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International Archives of Occupational and Environmental Health (2021) 94:147–189
https://doi.org/10.1007/s00420-020-01567-w
REVIEW
The associations betweenlate effects ofcancer treatment, work ability
andjob resources: asystematic review
IngridG.Boelhouwer1 · WillemijnVermeer1· TinkavanVuuren2,3
Received: 30 July 2019 / Accepted: 25 August 2020 / Published online: 15 September 2020
© The Author(s) 2020
Abstract
Objective The aim of this review is to evaluate associations between possible late effects of cancer treatment (i.e. physical
complaints, fatigue, or cognitive complaints) and work ability among workers beyond 2years after cancer diagnosis who
returned to work. The role of job resources (social support, autonomy, leadership style, coaching, and organizational culture)
is also evaluated.
Methods The search for studies was conducted in PsycINFO, Medline, Business Source Premier, ABI/Inform, CINAHL,
Cochrane Library and Web of Science. A quality assessment was used to clarify the quality across studies.
Results The searches included 2303 records. Finally, 36 studies were included. Work ability seemed to decline shortly after
cancer treatment and recover in the first 2years after diagnosis, although it might still be lower than among healthy workers.
No data were available on the course of work ability beyond the first 2years. Late physical complaints, fatigue and cognitive
complaints were negatively related with work ability across all relevant studies. Furthermore, social support and autonomy
were associated with higher work ability, but no data were available on a possible buffering effect of these job resources on the
relationship between late effects and work ability. As far as reported, most research was carried out among salaried workers.
Conclusion It is unknown if late effects of cancer treatment diminish work ability beyond 2 years after being diagnosed with
cancer. Therefore, more longitudinal research into the associations between possible late effects of cancer treatment and
work ability needs to be carried out. Moreover, research is needed on the buffering effect of job resources, both for salaried
and self-employed workers.
Keywords Cancer treatment· Job resources· Late effects· Work ability· Work ability index
Introduction
A growing number of people in the workforce have experi-
enced a cancer diagnosis at some time during their life. The
majority of working people diagnosed with cancer re-enter
the workplace. The mean rates of return to work reported in
reviews are 62% (Spelten etal. 2002), 64% (Mehnert 2011),
and 73% (De Boer etal. 2020a). Return to work pathways
vary, among others because of differences in reintegration
strategies between countries (Kiasuwa Mbengi etal. 2018),
the availability of disability pension (Tikka etal. 2017), or
the effectiveness of programs to support return to work (de
Boer etal.2015).
Compared to healthy people 1.4 times more unemploy-
ment is observed among cancer patients (De Boer etal.
2009). However, the group of workers with a cancer diag-
nosis in their life history will continue to expand as survival
rates are greatly improving, as the incidence of cancer is
expected to rise a further 75% over the next two decades
(World Health Organization 2012; Stewart and Wild 2014)
and as the retirement age is expected to be raised even fur-
ther in many countries. As studies concerning cancer and
work merely focus on the first two years after diagnosis and
Electronic supplementary material The online version of this
article (https ://doi.org/10.1007/s0042 0-020-01567 -w) contains
supplementary material, which is available to authorized users.
* Ingrid G. Boelhouwer
i.g.boelhouwer@hva.nl
1 Department ofApplied Psychology, Amsterdam University
ofApplied Sciences, Wibauthuis, Wibautstraat 3b,
1091GHAmsterdam, TheNetherlands
2 Faculty ofManagement, Open University ofThe
Netherlands, Heerlen, TheNetherlands
3 Loyalis Knowledge andConsult, Heerlen, TheNetherlands
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148 International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
often concern whether people return to work, less is known
about the population after return to work beyond these first
two years. As a consequence, it is important to focus on the
occupational well-being and the situation in the workplace
of this group of workers after they returned to work.
A range of long-term physical and psychological changes
can be experienced by cancer survivors (Ganz 2001). These
changes may present during active treatment and persist on
the long term, beyond the first two years after cancer diag-
nosis, or changes may appear months or years later as late
effects (Stein etal. 2008). As a clear distinction between
long-term and late effects is not always possible, in this
review all these long-term changes that affect daily function-
ing are indicated as late effects in line with the definition of
the Dutch Federation of Cancer Patient Organizations (Dutch
Federation of Cancer Patient Organizations NFK 2017). Late
effects of cancer treatment include, for instance, fatigue
(Prue etal. 2006; Servaes etal. 2007; Reinertsen et al.
2010), lymphedema (Cormier etal. 2010), cardiovascular
disease (Keating etal. 2006; Drafts etal. 2013), osteoporosis
(Miller etal. 2016), anxiety (Mitchell etal. 2013), fear of
recurrence (Lebel etal. 2016), or cognitive complaints (e.g.
problems with concentration, learning and memory) (Wefel
etal. 2015). Late effects of cancer treatment may continue
to influence the ability to function at work for as long as
ten or even more years after diagnosis (Koppelmans etal.
2012; Silver etal. 2013). The Dutch Federation for Cancer
Patient Organizations reported that impairments resulting
from these late effects were experienced in particular also
in the context of work (Dutch Federation of Cancer Patient
Organizations NFK 2017). This underlines the importance
of studying late effects in the context of work.
To make comparisons possible it is necessary to study the
associations of late effects of cancer treatment with a work
outcome measure also used in studies among the general
population or populations with chronic diseases. Therefore, a
useful concept is ‘work ability’, which generally refers to the
extent to which someone is able to carry out their work, taking
the demands of the job, and health and mental resources into
account (Ilmarinen etal. 2005). Work ability is reported to be
a predictor of other work outcome measures among healthy
populations, like absenteeism or early retirement (Ilmarinen
and Tuomi 2004). In general, different (chronic) health prob-
lems are reported to be associated with decreased work ability
(Leijten etal. 2014), and predictors of work ability are similar
for workers with and without chronic health conditions (Kool-
haas etal. 2013). However, other definitions are also used in
the scientific literature (Lederer etal. 2014) and measurement
methods of work ability may vary between studies (Brady etal.
2019; Cadiz etal. 2019). About a decade ago in an overview
by Munir, Yarker, and McDermott (2009) on work ability and
cancer, it was reported that very few well-validated measures
of work ability had been used in previous studies. Therefore, it
is important to report about the way work ability was assessed
in the included studies within the current systematic literature
review as well.
Furthermore, it is important to determine whether specific
supporting factors in achieving work goals, so-called job
resources within the Job Demands-Resources (JD-R) model
(Demerouti etal. 2001), demonstrate an association with
work ability in this specific population workers past can-
cer diagnosis or if job resources can even buffer a possible
negative association of late effects of cancer treatment with
a lower work ability. In the JD-R model, job demands are
regarded as the aspects of the job that require effort and it
is possible that the late effects of cancer treatment result in
work demands being experienced as heavier. Furthermore,
across studies among general populations job resources are
positively related to work ability (Brady etal. 2019). In addi-
tion, in some studies job resources were reported to buffer
the impact of job demands on burn-out (Bakker etal. 2005;
Xanthopoulou etal. 2007). Clearly, job resources in the cur-
rent work situation might be of great importance for work
functioning among workers experiencing any late effects of
cancer treatment after they returned to work.
As there is a shift in labor markets towards more flex-
ible contracts, and smaller enterprises, the subpopulation of
self-employed, freelancers and entrepreneurs, in other words
the non-salaried, grows in several European Union member
states (CBS 2019). These workers show different behavior
after a cancer diagnosis than the salaried (Torp etal. 2018),
as they more often continue working during treatment and
take fewer time off work due to cancer. This might be due
to the financial necessity to earn an income. Another dif-
ference is that the non-salaried have neither an employer,
a supervisor, a human resource manager, an occupational
physician, nor colleagues to provide job resources such as
social support.
In short, this systematic literature review will focus on the
work ability of all people working after a cancer diagnosis
and cancer treatment (salaried and non-salaried). The aim
is to present an overview of the studies that present data on
work ability, also reporting on the method used to assess
work ability. Furthermore, any available results on a pos-
sible association of late effects (physical complaints, fatigue
or cognitive complaints) and work ability beyond the first
twoyears after diagnosis will be reviewed. Finally, the role
of job resources will also be evaluated.
Methods
Search strategy
To structure this systematic literature review the checklist
of Preferred Reporting Items for Systematic Reviews and
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149International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
Meta-Analyses (PRISMA) was used (Moher etal. 2009).
Systematic searches for publications were conducted on
March 10th, 2020 in the databases PsycINFO, Medline,
Business Source Premier and CINAHL, and on March 13th,
2020 in the databases ABI/Inform, Cochrane Library and
Web of Science. Search terms were determined by the first
author and an information specialist in mutual agreement
with the other authors. In general, the search consisted of
search terms for cancer combined with search terms for paid
work. Search terms were broad to ensure no relevant studies
would be missed. No restrictions were placed on publication
date. For full search strategies, see Supplementary Appen-
dix1. Additional searches consisted of citation tracking by
the first author to discover articles not found by the system-
atic search.
Inclusion criteria: considered studies had to (1) be pub-
lished in English peer-reviewed journals, (2) be an original
quantitative research article (including pilot studies), (3)
focus on work ability in people working after a cancer diag-
nosis, and (4) include adults (18years or older).
Exclusion criteria: articles were excluded if they focused
on (1) work-related risk factors for cancer, or (2) the ability
to work if regarded as the ability to be at work rather than
in the sense of work ability during work, or (3) populations
entirely without paid work, or (4) populations entirely on
long term sick leave, or (5) predicting return to work by
work ability, or (6) the assessment of the effect of an inter-
vention regarding return to work after a cancer diagnosis.
Study selection
First, after the removal of duplicates, the search results
were screened by title and abstract in Rayyan (Ouzzani
etal. 2016) independently by the first author and two other
researchers (the second author and research trainees). Those
papers clearly not relevant to this review were eliminated. In
case of a missing abstract or missing relevant details needed
for screening, full paper copies were retrieved and screened.
Second, the then included papers were used for additional
citation tracking by the first author to identify possible addi-
tional studies. Third, the three authors discussed the eligibil-
ity of the remaining papers based on the criteria for inclusion
and exclusion.
Data extraction
After this, the first author extracted a range of data from the
included papers relevant for this review, including data on
(1) study design, (2) population (e.g. number of participants
included in analyses, age, gender, cancer type, time since
cancer diagnosis), (3) setting, (4) the assessment method
of work ability, (5) possible late effects of cancer treat-
ment, namely physical complaints, fatigue, and cognitive
complaints, and (6) possible job resources (leadership style,
coaching, organizational culture, social support, and auton-
omy). This data-extraction was reviewed by the second and
the third author.
Study characteristics
The searches included 2303 records, including two results by
additional citation tracking. After the removal of duplicates,
1565 titles and abstracts were screened. After elimination of
the studies clearly not relevant to this review and after close
reading 36 studies remained. A reason for this decrease in
numbers was that studies on cancer and work mostly con-
cern whether people return to work during the first twoyears
after diagnosis and that these studies also focus on many
other work-related aspects other than work ability. The study
selection is documented in a PRISMA flow diagram, see
Fig.1. The data-extraction of the 36 studies is presented in
Table1.
The 36 studies covered 12 (33%) longitudinal studies (De
Boer etal. 2008; Nieuwenhuijsen etal. 2009; Bains etal.
2012; Nilsson etal. 2016; Doll etal. 2016; Zanville etal.
2016; Duijts etal. 2017; Hartung etal. 2018; Wolvers etal.
