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Effects of neu roticism and workload history on performance

Article in Per sonality and Individual Diff erenc es · Januar y 2004

DOI: 10.1016/S0191-8869(03)00108-9

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Eugenia F uenzalida

University of Oklahoma

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James B Hittner

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The user has requested enhanc ement of the do wnloaded file. Eﬀects of neuroticism and workload history on performance

Luz-Eugenia Cox-Fuenzalida a,*, Rhonda Swickert b, James B. Hittner b

aDepartment of Psychology, University of Oklahoma, 455 W. Lindsey Street, DHT-705, Norman, OK 73019, USA bDepartment of Psychology, College of Charleston, 66 George Street, Charleston, SC 29424, USA

Received 25 July 2002; received in revised form 23 December 2002; accepted 7 February 2003

Abstract

This study manipulated workload levels to test Eysenck’s theory of neuroticism by examining indivi-

duals’ diﬀerential responses to the stress of sudden shifts in workload. A sample of 194 participants who

had completed an inventory to assess neuroticism were randomly assigned to either a High-to-Low or

Low-to-High testing condition. Participants performed an auditory vigilance task while reaction time and

correct responses were assessed. Multiple regression analyses were conducted and results indicated that

higher levels of neuroticism were associated with decreased reaction time in both conditions. In addition,

individuals higher in neuroticism evidenced fewer correct responses in the Low-to-High workload condi-

tion. Results of this study are generally consistent with Eysenck’s theory of neuroticism.

Keywords:Neuroticism; Workload history; Task performance; Stress

The concept of neuroticism has received considerable attention in the stress and coping litera-

ture as it is believed to be an important predictor of how people deal with stressful events.

Although many theories have been proposed to explain this dimension, one of the most widely

cited is Hans Eysenck’s theory.Eysenck (1967)deﬁned neuroticism as a dimension that ranges

from emotional stability to instability and he suggested that individual diﬀerences in neuroticism

are a result of arousal diﬀerences that are mediated by the limbic system. The putative function of

the limbic system is to regulate autonomic and emotional reactions, in particular, reactions that

are cued by physically or psychologically stressful experiences (Eysenck, 1967). Consequently,

individuals who are high in neuroticism, compared with those who are low, are believed to evi-

dence greater activation of the limbic system when responding to environmental stressors. This

doi:10.1016/S0191-8869(03)00108-9

Personality and Individual Differences 36 (2004) 447–456

www.elsevier.com/locate/paid

* Corresponding author. Tel.: +1-405-325-4511; fax: +1-405-325-4737.

E-mail address:[email protected] (L.-E. Cox-Fuenzalida). diﬀerential autonomic arousal level is believed to form the basis for the behavioral diﬀerences

observed between those scoring high and low in neuroticism.

Although behavioral diﬀerences across the neuroticism continuum have been examined using a

variety of approaches, one important strategy used to test Eysenck’s arousal-based theory

involves the examination of performance diﬀerences between high and low neurotics using com-

puter-based human performance tasks. Indeed, several studies have demonstrated that indivi-

duals scoring high in neuroticism (and trait anxiety) typically perform more poorly on a variety

of tasks compared with those low in neuroticism (Eysenck, 1983; Eysenck & Eysenck, 1985;

Spence & Spence, 1966). Typically, the detrimental eﬀects of neuroticism are particularly evident

in studies using vigilance and monitoring tasks—tasks that require high levels of attention (for

reviews, seeEysenck, 1983; Matthews & Deary, 1998). For example,Newton, Slade, Butler, and

Murphy (1992)conducted a study with 123 participants that employed a visual search task

requiring participants to scan a random display of letters to determine the presence or absence of

a target letter. This study found neuroticism to be signiﬁcantly related to slower reaction time in

the predicted direction, that is, high neurotics evidenced slower reaction times. Although some

studies have found an association between neuroticism and improved performance (Eysenck &

Calvo, 1992), generally, ﬁndings are consistent withNewton et al. (1992)suggesting that neuro-

ticism eﬀectively predicts decrements in performance on vigilance tasks (Darke, 1988; Eysenck,

1992, 1997).

In addition to predicting simple vigilance and monitoring task performance, studies have also

demonstrated that neuroticism inﬂuences performance on other, more complex, types of tasks.

