Psychometric properties of the Maslach Burnout Inventory for Human Services among Italian nurses: a test of alternative models

RESEARCH METHODOLOGY

Psychometric properties of the Maslach Burnout Inventory for

Human Services among Italian nurses: a test of alternative models

Renato Pisanti, Caterina Lombardo, Fabio Lucidi, Cristiano Violani & David Lazzari

Accepted for publication 7 July 2012

Correspondence to R. Pisanti:

e-mail: [email protected]

Renato Pisanti BSc PhD PsyD

Research Assistant

Department of Psychology, University of

Rome ‘Sapienza’, Italy

Caterina Lombardo BSc PhD

Associate Professor of Clinical and Health

Psychology

Department of Psychology, University of

Rome ‘Sapienza’, Italy

Fabio Lucidi BSc PhD

Full Professor of Psychometry

Department of Psychology, University of

Rome ‘Sapienza’, Italy

Cristiano Violani BSc PhD

Full Professor of Clinical and Health

Psychology

Department of Psychology, University of

Rome ‘Sapienza’, Italy

David Lazzari BSc PsyD

Clinical and Health Psychologist

Head of Division of Clinical and Health

Psychology

Hospital ‘S. Maria’, Terni, Italy

P I SANT I R . , LOMBARDOC . , LUC ID I F . , V IOLAN I C . & LAZZAR I D ( 2 0 13 )

Psychometric properties of the Maslach Burnout Inventory for Human Services

among Italian nurses: a test of alternative models. Journal of Advanced Nursing

69(3), 697–707. doi: 10.1111/j.1365-2648.2012.06114.x

AbstractAim. The purpose of this study was to test the factor structure of an Italian

version of the Maslach Burnout Inventory for Human Service employees. In

addition we examined the reliability and construct validity of the scale.

Background. There is increasing evidence that nurses are at risk of experiencing

burnout. Despite the vast international use of the Maslach Burnout Inventory-

Human Service Survey, its factor structure and reliability are not beyond question.

Method. In a sample of nurses (N = 1613) six alternative factor models of the

instrument were tested using confirmatory factor analysis. Furthermore, we

examined the invariance of the pattern of factor loadings of the model that better

fitted the data across gender groups. To test construct validity, participants

completed four subscales of Symptoms Check List 90-R. Internal consistency was

evaluated computing Cronbach’s alpha estimates of the scales. The study was

conducted in 2007 and 2008 in Italy.

Results. The factor analysis provided support for a 20-item version identifying

the three original dimensions. The model was found to be factorially invariant

between men and women. Correlations between the latent MBI-HSS dimensions

and distress variables were in line with theoretical predictions. Reliability was

supported by acceptable Cronbach’s alpha indexes.

Conclusion. The Maslach Burnout Inventory-Human Service Survey has

acceptable validity and reliability for measuring burnout among nurses, and can

help healthcare managers to offer interventions to reduce burnout among nurses.

Limitations of the study and suggestions for further research are highlighted.

Keywords: factor analysis, instrument development, maslach burnout inventory,

occupational health, psychometric testing

Introduction

Burnout is a response to chronic work-related stress typical of

people who work in inter personally oriented professions, where

the relationship between providers and recipients is central to the

job, and the nature of the work (be it healthcare service, treat-

ment, or education) can be highly emotional. There is increasing

evidence that nurses are at risk of experiencing burnout.

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JAN JOURNAL OF ADVANCED NURSING

Background

In the course of their career, nurses have to face many

stressors, such as organizational restructuring and down-

sizing, inadequate pay, lack of social recognition, heavy

workload, inadequate preparation to meet emotional

needs of patients and family, and exposure to death and

dying (McVicar 2003). Prevalence of burnout among

nurses has been estimated between 2% (Grau-Alberola

et al. 2010) and 10% (Pinikahana & Happell 2004).

