Fight, Not Flight! Avoidant Behavior Strengthens Attentional Shift Toward Threat Stimuli During Anxiety

Fight, Not Flight! 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Avoidant Behavior Strengthens Attentional Shift Toward Threat Stimuli During Anxiety Natsuki Sakemoto, Hideyuki Tanaka This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3123023/v2 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 12 Dec, 2024 Read the published version in Psychiatry International → Version 2 posted You are reading this latest preprint version Show more versions Abstract Attentional systems prioritize threat-related stimuli, and this tendency increases with heightened anxiety. The detrimental effects of anxiety on perceptual and motor performance may result in part from this automatic mechanism in which attention is predominantly biased toward threat stimuli, that is, attentional bias. Understanding the relationship between attentional bias and motor control systems is expected to aid in the development of methods to cope with anxiety in athletic situations. With this in mind, the present study investigated how the difference in behavioral goals affects attentional control against threat-related stimuli during induced anxiety. Participants performed a visual probe task, with half responding to the probe target in hit mode and half in avoidance mode. Anxiety levels were manipulated using a threat-of-shock method. Threatening conditions increased the degree of attentional bias toward negative information compared to safe conditions for the avoidance action goal but had no effect on the hit action goal. The differences in fight-or-flight behavioral goals, represented by hit or avoidant actions, were found to interact with state anxiety, resulting in the different degrees of attentional bias toward threat stimuli. Avoidance behavior may strengthen the relationship between attentional bias and anxiety. These findings suggest a hypothesis that when anxiety increases, deliberate efforts to avoid threatening stimuli would rather worsen perceptual and motor performance. Psychology disengagement difficulty emotional cue state-anxiety healthy individuals reaction time Figures Figure 1 Figure 2 Figure 3 Introduction The deterioration of perceptual and motor performance often occurs in anxious situations. Such negative effects of anxiety on perceptual and motor performance can be explained on the attentional and interpretive levels (Nieuwenhuys & Oudejans, 2012). Let us take the example of a football penalty kicker feeling anxious in the 2022 FIFA World Cup Final, which is a high psychological pressure situation. The kickers’ attention may be drawn to the goalkeeper against their intentions or they may interpret the goalkeeper as threatening (e.g., Wilson et al., 2009). Furthermore, task goals that intentionally avoid something are known to worsen motor performance (Gorgulu et al., 2019). It is therefore hypothesized that avoidant behavior from threat stimuli alone can affect not only the degree of attentional shift to potential threat sources but also the degree to which task-irrelevant stimuli are perceived as threatening. Against this background, the present study examined how the alteration of action goals affects automatic attentional control against threat-related stimuli during exogenously induced anxiety. Akin to other animals, humans can rapidly detect and respond to potential dangers in their environment, particularly the events and objects threatening their lives. Such hypervigilance and defense responses to danger (e.g., freezing and fight-or-flight reactions; Cannon, 1932; Roelofs, 2017) are underpinned by attentional mechanisms that prioritize threat-related stimuli. The degree to which threat-related stimuli capture attention differs between individuals, and, in general, people with neuroticism or anxiety disorders are particularly prone to attentional shifts toward threat-related stimuli, that is, attentional bias (Bar-Haim et al., 2007; Mogg & Bradley, 2016). Neuroimaging studies have demonstrated that the effect of a threat-related stimulus capturing attention is mediated by a subcortical brain network centered on the amygdala (e.g., Anderson & Phelps, 2001; Vuilleumier et al., 2003). The subcortical system likely interacts with the prefrontal cortex to modulate emotional and behavioral responses to cope with environmental circumstances (Homan, 2005; Roelofs, 2017). Given the neural links between the cortical and subcortical systems, it is safe to conclude that the effort to cope with anxiety through the voluntary control process of thoughts and behaviors may affect the degree of attentional bias toward threat-related stimuli. Failure of such efforts may result in reinforcing a loop of anxiety, which may induce motor impairments such as yips. Some cognitive theories of anxiety suggest that vulnerability to anxiety is associated with perturbed cognitive processing of threats (Eysenck et al., 2007). Following this tenet, the phenomenon of attentional bias toward threat-related stimuli has been extensively studied, particularly for the treatment of anxiety disorders, using emotional cues that elicit threat or fear, such as angry faces (Fox et al., 2008; Grafton & MacLeod, 2016); aggressive words (Bar-Haim et al., 2007; Fox et al., 2001); and aversive sounds (Massar et al., 2011; Wang et al., 2019). Previous research has demonstrated that people with high-trait anxiety and anxiety disorders are characterized by facilitated attentional engagement. In other words, attention is more easily and faster drawn to a threat or disengagement difficulty—that is, the difficulty of releasing attention from a threat and switching attention from the threat to another stimulus (Cisler & Koster, 2010; Fox et al., 2001, 2002; Koster et al., 2004). In contrast, individuals with low trait anxiety have the opposite bias—to avoid attending to threats—although this tendency