Development and Validation of a Scale toMeasure Work-Related Fatigue and Recovery:The Occupational FatigueExhaustion/Recovery Scale (OFER)

P. C. Winwood, BDS, B Psych (Hons)A. H. Winefield, PhDD. Dawson, PhDK. Lushington, PhD

Objective: Various empirical studies link persistent failure to recoverfrom acute fatigue to the evolution of chronic fatigue. However, existingfatigue measurement scales do not tend to distinguish between acute andchronic fatigue elements well, and none include a measure of effectiverecovery from fatigue. Methods: The 15 item Occupational FatigueExhaustion Recovery (OFER) scale has been developed and validated inthree study populations specifically to measure work-related fatigue.Results: The OFER scale possesses robust, gender-bias free psychometriccharacteristics. Its three subscales identify and distinguish betweenchronic work-related fatigue traits, acute end-of-shift states and effectivefatigue recovery between shifts. Conclusion: These studies confirm themediating role of intershift-shift recovery in the evolution of adaptiveend-of-shift fatigue states to maladaptive persistent fatigue traits. TheOFER scale is suggested as a potentially valuable new tool for use inwork-related fatigue research. (J Occup Environ Med. 2005;47:594–606)

W ork-related fatigue is a source ofconcern in most industrialized coun-tries. Within the European commu-nity, it is reported that 40% ofworkers experience significant fa-tigue associated with an excessiveworkload on a daily basis.1 Similarconcerns have been reported fromNorway,2 Canada,3 the UnitedStates,4 and Sweden5; and in Japan,work-related death resulting fromoverwork (Karoshi) is considered asignificant occupational hazard.6,7

The consequences of work-relatedfatigue are significant, affecting na-tional and personal productivity,8–10

occupational health and safety,11–16

healthcare costs,17–19 and personalwell-being.20,21

There is agreement between au-thors that the most serious maladap-tive effects of occupational fatiguearise when it becomes chron-ic.12,22,23 Such fatigue has beendescribed as an enduring trait char-acterized by: “. . . inefficient actionpatterns; declining interest, involve-ment and commitment; reducedconcentration and motivation; andnegative emotions.”24 In Holland, amajority of chronic disability pen-sion recipients are categorized assuffering from chronic exhaustionassociated with work.25,26 However,the mechanisms by which normalacute fatigue states progress to mal-adaptive chronic fatigue traits remainincompletely understood.

Studies of human response tostress suggest that although the body/

From the School of Psychology, University of South Australia (Drs Winwood and Lushington); theCentre for Applied Psychological Research (Dr Winefield) and the Centre for Sleep Research (DrDawson), University of South Australia.

A copy of the OFER Scale may be requested via email from the author. The instrument may not beused or reproduced without author’s permission; permission for use in research studies is granted onthe understanding that OFER scale results will be shared with the author. For permissions e-mail:peter.winwood@unisa.edu.au or pwinwood@internode.on.net.

Address correspondence to: P. C. Winwood, c/o School of Psychology, University of South Australia,City East Campus, Frome Road, Adelaide 5000, South Australia; E-mail: peter.winwood@unisa.edu.au;pwinwood@internode.on.net.

Copyright © by American College of Occupational and Environmental Medicine

DOI: 10.1097/01.jom.0000161740.71049.c4

594 Validation of the OFER Scale • Winwood et al

mind complex can adapt to a widevariation in task demand, maintain-ing an adaptive response to stress/fatigue, however, depends on ade-quate recovery between successiveepisodes of such demands.27–32 Thissuggests that understanding recoveryfrom fatigue is as important as un-derstanding its causation. Althoughthere has been extensive researchinto the latter, the study of fatiguerecovery has received less attention.Some recovery from occupational fa-tigue may be achieved within theworkplace itself, during official workbreaks or spontaneous breaks be-tween tasks (microrecovery).33 Nev-ertheless, the majority of recoveryfrom work-related fatigue occurs inthe nonwork period between workshifts (intershift recovery). Conse-quently, understanding the genesis ofchronic occupational fatigue argu-ably demands a more completeunderstanding of nonwork-time ac-tivity, and its relationship to recoveryprocesses, than currently exists.There is a wide body of literatureexamining work/home conflict, forexample,34–36 but in the main, thisresearch has been limited to identify-ing the extent to which work stresshas a negative effect on home lifeactivity as opposed to the manner inwhich nonwork-time activities, athome, can moderate recovery fromthe stress/fatigue acquired at work.

Understanding the mediation andmoderation of fatigue recovery, how-ever, is hampered by the paucity ofinstruments with which to measurefatigue recovery, or its relationshipto acute (end of work) fatigue, andthe evolution of chronic fatigue.

Measuring Occupational FatigueThe term “fatigue” encompasses a

complex of multifactorial and over-lapping constructs with differenttemporal associations. Even after acentury of study, a comprehensivedefinition of fatigue has not beenarticulated, and it is clear that theabsence of an agreed definition haslimited the development of measure-ment tools.37 A solution to this di-

lemma followed the adoption bysome researchers, during the latterthird of the 20th century, of the broadparadigm that self-reported fatigueeffects may be measured, even if theunderlying psycho/physiologicalprocesses remain to be fullydescribed.

