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Personality and Attention: Levels of Neuroticism and Extraversion Can Predict Attentional Performance during a Change Detection Task a
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Sowon Hahn , Daniel R. Buttaccio , Jungwon Hahn & Taehun Lee a
Department of Psychology, University of Oklahoma Accepted author version posted online: 24 Mar 2015.
Click for updates To cite this article: Sowon Hahn, Daniel R. Buttaccio, Jungwon Hahn & Taehun Lee (2015): Personality and Attention: Levels of Neuroticism and Extraversion Can Predict Attentional Performance during a Change Detection Task, The Quarterly Journal of Experimental Psychology, DOI: 10.1080/17470218.2015.1032986 To link to this article: http://dx.doi.org/10.1080/17470218.2015.1032986
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Publisher: Taylor & Francis & The Experimental Psychology Society Journal: The Quarterly Journal of Experimental Psychology DOI: 10.1080/17470218.2015.1032986 RUNNING HEAD: PERSONALITY AND ATTENTION
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Personality and Attention: Levels of Neuroticism and Extraversion Can Predict Attentional
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Sowon Hahn, Daniel R. Buttaccio, Jungwon Hahn, & Taehun Lee Department of Psychology
Please address correspondence to:
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Department of Psychology
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Sowon Hahn, Ph.D.
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University of Oklahoma
The University of Oklahoma
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455 W. Lindsey St.
Norman, OK 73019
Phone: (405) 325-1620
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Performance during a Change Detection Task
Email: [email protected]
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Abstract The present study demonstrates that levels of extraversion and neuroticism can predict attentional performance during a change detection task. After completing a change detection task built on the flicker paradigm, participants were assessed for personality traits using the EPQ-R.
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Multiple regression analyses revealed that higher levels of extraversion predict increased change
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detection accuracies, while higher levels of neuroticism predict decreased change detection
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fixation dwell times. Hierarchical regression analyses further revealed that eye movement
measures mediate the relationship between neuroticism and change detection accuracies. Based
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on the current results, we propose that neuroticism is associated with decreased attentional control over the visual field, presumably due to decreased attentional disengagement. Extraversion can predict increased attentional performance, but the effect is smaller than the
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relationship between neuroticism and attention.
Personality and Attention: Levels of Neuroticism and Extraversion Can Predict Attentional Performance during a Change Detection Task
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Attentional paradigms are frequently used in personality research, but many studies
neglected the distinction between functionally and anatomically separate attentional mechanisms.
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accuracies. In addition, neurotic individuals exhibited decreased sensitivity A′ and increased
For instance, spatial orienting is supported by the posterior parietal cortex while detection or discrimination is supported by the anterior cortex (Posner & Peterson, 1990). Vigilance, based on the subcortical regions of the brain, is another distinct attentional mechanism and arousal plays an important role in vigilance tasks. According to the arousal theory of personality (Eysenck, 1967), introverts have higher cortical arousal than extraverts and therefore perform well at low
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levels of stimulation. Extraverts, on the other hand, are prone to under-arousal and expected to show performance decrement during vigilance tasks. Given the close connection between arousal and vigilance task performance, much research has investigated the relationship between personality and vigilance (Koelega, 1992).
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Vigilance is not the only attentional mechanism associated with personality. By using the
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spatial orienting task, Derryberry and Reed (1994) found that extraverts are relatively slow
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negative ones. It has been shown that individuals with high levels of anxiety have trouble disengaging attention from threatening stimuli (Fox et al., 2001). In addition, anxiety is
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associated with general attentional control deficits (Eysenck, Derakshan, Santos, & Calvo, 2007). Studies using the attentional blink paradigm report that anxiety and neuroticism predict larger attentional blink costs, whereas openness and extraversion predict smaller attentional blink costs (Bredemeier et al, 2011; MacLean & Arnell, 2010). These studies suggest that personality traits
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may be indicative of individual differences of attentional control and disengagement. Gazing plays a significant role in guiding the direction of attention. Researchers have also shown that personality traits are associated with individual differences in eye movement control
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(Isaacowitz, 2005; Rauthmann et al., 2012). Using the natural viewing condition, Issacowitz (2005) found that optimists had a significantly fewer number of fixations on negative images
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shifting attention away from positive locations and introverts are slow shifting away from
than pessimists did. In addition, personality traits are not only associated with the direction of the gaze but also with eye movement parameters beyond stimulus variations. For instance, Rauthmann et al. (2012) found that individuals with high levels of neuroticism exhibited longer fixation times and a fewer number of fixations, while extraversion was associated with shorter dwell times and a higher number of fixations.
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One potential mechanism for the relationship between personality and attention is the affective state associated with personality, such that extraversion is associated with positive affect and neuroticism with negative affect (Watson & Clark, 1992). Psychologists have long studied the relationship between emotion and attention. Our affective states influence not only
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what we attend to, but also how we attend to the world. In other words, affect influences whether
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we focus on the individual trees or on the forest as a whole (Fredrickson & Branigan, 2005).
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tension lead to a decreased number of cues utilized from the environment. In the visual field, a reduction of flexible cue utilization can be equivalent to narrowed attentional breadth. Indeed,
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much research has supported that positive affect broadens and negative affect narrows the scope of attention (Fredrickson & Branigan, 2005; Rowe, Hirsh, & Anderson, 2007). Interestingly, earlier findings for the relationship between affect and attention came from research examining affect-related personality traits. For instance, research showed that positive mood and optimism
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were associated with global bias, while anxiety and depression were associated with local bias (Basso, Schefft, Ris & Dember, 1996).
