FACTORS AFFECTING WORK ABILITY IN DAY AND

SHIFT-WORKING NURSES

Donatella Camerino,1 Paul Maurice Conway,1 Samantha Sartori,1

Paolo Campanini,1 Madeleine Estryn-Behar,2

Beatrice Isabella Johanna Maria van der Heijden,3 and Giovanni Costa1

1Department of Occupational and Environmental Health, University of Milano, andIRCCS Maggiore Hospital, Mangiagalli and Regina Elena Foundation, Milano, Italy2Service Central de Medecine du Travail Hopitaux Hotel Dieu AP-HP de Paris, Paris,France3Maastricht School of Management, Maastricht, the Netherlands, Open Universityof the Netherlands, Heerlen, the Netherlands; University of Twente, Enschede,the Netherlands

Satisfactory work ability is sustained and promoted by good physical and mental healthand by favorable working conditions. This study examined whether favorable andrewarding work-related factors increased the work ability among European nurses.The study sample was drawn from the Nurses’ Early Exit Study and consisted of7,516 nursing staff from seven European countries working in state-owned andprivate hospitals. In all, 10.8% were day, 4.2% were permanent night, 20.9% wereshift without night shift, and 64.1% were shift workers with night shifts. Participantswere administered a composite questionnaire at baseline (Time 0) and 1 yr later(Time 1). The Work Ability Index (WAI) at Time 1 was used as the outcomemeasure, while work schedule, sleep, rewards (esteem and career), satisfaction withpay, work involvement and motivation, and satisfaction with working hours at Time0 were included as potential determinants of work ability. Univariate and multivariateanalyses were conducted after adjusting for a number of confounders (i.e., country,age, sex, type of employment, family status, and other job opportunities in the samearea). Work schedule was not related to Time 1 changes in WAI. Higher sleepquality and quantity and more favorable psychosocial factors significantly increasedwork ability levels. Higher sleep quality and quantity did not mediate the effect ofwork schedule on work ability. No relevant interaction effects on work ability wereobserved between work schedule and the other factors considered at Time 0. As awhole, sleep and satisfaction with working time were gradually reduced from daywork to permanent night work. However, scores on work involvement, motivation,

Address correspondence to Donatella Camerino, Department of Occupational and Environ-mental Health, University of Milano, San Barnaba 8, 20122, Milano, Italy. Tel.: þ 39 02 50320159;Fax: þ39 02 50320150; E-mail: donatella.camerino@unimi.it

Chronobiology International, 25(2&3): 425–442, (2008)Copyright # Informa HealthcareISSN 0742-0528 print/1525-6073 onlineDOI: 10.1080/07420520802118236

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and satisfaction with pay and rewards were the highest in permanent night workersand the lowest in rotating shift workers that included night shifts. (Author correspon-dence: donatella.camerino@unimi.it)

Keywords Nursing staff, Work ability index, Shift work, Sleep, Psychosocial factors

INTRODUCTION

Background

Since 1870, there has been a gradual decline in the average annualworking hours in Europe, North America, and Australia (Maddison,1995), with some differences across countries in terms of the speed orintensity of the reduction. The importance of guaranteeing leisure timefor workers has been increasingly acknowledged, and in 1919, the prin-ciples of the 8 h work day and 48 h work week were adopted in theHours of Work Convention number 1 (International Labour Office,1919). Such progress was also accompanied by the recognition of the econ-omic value of leisure. The increased emphasis laid in Europe by tradeunions and enlightened employers toward shorter working hours wasmainly aimed at protecting workers’ health, preserving and/or creatingnew jobs, and more recently guaranteeing a better work-life balance.

Against this historical trend, the current nursing shortage in Europeoften requires healthcare organizations to overlook regulations concerningworking hours in an attempt to guarantee adequate coverage of vacantposts. This may lead to increased working hours and non-ergonomic plan-ning of work schedules (e.g., reduction of rest time between shifts, too manyconsecutive night shifts or weekends worked, low work-time predictability,etc.). Hence, the current nursing shortage may increase difficulties in facingshift-work-related problems, both for the nurses and for those in charge oftheir health and well-being, including employers.

