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Predictors of nurse absenteeism in hospitals:a systematic review
MANDY M. DAVEY B S C N , R N , M N1, GRETA CUMMINGS P h D , R N
2,3, CHRISTINE V. NEWBURN-COOK P h D ,
R N2,4 and ELIZA A. LO B S C N , R N
2,5
1Registered Nurse, Bonnyville Health Centre, Bonnyville, AB, Canada, 2Associate Professor, Faculty of Nursing,University of Alberta, 3Principal Investigator, CLEAR Outcomes Research program; New Investigator, CanadianInstitutes of Health Research; Population Health Investigator, Alberta Heritage Foundation for Medical Research,University of Alberta, 4Associate Professor & Associate Dean (Research), Faculty of Nursing, University of Albertaand 5MN Student, Faculty of Nursing, University of Alberta, Edmonton, AB, Canada.
Introduction
Absenteeism of front-line staff nurses is of increasing
concern and a costly problem for hospital employers
(Taunton et al. 1995, Buschak et al. 1996, Benefits
Interface 2000). This issue amplifies the nursing short-
age, decreases employee morale (Seago 1996, Haun
et al. 2002) and disrupts the continuity of patient care
Correspondence
Greta Cummings
5-125 Clinical Sciences Building
Edmonton, AB T6G 2G3
Canada
E-mail: greta.cummings@ualberta.ca
D A V E Y M . M . , C U M M I N G S G . , N E W B U R N - C O O K C . V . & L O E . A . (2009) Journal of Nursing
Management 17, 312–330
Predictors of nurse absenteeism in hospitals: a systematic review
Aim This study aimed to identify and examine predictors of short-term absences ofstaff nurses working in hospital settings reported in the research literature.
Background Front-line staff nurse absenteeism contributes to discontinuity of
patient care, decreased staff morale and is costly to healthcare.
Evaluation A systematic review of studies from 1986 to 2006, obtained through
electronic searches of 10 online databases led to inclusion of 16 peer-reviewed
research articles. Seventy potential predictors of absenteeism were examined and
analysed using content analysis.
Key issue Our findings showed that individual �nurses� prior attendance records�,�work attitudes� (job satisfaction, organizational commitment and work/job
involvement) and �retention factors� reduced nurse absenteeism, whereas �burnout�and �job stress� increased absenteeism. Remaining factors examined in the literature
did not significantly predict nurse absenteeism.
Conclusions Reasons underlying absenteeism among staff nurses are still poorly
understood. Lack of robust theory about nursing absenteeism may underlie the
inconsistent results found in this review. Further theory development and research is
required to explore the determinants of short-term absenteeism of nurses in acute
care hospitals.
Implications for nursing management Work environment factors that increase
nurses� job satisfaction, and reduce burnout and job stress need to be considered in
managing staff nurse absenteeism.
Keywords: absenteeism, nurse, predictors, systematic review
Accepted for publication: 6 September 2008
Journal of Nursing Management, 2009, 17, 312–330
DOI: 10.1111/j.1365-2834.2008.00958.x312 ª 2009 The Authors. Journal compilation ª 2009 Blackwell Publishing Ltd
(Taunton et al. 1995) ultimately having a negative im-
pact on the cost and quality of care and outcomes for
patients.
In Canada, absenteeism data of individual nurses are
difficult to find, largely owing to privacy of information
legislation. The Canadian Institute of Health Informa-
tion (CIHI) reports absenteeism statistics that incorpo-
rate and compare all healthcare professionals (including
nurses) to other non-healthcare occupations. On aver-
age, healthcare professionals are 1.5 times more likely
to be absent from work as a result of illness or injury
than other occupations (CIHI 2005). Average days lost
per year for Canadian healthcare professionals range
from 12 to 15 days (CIHI 2005). If a nurse makes $28/
h, works 40 hours a week, and has called in sick six
times in 1 year, it costs the organization $1344.00 (not
including benefits) to pay that nurse while absent. To
replace that nurse at double time (should overtime rates
for replacement be required) costs the organization
$2688; the total cost is $4032. To replace 50 nurses
who are absent six times in one year would cost
approximately $201, 600. Absenteeism is a current and
expensive problem that must be explored in greater
detail.
Defining and measuring absence
�Absenteeism� is defined as not coming to work when
scheduled, and is measured by frequency or duration
of work days missed. There are two types of absen-
teeism – �non-culpable� (involuntary or approved) and
�culpable� (voluntary or unapproved) absence (Ham-
mer & Landau 1981, Buschak et al. 1996, Australian
Faculty of Occupational Medicine 1999, Thomson
2005). Non-culpable or involuntary absence occurs for
reasons beyond the control of the nurse (e.g. personal
illness, family death, weather, transportation prob-
lems). In contrast, voluntary or motivated absences
occur when the nurse makes a decision to be absent.
Distinguishing between voluntary and involuntary
absences can be very difficult because hospital-based
nurses with formal sick-leave programmes typically
only receive benefits when they �call in sick� (Hackett
et al. 1989, Gellatly & Luchak 1998, Hemmingway &
Smith 1999). Thus, virtually all absences are classified
as sick days (i.e. non-culpable; involuntary), whether
the absence is for personal illness or not (for a
description of these classification errors, see Hammer
& Landau 1981).
Although imperfect, a practical way to distinguish
non-culpable from culpable absence is to assess the
frequency and duration of absences/sick days. Research
has shown consistently that frequency measures provide
a reasonable index of culpable or voluntary absenteeism
(Chadwick-Jones et al. 1971, Hammer & Landau
1981, Hackett & Guion 1985). To measure absence
frequency, each incident or episode of absence is
counted regardless of the duration of absence. Higher
frequency scores are interpreted as a sign of more rather
than less voluntary absence. Duration measures provide
an index of involuntary absence such as the Time Lost
Index (Hammer & Landau 1981, Hackett & Guion
1985). To assess absence duration, the total number of
days lost are tallied, regardless of the number of inci-
dents. Nurses with high rather than low duration scores
tend to have more involuntary absence (e.g. broken leg,
recovering from surgery). Often, studies include one or
more measures of absence.
Predictors of absenteeism
The 2005 CIHI report stated that nurses with absen-
teeism totalling more than 20 days commonly reported
�high job strain, low supervisor support and high
physical demands on the job, low control over practice,
lack of respect from supervisors, or high role overload
as factors responsible for absenteeism� (CIHI 2005,
p. xvi). Additionally, while considerable research has
been conducted identifying factors related to nurse
absenteeism, no current systematic reviews were found
that examined the relationship between individual
and organizational characteristics and absenteeism of
nurses.
Objective
This systematic literature review examined the rela-
tionships between individual and organizational fac-
tors, and absenteeism of staff nurses (Registered Nurses
and Licensed Practical Nurses) in acute care hospital
settings. The following research question guided this
review: �What are the determinants of individual staff
nurse absenteeism in hospital settings?�.
Methods
Search strategy
The search was conducted using 10 online databases:
ABI Inform, Academic Search Complete, CINAHL Plus
with Full Text, Cochrane Library, EMBASE, Health
Source Nursing/Academic Addition, Ovid Healthstar,
Ovid Medline, PsychINFO and SCOPUS. English-only
studies from 1986 to 2006 were accessed.
Staff nurse absenteeism
ª 2009 The Authors. Journal compilation ª 2009 Blackwell Publishing Ltd, Journal of Nursing Management, 17, 312–330 313
Inclusion criteria
Titles and abstracts were screened twice for the fol-
lowing keywords: �hospital�, �tertiary care centre�, �nur-
ses (RNs, LPNs)� and �absenteeism� or �sick leave�, to
ensure that key articles were not missed. Only primary
reports of qualitative or quantitative research published
in peer-reviewed journals were included. Absenteeism
must have been measured or qualitatively analysed.
Articles were excluded that reported absenteeism of
student nurses, nursing attendants, psychiatric nurses,
or nurses who worked in public health, the community,
or in long-term care facilities. Only studies that sampled
nurses from hospitals were included. Articles discussing
absenteeism related to true (certified) mental or physical
illness, pregnancy or injury were excluded; these
determinants would have skewed the results as they are
legitimate causes of unplanned absenteeism.
Screening
From the review of titles and abstracts, full manuscripts
were retrieved for screening using the primary inclusion
criteria. To meet the final inclusion criteria, a relation-
ship between the determinant (independent variable)
and absenteeism (dependent variable) had to be re-
ported and measured. No qualitative studies were found
that met the inclusion criteria.