In the present study, we employed a change detection task to investigate the interaction
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between personality and attention. We adopted the change detection paradigm to investigate attentional distribution over the visual field as well as effective attentional filtering. Perceiving
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According to Easterbrook’s cue-utilization theory (1959), suboptimal affective states such as
details and changes in the environment is fundamental to our survival and safety. However,
humans are surprisingly slow to detect changes in the environment and often fail to detect large changes with the presence of a brief visual disruption, a phenomenon known as change blindness (Rensink, O’Regan, & Clark, 1997). We adopted a flicker paradigm in which participants viewed a sequence of displays alternating between an original and a modified image and were required
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to indicate the presence or absence of a change in each of the trial sequences. Previous studies investigating the relationship between personality and spatial attention often employed a cueing paradigm in which participants were required to move attention towards or away from the cued location (Derryberry & Reed, 1994). In the present study, we investigated individual differences
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of visual attention using a change detection paradigm, in which participants scan the visual
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display with their eyes moving freely. Based on previous studies, we hypothesized that
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performance, and that neuroticism, correlated with decreased attentional inhibition and eye movements, would predict decreased change detection performance.
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Method Participants
Eighty students from the introductory psychology class at the University of Oklahoma participated in the study for course credit. The age of participants ranged from 18 to 25 years
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(mean age = 19.1), and 51 were females. Eight of them showed less than 50% accuracy or more than 30% no response trials, and were thus excluded from the analyses. Task and Stimuli
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Each participant conducted a computerized change detection task and was administered
for the Revised Eysenck Personality Questionnaire (EPQ-R; Eysenck, Eysenck, & Barrett, 1985).
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extraversion, associated with wide attentional breadth would predict increased change detection
The EPQ-R is one of the most widely used and well-researched personality instruments, and includes the extraversion (E), neuroticism (N), psychoticism (P), and lie (L) scales. In the present study, reliabilities for E and N scales, as measured by Cronbach's coefficient alpha, are .860
and .861, respectively.
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The stimulus display presentation and response collection were controlled by a 3-GHz Pentium 4 computer and two 17’ SVGA monitors. A Viewpoint Eyetracker by Arrington Research was used to record eye movements. The eyetracker utilized the infrared video tracking method to capture the participant’s pupil and corneal reflection and collected monocular eye
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movement information with 60 Hz sampling rates and a spatial resolution of .15º visual arc.
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Participants’ head movements were minimized with the QuickClamp head positioner and a chin
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abnormalities of eye movements. Before the change detection experiment was initiated, the x-y coordinates of the eye gaze were calibrated for the stimulus display. Three types of eye
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movement measures were collected: initial saccade latency, number of saccadic eye movements per trial, and average fixation time. In the eye movement analyses, we included the number of saccades and fixation dwell time while participants were searching the display. For the change detection task, 45 digital photographs of outdoor scenes were used as
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flicker images. The photographs were taken from local parks, farms, or roadways. Examples of the stimulus set are listed in the Appendix. To keep the emotional neutrality of the pictures, we did not include any persons or animals. The modified image was different from the original
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image by a single object. For a third of the trials, two images were identical. Procedure
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rest. Throughout the task, the experimenter sat in front of the second monitor to check for any
For the visual change detection task, each trial sequence began with a fixation cross on
the center of the display. Participants pressed the space bar to initiate the flicker sequence in which the original image (A) and the modified image (A′) were alternately displayed (i.e., A, A′, A, A′). Every image was displayed for 250 ms with a blank interval of 100 ms. Participants were instructed to view the sequentially alternating images and determine whether there was a change
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between the images by pressing one of the two keys. The ‘Z’ key and the ‘?/’ key were used for the change presence and absence responses, and the key assignment was counterbalanced across participants. Participants were not instructed in terms of the speed of the responses. If participants did not respond for 12 seconds, the trial ended and it was considered a change-
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absence response. The change detection task was composed of 45 trials with different set of
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images for each trial.
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Correlation and multiple regression analyses were conducted to examine the relationship between personality traits and attentional performance during the change detection task. The
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extraversion and neuroticism scores for each individual were calculated following the EPQ-R scoring instructions. The extraversion scores varied from 6 to 22 (M = 15.1, SD = 4.52) and the neuroticism scores varied from 2 to 24 (M = 11.9, SD = 5.45). The overall change detection accuracy was calculated by collapsing across change and no-change conditions. For the RT
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analyses, we included only the correct change-present trials.
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(Insert Figure 1 about here)
We adopted a matrix plot to concisely present the pairwise relationships between
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Results
personality variables and change detection accuracy, with multiple variables plotted against each other at a time. Figure 1 presents the matrix plot for change detection accuracy, extraversion and neuroticism. Correlational analyses support that extraversion is positively correlated with the change detection accuracy (r = .31, p < .01), and neuroticism is negatively correlated with the change detection accuracy (r = -.33, p < .01). In addition, extraversion and neuroticism scores
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are negatively correlated (r = -.27, p < .01). Although extraversion and neuroticism are theoretically independent dimensions, it is not uncommon to find negative correlations between these scores in the real world samples. We further conducted multiple regression analyses to identify the unique effect of
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extraversion (neuroticism) after considering the effect of neuroticism (extraversion). Table 1
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presents the summary of the multiple regression analyses. For the accuracy variable, extraversion
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considering the effect of neuroticism, extraverts were expected to be more accurate during the change detection task than introverts. Neuroticism showed significant negative regression
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weights (b = -.005. β = -.269, p < .03), indicating that after considering the effect of extraverion, individuals with high neuroticism scores were expected to be less accurate. Our task can be conceptualized using a signal detection model, so we also analyzed
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participants’ sensitivity and response bias by using the nonparametric measures of sensitivity A′
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and response bias B″d. Note that we used a new measure of bias B″d instead of B″ due to limitations of B″ at low levels of discrimination and marked dependence between B″ and A′
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(Donaldson, 1992). In the present study, neuroticism showed significant negative regression weights for the sensitivity A′ (b = -.004, β = -.244, p < .04), revealing that high levels of neuroticism are associated with the low signal-to-noise discriminability. Extraversion did not
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showed significant positive regression weights (b = .005, β = .237, p < .05), indicating that after
show significant regression weights for the sensitivity A′ (b = .005, β = .206, p > .08). For the eye movement measures, neuroticism revealed a significant negative regression weight for the fixation dwell time variable (b = -.002, β = -.249, p < .05), suggesting the association between the levels of neuroticism and eye movement control.
