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A Cross Sectional Study in Greece to Investigate Burnout, Anxiety and Depression in Medical and Nursing Staff during the Pandemic Crisis: The Impact of Occupational and Demographic Factors
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23 April 2023
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24 April 2023
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Abstract
The presence of burnout, anxiety and depression among health professionals is a crucial issue that must be carefully addressed. The aim of the present study is to investigate levels of burnout, anxiety and depression among health professionals (medical and nursing staff) during the pandemic crisis, the association of burnout with anxiety and depression as well as the impact of occupational and demographic factors. One hundred twenty-five health professionals (medical and nursing staff) participated who were working in a public hospital in the broader area of Athens (sample of convenience). Specifically, 41 males and 84 females with the majority of them being in the category of 36-45 years of age. For the data collection, the Maslach Burnout Inventory (MBI) and the HADS questionnaire were used. The results showed that there was a statistically significant and negative correlation of emotional exhaustion to HADS total (r= -0,377, p=0,000) as well as HADS anxiety (r= -0,417, p=0,000). Also, there was a statistically significant and negative correlation of depersonalization to HADS total (r= -0,370, p=0,000) as well as HADS anxiety (r= -0,431, p=0,000). Moreover, there was a statistically significant effect (p<0,05) of occupational and demographic characteristics.
Keywords:Â
Subject: Public Health and Healthcare -  Public Health and Health Services
Introduction
The pandemic (COVID-19), which is considered one of the three pandemics that have affected the population worldwide in the last twenty years (1), started worldwide in 2019. This disease is due to the SARS-CoV-2 coronavirus that first appeared in the city of Wuhan, the capital of China's Hubei province. The virus was aggressive and spread particularly quickly, as confirmed by the numbers that accompany it, since more than 113 million people in 215 different countries have been confirmed to have been infected to date. Specifically, its dangerousness is clearly shown by the fact that by 2020 (2) 2.51 million deaths and 89 million recoveries had been recorded.
The outbreak of the COVID 19 pandemic was the reason for the exacerbation of the already existing problems in the public hospitals, whether they were related to the adequacy of the accommodation structures, or to the adequate degree of dealing with emergencies, as they arose from the influx of patients who were facing the virus privately, without success or by utilizing the resources that were intended to achieve and upgrade them, but had not yet been achieved. Against all this stood the medical and nursing staff who, regardless of the problems they faced, due to the aforementioned, responded to an excessive degree to the demands of the pandemic, with a disproportionate, however, result, since among other things they were led to burnout.
It is understood that the human resource management policies of public hospitals played a big role, as they are linked to the promotion of a system of high work performance related to the utilization of personnel in key positions, their training, participation in decision-making, safety. Equally understandable is the fact that the promotion of such a system, if it is not properly structured with respect to the human factor (i.e., the medical and nursing staff), giving weight to their well-being, collapses.
Globally, before the spread of the virus, most healthcare systems in Europe were facing many challenges. An element that can be evaluated concerns the elderly population of Europe, as 20% of it is over 65 years old, a statistic which translates into a prevalence of important chronic diseases, which the national budget must deal with. It is possible that Europe's aging population is one of the main reasons why the pandemic spread so quickly (3). History has shown that no country in the world was prepared to face such a pandemic and for this reason a series of measures, such as a curfew, were put in place to stop its spread and to properly prepare hospitals to receive them. patients who were still pouring in. This preparation included, among other things, the supply of necessary equipment, necessary medicines and ICU beds. In the next phase, the hospitals proceeded to categorize the cases into urgent and non-urgent, with the result that some cases of the pandemic are dealt with immediately, while the other cases do not receive immediate help but are postponed (4). An example that can be given is the vulnerable category of the elderly around the world, whose hospitalization and medical care was suspended as the coronavirus patients preceded them (3).
This treatment resulted in the postponement of major hospitalization programs and thus in financial losses for both hospitals and doctors and other health professionals, with an equally direct effect of burdening an already burdened workplace with an object that could no longer be adequately addressed (4).