Impact of Working Hours on Work Ability

A number of studies have concluded that inadequate work planning anda poorly organized work schedule may impact health. In particular, this mayresult in a reduced quantity and quality of sleep, a decline in cognitive andphysical performance and an associated increased risk for errors and acci-dents, and interference with family and social engagements (Akerstedt,2003; Dorrian et al., 2006; Eriksen & Akerstedt, 2006; Fitzpatrick et al.,1999; Oginska & Pokorski, 2006; Poissonnet & Veron, 2000). All of thesenegative consequences may be perceived by a worker as a reduction inhis/her capacity to perform his/her work (work ability). For this reason,work ability is seen as a relevant parameter to evaluate the impact of work

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schedules on individual health and performance (Takahashi et al., 2006).The disruption of circadian rhythms and sleep homeostasis (whichimplies both work tasks being carried out during sub-optimal physiologicalactivation and work breaks being taken in periods and in ways not suitablefor an adequate recovery) and unfavorable working conditions associatedwith shift work (such as lighting, temperature, an impoverishment of inter-personal relationships, and a reduction in the number of available services)may negatively influence the perception of one’s own work ability (Costaet al., 2004a; Foster & Kreitzman, 2004).

As for studies specifically addressing the relationship between workinghours and work ability, Costa et al. (2005) and Capanni et al. (2005) foundin their cross-sectional study of healthcare personnel that work ability asassessed by the Work Ability Index (WAI) decreased more steeply withage in shift compared to day workers. Fischer et al. (2006) observed intheir nursing study a significant association between sleep problems andWAI and also a dose-response relationship between fatigue and WAI.While in the univariate analysis, working one 12 h night shift followedby 36 h off was associated with a higher risk for inadequate WAI (,37 inthis study), in the fully-adjusted model (also including sleep), workability was not significantly associated with work schedule, suggesting apossible mediation of sleep in the relationship between work scheduleand WAI (even if Fisher et al. did not explicitly test for this hypothesis).

Psychosocial Characteristics and Shift Work: Interactive

Effects on Work Ability

Other studies have demonstrated that work ability is also linked to anumber of work-related psychosocial factors. These include mentaldemands, development opportunities, satisfaction with working time,interesting job, management style, and satisfaction with work prospectsand salary (Goedhard & Goedhard, 2005; Ilmarinen et al., 2005;Kerkhof et al., 2006; Sjogren-Ronka et al., 2002; Tuomi et al., 1991,2001). These factors can be considered to be consistent with Ilmarinen’set al. (2005) “fourth floor of the work ability house” (including physicaland psychological working characteristics). Ilmarinen et al. considergood work ability as an interactive process between the ‘fourth floor’ andthe three other floors or levels (i.e., health, competence, and values).Within this framework, work ability is determined by the demands ofthe situation and the perceived recourses available to meet them. Individ-uals derive a sense of self-mastery (Ben-Zur, 2002) in their “perceivedability to alter events” (Burger, 1989), a personal characteristic that mayenhance individual coping skills and thus the capacity to establish abalance between one’s resources and work demands (Ilmarinen, 2006).Accordingly, rewarding characteristics of the job may be considered as

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buffers against the negative effects on work ability related to shift work.Specifically, this means that for those experiencing higher compared tolower levels of rewarding job characteristics, the adverse impact of shiftwork on work ability may be reduced.

One limitation of the research examining the relationship betweenwork schedule and work ability is that it is mainly explored via cross-sec-tional designs, which reduces the ability to provide conclusive evidenceconcerning causal effects. To remedy this, our study used a prospectivedesign to examine causal relationships.

Study Hypotheses

The first aim of our study was to test the following hypothesis:At the 1 yr follow-up time, day workers, as compared to shift workers, with

favorable conditions, such as satisfaction with working hours, overall reward(and more specifically esteem and career reward), satisfaction with pay, and workinvolvement and motivation, demonstrate an increased work ability (H1).

Moreover, drawing upon Fischer et al.’s study (2006), we tested the fol-lowing hypothesis:

At the 1 yr follow-up, the quantity and quality of sleep will mediate the effect ofwork schedule on work ability (H2).

We earlier indicated the possible buffering effects of work that containsrewarding characteristics. Therefore, we also tested the followinghypothesis:

At the 1 yr follow-up, favorable conditions, such as quantity and quality of sleep,satisfaction with working hours, overall reward (and more specifically esteem andcareer reward), satisfaction with pay, and work involvement and motivation moder-ate the adverse effects on work ability potentially associated with shift-work (H3).

Finally, because perceived psychosocial factors may vary according towork schedule (Harma, 2006), we also evaluated if differences betweenshift patterns may exist in the rewarding components of the job, such assatisfaction with working hours, esteem and career reward, pay, andwork involvement and motivation.

