4Coetzee.qxd


The environment in which employees in South Africa and

elsewhere in the world function, demands more of them than

had been the case in any previous period. The employment

relationship is changing, altering the type of work that people

do, when they work and how much they do (Barling, 1999).

Some employees also face diminished choice and control in that

they are forced to take on hours and working arrangements that

are against their preferences (Turner, Barling & Zacharatos,

2002). Additional unpredictability results as many employers

move toward greater flexibility by expanding and shrinking the

work force to correspond with shifting production and service

demands, resulting in loss of control over working hours and in

job insecurit y (Martin, 1997). Many organisations have

implemented practices that attempt to reduce costs and increase

productivity, which often leads to a mentality that favours

profitability over the welfare of people (Turner, Barling &

Zacharatos, 2002). 

These changes in the world of work also impact on higher

education institutions that have to adapt unremittingly in order

to survive (Gilbert, 2000). A global phenomenon in the changing

landscape of higher education institutions is the expansion from

elite systems to institutions of mass student numbers (Gilbert,

2000; Kistan, 1999; Kraak, 2000). Other consequences are life-

long learning (Shortlidge, 2003; Wallace & Ipson, 1992), adult

learning (Kraak, 2000), internet-based education and training

(Gilbert, 2000), formation of strategic alliances on international

level (Rowley, 2000), new trends in teaching and learning

(Kistan, 1999; Kraak, 2000), changes in the market place

(Blackmore, 2001; Brown, 1999; Gilbert, 2000; Kistan, 1999;

Lomas, 1997; Robertson, 1998; Rowley, 2000), the growth of

alternative systems of education, and the new demands and

needs of society (Kistan, 1999). These changes will have a direct

impact on the experience of work of employees at higher

education institutions. Zhao and Guo (2002) cautioned that to

become more competitive in the era of globalisation, more

educated and better trained work forces are required.

The landscape of higher education in South Africa is also

changing. Since 1994, the aim of the post-apartheid government

has been the redress of the apartheid legacy in an attempt to

move toward a democratic society (Cross, Mungadi & Rouhani,

2002). One of the focus areas of redress is the education system.

At an institutional level this boils down to the introduction of

policies and mechanisms aimed at redress on different levels and

demands in terms of access to education (Kraak, 2000). This has

resulted in a restructuring of the higher education system in

South Africa, which poses the following challenges to the

management as well as the employees of tertiary institutions:

New organisational cultures have to be introduced; values,

cultural norms and organisational support systems are subjected

to ongoing changes; peer support within the organisation is

challenged with issues like equity, diversity and resistance;

establishing an organisational climate is continuously and

inevitably influenced by ongoing change. 

Higher education instit utions can make an important

contribution to the reconstruction and development of South

Africa (Marais, Grobbelaar & Potgieter, 1997). However, of great

importance are those responsible for producing the outcomes of

higher education institutions. Administrators (Blaise, 1996;

Goldstein, 1992), lecturers/teachers (Schnacke, Martray & Heck,

1994; Seldin, 1991) and support staff (Alexy, 1991; Glasgow,

Terborg, Hollis, Severson, Boles, 1995) comprise the “human

capital” of an education instit ution and therefore it is

important to care for these groups of people (Sackney, Noonan

& Miller, 2000). 

The current changes and demands in the higher education

scenario will inevitably have an impact on the levels of burnout

of employees at higher education institutions. Meléndeze and

De Guzman (1983, p. 1) define burnout as a “state of mind that

affects people who work with other people and give much more

than what they get in return from their colleagues, friends,

supervisors and clients”, and include symptoms such as lack of

enthusiasm for work, helplessness and frustration. A more recent

and elaborated definition on burnout is that of Schaufeli and

Enzmann (1998, p. 36). They define burnout as “a persistent,

S.E. COETZEE

S. ROTHMANN
Workwell: Research Unit for People, Policy and Performance, 

North-West University, Potchefstroom

ABSTRACT
The objectives of this study were to test an adapted four-factor model of burnout consisting of Exhaustion,

Cynicism, Professional Efficacy and Cognitive Weariness for employees of a higher education institution in South

Africa and to determine differences in burnout levels between different language groups and employees with

different years of experience at the institution. A cross-sectional survey design (N = 372) was used. The Maslach

Burnout Inventory – General Survey, the Cognitive Weariness Scale and a biographical questionnaire were

administered. Structural equation modelling confirmed the hypothesised four-factor model of burnout. The scales

showed acceptable internal consistencies. Analysis of variance revealed differences in burnout and cognitive

weariness for groups with different languages and different years of experience at the institution. 

OPSOMMING
Die doelstellings van hierdie studie was om ’n aangepaste vierfaktormodel van uitbranding bestaande uit

Uitputting, Sinisme, Professionele Doeltreffendheid en Kognitiewe Vermoeidheid vir werknemers van ’n

hoëronderwysinstansie in Suid-Afrika te toets en om te bepaal of verskillende taalgroepe en werknemers met

verskillende jare ervaring by die instansie verskille in uitbrandingsvlakke ervaar. ’n Dwarssneeopname-ontwerp

(N = 372) is gebruik. Die Maslach Uitbrandingsvraelys – Algemene Opname, die Kognitiewe Vermoeidheidskaal en

’n biografiese vraelys is afgeneem. ’n Vierfaktormodel van uitbranding is met strukturele vergelykings-

modellering bevestig. Die skale het aanvaarbare interne konsekwentheid getoon. Variansie-analise het verskille ten

opsigte van uitbranding en kognitiewe vermoeidheid by verskillende taalgroepe en groepe met verskillende jare

ervaring by die instansie opgelewer.

AN ADAPTED MODEL OF BURNOUT FOR EMPLOYEES AT A

HIGHER EDUCATION INSTITUTION IN SOUTH AFRICA

Requests for copies should be addressed to: S Rothmann, Department of Industrial

Psychology, North-West University, Potchefstroom Campus, Private Bag X6001,

Potchefstroom, 2520

29

SA Journal of Industrial Psychology, 2004, 30 (3), 29-40

SA Tydskrif vir Bedryfsielkunde, 2004, 30 (3), 29-40



negative, work related state of mind in ‘normal’ individuals that

is primarily characterized by exhaustion, which is accompanied

by distress, a sense of reduced effectiveness, decreased

motivation, and the development of dysfunctional attitudes and

behaviors at work”. According to Levert, Lucas and Ortlepp

(2000), burnout can be seen as the end result of consistently

unmediated or unsuccessful attempts of the individual at

mediating stressors in the environment. 

Burnout affects the individual on a cognitive, affective

(motivational), physical and behavioural level as a result of a

general breakdown in defences against prolonged job-stressors

(Brill, 1984). This breakdown occurs gradually and often

remains unnoticed for a long time, perpetuated by ineffective

coping strategies and frustrated intentions brought about by

the subjective experience of work-realit y. The gradual

depletion of emotional resources results in a sense of reduced

effectiveness, decreased motivation and the development of

dysfunctional behaviours and attitudes at work (Schaufeli &

Enzmann, 1998).