For instance,Mayer (1977)conducted a study manipulating task diﬃculty while examining the

eﬀect of trait anxiety on easy versus diﬃcult tasks. He concluded that although high trait anxiety

facilitated performance on easy tasks (requiring simple, rote problems—e.g. searching for the

letter ‘‘a’’), it had a detrimental eﬀect on diﬃcult tasks (e.g. anagram solving).

Although the studies cited earlier have established a link between neuroticism and task perfor-

mance, to date little is known about the relationship between neuroticism and basic performance

dynamicssuch as variability in workload, or changes in task demand. In other words, while pre-

vious research seems to be generally consistent with Eysenck’s arousal-based theory of neuroti-

cism, most of these performance-based studies lack generalizability because they do not examine

parameters associated with real-world work environments, such as changing workload levels. The

study of workload history may help to address this problem.

The study of workload history typically involves the manipulation of workload levels over time

with individuals moving from either high-to-low, or low-to-high, workload levels. Because per-

formance is examined in this manner, the study of workload history might be considered more

ecologically valid than less dynamic approaches (e.g. ﬁxed workload level studies). Currently,

little is known about the eﬀects of neuroticism and workload history on performance, however,

there is a body of work that has examined the manner in which workload shifts inﬂuence general

performance. One consistent ﬁnding reported in the workload history literature suggests that

there is a signiﬁcant decrement in performance following a sudden decrease in workload level

(Cumming & Croft, 1973; Goldberg & Stewart, 1980; Matthews, 1986). In a recent study, how-

ever,Cox-Fuenzalida (2000)found that either a sudden decrease or increase in workload level

results in a signiﬁcant performance decrement. One explanation for the performance decrements

following both types of workload shift is that any change in workload conditions might serve as a

448L.-E. Cox-Fuenzalida et al. / Personality and Individual Diﬀerences 36 (2004) 447–456 stimulus that induces stress. In fact, it has been widely discussed in stress literature that one

essential component of stress is change in environmental conditions (Holmes & Rahe, 1967;

Selye, 1956). Therefore, one might argue that the study of workload history creates the necessary

conditions for directly studying stress responses and, in so doing, allows for a direct test of neu-

roticism theory. Moreover, by manipulating stress in this manner (i.e. by changing workload

levels), this approach may represent a more ecologically valid procedure for testing Eysenck’s

theory of neuroticism than has been utilized by previous studies. Therefore, the purpose of this

study was to examine the association between neuroticism and task performance across two dif-

ferent types of changing workload conditions (Low-to-High versus High-to-Low). Given that

higher levels of neuroticism are believed to be associated with greater stress-proneness, and that a

sudden change in workload constitutes a stressful event, it was hypothesized that neuroticism

would be signiﬁcantly positively associated with performance decrements following either a sud-

den increase or decrease in workload demand.

1. Method

1.1. Participants

Participants were 194 undergraduate students (103 females, 91 males) from the University of

Oklahoma. Participants were randomly selected from a larger pool of 450 lower division psy-

chology students who had participated in a pretesting session in which neuroticism was assessed.

Following the random selection procedure, participants were contacted by telephone and invited

to participate in the study.

1.2. Materials

A computer-based version of theBakan Vigilance Task (1959)was utilized. The Bakan is an

auditory vigilance task comprised of a sequence of digits presented to participants by way of

earphones. Each training and test trial was 3 min in duration. During each trial, participants were

instructed to detect odd–even–odd sequences of digits (the signal, e.g. 7–8–3). Participants were

directed to press a speciﬁed key on the computer keyboard when they detected a signal. A total of

10 signals were presented in each 3-min period among a string of random digits for the high and

low workload conditions (225 and 90 digits total, respectively). Workload level was manipulated

by changing the speed of digit presentation (i.e. high workload consisted of 1 digit every 0.8 s and

low workload consisted of 1 digit every 2 s). In other words, the number of signals was the same

for both high and low workload conditions but the total number of digits, and the diﬃculty level,

varied due to digit rate presentation during the trial. Following signal presentation, the time out

period for participants’ responses was 4.8 s. An error was recorded if the participant did not

respond within this time frame.

