Discussion 2 week 6

ORIGINAL ARTICLE

Burnout among employees in human service work: design and baseline findings of the PUMA study

MARIANNE BORRITZ 1,2

, REINER RUGULIES 1 , JAKOB B. BJORNER

1,3 ,

EBBE VILLADSEN 1 , OLE A. MIKKELSEN

1 & TAGE S. KRISTENSEN

1

1 National Institute of Occupational Health, Denmark,

2 Department of Occupational Medicine, Bispebjerg Hospital,

Copenhagen, Denmark, and 3 Quality Metric Incorporated, Lincoln, RI, USA

Abstract Aim: To present the theoretical framework, design, methods, and baseline findings of the first Danish study on determinants and consequences of burnout, and the impact of workplace interventions in human service work organizations. Method: A 5-year prospective intervention study comprising 2,391 employees from different organizations in the human service sector: social security offices, psychiatric prison, institutions for severely disabled, hospitals, and homecare services. Data were collected at baseline and at two follow-ups. The authors developed a new burnout tool (the Copenhagen Burnout Inventory) covering work- related, client-related, and personal burnout. The study includes potential determinants of burnout (e.g. the psychosocial work environment, social relations outside work, lifestyle factors, and personality aspects) and consequences of burnout (e.g. poor health, low job satisfaction, turnover, and absenteeism). Here, the focus is on the description of the study population at baseline, including associations of work burnout with psychosocial work environment scales and absence. Results: Response rate at baseline was 80.1%. Midwives and homecare workers had high levels on both work- and client-related burnout. Prison officers had the highest level on client-related burnout. Supervisors and office assistants had low levels on both scales. Work burnout showed the highest correlations with job satisfaction (r520.51), quantitative demands (r50.48), role-conflicts (r50.44), and emotional demands (r50.42). Sickness absence was 13.9 vs 6.0 days among participants in the highest and lowest work burnout quartile, respectively. Conclusion: The findings indicate that study design and methods are adequate for the upcoming prospective analyses of aetiology and consequences of burnout and of the impact of workplace interventions.

Key Words: Burnout, Copenhagen Burnout Inventory, exhaustion, human service work, intervention study, occupational health, prospective study, psychosocial factors

Introduction

During the mid-1990s Danish unions in the human

service sector recognized that an increasing number

of their members took long-term sick leave, or

applied for retraining or early retirement, because of

burnout symptoms. Although Denmark has one of

the largest numbers of employees working in the

human service sector in the Western world no major

study on burnout had been conducted in Denmark.

For these reasons, we designed the study on Burn-

out, Motivation and Job satisfaction (Danish acro-

nym: PUMA), a five-year prospective intervention

study on burnout in the human service sector. The

study has four aims: (1) to map the extent of burnout

among different occupational groups in the human

service sector in Denmark; (2) to identify individual

and workplace factors that increase the risk of

burnout; (3) to analyse the impact of burnout on

job satisfaction, job turnover, absenteeism, early

retirement, morbidity, and mortality; and (4) to

evaluate whether workplace interventions that aim to

improve the psychosocial work environment can

reduce burnout and its repercussions.

Burnout is a concept developed in practice. It first

emerged in the United States in the mid-1970s when

Correspondence: Marianne Borritz, National Institute of Occupational Health, Denmark, Lersø Parkallé 105, DK-2100 Copenhagen Ø, Denmark.

Tel: +45 39 16 52 87. Fax: +45 39 16 52 01. E-mail: [email protected]

(Accepted 17 February 2005)

Scandinavian Journal of Public Health, 2006; 34: 49–58

ISSN 1403-4948 print/ISSN 1651-1905 online/06/010049-10 # 2006 Taylor & Francis

DOI: 10.1080/14034940510032275

two researchers, Herbert Freudenberger and Christina

Maslach, independently described burnout as a

negative consequence of human service work,

characterized by emotional exhaustion, loss of

energy, and withdrawal from work [1–11]. In the

pilot phase of the PUMA study we tested the

Maslach Burnout Inventory (MBI) but did not find

it satisfactory [4]. First, the respondents strongly

criticized a number of the questions. Hence, we did

not find the questionnaire usable in the Danish

context. Second, the questionnaire is restricted to

use among employees working with recipients

(clients). Third, the burnout concept of the MBI

consists of three parts of which one can be regarded

as a coping strategy (depersonalization) and

another as a consequence of burnout (reduced

personal accomplishment). Fourth, the MBI

defines burnout as a reaction that only takes place

among people who do ‘‘people work’’, which leads

to a circular argument. In the PUMA study we

wanted to focus on exhaustion as the core element

of burnout. In order to do this, we developed our

own instrument, the Copenhagen Burnout

Inventory (CBI), that focuses on exhaustion. We

distinguish between three different types of exhaus-

tion: personal burnout, work-related burnout, and

client-related burnout. A detailed description of the

CBI is given in the method section of this paper,

and a manuscript with a detailed comparison of the

CBI burnout concept with the burnout concept of

other researchers is in preparation.