Besides, it is not unreasonable to expect nurses burnout

to interfere with the nurse’s performance and consequently

with the care process. According to Garman et al. (2002),

burnout may lead to intent to change work involvement,

to leave the workforce, and high turnover rates. Because

burnout is associated with remediable factors including

demands at work, nurses autonomy and social support in

the workplace measuring burnout has important practical

applications.

According to Maslach et al. (1996), emotional exhaus-

tion (EE), depersonalization (DP), and diminished personal

accomplishment (PA) are the key dimensions of Burnout.

EE refers to the feeling of being drained or used up and

emotionally unable to face a day’s work. DP involves a neg-

atively, indifferent, or overly detached attitude to patients.

Finally reduced PA, refers to a decline of feelings of compe-

tence and successful achievement in one’s work. The way

that Maslach and colleagues defined burnout resulted in the

Maslach Burnout Inventory-Human Service Survey version

(MBI-HSS; Maslach et al. 1996).

Despite the vast international use of the MBI-HSS, its

factor structure is not beyond question (Worley et al.

2008). Factor analytic studies conducted in various occupa-

tional groups (Gold 1984, Green & Walkey 1988, Sirigatti

& Stefanile 1991, Evans & Fischer 1993, Kantas & Vass-

ilaki 1997, Kokkinos 2006, Poghosyan et al. 2009) support

the original 22 items oblique three-dimensional structure

with factors corresponding to EE, DP, and reduced PA.

Others have suggested that fit indices could be improved by

deleting poor performing items and/or allowing items to

load on more than one factor (Golembiewski & Munzen-

rider 1984, Brookings et al. 1985, Walkey & Green

1992, Schaufeli & Dierendonck 1993, Gorter et al.

1999, Beckstead 2002, Hallberg & Sverke 2004, Richard-

sen & Martinussen 2004, Vanheule et al. 2007). Others

have argued that an alternative factorial structure is more

appropriate (Brookings et al. 1985, Firth et al. 1985,

Walkey & Green 1992, Taris et al. 1999, Densten 2001).

The different measurement models are summarized in

Table 1. Beside the factor problems structures highlighted

above, other psychometric problems might affect research

based on the MBI-HSS.

An important finding in burnout research is that men and

women develop different symptoms: e.g. men are more

prone to develop depersonalization than women (Schaufeli

& Greenglass 2001). It is known that, to test meaningfully

for gender differences, the factor structure of the scale is

needed to be invariant between females and males (Rock

et al. 1978). Surprisingly, to our knowledge, so far research

on the factor structure of MBI-HSS has not considered gen-

der invariance.

Concerns also remain about the reliability of the MBI-

HSS scales. A recent quantitative review (Wheeler et al.

2011) found that the EE scale consistently produced the

largest and most consistent coefficient alpha estimates, with

most studies sampled reporting values of or above 0�80;whereas the DP and PA alpha estimates were both lower

and less consistent. Different translations of the MBI

account for statistically significant variability in the reliabil-

ity on the EE and DP scales, with higher alpha values for

English versions of the MBI. Translations into languages

different from English did not affect the reliability scores of

the PA scale. Moreover, the profession of the study partici-

pants accounts for great part of the variance in coefficient

alpha estimates. Among nurses, Wheeler et al. (2011) found

that results are mixed and, quoting Vanheule et al. (2007),

concluded that ‘interpretation of the meaning of emotional

exhaustion, depersonalization, and reduced personal accom-

plishment is sample specific’ (p. 91).

Finally, a further purpose of the present article was to

assess the construct validity of MBI-HSS examining the

associations between the MBI-HSS dimensions and other

psychological distress variables Which are known to share

considerable amounts (5–25%) of variance with burnout

dimensions. (Schaufeli 2007).

The study

Aim

The aims of the present article were to: (a) test a series of

alternative models of the factor structure of MBI-HSS in a

sample of nurses, using confirmatory factor analysis (CFA);

(b) analyse the invariance of the pattern of factor loadings

of the model that better fitted the data across gender

groups using CFA; (c) examine the reliability of MBI-HSS

computing Cronbach’s alpha estimates; (d) analyse the con-

struct validity measuring how and to what extent various

individual distress variables could be related with MBI-HSS

dimensions.