Taking into account the above, we understand that the rapid spread of the coronavirus has suddenly become a huge threat to the health personnel of hospitals, internationally but especially in Greek public hospitals. More specifically, its transmission took place at a rapid rate even among the medical and nursing staff themselves, which had negative effects on the mental health of the workers (5-7), as the effort coping with it caused anxiety, depression and fear, denial and anger (8), all of which intensified even outside their working hours. In particular, they were forced to shoulder hard hours, under physical and psychological pressure, putting themselves at risk, in order to respond professionally (9) and without having sufficient but also capable equipment in order to come out unscathed from the battle with the virus. On the contrary, their direct contact with infected patients, grueling hours, work demands and their exposure to potential psychological problems led to accumulated stress and problems which cumulatively created symptoms of post-traumatic stress (PTSD), depression and burnout (10).
According to the above study (10), factors of employees' mental distress are influenced by employees' personality, age, gender, education and family status, as well as workload, work environment and work anxiety. Specifically for the period of Covid-19, a high frequency of anxiety and post-traumatic stress disorder (PTSD) was found in women and nurses, compared to men and doctors, respectively. This result was interpreted in the sense that the nurses had a more direct relationship with the patients and therefore the rates of fatigue, fear and anxiety were much more intense, especially in those who had work experience and conscience and were quick to respond immediately to the situation. At an international level, statistics showed that the medical staff of hospitals such as in Spain (11) and Canada (12), who were affected by the virus, presented severe problems of burnout, anxiety, depression and post-traumatic stress.
At this point we should also refer to the study by Guixia et al. (13), which showed that the staff who worked in intensive care units, during the pandemic, presented symptoms of the syndromes under study, at a rate of 89.57%, compared to the other departments with a rate of 49.15%.
In Greece, statistical studies were carried out in public hospitals, such as, for example, in ACHEPA (Thessaloniki), where the degree of control of the pandemic was examined in relation to the training of each professional, the equipment he/she had at his/her disposal and the support provided to him/her, finding that the levels of employee burnout are proportional to those in the international arena (14). In more detail, regarding the levels of fear of illness, no significant differences were found in the level of fear and also among professionals, something that was also found in a survey carried out in public hospitals in Attica (15). On the contrary, the frontline staff, who cared for the patients, showed greater problems, in proportion to the rest of the staff, which statistically agrees with comparisons made internationally (16-18). Similarly, health professionals working in ICUs showed more serious mental health incidents (14), with a focus on the female gender in proportion to male professionals, which was also found in another research in Greece and internationally (19). Occupational burnout and depression were also experienced by younger, comparatively, ages (14), again agreeing with international data (20-22).
A distinction is generally made between burnout and depression, despite the fact that the syndromes under study appear to have similar symptoms. In reality, however, these symptoms differ as work burnout refers to specific conditions and environments while depression refers to something more general (23). Other studies have also shown that the symptoms of these two syndromes are distinct but both present interrelated negative moods (24), as they present identical psychological states, such as weakness, hopelessness and negative emotions which are accompanied by a complete absence of positive emotions (25, 26). Finally, it seems that burnout and depression are highly correlated, which is also proven by the Maslach Burnout Inventory (MBI) scale, as the component of emotional exhaustion shows a high correlation with depression than with the other dimensions of burnout (27). It is understood that there is a bidirectional relationship between burnout and depression as each of these syndromes overlaps the other (28).
Specifically for the depression of health professionals, international research on the subject of "COVID 19 Mental health international for the General Population (COMET-G) Study", organized by the Department of Medicine in Aristotle University of Thessaloniki and the World Psychiatric Association, during the period from March 2020 to and April 2021, clinical depression afflicted 18% of the total population and severe stress was seen in about the same percentage of people. Cause and effect were the same: low level in terms of quality of life combined with problems in intra-family relationships. The results focused on people with a psychiatric history, who showed very high rates (>15%) of suicidal tendencies. Adherence to conspiracy theories was also important, where a large percentage (at least half of the participants) accepted at least one theory (29). According to the aforementioned statistical study, burnout during the pandemic was directly related to the escalation of stressful situations leading to depression, as the former affects the employee's mental health (29), as it has negative consequences on the quality of life of health workers.
Given that our country was in a period of economic crisis for several years, the studies carried out in Greece and related to the psychological state of the population showed a high level of depression and anxiety, with symptoms similar or higher in proportion to previous estimates, but certainly higher in comparison with the period before the financial crisis of 2009, an element that was due to the prevalence of the syndrome while the country faltered due to the virus (30).