MATERIALS AND METHODS

Sample and Procedure

The present study is based on data collected from the longitudinalNurses’ Early Exit Study (NEXT study). The study was conductedin several European countries between 2002 and 2004 and aimed atidentifying reasons to explain the premature departure from thenursing profession. The NEXT study complies with the ethical

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requirements of the journal (Touitou et al., 2006) and was approved cen-trally by the University of Wuppertal (Germany) and locally at eachnational study center.

In each country, participants were selected using a stratifiedsampling procedure to reflect the national distribution of nursingstaff by type of institution (hospital, nursing home, and homecareservice), geographical spread, and ownership (public or private). A pro-spective questionnaire-based design was used for data collection, and aself-administered questionnaire was distributed at baseline (Time 0)and follow-up (Time 1). The first assessment was done between October2002 and June 2003, depending on the countries’ study planning, whilein each case the follow-up assessment was conducted 1 yr after baseline.In most countries, questionnaires were sent to participants via theinstitution’s internal mailing system. On a few occasions, directposting to the participants’ home addresses was done; in these cases,a prepaid envelope was supplied for the return of the survey. Partici-pants were assured about their anonymity via a complex individualcode. The code was necessary to match cases over the two assessments.More detailed objectives and procedures of the NEXT study have beendescribed elsewhere (Hasselhorn et al., 2003, 2006).

The sample consisted of nursing staff only and excluded thoseholding management positions. The nurses were employed in state-owned and private hospitals in Belgium, Germany, France, Italy, TheNetherlands, Poland, and Slovakia. This case selection was done so asto increase homogeneity in working conditions. A total of 18,726replies were received at Time 0 and response rates varied between41.3–75.8% across the countries. At Time 1, some 7,516 replies werereceived, resulting in an overall response rate at follow-up of 41.7%.Those who did not respond at Time 1 included participants who lefttheir institution, were no longer able to take part in the investigationfor whatever reason, or had lost interest in the research. To ascertainif drop-outs from the study was selective, we ran several analyses on anumber of baseline variables to compare those who were respondentswith those who were non-respondents at follow-up. The proportion ofparticipants who dropped out from the study, compared to those whotook part at Time 1, was higher for the age group .45 yrs (20.4% vs.16.9%), for day workers (39.3% vs. 31.4%), for temporary contractworkers (9.8% versus 6.4%), and for those perceiving difficulty infinding a new job (64.2% vs. 56.6%), while it was lower for maleworkers (11.8% vs. 14.2%). These results suggest a possible selectionbased on the healthy worker effect, mostly if one considers that olderpeople, women, workers deemed not fit for shift work, temporary con-tract workers, and workers with low expectations of finding new jobs areusually those having the poorest health status. Finally, it should be noted

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that in the multivariate analyses, sample size decreased due to missingvalues for the variables considered.

Measures

Baseline Predictors

Work Schedule. For the present study, the responses to type of workschedules were categorized into day work, shift work without nights,shift work with nights, and night shift only.

Sleep. Sleep was assessed using four items. The questions ask therespondents to assess sleep quantity (two items) and sleep quality (twoitems). An overall sleep scale was created by calculating the mean of thefour items. The score of sleep quantity and quality scale ranged from 1to 5, with higher scores indicative of more restorative sleep. One missingitem per participant was tolerated for scale construction. For cases withone missing value, the mean of the remaining three items was substituted.The sleep quality and quantity scale obtained a Cronbach’s alpha of 0.78.

Reward. Reward was measured using the reward component of theEffort-Reward Imbalance Questionnaire (ERI-Q, Siegrist & Peter, 1996).The ERI-Q has been previously proven to have optimal (Siegrist et al.,2004) and predictive validity (van Vegchel et al., 2005). Reward wasmeasured by 11 items, covering three components of reward (i.e.,esteem reward, five items; career reward including job security, fiveitems; and pay, one item). The overall reward score, ranging from 11(“lowest reward”) to 55 (“highest reward”), was formed by summing upthe scores obtained on the eleven individual items. The scores of thereward components esteem reward and career reward ranged from 5(“lowest reward”) to 25 (“highest reward”). Two missing items per partici-pant were tolerated for scale construction. The individual mean calculatedon the data provided was used to replace missing values. The scales overallreward, esteem reward, and career reward obtained a Cronbach’s alpha of0.80, 0.76, and 0.64, respectively.

Satisfaction with Pay. Satisfaction with pay was assessed using a three-item measure (e.g., “How satisfied are you with your pay in relation to yourneed for income?”). Answers were given on a five-point scale ranging from“not at all satisfied” to “very much satisfied.” No missing items were toler-ated for scale construction. Cronbach’s alpha for this scale was 0.79.