is weak and inconsistent (Bar-Haim et al., 2007). Given that anxiety can alter the cognitive processing of stimuli, low-trait anxious individuals might also show the same tendency of attentional bias toward negative emotional information as high-trait anxious individuals when their anxiety states are temporarily considerably elevated. To the best of our knowledge, however, few studies have clarified the relationship between state anxiety and the extent, direction, or both of attentional bias. Robinson and colleagues used a threat-of-shock procedure to manipulate state anxiety levels in healthy participants (Robinson et al., 2011). Although this work has not directly examined the effect of increased state anxiety on the extent and direction of attentional bias, its findings can inform predictions. Threat-of-shock conditions enhanced aversive processing in negative emotional cues (e.g., angry faces). Safe conditions without shocks induced bias toward positive emotional cues (e.g., happy faces). Notably, the authors demonstrated that the combination of a threat-of-shock procedure with emotional cues is a useful tool for investigating the attentional bias phenomenon in healthy individuals without anxiety disorders. Besides changing the cognitive processing of stimuli, increased anxiety is known to alter the function of behavioral control and then deteriorate motor performance. For instance, state anxiety affects eye-gaze control during motor tasks. When anxious, performers tend to exhibit less efficient visual search behaviors and shorter duration of visual fixations (e.g., Murray & Janelle, 2003; Vickers & Williams, 2007; Williams et al., 2002), which probably leads to a decreased efficiency of task-relevant information extraction. A high level of state anxiety also interferes with conscious risk-avoidant movement patterns such as walking and running in a conservative direction (Nibbeling et al., 2012). These behavioral changes, reflecting the function of motor processing against threat circumstances, are likely associated with an underlying mechanism whereby anxiety causes freezing and fight-or-flight behaviors. Thus, effective strategies for coping with anxiety are necessary to maintain motor performance. From the therapeutic perspective for social anxiety disorders, Mogg and Bradley (2016) claimed that treatments to remove attentional bias toward threats and encourage threat avoidance may be effective in reducing anxiety (see also MacLeod & Mathews, 2012; Mathews & MacLeod, 2005). This idea has implications for the development of effective methods to prevent the decline in motor performance associated with increased state anxiety. If the degree and direction of attentional bias depend on whether one confronts or avoids threat-related stimuli through voluntary attentional control, changing action goals such as fight or flight may also be an effective way to cope with anxiety. Furthermore, it is important to understand the effect of action goals on attentional control against threats to gain a broader perspective on how anxiety affects human perceptual–motor behaviors. With these general issues in mind, the present study aims to determine the relationship between action goals and attentional bias toward threat-related stimuli under increased state anxiety. To this end, we applied a threat-of-shock method for the manipulation of state anxiety while employing a modified version of the visual-probe task. A typical trial of the visual-probe task briefly presents emotional cues (happy faces or angry faces), and then the cues is replaced by a probe. Attentional bias toward an emotional cue is inferred from the quickness to respond to the probe. The modified visual-probe task in this study required hitting or avoiding the probe target as a response mode. Based on the review on previous research, we tested the following specific hypotheses: Hypothesis 1 : Threat conditions with shocks would increase the degree of attentional bias toward threat-related stimuli as compared to safe conditions without shocks. Hypothesis 2 : If the alteration of action goals affected the degree or direction of attentional bias, the threat condition would have different effects on attentional bias when hitting or avoiding threat-irrelevant targets. Following the claim that treatments encouraging threat avoidance are effective in reducing anxiety (as mentioned above), volitional motor control to avoid a target could reduce attentional bias toward task-irrelevant, threat-related stimuli. The present results contradicted this prediction. The avoidance action goal interacted with anxiety, not only enhancing attentional bias toward threat-related stimuli but also inducing attentional bias toward stimuli with lower threatening valence. Methods Participants Thirty-two university students (17 males and 15 females aged 20–28 years, = 21.7 years) participated in this experiment after providing written informed consent. Participants were unaware of the experimental hypotheses, and all reported having normal or corrected-to-normal vision. The experimental protocol was approved by the Research Ethics Committee of Tokyo University of Agriculture and Technology (Approval No. 200908-0236), and all experiments were conducted in accordance with the Declaration of Helsinki developed by the World Medical Association. The present experiment was a between-participants design, with two response modes: hitting or avoiding a probe target. Each participant performed either of the two modes in the visual-probe task. The participants completed the trait scale of the Spielberger State-Trait Anxiety Inventory-Japanese version (STAI-JYZ) prior to beginning the experiment. There was no significant difference in the trait anxiety score between the two groups ( t (30) = 0.69, p = .485, Cohen’s d = 0.16), with = 50.4 and SD = 8.6 for the hit group and = 48.2 and SD = 9.8 for the avoidant group. The group means did not