|Year : 2012 | Volume
| Issue : 2 | Page : 119-124
Internal predictors of burnout in psychiatric nurses: An Indian study
Rudraprosad Chakraborty1, Arunima Chatterjee2, Suprakash Chaudhury3
1 Department of Psychiatry, Berhampore Mental Hospital, Berhampore, Murshidabad, West Bengal, India
2 Department of Psychiatry, Berhampore Sadar Hospital, Berhampore, Murshidabad, West Bengal, India
3 Pravaara Institute of Medical Sciences (Deemed University), Rural Medical College and Pravara Rural Hospital, Loni, Maharashtra, India
|Date of Web Publication||9-Oct-2013|
Department of Psychiatry, Pravaara Institute of Medical Sciences (Deemed University), Rural Medical College and Pravara Rural Hospital, Loni - 413 736, Dist. Ahmednagar, Maharashtra
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: Research has not adequately focused on the issue of burnout in Psychiatric nurses, despite the fact that they suffer considerable stress in their work. Till date no study has been conducted on burnout among psychiatric nurses in India. Further, there is a particular lack of research in internal variables predicting burnout in them. Aims: To determine whether there are any internal psychological factors relevant to burnout in psychiatric nurses in India. Materials and Methods: We recruited 101 psychiatric nurses scoring less than two in General Health Questionnaire, version 12 (GHQ-12) from two psychiatric hospitals after obtaining informed consent. All subjects filled up a sociodemographic data sheet along with global adjustment scale, emotional maturity scale, PGI general well-being scale, locus of control scale, and Copenhagen burnout inventory (CBI). Correlations between burnout and sociodemographic/clinical variables were done by Pearson's r or Spearman's rho. Signi ficant variables were entered in a stepwise multiple linear regression analysis with total burnout score as dependent variable. Results: Age, duration of total period of nursing, prior military training, locus of control, sense of general well-being, adjustment capabilities, and emotional maturity had significant relation with burnout. Of them, emotional maturity was the most significant protective factors against burnout along with adjustment capabilities, sense of physical well-being, and military training in decreasing significance. Together they explained 41% variation in total burnout score which is significant at <0.001 level. An internal locus of control was inversely correlated with burnout, but failed to predict it in regression analysis. Conclusion: Emotional maturity, adjustability, sense of general physical well-being as well as prior military training significantly predicted lower burnout. Of them, emotional maturity was the most important predictor. Internal locus of control was also correlated with lower burnout.
Keywords: Adjustability, burnout, emotional maturity, psychiatric nurses, well-being
|How to cite this article:|
Chakraborty R, Chatterjee A, Chaudhury S. Internal predictors of burnout in psychiatric nurses: An Indian study. Ind Psychiatry J 2012;21:119-24
Freudenberger  first used the term burnout to describe the feeling of failure and exhaustion that can be observed in social workers that worked in institutions, and it was the result of immoderate requirements of energy, effort, and qualifications. Burnout is a state of physical, mental, and emotional exhaustion that often results from a combination of very high expectation and persistent situational stress. It describes a state of depletion of a person's resources, particularly energy due to excessive demands made on him as a result of which the individual becomes apathetic and impassive towards his work and other aspects of his life. It has dysfunctional repercussions on the individual and adverse effects on the organization. It may reflect in a continued dissatisfaction with the situation, ranging from mild boredom to severe depression, irritation, exhaustion, and physical ailment. The experience of too much pressure and very few sources of satisfaction can develop into a feeling of exhaustion leading to burnout. 
Professionals that have frequent contact with individuals are more sensitive to develop burnout.  Among the different health professions, nursing has been considered a profession highly susceptible to stress. Several major factors of nursing stress have been proposed including: Work overload, interprofessional conflict, lack of clarity, task ambiguity, and supervision problems. ,, Overload and role ambiguity are frequently highlighted.  Other authors have underlined the increasing complexity of the tasks and lack of clarity of nursing functions as a source of overload and role ambiguity. , Some studies have specifically reported that burnout is related to the amount of time that nurses spend with their patients,  with the intensity of patients' emotional demands,  and with patients' poor prognosis.  Among the sociodemographic factors, age has been the factor most consistently related to burnout. 