Originally restricted to the helping professions, burnout is now

recognised as a phenomenon found in a variet y of

occupational groups (Cordes & Dougherty, 1993). Research

over the last three decades has shown that the consequences of

burnout are not just limited to the individual’s subjective

experience, but also to various organisational outcomes.

Burnout has been associated with reduced organisational

efficiency and work-related problems such as employee

t urnover, low morale, poor qualit y of care, lowered

productivity, absenteeism and interpersonal problems (Levert

et al., 2000; Rosse, Boss, Johnson & Crown, 1991). Maslach and

Jackson (1986) suggested that burnout could lead to a

deterioration in the quality of care or service that is provided

by staff. It correlates with various self-reported indices of

personal dysfunction, increased use of alcohol and drugs, 

and marital and family problems (Maslach & Jackson, 1986).

The st udy of burnout, therefore, certainly seems to be

beneficial to organisations and the general welfare of

companies and their workers in various organisational

contexts. 

Probably the most influential development in terms of scientific

exploration of the burnout construct was the development of 

the Maslach Burnout Inventory (MBI) (Maslach & Jackson, 

1986). Initially two versions of the MBI were developed, 

namely the MBI-ED (Educators) and MBI-HSS (Human Services

Survey). These versions measure Emotional Exhaustion,

Depersonalisation and Personal Accomplishment. When slightly

adapted versions of he MBI-HSS/ED were used outside the

targeted professions, psychometric results were rather

disappointing (e.g. Boles, Dean, Ricks, Short & Wang, 2000;

Evans & Fisher, 1993). The fact that, obviously, the MBI should

be used exclusively in those occupational contexts it has been

designed for – human services and education – has led to the

development of a version that can be used universally: The MBI

– General Survey (MBI-GS). The MBI-GS contains dimensions

similar to the original version, except that the items do not

explicitly refer to recipients or students (Schaufeli, Leiter,

Maslach & Jackson, 1996). Accordingly, the dimensions of the

MBI-GS have been renamed slightly as: exhaustion, cynicism

and professional efficacy. In the current study, the MBI-GS has

been used.

The importance of establishing a reliable and valid instrument to

assess burnout in a higher education institution is evident not

only for the purpose of empirical research, but also ultimately

for individual assessment. When determining factorial validity,

confirmatory factor analysis (through structural equation

modelling) should be used, because exploratory factor analysis

shows some weaknesses (Byrne, 1991). As such, a considerable

amount of research seems to support the psychometrical

soundness of the MBI in various occupational settings.

Regarding the MBI-GS, satisfactory internal consistencies for all

the subscales were found (Leiter & Schaufeli, 1996; Schutte,

Toppinen, Kalimo & Schaufeli, 2000). The three-factor structure

of the MBI-GS is generally confirmed (Taris, Schreurs &

Schaufeli, 1999; Schutte et al., 2000), although different results

in specific samples are found occasionally. For example, 

Salanova and Schaufeli (2000) observed four factors in 

Spanish workers. 

A systematic negative finding is that one particular cynicism

item (item 13 (sic!), ‘I just want to do my job and not to be

bothered’) seems to be unsound (e.g. Schutte et al., 2000). In

their studies Schaufeli, Leiter and Kalimo (1995) and Leiter and

Schaufeli (1996) also found that this item had the lowest factor

loadings of the three sub-scales. Therefore, this item was deleted

in the Dutch version of the MBI-GS (Schaufeli & Van

Dierendock, 2000). The three-factor structures of the original

version as well as the general version seem to be invariant across

countries (MBI-HSS: Enzmann, Schaufeli & Girault, 1995; MBI-

GS: Schutte et al., 2000) and occupations (Bakker, Demerouti &

Schaufeli, 2002; MBI-ED: Byrne, 1991; MBI-GS: Leiter &

Schaufeli, 1996; Bakker, Demerouti & Schaufeli, 2002). 

In South Africa few studies regarding the validity, reliability and

establishment of norms for various occupational settings using

the MBI-GS could be found (Rothmann, Jackson & Kruger, 2003;

Rothmann & Jansen van Vuuren, 2002; Rothmann & Malan,

2003; Storm & Rothmann, 2003). A lack of research in this area

within the South African higher education context necessitates

the current research. 

Rothmann (2003) stressed the need for burnout research in

South Africa in stating that serious limitations of burnout

research in South Africa include poorly designed studies (i.e.

small sample size), a lack of sophisticated statistical analysis (i.e.

confirmatory factor-analytical analysis by means of structural

equation modelling) and poorly controlled studies.

Despite the fact that, from a psychometrical point of view, the

MBI is a good tool for assessing burnout, a basic problem

remains. Because of the absolute predominance of the MBI, the

concept is narrowed to the three dimensions that are included in

the MBI, namely exhaustion, cynicism (or depersonalization),

and reduced professional efficacy (or personal accomplishment).

Although this common standard has the advantage that findings

across studies can be compared straightforwardly, for instance

by using meta-analyses, the narrow focus remains an issue. This

is all the more serious since the MBI is neither grounded in firm

clinical observation nor based on sound theorising. Instead, it

has been developed inductively by factor-analysing a rather

arbitrary set of items (Schaufeli, 2003). 

Clinical experience shows that burned-out employees who

receive psychotherapeutic treatment report a host of distress

complaints that are for a large part similar to those subsumed

under the ICD-10 diagnostic label of neurasthenia (Schaufeli,

Bakker, Schaap, Kladler & Hoogduin, 2001). Depending on one’s

definition, such at ypical distress symptoms as sleep

disturbances, irritabilit y, inabilit y to relax and tension

headaches can either be considered elements of burnout,

consequences of burnout or accompanying symptoms. More

specifically, clinical practice suggests that employees suffering

from severe burnout are characterised by cognitive impairment,

and report symptoms such as inabilit y to concentrate,

forgetfulness and difficulties with solving complex tasks

(Hoogduin, Schaap, Methorst, Peters Van Neyenhof & Van de

Griendt, 2001). Such cognitive symptoms typically occur when

one feels exhausted. 

Recently, Van Horn, Taris, Schaufeli and Schreurs (in press)

developed an alternative exhaustion scale that was labelled ‘The

Cognitive Weariness Scale’ which includes items such as “I have

trouble concentrating” and “I’m absent-minded”. Their study

COETZEE, ROTHMANN30



among teachers showed that this scale was reliable and that it was

substantively correlated with all MBI burnout scales, but

particularly with emotional exhaustion. Hence, based on

clinical experience, the MBI burnout concept should be

supplemented by cognitive exhaustion or weariness, and

perhaps also with distress symptoms (Schaufeli, 2003). The

Cognitive Weariness Scale was included for the purposes of 

this study.

Burnout can be enhanced by biographical factors. Biographical

factors that could explain burnout include age, work experience

and gender. Burnout is observed more often among younger

employees compared with those older than 30 years, and

burnout is negatively related to work experience (Cherniss,

1980; Künzel & Schulte, 1986; Maslach, Jackson & Leiter, 1996).