The Eysenck Personality Inventory (EPI, Form A;Eysenck & Eysenck, 1968) was used to

assess the dimension of neuroticism. Items on the Neuroticism Scale of the EPI measure an

individual’s level of emotional stability versus emotional reactivity. Higher scores indicate greater

levels of neuroticism. Reliability estimates for the EPI neuroticism scale range from 0.84 to 0.92,

L.-E. Cox-Fuenzalida et al. / Personality and Individual Diﬀerences 36 (2004) 447–456449 while internal consistency coeﬃcients range from 0.89 to 0.95. Construct validity for this test is

reported in the EPI Manual (Eysenck & Eysenck, 1968). In the current study the mean of neu-

roticism was 11.08 with a standard deviation of 4.51 which is generally consistent with normative

data reported in the EPI.

1.3. Procedure

When participants arrived at the laboratory they were seated at individual workstations and

asked to complete informed consent forms. Workstation partitions minimized distraction from

other participants yet permitted individuals to view the experimenter during instruction admin-

istration.

1.4. Training and baseline data collection

Participants performed the Bakan Vigilance Task during three phases: training, baseline, and

the experimental testing session.Table 1presents the counterbalanced orderings for all training,

baseline, and test trials. Each of the 194 participants was block randomized to one of the four

training/baseline/testing sequences inTable 1.

Each participant was ﬁrst familiarized with the location and operation of the computer

response keys relevant for performing the monitoring task. Participants then completed an initial

feedback trial followed by an 18-min training session (three, 3-min trials at high diﬃculty and

three, 3-min trials at low diﬃculty, counterbalanced in their order of presentation) to ensure

understanding of task instructions and to lessen the likelihood of the test trials being con-

taminated by learning eﬀects. The training regimen was patterned after that used bySchlegel and

Gilliland (1990), who found that thorough instructions followed by ﬁve to six, 3-min trials were

suﬃcient to produce reasonably asymptotic performance on a variety of human performance

tasks. Training session trials were followed by an 18-min baseline session (three, 3-min trials at

high diﬃculty and three, 3-min trials at low diﬃculty, in counterbalanced order) to establish

baseline data for later comparisons. To minimize fatigue, 5-min rest breaks were given between

each series of three training and three baseline trials. During these breaks, participants were

required to engage in a low-demand distracter task (i.e. completion of participant demographic

survey). The three trials of either training or baseline were each 3 min long and were presented

with no discernable break between trials (i.e. the task appeared to be nine continuous minutes).

Following the second series of three baseline trials and prior to the testing session, participants

were given a 15-min break.

1.5. Testing session

A participant’s assignment to the High-to-Low or Low-to-High testing condition was based on

the training/baseline/testing protocol sequence to which the participant was originally block

randomly assigned (seeTable 1). During the test session, participants in the High-to-Low condi-

tion engaged in three, 3-min trials at high task diﬃculty followed immediately by a 3-min trial at

low task diﬃculty. In contrast, participants in the Low-to-High test condition engaged in three, 3-

min trials at low task diﬃculty followed immediately by a 3-min trial at high task diﬃculty. These

450L.-E. Cox-Fuenzalida et al. / Personality and Individual Diﬀerences 36 (2004) 447–456 Table 1

Counterbalanced orderings for training, baseline and test trials for Low-to-High and High-to-Low conditions

L.-E. Cox-Fuenzalida et al. / Personality and Individual Diﬀerences 36 (2004) 447–456451 two test conditions created a situation where participants developed a workload history at one

workload level and then moved immediately to a dramatically diﬀerent workload level. Thus,

transitions between workload levels during the High-to-Low and Low-to-High test sessions were

uninterrupted by rest periods and consequently were perceived by participants as 12 min of con-

tinuous work. Participants were tested between the hours of 9.00 a.m. and 4.00 p.m. to control

for time-of-day eﬀects (Revelle, Humphreys, Simon, & Gilliland, 1980).

2. Results

The two dependent variables, reaction time and number of correct responses, were analyzed

separately. In addition, for each dependent variable, the Low-to-High and High-to-Low work-

load training conditions were ﬁrst examined independently before being compared. Finally, for

each dependent variable, only the last 3-min trial of the 12-min testing trial was considered in the

analyses. Analyses were limited to this trial because only the last trial reﬂects the eﬀects of chan-

ging workload level. Means and standard deviations for the reaction time and correct response

variables, for both the baseline and testing conditions, are presented inTable 2.