Although psychiatric nurses face considerable stress in their job, ,,, research into nursing burnout has mainly focused on general nursing rather than psychiatric nursing. , Further, most studies on nurses' burnout have focused almost exclusively on the workplace environment. , It is increasingly recognized that some internal characteristics may prevent work-related tension from becoming stress-related health problems,  thus preventing burnout. Empirical studies have linked burnout to emotional exhaustion,  'poorer' locus of control,  control and challenged hardy personality, , emotion-focused coping,  active coping,  and a decreased sense of well-being. 
Unfortunately most of the studies on burnout in psychosocial nursing have been conducted in Europe and United States. ,,,,, There are few studies from Asian countries. , Indeed, a thorough search in PubMed on 01.10.2011 using keywords of burnout, psychiatric nursing, and India revealed no research on burnout in psychiatric nursing from India. One reason why psychiatric nurses and their burnout is an under studied area could be the fact that there are many states where psychiatric nurses are scarce. In view of the paucity of Indian in this area, the present work was undertaken to identify the predictors of burnout in an Indian psychiatric nursing population. As majority of the studies in burnout focused on work environment, , we tried to examine mainly the role of several internal factors like emotional maturity, adjustment capability, sense of well-being, and locus of control apart from different sociodemographic variables. As the sociocultural background of Indian psychiatric nurses varies widely from their western counterparts, we expected to identify predictors of burnout relevant to them. Finding predictors of burnout relevant in an Indian setting should have important policy implications in human resource management in this sector in similar developing countries.
| Materials and Methods|| |
We approached the psychiatric nurses working in two major tertiary psychiatric centers in India for participation in the study. To be included in the study, participants needed to be psychologically healthy, which was determined by a score of less than two on General Health Questionnaire, version 12 (GHQ-12).  We assured full confidentiality of the information given to all participants in writing. This helped them to answer questions freely. A total of 101 staff nurses fulfilled the inclusion criterion and also consented for the study. There was no refusal of consent among those who fulfilled the study inclusion criteria.
All the participants filled up a sociodemographic information sheet and the following self-rating questionnaires.
Global adjustment scale
GAS  measures adjustment in six primary areas of adjustment. It is used to analyze and report individual differences in adjustment, and point out specific problem areas. It measures adjustment in six areas: Family, health, social, emotional, occupational, and sexual adjustment. It has acceptable reliability and validity.
Emotional maturity scale
Emotional maturity scale  measures a construct of emotional maturity by the following components: Emotional instability (inability to dispose of problems, need for constant help, stubbornness, temper tantrums), emotional regression (feeling of inferiority, aggression, restlessness and self-centeredness), social maladjustment (lack of social adaptability), personality disintegration (pessimism, reaction formation, rationalization), and lack of independence. Higher the mean score on the scale, greater the degree of emotional immaturity and vice versa. The scale enjoys a good reliability coefficient using both test-retest and internal consistency methods.
PGI general well-being scale
PGI general well-being scale  is a 20-item questionnaire measuring how much the respondent has a sense of general physical well-being. It deals with various aspects of well-being such as worry, distress, life satisfaction, control, etc., It has satisfactory validity and highly significant reliability, that is, K.R. 98 and discriminative value. The scale correlated significantly with Bradburn's scale.
Locus of control scale
Locus of control scale  is a 36-item self rating questionnaire measuring locus of control. The higher a person's score in this scale, the more internally oriented the individual will be. The scale is highly reliable and valid having reliability coefficient of 0.55 and coefficient of temporal stability of 0.76.
All the above scales were selected as they have been developed and standardized on Indian population and have proven reliability and validity. ,,, As these scales are in Hindi, they could be easily administered in the study population.
Copenhagen burnout inventory
The CBI  is a public domain questionnaire measuring the degree of physical and psychological fatigue experienced in three subdimensions of burnout: Personal, work-related, and client-related burnout. The combination of these gives a score of total burnout. The CBI had acceptable reliability (internal consistency and homogeneity) as well as factorial and criterion-related validity. The CBI has been widely used in Asian countries ,, including India.  The CBI is very appropriate for measuring burnout in hospital personnel.