The study by Pappa et al. is important. (19), who assessed levels and risk factors for anxiety, depression, traumatic stress, and burnout in 464 individuals employed in six hospitals in Greece and specifically on the front line of dealing with the pandemic. After completing questionnaires on social, demographic, work-related information and psychometric scales, results showed moderate to severe depression (30%), anxiety (25%) and traumatic stress (33%). Work stress was particularly high as the staff presented moderate/severe emotional exhaustion (65%), 92% showed increased levels of depersonalization while 51% showed low/moderate levels of personal achievement. The study under discussion was very important, as it made it clear that a large percentage of health professionals in Greece were significantly burdened due to the pandemic, while at least half were facing problems related to their mental health (19).
In light of the above theoretical approaches, the aim of the present study is to investigate levels of burnout, anxiety and depression among health professionals (medical and nursing staff) during the pandemic crisis, the association of burnout with anxiety and depression as well as the impact of occupational and demographic factors. The main research hypothesis is that burnout will be related to anxiety and depression. We, also, hypothesize that there will be a statistically significant effect of occupational and demographic variables on the levels of burnout, anxiety and depression respectively.
Method
Research Design
The present study is a quantitative and cross-sectional study including the variables of burnout, anxiety and depression as well as occupational and demographic factors. In the context of the investigation of the impact of occupational and demographic variables on the levels of burnout, anxiety and depression respectively, the dependent variables are burnout, anxiety and depression while the independent variables are the occupational and demographic factors.
Participants
In this study, 125 health professionals (medical and nursing staff) participated who were working in a public hospital in the broader area of Athens (sample of convenience). Specifically, 41 males and 84 females with the majority of them being in the category of 36-45 years of age (38 individuals, 30.4%). The inclusion criteria of the sample were the following:
- ➢
- >18 years of age
- ➢
- Speaking the Greek language
- ➢
- Belonging to medical or nursing staff
- ➢
- Working in a public hospital
- ➢
- Participating in the study voluntarily
Questionnaires
The first part of the measurement tool consisted of the Personal Information Form, in which personal information, such as gender, age, marital status etc., were reported.
The second part consisted of the Maslach Burnout Inventory (MBI) questionnaire, which is one of the most widely used tools for measuring burnout and which was created by Maslach & Jackson (31), basing its questions on three dimensions of this syndrome (emotional exhaustion, depersonalization, personal accomplishment). This is a standardized questionnaire, which requires that each dimension assessed in the questionnaire has a negative value in order for an employee to be considered "suffering" from burnout (31). The MBI consists of 22 self-report statements, 7 for emotional exhaustion, 7 for depersonalization and 8 for personal accomplishment. Specifically, each statement is evaluated on a seven-point Likert scale, with responses from 0=never, 1=a few times per year, 2=once a month, 3=a few times per month, 4=once a week, 5=a few times per week, 6=every day. Scores for each of the three dimensions of burnout (emotional exhaustion, depersonalization and personal accomplishment) are calculated by summing the scores of the relevant items (32). It should be noted that its reliability and validity has been evaluated internationally (33).
As the concept of burnout refers to a spectrum of symptoms of the syndrome, according to more recent research (Leiter & Maslach, 2016), the additional use of the Anxiety and Depression Scale (HADS) developed by Zigmond and Snaith (34) was necessary. The HADS is a self-administered scale consisting of 14 items, each with four possible responses (34). The HADS has demonstrated good validity in terms of its ability to accurately assess symptoms of anxiety and depression in medical patients. Studies have found that scores on the HADS are significantly related to diagnoses of anxiety and depression based on structured clinical interviews, as well as measures of general psychological distress.
Procedure
The final research proposal of the present study was approved by the research and ethics committee of the Scientific College of Greece (Protocol Number: TER2023225). The data collection took place in the period of February - March 2023. The participants received an informed consent form, which together with the individual's data, contained the purpose of the research, information on the confidentiality and privacy of the information. In addition, there was information on the rights of research participants, such as withdrawing consent and participation at any time they wish. The process was conducted remotely with electronic administration of the questionnaires and more specifically through Microsoft Forms. Participants were asked to complete all the questionnaires.