Zijlstra and De Vries (2001), however, found that older, more

experienced, single workers who experienced a high workload

were significantly more at risk compared to younger, less

experienced, married workers with a low workload. Women

tend to score higher on emotional exhaustion, whereas men

score higher on depersonalization (Schaufeli & Enzman, 1998).

Cash (1988) found that individuals with a higher level of

education were more prone to burnout, possibly due to the

higher expectations of both the individual and the organisation

of these individuals.

The objectives of this study were to determine the factorial

validity and internal consistency of an adapted version of the

Maslach Burnout Inventory – General Survey (MBI-GS) (by

including a Cognitive Weariness Scale), for employees at a

higher education institution in South Africa and to determine

differences in burnout levels among different biographical

groups. 

The Maslach Burnout Inventory – General Survey

In the beginning of the eighties, the first easy-to-administer self-

report inventories on burnout appeared – most notably the

Maslach Burnout Inventory (Maslach & Jackson, 1981). This

initiated a major stimulation of the scientific interest in

burnout. It is estimated that the MBI was used in over 90% of the

empirical publications on burnout since the mid-eighties

(Schaufeli & Enzmann, 1998). According to Koeske and Koeske

(1993), the MBI has taken a central position in shaping the

theoretical debate over the nature of burnout.

With the introduction of the MBI-GS, the three burnout

dimensions can be measured independently from the

professional context. The MBI-GS was designed to measure

burnout universally by means of three subscales, namely

exhaustion, cynicism and professional efficacy. The exhaustion

items are generic and refer to fatigue without direct reference to

service recipients as its source; the cynicism items reflect a

distant attitude towards one’s work instead of towards the people

one is working with; and the professional efficacy items

encompass the non-social aspects of occupational

accomplishments instead of exclusively focusing on the social

aspects of these accomplishments. Hence, the MBI-GS has a

broader scope than the original MBI (Schaufeli, 2003). Or put

the other way around, the original MBI dimensions can be seen

as manifestations of a more general burnout symptomatology;

that is, emotional exhaustion is a particular kind of exhaustion

(namely caused by emotional demands), depersonalisation is a

particular kind of cynicism (namely directed towards

recipients), and personal accomplishments is a particular kind of

professional efficacy (namely in relation to recipients).

An advantage is that the MBI-GS can be used both in human

services and non-human services samples, so that they can be

directly compared. For instance, Taris et al. (1999) showed that,

psychometrically speaking, the MBI-GS performed equally well

in a sample of software engineers as among university teaching

staff, but that levels of exhaustion and cynicism were

significantly higher in the former sample compared to the latter,

whereas the reverse was true for professional efficacy. In

addition, their theoretical model fitted equally well across both

samples: exhaustion was predicted by job demands and lack of

decision latitude, while cynicism and professional efficacy were

predicted by lack of decision authority and a lack of skill

discretion. In other words, the study of Taris et al. (1999) shows

that the MBI-GS can be used to measure burnout among

educators and corporate employees and that – despite differences

in levels – burnout is predicted by similar variables in both

samples. This is another indication that burnout is not a typical

helper syndrome. Other studies, using the MBI-GS have also

demonstrated the consistency of the burnout construct across

human services and non-human services samples (e.g. Bakker et

al., 2002; Leiter & Schaufeli, 1996).

In the literature regarding the MBI-GS, satisfactory internal

consistencies ranging from 0,73 (Cynicism) to 0,91 (Exhaustion)

were found (Leiter & Schaufeli, 1996). Reliability analysis done

by Schutte et al. (2000) showed that the Exhaustion and

Professional Efficacy sub-scales were sufficiently internally

consistent, but that one Cynicism item (item 13) should be

removed in order to increase the internal consistency beyond the

criterion of 0,70. According to them, this might be caused by the

ambivalence of the particular item: “I just want to do my job and

not be bothered”. In their studies, Schaufeli et al. (1995) and

Leiter and Schaufeli (1996) also found that this item had the

lowest factor loadings of the three sub-scales.

Four studies that used the MBI-GS in South African samples were

found. In a sample of senior managers in a manufacturing

industry, Rothmann and Jansen van Vuuren (2002) found

satisfactory alpha coefficients: Exhaustion = 0,79; Cynicism =

0,84 (after item 13 had been omitted); and Professional Efficacy

= 0,84. Rothmann and Malan (2003) found higher alphas

(Exhaustion = 0,98; Cynicism = 0,76; Professional Efficacy =

0,85), while Rothmann et al. (2003) found lower alphas for

Cynicism (0,72 after item 13 had been omitted) and Professional

Efficacy (0,69). Storm and Rothmann (2003) found alpha

coefficients of 0,88 (Exhaustion), 0,78 (Cynicism) and 0,79

(Professional Efficacy) in a sample of 2 396 police officers in

South Africa. They also confirmed the three-factor structure of

the MBI-GS. 

A large body of research has addressed the factor structure of

the MBI-HSS (Maslach & Jackson, 1986; Maslach, 1993), but it

seems as if there is a paucity of research on the internal and

external validit y of the MBI-GS (Taris et al., 1999).

Confirmatory factor analysis done by Schutte et al. (2000)

showed that the three-factor model was clearly superior to

alternative one-factor and t wo-factor models. Schaufeli,

Martinez, Pinto, Salanova and Bakker (2002) confirmed these

findings. Leiter and Schaufeli (1996) employed confirmatory

factor analysis using linear structural equation modelling and

also confirmed a three-factor structure. Similar results were

obtained by Taris et al. (1999). 

Confirmatory factor analyses by Rothmann et al. (2003),

Rothmann and Jansen van Vuuren (2002) and Rothmann and

Malan (2003) consistently showed low loadings on item 13 of

the MBI-GS on Cynicism. Storm and Rothmann (2003) used

structural equation modelling (SEM) methods as implemented

by AMOS (Arbuckle, 1997) to test the factorial model for the

MBI-GS on a random, stratified sample in the South African

Police Services (N = 2396). Prior to testing the three-factor model

of burnout, a one-factor model was tested. However, the one-

factor model showed poor fit, while a three-factor model, using

15 of the original items, resulted in a good fit.

Cognitive weariness refers to the lack of capacity to take up new

information and loss of concentration at work. Cognitive

weariness was devised as an analogue to Maslach’s (1993)

emotional exhaustion concept. Whereas the latter concept taps

feelings of work-related fatigue (thus reflecting the tiredness-

AN ADAPTED MODEL OF BURNOUT 31



vigour dimension of affect), cognitive weariness specifically

reflects employee’s cognitive functioning, especially the degree

to which workers are able to take up new information and are

able to concentrate on their work (Van Horn et al., in press).