The commencement of this ap-proach can be traced, arguably, to theidentification of “burnout” as a mal-adaptive response to work stress/fatigue among human service work-ers by Freudenberger.38 Researchinto the “burnout” phenomenon re-sulted in the development of theMaslach Burnout Inventory (MBI),39

which has become the most widelyused instrument within fatigue re-search. However, it can be arguedthat “burnout” is not synonymouswith generalized chronic work-related fatigue. Burnout, as definedand measured by the MBI, is usuallyrelated to particular types of workwith high emotional demands ratherthan to work in general. Further-more, the exhaustion subscale of theMBI is structured to identify a quitespecific trait of chronic emotionalexhaustion among human serviceworkers and has not proved reli-able when applied across occupa-tions.40 – 43 Although a “general”form of the MBI has been developedfor use in occupations outside thehuman services field, the MaslachBurnout Inventory–General Scale(MBI-GS),44 its exhaustion subscaleremains unchanged from the originalMBI and is thus open to the samecriticisms.

The study of the fatigue phenom-enon within medically compromisedpatients has produced a great manyfatigue instruments,45–48 includingthe oldest of the currently used fa-tigue instruments, the “fatigue” and“vigor” subscales of the Profile ofMoods Scale (POMS), originally de-veloped for the assessment of psy-chiatric outpatients.49 The long listof “medical-fatigue” scales includesthose intended to measure the vexedcondition of chronic fatigue syn-drome (CFS)50: the Checklist Indi-

vidual Strength,51 the MultifactorialFatigue Inventory,52 the FatigueSeverity Scale (FSS),53 the FatigueAssessment Scale (FAS),54 and theFatigue Scale (FS).55 Although someauthors accept that CFS has a workor stress-related component in itsetiology, CFS is arguably also a dif-ferent construct from chronic work-related fatigue/exhaustion. Despitethis, instruments validated for mea-suring CFS are often used in work-related fatigue studies56–59 possiblybecause these instruments are avail-able, rather than because they areappropriate for the task. However,given the paucity of validated instru-ments for measuring work-related fa-tigue (specifically) across the fullspectrum of occupations, researchersmay experience difficulty finding in-struments that are appropriate. Onlythree extant instruments fall strictlywithin this category: the Swedish Oc-cupational Fatigue Inventory (SOFI),60

the Fatigue Assessment Scale (FAS),54

and the Need for Recovery FromWork scale (NRFW).61

The SOFI is limited to measuringphysical signs of acute postwork fa-tigue and is not appropriate forchronic fatigue assessment. By com-parison, the FAS is a measure ofsubchronic/chronic fatigue traitsarising from work, including bothperipheral and central effects. How-ever, like the SOFI, it does not in-clude any measure of recovery fromfatigue or encompass the interactionof acute fatigue states with chronicfatigue traits.

The NFRW, which is a subscale ofthe general Questionnaire on the Ex-perience and Evaluation of Workscale (QEEW),61,62 appears to ad-dress this issue. However, its veryhigh correlation of 0.84 with theexhaustion subscale of the MBIstrongly suggests that it a measure offatigue acquired rather than a mea-sure of recovery from such fatigue.61

Furthermore, this high correlationsuggests that neither the MBI nor theNFRW scales distinguish betweenchronic fatigue as an enduring traitand acute fatigue as a variable state.

JOEM • Volume 47, Number 6, June 2005 595

The main advantage of the NFRWscale is that is not limited to, ortargeted at, particular types of work.

In summary, it is evident that thereis a need for a simple instrument ableto measure and distinguish betweenchronic fatigue/exhaustion traits andacute (end of shift) fatigue states, andbe capable of measuring recoveryfrom work-related fatigue reliably.

It is hypothesized that persistentlow recovery from high levels ofacute fatigue is associated withhigher levels of chronic fatigue. Con-sequently, a significant and negativecorrelation between both chronic andacute fatigue scores, and recoveryscores, on the proposed instrument ispredicted. Furthermore, given thatacute work-related fatigue is princi-pally mediated through work-timefactors, and hypothesizing thatchronic fatigue is an evolving traitmediated by persistent low intershiftrecovery, a higher negative correla-tion between the proposed scale’srecovery scores and chronic fatiguescores is predicted.

This article describes the develop-ment and validation of such aninstrument.

Materials and MethodsAlthough there is no generally ac-

cepted definition of fatigue, the earlyobservations of Bartley63–65 that itrepresents a relative “incapacitation”after work activity suggested a phil-osophical base for selecting itemsrepresenting acute fatigue in the pro-posed scale. Namely, there are pa-thognomonic changes of behaviorand attitude that consistently accom-pany and discriminate between acuteand chronic fatigue, and recoveryfrom it. For example, the depletionof available energy by work activity(acute fatigue) produces consistentchanges in the ability to engage self-chosen nonessential tasks in non-work time. Thus, the self-report of anincapacity or unwillingness to en-gage in self-chosen pleasurable ac-tivities in nonwork time is arguablyrelated to the level of acute (post-shift) work fatigue.