In PUMA, we are focusing on the specific type of

human service work called ‘‘client work’’. In our basic

understanding of working with humans we distin-

guish between three categories: clients, customers,

and colleagues. Clients can be social service recipi-

ents, patients, elderly citizens, pupils, or inmates.

The basic relation to the client is professional, and

the employee is acting on behalf of society in order to

bring about a change in the client (to become

healthy, more educated, less criminal, etc.) [12].

Customers are buying a commodity on the market.

Relations with customers are commercial and

usually much shorter and less emotionally involving

for the employee. Finally, we use the term colleagues

to describe all employees at the worksite with whom

the person has interaction (including supervisors and

subordinates). Relations with colleagues can be

emotionally involving and long lasting but also

superficial and short. Unfortunately, the interna-

tional literature on burnout rarely distinguishes

between clients and customers [8,13].

Since the 1980s, more than 5,500 studies on

burnout have been published [8]. Most studies

indicate that burnout is a serious problem. In

Sweden and Finland population-based studies found

severe burnout in 5–7% of the workforce [14,15]. In

the Netherlands researchers estimated that 3–16% of

Dutch human service work professionals have severe

burnout [8].

Research indicates that work-related factors such

as high demands and low influence, low social

support, and low role-clarity increase the risk of

burnout [8]. Factors outside work that need to be

considered are social relations and personality [8].

However, knowledge about causality is still limited,

because most studies are cross-sectional and there-

fore do not allow causal inference. The relatively few

prospective studies often involved participants from

only one occupational group, which results in low

variation of exposure and therefore limits the

ability to analyse causal associations. Moreover,

most prospective studies covered only one year or

less of follow-up, included few participants, or had

low response rates [4,8]. Burnout, however, is

associated with risk of absenteeism, sick leave and

disability claims, as well as low job satisfaction, and

high job turnover [8,14].

Figure 1 shows the theoretical framework of

PUMA regarding the determinants and conse-

quences of burnout. The framework is based on

both extensive reviews of the literature and on

discussions with focus groups, employers, and

employees’ representatives. We hypothesize that

the psychosocial work environment plays a major

role in the onset of burnout (see Figure 1). Because

working with clients is a core characteristic of human

service work [12,13], we differentiate the psychoso-

cial work environment in client-related and non-

client-related factors. Client-related factors include

emotional demands and demands for hiding emo-

tions at work. This also covers situations where focus

is solely on helping the client and when focus is on

both help and control, e.g. in a psychiatric hospital

[12]. Non-client-related factors are psychosocial

exposures often measured in work and health

research, such as quantitative demands, influence

in the workplace, or social support from supervisors

and colleagues [17]. Interestingly, although the

relation of burnout to client work is widely acknowl-

edged, most burnout studies have focused on these

general psychosocial exposures, whereas only a

few studies have explicitly addressed client-related

factors [13].

In addition to psychosocial work environment

factors, sociodemographic characteristics of the

employees (e.g. age, sex, and cohabitant status),

social relations outside the workplace, lifestyle (e.g.

smoking and alcohol consumption), and personality

aspects may influence the risk of burnout. These

50 M. Borritz et al.

factors could act independently, but could also

interact or mediate each other’s effect.

Potential consequences of burnout (Arrow B) are

job dissatisfaction, job turnover, absenteeism, and

early retirement, and possibly morbidity and mortality.

As with the determinants, the consequences might be

interrelated. For example, poor health will probably

increase absenteeism from work and early retirement.

Whereas the main interest of PUMA is to analyse

the determinants and consequences of burnout, we

acknowledge that not all causal associations in the

figure are uni-directional. It is possible that burnout

influences some of the variables we plan to analyse as

determinants (Arrow C). For example, high levels of

burnout may lead to changes in workplace char-

acteristics, such as an increase in part-time employ-

ment or a decrease in the amount of time working

with clients. Conversely, some consequences might

also influence burnout (Arrow D). For example,

quitting a highly demanding job and getting a less

demanding job (job turnover) could result in a

decreasing level of burnout. These issues of bi-

directionality and reciprocal effects need to be

addressed in the data analyses. We are able to do

this because PUMA is a prospective study with a

full-panel design, including three measurement

times (baseline, three-year follow-up, five-year fol-

low-up) at which both potential predictors and

potential consequences of burnout are measured.

