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Attentional control, attentional network functioning, and emotion regulation styles a
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Miquel Tortella-Feliu , Alfonso Morillas-Romero , Maria Balle , Xavier a
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Bornas , Jordi Llabrés & Antonia P. Pacheco-Unguetti
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University Institute for Research on Health Sciences, University of the Balearic Islands, Palma (Majorca), Spain Published online: 03 Dec 2013.
Click for updates To cite this article: Miquel Tortella-Feliu, Alfonso Morillas-Romero, Maria Balle, Xavier Bornas, Jordi Llabrés & Antonia P. Pacheco-Unguetti (2014) Attentional control, attentional network functioning, and emotion regulation styles, Cognition and Emotion, 28:5, 769-780, DOI: 10.1080/02699931.2013.860889 To link to this article: http://dx.doi.org/10.1080/02699931.2013.860889
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COGNITION AND EMOTION, 2014 Vol. 28, No. 5, 769–780, http://dx.doi.org/10.1080/02699931.2013.860889
Attentional control, attentional network functioning, and emotion regulation styles Miquel Tortella-Feliu, Alfonso Morillas-Romero, Maria Balle, Xavier Bornas, Jordi Llabrés, and Antonia P. Pacheco-Unguetti
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University Institute for Research on Health Sciences, University of the Balearic Islands, Palma (Majorca), Spain
Attentional network functioning in emotionally neutral conditions and self-reported attentional control (AC) were analysed as predictors of the tendency to engage in dysfunctional emotion regulation strategies. Diminished attentional orienting predicted an increased tendency to engage in brooding rumination, and enhanced alertness predicted a greater chance of suppression, beyond trait anxiety and self-reported AC, which were not predictive of either rumination or suppression. This is the first study to show that some forms of dysfunctional emotion regulation are related to the attentional network functioning in emotionally neutral conditions. Results are discussed in relation to regulatory temperament and anxiety-related attentional biases literature. Keywords: Attentional control; Attentional network functioning; Attentional Network Test; Emotion regulation; Anxiety.
Attentional control (AC) refers to the cognitive ability to regulate attentional allocation. This attentional skill has traditionally been related to voluntary executive functions, such as the capability to concentrate and resist distraction, to switch attention between tasks, and to flexibly control thoughts (Derryberry & Reed, 2002). Low selfreported AC has been associated with heightened negative affectivity (Fajkowska & Derryberry, 2010; Reinholdt-Dunne, Mogg, & Bradley, 2009;
Sportel, Nauta, de Hullu, & de Jong, 2013), anxiety and depressive symptomatology (e.g., Olatunji, Ciesielski, Armstrong, Zhao, & Zald, 2011; Ólafsson et al., 2011) and several anxiety-related processes (e.g., Baas, 2013; Massar, Mol, Kenemans, & Baas, 2011; Richey, Keough, & Schmidt, 2012), including a moderating role in the relationship between negative affectivity and attention biases to threat (Derryberry & Reed, 2002; Susa, Pitică, Benga, & Miclea, 2012).
Correspondence should be addressed to: Miquel Tortella-Feliu, University Institute for Research on Health Sciences, Universitat de les Illes Balears. Edifici IUNICS. Carretera de Valldemossa km.7.5. 07122 Palma (Mallorca), Spain. E-mail: [email protected] The remaining authors share the same affiliation and postal address. We thank professor Juan Lupiáñez for providing us with the Attentional Network Test for Interactions (ANT-I) and Blanca Aguayo-Siquier for her assistance in the recruitment of participants and data collection. This research was supported by the Spanish Government [grant number PSI2009-12711]. © 2013 Taylor & Francis
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To a lesser extent, self-reported AC deficits have also been related to an increased tendency to engage in maladaptive emotional regulation (ER) strategies (Armstrong, Zald, & Olatunji, 2011; Fajkowska & Derryberry, 2010). Low self-reported effortful control, which includes AC as one of its components, has been positively associated with rumination in both adolescents (Verstraeten, Vasey, Raes, & Bijttebier, 2009) and adults, along with compensatory processes like cognitive suppression (Tortella-Feliu et al., 2012). Fajkowska and Derryberry (2010) suggested that people with limited AC may be compelled to rely on maladaptive ER strategies as a result of a decreased ability to focus and shift attention. This is a relevant question to further investigate, since the use of dysfunctional ER strategies seem to facilitate the emergence and maintenance of anxiety and depressive symptoms (e.g., Aldao, Nolen-Hoeksema, & Schweizer, 2010). AC capabilities can also be measured by using emotionally neutral performance-based tasks (e.g., task switching paradigms, several kinds of conflict tasks, etc.). Frequently used tasks in the search for associations between attention and anxiety are derived from the attention system model by Posner and Petersen (1990). This model postulates attention as being comprised of three major attentional systems or networks—alerting, orienting and executive control—with different functions (see Posner, Rueda, & Kanske, 2007, for a review). The orienting network, which includes operations such as engaging attention to new stimuli and disengaging attention from its current focus, and the executive network, specialising in conflict resolution and voluntary action control, are core elements of AC. The alerting network is devoted to maintaining an adequate sensitivity level to perceive and process stimuli. The Attentional Network Test (ANT; Fan, McCandliss, Sommer, Raz, & Posner, 2002) was originally designed to evaluate the functioning of each of these networks, combining a spatial cueing paradigm with a flanker task. Modified versions of the ANT have been developed to allow analysis of the interactions within these networks or in the context of emotionally loaded stimuli (e.g., Attentional Network
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Test for Interactions, ANT-I; Callejas, Lupiáñez, & Tudela, 2004). Focusing exclusively on research conducted with non-emotional ANT versions, both high trait and clinical anxiety have been associated with a reduced efficiency of the executive control network (Pacheco-Unguetti, Acosta, Callejas, & Lupiáñez, 2010; Pacheco-Unguetti, Acosta, Marqués, & Lupiáñez, 2011), and with an increased orienting network functioning (Pacheco-Unguetti et al., 2011), specifically with greater difficulties in disengaging attention from invalid cues. This finding fits with the impaired attentional disengagement hypothesis (Koster, De Lissnyder, Derakshan, & De Raedt, 2011) which was postulated to explain the tendency of anxious-depressive individuals to rely on some maladaptive forms of ER (e.g., perseverative negative thinking). Recent studies have shown a relationship between an increase in orienting network functioning and heightened Behavioural Inhibition System reactivity (Tull, Maack, Viana, & Gratz, 2012). On the contrary, Moriya and Tanno (2009) reported a negative relationship between high trait anxiety and the orienting network functioning. Some of these results are consistent with those reported by Bishop (2009) and partly with some of the basic assumptions of the attention control theory (Eysenck & Derakshan, 2011). That is, anxiety impairs general cognitive control capacity, mainly by eroding the efficiency of executive functions (inhibition and shifting). However, it may also be considered that AC ability by itself could be responsible for the quality of attentional top-down processes after accounting for the detrimental effects of anxiety on attention. In fact, the abovementioned studies have raised the question of whether the attentional biases to threat that characterise anxiety-prone individuals (see Bar-Haim, Lamy, Pergamin, Bakermans-Kranenburg, & van IJzendoorn, 2007; Cisler & Koster, 2010, for reviews) may reflect a much broader dysregulation of AC. In this case, AC impairments may be understood as a regulatory temperamental vulnerability factor that, interacting with negative affectivity, can facilitate the development of emotional disorders as well as engaging in dysfunctional