698 © 2012 Blackwell Publishing Ltd

R. Pisanti et al.

Methodology

Sample and procedure

We randomly selected 2886 nurses who were representative

of nurses of the Central Italy (Umbria and Lazio regions).

Healthcare managers provided basic demographics charac-

teristics (i.e. gender and age) of all nurses. Among them,

1647 agreed to volunteer for the study, with a response

rate of 57%, typical for surveys of this length (Gelsema

et al. 2006). They were asked to leave their completed

anonymous questionnaires in a sealed box placed in the

office of nurses of each ward. The data were collected

between February 2007 and May 2008 in 11 hospitals.

Thirty-four incomplete protocols were excluded. The com-

parison of the respondents to the non-respondents on gen-

der and age showed that the 1613 nurses participating in

the study were representative of those 2886 nurses who

were asked to participate. Participant demographics are

shown in Table 2.

Ethical considerations

The study was approved by ethics committees of each hos-

pital. Informed consent was obtained from all participants.

Data were anonymously gathered and the voluntary nature

of the study was emphasized. Data were stored in accor-

dance with the Italian Data Protection Act (2006).

Measures

A questionnaire was compiled to assess background vari-

ables, burnout, and psychological distress.

Background variables

Gender, age, type of employment contract, years of nursing

experience, and type of clinical placement were assessed.

Maslach Burnout Inventory for Human Service Survey

We prepared an Italian version of the MBI-HSS, which

was back translated into English by a native speaker.

0·64 Item 1

0·80

Emotionalexhaustion

Depersonalization

·49

–·14

–·39

Personalaccomplishment

0·55

0·570·68

0·84

0·720·59

0·78

0·60

0·58

0·70

0·54

0·43

0·650·67

0·630·79

0·65

0·51 0·67

Item 2

Item 3

Item 6

Item 8

Item 13

Item 14

Item 20

Item 5

Item 10

Item 11

Item 15

Item 22

Item 4

Item 7

Item 9

Item 17

Item 18

Item 19

Item 21

0·30

0·33

0·47

0·71

0·53

0·35

0·62

0·36

0·34

0·49

0·29

0·18

0·42

0·45

0·40

0·62

0·42

0·26

0·45

Figure 1 Results of Confirmatory Factor Analysis of Italian Version of the MBI-HSS 20 items. v2 = 1155,23, d.f. = 167, CFI = 0�92,RMSEA = 0�06, RMSEA 90% CI = 0�06–0�06, ECVI = 0�77, CAIC = 1515,82

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JAN: RESEARCH METHODOLOGY Psychometric properties of the MBI-HSS among Italian nurses

Our version is substantially equivalent (differences in

translation were minor and did not concern the meaning

of the items) to the Italian version of Sirigatti and Stefa-

nile (1991). Of the 22 items, nine are designed to mea-

sure EE, five to reflect DP, and eight to assess PA. All

items ask for frequencies and are scored on a seven-point

scale (from ‘never’ – 0 points - to ‘every day’ – 6 points)

with higher scores indicating higher levels of EE, DP, and

PA.

Psychological distress

It was measured through 41 items of the SCL-90R (Symp-

tom Check List: Derogatis 1983, Italian translation and

adaptation by Violani & Catani 1995). The SCL-90R items

ask respondents to indicate the extent to which they were

bothered by symptoms of depression (16 items, e.g. ‘feeling

lethargic’); anxiety (10 items, (e.g. ‘feeling afraid’); somatic

complaints (12 items, e.g. headaches); and sleep disorders

Table 1 Alternative structure models of MBI-HSS.

Name of

Model

Number

of factors

Number

of items Authors Notes

Model M1 1 22 Golembiewski and

Munzenrider (1984)

Burnout is viewed as a unitary concept

Model M2 2 22 Brookings et al.