Empirical research has shown that (affective) well-being on the

one hand and indicators of cognitive functioning (e.g. “the

number of minor everyday errors people make”, Broadbent,

Cooper, FitzGerald & Parkes, 1982) and self-reports about one’s

ability to concentrate and decision making skills (e.g. Goldberg,

1972; Wissing & Van Eeden, 2002) on the other are correlated. As

cognitive functioning is relevant for many of today’s jobs (e.g.

56% of the European workers report that they must solve

complex tasks (Merllié & Paoli, 2001), it was decided that this

dimension deserved an additional place in the model of burnout

(Schaufeli, 2003).

Burnout and biographical factors

Schaufeli (2003) est imated the prevalence of burnout

amongst the workforce in the Netherlands at about 4–7% 

of the working population, amounting to about 10% in

specific occupations. He warned that it should be kept in

mind that because of the healthy worker effect, these rates 

are inflated and most likely represent an underestimation of

the true number of burnout cases. Landsbergis (2003) 

stated that there is indeed no a priori reason why the

experience of burnout should be restricted to a particular

country or cult ural setting, all the more because the

organisation of work undergoes similar sweeping changes

across the globe, especially in developing countries. 

Research has shown that biographical factors can enhance

burnout. Using the MBI-GS in a national, representative

sample of the Dutch working population (N = 1,129), Zijlstra

and De Vries (2001) found that no differences in 

burnout levels were observed bet ween males and females, 

but that older, more experienced single workers who

experienced high workload were significantly more at risk

compared to younger, less experienced, married workers who

experience low workload. 

In order to determine a risk profile of employees at any

organisation, biographical indicators of burnout can be

helpful and can be used to direct future interventions.

Factors like job/role demand stressors, individual demand

stressors, participation, career progress opportunities and

supervisory st yle can act as antecedents of burnout (Posig

& Kickul, 2003). Biographical information of participants 

can shed light on which antecedent factors are prevalent 

in an organisation and can be utilised in directing both

proactive and reactive interventions. This information on

burnout should be relevant for all organisations, especially 

in the light of recent evidence which suggests that 

object ive work characterist ics (i.e. job autonomy, 

workload) which can be influenced by management are

related to burnout (Aiken, Clarke, Sloane, Sochalski & 

Silber, 2002; Taris, Stoffelson, Bakker, Schaufeli & Van

Dierendonck, 2002). 

Referring to the literature study of this research it can be

expected that regarding biographical characteristics of the

population the following differences may be expected: It seems

as if younger employees with less work experience will be more

prone to burnout than those older than 30 years (Cherniss, 1980;

Künzel & Schulte, 1986; Maslach, Jackson & Leiter, 1996). This

implies that it can be expected that younger employees will

reflect higher levels of burnout, and also that those with 

fewer years of experience at the institution will reflect higher

levels of burnout. 

With regard to differences bet ween employees from different

language groups, indications are that, even though not much

research evidence is available, no significant differences

regarding burnout patterns and burnout levels could be

found internationally bet ween different cultures (Enzmann

et al., 1995; Schutte et al., 2000). Therefore, it can be

expected that there would be no significant differences

bet ween language groups. With regard to gender differences,

Schaufeli and Enzmann (1998) found that women tend to

score higher on emotional exhaustion, whereas men score

higher on depersonalisation. Based on this, it can be expected

that women will reflect higher levels of burnout than their

male counterparts.  

The hypotheses of this study are as follows:

H1: Burnout, as measured by the MBI-GS and Cognitive

Weariness Scale, can be defined as a four-dimensional

construct with acceptable levels of internal consistency for

each of its subscales, namely Exhaustion, Cynicism,

Professional Efficacy and Cognitive Weariness.

H2: In terms of burnout levels of employees, significant

differences based on biographical characteristics like 

age, language group, gender and years of experience 

at the institution exist. Younger employees will reflect

higher levels of burnout, and those with fewer years 

of experience at the instit ution have will ref lect 

higher levels of burnout. No significant differences

regarding language group are expected. It can be 

expected that women will reflect higher levels of burnout

than their male counterparts.

METHOD

Research design

A cross-sectional survey design was used. Cross-sectional

designs are appropriate where groups of subjects at various

stages of development are studied simultaneously, whereas the

survey technique of data collection gathers information from

the target population by means of questionnaires (Burns &

Grove, 1993). A lthough Schaufeli and Enzmann (1998)

criticise the use of cross-sectional designs in the study of

burnout research and recommend that experiments and

longitudinal designs should be used as far as possible, it offers

the best possible design for the validation of the adapted

version of the MBI-GS.

Participants

AThe study population consisted of academic and administrative

staff at a tertiary institution in South Africa participated in the

study. A total of 820 questionnaires were sent out: academic staff

(N = 320); and administrative staff (N = 500). A total of 372

completed questionnaires were received back. This comprised

175 questionnaires from academic and 197 questionnaires from

administrative staff members, giving a total response rate of

45,36% (47,04% for academic staff and 52,96% for

administrative staff).

Females constit uted 63% of the participants. Different

language groups were included in the study. A total of 55% of

the participants were Afrikaans-speaking; 19% were English-

speaking; 11% Setswana-speaking; and 15% spoke other

indigenous languages. The majorit y (44%) of the participants

were married. In total, 25% of the populat ion had 

obtained master’s (or related) degrees and/or higher

qualifications. 47% indicated that they were improving their

qualifications. 34% of the participants had been at the

institution for 10 or more years of service. 66% reported to

have had no opportunit y to be promoted during their years

of service. The characteristics of the participants are shown

in Table 1.

COETZEE, ROTHMANN32



TABLE 1 

CHARACTERISTICS OF PARTICIPANTS

Item Category Percentage 

Employment category Academic 47,04

Administrative 52,96

Gender Male 37,12

Female 62,88

Language Afrikaans 54,59

English 19,46

Setswana 10,81

Other 15,14

Education Highest grade/standard 21,95

3-year qualification 23,04

4-year qualification 30,08

Master’s 19,24

Doctorate 5,69

Marital status Single/Divorced 15,76

Engaged/in relationship 37,77

Married 44,29

Years of service 0–5 years 31,29

5,1–10 years 35,19

10+ years 33,52

Opportunity for promotion none 65,71

1 23,49

2+ 10,80

Studying further Yes 47,28

No 52,72

Age distribution 23–30 19,94

31–40 37,19

41–50 26,21

51–60 15,95 

Measuring battery

The Maslach Burnout Inventory – General Survey (MBI-GS)

(Maslach et al., 1996) was used to measure burnout. The MBI-GS

consists of 16 items and has three subscales, namely Exhaustion

(Ex) (five items; e.g. “I feel used up at the end of the workday”);

Cynicism (Cy) (five items; e.g. “I have become less enthusiastic

about my work”) and Professional Efficacy (PE) (six items; e.g.

“In my opinion, I am good at my job”). These three components

of the burnout construct are conceptualised in broader terms

relating to the job and not just to the personal relationships that

may be part of the job (Maslach, Schaufeli & Leiter, 2001).

Together the sub-scales of the MBI-GS provide a three-

dimensional perspective on burnout. 