After initial screening, articles that met the inclusion
criteria discussed a predictor or determinant and
absenteeism. These articles were then grouped into
two categories, those that measured the independent
variable and absenteeism, and those that discussed a
non-measurable intervention or strategy to influence
absenteeism. As a result of the lack of precision in
measuring the relationship between independent and
dependent variables, research studies that measured only
absenteeism, but not the independent variable, were
removed. Only studies that measured the relationship
between absenteeism and its predictors were analysed.
A second reviewer independently screened 30 ran-
domly selected articles to ensure inter-rater reliability.
One discrepancy between the reviewers regarding the
inclusion of an article was dealt with by consensus.
Methodological assessment
A methodological quality assessment was completed on
each included study using a tool adapted from prior
published systematic reviews (Estabrooks et al. 2001,
Cummings & Estabrooks 2003, Estabrooks et al. 2003,
Wong & Cummings 2007). Thirteen items in this tool
were used to rate four areas of research: design, sam-
pling, measurement and statistical analysis. Twelve out
of 13 items scored 1 point. An additional point was
awarded if absenteeism was observed rather than self-
reported. If authors did not report an item addressed in
the quality assessment tool, zero points were assigned.
The total quality assessment scores ranged from 1 to 14
and, each article was categorized into low (1–4), med-
ium (5–9) or high quality (10–14). Studies of low
quality were excluded.
Results
Search results
The initial search yielded 2401 titles and abstracts. Of
these, 423 papers were retrieved for screening and 71
papers met the inclusion criteria. Thirty-three papers
were removed because they did not measure a predictor
or influence of absenteeism (an intervention designed to
influence absenteeism). Twenty-two papers were of low
quality and removed from the review. These papers had
discrepancies in the reliability and validity of their
instrumentation; eleven did not use a prospective
design, and all had sampling deficiencies. In total, 16
articles were included. Two authors (Boumans &
Landeweerd 1993, 1994, Gellatly 1995, Gellatly &
Luchak 1998) used the same sample and data in each of
two papers, reporting separate analyses in each paper.
Therefore, each of these two sets of papers was con-
sidered as one study, to prevent inflation of reported
results, leaving a total of 14 studies for analysis. Table 1
provides a summary of the search strategy results.
Table 2 provides a summary of the strengths and
limitations for the final group of 14 studies (which had
yielded 16 papers).
Of the 16 papers included in the systematic review,
three were published between 1986 and 1989, 10
between 1990 and1999, and three between 2000 and
2002. Table 3 summarizes the characteristics of each
paper. This reflects that most data were collected in the
1980s and 1990s, even although some studies were
published between 2000 and 2002.
Seven studies were conducted in the USA and three in
Canada. One Canadian study was published in 2002,
the remainder in the 1990s. Two studies were con-
ducted outside of North America, one in the Nether-
lands and the other in Israel. Two researchers did not
report which country their data came from.
Demographics were reported in 13 out of the 14
studies. Eleven studies reported the age of the nurses,
and the mean age across studies was 35.1 years. All
M. M. Davey et al.
314 ª 2009 The Authors. Journal compilation ª 2009 Blackwell Publishing Ltd, Journal of Nursing Management, 17, 312–330
other studies reported the average nurse age range as
mid-thirties to early forties. In all studies, the majority
of respondents were female (>90%). The unit of anal-
ysis in four studies was at the individual level and in
three studies was at the group level. The remaining nine
studies did not identify the unit of analysis. Each study
discussed collecting data at the individual level, but did
not explain how the results were analysed and reported
(individual or group). This is problematic, as nurse
information and results were not consistently reported
independently from other healthcare workers in each
sample.
Absenteeism
The most common measure of absenteeism reported
was �absence frequency�, which was defined as the
number of days absent (incidents) over a given period of
time. Other measures used were total days, duration
and percentage. Three studies asked participants to self-
report their personal absenteeism rates (Boumans &
Landeweerd 1993, 1994, Gellatly 1995, 1998, Gold-
berg & Waldman 2000).
Four studies reported using a theoretical framework
that directly conceptualized absenteeism and its rela-
tionship with other factors (Hackett et al. 1989, Gel-
latly 1995, 1998, Taunton et al. 1995, Goldberg &
Waldman 2000). Ten papers (nine studies) included a
conceptual model or theoretical framework that incor-
porated absenteeism, but absenteeism was not the cen-
tral focus (Boumans & Landeweerd 1993, 1994,
Somers 1995, Taunton et al. 1995, Seago 1996, Griff-
eth et al. 1997, 1998, Zboril-Benson 2002). Two
studies did not report using a theoretical framework
(Blau 1986, Parker & Kulik 1995). Each of the absen-
teeism theoretical frameworks was different. Gellatly
(1995) and Gellatly and Luchak (1998) used an absence
culture framework by Nicholson and Johns (1985),
which suggests that the level of trust and salience of the
culture are necessary for members to develop an ab-
sence culture (p. 1086). Four different absence cultures
were presented based on high and low dimensions of
trust and salience. This framework suggests that
Table 1Search strategy
Database 1986–October 2006 Search terms Number
ABI Inform Absenteeism OR sick leave AND nurse (KW) 42Academic Search Premiere Absenteeism OR sick leave AND nurse (KW & Heading) 101CINAHL Plus with Full Text Absenteeism OR sick leave AND nurse (KW & Heading) 175Cochrane Library (CDSR, ACP Journal Club, DARE, CCTR) Absenteeism OR sick leave AND nurse (KW) 115EMBASE Absenteeism OR sick leave AND nurse 344Health Source: Nursing/Academic Edition Absenteeism OR sick leave AND nurse (KW) 74Ovid Healthstar Absenteeism OR sick leave AND nurse (KW) 561Ovid Medline Absenteeism OR sick leave AND nurse (KW) 552PsychINFO Absenteeism OR sick leave AND nurse (KW) 85SCOPUS Absenteeism OR sick leave AND nurse (KW) 335Manual Search of Journal of Organizational Behavior Absenteeism OR sick leave AND nurse (KW) 17Total Titles and Abstracts 2401Articles retrieved and screened 423First selection of articles 71Second selection of articles 38Final Selection of included articles 16Final Selection of included studies 14
Table 2Quality assessment of included studies
Summary of quality assessment – 14 studies included
CriteriaNumber of
studies
Yes No
Design:Prospective studies 7 7Used probability sampling 3 11Sample:Appropriate/justified sample size 0 14Sample drawn from more than one site 7 7Anonymity protected 3 11Response rate >60% 5 9Measurement:Determinant measured reliably 12 2Determinant measured with a valid instrument 3 11Absenteeism observed rather than self-reported* 11 3Internal consistency ‡ .70 when scale used 0 14Theoretical model/framework used 11 3Statistical analyses:Correlations analysed when multipledeterminants studied
10 4
Management of outliers addressed 0 14
*This item scored two points. All others scored one point.
Staff nurse absenteeism
ª 2009 The Authors. Journal compilation ª 2009 Blackwell Publishing Ltd, Journal of Nursing Management, 17, 312–330 315
Tab
le3
Cha
ract
eris
tics
ofin
clud
edst
udie
s
Aut
hor(
s)Y
ear
Jour
nal&
Cou
ntry
Sam
ple
Mea
sure
men
t/Ins
trum
ents
Sco
ring
Rel
iabi
lity
Val
idity
Ana
lysi
s
Bla
u19
86,
JM
anag
eU
SA
228
RN
s(8
2su
b-sa
mpl
e)1
city
hosp
ital
Job
Invo
lvem
ent
(no
title
:K
anug
o19
82)
Org
aniz
atio
nalC
omm
itmen
t(n
otit
le:
mod
ified
scal
eP
orte
ret
al.