(1985)

Due to a moderate to high correlation between emotional exhaustion and

depersonalization, some authors have argued that an alternative factorial

structure is more appropriate, namely a two factor model consisting of: a)

emotional exhaustion-depersonalization (a dimension called ‘The Core of

Burnout’), and b) personal accomplishment (e.g. Brookings et al. 1985,

Walkey & Green 1992). These findings support current theories holding that

either exhaustion results from depersonalization (Golembiewski et al. 1996)

or, conversely, that depersonalization is the result of exhaustion (Leiter &

Maslach 1988). Whichever the causal direction, cause and effect are strongly

correlated.

Model M3a 3 22 Maslach et al. (1996) The original 22 items oblique three dimensional structure with factors

corresponding to emotional exhaustion (nine items), depersonalization

(five items), and reduced personal accomplishment (eight items).

Model M3b 3 20 Schaufeli and

Dierendonck (1993)

A confirmatory study conducted among Dutch nurses by Schaufeli and

Dierendonck (1993), found the fit of the original three-factor model to be

superior to several alternative models. However, the authors agreed with Byrne

(1993) recommending to delete Items 12 (‘I feel very energetic’ -personal

accomplishment) and 16 (‘Working with people directly puts too much stress

to me’ - emotional exhaustion), given that Confirmatory Factor Analyses

(CFA) findings showed that these items tended to load on EE and DP,

respectively; as a consequence of the deletion, the fit of the three-factor

model was improved. Several confirmatory studies, conducted in samples of

nurses and healthcare workers (Gorter et al. 1999, Beckstead 2002, Hallberg

& Sverke 2004, Richardsen & Martinussen 2004, Vanheule et al. 2007)

confirmed this factorial structure.

Model M4 4 18 Firth et al. (1985) Firth et al. (1985) observed a basically different factorial structure with an 18

items version. In their sample of British nurses emotional exhaustion was split

in two factors: a) feelings of being ‘emotionally drained’; and b) feelings of

‘frustration and discouragement about work’. In the same study

depersonalization was identified by three items (10, 11 and 22) and was

named ‘hardening’.

Model M5 5 19 Densten (2001) Furthermore in a confirmatory study carried out among Australian law

enforcement managers, Densten (2001) proposed a five factors model for a

19 items version of the instrument. The factors were: ‘psychology’ and

‘somatic strain’, obtained splitting into two the emotional exhaustion

dimension, depersonalization, and two more factors drawn from personal

accomplishment splitted in two factors namely ‘self accomplishment’ and

‘working with others’. The series of confirmatory factor analyses provided

evidence that the hypothesized five factor structure was superior to a range

of alternative models (one, two, three and four factors).

700 © 2012 Blackwell Publishing Ltd

R. Pisanti et al.

(three items, e.g. ‘wake up early’) over the past week.

Answers were provided on a five-point scale (1 = not at

all; 5 = very much).

Data analysis

To investigate the factor structure of the MBI-HSS, six

alternative confirmatory factor models were considered.

The structure of each model is shown in Table 3. For all

models, the factors were specified to be correlated. Only

model M4 incorporated cross-factor loadings that were

consistent with the solutions reported by Firth et al. (1985)

with item three and eight loading on both EE dimensions

(frustration and emotional draining).

Confirmatory factor models were estimated using ‘AMOS’

(Analysis of Moment Of Structure) software (version 7,

Byrne 2010). The model fit was assessed using the following

indices: Chi-Square, Root Mean-Square Error of Approxima-

tion (RMSEA), Comparative Fit Index (CFI), Consistent

version of Akaike’s information criterion (CAIC) and

expected cross-validation index (ECVI). Chi-square tests the

null hypothesis of perfect model fit where the residual covari-

ance equals zero. Most investigators interpret the RMSEA as

indicating a poor model fit when it is above some upper

bound, typically set between 0�05–0�08 (Thompson 2004). A

CFI value of 0�90 served as the rule-of-thumb lower limit cut

point of acceptable fit. To facilitate the comparison of differ-

ent models, CAIC (in this paper we preferred the consistent

version of AIC to the Akaike’s index because the former is

less sensitive to the large sample size than the later) is

reported. The model with the lowest CAIC, given parsimony

considerations, is the preferred model (Byrne 2010). Finally,

the ECVI is an estimate of how well a solution obtained from

one sample will generalize to other samples (Byrne 2010).

