Economic and health consequences of
the initial stage of Mobbing: the
Spanish case
M. Angeles Carnero∗and Blanca Martı́nez†
June 7, 2005
Very Preliminary
Abstract
The objective of this paper is to analyze empirically the problem of mobbing in
Spain. Based on the fifth Spanish survey on working conditions, we measure the
cost of this problem in terms of health and medical expenses. We find that during
2003 mobbing affected around 5% of workers who were at their workplace and
had negative and significative effects on their health.
JEL Classification:C20, I10, J28
Keywords:Bullying at workplace, Moral harassment.
∗
Dpt.
Fundamentos del Análisis Económico, Universidad de Alicante.
E-mail:
[email protected]
†
Corresponding Author. Dpt. Fundamentos del Análisis Económico, Universidad de Alicante. Campus de S. Vicente del Raspeig, 03690, Alicante, Spain. Tel: 34 965903400 (ext.
3255), Fax: 34 965903898. E-mail: [email protected]
1
1
Introduction
The term Mobbing was popularized during the 80’s by Heinz Leymann, who
called mobbing to a kind of long-term hostile behavior detected in employees at
workplaces. Using Leymann’s definition1 , “psychological terror or mobbing in
working life involves hostile and unethical communication which is directed in
a systematic manner by one or more individuals, mainly toward one individual,
who, due to mobbing, is pushed into a helpless and defenseless position and held
there by means of continuing mobbing activities. These actions occur on a very
frequent basis (at least once a week) and over a long period of time (at least six
months’ duration). Because of the high frequency and long duration of hostile
behavior, this maltreatment results in considerable mental, psychosomatic and
social misery”.
The objective of mobbing is to push the victim to quit the job. One of the
reasons for it could be envy. Mobbed workers are, typically, good professionals
who are potential competitors for the mobber or person/people mobbing them.
Another reason for mobbing could be a strategy of the firm when wanting to
dismiss a worker without having any objective reason. So, mobbing is a way of
getting rid of the worker without having to pay any compensation.
Different words for this hostile behavior are used in different countries. Mobbing
is the word used in most European countries. In English-speaking countries, like
USA, UK or Australia, the term describing such hostile activities at work is
Bullying. However, in most parts of Europe, bullying is the word to define hostile
behavior of children at school. Moral harassment, victimization or psychological
terror are other terms used in the literature.
The identification of mobbing is not a trivial task since hostile activities at
work are sometimes of quite normal interactive behaviors. However, it is when
such activities are used frequently and over a long period of time in order to
harass, when they turn into dangerous communicative weapons. It is their systematic use what starts the mobbing process.
Leymann considered 45 activities representative of mobbing which are contained in the LIPT -Leymann Inventory of Psychological Terrorization- questionnaire; see Appendix A. Following this questionnaire, a person answering yes, daily
or yes, at least once a week, to one or more of these 45 activities is considered
mobbed or a mobbing victim.
During the last years, several works have dealt with the problem of mobbing
in Europe. However, most of them look at it from the legal and psychological
1
See, for example, The Mobbing Encyclopedia at http://www.leymann.se.
2
perspective; see, for example, Leymann (1996) and Hirigoyen (2001), and just
few of them analyze it from the economic point of view; see, for example, Hoel
et al. (2001). There are recent studies for almost any European country and
the percentages of mobbing victims range quite a lot. For example, Hubert et.
al (2001) find that 1% of workers in the financial sector in Holland suffer from
mobbing. Cowie et.al (2000) find that 38% of international Institutions workers
are mobbed in England. However, since the methodology used and the sample
of workers are different in the previous works, such percentages are not really
comparable.
The Informe Cisneros is the first and more complete research about mobbing
developed in Spain. The Barómetro Cisneros elaborated by Piñuel y Zabala, was
carried out in 2001 and 2002. For the 2001 survey, around 1000 workers from
Madrid and Guadalajara were interviewed. In order to avoid subjectivity, the
questionnaire includes a first part in which the workers do not know that the behaviors cited in the questionnaire describe mobbing activities. Then, the workers
are asked about the scale, intensity, causes and reactions of the mobbing experience. For the 2002 survey, a total of 2410 workers from the area of the corredor
del Henares were interviewed. The 2002 survey includes questions related to
the physical and psychological problems derived from mobbing. Following the
Barómetro Cisneros around 16% of workers reported being subjected to moral
harassment or mobbing, and over half of the mobbing victims answered that
mobbing affects their physical and mental health2 .
