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Occupational Medicine 2009;59:159–166

Published online 6 March 2009 doi:10.1093/occmed/kqp015

Shiftwork impacts and adaptation among health

care workers

James B. Burch1,2, Jasmine Tom3, Yusheng Zhai1, Lela Criswell3, Edward Leo3 and Kisito Ogoussan1

Background Shiftwork among health care workers impacts upon the safety and health of both employees and

patients.

Aims To characterize shiftwork-related attitudes, behaviours, symptoms and coping strategies among health

care workers, two validated questionnaires (the Standard Shiftwork Index and the Pressure Manage-

ment Indicator) were used to identify factors predicting shiftwork adaptation.

Methods Participants (n 5 376, response rate 25%) were grouped according to their work schedule (days,

permanent evenings, rotating days plus evenings, permanent nights or relief and combined shifts).

Indicators of lifestyle, work organization, sleep disruption, health and pressure management among

workers on irregular shifts were compared with participants on day shifts, after adjustment for gender,

age and marital status. Principal components analysis and ordinal logistic regression were used among

irregular shiftworkers to identify factors predicting schedule adaptation.

Results Night and relief/combined shiftworkers reported a greater ability to accommodate irregular schedules

and disrupted sleep, but were also more likely to report work-related impacts than day workers.

Permanent night workers generally reported poorer health, more absenteeism and less job satisfaction

than day workers. Factors associated with optimal work performance or schedule contentment among

shiftworkers included adequate sleep, evening circadian preference, increased age and organizational

satisfaction. Reduced work performance or schedule discontent was associated with sleep/wake

difficulties and poor health.

Conclusions This study confirmed previous research and identified factorsthat can be targeted for the development

of more effective shiftwork adaptation programmes in a health care setting (sleep timing and duration,

exercise and optimal health and organizational satisfaction).

Key words Circadian rhythm; medical care; nursing; shiftwork.

Introduction

The modern world depends on employees who work ir-

regular, round-the-clock schedules in critical work sectors

where the consequences of errors can be severe, such as in

the public transportation, utility, safety and health care

occupations. Working irregular shifts (shiftwork) has been

defined as a work schedule outside the customary 8.00

a.m. to 5.00 p.m., Monday to Friday working week. Night

workers tend to sleep more poorly and for shorter dura-

tions than their counterparts on day shifts [1], which can

lead to fatigue, daytime sleepiness, reduced alertness and

impaired job performance [1,2]. In addition to reduced

mental and physical well-being, irregular work schedules

can lead to social disruption and familial discord [2,3].

Irregular shifts are an integral feature of the health care

sector since many patients require continuous medical

care and monitoring, and because of personnel shortages,increasing numbers of health care professionals are re-

quired to work irregular hours. Almost 75% of nurses

in the USA participate in some form of shiftwork and

18% of nurses work night shifts consistently [4]. Occu-

pational stress due to shiftwork among health care pro-

viders contributes to burnout, reduced work efficiency,

poor performance, decreased job satisfaction, increased

rates of absenteeism and turnover, decreased quality

and quantity of care and ultimately to higher health care

1

Department of Epidemiology and Biostatistics, Cancer Prevention and ControlProgram, Center for Colon Cancer Research, University of South Carolina,

Columbia, SC 29208, USA.

2Dorn Department of Veteran’s Affairs Medical Center, Columbia, SC 29208,

USA.

3Department of Environmental and Radiological Health Sciences, Colorado State

University, Fort Collins, CO 80523, USA.

Correspondence to: James B. Burch, Department of Epidemiology and

Biostatistics, Cancer Prevention and Control Program, Center for Colon Cancer

Research, University of South Carolina, 915 Green Street, Room 228, Columbia,

SC 29208, USA. Tel: 11 803 576 5659; fax: 11 803 576 5624; e-mail:

[email protected]

Ó The Author 2009. Published by Oxford University Press on behalf of the Society of Occupational Medicine.All rights reserved. For Permissions, please email: [email protected]



costs [5,6]. Night work among health care workers is as-

sociated with difficulties performing routine tasks, lower

performance ratings or increased accident and injury

rates [7,8]. The impact of working irregular shifts can

contribute to a range of adverse health outcomes includ-

ing gastric ulcers, cardiovascular disease, depression, re-

productive disorders and cancer [7,9–11].

Strategies for coping with irregular work schedules

can be either detrimental or beneficial to worker health

[3,12]. It is still unclear whether shiftwork-related adverse

health outcomes are primarily due to unhealthy coping

strategies (e.g. long-term alcohol or tobacco use), chronic

alterations in physiological homeostasis, disruption and

desynchronization of circadian rhythms or to intrinsic

susceptibility factors that are more prevalent among

long-term shiftworkers. Consequently, there is a recog-

nized need for more research on specific shift-related

characteristics that have an adverse impact on health

and on how health care workers adapt to irregular work

schedules [3,13]. The objectives of this study were to

characterize work organization and attitudes, health be-haviours, coping strategies, health-related symptoms,

sleep characteristics and social and lifestyle factors

among health care workers on different shifts and to eval-

uate how these factors differ among those with irregular

schedules compared to those working permanent

days. Exploratory factor analysis and logistic regression

were then used to identify factors predicting shiftwork

adaptation.