Correlations between total burnout score and different sociodemographic and clinical variables were examined using Pearson's r for continuous variables and Spearman's rho for categorical variables. Variables which had significant correlation were entered as independent variables in a multiple linear regression analysis. Stepwise method was chosen as we did not have any past research data in this regard to base our model. Total burnout score was entered as the dependent variable.
| Results|| |
Mean age of the participants was 44 ± 8.53 years. Majority were female (n = 85; 84.2%), married (n = 94; 93.1%), and from tribal background (n = 71; 70.3%). Thirty-six participants (35.6%) hailed from joint family, 61 (60.4%) from nuclear family, and four (4%) were living alone. Sixty-six (65.3%) were Christian, 29 (28.7%) Hindus, three (3%) Muslims, and three (3%) were from other religious background.
Participants had an average 20.79 ± 8.21 years' experience in nursing of which 15.19 ± 9.00 years were spent in psychiatric nursing. They had 13.23 ± 2.32 years of education of which 50 persons (49.01%) had a postgraduate diploma in psychiatric nursing. Average income of the participants was Indian rupees (INR) 14858.65 ± 3654.08 per month. Out of total 17 male participants, 14 (13.9%) were ex-servicemen.
Age, duration of total period of nursing, duration of army service, locus of control, sense of general well-being, adjustment, and emotional maturity had significant correlation with total burnout [Table 1] while qualification, marital status and family status dis not have a significant correlation [Table 2].
|Table 1: Pearson's correlation: Burnout and continuous predictor variables|
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|Table 2: Spearman's correlation: Burnout and discrete predictor variables|
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These variables were then included as independent variables in a stepwise multivariate regression analysis. Total burnout was entered as the dependent variable. R 2 value implied that 43.9% of total variance in burnout in sample population was explained by the model. Adjusted R 2 value implied if this model was applied in psychiatric nursing population in general, still it would be able to explain about 41.5% of variance in total burnout scores. This prediction was significant at ≤ 0.001 level. Durbin-Watson value implied that assumption of independent errors was satisfied [Table 3]. Emotional maturity, adjustment, duration of prior army service, and sense of general well-being were significant predictors of burnout score in decreasing order of significance. Among the predictors, emotional maturity explained 31%, adjustment capacity 6.8%, army service 3.7%, and sense of well-being explained 2.4% of variance in total burnout scores. Variation inflation factor (VIF) and tolerance value confirmed that there was little collinearity among the predictors in the model [Table 4]. ZPRED (x-axis) × ZRESID (y-axis) histogram and scatterplot were drawn [Figure 1] and [Figure 2]. These showed that the residuals are normally distributed and assumptions of linearity and homoscedasticity were satisfied. Fulfilling these assumptions indicated that we can generalize the findings from this study in any similar Indian psychiatric nursing population.
| Discussion|| |
In the recent past, several Asian studies have focused on burnout syndrome in nurses. Compared with the prior studies of hospital staffs in other countries, doctors and nurses in Mongolia had relatively higher burnout rates.  Singaporean nurses experience high levels of stress related to work. Emergency and surgical nurses appear to perceive higher levels of stress than ward- and clinic-based nurses. The most stressful situations for Singaporean nurses were patient-related difficulties and conflicts with colleagues. Organizational issues, such as lack of participation in planning and difficulty in making changes also contributed to work stress experienced by nurses. They also felt vulnerable to stress arising from the interface of work and family commitments.  Problems with childcare were significantly associated with emotional exhaustion among Turkish nurses.  Iranian nurses also reported perceived work dissatisfaction and health threats, and disequilibrium between family and work demands.  Psychiatric nurses in Iran experienced a significantly greater degree of emotional exhaustion than the medical nurses. Significant positive correlation was noted between ages, years of experience, frequency of on-calls, and emotional exhaustion for the psychiatric nurses. Frequency of on-calls was also significantly associated with a sense of non-accomplishment. Longer duration of service was accompanied by higher degree of emotional depersonalization for medical nurses.  Burnout syndrome was highly prevalent among nurses and medical residents from a Tunisian hospital. High scores in emotional tiredness correlated with depression and with personal difficulties.  In Saudi Arabia, the prevalence of burnout syndrome among multinational nurses was high. Frequency of depersonalization was 42%, whereas 45% had high emotional exhaustion and 71.5% had a sense of low personal accomplishment. Married nurses were prone to emotional exhaustion. The nurses in the patients' wards and clinics were more emotionally exhausted with higher depersonalization. Non-Saudi nurses were significantly more prone to emotional exhaustion than Saudi nurses. Working away from their home countries was an additional risk factor in expatriate nurses. 