This will enable us to disentangle uni-directional

and bi-directional (reciprocal) effects of the vari-

ables we regard as potential ‘‘determinants’’ and

‘‘outcomes’’.

In this first paper, we describe the design and

methods of PUMA and present selected baseline

findings regarding psychosocial work environment,

sickness absence, and burnout.

Material and methods

Study design

PUMA is designed as a five-year prospective

intervention study in different organizations in the

human service sector. All organizations were self-

selected to the study after meetings between

representatives from employers’ and employees’

organizations and the PUMA project group.

Criteria for inclusion were (1) the organizations

should represent different areas within the human

service sector; (2) the size of the organization should

be between 200 and 500 employees; (3) all occupa-

tional groups within each organization should be

willing to participate; (4) the organizations should

commit themselves to the entire five-year study

period and (5) personal registration numbers

(national identity numbers) of the employees could

be collected and used in later record linkages by the

Danish Institute of Occupational Health, including

linkages to Danish registries for hospitalization and

mortality (Hospitalsindlæggelsesregisteret, Dødsår-

sagsregisteret).

Initially, we also had the criterion that the

organizations should agree to implement interven-

tions after the collection of baseline data, but neither

employers nor employees were willing to commit

themselves in advance. However, it was agreed that

the organizations should receive the survey results

after each round and establish project committees to

review and discuss the findings. Based on the survey

results and the work in the committees, the

organizations could develop and implement inter-

ventions. PUMA therefore is a quasi-experimental

study, in which the feedback of the survey results

could initiate ad-hoc interventions. Type, implemen-

tation, and conduct of these interventions will be

Figure 1. Theoretical framework of the PUMA study.

Burnout among employees in human service work 51

evaluated through separate telephone interviews

with key informants and questionnaires to all

participants at later stages of the PUMA study.

The impact of the interventions on working condi-

tions, burnout, and health outcomes will be analysed

both at the individual level and at the workplace

level.

Study population

Seven different organizations within the human

service sector participated in the study: (1) 10 social

security offices in an urban area; (2) a state

psychiatric prison; (3) 16 county institutions for

severely disabled people; (4) three somatic wards

(surgical, medical, gynaecological-obstetric) from

two county hospitals; (5) one psychiatric ward from

a psychiatric hospital; (6) one homecare service in a

rural area; and (7) one homecare service in an urban

area. All occupational groups in each organization

were invited to join the study, resulting in 2,391

eligible employees. At baseline, 1,914 employees

participated in the survey, yielding a response rate of

80.1%.

The Danish Data Protection Agency (Datat-

ilsynet) and Scientific Ethical Committees (Viden-

skabsetisk Komité) in the respective counties have

given approval for the PUMA study.

Data collection

Data were collected in 1999–2000 (baseline) and in

2002–03 (first follow-up). A third round of data

collection is planned in 2005 (second follow-up).

Therefore, PUMA consists of three cross-sectional

samples and one prospective cohort (baseline

participants followed up over time). All rounds have

the same sampling procedure: we obtained the home

address of all employees from the participating

workplaces and then sent an invitation letter from

the organization together with a study description

and the survey questionnaire. We contacted the

project committee at worksites with low response

rates to find the reasons for low participation and to

help improve employers’ and employees’ commit-

ment to the study. Employees who left the cohort

after baseline or first follow-up assessment will get a

special questionnaire in the 2004–05 follow-up to

assess their current connection to the labour market.

Employees who entered the workforce in the

organizations after the baseline assessment were

eligible for participation in the follow-up surveys

(open cohort principle).

Measurements

Measurements in PUMA were mainly based on self-

reported questionnaires. In accordance with the

theoretical framework presented in Figure 1, we

measured burnout, its potential determinants, and

its potential consequences.

Burnout. Burnout was measured with the

Copenhagen Burnout Inventory (CBI), an

instrument specifically developed for PUMA

[18,19]. The CBI focuses on exhaustion and is

divided into three scales. Personal burnout contains

six items on general symptoms of exhaustion and is

applicable to every person, regardless of whether

the person is a member of the workforce or not.

Work-related burnout comprises seven items on

symptoms of exhaustion related to work and

applies to every person in the workforce. Client-

related burnout is based on six items on symptoms of

exhaustion related to working with recipients in

human services and is applicable only to people who

work with clients. All items have five response

categories. The responses are rescaled to a 0–100

metric (the values being 0–25–50–75–100). Scale

scores are calculated by taking the mean of the items

in that scale. A full list of all burnout items – together

with the response frequencies and Cronbach’s

alphas for the scales – is provided in the result

section.