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forms of ER (e.g., Koster et al., 2011; Rueda, Posner, & Rothbart, 2005; White, Helfinstein, Reeb-Sutherland, Degnan, & Fox, 2009). Difficulties in disengaging attention from non-valid information and the impaired executive control functioning both seem to be related to an increased tendency to engage in dysfunctional ER strategies. However, to our knowledge, no previous studies have directly addressed this question. Previous studies using non-emotional task switching paradigms have investigated the potential links between impairment in attentional executive control, depressive symptoms and rumination. Whitmer and Banich (2007) found that the brooding facet of rumination was associated with attentional inhibition impairment, but not with shifting impairment. However, De Lissnyder, Koster, Derakshan, and De Raedt (2010) reported that the tendency to ruminate was related to both inhibition and shifting impairments, but only when processing negative emotional stimuli, not when facing non-emotionally laden tasks. Moreover, depressive symptoms were not associated with executive control functioning, which suggests that impairment in these functions is specific to the tendency to engage in repetitive thinking. Other studies using emotionally laden tasks have also found that increased brooding was related to difficulties in inhibiting sad information (i.e., Vanderhasselt, Kühn, & De Raedt, 2011). Additionally, Hirsch and Mathews (2012) have recently stated that worry, another form of perseverative thinking, partially arises from AC difficulties. It appears that AC, assessed by self-reports or through performance-based measures, is an important feature of anxiety and depression processes. However, research has reported inconsistent results regarding the association between selfreported AC and performance-based AC measures (Muris, van der Pennen, Sigmond, & Mayer, 2008; Pacheco-Unguetti et al., 2011; ReinholdtDunne et al., 2009; Reinholdt-Dunne, Mogg, & Bradley, 2013). Moreover, whereas PachecoUnguetti, Acosta, Marqués, and Lupiáñez (2011) found that both kinds of AC measures were related to depression and anxiety symptoms, other studies only showed self-reported AC measures to
be associated with emotional symptomatology (Muris et al., 2008; Reinholdt-Dunne et al., 2009, 2013). As stated above, previous research has reported maladaptive ER styles to be associated with low self-reported AC, as well as with high trait anxiety. Additionally, some studies have suggested that impairments in the attentional executive control, as measured by several laboratory tasks, are related to an increased tendency to engage in rumination. However, no previous research has yet addressed whether the functioning of the three major attentional networks (orienting, alertness and executive control) is related to an increased tendency to engage in dysfunctional ER strategies. The main aim of the study was to analyse whether attentional network functioning was related to the tendency to engage in dysfunctional ER strategies beyond trait anxiety and self-reported AC. We expected that both diminished functioning in the orienting network, specifically in the form of experiencing more difficulties to disengage from invalid cues, and reduced efficiency in the executive control network functioning would be related to an increased self-reported use of dysfunctional ER strategies (brooding rumination and suppression) beyond those explained by trait anxiety and self-reported AC. A second aim of the study was to further explore the link between self-reported AC and performance-based AC. Since data from prior studies are largely inconsistent, no specific predictions could be made.
METHOD Participants One hundred and forty-two healthy university students and staff members (M = 29.5 years; SD = 10.01; range 18–55; 72.5% female) not previously selected by any psychological or sociodemographic characteristic, agreed voluntarily to participate and signed an informed consent form. Participants were recruited via electronic or posted advertisements. COGNITION AND EMOTION, 2014, 28 (5)
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Seven participants were excluded due to the presence of an anxiety or depressive disorder (see “Materials and Procedure” section), and three for missing data in self-reported measures or problematic attentional task execution. Finally, data from 132 participants (M = 29.67 years; SD = 10.29, 73.4% female) were analysed.
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Materials and procedure Before performing the attentional task, selfreported measures on trait anxiety, AC, rumination and suppression were collected through online versions of the questionnaires. Later, participants were invited to attend a laboratory session for an individual administration of the ANT-I (Callejas et al., 2004). Prior to performing the attentional task, two short screening measures of anxiety and depressive symptoms (see below) were administered. Participants with high scores in any of these measures were individually interviewed using the Anxiety Disorders Interview Schedule (ADIS-IV) from Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSMIV; Brown, DiNardo, & Barlow, 1994) to determine potential clinical status. Interviewers were aware of the study hypotheses and were instructed to exclude participants meeting diagnostic criteria for any current psychopathological disorder. Participants were asked to refrain from alcohol, drug use, and caffeinated beverages for four hours prior to attending the laboratory. All procedures were approved by the University Bioethics Committee.
Screening measures
type scale (0 = none/little; 4 = constant, extreme or all the time). Following Roy-Byrne et al. (2010), participants scoring 8 or more were individually interviewed by using the ADIS-IV (Brown et al., 1994). Depression The three-item version (Craske et al., 2009) of the Patient Health Questionnaire-9 (Kroenke, Spitzer, & Williams, 2001) was used. Respondents were asked to rate each item (two depression and on fatigue items) on a 4-point Likert-type scale (1 = not at all; 4 = nearly every day). Those scoring 4 or more were individually interviewed using the ADIS-IV (Brown et al., 1994).
Self-reported measures Internal consistency for our sample for each of the self-report instruments is depicted in Table 2 (see “Results” section). Dispositional factors Trait anxiety. The State-trait Anxiety Inventory, trait subscale (Spielberger, Gorsuch, & Lushene, 1970) was used. It consists of 20 statements measuring subjective feelings of anxiety in a 4-point Likert-type scale (1 = almost never; 4 = almost always). Attentional control. The Attentional Control Scale (Derryberry & Reed, 2002) was used. The scale comprises 20 items to be rated on a 4-point Likert-type scale (1 = almost never; 4 = always) measuring the self-reported ability to voluntarily manage attention.
Anxiety/fear The Overall Anxiety Severity and Impairment Scale (Norman, Cissell, Means-Christensen, & Stein, 2006; Norman et al. 2011) was used. It consists of five items that measure the frequency and severity of experiences of anxiety/fear, avoidance, work/school/home interference, and social interference due to anxiety over the past week. Respondents are requested to rate each item on a 5-point Likert-
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Dysfunctional emotional regulation strategies Suppression. The White Bear Suppression Inventory (Wegner & Zanakos, 1994) was used. The scale consists of 15 items to be rated on a 5-point Likert-type scale (1 = totally disagree; 5 = totally agree) measuring the extent to which each of the statements fits the person’s typical behaviours.
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ANT-I (Callejas et al., 2004) The experimental conditions and the sequence of events for each trial are depicted and explained in Figure 1. The task was composed of six blocks of 48 trials each, representing all experimental conditions. Participants’ reaction times in the different trial types were used to compute an efficiency index for
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Rumination. The shortened Ruminative Response Scale (Treynor, Gonzalez, & Nolen-Hoeksema, 2003) was used. The scale is divided into two subscales: brooding and reflection. Each subscale consists of five items to be rated on a 4-point Likert-type scale (1 = totally disagree; 4 = totally agree) according to the frequency in which ruminative responses are performed when experiencing a dysphoric mood.
