|Year : 2021 | Volume
| Issue : 2 | Page : 139-143
A study to assess the level of burnout and its determinants among medical practitioners working in a tertiary care center in South India
G Ananda Krishna1, Chandra Sekhar Chittooru2, Sravana Deepthi Chittem2, Surendra Babu Darivemula3, Niharika Bheemisetty2
1 Department of Community Medicine, Osmania Medical College, Hyderabad, Telangana, India
2 Department of Community Medicine, Apollo Institute of Medical Sciences and Research, Chittoor, Andhra Pradesh, India
3 Department of Community Medicine, ESIC Medical College and Hospital, Hyderabad, Telangana, India
|Date of Submission||05-Apr-2021|
|Date of Decision||04-Jul-2021|
|Date of Acceptance||05-Jun-2021|
|Date of Web Publication||02-Feb-2022|
Chandra Sekhar Chittooru
Department of Community Medicine, Apollo Institute of Medical Sciences and Research, Murukambattu, Chittoor - 517 127, Andhra Pradesh
Source of Support: None, Conflict of Interest: None
Background: Burnout is defined as a feeling of hopelessness and inability in carrying out one's job effectively. Burnout in the life of medical practitioners is a term used to describe a psychological state, which appears after a long period of exposure to psychosocial risk factors such as high patient load, long working hours, and unreasonable demands from patients. The objective was to study the prevalence of burnout among medical practitioners and factors associated with burnout. Methodology: The study was a descriptive cross-sectional study conducted among medical practitioners of tertiary care hospital with a sample of 102. The study was conducted using the Maslach Burnout Inventory with additional questions on demographic factors, work experience, hours of work, and specialty. Data were entered in MS Excel 2007 and analyzed with IBM SPSS statistics 21 version. Results: Out of 102 subjects, 26 (25.5%) members were suffering from burnout in any one of the three dimensions. In the emotional exhaustion, 15 (14.7%) were experiencing high scores, 14 (13.7%) members, and 73 (71.6%) members were experiencing moderate and low scores, respectively. However, in the depersonalization dimension, just 1 (1%) member was experiencing high score, whereas 11 (10.8%) members and 90 (88.2%) members were experiencing moderate and low scores, respectively. In the personal accomplishment dimension, 16 (15.7%) members were experiencing high scores, whereas 13 (12.7%) members and 73 (71.6%) members were experiencing moderate and low scores, respectively. Conclusions: Burnout exists among medical practitioners, and measures should be taken to identify causes and take remedial actions.
Keywords: Burnout, medical practitioners, tertiary care center
|How to cite this article:|
Krishna G A, Chittooru CS, Chittem SD, Darivemula SB, Bheemisetty N. A study to assess the level of burnout and its determinants among medical practitioners working in a tertiary care center in South India. J Mental Health Hum Behav 2021;26:139-43
|How to cite this URL:|
Krishna G A, Chittooru CS, Chittem SD, Darivemula SB, Bheemisetty N. A study to assess the level of burnout and its determinants among medical practitioners working in a tertiary care center in South India. J Mental Health Hum Behav [serial online] 2021 [cited 2022 Jun 26];26:139-43. Available from: https://www.jmhhb.org/text.asp?2021/26/2/139/337176
| Introduction|| |
In the contemporary world, health care has emerged as an industry. The health-care industry is no exception from being tormented by the stress factor. Stress has been incriminated in various manifestations by many research studies. One of such manifestation is “Burnout.” Burnout is defined as a feeling of hopelessness and inability to carry out one's job effectively. Burnout was coined to describe worker's reactions to the chronic stress common in occupations having a direct interface with people. Burnout in the life of medical practitioners is a term used to describe a psychological state which appears after a long period of exposure to psychosocial risk factors such as high patient load, long working hours, and unreasonable demands from the patients. This can be indicated by feelings of overwhelming exhaustion, depersonalization (DP), or cynicism toward people and work and a sense of professional inefficacy.,
The doctor should be ready to attend the patient whenever in need, which means have to go to their place of employment or wherever the patient is at that time. It can sometimes result in varying levels of exhaustion and sleep deprivation. Burnout may lead to interpersonal problems, insomnia, irritability, and suicidal ideation. It may closely resemble a psychological mood disorder known as dysthymia. Burnout has been linked to risk factors of cardiovascular disease. It has been associated with high levels of cholesterol, glucose, triglycerides, uric acid, and marginally with electrocardiography abnormalities. Burnout has also been linked to a higher risk of Type II diabetes. At the organizational level, burnout entails adverse outcomes such as a lack of concentration, poor timekeeping, reduced productivity, difficulty in comprehending new procedures, lack of cooperation, irritability, aggressiveness, resentment, and increased tendency to make mistakes., It may endanger the reputation of the health-care system and put the confidence among the public at stake.