Methods

Participants were employed at a regional medical facilitycomprising four campuses: a main hospital campus with

a Level II trauma centre, a family practice clinic with an

associated family medicine residency programme, an out-

patient facility that included a walk-in urgent care clinic,

breast diagnostic centre, imaging centre (ultrasound,

X-ray, computed tomography, magnetic resonance imag-

ing), satellite laboratory, outpatient surgery centre and

cardiac catheterization facility and a fourth campus with

an inpatient mental health facility and a neurodiagnostic

laboratory. Eligible employees were those working on any

campus in a department with both day and irregular

shifts. Self-administered questionnaires solicited infor-

mation on work, sleep, health and stress, in addition todemographic parameters [e.g. gender, age, body mass in-

dex (BMI), race/ethnicity, education and income]. The

Standard Shiftwork Index (http://www.workingtime.org)

[14] was used to acquire information on schedule char-

acteristics and attitudes towards work (41 items), sleep

and fatigue (33 items) and general health, well-being

and lifestyle (47 items). Circadian preference responses

(‘definitely a . . .’ and ‘more a . . .’) were combined to form

two groups: morning or evening types.

The Pressure Management IndicatorÓ (PMI, http://

www.resourcesystems.co.uk/pmi) was used to assess ma-

jor dimensions of occupational stress [15]. This 120-item

instrument uses Likert scale responses that are summa-

rized into 24 subscales characterizing stress inducers

(pressure from workload, relationships, career develop-

ment, managerial responsibility, personal responsibility,

home demands and daily hassles), job strain and stress

indicators (job satisfaction, organizational satisfaction,

organizational security, organizational commitment, anx-

iety/depression, resilience, worry, physical symptoms and

exhaustion) and stress moderators (drive, impatience,

control, decision latitude, problem focus, life work bal-

ance and social support). Following university and hospi-

tal Institutional Review Board approvals, questionnaires

were delivered to individual workplace mail compart-

ments with an introductory letter. Subjects were asked ei-

ther to rate their level of preference or agreement with

a question or to quantify personal or work-related factors

(e.g. hours of overtime work, sleep amount). No personal

identifiers were requested. The questionnaire was com-pleted either during work hours or on days off, and a min-

imum of 60 min was typically required for completion.

Completed questionnaires were returned anonymously

in sealed envelopes via drop boxes in several locations

at each facility.

Data were analysed using the SAS computer program

(SAS Institute, Cary, NC, USA). Participants were

grouped in one of five work schedule categories as follows:

permanent day shifts (work started between 4.30 and

9.00 a.m. and ended between 12.30 and 5.00 p.m.), per-

manent evening shifts (shift started mid to late afternoon

and ended by midnight), days plus evenings (rotating

schedule that included both previous categories), perma-nent nights (shift started mid to late afternoon and ended

the following morning) and relief or combined shifts,

which included those with variable schedules including

nights, evenings and days (e.g. 24-h on, 48-h off). Others

in the relief/combined category had long, variable shifts

(e.g. medical residents) or worked relief positions (on

call) with unpredictable hours that included nights. Par-

ticipants on day shifts served as the comparison group.

Initially, demographic or lifestyle characteristics among

workers on irregular shifts (evenings, days plus evenings,

nights, relief/combined) were compared to those on day

shifts using the generalized linear models procedure (con-

tinuous variables) or the Mantel–Haenszel chi-squaredstatistic with Fisher’s exact P -value (categorical varia-

bles). Average scores concerning work organization, sleep

disruption, health-related symptoms, occupational stress

and pressure management were compared similarly [16].

For continuous variables and Likert scale scores, least

squares means adjusted for gender, age and marital status

were calculated and responses among workers on day

shifts were compared to those on each of the irregular

shifts using the least significant differences statistic.

