Stress and wellbeing in healthcare staff: the role of negative affectivity, and perceptions of job demand and discretion

STRESS AND WELL-BEING IN HEALTH-CARESTAFF: THE ROLE OF NEGATIVE AFFECTIVITY,

AND PERCEPTIONS OF JOB DEMANDAND DISCRETION

PATRICK TYLER* AND DELIA CUSHWAY

School of Psychology, University of Birmingham, Birmingham, UK

SUMMARY

A questionnaire survey was administered to volunteer sta� from the Surgical and Mental Health Directorates of anEnglish hospital district. The aim was to investigate the relationships between job stressors, coping strategies, jobsatisfaction and well-being, in light of Karasek's demand±discretion model. The e�ects of controlling for age, genderand negative a�ectivity were also of interest. After controlling for these factors, there was found to be no interactionbetween job demand and discretion for either job satisfaction or psychological distress, so Karasek's model was notsupported. Both job dissatisfaction and psychological distress were found to be in¯uenced by lack of resources, whileperception of demand was strongly in¯uenced by workload; these were also the stressors that di�erentiated the twohospital directorates, with the surgical sta� su�ering higher levels of both. Controlling for negative a�ectivity had astronger in¯uence on the measure of distress than on job satisfaction and the two outcome measures were notinterchangeable. Recommendations centred on improving structural conditions, especially for surgical sta�, and onreducing levels of anxiety and hostility by promoting stress management. # 1998 John Wiley & Sons, Ltd.

Stress Med., 14: 99±107, 1998.

KEY WORDS Ð health-care sta�; negative a�ectivity; job stressors; coping stategies; job satisfaction; Karasek'sdemand±discretion model

It is becoming increasingly well recognized thatstress a�ects the health and caring professionsdisproportionately.1,2 The job of caring for vulner-able people, together with associated uncertaintiesabout the e�ectiveness of treatment and the need tohide their natural self-doubt about their owncompetence, makes health professionals a high-risk group. Imposed on this is the pressure of beinga rather small part of a large organization onwhose policies they have practically no in¯uence,and which is subject to unpredictable and frequentchange. The rapid changes undergone by theBritish National Health Service in recent yearshave included regrading of sta�, contraction andmerging of health districts, closures of hospitalwards and hospitals, introduction of contracts fordoctors and allied professions, and a dramaticincrease in managers and paperwork; little account

has been taken of the impact of these changes onhealth personnel. For example nurses, of whom themajority are still female, have a much highermortality from stress-related causes than otherwomen of their age and status. Doctors haverelatively high rates of alcoholism.1 Because ofthese concerns, one hospital management agreed tocooperate with a stress audit which forms the basisof this study.

Sources of stress have been studied in Britishhospital nurses,3,4 psychiatric nurses,2,5 doctors,in training,6,7 general practitioners8 and clinicalpsychologists.9 Similar themes emerge from thesestudies: for example, workload, relationships withclients or patients, self-doubt and relationshipswith other professionals are common stressors forall groups. However, it has proved to be di�cult tomake comparisons across groups because of thelack of an appropriate questionnaire. In our workwith nurses4,10 we have found Gray-Toft andAnderson's Nursing Stress Scale11 useful but toospeci®c to hospital nurses to be used for other

*Correspondence to: Patrick Tyler, School of Psychology,University of Birmingham, Birmingham, B15 2TT, UK.

CCC 0748±8386/98/020099±09$17.50 Received 14 August 1996# 1998 John Wiley & Sons, Ltd. Accepted 7 July 1997

STRESS MEDICINE, VOL. 14: 99±107 (1998)

groups. Similarly, our clinical psychologists'scale9,12 would be inappropriate for doctors ornurses. For this reason we have recently producedand validated the Mental Health ProfessionalsStress Scale2,13 and used it to compare a cross-section of mental health nurses and clinicalpsychologists. The sources of stress measured bythis scale are workload, client-related di�culties,self-doubt, organizational processes, relationshipsand con¯icts with other professionals, lack ofresources and home±work con¯ict. It seems likelythat these pressures are salient ones for healthprofessionals other than those in mental health forwhom it was devised. Therefore, a sample of bothmental health and other health workers in thehospital district was obtained and measured, withthe intention of extending the application of thescale to other health-related professions.

