiatric disorder or using psychiatric medication, and having a substance abuse or alcohol addiction.
After visiting dental clinics in Kermanshah city and obtaining consent and providing necessary explanations regarding the research, the questionnaires were distributed among dentists who met the inclusion criteria. Descriptive data related to the research variables will be described using descriptive statistical indices such as mean, standard deviation, frequency, and percentage. The statistical assumptions, including the Kolmogorov-Smirnov test for normality of data, will be evaluated. The hypotheses will be analyzed using Pearson correlation coefficient and multiple linear regression. Path analysis will be used to evaluate the mediating role of stress. A significance level of 0.05 will be considered. The data will be analyzed using SPSS software version 26. The tools used in this study included a demographic questionnaire, the Schutte Emotional Intelligence Scale, the Health and Safety Executive (HSE) Stress Questionnaire, and the Maslach Burnout Inventory.
3.1. Instruments
3.1.1. Demographic Questionnaire
This includes information related to the consent form for participation in the research and demographic information of the participants. This information includes age, gender, marital status, level of education, work experience, place of employment, average working hours per week, background illness, disability, addiction to drugs or alcohol, experience of grief in the past year, separation from spouse in the past year, presence of psychiatric disorders, and use of psychiatric medications.
3.1.2. Schutte Emotional Intelligence Questionnaire
Developed in 1998 based on the initial model of emotional intelligence by Mayer and Salovey (1990), this scale is a self-descriptive questionnaire consisting of 33 items. It assesses three subscales: Appraisal and expression of emotions (13 items), regulation of emotions (10 items), and utilization of emotions (10 items) on a five-point Likert scale ranging from strongly disagree to strongly agree. Items 5, 28, and 33 are reverse scored. A higher score indicates higher emotional intelligence. The reliability coefficient for the overall emotional intelligence scale is reported to be 0.87, with a validity of 0.78. Internal consistency has been reported to be higher than 0.87 in various studies. The validity of the scale has been confirmed through correlations between emotional intelligence and anxiety (-0.25), depression (-0.37), and alexithymia (-0.65). The validity of this scale has also been reported through its correlation with the Bar-On test (0.67) (22). In Javaheri's study, the Cronbach's alpha coefficient for the overall scale was 0.78 (23).
3.1.3. Health and Safety Executive Stress Questionnaire
Developed in the late 1990s by the HSE of England to measure job stress, this questionnaire consists of seven subscales measuring demands, control, manager support, peers support, relationships, role, and change. It contains 35 items and is scored on a five-point Likert scale ranging from never to always. Items 3, 5, 6, 9, 12, 14, 16, 18, 20, 21, 22, and 34 are reverse scored. The minimum score a person can obtain is 35, and the maximum score is 175. A higher score indicates higher levels of job stress and pressure, while a lower score indicates lower levels of stress. In the study by Azadmarzabadi and Gholami, the validity of this test was confirmed through correlations with anxiety (-0.43) and insomnia (-0.41), as well as depression (0.78) (24). The Cronbach's alpha coefficient for all subscales ranged from 0.79 to 0.89, indicating high internal consistency (25).
3.1.4. Maslach Burnout Inventory
This questionnaire consists of 22 items, including nine items to measure emotional exhaustion, five items to measure depersonalization, and eight items to assess personal accomplishment. It measures the frequency of experiencing job burnout on a seven-point Likert scale ranging from never to everyday. The score for personal accomplishment is reverse coded. The obtained score in each domain is categorized as low, moderate, or high. A higher score indicates higher levels of burnout. The reliability of the questionnaire has been reported with Cronbach's alpha coefficients ranging from 0.71 to 0.90 and test-retest reliability coefficients ranging from 0.60 to 0.80. The reliability for the subscales of emotional exhaustion, depersonalization, and personal accomplishment are reported as 0.90, 0.79, and 0.71, respectively. Maslach and Jackson have evaluated the validity of this test through various examinations, reporting high validity (26). Najafy et al. obtained a reliability coefficient of 0.86 for this test through Cronbach's alpha (27).
4. Results
Table 1 presents the distribution of demographic variables, including age, gender, marital status, background of disease, education, work experience, place of employment, and average weekly working hours. Table 2 shows a significant correlation between the research variables (P < 0.01), with the highest correlation being between stress and job burnout (P < 0.01, r = 0.734). The results of the Pearson correlation analysis showed that emotional intelligence predicts job burnout in dentists in an inverse and significant manner. Among the dimensions of emotional exhaustion (P < 0.01, r = 0.242) and personal inefficiency (P < 0.05, r = 0.229), there was a significant inverse relationship with emotional intelligence, while no significant relationship was observed between emotional intelligence and depersonalization. To examine the relationship between the variables of age, gender, work experience, and weekly working hours with the main research variables, the Pearson correlation test was used, and the results are reported in Table 3. There was a significant inverse relationship between age and the two variables of stress (r = 0.289) and job burnout (r = 0.372), indicating that as age increases, stress and burnout decrease, and vice versa. However, no significant relationship was observed between emotional intelligence and age. No significant relationship was found between gender and the research variables. The results in Table 4 indicate a significant indirect effect between emotional intelligence and job burnout (r2 = -0.583), confirming the mediating role of stress between emotional intelligence and burnout.