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(Insert Table 1 about here)
In order to further examine the effects of eye movements that might mediate the relationship between personality and attention, we conducted an additional hierarchical
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regression analysis. In this regression analysis, extraversion and neuroticism were entered
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together in the first step, and then the number of saccades and fixation dwell time variables were
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regression weights for extraversion remained the same (b = .005. β = .225, p < .05), but
regression weights for neuroticism became non-significant (b = -.002. β = -.117, p > .3). That is,
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when the eye movement measures were added as mediator variables for personality and attention, the effect of neuroticism on change detection accuracy disappeared. In other words, eye movement measures mediated the effects of neuroticism to predict the change detection accuracy.
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Discussion
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The present study demonstrates that the levels of extraversion and neuroticism can predict attentional performance during a change detection task. Multiple regression analyses support that higher levels of neuroticism predict lower change detection accuracies, whereas
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higher levels of extraversion predict higher change detection accuracies. In addition, higher levels of neuroticism are associated with lower sensitivity A′, indicating decreased selective
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added together in the second step. When the eye movement measures were added to the model,
attention performance. Hierarchical regression analyses also revealed that eye movement parameters, including the number of saccades and fixation dwell times, mediated the effects of neuroticism on change detection accuracies. We consider three possible mechanisms to account for the present findings. First, affective states associated with personality traits can either broaden or reduce attentional breadth,
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modulating attentional performance. The affect-as-information hypothesis proposes that affective cues of mood can serve as immediately accessible information (Schwarz & Clore, 1983). For instance, focusing on global stimuli is usually the dominant strategy (Navon, 1977) and as a result, happy individuals may be more inclined to use global processing strategy. Rowe et al.
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(2007) suggests that positive affect is associated with a relaxation of attentional selection and
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loosened inhibitory control, resulting in increased attentional breadth. Indeed, previous research
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attentional breadth (Pringle et al., 2001).
Second, personality traits may be linked to dispositional tendencies toward more or less
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stringent attentional control. In particular, neuroticism may be associated with impaired attentional selectivity and inhibitory control. Previous research found that neuroticism is particularly associated with decreased attentional control (Bredemeier et al., 2011). In the present study, we found that neuroticism is associated with multiple indexes of attentional performance,
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suggesting a strong link between neuroticism and attention. Third, dispositional differences of eye movement control may account for the observed relationship between personality and attention. In the attention literature, goal-directed eye
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movement is considered as overt shift of attention while attentional movement without eye movements is considered as covert shift of attention (Posner, 1980). Since saccadic eye
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demonstrated a strong correlation between change detection RTs and individual differences of
movements and attention are closely linked, behavioral disposition of eye movement control can guide attention in the visual field. Consistent with previous studies (Rauthmann et al., 2012), neurotic individuals showed longer fixations duration in the present study. In addition, the
present results show that eye movement patterns of neurotic individuals lead to decreased change detection accuracy. Since increased fixation dwell time mediates the decreased change detection
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accuracy, we suggest that the present results are indicative of attentional disengagement deficits associated with neuroticism. Although it is plausible to assume a connection between affect and personality, the present study does not provide direct support for the affect-related attentional modulation.
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Instead, we would like to emphasize the association between neuroticism and decreased
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attentional control as well as the dispositional tendency of eye movement control in guiding
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contribution that personality traits are predictive of attentional performance requiring visual search beyond cuing paradigms.
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One of the limitations of the present study was that we did not collect normative data to ensure the emotional neutrality of the images we used. In fact, outdoor scenes might be considered as slightly positive in valence. However, this limitation does not change the conclusion of the study. The attentional deficit of highly neurotic individuals should decrease
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attentional disengagement, particularly disengagement from emotionally negative stimuli. The present study, however, found that neuroticism is negatively correlated with change detection accuracy even when the stimuli were neutral to slightly positive. In our future study, we plan to
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investigate the effects of stimuli types on the relationship between personality and attention. We will continue to investigate the relationship between personality other behavioral tendencies
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attention. By using the change detection task, the present results can make the unique
including RTs, eye movements, and reaching behavior to further understand factors that are predictive of individual differences of attentional performance. One of the challenges of conducting research bridging individual differences and cognitive performance is to correctly understand interactions and mediations among variables. In the future, we plan to conduct a
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larger scale study to better understand mechanisms underlying individual differences of
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cognitive performance.
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References Basso, M. R., Schefft, B. K., Ris, M., & Dember, W. N. (1996). Mood and global-local visual processing. Journal of the International Neuropsychological Society, 2(3), 249-255. doi:10.1017/S1355617700001193
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Bredemeier, K., Berenbaum, H., Most, S. B., & Simons, D. J. (2011). Links between neuroticism,
rip
emotional distress, and disengaging attention: Evidence from a single-target RSVP task.
us c
Derryberry, D. & Reed, M. A. (1994). Temperament and attention: Orienting toward and away from positive and negative signals. Journal of Personality and Social Psychology, 66, 1128-
M an
1139. doi:http://dx.doi.org/10.1037/0022-3514.66.6.1128
Esterbrook, J. A. (1959). The effect of emotion on cue utilization and the organization of behavior. Psychological Review, 66 (3), 183-201. doi:http://dx.doi.org/10.1037/h0047707 Eysenck, H. J. (1967). The biological basis of personality. Thomas: Springfield, IL.