Statistical Analysis
Statistical data analysis was performed using statistical analysis software, IBM SPSS version 26. Data analysis was based on descriptive statistics indicators, frequencies (ν) or percentage (%), as well as mean (SD) and standard deviation (SD). Kolmogorov – Smirnov test was preformed to check the normality of the sample. In order to investigate the relation of burnout to anxiety and depression among health professionals, Spearman correlation was performed. Moreover, to explore the impact of occupational and demographic variables on the levels of burnout, anxiety and depression respectively, Mann-Whitney test and Kruskal Wallis test were performed. All comparisons were made using a significance level of α=0.05.
Results
In the current study, 125 health professionals (medical and nursing staff) participated who were working in a public hospital in the broader area of Athens (sample of convenience). Specifically, 41 males and 84 females with the majority of them being in the category of 36-45 years of age (38 individuals, 30.4%). All the sociodemographic and occupational characteristics are presented in Table 1.
Regarding the clinical characteristics of the sample (Table 2), the results indicated that the majority of the participants had low emotional exhaustion (74, 59,2%), high depersonalization (54, 43,2%) and low personal accomplishment (54, 43,2%). As far as anxiety and depression is concerned, the results showed that the majority of the participants scored very high in anxiety, which is categorized as abnormal (86, 68,8%) while in depression 80 health professionals (64,0%) presented a borderline abnormal level.
Moreover, the results of this study indicated that the mean scores of the MBI were 16,69 for the emotional exhaustion, 12,44 for the depersonalization and 32,70 for the personal accomplishment. In HADS questionnaire, the results indicated that the mean scores were 21,00 for anxiety and depression in total, 11,50 for anxiety exclusively and 9,49 for depression exclusively (Table 3).
In Table 4, we see the correlation of burnout to anxiety and depression. Specifically, the results showed that there was a statistically significant and negative correlation of emotional exhaustion to HADS total (r= -0,377, p=0,000) as well as HADS anxiety (r= -0,417, p=0,000). Also, there was a statistically significant and negative correlation of depersonalization to HADS total (r= -0,370, p=0,000) as well as HADS anxiety (r= -0,431, p=0,000). Finally, a statistically significant and positive correlation was observed between personal accomplishment and HADS total (r= 0,339, p=0,000) as well as HADS anxiety (r= 0,401, p=0,000).
In Table 5, we see the differences between health professionals with various levels of emotional exhaustion in relation to anxiety and depression. Specifically, the results indicated that in HADS total as well as in HADS anxiety there were statistically significant differences with health professionals with low emotional exhaustion to present more anxiety and depression in total and anxiety exclusively (p<0,05) compared to the other groups.
In Table 6, we see the differences between health professionals with various levels of depersonalization in relation to anxiety and depression. Specifically, the results indicated that in HADS total, HADS anxiety as well as in HADS depression there were statistically significant differences with health professionals with low depersonalization to present more anxiety and depression in total as well as anxiety and depression exclusively (p<0,05) compared to the other groups.
In Table 7, we see the differences between health professionals with various levels of personal accomplishment in relation to anxiety and depression. Specifically, the results indicated that in HADS total as well as in HADS anxiety there were statistically significant differences with health professionals with high personal accomplishment (which means low burnout) to present more anxiety and depression in total and anxiety exclusively (p<0,05) compared to the other groups.
In Table 8, we see the differences between health professionals with various levels of anxiety in relation to burnout. Specifically, the results indicated that health professionals with borderline abnormal anxiety presented higher scores of emotional exhaustion (p<0,05). Moreover, health professionals with normal anxiety presented higher scores of depersonalization (p<0,05) while health professionals with abnormal anxiety presented higher scores in personal accomplishment (p<0,05).
There were no statistically significant differences regarding burnout between health professionals presenting different levels of depression (p>0,05).
Regarding differences between males and females in relation to burnout, anxiety and depression, the results showed that females presented higher emotional exhaustion in comparison to males (p<0,05) while males presented more depression and anxiety (p<0,05) (Table 9).
Regarding differences between levels of age in relation to burnout, anxiety and depression, the results showed that older health professionals (>55 years) presented higher anxiety in comparison to the other age groups (p<0,05) (Table 10).