Most studies of occupational stress in healthprofessionals have adopted one of two sorts ofoutcome measure: (a) a measure of psychologicaldistress such as anxiety, depression, somatic symp-toms or a combination of these; or (b) a measure ofjob satisfaction. Any theory of occupational stressshould predict that employees who perceive jobpressures to be high will experience more symptomsof poor health and higher job dissatisfaction.Therefore the correlations between self-reportedstressors and self-reported outcome measuresshould be fairly high. However, the situationappears not to be this simple and in practicecorrelations tend to be modest, often accountingfor no more than about 10 percent of the variancein the outcome measure.14 Current thinkingaccounts for the discrepancy by postulating thatintervening factors such as coping strategies, socialsupport and personality act as moderators of therelationship. Some people cope better than otherswhen under stress15 perhaps because they have ahardier personality, or more adaptive copingstrategies, or a stronger support network. On theother hand, personality di�erences may enhance oreven fully account for the relationship betweenperceived stressors and outcome. In particular,di�erences in negative a�ectivity, the tendency toevaluate both oneself and one's environment in aconsistently negative way, can increase such arelationship.16 Negative a�ectivity is closely relatedto trait anxiety and neuroticism and may bemeasured on one of these scales. The study wasdesigned to investigate and control for the e�ects ofnegative a�ectivity on the relationship betweenstressors, coping and outcome measures.

The general contextual model of stress withinwhich this study, like most others in this ®eld, wasconceived is the cognitive transactional model,17±19

whereby feelings of stress are seen as arising from aset of appraisals which compare perceptions ofthe external and internal pressures with copingresources and potentials for action. A state of stress`is the imbalance between perceived demand andperceived inability to meet that demand'1 (p. 19). Amore stringent, interactive model of stress withinthe cognitive paradigm was proposed by Karasek20

and has proved both popular and powerful.Karasek's demand±discretion model suggests thatstress only gives rise to strain (ie feelings ofdissatisfaction and depression, leading to symp-toms of ill-health) when job demands are high andjob discretion is low. Discretion refers to theamount of control that workers have over theirwork environment, including the freedom tochoose their tasks, allocate their time and developnew skills. If job discretion is high, then high jobdemands can lead to the development of adaptivecoping strategies and new skills, giving rise togreater satisfaction and well-being. The model thuspredicts a strong statistical interaction betweendemand and discretion, and is partially supportedby recent studies on health-care sta� by Parkes andher associates.21 Measures of demand and discre-tion have been included in this study, in order totest the Karasek model.

The aims of the study may therefore besummarized as follows:

1. To extend the application of the Mental HealthProfessionals Stress Scale (MHPSS) to othergroups of health professionals.

2. To include a measure of negative a�ectivity(NA) and observe its e�ects on the relation-ship between stressors, coping and outcomemeasures.

3. To evaluate Karasek's demand±discretionmodel with two populations which may di�erin overall level of job demand and job discretion.

METHOD

Participants

A total of 155 sta� from two directorates ofa hospital in the English Midlands volunteeredto ®ll in questionnaires; they represented about25 percent of the targeted population. Of these,83 (53.5 percent) were from the Mental Health