In view of the consequences brought out by burnout, it is high time to pay much attention to this plaguing problem and prevent it from wreaking havoc at the individual and organizational levels. This requires in-depth research into the problem, which will give better insight to cope up. Many studies have been done in the west regarding burnout and its determinants. In India, except for a few, there is a paucity of knowledge to throw light over the issue. Hence, this study was planned among medical practitioners in a tertiary care setup in an urban area to find the prevalence of burnout and its associated factors.
| Methodology|| |
It was an observational descriptive cross-sectional study done among medical practitioners of the grade assistant professor and above registered under the Medical Council of India, working in Apollo Institute of Medical Sciences and Research, Chittoor, Andhra Pradesh, during October to December 2019. A “health professional” whose practice is based on direct observation and treatment of a patient, as distinguished from other types of health workers such as laboratory technicians and those employed in research were included in the study. A sample size of 97 was obtained by considering 70% prevalence based on previous studies, absolute precision of 10, and an anticipated nonresponse rate of 15%. A list of 186 medical practitioners working in the hospital was prepared, and 102 practitioners were selected from them using a simple random sampling method by computer-generated random numbers.
The study was conducted using a Modified Maslach Burnout Inventory – human services survey (MBI-HSS) for assessing burnout. It consists of 22 items, divided into three subscales: emotional exhaustion (EE) – nine items, DP – five items, and personal accomplishment (PA) – eight items. The questions were answered in terms of the frequency with which the respondent experiences these feelings on a 7-point scale ranging from 0 (never) to 6 (every day). The three scores were calculated for each respondent. A higher score indicates higher burnout except for the PA scale, which was rated inversely.
Burnout was defined as the presence of one or more of the following:
- A high score in EE (>27)
- A high score in DP (>13)
- A low score in PA (<31).
However, the burnout experienced by the respondent in every individual dimension was categorized into low, moderate, and high level based on the cutoff scores:  in EE dimension, ≥27 was considered as high, 17–26 was taken as moderate, and 0–16 as low; in DP dimension, ≥14 was taken as high, 9–13 as moderate, and 0–8 as low; and in PA dimension, 0–30 was considered as high, 31–36 as moderate, and ≥ 37 as low.
The MBI-HSS is a self-administered questionnaire, and it takes 10–15 min to fill. Along with this, information regarding sociodemographic (age, gender, and marital status) and occupation-related information (work experience, hours of work, and specialty) also were gathered to assess their role in burnout. The interviewer personally met the participants and explained the purpose of the study. Before administering the questionnaire, consent was taken from them, and they were assured about the confidentiality of the data and asked to fill this questionnaire when they were free and alone to avoid bias. Institutional ethical committee permission was also obtained to conduct the study. Data were entered into an Excel sheet, and analysis was done using the
IBM SPSS software 21 version (IBM Corp., Armonk, New York, USA). Data with categorical variables were presented in percentages and the association between variables were tested using the Chi-square test. The correlation between the subscales, work experience in years, and working hours per day was assessed using the Pearson correlation coefficient. Binary logistic regression was done to know the predictor variables for burnout. Significance was estimated at a probability of 5% level (P < 0.05).
| Results|| |
Actually, 102 medical practitioners were included in the study, above the sample size of 97. Out of them, 62 (60.8%) were males and 40 (39.2%) were females. The mean age of the study group was found to be 41.7 years ranging from 29 to 59 years. About 50 (49%) members were working in the medical or related specialties, whereas the rest 52 (51%) were in the surgical or associated specialties. Around 30 (29.4%) members had a practice experience of 0–5 years, 30 (29.4%) members had an experience of 6–10 years, 17 (16.7%) members had an experience of 11–15 years, and 25 (24.5%) members had a practice experience of over 15 years at the time of data collection.