2019; Gregorowitsch etal. 2019; Tamminga etal. 2019;
Couwenberg etal. 2020), six (17%) case–control studies
(Taskila etal. 2007; Gudbergsson etal. 2008a, 2011; Lee
etal. 2008; Lindbohm etal. 2012; Carlsen etal. 2013), and
18 (50%) cross-sectional studies. Almost half of all included
studies was published in 2017 or later. The setting of 14
studies was Northern Europe. Other European settings were
the Netherlands (eight studies), and the United Kingdom,
Germany, Italy, Switzerland, and Slovakia with one study
each. Other settings outside Europe were the United States
of America (five studies), Brazil (one study), and Asia (three
studies). The studies focused on a combination of types of
cancer in 16 studies, breast cancer in ten studies, prostate
cancer in three studies, and ovarian, rectal, colorectal, thy-
roid, stomach cancer, hematological cancer and lymphoma
in one study each. Gender was not mentioned in five studies
(14%) among populations with a past breast cancer diag-
nosis, very likely to be women but possibly not all, and not
in two studies among prostate cancer diagnoses, the latter
certainly concerning men. The gender distribution therefore
showed eight studies (22%) among women, five (14%) not
with full certainty only among women, three studies (8%)
among men, and 20 studies (56%) among both genders. Type
of employment was not clear in 16 studies (44%). The other
20 studies concerned 13 studies (36%) with both employed
and self-employed, 7 studies with employed only (20%),
and none of the studies only included self-employed. The
baseline of the data collection varied from the moment of
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150 International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
diagnosis, the first day of sick leave, to the end of primary
treatments.
Quality assessment
The methodological quality of the studies was assessed
using three quality assessment checklists. For cohort
and case–control studies the checklists from the ‘Critical
Appraisal Skills Programme’ (CASP) were used (Criti-
cal Appraisal Skills Programme 2018a, b). Some items
were adapted to the current study. These adjustments are
described in the notes below the Tables2, 3, and 4. For
cross-sectional studies (except case–control studies) the
Appraisal tool for Cross Sectional Studies (AXIS tool)
(Downes etal. 2016) was used. The quality assessment was
used to test the quality across studies.
The quality assessment was performed for all 36 studies
by the first author. The second and the third author indepen-
dently assessed the quality of different subsets of cohort,
case–control and cross-sectional studies. The results were
discussed afterwards, and agreement was reached on the
level of quality of each of the included studies for the pre-
sent study.
The 12 cohort studies were all of good quality and
therefore no studies were excluded. Of the 12 included
cohort studies two studies made use of a follow up period
long enough to possibly investigate late effects of cancer
treatment that is beyond two years after diagnosis (Duijts
etal. 2017; Gregorowitsch etal. 2019). Furthermore, these
two studies concerned European populations.
Also the six case–control studies were all of good qual-
ity, not resulting in any exclusions. The time since diag-
nosis was beyond twoyear after diagnosis in four studies
and two studies also included participants within the first
two years after diagnosis. Five studies of the case–control
studies concerned European populations (Taskila etal.
2007; Gudbergsson etal. 2008a, 2011; Lindbohm etal.
2012; Carlsen etal. 2013).
The 18 cross-sectional studies showed some quality
differences, but the quality of all studies was acceptable.
The selection process in two pilot studies might have
impaired representativeness (Neudeck etal. 2017; Bielik
etal. 2020). In one cross-sectional study the time since
Fig. 1 PRISMA 2009 flow
diagram
Records identified through database
searching
(n = 2.301)
ScreeningIncluded Eligibility Idenficaon
Additional records identified through
other sources
(n = 2)
Records after duplicates removed
(n = 1.565)
Records screened
(n = 1.565)
Records excluded
(n = 1.516)
Full-text articles assessed for
eligibility
(n = 49)
Full-text articles excluded after
close reading
(n = 13)
Reasons:
-No assessment of work
ability in the study (n=2)
-Concerned the ability to (be
at) work (n=2)
-Work ability as a % disability
pension (n=2)
-Concerned the desire for
early retirement (n=1)
-Focus on return to work
(n=3)
-Only employees approaching
24 months sick leave (n=1)
-Focus on unemployment
(n=1)
-Only one of the 41
participants was member of
the workforce (n=1).
Studies included in synthesis
(n = 36)
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151International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
Table 1 Summary of study results on the work ability in (self-)employed populations with a past cancer diagnosis
Authors
and year of
publication
(reference
number)
Study population Study design Work ability Late effects of cancer treatment and work ability (> 2years
after diagnosis)
Job resources and
work ability
Type of cancer,
N = (ex-) cancer
patients in analysis,
(gender), age in
years, (% at work,
type of employ-
ment), setting
Study approach and
time points measured
Assessment
method
Results in general Physical com-
plaints
Fatigue Cognitive com-
plaints
Job resources: social
support, leadership
style, coaching,
autonomy, organiza-
tional culture
Bains etal.
(2012)
Colorectal, primary
diagnosis with
curative treat-
ment, N = 49 at
T2, 44% female,
mean age 52.49
(SD 5.42), 39%
working at T2,
United Kingdom
Longitudinal,
T0 = post-surgery/
pre-treatment,
T1 = 3months,
T2 = 6months
WAI item 1 is
described (the
method refers to
three items)
Item 1: High work
ability at baseline was
associated with greater
work ability at follow-
up (β = 0.67, t = 3.99,
p = .0005, f2 = 0.53)
Bielik etal.
(2020)
Ovarian, 13.8%
metastatic,
N = 123, female,
mean age 59.7,
34.1% currently
employed, Slo-
vakia
Cross-sectional,
mean 3.13years
after diagnosis
Current work abil-
ity 1 (worst)–10
(best)
Work ability
covered by differ-
ent dimensions
surveys
Current work ability:
Full health: 9.58 With-
out cancer: 9.07*
At diagnosis: 4.20*
At time of survey: 6.22
*Significant difference
p < .001
Carlsen
etal.
(2013)
Breast,
N = 170,
recurrence
excluded,
female, mean
age 54.2 (range
42–64),
controls N = 391,
Denmark
Case–control,
5–8years after
diagnosis
WAI item 1 Item 1: mean 8.66 (con-
trols 8.99), p < .0001
Fatigue (often),
was associated
with reduced
work ability in
a fully adjusted
model (also
controlled for
health-related
factors) (OR
10.7, CI 3.31–
34.3) [stronger
as among con-
trols, OR 4.11
(CI1.97–8.57)]
Less help and support
from a supervisor
was significantly
associated with
reduced work abil-
ity (OR 2.40; CI
1.04–5.54) among
the cancer survivors
in the full model
(also controlled
for health-related
factors). The latter
was not the case for
help and support
from colleagues,
but when only con-
trolled for age this
support showed a
significant associa-
tion (OR 3.47, CI
1.73–6.97)
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152 International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
Table 1 (continued)
Authors
and year of
publication
(reference
number)
Study population Study design Work ability Late effects of cancer treatment and work ability (> 2years
after diagnosis)
Job resources and
work ability
Type of cancer,
N = (ex-) cancer
patients in analysis,
(gender), age in
years, (% at work,
type of employ-
ment), setting
Study approach and
time points measured
Assessment
method
Results in general Physical com-
plaints
Fatigue Cognitive com-
plaints
Job resources: social
support, leadership
style, coaching,
autonomy, organiza-
tional culture
Cheung
etal.
(2017)
Breast, primar-
ily diagnosed,
N = 151, mean
age 49.98 (range
22–66), 43.1%
currently work-
ing, 9.7% self-
employed, Hong
Kong
Cross-sectional,
1–16years after
diagnosis
Work ability before
diagnosis, during
treatment and cur-
rently reported at
time of survey
WAI items, 1, 2, 3,
and 6
Item 1: work ability
before diagnosis mean
8.48, SD 1.26, during
treatment mean 4.95,
SD 2.91, current mean
7.21, SD 1.81
Item 2: physical work
ability (N = 54): 7.4%
very good, 1.1% good,
64.8% moderate, 13.0%
poor
Item 2: mental work
ability (N = 55):
10.9% very good, 45.5%
good, 36.4% moderate,
5.5% poor
1.8% very poor
Item 6:
35% of the currently
working not sure if
they could continue to
work in the subsequent
2years
Work ability before the
diagnosis and work
ability during treat-
ment were associated
with current work abil-
ity (0.63, p = .005 resp.
.49, p < .0001)
Higher current work
ability if less effects
of health-related
problems
Control at work was
correlated with
current work ability
(Spearman’s rho
0.29, p = .038)
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153International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
Table 1 (continued)
Authors
and year of
publication
(reference
number)
Study population Study design Work ability Late effects of cancer treatment and work ability (> 2years
after diagnosis)
Job resources and
work ability
Type of cancer,
N = (ex-) cancer
patients in analysis,
(gender), age in
years, (% at work,
type of employ-
ment), setting
Study approach and
time points measured
Assessment
method
Results in general Physical com-
plaints
Fatigue Cognitive com-
plaints
Job resources: social
support, leadership
style, coaching,
autonomy, organiza-
tional culture
Couwen-
berg etal.
(2020)
Rectal, N = 172,
8,7% meta-
static, 71%
male, median
age 57, 100%
paid employ-
ment, controls
N=58,Dutch
Prospective cohort
study (survey
before treatment,
3, 6, 12, 18, and
24months after
treatment)
WAI Significant decrease at 3,
and 6months
Significantly lower than
controls at 24months
Dahl etal.
(2020)
Prostate, N = 730,
100% male, mean
age 65.5 (SD
5.9), 46% work-
ing at time of
survey, Norway
Cross-sectional,
3years (SD 1.4)
after treatment
WAI item 1 Current work ability 7.4
(SD 2.1)
Dahl etal.
(2016)
Prostate, N = 563,
mean age 62.6
(SD 5.38) with
66% < 65years,
93% working at
time of survey,
Norway
Cross-sectional,
merge of national
prospective study
(questionnaires at
baseline, 3, 12 and
24months) and
a cross-sectional
single-hospital
based survey,
performed up to
6years after radical
prostatectomy
WAI items 1 and 2 Item 1 (N = 563): 8.6
(SD 0.5)
Score 10: 30%, 8–9:
46%, 6–7: 15%, 0–5:
9%
Item 2 (N = 542)
physical work ability
55% very good, 28%
pretty good, 13% fairly
good, 3% quite bad, 1%
very bad
Item 2 (N = 539)
mental work ability:
56% very good, 28%
pretty good, 12% fairly
good, 3% quite bad
1% very bad
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154 International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
Table 1 (continued)
Authors
and year of
publication
(reference
number)
Study population Study design Work ability Late effects of cancer treatment and work ability (> 2years
after diagnosis)
Job resources and
work ability
Type of cancer,
N = (ex-) cancer
patients in analysis,
(gender), age in
years, (% at work,
type of employ-
ment), setting
Study approach and
time points measured
Assessment
method
Results in general Physical com-
plaints
Fatigue Cognitive com-
plaints
Job resources: social
support, leadership
style, coaching,
autonomy, organiza-
tional culture
Dahl etal.
(2019)
Breast, colorec-
tal, leukemia,
non-Hodgkin
lymphoma,
melanoma. 63%
female, median
age 49years
(range 27–65),
N = 1189, 75%
employed (3%
sick leave),
Norway
Cross-sectional,
median time since
first cancer diag-
nosis was 16years
(range 6–31)
WAI item 1 Current work ability
8.3 (SD 1.8) among
employed
Those with low
work ability
reported sig-
nificantly higher
mean levels of
general health
p < 0.001
Those with low
work ability
reported sig-
nificantly higher
mean levels of
total fatigue
p < 0.001
De Boer
etal.