100 P. TYLER AND D. CUSHWAY

# 1998 John Wiley & Sons, Ltd. STRESS MEDICINE, VOL. 14: 99±107 (1998)

Directorate and 72 (46.5 percent) were in theSurgical Directorate. There were 112 (72 percent)females, 34 (22 percent) males, and the remainingnine declined to say; 107 were full-time employees,27 were part-time and 21 did not say. Eighty-two (53 percent) were quali®ed nurses (SRN ormental health/learning disability nurses); of therest, 25 were nursing or health-care assistants;20 were administrative/clerical sta�; 23 wereclinical/medical sta�; the remaining ®ve did notsay. Within three broad age bands, 40 (26 percent)were under 30 years, 90 (58 percent) were between30 and 50 years and 18 (12 percent) were over 50;seven did not say. Eighty (52 percent) of the sta�had taken time o� for ill health in the past6 months, and 73 (47 percent) indicated that theyhad been subjected to various forms of harass-ment (eg sexual/racial) or violence at work duringthat period. There was a signi®cant di�erencebetween the directorates in the amount of harass-ment, with 56 percent of surgical sta� complain-ing of some form of harassment compared to40 percent of mental health sta�; this di�erencemay be accounted for by the signi®cantly highproportion of females in the Surgical Directorate(90 percent vs 66 percent). Surgical Directoratesta� were hospital-based, while 49 out of 83 of theMental Health Directorate sta� were community-based.

Questionnaires

1. Background information: the initial page askedfor details about the respondent's directorate,age band, gender, whether full- or part-time,occupation, area (eg community/surgical ward),years in current job, years in occupation, dayso� sick, nature of illness, and whether he/shehad been a victim of harassment or violence.

2. There were four items asking respondents torate on a seven-point scale to what extent theythought they had been under stress as a resultof their work (`stress'), how con®dent theyfelt of their ability to cope with stress at work(`coping'), how demanding the job was(`demand') and how free they were to decidewhat to do and where and when to do things(`discretion').

3. The 20-item Trait Scale of the State±TraitAnxiety Inventory22 was included as a measureof negative a�ectivity.

4. The Mental Health Professionals Stress Scale:2

this scale consisted of 42 items answered on a

four-point response scale scored from 0(does not apply) to 3 (does apply to me).There were seven subscales on the MentalHealth Professionals Stress Scale (see Table 1).

5. The coping scale of the Health and DailyLiving Schedule23 adapted and shortened to25 items by Tyler and Cushway.14 Each itemwas answered on a four-point scale scored from0 to 3 (`no', `yes, once or twice', `yes, sometimes'and `yes, fairly often'). There were threesubscales representing di�erent response strat-egies: active cognitive coping, active behaviour-al coping and avoidance coping.

6. The General Health Questionnaire 28-itemversion.24 Each of the 28 items was answeredon a four-point response scale of relative ill-health (feeling worse than usual), from 0 to 3.There were four subscales of the General HealthQuestionnaire (see Table 1), and in addition theoverall General Health Questionnaire mean wascalculated using the Likert method. A `caseness'index was also obtained for each person: a scoreof 5 or more overall is taken as an indication ofpoor mental health.

Procedure

The questionnaires were distributed directlyto all sta� in each hospital department and to sta�in community houses by members of the districtpsychology department. Sta� were requested toreturn questionnaires to conveniently placed boxesin central locations. The questionnaires wereanswered independently and anonymously andrespondents were told that they would be readand analysed by experts at the university. Becauseof the assurance of anonymity and the `blind'distribution procedure it was not possible todistinguish those who did not volunteer to ®ll ina questionnaire or to follow them up except bygeneral appeals.

Analysis

Comparisons between groups were madeusing MANOVA, followed by univariate ANOVAif the overall e�ect was signi®cant. Hierarchicalmultiple regression was used to investigate thedemand±discretion interaction and stepwisemultiple regression was used to identify thestrongest predictors of mental distress.

STRESS IN HEALTH-CARE STAFF 101


RESULTS

Comparisons among means

No di�erences were found between full-timeand part-time employees. Those who reported arecent illness were compared with those who didnot and they did not di�er on any other dimen-sion. Those who reported incidents of violenceor harassment indicated more pressure than thosewho did not on all the stressor scales (F7,145�2.19, p5 0.05) and were higher on all theGeneral Health Question-naire scales (F4,147�3.13, p5 0.05). They were also more likely toreport use of avoidance coping strategies (F1,148�11.43).