significantly differ from those for the Japanese population, with µ = 48.2, σ = 10.0 (Hinoda et al., 2000) for the hit group ( Z = 0.89, p = .375) and the avoidant group ( Z = -0.01, p = .990). Apparatus and Materials We followed the threat-of-shock procedure delineated in previous studies (e.g., Bublatzky et al., 2017; Clark et al., 2012; Schmitz & Grillon, 2012). A portable constant-current stimulator (USE-100, Unique Medical, Japan) was set to deliver bipolar electric pulses with a duration of 5.0 ms and a frequency of 5.0 Hz. The stimulation intensity was varied between 4 mA and 10 mA. A watch-type heart rate (HR) monitor (Polar Vantage M, Polar, Finland) and three visual analogue scales (VASs) with a line segment of 100 mm to indicate their levels of anxiety , fear , and happiness were used to assess the degree of threat manipulation. The participants executed the visual-probe task using three buttons on a handmade response box (233 mm long, 187 mm wide, and 50 mm high). The three buttons with a diameter of 20 mm were arranged in a horizontal row with a gap of 25 mm. During the task trials, the participants pressed each button with the index finger while resting their palm on this device. A fixation point (black crosslines with a line length of 110 pixels and a line width of 5 pixels), face images, and a probe image were presented in a light grey target frame (1,840 × 780 pixels) with a black background. The face images were collected from the FACES database developed by the Center for Lifespan Psychology, Max Planck Institute for Human Development (Ebner et al., 2010). Three face images representing Angry , Happy , and Neutral emotions were selected from two male models (ID: 008 and 114) and two female models (ID: 048 and 140). In total, 12 images were prepared. Irrelevant backgrounds surrounding the faces in the photographs were removed, and the image sizes were adjusted so that the faces fit within a transparent frame of 390 × 520 pixels. To minimize the effect of color on the participants’ responses, all pictures were transformed into grayscale images. A black shadow illustration of a human-like figure was used as a probe target to indicate the start signal and the direction of the response actions. The image size was adjusted to fit within a transparent frame of 520 × 520 pixels. All the visual stimuli were presented on a 27-inch LCD system with a 1,920 × 1,080 pixels resolution and a refresh rate of 60 Hz. During the experiment, the participants faced the display at a distance of 1.2 m. The visual angle of each face image was then approximately 5.8° × 7.5° with a 13.5° disparity between the centers of the two face images. The presentation of the visual stimuli, collection of participants’ responses, and trigger of electric shocks were controlled by a personal computer running an application of the visual-probe task that was originally developed using commercial software (LabVIEW ver. 2019 for Windows, National Instruments, USA). The participants’ responses to manipulating the buttons were acquired at a sampling rate of 1 kHz. Experimental Design and Procedure Half of the participants performed the hit task, and the other half performed the avoidant task. Each action task was block-designed with threat-of-shock conditions (i.e., safe and threat conditions), each of which consisted of three blocks. There were no shocks in the three safe blocks. Electric shocks were delivered after the 10th trial in the 1st threat block and the 30th trial in the 2nd threat block. No shocks were given in the 3rd threat block. Considering two trials after the electric shocks needed to be excluded from the data, two additional trials were added at the end of those blocks. Each of the 6 blocks contained 40 trials, resulting in 240 trials in total. The safe and threat blocks alternated, and the order of the sequence was counterbalanced across the participants within each task group. [Insert Figure 1 about here.] Figure 1 illustrates the sequence of the stimulus presentations and motor responses in each trial. The illustration exemplifies a trial in which the locus of a threat cue (i.e., an angry face) is spatially congruent with the locus of the probe. Each trial began with a beep sound that requested each participant to keep pressing the center button (i.e., the home button) of the response box. Then, the fixation point was displayed at the center of the target frame. It remained visible until each participant pressed either the right or left button (i.e., response buttons). After the presentation of the fixation point, a standby interval of 500 ms followed. Next, a pair of emotional cues (e.g., a pair of happy and neutral faces or a pair of angry and neutral faces from the same model) were simultaneously presented on the left and right sides of the fixation point and remained visible for 200 ms. Next, the probe target appeared on either the left or right side of the fixation point and remained visible for 150 ms. The interstimulus interval was fixed at 350 ms. The hit task was to press the response button that spatially corresponded to the side on which the probe target was presented. The avoidant task was to press the button on the opposite side. Before beginning the hit or avoidant task, each participant decided on the preferred hand to manipulate the response device. The HR monitor was attached to the contralateral wrist. Two disposable electrodes were placed on the surface of the dorsal skin above the third proximal and third intermediate phalanx bones of the contralateral hand. The shock intensity was calibrated for each participant to a level that was “quite unpleasant/uncomfortable but not painful,” following the established protocol (Schmitz & Grillon, 2012). The participants were informed that electric shocks might arrive during some of the trials within the threat blocks but never within the safe blocks. While executing the task, the participants were