Out of 102 subjects, 26 (25.5%) members were suffering from burnout in any one of the three dimensions. In the EE dimension, 15 (14.7%) were experiencing high scores, 14 (13.7%) were experiencing moderate scores, and 73 (71.6%) were experiencing low scores. However, in the DP dimension, just 1 (1%) member was experiencing a high score, whereas 11 (10.8%) members and 90 (88.2%) members were having moderate and low levels of scores, respectively. In the PA dimension, 16 (15.7%) members had high scores, whereas 13 (12.7%) members and 73 (71.6%) members had moderate and low levels of scores, respectively [Figure 1].
Burnout was not showing a significant association with gender, practitioners belonging to the medical or surgical branches, work experience, and marital status, but it was significantly higher in practitioners of age ≤35 years (37.9%) than practitioners of age 36–50 years (25.9%) and above 50 years (0%) [Table 1].
Work experience showed a significant positive correlation with PA scores and negative correlation with EE (not significant) and the DP dimensions (significant). Working hours per day showed a positive correlation with EE and PA dimensional scores and a negative correlation with DP dimensional scores. However, nowhere, these correlations were found to be statistically significant. EE scores showed a significant positive correlation with DP dimensional scores and negative correlation with PA dimensional scores (not significant). DP dimensional scores and PA dimensional scores were negatively correlated with each other (not significant) [Table 2].
|Table 2: Correlation of the domains with work experience, working hours per day, and with another domain|
Click here to view
The predictors of burnout tested in the Binary logistic regression were age, gender, marital status, years of practicing experience, working hours/day, and specialty. Predictor's Odd's ratios along with their 95% confidence interval limits were obtained [Table 3]. It was evident that only the female gender and the age were having an adequate predictive capacity for the burnout outcome, and the observation was found to be statistically significant. Nagelkerke R2 value for the binary logistic regression model was found to be 0.260 which meant that 26% of variation in the burnout can be explained by the variations in the predictors in the model.
| Discussion|| |
The prevalence of burnout in the present study was found to be 25.5%. It was almost comparable with the prevalence reported by a study done in the nearby region, Vishakhapatnam, among clinicians (32.9%). It might be due to the same working environmental conditions prevailing in the region. Rotenstein et al. reported that the prevalence of overall burnout among physicians will vary from 0% to 80.5%, depending on the burnout ascertainment methods, definitions, and outcomes, as well as statistical heterogeneity by reviewing 182 studies. Around 14.7% of the practitioners reported that they have high scores in the EE dimension, and 15.7% had shown low PA scores. These figures are comparable to the prevalence of high EE scores (18%) and the low PA scores (21%) in the study from Vishakhapatnam. High EE burnout scores were reported in the study from Yemen (63.2%), Nigeria (45.6%), Spain (36.5%), USA (54%), and in India (45%). It has been clear from this that the EE burnout in our study was nowhere comparable to them. Low levels of PA scores in the present study (21%) were somewhat comparable to the study from Yemen (33%). As in other dimensions, it was far lower than the earlier studies.,,, However, the prevalence of burnout in the DP dimension in our study (1%) is far less than the study from Vishakhapatnam (10%).
In the present study, the high degree of burnout, which was inclusive of all dimensional burnouts in an individual, is just 1%. This was brought out by the 1% DP high burnout score. This paltry figure might be due to the practitioner's perception of moral restraint on themselves to be more accommodative with the patients. However, this prevalence was found to be much higher in the study from Yemen (11.7%) and China (12.1%).