pt e
d
Eysenck, S. B. G., Eysenck, H. J., & Barrett, P. (1985). A revised version of the psychoticism scale. Personality and Individual Differences, 6, 21-29. doi:10.1016/0191-8869(85)90026-1 Eysenck, M. W., Derakshan, N., Santos, R., & Calvo, M. G. (2007). Attention and cognitive
ce
performance: Attentional control theory. Emotion, 7, 336-353. doi:10.1037/15283542.7.2.336
Ac
Downloaded by [University of Montana] at 08:46 05 April 2015
Cognition and Emotion, 25(8), 1510-1519. doi:10.1080/02699931.2010.549460
Fox, E., Russo, R., Bowles, R., & Dutton, K. (2001). Do threatening stimuli draw or hold visual attention in subclinical anxiety? Journal Of Experimental Psychology: General, 130(4), 681700. doi:10.1037/0096-3445.130.4.681
13
Fredrickson, B. L., & Branigan, C. (2005). Positive emotions broaden the scope of attention and thought-action repertoires. Cognition and Emotion, 19(3), 313-332. doi:10.1080/02699930441000238 Isaacowitz, D. M. (2005). The gaze of the optimist. Personality and Social Psychology Bulletin,
t
31(3), 407-415. doi:10.1177/0146167204271599
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Koelega, H. S. (1992). Extraversion and vigilance performance: 30 years of inconsistencies.
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MacLean, M. H., & Arnell, K. M. (2010). Personality predicts temporal attention cost in the attentional blink paradigm. Psychonomic Bulletin & Review, 17 (4), 556-562.
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doi:10.3758/PBR.17.4.556
Navon, D. (1977). Forest before trees: The precedence of global features in visual perception. Cognitive Psychology, 9(3), 353-383. Retrieved from
http://search.proquest.com/docview/616214525?accountid=12964
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d
Posner, M. I. (1980). Orienting of attention. The Quarterly Journal of Experimental Psychology, 32(1), 3-25. http://search.proquest.com/docview/616495117?accountid=12964 Posner, M. I., & Petersen, S. E. (1990). The attention system of the human brain. Annual Review
ce
of Neuroscience, 13, 25-42. Retrieved from http://search.proquest.com/docview/617759185?accountid=12964
Ac
Downloaded by [University of Montana] at 08:46 05 April 2015
Psychological Bulletin, 112, 239-258. doi:http://dx.doi.org/10.1037/0033-2909.112.2.239
Pringle, H. L., Irwin, D. E., Kramer, A. F., & Atchley, P. (2001). The role of attentional breadth in perceptual change detection. Psychonomic Bulletin & Review, 8(1), 89-95.
doi:10.3758/BF03196143 Rauthmann, J. F., Seubert, C. T., Sachse, P., & Furtner, M. R. (2012). Eyes as windows to the soul: Gazing behavior is related to personality. Journal of Research in Personality, 46(2),
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147-156. doi:10.1016/j.jrp.2011.12.010 Rensink, R., A., O’Regan, J. K., & Clark, J. J. (1997). To see or not to see: The need for attention to perceive changes in scene. Psychological Science, 8, 368-373. doi:10.1111/j.1467-9280.1997.tb00427.x
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Rowe, G., Hirsh, J. B., & Anderson, A. K. (2007). Positive affect increases the breadth of
rip
attentional selection. Proceedings of National Academy of Science, 104, 383-388.
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Schwarz, N., & Clore, G. L. (1983). Mood, misattribution, and judgments of well-being:
Informative and directive functions of affective states. Journal of Personality and Social
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Psychology, 45(3), 513-523. doi:10.1037/0022-3514.45.3.513
Watson, D., & Clark, L. A. (1992). Affects separable and inseparable: On the hierarchical arrangement of the negative affects. Journal of Personality and Social Psychology, 62(3),
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489-505. doi:10.1037/0022-3514.62.3.489
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doi:10.1073/pnas.0605198104
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Appendix
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Examples of the stimulus set including the original and modified images: see Figure A1.
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Figure Captions
Figure 1. The matrix plot illustrates relationships among Extraversion, Neuroticism and Accuracy. The histograms show the frequency distribution of each variable. The lines in the
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scatterplots illustrate linear fitting functions: Neuroticism = 16.84 - .32 * Extraversion,
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Accuracy = .63 + .007 * Extraversion, and Accuracy = .80 - .006 * Neuroticism.
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Table 1 Summary of the multiple regression analyses with Extraversion and Neuroticism as predictor variables
.237 -.269
.146 -1.24
1.87 -13.1
.018 -.153
adj R2
p
6.71
.163
.139
.002 * .042 * .022 *
.889
.025
t
.005 -.005
R2
5.12
.005 -.004
.206 -.244
.991 -1.46
.010 -.012
.120 -.177
.222 -.231
.158 -.199 -.194 -.249
.008 * .081 .039 *
2.10
.057
.030
.130 .158 .077
3.05
.081
.055
.053 .192 .102
-.001 -.002
2.75
.074
.047
.071 .111 .042 *
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-1.61 -2.07
.415 .884 .220
.104
d
1.31 -1.65
-.003
.129
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1.76 -2.09
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2.08 -2.35
F
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β
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Accuracy Overall model Extraversion Neuroticism Target-present RT Overall model Extraversion Neuroticism A′ Overall model Extraversion Neuroticism B″d Overall model Extraversion Neuroticism Number of saccades Overall model Extraversion Neuroticism Fixation dwell time Overall model Extraversion Neuroticism
b
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The Quarterly Journal of Experimental Psychology Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/pqje20
Personality and Attention: Levels of Neuroticism and Extraversion Can Predict Attentional Performance during a Change Detection Task a
a
a
a
Sowon Hahn , Daniel R. Buttaccio , Jungwon Hahn & Taehun Lee a
Department of Psychology, University of Oklahoma Accepted author version posted online: 24 Mar 2015.