restricted to using their index fingers alone to press the buttons. They were asked not to release the finger from the home button earlier than the appearance of the probe target and to press the correct response button as quickly and accurately as possible when the probe target was presented. The participants performed 40 practice trials without electric shocks, and then the test trials began. At the beginning of each block, a warning appeared on the display: “ You are now safe from shock this next set of trials ” in black letters on a blue background for the safe condition blocks and “ You may receive an electric shock at some points during the next set of trials ” in black letters on a red background for the threat condition blocks. A 3 min break was given between the blocks. Immediately after completing each block, the participants answered the VAS questionnaires about their moods during the block. The experiment took 60 min. Measurements and Statistical Analysis HR and VAS scores . The raw time-sequence data of the HR records were averaged during each participant’s test block. Next, the average HR and raw VAS scores were averaged among the three test blocks in each of the safe and threat conditions. The participants’ mean measurements were used to statistically test the effect of anxiety manipulation and the difference in induced anxiety levels between the two action goal groups. Anderson–Darling tests revealed that deviations from the normal distribution were significant for some of these variables ( p < .05). For variables with a skewed distribution, Wilcoxon signed-rank tests and Wilcoxon rank-sum tests were used to evaluate the effect of anxiety manipulation and the difference between the action goals, respectively. We calculated r ( Z -score divided by the square root of the sample size) as a measure of effect size. For variables with normal distribution, paired t -tests and t -tests were performed to evaluate those effects, respectively. Cohen’s d was calculated as a measure of effect size. Reaction Times. Task performance was evaluated by measuring the release reaction time (RT), press RT, and total RT. The release RT was defined as the time between the presentation of the probe target and the release of the home button. The press RT was defined as the time between releasing the home button and pressing the right or left response button. The total RT was defined as the sum of the release RT and press RT per trial. Errors, such as pressing the wrong response button, were negligible (8 errors, 0.21% of all hit trials; 16 errors, 0.42% of all avoidant trials). Thus, these error responses were excluded from the full dataset, and the error rates were not statistically analyzed. Trials with release RTs 1,000 ms were eliminated from the analysis as outliers (2.6% of all hit trials and 6.7% of all avoidant trials in the full dataset). Among each participant dataset, the three RT measurements were averaged within the emotional cue condition (i.e., angry faces and happy faces), threat-of-shock condition (i.e., safe and threat), and spatial congruency condition (i.e., the locus of the angry/happy faces was spatially congruent or incongruent with the locus of the probe target). Then, the degree of attentional bias was assessed using the following equation: RT difference [ms] = RT congruent – RT incongruent The individuals’ mean RT differences were used for statistical testing. Anderson–Darling tests revealed that the deviations from the normal distribution were not significant ( p > .05). A three-way, mixed-design analysis of variance (ANOVA) with the emotional cue condition and threat-of-shock condition as the within-participant factors and the task group as the between-participant factor was performed for all the RT variables. If the three-way interaction term reached a significant level ( p < .05), two-way repeated measures ANOVA was performed separately for each of the task groups to estimate the effects of the emotional cue and threat-of-shock condition factors. If the two-way interactions of this ANOVA were significant, multiple comparison tests using paired t -tests with the Bonferroni correction were performed separately for each combination of interests between the levels of the factors. A Greenhouse–Geisser correction was applied when sphericity was violated for the repeated measures. For all the ANOVA tests, the generalized eta squared ( η 2 G ) was calculated as a measure of effect size (Bakeman, 2005). For all multiple comparison tests, Cohen’s d was calculated as a measure of effect size. Results Manipulation Checks There were no significant differences in HR and happiness VAS scores between the safe and threat conditions for either task group ( p > .05). Compared to the safe condition, the anxiety VAS scores increased under the threat condition for the hit group ( Z = 2.74, p = .006, r = .69) and avoidant group ( t (15) = 5.34, p = .001, d = 1.00). The fear VAS scores also increased under the threat condition for the hit group ( t (15) = 3.79, p = .002, d = 2.28) and the avoidant group ( Z = 3.14, p = .002, r = .78). There were no significant group differences in HR, anxiety scores, and fear scores ( p > .05). The happiness VAS scores of the avoidant group were significantly larger than those of the hit group ( Z = 2.36, p = .018, r = .42). These results confirm that by providing a very few electric shocks during the task trials, the threat manipulation protocol induced anxiety in the participants. Task Performance A mixed-design ANOVA test demonstrated a significant three-way interaction effect in the press RT ( F (1,30) = 6.00, p = .02, η 2 G = 0.03) and total RT ( F (1,30) = 6.16, p = .019, η 2 G = 0.05). However, the three-way interaction effect in the release RT did not reach a significant level ( F (1,30) = 0.15, p = .705, η 2 G = 0.00). [Insert Figure 2 about here.] Figure 2 shows the group means and standard errors (SEs) of the RT