Occupational stress and psychopathology in health professionals:An explorative study with the Multiple Indicators Multiple Causes(MIMIC) model approach

PAOLO ILICETO1, MAURIZIO POMPILI1,2, SALLY SPENCER-THOMAS3,

STEFANO FERRACUTI1, DENISE ERBUTO1, DAVID LESTER4,

GABRIELLA CANDILERA5, & PAOLO GIRARDI1

1Department of Neurosciences, Mental Health and Sensory Organs, Suicide Prevention Center, Department of Psychiatry,

Sant’Andrea Hospital, Sapienza University of Rome, Rome, Italy, 2McLean Hospital, Harvard Medical School, Belmont,

MA, USA, 3Carson J Spencer Foundation, Denver, CO, USA, 4The Richard Stockton College of New Jersey, Galloway, NJ,

USA, and 5Clinical Psychologist, Private Practice, Rome, Italy

(Received 29 December 2011; revised 21 April 2012; accepted 26 April 2012)

AbstractOccupational stress is a multivariate process involving sources of pressure, psycho-physiological distress, locus of control,work dissatisfaction, depression, anxiety, mental health disorders, hopelessness, and suicide ideation. Healthcare professionalsare known for higher rates of occupational-related distress (burnout and compassion fatigue) and higher rates of suicide. Thepurpose of this study was to explain the relationships between occupational stress and some psychopathological dimensions ina sample of health professionals. We investigated 156 nurses and physicians, 62 males and 94 females, who were administeredself-report questionnaires to assess occupational stress [occupational stress inventory (OSI)], temperament (temperamentevaluation of Memphis, Pisa, Paris, and San Diego autoquestionnaire), and hopelessness (Beck hopelessness scale). The bestMultiple Indicators Multiple Causes model with five OSI predictors yielded the following results: x 2(9) ¼ 14.47 ( p ¼ 0.11);x 2/df ¼ 1.60; comparative fit index ¼ 0.99; root mean square error of approximation ¼ 0.05. This model provided a good fitto the empirical data, showing a strong direct influence of casual variables such as work dissatisfaction, absence of type Abehavior, and especially external locus of control, psychological and physiological distress on latent variable psychopathology.Occupational stress is in a complex relationship with temperament and hopelessness and also common among healthcareprofessionals.

Keywords: Health professionals, hopelessness, MIMIC model, occupational stress, psychopathology, temperament

Introduction

Selye defined stress as the nonspecific response of the

body to any demand, after subtraction of the specific

components from the total response, emphasizing that

the stress syndrome would result from exposure to any

stressor (the causative agent) retaining stress (the

resulting condition) (Selye 1936). He stated that

different biological responses could be predicted

based on the introduction of a toxin into a specific

bodily system. On the basis of these findings, he

developed his theory of the general adaptation

syndrome with three distinct stages: (1) alarm

reaction, (2) stage of resistance, and (3) stage of

exhaustion (Selye 1974). Another important contri-

bution was the distinction between the effects of

different types of stress: he considered that there was

eustress, which was harmless or seemingly beneficial

stress, and distress, which was harmful or bad stress

(Selye 1976). Regulation around an altered state is the

essence of allostasis, a term referring to the levels of

activity required for the individual to adapt and

maintain stability through change (McEwen 1998,

2000), while allostatic load refers to effects of

Correspondence: M. Pompili, Department of Psychiatry, Sant’Andrea Hospital, Sapienza University of Rome, 1035 Via di Grottarossa,00189 Rome, Italy. Tel: þ 39 06 33775675. Fax: þ 39 06 33775342. E-mail: maurizio.pompili@uniroma1.it

Stress, 2012; Early Online: 1–10q Informa Healthcare USA, Inc.ISSN 1025-3890 print/ISSN 1607-8888 onlineDOI: 10.3109/10253890.2012.689896

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prolonged continuous or intermittent activation of

effectors involved in allostasis, and long-term allo-

static load provides a conceptual basis for studying

long-term health consequences of stress (McEwen

and Stellar 1993).