As far as we know, Pastrana (2002) is the first and single work that estimates
the cost of mobbing in Spain. He focusses on the costs related to one of the
possible mobbing outcome: disability. By analyzing a sample of 6500 temporary
disability cases, he found that mobbing victims account for 1.71% of the temporary disability cases. Hence, during the year 2002, 52 millions of Euros were lost
in work compensation as a consequence of mobbing behaviors in Spain.
Other related works are López (2003) and Velázquez (2005). The latter analyzes the problem pointing at directions on how to prevent it.
The aim of this work is to study the economic consequences of mobbing behaviors at the workplace in terms of health. Clearly, there are lots of factors affecting
the cost of mobbing and most of them are unobservable or difficult to quantify
such as effects on health, absenteeism, decision to quit the job, premature retirement, productivity loss, satisfaction, etc. In this paper, we are going to focus
on the costs associated to the mobbing victims with physical and psychological
2
The Barómetro Cisneros does not incorporate questions related to medical visits or
medicines to estimate medical expenses.
3
health outcomes but who are still at their workplace.
The paper is organized as follows. Section 2 describes the data analyzed.
Section 3 reveals some empirical facts of mobbing in Spain. The economic consequences of the problem are discussed in Section 4. Finally, section 5 contains
the conclusions and further lines of research.
2
Data description
We have used data from the fifth Spanish survey on working conditions, VENCT
(2003), which was conducted by the Instituto Nacional de Seguridad e Higiene en
el Trabajo. It covers 5236 workers and provides detailed information on working
conditions, including some questions related to psychological factors and violence
at work for the first time.
With the information available we can identify mobbing victims, following
Leyman’s definition, by focusing on the questions related to violence behavior
at work and concentrating on workers answering yes to at least one of the 45
behaviors, in the LIPT questionnaire, at least once per week. The two questions
we used for identifying mobbed workers are:
P.79. During the last 12 months, have you been subjected at work to: physical
violence from people form your workplace, from other people or unwanted sexual
attention?
P.80. During the last 12 months, have you and how often, while working, been
silenced, ignored, isolated, humiliated or ridiculed in connection with your work or
personal life, suffering from verbal and written threats, or other similar behaviors?
P.79 is a yes/no question and does not give information about the frequency
of the violent behavior. P.80 is a multiple choice question. The possible answers
are: yes, daily; yes, at least once per week; yes, several times per month; yes,
several times per year; no.
We select the mobbing victims as those workers answering yes to P.79 plus
those workers who answered yes, daily or yes, at least once per week to P.80.
In order to explore the differences between mobbed and not-mobbed workers, we
consider workers answering no to P.79 and P.80 are not-mobbed. With this
definition, those workers answering yes, several times per month and yes, several
times per year to P.80 and also those not answering to any of the P.79 and P.80
are not considered in any of the groups.
The VENCT (2003) also gives us information about the health of workers. In
section 4, we will use this information on health to estimate the cost of mobbing.
The questions we will focus on for this point are:
4
P.87. Lately, do you frequently suffer from any of the following symptoms:
Sleeping problems, Overall fatigue, Headache, Dizziness, Concentration difficulties, Memory problems, Irritability, Stomach pain, Vision problems, Discouragement, None?
P.88. During the last 12 months, how often did you visit a doctor?: One,
Two, Three, More than three, None.
P.91. Do you frequently take medicines such as: Pain relievers: Analgesics,
anti-inflammatory; Vitamins; Digestive problems relievers: Anti-acids; Anti-depressives;
Tranquilizing, relaxing agents; None?
Other relevant information provided by the survey and that we will use along
this work is the gender of the worker, age, level of education, sector, type of
contract, and other personal and professional details.
3
Facts of Mobbing in Spain
A total of 263 workers out of the 5236 respondents are identified as mobbing
victims. From this, we can conclude that around 5.02% of the workers declare
being mobbed. Under the usual assumptions, we can construct a 95% confidence
interval for this number3 which is (4.43%, 5.61%). We find wide variations statistically significant between regions as Figure 1 shows. With the exception of
Asturias, where none worker has been identified as a mobbing victim, this figure
varies from 1.16% in Navarra to 11.2% in Madrid.