Click for updates To cite this article: Sowon Hahn, Daniel R. Buttaccio, Jungwon Hahn & Taehun Lee (2015): Personality and Attention: Levels of Neuroticism and Extraversion Can Predict Attentional Performance during a Change Detection Task, The Quarterly Journal of Experimental Psychology, DOI: 10.1080/17470218.2015.1032986 To link to this article: http://dx.doi.org/10.1080/17470218.2015.1032986
Disclaimer: This is a version of an unedited manuscript that has been accepted for publication. As a service to authors and researchers we are providing this version of the accepted manuscript (AM). Copyediting, typesetting, and review of the resulting proof will be undertaken on this manuscript before final publication of the Version of Record (VoR). During production and pre-press, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal relate to this version also.
PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http:// www.tandfonline.com/page/terms-and-conditions
Publisher: Taylor & Francis & The Experimental Psychology Society Journal: The Quarterly Journal of Experimental Psychology DOI: 10.1080/17470218.2015.1032986 RUNNING HEAD: PERSONALITY AND ATTENTION
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Personality and Attention: Levels of Neuroticism and Extraversion Can Predict Attentional
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Sowon Hahn, Daniel R. Buttaccio, Jungwon Hahn, & Taehun Lee Department of Psychology
Please address correspondence to:
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Department of Psychology
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Sowon Hahn, Ph.D.
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University of Oklahoma
The University of Oklahoma
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455 W. Lindsey St.
Norman, OK 73019
Phone: (405) 325-1620
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Performance during a Change Detection Task
Email: [email protected]
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Abstract The present study demonstrates that levels of extraversion and neuroticism can predict attentional performance during a change detection task. After completing a change detection task built on the flicker paradigm, participants were assessed for personality traits using the EPQ-R.
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Multiple regression analyses revealed that higher levels of extraversion predict increased change
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detection accuracies, while higher levels of neuroticism predict decreased change detection
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fixation dwell times. Hierarchical regression analyses further revealed that eye movement
measures mediate the relationship between neuroticism and change detection accuracies. Based
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on the current results, we propose that neuroticism is associated with decreased attentional control over the visual field, presumably due to decreased attentional disengagement. Extraversion can predict increased attentional performance, but the effect is smaller than the
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relationship between neuroticism and attention.
Personality and Attention: Levels of Neuroticism and Extraversion Can Predict Attentional Performance during a Change Detection Task
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Attentional paradigms are frequently used in personality research, but many studies
neglected the distinction between functionally and anatomically separate attentional mechanisms.
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accuracies. In addition, neurotic individuals exhibited decreased sensitivity A′ and increased
For instance, spatial orienting is supported by the posterior parietal cortex while detection or discrimination is supported by the anterior cortex (Posner & Peterson, 1990). Vigilance, based on the subcortical regions of the brain, is another distinct attentional mechanism and arousal plays an important role in vigilance tasks. According to the arousal theory of personality (Eysenck, 1967), introverts have higher cortical arousal than extraverts and therefore perform well at low
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levels of stimulation. Extraverts, on the other hand, are prone to under-arousal and expected to show performance decrement during vigilance tasks. Given the close connection between arousal and vigilance task performance, much research has investigated the relationship between personality and vigilance (Koelega, 1992).
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Vigilance is not the only attentional mechanism associated with personality. By using the
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spatial orienting task, Derryberry and Reed (1994) found that extraverts are relatively slow
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negative ones. It has been shown that individuals with high levels of anxiety have trouble disengaging attention from threatening stimuli (Fox et al., 2001). In addition, anxiety is
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associated with general attentional control deficits (Eysenck, Derakshan, Santos, & Calvo, 2007). Studies using the attentional blink paradigm report that anxiety and neuroticism predict larger attentional blink costs, whereas openness and extraversion predict smaller attentional blink costs (Bredemeier et al, 2011; MacLean & Arnell, 2010). These studies suggest that personality traits
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may be indicative of individual differences of attentional control and disengagement. Gazing plays a significant role in guiding the direction of attention. Researchers have also shown that personality traits are associated with individual differences in eye movement control
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(Isaacowitz, 2005; Rauthmann et al., 2012). Using the natural viewing condition, Issacowitz (2005) found that optimists had a significantly fewer number of fixations on negative images
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shifting attention away from positive locations and introverts are slow shifting away from
than pessimists did. In addition, personality traits are not only associated with the direction of the gaze but also with eye movement parameters beyond stimulus variations. For instance, Rauthmann et al. (2012) found that individuals with high levels of neuroticism exhibited longer fixation times and a fewer number of fixations, while extraversion was associated with shorter dwell times and a higher number of fixations.
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One potential mechanism for the relationship between personality and attention is the affective state associated with personality, such that extraversion is associated with positive affect and neuroticism with negative affect (Watson & Clark, 1992). Psychologists have long studied the relationship between emotion and attention. Our affective states influence not only
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what we attend to, but also how we attend to the world. In other words, affect influences whether
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we focus on the individual trees or on the forest as a whole (Fredrickson & Branigan, 2005).
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tension lead to a decreased number of cues utilized from the environment. In the visual field, a reduction of flexible cue utilization can be equivalent to narrowed attentional breadth. Indeed,
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much research has supported that positive affect broadens and negative affect narrows the scope of attention (Fredrickson & Branigan, 2005; Rowe, Hirsh, & Anderson, 2007). Interestingly, earlier findings for the relationship between affect and attention came from research examining affect-related personality traits. For instance, research showed that positive mood and optimism
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were associated with global bias, while anxiety and depression were associated with local bias (Basso, Schefft, Ris & Dember, 1996).