Non-client-related psychosocial work environment

factors. In accordance with the theoretical framework

in Figure 1, we distinguished between client-related

and non-client-related psychosocial work environment

factors. Non-client-related factors were measured

with scales from the Copenhagen Psychosocial

Questionnaire (COPSOQ), a comprehensive and

validated instrument on work and health [20–22].

Among other things, the COPSOQ includes scales on

well-established psychosocial workplace factors such

as demands, control, and social support at work [23].

We used a total of 16 scales: two scales on demands

(quantitative demands, cognitive demands), five scales

on active and developmental work (influence,

possibilities for development, meaning of work,

commitment to the workplace, and quality of

leadership), seven scales on interpersonal relations at

work (feedback, predictability, role clarity, role conflict,

social support at work, social relations, and sense of

community), one scale on job insecurity, and one scale

on job satisfaction. A complete list of all scales,

including their correlations with work burnout, is

presented in the results section.

52 M. Borritz et al.

Client-related psychosocial work environment

factors. Client-related factors were assessed with

scales on emotional demands and demands for

hiding emotions from the COPSOQ, single items

with specific questions about working with clients,

and one proxy measure about types of client. The

single items were developed de novo for the PUMA

study to obtain more detailed information on the

daily work with clients: (1) frequency of client contact

was measured with the question ‘‘How much

contact do you have on average with clients during

the working week?’’), with the four response

categories ‘‘almost all the working time’’, ‘‘more

than half the working time’’, ‘‘less than half the

working time’’, and ‘‘never/almost never’’; (2)

demands from clients were measured with the

question ‘‘The demands are many in the xxx

sector. How do you experience these demands?’’,

with seven response options ranging from ‘‘very low

demands’’ to ‘‘very high demands’’; (3) increasing

demands from clients was measured with the question

‘‘Do you experience that the clients in general have

become more demanding during the last few

years?’’, with five response categories ranging from

‘‘to a very high degree’’ to ‘‘to a very low degree’’;

(4) rewards from clients was measured with the

question ‘‘Do you feel that your work is

appreciated by the clients?’’, with five response

categories ranging from ‘‘always’’ to ‘‘never’’;

and (5) violence and threats from clients was

measured by asking the participants to list the

number of these occurrences during the last 12

months. Finally, we used the type of organization

(prison, hospital, social security office etc.) as a

proxy measure for the type of client that the

participants are exposed to.

Other workplace characteristics. We collected data on

other workplace characteristics, such as the type of

department or institution, job title, seniority, and

number of working hours per week of the

participants and work shift arrangement.

Sociodemographic factors. We assessed age, sex,

education, cohabitant status, number and age of

children living at home.

Social relationships outside the workplace. We

measured social support and social networks

outside the workplace and interferences between

demands at work and at home with single items,

which had been previously been used in the

Intervention Project on Absence and Well-being

(IPAW study) [24].

Lifestyle. We asked the participants about their

smoking habits (never smoked, former smoker, and

current smoker) and the number of cigarettes or

amount of tobacco smoked per day. Weekly physical

activity was assessed on a four-point response scale,

ranging from almost totally passive to strenuous

exercising for more than four hours per week.

Alcohol consumption was measured by asking the

participants how many drinks per week they had

consumed on average during the last four weeks. We

assessed height and weight and calculated the body-

mass index (BMI).

Personality. We used the Sense of Coherence Scale

(SOC) to assess an important aspect of personality.

The concept was developed by Antonovsky and

describes a perception of the world as

comprehensive, manageable, and meaningful [25].

We used a nine-item SOC scale, which was

developed by Setterlind and is included in the

COPSOQ.

Job satisfaction and job turnover. We measured job

satisfaction by using the respective scale from the

COPSOQ. Job turnover was defined as leaving the

organization and was assessed by comparing the lists

of employees at baseline and at follow-up.

Absenteeism and early retirement. We measured

sickness absence by asking the participants to list the

number of sickness absence days and sickness

absence spells over the last 12 months. In

accordance with regulations in Denmark, we

defined early retirement as retiring before the age of

60 years. We will also assess this variable objectively

by linking the PUMA study population to national

registers.

Self-reported health indicators. We measured self-

rated health with scales on general health, mental

health, and vitality from the Danish version of the

Short-Form 36 (SF-36) questionnaire [26–28].

Stress reactions were measured with three scales on

behavioural, somatic, and cognitive stress reactions,

which were developed by Setterlind and are included

in the COPSOQ. We further asked the participants

about the frequencies of headaches and migraines and

their medicine intake (pain-killers, tranquillizers and

sedatives) over the last four weeks.