(2011)
Esophageal, stom-
ach, colorectal,
hepatic, pancre-
atic or biliary,
new patients,
22% female,
mean age 56 (SD
8), N = 333, 95
(self-) employed
of whom 45
participated, the
Netherlands
Cross-sectional,
before treatment
WAI items 1 and 2 Item 1: mean current
work ability was 5.4;
for the subgroup not on
sick leave higher (7.1,
SD 2.7), than for the
subgroup on sick leave
(3.7, SD 2.2), p < .001
Item 2: Physical work
ability and mental
work ability higher for
the group not on sick
leave
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155International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
Table 1 (continued)
Authors
and year of
publication
(reference
number)
Study population Study design Work ability Late effects of cancer treatment and work ability (> 2years
after diagnosis)
Job resources and
work ability
Type of cancer,
N = (ex-) cancer
patients in analysis,
(gender), age in
years, (% at work,
type of employ-
ment), setting
Study approach and
time points measured
Assessment
method
Results in general Physical com-
plaints
Fatigue Cognitive com-
plaints
Job resources: social
support, leadership
style, coaching,
autonomy, organiza-
tional culture
De Boer
etal.
(2008)
Breast, female
genitals or
genito-urological
mostly, primary
diagnosis of
cancer, N = 195 at
T3 (24% already
returned to work
at 6months), 60%
female, mean age
42.2 (SD 9.3), the
Netherlands
Longitudinal
(prospective),
T1 = 6months
after first day
of sick leave,
T2 = 12months
after first day
of sick leave,
T3 = 18months
after first day of
sick leave
WAI items 1 and 2 Item 1:
significant rise in scores
from T1 to T2 and
from T2 to T3 (4.6, SD
3.2, 6.3, SD 2.7, and
6.7, SD 2.7 resp.)
Both men and women
improved over time
(p < .001), but women
improved more
(p = .002)
Patients with cancer of
the female genitals and
breast cancer patients
improved most over
time (p = .01)
Doll etal.
(2016)
Uterine, ovarian,
cervical, vulvar,
and other (only
new), and also
benign disease,
N = 185 at
baseline, female,
mean age 56.5
(SD 13), N = 174
at T3, United
States of America
Longitudinal
(prospective),
T1 = 1month
after surgery,
T2 = 3months
after surgery,
T3 = 6months after
surgery
A subset of ques-
tions of the WAI,
in this study item
1 is used
Item 1:
Baseline without surgi-
cal complications 8.8
(SD 2.3), with surgical
complications
7.7 (SD 3.2)
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156 International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
Table 1 (continued)
Authors
and year of
publication
(reference
number)
Study population Study design Work ability Late effects of cancer treatment and work ability (> 2years
after diagnosis)
Job resources and
work ability
Type of cancer,
N = (ex-) cancer
patients in analysis,
(gender), age in
years, (% at work,
type of employ-
ment), setting
Study approach and
time points measured
Assessment
method
Results in general Physical com-
plaints
Fatigue Cognitive com-
plaints
Job resources: social
support, leadership
style, coaching,
autonomy, organiza-
tional culture
Duijts etal.
(2017)
Various (48%
breast), part 1
of the study:
N = 252, 69.8%
female, mean age
50.7 (SD 7.4) at
T0, with employ-
ment contract,
The Netherlands
Longitudinal
(prospective),
T0 = 2years
after diagnosis,
T1 = 3years after
diagnosis,
T2 = 4years after
diagnosis
WAI item 1 Item 1:
Group N = 151 ‘continu-
ously working’ 5.6 (SD
1.8)
Multivariate time lag
model: current work
ability predictor of
work continuation one
year later (p = .007),
β = 0.38 (SE 0.14)/ OR
1.46; CI 1.11–1.92)
Fosså etal.
(2015)
Prostate, N = 612
(30% working),
mean age 69
(range 47–105,
with 30% < 65)
Norway
Cross-sectional,
median observation
time since diagno-
sis 4.0years (range,
0–23years)
Self-reported
reduction of work
ability (“no”:
score of 0–5 vs.
“yes”: score of
6–10)
Limitations of work abil-
ity: 10–22%
Significantly fewer
patients experi-
enced limitations
of their work
ability after
radical prostatec-
tomy (10%) than
after high-dose
radiotherapy
(22%)
Gregorow-
itsch etal.
(2019)
Breast, N = 939
(68% employed at
baseline, median
age 52), The
Netherlands
Prospective cohort
study (baseline, 6,
18, and 30months)
Controls N = 3,641
WAI Employed: baseline 71%
moderate-poor work
ability, 30months 24%
moderate-poor work
ability (lower than
controls)
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1 3
Table 1 (continued)
Authors
and year of
publication
(reference
number)
Study population Study design Work ability Late effects of cancer treatment and work ability (> 2years
after diagnosis)
Job resources and
work ability
Type of cancer,
N = (ex-) cancer
patients in analysis,
(gender), age in
years, (% at work,
type of employ-
ment), setting
Study approach and
time points measured
Assessment
method
Results in general Physical com-
plaints
Fatigue Cognitive com-
plaints
Job resources: social
support, leadership
style, coaching,
autonomy, organiza-
tional culture
Gudbergs-
son etal.
(2008a)
Breast, testicu-
lar, or prostate,
N = 446 (all
returned to
work), 51%
female, age 49.1
(SD 9.3), (also
self-employed)
and norm group
N = 588, Norway
Case–control
2–6years after
primary surgery or
chemotherapy
WAI items 1, 2
and 3
Item 1:
Survivors scored lower
(mean 8.2, SD 2.0)
than norm group (mean
8.6, SD 1.6), p < .001,
effect size 0.25
Item 2: Survivors scored
more moderate/rather
poor/poor physical
work ability (21%
versus 9%, p < .001,
effect size 0.34) and
more moderate/rather
poor/poor mental work
ability (19% versus 9%,
p < .001, effect size
0.30)
Survivors experi-
enced more support
from colleagues at
work (p = .005), but
similar control as
the norm group
No data on possible
associations of these
factors with work
ability reported
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1 3
Table 1 (continued)
Authors
and year of
publication
(reference
number)
Study population Study design Work ability Late effects of cancer treatment and work ability (> 2years
after diagnosis)
Job resources and
work ability
Type of cancer,
N = (ex-) cancer
patients in analysis,
(gender), age in
years, (% at work,
type of employ-
ment), setting
Study approach and
time points measured
Assessment
method
Results in general Physical com-
plaints
Fatigue Cognitive com-
plaints
Job resources: social
support, leadership
style, coaching,
autonomy, organiza-
tional culture
Gudbergs-
son etal.
(2008b)
Breast, testicular,
or prostate, first
cancer diag-
nosis between
25–57years of
age, N = 513, 51%
female, 84% had
returned to work,
and of this group
83% had no work
changes and 17%
did have work
changes, Norway
Cross-sectional,
2–6years after pri-
mary treatment
WAI items 1, 2,
and 3
Item 1:
the subgroup with work
changes scored lower
(mean 6.9, SD 2.4)
than group without
work changes (mean
8.5, SD 1.8), p < .001,
effect size 0.75
Item 2:
The subgroup without
work changes scored
less low (moderate,
rather poor, poor) on
physical work ability
(16% versus 38%) and
mental work ability
(14% versus 30%) than
the subgroup with
work changes (both
p < .001, effect sizes
0.51 and 0.61)
Mental work ability
(and not physical work
ability) reduced due to
cancer was associated
with current work abil-
ity in univariate and
multivariate analyses
(β −0.139, p = .003)
Symptom scale
score was associ-
ated with current
work ability in
univariate analy-
ses (β = 0.396,
p < .001)
Social support from
colleagues was
associated with cur-
rent work ability in
univariate analyses
(β = 0.241, p < .001)
No data on possi-
ble association of
control with work
ability reported
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159International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
Table 1 (continued)
Authors
and year of
publication
(reference
number)
Study population Study design Work ability Late effects of cancer treatment and work ability (> 2years
after diagnosis)
Job resources and
work ability
Type of cancer,
N = (ex-) cancer
patients in analysis,
(gender), age in
years, (% at work,
type of employ-
ment), setting
Study approach and
time points measured
Assessment
method
Results in general Physical com-
plaints
Fatigue Cognitive com-
plaints
Job resources: social
support, leadership
style, coaching,
autonomy, organiza-
tional culture
Gudbergs-
son etal.
(2011)
Breast, testicu-
lar, or prostate,
N = 446, 52%
female, mean age
52.9 (SD 6.5),
and control group
N = 588, Norway
Case control,
2–6years after pri-
mary treatment
WAI items 1, 2
and 3
Item 1:
males had a higher work
ability (8.4, SD 1.8)
than females (8.0, SD
2.1), p = .04, effect
size = 0.20)
No gender differences
in control group (8.6,
SD 1.6)
Item 2:
No difference in physical
work ability or mental
work ability between
male and female
survivors
Difference between male
survivors and male
controls on physical
work ability (effect
size 0.37, p < .001) and
mental work abil-
ity (effect size 0.27,
p = .004)
Difference between
female survivors and
female controls on
mental work abil-
ity (effect size 0.30,
p < .001). No gender
difference between
female survivors and
female controls on
physical work ability
Somatic symptoms
were associated
with overall cur-
rent work ability
in univariate
analyses and
multivariate
analyses
(β =−0.078,
p = .012)
Support from col-
leagues and supervi-
sors was assessed
and combined with
communication
No separate data of an
association of only
social support with
overall current work
ability
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1 3
Table 1 (continued)
Authors
and year of
publication
(reference
number)
Study population Study design Work ability Late effects of cancer treatment and work ability (> 2years
after diagnosis)
Job resources and
work ability
Type of cancer,
N = (ex-) cancer
patients in analysis,
(gender), age in
years, (% at work,
type of employ-
ment), setting
Study approach and
time points measured
Assessment
method
Results in general Physical com-
plaints
Fatigue Cognitive com-
plaints
Job resources: social
support, leadership
style, coaching,
autonomy, organiza-
tional culture
Hartung
etal.
(2018)
Hematological,
N = 91 at base-
line, 67% male,
mean age 49 (SD
8), N = 52 at T1,
N = 40 at T2, 10%
self-employed,
Germany
Longitudinal,
baseline (less
than 4weeks
before treatment),
6months, and
1year
WAI Mean WAI significantly
increased from 18.5 at
baseline to 28.3 after
12months (p = 0.001)
Ho etal.
(2018)
Breast, N = 327,
female, 6%
recurrent disease,
mean age at time
of diagnosis: 47
(range 42–52),
mean age at time
of survey: 53
(range 48–58),
53% employed,
Singapore
Cross-sectional,
3–8years after
diagnosis
WAI Item 1
N = 168 employed: work
ability 8% poor, 29%
moderate, 48% good,
and 15% excellent
Survivors with
suboptimal work
ability expressed
more breast and
arm symptoms,
as compared with
survivors with
good or excellent
work ability
General, physi-
cal, and mental
fatigue were
less common in
survivors with
optimal work
ability
Higher level of
physical fatigue
remained signifi-
cantly associated
with poorer work
ability in the full
model
Breast cancer
survivors with
suboptimal cur-
rent workability
had lower scores
for cognitive
functioning
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1 3
Table 1 (continued)
Authors
and year of
publication
(reference
number)
Study population Study design Work ability Late effects of cancer treatment and work ability (> 2years
after diagnosis)
Job resources and
work ability
Type of cancer,
N = (ex-) cancer
patients in analysis,
(gender), age in
years, (% at work,
type of employ-
ment), setting
Study approach and
time points measured
Assessment
method
Results in general Physical com-
plaints
Fatigue Cognitive com-
plaints
Job resources: social
support, leadership
style, coaching,
autonomy, organiza-
tional culture
Kiserud
etal.
(2016)
Lymphoma.
N = 312, also
second cancers,
85% working
or on sick leave
at baseline and
58% at moment
of survey, 40%
female, mean age
41.5 (SD 13.5)
at diagnosis and
54.0 (SD 11.3) at
time of survey,
Norway
Cross-sectional
follow-up study,
mean time from
diagnosis to survey
was 12.4 years
(SD 6.1) and from
HDT-ASCT to
survey 9.7years
(SD 5.1)
WAI items 1 and 2 Item 1:
The subgroup employed
at follow up: 9.2 (SD
1.8) at diagnosis
and 7.3 (SD 2.5) at
moment of survey
Lee etal.