Single-Item Questions. Satisfaction with working hours was assessedwith the following item: “All in all, are you satisfied with your workingtime with respect to your well being?” The response options were “yes”or “no.” Work involvement and motivation were assessed by the item:“Do you feel motivated and involved in your work?” Responses were

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made on a five-point scale (from “to a very small extent” to “to a largeextent”).

Outcome Measure

Perceived work ability was measured using the WAI (Ilmarinen &Tuomi, 2004). The total score was calculated by summing the scoresacross the seven items of the WAI (Tuomi et al., 1998). The range forthe total score was 7–49 points, with higher scores indicative of higher per-ceived work ability. Work ability was categorized using the original cut-offpoints: poor (7–27), moderate (28–36), good (37–43), and excellent (44–49). Internal validity of the WAI has been demonstrated (Eskelinen et al.,1991; Nygard et al., 1991), and the instrument has shown stable test–retestreliability (De Zwart et al., 2002). In this study, however, we adopted ashort version of the WAI. This version differs from the original WAIinstrument in that item three contains only 15 of the 51 medical conditionscontained in the full WAI, thus improving face validity. Nubling et al.(2004) developed an algorithm to allow comparability of the data obtainedby the two versions and found a good convergent validity.

Confounders

Based on the existing WAI literature (e.g., Tuomi et al., 1991) and alsoon other analyses of the data from the NEXT study (Hasselhorn, 2003),the following confounders were included: country, age (continuous),gender, type of employment contract (fixed/temporary), family status(living alone, living as the only adult with child/children, living withanother adult, living with another adult and child/children), and avail-ability of job alternatives (five response categories). For the presentstudy, the variable “availability of job alternatives” was dichotomized into“difficult finding job alternatives” and “easy finding job alternatives.”Age was entered in the regression model as a continuous variable. Usingage as a category and in a quadratic form did not provide a better fit tothe data.

Statistical Analysis

To test univariate associations between WAI at Time 0 and the otherstudy variables, AVOVA tests or Pearson’s bivariate correlations were com-pleted, depending on the scale of measurement. ANOVA or chi-squaretests were also conducted to evaluate the associations of work schedulewith sociodemographic and work-related factors. In the case of theANOVAs, we conducted Tukey’s post-hoc tests to test for homogeneoussubsets of means.

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A hierarchical linear regression model was fitted to test the multivariateeffects of the study variables on WAI at Time 1. Variables were enteredinto the regression model in four sequential steps. In Step 1, we intro-duced WAI at Time 0 and only the confounders (i.e., country, gender,age, family status, employment contract, and availability of job alternatives;job seniority was not included for its high collinearity with age) in order toassess the independent effect of predictors on WAI change over the twotime points. In Step 2, the study predictors measured at baseline (workschedule, satisfaction with working hours, overall reward [and esteemand career reward separately], satisfaction with pay, work involvementand motivation) were then entered into the regression model (H1). InStep 3, sleep quality and quantity was then entered to control for a possiblemediation effect of this variable in the relationship between work scheduleand WAI at Time 1 (H2). In the final step (Step 4), the interaction termswere added to the model (H3). Each interaction was tested in separateregression models (in Table 3, interactions are displayed together forspace reasons). F-change tests were calculated to assess the contributiongiven to the explanation of the outcome by each specific group of variablesincluded in the sequential steps. All analyses were conducted using the stat-istical package SPSS 14.0 (SPSS, Inc., Chicago, Illinois, USA).

RESULTS

Descriptive Analysis

As shown in Table 1, nearly one-third of the sample consisted ofnursing staff from Italy, while the other countries contributed between6.6% and 16.8% to the total sample. The overall sample was mainlywomen (85.8%), with age ranging from 18 to 63 yrs (20.1% were .45yrs of age) and job seniority in nursing ranging from 1 to 43 yrs. Morethan one-half of the nursing staff lived with another adult plus child/chil-dren (56.9%). The majority held a fixed job post (93.6%). As for work sche-dule, 10.8% were day, 4.2% permanent night, 20.9% shift without nights,and 64.1% shift with night work.