Occupational stress is the emotional, cognitive,

behavioral, and physiological reaction to aversive and

noxious aspects of work, work environments, and work

organizations and contributes to negative psychologi-

cal and physiological outcomes; moreover, in health

professionals, occupational stress involves client-

related difficulties, lack of resources, and workload

(Edwards and Burnard 2003; Mandy and Tinley

2004). Stress is a complex phenomenon with the three

key elements of sources, effects, and individual

differences, and it exists in a state of disequilibrium

in the system of variables relating people to their

environment that results in a change in their normal

levels of well-being (Hart et al. 1993). On the basis of

this definition, occupational stress cannot be expressed

as a single variable but as a multivariate process linked

to personality characteristics, coping processes, and

positive and negative work experiences (Hart and

Wearing 1995). Hence, occupational stress may be

considered as a lack of fit between subjects and the

work environment, and stress-related risk factors are

also linked with sociodemographic factors, subjective

perceptions of the work environment, and all the

processes of cognitive appraisal (Albini et al. 2011).

The relationship between stressors and disease is

affected by the nature and persistence of the stressors

as well as by an individual’s biological factors,

psychosocial resources, and learned patterns of coping

(Schneiderman et al. 2005). Work-related environmen-

tal conditions, acting as job stressors and pressures, may

be direct predictors of work dissatisfaction, negative

mental and physical health outcomes, and reduced

coping strategies, while this relationship may be

moderated by individual difference variables (Cooper

and Baglioni 1988; Baglioni et al. 1990).

Suicide risk in the healthcare professions is some-

what difficult to determine because of controversy in

the data collection process and the stigma surrounding

suicide in the helping professions. Aasland et al.

(2011) and Hem et al. (2005) reported in a

longitudinal study that Norwegian doctors had a

lower mortality rate than the general population for all

causes of death except suicide. The most compelling

research to date indicates that on average, death by

suicide is about 70% more likely among male

physicians in the USA than among other professionals

and 250–400% higher among female physicians

(American Foundation for Suicide Prevention, n.d.).

While most research has been on physicians and

medical students, there is evidence from several

countries that female nurses and nursing associate

professionals are also at a significantly increased risk of

suicide (Hawton and Vislisel 1999; Pompili et al.

2006; Agerbo et al. 2007). These increased risk rates

are sustained even after adjustments are made for

psychiatric admission, employment status, marital

status, and gross income. Many explain these findings

by noting that healthcare professionals work in a high

stress environment where they are not allowed to show

any weaknesses. They are supposed to be in the role of

helping save lives, but sometimes they are not able to

save their own because they are ashamed of having a

mental or substance abuse disorder. Combining these

factors with access to the lethal means of suicide and

in-depth knowledge of how to end life, it is evident

that those in the medical profession who are

committed to taking their lives are usually able to do

so in one lethal attempt.

The striking elevated suicide rate for female

physicians is particularly disturbing. According to

one reviewer (Alexander 2001), female physicians

tend to be more suicidal at the beginning of their

careers and in midlife, suggesting a conflict between

double duties as family providers and healthcare

providers. Furthermore, a review of the literature has

revealed that prejudices against women may also

contribute to their distress. Evidently, stigma prevents

those in the healthcare profession from seeking

medical care and often drives the suicidal person to

dangerous self-medication (Myers and Fine 2003).

Furthermore, Myers reports that the “conspiracy of

silence” following a physician’s death by suicide

compounds suffering, confuses surviving family

members and thwarts public health efforts at

prevention.

Many studies have documented that health workers,

especially emergency service workers and mental

health professionals, show higher levels of stress and

health problems than many other occupational groups

(Moore and Cooper 1996; O’Connor et al. 2000; Lee

and Wang 2002; Gellis and Kim 2004; Falkum and

Vaglum 2005; Marine et al. 2006; Oginska-Bulik

2006; Belkic and Nedic 2007; Augusto Landa et al.