Concerning the variable of education, the results indicated that only in emotional exhaustion differences were observed (p<0,05) with those who have studied in Institutes of Vocational Training to present higher values of emotional exhaustion (75,42) while graduates from high school presented 73,95 and graduates from university education presented 71,31 and finally those health professionals holding a master or PhD presented 48,89.
Concerning the variable of profession, the results indicated that only in emotional exhaustion differences were observed (p<0,05). Specifically, those who were nursing assistants (which means graduates from a secondary school) presented higher values of emotional exhaustion (79,37) while nurses (which means graduates from university) presented 77,39 and supporting healthcare staff (graduates from an obligatory school) presented 59,57. Finally, medical staff indicated the lower scores of emotional exhaustion (48,73) compared to the groups of nurses.
With regards to the factors of marital status and work experience (in years), no statistically significant differences were observed.
Discussion
The aim of the present study is to investigate levels of burnout, anxiety and depression among health professionals (medical and nursing staff) during the pandemic crisis, the association of burnout with anxiety and depression as well as the impact of occupational and demographic factors.
Regarding the levels of burnout, anxiety and depression of the sample, the findings show that the majority of the health professionals present low emotional exhaustion but high depersonalization as well as low personal accomplishment. As far as anxiety and depression is concerned, most participants seem to be very anxious in an abnormal level while in depression a borderline abnormal level is, also, observed. The high values of burnout are confirmed in another study of Theofilou et al. (35), in which burnout among health workers during the period of COVID-19 was investigated. Poor mental health with the presence of anxiety and depression in health professionals is in line with other similar studies (36,37). A recent systematic review conducted by Li et al. (38) across 65 studies, involving 97,333 health care workers in 21 countries, has identified a high prevalence of moderate depression (21.7%), anxiety (22.1%), and PTSD (21.5%) among healthcare workers during the COVID-19 pandemic.
Moreover, our study shows that there is a strong relation of burnout to the presence of anxiety and depressive symptoms in medical and nursing staff. This finding corresponds to other similar research findings (39, 40). In the study of Zheng et al. (41) regarding burnout among healthcare providers and the association with anxiety and depression during the COVID-19 pandemic in Macao, China, the results indicate that anxiety and depression remain significantly and positively associated with all types of burnout after controlling for the strong effects of demographic and work factors (41).
In the context of the investigation of the impact of demographic and occupational factors on the level of burnout, anxiety and depression, this study has demonstrated the close association between the above variables. More specifically, it seems that age, gender, education and profession may play a crucial role and affect the degree of burnout as well as anxiety and depression. The findings, in general, are not controversial. For instance, in a study of Nikolaou et al. (42) concerning predictors of anxiety and depressive symptoms among Greek nurses, it was found that younger nurses, unmarried, those without children, those with less work experience, and working in the general medical units were more vulnerable.
The current study presents some limitations. The small number of participating hospitals and research health professionals is its great disadvantage. Moreover, in future studies, apart from demographic and occupational features, other variables could be also studied to see if they can affect burnout and mental health.
It is concluded that public hospitals should be immediately staffed with a psychiatrist specialty as well as with a psychologist-psychotherapist in order to cover the needs of health workers and to support the therapeutic work. It is also suggested that scheduled regular screening for mental disorders in workers, at intervals which will allow the examiners doctors to follow on a personal level the course of the employees as well as to be able to carefully monitor the progress of the group.
Author Contributions
Conceptualization, all authors; Methodology, all authors; Formal Analysis, P.T., A.C.; Writing - Original Draft Preparation, P.T., A.C.; All authors have read and agreed to the published version of the manuscript.
Funding
No funding.
Institutional Review Board Statement
The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the research and ethics committee of the Scientific College of Greece (Protocol Number: TER2023225).
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement
Restrictions apply to the availability of these data. Data are available from the corresponding authors with the permission of Scientific College of Greece. The data are not publicly available because of privacy concerns, and ethical and legal restrictions.
Acknowledgments
The authors would like to thank all the health professionals who participated in the present study.
Conflicts of Interest
The authors declare no conflict of interest.
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Table 1.