Relatively few signi®cant di�erences werefound between the directorates; while sta� of theSurgical Directorate reported marginally lower job

satisfaction (F1,148� 4.27, p5 0.05), the corre-sponding MANOVA was non-signi®cant, so thereis doubt about the reliability of the di�erence. Thestressor scales did, however, show clearly signi®-cant di�erences between the directorates (multi-variate F7,145� 3.48, p5 0.005). In particular,surgical sta� reported more pressure due to work-load (F1,150� 8.20, p5 0.01) and lack of resources(F1,150� 6.47, p5 0.01). Sta� from the two direct-orates did not di�er in their use of coping strategies.

There were age and gender di�erences. Sta�in the oldest (over 50) age band di�ered sub-stantially from their younger colleagues in thedirection of experiencing lowest job pressures(from client-related di�culties, organizationalstructure, relationships with other professionals,lack of resources and self-doubt; multivariateF14,276� 2.17, p5 0.01), highest job satisfaction

Table 1 Ð Means and standard deviations of item scores for all subscales in the questionnaire shown separately forsta� from the two directorates. Previously published means for mental health nurses are shown for comparison

Scale Mental health Directoratenurses* Mental health Surgical

N Mean N Mean SD N Mean SD

Mental Health Professionals Stress Scale (MHPSS)Workload 107 1.31 83 1.23 0.76 72 1.61 0.80Client-related di�culties 100 1.20 82 1.08 0.65 72 1.03 0.65Relationships and con¯ict with 104 1.18 83 1.12 0.68 72 1.12 0.76other professionalsLack of resources 103 1.62 82 1.30 0.72 72 1.60 0.71Organizational structuresand processes 102 1.61 83 1.41 0.71 72 1.40 0.73Professional self-doubt 100 1.24 83 1.07 0.63 72 1.07 0.69Home±work con¯ict 103 0.97 83 0.86 0.62 72 0.97 0.63MHPSS mean 88 1.30 81 1.16 0.51 72 1.26 0.58

Stress level 109 4.51 82 4.11 1.57 72 4.68 1.64Coping level NA 82 5.43 1.23 72 5.60 1.45Demand level NA 82 5.30 1.37 72 6.18 1.14Discretion level NA 82 4.80 1.70 72 4.31 1.74Job satisfaction 108 1.73 82 2.21 1.02 72 1.86 0.95Trait anxiety NA 83 38.32 9.06 72 39.76 7.94

General Health Questionnaire (GHQ)Somatic symptoms 110 0.91 81 0.83 0.61 72 0.97 0.54Anxiety and insomnia 109 0.84 81 0.74 0.67 72 0.90 0.60Social dysfunction 108 1.14 81 1.06 0.37 72 1.07 0.36Severe depression 109 0.26 81 0.17 0.32 72 0.30 0.44GHQ mean 104 0.80 80 0.69 0.40 72 0.81 0.38

Coping strategiesActive cognitive coping 109 1.89 79 1.90 0.58 72 1.86 0.63Active behavioural coping 104 1.43 79 1.46 0.46 71 1.47 0.52Avoidance coping 98 0.75 80 0.73 0.44 72 0.76 0.40

*From Cushway et al., 19962



(F2,140� 5.45, p5 0.005), lowest General HealthQuestionnaire mean (F2,140� 3.41, p5 0.05) andgenerally lower levels of active cognitive andbehavioural coping (multivariate F6,278� 4.66,p5 0.001). Gender di�erences only in¯uenced theGeneral Health Questionnaire measures, withfemales reporting considerably higher levels onthe somatic symptoms (F1,141� 11.35, p5 0.001)and anxiety and insomnia scales (F1,141� 7.88,p5 0.01). There were no accompanying genderdi�erences on the stressor or coping measures.