160 OCCUPATIONAL MEDICINE



A primary objective was to screen a wide variety of in-

dividual and work-related factors to identify those associ-

ated with schedule adaptation among the irregular

shiftworkers (day workers excluded, n 5 202). Explor-

atory principal components analysis was first used to

group predictor variables into factors [17]. Logistic re-

gression was then used to determine factors associated

with adaptation, which was defined by responses to three

questions: ‘Do you consider your work performance op-

timal on your current work schedule?’ (optimal perfor-

mance), ‘Are you content with your current work

schedule?’ (content with schedule) and ‘How well do

you adapt to changes in your work schedule?’ (schedule

adaptation). Principal components analysis was applied

to three groups of predictor variables: PMI subscale

scores (n 5 24), work characteristics (n 5 13) and sleep,

fatigue or coping items (n 5 17). Polychoric data trans-

formations were performed on non-continuous or non-

Likert scale data. Items with initial eigenvalues .1 that

contributed up to 70% of the total model variance were

subjected to a secondary principal components analysiswith varimax rotation. Variables were incorporated into

a given factor if the absolute value of the loading exceeded

0.5. Responses to tolerance questions were grouped into

three categories (disagree, neutral or agree, in ascending

order), and ordinal logistic regression was used (to ac-

commodate three levels of each response) to identify ad-

aptation predictors. Associations between tolerance

answers and factors were determined by computing odds

ratios (OR) with 95% confidence intervals (CIs), after ad-

justment for other factors in the model (Proc Logistic in

SAS, Type III sums of squares). Age, gender, BMI, race,

education and income were also included in each analysis.

Tests of proportional odds assumptions were satisfied.

Results

Approximately 1600 anonymous questionnaires were dis-

tributed and 401 (25%) were returned. Complete data

were available for 376 employees: 46% of respondents

worked day shifts, 7% worked evenings, 15% rotated be-

tween days and evenings, 19% worked permanent nights

and 12% worked relief or combined shifts. The average

age (39 years) and proportion of females (90%) and

non-Hispanic Caucasians (90%) among participants

were similar to the entire workforce (40 years and 82%

and 91%, respectively). Most participants were college

educated, married and worked full time (Table 1). Posi-tions held by permanent day or evening workers included

nurses, nursing assistants, transcriptionists (document

preparation from dictated recordings), secretaries, house-

keepers, unit assistants, radiology technologists, social

workers, laboratory technicians, medical technologists,

clerks, receptionists, patient service representatives, envi-

ronmental service technicians and operating room

Table 1. Characteristics of study population (n 5 376)

Characteristic Permanent days

(n 5 174)

Permanent evenings

(n 5 55)

Rotating days and

evenings (n 5 28)

Permanent nights

(n 5 73)

Relief or combined shifts

with nights (n 5 46)

Gender n (%)

Female 160 (94) 45 (87) 24 (92) 65 (89) 35 (76)**Male 11 (6) 7 (13) 2 (8) 8 (11) 11 (24)

Age (years)a 41 6 1 36 6 2 33 6 2** 38 6 2 39 6 2

Ethnicity

Caucasian, non-Hispanic 129 (74) 37 (67) 21 (75) 52 (71) 39 (85)

Non-Caucasian and Hispanic 45 (26) 18 (33) 7 (25) 21 (29) 7 (15)

Education n (%)

High school 13 (7) 6 (11) 2 (7) 5 (7) 5 (11)

Undergraduate 134 (77) 37 (67) 23 (82) 63 (86) 32 (69)

Graduate school 27 (16) 12 (22) 3 (11) 5 (7) 9 (20)

Annual income n (%)

,$39 999 53 (32) 21 (40) 8 (28) 19 (26) 10 (22)

$40 000–$59 999 44 (26) 17 (32) 5 (18) 32 (45)** 15 (33)

$$60 000 70 (42) 15 (28) 15 (54) 21 (29) 20 (45)Marital status n (%)

Married/live-in partner 132 (76) 34 (62)* 21 (75) 45 (62)* 33 (72)

Single, divorced, widowed 42 (24) 21 (38) 7 (25) 27 (38) 13 (28)

Work status n (%)

Full time 130 (75) 39 (71) 16 (57) 51 (70) 31 (67)

Part time 31 (18) 14 (25) 9 (32) 20 (27) 9 (20)

Other 13 (7) 2 (4) 3 (11) 2 (3) 4 (10)

aMean 6 SEM.

*P , 0.05 and **P , 0.01 compared with day shift. Percentages totalling ,100% are due to refusals or missing data.

J. B. BURCH ET AL.: SHIFTWORK ADAPTATION AMONG HEALTH CARE WORKERS 161



technicians. In addition to those listed above, workers on

rotating days plus evenings included: phlebotomists,

nurse managers and administrative coordinators. Perma-

nent night workers included transcriptionists, nursing as-

sistants, nurses, nurse specialists, operating room

technicians, clinical technicians, radiological technolo-

gists, laboratory technicians, medical technologists,

clerks and case managers. Relief shifts were staffed by fa-

cilities maintenance workers, nurses, nurse shift coordi-

nators, transcriptionists, patient registration clerks,

cardiovascular technicians, unit assistants, laboratory

processors, case managers, therapists, ultrasound techni-

cians, medical technologists and labour or delivery tech-

nicians. Workers in the relief or combined shift category

also included emergency medical technicians, paramedics

and family practice residents and faculty. The distribution

of age, gender and marital status among day workers dif-

fered from those on irregular shifts (Table 1). There were

no differences in consumption of cigarettes, alcoholic or

caffeinated beverages, BMI or access to different types of

eating establishments among irregular shiftworkers com-

pared with day workers (data not shown). Tables incor-

porating all results are provided as supplementary data

(available at Occupational Medicine Online).