Figure 1. Sequence of events for each trial of the Attentional Network Test for Interactions (ANT-I). Each trial began with a fixation point (a plus sign) presented for 400–1600 ms in the centre of the screen. After this, and only in half of the trials, an alerting tone was then presented for 50 ms. In two-thirds of the trials, after 400 ms this was followed by an asterisk as an orienting signal that was presented for 50 ms either above or below the fixation point (cued trials). No asterisk was presented in the remaining third of the trials (uncued condition). Then, the asterisk disappeared leaving only the fixation point. After 50 ms, an arrow flanked by four distractor arrows (two on each side) was presented. The distractors pointed either in the same direction as the arrow target (i.e., congruent trials) or in the opposite direction (i.e., incongruent trials), and at the same position as the orienting cue (i.e., valid trials) or at the opposite location (i.e., invalid trials). Participants were instructed to indicate, as fast as possible, the direction in which the target was pointing (either right or left) by pressing one of the two possible keys (M and C, respectively) of a computer keyboard. After the response, the fixation point was presented for up to 3000 ms. RT, reaction time; SOA = stimulus onset asynchrony. COGNITION AND EMOTION, 2014, 28 (5)
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each attentional network (Callejas et al., 2004; Pacheco-Unguetti et al., 2010, 2011): alertness = no alerting–alerting tone (restricted to the uncued condition); orienting = invalid–valid trials; executive control = incongruent–congruent trials. Orienting was also divided into costs (i.e., disengagement of attention from invalid cues) = invalid–uncued trials and benefits (i.e., facilitated orientation) = uncued–valid trials. The ANT-I was administered after a verbal explanation of the procedure and a practice block of two trials. In the current study, attentional network functioning was assessed by means of the four central blocks of the ANT-I. The task lasted about 30 minutes.
RESULTS ANT-I reaction time analysis In a preliminary analysis, we examined reaction time in the ANT-I by means of a factorial mixed analysis of variance (ANOVA) for overall intrasubjects effects. Following previous studies (e.g., Pacheco-Unguetti et al., 2011), extreme values (faster than 200 or slower than 1200 ms) were eliminated in order to avoid anticipations and very long response latencies, respectively. Reaction time for correct response trials as a dependent variable, was introduced into a 2 (Alertness: No alerting, Alerting Tone) × 3 (Orienting: Valid, Invalid, Uncued) × 2 (Executive Control: Congruent, Incongruent) factorial mixed ANOVA to explore the overall attentional effects. Mean reaction time per experimental condition, after eliminating extreme values and error rates are depicted in Table 1.
Consistent with previous studies (Callejas et al., 2004; Pacheco-Unguetti et al., 2010, 2011), the main effects of alertness, F(1, 131) = 252.5, mean square error (MSE) = 1167.56, p < .000, η2 = 0.658; orienting, F(2, 262) = 554.4, MSE = 818.35, p < .000, η2 = 0.809 and executive control, F(1, 131) = 1575.9, MSE = 2157.20, p < .000, η2 = 0.923, were significant. Specifically, responses were significantly faster in trials where an alerting tone was present compared with trials in which it was absent, in trials with the presence of an orienting signal, and in trials where distractors pointed in the same direction as the arrow target (i.e., congruent trials). Interactions between attentional networks were also significant. In the alertness and orienting interaction, F(2, 262) = 82.55, MSE = 495.68, p < .000, η2 = 0.387, we found larger reaction time differences between cued and uncued trials in trials with the alerting tone. In the interaction between alertness and executive control, F(1, 131) = 72.21, MSE = 494.74, p < .000, η2 = 0.355, a larger congruency effect was observed when the alerting tone was presented. Finally, the interaction between orienting and executive control, F(2, 262) = 68.11, MSE = 551.10, p < .000, η2 = 0.342, showed a reduction of congruency effect on valid trials. These interactions showed the pattern usually observed in this task (e.g., Callejas et al., 2004; Pacheco-Unguetti et al., 2010, 2011).
Predictive power of attentional control on dysfunctional emotion regulation To determine the role of AC in predicting the tendency to engage in dysfunctional forms of ER, a series of multiple stepwise regression analyses
Table 1. Mean reaction times (in milliseconds) and error rates (in parentheses) for each ANT-I condition
Without alerting tone
Congruent Incongruent
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With alerting tone
Uncued
Valid
Invalid
Uncued
Valid
Invalid
610 (0.02) 684 (0.00)
570 (0.02) 648 (0.02)
606 (0.05) 705 (0.00)
555 (0.00) 653 (0.01)
537 (0.02) 620 (0.00)
585 (0.01) 710 (0.01)
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Table 2. Summary of stepwise multiple regression analyses predicting brooding, reflection, and suppression (n = 132)
Predictors Brooding STAI-T Orienting network
ΔR2
B
SE B
β
0.466** 0.031**
2.06 −0.030
0.019 0.010
0.684 −0.178 F(1, 129) = 63.78**
Reflection STAI-T
0.112**
0.105
0.026
0.335
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F(1, 130) = 16.46** Suppression STAI-T Alertness network Age
0.373** 0.026* 0.021*
0.704 0.085 −0.193
0.080 0.036 0.089
0.611 0.163 −0.148 F(1, 128) = 30.97**
Note: STAI-T = State-trait Anxiety Inventory–Trait. *p < .05; **p < .0001.
(with probability of F-to-enter ≤5 and probability F-to-remove ≥0.10) were conducted using brooding and reflection facets of rumination and suppression as dependent variables. Trait anxiety, self-reported AC, performance-based AC (i.e., the functioning of each of the orienting, alertness and executive control networks) and age (see Zhou, Fan, Lee, Wang, & Wang, 2011) were introduced as independent variables. Results are depicted in Table 2. In all regression analyses, trait anxiety entered first into the equations and explained the greatest percentage of variance in brooding (46.6%), reflection (11.2%) and suppression (37.3%). For reflection, in fact, trait anxiety was the only variable that entered into the model. That is, neither selfreported AC nor attentional network functioning appeared to be related with this form of ER. For brooding, the functioning of the orienting network explained an additional 3.1% of the variance of this facet of rumination. Age and the alerting network functioning also contributed to explain additional variance of suppression (2.6% and 2.1%, respectively). No significant effects were found either for executive control network functioning or for self-reported AC for any of the dependent variables included in this analysis.
Relationships between self-reported AC and ANT-I Partial two-tailed correlations controlling for age in all variables included in the study (see Table 3) showed that self-reported AC was negatively associated with trait anxiety, both brooding and reflection facets of rumination and suppression. That is, self-reported AC only appeared to be related with these ER styles when other variables, such as trait anxiety or performance-based AC, are not taken into account as was done in the regression analyses previously reported. By contrast, a significant positive association was found between self-reported AC and the orienting functioning, showing, surprisingly, higher self-reported AC to have greater difficulty in disengaging attention from false cues and no significant association with benefits.