1976
)U
nexc
used
abse
nce
(#of
indi
vidu
alab
senc
esw
ithou
tpe
rmis
sion
in3
time
bloc
ks)
10ite
ms,
5pt
scal
e9
item
s,5
ptsc
ale
ƒ(d
ays)
a=
.84
a=
.86
a=
.63
Var
imax
Rot
atio
nV
arim
axR
otat
ion
NR
Hie
rarc
hica
lR
egre
ssio
n
Bou
man
s&
Land
ewee
rd19
93,
JA
dvN
urs
Net
herla
nds
305
ICU
nurs
es25
6ge
nera
lnur
ses
16ho
spita
ls
Soc
ial&
Inst
rum
enta
lLea
ders
hip
(Lea
ders
hip
Beh
avio
rQ
uest
ionn
aire
:S
togd
ill19
63)
Abs
ente
eism
(sel
fre
port
)
20ite
ms,
5pt
scal
eƒ
(day
s)
a=
.90
&.8
2r
=.7
5F
acto
rA
naly
sis
Pilo
ted
AN
OV
A
AN
CO
VA
Fis
her�s
ZR
egre
ssio
nB
oum
ans
&La
ndew
eerd
1994
,H
eart
&Lu
ngN
ethe
rland
s30
5IC
Unu
rses
256
gene
raln
urse
s16
hosp
itals
Wor
kS
ituat
ion
Cha
ract
eris
tics
job
char
acte
ristic
s,fe
edba
ck&
clar
ity,
wor
kpr
essu
re,
auto
nom
y,pr
omot
iona
l&gr
owth
oppo
rtun
ities
(Ite
ms
deriv
edfr
omH
ackm
an&
Old
ham
�sJo
bD
iagn
ostic
Sur
vey
and
ast
udy
byA
legr
a)S
eeab
ove
for
othe
rm
easu
res
40ite
ms
Sam
eas
abov
e
NR
Sam
eas
abov
eN
RS
ame
asab
ove
Reg
ress
ion
T-T
est
Coh
en20
00,
Hum
Rel
atIs
rael
283
nurs
es3
hosp
itals
Org
aniz
atio
nalC
omm
itmen
t(O
rgan
izat
iona
lC
omm
itmen
tQ
uest
ionn
aire
-Sho
rt:
Por
ter
etal
.19
74)
Occ
upat
iona
l(C
aree
r)C
omm
itmen
t(n
otit
le:
Bla
u19
85)
Job
Invo
lvem
ent
&W
ork
Invo
lvem
ent
(no
title
:K
anun
go19
79,
1982
)G
roup
Com
mitm
ent
(no
title
:R
anda
ll&
Cot
e19
91)
Wor
kC
omm
itmen
tC
onst
ruct
s(n
otit
leor
auth
or)
Abs
ente
eism
(1ye
ar–
hosp
italr
ecor
ds)
Tur
nove
rIn
tent
ion
(sel
fre
port
)
9ite
ms
8ite
ms
10ite
ms;
6ite
ms
6ite
ms
5ite
ms
Tot
alda
ys3
item
s,5
ptLi
kert
a=
.92
a=
.83
a=
.76;
a=
.74
a=
.71
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
Str
uctu
ral
Equ
atio
nM
odel
ing
Gel
latly
&Lu
chak
1998
,H
umR
elat
Can
ada
164
hosp
itale
mpl
oyee
s(n
urse
sin
clud
ed)
1ho
spita
l
Per
ceiv
edA
bsen
ceN
orm
(est
imat
eav
erag
e#
ofda
ysot
her
empl
oyee
sw
ere
abse
ntdu
ring
prev
ious
12m
onth
s–
self
repo
rt)
Prio
rIn
divi
dual
Abs
ence
(#of
days
abse
ntdu
ring
prev
ious
12m
onth
s-se
lfre
port
)G
roup
-Lev
elA
bsen
ce(a
vera
gele
velo
fac
tual
abse
ntee
ism
with
inim
med
iate
wor
kgr
oup
–fr
omho
spita
lrec
ords
atin
divi
dual
leve
l)F
utur
eIn
divi
dual
Abs
ence
(#da
ysab
sent
over
12-m
onth
sfo
llow
ing
surv
ey)
NR
N/R
Equ
atio
nƒ
(day
s)
NR
NR
NR
NR
NR
NR
NR
NR
Hie
rarc
hica
lR
egre
ssio
n
Gel
latly
1995
,J
Org
anB
ehav
Can
ada
135
nurs
es31
food
serv
ices
1ho
spita
l
Abs
ente
eism
(12
mon
ths
post
surv
ey–
hosp
italr
ecor
ds)
Gro
up-A
bsen
teei
sm(ƒ
&to
tald
ays
abse
ntfo
rea
chun
itfo
r12
mon
ths
prio
rto
surv
ey)
Per
ceiv
edab
senc
eno
rm(a
vera
ge#
ofda
ysot
hers
wer
eab
sent
durin
gpr
evio
us12
mon
ths
–se
lfre
port
)O
rgan
izat
iona
lCom
mitm
ent
(Affe
ctiv
e&
Con
tinua
nce
Com
mitm
ent:
Alle
n&
Mey
er19
90;
Mey
er&
Alle
n19
84,
1991
)2
addi
tiona
lcon
tinua
nce
com
mitm
ent
scal
esus
edIn
tera
ctio
nalJ
ustic
e(I
nter
actio
nalJ
ustic
eS
cale
:M
oorm
an19
91)
ƒ&
tota
lday
sM
ean
NR
8ite
m,
7pt
scal
e4
item
10ite
ms,
7pt
scal
e
r=
.58
&.2
6N
Rr
=.8
4a
=.8
6&
.72
a=
.65
&.5
5a
=.9
4
NR
NR
Prio
rE
xper
ienc
eN
RN
RN
R
Str
uctu
ral
Equ
atio
nM
odel
ing
M. M. Davey et al.
316 ª 2009 The Authors. Journal compilation ª 2009 Blackwell Publishing Ltd, Journal of Nursing Management, 17, 312–330
Tab
le3
Con
tinue
d
Aut
hor(
s)Y
ear
Jour
nal&
Cou
ntry
Sam
ple
Mea
sure
men
t/Ins
trum
ents
Sco
ring
Rel
iabi
lity
Val
idity
Ana
lysi
s
Gol
dber
g&
Wal
dman
2000
,J
Org
anB
ehav
US
A24
4nu
rses
&ot
her
(Onl
y98
abse
nce
reco
rds
obta
ined
)1
hosp
ital
Wag
eJo
bC
hara
cter
istic
s(n
otit
le,
noau
thor
)R
ole
Am
bigu
ity&
Con
flict
(no
title
:R
izzo
etal
.19
70)
Org
aniz
atio
nalP
erm
issi
vene
ss(n
otit
le:
Bro
oke
&P
rice
1989
)Jo
bS
atis
fact
ion
(no
title
:P
rice
&M
uelle
r19
81)
Abs
ente
eism
(sel
fre
port
edƒ,
time
lost
&re
cord
s-ba
sed
time
lost
)D
escr
iptiv
esH
ealth
Pos
ition
leve
lT
enur
eM
arita
lsta
tus
No
ofch
ildre
n
Equ
atio
n4
item
s,5
ptsc
ale
5ite
ms,
5pt
scal
e1
item
,5
ptsc
ale
3ite
ms,
5pt
scal
eƒ
&to
tald
ays
4pt
scal
eC
oded
scal
eN
RN
RN
R
NR
a=
.76
a=
.74
NR
a=
.86
NR
a=
.88
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
Par
tialL
east
Squ
ares
Roo
tM
ean
Squ
are
Res
idua
lS
quar
edm
ultip
leco
rrel
atio
n
Grif
feth
etal
.199
7,J
Man
age
Cou
ntry
NR
221
new
nurs
es1
hosp
ital
Rec
ruiti
ngS
ourc
es(n
otit
le:
noau
thor
)In
divi
dual
Diff
eren
ces
(App
lican
tQ
ualit
yIn
dex:
inte
rvie
w–
7di
men
sion
s)R
ole
Cla
rity
(no
title
:R
izzo
etal
.19
70)
Com
mitm
ent
toJo
bC
hoic
e(n
otit
le:
Col
arel
li19
84)
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Exp
ecta
tions
(no
title
:no
auth
or)
Cop
ing
(Ind
exC
opin
gE
ffect
iven
ess,
Dug
oni&
Ilgen
1981
)Jo
bS
atis
fact
ion
(no
title
:H
om&
Grif
feth
1991
;28
face
ts)
Abs
ente
eism
(did
not
atte
ndw
ork
whe
nsc
hedu
led
durin
g1s
tye
arof
empl
oym
ent)
Bla
nkre
spon
ses
4pt
scal
e6
item
s,5
ptLi
kert
Ave
rage
ofite
ms
2ite
ms
NR
NR
Tot
alda
ys
NR
a=
.86
a=
.83
a=
.79
a=
.82
a=
.93
a=
.94
NR
Mul
tiple
auth
ors
NR
NR
NR
NR
NR
NR
NR
Str
uctu
ral
Equ
atio
nM
odel
ing
Hac
kett
etal
.198
9,A
cad
Man
age
JC
ount
ryN
RP
hase
1:14
0nu
rses
Pha
se2:
54nu
rses
2ho
spita
ls(G
ener
al&
Ped
s)
Pha
se1
Que
stio
nnai
res
rega
rdin
gde
scrip
tive
wor
k-re
late
dat
titud
es,
valu
es&
stre
ssor
sof
thei
rpe
rson
nel
Incl
uded
self-
repo
rted
reas
ons
for
abse
nces
&at
tend
ance
(no
title
,re
sear
cher
mad
e)P
hase
2Q
uest
ionn
aire
for
each
shift
(4–5
mo)
tom
onito
roc
curr
ence
ofab
senc
e-re
leva
ntev
ents
(no
title
,re
sear
cher
mad
e)
NR
2-ite
ms
20ite
ms
NR
NR
a=
.30–
.97
NR
NR
NR
Prin
cipa
lC
ompo
nent
sM
ultip
leR
egre
ssio
n
Hem
min
gway
&S
mith
1999
,J
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upO
rgan
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chC
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2R
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4ho
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ccup
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nalC
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e(w
ork
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sure
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tono
my,
supe
rvis
or,
supp
ort
&pe
erco
hesi
onsu
bsca
les
ofW
ork
Env
ironm
ent
Sca
le;
Moo
s&
Inse
l197
4)R
ole
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flict
(no
title
:R
izzo
etal
.19
70)
Rol
eA
mbi
guity
(no
title
:R
izzo
etal
.19
70)
Wor
kloa
d(N
ursi
ngS
tres
sS
cale
,G
rey
etal
.19
81)
Dea
th&
dyin
gof
patie
nts
(Nur
sing
Str
ess
Sca
le,
Gre
yet
al.