2008; Ruotsalainen et al. 2008). Moreover, Bamber

and McMahon (2008) pointed out the high costs of

occupational stress and reported the need for

psychological interventions in reducing stress-related

disorders at work among healthcare workers, which

may influence the course of diseases. Furthermore,

stressful life event dimensions are related to the

development of neuroticism (Knussen and Niven

1999), major depression and generalized anxiety

(Kendler et al. 2003), mental health disorders

(McNally 2003) as well as hopelessness and suicide

ideation (O’Connor et al. 2004), and facets of

stress that act synergistically are more potent than a

single aspect, including the area of work stress

(Stanton et al. 2001).

This study aimed to provide empirical data about

occupational stress and its relationships with some

psychopathological dimensions in a sample of health

P. Iliceto et al.2

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workers. Specifically, it was hypothesized that there

are many sources of occupational stress, psychological

and physical diseases that may have a direct

relationship with psychopathology. We tested our

hypotheses with a Multiple Indicators Multiple

Causes (MIMIC) model (Joreskog and Goldberger

1975; Muthen 1989) that involves psychopathology as

a latent variable, defined by dysthymic/cyclothymi-

c/anxious temperament, irritable temperament, and

hopelessness as indicators.

Method

Participants

In the first half of 2010, all 230 health professionals

(nurses and physicians) from three hospitals in the

district of Rome (Italy; San Sebastiano Hospital,

Frascati, San Giuseppe Hospital, Marino, and A.C.

Cortoni Hospital, Rocca Priora) were handed an

envelope containing description of the aims of this

research. Of the 230 health professional contacted,

156 voluntarily participated in this study and each

subject provided written informed consent. The study

protocol received ethical approval from the local

research ethics review board in accordance with the

Helsinki Declaration. The participants were 62 males

(mean age ¼ 44.3 years, SD ¼ 11.18) and 94 females

(mean age ¼ 42.0 years, SD ¼ 8.49). Their socio-

demographic characteristics are shown in Table I. No

differences were found between the age of the females

and the age of the males (t(154) ¼ 1.46; p ¼ 0.14);

there were more female than male nurses (x 2(1) 4.41;

p ¼ 0.03); there were no differences for the years of

education (x 2(2) 5.00; p ¼ 0.08). Those who declined

the invitation to participate were not different with

regard to sociodemographic variables from partici-

pants enrolled in the study.

Instruments

The occupational stress inventory (OSI; Cooper et al.

1988) consists of 167 items with six-point Likert

response keys for all items and yields 25 subscales

divided into six areas. (1) How you feel about your job

assesses job satisfaction with 22 items and a response

key ranging from very much satisfaction to very much

dissatisfaction. There are five subscales: achievement,

value, and growth; job itself; organizational design and

structure; organizational processes; and personal

relationships. (2) How you assess your current state of

health is in two parts: part A is an 18-item (response

key: from very true to very untrue) measure of mental

ill-health, and part B is a 12-item measure of physical

ill-health (response key: from never to very frequently

experience the particular symptom). (3) The way you

behave generally is a type A behavior pattern measure

with 14 items (response key: from very strongly agree

to very strongly disagree). There are three subscales:

attitude to living, style of behavior, and ambition. (4)

How you interpret events around you is a measure of

workplace locus of control with 12 items (response

key: from very strongly agree to very strongly

disagree). It yields three subscales: organizational

forces, management processes, and individual influ-

ences. (5) Sources of pressure in your job has 61 items

(response key: very definitely is to very definitely is not

a source). Six subscales assess sources of pressure:

factors intrinsic to the job, managerial role, relation-

ships with others, career and achievement, organiz-

ational structure and climate, and home–work

interface. (6) How you cope with the stress you experience

has 28 coping items (response key: from never to very

extensively). There are six subscales that assess the

following coping strategies: social support, task

strategies, logic, home–work relationships, time

management, and involvement. The validated Italian

version of the questionnaire was used, and Cronbach’s

alpha for the subscale coefficients ranged from 0.72 to

0.86 (Sirigatti and Stefanile 2002).