According to Table 1, WAI at Time 0 was significantly associated withall the baseline variables. Specifically, WAI was significantly lower innurses �45 yrs than in those �45 yrs (poor: 6% vs. 3%; moderate 28%vs. 23%; good 44.4% vs. 50.7%; excellent 21.7% vs. 23.3%) and lower inpermanent night workers compared to nursing staff involved in theother shift patterns, even after adjustment for age (F(3,6430) ¼ 3.0,p ¼ .03). Moreover, we did not find any significant interaction betweenage and work schedule on the WAI. WAI means at Time 0 and at Time1 were 39.0 (SD ¼ 5.7) and 39.2 (SD ¼ 5.5) and Pearson’s bivariate corre-lation 0.61 ( p , .001). We combined the four WAI categories into two by

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TABLE 1 Socio-demographic and Work-Related Characteristics of the Study Sample and AssociationsWith the Work Ability Index (WAI) at Time 0

Sample†

Variables (T0) N% or mean

(SD)

WAI (T0) meanor Pearson’s

bivariatecorrelation

Socio-demographic characteristicsCountry (%)Belgium 589 7.8% 39.4 (4.8)Germany 1025 13.6% 38.1 (6.1)France 953 12.7% 38.6 (5.3)Italy 2460 32.7% 39.8 (5.3)The Netherlands 730 9.7% 41.8 (4.8)Poland 1260 16.8% 37.6 (5.8)Slovakia 499 6.6% 40.0 (4.6)

F(6,6494) ¼ 58.84( p . .001)

Gender (%)Female 6448 85.8% 39.0 (5.5)Male 1063 14.2% 40.4 (5.4)

F(1,6496) ¼ 48.99( p . .001)

Age (mean) 7479 37.3 (8.1) r ¼ 2.13( p , .001)

Seniority in nursing (mean) 7465 14.5 (8.3) r ¼ 2.14( p , .001)

Family status (%)Alone 920 12.5% 39.1 (5.7)��

Only adult together withchild/children

404 5.5% 38.1 (6.2)�

With another adult 1853 25.1% 39.3 (5.6)��

With another adult and child/children 4199 56.9% 39.3 (5.4)��

F(3,6412) ¼ 5.16( p ¼ .001)

Work schedule (%)Day work 802 10.8% 39.2 (5.8)��

Shift work without nights 1560 20.9% 38.8 (5.7)��

Shift work with nights 4775 64.1% 39.4 (5.4)��

Only night shift 311 4.2% 38.4 (5.5)�

F(3,6451) ¼ 4.94( p ¼ .002)

Employment contractFixed 6996 93.6% 39.1 (5.5)Temporary 481 6.4% 40.1 (5.4)

F(1,6466) ¼ 12.04( p ¼ .001)

Availability of job alternatives (%)Difficult finding job alternatives 4208 56.1% 38.6 (5.7)Easy finding job alternatives 3221 43.9% 39.9 (5.3)

F(1,6427) ¼ 80.02( p ¼ .001)

(continued)

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adding the poor and moderate categories, and the good and excellent cat-egories. This showed that 23.1% of the sample experienced a change inWAI after the 1 yr time span; 10.8% improved and 12.1% decreasedtheir WAI.

As shown in Table 2, at baseline a slightly higher percentage of menthan women were involved in night work. Day and permanent nightworkers reported higher age and seniority in nursing. All study predictorswere associated with work schedule. In general, all predictor scores weresignificantly less favorable among the nursing staff working shifts, includ-ing nights. Interestingly, staff working permanent night shifts, whileshowing the poorest sleep (as expected) and the second lowest satisfactionwith working hours, reported the highest scores for reward (both foroverall reward and for esteem and career reward separately) and satisfac-tion with pay.

Multivariate Analysis

Table 3 reports the results of the hierarchical linear regression. Step 1included all confounders plus WAI at Time 0. This model significantlyimproved the explanation of WAI at Time 1 compared to a null modelwith no independent variables included ( p , .001). Working as a nursein The Netherlands, being younger, and living as the only adult with

TABLE 1 Continued

Sample†

Variables (T0) N% or mean

(SD)

WAI (T0) meanor Pearson’s

bivariatecorrelation

Study predictorsSatisfaction with working hours (%)

Yes 4853 66.2% 40.1 (5.10)No 2473 33.8% 37.3 (5.9)

F(1,6367) ¼ 405.68( p . .001)

Sleep (1–5) 7414 3.4 (0.8) r ¼ .33 ( p , .001)Reward (11–55) 7332 43.8 (8.1) r ¼ .31 ( p , .001)Esteem reward (5–25) 7394 212 (4.3) r ¼ .27 ( p , .001)Career reward (5–25) 7333 20.0 (4.2) r ¼ .26 ( p , .001)Satisfaction with pay (1–5) 7136 2.2 (0.9) r ¼ .15 ( p , .001)Work involvement and motivation (1–5) 7425 3.9 (1.1) r ¼ .23 ( p , .001)

Equal number of asterisks indicates homogeneity of means among groups according to Tukey’s post-hoc test (by country, the following homogeneous subsets were found: Poland–Germany, Germany–France, France–Belgium, Belgium–Italy–Slovakia, The Netherlands).