Most of the above studies focused on external causes of burnout like organizational variables and interpersonal and emotional interactions at work. In the present study; it was found that internal factors like emotional maturity, adjustment capability, sense of well-being as well as prior military training explained more than 41% variation in total burnout score; which was significant at ≤0.001 level. It implies that workplace factors are not the only reason for burnout. There have to be some intrinsic variables as revealed in our study. Among these predictors, emotional immaturity was found to be the most important. The emotional immaturity construct as measured by emotional maturity scale in this study implied that persons who experienced high burnout were emotionally unstable, vulnerable to emotional regression, and personality disintegration had social maladjustment and suffered from lack of independence. In a way, it indicates that burnout may be related with a poor management of emotions. This is consistent with earlier reports that burnout in nurses was associated with more psychosomatic symptoms, more medication use, lower levels of positive affect, and less life satisfaction.  Further, a recent study has reported that a mindfulness course improved well-being and decreased burnout among healthcare providers in Australia. 
Burnout also appears to be related with inability to adjust with surrounding environment, as evidenced by significant prediction by adjustment score. Indeed, persons who experienced burnout had poor adjustment in their family, society, health-related matters, and even in sexual life. It appears that poor adjustment skills along with poor management of emotions were sure recipe of burnout. Previous studies also found that problematic relationships among team members increased burnout.  Verbal abuse from physicians was noted to be stressful for staff nurses.  In a study of 260 registered nurses (RNs), conflict with physicians was found to be more psychologically damaging than conflict within the nursing profession.  However, a study exploring verbal abuse among 213 nursing personnel (95% RNs) found the most frequent source of abuse was other nurses (27%), families were the second most frequent source of abuse (25%), while physicians ranked third (22%).  This finding underlines the importance of good adjustment in work and home for reducing burnout.
Interestingly, prior military training prevented burnout in nursing personnel. This may be related to the inherent discipline and adaptation to challenges in army service. Also, a sense of general physical well-being prevented burnout. May be such a feeling led to less chance of emotional exhaustion. Interestingly all participants were free of any comorbid mental disorder as screened by GHQ-12 which means there was no confounding effect of psychiatric morbidity among participants.
Burnout was negatively correlated with an internal locus of control. Individuals with an internal locus of control define stressors as controllable and are more likely to attempt to cope with them through problem focused action, and thereby do not suffer burnout.  However, internal locus of control failed to predict burnout in the regression analysis.
Similarly in an earlier study, external locus of control had demonstrated a positive relationship with burnout. 
Overall, this study has some valuable implications for psychiatric nursing as well as other mental health professionals. Predictors of burnout such as emotional maturity, locus of control, general well-being, and adjustment may be modulated by proper training and therapeutic programs to promote positive mental health in mental health professionals. Further, this study indicates that some people may be particularly prone to burnout than others. This may have important implication in management and recruitment policies. As, burnout leads to decrease in quality of care and in turn, financial loss for organizations, recruitment policy may be suitably tailored to identify personnel with low propensity to burn out.
An important limitation of the present study was that the two hospitals were located at the same place. A multicentric study would have been more useful. The lack of a control group was another limitation.
| Conclusions|| |
Emotional maturity, adjustability, sense of general physical well-being as well as prior military training significantly predicted lower burnout. Of them, emotional maturity was most important predictor. Internal locus of control was also correlated with lower burnout.
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[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4]