1981
)A
bsen
teei
sm(s
hort
-ter
m,
2da
ysor
less
–se
lfre
port
ofpr
evio
us6
mon
ths)
10tr
ue/fa
lse
per
subs
cale
8ite
ms
6ite
ms
6ite
m,
4pt
scal
e7
item
sƒ
a=
.52–
.73
a=
.50
a=
.78
a=
.79
a=
.81
NR
NR
NR
NR
NR
NR
NR
Hie
rarc
hica
lR
egre
ssio
n
Staff nurse absenteeism
ª 2009 The Authors. Journal compilation ª 2009 Blackwell Publishing Ltd, Journal of Nursing Management, 17, 312–330 317
Tab
le3
Con
tinue
d
Aut
hor(
s)Y
ear
Jour
nal&
Cou
ntry
Sam
ple
Mea
sure
men
t/Ins
trum
ents
Sco
ring
Rel
iabi
lity
Val
idity
Ana
lysi
s
Par
ker
&K
ulik
1995
,J
Beh
avM
edU
SA
73R
Ns
1ho
spita
lB
urno
ut(M
asla
chB
urno
utIn
vent
ory-
3su
bsca
les:
Mas
lach
&Ja
ckso
n19
86)
Em
otio
nale
xhau
stio
nD
eper
sona
lizat
ion
Per
sona
lacc
ompl
ishm
ent
Abs
ente
eism
(#da
ysab
sent
inpa
st6
mon
ths
–se
lfre
port
&ho
spita
lrec
ords
for
46nu
rses
)
22ite
m,
7pt
scal
eN
RN
R›v
alue
s=
flbu
rnou
tƒ
a=
.78–
.90
NR
NR
NR
NR
NR
NR
NR
NR
NR
Mul
tiple
Reg
ress
ion
Sea
go19
96,
JN
urs
Adm
US
A67
nurs
ing
units
5ho
spita
lsW
orkg
roup
Cul
ture
(Org
aniz
atio
nalC
ultu
reIn
vent
ory:
Coo
ke&
Laffe
rty
1987
)W
orkp
lace
Str
ess
(Job
Con
tent
Que
stio
nnai
re:
Kar
asek
1979
)H
ostil
ity(C
ook
&M
edle
yH
ostil
ityS
cale
:C
ook
&M
edle
y19
54)
Abs
ente
eism
(per
cent
age
ofsh
ifts
not
atw
ork
assc
hedu
led
over
3m
onth
s–
hosp
italr
ecor
ds)
120
item
s,5
ptLi
kert
15ite
ms
50T
rue/
Fal
seite
ms
%
a=
.94
a=
.69–
.77
a=
.83
NR
Fac
tor
Ana
lysi
sN
RN
RN
R
Cor
rela
tion
Som
ers1
995,
JO
rgan
US
A30
3nu
rses
1ur
ban
hosp
ital
Org
aniz
atio
nalC
omm
itmen
t(A
ffect
ive,
Con
tinua
nce,
&N
orm
ativ
e–
notit
le:
Alle
nan
dM
eyer
1990
)Jo
bW
ithdr
awal
Inte
ntio
n(n
o-tit
le:
Blu
edor
n19
82)
Abs
ente
eism
(Tot
alab
senc
esdu
ring
a12
mon
thpe
riod
&A
nnex
edab
senc
es–a
ttach
edto
wee
kend
/ho
liday
perio
dsfo
rsa
me
12m
onth
s–
hosp
italr
ecor
ds)
NR
NR ƒ
a=
.71–
.81
a=
.88
NR
NR
NR
NR
Logi
stic
Reg
ress
ion
Tau
nton
etal
.198
9,JO
NA
US
A71
wor
kers
(59
RN
s)1
hosp
ital
Ret
entio
n(n
otit
le:
Pric
e&
Mue
ller
1981
)T
urno
ver
(no
title
:P
rice
&M
uelle
r19
81)
Job
Sat
isfa
ctio
n(n
otit
le:
Pric
e&
Mue
ller
1981
)In
tent
toS
tay
(no
title
:P
rice
&M
uelle
r19
81)
Opp
ortu
nity
Els
ewhe
re(n
otit
le:
Pric
e&
Mue
ller
1981
)S
ocia
lInt
egra
tion
(no
title
:P
rice
&M
uelle
r19
81)
Edu
catio
n(n
otit
le:
Pric
e&
Mue
ller
1981
)K
insh
ipR
espo
nsib
ility
(no
title
:P
rice
&M
uelle
r19
81)
Rou
tiniz
atio
n(n
otit
le:
Pric
e&
Mue
ller
1981
)P
artic
ipat
ion
(no
title
:P
rice
&M
uelle
r19
81)
Inst
rum
enta
lCom
mun
icat
ion
(no
title
:P
rice
&M
uelle
r19
81)
Pay
(no
title
:P
rice
&M
uelle
r19
81)
Dis
trib
utiv
eJu
stic
e(n
otit
le:
Pric
e&
Mue
ller
1981
)P
rom
otio
nalO
ppor
tuni
ty(n
otit
le:
Pric
e&
Mue
ller
1981
)A
bsen
teei
sm(T
ime
Lost
,A
bsen
ceS
pells
,1–
2da
yA
bsen
ceS
pells
)