DISCUSSION The current study investigated whether attentional network functioning would be related to the tendency to engage in rumination (brooding and reflection facets) and suppression. Moreover, it also aimed to further analyse the controversial links between self-reported and performanceCOGNITION AND EMOTION, 2014, 28 (5)
775
– −0.405**
58.50 92.65 43.27 23.72 28.18 – −0.246** 0.219* – 0.054 0.050 −0.022
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Note: STAI-T = State-trait Anxiety Inventory–Trait; ACS = Attentional Control Scale. *p < .05 two-sided; **p < .01 two-sided.
– 0.030 −0.056 0.636** 0.448** −0.192* 0.074 0.150 −0.077 −0.137 −0.164 0.159 −0.114 0.045 −0.247** −0.271** 0.111 0.026 −0.185* −0.107 0.192* 0.082 −0.076 0.253** −0.066 Behavioural measures 6. Orienting 7. Executive control 8. Alertness 9. Costs 10. Benefits
−0.136 0.200* −0.036 −0.138 −0.002
– −0.281** 0.004 −0.289** Self-reported measures 1. STAI-T – 2. ACS −0.363** 3. Brooding 0.683** 4. Reflection 0.327** 5. Suppression 0.602**
– 0.452** 0.690**
– 0.385**
–
6 5 4 3 2
21.39 26.81 25.65 5.23 4.8
0.934 0.822 0.792 0.774 0.916 11.25 8.77 3.54 3.66 13.46 40.79 54.25 10.87 10.83 38.86
8 7
776
1
Table 3. Partial correlations controlling for age for self-reported and behavioural measures
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9
Mean
SD
Cronbach’s α
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based AC. Prior to this study, ER styles had not been explored as related to attentional network functioning. A significant finding, only partially in accordance with the first hypothesis, was that reduced attentional orienting was predictive of a tendency to engage in brooding rumination, more than trait anxiety, while self-reported AC did not provide any additional predictive power to trait anxiety. As enhanced attentional orienting entails paying and shifting attention to external cues in anticipation of an upcoming stimulus, and brooding can be considered a prototypical form of self-focused ER (i.e., favouring focus on inner conditions rather than external ones), this could explain why individuals with diminished orienting network functioning are more prone to exhibit a perseverative thinking pattern. According to some influential theoretical approaches in the field, such as the disengagement hypothesis (e.g., Koster et al., 2011), we expected that enhanced orienting functioning would be related with less costs (experiencing less difficulties to disengage from invalid cues) but not with more costs, as our data reflected. It is quite intriguing that difficulties in disengaging attention from invalid cues were negatively associated with brooding. Tull, Maack, Viana, and Gratz (2012) proposed that enhanced orienting response in higher Behavioural Inhibition System sensitivity individuals may be simultaneously considered as adaptive (preparing for adequate responses) and dysfunctional (facilitating attention to threat). Perhaps the same reasoning can be applied to difficulties in disengaging: it may be adaptive when focused on external cues and in tasks without emotional content, as a way to reduce the probability of engaging in dysfunctional ER strategies, but potentially harmful when related to emotional inner experiences. Contrary to our predictions, the executive control was not related to brooding. It was, however, negatively associated with trait anxiety in the correlational analysis. These findings are consistent with previous studies (Pacheco-Unguetti et al., 2010, 2011).
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Regarding suppression, enhanced alertness network functioning was predictive of a greater chance to suppress distressing cognitions, but contrary to our hypothesis, orienting and executive control did not predict suppression. As alerting reflects the sensitivity to perceive and process stimuli, we can consider that, if enhanced, individuals would be more capable of detecting and/or appraising cognitive responses as distressing or inappropriate, and then would try to suppress them. Finally, once again, self-reported AC was not predictive of this ER style while performancebased AC was. However, self-reported AC was positively correlated with orienting functioning. To our knowledge, this finding has not been reported before, since previous literature has only found selfreported AC to be related to performance-based executive AC (Muris et al., 2008; PachecoUnguetti et al., 2011; Reinholdt-Dunne et al., 2009). In the current study, higher self-reported AC was specifically related to greater difficulty in disengaging attention from false cues, not to enhanced orienting benefits. No significant associations were found in the correlational analysis between self-reported AC, alertness and the executive control network. Based on this finding and others reported in the literature, it seems clear that self-reported AC cannot be taken as a direct reflection of performance-based AC and/or the true functioning of attentional capabilities in everyday life. From our data, it is tempting to speculate that self-reported AC is akin to perceived AC derived from personal experiences when trying to focus and shift attention in the real world. Additionally, this subjective evaluation is possibly not only affected by a pure selfobservation of “true” attentional capabilities, but also by trait anxiety or, more widely, by negative affectivity. It is quite well established that individuals with heightened negative affectivity tend to react more intensely to potential stressful or disrupting conditions, and consequently to interpret external events or one’s own performance more negatively. Since both variables always appear highly positively associated with the literature, it is possible that high trait anxiety
determines an individual’s perceptions about impaired attentional capabilities to a considerable extent, beyond what they actually are. We consider that further studies analysing the association between self-reported AC and performance-based AC are warranted with some of the ideas outlined in this discussion to be empirically tested. In summary, the current study shows that rumination and suppression tendencies are related to AC impairments, which has been demonstrated through an attentional task without emotional stimuli rather than using self-reported measures. These findings are consistent with those described in previous studies (e.g., De Lissnyder, Koster, Derakshan, & De Raedt, 2010; Fajkowska & Derryberry, 2010; Hirsch & Mathews, 2012). Specifically, enhanced orienting and alertness functioning were related to increased brooding and suppression, respectively. It may be argued that the associations found in the current study between the functioning of some attentional networks and brooding and rumination reflect a global tendency to engage in more ER rather than a tendency to specifically engage in maladaptive ones. Unfortunately, we did not assess the other forms of ER apart from rumination and suppression to test this hypothesis. However, some kind of specificity can be considered as the reflection facet of rumination exhibited a different pattern of association with the other variables, as compared to brooding and suppression. We believe the topic addressed in the current study deserves further research, in order to overcome some of the limitations in the current experiment and to broaden it to related aspects. For example, it would be interesting to explore whether AC and attentional network functioning with non-emotionally laden tasks is related to ER beyond retrospective self-reporting, as in the present work, but also related to spontaneous ER after emotional induction or by using ecological momentary records of ER strategies used in everyday life. Following these suggestions, a more accurate figure of the relationship could be discovered. We think that expanding the knowledge of how AC and attentional network functioning COGNITION AND EMOTION, 2014, 28 (5)
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relates to core features of emotional disorders (i.e., maladaptive ER styles), could help to inform interventions focused on modifying biased attentional processes in the prevention and treatment of pathological anxiety and depression. Despite the current limitations of the study, the results provide novel insights on the topic. Manuscript received 24 May Revised manuscript received 11 September Manuscript accepted 26 October First published online 3 December
2013 2013 2013 2013
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Cognition and Emotion Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/pcem20
Attentional control, attentional network functioning, and emotion regulation styles a
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Miquel Tortella-Feliu , Alfonso Morillas-Romero , Maria Balle , Xavier a
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Bornas , Jordi Llabrés & Antonia P. Pacheco-Unguetti
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University Institute for Research on Health Sciences, University of the Balearic Islands, Palma (Majorca), Spain Published online: 03 Dec 2013.