Table 1.Demographic Characteristics
| Variables | No. (%) |
|---|---|
| Age | |
| < 30 | 53 (46.5) |
| 30 - 49 | 53 (46.5) |
| 50 < | 8 (7) |
| Gender | |
| Female | 54 (46.5) |
| Male | 60 (52.6) |
| Marital status | |
| Single | 68 (59.6) |
| Married | 43 (37.7) |
| Divorced | 3 (2.6) |
| Illness | |
| Yes | 5 (4.4) |
| No | 109 (95.6) |
| Education | |
| General | 110 (96.5) |
| Specialist | 4 (3.5) |
| Work experience | |
| < 6 | 73 (64) |
| 6 - 17 | 31 (27.2) |
| 18 - 29 | 5 (4.4) |
| 30 < | 5 (4.4) |
| Place of employment | |
| Private practice | 24 (21.1) |
| Clinic | 90 (78.9) |
| Working hours per week | |
| < 27 | 21 (18.4) |
| 27 - 50 | 82 (71.9) |
| 50 < | 11 (9.6) |
Table 4.Multiple Linear Regression Model with Burnout Domains and the Predictor Variables and Stress or Burnout Components as the Criterion Variable a
| Predictor Variables | B | β | t | P-Value |
|---|---|---|---|---|
| Stress | 1.114 | 0.768 | 10.77 | 0.000 |
| Emotional intelligence | 0.134 | 0.077 | 1.084 | 0.281 |
a R = 0.737; R2 = .544; AdgR = 0.536.
5. Discussion
Overall, this study aims to investigate the relationship between emotional intelligence, stress, and job burnout among dentists in Kermanshah city. The results showed that emotional intelligence has a significant impact on stress, which is consistent with the studies of Partido and Owen (28), Pau et al. (29), and Swami et al. (30). In this study, no significant relationship was observed between gender and emotional intelligence and stress, indicating no significant difference in emotional intelligence and stress scores between male and female participants. This finding is consistent with the research of Augusto Landa et al. (31) but contradicts the studies of Natalio Extremera et al. (32) and Delpasand et al. (33). One possible reason may be that self-assessment tools such as standardized questionnaires (like the Perceived Stress Scale or the Bar-On Emotional Quotient Inventory) can yield varying results depending on their design and content. The results did not show a significant relationship between age and emotional intelligence scores, indicating the stability of this trait over time. Since emotional intelligence is considered a stable trait, it is likely that it influences stress rather than vice versa.
The results showed that emotional intelligence predicts job burnout in dentists in an inverse and significant manner. Among the dimensions of emotional exhaustion and personal inefficiency, there was a significant inverse relationship with emotional intelligence, while no significant relationship was observed between emotional intelligence and depersonalization. This finding is consistent with the studies of Bin Dahmash et al. (34), Haresabadi et al. (35), and Shariatpanahi et al. (36), but contradicts the study by Fox (37), indicating that high emotional intelligence is associated with lower levels of burnout. One of the reasons for the negative relationship between emotional intelligence and job burnout is self-control or emotion management. Emotion control is a skill that is developed through creating awareness. Effective individuals in this area are better able to manage negative emotions such as hopelessness, anxiety, and irritability and are less likely to face difficulties in the ups and downs of life or can quickly return to favorable conditions in case of problems. Understanding the emotions of others and employing appropriate empathy or compassion is another reason for the relationship between emotional intelligence and job burnout (38).
There is a significant and meaningful relationship between stress and job burnout in dentists. The results showed that stress has a significant impact on the level of job burnout, which is consistent with the studies of Choy and Wong (39), Toon et al. (40), and Swami et al. (30). The results confirmed the mediating role of stress between emotional intelligence and job burnout among dentists. This means that stress mediates the effect of emotional intelligence on job burnout. This finding is consistent with the research conducted by Swami et al. (30). The study will provide valuable insights into the factors contributing to job burnout among dentists and may help identify potential interventions to reduce burnout and promote well-being in this professional group.
5.1. Conclusions
Given the inherent stress in the dental profession, it seems necessary for relevant organizations to plan for supportive programs and hold stress management workshops, as well as provide assessment services and counseling, to reduce the effects of stress and job burnout.
5.2. Suggestion
Future research should explore the impact of enhanced emotional intelligence (EI) scores on the perceived levels of stress and burnout among dentists. Additionally, further studies are necessary to develop strategies for improving EI levels to better manage stress and reduce burnout. It is also suggested that training related to stress control and communication skills be included in the curriculum at universities. Future research is needed to improve EI levels to tolerate stress and minimize burnout levels.
5.3. Limitations
Several limitations were identified in this study. The data were collected from 114 dentists at one institution, which restricts the generalizability of the findings. Additionally, the cross-sectional design of the research limits the ability to establish causal relationships. Employing prospective, longitudinal experimental research designs could enhance the identification of causal links. Furthermore, since the data obtained from the questionnaires were based on self-reports, there is a possibility that social desirability bias may have affected the participants' responses.