(2008)
Stomach, N = 408,
73.5% male, also
self-employed
and not-working
included, also
994 general
population, Korea
Case control,
21–36months after
diagnosis
Multiple-choice
item regarding
lessened work-
related ability
than before can-
cer diagnosis
More cancer survivors
had lessened work-
related ability (37%)
than the general popu-
lation (10.6%), OR
6.11, CI 3.64–10.27
Easily fatigued and
exhausted in the
workplace: 50%
of the cancer
survivors versus
22.4% in the
general popula-
tion (OR 4.02,
CI 2.55–6.33)
No data on the
association with
work ability
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162 International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
Table 1 (continued)
Authors
and year of
publication
(reference
number)
Study population Study design Work ability Late effects of cancer treatment and work ability (> 2years
after diagnosis)
Job resources and
work ability
Type of cancer,
N = (ex-) cancer
patients in analysis,
(gender), age in
years, (% at work,
type of employ-
ment), setting
Study approach and
time points measured
Assessment
method
Results in general Physical com-
plaints
Fatigue Cognitive com-
plaints
Job resources: social
support, leadership
style, coaching,
autonomy, organiza-
tional culture
Lindbohm
etal.
(2012)
Breast, testicular,
prostate, or lym-
phoma, N = 1449,
66% female, age
25–57 at time
of diagnosis,
reference group
N = 2709, Den-
mark, Finland,
Iceland, and
Norway (in the
Iceland sample
cancer recurrence
excluded)
Case control,
1–8years after
diagnosis
WAI item 1 Item 1: age-adjusted
mean work ability was
slightly lower among
the breast cancer
survivors (8.41) than
among the female
reference group (8.58,
p < .01). No difference
in work ability between
men with testicular
cancer diagnosis (8.76)
and the male reference
group (8.69). Prostate
cancer survivors had
a lower work ability
(8.28) than the male
reference group
(p < .01)
Low support from
supervisor or col-
leagues were associ-
ated with low work
ability among both
men and women,
in the cancer group
and the reference
group
High colleagues’
avoidance behavior
was related to lower
work ability among
female cancer
survivors (p < .001)
(and not in female
references)
Supervisors’ high
avoidance behavior
was related to lower
work ability among
male cancer survi-
vors (p < .01) (and
not in references)
No data of an asso-
ciation of social
climate with work
ability
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1 3
Table 1 (continued)
Authors
and year of
publication
(reference
number)
Study population Study design Work ability Late effects of cancer treatment and work ability (> 2years
after diagnosis)
Job resources and
work ability
Type of cancer,
N = (ex-) cancer
patients in analysis,
(gender), age in
years, (% at work,
type of employ-
ment), setting
Study approach and
time points measured
Assessment
method
Results in general Physical com-
plaints
Fatigue Cognitive com-
plaints
Job resources: social
support, leadership
style, coaching,
autonomy, organiza-
tional culture
Moskow-
itz etal.
(2014)
Breast, testicu-
lar, colorectal,
and prostate
cancer, Hodgkin
lymphoma and
non-Hodgkin
lymphoma,
among others,
N = 1525, 15.8%
recurrence or
secondary cancer,
61.6% female,
mean age 49.1
(SD 10.8), also
self-employed
included, United
States of America
Cross-sectional,
average time
since completion
of treatment was
3years (range
0–464months)
Whether unable to
work full time,
unable to work
the same as
before cancer, or
unable to work
at all
A greater level of
functional limita-
tions (physical,
cognitive and
social) were sig-
nificantly related
to limited work
ability (β = 5.88,
p < .001)
A greater level of
functional limi-
tations (physical,
cognitive and
social) were sig-
nificantly related
to limited work
ability (β = 5.88,
p < .001)
A greater level of
symptoms (cog-
nitive, distress,
fatigue, cancer
fear, family fear)
were not sig-
nificantly related
to limited work
ability
A greater level
of symptoms
(cognitive,
distress, fatigue,
cancer fear,
family fear) were
not significantly
related to limited
work ability
Musti etal.
(2018)
Breast, N = 503,
mean age 51.5
(SD 3.6), perma-
nent, fixed term
and other type of
contract, Italy
Cross-sectional,
survey 3.2 (SD 0.9)
years since treat-
ment, retrospective
about moment
return to work
(23.0% experi-
enced > 6months
sick leave)
Same or reduced
work ability
43.5% reduced work
ability at moment of
return to work
Support/solidarity
from employer
85.1% in group with
no reduced work
ability and 70.2% in
group with reduced
work ability,
p < 0.001
Support/solidarity
from colleagues
91.5% in group with
no reduced work
ability and 76.8% in
group with reduced
work ability,
p < 0.001
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1 3
Table 1 (continued)
Authors
and year of
publication
(reference
number)
Study population Study design Work ability Late effects of cancer treatment and work ability (> 2years
after diagnosis)
Job resources and
work ability
Type of cancer,
N = (ex-) cancer
patients in analysis,
(gender), age in
years, (% at work,
type of employ-
ment), setting
Study approach and
time points measured
Assessment
method
Results in general Physical com-
plaints
Fatigue Cognitive com-
plaints
Job resources: social
support, leadership
style, coaching,
autonomy, organiza-
tional culture
Neudeck
etal.
(2017)
Thyroid, N = 66,
69.7% female,
68% working,
Switzerland
Cross-sectional, max.
7years after treat-
ment. Mean time
since the diagnosis
of thyroid cancer
was 37.8months
(SD: 21.7; range:
7–79)
Ad hoc question-
naire
71.2% felt impaired with
respect to their work
ability during the first
year after the diagnosis
Nieuwen
huijsen
etal.
(2009)
Gastrointestinal,
breast, female
genitals, male
genitals, urologi-
cal haematologi-
cal, and other
types, primary
diagnosis of can-
cer, N = 195 at T1
(of whom N = 45
neuropsychologi-
cal tested at T2),
67% female,
mean age 44 (SD
9), the Nether-
lands
Longitudinal
(prospective),
T1 = 6months
after first day
of sick leave,
T2 = 12months
after first day of
sick leave, also
neuro-psycho-
logical testing,
T3 = 18months
after first day of
sick leave
WAI item 1 on T2 Item 1:
At T1 no difference
(p = .27) between the
participants in the
neuro- psychological
study (4.1, SD 3.0) and
the rest of the cohort
(4.7, SD 3.3)
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165International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
Table 1 (continued)
Authors
and year of
publication
(reference
number)
Study population Study design Work ability Late effects of cancer treatment and work ability (> 2years
after diagnosis)
Job resources and
work ability
Type of cancer,
N = (ex-) cancer
patients in analysis,
(gender), age in
years, (% at work,
type of employ-
ment), setting
Study approach and
time points measured
Assessment
method
Results in general Physical com-
plaints
Fatigue Cognitive com-
plaints
Job resources: social
support, leadership
style, coaching,
autonomy, organiza-
tional culture
Nilsson
etal.
(2016)
Breast, female,
N = 692 at T1,
mean age 50.8
(SD 8.07),
Sweden
Longitudinal
(prospective),
T1 = 4weeks after
surgery
T2–T6 during
24months
WAI item 2 Item 2: significant dif-
ference in physical
work ability between
baseline (β = 0.354,
p < .001) and 4months
(β = 0.138, p < .001) as
well as between 4 and
8months (β = 0.285,
p < .001)
Item 2: significant differ-
ences in mental/social
work ability were
found between 8 and
12months (β = 0.286,
p < .001)
Ortega etal.
(2018)
Breast, N = 114
(three treatment
groups of N = 38),
female, mean
ages 48.1–50.1,
self-employed
36.8–52.6%,
Brazil
Cross-sec-
tional, > 1year
after treatment
Work Limitations
Questionnaire
(the percentage
of time limited in
performing work
tasks in the last
2weeks)
Patients in the mas-
tectomy and breast-
conserving surgery
groups showed reduced
work effectiveness
(presenteeism) and
loss of productivity
compared with women
in the breast recon-
struction and control
groups (p = 0.0004 and
p = 0.0006, respec-
tively)
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1 3
Table 1 (continued)
Authors
and year of
publication
(reference
number)
Study population Study design Work ability Late effects of cancer treatment and work ability (> 2years
after diagnosis)
Job resources and
work ability
Type of cancer,
N = (ex-) cancer
patients in analysis,
(gender), age in
years, (% at work,
type of employ-
ment), setting
Study approach and
time points measured
Assessment
method
Results in general Physical com-
plaints
Fatigue Cognitive com-
plaints
Job resources: social
support, leadership
style, coaching,
autonomy, organiza-
tional culture
Tamminga
etal.
(2019)
Breast (61%),
gynecological
cancer (35%),
or other type of
cancer (4%)
Intervention group
N = 49, mean age
47.1 (SD 8.2),
98% female
Control group
N = 57, mean age
47.8 (SD 7.6),
100% female, 4%
self-employed,
The Netherlands
Longitudinal, base-
line and at 6, 12,
18, and 24months
of follow-up
WAI items 1 and 2 Work ability improved
from baseline to 1year
and stable from 1 to
2years
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167International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
Table 1 (continued)
Authors
and year of
publication
(reference
number)
Study population Study design Work ability Late effects of cancer treatment and work ability (> 2years
after diagnosis)
Job resources and
work ability
Type of cancer,
N = (ex-) cancer
patients in analysis,
(gender), age in
years, (% at work,
type of employ-
ment), setting
Study approach and
time points measured
Assessment
method
Results in general Physical com-
plaints
Fatigue Cognitive com-
plaints
Job resources: social
support, leadership
style, coaching,
autonomy, organiza-
tional culture
Taskila etal.
(2007)
Breast, lymphoma,
testicular or
prostate, no
distant metas-
tasis, N = 591,
73,9% female,
age 25–57 at time
of diagnosis, also
freelancers and
entrepreneurs
included, also
757 referents,
Finland
Case control,
2–6years after
diagnosis
WAI items 1 and 2 Item 1: nearly the same
as in referents and
highest mean value
for men with testicular
cancer (8.95), and
lowest for men with
prostate cancer (8.00)
Item 2: 26% reported
deteriorated physical
work ability due to
cancer 19% reported
deteriorated mental
work ability due to
cancer
Among the female
survivors (and male
referents, but not
among male survi-
vors), co-workers’
support was related
to reduced risk of
impaired physical
work ability (OR
0.83, CI 0.73–0.94)
and for impaired
mental work abil-
ity (OR 0.84, CI
0.73–0.96)
A better social
climate at work
was only related to
impaired mental
work ability (and
not to physical work
ability), for male
survivors (OR 0.80,
CI 0.70–0.91) and
for female survivors
(OR 0.84, CI
0.76–0.94)
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168 International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
Table 1 (continued)
Authors
and year of
publication
(reference
number)
Study population Study design Work ability Late effects of cancer treatment and work ability (> 2years
after diagnosis)
Job resources and
work ability
Type of cancer,
N = (ex-) cancer
patients in analysis,
(gender), age in
years, (% at work,
type of employ-
ment), setting
Study approach and
time points measured
Assessment
method
Results in general Physical com-
plaints
Fatigue Cognitive com-
plaints
Job resources: social
support, leadership
style, coaching,
autonomy, organiza-
tional culture
Torp etal.