Data analysis

In this paper, we explore the distribution of burnout

in the study population on organizational and

occupational group-level based on data from the

Burnout among employees in human service work 53

baseline survey. We dichotomized the responses on the

client factors: contact less than half or more, versus none

of the working time; demands from clients rated 6–7

versus 1–5; rewards from clients always or often versus

sometimes to never; and 1+ versus 0 events of violence/ threats during the last 12 months. All analyses were

stratified by organization and occupational group. We

investigated the internal consistency of the three

burnout scales by calculating Cronbach’s alphas (with

an alpha of 0.70 or higher indicating satisfactory

internal consistency), analysed inter-correlations

between the scales with Spearman’s rank correlation,

and examined the response pattern for each item of the

scales. We plotted work burnout and client burnout

scores to identify occupational groups with co-

occurrence of both high work burnout and high client

burnout. For the psychosocial work environment

scales, we determined the internal consistency with

Cronbach’s alphas and calculated Spearman’s correla-

tion coefficients with work burnout. Finally, we

explored associations between work burnout and

sickness absence by dividing the burnout scores in

quartiles and calculated the number of absence days

for each quartile.

Results

Characteristics of the PUMA study population at

baseline

All organizations had high response rates of 74% or

more at baseline (Table I). Most occupational groups

had client contact for more than two-thirds of the

working week, except some supervisors and office

assistants. Hospital doctors and midwives reported the

highest demands from clients, while district nurses in

urban homecare reported low client demands. District

nurses (urban homecare) and senior doctors reported

the highest rewards from clients, while supervisors and

office assistants in the psychiatric prison reported low

rewards. Threats and violence were reported by 67%

of the psychiatric staff, and were reported more often

in the psychiatric prison and the institutions for

severely disabled than in the other organizations.

The average age of the study participants was 42

years (SD 10.3), with only small variations between

the organizations. The majority were women (83%),

with the exception of the psychiatric prison, which

had a near equal gender distribution.

Response to the burnout items and psychometric

properties of the burnout scales

Cronbach’s alphas for the scales were 0.87 for both

personal and work-related burnout, and 0.85 for

client-related burnout (Table II). The correlation

coefficients between the scales were 0.73 for

personal and work burnout, 0.46 for personal and

client burnout, and 0.61 for work and client

burnout.

Work burnout and client burnout among occupational

groups

In Figure 2 we plotted work burnout against client

burnout for the occupational groups. A co-

occurrence of both high client and high work

burnout was found in midwives, urban home care

workers, social workers in the social security service,

and social care workers in the institutions for the

chronically disabled.

Internal consistency of psychosocial work environment

and associations with work burnout

Cronbach’s alphas were satisfactory (0.70 or higher)

for 12 of the 18 scales (Table III). Correla-

tion coefficients between the psychosocial work-

environment scales and work burnout were highest

for job satisfaction (20.51), quantitative demands

(0.48), role conflict (0.44), and emotional demands

(0.42); and lowest for job insecurity (0.11) and

cognitive demands (0.14).

Participants who scored in the lowest quartile of

work burnout had 6.0 days of sickness absence,

while participants in the following quartiles had 6.9,

10.3, and 13.9 absence days per year, respectively

(test for linearity: pv0.0001).

Discussion

All three burnout scales of the CBI showed good

internal consistency. Several occupational groups

had high scores on either the work- or the client-

related burnout scale, but not necessarily on both

scales, indicating that a differentiation between these

two types of burnout is justified. All scales on

demands at work and the scale on role conflicts

correlated positively with work burnout, whereas all

scales on resources correlated negatively. As pointed

out in the introduction, these associations do not

establish causal associations, because of the cross-

sectional nature of the data. However, the correla-

tions indicate that it is worthwhile to pursue analyses

of the impact of psychosocial work environment

factors on burnout further, when prospective data

are available. With regard to consequences of

burnout, we found a linear association between

burnout levels and numbers of sickness absence

days. As with determinants of burnout, this does not

54 M. Borritz et al.

establish causality, but it encourages further pro-

spective research.

A limitation of the study is the self-selection of the

participating organizations. These organizations may

represent very active workplaces in which both

management and employees have an interest in

reducing burnout. Therefore, we cannot assume that

the organizations are representative of the human

service sector in Denmark.

The participation rate at the baseline survey was

high, with 80% overall and 74% to 87% for the

different organizations respectively. Whereas this rate

indicates a low likelihood of selection bias, we must

consider that people with high levels of burnout might

have felt too exhausted to complete the questionnaire

and therefore might be underrepresented among the

responders. Furthermore, as in all work and health

studies the so-called ‘‘healthy worker effect’’ should be

considered; this means that people in the workforce are

usually in better health (and may also have less

burnout) than those who are not working. It is

important to note that the purpose of PUMA is not

to identify persons with very high levels of burnout, but

to study determinants and changes in the level of

burnout over time and to explore how burnout might

impact on certain outcomes.