difference as a function of the emotional cue condition under each of the threat-of-shock levels for the hit group. For the release RT and press RT, the effects of the emotional cue, threat-of-shock, and interaction factors did not reach a significant level ( p > .05). However, the emotional cue had a significant effect on the total RT ( F (1,15) = 4.77, p = .045, η 2 G = 0.09), whereas the effects of threat-of-shock and interaction factors were not significant ( p > .05). The negative cues (angry faces) significantly decreased the mean of total RT compared to the positive cues (happy faces) ( = -6.8, SE = 3.1, 95% CI [-13.5, -0.2]). In sum, Hypothesis 1 was not supported for the hit action mode. [Insert Figure 3 about here.] Figure 3 shows the group means and SEs of the RT difference for the avoidant group. The effects of the emotional cue, threat-of-shock, and interaction factors on the release RT were not significant ( p > .05). On the press RT, the two-way interaction effect was significant ( F (1,15) = 6.26, p = .024, η 2 G = 0.07), whereas the effects of the emotional cue and threat-of-shock factors were not significant ( p > .05). There was a significant difference between the negative/angry and positive/happy emotional cues under the threat condition ( t (15) = 3.11, p = .007, d = 0.91, = 15.4, SE = 4.9, 95% CI [4.8, 25.9]). The safe condition did not show a significant difference between the negative/angry and positive/happy emotional cues ( p > .05). For each of the negative/angry and positive/happy emotional cues, no significant differences were found between the safe and threat conditions ( p > .05). On the total RT, there was a significant effect of the emotional cue factor ( F (1,15) = 5.00, p = .042, η 2 G = 0.07) and a significant effect of the interaction ( F (1,15) = 13.20, p = .002, η 2 G = 0.16). The effect of the threat-of-shock factor did not reach significance ( p > .05). For the positive/happy emotional cue, the threat condition significantly decreased the mean of the RT difference against the safe condition ( t (15) = 2.63, p = .019, d = 0.80, = -12.3, SE = 4.7, 95% CI [-22.3, -2.3]). In contrast, for the negative/angry emotional cue, the threat condition significantly increased the mean of the RT difference against the safe condition ( t (15) = 2.76, p = .015, d = 0.80, = 11.0, SE = 4.0, 95% CI [2.5, 19.5]). There was a significant difference between the positive and negative emotional cues under the threat condition ( t (15) = 3.98, p = .001, d = 1.28, = 19.0, SE = 4.8, 95% CI [8.8, 29.2]), whereas no significant difference was found under the safe condition ( p > .05). In sum, Hypothesis 1 was supported for the avoidance action mode. Thus, Hypothesis 2 was supported. Discussion To the best of our knowledge, this was the first attempt to investigate how the alteration of action goals interacts with state anxiety, affecting attentional bias toward threat stimuli in healthy individuals. The present study revealed that during elevated anxiety levels, the difference in behavioral goals of fight or flight, represented by hit or avoidance actions, induces the different characteristics of attentional bias toward threat stimuli. Specifically, the hit action mode enhanced faster responses to the probe target that appeared in the same location as the angry faces (hereafter, threat-congruent trials) than in the opposite location (hereafter, threat-incongruent trials). This faster response in the threat-congruent trials was independent of the anxiety level. In contrast, when the participants were required to avoid the probe target (i.e., to choose the space opposite to where the probe target was presented), their motor responses were delayed in the threat-congruent trials. Interestingly, the avoidance action mode enhanced faster responses to the probe target that appeared in the same location as the happy faces (hereafter, safe-congruent trials) than in the opposite location (hereafter, safe-incongruent trials). These tendencies were elicited depending on the anxiety level. The conventional visual-probe task assumes that the faster response to probes in the threat-congruent trials reflects an attentional bias toward threat-related stimuli (Grafton et al., 2012). It is noteworthy that most other studies used the hit mode. An attentional bias toward threat cues occurs not only in anxious adults (Bar-Haim et al., 2007) but also in healthy adults (Holmes et al., 2009) at shorter stimulus durations (≤ 500 ms). In contrast, the attentional bias effect observed at longer stimulus durations (> 500 ms) is still a subject of debate. In the present experiment using an interstimulus duration of 350 ms, the release RT did not reflect a faster (or delayed) response enhanced by the presence of negative emotional stimuli. Theoretically, the release RT measures efficiency in detecting the probe target. When considered together with this methodological basis, the present results suggest that attentional bias toward threat-related stimuli may play an important role in processing the selection and execution of rapid motor response rather than in stimulus detection processing. Notably, such quick motor responses to threats, which appear to be underpinned by an automatic attentional bias, were elicited independently of state anxiety in the hit action mode. In other words, the fight action goal seems to have the effect of increasing reactivity to threat stimuli through the biased attention regardless of anxiety level. Regarding the direction of attentional bias, there are two possible accounts for the results of the avoidance mode. The characteristics of attentional bias in highly anxious individuals can be classified into three observable components: facilitated attentional engagement, disengagement difficulty, and attention avoidance (Cisler & Koster, 2010; Fox et al., 2001, 2002; Koster et al., 2004). If the tendencies of attention avoidance from threats