(2012)
15 most common
cancers: like
breast, gyneco-
logical, pros-
tate, testicular,
N = 653, primary
diagnoses, 9%
with metastasis,
68% female,
mean age 51.9
(SD 7.9), 6%
self-employed,
Norway
Cross-sectional,
15–39months after
cancer diagnosis
WAI items 1 and 2 Item 1: mean total (cur-
rent) work ability was
8.6 (SD 1.8) among
men and 8.6 (SD 1.7)
among women
Self-employment was
a predictor for lower
work ability. Comor-
bidity (36%) was
strongly correlated
with work ability
Item 2: 31% reported a
reduction in physical
work ability due to
cancer, 23% reported
a reduction in mental
work ability. More
women than men had
reduced mental work
ability due to cancer
General social sup-
port (β = 0.15,
p ≤ .001) is a
significant predictor
of total work ability
in univariate (and
not in multivariate)
regression
Cancer-related col-
league support was
a significant predic-
tor of total work
ability (β = 0.15,
p ≤ .01) in multi-
variate regression
Cancer-related super-
visor support was
not a significant pre-
dictor of total work
ability in regression
analyses
Decision latitude
(β = 0.08, p ≤ .05) is
a significant predic-
tor of work ability
in univariate (and
not in multivariate)
regression
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169International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
Table 1 (continued)
Authors
and year of
publication
(reference
number)
Study population Study design Work ability Late effects of cancer treatment and work ability (> 2years
after diagnosis)
Job resources and
work ability
Type of cancer,
N = (ex-) cancer
patients in analysis,
(gender), age in
years, (% at work,
type of employ-
ment), setting
Study approach and
time points measured
Assessment
method
Results in general Physical com-
plaints
Fatigue Cognitive com-
plaints
Job resources: social
support, leadership
style, coaching,
autonomy, organiza-
tional culture
Torp etal.
(2017)
Most common
invasive types
of cancer: colon,
rectal, lung, skin
(melanoma),
breast, cervical,
uterine, ovarian,
prostate, tes-
ticular, bladder,
central nervous
system, thyroid,
non-Hodgkin
lymphoma,
and leukemia,
N = 1115, 69%
female, 8% self-
employed
Not returned to
work at time of
survey: 24% self-
employed and
18% salaried
Cross-sectional,
15–39months after
diagnosis
WAI items 1 and 2 Item1: compared with
the salaried workers,
the self-employed
people reported
significantly more
often reduced total
work ability (p = .02,
effect size 0.26).
The negative effect
of self-employment
on total work ability
seems to be medi-
ated by reduced work
hours and a negative
cancer-related financial
change
Item 2: no significant
differences between the
salaried and the self-
employed
Poor-self rated
health status cor-
related signifi-
cantly with low
total work ability
in logistic regres-
sion analyses
Having higher deci-
sion latitude at
work was a factor
preventing low total
work ability (OR
0.80, CI 0.68–0.94)
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170 International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
Table 1 (continued)
Authors
and year of
publication
(reference
number)
Study population Study design Work ability Late effects of cancer treatment and work ability (> 2years
after diagnosis)
Job resources and
work ability
Type of cancer,
N = (ex-) cancer
patients in analysis,
(gender), age in
years, (% at work,
type of employ-
ment), setting
Study approach and
time points measured
Assessment
method
Results in general Physical com-
plaints
Fatigue Cognitive com-
plaints
Job resources: social
support, leadership
style, coaching,
autonomy, organiza-
tional culture
Von Ah
etal.
(2018)
Breast, N = 68,
exclusion of sec-
ondary cancers
or metastasis,
mean age 52.12
(SD 8.16), United
States of America
Cross-sectional,
study population on
average 5 (SD 3.8)
years post-treat-
ment (minimum
1year)
WAI Mean 38.9 (SD 7.5).
Poor or moderate work
ability: 26.5%
Significant rela-
tionship between
perceived cogni-
tive impairment
and work ability
(β = − 0.658,
p < .000),
explained vari-
ance: 46,5%
Significant rela-
tionship between
perceived
cognitive ability
and work abil-
ity (β = 0.472,
p < .000),
explained vari-
ance: 29,9%
Von Ah
etal.
(2017)
Breast N = 68,
exclusion of
brain metastasis,
mean age 52.12
(SD 8.603), 1%
self-employed,
United States of
America
Cross-sectional,
study population
on average 4.97
(SD 3.36) years
post-treatment
(minimum 1year)
WAI WAI:
Mean 38.91 (SD 7.45)
Poor 7–27: 10%, moder-
ate 28–36: 16%, good
37–43: 46%, excellent
44–49: 28%
Linear regres-
sion: significant
relationship
between atten-
tional fatigue
(higher = higher
level of atten-
tion) and per-
ceived work abil-
ity (β = 0.627,
p < .001),
explained vari-
ance: 39%
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171International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
Table 1 (continued)
Authors
and year of
publication
(reference
number)
Study population Study design Work ability Late effects of cancer treatment and work ability (> 2years
after diagnosis)
Job resources and
work ability
Type of cancer,
N = (ex-) cancer
patients in analysis,
(gender), age in
years, (% at work,
type of employ-
ment), setting
Study approach and
time points measured
Assessment
method
Results in general Physical com-
plaints
Fatigue Cognitive com-
plaints
Job resources: social
support, leadership
style, coaching,
autonomy, organiza-
tional culture
Wolvers
etal.
(2019)
Breast 84%,
colorectal,
Non-Hodgkin,
lymphoma, other,
N = 89, 91%
female, mean age
47.9 (7.2), 10%
self-employed,
The Netherlands
Longitudinal
intervention study,
baseline, 6, 12,
18months
WAI item 1 Inverse, longitudinal
association between
fatigue and perceived
work ability
Zanville
etal.
(2016)
Breast, N = 44
(22 chemo-
therapy-treated
and 22 chemo-
therapy-naïve),
non-metastatic,
female, mean age
resp. 49.68 (SD
8.0) and 52.68
(SD 9.3), United
States of America
Longitudinal,
T0 = pre-treatment
(approximately one
third of chemo-
therapy-treated
received neo-adju-
vant chemotherapy
and were surgery
and treatment
naïve at baseline),
T1 = approximately
1-month post-
chemotherapy,
T2 = approximately
1year after T1
Item from Func-
tional Well-Being
subscale of
FACT/GOG-Ntx
(version 4)
–
N Number, SD Standard Deviation, OR Odds Ratio, CI Confidence Interval
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172 International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
diagnosis was not clear (Ortega etal. 2018), but the other
17 cross-sectional studies concerned populations with par-
ticipants beyond twoyears after diagnosis. For the check-
lists see Tables2, 3 and 4.
Assessment methods used tomeasure work
ability
Six (17%) of the included studies (Von Ah etal. 2017,
2018; Ho etal. 2018; Hartung etal. 2018; Gregorowitsch
etal. 2019; Couwenberg etal. 2020) used the complete
Work Ability Index (WAI), a questionnaire that consists
of seven items. These 7 items are (1) current work abil-
ity compared with the lifetime-best (on a scale of 0–10),
(2) work ability in relation to the (physical and mental)
demands of the job, (3) number of current diseases diag-
nosed by a physician, (4) estimated work impairment due
to diseases, (5) sick leave during the past 12months, (6)
own prognosis of work ability two years from now, and
(7) mental resources. Only partial use of the WAI (one or
more items) was made by 22 (61%) studies, with the first
WAI item being used in 21 studies (see Table1).
Of the eight (22%) studies not using the complete or
partial WAI, different ways to assess work ability were
used, namely (1) the Functional Well-Being subscale of
the FACT/GOG-Ntx (version 4) (Zanville etal. 2016), (2)
a multiple-choice question regarding lessened work-related
ability (Lee etal. 2008), (3) a self-reported reduction of
work ability (Fosså and Dahl 2015; Musti etal. 2018), (4)
a multiple choice question regarding being unable to work
full time, unable to work the same as before cancer or
unable to work at all (Moskowitz etal. 2014), (5) the Work
Limitations Questionnaire (the percentage of time limited
in performing work tasks in the last two weeks) (Ortega
etal. 2018), (6) a question on current work ability in com-
bination with other information (Bielik etal. 2020), and
(7) a non-validated ad hoc questionnaire (Neudeck etal.
2017). In brief, 22% of the studies did not use the complete
or partial WAI but other ways to assess work ability.
Results: work ability inworking people
withapastcancer diagnosis
After a cancer diagnosis the level of work ability tended to
be experienced as lower than before diagnosis. However,
cohort studies demonstrated that the level of work abil-
ity among workers during the first two years past cancer
diagnosis appeared to improve significantly (De Boer etal.
2008; Nilsson etal. 2016). One longitudinal study with a
2 year follow up reported work ability improved over time
most prominently from baseline to 1year of follow-up
and thereafter remained stable up to 2years of follow-up
(Tamminga etal. 2019). However, other longitudinal stud-
ies that focused on the first two years did not have data on
the course of work ability (Nieuwenhuijsen etal. 2009;
Bains etal. 2012; Doll etal. 2016; Zanville etal. 2016),
nor had the study with a follow-period of four years past
cancer diagnosis (Duijts etal. 2017). However, compared
to controls work ability was reported to be significantly
lower when twoyears after diagnosis (Couwenberg etal.
2020).
Cross-sectional studies that used data reported by the
respondents retrospectively with regard to different time
points after cancer diagnosis, also reported that work abil-
ity was lowered after cancer diagnosis and experienced as
increasing again (Kiserud etal. 2016; Cheung etal. 2017;
Musti etal. 2018; Bielik etal. 2020). Some studies only
focused on the association of different types of treatment
and work ability (Ortega etal. 2018; Dahl etal. 2020). Fur-
thermore, when the complete Work Ability Index (WAI) was
used to assess work ability the results were as follows. Sub-
optimal work ability was reported in 26% and 37% of cases
(Von Ah etal. 2017; Ho etal. 2018) and among a population
with a prostate cancer diagnosis in the previous 0–23years
(mean 4years) and partially at work, 10% or 22% reported
a reduction of their work ability (Fosså and Dahl 2015). As
the studies made use of different ways to assess work ability
at various moments after diagnosis and also included differ-
ent types of cancer, case–control studies offer a possibility
to make comparisons between workers with and workers
without a past cancer diagnosis. Six studies made use of a
reference group or a norm group, mostly beyond the first two
years after diagnosis of which five studies found that work
ability was lower in workers with a past cancer diagnosis,
than in workers without such a diagnosis (Gudbergsson etal.
2008a, 2011; Lee etal. 2008; Lindbohm etal. 2012; Carlsen
etal. 2013). Only one study, using a sample 2–6years after
different types of cancer diagnosis, did not report any dif-
ferences (Taskila etal. 2007). These results demonstrate
that work ability tends to be lower among cancer survivors
than among samples without a past cancer diagnosis also on
the long term. In summary, a number of the cross-sectional
and case–control studies showed that workers more than
twoyears past cancer diagnoses experience a lower level of
work ability than before the cancer diagnosis.
An important finding was that a lower work ability at
baseline was one of the strongest predictors of poorer fol-
low-up work ability at 6months after treatment among a
sample with colorectal cancer in one of the longitudinal
studies (Bains etal. 2012). Also in a cross-sectional study
among a sample 1–16years after breast cancer diagnosis,
the retrospectively self-reported work ability during treat-
ment, as well as that before diagnosis, was associated with
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173International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
Table 2 Quality assessment for the cohort studies by means of the checklist from the ‘Critical Appraisal Skills Programme’ (CASP)
Bains etal.
(2012)
De Boer
etal. (2008)
Couwenberg
etal. (2020)
Doll etal.
(2016)
Duijts etal.
(2017)
Gregorow-
itsch etal.
(2019)
Hartung
etal. (2018)
Nieuwen-
huijsen etal.
(2009)
Nilsson etal.
(2016)
Tamminga
etal. (2019)
Wolvers
etal. (2019)
Zanville etal.