Sociodemographic and occupational characteristics of the sample (N=125).
| n | 125 | |
|---|---|---|
| Gender | ||
| (Male) n (%) | 41 | 32,8 |
| (Female) n (%) | 84 | 67,2 |
| Age | ||
| 18-25 | 4 | 3,2 |
| 26-35 | 36 | 28,8 |
| 36-45 | 38 | 30,4 |
| 46-55 | 36 | 28,8 |
| >55 | 11 | 8,8 |
| Education | ||
| High school n (%) | 10 | 8,0 |
| Institute of Vocational Training n (%) | 19 | 15,2 |
| University education n (%) | 45 | 36,0 |
| Master/PhD n (%) | 51 | 40,8 |
| Marital status | ||
| Single n (%) | 36 | 28,8 |
| Married n (%) | 81 | 64,8 |
| Divorced n (%) | 6 | 4,8 |
| Widowed n (%) | 2 | 1,6 |
| Profession | ||
| Medical staff n (%) | 60 | 48,0 |
| Nurse n (%) | 35 | 28,0 |
| Nursing assistant n (%) | 23 | 18,4 |
| Supporting health care staff n (%) | 7 | 5,6 |
| Work experience (in years) | ||
| 0-5 n (%) | 24 | 19,2 |
| 6-10 n (%) | 17 | 13,6 |
| 11-15 n (%) | 25 | 20,0 |
| 16-20 n (%) | 22 | 17,6 |
| >20 n (%) | 37 | 29,6 |
Table 2.
Clinical characteristics of the sample (N=125).
| n | 125 | |
|---|---|---|
| Emotional exhaustion - MBI | ||
| 17 or less low burnout n (%) | 74 | 59,2 |
| 18-29 moderate burnout n (%) | 29 | 23,2 |
| 30 and greater high burnout n (%) | 22 | 17,6 |
| Depersonalization - MBI | ||
| 5 or less low burnout n (%) | 38 | 30,4 |
| 6-11 moderate burnout n (%) | 33 | 26,4 |
| 12 and greater high burnout n (%) | 54 | 43,2 |
| Personal accomplishment - MBI | ||
| 33 or less high burnout | 54 | 43,2 |
| 34-39 moderate burnout | 24 | 19,2 |
| 40 and greater low burnout | 47 | 37.6 |
| Anxiety - HADS | ||
| 0-7 normal | 7 | 5,6 |
| 8-10 borderline abnormal | 32 | 25,6 |
| 11-21 abnormal | 86 | 68,8 |
| Depression - HADS | ||
| 0-7 normal | 11 | 8,8 |
| 8-10 borderline abnormal | 80 | 64,0 |
| 11-21 abnormal | 34 | 27,2 |
Table 3.
Clinical characteristics of the sample (N=125).
| N | Minimum | Maximum | Mean | Std. Deviation | |
|---|---|---|---|---|---|
| Emotional exhaustion - MBI | 125 | ,00 | 41,00 | 16,6960 | 11,51382 |
| Depersonalization - MBI | 125 | ,00 | 39,00 | 12,4400 | 9,79911 |
| Personal accomplishment - MBI | 125 | 4,00 | 48,00 | 32,7040 | 12,55955 |
| Total - HADS | 125 | 1,00 | 29,00 | 21,0000 | 3,96964 |
| Anxiety - HADS | 125 | ,00 | 16,00 | 11,5040 | 2,80732 |
| Depression - HADS | 125 | 1,00 | 15,00 | 9,4960 | 1,98228 |
Table 4.
Correlation of burnout to anxiety and depression.