†Total number of cases may vary across variables owing to different number of missing values.

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children or with another adult with children (both compared to livingalone) were significantly related to an increase in WAI 1 yr later.

Overall, predictors included in step 2 significantly improved theregression model ( p , .001) compared to step 1, which only included theconfounders. A 1 yr increase in WAI was significantly predicted (afteradjustment for baseline WAI and confounders) by a higher work involve-ment and motivation, a higher satisfaction with pay, higher overallreward, and higher esteem and career reward at Time 0. However, inthe multivariate model, work schedule was not related to changes in WAIscores over the 1 yr interval considered. Note that work schedule was notrelated to changes in WAI even in a model with no adjustment for all theother variables entered in step 2 (analysis not shown in Table 3). Theseresults provide some support for the first hypothesis, with the onlyexception being work schedule and satisfaction with working hours.

TABLE 2 Prevalence (%) or Means (and Standard Deviation in Brackets) of Work-Related Variablesby Work Schedule

Work schedule

Socio-demographic andwork-related variables

Daywork

Shift workwithout nights

Shift workwith nights

Only nightshift

N (overall) 802 1560 4775 311Gender

Female 11.3% 21.3% 63.0% 4.4%Male 7.8% 18.7% 70.9% 2.6%

x2 ¼ 29.47 ( p , .001)Age (yrs) 40.4 (8.1)� 38.4 (8.6)�� 36.1 (7.7)��� 40.5 (7.8)�

F(3,7410) ¼ 102.68 ( p , .001)Seniority in nursing

(yrs)17.6 (8.1)� 15.5 (8.8)�� 13.5 (8.0)��� 17.6 (7.9)�

F(3,7393) ¼ 86.57 ( p , .001)Unsatisfied with

working hours16.0% 25.3% 39.7% 31.2%

x2 ¼ 232.14 ( p , .001)Sleep (1–5) 3.7 (0.76)� 3.5 (0.77)�� 3.4 (0.78)���� 3.2 (0.81)����

F(3,7351) ¼ 41.95 ( p , .001)Reward (11–55) 451 (7.86)� 44.9 (7.93)� 43.1 (8.14)�� 46.3 (6.53)���

F(3,7274) ¼ 38.06 ( p , .001)Esteem reward (5–25) 21.5 (4.1)� 21.3 (4.3)�/�� 21.1 (4.4)�� 21.8 (3.5)�

F(3,7333) ¼ 83.27 ( p ¼ .004)Career reward (5–25) 20.4 (4.2)�� 20.6 (4.0)��/��� 19.6 (4.3)� 21.2 (3.4)���

F(3,7279) ¼ 36.29 ( p , .001)Satisfaction with pay

(1–5)2.5 (0.91)� 2.4 (0.97)� 2.1 (0.88)�� 2.7 (0.86)���

F(3,7082) ¼ 94.44 ( p , .001)Work involvement

and motivation (1–5)4.0 (1.04)� 4.0 (1.03)� 3.8 (1.07)�� 4.2 (0.87)�

F(3,7358) ¼ 29.62 ( p , .001)

Equal number of asterisks across columns indicates homogeneity of means among groups accordingto Tukey’s post-hoc test.

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TABLE 3 Hierarchical Linear Regression Analysis for the Effects of Work-Related Variables (Time 0)on Work Ability Index (WAI) at Time 1

Variables b�

t p Model F change ( p)

Step 1WAI T0 .60 51.01 ,.001

Country (ref: The Netherlands)Germany 21.94 27.82 ,.001France 21.78 27.09 ,.001Italy 2.89 23.90 ,.001Poland 22.20 28.22 ,.001Slovakia 2.94 22.93 ,.001Belgium 21.40 25.10 .003

Gender (ref: male)Female 2.22 21.11 NsAge 2.04 25.40 ,.001

Family status (ref: alone)Only adult together with child/children .59 2.14 .03With another adult .22 1.05 NsWith another adult and child/children .50 2.57 .01

Employment contract (ref: fixed)Temporary 2.09 2.35 Ns

Availability of job alternatives (ref: easyfinding job alternatives)Difficult finding job alternatives 2.26 21.71 Ns F(14,5341) ¼ 246.05