%st
ayer
orle
aver
rang
e7–
35ra
nge
2–10
rang
e4–
17ra
nge
4–23
degr
eeor
high
erra
nge
2–6
rang
e4–
20ra
nge
4–20
rang
e7–
35N
AR
ange
3–18
Ran
ge8–
40ƒ
IRR
100%
IRR
100%
a=
.87
a=
.85
a=
.75
a=
.84
NA
NA
a=
.82
NR
a=
.90
IRR
100%
a=
.76
a=
.93
NR
All
fact
oran
alyz
edex
cept
last
varia
ble
NR
Cor
rela
tion
M. M. Davey et al.
318 ª 2009 The Authors. Journal compilation ª 2009 Blackwell Publishing Ltd, Journal of Nursing Management, 17, 312–330
Tab
le3
Con
tinue
d
Aut
hor(
s)Y
ear
Jour
nal&
Cou
ntry
Sam
ple
Mea
sure
men
t/Ins
trum
ents
Sco
ring
Rel
iabi
lity
Val
idity
Ana
lysi
s
Tau
nton
etal
.199
5,N
urs
Eco
nU
SA
1107
nurs
es4
chur
chho
spita
lsN
urse
Cha
ract
eris
tics
(9di
men
sion
s)W
ork
Invo
lvem
ent
(Kun
ungo
1982
)W
orks
full/
part
time
(<or
>32
hour
s/w
eek)
Hea
lthS
tatu
s(9
sub
scal
es:
War
e,19
76)
Opp
ortu
nity
Els
ewhe
re(P
rice
&M
uelle
r19
86)
Uni
tS
epar
atio
n(s
taye
ror
leav
er)
Mar
italS
tatu
sJo
bD
ecis
ion
Prio
ritie
s,W
ork
Env
ironm
ent
Res
pons
ibili
tyM
anag
erC
hara
cter
istic
s(3
dim
ensi
ons)
Pow
er(2
subs
cale
s:S
herid
an&
Vre
denb
urgh
1978
)In
fluen
ce(2
subs
ales
:M
och
etal
.19
83)
Lead
ersh
ipS
tyle
(2di
men
sion
s:K
ruse
&S
togd
ill19
73)
Org
aniz
atio
nalC
hara
cter
istic
s(5
dim
ensi
ons)
Dis
trib
utiv
eJu
stic
e(P
rice
&M
uelle
r19
81)
Pro
mot
iona
lOpp
ortu
nity
(Pric
e&
Mue
ller
1981
)C
ontr
olov
erN
ursi
ngP
ract
ice
(5su
bsca
les:
Hin
shaw
etal
.19
87)
Pay
Per
mis
sive
ness
Wor
kC
hara
cter
istic
s(4
dim
ensi
ons)
Rou
tiniz
atio
n(P
rice
&M
uelle
r19
86)
Aut
onom
y(H
insh
awet
al.
1987
)In
stru
men
talC
omm
unic
atio
n(P
rice
&M
uelle
r19
86)
Gro
upC
ohes
ion
(HIn
shaw
etal
.19
87)
Job
Str
ess
(no
title
:H
insh
awet
al.
1987
)Jo
bS
atis
fact
ion
(no
title
-8
subs
cale
s:H
insh
awet
al.
1987
)Jo
bIn
volv
emen
t(K
anun
go19
82)
Com
mitm
ent
(Pric
e&
Mue
ller
1986
)In
tent
toS
tay
(Pric
e&
Mue
ller
1981
)A
bsen
teei
sm(f
ailu
reto
repo
rtfo
ra
sche
dule
dda
yof
wor
k-to
tal#
1-da
yab
senc
esov
er6
mon
ths)
NR
NR
NR
NR
NR
NR
NR
NR
NR
ratio
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
NR
AN
OV
A
Dun
can
post
hoc
Pea
rson
Cor
rela
tion
Zbo
ril-B
enso
n200
2,C
anJ
Nur
sR
esC
anad
a10
79nu
rses
Mul
tiple
Acu
te&
Long
-Ter
mC
are
Abs
ente
eism
(Que
stio
nnai
re)
#of
abse
nces
,ƒ
of&
susc
eptib
ility
toab
sent
eeis
m,
rate
caus
es,
open
ende
dqu
estio
nson
inte
nt-t
o-le
ave
&re
com
men
datio
nsto
redu
ceab
sent
eeis
mJo
bS
atis
fact
ion
(no
title
;re
sear
cher
mad
e)
6ite
ms
5pt
scal
eP
ilote
dP
ilote
dP
ilote
dP
ilote
dC
hiS
quar
e
Staff nurse absenteeism
ª 2009 The Authors. Journal compilation ª 2009 Blackwell Publishing Ltd, Journal of Nursing Management, 17, 312–330 319
absenteeism is not an individual-level phenomenon, but
a socially constructed event.
Goldberg and Waldman (2000) amalgamated two
theories by Brooke and Price (1989) and Steers and
Rhodes (1978), to create a conceptual model. In short,
individual predictors (marital status, number of chil-
dren, health, tenure and position level) and situational
predictors (organizational permissiveness, role prob-
lems, pay and job characteristics) influenced both job
satisfaction and absenteeism.
Building on Morgan and Herman�s (1976) earlier
research, Hackett et al. (1989) discussed absenteeism as
a volitional behaviour in that employees choose whe-
ther or not they attend work. Zboril-Benson�s (2002)
followed Nicholson�s (1977) framework, which dis-
cussed attendance at work as a �normal� behaviour.
People attend work regularly, until absence-inducing
advents �interrupt the regularity of attendance� (p. 92).
Nicholson explained this theory using a continuum
from unavoidable to avoidable absences. The theoreti-
cal frameworks are summarized in Table 4.
Predictors of absenteeism
Using content analysis, a total of 70 independent vari-
ables (potential predictors) were categorized into eight
types of determinants: prior attendance, work attitudes,
retention, burnout and stress, manager characteristics,
human resource management practices, nurse charac-
teristics, and work and job characteristics (Table 5).
�Attendance� was defined as being present at work
when scheduled. Using structural equation modelling,
Gellatly (1995) and Gellatly and Luchak (1998) found
that perceived �absence norm� (what individuals thought
about the unit�s absenteeism rate) and �prior individual
absence� were significantly related to absenteeism. As
absence norms and prior absences increased, so did
absenteeism. However, group level absence was not a
predictor of individual absenteeism. Poor standing,
referring to previous attendance records (Hackett et al.
1989), was significant and positively related to nine out
of 51 nurses� desire to be absent, whereas significant and
negatively related to two out of 51 nurses� desire to be
absent. In addition, actual absenteeism significantly
increased for three out of 22 nurses and significantly
decreased for two out of 22 nurses when poor standing
increased.
�Work attitudes� refer to personal feelings or beliefs
associated with work, such as job and work involve-
ment, organizational commitment, group commitment,
occupational commitment and job satisfaction or dis-
satisfaction. Job satisfaction significantly predicted
absenteeism in three studies (Hackett & Guion 1985,
Taunton et al. 1989, 1995) in that as job satisfaction
increased, absenteeism decreased. Zboril-Benson (2002)
reported that as job dissatisfaction increased, self-re-
ported absenteeism increased.
The direct relationship of job involvement to absen-
teeism was not significant in two studies (Blau 1986,
Taunton et al. 1995); however, Taunton et al.�s study
showed a significant negative relationship of job
involvement and absenteeism if job involvement and
organizational commitment were both high. Cohen
(2000) reported that, as job involvement increased,
absenteeism significantly decreased. Cohen also de-
scribed a significant positive relationship between work
involvement and absenteeism. Job involvement differed
from work involvement in that �job involvement� de-
scribed a general attitude towards an organization as a
whole (Kanungo 1982). �Work involvement� described
how much the job can satisfy present needs (Kanungo
1982).
Five studies discussed the relationship between orga-
nizational commitment and absenteeism (Blau 1986,
Gellatly 1995, Somers 1995, Taunton et al. 1995,
Cohen 2000). Five out of 12 results were significant and
negatively related to absenteeism (Gellatly 1995, Som-
ers 1995, Taunton et al. 1995), indicating that the more
committed one was to the organization, the less one was
absent from work.
�Retention� refers to any type of attitude or behaviour
associated with staying or leaving the job, including
turnover, turnover intentions, intent-to-stay, promo-
tional opportunities and opportunities elsewhere. In
three studies, retention, intent-to-stay and promotional
opportunities were negatively and significantly related
to absenteeism (Taunton et al. 1989, 1995, Boumans &
Landeweerd 1994). Turnover was significantly and
positively related to absenteeism (Taunton et al. 1989).
Overall, retention factors were related to lower nurse
absenteeism.
�Burnout and stress� were grouped together because
the two concepts are closely linked. �Burnout is a syn-
drome of emotional exhaustion and cynicism that
occurs frequently among individuals who do �people
work� of some kind� (Maslach & Jackson 1981, p. 99).