The present study showed that age was significantly related to the presence of burnout among practitioners. It was evident from the study that the burnout was found more in the younger ones. This finding had a resemblance to the study from Vishakhapatnam, Yemen, Nigeria, China, and India. However, the association was not statistically significant in the study from China. Similar to the present study, in the study from Yemen also, binary logistic regression was done, which had shown a significant predictive capacity of age over burnout.
Regarding gender, the present study showed that the prevalence of burnout was higher in females (35%) than males (19.4%). Female gender was proving to have a more predictive capacity over males on burnout in binary logistic regression with an odds ratio of 3.9. A similar finding was seen in the study from Vishakhapatnam, India, and Holland. It coulb be explained by the relative masculinity required to cope up with the demanding work environment, which might be less among the females and the gender role conflicts among females to fulfill their mundane family tasks. However, the contrary finding was seen in a study from Nigeria and family medicine and psychiatry resident's study. There was no significant association observed between gender and burnout in a study from China. It might be due to the cultural differences and the gender expectation differences prevailing in the respective countries.
Among specialties, the difference in the prevalence rates of burnout between medical and surgical specialty groups was not found to be significant because burnout was marginally higher in the surgical specialty (26.9%) than medical specialty group (24%). Similar finding also reported in studies from Vishakhapatnam and Nigeria. Coming to marital status, the difference in burnout levels between the married group and the unmarried ones was not statistically significant even though the prevalence was higher in the unmarried group (40%). However, a similar result was obtained in a study done on family medicine and psychiatry residents.
It was found in this study that those having lower experience in terms of practice in years were having higher burnout scores than the ones with more experience. The resemblance to this had been shown in the studies from Vishakhapatnam and Yemen. Antithetically, in the study from India where subjects were taken across the country, burnout has been positively correlated with the work tenure in years. Hence, more research is imperative in this direction. It was evident from the binary logistic regression that more working hours per day was a predictor for burnout with an odds ratio of 1.24, but this was not significant statistically. Heavy workload has been complained by many study subjects with a burnout in the study from Nigeria.
EE scores were found to be correlated positively and negatively with the DP and PA scores, respectively. However, only the former correlation was statistically significant. In line with the design of the MBI scale, the DP score was negatively correlated with the PA scores, but the correlation was not statistically significant. However, these correlations could not give any information regarding the sequential or parallel development of the dimensions of burnout, as proclaimed in the earlier studies.,
Although we tried hard to minimize the limitations, following limitations were reported in the study. First, causal relationship between the variables cannot be ascertained because of cross-sectional nature of the study. Second, likelihood of recall bias in the self-reported measures may hinder the drawing up of generalisations. Third, negative affectivity was not taken into consideration while conducting the study. Individuals with high negative affectivity may perceive their work context more negatively, which would artificially strengthen the associations between burnout symptoms and the work environment.
| Conclusions|| |
The prevalence of burnout reported was 25.5%, and it was more profound in females than in males and younger age group practitioners than older age group practitioners. The burnout of the practitioners was not dependent on the type of specialty and the marital status of the practitioners. The workload was positively associated with burnout. More experienced practitioners had reported low levels of burnout than the less experienced ones. The EE dimension correlated significantly with the DP dimension.
In this regard, mental health prevention and promotion programs should be targeted at health-care providers as they constitute a high-risk group. Measures should be taken to sensitize the doctors about stress management and self-regulation. Improving the doctor-to-patient ratio on a priority basis can curtail to some extent the misconceptions among patients about doctors such as apathy and callousness. Health reforms should be brought in where doctor's well-being should be seen by the health-care organizations as primacy and central to the patient care. Female doctors should get the support from family, colleagues, and from the management to cope up and to lead a burnout free life. Internationally coordinated research efforts are the need of the hour to identify evidence-based strategies to reverse the rising tide of burnout globally.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Pfifferling JH, Gilley K. Overcoming compassion fatigue. Fam Pract Manag 2000;7:39-44.