Work characteristics and attitudes are summarized in

Table 2. In general, responses among workers on days

plus evenings tended to be similar to those on permanent

days. Those working other irregular shifts tended to re-

port less contentment with their work schedule, more

schedule-related disruption of social, recreational, do-

mestic or work activities, and shorter job durations com-

pared with those on day shifts and that their schedule

disadvantages outweighed the advantages. However,

these groups also tended to prefer working nights or un-

usual times (Table 2). The primary motivation for work-

ing irregular shifts was higher pay (Table 2). Participants

working evenings, nights or relief/combined shifts were

more likely to report impacts on sleep and had a greater

circadian preference for evenings compared to day work-

ers (Table 3). Night workers exhibited the greatest

Table 2. Work characteristics and attitudes among health care workers (n 5 376)a

Characteristic Permanent

days (n 5 174)

Permanent

evenings (n 5 55)

Rotating days and

evenings (n 5 28)

Permanent

nights (n 5 73)

Relief or combined shifts

with nights (n 5 46)

Overtime hours worked per week 2.26 0.6 1.7 6 0.8 4.7 6 1.1 1.3 6 0.7 4.5 6 0.8*Years working at present job 8.26 0.7 4.3 6 1.0** 5.5 6 1.4 5.6 6 0.9* 5.3 6 1.0*Content with current work schedule 4.0 6 0.1 3.6 6 0.2 3.9 6 0.2 3.7 6 0.2 3.5 6 0.2*

Advantages of work schedule

outweigh disadvantages

4.5 6 0.1 4.3 6 0.1 4.4 6 0.2 3.9 6 0.1** 3.5 6 0.1**

Performance is optimal on

current schedule

4.0 6 0.1 4.1 6 0.1 4.3 6 0.2 3.8 6 0.1 3.7 6 0.1

Work schedule does not affect

Exercise, sports 3.1 6 0.1 2.9 6 0.2 3.0 6 0.2 2.5 6 0.1**

2.8 6 0.2Work activities 3.5 6 0.1 3.3 6 0.1 3.6 6 0.2 3.1 6 0.1** 3.2 6 0.1*Social life 3.3 6 0.1 2.6 6 0.2** 3.4 6 0.2 2.5 6 0.1** 2.6 6 0.2**Domestic activitiesb 3.3 6 0.1 3.2 6 0.2 3.6 6 0.2 2.8 6 0.2** 3.0 6 0.2

Non-domestic activitiesc

3.1 6 0.1 3.5 6 0.2 3.5 6 0.2 3.1 6 0.1 3.1 6 0.2

Education/career development 3.06 0.1 3.0 6 0.1 3.3 6 0.2 2.8 6 0.1 2.8 6 0.1

Reason for current schedule

More convenient domestically 3.16 0.1 3.0 6 0.2 3.0 6 0.2 2.7 6 0.1* 2.7 6 0.2

Higher pay 2.0 6 0.1 2.8 6 0.2** 2.3 6 0.2 3.2 6 0.2** 2.6 6 0.2**Fits sleep schedule 2.8 6 0.1 2.5 6 0.2 2.7 6 0.2 1.8 6 0.2** 2.0 6 0.2**Job requirement 3.0 6 0.1 2.7 6 0.2 2.7 6 0.3 2.2 6 0.2** 3.4 6 0.2

Only job available 1.9 6 0.1 2.0 6 0.2 2.0 6 0.2 2.1 6 0.2 2.4 6 0.2*Required to switch shifts

with co-workers

2.1 6 0.1 2.2 6 0.1 2.1 6 0.2 2.3 6 0.1 2.6 6 0.1**

Can handle night work easily 3.16 0.2 2.9 6 0.2 2.6 6 0.3 4.2 6 0.2** 3.6 6 0.3

Prefer to work

Days, no night shifts 4.7 6 0.1 3.4 6 0.2** 4.5 6 0.3 3.2 6 0.2** 3.7 6 0.2**Days, occasional night shifts 1.9 6 0.1 2.1 6 0.1 1.8 6 0.2 1.9 6 0.2 2.1 6 0.2

Night shift only 1.4 6 0.1 1.7 6 0.2 1.2 6 0.2 3.3 6 0.1** 1.8 6 0.2*Rotating shifts (nights and days) 1.3 6 0.1 1.2 6 0.1 1.4 6 0.1 1.5 6 0.1 1.6 6 0.1*

aLeastsquares mean6SEMof quantity or score after adjustmentfor gender,age andmarital status.Higher scoresindicate more agreement with thestatementor a stronger

preference.

bActivities at home (e.g. house cleaning).

cNon-work activities away from home (e.g. shopping).