The items of the MBI-GS are phrased as statements about

personal feelings and attitudes, which are self-scored on a seven-

point frequency scale, ranging from 0 (never) to 6 (every day).

Internal consistencies found by Leiter and Schaufeli (1996) and

Schaufeli, Van Diederendonck and Van Gorp (1996) range from

0,73 (Cynicism) to 0,91 (Exhaustion). Test-retest reliabilities

after one year were 0,65 (Exhaustion), 0,60 (Cynicism) and 0,67

(Professional Efficacy) (Schaufeli et al., 1996). Test-retest

reliability form three months to one year ranged from 0,50–0,82

(Leiter & Durup, 1996). In four South African samples

(Rothmann et al. 2003; Rothmann & Jansen van Vuuren, 2002;

Rothmann & Malan, 2003; Storm & Rothmann, 2003) alpha

coefficients ranging from 0,69 (Professional Efficacy) to 0,98

(Exhaustion) were found. Storm and Rothmann (2003)

confirmed the three-factor structure of the MBI-GS in the South

African Police Service (SAPS), but also recommended that Item

13 should be dropped from the questionnaire. This study

confirmed the structural equivalence of the MBI-GS for different

race groups. 

The Cognitive Weariness Scale (CWS) was developed by Van

Horn et al. (in press) to measure cognitive well-being. Initially

this scale consisted of seven items, but they recommended that,

due to high internal consistency of items 3 and 7, item 7 be

dropped in the general six-item version. The scale refers to the

capacity to take up new information and loss of concentration

at work, for instance, “I have trouble concentrating”. It is scored

on a seven-point frequency scale with 0 (a few times a year) to 6

(every day). Van Horn et al. (in press) reported a Cronbach alpha

coefficient of 0,92. 

A biographical questionnaire was designed to gather gender,

position, education and marital status information. 

Statistical analysis

The statistical analysis was carried out with the help of the SAS

program (SAS Institute, 2000) and the AMOS program

(Arbuckle, 1997). 

To test the factorial validity of the MBI-GS, structural equation

modelling (SEM) methods were used with the maximum

likelihood method of the AMOS program (Arbuckle, 1997).

Hypothesised relationships are tested empirically for goodness

of fit with the sample data. The �2 statistic equals (N – 1) Fmin,

which value tends to be substantial when the model does not

hold, and the sample size is large (Byrne, 2001). A large �2

relative to degree of freedom indicates a need to modif y the

model to fit the data better. Researchers addressed the �2

limitations by developing goodness-of-fit indices that take a

more pragmatic approach to the evaluation process . One of

the first fit statistics to address this problem was the �2 /degree

of freedom ratio (CMIN/DF; Wheaton, Muthèn Alwin &

Summers, 1977). These criteria, commonly referred to as

“subjective/practical” indices of fit, are typically used as

adjuncts to the �2 statistics (Byrne, 2001). The following

goodness-of-fit-indices were used as adjuncts to the �2

statistics: a) The Goodness of fit Index (GFI); b) The Adjusted

Goodness of Fit Index (AGFI); c) The Normed Fit Index (NFI);

d) The Comparative Fit Index (CFI); e) The Tucker-Lewis Index

(TLI), and f) The Root Mean Square Error of Approximation

(RMSEA). 

Consequently descriptive statistics (e.g. means, standard

deviations, skewness and kurtosis) were used to analyse the data.

Cronbach alpha coefficients, inter-item correlation coefficients

and confirmatory factor analysis were used to assess the

reliability and validity (i.e. internal consistency, homogeneity

and unidimensionality) of the measuring instruments (Clark &

Watson, 1995). Coefficient alpha contains important

information regarding the proportion of variance of the items of

a scale in terms of the total variance explained by that particular

scale. According to Clark and Watson (1995), the mean inter-item

correlation (which is a straightforward measure of internal

consistency) provides useful information in conjunction with

the alpha coefficient of a scale (which is an indication of

homogeneity of a scale), but cannot ensure unidimensionality

of a scale. The range of inter-item correlations should also be

inspected in this regard. Sufficient clustering of correlations

around the mean should provide sufficient support for the

unidimensionality of a scale. 

Finally multivariate analysis of variance (MANOVA) was used to

determine the significance of differences between burnout

(exhaustion, cynicism, professional efficacy and cognitive

weariness) and various biographical characteristics of the

sample. MANOVA tests whether mean differences among

groups on a combination of dependent variables are likely to

AN ADAPTED MODEL OF BURNOUT 33



have occurred by chance (Tabachnick & Fidell, 2001). In

MANOVA a new dependent variable that maximises group

differences is created from the set of dependent variables. One-

way analysis is then performed on the newly created dependent

variable. Wilk’s Lambda was used to test the significance of the

effects. Wilk’s Lambda is a likelihood ratio statistic that tests

the likelihood of the data under the assumption of equal

population mean vectors for all groups against the likelihood

under the assumption that the population mean vectors are

identical to those of the sample mean vectors for the different

groups. When an effect was significant in MANOVA, ANOVA

was used to discover which dependent variables were affected.

Because multiple ANOVAs were used, a Bonferroni type

adjustment was made for inflated Type 1 error. Tukey tests were

done to indicate which groups differed significantly when

ANOVAs were done.

T-tests were used to determine differences between the groups

in the sample. Effect sizes (Cohen, 1988; Steyn, 1999) were used

in addition to statistical significance to determine the

significance of relationships. Effect sizes indicate whether

obtained results are important (while statistical significance

may often show results which are of little practical relevance).

The use of only statistical significance testing in a routine

manner has been criticised and from editors of some

periodicals there have been appeals to place more emphasis on

effect sizes (Steyn 1999). The following formula was used to

determine the practical significance of differences (d) when t-

tests were used (Steyn, 1999):

Where

Mean A = Mean of the first group

Mean B = Mean of the second group

SDmax = Highest standard deviation of the two groups

The following formula was used to determine the practical

significance of means of more than two groups (Steyn, 1999):

Where

Mean A = Mean of the first group

Mean B = Mean of the second group

Root MSE = Root Mean Square error

According to Cohen (1988), 0,10 = d = 0,50 indicates a small

effect, 0,50 = d = 0,80 indicates a medium effect, and d = 0,80

indicates a large effect. 

A cut-off point of 0,50 (medium effect) (Cohen, 1988) was set for

the practical significance of differences between group means.

RESULTS

Structural equation modelling (SEM) methods, as implemented

by AMOS (Arbuckle, 1997), were used to test the factorial

models for the MBI-GS. Data analysis was conducted in two

consecutive steps. Firstly, a quick overview of the model fit 

was done by looking at the overall �2 value, together with 

its degrees of freedom and probability value. Several goodness-

of-fit statistics (GFI, AGFI, PGFI, NFI, TLI, CFI and RMSEA)

were used for the global assessment of the model fits. 

Secondly, given findings of a poor-fitting initially

hypothesised model, exploratory analysis was done. Possible

misspecifications, as suggested by the so-called modification

indices, were looked for in order to fit a revised, re-

specified model to the data.