Di�erences were also found between quali®ednurses and other workers. Nurses complained ofhigher pressures from workload (F1,151� 14.21,p5 0.001), client-related di�culties (F1,151� 6.53,p5 0.05) and home±work con¯ict (F1,151� 6.41,p5 0.05). Sta� in administrative and clericalpositions reported correspondingly lower stressin each of these areas as well as in self-doubt;and nursing and health-care assistants alsoreported lower stress from workload. The jobcategories did not di�er signi®cantly in coping oroutcome measures.

Hierarchical multiple regression

Themain aims of the study, evaluation of the roleof negative a�ectivity and testing the demand±discretion hypothesis, were accomplished using a

series of hierarchical multiple regression equations.In hierarchical multiple regression, groups of pre-dictors are entered in a predetermined order andtheir additional contributions to variance in thedependent variable observed. The dependent vari-ables chosen for analysis were the two outcomevariables, namely General Health Questionnairemean and job satisfaction. When testing thedemand±discretion model, the order in which thepredictors were entered was as follows: at stage 1,the demographic variables age and gender, thethree age bands having been coded 1, 2 and 3; atstage 2, the negative a�ectivity variable traitanxiety; at stage 3, the two job type variablesnurse vs other sta� and directorate membership; atstage 4, the standardized single-item measures ofdemand and discretion; and at stage 5, the inter-action of demand and discretion.

As may be seen from Table 2, the ®ve stages(comprising seven variables and one interaction)accounted for much more of the variance inGeneral Health Questionnaire mean (®nalR2� 0.50, F8,132� 16.49, p5 0.0001) than injob satisfaction (®nal R2� 0.21, F8,134� 4.37,p5 0.001). In both equations, the interaction ofdemand and discretion contributed no additionalvariance, so the demand±discretion model is notsupported by these data. The variance accountedfor by the addition of demand and discretion

Table 2 Ð Hierarchical regression analysis showing the e�ect of job demand and job discretion on mean GHQ andjob satisfaction after controlling for demographic factors, negative a�ectivity and job type

Stage Variable Cum R2 F df DR2 Fchange pchange Final b p

GHQ mean1 Age ÿ0.07

Gender 0.078 5.82 2,138 0.112 NA 0.456 38.35 3,137 0.379 95.45 50.0001 0.62 5 0.00013 Nurse/other ÿ0.06

Directorate 0.461 23.11 5,135 0.005 51 NS 0.004 Demand 0.20 50.01

Discretion 0.500 18.96 7,133 0.038 5.09 50.01 ÿ0.065 Dem.� disc. 0.500 16.49 8,132 0.00 51 NS ÿ0.02

Job satisfaction1 Age 0.18 50.05

Gender 0.050 3.66 2,140 0.002 NA 0.104 5.39 3,139 0.055 8.48 50.005 ÿ0.20 50.053 Nurse/other ÿ0.05

Directorate 0.130 4.10 5,137 0.026 2.03 NS ÿ0.064 Demand ÿ0.21 50.05

Discretion 0.205 4.96 7,135 0.075 6.33 50.005 0.21 50.015 Dem.� disc. 0.207 4.37 8,134 0.002 51 NS ÿ0.05



together was small but signi®cant in both cases,but seems to be due mainly to job demandcharacteristics in the case of General HealthQuestionnaire whereas job discretion also contri-buted in the case of job satisfaction. At theprevious stage, adding job type contributed nosigni®cant additional variance in either measure,providing support for the view that the marginaldi�erence between the directorates in job satisfac-tion mentioned above can be explained by theirdemographic and personality di�erences.