*P , 0.05 and **P , 0.01 compared with day shift.




tendencies towards poor health (Table 4). There were no

statistically significant differences in mean subscale PMI

scores for workers on irregular shifts compared to those

working days (data not shown).The principal components analysis identified 16 fac-

tors that were subsequently evaluated as potential deter-

minants of schedule adaptation. The factors (and the

questionnaire items they included) were: work schedule

(overtime hours and schedule changes on short notice),

work perceptions (organizational security, workload, rela-

tionships, recognition, organization climate, personal re-

sponsibility, managerial role, home/work balance and

daily hassles), organizational satisfaction (job and organi-

zational satisfaction and organizational commitment), job

duration (years at current job and smoking status), com-

muting (hours spent driving to/from work), family and

coping (number of dependents, partner support and al-cohol use), perceived stress (ongoing negative pressures),

health status (number of sick days within 3 months),

medications (number of prescriptions and non-steroidal

anti-inflammatory use), exercise (amount per week and

achieving the recommended amount), diet and perceived

health (self-rated calorie and fat intake, diet and fitness),

lifestyle and coping (daily caffeinated beverage intake and

average hours moderate physical activity at work and

home), rest (napping, tiredness and circadian

Table 3. Sleep characteristics among health care workers (n 5 376)a


days (n 5 174)

Permanent

evenings

(n 5 55)

Rotating days

and evenings

(n 5 28)

Permanent

nights (n 5 73)

Relief or combined

shifts with nights

(n 5 46)

Evening circadian preference n (%) 55 (32) 41 (75)** 8 (29) 49 (68)** 23 (53)**

Work schedule does not affect sleep 3.4 6 0.1 3.0 6 0.2* 3.3 6 0.2 2.0 6 0.1** 2.5 6 0.2**Can stay up late to finish

tasks without feeling tired

3.1 6 0.1 3.5 6 0.1 3.2 6 0.2 3.6 6 0.1** 3.3 6 0.2

Normally sleep well 3.2 6 0.1 3.0 6 0.2 3.6 6 0.2* 3.3 6 0.1 3.2 6 0.2

Can miss sleep without much difficulty 2.2 6 0.1 2.4 6 0.2 2.0 6 0.2 3.3 6 0.1** 2.6 6 0.2*

When waking early, feel tired all day 2.8 6 0.1 3.3 6 0.1** 2.8 6 0.2 3.0 6 0.1 3.1 6 0.2

aLeastsquares mean6SEMof quantity or score after adjustment forgender, ageand maritalstatus. Higherscoresindicatemore agreement with thestatementor a stronger

preference.


Table 4. Health status and symptoms among health care workers (n 5 376)a


days (n5

174)

Permanent

evenings (n5

55)

Rotating days

and evenings(n 5 28)

Permanent

nights(n 5 73)

Relief or combined

shifts with nights(n 5 46)

In good health n (%) 166 (95) 50 (91) 28 (100) 66 (90) 41 (89)

Number of sick leave days

past 3 months

0.4 6 0.7 0.2 6 1.0 0 6 1.3 2.4 6 0.9 0.9 6 1.0

Number of sick days taken due

to personal (not family) illness

0.2 6 0.7 0.1 6 1.0 0 6 1.3 2.3 6 0.9 0.8 6 1.0

Non-prescription medications n (%)

Acetaminophen (paracetamol) 33 (19) 12 (22) 5 (18) 19 (26)* 6 (13)

NSAIDs 78 (45) 14 (25)* 7 (25) 28 (38) 20 (43)

Caffeine tablets 2 (1) 0 (0) 0 (0) 0 (0) 1 (2)

Antacids 28 (16) 8 (15) 6 (21) 21 (29)* 8 (17)

Melatonin 4 (2) 0 (0) 1 (4) 4 (5) 1 (2)

Sleep aids 16 (9) 3 (5) 1 (4) 9 (12) 2 (4)

Physically fit compared to others 3.26

0.1 3.16

0.2 3.46

0.2 2.96

0.1*

3.06

0.2Often experience chest pain or tightness 1.5 6 0.1 1.5 6 0.1 1.5 6 0.2 1.6 6 0.1 1.4 6 0.1

Often have heart palpitations 1.8 6 0.1 1.9 6 0.2 1.6 6 0.2 2.1 6 0.2* 1.7 6 0.2

Often have gastrointestinal symptoms 3.1 6 0.1 3.1 6 0.2 2.5 6 0.3 3.8 6 0.2** 3.2 6 0.2

NSAIDs, non-steroidal anti-inflammatory drugs.

aLeastsquares mean6SEMof quantity or score after adjustment forgender, ageand maritalstatus. Higherscoresindicatemore agreement with thestatementor a stronger

preference.





preference), sleep amount (hours sleep needed and sleep

medication use), sleep timing (difficulty falling asleep and

waking up early) and mental well-being (state of mind,

resilience, confidence level, physical symptoms, energy

level and life/work balance).