In the present study, we employed a change detection task to investigate the interaction
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between personality and attention. We adopted the change detection paradigm to investigate attentional distribution over the visual field as well as effective attentional filtering. Perceiving
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According to Easterbrook’s cue-utilization theory (1959), suboptimal affective states such as
details and changes in the environment is fundamental to our survival and safety. However,
humans are surprisingly slow to detect changes in the environment and often fail to detect large changes with the presence of a brief visual disruption, a phenomenon known as change blindness (Rensink, O’Regan, & Clark, 1997). We adopted a flicker paradigm in which participants viewed a sequence of displays alternating between an original and a modified image and were required
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to indicate the presence or absence of a change in each of the trial sequences. Previous studies investigating the relationship between personality and spatial attention often employed a cueing paradigm in which participants were required to move attention towards or away from the cued location (Derryberry & Reed, 1994). In the present study, we investigated individual differences
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of visual attention using a change detection paradigm, in which participants scan the visual
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display with their eyes moving freely. Based on previous studies, we hypothesized that
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performance, and that neuroticism, correlated with decreased attentional inhibition and eye movements, would predict decreased change detection performance.
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Method Participants
Eighty students from the introductory psychology class at the University of Oklahoma participated in the study for course credit. The age of participants ranged from 18 to 25 years
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(mean age = 19.1), and 51 were females. Eight of them showed less than 50% accuracy or more than 30% no response trials, and were thus excluded from the analyses. Task and Stimuli
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Each participant conducted a computerized change detection task and was administered
for the Revised Eysenck Personality Questionnaire (EPQ-R; Eysenck, Eysenck, & Barrett, 1985).
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extraversion, associated with wide attentional breadth would predict increased change detection
The EPQ-R is one of the most widely used and well-researched personality instruments, and includes the extraversion (E), neuroticism (N), psychoticism (P), and lie (L) scales. In the present study, reliabilities for E and N scales, as measured by Cronbach's coefficient alpha, are .860
and .861, respectively.
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The stimulus display presentation and response collection were controlled by a 3-GHz Pentium 4 computer and two 17’ SVGA monitors. A Viewpoint Eyetracker by Arrington Research was used to record eye movements. The eyetracker utilized the infrared video tracking method to capture the participant’s pupil and corneal reflection and collected monocular eye
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movement information with 60 Hz sampling rates and a spatial resolution of .15º visual arc.
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Participants’ head movements were minimized with the QuickClamp head positioner and a chin
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abnormalities of eye movements. Before the change detection experiment was initiated, the x-y coordinates of the eye gaze were calibrated for the stimulus display. Three types of eye
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movement measures were collected: initial saccade latency, number of saccadic eye movements per trial, and average fixation time. In the eye movement analyses, we included the number of saccades and fixation dwell time while participants were searching the display. For the change detection task, 45 digital photographs of outdoor scenes were used as
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flicker images. The photographs were taken from local parks, farms, or roadways. Examples of the stimulus set are listed in the Appendix. To keep the emotional neutrality of the pictures, we did not include any persons or animals. The modified image was different from the original
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image by a single object. For a third of the trials, two images were identical. Procedure
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rest. Throughout the task, the experimenter sat in front of the second monitor to check for any
For the visual change detection task, each trial sequence began with a fixation cross on
the center of the display. Participants pressed the space bar to initiate the flicker sequence in which the original image (A) and the modified image (A′) were alternately displayed (i.e., A, A′, A, A′). Every image was displayed for 250 ms with a blank interval of 100 ms. Participants were instructed to view the sequentially alternating images and determine whether there was a change
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between the images by pressing one of the two keys. The ‘Z’ key and the ‘?/’ key were used for the change presence and absence responses, and the key assignment was counterbalanced across participants. Participants were not instructed in terms of the speed of the responses. If participants did not respond for 12 seconds, the trial ended and it was considered a change-
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absence response. The change detection task was composed of 45 trials with different set of
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images for each trial.
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Correlation and multiple regression analyses were conducted to examine the relationship between personality traits and attentional performance during the change detection task. The
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extraversion and neuroticism scores for each individual were calculated following the EPQ-R scoring instructions. The extraversion scores varied from 6 to 22 (M = 15.1, SD = 4.52) and the neuroticism scores varied from 2 to 24 (M = 11.9, SD = 5.45). The overall change detection accuracy was calculated by collapsing across change and no-change conditions. For the RT
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analyses, we included only the correct change-present trials.
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(Insert Figure 1 about here)
We adopted a matrix plot to concisely present the pairwise relationships between
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Results
personality variables and change detection accuracy, with multiple variables plotted against each other at a time. Figure 1 presents the matrix plot for change detection accuracy, extraversion and neuroticism. Correlational analyses support that extraversion is positively correlated with the change detection accuracy (r = .31, p < .01), and neuroticism is negatively correlated with the change detection accuracy (r = -.33, p < .01). In addition, extraversion and neuroticism scores
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are negatively correlated (r = -.27, p < .01). Although extraversion and neuroticism are theoretically independent dimensions, it is not uncommon to find negative correlations between these scores in the real world samples. We further conducted multiple regression analyses to identify the unique effect of
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extraversion (neuroticism) after considering the effect of neuroticism (extraversion). Table 1
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presents the summary of the multiple regression analyses. For the accuracy variable, extraversion
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considering the effect of neuroticism, extraverts were expected to be more accurate during the change detection task than introverts. Neuroticism showed significant negative regression
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weights (b = -.005. β = -.269, p < .03), indicating that after considering the effect of extraverion, individuals with high neuroticism scores were expected to be less accurate. Our task can be conceptualized using a signal detection model, so we also analyzed
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participants’ sensitivity and response bias by using the nonparametric measures of sensitivity A′
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and response bias B″d. Note that we used a new measure of bias B″d instead of B″ due to limitations of B″ at low levels of discrimination and marked dependence between B″ and A′
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(Donaldson, 1992). In the present study, neuroticism showed significant negative regression weights for the sensitivity A′ (b = -.004, β = -.244, p < .04), revealing that high levels of neuroticism are associated with the low signal-to-noise discriminability. Extraversion did not
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showed significant positive regression weights (b = .005, β = .237, p < .05), indicating that after
show significant regression weights for the sensitivity A′ (b = .005, β = .206, p > .08). For the eye movement measures, neuroticism revealed a significant negative regression weight for the fixation dwell time variable (b = -.002, β = -.249, p < .05), suggesting the association between the levels of neuroticism and eye movement control.