Hypothesised model

The aim of this study was to verif y an adapted model 

of burnout consisting of a three-factor model (as confirmed 

in research) with Cognitive Weariness as a fourth factor. 

Three default models using the total population were tested:

A one-factor model of burnout; a four-factor model of 

burnout (with Cognitive Weariness as fourth factor); and a

three-factor model of burnout with Cognitive Weariness

loading on Exhaustion. Table 2 presents fit statistics for the

default models.

TABLE 2

THE GOODNESS-OF-FIT STATISTICS FOR THE HYPOTHESISED ONE-

FACTOR, THREE-FACTOR AND FOUR-FACTOR MBI-GS MODELS

Default Model �2 �2/df GFI AGFI NFI TLI CFI RMSEA 

Model 1 1456,77 4,50 0,72 0,68 0,62 0,65 0,68 0,10

(1 factor)

Model 2 595,89 2,92 0,87 0,84 0,80 0,84 0,85 0,07

(3 factor)

Model 3  557,19 2,74 0,88 0,85 0,81 0,85 0,87 0,07

(4 factor)

The first model (Default Model 1) tested was a one-factor model

of the MBI-GS, but very poor overall fit was obtained, as

indicated by the statistically significant �2 value of 1456,77 (df =

323,72; p = 0,00). All the other fit indices confirmed an

extremely poor fit with the data.

The second model (Default Model 2) consisted of three factors,

namely Weariness (consisting of Exhaustion and Cognitive

Weariness), Cynicism and Professional Efficacy. Again a rather

poor overall fit was obtained, as indicated by the statistically

significant �2 value of 557,19 (df = 204,07; p = 0,00)

(Golembiewski & Munzenrider, 1988; Meier, 1984). All the other

fit indices confirmed a poor fit with the data.

The full hy pothesised four-factor model (Exhaustion;

Cynicism; Professional Efficacy; Cognitive Weariness)

consisting of 22 items (Default Model 3) was consequently

tested. The statistically significant �2 value of 557,19 (df = 203;

p = 0,00) still revealed a very poor overall fit with the

originally hypothesized four-factor model, but it is better

than the �2 values of the one-factor and three-factor models.

A ll other indices indicated a poor fit bet ween the

hypothesised model and the data obtained. From a practical

perspective, a large �2 value relative to the degrees of

freedom, together with NFI, TLI and CFI values lower than

0,95 and a RMSEA value higher than 508, are indicative of a

failure to confirm the hypothesised model and requires a need

to modif y the model to better fit the data. In order to

determine a model that better represents the sample data,

modification indices (MI) were examined to identif y possible

areas of misfit. Table 3 presents fit statistics for the subsequent

changes of the 4-factor model.

Looking at the regression weights, t wo parameters which

represent the cross-loading of Item 13 and 27 (Model 1)

indicated a considerably lower regression weight compared

with the other MBI items. Item 16 (Model 2) and Item 4

(Model 3) were also problemat ic. In the next step

considerable constrained error co-variation was detected

bet ween error 14 and error 15 (items 14 and 15) and error 11

and error 12 (items 11 and 12) (Model 4). These parameters

could account for the substantial misspecification of the

hypothesised factor loading.

_
A BMean Mean

Root MSE

max

_
A BMean Mean

SD

COETZEE, ROTHMANN34



TABLE 3

THE GOODNESS-OF-FIT STATISTICS FOR THE HYPOTHESISED

FOUR-FACTOR MBI-GS MODEL

Model �2 �2/df GFI AGFI NFI TLI CFI RMSEA 

Model 1 459,16 2,80 0,89 0,86 0,84 0,87 0,89 0,07

Model 2 361,77 2,48 0,91 0,88 0,86 0,89 0,91 0,06

Model 3 313,77 2,43 0,92 0,89 0,86 0,90 0,91 0,06

Model 4 298,87 2,35 0,92 0,89 0,87 0,90 0,92 0,06

Post-hoc analysis

Based on the regression weights and standardised residual co-

variances, the four-factor model was re-estimated with Item 13

and Item 27 removed (see Model 1). Consequently Item 16 (see

Model 2) and Item 4 (see Model 3) were removed. Errors of two

item pairs, namely Items 14 and 15 (errors 14 and 15) and Items

11 and 12 (errors 11 and 12) were allowed to correlate. The final

model of the MBI-GS structure (Model 4) was based on 18 of the

original 22 items and included correlated errors between items

14 and 15, as well as items 11 and 12. After testing each of the

resulting models, based on the adjustments as described, the �2

value and other indices appeared to have improved compared to

those of the original four-factor model.

The results of the final model (Model 4) are shown in Table 3.

Although the �2 value of 298,87 (df = 127; p = 0,00) is still high,

it is considerably lower than that of the hypothesised model. The

other fit statistics indicate an acceptable fit for the re-specified

model.

The descriptive statistics, alpha coefficients and inter-item

correlations of the four factors of the MBI-GS are given in 

Table 4.

TABLE 4

DESCRIPTIVE STATISTICS, ALPHA COEFFICIENTS AND INTER-ITEM

CORRELATIONS OF THE MBI-GS

Dimension Mean SD Skewness Kurtosis r (Mean) �

Exhaustion 11,32 6,37 0,13 -0,90 0,58 0,85

Cynicism 8,03 5,46 0,41 -0,20 0,37 0,70

Professional Efficacy 23,34 5,03 -0,76 0,25 0,28 0,66

Cognitive Weariness 9,50 6,05 0,47 -0,38 0,39 0,76 

The results in Table 4 indicate that the scores on the four

dimensions of the adapted model of burnout are normally

distributed. It is evident that with regard to internal consistency

three dimensions, namely Exhaustion, Cynicism and Cognitive

Weariness, seem to demonstrate acceptable coefficient alphas

above the 0,70 guideline provided by Nunnally and Bernstein

(1994). Even though the alpha coefficient for Professional

Efficacy (0,66) is below the guideline of 0,70, it is consistent

with the findings of Rothmann et al. (2003) in their study of

burnout (MBI-GS) and job stress in local government, and

Storm and Rothmann (2003) in the South African Police

Service. Furthermore, acceptable levels of inter-item

correlations have been obtained for three factors (Cynicism,

Professional Efficacy and Cognitive Weariness) consistent with

the guideline of 0,15 � r � 0,50 suggested by Clark and Watson

(1995). Exhaustion (0,58) had an inter-item correlation higher

than the guideline. A measure of internal consistency

(Cronbach alpha) is not an indication of the homogeneity or

unidimensionality of a scale, but it is necessary to take the

range of inter-item correlations into consideration when

considering homogeneity and unidimensionality (Clark &

Watson, 1995). In terms of these guidelines, the MBI-GS seems

to satisf y the requirements of homogeneity (acceptable internal

consistencies) and unidimensionality (acceptable clustering of

inter-item correlations around the mean).

These results provide support for Hypothesis 1. 