Smaller values of the ECVI indicate a better expected cross-

validation of the model.

The invariance of the pattern of factor loadings of the

model that best fitted the data was examined across male

and female subsamples. The Cronbach’s alpha coefficient

was used to estimate the internal consistency for the scale

(s) derived from the CFAs.

Results

Table 4 reports the fit indices for the six models tested. The

fit of the three-factor model originally specified by Maslach

et al. (1996), (M3a) is superior to both the one factor (Dv2

(3) = 4333,36, P < 0�0000) and the two factor (Dv2

(2) = 891,83, P < 0�0000) models. However, although the

chi-squared test, CAIC, and ECVI values decreased and the

RMSEA criterion was met, the CFI indicated that the fit

could be further improved. Moreover, the modification

indices (meaning that the fit would improve significantly if

fixed parameters in the model would be relaxed, Byrne

2010) signalled that item 12 (PA) tends to double load on

EE (Modification Index = 186�31), and that item 16 (EE)

tends to double load on DP (MI = 34�75). Furthermore, the

standardized residuals (smallest = –10�59 and larg-

est = 8�23) often involved these items, thus further suggest-

ing that they were problematic. The Model M3b did not

consider items 12 and 16 and, based on the analysis of the

fit values, it provided the best description of the data

among the alternative models, showing the lowest CAIC,

ECVI, and RMSEA values and the highest value for the

CFI. Only in this case the CFI was above 0�90, the value

typically considered evidence of good fit. The adequacy of

this model must also be considered in terms of the parame-

ter estimates: all the factor loadings were high, positive,

and statistically significant (P < 0�05). The standardized

loadings on EE ranged between 0�55–0�84 (median = 0�70),for DP the factor loadings ranged between 0�43–0�70

Table 2 Participant demographics.

Variables Sample (n = 1613)

Gender (%)

Male 361 (22�4)Female 1252 (77�6)

Age (years)

20–29 170 (10�5)30–39 633 (39�2)40–49 515 (31�9)50–59 232 (14�4)60–69 49 (3�0)> 70 14 (0�9)

Type of employment contract

Permanent 1550 (96�1)Temporary 63 (3�9)

Years of experience as a nurse (%)

< 5 241 (14�9)6–9 327 (20�3)10–14 298 (18�5)15–19 213 (13�2)> 20 534 (33�1)

Type of clinical placement

General hospital 550 (34�1)University hospital 895 (55�5)Oncology hospital 168 (10�4)

Ward type

Surgical 384 (23�8)Medical 309 (19�2)Emergency 182 (11�3)Mixed 572 (35�5)Other wards 166 (10�2)

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JAN: RESEARCH METHODOLOGY Psychometric properties of the MBI-HSS among Italian nurses

Table 3 Model specifications for the alternative factor models of the MBI-HSS.

Nr Item

Model M1 Model M2 Model M3a Model M3b Model M4 Model M5

1 Factor

(22 items)

2 Factors

(22 items,

Brookings

et al.

1985)

3 Factors (22

items, Maslach

et al. 1996)

3 Factors (20

items, Schaufeli

& Dierendonck

1993)

4 Factors (18 items;

Firth et al. 1985)

5 Factors (19 items; Densten

2001)

MBI CoB PA EE DP PA EE DP PA FD ED H PA PS SS DP SA WO

1 * * * * * NI *

2 * * * * * * *

3 * * * * * * *

4 * * * * *

5 * * * * * NI *

6 * * * * * *

7 * * * * * *

8 * * * * * * *

9 * * * * * * * *

10 * * * * * *

11 * * * * * *

12 * * * NI * NI

13 * * * * NI

14 * * * * NI NI

15 * * * * NI *

16 * * * NI NI *

17 * * * * * *

18 * * * * * *

19 * * * * * *

20 * * * * * * *

21 * * * * *

22 * * * * * * *

Free parameters are indicated by an asterisk *.