Click for updates To cite this article: Miquel Tortella-Feliu, Alfonso Morillas-Romero, Maria Balle, Xavier Bornas, Jordi Llabrés & Antonia P. Pacheco-Unguetti (2014) Attentional control, attentional network functioning, and emotion regulation styles, Cognition and Emotion, 28:5, 769-780, DOI: 10.1080/02699931.2013.860889 To link to this article: http://dx.doi.org/10.1080/02699931.2013.860889
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COGNITION AND EMOTION, 2014 Vol. 28, No. 5, 769–780, http://dx.doi.org/10.1080/02699931.2013.860889
Attentional control, attentional network functioning, and emotion regulation styles Miquel Tortella-Feliu, Alfonso Morillas-Romero, Maria Balle, Xavier Bornas, Jordi Llabrés, and Antonia P. Pacheco-Unguetti
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University Institute for Research on Health Sciences, University of the Balearic Islands, Palma (Majorca), Spain
Attentional network functioning in emotionally neutral conditions and self-reported attentional control (AC) were analysed as predictors of the tendency to engage in dysfunctional emotion regulation strategies. Diminished attentional orienting predicted an increased tendency to engage in brooding rumination, and enhanced alertness predicted a greater chance of suppression, beyond trait anxiety and self-reported AC, which were not predictive of either rumination or suppression. This is the first study to show that some forms of dysfunctional emotion regulation are related to the attentional network functioning in emotionally neutral conditions. Results are discussed in relation to regulatory temperament and anxiety-related attentional biases literature. Keywords: Attentional control; Attentional network functioning; Attentional Network Test; Emotion regulation; Anxiety.
Attentional control (AC) refers to the cognitive ability to regulate attentional allocation. This attentional skill has traditionally been related to voluntary executive functions, such as the capability to concentrate and resist distraction, to switch attention between tasks, and to flexibly control thoughts (Derryberry & Reed, 2002). Low selfreported AC has been associated with heightened negative affectivity (Fajkowska & Derryberry, 2010; Reinholdt-Dunne, Mogg, & Bradley, 2009;
Sportel, Nauta, de Hullu, & de Jong, 2013), anxiety and depressive symptomatology (e.g., Olatunji, Ciesielski, Armstrong, Zhao, & Zald, 2011; Ólafsson et al., 2011) and several anxiety-related processes (e.g., Baas, 2013; Massar, Mol, Kenemans, & Baas, 2011; Richey, Keough, & Schmidt, 2012), including a moderating role in the relationship between negative affectivity and attention biases to threat (Derryberry & Reed, 2002; Susa, Pitică, Benga, & Miclea, 2012).
Correspondence should be addressed to: Miquel Tortella-Feliu, University Institute for Research on Health Sciences, Universitat de les Illes Balears. Edifici IUNICS. Carretera de Valldemossa km.7.5. 07122 Palma (Mallorca), Spain. E-mail: [email protected] The remaining authors share the same affiliation and postal address. We thank professor Juan Lupiáñez for providing us with the Attentional Network Test for Interactions (ANT-I) and Blanca Aguayo-Siquier for her assistance in the recruitment of participants and data collection. This research was supported by the Spanish Government [grant number PSI2009-12711]. © 2013 Taylor & Francis
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To a lesser extent, self-reported AC deficits have also been related to an increased tendency to engage in maladaptive emotional regulation (ER) strategies (Armstrong, Zald, & Olatunji, 2011; Fajkowska & Derryberry, 2010). Low self-reported effortful control, which includes AC as one of its components, has been positively associated with rumination in both adolescents (Verstraeten, Vasey, Raes, & Bijttebier, 2009) and adults, along with compensatory processes like cognitive suppression (Tortella-Feliu et al., 2012). Fajkowska and Derryberry (2010) suggested that people with limited AC may be compelled to rely on maladaptive ER strategies as a result of a decreased ability to focus and shift attention. This is a relevant question to further investigate, since the use of dysfunctional ER strategies seem to facilitate the emergence and maintenance of anxiety and depressive symptoms (e.g., Aldao, Nolen-Hoeksema, & Schweizer, 2010). AC capabilities can also be measured by using emotionally neutral performance-based tasks (e.g., task switching paradigms, several kinds of conflict tasks, etc.). Frequently used tasks in the search for associations between attention and anxiety are derived from the attention system model by Posner and Petersen (1990). This model postulates attention as being comprised of three major attentional systems or networks—alerting, orienting and executive control—with different functions (see Posner, Rueda, & Kanske, 2007, for a review). The orienting network, which includes operations such as engaging attention to new stimuli and disengaging attention from its current focus, and the executive network, specialising in conflict resolution and voluntary action control, are core elements of AC. The alerting network is devoted to maintaining an adequate sensitivity level to perceive and process stimuli. The Attentional Network Test (ANT; Fan, McCandliss, Sommer, Raz, & Posner, 2002) was originally designed to evaluate the functioning of each of these networks, combining a spatial cueing paradigm with a flanker task. Modified versions of the ANT have been developed to allow analysis of the interactions within these networks or in the context of emotionally loaded stimuli (e.g., Attentional Network
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Test for Interactions, ANT-I; Callejas, Lupiáñez, & Tudela, 2004). Focusing exclusively on research conducted with non-emotional ANT versions, both high trait and clinical anxiety have been associated with a reduced efficiency of the executive control network (Pacheco-Unguetti, Acosta, Callejas, & Lupiáñez, 2010; Pacheco-Unguetti, Acosta, Marqués, & Lupiáñez, 2011), and with an increased orienting network functioning (Pacheco-Unguetti et al., 2011), specifically with greater difficulties in disengaging attention from invalid cues. This finding fits with the impaired attentional disengagement hypothesis (Koster, De Lissnyder, Derakshan, & De Raedt, 2011) which was postulated to explain the tendency of anxious-depressive individuals to rely on some maladaptive forms of ER (e.g., perseverative negative thinking). Recent studies have shown a relationship between an increase in orienting network functioning and heightened Behavioural Inhibition System reactivity (Tull, Maack, Viana, & Gratz, 2012). On the contrary, Moriya and Tanno (2009) reported a negative relationship between high trait anxiety and the orienting network functioning. Some of these results are consistent with those reported by Bishop (2009) and partly with some of the basic assumptions of the attention control theory (Eysenck & Derakshan, 2011). That is, anxiety impairs general cognitive control capacity, mainly by eroding the efficiency of executive functions (inhibition and shifting). However, it may also be considered that AC ability by itself could be responsible for the quality of attentional top-down processes after accounting for the detrimental effects of anxiety on attention. In fact, the abovementioned studies have raised the question of whether the attentional biases to threat that characterise anxiety-prone individuals (see Bar-Haim, Lamy, Pergamin, Bakermans-Kranenburg, & van IJzendoorn, 2007; Cisler & Koster, 2010, for reviews) may reflect a much broader dysregulation of AC. In this case, AC impairments may be understood as a regulatory temperamental vulnerability factor that, interacting with negative affectivity, can facilitate the development of emotional disorders as well as engaging in dysfunctional