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(Insert Table 1 about here)
In order to further examine the effects of eye movements that might mediate the relationship between personality and attention, we conducted an additional hierarchical
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regression analysis. In this regression analysis, extraversion and neuroticism were entered
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together in the first step, and then the number of saccades and fixation dwell time variables were
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regression weights for extraversion remained the same (b = .005. β = .225, p < .05), but
regression weights for neuroticism became non-significant (b = -.002. β = -.117, p > .3). That is,
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when the eye movement measures were added as mediator variables for personality and attention, the effect of neuroticism on change detection accuracy disappeared. In other words, eye movement measures mediated the effects of neuroticism to predict the change detection accuracy.
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Discussion
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The present study demonstrates that the levels of extraversion and neuroticism can predict attentional performance during a change detection task. Multiple regression analyses support that higher levels of neuroticism predict lower change detection accuracies, whereas
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higher levels of extraversion predict higher change detection accuracies. In addition, higher levels of neuroticism are associated with lower sensitivity A′, indicating decreased selective
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added together in the second step. When the eye movement measures were added to the model,
attention performance. Hierarchical regression analyses also revealed that eye movement parameters, including the number of saccades and fixation dwell times, mediated the effects of neuroticism on change detection accuracies. We consider three possible mechanisms to account for the present findings. First, affective states associated with personality traits can either broaden or reduce attentional breadth,
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modulating attentional performance. The affect-as-information hypothesis proposes that affective cues of mood can serve as immediately accessible information (Schwarz & Clore, 1983). For instance, focusing on global stimuli is usually the dominant strategy (Navon, 1977) and as a result, happy individuals may be more inclined to use global processing strategy. Rowe et al.
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(2007) suggests that positive affect is associated with a relaxation of attentional selection and
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loosened inhibitory control, resulting in increased attentional breadth. Indeed, previous research
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attentional breadth (Pringle et al., 2001).
Second, personality traits may be linked to dispositional tendencies toward more or less
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stringent attentional control. In particular, neuroticism may be associated with impaired attentional selectivity and inhibitory control. Previous research found that neuroticism is particularly associated with decreased attentional control (Bredemeier et al., 2011). In the present study, we found that neuroticism is associated with multiple indexes of attentional performance,
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suggesting a strong link between neuroticism and attention. Third, dispositional differences of eye movement control may account for the observed relationship between personality and attention. In the attention literature, goal-directed eye
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movement is considered as overt shift of attention while attentional movement without eye movements is considered as covert shift of attention (Posner, 1980). Since saccadic eye
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demonstrated a strong correlation between change detection RTs and individual differences of
movements and attention are closely linked, behavioral disposition of eye movement control can guide attention in the visual field. Consistent with previous studies (Rauthmann et al., 2012), neurotic individuals showed longer fixations duration in the present study. In addition, the
present results show that eye movement patterns of neurotic individuals lead to decreased change detection accuracy. Since increased fixation dwell time mediates the decreased change detection
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accuracy, we suggest that the present results are indicative of attentional disengagement deficits associated with neuroticism. Although it is plausible to assume a connection between affect and personality, the present study does not provide direct support for the affect-related attentional modulation.
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Instead, we would like to emphasize the association between neuroticism and decreased
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attentional control as well as the dispositional tendency of eye movement control in guiding
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contribution that personality traits are predictive of attentional performance requiring visual search beyond cuing paradigms.
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One of the limitations of the present study was that we did not collect normative data to ensure the emotional neutrality of the images we used. In fact, outdoor scenes might be considered as slightly positive in valence. However, this limitation does not change the conclusion of the study. The attentional deficit of highly neurotic individuals should decrease
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attentional disengagement, particularly disengagement from emotionally negative stimuli. The present study, however, found that neuroticism is negatively correlated with change detection accuracy even when the stimuli were neutral to slightly positive. In our future study, we plan to
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investigate the effects of stimuli types on the relationship between personality and attention. We will continue to investigate the relationship between personality other behavioral tendencies
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attention. By using the change detection task, the present results can make the unique
including RTs, eye movements, and reaching behavior to further understand factors that are predictive of individual differences of attentional performance. One of the challenges of conducting research bridging individual differences and cognitive performance is to correctly understand interactions and mediations among variables. In the future, we plan to conduct a
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larger scale study to better understand mechanisms underlying individual differences of
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cognitive performance.
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References Basso, M. R., Schefft, B. K., Ris, M., & Dember, W. N. (1996). Mood and global-local visual processing. Journal of the International Neuropsychological Society, 2(3), 249-255. doi:10.1017/S1355617700001193
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Bredemeier, K., Berenbaum, H., Most, S. B., & Simons, D. J. (2011). Links between neuroticism,
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emotional distress, and disengaging attention: Evidence from a single-target RSVP task.