( p , .001)Step 2Work schedule (WS) (ref: day work)

Shift work without nights .35 1.47 NsShift work with nights .15 0.70 NsOnly night shift 2.23 2.67 Ns

Satisfaction with working hours (ref:unsatisfied)

2.13 2.95 Ns

Reward (11–55)† .03 2.88 .01Esteem reward† .03 1.96 .05Career reward† .04 2.34 .02Satisfaction with pay (1–5) .31 3.79 ,.001Work involvement and motivation (1–5) .18 2.73 .006 F(7,5334) ¼ 7.82 ( p , .001)

Step 3Sleep (1–5) .39 4.29 ,.001 F(1,5333) ¼ 18.36 ( p , .001)

Step 4 (interaction)‡

Age � WS F(3,5330) ¼ 0.20 (ns)Satisfaction with working hours � WS F(3,5330) ¼ 1.92 (ns)Sleep � WS F(3,5330) ¼ 1.91 (ns)Reward � WS F(3,5330) ¼ 3.76 ( p ¼ .01)Esteem reward � WS F(3,5305) ¼ 2.08 ( p ¼ .04)Career reward � WS F(3,5280) ¼ 2.89 ( p ¼ .04)Satisfaction with pay � WS F(3,5330) ¼ 0.92 (ns)Work involvement and

motivation � WSF(3,5330) ¼ 1.22 (ns)

�Adjusted unstandardized regression coefficient.†Reward, esteem reward, and career reward were entered separately into the analysis: Step 2 model

with esteem reward: F-change(7,5308) ¼ 9.36 ( p , .001); Step 2 model with career reward:F-change(7,5283) ¼ 9.43 ( p , .001).

‡Each product term in Step 4 entered in separate regression analyses.

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The inclusion of sleep quality and quantity at Time 0 in step 3 signifi-cantly improved model fit ( p , .001), with a better sleep predicting anincreased WAI at Time 1 ( p , .001). Sleep did not play the hypothesizedmediation role between work schedule and WAI (second study hypoth-esis), but this is mainly attributable to the fact that work schedule, itself,did not show any significant impact on WAI.

According to step 4, only overall reward and the two reward com-ponents separately (esteem and career) significantly interacted with workschedule in predicting WAI at Time 1 ( p ¼ .01), indicating that the thirdhypothesis claiming an interactive effects between work schedule, on theone hand, and psychosocial factors and sleep, on the other hand, did notfind consistent support in the present study.

DISCUSSION

The first hypothesis of our study stated that among hospital nursingstaff working in seven European countries, work schedule and work-related psychosocial factors are related to changes in work ability over a1 yr time span.

In our prospective analysis, work schedule did not significantly predictchanges in WAI at Time 1. The lack of association between work scheduleand work ability 1 yr later may be partly attributed to the high inter-indi-vidual variability in tolerance to shift work (and consequently in its effectson health) due to both endogenous and exogenous factors (Costa, 2003).However, it should be noted that as far as the cross-sectional data of ourstudy are concerned, night work was linked with lower work ability evenwhen age was adjusted. This may suggest a possible cumulative effect ofnight work on work ability that cannot be seen within a 1 yr interval. Not-withstanding, work ability did not show any steeper age-related decreaseamong shift compared to day workers, thus not confirming results of pre-vious cross-sectional studies that found shift workers to report lower workability compared to day workers, with increased discrepancies occurringwith age (Costa et al., 2000, 2004b, 2005). This result may be accountedfor, at least partly, by the “healthy worker effect” acting at two possiblelevels: early retirement and selection of healthier nursing staff into lessfavorable shift schemes.

In our study, higher levels of work involvement and motivation, satis-faction with pay, esteem reward, and career reward were found to signifi-cantly increase work ability of the nursing staff at Time 1, though effectsizes were small. As for the psychosocial characteristics of the job, our find-ings complement results of previous studies involving non-nursing occu-pations in which work ability was found to be associated withpsychosocial aspects of the job, such as work stress, time pressure, jobcontrol, and leadership (Ilmarinen et al., 2005; Pohjonen, 2001; Salonen

Work Ability in Day and Shift-Working Nurses 437

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et al., 2003; Sjogren-Ronka et al, 2002). In addition, our prospective studysuggests that increasing rewards may promote a better work ability even ina short time frame of 1 yr.