Prior to addressing the primary hypotheses, the univariate distributions for the two dependent

variables, across both workload training conditions, and the independent variable of neuroticism,

were examined for departures from normality. Due to the signiﬁcant negative skewness of the

correct response variables in both conditions, and the signiﬁcant positive skewness of the reaction

time data in both conditions, these variables were transformed toward normality usingManly’s

(1976)single parameter exponential transformation. These transformed variables, in turn, were

used in all inferential data analyses.

Given that all of the variables in the study were continuously scaled, a multiple regression

approach was used to analyze the data. In particular, prior to examining the inﬂuence of neuro-

ticism on testing performance, the baseline level of performance was controlled for by regressing

the testing variable on the baseline variable, and then saving the standardized residuals, or

residualized change scores, as a new variable. The residualized change scores—free from the

inﬂuence of baseline training performance—were then analyzed as the dependent variable of

interest. To screen for bivariate outliers, scatterplots were examined (xaxis=neuroticism;y

axis=residualized scores) and all extreme outliers that deviated from the swarm of data points

were identiﬁed. Next, a regression analysis was conducted, excluding the bivariate outliers, in

which the residualized scores were regressed onto neuroticism. Results for the reaction time con-

ditions are as follows. For the Low-to-High condition (n=89 after removing 2 bivariate outliers),

Table 2

Means and standard deviations by testing condition

Low-to-High

reaction timeHigh-to-Low

reaction timeLow-to-High

correct responseHigh-to-Low

correct response

Baseline 0.81 (S.D.=0.37) 0.82 (S.D.=0.15) 6.80 (S.D.=1.97) 9.23 (S.D.=1.54)

Testing 0.94 (S.D.=0.45) 0.87 (S.D.=0.24) 6.15 (S.D.=2.08) 8.78 (S.D.=1.70)

Note. Reaction time is measured in seconds and correct response scores can range from 0 to 10. 452L.-E. Cox-Fuenzalida et al. / Personality and Individual Diﬀerences 36 (2004) 447–456 neuroticism was a signiﬁcant predictor of testing performance accounting for 5.7% of the var-

iance [t(87)=2.29,P=0.024, =0.24]. In the High-to-Low condition (n=103, no bivariate out-

liers), neuroticism also signiﬁcantly predicted testing performance accounting for 4.2% of the

variance [t(101)=2.10,P=0.038, =0.21]. To determine whether the strength of association

between neuroticism and reaction time performance diﬀered across the two workload conditions

(Low-to-High versus High-to-Low), a Fisher’sz-test for independent regression coeﬃcients was

conducted. The result of thez-test was statistically nonsigniﬁcant (z=0.15,P>0.05).

In analyzing the correct response variables, the same approach as described above for the

reaction time data was utilized. Regarding the Low-to-High condition (n=84 after removing 7

bivariate outliers), neuroticism was a signiﬁcant predictor of testing performance accounting for

6.6% of the variance [t(82)= 2.42,P=0.018, = 0.26]. However, in the High-to-Low condi-

tion (n=96 after removing 7 bivariate outliers), neuroticism was not a signiﬁcant predictor of

testing performance [t(94)= 1.14,P=0.259, = 0.12]. Despite this diﬀerence across the two

workload conditions, the result of a Fisher’sz-test comparing the two regression coeﬃcients was

not statistically signiﬁcant (z=0.80,P>0.05).

3. Discussion

This study is the ﬁrst to suggest that the examination of workload history might provide a

systematic method for testing Eysenck’s theory of neuroticism. It was hypothesized that higher

levels of neuroticism would be associated with signiﬁcant decrements in performance following

changes in workload history. Results revealed signiﬁcant ﬁndings conﬁrming this prediction for

reaction time in both conditions (High-to-Low and Low-to-High). Indeed, it appears that at least

in terms of reaction time, either a sudden increase or decrease in workload can result in a sig-

niﬁcant performance decrement for those scoring higher in neuroticism. Regarding the correct

response data, individuals scoring higher in neuroticism showed a signiﬁcant performance decre-

ment only in the Low-to-High workload condition. There was no signiﬁcant association between

neuroticism and performance in the High-to-Low condition, although the data did show a trend

in the expected direction.