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forms of ER (e.g., Koster et al., 2011; Rueda, Posner, & Rothbart, 2005; White, Helfinstein, Reeb-Sutherland, Degnan, & Fox, 2009). Difficulties in disengaging attention from non-valid information and the impaired executive control functioning both seem to be related to an increased tendency to engage in dysfunctional ER strategies. However, to our knowledge, no previous studies have directly addressed this question. Previous studies using non-emotional task switching paradigms have investigated the potential links between impairment in attentional executive control, depressive symptoms and rumination. Whitmer and Banich (2007) found that the brooding facet of rumination was associated with attentional inhibition impairment, but not with shifting impairment. However, De Lissnyder, Koster, Derakshan, and De Raedt (2010) reported that the tendency to ruminate was related to both inhibition and shifting impairments, but only when processing negative emotional stimuli, not when facing non-emotionally laden tasks. Moreover, depressive symptoms were not associated with executive control functioning, which suggests that impairment in these functions is specific to the tendency to engage in repetitive thinking. Other studies using emotionally laden tasks have also found that increased brooding was related to difficulties in inhibiting sad information (i.e., Vanderhasselt, Kühn, & De Raedt, 2011). Additionally, Hirsch and Mathews (2012) have recently stated that worry, another form of perseverative thinking, partially arises from AC difficulties. It appears that AC, assessed by self-reports or through performance-based measures, is an important feature of anxiety and depression processes. However, research has reported inconsistent results regarding the association between selfreported AC and performance-based AC measures (Muris, van der Pennen, Sigmond, & Mayer, 2008; Pacheco-Unguetti et al., 2011; ReinholdtDunne et al., 2009; Reinholdt-Dunne, Mogg, & Bradley, 2013). Moreover, whereas PachecoUnguetti, Acosta, Marqués, and Lupiáñez (2011) found that both kinds of AC measures were related to depression and anxiety symptoms, other studies only showed self-reported AC measures to
be associated with emotional symptomatology (Muris et al., 2008; Reinholdt-Dunne et al., 2009, 2013). As stated above, previous research has reported maladaptive ER styles to be associated with low self-reported AC, as well as with high trait anxiety. Additionally, some studies have suggested that impairments in the attentional executive control, as measured by several laboratory tasks, are related to an increased tendency to engage in rumination. However, no previous research has yet addressed whether the functioning of the three major attentional networks (orienting, alertness and executive control) is related to an increased tendency to engage in dysfunctional ER strategies. The main aim of the study was to analyse whether attentional network functioning was related to the tendency to engage in dysfunctional ER strategies beyond trait anxiety and self-reported AC. We expected that both diminished functioning in the orienting network, specifically in the form of experiencing more difficulties to disengage from invalid cues, and reduced efficiency in the executive control network functioning would be related to an increased self-reported use of dysfunctional ER strategies (brooding rumination and suppression) beyond those explained by trait anxiety and self-reported AC. A second aim of the study was to further explore the link between self-reported AC and performance-based AC. Since data from prior studies are largely inconsistent, no specific predictions could be made.
METHOD Participants One hundred and forty-two healthy university students and staff members (M = 29.5 years; SD = 10.01; range 18–55; 72.5% female) not previously selected by any psychological or sociodemographic characteristic, agreed voluntarily to participate and signed an informed consent form. Participants were recruited via electronic or posted advertisements. COGNITION AND EMOTION, 2014, 28 (5)
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Seven participants were excluded due to the presence of an anxiety or depressive disorder (see “Materials and Procedure” section), and three for missing data in self-reported measures or problematic attentional task execution. Finally, data from 132 participants (M = 29.67 years; SD = 10.29, 73.4% female) were analysed.
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Materials and procedure Before performing the attentional task, selfreported measures on trait anxiety, AC, rumination and suppression were collected through online versions of the questionnaires. Later, participants were invited to attend a laboratory session for an individual administration of the ANT-I (Callejas et al., 2004). Prior to performing the attentional task, two short screening measures of anxiety and depressive symptoms (see below) were administered. Participants with high scores in any of these measures were individually interviewed using the Anxiety Disorders Interview Schedule (ADIS-IV) from Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSMIV; Brown, DiNardo, & Barlow, 1994) to determine potential clinical status. Interviewers were aware of the study hypotheses and were instructed to exclude participants meeting diagnostic criteria for any current psychopathological disorder. Participants were asked to refrain from alcohol, drug use, and caffeinated beverages for four hours prior to attending the laboratory. All procedures were approved by the University Bioethics Committee.
Screening measures
type scale (0 = none/little; 4 = constant, extreme or all the time). Following Roy-Byrne et al. (2010), participants scoring 8 or more were individually interviewed by using the ADIS-IV (Brown et al., 1994). Depression The three-item version (Craske et al., 2009) of the Patient Health Questionnaire-9 (Kroenke, Spitzer, & Williams, 2001) was used. Respondents were asked to rate each item (two depression and on fatigue items) on a 4-point Likert-type scale (1 = not at all; 4 = nearly every day). Those scoring 4 or more were individually interviewed using the ADIS-IV (Brown et al., 1994).
Self-reported measures Internal consistency for our sample for each of the self-report instruments is depicted in Table 2 (see “Results” section). Dispositional factors Trait anxiety. The State-trait Anxiety Inventory, trait subscale (Spielberger, Gorsuch, & Lushene, 1970) was used. It consists of 20 statements measuring subjective feelings of anxiety in a 4-point Likert-type scale (1 = almost never; 4 = almost always). Attentional control. The Attentional Control Scale (Derryberry & Reed, 2002) was used. The scale comprises 20 items to be rated on a 4-point Likert-type scale (1 = almost never; 4 = always) measuring the self-reported ability to voluntarily manage attention.
Anxiety/fear The Overall Anxiety Severity and Impairment Scale (Norman, Cissell, Means-Christensen, & Stein, 2006; Norman et al. 2011) was used. It consists of five items that measure the frequency and severity of experiences of anxiety/fear, avoidance, work/school/home interference, and social interference due to anxiety over the past week. Respondents are requested to rate each item on a 5-point Likert-
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Dysfunctional emotional regulation strategies Suppression. The White Bear Suppression Inventory (Wegner & Zanakos, 1994) was used. The scale consists of 15 items to be rated on a 5-point Likert-type scale (1 = totally disagree; 5 = totally agree) measuring the extent to which each of the statements fits the person’s typical behaviours.
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ANT-I (Callejas et al., 2004) The experimental conditions and the sequence of events for each trial are depicted and explained in Figure 1. The task was composed of six blocks of 48 trials each, representing all experimental conditions. Participants’ reaction times in the different trial types were used to compute an efficiency index for
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Rumination. The shortened Ruminative Response Scale (Treynor, Gonzalez, & Nolen-Hoeksema, 2003) was used. The scale is divided into two subscales: brooding and reflection. Each subscale consists of five items to be rated on a 4-point Likert-type scale (1 = totally disagree; 4 = totally agree) according to the frequency in which ruminative responses are performed when experiencing a dysphoric mood.