In a similar way, a consistent re-port of feeling fully rested and func-tionally alert at the start of a workshift can be argued to indicate anadaptive level of recovery from fa-tigue acquired during the previousshift. By the same logic, the progres-sion of acute fatigue states to chronicfatigue traits is indicated by self-reports of doubt and despair in thecapacity to maintain current workpatterns; declining interest, involve-ment, and commitment; reducedconcentration and motivation; andnegative emotions,66 combined withphysical manifestations of persistenttiredness, these being the consis-tently reported descriptors of chronicfatigue.24 Interestingly, this clusterof symptoms is consistent with thedescriptors of depression listed in theDiagnostic and Statistical Manual ofMental Disease, 4th Edition.67 Thepossibility that changes in centralnervous system structure and func-tion, that are known to be associatedwith the persistently high allostatic(neuroendocrine) load, resultingfrom unrelieved stress, mediate thedepressive symptomology character-istic of chronic work-related fatigueremains to be fully explored.31,68–70

Based on theory, and after exam-ining the fatigue literature and exist-ing fatigue measures, 30 items withstrong face validity were chosen toform the basis of the proposed instru-ment. In particular, items that wereanticipated to form a chronic fatiguesubscale included several intended toidentify the element of depression.

The literature suggested that a sev-en-point Likert response scale from0–6 would yield a measurement ofsufficient sensitivity for respondingto a series of statements about acutefatigue, chronic exhaustion, and re-covery between the limits of com-pletely disagree to completely agree.A 0–6 scale was chosen to expeditethe computation of subscale scoresas a comparable quotient between 0and 100 by the formula [sum (scalescores)/(n items in scale � 6)] �100.

Various studies have pointed tothe significance of scale item keying.Failure to include both negative andpositively keyed items has been sug-gested to lead to artificial factorsolutions and are inferior to unidirec-tional scales such as the MBI.71,72

On the other hand, Schmitt73 hassuggested that negatively keyeditems answered in error by carelessrespondents as if they were posi-tively keyed may also result in arti-ficial solutions. On balance, it wasdecided to include (10/30) negativelykeyed items in the original scale itemlist but not insist on an equal splitbetween positive and negativekeying.

Exploratory (Pilot) StudiesTo select items from the initial

30-item pool into factors that re-flected the proposed scale’s inten-tion, two substantial pilot studieswere undertaken in: 1) a populationof 247 (88% female) nurses and 2) apopulation of 232 (92% male) quarryworkers. The significant gender dif-ference between the populations en-abled any gender bias in the scale tobe identified. Analysis of these pilotstudy results by means of principlecomponents factor analysis (not re-ported here in the interests of brev-ity) indicated that 20 of the 30 initialitems formed three identifiable fac-tors of chronic fatigue, acute fatigue,and (intershift) recovery, as in-tended. Of note, the items selected toform the chronic fatigue subscaledemonstrated convergent validitywith the exhaustion subscale of theMBI (0.69) and with the CIS scale(0.53). These correlations were re-garded as both significant and appro-priate given the different fatiguecharacteristics measured by thesescales (emotional and global, respec-tively). No significant differences inresponding patterns indicating gen-der bias were evident. On the basis ofthese encouraging results, a potential20-item scale was tested in a large-scale study.

596 Validation of the OFER Scale • Winwood et al

Validation Study

MethodA large-scale study among nurses

at an Australian metropolitan hospi-tal was undertaken to confirm the psy-chometric properties of the proposedinstrument, which was tentativelynamed the Occupational Fatigue Ex-haustion Recovery (OFER) scale.Study questionnaires were distrib-uted by attachment to the payslips ofall 1600 nurses in this hospital in thesame pay period.

ParticipantsA total of 770 respondents re-

turned completed questionnaires,representing a response rate of 48%.Given the distribution method, non-response analysis was not possible.Mean age (standard deviation [SD])of participants was 38.9 (10.5) years,of whom 87% (n � 671) identifiedas female. Full-time working partic-ipants comprised 82% (n � 632) andthe mean (SD) total hours workedwas 35.3 (10.9) hours. Among allrespondents, 73% (n � 580) workedsome combination of multiple shifttypes (early, late, and nights); theremainder worked only one shifttype (usually early or day shift).

MaterialsA comprehensive questionnaire,

including the 20-item OFER scale tobe tested, was distributed in an enve-lope, which also contained an ex-planatory letter and a reply-paidenvelope. The study questionnaireincluded validated scales with whichto measure constructs believed to beassociated with both fatigue and re-covery from fatigue so as to deter-mine their correlation with the OFERscale factors.