NI, Not Included; CoB, Core of Burnout (emotional exhaustion plus depersonalization); PA, personal accomplishment; EE, emotional

exhaustion; DP, depersonalization; FD, frustration and discouragement; ED, emotional draining; H, hardening; PS, Psychological strain; SS,

Somatic strain; SA, Self accomplishment-; WO, working with others.

Table 4 Fit indexes of the alternative models.

Models v2 d.f. CFI RMSEA RMSEA 90% CI ECVI CAIC

M0 14007,78 231 0�00 0�19 0�19; 0�19 8,72 14192,26

M1 6196,45 209 0�56 0�13 0�13; 0�14 3,90 6565,43

M2 2754,92 208 0�81 0�09 0�08; 0�09 1,76 3132,29

M3a 1863,09 206 0�88 0�07 0�07; 0�07 1,21 2257,23

M3b 1155,23 167 0�92 0�06 0�06; 0�06 0,77 1515,82

M4 1210,91 127 0�89 0�07 0�07; 0�08 0,81 1579,89

M5 1181,98 142 0�56 0�07 0�06; 0�07 0,79 1584,50

Note: v2, Chi-Square; df, degree of freedom; Goodness of Fit; CFI, Comparative Fit Index; CAIC, Consistent version of Akaike Information

Criterion; RMSEA, Root Mean-Square Error of Approximation; M0, independence model (i.e. in which all correlations among variables are

zero); M1, one factor (22 items); M2, two correlated factors (22 items): (emotional exhaustion and depersonalization (14 items), personal

accomplishment (nine items); M3a, three correlated factors (22 items): emotional exhaustion (nine items), depersonalization (five items), per-

sonal accomplishment (nine items); M3b, three correlated factors (20 items); M3a model minus items 12 and 16; M4, four correlated factors

(16 items): frustration about work (two items), emotional draining (three items), depersonalization (three items), and personal accomplish-

ment (eight items); M5, five correlated factors (19 items): psychological strain (three items), emotional exhaustion (four items), personal

accomplishment-self (four items); personal accomplishment-others (three items), depersonalization (five items).

702 © 2012 Blackwell Publishing Ltd

R. Pisanti et al.

(median = 0�58), and for PA, the loadings ranged between

0�63–0�79 (median = 0�65).As regards the remaining models M4 and M5, in both

cases the RMSEA was acceptable. However, in the case of

M4 model the CFI was 0�89 which is slightly lower than

0�90, whereas in the case of M5 model the CFI score has

been deemed as unacceptable.

Concerning the invariance of factor loadings of Model

M3b across genders, the model that assumed the patterns

to be equal in both subsamples resulted in a v2(351) of

1422,28 (P < 0�0001). When the loadings were allowed to

load independently across the subsamples, given the number

of factors and the pattern of loadings, a comparable fit was

obtained (v2 (334) of 1401,52, P < 0�0001). The hypothesis

of an invariant pattern of factor loadings of Model M3b

across genders was tenable (Δv2 (17) = 20�76, P = 0�24) andfemale nurses scored higher on EE (t (1611) = �2�44,P < 0�05), and lower on DP (t (1611) = 3�12, P < 0�05) thanmale counterparts.

Reliability

The Cronbach’s alpha estimates for the MBI dimensions

were good (EE = 0�88, PA = 0�83), or acceptable:

(DP = 0�70). As shown in the Table 5, deletions of items

did not improve the indices.

Relationships between burnout factors and psychological

distress

The fit of the model, including the M3b and the four

distress variables of the SCL-90, was acceptable, v2 =

Table 5 Internal consistency of the MBI-HSS (20 items–Total correlations and list of Cronbach’s alpha if deleted in each subscale.