(2016)
1. Did the
study
address
a clearly
focused
issue?
Yes Yes Yes Yes Yes Yes Ye s Yes Yes Yes Yes Ye s
2. Was the
cohort
recruited in
an accept-
able way?
Yes Yes Yes Yes Yes Yes Ye s Yes Yes Yes Yes Ye s
3. Was the
exposure
accurately
measured
to mini-
mize bias?
Yes Yes Yes No
Benign
tumors
included
Yes Ye s Yes Ye s Yes Yes Yes Yes
4. Was work
ability
accurately
measured
to mini-
mize bias?
Yes Yes Yes Yes Yes Yes Ye s Yes Yes Yes Yes Ye s
5. Have the
authors
identi-
fied all
important
confound-
ing factors?
Yes N.a. Ye s N.a. N.a. N.a. Yes N.a. N.a. Yes Yes Ye s
6. Have
they taken
account of
the con-
founding
factors in
the design
and/or
analysis?
Yes N.a. Ye s N.a. N.a. N.a. Yes N.a. N.a. Yes Yes Ye s
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174 International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
Table 2 (continued)
Bains etal.
(2012)
De Boer
etal. (2008)
Couwenberg
etal. (2020)
Doll etal.
(2016)
Duijts etal.
(2017)
Gregorow-
itsch etal.
(2019)
Hartung
etal. (2018)
Nieuwen-
huijsen etal.
(2009)
Nilsson etal.
(2016)
Tamminga
etal. (2019)
Wolvers
etal. (2019)
Zanville etal.
(2016)
7. Was the
follow up
of subjects
complete
enough?
Yes Yes Yes N.a. N.a. Ye s Yes N.a. N.a. Yes Ye s Yes
8. Was the
follow up
of subjects
long
enough to
investi-
gate late
effects?
No
(6months)
No
(18months)
No
(24months)
No
(6months)
Yes Ye s No
(12months)
No
(18months)
Sub study
was cross-
sectional
No
(2years)
No
(2years)
No
(18months)
No
(1year)
9. What are
the results
of this
study?
See Table1See Table1See Table1See Table1See Table1See Table1See Table1See Table1See Table1See Table1See Table1See Table1
10. Are the
results
precise?
Yes Yes Yes Yes Yes Yes Ye s Yes Yes Yes Yes Ye s
11 Do you
believe the
results?
Yes Yes Yes Yes Yes Yes Ye s Yes Yes Yes Yes Ye s
12. Can the
results be
applied to
the local
(European)
popula-
tion?
Yes Yes Yes No
(USA)
Yes Ye s Yes Ye s Yes Yes Yes No
(USA)
13. Do the
results
of this
study fit
with other
available
evidence
with regard
to work
ability?
Yes Yes Yes N.a. N.a. Ye s Yes N.a. N.a. Yes Ye s Yes
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175International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
current work ability (Cheung etal. 2017). Moreover, in a
cross-sectional study 2–6years after primary treatment of
breast, testicular or prostate cancer, mental work ability (and
not physical work ability) correlated with lower current work
ability (Gudbergsson etal. 2008b). Another finding is that a
higher current work ability is associated with work continu-
ation one year later (Duijts etal. 2017).
Furthermore, self-employment among cancer survivors
appeared to be a predictor for lower work ability (Torp etal.
2012). Moreover, the negative effect of self-employment on
work ability among cancer survivors was reported to be
mediated by reduced working hours and a negative cancer-
related financial change (Torp etal. 2017). All in all, self-
employed, without employees (freelancers) or with employ-
ees, were not a prominent focus in the included studies. The
few available results among the non-salaried show a lower
work ability and the importance of negative changes in the
financial situation.
Gender differences in work ability among cancer sur-
vivors were also reported, but it is difficult to present an
overview of possible gender differences with regard to work
ability, as factors like type of cancer (and connected gender
and age differences) and differences in physical and mental
work ability cloud the issue. For instance, breast cancer, tes-
ticular cancer and prostate cancer have different profiles with
regard to gender and age. Men had a higher current work
ability (8.4, SD 1.8) than women (8.0, SD 2.1)(effect size
0.20, p < 0.04), while no gender differences were reported
for current work ability in the group of matched controls
without a past cancer diagnosis (8.6, SD 1.6) (Gudbergsson
etal. 2011). Furthermore, female survivors had lower mental
work ability than controls (effect size 0.30, p < 0.001) but no
lower physical work ability, while male survivors had lower
physical work ability (effect size 0.37, p < 0.001) and also
lower mental work ability (effect size 0.27, p = 0.004) than
male controls (Gudbergsson etal. 2011). In a study among
workers 15–39months after a diagnosis with one of various
types of the most common cancer types high current work
ability was reported for men (8.6, SD 1.8), as well as for
women (8.6, SD 1.7) (Torp etal. 2012). Taskila etal. (2007)
reported the highest mean current work ability for testicu-
lar cancer (9.0) and the lowest for prostate cancer (8.0), in
a study which also covered breast cancer and lymphoma.
Furthermore, in another study no difference in work abil-
ity between men with testicular cancer diagnosis (8.8) and
controls (8.7) was reported, while prostate cancer survivors
had a lower work ability (8.3) than controls (p < 0.01) (Lind-
bohm etal. 2012).
Table 2 (continued)
Bains etal.
(2012)
De Boer
etal. (2008)
Couwenberg
etal. (2020)
Doll etal.
(2016)
Duijts etal.
(2017)
Gregorow-
itsch etal.
(2019)
Hartung
etal. (2018)
Nieuwen-
huijsen etal.
(2009)
Nilsson etal.
(2016)
Tamminga
etal. (2019)
Wolvers
etal. (2019)
Zanville etal.
(2016)
14. What are
the impli-
cations of
this study
for prac-
tice?
See Table1See Table1See Table1See Table1See Table1See Table1See Table1See Table1See Table1See Table1See Table1See Table1
(a) Because of the aim of the systematic literature review in question 3 a past cancer diagnosis was regarded as exposure
(b) Because of the aim of the systematic literature review questions 5 and 6 were answered in the case that ‘work ability’ was an outcome measure. In all other cases ‘N.a.’ was noted
(c) Because of the aim of the systematic literature review in question 8 the criterion is two years
(d) In questions 7 and 13 the quality assessment is only made in the case of measurements of the level of work ability at different time points. In all other cases ‘N.a.’ was noted
(e) In question 8 ‘late effects?’ was added
(f) Question 10 was rephrased
(g) In question 12 Europe was regarded as the region of the local population
(h) In question 13 ‘with regard to work ability’ is added
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176 International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
Results: late eects ofcancer treatment
andwork ability
Physical complaints andwork ability
Eight (22%) of the included studies analyzed a possible
association between late physical complaints and work
ability. One study had a case–control design (Gudbergs-
son etal. 2011), and the other studies were cross-sectional
(Gudbergsson etal. 2008b; Moskowitz etal. 2014; Fosså
and Dahl 2015; Dahl etal. 2016, 2019; Torp etal. 2017;
Ho etal. 2018). In the studies physical impairments or the
experienced limitations were associated with lower work
ability or were seen more frequently in cases of subopti-
mal work ability beyond twoyears after diagnosis. In short,
physical complaints after cancer treatment continue to show
associations with lower work ability beyond the first two
years after cancer diagnosis.
Fatigue andwork ability
Four (11%) of the included studies analyzed a possible
association between late fatigue and work ability. Carlsen
etal. (2013), used the first WAI item in a case–control
Table 3 Quality assessment for the case–control studies by means of the checklist from the ‘Critical Appraisal Skills Programme’ (CASP)
(a) Because of the aim of the systematic literature review in questions 6 and 8 ‘(cancer–no cancer)’ was added
(b) Question 9 was not applicable as there is no treatment effect involved
(c) In question 11 Europe was regarded as the region of the local population
Carlsen etal. (2013) Gudbergsson
etal. (2008a)
Gudbergs-
son etal.
(2011)
Lee etal. (2008) Lindbohm etal. (2012) Taskila etal.
(2007)
1. Did the study address a
clearly focused issue?
Yes Yes Yes Yes Yes Yes
2. Did the authors us an
appropriate method to
answer their question?
Yes Yes Yes Yes Yes Yes
3. Were the cases recruited
in an acceptable way?
Yes Yes Yes Yes Yes Yes
4. Were the controls
selected in an acceptable
way?
Yes Yes Yes Yes Yes Yes
5. Was the exposure
accurately measured to
minimize bias?
Yes Yes Yes Yes Yes Yes
6. Aside from the experi-
mental intervention (can-
cer–no cancer), were the
groups treated equally?
Yes Yes Yes Yes Yes Yes
7. Have the authors taken
account of the potential
confounding factors in
the design and/or in their
analysis?
Yes Yes Yes Yes Yes Yes
8. How large was the treat-
ment (cancer–no cancer)
effect?
See Table1See Table1See Table1See Table1See Table1See Table1
9. How precise was the
estimate of the treatment
effect?
N.a. N.a. N.a. N.a. N.a. N.a.
10. Do you believe the
results?
Yes Yes Yes Yes Yes Yes
11. Can the results be
applied to the local (Euro-
pean) population?
Yes Yes Yes No
(Korea)
Yes Ye s
12. Do the results of this
study fit with other avail-
able evidence?
Yes Yes Yes Yes Yes Yes
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177International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
Table 4 Quality assessment for the cross-sectional studies by means of the Appraisal tool for Cross Sectional Studies (AXIS tool)
Bielik
etal.
(2020)
Cheung
etal.
(2017)
Dahl
etal.
(2020)
Dahl
etal.
(2016)
Dahl
etal.
(2019)
De
Boer
etal.
(2011)
Fosså
etal.
(2015)
Gud-
bergs-
son
etal.
(2008b)
Ho
etal.
(2018)
Kise-
rud
etal.
(2016)
Moskow-
itz etal.
(2014)
Musti
etal.
(2018)
Neu-
deck
etal.
(2017)
Ortega
etal.
(2018)
Torp
etal.
(2012)
Torp,
Syse
etal.
(2017)
Von
Ah
etal.
(2018)
Von Ah
etal.
(2017)
1. Were the
aims/objec-
tives of
the study
clear?
Yes Yes Yes Ye s Yes Ye s Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
2. Was the
study
design
appropri-
ate for
the stated
aim(s)?
Yes Yes Yes Ye s Yes Ye s Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
3. Was the
sample size
justified?
Yes Yes Yes Ye s Yes Ye s Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
4. Was the
target/
reference
population
clearly
defined?
Is it clear
who the
research
was about?
Yes Yes Yes Ye s Yes Ye s Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
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1 3
Table 4 (continued)
Bielik
etal.
(2020)
Cheung
etal.
(2017)
Dahl
etal.
(2020)
Dahl
etal.
(2016)
Dahl
etal.
(2019)
De
Boer
etal.
(2011)
Fosså
etal.
(2015)
Gud-
bergs-
son
etal.
(2008b)
Ho
etal.
(2018)
Kise-
rud
etal.
(2016)
Moskow-
itz etal.
(2014)
Musti
etal.
(2018)
Neu-
deck
etal.
(2017)
Ortega
etal.
(2018)
Torp
etal.
(2012)
Torp,
Syse
etal.
(2017)
Von
Ah
etal.
(2018)
Von Ah
etal.
(2017)
5. Was the
sample
frame
taken
from an
appropriate
popula-
tion base
so that it
closely
represented
the target/
reference
popula-
tion under
investiga-
tion?
Yes Don’t
know.
Con-
veni-
ence
sample
from
three
sources
Yes Ye s Yes Ye s Yes Yes Yes Ye s Yes Yes Ye s Yes Yes Yes Yes Yes
6. Was the
selection
process
likely to
select sub-
jects/par-
ticipants
that were
representa-
tive of the
target/
reference
popula-
tion under
investiga-
tion?
