|Year : 2015 | Volume
| Issue : 2 | Page : 131-137
Job satisfaction among hospital staff working in a Government teaching hospital of India
Poonam Jaiswal1, AK Gadpayle2, Ashok K Singhal1, Sandeep Sachdeva3, Rajesh Kumar Modi4, Rabindra Padaria5, V Ravi6
1 Department of Hospital Administration, PGIMER, Dr. RML Hospital, New Delhi, India
2 Department of Medicine, PGIMER, Dr. RML Hospital, New Delhi, India
3 Department of Community Medicine, PGIMER, Dr. RML Hospital, New Delhi, India
4 New Delhi, India
5 Indian Agricultural Research Institute, New Delhi, India
6 Lady Shri Ram College, New Delhi, India
|Date of Web Publication||13-Mar-2015|
Department of Hospital Administration, PGIMER, Dr. RML Hospital, New Delhi
Source of Support: None, Conflict of Interest: None
Background: In a resource-limited and high burden disease setting, satisfied human resource is an asset in terms of high productivity, efficiency and quality care. Aim: To assess job satisfaction among permanent employees working in a government hospital. Materials and Methods: A sample of 200 staff members was interviewed using 34-item, Likert response based, modified job satisfaction scale. Key factors for job satisfaction were identified after subjecting data to principal component analysis, varimax rotation and multivariate analysis using step-wise regression procedure. Results: The mean job satisfaction index was computed to be in a similar range, but was found to be highest for nurses (0.68), followed by doctors (0.66), support staff (0.63) and technicians (0.62). Nine uncorrelated and critical factors related to job satisfaction that explained 68.09% of the variability was identified, that is, communication, pay/salary, working conditions, organization supervision system, co-workers, workload, benefits, career aspects and rewards. A positive association was reported between job satisfaction score and factor scores (units) of communication (0.133), benefits (0.110), working condition (0.027) and co-workers (0.032) and a negative relation with organizational supervision system (0.118), workload (0.093), rewards (0.035), pay/salary (0.034) and career prospects (0.017) respectively for all categories of respondents. However in case of doctors, co-workers (0.023 units) showed a negative relation. Conclusion: There is scope for interventions to enhance job satisfaction and concomitant continuous monitoring can be useful in determining various service aspects that necessitate improvement. By enhancing job satisfaction, hospital administrator can improve not only the mental, psychological and social well-being of work-force, but also the financial health of an organization.
Keywords: Benefits, communication, environment, factor analysis, human relation, organization, public, rewards, salary, supervision, work
|How to cite this article:|
Jaiswal P, Gadpayle A K, Singhal AK, Sachdeva S, Modi RK, Padaria R, Ravi V. Job satisfaction among hospital staff working in a Government teaching hospital of India. Med J DY Patil Univ 2015;8:131-7
| Introduction|| |
Healthcare system is a labor intensive sector. Over the years, it has undergone a dramatic change as a result of razor edge competition, technological advancement, knowledge transfer, escalating cost and concomitant demand for better-patient care services. Job satisfaction is one of the most important determining factors of enhanced efficiency, productivity and also quality of work within an organization. The phenomenon of job satisfaction has been inversely associated with absenteeism, stress, exhaustion, and increase turnover. , Dissatisfaction affects patient rated quality of care and is strongly related to early retirement and cutback of working hours. , Studies on this subject matter remain scanty in the Indian settings where shortage of health manpower and high burden of disease are prevalent. With this back ground, a cross-sectional study was undertaken to assess job satisfaction amongst permanent employees working in government teaching hospital of north India.
| Materials and Methods|| |
The study was conducted in Ram Manohar Lohia (RML) Hospital, New Delhi. RML was originally named Willingdon hospital and established by the British government in the heart of New Delhi during 1932. The hospital was administratively taken over by Government of India in 1954 and with continuous expansion/growth over the years; Post-Graduate Institute of Medical Education and Research started functioning from the year 2008. Currently, hospital caters to an average daily outpatient department attendance of 5000 patients with an annual admission of 60,000 supported by 1065 patient beds and managed by 2270 permanent government employees (doctors-192, nurses-1025, technician-376, and support staff-677) in addition to residents and contractual employees.
Considering operational feasibility, a total of 200 staff members, 50 in each category, that is, doctors, nurses, technicians, and support staff were covered using systematic random sampling from the universe. Only permanent government employees were included in the study thus excluding residents/temporary/contract/daily wagers employed by this hospital. Respondents were contacted (February-April 2011) after taking informed verbal consent in a nonjudgmental manner by a single researcher. Ethical clearance was obtained from Institutional Review Board.