Figure 1. Sequence of events for each trial of the Attentional Network Test for Interactions (ANT-I). Each trial began with a fixation point (a plus sign) presented for 400–1600 ms in the centre of the screen. After this, and only in half of the trials, an alerting tone was then presented for 50 ms. In two-thirds of the trials, after 400 ms this was followed by an asterisk as an orienting signal that was presented for 50 ms either above or below the fixation point (cued trials). No asterisk was presented in the remaining third of the trials (uncued condition). Then, the asterisk disappeared leaving only the fixation point. After 50 ms, an arrow flanked by four distractor arrows (two on each side) was presented. The distractors pointed either in the same direction as the arrow target (i.e., congruent trials) or in the opposite direction (i.e., incongruent trials), and at the same position as the orienting cue (i.e., valid trials) or at the opposite location (i.e., invalid trials). Participants were instructed to indicate, as fast as possible, the direction in which the target was pointing (either right or left) by pressing one of the two possible keys (M and C, respectively) of a computer keyboard. After the response, the fixation point was presented for up to 3000 ms. RT, reaction time; SOA = stimulus onset asynchrony. COGNITION AND EMOTION, 2014, 28 (5)
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each attentional network (Callejas et al., 2004; Pacheco-Unguetti et al., 2010, 2011): alertness = no alerting–alerting tone (restricted to the uncued condition); orienting = invalid–valid trials; executive control = incongruent–congruent trials. Orienting was also divided into costs (i.e., disengagement of attention from invalid cues) = invalid–uncued trials and benefits (i.e., facilitated orientation) = uncued–valid trials. The ANT-I was administered after a verbal explanation of the procedure and a practice block of two trials. In the current study, attentional network functioning was assessed by means of the four central blocks of the ANT-I. The task lasted about 30 minutes.
RESULTS ANT-I reaction time analysis In a preliminary analysis, we examined reaction time in the ANT-I by means of a factorial mixed analysis of variance (ANOVA) for overall intrasubjects effects. Following previous studies (e.g., Pacheco-Unguetti et al., 2011), extreme values (faster than 200 or slower than 1200 ms) were eliminated in order to avoid anticipations and very long response latencies, respectively. Reaction time for correct response trials as a dependent variable, was introduced into a 2 (Alertness: No alerting, Alerting Tone) × 3 (Orienting: Valid, Invalid, Uncued) × 2 (Executive Control: Congruent, Incongruent) factorial mixed ANOVA to explore the overall attentional effects. Mean reaction time per experimental condition, after eliminating extreme values and error rates are depicted in Table 1.
Consistent with previous studies (Callejas et al., 2004; Pacheco-Unguetti et al., 2010, 2011), the main effects of alertness, F(1, 131) = 252.5, mean square error (MSE) = 1167.56, p < .000, η2 = 0.658; orienting, F(2, 262) = 554.4, MSE = 818.35, p < .000, η2 = 0.809 and executive control, F(1, 131) = 1575.9, MSE = 2157.20, p < .000, η2 = 0.923, were significant. Specifically, responses were significantly faster in trials where an alerting tone was present compared with trials in which it was absent, in trials with the presence of an orienting signal, and in trials where distractors pointed in the same direction as the arrow target (i.e., congruent trials). Interactions between attentional networks were also significant. In the alertness and orienting interaction, F(2, 262) = 82.55, MSE = 495.68, p < .000, η2 = 0.387, we found larger reaction time differences between cued and uncued trials in trials with the alerting tone. In the interaction between alertness and executive control, F(1, 131) = 72.21, MSE = 494.74, p < .000, η2 = 0.355, a larger congruency effect was observed when the alerting tone was presented. Finally, the interaction between orienting and executive control, F(2, 262) = 68.11, MSE = 551.10, p < .000, η2 = 0.342, showed a reduction of congruency effect on valid trials. These interactions showed the pattern usually observed in this task (e.g., Callejas et al., 2004; Pacheco-Unguetti et al., 2010, 2011).
Predictive power of attentional control on dysfunctional emotion regulation To determine the role of AC in predicting the tendency to engage in dysfunctional forms of ER, a series of multiple stepwise regression analyses
Table 1. Mean reaction times (in milliseconds) and error rates (in parentheses) for each ANT-I condition
Without alerting tone
Congruent Incongruent
774
With alerting tone
Uncued
Valid
Invalid
Uncued
Valid
Invalid
610 (0.02) 684 (0.00)
570 (0.02) 648 (0.02)
606 (0.05) 705 (0.00)
555 (0.00) 653 (0.01)
537 (0.02) 620 (0.00)
585 (0.01) 710 (0.01)
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Table 2. Summary of stepwise multiple regression analyses predicting brooding, reflection, and suppression (n = 132)
Predictors Brooding STAI-T Orienting network
ΔR2
B
SE B
β
0.466** 0.031**
2.06 −0.030
0.019 0.010
0.684 −0.178 F(1, 129) = 63.78**
Reflection STAI-T
0.112**
0.105
0.026
0.335
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F(1, 130) = 16.46** Suppression STAI-T Alertness network Age
0.373** 0.026* 0.021*
0.704 0.085 −0.193
0.080 0.036 0.089
0.611 0.163 −0.148 F(1, 128) = 30.97**
Note: STAI-T = State-trait Anxiety Inventory–Trait. *p < .05; **p < .0001.
(with probability of F-to-enter ≤5 and probability F-to-remove ≥0.10) were conducted using brooding and reflection facets of rumination and suppression as dependent variables. Trait anxiety, self-reported AC, performance-based AC (i.e., the functioning of each of the orienting, alertness and executive control networks) and age (see Zhou, Fan, Lee, Wang, & Wang, 2011) were introduced as independent variables. Results are depicted in Table 2. In all regression analyses, trait anxiety entered first into the equations and explained the greatest percentage of variance in brooding (46.6%), reflection (11.2%) and suppression (37.3%). For reflection, in fact, trait anxiety was the only variable that entered into the model. That is, neither selfreported AC nor attentional network functioning appeared to be related with this form of ER. For brooding, the functioning of the orienting network explained an additional 3.1% of the variance of this facet of rumination. Age and the alerting network functioning also contributed to explain additional variance of suppression (2.6% and 2.1%, respectively). No significant effects were found either for executive control network functioning or for self-reported AC for any of the dependent variables included in this analysis.
Relationships between self-reported AC and ANT-I Partial two-tailed correlations controlling for age in all variables included in the study (see Table 3) showed that self-reported AC was negatively associated with trait anxiety, both brooding and reflection facets of rumination and suppression. That is, self-reported AC only appeared to be related with these ER styles when other variables, such as trait anxiety or performance-based AC, are not taken into account as was done in the regression analyses previously reported. By contrast, a significant positive association was found between self-reported AC and the orienting functioning, showing, surprisingly, higher self-reported AC to have greater difficulty in disengaging attention from false cues and no significant association with benefits.