Physical and emotional healthwere measured using the NottinghamHealth Profile,74 which is a well-validated, weighted, “quality-of-life”measure having several subscales,including energy level, sleep health,emotional health (particularly indi-cating depressive symptomology),

social isolation, and functionalhealth.75,76

Sleep quality and efficiency wasassessed with the Pittsburgh SleepQuality Index, which is a well-validated measure of sleep factorsthat has demonstrated significantsensitivity and specificity is discrim-inating sleep problems between in-somniacs and normals.77,78

Six measures of work-demandcharacteristics (work pace, mentaldemand, emotional demand, physicaleffort, peer support, and supervisorsupport) were assessed with relevantsubscales from the Questionnaire onthe Experience and Evaluation ofWork (QEEW) scale.62

Given that a high convergent va-lidity of the OFER chronic fatiguesubscale had already been estab-lished in the pilot studies, the inclu-sion of other exhaustion scales suchas MBI, CIS, or NFRW in the ques-tionnaire was regarded as unneces-sary. However, self-reported fatiguelevels typically experienced by par-ticipants both at the beginning ofshifts, and after shift completion,were measured using 0–6 visual an-alog scales bounded between the pa-rameters of “completely rested” and“completely exhausted.”

Test/Retest of the OccupationalFatigue Exhaustion RecoveryScale Responses

To establish the test/retest reliabil-ity of the OFER scale, an item in thequestionnaire requested respondentsto provide the researchers with ane-mail, or other contact address, ifthey were willing to take part in ashort follow-up study. A total of 308respondents agreed to this request,and 281 provided valid e-mail ad-dresses for this purpose.

Power of the StudyWith an N of 770, G-power anal-

ysis79 reported the power of thestudy to be 0.85 to detect a (small)0.03 effect size with an alpha valueof 0.01 in multiple regression analy-sis with up to eight predictors, and

0.85 to detect a (small) 0.15 effectsize with an alpha value of 0.01 incorrelation t tests. The N of 770 alsoensured a case/item ratio of nearly40:1 for the purposes of exploratoryand confirmatory factor analysisand ensured that the maximum num-ber of predictors could be validlytested simultaneously in regressionanalyses.

Results

Data Reduction Factor AnalysisAnalysis of the dataset for the 20

items of the OFER scale gave aKeyer-Meyer-Olgin value of 0.94,and the Bartlett Test of Sphericity(�2 [190] � 8242.9), indicating thatthe dataset was adequate for analysis.Principal components analysis withvarimax rotation and Kaiser normal-ization was undertaken. After exam-ining the scree plot, a minimum item/factor correlation of 0.52 wasspecified as the cutoff point for sig-nificance in the analysis, which re-sulted in two of the 20 items failingto reach significance. Table 1 reportsthe rotated solution of this analysis.

Three factors emerged from theexploratory factor analysis, which to-gether explained a significant 59% ofvariance. Each of these factors wasreadily identifiable from their facevalidity and their correspondence toitems identified in the exploratorystudies. These factors were:

Factor 1—Chronic Fatigue/Ex-haustion (OFER-CF). Comprising10 items with a minimum item/factorcorrelation of 0.55, this factor wasidentified as chronic fatigue. Theitems forming this factor were iden-tical to those emerging in the pilotstudies, and the face validity of thisfactor quite clearly suggests chronic,persistent fatigue/exhaustion com-prising both mental and physical el-ements. In addition, several of thecomponent items capture the depres-sive element of the chronic fatiguetrait appropriately. Fatigue identifiedby this factor is quite specificallyassociated with work, rather than ageneral and nonspecific fatigue state

JOEM • Volume 47, Number 6, June 2005 597

such as that identified by the CISscale, and the medical models offatigue. The reliability coefficient ofinternal consistency (Cronbach’s al-pha) for the chronic fatigue factorwas 0.93.

Factor 2—Acute Fatigue (OFER-AF). Comprising five items with aminimum item/factor correlation of0.54, this factor has a reliability co-efficient of internal consistency(Cronbach’s alpha) of 0.82. Theitems forming this factor suggestedacute fatigue measured as the quan-tum of energy retained after a workshift, including: “I usually have lotsof energy for family/friends”; “Ihave energy for my hobbies or otherrelaxing activities at home”; and “I

have plenty of reserve energy when Ineed it.” Each of these items corre-lated negatively with the construct ofacute fatigue, such that higher valuesindicate lower acute fatigue levels.This is consistent with the Bartleyview of fatigue as relative incapaci-tation, which underpinned item se-lection. Scores on this factor thusrequire recoding to achieve confor-mity with the other factors of highscore � high construct value.

Factor 3—Intershift Recovery(OFER-IR). Comprising three itemswith a minimum item/factor correla-tion of 0.58, the reliability coeffi-cient of internal consistency (Cron-bach’s alpha) for this factor was0.75. Although this figure is below

the level of 0.80 commonly regardedas a cut point for acceptability, for athree-item factor (or subscale), thisfigure can be regarded as quite ade-quate. Items forming this factor sug-gested the extent to which recoveryis achieved from one work shift tothe next, including: “I can’t recovermy energy completely between workshifts” (negative correlation); “I feelfully rested at the start of each work-day/shift”; and “I don’t get enoughtime between work shifts to recovermy energy completely” (negativecorrelation).