Next, MANOVA and ANOVA analyses followed to determine

the relationship between burnout and various biographical

characteristics, such as age, gender, language and, age, years

experience at instit ution and job category. Biographical

characteristics were first analysed for statistical significance

using Wilk’s’ Lambda statistics. The results are shown in 

Table 5.

TABLE 5

MANOVAS – DIFFERENCES IN BURNOUT LEVELS BASED

ON BIOGRAPHICAL CHARACTERISTICS

Variable Value F df Den DF p

Language 0,87 6,50 8 706 0,00*

Age 0,98 0,78 8 688 0,62

Years experience 0,94 2,64 8 702 0,00*

* Statistically significant difference: p � 0,01

In an analysis of Wilk’s Lambda values, no statistically

significant differences (p < 0,01) regarding burnout levels 

could be found bet ween different age groups. However,

statistically significant differences (p � 0,01) were found for

different language groups and categories of different years of

experience at the institution. The relationship bet ween 

burnout and those biographical characteristics that showed a

statistically significant difference was further analysed to

determine practical significance using ANOVA, followed by

Tukey HSD tests.

The ANOVAs of differences in burnout levels of the different

language groups are given in Table 6.

TABLE 6

ANOVAS – DIFFERENCES IN BURNOUT LEVELS OF

DIFFERENT LANGUAGE GROUPS

Dimension Afrikaans English Indigenous p Root MSE 

Exhaustion 12,31b 12,61b 8,18 0,00* 6,09

Cynicism 8,39 8,85 6,78 0,03 5,44

Professional efficacy 23,05 23,38 23,82 0,54 5,06

Cognitive Weariness 10,94c 9,76b 6,36 0,00* 5,73

* Statistically significant difference: p � 0,01

a Practically significant differences from language group (in row) where b (medium

effect, d � 0,5) or c (large effect, d � 0,8) are indicated

According to Table 6, Afrikaans- and English-speaking 

language groups scored significantly higher on Exhaustion

than the indigenous language-speaking groups (practically

significant, medium effect). Afrikaans- (practically 

significant difference, large effect) and English-speaking

(practically significant difference, medium effect) 

language groups also scored significantly higher than

indigenous language-speaking groups in terms of Cognitive

Weariness levels.

Table 7 shows the ANOVAs of differences in burnout levels for

different categories of years of experience at the institution.

AN ADAPTED MODEL OF BURNOUT 35



TABLE 7

ANOVAS – DIFFERENCES IN BURNOUT LEVELS OF

YEARS OF EXPERIENCE CATEGORIES

Dimension 0–5 years 5,1–10 years 10,1–44 years p Root MSE 

Exhaustion 9,54 10,96 12,87b 0,00* 6,23

Cynicism 6,40 7,74 9,03a 0,01* 5,49

Professional efficacy 24,90 23,06 22,99 0,06 5,03

Cognitive Weariness 8,13 9,07 11,13b 0,00* 6,00

* Statistically significant difference: p � 0,01

a Practically significant differences from group (in row) where b (medium

effect, d � 0,5) or c (large effect, d � 0,8) are indicated

Table 7 indicates that people with more than 10 years’ experience

at the institution scored practically significantly higher on the

Exhaustion (medium effect), Cynicism and Cognitive Weariness

(medium effect) dimensions of burnout in comparison with

those with 0–5 years experience. This is contrary to research that

has shown that burnout is negatively related to work experience,

and that younger employees are more prone to burnout

(Cherniss, 1980; Künzel & Schulte, 1986; Maslach, Jackson &

Leiter, 1996), but might be in line with the findings of Zijlstra

and De Vries (2001) that older, more experienced, single workers

who experienced a high workload were significantly more at risk

compared to younger, less experienced, married workers with a

low workload. 

No statistically significant differences could be found regarding

the burnout levels of different gender groups.

The results in Tables 5–7 provide partial supporting evidence for

the acceptance of hypothesis 2, which statedprojected that

significant differences based on the biographical characteristics

of gender, job characteristics, age, language and years of

experience at the institution will exist. In contrast with the

hypothesis, higher levels of burnout were found among workers

with more years of experience at the institution and significant

differences were found between different language groups. Also

unexpectedly, no differences were found between genders. It can

thus be concluded that, as hypothesised, differences based on

biographical characteristics were found, but they reflected quite

a different picture from that expected on the basis of 

the literature. 

DISCUSSION

The aim of this study was to determine the factorial validity and

internal consistency validate of an adapted four-factor model of

the the MBI-GS and Cognitive Weariness Scale for employees at

a higher education institution in South Africa and to determine

differences bet ween genders, different language groups,

employees in different age groups and employees with different

years of experience at the institution. 

The psychometric soundness of an adapted version of the the

MBI-GS and CWS was tested, i.e. the construct validity and

internal consistency. Reliability analysis confirmed sufficient

internal consistency of the subscales. The results obtained

using the structural equation modelling approach supported a

four-factor structure for the adapted MBI-GS and Cognitive

Weariness Scale with Exhaustion, Cynicism, Professional

Efficacy and Cognitive Weariness as factors. These findings are

is a first in South African research on burnout, and consistent

with the findings of Van Horn et al. (in press). However, based

on both conceptual and empirical grounds, items 4, 13 and 16

were eliminated from the original MBI-GS, resulting in a 13-

item scale. It seems as if problems with item 13 (“I just want

to do my job and not be bothered”) might be caused by the

ambivalent nature of the item, as confirmed by previous

research (Rothmann et al., 2003; Rothmann & Jansen van

Vuuren, 2002; Rothmann & Malan, 2003; Schutte et al. 2000).

Even though item 4 (“Working all day is really a strain for

me”) and item 16 (“At my work I feel confident that I am

effective at getting things done”) also contributed to

unwanted variance in the model, no theoretical premise could

be found for its omission in the post hoc analysis. Possibly,

this could be attributed to small sample size (N = 372) in

subsequent analysis, or alternatively to the fact that these

items were perceived as not relevant in the work reality, due

to the fact that the population in general did not report

excessively high levels of burnout. These two questions are

specifically related to aspects of overload which do not seem

to be a major stressor among the population of this

institution, and thus could result in participants’ disregard of

the relevance of these specific questions in their work

situation, subsequently contributing to the unwanted variance

in the model. The ambivalent content of these two items

could also play a role here. Even though the elimination of

items 4 and 16 increased model fit, their omission in post hoc

analysis can be explained on conceptual grounds and should

be validated in future larger replicated studies in higher

education institutions. 

The fourth burnout dimension that was added in this study was

the six-item Cognitive Weariness scale as compiled by Van Horn

et al. (in press). Item 27 (“I have problems processing new

information”), which forms part of the six-item Cognitive

Weariness Scalet scale, proved to be problematic and was

subsequently eliminated on conceptual and empirical grounds.

Its omission from post hoc analysis might also be explained by

the ambivalence of this particular item. Participants might

relate this item to a study and not to a work scenario and

misinterpret its content as related to the processing of study

material which might not be relevant for the 53% of the

population not currently involved in improving their

qualifications. However, the omission of this item should be

validated in future research.