Table I. Characteristics of the PUMA study population at baseline.

Organization

Occupational

group

Participants

(n)

Response

(%)

Contact

with clients

(%)

High demands

from

clients (%)

High

rewards from

clients (%)

Violence or

threats (%)

Social security

offices

Social workers 183 99.4 50.3 56.9 23.5

Office assistants 72 54.2 41.3 41.5 6.9

Consultants 48 65.2 45.0 55.0 4.2

Supervisors 47 34.0 42.2 27.9 21.3

Project workers 29 100.0 44.4 82.1 20.7

Total 379 83.7 78.1 46.6 52.4 17.4

Psychiatric prison Prison officers 140 98.6 34.3 30.2 40.0

Prison professional

workers

27 100.0 64.0 63.0 25.9

Office assistants 21 52.4 20.0 25.0 0.0

Supervisors 8 85.7 37.5 25.0 50.0

Total 196 75.7 93.3 36.8 34.0 34.2

Institutions for

severely disabled

Social care assistants 87 100.0 43.0 62.4 33.3

Social care workers 86 98.8 43.5 69.8 37.2

Temporary social

assistants

67 100.0 41.8 74.2 22.4

Supervisors 35 82.4 37.1 48.6 45.7

Office assistants 32 86.7 12.0 69.0 9.4

Total 307 74.0 96.3 39.6 66.1 30.9

Hospital, somatic Nurses 189 100.0 38.9 92.6 13.8

Auxiliary nurses 52 96.2 36.0 88.0 13.5

Office assistants 47 78.7 34.0 61.4 0.0

Midwives 41 97.6 73.2 92.7 2.4

Senior doctors 37 100.0 62.2 94.6 5.4

Head nurses 27 74.1 38.5 84.0 3.7

Hospital doctors 20 100.0 80.0 90.0 25.0

Total 413 84.1 95.1 45.6 88.2 10.2

Hospital,

psychiatric

Psychiatric staff 43 79.6 95.3 53.5 47.6 67.4

Homecare service,

rural area

Homecare workers 207 100.0 24.4 82.0 23.7

Office assistants 32 68.8 37.0 71.9 12.5

Supervisors 28 78.6 29.6 89.3 21.4

District nurses 25 100.0 25.0 91.7 4.0

Total 292 87.2 94.5 26.2 82.4 20.5

Homecare service,

urban area

Homecare workers 198 100.0 44.7 77.3 4.5

Temporary home

workers

29 100.0 34.5 85.7 13.8

District nurses 26 100.0 16.0 96.2 7.7

Supervisors 21 95.0 52.4 57.1 4.8

Office assistants 10 80.0 70.0 70.0 0.0

Total 284 74.0 98.9 42.5 78.1 5.6

PUMA total 1914 80.1 90.9 39.3 67.3 19.6

Burnout among employees in human service work 55

With regard to studying the effects of workplace

interventions on burnout, the ideal design would

have been a randomized controlled trial (RCT). As

has been noted by others [29], RCTs are extremely

difficult to conduct in work and health studies:

PUMA is no exception. In the discussions with

management and employees it became clear that the

organizations were not willing to commit themselves

to the implementation of interventions, let alone to

participate in a randomized trial. We therefore

designed PUMA as a quasi-experimental study, in

which interventions could be conducted at some

workplaces, whereas workplaces without interven-

tions would form the comparison group.

To summarize, PUMA has six important

strengths:

Table II. Copenhagen Burnout Inventory (CBI): Scales, items and response frequencies.

Response category

Always a

Or

To a very

high degree b

Often or

to a high

degree

Sometimes

or somewhat

Seldom or

to a low

degree

Never/almost

never or to a

very low

degree Missing Score

Scoring: 100 75 50 25 0

% % % % % n

Mean

(SD)

Personal burnout (a 0.87)

How often do you feel tired? a

2.6 27.6 49.4 17.9 2.5 24 52.5 (20.2)

How often are you physically

exhausted? a

0.5 15.0 40.6 37.3 6.5 19 41.5 (20.7)

How often are you emotionally

exhausted? a

0.5 11.7 37.3 38.9 11.6 17 37.7 (21.6)

How often do you think: ‘‘I can’t take

it any more’’? a

0.3 5.4 18.6 39.3 36.4 19 23.5 (22.2)

How often do you feel worn out? a

0.5 12.4 35.7 38.4 13.0 19 37.3 (22.2)

How often do you feel weak and

susceptible to illness? a

0.5 3.6 16.8 44.7 34.4 19 22.8 (20.8)