Study instrument consisted of two broad parts:
- Part-A (socio-personal profile of respondents) and
- Part-B (Job Satisfaction Scale).
For operational purpose, job satisfaction scale developed by Spector  containing 36-item was adapted to measure job satisfaction in the present study. Pretesting was done on eight subjects not included in the study with the aim to check its clarity, comprehension and flow. The final data collection tool was slightly modified that comprised of 34-item [Table 1]. The reliability of the tool was checked and found acceptable using Cronbach's' alfa test (0.85). Content validation was done using jury's opinion method. 
Data management and statistical analysis
A summated rating scale format was used with a 5-point continuum of Strongly Disagree, Disagree, Undecided, Agree and Strongly Agree responses with respective weightage of 1, 2, 3, 4 and 5 points. As the items had been written in both positive and negative directions, scoring was reversed for the negative items in order to provide uniformity in statistical calculations. Hence, from the perspective of data analysis, a higher choice for each of the 34-item indicated a very good job satisfaction score. Data management was undertaken using Statistical Package for Social Sciences (SPSS) version 15.0 (Chicago, IL) to calculate descriptive statistics. Exploratory factor analysis using principal component technique with varimax rotation and multivariate analysis using stepwise regression procedure was applied for the analysis. Job satisfaction index for each respondent was worked out with the formula mentioned below and were classified into five groups according to the level of job satisfaction. The class intervals were generated with the ratio of the difference between the maximum and minimum obtained score and the number of the class interval.
A higher score indicated greater job satisfaction.
The data were summarized in terms of frequency distributions. However, in the absence of any consensus among the responses and also considering the large number of variables in the present study, factor analysis was used. This technique aided in reducing 34 possibly correlated variables into 9 uncorrelated and critical factors-related to job satisfaction. Principal component and varimax analysis were used as an extraction and rotation method respectively. The results of factor analysis may be interpreted as follows: The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy test indicates the degree to which the variables are related, which is helpful in evaluating if using a factor analysis makes sense.  The success of factor analysis also depends on significant correlations between variables. In this context, Bartlett's test for sphericity was highly significant indicating that random sample comes from a universe where many variables are correlated.
Once the adequacy of factor analysis is established, the next step is to identify the amount of information in every variable that is retained by the technique. Ideally, we would want the information retained to be 100%. However, there is always a certain amount of loss in the information. Criteria of retaining factors with an Eigen value of 1.0 or more had been used in the present study (Guttman-Kaiser rule). Varimax rotation was used since it alters the pattern of the factor loadings and hence improves interpretation. All the variables with factor loading of 0.60 and above are considered as significant under each factor.  All those variables, in each rotated factor that have high loading, are considered to be closely related variables. After careful examination of these variables in each factor, an attempt was made to identify commonness and delineate some kind of a hypothetical construct. On the basis of this analysis, appropriate domain was identified to label the clustering variables. While labeling the factors adequate care was taken in terms of loading of items as well as their signs.
| Results|| |
Socio-personal profile of respondents
The average age (years) of respondents was: Doctors (48.68; ±8.53), nurses (40.72; ±7.76), technicians (38.4; ±10.65) and support staff (43.24; ±9.52). The gender ratio was extremely skewed in favor of males in the case of technicians (90:10) and support staff (88:12) while it was relatively less skewed in favor of male (58:42) in case of doctors. However, nurse category with reversely skewed sex ratio showed female preponderance (2:98). Nearly 80% of the doctors were post-graduate, 96% of nurses had general nursing midwifery qualification; nearly 50% of technicians were graduate, and 52% of support staff had education of at least 10 th standard. The average work experience (years) was: Doctors 19.09 (±9.77), nurses 17.2 (±8.420), technicians 14.84 (±10.45) and support staff 14.84 (±10.45). The staff in each category did not differ significantly on above parameters except gender.
Level of job satisfaction
The mean job satisfaction index was computed to be highest for nurse (0.68) followed by doctor (0.66), support staff (0.63) and technician (0.62). Level of job satisfaction index is shown in [Table 2]. It was noted that higher proportion of nurses were satisfied in comparison to other staff.
|Table 2: Distribution of health staff (n = 200) according to level of job satisfaction|
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Determinant of job satisfaction
The job satisfaction data of respondents produced a KMO value of 0.847 which is meritorious and confirms that factor analysis is indeed a good procedure to use for data reduction. Nine factors were extracted from the correlation matrix accounting for 68.09% [Table 3] after subjecting data to principal component analysis and varimax rotation.
|Table 3: Eigen values, percentage of variance accounted by critical nine factors|
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A graphic presentation of the Eigen roots obtained at successive factor extraction is shown in [Figure 1]. Scree-plot is one of the criteria for deciding the number of factors to be retained for analysis and preserve all factors falling before "break-point or elbow." The Eigen values, percentage of variance accounted for by nine factors and the cumulative percentage are presented in [Table 3]. Due to space constraint and less significance, rest of the factors is not indicated in the table.