The first version of Temperament Evaluation of

Memphis, Pisa, Paris and San Diego Autoquestionnaire

(TEMPS-A) contained 84 items (Akiskal and Akiskal

2005). Later, clinical and theoretical considerations

led to the addition of 26 new items describing the

anxious temperament, resulting in the 110-item-long

version of the TEMPS-A (Akiskal et al. 1998). The

scale is different from most other temperament scales,

in that it taps subaffective trait expressions as they

were conceptualized in Greek psychological medicine

and, in more modern times, German psychiatry. The

TEMPS-A has been validated in Italian populations

(Pompili et al. 2008; , in press). In that investigation, a

principal-component analysis resulted in a three-

factor solution: the first represented a combination of

dysthymic, cyclothymic, and anxious (Dys/Cyc/Anx)

temperaments; the second represented irritable

temperament; and the third represented hyper-

thymic temperament. Kuder–Richardson reliability

coefficients ranged from 0.90 for the Dys/Cyc/Anx

factor to 0.76 for the hyperthymic factor.

Table I. Sociodemographic characteristics of participants.

Characteristics

Males

(N ¼ 62)

Females

(N ¼ 94) Statistics p

Age (years) 44.3 ^ 11.18* 42.0 ^ 8.49* t(154) ¼ 1.46 0.14

Groups

Nurses (%) 34.3 65.7 x 2(1) ¼ 4.41 0.03

Physicians (%) 52.1 47.9

Education (years)

# 8 (%) 6.5 3.2 x 2(2) ¼ 5.00 0.08

# 13 (%) 35.4 53.2

. 13 (%) 58.1 43.6

* Values are mean ^ SD.

MIMIC and job stress in health workers 3

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The Beck hopelessness scale (BHS: Beck et al. 1974;

Beck and Steer 1989) is a 20-item scale for

measuring negative attitudes about the future. Beck

originally developed this scale in order to predict

who would commit suicide and who would not. This

powerful predictor of eventual suicide addressed

three major aspects of hopelessness: feelings about

the future, loss of motivation, and expectations.

Responding to the 20 true or false items on the

BHS, individuals can either endorse a pessimistic

statement or deny an optimistic statement. Research

consistently supports a positive relationship between

BHS scores and measures of depression, suicidal

intent and current suicidal ideation. Studies on the

Italian population were carried out (Pompili et al.

2007) and led to successful validation of the scale

(Pompili et al. 2009). Kuder–Richardson reliability

coefficient of the BHS total score was 0.89 (Pompili

et al. 2009).

Statistical analyses

The two-tailed t-test was used for continuous

variables, and chi-square tests were used with Yates’s

correction where appropriate to identify differences in

sociodemographic characteristics. We computed a test

for the mean of a normally distributed variable for

which the population standard deviation is known

(norm values) to compare the sample means.

Structural equation modeling (SEM) relies on

several statistical tests to determine the adequacy of

model fit to the empirical data, taking into account the

modeling of multiple latent independents each

measured by multiple indicators, and one or more

latent dependents also each with multiple indicators.

The process centers around two steps: validating the

measurement model and fitting the structural model.

This starts by specifying a model on the basis of theory

and prior empirical research, and two or more

Table II. Comparisons between normative sample and research sample (males).

OSI scales

Mean research

sample (n ¼ 62) SD

Mean normative

sample (n ¼ 319) SD z p

Job satisfaction

Achievement value and growth 22.0 3.69 22.0 5.25 20.02 n.s.

Job itself 16.8 2.12 16.7 2.87 0.58 n.s.

Organizational design and structure 16.9 3.51 17.4 4.45 0.04 n.s.

Organizational processes 15.3 2.74 15.0 3.62 1.03 n.s.

Personal relationships 11.2 2.15 11.7 2.67 20.47 n.s.

OSI1 82.2 11.85 82.8 16.58 0.26 n.s.

Health

OSI2 55.2 10.65 60.4 10.12 23.18 0.000

OSI3 28.9 8.62 29.1 9.66 1.27 n.s.