Don’t
know.
Partly
pilot
study
Yes Yes Ye s Yes Ye s Yes Yes Yes Yes Yes Yes Don’t
know.
Pilot
study
Yes Ye s Yes Yes Ye s
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179International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
Table 4 (continued)
Bielik
etal.
(2020)
Cheung
etal.
(2017)
Dahl
etal.
(2020)
Dahl
etal.
(2016)
Dahl
etal.
(2019)
De
Boer
etal.
(2011)
Fosså
etal.
(2015)
Gud-
bergs-
son
etal.
(2008b)
Ho
etal.
(2018)
Kise-
rud
etal.
(2016)
Moskow-
itz etal.
(2014)
Musti
etal.
(2018)
Neu-
deck
etal.
(2017)
Ortega
etal.
(2018)
Torp
etal.
(2012)
Torp,
Syse
etal.
(2017)
Von
Ah
etal.
(2018)
Von Ah
etal.
(2017)
7. Were
measures
undertaken
to address
and catego-
rize non-
respond-
ers?
Don’t
know.
No
infor-
mation
Yes Yes Don’t
know
Data
from
other
stud-
ies
N.a. Yes No Ye s Yes Ye s No Yes No Don’t
know.
No
infor-
mation
No No No No
8. Was work
ability
measured
appropri-
ate to the
aims of the
study?
Mixed:
current
work
ability
appro-
priate,
work
ability
unclear
Yes Yes Ye s Yes Ye s Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
9. Was work
ability
measured
correctly
using
instru-
ments/
measure-
ments that
had been
trailed,
piloted or
published
previously?
Don’t
know
Yes Yes Ye s Yes Ye s Don’t
know.
No
infor-
mation
Yes Yes Yes Don’t
know.
No
infor-
mation
Don’t
know.
No
infor-
mation
No
A non-
vali-
dated
ad hoc
ques-
tion-
naire
Yes Ye s Yes Yes Ye s
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180 International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
Table 4 (continued)
Bielik
etal.
(2020)
Cheung
etal.
(2017)
Dahl
etal.
(2020)
Dahl
etal.
(2016)
Dahl
etal.
(2019)
De
Boer
etal.
(2011)
Fosså
etal.
(2015)
Gud-
bergs-
son
etal.
(2008b)
Ho
etal.
(2018)
Kise-
rud
etal.
(2016)
Moskow-
itz etal.
(2014)
Musti
etal.
(2018)
Neu-
deck
etal.
(2017)
Ortega
etal.
(2018)
Torp
etal.
(2012)
Torp,
Syse
etal.
(2017)
Von
Ah
etal.
(2018)
Von Ah
etal.
(2017)
10. Is it clear
what was
used to
determined
statistical
sig-
nificance
and/or
precision
estimates?
(e.g., p val-
ues, CIs)
Yes Yes Yes Ye s Yes Ye s Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
11. Were the
methods
(including
statistical
methods)
sufficiently
described
to enable
them to be
repeated?
Yes Yes Yes Ye s Yes Ye s Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
12. Were the
basic data
adequately
described?
Yes Yes Yes Ye s Yes Ye s Yes Yes Yes Yes Yes Yes Yes Time
since
diag-
nosis
unclear
Yes Ye s Yes Yes
13. Does the
response
rate raise
concerns
about non-
response
bias?
No No No No No No No No No No No No No No No No No No
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181International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
Table 4 (continued)
Bielik
etal.
(2020)
Cheung
etal.
(2017)
Dahl
etal.
(2020)
Dahl
etal.
(2016)
Dahl
etal.
(2019)
De
Boer
etal.
(2011)
Fosså
etal.
(2015)
Gud-
bergs-
son
etal.
(2008b)
Ho
etal.
(2018)
Kise-
rud
etal.
(2016)
Moskow-
itz etal.
(2014)
Musti
etal.
(2018)
Neu-
deck
etal.
(2017)
Ortega
etal.
(2018)
Torp
etal.
(2012)
Torp,
Syse
etal.
(2017)
Von
Ah
etal.
(2018)
Von Ah
etal.
(2017)
14. If appro-
priate, was
informa-
tion about
non-
responders
described?
Yes Yes Yes No N.a. Yes No Yes Yes Yes No Ye s No Yes No No No No
15. Were
the results
internally
consistent?
Yes Yes Yes Ye s Yes Ye s Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
16. Were
the results
for the
analyses
described
in the
methods,
presented?
Yes Yes Yes Ye s Yes Ye s Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
17. Were the
authors’
discussions
and con-
clusions
justified by
the results?
Yes Yes Yes Ye s Yes Ye s Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
18. Were the
limita-
tions of
the study
discussed?
Yes Yes Yes Ye s Yes Ye s Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
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182 International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
Table 4 (continued)
Bielik
etal.
(2020)
Cheung
etal.
(2017)
Dahl
etal.
(2020)
Dahl
etal.
(2016)
Dahl
etal.
(2019)
De
Boer
etal.
(2011)
Fosså
etal.
(2015)
Gud-
bergs-
son
etal.
(2008b)
Ho
etal.
(2018)
Kise-
rud
etal.
(2016)
Moskow-
itz etal.
(2014)
Musti
etal.
(2018)
Neu-
deck
etal.
(2017)
Ortega
etal.
(2018)
Torp
etal.
(2012)
Torp,
Syse
etal.
(2017)
Von
Ah
etal.
(2018)
Von Ah
etal.
(2017)
19. Were
there any
funding
sources or
conflicts
of interest
that may
affect the
authors’
interpreta-
tion of the
results?
No No No No No No No No No No No No Don’t
know.
Pilot
study
No No No No No
20. Was
ethical
approval
or consent
of par-
ticipants
attained?
No Yes Yes Ye s Yes Ye s Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes
(a) Because of the aim of the systematic literature review in questions 8 and 9 ‘work ability’ was inserted
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183International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
study design, and reported that fatigue was associated with
reduced current work ability 5–8years after a breast can-
cer diagnosis, and that this association was stronger among
cancer survivors (OR 10.7, CI 3.31–34.3) than among the
controls (OR 4.11, CI 1.97–8.57), suggesting moderation.
The other three studies were cross-sectional. In one of these
studies the complete WAI to assess work ability was used,
and general, physical, and mental fatigue were reported to be
less common in breast cancer survivors with optimal work
ability. A higher level of physical fatigue was significantly
associated with poorer work ability (Ho etal. 2018). Another
cross-sectional study used the first item of the WAI to assess
work ability and reported that those with low work ability
had significantly higher mean levels of total fatigue (Dahl
etal. 2019). Furthermore,another cross-sectional study did
not report a significant association of fatigue with work
ability, however fatigue was part of more comprehensive
constructs, making specific inferences difficult. In this study
work ability was assessed by a multiple choice question
regarding being unable to work full time, unable to work the
same as before cancer or unable to work at all (Moskowitz
etal. 2014) To summarize, the scarce data demonstrate that
fatigue can be associated with lower work ability among
workers with a past cancer diagnosis.
Cognitive complaints andwork ability
Four (11%) of the included studies analyzed a possible asso-
ciation between late cognitive complaints and work ability.
The study designs were all cross-sectional. In this systematic
literature review attentional fatigue, i.e. experiencing lower
levels of attention, is regarded as a cognitive complaint. A
significant relationship (β = 0.627, p < 0.001) between higher
levels of attention and perceived work ability assessed by the
complete WAI, was reported by Von Ah etal. (Von Ah etal.
2017). Attentional fatigue explained 40% of the variance in
perceived work ability among 68 breast cancer survivors
on average 5years after diagnosis. Von Ah etal. (2018)
also reported that cognitive impairment was associated with
poorer work ability (β = − 0.66, p < 0.000) and that perceived
cognitive ability was significantly related to higher levels
of work ability (β = 0.47, p < 0.000). Furthermore, Ho etal.
(2018) reported breast cancer survivors (3–8years after
diagnosis) to have lower scores for cognitive functioning in
case of suboptimal work ability. Another study, by Moskow-
itz etal. (2014), also included cognitive symptoms, but as
part of more comprehensive constructs, making specific
inferences difficult. So, although results are scarce, recent
studies indicate that cognitive complaints can be associated
with low work ability among working cancer survivors.
Results: current job resources andwork
ability
As has already been stated, job resources can be of impor-
tance for work functioning, also among workers who
returned to work after cancer treatment and experienc-
ing any late effects of cancer treatments. Job resources
can among others be provided by (1) social support, (2)
autonomy, (3) leadership style, (4) coaching, or (5) organi-
zational culture (Demerouti etal. 2001). Of these job
resources the current experienced level and their possible
association with work ability was taken into consideration
in nine (25%) of the included studies; three case–control
studies and six cross-sectional studies.
Social support by colleagues was reported to be associ-
ated with positive outcomes with regard to higher work
ability in case–control studies (Taskila etal. 2007; Lind-
bohm etal. 2012; Carlsen etal. 2013), as well in cross-
sectional studies (Gudbergsson etal. 2008b; Torp etal.
2012; Musti etal. 2018). For instance, a high level of
cancer-related support by colleagues was associated with
higher work ability 15–39months after diagnosis, also in
multivariate regression (Torp etal. 2012). Social support
by supervisors was reported to be associated with posi-
tive outcomes with regard to higher work ability as well
in case–control studies (Lindbohm etal. 2012; Carlsen
etal. 2013), as in cross-sectional studies (Torp etal. 2012;
Musti etal. 2018). For instance, less help and support from
a supervisor was significantly associated with reduced
work ability among workers 5–8years after breast cancer
diagnosis (Carlsen etal. 2013).
Three cross-sectional studies analyzed a possible asso-
ciation of autonomy at work with work ability, although the
construct of autonomy was defined somewhat differently.
In two of these studies the respondents reported the ‘deci-
sion latitude’ (opportunities to learn new things at work and
decide how to carry out the work tasks) at the time of the
cancer diagnosis (Torp etal. 2012, 2017). Decision lati-
tude was found to be significantly related with work ability
among a sample workers who returned to work after various
cancer diagnoses, 6% of whom were self-employed (Torp
etal. 2012). In addition, it was also reported that the self-
employed experienced a higher decision latitude, preventing
low work ability (Torp etal. 2017). Furthermore, Cheung,
Ching, Chan, Cheung, and Cheung (2017) reported ‘con-
trol’, a related concept, to be correlated with work ability
(Rs = 0.29, p = 0.04).
Leadership style, coaching and organizational culture
were assessed in almost none of the included studies. How-
ever, social climate at work, a concept related to organi-
zational culture (Ehrhart etal. 2013), was assessed in two
studies (Taskila etal. 2007; Lindbohm etal. 2012), with only
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184 International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
one study analyzing a possible association with work ability.
This study showed that a better social climate at work was
related to a higher mental work ability (Taskila etal. 2007).
The only behavior of supervisors related to leadership style
that was assessed in some of the studies was social support
from supervisors and their avoidance behavior. Worth noting
is that male workers with a cancer diagnosis experienced
lower work ability as a result of supervisors’ avoidance
behavior (p < 0.001), while female workers with a cancer
diagnosis in their past experienced lower work ability if
avoidance behavior of colleagues was higher (p < 0.001)
(Lindbohm etal. 2012).
All in all, the attention paid to job resources among the
included studies was limited. Nevertheless, the scarce results
indicate a positive association between job resources and
work ability, although no data on job resources that affect
the strength of the association of the late effects with work
ability have been found.
Discussion
As high numbers of working people diagnosed with cancer
re-enter the workplace and the group of workers with a can-
cer diagnosis in their life history will continue to expand, it
is important to have an overview over the current state of
knowledge about the course of work ability after diagnosis,
and about the associations between late effects of cancer
treatment and work ability. Knowledge about the role of job
resources (social support, autonomy, leadership style, coach-
ing, and organizational culture) in this is also relevant.