Figure 2 plots the proportion of mobbing victims by sectors and by the size
of the center. As this figure suggests, mobbing is much more prevalent in the
services sector (6.33%) and in particular, in service and sales occupation (8.41%)
and also in centers with more than 500 workers.
We did not find any differences statistically significant for the proportion of
mobbing victims by other relevant characteristics such as gender, age, level of
education or type of contract.
There are two different studies we can carefully compare these results with.
The first one is the Third European survey on working conditions 2000 finding
that 5% of the workers in Spain are subjected to intimidation. There are important variations between countries, ranging from 15% in Finland to 4% in Portugal,
but such differences probably reflect awareness of the issue rather than reality,
because the questionnaire does not specify any definition or behavior for intimi³
´
If we assume that p̂ ∼ N 0, p(1−p)
then a (1 − α)100% confidence interval for p is p̂ ±
N
q
p̂)
.
z α2 p̂(1−
N
3
5
Figure 1: Proportion of mobbing victims by CCAA
PREVALENCE OF MOBBING BY REGION
12
10
%
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dation. The second work is the Barómetro Cisneros pointing out that more than
16% of the workers interviewed suffer from moral harassment or mobbing. This
huge figure is obtained from a specific questionnaire about forms of harassment
asked to workers from the the area of the corredor del Henares. Notice that the
Comunidad de Madrid is the region where we estimate the higher proportion of
mobbing victims (11.2%). However, such number is statistically smaller than the
16% estimated by the Barómetro Cisneros.
Table 1 contains information about the proportion of the identified mobbed
Table 1: Negative behaviors which have frequently been identified with mobbing
Negative behaviors
Over the past 12 months (%)
Physical violence from people from the workplace
11
Physical violence from other people
38.3
7.1
Unwanted sexual attention
Regular experience (%)
Being silenced, ignored, isolated
39.6
Being humiliated, ridiculed, questioned
26.4
Suffering from verbal and written threats, accidents
6.4
6
Figure 2: Proportion of mobbing victims by sector and center size
PREVALENCE OF MOBBING BY SIZE OF CENTER
PREVALENCE OF MOBBING BY SECTOR
9
7
8
6
7
5
6
4
%
5
4
3
3
2
2
1
1
0
0
Industry
Services
Construction
less than 10
10--49
50--249
workers who suffer from behaviors usually associated with mobbing and representative of the 45 activities contained in the LIPT questionnaire. It is surprisingly
large the proportion of mobbed workers (at least 38.3%) who suffer from physical violence at their workplace. This violent behavior together with silencing,
ignoring or isolating the victim are the activities from which most mobbed workers suffer. Figure 3 plots the proportion of mobbing victims suffering from one,
two, three and more than three hostile behaviors related to mobbing. It is remarkable that most of the mobbing victims (75.9%) suffer from just one of the
mentioned hostile behaviors, which could be interpreted as being at the first stage
of mobbing. This gives an idea about the intensity of mobbing. As it is shown
in the graph, most of the mobbed workers at their workplace are weakly mobbed
while few of them are strongly mobbed. This was expected given that, as mentioned before, the workers we consider are still at their workplace. Most of the
workers strongly mobbed are expected to quit the job, to change jobs or to be
absent from work due to disability.
An important issue in analyzing this problem is identifying the effects on
health that mobbing has on the victims. It is difficult to give the number of
mobbed workers who develop health effects. This probably depends, on one
hand, on the intensity and length of the mobbing period and on the other hand,
on the personality of the victim. Nevertheless, it seems to be a positive correlation
between being mobbed and suffering from psychopathologic, psychosomatic and
behavioral disorders.
Table 2 contains the percentage of workers suffering from symptoms usually
associated to mobbing such as insomnia, fatigue, headache, dizziness, concen-
7
250-499
500
Figure 3: Proportion of mobbing victims by number of hostile behaviors suffered
Intensity of mobbing
0,8
0,7
0,6
%
0,5
0,4
0,3
0,2
0,1
0
1
2
3
more than three
Hostile behavior
tration problems, eating disorders, melancholy, etc. It is clear from the results
shown in the table that the proportion of mobbing victims suffering from such
symptoms is much higher4 than that of not-mobbed. As we can see, the percentage of mobbing victims who suffer from any of the symptoms considered is 74%,
almost double of the percentage in the not-mobbed group. For some cases the
differences are huge, for example, 25.50% of mobbed workers suffer from stomach
pain, being just 4.52% the percentage for not-mobbed workers. As expected, the
correlation between being mobbed and suffering from the symptoms in Table 2
is positive and equal to 0.10, 0.10, 0.07, 0.08, 0.08, 0.08, 0.13, 0.14, 0.07 and 0.18
respectively.