| Emotional exhaustion | Depersonalization | Personal accomplishment | HADS Total | HADS Anxiety | HADS Depression | |||
|---|---|---|---|---|---|---|---|---|
| Spearman's rho | Emotional exhaustion | Correlation Coefficient | 1,000 | ,754** | -,089 | -,377** | -,417** | -,076 |
| Sig. (2-tailed) | . | ,000 | ,321 | ,000 | ,000 | ,402 | ||
| N | 125 | 125 | 125 | 125 | 125 | 125 | ||
| Depersonalization | Correlation Coefficient | ,754** | 1,000 | -,235** | -,370** | -,431** | -,063 | |
| Sig. (2-tailed) | ,000 | . | ,008 | ,000 | ,000 | ,484 | ||
| N | 125 | 125 | 125 | 125 | 125 | 125 | ||
| Personal accomplishment | Correlation Coefficient | -,089 | -,235** | 1,000 | ,339** | ,401** | ,042 | |
| Sig. (2-tailed) | ,321 | ,008 | . | ,000 | ,000 | ,645 | ||
| N | 125 | 125 | 125 | 125 | 125 | 125 | ||
| HADSTotal | Correlation Coefficient | -,377** | -,370** | ,339** | 1,000 | ,834** | ,616** | |
| Sig. (2-tailed) | ,000 | ,000 | ,000 | . | ,000 | ,000 | ||
| N | 125 | 125 | 125 | 125 | 125 | 125 | ||
| HADSAnxiety | Correlation Coefficient | -,417** | -,431** | ,401** | ,834** | 1,000 | ,132 | |
| Sig. (2-tailed) | ,000 | ,000 | ,000 | ,000 | . | ,142 | ||
| N | 125 | 125 | 125 | 125 | 125 | 125 | ||
| HADSDepression | Correlation Coefficient | -,076 | -,063 | ,042 | ,616** | ,132 | 1,000 | |
| Sig. (2-tailed) | ,402 | ,484 | ,645 | ,000 | ,142 | . | ||
| N | 125 | 125 | 125 | 125 | 125 | 125 | ||
| **. Correlation is significant at the 0.01 level (2-tailed). | ||||||||
Table 5.
Differences between health professionals with various levels of emotional exhaustion in relation to anxiety and depression.
Table 5.
Differences between health professionals with various levels of emotional exhaustion in relation to anxiety and depression.
| Emotional exhaustion cut off points | N | Mean Rank | p-value | |
|---|---|---|---|---|
| HADS - Total | 17 or less low burnout | 74 | 74,17 | 0,000 |
| 18-29 moderate burnout | 29 | 51,57 | ||
| 30 or more high burnout | 22 | 40,50 | ||
| Total | 125 | |||
| HADS - Anxiety | 17 or less low burnout | 74 | 76,23 | 0,000 |
| 18-29 moderate burnout | 29 | 48,53 | ||
| 30 or more high burnout | 22 | 37,57 | ||
| Total | 125 | |||
| HADS - Depression | 17 or less low burnout | 74 | 63,74 | 0,958 |
| 18-29 moderate burnout | 29 | 62,31 | ||
| 30 or more high burnout | 22 | 61,43 | ||
| Total | 125 |
Table 6.
Differences between health professionals with various levels of depersonalization in relation to anxiety and depression.
Table 6.
Differences between health professionals with various levels of depersonalization in relation to anxiety and depression.
| Depersonalization cut off points | N | Mean Rank | p-value | |
|---|---|---|---|---|
| HADS Total | 5 or less low burnout | 38 | 81,82 | 0,000 |
| 6-11 moderate burnout | 33 | 58,26 | ||
| 12 and greater high burnout | 54 | 52,66 | ||
| Total | 125 | |||
| HADS Anxiety | 5 or less low burnout | 38 | 80,39 | 0,000 |
| 6-11 moderate burnout | 33 | 64,59 | ||
| 12 and greater high burnout | 54 | 49,79 | ||
| Total | 125 | |||
| HADS Depression | 5 or less low burnout | 38 | 73,88 | 0,029 |
| 6-11 moderate burnout | 33 | 51,35 | ||
| 12 and greater high burnout | 54 | 62,46 | ||
| Total | 125 |
Table 7.
Differences between health professionals with various levels of personal accomplishment in relation to anxiety and depression.
Table 7.
Differences between health professionals with various levels of personal accomplishment in relation to anxiety and depression.
| Personal accomplishment cut off points | N | Mean Rank | p-value | |
|---|---|---|---|---|
| HADS - Total | 33 or less high burnout | 54 | 52,41 | 0,004 |
| 34-39 moderate burnout | 24 | 61,08 | ||
| 40 and greater low burnout | 47 | 76,15 | ||
| Total | 125 | |||
| HADS - Anxiety | 33 or less high burnout | 54 | 51,13 | 0,000 |
| 34-39 moderate burnout | 24 | 57,56 | ||
| 40 and greater low burnout | 47 | 79,41 | ||
| Total | 125 | |||
| HADS - Depression | 33 or less high burnout | 54 | 61,87 | 0,929 |
| 34-39 moderate burnout | 24 | 62,52 | ||
| 40 and greater low burnout | 47 | 64,54 | ||
| Total | 125 |
Table 8.
