Job satisfaction among hospital staff working in a Government teaching hospital of India

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Medical Journal of Dr. D.Y. Patil Univers ity | March-April 2015 | Vol 8 | Issue 2 131

Address for correspondence:

Dr. Poonam Jaiswal, Department of Hospital Administration, PGIMER, Dr. RML Hospital, New Delhi.

E-mail: [email protected]

Job satisfaction among hospital staff working

in a Government teaching hospital of India

Poonam Jaiswal, A. K. Gadpayle1, Ashok K. Singhal, Sandeep Sachdeva2, Rajesh Kumar Modi3,Rabindra Padaria4, V. Ravi5

Departments of Hospital Administration, 1 Medicine and 2Community Medicine, PGIMER, Dr. RML Hospital, 3 Department of Medicine,

Dr. RML Hospital, 4 Indian Agricultural Research Institute, 5 Lady Shri Ram College, New Delhi

ABSTRACT

Background: In a resource-limited and high burden disease

setting, satisfied human resource is an asset in terms of high

product ivity, effic iency and quality care. Aim: To assess

job satisfac tion among permanent employees working in a

government hospital. Materials and Methods: A sampleof 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 organizat ion.

Keywords: Benets, communication, environment, factor

analysis, human relation, organization, public, rewards, salary,

supervision, work

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DOI:

10.4103/0975-2870.153136

Original Article

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 efciency,

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.[1,2] Dissatisfaction affects patient rated quality of

care and is strongly related to early retirement and cutback

of working hours.[3,4] 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

Study setting

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

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Jaiswal, et al.: Job satisfaction amongst hospital staff

132 Medical Journal of Dr. D.Y. Patil Univers ity | March-April 2015 | Vol 8 | Issue 2

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.

Data collection

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

Study instrument consisted of two broad parts:

• Part-A (socio-personal prole of respondents) and

• Part-B (Job Satisfaction Scale).

For operational purpose, job satisfaction scale developed

by Spector [5] 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 ow. The nal data

collection tool was slightly modied that comprised of

34-item [Table 1]. The reliability of the tool was checked

Table 1: Study instrument (job satisfaction scale)

Statement Strongly agree Agree Undecided Disagree Strongly disagree

I feel I am being paid a fair amount for the work I do

There is really too little chance for promotion on my job

My supervisor is quite competent in doing his/her job

I am not satisfied with the benefits I receive

When I do a good job, I receive the recognition for it that I should receive

Many of our rules and procedures make doing a good job difficult

I like the people I work with

I sometimes feel my job is meaningless

Communications seem good within this organization

My supervisor is unfair to me

The benefits we receive are as good as most other organizations offerI do not feel that the work I do is appreciated

My efforts to do a good job are seldom blocked by red tape

I find I have to work harder at my job because of the incompetence of people I work with

I like doing the things I do at work

The goals of this organization are not clear to me

I feel unappreciated by the organization when I think about what they pay me

People get ahead as fast here as they do in other places

My supervisor shows too little interest in the feelings of subordinates

The benefit package we have is equitable

There are few rewards for those who work here

I have too much to do at work

I enjoy working with my coworkers

I often feel that I do not know what is going on with the organizationI feel a sense of pride in doing my job

I feel satisfied with my chances for salary increases

There are benefits we do not have which we should have

I like my supervisor

I have too much paperwork

I don’t feel my efforts are rewarded the way they should be

I am satisfied with my chances for promotion

There is too much bickering and fighting at work

My job is enjoyable

Work assignments are not fully explained

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and found acceptable using Cronbach’s’ alfa test (0.85).

Content validation was done using jury’s opinion method.[6]

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 wasworked out with the formula mentioned below and were

classied into ve 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.

Factor analysis

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 variablesare related, which is helpful in evaluating if using a factor

analysis makes sense.[7] The success of factor analysis also

depends on signicant correlations between variables. In this

context, Bartlett’s test for sphericity was highly signicant

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 signicant under each factor.[8] 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 identied 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 prole 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

qualication; nearly 50% of technicians were graduate, and

52% of support staff had education of at least 10th 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 signicantly 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 ofnurses were satised in comparison to other staff.

Determinant of job satisfaction

The job satisfaction data of respondents produced a KMO

value of 0.847 which is meritorious and conrms 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.








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 signicance, 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 signicant factor loading, that

is, ≥0.6. The concepts conveyed by these items were used

to dene 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 identiedas 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 benets; 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 signicant

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 factorscore of communication, benets, 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 signicance of interactive

effects of variables and designation highlighted the fact that

above-mentioned units of increase/decrease are not the

Table 2: Distribution of health staff (n = 200) according to level of job satisfaction

Level of job satisfaction Doctor (n = 50) (%) Nurse (n = 50) (%) Technician (n = 50) (%) Supportstaff (n = 50) (%) Total n (%)

Highly satisfied (0.75-0.84) 14 (28) 08 (16) 01 (2) 03 (6) 26 (13)

Satisfied (0.66-0.74) 11 (22) 26 (52) 13 (26) 18 (36) 68 (34)

Somewhat satisfied (0.57-0.65) 12 (24) 14 (28) 26 (52) 26 (52) 78 (39)

Dissatisfied (0.48-0.56) 07 (14) 02 (4) 06 (12) 03 (6) 18 (9)

Highly dissatisfied (0.39-0.47) 06 (12) 0 (0) 04 (8) 0 (0) 10 (5)

Table 3: Eigen values, percentage of variance accounted by critical nine factors

Component Initial eigen values Rotation sums of squared loadings

Total Percentage of variance Cumulative % Total Percentage of variance Cumulative %

1 6.441 18.944 18.944 4.315 12.693 12.693

2 3.853 11.333 30.278 3.458 10.171 22.864

3 2.723 8.009 38.287 2.957 8.697 31.560

4 2.324 6.834 45.121 2.577 7.579 39.139

5 2.044 6.013 51.134 2.449 7.202 46.341

6 1.793 5.273 56.407 2.148 6.317 52.658

7 1.496 4.401 60.808 1.993 5.861 58.519

8 1.337 3.933 64.740 1.787 5.256 63.775

9 1.142 3.358 68.099 1.470 4.324 68.099Extraction method: Principal component analysis

Figure 1: Scree-plot showing Eigen value and factor








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 signicantly

lower at 3.181 for technicians and support staff.