However, there are other variables, apart from being mobbed, which could
have effects on the worker’s health. So, in order to measure the importance of
mobbing on the health of a worker, we estimate the impact that mobbing has
on the probability of suffering from any of the symptoms above when we control
for other relevant variables. We have fitted probit models to Ys , where for each
symptom s = Sleeping problems, Overall fatigue, ...,Discouragement, the dummy
variable Ys takes the value 1 if the individual suffers from symptom s and 0
4
Percentages for mobbed and not-mobbed are all statistically different at 95% confidence.
8
Table 2: Effects on health-symptomsMobbed(%) Not-mobbed (%)
Sleeping problems
29.6
12.8
Overall fatigue
22.8
10.9
Headache
26.2
12.55
Dizziness
11.8
2.84
Concentration difficulties
9.9
2.69
Memory problems
12.93
5.72
Irritability
20.20
6.70
Stomach pain
25.50
4.52
Vision problems
19.01
9.63
Discouragement
23.2
4.45
Any of the symptoms
74
38.13
otherwise. Under this specification
P r(Ys = 1|X) = Φ(Xβ)
where Φ(·) is the standard cumulative normal probability distribution and X is
a matrix containing explanatory variables such as gender, age, sector, stability
job perception, job promotion, mobbed, etc. Estimation results, obtained with
Stata 8.0, are shown in Table C.1 in Appendix C for the significant variables.
The variable mobbed, which takes the value 1 when the individual is a mobbing
victim and 0 otherwise, is significant at explaining the probability of suffering
from any of the previous symptoms. The marginal effect that being mobbed
has on the probabilities is 0.13 for Sleeping Problems, 0.11 for Overall fatigue,
0.08 for Headache, 0.05 for Dizziness, 0.03 for Concentration difficulties, 0.06 for
Memory problems, 0.13 for Irritability, 0.13 for Stomach pain, 0.05 for Vision
problems and, finally 0.14 for Discouragement. The results tell us that being
a mobbing victim increases significantly the probability of suffering from the
mentioned symptoms. When looking at the impact of mobbing on the probability
of not suffering from any of the symptoms the marginal effect is −0.26, meaning
that a mobbed worker has a probability 0.26 smaller than a not mobbed of not
suffering from any symptom.
Table 3 contains information about workers who have visited a doctor and the
number of visits during the last year. As we can see, 70% of the mobbing victims
have visited a doctor at least once. When we look at workers who have visited a
doctor just once, the percentage of not-mobbed is statistically different and higher
than the percentage of mobbed. However, the sign of the inequality changes when
9
Table 3: Effects on health-Medical visitsMobbed(%) Not-mobbed (%)
One
13.7
21.4
Two
14.9
16.5
Three
6.1
7.6
More than three
35.3
12.5
At least once
70
58.3
Table 4: Effects on health-drugsMobbed(%) Not-mobbed (%)
Pain relievers
33.84
15.20
Vitamins
12.54
4.38
15.59
4.63
Digestive problems relievers
Anti-depressives
3.05
1.16
12.55
2.54
Tranquilizing, relaxing agents
Any of the previous
51.71
23.21
we look at more than three visits. For those cases, the percentages are higher
and statistically different for mobbed workers than for not-mobbed. Therefore,
it seems to be a positive correlation between being mobbed and visiting a doctor
more than three times. As before, we have estimated a probit model5 in order to
measure the impact of mobbing on the probability of visiting a doctor more than
three times. The estimated effect on such probability is 0.12. As expected, being
mobbed increases significantly the probability of going to the doctor several times
per year.
Finally, Table 4 shows the percentages of workers taking drugs on a frequent
basis. Again, the percentages are higher and statistically different for mobbed
than for not-mobbed workers giving empirical evidence of a positive correlation
between suffering from mobbing and taking drugs. Some of the differences are
huge, for example, the number of mobbing victims taking medicines for stomach
pain is more than triple than the not-mobbed and in the case of mobbed workers
who take tranquilizing agents, the percentage is more than four times the notmobbed.