Differences between health professionals with various levels of anxiety in relation to burnout.
Table 8.
Differences between health professionals with various levels of anxiety in relation to burnout.
| HADS - Anxiety cut off points | N | Mean Rank | ||
|---|---|---|---|---|
| Emotional exhaustion | 0-7 Normal | 7 | 76,14 | 0,000 |
| 8-10 borderline abnormal | 32 | 86,05 | ||
| 11-21 Abnormal | 86 | 53,35 | ||
| Total | 125 | |||
| Depersonalization | 0-7 Normal | 7 | 84,57 | 0,000 |
| 8-10 borderline abnormal | 32 | 81,77 | ||
| 11-21 Abnormal | 86 | 54,26 | ||
| Total | 125 | |||
| Personal accomplishment | 0-7 Normal | 7 | 53,29 | 0,006 |
| 8-10 borderline abnormal | 32 | 46,50 | ||
| 11-21 Abnormal | 86 | 69,93 | ||
| Total | 125 |
Table 9.
Differences between males and females in relation to burnout, anxiety and depression.
| Gender | N | Mean Rank | p-value | |
|---|---|---|---|---|
| Emotional exhaustion | Male | 41 | 48,39 | 0,002 |
| Female | 84 | 70,13 | ||
| Total | 125 | |||
| Depersonalization | Male | 41 | 54,23 | 0,058 |
| Female | 84 | 67,28 | ||
| Total | 125 | |||
| Personal accomplishment | Male | 41 | 69,16 | 0,184 |
| Female | 84 | 59,99 | ||
| Total | 125 | |||
| HADS - Total | Male | 41 | 77,89 | 0,001 |
| Female | 84 | 55,73 | ||
| Total | 125 | |||
| HADS - Anxiety | Male | 41 | 73,72 | 0,020 |
| Female | 84 | 57,77 | ||
| Total | 125 | |||
| HADS - Depression | Male | 41 | 72,84 | 0,031 |
| Female | 84 | 58,20 | ||
| Total | 125 |
Table 10.
Differences between levels of age in relation to burnout, anxiety and depression.
| Age | N | Mean Rank | p-value | |
|---|---|---|---|---|
| Emotional exhaustion | 18-25 | 4 | 75,00 | 0,387 |
| 26-35 | 36 | 65,33 | ||
| 36-45 | 38 | 67,74 | ||
| 46-55 | 36 | 59,72 | ||
| 55+ | 11 | 45,36 | ||
| Total | 125 | |||
| Depersonalization | 18-25 | 4 | 73,13 | 0,231 |
| 26-35 | 36 | 69,81 | ||
| 36-45 | 38 | 63,47 | ||
| 46-55 | 36 | 61,17 | ||
| 55+ | 11 | 41,41 | ||
| Total | 125 | |||
| Personal accomplishment | 18-25 | 4 | 48,50 | 0,452 |
| 26-35 | 36 | 54,81 | ||
| 36-45 | 38 | 66,67 | ||
| 46-55 | 36 | 66,88 | ||
| 55+ | 11 | 69,73 | ||
| Total | 125 | |||
| HADS - Total | 18-25 | 4 | 50,25 | 0,087 |
| 26-35 | 36 | 51,76 | ||
| 36-45 | 38 | 74,66 | ||
| 46-55 | 36 | 62,19 | ||
| 55+ | 11 | 66,77 | ||
| Total | 125 | |||
| HADS - Anxiety | 18-25 | 4 | 66,00 | 0,016 |
| 26-35 | 36 | 46,53 | ||
| 36-45 | 38 | 72,99 | ||
| 46-55 | 36 | 64,35 | ||
| 55+ | 11 | 76,91 | ||
| Total | 125 | |||
| HADS - Depression | 18-25 | 4 | 37,63 | 0,446 |
| 26-35 | 36 | 66,07 | ||
| 36-45 | 38 | 67,88 | ||
| 46-55 | 36 | 59,61 | ||
| 55+ | 11 | 56,41 | ||
| Total | 125 |
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