As expected, the negative a�ectivity measuretrait anxiety made a substantially larger contribu-tion to variance in General Health Questionnairemean (accounting for an additional 38 percent ofthe variance, p5 0.0001) than in job satisfaction(an additional 5 percent, p5 0.01). This largedi�erence accounts for the greater predictability ofthe General Health Questionnaire measure. Ageand gender made a somewhat greater contributionto the General Health Questionnaire mean, wherethe initial R2 (8 percent) was signi®cant at p5 0.01,than to job satisfaction, where the initial R2

(5 percent) was signi®cant at p5 0.05, as alreadyindicated in the comparison between the means.Initially both age and gender accounted fordi�erences in the General Health Questionnairemean, with females and younger sta� having higherscores, but after adjusting for di�erences in theother variables (negative a�ectivity and jobcharacteristics), neither contributed signi®cantlyto the General Health Questionnaire mean in the®nal equation. Only age contributed to the initialequation for job satisfaction, with older workersbeing more satis®ed than younger ones. Even afteradjusting for the other variables, age made asigni®cant contribution to job satisfaction in the®nal equation.

Hierarchical multiple regression was also used toinvestigate the relationship between outcomemeasures (General Health Questionnaire meanand job satisfaction), stressors and coping, con-trolling for negative a�ectivity e�ects. At stage 1were entered the demographic, negative a�ectivityand job type variables of the previous analysis; atstage 2 the seven stress factors from the MentalHealth Professionals Stress Scale were entered atonce; and at stage 3 the three coping factors wereentered. As may be seen from Table 3, the additionof the coping variables made a small and non-signi®cant contribution to variance in both theGeneral Health Questionnaire mean and jobsatisfaction. The addition of the stressor variables

made a major contribution to variance in bothoutcome measures; this change was larger for jobsatisfaction (29 percent, p5 0.0001) than forGeneral Health Questionnaire mean (13 percent,p5 0.0001). The stressor which contributed mostto variance in mean General Health Questionnaire,independently of negative a�ectivity and before theaddition of the coping variables, was lack ofresources ( p5 0.05). For job satisfaction, organ-izational structure and processes ( p5 0.001) andlack of resources ( p5 0.01) were both negativelyrelated, but client-related di�culties ( p5 0.001)was positively related to the outcome.

The correlation between the General HealthQuestionnaire mean and job satisfaction wasÿ0.36( p5 0.01). In the ®nal regression equation it isnoteworthy that the largest contributor to variancein the General Health Questionnaire mean wasnegative a�ectivity (b� 0.47, p5 0.0001), whereasnegative a�ectivity was only marginally signi®cantfor job satisfaction and the two stressor variablesmade much larger contributions. This ®ndingwould argue against the view that stress measuresand outcome measures are all essentially justmeasuring negative a�ectivity.

Stepwise multiple regression

Because the respondents' views of job demand,job discretion, how stressed they felt and how wellthey were coping were measured on single-itemscales, stepwise multiple regression was used torelate these four self-ratings to the stressor andcoping variables and negative a�ectivity. Jobdiscretion was related to three of these variables,active behavioural coping (b� 0.29, p5 0.001),negative a�ectivity (b�ÿ0.19, p5 0.05) andlack of resources (b�ÿ0.19, p5 0.05; R2� 0.14,p5 0.0001). Job demand was related positively toworkload (b� 0.69) and negatively to home±work con¯ict (b�ÿ0.28, p5 0.01; R2� 0.28,p5 0.0001). Success in coping was related tonegative a�ectivity (b�ÿ0.49, p5 0.0001) andto active cognitive coping (b� 0.18, p5 0.05;R2� 0.30, p5 0.0001). Feeling stressed was relatedto three variables (R2� 0.46, p5 0.0001): work-load (b� 0.44, p5 0.0001), organizational pro-cesses (b� 0.44, p5 0.0001) and client-relateddi�culties (b�ÿ0.18, p5 0.05). Analysis of thecomponents of these four responses thus indicatedthat feelings of ability to cope are di�erentiablefrom job discretion, and feelings of stress areassociated with job demand.