Taunton et al. (1995) described two types of stress:
personal and situational. �Personal job stress� involves
�juggling multiple care expectations of various profes-
sionals as well as clients� (p. 228). �Situational job stress�involves �conflicting values between professional and
bureaucratic demands� (p. 228). One dimension of
burnout (personal accomplishment) was significantly
and negatively related to absenteeism (as personal
M. M. Davey et al.
320 ª 2009 The Authors. Journal compilation ª 2009 Blackwell Publishing Ltd, Journal of Nursing Management, 17, 312–330
Table 4Theoretical frameworks
Articles Theoretical framework
Goldberg &Waldman 2000
Brook & Price (1989) developed this model based on the work of Steers and Rhodes. Goldberg and Waldmanused the simplified model (drawn below) which includes only �those variables that were significantly relatedto absenteeism�. (Brooke & Price 1989, p. 12).
Path diagram of the causal model of absenteeism. (Brooke & Price 1989, p. 3).Hackett et al. 1989 Morgan and Herman (1976) conceptualized absenteeism in terms of two categories of consequences - deterrent
and motivating. Deterrent consequences, �can be controlled by the organization and are directly associated with the job(e.g., loss of pay, co-workers having to work harder)�. Motivating consequences �are controlled by the employee and arenot directly associated with the job (e.g., being absent to recover from illness or to have more leisure time)� (Morgan &Herman 1976, p. 738). They hypothesized that �employees will decide whether or not to attend work by weighing thedeterrent and motivating consequences of being absent�. (p. 173).
Zboril-Benson 2002 Nicholson�s (1977) theoretical framework assumes that attendance is a �normal� behavior (Zboril-Benson 2002).Nicholson characterized employee absence on an A–B continuum by identifying the avoidability of absence-inducingevents (Nicholson 1977, p. 231). A-type events are unavoidable (choice cannot influence absence) and B-type eventsare avoidable (employee has control over decision). This theory addresses the role that individual attributions play inabsenteeism (Zboril-Benson 2002, p. 92).
Gellatly 1995,Gellatly & Luchak1998
Nicholson and Johns (1985) developed this framework as a �set of shared understandings about absencelegitimacy…and the established ``custom and practice'' of employee absence behavior and its control�(Johns & Nicholson 1982, p. 136)
Absence culture depends on two factors (Nicholson & Johns 1985) – the level of trust and the salience of the culture tomembers (Gellatly & Luchak 1998, p. 1087).
There are 4 types of absence cultures; Type 1 (low salience & high trust); Type 2 (high salience & high trust); Type 3 (lowsalience & low trust); Type 4 (high salience & low trust).
�It can be hypothesized that more salient cultures have more extreme absence levels (high or low) and less variationamong employees than less salient cultures� (Nicholson & Johns 1985, p. 403).
Staff nurse absenteeism
ª 2009 The Authors. Journal compilation ª 2009 Blackwell Publishing Ltd, Journal of Nursing Management, 17, 312–330 321
accomplishment increased, absenteeism decreased).
Taunton et al. (1995) reported that as job stress
increased, absenteeism increased in one out of four
hospitals. Only one study measured workplace stress as
a predictor of nurse absenteeism (Seago 1996). In this
study, decision latitude (a dimension of workplace
stress) was negatively and significantly related to
absenteeism; however, decision latitude was not
defined. Overall, burnout and stress predicted increased
absenteeism.
�Manager characteristics� refer to traits or behaviours
such as leadership, influence and power, used by man-
agers to help guide staff members. Leadership was
examined in two studies. Leaders with high social and
high instrumental leadership or low social and low
instrumental leadership had the lowest rates of
employee absence (Boumans & Landeweerd 1993).
A significant negative relationship was reported – when
leaders showed consideration to employees, employee
absenteeism decreased. One manager characteristic
(influence in personnel resources) was significantly and
negatively related to staff nurse absenteeism in two out
of four hospitals. Overall, these few significant results in
this category suggest that relational leadership practices
of managers may reduce absenteeism.
�Human resource management practices� include
those policies, programmes or managerial activities
endorsed by the organization, such as distributive jus-
tice, pay, permissiveness, overstaffing, staffing ratios,
recruiting sources and control over nursing practice.
Taunton et al. (1995) showed that distributive justice
was significantly and negatively related to absenteeism
in one out of four hospitals. Pay was significantly and
negatively related to absenteeism in one study (Gold-
berg & Waldman 2000) but not in the others (Taunton
et al. 1989, 1995). Organizational permissiveness,
control over nursing practice, graduate nurse-filled full-
time equivalent (FTE) ratio and BSN-filled FTE ratio
were not significant predictors of absenteeism.
Overstaffing was significantly and positively related to
desired (18.9% of sample) and actual absenteeism
(0.5% of sample) (Hackett et al. 1989). As overstaffing
increased, the desire to be absent significantly decreased
for eight out of 10 nurses. Both the part-time staffing
ratio and recruiting sources significantly and negatively
predicted absenteeism. Overall, most results in this
category were not significant and no consistent pattern
was found.
�Nurse characteristics� in single studies were found to
be significantly related to nurse absenteeism: age, ten-
ure, marital status, education, position level, health,
disrupted sleep, doldrums, home responsibilities,
compassionate leave and unit separation. Doldrums
describe �low spirits, emotional and physical fatigue,
Table 4Continued
Articles Theoretical framework
Goldberg &Waldman 2000
Steers and Rhodes� (1978) theoretical framework premises employee attendance on two things – motivationto attend and ability to attend (Steers & Rhodes 1978, p. 392). Factors that affect an employee�s decision and ability tocome to work arise both from the individual (e.g., personal work ethic, demographic factors) and from the workenvironment (e.g., the job situation, incentive/reward systems, work group norms) (1978, p. 401).
Major influences on employee attendance (Steers & Rhodes, 1978).
M. M. Davey et al.
322 ª 2009 The Authors. Journal compilation ª 2009 Blackwell Publishing Ltd, Journal of Nursing Management, 17, 312–330
Table 5Predictors of absenteeism by category
Determinant Source
Significantrelationship
with absenteeism Comments
Prior attendancePerceived absence norm Gellatly & Luchak 1998 +
Gellatly 1995 +Prior individual absence Gellatly & Luchak 1998 +Group level absence Gellatly & Luchak 1998 NS
Gellatly 1995 NSPoor standing Hackett et al. 1989 + 9/51 staff (Desire to be absent)
) 2/51 staff (Desire to be absent)NS 40/51 staff (Desire to be absent)+ 3/22 staff (Actual absence)) 2/22 staff (Actual absence)
NS 17/22 staff (Actual absence)Work AttitudesJob satisfaction (JS) Goldberg & Waldman 2000 NS
Hackett & Guion 1985 )Taunton et al. 1989Taunton et al. 1995 ) Organizational JS & Hospitals C B & D
) Organizational JS in Hospital ANS Professional JS in all 4 hospitalsNS
Job dissatisfaction Zboril-Benson 2002 +Job involvement Blau 1986 NS
) Job involvement x CommitmentCohen 2000 ) Direct Model
NS Indirect Model ANS Indirect Model B
Taunton et al. 1995 NSWork involvement Cohen 2000 + Direct Model
NS Indirect Model ANS Indirect Model B
Organizational commitment (OC) Blau 1986 NS-Affective Commitment (AC)-Continuance Commitment (CC) Cohen 2000 NS-Normative Commitment (NC)
Somers 1995 ) AC & annexed absences) AC x CC & annexed absence
NS All subscales of OC & total absencesNS CC NC & AC x NC CC x NC &
annexed absenceGellatly 1995 ) AC & absence frequency (Models A & B2)
NS AC & absence frequency (Model B1)) AC & Total days absent (Model B1)
NS AC & total days absent (Models A & B2)NS CC & absence frequency & total days
absent (Models A B1 & B2)Taunton et al. 1995 ) Hospital B
NS Hospitals A C & DOccupational commitment Cohen 2000 NSGroup commitment Cohen 2000 NSRetention factorsRetention Taunton et al. 1989 )Turnover Taunton et al. 1989 +Turnover Intentions Cohen 2000 NSIntent to Stay Taunton et al. 1989 )
Taunton et al. 1995 NSPromotional Opportunity Taunton et al. 1989 NS
Taunton et al. 1995 )Boumans & Landeweerd 1994 NS Non-ICU nurses
) ICU-Nurses
Staff nurse absenteeism
ª 2009 The Authors. Journal compilation ª 2009 Blackwell Publishing Ltd, Journal of Nursing Management, 17, 312–330 323
Table 5Continued
Determinant Source
Significantrelationship
with absenteeism Comments
Opportunity Elsewhere Taunton et al. 1989, 1995 NSBurnout/StressBurnout Parker & Kulik 1995 ) Personal Accomplishment &
Hospital Record Sick LeaveNS Emotional Exhaustion depersonalization
& reported absenteeismJob Stress Taunton et al. 1995 NS
+Workplace Stress Seago 1996 ) Decision Latitude – a component
of workplace stressNS Psychological Demand – a
component of workplace stressManager CharacteristicsLeadership Boumans & Landeweerd 1993 NS Social & Initiating Structure (Leadership)
) Leader with ›social & ›instrumentalor flsocial & flinstrumental
NSBoumans & Landeweerd 1994Taunton et al. 1995 )
NSInfluence Taunton et al. 1995 NS All 4 hospitals (Work coordination
-manager influence variable)) Hospital C & D (Personnel resources
– manager influence variable)Power Taunton et al. 1995 NS Manager position (variable
included in power)NS Manager power
Human Resource Management PracticesDistributive Justice Taunton et al. 1989 NS
Taunton et al. 1995 ) Hospital DNS Hospital A B & C
Pay Goldberg & Waldman 2000 )Taunton et al. 1989, 1995 NS
Organizational Permissiveness Goldberg & Waldman 2000 NSTaunton et al. 1995 NS
Overstaffing Hackett et al. 1989 ) 8/51 staff (Desire to be absent)+ 2/51 staff (Desire to be absent)
NS 41/51 staff (Desire to be absent)+ 1/22 staff (Actual absenteeism)
NS 21/22 staff (Actual absenteeism)Graduate Nurse/ Filled FTE Ratio Taunton et al. 1995 NSBSN/Filled FTE Ratio Taunton et al. 1995 NSPart-Time/Filled FTE Ratio Taunton et al. 1995 ) Hospital C & D
NS Hospital A & BRecruiting Sources Griffeth et al. 1997 )Control Over Nursing Practice Taunton et al. 1995 NSNurse CharacteristicsAge Gellatly 1995 ) Model A B1 & B2 & absence frequency
NS Model A B1 & B2 & total days absentTaunton et al. 1995 NS
Tenure Goldberg & Waldman 2000 NSGellatly 1995 NS Model A B1 & B2 & absence frequency
+ Model A B1 & B2 & total days absentTenure Expectations Taunton et al. 1995 NSMarital Status Goldberg & Waldman 2000 NS