Summarizing all previous results, we could give a profile for a typical mobbing
victim: Someone working in Madrid, in the Services sector, in a center of more
than 500 workers, with some health problems and suffering from only one hostile
5
Estimation results can be found in the Appendix C
10
behavior.
4
Economic consequences
In this section we estimate the health cost of mobbing behaviors in Spain in
2003. Before presenting the main results, some considerations have to be made.
First, there are many costly outcomes derived from mobbing one should take
into account: effects on mental and physical health, premature retirement, decision to leave, reduced productivity, organization commitment and satisfaction,
replacement costs, absenteeism and so on. Given the difficulty of estimating all
components and due to data limitations we only estimate those costs related to
medical care. In that sense, the cost estimation we propose will be a lower bound
of the total expenses. Second, we are only focusing on the health costs related
to mobbing victims who are at their workplace; we do not include temporary
disability6 .
Finally, imputing the moral harassment costs to the different economic agents
is out of the interest of this paper, so we will compute the costs without taking
into account if the paymaster is the worker, the organization or the society.
With the information available, we propose to measure the medical costs of
mobbing by adding the cost of medical visits and the cost of medicines taken for
each victim that this problem causes. Since we do not have information concerned
with the type of medical visit, general physician or specialist, we will assume that
all visits are to general physician.
To estimate the direct cost of a visit to the doctor in the year 2003, we
follow Ahn et al. (2003) and divide the total amount of money spent by the
Government on Public Health-Primary Attention- by the total number of visits
in Primary Attention. We get an estimated cost of 25 approximately per visit.
This amount could seem too low in relation to the common price of a visit to a
private doctor, however, notice that we are talking about cost which can be very
different from price. While price is a function of what is paid in the marketplace,
cost is a function of the inputs required to produce the service. Therefore, it is
usual to find estimated costs of medical care very low in relation to its price.
Obviously, not all the health problems of the mobbed workers motivating
medical visits are caused by hostility practices at workplace. To analyze the effect
of mobbing on the medical visits we specify the demand for health as follows:
Vi = f (Xi , β),
i = 1, 2, ...N
6
(1)
See Pastrana (2002) for an estimation of the economic loss on temporary disability cases
due to mobbing.
11
where Vi is the number of medical visits of individual i, Xi is a vector of exogenous
explanatory variables and β is the vector of unknown parameters. We consider
three groups of explanatory variables: personal characteristics, health stock, job
status and mobbed. Given that the most commonly used count models are Poisson and negative binomial and the assumption of a Poisson distribution (the
mean being equal to the variance) is stronger than necessary we have estimated
the above specification by a negative binomial model7 where
0
E(Vi ) = eXi β
0
with Xi = [1 agei age2i riski genderi educationi accidenti permanenti mobbedi ].
The estimation results are presented in Table C.2, see Appendix C. We next
briefly comment the results.
Having had an accident at work and being mobbed are the most important determinants of the demand for primary attention visits. Both variables have a
positive effect on the frequency of medical visits.
Related to the gender of the individual, we find that women use more often medical services than men. This is a common result in this literature. Education and
having a risky job variables are significant (at 5% and 10% levels of significance)
and show a positive effect on the number of visits.
Note that being mobbed has a positive and significant effect on the frequency
of medical visits. This result implies that mobbing plays a role in explaining the
medical behavior of workers and then will help to find differences in medical costs
between mobbed and non-mobbed workers.
To calculate the monetary value of the medical visits due to mobbing, for each
mobbed worker we use the estimated model for computing the number of his/her
expected medical visits due to mobbing as follows:
E(Vi |mobbed = 1) − E(Vi |mobbed = 0)
With this specification we find that the increment of medical visits due to mobbing
is 0.6% on average. In order to estimate the indirect cost, or time lost, we assume
that workers spend on average one hour of work per medical visit. The VENCT
(2003) does not contain information about wages, but we can use the detailed
information on personal and job characteristics to approximate them. Using the
Encuesta de Estructura Salarial, 2002 we calculate the hourly wage taking into
account the following relevant variable: gender, occupation, sector and region.
The costs of medicines are computed assuming that frequently means at least
once per week. Based on this and looking at the prices of popular medicines,
7
See Alvarez (2001) and Jiménez-Martı́n et al (2003)
12
we have estimated 30 per year to each worker taking frequently Pain relievers,
and 50, 50, 300, and 200 approximately per year to each one taking Vitamins,
Digestive problems relievers, Anti-depressives and Tranquilizing agents respectively. The average medical cost estimated per mobbing victim is 100 . This
cost ranges from 0 , corresponding to those mobbed workers without health effects to 1710 corresponding to the mobbed workers suffering from more health
problems.