DISCUSSION

The stress pro®les of the two directorates proved tobe quite di�erent, with workers in the SurgicalDirectorate more highly stressed from workloadand lack of resources in particular. Workload is themain contributor to an appraisal that the job isdemanding, and adequate resources makes a smallbut signi®cant contribution to a feeling of jobdiscretion. Job demands were therefore felt to behigher in the Surgical Directorate and job discre-tion was marginally, although not signi®cantly,lower, so it would be expected that surgical sta�should experience lower job satisfaction andpoorer mental health outcomes. In fact, jobsatisfaction was only marginally lower, and noneof the General Health Questionnaire scales di�ered

between directorates. This pattern of results did notappear to ®t the Karasek model, which wouldpredict a much more substantial di�erence betweenthe directorates in outcome measures. There is,however, some correspondence with other results inthe literature (eg 21) which suggest that jobsatisfaction is rather more sensitive than mentaldistress to the demand±discretion interaction.

Another pattern was shown by older workers.They experienced lower demands from di�cultieswith clients, organizational structure, relationshipswith other professionals, lack of resources and self-doubt, but also lower levels of coping, and hadhigher job satisfaction and greater mental well-being. In the older workers, two of the variableswhich contributed to feelings of job discretionhad opposite e�ects: active behavioural coping was

Table 3 Ð Hierarchical regression analysis showing the e�ect of stressors and coping strategies on mean GHQ andjob satisfaction after controlling for demographic factors, negative a�ectivity and job type

Stage Variable Cum R2 F df DR2 Fchange pchange Final b p

GHQ mean1 Age ÿ0.04

Gender 0.14 50.05NA 0.47 5 0.0001Nurse/other 0.01Directorate 0.482 23.98 5,129 0.02

2 Workload 0.09Client rel. di�s ÿ0.11Relationships 0.08Resources 0.22 50.05Organization 0.09Self-doubt 0.00Home±work 0.611 15.95 12,122 0.129 5.77 50.0001 0.11

3 Avoidance 0.11Behavioural ÿ0.13Cognitive 0.632 13.62 15,119 0.021 2.29 NS ÿ0.04

Job satisfaction1 Age 0.16 50.05

Gender 0.00NA ÿ0.19 50.05Nurse/other ÿ0.09Directorate 0.139 4.22 5,131 ÿ0.08

2 Workload ÿ0.05Client rel. di�s 0.25 50.05Relationships ÿ0.07Resources ÿ0.34 5 0.005Organization ÿ0.32 5 0.005Self-doubt 0.08Home±work 0.430 7.80 12,124 0.291 9.06 50.0001 ÿ0.01

3 Avoidance 0.05Behavioural 0.14Cognitive 0.443 6.42 15,121 0.013 51 NS ÿ0.10



lower, but stress from lack of resources was alsolower, so job discretion was approximately thesame as for younger colleagues. Here low demandled to low strain, an outcome which is not entirelyconsistent with Karasek's interactive model.Although older and more experienced workersare often found to have better coping strategies(eg 14), it is not unusual to ®nd that more stressedworkers make more use of all coping strategies, asfound here (eg 4). Gender di�erences showedanother pattern of results which did not ®t theKarasek model. There appeared to be no demandor discretion di�erences, yet females showedevidence of higher strain.

The direct test of the Karasek model wasprovided by the hierarchical regression analysis.After controlling for the e�ects of age, gender, jobtype and negative a�ectivity, it was found that onlyjob demand signi®cantly in¯uenced psychologicalwell-being as measured by the General HealthQuestionnaire. Neither job discretion nor theinteraction between demand and discretion madeany di�erence. On the other hand, job satisfactionwas in¯uenced equally by both demand anddiscretion separately, but not by the interactionbetween them. It seems clear that our results do notsupport the Karasek interaction model, althoughthe model has been helpful in providing aframework for thinking about the factors whichin¯uence mental health outcomes. The results alsoindicate that the two outcome measures, althoughcorrelated, are not interchangeable. As has beenreported previously, job satisfaction is generallymore sensitive to job-related factors such asorganizational structure and lack of resources.Another large di�erence between the two out-