Corrected item-total

correlation

Cronbach’s alpha if item

deleted

Emotional exhaustion (Cronbach’s Alpha = 0�88)(1). I feel emotionally drained from my work 0�72 0�86(2). I feel used up at the end of the work day 0�56 0�87(3). I feel fatigued when I get up in the morning and have to face another

day in the morning

0�56 0�88

(6). Working with people all day is really a strain for me 0�64 0�87(8). I feel burned out from my work 0�78 0�85(13). I feel frustrated by my job 0�65 0�87(14). I feel I’m working too hard on my job 0�57 0�88(20). I feel like I’m at the end of my rope 0�73 0�86

Depersonalization (Cronbach’s Alpha = 0�70)(5). I feel I treat some recipients as if they were impersonal objects 0�48 0�64(10). I’ve become more callous towards people since I took this job 0�48 0�64(11). I worry that this job is hardening me emotionally 0�56 0�60(15). I don’t really care what happens to some patients 0�46 0�65(22). I feel recipients blame me for some of their problems 0�33 0�69

Personal accomplishment (Cronbach’s Alpha = 0�83)(4). I can easily understand how my recipients feel about things 0�59 0�81(7). I deal very effectively with the problems of my recipients 0�59 0�81(9). I feel I’m positively influencing other people’s lives through my work 0�58 0�81(17). I can easily create a relaxed atmosphere with my patients 0�70 0�80(18). I feel exhilarated after working closely with my patients 0�60 0�81(19). I have accomplished many worthwhile things in this job 0�48 0�83(21). In my work, I deal with emotional problems very calm 0�59 0�81

Table 6 Correlations between the latent constructs of burnout

dimensions and the measures of anxiety, depression, somatic com-

plaints, and sleep disorders for nurses (N = 1613).

MBI-HSS

Distress and well-being dimensions

ANX DEP SC SD

EE 0�48*** 0�55*** 0�54*** 0�35***DP 0�32*** 0�36*** 0�26*** 0�14**PA �0�15** �0�18** �0�13** �0�10**

Note: MBI-HSS, Maslach Burnout Inventory-Human Service; EE,

emotional exhaustion; DP, depersonalization; PA, personal accom-

plishment ANX, anxiety (Scl90-R); DEP, depression (Scl90-R); SC,

somatic complaints (Scl90-R); SD, sleep disorders (Scl90-R).

*P < 0�05.**P < 0�01.***P < 0�001.

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JAN: RESEARCH METHODOLOGY Psychometric properties of the MBI-HSS among Italian nurses

6124�99, d.f. = 1721, P < 0�001, RMSEA = 0�040 (0�039–041), CFI = 0�91. All correlation coefficients are shown in

the Table 6.

Discussion

Study limitations

This study has two important limitations that should be

acknowledged. First, the generalizability of our results

may be limited because the study was based on a selec-

tion of healthcare organizations in Italy; hence, the results

are not representative for Italy as such. Second, stability

of the psychometric properties was not tested. The study

should be replicated in different samples of nurse, adopt-

ing longitudinal designs for testing the stability of the

measures.

Factor structure and reliability

On the basis of the fit indices, the three-factor model with

20 items was considered to be the model that fit best the

data. Our results confirmed the troublesomeness of two

items: item 12 (‘I feel energetic’.) which double loads both

PA and on EE; and item 16 (‘Working directly with people

puts too much stress on me’.) that double loads both on EE

and on DP. In line with several studies conducted among

nurses, removing these two items improved the fit indices

and the interpretability of the MBI-HSS. Therefore, in terms

of factorial validity both items should be removed from the

MBI-HSS. Examination of the modification indexes for evi-

dence of possible misspecification suggested no viably sound

rationale for further modifying the existing parameteriza-

tion.

The fact that the three factors were lowly correlated pro-

vides evidence of the relative independence of the three

dimensions of the construct. Treatments may be differently

tailored for individuals with various levels of emotional

exhaustion, depersonalization, and personal accomplish-

ment. While aggregating the scales scores into a unique

burnout score may result in a loss of important information

and compromise the assessment of beneficial progresses of

interventions. Moreover, our results show that the three-

factor structure is tenable in both genders with invariant

factor loadings, error variances, and factor variance. This

corroborates our finding that female nurses report higher

scores on EE and lower scores on DP than their male

colleagues. Schaufeli and Greenglass (2001) have provided

a gender-role explanation arguing that men are more

inclined to hold instrumental attitudes, whereas women are

more emotionally responsive and more prone to disclose

emotions and health problems.