Confirmatory Factor AnalysisExploratory factor analysis indi-

cated a three-factor solution, and this

TABLE 1Rotated Solution of Principle Components Analysis of OFER Items: RAH Study

Item No./Wording

Factor

Communalities1

(Chronic Fatigue)2

(Acute Fatigue)3

(Intershift Recovery)

1. “I use a lot of my spare time recovering fromwork”

.55 .52

2. “I often feel at the end of my rope with my work” .81 .703. “I often dread waking up to another day of my

work”.77 .66

4. “I often wonder how long I can keep going at mywork”

.80 .70

5. “I feel most of the time I’m living to work” .71 .576. “My head feels dull/heavy a lot of the time” .64 .537. “I often feel exhausted at work” .70 .678. “Too much is expected of me at my work” .74 .569. “My working life takes all my energy from me” .76 .72

10. “I feel exhausted all the time” .67 .78 .6711. “I usually have lots of energy to give my family or

friends”.67 .55

12. “I wish I had more ‘get up and go’ generally” .3913. “I have energy for my hobbies/relaxing activities in

my spare time”.78 .66

14. “I have plenty of reserve energy when I need it” .78 .6915. “I can’t recover my energy completely between

work shifts”�.74 .65

16. “I fully rested at the start of each work day/shift” .58 .4717. “Worrying about work issues makes it hard to

relax at home”.36

18. “I usually recover my energy within a few hours ofgetting home from work”

.65 .53

19. “I usually feel fully relaxed by the time I go to bed” .54 .5320. “I don’t get enough time between work shifts to

recovery my energy fully”�.72 .69

Eigen Value 8.84 1.74 1.22

Variance Explained 29.9% 16.8% 12.3%

Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization.Rotation converged in 6 iterations. Cut off �.52. Two items failed to reach the item/factor cut off level and are not reported.

598 Validation of the OFER Scale • Winwood et al

was tested by confirmatory factoranalysis using Amos version 5 soft-ware.80 Initial maximum likelihoodanalysis indicated only a modest fitof the model to the study data; good-ness of fit (GFI) � 0.872. A GFIvalue of 0.92 is generally regarded asa minimum indication of adequate fitof data in the proposed model.81

Examination of the modification in-dices for regression weights and co-variances indicated that the model fitwould be improved by the removalof two items, one from the OFER-CFsubscale and one from the OFER-AFscale (the two items indicated werethose with the lowest communalityin the initial exploratory factor anal-ysis). In addition, a significant corre-lation in error variance betweenitems 1 and 2, 1 and 5, and items 6and 8 was indicated, which may haverepresented similarities in responseerror to these items. When theseadjustments to the model were un-dertaken, the GFI rose to 0.94, alongwith other fit indicators, confirminga satisfactory fit of the data to therevised model. The standardized es-timates of this model are reported inFigure 1.

Final revised model-fit analysiswas: NPAR (number of model pa-rameters) � 36; DF (degrees of free-dom) � 84; CMIN (�2 minimumvalue) � 394.06; CMIN/DF (�2/degree freedom ratio) � 4.89. GFI(goodness-of-fit index) � .936; CFI(cumulative fit index) � 0.946; RM-SEA (root mean square error of ap-proximation) � .069. The sum ofthese measures indicates a compre-hensive fit of the OFER scale model,of three subscales, to the study data.

The standardized model indicatedin Figure 1 confirms the hypothe-sized substantial interrelation of theseparate constructs of acute, chronicfatigue and intershift recovery,wherein higher levels of intershiftrecovery moderate both acute andchronic fatigue, and higher levels ofacute (end of shift) are associatedwith higher levels of chronic fatigue.As hypothesized, the negative corre-lation between recovery and chronic

fatigue is higher than with acutefatigue.

Correlations BetweenOccupational Fatigue ExhaustionRecovery Factors andOther Scales

Table 2 reports the correlationsbetween the final OFER scale sub-scales and other scales used in theRAH study. Of note are the correla-tions between the OFER subscaleswith the separately reported indicesof preshift fatigue, postshift fatigue,and intershift recovery. These corre-lations are all significant and in theanticipated direction, for example,high and positive correlation (r2 �.44) between preshift fatigue andOFER-CF, but a high negative cor-relation (r2 � -.45) with OFER-IR.This observation, and the other cor-relations with postshift fatigue andfatigue recovery reported in Table 2,

represents useful convergent valida-tion of the OFER subscales. In addi-tion, the variation in these respectivecorrelations support the view that theOFER subscales discriminate be-tween chronic and acute fatigue, andrecovery, in an appropriate way, asintended.

The observed correlations betweenthe NHP emotional health and en-ergy health scores and OFER-CF andOFER-AF scores suggests that thesesubscales also discriminate betweenthe depressive and low-energy char-acteristic of the (enduring) chronicfatigue state/trait and the acute fa-tigue state appropriately.

Regression AnalysesEnd-of-Shift Fatigue Average. To

test the predictive capacity of theOFER subscales, regression analyseswere conducted using a hierarchicalstepwise entry method. End-of-shift

Fig. 1. Standardized estimates of the Occupational Fatigue Exhaustion Recovery scaleadjusted model.

JOEM • Volume 47, Number 6, June 2005 599

fatigue average was chosen as thefirst dependent variable to be as-sessed. Because participants couldregularly work (and report fatiguelevels associated with) one, two, orall of three possible shifts (day, af-ternoon, or night), participants’scores on this metric were averagedacross the shift variations theyworked.