Taunton et al. 1995 ) For single & divorced people &only in Hospital B
NS Hospital A C & D
M. M. Davey et al.
324 ª 2009 The Authors. Journal compilation ª 2009 Blackwell Publishing Ltd, Journal of Nursing Management, 17, 312–330
Table 5Continued
Determinant Source
Significantrelationship
with absenteeism Comments
No. Children Goldberg & Waldman 2000 NSNursing Education Taunton et al. 1989 )
Taunton et al. 1995 NSPosition Level Goldberg & Waldman 2000 )Years in Profession Taunton et al. 1995 NSYears in Job Taunton et al. 1995 NSYears in Hospital Taunton et al. 1995 NSHealth Goldberg & Waldman 2000 )
Taunton et al. 1995 NS Current health) Resistance to illness) Rejection of sick role
NS Health outlookNS Sickness OrientationNS Health worry/Concerns) Prior health
NS Attitude toward going to physicianNS Drug use
Disrupted Sleep Hackett et al. 1989 + 2/51 staff (Desire to be absent)) 3/51 staff (Desire to be absent)
NS 47/51 staff (Desire to be absent)+ 5/22 staff (Actual absence)) 2/22 staff (Actual absence)
NS 17/22 staff (Actual absence)Doldrums Hackett et al. 1989 ) 36/51 staff (Desire to be absent)
NS 15/51 staff (Desire to be absent)+ 8/22 staff (Actual absence)
NS 14/22 staff (Actual absence)Home Responsibilities Hackett et al. 1989 + 8/51 staff (Desire to be absent)
) 3/51 staff (Desire to be absent)NS 40/51 staff (Desire to be absent)+ 1/22 staff (Actual absence)) 6/22 staff (Actual absence)
NS 15/22 staff (Actual absence)Kinship Responsibility Taunton et al. 1989 NSResponsibility Taunton et al. 1995 NSCompassionate Leave Hackett et al. 1989 + 4/51 staff (Desire to be absent)
) 3/51 staff (Desire to be absent)NS 44/51 staff (Desire to be absent)+ 2/22 staff (Actual absence)
NS 20/22 staff (Actual absence)Hostility Seago 1996 NSWorks Full-time/Part-time Taunton et al. 1995 NSJob Decision Priorities Taunton et al. 1995 NSUnit Separation (stayer/leaver) Taunton et al. 1995 + Hospital D
NS Hospital A B & CWork & Job CharacteristicsRoutinization Taunton et al. 1989, 1995 NSInstrumental Communication Taunton et al. 1989, 1995 NSWork Responsibilities Hackett et al. 1989 + 4/51 staff (Desire to be absent)
) 1/51 staff (Desire to be absent)NS 46/51 staff (Desire to be absent)+ 2/22 staff (Actual absence)) 1/22 staff (Actual absence)
NS 19/22 staff (Actual absence)Job Characteristics Goldberg & Waldman 2000 NSRole Ambiguity Goldberg & Waldman 2000 NSRole Conflict Goldberg & Waldman 2000 NSParticipation Taunton et al. 1989 NSSocial Integration Taunton et al. 1989 NS
ª 2009 The Authors. Journal compilation ª 2009 Blackwell Publishing Ltd, Journal of Nursing Management, 17, 312–330 325
Staff nurse absenteeism
and feeling down-trodden� (Hackett et al. 1989) How-
ever, in other studies many of these same characteristics
did not significantly predict absenteeism rates. For
example, Gellatly (1995) reported that as age increased,
absenteeism decreased. Taunton et al. (1995) found
that absenteeism was not related to age. Gellatly (1995)
also reported that as tenure increased, total days absent
increased. Goldberg and Waldman (2000) found no
relationship between tenure and absenteeism. Taunton
et al. (1995) found that being single or divorced nega-
tively and significantly predicted nurse absenteeism in
one out of four hospitals. Thus, no consistent pattern
between demographic characteristics and absenteeism
was shown in this review.
Two studies suggested a relationship between nurses�health and their absence rates. Goldberg and Waldman
(2000) reported that health was significantly and neg-
atively related to absenteeism. Taunton et al. (1995)
reported that in three out of four hospitals, as resistance
to illness increased, absenteeism decreased. Rejection of
the sick role and prior health were both significantly
and negatively associated to absenteeism.
�Work and job characteristics� were associated with
the work or job itself, and included routinization,
instrumental communication, work responsibilities, job
characteristics, role ambiguity, role conflict, participa-
tion, social integration, work group culture, group
cohesion, interactional justice, complexity/difficulty,
feedback/clarity, work pressure, autonomy, task allo-
cation and unit workload (see Table 5). The impact of
work responsibilities on absenteeism was equivocal –
some studies reported significant associations (Hackett
et al. 1989, Boumans & Landeweerd 1994, Taunton
et al. 1995), whereas other studies found no significant
associations (Taunton et al. 1989, 1995, Boumans &
Landeweerd 1994, Gellatly 1995, Seago 1996, Gold-
berg & Waldman 2000). This category of predictor
variables was not associated with staff nurse absentee-
ism.
Discussion
In Canada, absenteeism of front-line staff nurses is a
concern for administrators and health care organiza-
tions. CIHI (2005) denotes absenteeism as a current
issue in Canada, yet the majority of nursing and inter-
disciplinary healthcare research on absenteeism was
conducted in the United States. Studying the predictors
of nurse absenteeism in the Canadian context is
important because of differences in the US and Cana-
dian healthcare systems.
Predictors of absenteeism
Attendance (i.e. previous attendance and perceived
absence norm) was the best predictor of absenteeism,
with greater than 50% significant results. If perceived
absence norms, prior individual absence or poor atten-
dance records have been high, then current absenteeism
may increase, as absence cultures may develop. When
the culture supports poor attendance, future individual
attendance will align itself with cultural norms and
expectations (Nicholson & Johns 1985). This suggests
that it is important for administrators to screen prior
absence behaviour of potential employees and monitor
attendance behaviour of current employees for patterns
in absenteeism. Finding such attendance patterns will
allow administrators and researchers to implement
interventions in collaboration with individuals or
groups to improve absenteeism rates.