What is already known about this topic

● Burnout is a maladaptive response to chronic work-

related stress typical of people who work in inter per-

sonally oriented professions.

● Nurses are at risk of experiencing burnout: epidemio-

logical studies in nurses have estimated a prevalence

between 2 and 10%.

● One of the most widely internationally used burnout

measure is the Maslach Burnout Inventory-Human

Service Survey. However, researchers have been trou-

bled by the factor structure of that scale, since factor

analytic studies have reported various multidimen-

sional structures.

What this paper adds

● Results provided support for a version composed by

20 items (excluding items number 12 and 16 of the

original version) identifying the three original dimen-

sions (emotional exhaustion, depersonalization, and

personal accomplishment).

● Correlations between the Maslach Burnout Inventory-

Human Service Survey dimensions and distress vari-

ables were in line with theoretical predictions and

extended empirical support for the construct validity

of the subscales.

● Reliability was supported by satisfactory Cronbach’s

alpha coefficients in the case of emotional exhaustion

and personal accomplishment. As regards depersonal-

ization, internal consistency was acceptable.

Implications for practice and/or policy

● The MBI-HSS 20 can be applied as a valid and reliable

instrument for assessing burnout among nursing staff,

and can inform related healthcare managers to offer

intervention strategies to reduce burnout in nursing

populations.

● In Italian samples, further efforts are needed to

improve the reliability of the depersonalization scale.

● Further research is also needed to assess whether the

three-factor structure with 20 items implied by the

scoring instructions holds for other nursing popula-

tions.

704 © 2012 Blackwell Publishing Ltd

R. Pisanti et al.

About the internal consistency of MBI-HSS both EE

and PA have good internal consistencies, while the DP

dimension is only acceptable. This is consistent with find-

ings reported in several studies that used English and

non-English versions of the scale (e.g. Wheeler et al.

2011) and is, therefore, unlikely to be due to our transla-

tion. The reliability of depersonalization dimension may

be increased by modifying or by increasing the number

of its items (Dierendonck et al. 2001). On this ground,

the Spearman–Brown prediction formula suggests that

including three additional items would achieve an a coef-

ficient of 0�80.

Criterion-related validity of the MBI-HSS

The correlations among depression, anxiety, somatic com-

plaints, and sleep disorders, and the MBI-HSS dimensions

were consistent with previous studies and confirm the con-

struct validity of the MBI-HSS scales. EE shows positive

and robust correlations with depression, anxiety, somatic

complaints, and sleep disorders. Likewise DP shows positive

associations with all psychological distress variables; how-

ever, all values were lower than EE. PA shows negative

relationships with the measures of psychological distress

that are lower than other two dimensions of burnout. These

results are in line with previous studies (Roelofs et al.

2005, Schaufeli 2007) and give further support for the dis-

tinction among the three aspects of burnout.

Conclusion

The MBI-HSS 20 can be applied as a valid and reliable

indicator of assessing burnout among nursing staff, and can

help healthcare managers to assess and design interventions

to reduce burnout among nurses.

Acknowledgements

We gratefully acknowledge the cooperation of the nurses

who participated in this study.

Funding

This research received no specific grant from any funding

agency in the public, commercial, or not-for-profit sectors.

Conflict of interest

No conflict of interest has been declared by the authors.

Author contributions

All authors meet at least one of the following criteria (rec-

ommended by the ICMJE: http://www.icmje.org/ethi-

cal_1author.html) and have agreed on the final version:

● substantial contributions to conception and design,

acquisition of data, or analysis and interpretation of

data;

● drafting the article or revising it critically for impor-

tant intellectual content.

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