Predictors were entered into theequation in blocks on the basis oftheir theoretical association with thedependent variable. They included:Nottingham Health Profile factors(energy level and emotional health),QEEH factors (work pace, physicaleffort, emotional demand, mental de-mand, peer problems, supervisorproblems), and the PSQI factor. Eachof the OFER subscales (OFER-CF,OFER-AF, and OFER-IR) was en-tered individually in their own block.

Initial analysis indicated that all ofthe NHP subscale predictors, thePSQI predictor, and the QEEH pre-dictors of mental demand, peer prob-lems, and supervisor problems failedto reach statistical significance andwere removed from the analysis,which was then repeated with onlythe significant predictors entered.Table 3 reports the final parsimoni-ous model. A total of 26% of vari-ance was predicted, with the (OFER)acute fatigue subscale being the mostsignificant predictor (as expected),explaining 12% of variance uniquely.

Preshift Fatigue Average. Fatiguelevels experienced before the differentshifts worked were also averaged andentered as the dependent variable inhierarchical regression analysis withthe NHP factors, the PSQI factor, theQEEW factors, and the OFER sub-scales as predictors. A significant 26%of variance was explained, with(OFER-IR) intershift recovery sub-scale score being the strongest predic-tor (as hypothesized), explaining 20%of variance uniquely. Table 4 showsthe final model of this analysis.

Recovery From Fatigue. An indexof (intershift) recovery from fatiguewas derived from the averaged post-shift and preshift scores according toTA

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the formula: (average postshift fa-tigue � average preshift fatigue)/average pre-shift fatigue � 100. Thisformula ensures the index of recov-ery, so derived was proportionate theactual preshift fatigue recorded. Forexample, an individual postfatiguescore of 6 and preshift fatigue scoreof 2 has a recovery index of: 6 �2/6 � 100 � 66.

By comparison, a postshift fatiguevalue of 4, followed by a preshiftfatigue value of 0, results in a recov-ery index of 4 � 0/4 � 100 � 100.In both instances, a reduction in fa-tigue level (from the end of one shiftto the beginning of the next) of 4units has been recorded, but its actualsignificance is different, ie, completerecovery or incomplete recovery be-tween shifts.

A hierarchical regression analysis,to determine the strongest predictorsof this metric, was undertaken, and

the results are reported in Table 5. Atotal of 16% of variance was ex-plained with the (OFER) intershiftrecovery subscale score being thestrongest predictor (as hypothesized)explaining 13% of variance uniquely.

Taken together, the results of theseanalyses support the conclusions thatthe OFER-IR subscale is a valid andreliable measure of recovery fromacute work-related fatigue betweenwork shifts; the OFER-CF subscaleis a valid measure of chronic fatigue/exhaustion; and finally, that theOFER-AF subscale is a valid mea-sure of acute (end-of-shift) fatigue.

CrosstabulationTo test the consistency of response

levels within the OFER subscales, acrosstabulation analysis was per-formed. Table 6 reports the results ofthis analysis in which quartiles ofscore distribution on the three OFER

subscales scores are crosstabulated.This indicates a theoretically appro-priate match in 596 of 767 cases(80%) in which “high” chronicfatigue is associated with “high” (af-ter-work) acute fatigue and “low”intershift recovery; and “low” acutefatigue in company with “high” in-tershift recovery is associated with“low” chronic fatigue/exhaustion.

Test/Retest of the OccupationalFatigue ExhaustionRecover Scale

Approximately 2 months aftercompleting the OFER scale, the 281respondents who had provided ane-mail contact for the purpose werecontacted by e-mail and asked tocomplete the OFER scale again, re-turning their response electronically.

A total of 141 replies were re-turned to give an overall response

TABLE 3Hierarchical Regression Analysis of End-of-Shift Fatigue

Significance

F Change Significance FHierarchical Step � t � R2 �R2

Step 1 OFER-AF .35 10.22 .000 .12 .12 104.63 .000Step 2 OFER-AF .25 6.65 .000

OFER-IR �.23 �6.26 .001 .17 .05 39.22 .000Step 3 OFER-AF .20 3.32 .000

OFER-IR .12 �3.12 .000OFER-CF .30 7.30 .000 .22 .05 53.36 .000

Step 4 OFER-AF .12 3.12 .002OFER-IR �.09 �2.33 .002OFER-CF .18 4.05 .000Work Physical Effort .13 3.28 .001Work Pace .11 2.85 .004Work Emotional Demand .10 2.19 .029 .26 .04 4.78 .000

Final Model: R2 � .26, Adjusted R2 � .26, F (3,753) � 44.73, P � .000.

TABLE 4Hierarchical Regression Analysis of Beginning-of-Shift Fatigue

Hierarchical Step

Significance

F Change Significance F� t � R2 �R2

Step 1 OFER-IR �.47 �13.76 .000 .20 .20 189.43 .000Step 2 OFER-IR �.29 �7.94 .000

OFER-CF .30 7.82 .000 .26 .06 132.8 .000Step 3 OFER-IR �.30 �8.02 .000

OFER-CF .26 6.92 .000Work Peer Problems .08 2.58 .01 .27 .01 91.42 .000

Final Model: R2 � .27, Adjusted R2 � .26, F(3,757) � 91.42, P � .000.