Furthermore, error terms within the subscales were allowed to

correlate in order to improve model fit. Although correlated

error terms may be derived from specific characteristics of

either the respondents or the items of a survey, they represent

systematic rather than random measurement error in item

responses. This could indicate, for example, a small omitted

factor or, which is more likely the case in the current study,

could be reflective of respondent characteristics contributing

to the bias of an instrument by means of randomly

responding to items without really reading the items, social

desirabilit y (Aish & Jöreskog, 1990) as well as a high degree

of item content overlap, i.e. different wording of an item, but

essentially meaning the same thing (Byrne, 2001). From a

technical, psychometric point of view the MBI-GS is a good

instrument. From a clinical psychological perspective the

MBI-GS does not cover the whole range of symptoms that are

observed among employees with severe burnout (Schaufeli,

2003). Most notably cognitive impairment and, distress

symptoms (neurasthenic distress) are excluded while and

reduced professional efficacy does not seem to play an

important role. This research seems to prove that the original

model of the MBI-GS is in need of re-specification and that

additional aspects (e.g. cognitive weariness and, neurasthenic

symptoms and professional efficacy) need to be considered

for future inclusion.

Regarding the differences in burnout levels based on

biographical characteristics, it was found that Afrikaans (55%

of the population) and English (19% of the population)

language groups experience significantly higher levels of

Exhaustion and Cognitive Weariness than the indigenous

language groups (26% of the population). Employees with

more than 10 years experience at the institution (34% of the

COETZEE, ROTHMANN36



population) also experience significantly (practically and

statistically significant differences) higher levels of

Exhaustion, Cynicism and Cognitive Weariness. This is in

contrast with research that has shown that younger employees

are more prone to burnout and that burnout is negatively

related to work experience (Cherniss, 1980; Künzel & Schulte,

1986; Maslach et al., 1996), but might be in line with the

findings of Zijlstra and De Vries (2001) that older, more

experienced, single workers who experienced a high workload

were significantly more at risk compared to younger, less

experienced, married workers with a low workload. 

These observations might be understood if the recent history

of this institution is taken into account. During the past eight

years the student population has been transformed from

predominantly white to predominantly black students. This

led to the change of the official language used at the

institution from Afrikaans to English. During the same time

(in adherence to the equity legislation passed by the post-

apartheid government of South Africa), a decision was made to

appoint only designated groups (i.e. black, Indian, Coloured

and white female applicants, in order of preference) in vacant

positions to ensure that the staff component reflects the

demographics of the area (Vaal Triangle). Consequently, the

staff component was changed from predominantly white to

being demographically representative, and the management of

the institution was also transformed. 

As a result of these fast-paced and radical interventions, most

of the employees with more than 10 years’ experience are white

and in the Afrikaans- (55%) and English-speaking (19%)

language groups. The Afrikaans speaking, white employees

additionally had to adjust to communicate/educate second

language-speaking students (indigenous languages) in , for

them also, a second language (English). Both the Afrikaans and

English language groups who have been employed at the

institution for more than 10 years were are also subjected to

radical changes with regard to the culture of their clients (the

students) and their co-workers. Another source of change

might be the total transformation of the top management of

the institution and its secondary impact on the governance,

culture and climate of the organisation. Adjusting to these

changes in a relatively short period of time might have resulted

in elevated levels of Exhaustion, Cognitive Weariness and

Cynicism among the Afrikaans- and English-language groups

in comparison with the indigenous language-speaking (26%)

staff component, who in the population also predominantly

represent those with 0–5 years of experience. Of concern is the

fact that those employees adversely affected by Exhaustion,

Cognitive Weariness and Cynicism represent, based on

language groups, 74%, and based on years of experience, 34%

of the population – figures that cannot be ignored if employee

wellness is a priority in an organisation. 

In conclusion, a this st udy could serve as a standard

regarding burnout levels of the total population in a higher

education instit ution. Added to the previously accepted

three-factor structure of burnout, an adapted four-factor

structure of burnout is largely confirmed, as well as the

internal consistency of Exhaustion, Cynicism, Professional

Efficacy and Cognitive Weariness. Based on the results

obtained in the study, it would seem as if the adapted version

of the MBI-GS in combination with the Cognitive Weariness

Scale could be regarded as a suitable instrument for

measuring burnout in higher education institutions in South

Africa. The higher levels of Exhaustion, Cognitive Weariness

and Cynicism that were observed among Afrikaans- and

English-language groups, as well as among those with more

than 10 years’ experience at the institution, are also an

alarming aspect that certainly justifies further research,

especially in inst it ut ions that are marked by radical

transformation in a short period of time.

A limitation of this study is its reliance solely on self-report

measures. According to Schaufeli, Enzmann and Girault (1993)

the exclusive use of self-report measures in validation studies

increases the likelihood that at least part of the shared

variances between measures can be attributed to method

variance. Another limitation is the size of the sample, which

has significant limitations in terms of the generalisation of the

findings applied to the total study population. Future studies

could benefit hugely in terms of a stratified random-sample

design which would ensure sufficient representation of the

different groups in the total population. Also, in terms of the

research design, future studies should focus on longitudinal

designs where inferences in terms of cause and effect could be

made. Future studies conducted should consider extending the

sample to include employees of all the higher education

institutions in South Africa in order to standardise an adapted

version of the MBI-GS for employees of higher education

institutions in South Africa.

RECOMMENDATIONS

According to the results obtained in this study, the use of the

MBI-GS combined with the Cognitive Weariness Scale is

recommended to assess burnout in higher education institutions

in South Africa. However, item 13 should be omitted from 

the MBI-GS. The additional omission of items 4 and 16 from 

the MBI-GS and item 27 from the Cognitive Weariness Scale

(item 6 in the original version of CWS) should be validated in

future research.

In order to fully understand the effect of different biographic

characteristics on burnout and cognitive weariness, especially

in institutions undergoing radical transformation on different

levels simultaneously, it is recommended that future studies

with regard to higher education institutions in South Africa

be expanded to measure the secondary impact that the

negative residue of burnout might have on affected

employees, students and co-workers. Another informative

investigation could include the effect of burnout and

cognitive weariness on the psychological contract and

organisational commitment of the individual. 

It is suggested that future research focus on the MBI-GS and

Cognitive Weariness Scale in other higher education institutions

in South Africa to verif y the current findings. Other

occupational settings should also be investigated in a similar

manner in order to verif y the reliability and validity of the MBI-

GS and Cognitive Weariness Scale. It is also important to

determine norm levels for other occupations in South Africa. It

is recommended that larger samples with a more powerful

sampling method be utilised to enable generalisation of the

findings to other similar groups. It might also be necessary to

translate the adapted version of the the MBI-GS and Cognitive

Weariness Scale into other languages used in South Africa.

AUTHOR NOTE

The material described in this article is based upon work

supported by the National Research Foundation under Grant

number 2053344.

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