predominated, the general shortening of the RT would occur in threat-incongruent trials. However, attention avoidance has not been reported at shorter stimulus durations (≤ 500 ms) (see Mogg & Bradley, 2016 for a review). Thus, the involvement of attention avoidance is also unlikely to occur in the present experiment. At the same time, findings from conventional visual-probe tasks have been explained in terms of either facilitated attentional engagement with threat or difficulty in disengaging from threat in anxious individuals (Clarke et al., 2013). If attention is unconsciously engaged with threat-related stimuli prior to the presentation of the probe, this will result in shorter latencies to identify the probe in its vicinity. The release RT showed that the latency to detect the probe was not associated with the threat-congruency and state anxiety levels for either mode of action. It is possible that the participants initially engaged their attention equally with either the threatening or neutral stimuli. This raises the possibility that the attentional bias tendencies observed in the present study could be explained by disengagement difficulty, which results in slowing down to reorient attention away from threatening stimuli once they have been identified rather than facilitating attentional engagement with threatening stimuli (Fox et al., 2001). If this were the case, when attention tends to remain in the vicinity of threatening stimuli, the tendency of disengagement difficulty increased by anxiety would lead to longer latencies in the avoidance action mode in threat-congruent trials. Therefore, the disengagement difficulty hypothesis is a plausible explanation for the present results. The avoidance action mode revealed another unique phenomenon. Enhanced faster responses to the probe were found in the safe-congruent trials as compared to the safe-incongruent trials. In general, organisms are endowed with mechanisms that automatically regulate approach behavior toward positive objects and avoid negative objects (e.g., Kielmeyer et al., 2010, 2011). The results of the avoidance action mode are inconsistent with what this innate approach–avoidance control mechanism predicts. One possible explanation for this result is that anxiety can also lead to threat-related interpretations (Bishop, 2007; Blanchette & Richards, 2010). This means that despite visual attention to task-relevant information, this information may be perceived differently or misinterpreted depending on one’s current emotions or state (Nieuwenhuys & Oudejans, 2012). To the extent that threat-of-shock led the participants to interpret neutral faces as being more threatening than happy faces, the disengagement difficulty function would work to slow down the redirection of attention away from the neutral stimuli. This might result in the faster responses to the probe in the safe-congruent trials. In any case, this appears to be a specific phenomenon induced by the avoidance action mode. In conclusion, behavioral goals such as fight or flight, represented by hitting and avoiding a target, were found to interact with state anxiety, leading to different degrees of attentional bias. Avoidance behavioral goals may function to strengthen the link between attentional bias (in this case disengagement difficulty) and anxiety. Furthermore, they may induce a tendency to interpret stimuli with lower threatening valence as threatening. Therefore, it is safe to assume that treatments or instructions that encourage the avoidance of threatening stimuli as an action mode are not effective in reducing state anxiety, at least for healthy individuals. The ironic process theory of mental control predicts that intentional control of actions to avoid unwanted goals will produce counter-intentional errors (Wegner et al., 1998). This seems to be another possible explanatory theory for our result. In discussing the mechanisms underlying the present findings, three limitations arise, particularly regarding the research methodology. First, this study employed visual-probe tasks; therefore, we cannot fully dissociate the disengagement difficulty component from the facilitated attentional engagement component in anxiety, as reported by Clarke et al. (2013). To elucidate this point, we attempted to measure the latency to detect the presence of the probe stimulus and the latency to choose the response direction separately. This separation evidenced the possibility that disengagement difficulty is involved in threat stimulus-driven process of attentional control for healthy individuals as well. Second, the threat-of-shock protocol in the present study did not induce a high enough level of state anxiety to significantly increase HR, although it did increase the levels of subjective state anxiety. The results showing higher levels of state anxiety to the extent that it manifests itself in physiological responses could aid in elucidating the background mechanism that may explain the present findings. Third, we did not test the effect of the alteration of action goals on biased attention using a within-participants design. In this study, a group comparison design was adopted because the frequent repetition of electric shocks may allow each participant to become accustomed to the stimulus intensity and consequently reduce state anxiety levels. Therefore, future research should focus on developing methods that can consistently induce high state anxiety levels in healthy individuals to advance our understanding in this area. Conclusions Most other studies have employed the hit action mode as a response to a probe stimulus to investigate attentional bias toward threat-related stimuli. We have adopted a different strategy to determine whether the alteration of action goals affects the degree of attentional bias. The present approach provided the first evidence to suggest that the voluntary control process of avoidance behaviors may function