Type A behavior

Attitude to living 21.2 2.71 22.2 4.35 23.14 0.000

Style of behavior 19.5 3.61 18.5 4.66 2.05 0.02

Ambition 10.6 1.91 10.8 2.57 21.96 0.02

OSI4 51.3 5.41 51.5 8.05 21.09 n.s.

Locus of control

Organizational forces 20.4 3.66 18.9 4.14 4.04 0.000

Management processes 13.2 1.94 15.6 3.25 27.82 0.000

Individual influences 9.0 2.87 10.2 2.78 23.21 0.000

OSI5 42.5 4.93 44.7 6.29 22.57 0.005

Sources of pressure

OSI6 33.7 5.32 33.1 6.57 2.14 0.01

OSI7 44.6 7.77 44.0 7.61 1.31 n.s.

OSI8 37.6 7.14 36.4 6.86 1.88 0.03

OSI9 35.5 6.13 35.7 6.43 1.18 n.s.

OSI10 46.2 7.59 44.9 7.46 2.07 0.01

OSI11 43.7 7.14 43.5 8.18 1.06 n.s.

Coping strategies

Social support 16.4 3.03 15.8 3.61 1.59 0.05

Task strategies 27.6 3.70 27.0 4.62 2.93 0.001

Logic 13.2 2.05 13.2 2.55 1.42 n.s.

Home–work relationships 17.4 3.36 17.1 3.76 2.09 0.01

Effective use of time 16.7 2.15 16.8 2.71 20.88 n.s.

Involvement 26.3 4.10 25.8 3.82 2.44 0.007

Notes: OSI, occupational stress inventory; OSI1, total job satisfaction; OSI2, mental health; OSI3, physical health; OSI4, total type A; OSI5,

total locus of control; OSI6, factors intrinsic to the job; OSI7, managerial role; OSI8, relationships with other people; OSI9, career and

achievement; OSI10, organizational structure and climate; OSI11, home–work interface.

P. Iliceto et al.4

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alternative models are then compared in terms of

model fit, which measures the extent to which the

covariances predicted by the model correspond to

the observed covariances in the data, by means of the

statistical fitting of the factor model to the observed

data (variances and covariances or correlations), the

assessment of fit, and the interpretation of the results if

the model is consistent with the data (Bollen 1989).

The chi-square test indicates the amount of

difference between expected and observed covariance

matrices. A chi-square value close to zero indicates

little difference between the expected and the

observed covariance matrices. In addition, the

probability level must be greater than 0.05 when

chi-square is close to zero. The comparative fit index

(CFI) is equal to the discrepancy function adjusted for

sample size. The CFI ranges from 0 to 1 with a larger

value indicating better model fit. Acceptable model fit

is indicated by a CFI value of 0.90 or greater. Root

mean square error of approximation (RMSEA) is

related to the residual in the model. RMSEA values

range from 0 to 1 with a smaller RMSEA value

indicating better model fit. Acceptable model fit is

indicated by an RMSEA value of 0.06 or less (Hu and

Bentler 1998, 1999).

The MIMIC model (Joreskog and Goldberger

1975; Muthen 1989) involves latent variable(s) with

usual multiple indicators, but in addition, it is also

predicted by observed variables. A MIMIC model is a

specific application of SEM that contains one or more

latent variables simultaneously identified by multiple

endogenous indicators and multiple exogenous causal

variables. All analyses were carried out using SPSS

17.0. The hypothesized structural relations in the

model were assessed by using LISREL 8.80.

Results

With regard to OSI scales, we used the data from the

Italian normative sample that consisted of 534 women

Table III. Comparisons between normative sample and research sample (females).

OSI scales

Mean research

sample (n ¼ 94) SD

Mean normative

sample (n ¼ 534) SD z p

Job satisfaction

Achievement value and growth 20.8 5.36 21.4 5.13 20.28 n.s.

Job itself 16.1 3.11 16.6 2.75 20.93 n.s.

Organizational design and structure 15.8 4.33 17.1 4.24 0.05 n.s.

Organizational processes 14.4 3.53 14.9 3.6 20.27 n.s.

Personal relationships 10.6 2.33 11.5 2.56 21.08 n.s.