DISCUSSION The current study investigated whether attentional network functioning would be related to the tendency to engage in rumination (brooding and reflection facets) and suppression. Moreover, it also aimed to further analyse the controversial links between self-reported and performanceCOGNITION AND EMOTION, 2014, 28 (5)
775
– −0.405**
58.50 92.65 43.27 23.72 28.18 – −0.246** 0.219* – 0.054 0.050 −0.022
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Note: STAI-T = State-trait Anxiety Inventory–Trait; ACS = Attentional Control Scale. *p < .05 two-sided; **p < .01 two-sided.
– 0.030 −0.056 0.636** 0.448** −0.192* 0.074 0.150 −0.077 −0.137 −0.164 0.159 −0.114 0.045 −0.247** −0.271** 0.111 0.026 −0.185* −0.107 0.192* 0.082 −0.076 0.253** −0.066 Behavioural measures 6. Orienting 7. Executive control 8. Alertness 9. Costs 10. Benefits
−0.136 0.200* −0.036 −0.138 −0.002
– −0.281** 0.004 −0.289** Self-reported measures 1. STAI-T – 2. ACS −0.363** 3. Brooding 0.683** 4. Reflection 0.327** 5. Suppression 0.602**
– 0.452** 0.690**
– 0.385**
–
6 5 4 3 2
21.39 26.81 25.65 5.23 4.8
0.934 0.822 0.792 0.774 0.916 11.25 8.77 3.54 3.66 13.46 40.79 54.25 10.87 10.83 38.86
8 7
776
1
Table 3. Partial correlations controlling for age for self-reported and behavioural measures
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9
Mean
SD
Cronbach’s α
TORTELLA-FELIU ET AL.
based AC. Prior to this study, ER styles had not been explored as related to attentional network functioning. A significant finding, only partially in accordance with the first hypothesis, was that reduced attentional orienting was predictive of a tendency to engage in brooding rumination, more than trait anxiety, while self-reported AC did not provide any additional predictive power to trait anxiety. As enhanced attentional orienting entails paying and shifting attention to external cues in anticipation of an upcoming stimulus, and brooding can be considered a prototypical form of self-focused ER (i.e., favouring focus on inner conditions rather than external ones), this could explain why individuals with diminished orienting network functioning are more prone to exhibit a perseverative thinking pattern. According to some influential theoretical approaches in the field, such as the disengagement hypothesis (e.g., Koster et al., 2011), we expected that enhanced orienting functioning would be related with less costs (experiencing less difficulties to disengage from invalid cues) but not with more costs, as our data reflected. It is quite intriguing that difficulties in disengaging attention from invalid cues were negatively associated with brooding. Tull, Maack, Viana, and Gratz (2012) proposed that enhanced orienting response in higher Behavioural Inhibition System sensitivity individuals may be simultaneously considered as adaptive (preparing for adequate responses) and dysfunctional (facilitating attention to threat). Perhaps the same reasoning can be applied to difficulties in disengaging: it may be adaptive when focused on external cues and in tasks without emotional content, as a way to reduce the probability of engaging in dysfunctional ER strategies, but potentially harmful when related to emotional inner experiences. Contrary to our predictions, the executive control was not related to brooding. It was, however, negatively associated with trait anxiety in the correlational analysis. These findings are consistent with previous studies (Pacheco-Unguetti et al., 2010, 2011).
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Regarding suppression, enhanced alertness network functioning was predictive of a greater chance to suppress distressing cognitions, but contrary to our hypothesis, orienting and executive control did not predict suppression. As alerting reflects the sensitivity to perceive and process stimuli, we can consider that, if enhanced, individuals would be more capable of detecting and/or appraising cognitive responses as distressing or inappropriate, and then would try to suppress them. Finally, once again, self-reported AC was not predictive of this ER style while performancebased AC was. However, self-reported AC was positively correlated with orienting functioning. To our knowledge, this finding has not been reported before, since previous literature has only found selfreported AC to be related to performance-based executive AC (Muris et al., 2008; PachecoUnguetti et al., 2011; Reinholdt-Dunne et al., 2009). In the current study, higher self-reported AC was specifically related to greater difficulty in disengaging attention from false cues, not to enhanced orienting benefits. No significant associations were found in the correlational analysis between self-reported AC, alertness and the executive control network. Based on this finding and others reported in the literature, it seems clear that self-reported AC cannot be taken as a direct reflection of performance-based AC and/or the true functioning of attentional capabilities in everyday life. From our data, it is tempting to speculate that self-reported AC is akin to perceived AC derived from personal experiences when trying to focus and shift attention in the real world. Additionally, this subjective evaluation is possibly not only affected by a pure selfobservation of “true” attentional capabilities, but also by trait anxiety or, more widely, by negative affectivity. It is quite well established that individuals with heightened negative affectivity tend to react more intensely to potential stressful or disrupting conditions, and consequently to interpret external events or one’s own performance more negatively. Since both variables always appear highly positively associated with the literature, it is possible that high trait anxiety
determines an individual’s perceptions about impaired attentional capabilities to a considerable extent, beyond what they actually are. We consider that further studies analysing the association between self-reported AC and performance-based AC are warranted with some of the ideas outlined in this discussion to be empirically tested. In summary, the current study shows that rumination and suppression tendencies are related to AC impairments, which has been demonstrated through an attentional task without emotional stimuli rather than using self-reported measures. These findings are consistent with those described in previous studies (e.g., De Lissnyder, Koster, Derakshan, & De Raedt, 2010; Fajkowska & Derryberry, 2010; Hirsch & Mathews, 2012). Specifically, enhanced orienting and alertness functioning were related to increased brooding and suppression, respectively. It may be argued that the associations found in the current study between the functioning of some attentional networks and brooding and rumination reflect a global tendency to engage in more ER rather than a tendency to specifically engage in maladaptive ones. Unfortunately, we did not assess the other forms of ER apart from rumination and suppression to test this hypothesis. However, some kind of specificity can be considered as the reflection facet of rumination exhibited a different pattern of association with the other variables, as compared to brooding and suppression. We believe the topic addressed in the current study deserves further research, in order to overcome some of the limitations in the current experiment and to broaden it to related aspects. For example, it would be interesting to explore whether AC and attentional network functioning with non-emotionally laden tasks is related to ER beyond retrospective self-reporting, as in the present work, but also related to spontaneous ER after emotional induction or by using ecological momentary records of ER strategies used in everyday life. Following these suggestions, a more accurate figure of the relationship could be discovered. We think that expanding the knowledge of how AC and attentional network functioning COGNITION AND EMOTION, 2014, 28 (5)
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relates to core features of emotional disorders (i.e., maladaptive ER styles), could help to inform interventions focused on modifying biased attentional processes in the prevention and treatment of pathological anxiety and depression. Despite the current limitations of the study, the results provide novel insights on the topic. Manuscript received 24 May Revised manuscript received 11 September Manuscript accepted 26 October First published online 3 December
2013 2013 2013 2013
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