It is evident from [Table 2] that out of 34-item, 9-item explained maximum proportion of variability (68.09%). The interpretation of the rotated items was achieved by selecting only those items which had a significant factor loading, that is, ≥0.6. The concepts conveyed by these items were used to define the factor. Rotation converged in 14 iterations. [Table 4] gives a comprehensive summary of factor analysis undertaken on 34-item statements.
In decreasing order, the factors that respondent strongly felt (in terms of percentage mean score) were identified as follows: Highest proportion (75.6%) showed that respondents felt that good co-workers lead to higher job satisfaction. Even though the working environment as well as pay packages appears to be good, there exists quite a few lacunae as far as benefits; supervisory roles and management is concerned. In order to assess the impact of each factor and its corresponding interaction with job satisfaction score, multivariate analysis using stepwise regression procedure was performed. The best model arrived in 14 iterations had an R 2 = 0.938 (P < 0.001). This implied that 93.8% variation in job satisfaction score was explained by the variables in the regression equation. The significant explanatory variables are given in [Table 5]. It was observed that job satisfaction score increased by 0.133, 0.110, 0.027 and 0.032 units respectively with a unit increase in factor score of communication, benefits, working condition and co-workers.
Similarly, a unit increase in the organizational supervision system, workload, rewards, pay/salary and career prospects decreased job satisfaction score by 0.118, 0.093, 0.035, 0.034 and 0.017 units respectively. The significance of interactive effects of variables and designation highlighted the fact that above-mentioned units of increase/decrease are not the same for every designation. While co-workers showed a positive relation with the job satisfaction score for nurses, technicians and support staff, it had an inverse relation in case of doctors. This inverse relation showed a decrease of 0.023 units in job satisfaction score with a unit increase in co-workers score. Inverse relation was also noted between rewards and job satisfaction score. This inverse relation became even more acute for technicians and support staff when compared to doctors and nurses that is, for technicians and support staff, a unit increase in the rewards score decreased the job satisfaction score by 0.086 times while for a nurse/doctor it was 0.035 times only. Overall, job satisfaction score for doctors and nurses was 3.235 but was significantly lower at 3.181 for technicians and support staff.
|Table 4: Share of data variability and factor loading contributed by key nine factors|
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| Discussion|| |
Our study showed highest job satisfaction (mean score) for nurses followed by doctors, support staff and technicians. Proportion of job satisfaction rate was also highest (68%) among nurses [Table 1]. A plausible explanation for this finding among the nurses might be that the nature of the job and working environment in government of India funded public hospitals is perceived to be good. The other explaining factors might be very good salary (proportionate to working hours) in comparison to their colleagues working in the private sector; favorable and safe working condition; flexible assignments; flexible duty hours; good collaboration between occupational groups; leave provision like maternity leave, child care leave and compensatory leave, etc. Higher job satisfaction amongst nurses when compared to doctors was also reported at Nicosia General Hospital (Cyprus).  The reasons for technicians being the least satisfied in our study could be wide variation of educational qualification among them, improper recruitment policy, improper deployment, very few career growth opportunities, lesser option for trainings, etc. The access to capacity building program was highly limited which restricted their career advancement.
Our study found that the proportion of doctors satisfied with their job was only 50% [Table 1] that is comparable to the findings even among Norwegian doctors  and Japanese physician;  both studies found the same satisfaction rate of 50%. However, higher job satisfaction among physicians was noticed in Switzerland (77%) and Canada (75%). , Some Indian studies reported higher proportion (70%) of satisfaction among physicians working at tertiary care institute in Delhi, India.  Another study also found same satisfaction rate amongst physicians working at Employee State Insurance hospital.  About two-thirds of the physicians were satisfied with their job was also reported by another Indian study conducted at Chandigarh. 