OSI1 77.8 16.05 81.5 15.71 20.48 n.s.

Health

OSI2 53.2 11.62 60.0 11.12 25.03 0.000

OSI3 28.9 11.12 32.4 10.46 20.82 n.s.

Type A behavior

Attitude to living 21.3 3.43 21.4 4.31 20.07 n.s.

Style of behavior 18.0 4.60 18.0 4.44 1.10 n.s.

Ambition 10.0 2.43 10.5 2.45 22.42 0.007

OSI4 49.4 6.91 49.9 7.81 20.18 n.s.

Locus of control

Organizational forces 20.0 5.02 19.4 4.16 1.84 n.s.

Management processes 13.5 2.18 14.7 3.42 26.21 0.000

Individual influences 9.7 2.76 10.3 2.67 25.41 0.000

OSI5 43.2 5.50 44.4 6.68 23.85 0.000

Sources of pressure

OSI6 33.5 7.05 33.5 6.12 1.29 n.s.

OSI7 45.0 8.86 45.4 7.26 0.37 n.s.

OSI8 37.5 7.37 37.7 6.6 1.05 n.s.

OSI9 35.1 6.84 35.2 6.78 1.63 n.s.

OSI10 46.0 9.29 45.3 7.72 1.04 n.s.

OSI11 44.2 8.92 44.1 8.6 0.81 n.s.

Coping strategies

Social support 16.0 3.00 16.9 3.31 21.74 n.s.

Task strategies 28.2 3.49 27.3 4.13 4.33 0.000

Logic 13.4 2.60 12.9 2.66 3.01 0.000

Home–work relationships 17.8 3.67 17.9 3.52 0.00 n.s.

Effective use of time 17.3 2.84 16.7 2.58 1.98 0.02

Involvement 26.3 3.49 26.6 3.66 1.03 n.s.

Notes: OSI, occupational stress inventory; OSI1, total job satisfaction; OSI2, mental health; OSI3, physical health; OSI4, total type A; OSI5,

total locus of control; OSI6, factors intrinsic to the job; OSI7, managerial role; OSI8, relationships with other people; OSI9, career and

achievement; OSI10, organizational structure and climate; OSI11, home–work interface.

MIMIC and job stress in health workers 5

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with a mean age of 36.2 years (SD ¼ 11.8) and 319

men with a mean age of 34.4 years (SD ¼ 16.3), with

education from medium to high. The subjects were

primarily employees, teachers, engineers, and man-

agers involved in different areas, such as health,

communications, banking, and trading(Sirigatti and

Stefanile 2002). Compared with the normative

sample, both men (Table II) and women (Table III)

obtained lower scores on most OSI scales, such as

mental health (OSI2, z ¼ 3.18; p ¼ 0.000 and

z ¼ 5.03; p ¼ 0.000) and locus of control (OSI5,

z ¼ 2.57; p ¼ 0.005 and z ¼ 3.85; p ¼ 0.000); no

differences were found in job satisfaction and type A

behavior (OSI4), while only males showed higher

scores in some stress sources such as factors intrinsic

to the job (OSI6, z ¼ 2.14; p ¼ 0.01), relationships

with others (OSI8, z ¼ 1.88; p ¼ 0.03), and organiz-

ational structure and climate (OSI10, z ¼ 2.07;

p ¼ 0.01).

The MIMIC model is shown in Figure 1. The latent

variable (psychopathology) has arrows going out to

three indicators with measurement error terms and

arrows pointed toward it from 11 observed predictor

variables. On the right side of the figure, our model

Psychopathology

Dysthymic/Cyclothymic/Anxious

Irritable

Hopelessness

OSI11

OSI10

OSI9

OSI8

OSI7

OSI6

OSI5

OSI4

OSI3

OSI2

OSI1

Measurement model

Structural model

Figure 1. MIMIC model. OSI, occupational stress inventory; OSI1, total job satisfaction; OSI2, mental health; OSI3, physical health; OSI4,

total type A; OSI5, total locus of control; OSI6, factors intrinsic to the job; OSI7, managerial role; OSI8, relationships with other people;

OSI9, career and achievement; OSI10, organizational structure and climate; OSI11, home–work interface.