Factors that were associated with optimal work perfor-

mance included increased age, fewer sick days and con-

structs related to sleep and rest (Table 5). Reduced

performance was associated with poor health, difficulty

falling asleep or early wakening and better performance

was associated with sleep aid consumption, an acknowl-

edged need for more sleep and a rest-related factor that

incorporated napping, lack of tiredness and evening

circadian preference (Table 5). When items in the rest-

related factor were evaluated separately, evening circadian

preference was the only item associated with a statistically

significant positive performance rating (OR: 2.26, 95%

CI: 1.00– 5.14). Factors that predicted ‘schedule content-

ment’ included a slightly elevated BMI, exercise and

greater organizational satisfaction and commitment

(Table 5). None of the evaluated factors were associatedwith ‘schedule adaptation’ (data not shown).

Discussion

This study found that night workers had more sick days,

non-prescription medication use (antacids and acetamin-

ophen or paracetamol), gastrointestinal complaints and

poorer self-rated fitness, which is consistent with previous

research [10]. Results among workers on rotating days

and evenings were generally similar to those among per-

manent day workers, which may suggest that this sched-

ule has fewer impacts and allows for better schedule

tolerance.In general, night and relief/combined shiftworkers

reported a greater tolerance to irregular schedules, even

though they were less likely to consider their current

schedule as advantageous. The primary motivators for

performing night or relief/combined shiftwork were in-

creased pay and work availability. A perceived ability to

tolerate irregular shifts coincided somewhat paradoxically

with greater impacts on sleep, fitness and health. This

suggests that schedule-related impacts were still occur-

ring, particularly among night and relief/combined shift-

workers, despite a tendency towards greater self-reported

schedule tolerance.

There is considerable variation in the ability of workersto adapt to irregular schedules. Factors previously linked

with shiftwork tolerance include sleep quality and flexibil-

ity, greater circadian rhythm amplitude or more rapid

phase resetting, positive mood, good health, an internal

locus of control, evening chronotype, less domestic dis-

ruption, more organizational support and the ability to

choose one’s schedule [2,3,18–25]. After screening and

consolidating 145 items addressing work organization

and attitudes, psychological and social factors, coping

strategies, as well as behavioural and lifestyle characteris-

tics, our analysis identified several factors associated with

shiftwork adaptation. Factors associated with adequate

sleep figured prominently in our results and were consis-

tent with previous studies among health care workers

[1,10,23]. Night workers commonly revert to a daytimeschedule on their days off, which can disrupt diurnal rest/

activity patterns. Forced sleep at inappropriate times dur-

ing the circadian cycle may result in shorter sleep duration

and greater fragmentation [1]. To adapt to a new sched-

ule, night workers typically realign their endogenous cir-

cadian phase to coincide with their rest/activity rhythm.

During this time, mismatches between endogenous circa-

dian timing and environmental cues (ambient light, social

interactions) can lead to disturbed sleep/wake timing, im-

paired performance and reduced safety. Irregular shift-

workers in our study who had difficulties falling asleep

or tended to wake up early were less likely to report op-

timal performance and were less content with their workschedule, whereas optimal performance was associated

with the use of sleep aids and an acknowledged need

for more sleep. The results also suggest that exercise

may help optimize performance, consistent with studies

demonstrating a beneficial effect of exercise on sleep

[26]. The results indicate a need to prioritize sleep timing

and duration in order to optimize job satisfaction and per-

formance. Strategies that can help achieve this include

napping, use of sleep aids, minimizing domestic noise

Table 5. Factors predicting schedule adaptation among health care

workers on irregular shifts (n 5 202)

Characteristic or factor Performance optimal on current

work schedule

OR 95% CI

Age 1.1 (1.0–1.1)Health statusa 0.6 (0.4–0.9)

Rest-related itemsb 1.6 (0.9–2.8)

Sleep timingc 0.5 (0.3–0.9)

Sleep amountd 1.7 (1.0–2.6)

Organizational satisfactione 1.6 (0.9–2.9)

Content with work schedule

OR 95% CI

BMI 1.1 (1.0–1.2)

Exercisef 1.5 (1.0–2.3)

Sleep timingc 0.7 (0.4–1.0)

Organizational satisfactione 1.7 (1.1–2.8)

aNumber of sick days within 3 months.

bTakes naps, not often tired, evening circadian preference.

cDifficulty falling asleep, wake up early.

dMore sleep needed, use sleep medication.

eMore job or organizational satisfaction, more organizational commitment.

f Get more weekly exercise, achieving the recommended amount.




and lighting and appropriately timed exposure to factors

that reset circadian phase, such as bright light, melatonin

ingestion or exercise.