The searches included 2303 records in total, and 36
studies were selected. A quality assessment was used to
clarify the quality across studies and we found that most
research was cross-sectional (50%). These studies and the
six case–control studies were mostly completely or in part
focused on workers beyond two years past cancer diagnosis.
However, only two of the 12 cohort studies had a follow-up
beyond 2years after diagnosis.
It is an important finding that studies with various study
populations and study designs demonstrate that work ability
seems to be lowered shortly after the start of cancer treat-
ment and tends to recover during the first two years after the
diagnosis, although work ability might still be lower than in
healthy populations. Because there is a lack of longitudinal
data beyond the first two years after diagnoses, the further
course of work ability is not clear. Differences in the level of
work ability between workers with different types of cancer
diagnosis in the past are reported. Late physical complaints,
fatigue or cognitive complaints are associated with lower
work ability across all relevant studies. None of these studies
had a longitudinal design.
Social support and characteristics of autonomy were
assessed in some of the studies, indicating that these cur-
rent job resources are associated with higher work ability,
in line with results in the healthy population (Gould etal.
2000) and also in populations experiencing chronic health
problems (Leijten etal. 2014). No data were available on the
possible buffering effects of social support and autonomy on
the relationship between late effects of cancer treatments and
work ability. Organizational culture in general was not inves-
tigated, only social climate at work in one study, which was
positively related to a higher work ability. No results were
found for leadership style, and coaching. In short, research
on late effects of cancer treatment and work ability among
workers past cancer diagnosis has not yet been enriched or
combined with investigations of possible buffering by job
resources.
Limitations
First, of the 36 studies included, ten studies (28%) solely
concerned workers with a breast cancer diagnosis, which
may have caused bias. The other studies used in this review
included considerable variations in type(s) of cancer and
cancer treatments. However, the impact of differences in
diagnosis is not clear. For instance, survivors of testicular
cancer reported the highest work ability (even comparable
to controls), survivors with prostate cancer the lowest level,
and the breast cancer population in between (Taskila etal.
2007; Lindbohm etal. 2012). It is important to be aware
of the very different profiles with regard to gender and age
of these types of cancer. Among healthy populations age
is generally associated with work ability, younger workers
usually estimating their work ability at a higher level (Gould
etal. 2000; Berg van de etal. 2010; Bender etal. 2015).
Also, variation among participants in the disease status
may cause a lack of comparability, as there are differences
between studies with regard to including participants with
recurrence, or distant metastasis, while awareness of disease
progression or the possibility of the cancer not being cur-
able, might influence perceived work ability.
Second, the way that work ability was measured did not
seem to influence the results. The complete WAI (Work
Ability Index) was used in a few studies only, while the
vast majority of studies used only one or more of the items
adopted from the WAI, with the first item (current work abil-
ity compared to life-time best) being used most frequently.
The complete WAI is reported to be a very predictive and
cross-nationally stable instrument (Radkiewicz and Wid-
erszal-Bazyl 2005) to predict work disability, retirement and
mortality in a reliable way (Ilmarinen and Tuomi 2004).
Furthermore, the first item of the WAI is reported to have a
very strong association with the complete WAI (Ahlstrom
etal. 2010), and to show similar strong predictive value for
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185International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
the degree of sick leave, health-related quality of life (Ahl-
strom etal. 2010) and future disability (Alavinia etal. 2009).
Although in the general populations the use of the complete
WAI might result in a higher probability of lower work abil-
ity in women compared to using only the first item of the
WAI (El Fassi etal. 2013), using only one item of the WAI
is regarded as a good alternative for the complete WAI. A
minority of the included studies did not use any of the WAI
items, but used different surveys, ad hoc questions, a percep-
tion of the participant, etcetera. In short, when interpreting
results on work ability in workers with a past cancer diag-
nosis, conscientiousness in reviewing the assessment tool of
work ability is wise, although the results across the studies
included in this review do not lead to different conclusions.
Third, the late effects of cancer treatment evaluated in
this systematic literature review were not all possible preva-
lent late effects. For instance, depression was not included,
and the effect of co-morbidities was not clear. However, the
scarce studies that investigated a possible association of late
physical complaints, fatigue and cognitive complaints with
work ability, indicated that these complaints after cancer
treatment were associated with lower work ability in almost
all included studies. It is important to be alert of the likeli-
hood of stronger associations of specific complaints with
work ability in the cancer population, as this was already
reported for fatigue in one of the included studies (Carlsen
etal. 2013). More knowledge is needed to be able to know
what subgroups are at risk and aim rehabilitation interven-
tions at the right objectives. Furthermore, it is important to
realize that the prevalence of late effects might also differ
due to different types of treatment (Stein etal. 2008), while
these differences are not always taken into account.
Fourth, the work status, the type of employment and
the personal work histories of the study participants were
not clear in a vast majority of the studies. Study samples
did not in all instances include participants who had fully
recovered 100% of their previous working hours currently or
were not always entirely actively at work during the study’s
data selection for unknown reasons. Only some studies men-
tioned type of work, like blue or white collar. Also, informa-
tion on previous work adjustments, previous changes of job
or of employer, was mostly not presented. So, results might
be biased by those not actually active in work, by differences
in type of work or already made adjustments in job demands
made in an earlier stage. Furthermore, the setting of 75%
of the studies was a European country, preventing global
generalizability.
Fifth, only 13 (36%) of the 36 studies mentioned the
inclusion of self-employed workers; freelancers, or entre-
preneurs (Taskila and Lindbohm 2007; Gudbergsson etal.
2008a; Lee etal. 2008; De Boer etal. 2011; Torp etal.
2017, 2012; Moskowitz etal. 2014; Von Ah etal. 2017;
Cheung etal. 2017; Hartung etal. 2018; Ortega etal. 2018;
Wolvers etal. 2019; Tamminga etal. 2019). However, the
self-employed might have different characteristics in regard
to age, educational level, gender and decision latitude, as
was reported in one of the studies (Torp etal. 2017). Also,
a recent European multi-country study (Torp etal. 2018),
reported that differences in work ability could be observed
between salaried and self-employed but that the direction
and magnitude of these differences differed across countries.
The variation between different kinds of self-employment
should probably be considered too, as self-employment
occurs in very different professional areas, and among the
healthy population agricultural entrepreneurs, for instance,
have a lower work ability than other occupational groups
(Gould etal. 2000). The conclusion from this review is
that the non-salaried workers among cancer survivors are
reported to have a lower work ability than salaried workers.
However, differentiation in occupational groups within the
self-employed is not clear, stressing the need to take this into
account as self-employment shows varying profiles. This
review does not clarify whether predictors of lower work
ability in this type of employment differ from the predictors
of lower work ability in the salaried work situation. Never-
theless, the role of reduced working hours and a negative
cancer-related financial change underlines that targets for
occupational rehabilitation in this group of workers could
also be interventions directed at business support, as some
rehabilitation providers focusing on the self-employed are
already offering. Future studies should focus on the needs
of this specific group of the non-salaried workers with a past
cancer diagnosis.
Finally, this review was limited to five well-known job-
resources for the general working population. Other job
resources, such as growth opportunities, performance feed-
back or organizational prestige, might also be relevant for
the salaried, and also or even exclusively for the non-sal-
aried. Furthermore, also personal resources are important
(McGonagle etal. 2015), however these were not the focus
of this review.
Strengths
This is the first review to focus on late effects of cancer
treatment, work ability and job resources. This review com-
bines findings on the effects of cancer treatment with work
ability (Ilmarinen etal. 2005), and with the Job Demands-
Resources (JD-R) model (Demerouti etal. 2001), which
is unique to our knowledge. The goal of sustainable work
participation of cancer survivors needs tailored interven-
tions (De Boer etal. 2020b) and the outcome measure of
work ability is an important factor in this research area. This
review integrates concepts originated in different research
disciplines with the intention to be able to focus on targets in
the workplace to preserve and enhance work ability among
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186 International Archives of Occupational and Environmental Health (2021) 94:147–189
1 3
workers experiencing late effects of cancer treatment beyond
the first two years after cancer diagnosis.
Conclusion
To conclude, this systematic literature review confirms
that a lowered work ability after the start of cancer treat-
ment, might recover during the first two years after diagno-
sis. However, at two or more years beyond cancer diagno-
sis work ability might still be lower than before the cancer
diagnosis. The course of work ability among workers
beyond the first two years after diagnoses is unknown as
no longitudinal data are available. Longitudinal research
in salaried and non-salaried populations is needed to study
in more detail what factors are important for sustainable
occupational rehabilitation after cancer treatment. Besides
this, an interesting methodological finding is that although
the majority of the studies uses one of more items of the
Work Ability Index (WAI) to assess work ability, also a
substantive part of the included studies makes use of a
variety of validated and non-validated measurement tools.
The method to measure work ability did not seem to lead
to different conclusions.
Physical complaints, fatigue and cognitive complaints
may be present as late effects of cancer treatment beyond
two years after diagnosis and can be associated with a
lower level of work ability. However, data on the asso-
ciation between late effects and work ability is scarce.
Furthermore, it is unknown if late effects of cancer treat-
ment diminish work ability beyond two years after being
diagnosed with cancer because longitudinal studies are
lacking.
Furthermore, this review also makes clear that the job
resources leadership style, coaching and organizational cul-
ture were not taken into account in studies on late effects
of cancer treatment and work ability, and that for the job
resources that were included (autonomy and social support
in the workplace) no possible buffering effect was analyzed.
However, autonomy and social support were associated with
higher work ability and therefore are important for work
functioning among workers past cancer diagnosis and it is
recommended to enhance these job resources as much as
possible.
This review indicates that there is an urgent need to
close this gap in our knowledge. It is important to study late
effects of cancer treatment, work ability and job resources
in combination within studies among various samples of
workers with a past cancer diagnosis, as well in large inter-
national cohorts. These studies need to be carried out beyond
the first two years of cancer diagnosis. A focus on a broad
range of job resources is essential, both for salaried and
self-employed workers. It should be clear what range of job
resources might accelerate a recovery of work ability, cre-
ating an important step towards clarifying the issue of the
rehabilitation of work ability beyond return to work among
workers with a history of cancer.
Acknowledgements We thank Janneke Staaks and Jolanda Kleen,
information specialists, for providing the needed selection param-
eters for the various databases and performing the searches. Further-
more, we thank our two research trainees, Dana Landman and Sterre
Albrecht, for their individual effort to screen the search results by title
and abstract.
Author contributions First author IGB: defined search terms in col-
laboration with an information specialist in mutual agreement with the
other authors, screened by title and abstract in collaboration with the
second author and two research trainees, performed citation tracking
and the data extraction, discussed the eligibility of the papers after
the screening, the quality assessment, the analysis and interpretation
of the data, and performed the drafting and the critical revision of the
manuscript. Second author WV: screened by title and abstract in col-
laboration with the first author, discussed the eligibility of the papers
after the screening, the quality assessment, the analysis and interpreta-
tion of the data, and contributed to the drafting and the critical revision
of the manuscript. Third author TvV: discussed the eligibility of the
papers after the screening, the quality assessment, the analysis and
interpretation of the data, and contributed to the drafting and the criti-
cal revision of the manuscript.
Funding This research received no specific grant from any funding
agency in the public, commercial or not-for-profit sectors.
Compliance with ethical standards
Conflict of interest The authors declare that they have no conflict of
interest.
Open Access This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long
as you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article are
included in the article’s Creative Commons licence, unless indicated
otherwise in a credit line to the material. If material is not included in
the article’s Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will
need to obtain permission directly from the copyright holder. To view a
copy of this licence, visit http://creat iveco mmons .org/licen ses/by/4.0/.
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