to strengthen the link between attentional bias and anxiety. The present findings put forward the hypothesis that when anxiety increases, deliberate efforts to avoid threatening stimuli may actually worsen perceptual and motor performance. Declarations Funding This work was supported by a Grant-in-Aid for Young Scientists from JSPS (Grant No. 20K19607) awarded to NS and a Grant-in-Aid for Scientific Research (C) from JSPS (Grant No. 22K11631) awarded to HT. Declaration of conflicting interests The authors declare that no conflicts of interest exist. References Anderson, A. K., & Phelps, E. A. (2001). Lesions of the human amygdala impair enhanced perception of emotionally salient events. Nature , 411 (6835), 305–309. https://doi.org/10.1038/35077083 Bakeman, R. (2005). Recommended effect size statistic. Behavior Research Methods , 37 (3), 379–384. Bar-Haim, Y., Lamy, D., Pergamin, L., Bakermans-Kranenburg, M. J., & Van Ijzendoorn, M. H. (2007). Threat-related attentional bias in anxious and nonanxious individuals: A meta-analytic study. 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L., & Baas, J. M. P. (2011). Attentional bias in high- and low-anxious individuals: Evidence for threat-induced effects on engagement and disengagement. Cognition & Emotion , 25 (5), 805–817. https://doi.org/10.1080/02699931.2010.515065 Mathews, A., & MacLeod, C. (2005). Cognitive vulnerability to emotional disorders. Annual Review of Clinical Psychology , 1 (1), 167–195. https://doi.org/10.1146/annurev.clinpsy.1.102803.143916 Mogg, K., & Bradley, B. P. (2016). Anxiety and attention to threat: Cognitive mechanisms and treatment with attention bias modification. Behaviour Research and Therapy , 87 , 76–108. https://doi.org/10.1016/j.brat.2016.08.001 Murray, N. P., & Janelle, C. M. (2003). Anxiety and performance: A visual search examination of the processing efficiency theory. Journal of Sport and Exercise Psychology , 25 (2), 171–187. https://doi.org/10.1123/jsep.25.2.171 Nibbeling, N., Daanen, H. A. M., Gerritsma, R. M., Hofland, R. M., & Oudejans, R. R. D. (2012). Effects of anxiety on running with and without an aiming task. Journal of Sports Sciences , 30 (1), 11–19. https://doi.org/10.1080/02640414.2011.617386 Nieuwenhuys, A., & Oudejans, R. R. D. (2012). Anxiety and perceptual-motor performance: Toward an integrated model of concepts, mechanisms, and processes. Psychological Research , 76 (6), 747–759. https://doi.org/10.1007/s00426-011-0384-x Robinson, O. J., Letkiewicz, A. M., Overstreet, C., Ernst, M., & Grillon, C. (2011). The effect of induced anxiety on cognition: threat of shock enhances aversive processing in healthy individuals. Cognitive, Affective, & Behavioral Neuroscience , 11 (2), 217–227. https://doi.org/10.3758/s13415-011-0030-5 Roelofs, K. (2017). Freeze for action: Neurobiological mechanisms in animal and human freezing. Philosophical Transactions of the Royal Society B: Biological Sciences , 372 (1718), 20160206. https://doi.org/10.1098/rstb.2016.0206 Schmitz, A., & Grillon, C. (2012). Assessing fear and anxiety in humans using the threat of predictable and unpredictable aversive events (the NPU-threat test). Nature Protocols , 7 (3), 527–532. https://doi.org/10.1038/nprot.2012.001 Vickers, J. N., & Williams, A. M. (2007). Performing under pressure: The effects of physiological arousal, cognitive anxiety, and gaze control in biathlon. Journal of Motor Behavior , 39 (5), 381–394. https://doi.org/10.3200/JMBR.39.5.381-394 Vuilleumier, P., Armony, J. L., Driver, J., & Dolan, R. J. (2003). Distinct spatial frequency sensitivities for processing faces and emotional expressions. Nature Neuroscience , 6 (6), 624–631. https://doi.org/10.1038/nn1057 Wang, Y., Xiao, R., Luo, C., & Yang, L. (2019). Attentional disengagement from negative natural sounds for high-anxious individuals. Anxiety, Stress, & Coping , 32 (3), 298–311. https://doi.org/10.1080/10615806.2019.1583539 Wegner, D. M., Ansfield, M., & Pilloff, D. (1998). The putt and the pendulum: Ironic effects of the mental control of action. Psychological Science , 9 (3), 196–199. https://doi.org/10.1111/1467-9280.00037 Williams, A. M., Vickers, J., & Rodrigues, S. (2002). The effects of anxiety on visual search, movement kinematics, and performance in table tennis: A test of Eysenck and Calvo’s processing efficiency theory. Journal of Sport and Exercise Psychology , 24 (4), 438–455. https://doi.org/10.1123/jsep.24.4.438 Wilson, M. R., Wood, G., & Vine, S. J. (2009). Anxiety, attentional control, and performance impairment in penalty kicks. Journal of Sport and Exercise Psychology , 31 (6), 761–775. https://doi.org/10.1123/jsep.31.6.761 Additional Declarations The authors declare no competing interests. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3123023","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":216009801,"identity":"7cc691e8-e6de-43e7-87d5-60464357b272","order_by":0,"name":"Natsuki Sakemoto","email":"","orcid":"","institution":"Seiwa University","correspondingAuthor":false,"prefix":"","firstName":"Natsuki","middleName":"","lastName":"Sakemoto","suffix":""},{"id":216009802,"identity":"208413e6-5f09-4a1c-8f15-48ddd339a27a","order_by":1,"name":"Hideyuki Tanaka","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYJACZgYDZgZ+FCEJPMp5YFokG4CsAzDFhLWAdB1A1oIP2LOfPfi5oMBazvj44QfMH9vs6hjYDz9gsNyBxxaevGTpGQbpxmZn0gwYDrYlSzDwABmSZ/A5LMdAmsfgcOK2G0A3HmxjBjosh4FBsg2PFv43xr+BWuo3zwBrqZdg4H9DQItEjhnIlgQDCbCWwxIMEoRsufHGzJrHIN1wBtAvB86cOy7ZJvHM4AA+v7D35xjf5vljLc/ffvjhg4qyan5+/uSHjyXxhBgKOAAi2ID4MDhiSQKMH0nWMgpGwSgYBcMYAADMtkWNaf0BUQAAAABJRU5ErkJggg==","orcid":"","institution":"Tokyo University of Agriculture and Technology","correspondingAuthor":true,"prefix":"","firstName":"Hideyuki","middleName":"","lastName":"Tanaka","suffix":""}],"badges":[],"createdAt":"2023-06-29 