The long-term health and well-being of workers on ir-

regular shifts hinges on their ability to adapt to the

impacts of their schedule. It is still unclear whether sched-

ules that induce frequent circadian rhythm phase shifts

facilitate better schedule tolerance [20,27] or lead to

rhythm desynchronization, schedule intolerance and ad-

verse health effects [19,28]. By understanding what fac-

tors predict shiftwork adaptation, more effective

strategies can be developed to foster optimal health

and performance. In this study, the association of in-

creased age with optimal work performance was consis-

tent with studies indicating that older workers have

more job satisfaction [29] and less fatigue, possibly due

to a survivor effect [2], or more seniority and greater de-

cision latitude. Evening circadian preference was another

characteristic that was more common among irregular

shiftworkers in this study, consistent with previous obser-

vations [18,23], and was linked with better performance.Circadian preference (chronotype) is associated with the

diurnal timing of numerous psychological and physiolog-

ical processes including sleep patterns and preferences,

subjective arousal and alertness, meal timing, body tem-

perature, blood pressure and secretion of melatonin, cor-

tisol and catecholamines [18,23,30]. Our results suggest

that intrinsic, environmental and lifestyle factors contrib-

uting to circadian preference may be further explored to

facilitate better shiftwork tolerance.

Interpretation of this study’s results is limited by the

cross-sectional, self-administered design. Also, a selection

bias may have been introduced due to the relatively low

response rate. However, demographic characteristics of participants were similar to those of the entire workforce.

Anonymous data collection avoided biased responses to

sensitive questions but precluded assessment of non-

respondents. Potential reasons for non-response range

from simple inconvenience to schedule- or health-related

issues. It is unknown whether this may have impacted the

identification of tolerance predictors. Study strengths in-

cluded the use of validated instruments and statistical ad-

justment for potential confounding. Although the

potential for confounding due to different job or worksite

characteristics, differential response rates among workers

on different shifts or other unmeasured factors cannot be

excluded, no differences were observed between day andirregular shifts for the proportion of full- or part-time

workers, job demand or satisfaction, organizational secu-

rity or satisfaction and personal or managerial responsi-

bility. A primary study objective was to screen a wide

range of individual and work characteristics to identify

predictors of shiftwork adaptation. Principal components

analysis was effective for this purpose since it allowed for

screening and consolidation of many variables into con-

ceptual groups (factors), facilitating a parsimonious anal-

ysis [17]. Also, by restricting these analyses to

shiftworkers only, potential biases due to differences be-

tween day and irregular shifts were eliminated.

This study characterized shiftwork-related attitudes,

behaviours, coping strategies and symptoms and explored

dimensions of self-reported shiftwork tolerance. Several

factors related to shiftwork adaptation identified in this

study (organizational satisfaction, adequate sleep, evening

circadian preference and age) were consistent with previous

research. Others (sleep timing and duration, exercise and

optimal health, organizational satisfaction and commit-

ment) represent modifiable targets for the development

of more effective schedule adaptation strategies among

health care workers on irregular shifts.

Funding

College Research Council of the Colorado State University Col-

lege of Veterinary Medicine and Biomedical Sciences; Career

Development Award from the U.S. Department of VeteransAffairs VISN-7 to Dr J.B.B.

Acknowledgements

The authors gratefully acknowledge Prof. Simon Folkard, Uni-

versity of Wales Swansea, Wales, UK, for allowing use of ques-

tions from the Standard Shiftwork Index and Resource Systems,

Harrogate, UK, for use of the PMI. The authors express their

gratitude to management and staff of Poudre Valley Hospital

(Fort Collins, CO, USA), particularly Yvonne Chudd and

Margo Karsten.

Conflicts of interestNone declared.

References

1. Rajaratnam SM, Arendt J. Health in a 24-h society. Lancet

2001;358:999–1005.

2. Winwood PC, Winefield AH, Lushington K. Work-related

fatigue and recovery: the contribution of age, domestic

Key points

• Shiftwork has been associated with health and

safety impacts among health care workers.

• Identification of factors predicting shiftwork toler-

ance can lead to the development of more effective

strategies for schedule adaptation.

• Modifiable targets for improving shiftwork adapta-

tion identified in this study included: sleep timing

and duration, exercise and optimal health and orga-

nizational satisfaction and commitment.




responsibilities and shiftwork. J Adv Nurs 2006;56:

438–449.

3. Costa G. Factors influencing health of workers and toler-

ance to shift work. Theor Issues Ergon Sci 2003;4:263–288.