Freudenberger HJ. Staff burn-out. J Social Issues 1974;30:159-65.
Maslach C, Schaufeli WB, Leiter MP. Job burnout. Annu Rev Psychol 2001;52:397-422.
Maslach C, Leiter MP. Understanding the burnout experience: Recent research and its implications for psychiatry. World Psychiatry 2016;15:103-11.
Lee YY, Medford AR, Halim AS. Burnout in physicians. J R Coll Physicians Edinb 2015;45:104-7.
Salanova M, Llorens S. Current state of research on burnout and future challenges. Papeles Psicól 2008;29:59-67.
Melamed S, Kushnir T, Shirom A. Burnout and risk factors for cardiovascular diseases. Behav Med 1992;18:53-60.
Melamed S, Shirom A, Toker S, Shapira I. Burnout and risk of type 2 diabetes: A prospective study of apparently healthy employed persons. Psychosom Med 2006;68:863-9.
Barnett RC, Brennan RT, Gareis KC. A closer look at the measurement of burnout. J Appl Biobehav Res 1999;4:65-78.
Wood BD, Killion JB. Burnout among healthcare professionals. Radiol Manage 2007;29:30-5.
Mosby. Mosby's Medical Dictionary. 9th ed. St. Louis, MO: Elsevier; 2013.
Aldrees TM, Aleissa S, Zamakhshary M, Badri M, Sadat M. Alid Physician well-being: Prevalence of burnout and associated risk factors in a tertiary hospital, Riyadh, Saudi Arabia. Ann Saudi Med 2013;33:451-6.
Rafferty JP, Lemkau JP, Purdy RR, Rudisill JR. Validity of the Maslach Burnout Inventory for family practice physicians. J Clin Psychol 1986;42:488-92.
Guntupalli KK, Wachtel S, Mallampalli A, Surani S. Burnout in the intensive care unit professionals. Indian J Crit Care Med 2014;18:139-43.
] [Full text]
Chepuru R, Lotheti SK, Bhimarasetty DM. Burnout among clinicians in the tertiary care setting. Int J Community Med Public Health 2018;5:1157-61.
Rotenstein LS, Torre M, Ramos MA, Rosales RC, Guille C, Sen S, et al.
Prevalence of burnout among physicians: A systematic review. JAMA 2018;320:1131-50.
Al-Dubai SA, Rampal KG. Prevalence and associated factors of burnout among doctors in Yemen. J Occup Health 2010;52:58-65.
Ogundipe OA, Olagunju AT, Lasebikan VO, Coker AO. Burnout among doctors in residency training in a tertiary hospital. Asian J Psychiatr 2014;10:27-32.
Escribà-Agüir V, Martín-Baena D, Pérez-Hoyos S. Psychosocial work environment and burnout among emergency medical and nursing staff. Int Arch Occup Environ Health 2006;80:127-33.
Langade D, Modi PD, Sidhwa YF, Hishikar NA, Gharpure AS, Wankhade K, et al.
Burnout syndrome among medical practitioners across India: A questionnaire-based survey. Cureus 2016;8:e771.
Wu H, Liu L, Wang Y, Gao F, Zhao X, Wang L. Factors associated with burnout among Chinese hospital doctors: A cross-sectional study. BMC Public Health 2013;13:786.
Geurts S, Rutte C, Peeters M. Antecedents and consequences of work-home interference among medical residents. Soc Sci Med 1999;48:1135-48.
Woodside RD, Miller MN, Floyd MR, McGowen R, Pfortmiller DT. Observations on burnout in family medicine and psychiatry resident. Acad Psychiatry 2008;32:13-9.
Leiter MP. Burnout as a Developmental Process: Consideration of Models. In: W Schaufeli, C Maslach, Marek T, editors. Professional burnout: Recent developments in theory and research. Washington: Taylor & Francis; 1993. p. 237-50.
Leiter MP, Maslach C. The impact of interpersonal environment on burnout and organization commitment. J Organ Behav 1988;9:297-308.
[Table 1], [Table 2], [Table 3]