JOEM • Volume 47, Number 6, June 2005 601

rate of 50%. The Pearson correla-tions between respondents’ originaland retest responses were: OFER-CF/OFER-CF retest 0.84, OFER-AF/OFER-AF retest 0.64, andOFER-IR/OFER-IR retest 0.62.

Analysis of test/retest data by re-peated measures t tests was alsoundertaken.

For the OFER-CF subscale, t(111) � �1.13, P � 0.24. For theOFER-AF subscale, t (111) � 24.76,P � 0.000. For the OFER-IR sub-scale, t (111) � 1.85, P � 0.07. Thetest/retest results are consistent withhypothesized relationships betweenthe different fatigue and recoveryconstructs.

DiscussionThe factor structure of the OFER

scale, initially derived by exploratoryfactor analysis, was confirmed andimproved following confirmatoryfactor analysis. This strongly sup-ports the soundness of the fundamen-tal structure of the instrument. Thethree subscale’s internal reliabilities,as measured by Cronbach’s alphavalues, are satisfactory.

Detailed analysis of the resultstaken together suggest that the inten-tion to develop and validate aninstrument measuring the fatigue el-ements of chronic fatigue (exhaustion),acute fatigue (after work), and inter-shift recovery has been successful.

The subscale of chronic fatigue(OFER-CF) is a measure of an en-

during trait of maladaptive fatigue/exhaustion comprising physical, cog-nitive, and emotional elements. Itdemonstrated a high Pearson test–retest correlation of 0.84 and notsignificant repeated-measures t testconfirming the fact that it measureschronic fatigue as a stable trait. Al-though work-specific, it is not jobtype- or job category-specific, unlikethe MBI instrument,39 and it does notrely on limited and dispositionallyvariable outcome measures such ascynicism or self-efficacy like theMBI-GS.44 This subscale is a mea-sure of the psycho/physical outcomeof the balance between energy ex-penditure and energy recovery overtime.

The subscale of acute fatigue(OFER-AF) is a measure of acutework fatigue. The Pearson test–retestcorrelation of 0.67 and significantrepeated-measures t test suggeststhat it measures a temporally vari-able state rather than a stable trait.This is consistent with acute fatigueexperience varying from shift to shiftor from week to week depending onworkplace requirements. It assessesthe quantum of available energy leftafter a worker completes a givenwork shift and which is available innonwork time. A worker scoring inthe high category on this subscalehas depleted his or her availableenergy through work to a substantialdegree. This subscale can be a mea-sure of the general demands of a

given work type, if the averagedresponses of a group undertaking thesame work are assessed, or alterna-tively, an individual worker’s expe-rience of his or her work.

The subscale of intershift recovery(OFER-IR) is a measure of the extentto which a worker recovers energyexpended during the previous workshift. A worker who consistentlyscores low on this subscale is at riskof progressing to chronic fatigue traitunless this measure improves. Themagnitude of the Pearson test–retestcorrelation of this subscale of (0.64)and close to significant repeated-measures t test suggests this might beviewed as a subchronic experience,which can vary according to changesin both workplace demand and alsoin nonwork-time behaviors. Thissubscale is applicable for assessingthe contribution of nonwork-timeactivity variables to recovery effi-ciency, and for the effects thatchanges in workers’ individual non-work circumstances have onrecovery.

When the OFER subscales weremade predictors in regression analy-ses, they were more powerful predic-tors of postshift and preshift fatigueand intershift recovery than mea-sures of work demand characteris-tics, quality-of-life, and sleepquality.

All three subscales of the OFERinstrument have high face validity.The OFER-CF subscale demon-

TABLE 5Hierarchical Regression Analysis of Recovery-From-Fatigue

Hierarchical Step

Significance

F Change Significance F� t � R2 �R2

Step 1 OFER-IR .36 10.65 .000 .13 .13 113.33 .000Step 2 OFER-IR .29 7.57 .000

OFER-CF �.14 �3.54 .000 .14 .01 63.86 .000Step 3 OFER-IR .29 8.43 .000

OFER-CF �.20 7.40 .000Work Pace .121 �4.50 .003 .15 .01 46.07 .000

Step 4 OFER-IR .30 7.57 .000OFER-CF �.16 �3.54 .000Work Pace .12 3.16 .002Work Supervisor Problems �.10 �2.83 .004 .16 36.88 .000

Final Model: R2 � .163 (Adjusted R2 � .159), F (4,755) � 36.88, P � .000.

602 Validation of the OFER Scale • Winwood et al

strates significant correlations withthe MBI-E subscale and CIS scale. Itis not intended to measure either thelimited perspective of emotional ex-haustion inherent in the MBI-E burn-out subscale or an acute/subchronicmeasure of nonwork-specific globalfatigue, like the CIS scale. Conse-

quently, the correlational level of theOFER-CF subscale with these scales(r2 � .71 with MBI-E) and (r2 � .53with the CIS) indicate a level ofconvergent validity, which is bothappropriate and expected.