4. Himali U. RN burnout: the hidden cost of hospital restruc-

turing. Am Nurse 1995;27:18.

5. AbuAlRub RF. Job stress, job performance, and social sup-

port among hospital nurses. J Nurs Scholarsh

2004;36:73–78.6. Edwards D, Burnard P. A systematic review of stress and

stress management interventions for mental health nurses.

J Adv Nurs 2003;42:169–200.

7. Berger AM, Hobbs BB. Impact of shift work on the health

and safety of nurses and patients. Clin J Oncol Nurs

2006;10:465–471.

8. Suzuki K, Ohida T, Kaneita Y, Yokoyama E, Uchiyama M.

Daytime sleepiness, sleep habits and occupational accidents

among hospital nurses. J Adv Nurs 2005;52:445–453.

9. Jamal M. Burnout, stress and health of employees on non-

standard work schedules: a study of Canadian workers.

Stress Health 2004;20:113–119.

10. DeMoss C, McGrail MJ, Haus E, Crain AL, Asche SE.

Health and performance factors in health care shift workers.J Occup Environ Med 2004;46:1278–1281.

11. Haus E, Smolensky M. Biological clocks and shift work: cir-

cadian dysregulation and potential long-term effects. Cancer

Causes Control 2006;17:489–500.

12. Kivimaki M, Paivi K, Virtanen M, Elovainio M. Does

shift work lead to poorer health habits? A comparison

between women who had always done shift work with

those who had never done shift work. Work Stress 2001;15:

3–13.

13. Trinkoff A, Geiger-Brown J, Brady B, Lipscomb J,

Muntaner C. How long and how much are nurses now

working? Am J Nurs 2006;106:60–71.

14. Barton J, Spelten E, Totterdell P, Smith L, Folkard S,

Costa G. The Standard Shiftwork Index: a battery of ques-tionnaires for assessing shiftwork-related problems. Work

Stress 1995;9:4–30.

15. Williams S, Cooper CL. Measuring occupational stress: de-

velopment of the pressure management indicator. J Occup

Health Psychol 1998;3:306–321.

16. Dawes J. Do data characteristics change according to the

number of scale points used—an experiment using 5-point,

7-point and 10-point scales. Int J Mark Res

2008;50:61–104.

17. Kleinbaum DG, Kupper LL, Muller KE. Applied Regression

Analysis and Other Multivariable Methods. Boston, MA:

PWS-Kent Publishing Co, 1988.

18. Tamagawa R, Lobb B, Booth R. Tolerance of shift work.

Appl Ergon 2007;38:635–642.

19. Reinberg A, Ashkenazi I. Internal desynchronization of cir-

cadian rhythms and tolerance to shift work. Chronobiol Int 2008;25:625–643.

20. Crowley SJ, Lee C, Tseng CY, Fogg LF, Eastman CI. Com-

plete or partial circadian re-entrainment improves perfor-

mance, alertness, and mood during night-shift work.

Sleep 2004;27:1077–1087.

21. Parkes K. Age, smoking, and negative affectivity as predic-

tor of sleep patterns among shiftworkers in two environ-

ments. J Occup Health Psychol 2002;7:156–173.

22. Smith L, Jeppesen HJ, Bøggild H. Internal locus of control

and choice in health service shift workers. Ergonomics

2007;50:1485–1502.

23. Paine SJ, Gander PH, Travier N. The epidemiology of

morningness/eveningness: influence of age, gender, ethnic-

ity, andsocioeconomic factors in adults (30–49years). J Biol Rhythms 2006;21:68–76.

24. Pisarski A, Brook C, Bohle P, Gallois C, Watson B,

Winch S. Extending a model of shift-work tolerance. Chro-

nobiol Int 2006;23:1363–1377.

25. Barton J. Choosing to work at night: a moderating influence

on individual tolerance to shift work. J Appl Psychol

1994;79:449–454.

26. Youngstedt SD, Kline CE. Epidemiology of exercise and

sleep. Sleep Biol Rhythms 2006;4:215–221.

27. Quera-Salva MA, Guilleminault C, Claustrat B et al . Rapid

shift in peak melatonin secretion associated with improved

performance in short shift work schedule. Sleep 1997;20:

1145–1150.

28. Reinberg AE, Ashkenazi I, Smolensky MH. Euchronism,allochronism, and dyschronism: is internal desynchroniza-

tion of human circadian rhythms a sign of illness? Chronobiol

Int 2007;24:553–588.

29. Ruggiero JS. Health, work variables, and job satisfaction

among nurses. J Nurs Adm 2005;35:254–263.

30. Roenneberg T, Kuehnle T, Juda M etal . Epidemiology of the

human circadian clock. Sleep Med Rev 2007;11:429–438.


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