Figure 4: Total medical costs
160
140
120
Frequency
100
80
60
40
20
0
0
200
400
600
800
1000
1200
1400
1600
1800
Euros
Figure 4 plots the histogram of medical costs estimated for the sample of
individuals who are mobbed. As we can observe, the distribution of the costs
is asymmetric to the right, meaning that most of the mobbed workers have low
medical costs and just few of them account for the higher costs. This seems to
be very much related with the intensity of the mobbing discussed in the previous
section. It reflects that most of the workers are weakly mobbed and still with
few health problems. Again, it is important to point out that the workers we are
considering are at their workplace, so mobbing is still in the first stages. Lots of
mobbing victims, at the end, quit their jobs, other become disable. Consequently,
this asymmetric distribution for the medical costs was expected from the asymmetric distribution of the proportion of mobbing victims by the number of hostile
behaviors in Figure 3.
We find that the average annual total cost per mobbing victim is around 100
. As we mentioned before this is a lower bound and a conservative measure; but
even in this case the estimated medical costs of mobbing at workplace, extrapolating the 5.02% of mobbing victims to the total working population, is around
64 millions of Euros; that is about 0.12% of the health public expenses in primary
13
attention in 2003, a non negligible loss income.
5
Conclusions
In this paper we have addressed the problem of mobbing in Spain during 2003. We
found that around 5% of workers who are at their workplace suffer frequently from
hostile behaviors. Significant differences in the percentage of mobbed workers
are found by C.C.A.A., sectors and size of the center, being Madrid, the services
sector and centers with more than 500 workers where we find the larger mobbing
rates.
Hostile attitudes at work are important not only because of the number of
victims suffering from them, but also because of the related loss of income. At a
first approximation we have estimated, following standard econometric methodology, the economic costs of this problem in terms of health. Given the difficulty
of measuring the total costs and data limitation we have restricted ourselves, as a
first step, to the costs of medical visits (direct and indirect costs) due to mobbing
and the costs of drugs taken by the victims in relation to illness associated to
mobbing. We obtain that on average 0.6% of the medical visits of mobbed workers can be imputed to hostile behaviors, and the approximated aggregate costs
account for 0.12% of the health public expenses in primary attention during 2003.
Clearly our estimation is a lower bound of the total costs of mobbing. To give
a more realistic number we should take into account disability costs, penalties
(nowadays, mobbing is being legislated in Spain), absenteeism, intention to leave,
job-satisfaction, premature retirement, replacement costs in connection with labor
turnover, and so on.
Improving the actual models, including other potential relevant variables increasing the costs of mobbing and estimating the probability of being a mobbing
victim are in our research agenda.
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[10] Pastrana, J.I. (2002), “ Cúanto cuesta el mobbing en España? ” Lan Harremanak /7, 171-181.
[11] Piñuel y Zabala, I. and A. Oñate (2002), “La incidencia del mobbing o
acosos psicológico en el trabajo en Espña: resultaos del barómetro Cisneros
sobre violencia en el entorno laboral”, Lan Harremanak /7, 35-62.
[12] Velázquez, M., Mobbing, Violencia fı́sica y estrés en el trabajo. Aspectos
jurı́dicos y los riesgos psicosociales. Ed Gestión 2000, 2005.
15
A
Leymann Inventory of Psychological Terrorization: LIPT
(A) Activities on the possibilities of the mobbed person or mobbing victim to
communicate adequately:
1. The aggressor or mobber gives the victim no possibility to communicate.
2. The victim is silenced or continuously interrupted.
3. Colleagues prevent the victim to communicate.
4. Colleagues scream and shout at the victim.
5. The victim suffers verbal attacks regarding work assignments.
6. The victim suffers verbal attacks regarding her/his personal life.
7. The victim is terrorized by means of phone calls.
8. The victim suffers verbal threats.
9. The victim suffers written threats.
10. People at work refuse to make any contact with the victim.
11. The victim’s presence is ignored.
(B) Activities on the possibilities of the victim to maintain social contacts:
12. The aggressor does not talk to the victim.
13. The victim is forbidden to talk to the aggressor.
14. The victim is isolated in a room far away from others.
15. Colleagues are forbidden to talk to the victim.
16. The physical presence of the victim is denied.
(C) Activities on the possibilities of the victim to maintain his/her personal
reputation:
17. Slanders and lies about the victim are used at work.
18. Gossiping about the victim.
19. The victim is ridiculed.
20. The victim is said to have a mental illness.
21. The aggressor tries the victim to go through psychiatric exams.
16
22. The victim is supposed to be ill.
23. The victim’s voice, gestures, way of moving are imitated.
24. The victim suffers verbal attacks regarding her/his political and religious beliefs.
25. People at work make fun about the victim’s personal life.
26. People at work make fun about the ethnic heritage or nationality of
the victim.