P. Iliceto et al.6

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represents a latent variable (psychopathology) that is

defined by dysthymic/cyclothymic/anxious tempera-

ment, irritable temperament, and hopelessness. On

the left side of the figure, the structural model relates

the latent variable to the causal variables; the OSI

scales: job satisfaction, psychological and physiologi-

cal illness, type A behavior, locus of control, and six

stress sources.

Table IV contains the results of the model selection

procedures, showing several fit indices. Initially, the

first model considers all 11 OSI scales as predictors

and showed the following results: x 2(22) ¼ 32.93

( p ¼ 0.06); x 2/df ¼ 1.49; CFI ¼ 0.99; RMSEA ¼

0.06. Despite the first model yielding a reasonably

acceptable global model fit of the structural model,

many predictors have low loadings. Then, we tested

a second model only with the six stress sources

as predictors, which produced fit indices as

follows: x 2(12) ¼ 35.91 ( p ¼ 0.000); x 2/df ¼ 2.99;

CFI ¼ 0.98; RMSEA ¼ 0.11; the hypothesis that this

model has a good fit to the data is easily rejected.

Finally, we tested a third model with only the

remaining five OSI predictors, which yielded

the following results: x 2(9) ¼ 14.47 ( p ¼ 0.11);

x 2/df ¼ 1.60; CFI ¼ 0.99; RMSEA ¼ 0.05, and this

model provided a good fit to the empirical data,

substantially better than the previous factor models.

All factor loadings of the measurement model were

high, all above 0.50; moreover, in terms of squared

multiple correlation coefficients (R 2) that describe the

amount of variance the common factor accounts for

in the indicator variables, in order of increasing

magnitude, the latent variable psychopathology

explains about 26% of the variance of hopelessness,

56% of the variance of irritable temperament, and

71% of dysthymic/cyclothymic/anxious temperament.

Table V contains the regression coefficients for this

final model.

Discussion

In this study, the MIMIC model framework was used

for understanding the relationship between stress

occupational variables and the possible onset of

psychopathology carefully assessed by other observed

variables as the affective temperaments and hope-

lessness. The present study showed that specific

sources of stress from factors intrinsic to the job such

as managerial role, relationships with other people,

career and achievement, organizational structure, and

home–work interface indicated only a moderate

relationship with psychopathology. In contrast, work

dissatisfaction, absence of type A behavior, and

especially external locus of control, psychological

and physiological distress showed a strong direct

influence on the latent variable psychopathology.

Langballe et al. (2011) investigated physician

burnout in association with individual factors, work

characteristics, and work–home interaction (job

performance-based self-esteem, goal orientation,

value congruency, workload, autonomy, work–home

conflict, and work–home facilitation). They found

that many of the assumed predictors play significant

roles in physician burnout. Specifically, work–home

conflict was a particularly strong burnout predictor in

female physicians, whereas workload was the strongest

burnout predictor in male physicians.

Work-related stress increases the risk of sick leave,

early retirement, and use of antidepressants in the

working population in all sectors of employment.

Different working conditions, such as work overload

and disparity between individual and work resources,

cause work-related stress, and prolonged work stress

has a negative effect on workers’ health; indeed, in

different studies associations between work-related

stress and cardiovascular diseases and depression have

emerged (Michie and Williams 2003; Bonde 2008).

Many studies have been carried out on different

work-related stress factors and their influence on

health and work ability of physicians and nurses in

healthcare. Often health professionals have tensions

specifically related to occupational stress, and, in

addition to psychological disorders, they suffer high

levels of stress (van der Doef and Maes 1999). The

relationship between psycho-physiological stressors

and chronic disease is complex, and adverse effects of

chronic stressors are particularly common in

health professionals with negative work experiences

Table IV. Global fit of factor models.

x 2 (df) p CFI RMSEA

Model 1 (OSI1–OSI11) 32.93 (22) 0.06 0.99 0.06

Model 2 (OSI6–OSI11) 35.91 (12) 0.000 0.98 0.11

Model 3 (OSI1–OSI5) 14.47 (9) 0.11 0.99 0.05

Notes: OSI1, total job satisfaction; OSI2, mental health; OSI3,

physical health; OSI4, total type A; OSI5, total locus of control;

OSI6, factors intrinsic to the job; OSI7, managerial role; OSI8,

relationships with other people; OSI9, career and achievement;

OSI10, organizational structure and climate; OSI11, home–work

interface; CFI, comparative fit index; RMSEA, root mean square

error of approximation.