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Derryberry, D. & Reed, M. A. (1994). Temperament and attention: Orienting toward and away from positive and negative signals. Journal of Personality and Social Psychology, 66, 1128-
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1139. doi:http://dx.doi.org/10.1037/0022-3514.66.6.1128
Esterbrook, J. A. (1959). The effect of emotion on cue utilization and the organization of behavior. Psychological Review, 66 (3), 183-201. doi:http://dx.doi.org/10.1037/h0047707 Eysenck, H. J. (1967). The biological basis of personality. Thomas: Springfield, IL.
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Eysenck, S. B. G., Eysenck, H. J., & Barrett, P. (1985). A revised version of the psychoticism scale. Personality and Individual Differences, 6, 21-29. doi:10.1016/0191-8869(85)90026-1 Eysenck, M. W., Derakshan, N., Santos, R., & Calvo, M. G. (2007). Attention and cognitive
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performance: Attentional control theory. Emotion, 7, 336-353. doi:10.1037/15283542.7.2.336
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Downloaded by [University of Montana] at 08:46 05 April 2015
Cognition and Emotion, 25(8), 1510-1519. doi:10.1080/02699931.2010.549460
Fox, E., Russo, R., Bowles, R., & Dutton, K. (2001). Do threatening stimuli draw or hold visual attention in subclinical anxiety? Journal Of Experimental Psychology: General, 130(4), 681700. doi:10.1037/0096-3445.130.4.681
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Fredrickson, B. L., & Branigan, C. (2005). Positive emotions broaden the scope of attention and thought-action repertoires. Cognition and Emotion, 19(3), 313-332. doi:10.1080/02699930441000238 Isaacowitz, D. M. (2005). The gaze of the optimist. Personality and Social Psychology Bulletin,
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31(3), 407-415. doi:10.1177/0146167204271599
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Koelega, H. S. (1992). Extraversion and vigilance performance: 30 years of inconsistencies.
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MacLean, M. H., & Arnell, K. M. (2010). Personality predicts temporal attention cost in the attentional blink paradigm. Psychonomic Bulletin & Review, 17 (4), 556-562.
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doi:10.3758/PBR.17.4.556
Navon, D. (1977). Forest before trees: The precedence of global features in visual perception. Cognitive Psychology, 9(3), 353-383. Retrieved from
http://search.proquest.com/docview/616214525?accountid=12964
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Posner, M. I. (1980). Orienting of attention. The Quarterly Journal of Experimental Psychology, 32(1), 3-25. http://search.proquest.com/docview/616495117?accountid=12964 Posner, M. I., & Petersen, S. E. (1990). The attention system of the human brain. Annual Review
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of Neuroscience, 13, 25-42. Retrieved from http://search.proquest.com/docview/617759185?accountid=12964
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Downloaded by [University of Montana] at 08:46 05 April 2015
Psychological Bulletin, 112, 239-258. doi:http://dx.doi.org/10.1037/0033-2909.112.2.239
Pringle, H. L., Irwin, D. E., Kramer, A. F., & Atchley, P. (2001). The role of attentional breadth in perceptual change detection. Psychonomic Bulletin & Review, 8(1), 89-95.
doi:10.3758/BF03196143 Rauthmann, J. F., Seubert, C. T., Sachse, P., & Furtner, M. R. (2012). Eyes as windows to the soul: Gazing behavior is related to personality. Journal of Research in Personality, 46(2),
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147-156. doi:10.1016/j.jrp.2011.12.010 Rensink, R., A., O’Regan, J. K., & Clark, J. J. (1997). To see or not to see: The need for attention to perceive changes in scene. Psychological Science, 8, 368-373. doi:10.1111/j.1467-9280.1997.tb00427.x
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Rowe, G., Hirsh, J. B., & Anderson, A. K. (2007). Positive affect increases the breadth of
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attentional selection. Proceedings of National Academy of Science, 104, 383-388.
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Schwarz, N., & Clore, G. L. (1983). Mood, misattribution, and judgments of well-being:
Informative and directive functions of affective states. Journal of Personality and Social
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Psychology, 45(3), 513-523. doi:10.1037/0022-3514.45.3.513
Watson, D., & Clark, L. A. (1992). Affects separable and inseparable: On the hierarchical arrangement of the negative affects. Journal of Personality and Social Psychology, 62(3),
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489-505. doi:10.1037/0022-3514.62.3.489
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doi:10.1073/pnas.0605198104
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Appendix
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Examples of the stimulus set including the original and modified images: see Figure A1.
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Figure Captions
Figure 1. The matrix plot illustrates relationships among Extraversion, Neuroticism and Accuracy. The histograms show the frequency distribution of each variable. The lines in the
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scatterplots illustrate linear fitting functions: Neuroticism = 16.84 - .32 * Extraversion,
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Accuracy = .63 + .007 * Extraversion, and Accuracy = .80 - .006 * Neuroticism.
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Table 1 Summary of the multiple regression analyses with Extraversion and Neuroticism as predictor variables
.237 -.269
.146 -1.24
1.87 -13.1
.018 -.153
adj R2
p
6.71
.163
.139
.002 * .042 * .022 *
.889
.025
t
.005 -.005
R2
5.12
.005 -.004
.206 -.244
.991 -1.46
.010 -.012
.120 -.177
.222 -.231
.158 -.199 -.194 -.249
.008 * .081 .039 *
2.10
.057
.030
.130 .158 .077
3.05
.081
.055
.053 .192 .102
-.001 -.002
2.75
.074
.047
.071 .111 .042 *
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-1.61 -2.07
.415 .884 .220
.104
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1.31 -1.65
-.003
.129
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1.76 -2.09
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2.08 -2.35
F
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β
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Accuracy Overall model Extraversion Neuroticism Target-present RT Overall model Extraversion Neuroticism A′ Overall model Extraversion Neuroticism B″d Overall model Extraversion Neuroticism Number of saccades Overall model Extraversion Neuroticism Fixation dwell time Overall model Extraversion Neuroticism
b
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