27. The victim is forced to do humiliating jobs.
28. The victim is controlled and his/her job performance is tracked for
those with bad intentions.
29. Victim’s decisions are questioned.
30. The victim is reviled using obscene or degrading terms.
31. The victim is sexually harassed.
(D) Activities on the occupational situation of the victim:
32. The victim is not given any work assignments at all.
33. The victim is deprived of any activity when being at work.
34. The victim is given meaningless work assignments.
35. The victim is given work assignments far below her/his capacity.
36. The victim is continuously given new work assignments.
37. The victim is given humiliating work assignments.
38. The victim is given difficult work assignments far above her/his capacity.
(E) Activities on the physical health of the victim:
39. The victim is given dangerous work assignments.
40. The victim is physically threaten.
41. The victim is physically attacked as a threat.
42. The victim is physically attacked with serious consequences for his/her
health.
43. The victim is deliberately forced to spend big sums of money.
44. Accidents are caused in the victim’s workplace or home.
45. The victim is sexually attacked.
17
B
Variables definition
• Gender : Dummy variable taking the value 1 if female and 0 if male.
• Age: Age of the worker in years.
• Load of work : Discrete variable taking values from 0 to 4 increasing with
the load of work.
• Job monotony: Discrete variable taking values from 0 to 3 increasing with
the monotony of job.
• Job instability: Discrete variable taking values from 0 to 2 increasing with
the probability perception of being dismissed in the next 12 months.
• Sector services: Dummy variable taking the value 1 if working in the services sector and 0 otherwise.
• No promotion: Discrete variable taking values from 1 to 4 decreasing with
the promotion perspectives.
• Accident: Dummy variable taking the value 1 if have had an accident at
work and 0 otherwise.
• Mobbed : Dummy variable taking the value 1 if mobbed and 0 otherwise.
• Risk at job: Dummy variable taking the value 1 if being at risky job and 0
otherwise.
• Secondary: Dummy variable taking the value 1 if having at least secondary
school studies and 0 otherwise.
• Permanent job: Dummy variable taking the value 1 if having a permanent
job and 0 otherwise.
18
C
C.1
Tables
Probits
Probit Estimation for Sleeping problems
Variable Coefficient Std. Error p-value
Const.
−2.28
0.166
0.00
Gender
0.13
0.054
0.01
Age
0.02
0.003
0.00
Load of work
0.15
0.028
0.00
0.18
0.030
0.00
Job monotony
Mobbed
0.49
0.103
0.00
Log likelihood −1564.90
Pseudo R2
0.0399
Probit Estimation for Overall fatigue
Variable Coefficient Std. Error p-value
Const.
−2.44
0.179
0.00
Gender
0.39
0.056
0.00
Age
0.01
0.003
0.00
Load of work
0.19
0.030
0.00
Job monotony
0.21
0.032
0.00
Job unestability
0.12
0.049
0.01
Mobbed
0.48
0.106
0.00
Log likelihood −1338.29
Pseudo R2
0.0635
19
Probit Estimation for Headache
Variable Coefficient Std. Error p-value
Const.
−1.90
0.171
0.00
Gender
0.54
0.054
0.00
Load of work
0.12
0.029
0.00
Job monotony
0.10
0.033
0.01
0.34
0.11
0.01
Mobbed
Log likelihood −1448.07
0.0503
Pseudo R2
Probit Estimation for Dizziness
Variable Coefficient Std. Error p-value
Const.
−2.90
0.278
0.00
Gender
0.43
0.087
0.00
0.02
0.01
0.00
Age
Education level
−0.05
0.017
0.01
Load of work
0.088
0.047
0.06
Job monotony
0.22
0.045
0.00
Mobbed
0.57
0.137
0.00
Log likelihood
−507.37
2
Pseudo R
0.0838
Probit Estimation for Concentration difficulties
Variable Coefficient Std. Error p-value
Const.