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 nding 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; exible assignments; exible dutyhours; 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).[9] The reasons for

technicians being the least satised in our study could be

wide variation of educational qualication among them,

improper recruitment policy, improper deployment, very

few career growth opportunities, lesser option for trainings,

Table 4: Share of data variability and factor loading contributed by key nine factors

Factor Statementnumber

Factorloading

Concept Percentage ofexplained variance %

Cronbachα

Meanscore

Total maximumscore

Percentage ofmean score

I 9 0.955 Communication 12.69 0.8821 11.76 20 58.8

16 0.860

24 −0.716

34 0.773

II 1 0.724 Pay/salary 10.17 0.6657 9.41 15 62.717 0.800

26 0.881

III 6 0.688 Workingcondition

8.69 0.7357 8.72 15 58.1

12 −0.727

14 0.618

IV 3 0.622 Organizationalsupervisionsystem

7.58 0.6408 8.46 15 56.4

10 0.828

19 0.708

V 7 −0.634 Co-workers 7.20 0.7319 7.56 10 75.6

23 −0.649

VI 22 −0.620 Workload 6.32 0.8658 6.37 10 63.7

29 −0.809

VII 20 −0.785 Benefits 5.86 0.9206 5.15 10 51.527 0.695

VIII 2 0.770 Careerprospects

5.26 0.6046 6.88 10 68.8

18 −0.883

IX 21 0.811 Rewards 4.33 — 3.73 5 74.6

Table 5: Impact of each factor on job satisfaction

Model Un-standardizedcoefcient

t P value

B SE

Constant 3.235 0.007 457.369 <0.001

Communication 0.133 0.005 24.935 <0.001

Organizational supervision system −

0.118 0.005 −

23.018 <0.001Workload −0.093 0.005 −19.887 <0.001

Benefits 0.110 0.005 20.485 <0.001

Rewards −0.035 0.007 −5.171 <0.001

Working condition 0.027 0.005 5.821 <0.001

Pay/salary −0.034 0.005 −6.472 <0.001

Co-workers*Doctor −0.055 0.013 −4.348 <0.001

Co-workers 0.032 0.008 3.903 <0.001

Career prospects −0.017 0.005 −3.551 <0.001

Rewards*technician −0.051 0.012 −4.214 <0.001

Rewards*support staff −0.050 0.012 −4.148 <0.001

Support staff −0.054 0.013 −4.208 <0.001

Technician −0.054 0.013 −4.182 <0.001dependent variable: job satisfaction. SE: Standard error








etc. The access to capacity building program was highly

limited which restricted their career advancement.

Our study found that the proportion of doctors satised with

their job was only 50% [Table 1] that is comparable to the

ndings even among Norwegian doctors[10] and Japanese

physician;[11] both studies found the same satisfaction rate

of 50%. However, higher job satisfaction among physicianswas noticed in Switzerland (77%) and Canada (75%). [12,13]

Some Indian studies reported higher proportion (70%)

of satisfaction among physicians working at tertiary care

institute in Delhi, India.[14] Another study also found same

satisfaction rate amongst physicians working at Employee

State Insurance hospital.[15] About two-thirds of the

physicians were satised with their job was also reported by

another Indian study conducted at Chandigarh. [16]

But dissatisfaction rate of 50% (including 24% somewhat

satised) 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 ofcer cadre having

post-graduate qualication, 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 amongdoctors may also be a reection 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 allcategories 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 nd 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 ndings. The negative correlation

between pay and job satisfaction found in our study could beexplained 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 satised. This

especially is true in the case of doctors.

A signicant positive moderate association (r = 0.65) with

working environment on job satisfaction was found among

healthcare professionals in the public sector of Pakistan.[17]

It may be surprising that one unit increase in rewards and

career aspects also decreases job satisfaction. A plausible

explanation for this nding 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 respondentsincluded in our study may be those who are not getting the

rewards thus decreasing overall job satisfaction. This nding

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.[18] 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 etal . (corrected odds ratio −1.28, 95% condence interval:

1.07-1.45).[11,19]

A strong association of job satisfaction among physicians

and collaboration between occupational groups was also

reported by a researcher in Germany.[20] The possible

reasons for such surprising nding 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

ndings 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 ndings.

Limitations

Study limitations include nonconrmation 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, ndings presented in this

study are based upon purely subjective rating and based onself-assessment of respondents, which was not externally

validated and might be inuenced 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 satised with their jobs

however there is scope for further enhancement within

a realistic range. Various factors of job satisfaction were

dened along with their inter relation and also supported

two-factor theory. Monitoring of job satisfaction could beundertaken on a regular basis to nd 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 nancial health of an organization. We envisage

sharing results of our study with authorities to act upon

accordingly.

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How to cite this article: Jaiswal P, Gadpayle AK, Singhal AK,Sachdeva S, Modi RK, Padaria R, et al . Job satisfaction amonghospital staff working in a Government teaching hospital of India.Med J DY Patil Univ 2015;8:131-7.

Source of Support: Nil. Conict of Interest: None declared.




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Job satisfaction among hospital staff working in a Government teaching hospital of India