These ﬁndings add to a growing body of research suggesting that individuals high in neuroti-

cism adapt poorly to changing environmental conditions. For instance, researchers have noted

that individuals higher in neuroticism report greater levels of psychological distress when coping

with job relocation (Moyle & Parkes, 1999), and they adapt more poorly to shift work changes

(Akerstedt and Theorell, 1976). Additionally, it has also been found that individuals higher in

neuroticism are less likely to change work environments compared to those lower in neuroticism,

perhaps because of the aversiveness of changing work environments (for a review, seeTokar,

Fischer, & Subich, 1998). The ﬁndings of the present investigation complement the aforemen-

tioned studies in that unlike previous research that has focused on psychological and physi-

ological outcome measures, the present inquiry documented the interactive eﬀects of neuroticism

and changing workload conditions on behavioral performance indices.

While the ﬁndings of this study complement previous research and appear supportive of

Eysenck’s theory of neuroticism, it should be noted that other factors might also account for

these eﬀects. For example, one alternative interpretation of these results is that a vigilance

L.-E. Cox-Fuenzalida et al. / Personality and Individual Diﬀerences 36 (2004) 447–456453 decrement due to either fatigue or time-on-task, might explain the reduction in performance.

However, it is well-documented in the human performance literature that the vigilance

decrement is especially sensitive to event rate (Davies & Parasuraman, 1982; Parasuraman &

Davies, 1977; See, Howe, Warm & Dember, 1995). That is, according to previous research,

an increase in event presentation (e.g. the Low-to High shift) should reduce perceptual sen-

sitivity, resulting in degraded performance (Matthews, Davies, Westerman, & Stammers,

2000). Therefore, if time-on-task or fatigue were signiﬁcant factors in this experiment, a

stronger decrement in performance would be expected moving from a Low-to-High than a

High-to-Low workload level due to the diﬀerence in event rate between the two conditions.

Contrary to this prediction, in the present study the performance decrement moving from base-

line to testing was generally consistent across the two workload conditions (High-to-Low and

Low-to-High) for both reaction time and correct responses (seeTable 2). Consequently, this

alternative interpretation based on a vigilance decrement due to time-on-task or fatigue does not

appear applicable.

Another interpretation of the present ﬁndings can be derived from research on cognitive

appraisal mechanisms. This literature suggests that an individual’s appraisal of a situation can

strongly inﬂuence the subjective experience of stress (Lazarus, 1980; Lazarus & Folkman, 1984).

In addition, studies in personality research suggest that neuroticism may be associated with

maladaptive appraisal styles. While some individuals are able to handle signiﬁcant disturbances in

stride, others may be anxious when faced with relatively minor challenges (for a review of

appraisal and emotion, seeWells & Matthews, 1994). Therefore, individuals who score high in

neuroticism, compared with those who score low, might interpret the shift (or change) in work-

load more negatively. Such a negative appraisal might adversely aﬀect mood, attention and con-

centration, which could then negatively impact performance. Future studies might include a

subjective stress questionnaire to evaluate how stressful the sudden change in workload is per-

ceived by participants.

A ﬁnal alternative explanation for these results draws upon the relationship between neuroti-

cism and coping. To illustrate, a change or shift in workload requires a coping response. The lit-

erature suggests that in response to stressful events, individuals scoring higher in neuroticism

cope less adaptively (e.g., are less task-focused and more emotion-focused) than those scoring

lower in neuroticism (Dorn & Matthews, 1992; Endler & Parker, 1990; Matthews et al., 2000;

McCrae & Costa, 1986). In fact, participants high in neuroticism often lack conﬁdence in their

abilities, and tend to employ coping strategies (e.g. worry) that are likely to impair performance

(Wells & Matthews, 1994). In other words, in response to the sudden workload shift, individuals

high in neuroticism might use less adaptive coping strategies thereby resulting in poorer perfor-

mance. Future studies could employ a measure to investigate diﬀerential coping responses to the

workload shifts.

In conclusion, results of this study suggest that individuals across the neuroticism continuum

respond diﬀerently to sudden changes in workload level, though more studies are necessary

before any ﬁrm conclusions can be drawn. While these ﬁndings are consistent with Eysenck’s

theoretical model of neuroticism, they might also be accounted for by cognitive-behavioral pro-

cesses (e.g. cognitive appraisal, coping strategies). Additional work in this area might begin by

utilizing a workload history approach to examine these alternative explanations for the eﬀects of

neuroticism on performance.

454L.-E. Cox-Fuenzalida et al. / Personality and Individual Diﬀerences 36 (2004) 447–456 Acknowledgements

The authors express their gratitude to Dr. Gerald Matthews and Dr. Kirby Gilliland for their

many helpful suggestions.

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