−4.33
0.698
0.00
Gender
0.20
0.092
0.03
0.07
0.034
0.04
Age
Age2
−0.00
0.001
0.08
Load of work
0.13
0.048
0.01
Job monotony
0.25
0.047
0.00
Job unestability
0.25
0.075
0.00
0.28
0.096
0.00
Sector services
Mobbed
0.41
0.147
0.00
Log likelihood
−463.03
2
Pseudo R
0.0824
20
Probit Estimation for Memory problems
Variable Coefficient Std. Error p-value
Const.
−2.24
0.468
0.00
Gender
0.23
0.070
0.00
Load of work
0.16
0.036
0.00
Job monotony
0.19
0.037
0.00
Sector services
0.15
0.071
0.03
Mobbed
0.44
0.122
0.00
Log likelihood
−870.39
2
Pseudo R
0.0547
Probit Estimation for Irritability
Variable Coefficient Std. Error p-value
Const.
−3.36
0.465
0.00
Gender
0.12
0.065
0.06
Age
0.05
0.022
0.02
2
Age
−0.00
0.001
0.04
0.16
0.033
0.00
Load of work
Job monotony
0.16
0.035
0.00
Job unestability
0.17
0.053
0.00
Mobbed
0.64
0.109
0.00
Log likelihood
Pseudo R2
−1053.77
0.0530
Probit Estimation for Stomach pain
Variable Coefficient Std. Error p-value
Const.
−2.64
0.496
0.00
Gender
0.13
0.071
0.06
Load of work
0.09
0.037
0.02
Job monotony
0.20
0.038
0.00
Mobbed
0.75
0.113
0.00
Log likelihood
−836.80
2
Pseudo R
0.0572
21
Probit Estimation for Vision problems
Variable Coefficient Std. Error p-value
Const.
−1.78
0.403
0.00
Gender
0.19
0.061
0.00
2
Age
0.00
0.001
0.02
Load of work
0.16
0.031
0.00
Job monotony
0.23
0.033
0.00
Job unestability
0.10
0.052
0.05
Sector services
0.29
0.061
0.00
0.26
0.115
0.02
Mobbed
Log likelihood −1214.31
0.0573
Pseudo R2
Probit Estimation for Discouragement
Variable Coefficient Std. Error p-value
Const.
−4.29
0.550
0.00
0.12
.073
0.10
Gender
Age
0.07
0.026
0.00
2
Age
−0.00
0.001
0.02
Load of work
0.13
0.038
0.00
Job monotony
0.23
0.038
0.00
Job unestability
0.16
0.060
0.01
No Promotion
0.10
0.033
0.00
Sector services
0.18
0.074
0.02
Mobbed
0.83
0.110
0.00
Log likelihood
−784.87
2
Pseudo R
0.0986
Probit Estimation for Nosymptoms
Variable Coefficient Std. Error p-value
Const.
1.62
0.303
0.00
Gender
−0.37
0.046
0.00
Load of work
−0.20
0.023
0.00
Job monotony
−0.28
0.027
0.00
−0.07
0.039
0.06
Job unestability
Sector services
−0.09
0.044
0.03
Mobbed
−0.66
0.103
0.00
Log likelihood −2543.01
Pseudo R2
0.0674
22
Probit Estimation for Go to the doctor more than 3 times
Variable Coefficient Std. Error
p-value
Const.
−1.55
0.328
0.00
Gender
0.355
0.050
0.00
Load of work
0.10
0.027
0.00
Job monotony
0.08
0.029
0.01
0.31
0.064
0.00
Accident
Mobbed
0.47
0.101
0.00
Log likelihood −1704.90
Pseudo R2
0.0365
C.2
Negative Binomial
NB estimation for medical visits
Variable Coefficient Std. Error
p-value
Age
−0.216
0.0177
0.066
Age2
0.00
0.000
0.024
Gender
0.325
0.0366
0.00
Secondary
0.1
0.0367
0.00
Accident
0.397
0.0446
0.00
Risk at job
0.084
0.043
0.051
Permanent job
0.135
0.0479
0.00
Mobbed
0.327
0.0753
0.00
0.115
0.23
0.614
Constant
Likelihood-ratio test of α = 0,
chi2(1)=440.51
23
Prob > chi2=0.000