But dissatisfaction rate of 50% (including 24% somewhat satisfied) among doctors in this public sector hospital needs to be examined from a diverse perspective. The explaining factors for dissatisfaction could be many like existence of multiple cadres, underutilization of technical skills of doctors (especially general duty medical officer cadre having post-graduate qualification, but not posted in their respective departments), lack of autonomy regarding decision about patient treatment, limited opportunities, in-commensurate remuneration (by the presence of comparison effects in the job satisfaction function whereby some characteristics of the respondent's job are compared with the job characteristics of some reference groups or with the respondent's own expectation about their jobs). Job dissatisfaction among doctors may also be a reflection of the changing role of doctors in evolving society.
Nine critical factors of job satisfaction were derived from factor analysis that is comparable to numerous studies in different parts of the world. For assessing the impact of these factors on job satisfaction stepwise regression procedure was performed, and 93.8% variation in the job satisfaction score was explained by the variables in the regression equation. It was found that dependent variable job satisfaction had a positive relation with independent variables communication, benefits, working conditions and co-workers for all categories except doctors in which co-workers showed a negative correlation. Negative correlation was noted with independent variables, organizational supervision system, workload, rewards, pay/salary and career prospects. While there is a growing body of research that supports positive and negative association between dependent and some independent variables, it was hard to find any references (beyond our work) on the negative effects of some independent variable like pay, rewards and career on job satisfaction. Other advantage of our study over other is that we have found not only established positive and negative relations between variables, but also established the extent of change in job satisfaction with respect to change in factors.
There are a number of plausible explanations for these negative correlation findings. The negative correlation between pay and job satisfaction found in our study could be explained on the basis of "equity" "discrepancy" or "relative deprivation" which implies that it is not only the absolute level of pay that matters to workers, but also the level of pay in relation to what they expect or what others receive. An alternative explanation relies on the idea that income is evaluated relatively to some comparison level and not in an absolute sense. It is also possible that this result stems from the un-observability of some variables that are correlated with both pay and job satisfaction. It is also possible that higher paid worker as a result of the promotion will be doing harder work, having more stress, more responsibility, but in-commensurate authority and so will be less satisfied. This especially is true in the case of doctors.
A significant positive moderate association (r = 0.65) with working environment on job satisfaction was found among healthcare professionals in the public sector of Pakistan.  It may be surprising that one unit increase in rewards and career aspects also decreases job satisfaction. A plausible explanation for this finding may be that there are very few rewards like specialized training, foreign assignment etc., and that also for a very limited numbers of professionals thus creating inequality and it is also possible that respondents included in our study may be those who are not getting the rewards thus decreasing overall job satisfaction. This finding contrasts the results of most researchers. A recent study conducted in Tanzania reported poor job satisfaction in their health system due to poor rewards system, discouraging working environment and weak communications in the staff.  Our study found a negative correlation between co-workers and job satisfaction for doctors that is very unusual and did not get any supportive evidence from the review of the literature. Jahrami et al. found a positive relationship with co-workers and job satisfaction (mean 17.7, ±3.4; range: 10-24) and same was found by Wada et al. (corrected odds ratio −1.28, 95% confidence interval: 1.07-1.45). ,
A strong association of job satisfaction among physicians and collaboration between occupational groups was also reported by a researcher in Germany.  The possible reasons for such surprising finding in our study may be that doctors being most intellectual and visionary among all staff members see their co-workers as competitor in their professional development. Prevailing diverse cadre and/or social cast based reservation may also be a reason. The reasons for working condition as a critical factor in our study could be the autonomy and appreciation which every healthcare provider aspire and administrator should consider this factor while formulating a policy for good working condition. The study has explored some surprising findings of job satisfaction, which needs to be reviewed in the context of distribution of satisfaction against prevailing political/sociodemographic characteristics to support or contradict study findings.
Study limitations include nonconfirmation of the causal relationship because of cross-sectional designs of study. Only 10% of the total population was taken and nonsampled staff might have had a different response, and the results cannot be extrapolated. Further, findings presented in this study are based upon purely subjective rating and based on self-assessment of respondents, which was not externally validated and might be influenced by the respondent's lack of knowledge with the subject matter.
| Conclusions|| |
Our study documented that majority of staff working in this public sector hospital were satisfied with their jobs however there is scope for further enhancement within a realistic range. Various factors of job satisfaction were defined along with their inter relation and also supported two-factor theory. Monitoring of job satisfaction could be undertaken on a regular basis to find out the factors that need improvement. By enhancing job satisfaction, hospital administrator and managers can improve not only the mental, psychological and social well-being of work-force, but also the financial health of an organization. We envisage sharing results of our study with authorities to act upon accordingly.
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[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]
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