Total score 35.9 (16.5)

Work-related burnout (a 0.87)

Do you feel worn out at the end of the

working day? a

4.7 23.1 40.5 22.1 9.6 14 47.8 (25.2)

Are you exhausted in the morning at

the thought of another day at work? a

0.8 5.6 24.1 34.2 35.3 12 25.6 (23.6)

Do you feel that every working hour is

tiring for you? a

0.3 2.1 12.1 36.9 48.7 17 17.1 (19.6)

Do you have enough energy for family

and friends during leisure time? a

(inverse coding)

26.5 40.6 27.5 4.9 0.4 15 28.0 (21.8)

Is your work emotionally exhausting? b

4.9 13.3 43.1 29.5 9.1 15 43.9 (24.1)

Does your work frustrate you? b

3.8 10.5 36.9 33.9 14.9 24 38.6 (24.8)

Do you feel burnt out because of your

work? b

3.5 7.3 27.5 36.4 25.2 19 31.9 (25.8)

Total score 33.0 (17.7)

Client-related burnout (a 0.85)

Do you find it hard to work with

clients? b

1.7 8.5 35.8 35.6 18.5 22 34.9 (23.5)

Does it drain your energy to work with

clients? b

3.3 8.4 35.5 37.3 15.5 19 36.7 (24.1)

Do you find it frustrating to work with

clients? b

0.7 3.0 20.7 43.5 31.9 18 24.3 (21.1)

Do you feel that you give more than

you get back when you work with

clients? b

4.7 13.9 32.8 32.7 15.9 39.8 (26.5)

Are you tired of working with clients? a

0.3 2.2 22.3 40.7 34.4 16 23.4 (20.7)

Do you sometimes wonder how long

you will be able to continue working

with clients? a

0.6 5.8 26.0 35.4 32.1 18 26.9 (23.3)

Total score 30.9 (17.6)

56 M. Borritz et al.

Figure 2. Work burnout and client burnout across occupational groups.

Table III. Psychosocial work environment scales: Internal consistency and correlations with work burnout.

Scale Number of items Cronbach’s alpha

Spearman’s rank correlation with

work burnout

Client-related demands:

Emotional demands 3 0.83 0.42

Demands for hiding emotions 2 0.46 0.35

Other demands:

Quantitative demands 4 0.79 0.48

Cognitive demands 4 0.74 0.14

Active and developmental work:

Influence at work 4 0.73 20.24

Possibilities for development 4 0.75 20.18

Meaning of work 3 0.78 20.25

Commitment to the workplace 4 0.69 20.27

Interpersonal relations at work:

Quality of leadership 4 0.90 20.35

Feedback at work 2 0.61 20.17

Predictability 2 0.81 20.33

Role clarity 4 0.84 20.29

Role conflicts 4 0.72 0.44

Social support 2 0.58 20.20

Social relations 2 0.54 20.15

Sense of community 2 0.78 20.28

Job insecurity:

Job insecurity 4 0.57 0.11

Job satisfaction:

Job satisfaction 4 0.71 20.51

All correlations are significant at pv0.001.

Burnout among employees in human service work 57

1. PUMA is a prospective study over five years

following a number of different professions in

different human service sectors.

2. PUMA includes interventions at the worksites

based on the decisions and participation of the

individual workplaces.

3. PUMA includes a number of client-focused

variables such as emotional demands, demands

from clients, rewards from clients etc.

4. PUMA also includes a number of other relevant

psychosocial work environment factors.

5. PUMA makes it possible to study a number of

potential consequences of burnout such as

absence, turnover, use of medicine, exclusion

from the labour market, morbidity, and mortality.

6. Finally, PUMA includes measures of person-

ality, lifestyle factors, family–work conflict, and

sociodemographic factors.

Acknowledgements

The PUMA study has been funded by grants from the

Work Environment Fund (Arbejdsmiljøfondet), the

Danish Work Environment Service (Arbejdstilsynet),

the Work Environment Council (Arbejdsmiljørådets

Servicecenter via Arbejdsministeriets sundhedsfrem-

mepulje), and the Health Insurance Foundation

(Sygekassernes Helsefond).

References

[1] Ekman R, Arnetz B. Stress: Molekylerna, individen,

organisationen, samhället [Stress: molecules, individuals,

organisations, and society]. Stockholm: Liber, 2002.

[2] Freudenberger HJ. Staff burn–out. J Soc Issues 1974;

30:159–207.

[3] Kahill S. Symptoms of professional burnout: A review of the

empirical evidence. Can Psychol 1988;29:284–97.

[4] Kristensen TS, Borritz M. Forebyggelse af udbrændthed.