Also, restorative sleep (both in terms of quality and quantity) was foundto be predictive of increased work ability, corroborating in a longitudinalperspective the association between good sleep and high WAI observedby Fischer et al. (2006) in their cross-sectional study. However, the hypoth-esized mediation effect of sleep on the relationship between work scheduleand work ability could not be confirmed, but this finding should be con-sidered to be inconclusive because, as previously stated, no main effectsof work schedule, itself, were observed.

As a whole, the third hypothesis concerning interactions was not sup-ported in our study. In fact, apart from overall reward (and also esteemand career reward separately), there was no consistent evidence for thehypothesized modification effect of sleep and psychosocial work character-istics on the relationship between work schedule and work ability. Thoughstatistically significant, the interaction between work schedule and rewardis not discussed, as it may be a chance finding.

Finally, our study also explored if levels of the potential predictors ofwork ability differed among nursing staff working distinct shift patterns.While sleep and satisfaction with working hours were lower in shift com-pared to day workers, nursing staff working permanent night shiftsreported the highest rewards. This is probably related to specific incentivesgiven by the organization that may have stimulated nursing staff to choosethis particular shift pattern. In contrast, personnel involved in rotatingshift schedules that included night work, which is the most usual shiftpattern among healthy nursing staff, reported the least rewards. Thenursing staff may suffer from a lack of voluntary choice of the type ofshift scheme they can work, but it may be also that they are not offered ade-quate incentives for their night duties.

Study Limitations

The main advantage of our study resides in its longitudinal design.This makes it possible to exclude the hypothesis that the causal relation-ship between WAI and the psychosocial factors is reversed; that is, thatwork ability determines the variation in psychosocial factors and not theopposite, as is commonly hypothesized (de Lange et al., 2005).

This study has some limitations, which should be taken into accountwhen interpreting results. The interval between the two data collectionsmay be too short to observe significant relationships between work charac-teristics and work ability. The obtained mean scores for the WAI werehighly similar across the 1 yr period. This would partly explain the lackof prospective association in our study between work schedule and WAI.

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The short time lag may also explain the reduced size of the regression coef-ficients due to the high stability of the outcome variable (Zapf et al., 1996).

A second limitation is that the work schedule was measured only atbaseline, which prevented us from tracking any changes to the work sche-dule at Time 1. It may be possible that some nurses changed their workschedule at Time 1, and the reported WAI score at this point reflectedthe new, rather than the original, schedule. Because the transition to daywork may be associated with increased work ability and transition to shiftwork to decreased work ability, differences in the outcome may bereduced if changes in work schedule occurred during follow-up.

Finally, the little evidence about interactions in our study may be partlyattributable to the fact that no main effects of work schedule on WAI wereobserved. The above discussed limitation concerning inadequate timeinterval between measurements may also apply to interactions, with theadditional limitation of measurement error that may increase in the pre-sence of interaction terms, with consequences on association strength.

CONCLUSIONS AND PRACTICAL IMPLICATIONS

These results support the emphasis posed by European policies onincreasing resources available to workers, such as sufficient time for ade-quate recovery, in order to protect their health and well-being. Moreover,they confirm the relevance of working conditions and adequate balancesbetween human resources and work for sustaining and promoting goodwork ability, and also the need to take career stages of the workers intoaccount and look at the different needs arising through age (Ilmarinen,2006).

Despite the current nursing shortage and its consequences on the plan-ning of work schedules, our study suggests that healthcare organizationsmay find ways to support the intention of nursing staff to stay at workand to continue working until pension age. This can be achieved by activat-ing a process aimed at guaranteeing a balance between demands andresources, mainly through dynamic, continuous, and suitable changes inworking conditions (Ilmarinen, 2006). Careful attention to restorativesleep, provision of job alternatives, and career rewards (also by means ofhorizontal career steps), plus an organizational climate supporting per-sonal recognition and more satisfactory pay (“fourth floor” factors accord-ing to the “work ability house”), are the main resources that, along with jobinvolvement and motivation (“third floor”), seem to be effective, also in ashort- to medium-term, for improving work ability among nursing staff.As job involvement and motivation could also be the result of favorableworking conditions, further studies with longer and repeated follow-upassessments could help in clarifying the relationship between working con-ditions, job involvement/motivation, and work ability.

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ACKNOWLEDGMENTS

The funding for NEXT was provided by SALTSA and the EuropeanCommission within the Fifth Framework, Project ID: QLK-6-CT-2001-00475, and was academically coordinated by Dr. Hans-Martin Hasselhornfrom the University of Wuppertal, Germany. Web site: http://www.NEXTuni-wuppertal.de.

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