Although many authorities on fa-tigue consider that fatigue experi-

ence is a continuum, and that thecategorization of fatigue scores ac-cording to cutoff points can be mis-leading, it is nevertheless useful forfatigue instrument scores to be cate-gorized for comparative purposes.On the basis of results to hand, fourcutoff points of low, low/moderate,

TABLE 6OFER Subscales Cross Tabulation of Four Levels According to Quartiles of Score Distribution

OFER-IntershiftRecovery Categories

OFER-Chronic Fatigue Categories

TotalLow

ExhaustionLow/Moderate

ExhaustionModerate/High

ExhaustionHigh

Exhaustion

Low Intershift Recovery OFER AcuteFatigueCategories

Low AcuteFatigue

4 1 2 1 8

Low/Mod AcuteFatigue

5 17 18 9 49

Mod/High AcuteFatigue

3 41 59 34 137

High AcuteFatigue

0 10 44 44 98

Total 12 69 123 88 292

Low/Moderate IntershiftRecovery

OFER-AcuteFatigueCategories

Low AcuteFatigue

4 2 2 0 8

Low/Mod AcuteFatigue

19 34 26 6 85

Mod/High AcuteFatigue

9 50 63 14 136

High AcuteFatigue

1 7 21 21 50

Total 33 93 112 41 279

Moderate/High IntershiftRecovery

OFER-AcuteFatigueCategories

Low AcuteFatigue

7 4 1 0 12

Low/Mod AcuteFatigue

25 23 13 1 62

Mod/High AcuteFatigue

10 19 20 3 52

High AcuteFatigue

1 5 5 4 15

Total 43 51 39 8 141

High Intershift Recovery OFER-AcuteFatigueCategories

Low AcuteFatigue

16 2 1 0 19

Low/Mod AcuteFatigue

18 7 2 0 27

Mod/High AcuteFatigue

3 2 1 0 6

High AcuteFatigue

0 2 0 1 3

Total 37 13 4 1 55

Appropriate matches highlighted in bold � 568/770 � 74%.Low; Low/Moderate; Moderate high; and high levels of the subscale reflect scores on the relevant subscale of: 0–25, 26–50, 51– 75 and

76–100 respectively.

JOEM • Volume 47, Number 6, June 2005 603

moderate/high, and high levels ofthe subscale construct according toquartiles of score distribution aresuggested.

When the OFER subscale scoreswere crosstabulated according tothese levels, a very high correspon-dence was observed. This supportsthe hypothesized relationship be-tween the OFER subscales, namelythat a high level of acute fatigue afterwork (high OFER-AF score) with alow level of recovery between shifts(high OFER-IR score) is associatedwith high levels of chronic fatigueexhaustion (high OFER-CF score).This analysis also indicates the me-diating influence of intershift recov-ery on chronic fatigue prevalence,dependent on the average level ofacute fatigue.

Summary and ConclusionA simple-to-administer, 15-item

measure of chronic work-related fa-tigue, acute after-work fatigue, andrecovery between work shifts hasbeen developed. This instrument of-fers excellent psychometric proper-ties of face, construct, convergent,and discriminant validity; reliability;internal consistency; and strong pre-dictive power. It is free of genderbias and has been validated in amajor study.

The OFER scale represents theonly extant measure that includes asubscale measuring the construct ofrecovery actually achieved betweenwork shifts. This construct is argu-ably a significant mediator and mod-erator of the progression of acutefatigue states to chronic fatiguetraits. The final form of the instru-ment and a scoring key is reproducedin Appendix 1.

Having validated the OFER scaleas described, it is possible to broadenthe existing models of occupationalfatigue genesis by suggesting that thepersistent failure to recover energydepleted by acute work fatigue, dur-ing the nonwork time preceding sub-sequent work shifts, places a workerat greater risk of developing mal-adaptive chronic fatigue traits. It also

suggests that there may be morepoints for intercepting this progres-sion than has previously beenconsidered through modifying non-work-time behaviors so as to maxi-mize recovery levels before the nextwork shift (increased OFER-IRscore). Accordingly, this further sug-gests that in addition to studying theenergy-depleting characteristics ofwork itself, the study of nonwork-time behavior in relation to energyrecovery is a valuable direction forfuture research.

It is evident that the OFER mea-sure has produced valid and mean-ingful results within the substantialAustralian Health Service populationreported. Subject to further valida-tion within other populations, theOFER scale is suggested as a signif-icant tool to aid the study of work-related fatigue, and in particular, theas-yet underresearched nexus be-tween nonwork-time activity and theevolution of chronic work-relatedfatigue/exhaustion.

Future DirectionsGiven that the OFER-IR (intershift

recovery) and OFER-AF (acute fa-tigue) subscales are limited to threeand four items, respectively, the pos-sibility of further refinement to thisinstrument to increase the robustnessof these subscales is being activelyconsidered. In addition, future re-search into the correlation betweenthe levels fatigue/recovery identifiedby the OFER scale and the titers ofstress hormones such as cortisoneand nor-adrenalin, which are knownto be associated with the fatigue andrecovery levels,82–86 could be antic-ipated to add further objective vali-dation to the OFER scale.

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