En forundersøgelsesrapport [Prevention of burnout. A

pilot study. Danish Work Environment Fund, 1998].

Forskningsrapport, 1998:5–69.

[5] Maslach C. Burned-out. Hum Behav 1976;5:16–22.

[6] Maslach C, Schaufeli W, Leiter MP. Job burnout. Annu Rev

Psychol 2001;52:397–422.

[7] Pines AM, Aronson E, Kafry D. Burnout – from tedium to

personal growth. New York: Free Press, 1981.

[8] Schaufeli W, Enzmann D. The burnout companion to study

and practice: A critical analysis. London: Taylor & Francis,

1998.

[9] Schaufeli WB, Maslach C, Marek T. Professional burnout.

Recent development in theory and research. Washington:

Taylor & Francis, 1993.

[10] Schaufeli WB, Buunk BP. Professional burnout. In:

Schabracq MJ, Winnubst JAM, Cooper CL, editors.

Handbook of work and health psychology. New York:

Wiley, 1996: 311–46.

[11] Söderfeldt M. Burnout? Lund: Lunds Universitet, 1997.

[12] Hasenfeld Y. Human service organizations. Englewood

Cliffs, NJ: Prentice Hall, 1983.

[13] Zapf D, Vogt C, Seifert C, Mertini H, Isic A. Emotion work

as a source of stress: The concept and development of an

instrument. Eur J Work and Organizational Psychol

1999;8:371–400.

[14] Hallsten L, Bellaagh K, Gustavsson K. Utbränning i Sverige

– en populationsstudie [Burning-out in Sweden – a popula-

tion study]. Stockholm: Arbetslivinstitutet, 2002.

[15] Kalimo R. The challenge of changing work and stress for

human resources. The case of Finland. J Tokyo Med Univ

2000;58:349–56.

[16] Van Dierendonck D, Schaufeli WB. Burnout and inequity

among human service professionals: A longitudinal study.

J Occup Health Psychol 2001;6:43–52.

[17] Marmot M, Siegrist J, Theorell T, Feeney A. Health and

the psychosocial environment at work. In: Marmot M,

Wilkinson RG, editors. Social determinants of health.

North Yorkshire: Oxford University Press, 1999: 105–

31.

[18] Borritz M, Kristensen T. Copenhagen Burnout Inventory.

Scales used in the PUMA study. Available at: http://

www.ami.dk/upload/CBI-scales.pdf, accessed 2004.

[19] Kristensen TS, Borritz M, Villadsen E, Bjorner JB.

Validation of the Copenhagen Burnout Inventory [abstract]

2002.

[20] Borritz M, Kristensen TS. Copenhagen Psychosocial

Questionnaire (COPSOQ). Scales used in the PUMA study.

Available at: http://www/ami.dk/upload/COPSOQ-scales.

pdf, accessed 2004.

[21] Kristensen TS. A new tool for assessing psychosocial work

environment factors: The Copenhagen Psychosocial

Questionnaire. In: Hagberg M, Knave B, Lillienberg L,

Westberg H, editors. Exposure assessment in epidemiology

and practice. Bromma: Sweden: National Institute of

Working Life, 2001: 210–13.

[22] Kristensen TS, Borg V, Hannerz H. Socioeconomic status

and psychosocial work environment: Results from a Danish

national study. Scand J Public Health, 2002:41–8.

[23] Theorell T, Karasek R. Current issues relating to psycho-

logical job strain and cardiovascular disease research.

J Occup Health Psychol 1996;1:9–26.

[24] Nielsen ML, Kristensen TS, Smith-Hansen L. The

Intervention Project on Absence and Well-being (IPAW):

design and results from the baseline of a 5-year study. Work

Stress 2002;16:191–206.

[25] Antonovsky A. Unraveling the mystery of health: How

people manage stress and stay well. San Francisco: Jossey-

Bass, 2002.

[26] Bjorner JB, Damsgaard MT, Watt T, Groenvold M. Tests of

data quality, scaling assumptions, and reliability of the

Danish SF-36. J Clin Epidemiol 1998;51:1001–11.

[27] Bjorner JB, Thunedborg K, Kristensen TS, Modvig J,

Bech P. The Danish SF-36 health survey: Translation and

preliminary validity studies. J Clin Epidemiol 1998;51:

991–9.

[28] Ware JE, Sherbourne CD. The MOS 36-Item Short-Form

health survey (SF-36). I. Conceptual framework and item

selection. Med Care 1992;30:473–83.

[29] Griffiths A. Organizational interventions: Facing the limits

of the natural science paradigm. Scand J Work Environ

Health 1999;25:589–96.

58 M. Borritz et al.