The CIHI (2005) reported that nurses rated unit
leadership and personal health as important predictors
Table 5Continued
Determinant Source
Significantrelationship
with absenteeism Comments
Work Group Culture Seago 1996 NSGroup Cohesion Taunton et al. 1995 )Interactional Justice Gellatly 1995 NSComplexity/Difficulty Boumans & Landeweerd 1994 NSFeedback/Clarity Boumans & Landeweerd 1994 NS Non-ICU nurses
) ICU nursesWork Pressure Boumans & Landeweerd 1994 NSAutonomy Boumans & Landeweerd 1994 NS
Taunton et al. 1995 NSTask Allocation Boumans & Landeweerd 1994 NSUnit Workload Taunton et al. 1995 NS
326 ª 2009 The Authors. Journal compilation ª 2009 Blackwell Publishing Ltd, Journal of Nursing Management, 17, 312–330
M. M. Davey et al.
of absenteeism, and therefore the results reported in this
review were expected to support this relationship. Yet,
work attitudes, along with characteristics of the man-
ager, organization, work and the individual nurse,
provided inconclusive and mixed results about the
predictors of staff nurse absenteeism. Less than half of
the results within each category were significant. Only
organizational commitment was significantly related to
lower absenteeism in three studies. Organizational
commitment has been shown to be influenced by work
environment factors, such as leadership style and
organizational culture (McNeese-Smith 1995, Zboril-
Benson 2002). This indirect effect may explain why the
majority of the direct relationships between work
environment factors and absenteeism were not signifi-
cant. The lack of theoretical frameworks on absentee-
ism in nursing that specifically address these indirect
effects may also have contributed to the gap between
what nurses report, how studies are designed and what
is actually measured.
It is also possible that methodological errors (sam-
pling technique, retrospective design, self-report data,
unit-of-analysis, etc) in the studies reviewed also
contributed to the non-significant results. Vigorous
research is needed in this area to discover and conclude
whether these characteristics are predictors of absen-
teeism.
Theoretical framework
One of the objectives of doing research is to build and
test theory. A theoretical framework helps guide the
method and intervention(s) appropriately. Initially,
absenteeism was conceptualized to be an individual
phenomenon. Steers and Rhodes� (1978) model
described a variety of factors that influence motivation
and ability to attend. Many researchers have studied the
hypothesized predictor variables in that framework, but
have not found strong relationships in the data. A recent
movement to look at absenteeism from an organiza-
tional perspective began with Chadwick et al. (1971)
and was later developed by Nicholson and Johns (1995).
Absence culture, from a social-networking standpoint, is
beginning to dominate the multidisciplinary world of
absenteeism. This implies that absenteeism may be so-
cially created within groups of people (friends, peers,
colleagues, etc.). From this social-exchange perspective,
absenteeism can be seen to be exchanged for negative
managerial behaviours. A social-exchange framework
suggests that �people enter into relationships to acquire
valuable resources� (Fuller & Hester 2006), which can
be material goods or social goods.
Shamian and El-Jardali (2007) discussed the impor-
tance of creating healthy Canadian workplaces to
reduce organizational outcomes such as absenteeism
and turnover. Theory must be tested and developed in
this area to determine if these variables consistently
predict absenteeism. Once predictors are identified, it
may be easier for administrators to implement inter-
ventions that foster healthy work environments to
promote attendance and reduce absenteeism.
The majority of included studies did not explicitly
follow a theoretical framework focused on absenteeism.
This may have been as a result of inadequate theoriza-
tion of nursing absenteeism as well as its determinants
and consequences. This is reflected in the number of
studies where absenteeism was examined as an ancillary
variable rather than as the primary focus of the study. In
order to advance this area of organizational behaviour,
refinement and development of existing theories are
needed to guide future research and interventions to
reduce absenteeism.
Absenteeism
Self-report, retrospective research designs may not be as
accurate as direct observation or recording owing to
unreliable memory or social desirability forces. Self-
report designs may lead to false–negative or false–posi-
tive results when potential for behavioural judgements
exist, influencing the significance of the relationships
found. In this review, self-report bias may have con-
tributed to type 2 error, leading to a false representation
of the number of non-significant results.
The focus of this review was on reported relationships
between measured predictors and individual absentee-
ism. Additionally, a large body of literature on absen-
teeism among nurses examined the influence of an
unmeasured intervention, such as a programme or
development session, to reduce nurse absenteeism.
These interventions/strategies may influence absentee-
ism and must be considered in future review studies.
This review has several potential limitations.
A reporting bias may exist as only published studies in
English were included and published studies tend to
over-report positive findings. The unit of analysis was
unclear in more than half of the studies, thus affecting
how the results were reported (group or individual) and
specific nurse outcomes may be contaminated with
outcomes from other healthcare professionals or con-
textual factors influencing the sample. We did not
conduct a meta-analysis because of the variation in
independent variables and the heterogeneity of this
group of studies. None of the studies in this review were
ª 2009 The Authors. Journal compilation ª 2009 Blackwell Publishing Ltd, Journal of Nursing Management, 17, 312–330 327
Staff nurse absenteeism
conducted in rural hospital settings, making rural con-
texts a current and important area to research.
Based on our results, several recommendations are
provided for healthcare organizations and researchers
interested in staff nurse absenteeism. First, researchers
and healthcare organizations should invest in long-term
partnerships to examine the root causes of nurse
absenteeism using longitudinal prospective designs and
robust theory. This will help both administrators and
researchers to understand possible predictors of absen-
teeism within the organization�s context.
Second, it is clear from this review that the predictors of
short-term nurse absenteeism are still largely unknown.
Well-designed studies, using solid theoretical frame-
works, must be conducted in order to accurately display
the variables that significantly influence absenteeism.
Structural equation modelling techniques (Gellatly 1995,
Griffeth et al. 1997) would provide information about
the causal relationships between specific organizational
and individual level determinants of absenteeism,
including both indirect and direct effects.
Third, many studies on absenteeism (both included
and not included in this review) rely on only self-report
data, or on past absenteeism records. Both of these
methods may increase error in the study results. To
strengthen the use of self-reported absence measures,
these measures can be verified through comparisons
with actual administrative data. Collecting data in real
time increases the accuracy of the results, thus reducing
bias and error (Hackett et al. 1989, Gellatly 1995,
Gellatly & Luchak 1998). Absence behaviour is also
only detected over time. Therefore, repeated longitudi-
nal data collections are necessary to observe trends or
changes in absenteeism behaviour. Developing part-
nerships between organizations and researchers may
give rise to analysis of anonymized prospective per-
sonnel absenteeism data without violating the privacy
of individual nurses. Analysing group absence by
aggregating individual measures would also provide
useful correlates with absence cultures and be less
threatening to individual nurses.
Fourth, random sampling increases the generaliz-
ability of the results and reduces convenient and
voluntary sampling bias. Random sampling was a
limitation in the majority of the papers included in this
review. It is difficult to use prospective sampling within
hospitals because random selection immediately reduces
the sample size; and, as the sample population is already
small, the effect size is limited. However, sufficient
capacity to conduct such research designs can be cre-
ated through partnerships between researchers and
large health regions/organizations.
Conclusion
In this systematic review, we examined and integrated
70 independent variables from 14 different studies into
eight predictive categories of absenteeism. Our findings
show trends toward individual nurses� prior attendance
records, work attitudes (job satisfaction, organizational
commitment and work/job involvement) and retention
factors reducing nurse absenteeism, with burnout and
job stress increasing absenteeism. However, our find-
ings suggest that research on hospital nurse absenteeism
provides no conclusive evidence about the predictors of
staff nurse absenteeism. As long as the predictors
remain unclear, efforts at dealing with the costly
problems associated with absenteeism will be less
fruitful. Future research should be conducted in Cana-
dian contexts to provide Canadian healthcare organi-
zations with generalizable information, to use
prospective and longitudinal designs and to be theory
driven, using or developing robust absenteeism theory.
Partnerships between researchers and Canadian
healthcare organizations and predictive theory about
the determinants of absenteeism in nursing would guide
the development of individual and organizational
interventions to address this costly issue for individuals
and organizations in order to improve the continuity
and quality of care for patients.
Acknowledgement
Peter Davey for providing much needed support throughoutthis review and assistance as a second reviewer.
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