Table V. MIMIC model results. Regression coefficients between

exogenous variables and latent factor.

Psychopathology

Total job satisfaction 20.09

Mental health 0.49*Physical health 0.27*Total type A 20.12

Total locus of control 0.22*

Note: MIMIC, Multiple Indicators Multiple Causes. *p , 0.05.

MIMIC and job stress in health workers 7

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(Kinnunen-Amoroso 2011). Irritable temperament,

dysthymic/cyclothymic/anxious temperament as well

as the component of hopelessness are associated with a

psychological condition in which individuals are

characterized by generally pessimistic and self-critical

cognition. This involves a negative temporal perspec-

tive of the future, and responses to stressful events that

are likely to be more hopeless and, as a result, such

individuals are at enhanced risk of suicidal behavior

(Pompili et al. 2004; Rihmer et al. 2007). Our present

results confirm this framework provides evidence for

the relationship of specific stressors, indicated above,

with psychopathology.

Currently in Europe, work-related stress is a major

problem (de Smet et al. 2005), and by improving the

working conditions that cause it, stress and its

consequences can be controlled (van der Klink et al.

2001; Lamontagne et al. 2007). Specifically, among

health professionals, there are stress sources, such as

contact with suffering and/or dying patients and the

need to hide negative emotional responses, which are

accompanied by reduced effectiveness, decreased

motivation, and development of dysfunctional beha-

vior and attitudes at the workplace that may have a

direct consequence for development of psychopathol-

ogy (Ruotsalainen et al. 2008) and that represent part

of findings of the present study.

This study has noteworthy limitations, including

only a moderate sample size, the use of self-reported

instruments to assess job stressors without objective

observations that are generally more difficult to

obtain, and a cross-sectional study design. Obviously,

longitudinal studies are more informative about

temporal features of the stress process. Moreover,

the number of participants allowed for an adequate

test of the MIMIC model, but it could not permit

measurement of the impact of sex (male/female) and

professional role (nurses/physicians). Furthermore,

throughout this paper, we referred to suicide risk by

measuring hopelessness as a proxy of such risk. This is

a limitation because, despite its predictive value,

hopelessness is a marker that can indicate false

positives when assessing suicide risk, while several

other contributing factors can increase suicide risk

(Pompili 2010; Fowler 2012). This points to the fact

that our emphasis on suicide risk using the

measurement of hopelessness could be mitigated by

taking into account contributing factors that were not

part of the data collection for this study. Another

important factor that may limit generalization of

present findings is that a possible causal link between

working as a doctor and suicide risk would be

hazardous to support, especially given that the risk

increases with age, way into retirement, at least for

males (Hem et al. 2000).

In conclusion, our MIMIC model provided a good

fit to the empirical data, showing a strong direct

influence of casual variables such as work dissatisfac-

tion, absence of type A behavior, and especially

external locus of control, psychological and physio-

logical distress on latent variable psychopathology.

This model allows testing concurrently numerous

variables as indices of both stress and psychopathol-

ogy, and in this way, it should be possible to monitor

the effectiveness of interventions in reducing stress at

the workplace for this specific population. The

MIMIC methodology has potential in exploring

these issues, and further research is needed on how

the links between occupational stressors and psycho-

pathology may involve other variables, such as

emotional distress, mood disorders, and insecure

attachment. Studies in other working environments

would also be of interest.

Declaration of interest: The authors report no

conflicts of interest. The authors alone are responsible

for the content and writing of the paper.

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