come measures was that the General HealthQuestionnaire was strongly a�ected by negativea�ectivity (or trait anxiety) while negative a�ect-ivity had relatively small e�ects on job satisfaction.One of the unexpected ®ndings of the regressionanalyses in this study was that stressors such ashome±work con¯ict, which have been foundpreviously to be good predictors of the GeneralHealth Questionnaire,4 were non-signi®cant here.It seems quite likely that, in studies which havenot measured negative a�ectivity separately, theconstellation of anxiety, depression and hostilitywhich make up negative a�ectivity are allowedexpression in the questions on home±work con¯ict.Once negative a�ectivity is factored out in aregression analysis, these sources of stress appearless important. The same consideration seems to

apply to avoidance coping, which in past studieshas consistently predicted General HealthQuestionnaire. In this study, if trait anxiety is leftout of the prediction equation, the strongestpredictors of General Health Questionnaire meanare home±work con¯ict and avoidance copingstrategies, thus replicating our previous results.

In practice, because stress questionnaires andmental health outcome measures are imbued withnegative a�ectivity,16 it is di�cult to disentanglethe direct e�ects of stress on mental health fromthe overall relationship induced by negative a�ect-ivity. Controlling for a simultaneously taken traitmeasure like anxiety may have too strong an e�ectif that scale is also measuring anxiety state,22 as islikely if respondents ®nd it di�cult to make adistinction between how they generally feel andhow they feel at the moment. On the other hand, iftrait anxiety is not a perfect measure of negativea�ectivity, controlling for it will have too weak ane�ect; for example, elements of depression orhostility may contribute to the correlation betweenstressors and General Health Questionnaire aftertrait anxiety is removed.

In conclusion, the stress scale previously devel-oped by Cushway et al.2 for mental healthprofessionals has proved to be a useful and sensi-tive instrument for detecting sources of stress inother groups of health professionals too. Thesubscale which had the strongest direct e�ect onboth psychological distress and job dissatisfactionwas lack of resources, while workload was the maincontributor to a perception that the job wasdemanding, and this in turn contributed to bothdistress and dissatisfaction. Of the two directoratessampled, workers in the Surgical Directorate wereclearly more stressed by both lack of resources andworkload. Di�erences between the directorates inthe outcome measures job satisfaction and distressre¯ected these di�erences in the stressors, but werenot quite large enough to reach signi®cance on thefairly conservative statistical criteria used. Thisnarrowing of the di�erences is no doubt in partbecause there are other in¯uences on the outcomevariables which we did not measure, but also inpart because the levels of distress were relativelyhigh in both directorates, as indicated by theGeneral Health Questionnaire caseness levels. Inprevious studies we have found caseness frequenciesin nurses to be about 30 percent, itself a high®gure.4,25 Here caseness overall was 37 percent(31 percent in mental health and 44 percent insurgical sta�). Since caseness predicts future



psychiatric referral, and therefore absenteeism,health-related illness and dropout, these ratesshould be of concern to the employer. Our mainrecommendation would be to reduce stress fromlack of resources and workload by appropriatestructural adjustments, especially in the SurgicalDirectorate, and to initiate and promote stressmanagement among all sta� so as to improve levelsof anxiety and hostility.

REFERENCES

1. Sutherland, V. J. and Cooper, C. L. UnderstandingStress: A Psychological Perspective for HealthProfessionals. Chapman and Hall, London, 1990.

2. Cushway, D., Tyler, P. A. and Nolan, P.Development of a stress scale for mental healthprofessionals. Brit. J. Clin. Psychol. 1996; 35:279±295.

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Stress and wellbeing in healthcare staff: the role of negative affectivity, and perceptions of job demand and discretion