05:59:26","currentVersionCode":2,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-3123023/v2","doiUrl":"https://doi.org/10.21203/rs.3.rs-3123023/v2","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.3390/psychiatryint5040068","type":"published","date":"2024-12-13T00:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":49149481,"identity":"6db54814-4c11-480a-b395-05dfd5847725","added_by":"auto","created_at":"2024-01-03 23:00:13","extension":"tif","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":733802,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic illustration of a sequence of stimulus presentations and the motor response in each trial. The task goal was to press the correct response button on the same and opposite side of where the silhouette of a human figure (probe target) was presented on a display for the hit and avoidant tasks, respectively. This illustration shows a trial in which the locus of a threat cue (an angry face) is spatially congruent with the locus of the probe (a human figure).\u003c/p\u003e","description":"","filename":"Figure1.tif","url":"https://assets-eu.researchsquare.com/files/rs-3123023/v2/167e78f140248765a55c851e.tif"},{"id":49149479,"identity":"0c2e9d81-34bd-4b5c-821a-a2975d834e65","added_by":"auto","created_at":"2024-01-03 23:00:13","extension":"tif","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":159541,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of the mean RT difference under the safe and threat blocks as a function of the emotional cue condition (angry faces and happy faces) for the hit task. The error bars represent standard errors.\u003c/p\u003e","description":"","filename":"Figure2.tif","url":"https://assets-eu.researchsquare.com/files/rs-3123023/v2/4cf9b1d34c0fa28d8b6548f4.tif"},{"id":49149480,"identity":"a3d9b81a-3a85-4211-a8a9-6e7321c77481","added_by":"auto","created_at":"2024-01-03 23:00:13","extension":"tif","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":166782,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of the mean RT difference under the safe and threat blocks as a function of the emotional cue condition (angry faces and happy faces) for the avoidant task. The error bars represent standard errors.\u003c/p\u003e","description":"","filename":"Figure3.tif","url":"https://assets-eu.researchsquare.com/files/rs-3123023/v2/c300f6a169920289758708e8.tif"},{"id":71902788,"identity":"52a8eda6-2085-473a-ad4e-2afce06b6add","added_by":"auto","created_at":"2024-12-19 14:48:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":993376,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3123023/v2/cf9775a4-aaed-4739-8a24-6a038afddb35.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eFight, Not Flight! Avoidant Behavior Strengthens Attentional Shift Toward Threat Stimuli During Anxiety\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe deterioration of perceptual and motor performance often occurs in anxious situations. Such negative effects of anxiety on perceptual and motor performance can be explained on the attentional and interpretive levels\u0026nbsp;(Nieuwenhuys \u0026amp; Oudejans, 2012). Let us take the example of a football penalty kicker feeling anxious in the 2022 FIFA World Cup Final, which is a high psychological pressure situation.\u0026nbsp;The kickers\u0026rsquo; attention may be drawn to the goalkeeper\u0026nbsp;against their intentions\u0026nbsp;or they may interpret the goalkeeper as threatening (e.g., Wilson et al., 2009). Furthermore, task goals that intentionally avoid something are known to worsen motor performance (Gorgulu et al., 2019). It is therefore hypothesized that avoidant behavior from threat stimuli alone can affect not only the degree of attentional shift to potential threat sources but also the degree to which task-irrelevant stimuli are perceived as threatening. Against this background, the present study examined how the alteration of action goals affects automatic attentional control against threat-related stimuli during exogenously induced anxiety.\u003c/p\u003e\n\u003cp\u003eAkin to other animals, humans can rapidly detect and respond to potential dangers in their environment, particularly the events and objects threatening their lives. Such hypervigilance and defense responses to danger (e.g., freezing and fight-or-flight reactions; Cannon, 1932; Roelofs, 2017) are underpinned by attentional mechanisms that prioritize threat-related stimuli. The degree to which threat-related stimuli capture attention differs between individuals, and, in general, people with neuroticism or anxiety disorders are particularly prone to attentional shifts toward threat-related stimuli, that is, attentional bias (Bar-Haim et al., 2007; Mogg \u0026amp; Bradley, 2016). Neuroimaging studies have demonstrated that the effect of a threat-related stimulus capturing attention is mediated by a subcortical brain network centered on the amygdala (e.g., Anderson \u0026amp; Phelps, 2001; Vuilleumier et al., 2003). The subcortical system likely interacts with the prefrontal cortex to modulate emotional and behavioral responses to cope with environmental circumstances (Homan, 2005; Roelofs, 2017). Given the neural links between the cortical and subcortical systems, it is safe to conclude that the effort to cope with anxiety through the voluntary control process of thoughts and behaviors may affect the degree of attentional bias toward threat-related stimuli. Failure of such efforts may result in reinforcing a loop of anxiety, which may induce motor impairments such as yips.\u003c/p\u003e\n\u003cp\u003eSome cognitive theories of anxiety suggest that vulnerability to anxiety is associated with perturbed cognitive processing of threats (Eysenck et al., 2007). Following\u0026nbsp;this tenet, the phenomenon of attentional bias toward threat-related stimuli has been extensively studied, particularly\u0026nbsp;for the treatment of anxiety disorders,\u0026nbsp;using\u0026nbsp;emotional cues that elicit threat or fear, such as angry faces (Fox et al., 2008; Grafton \u0026amp; MacLeod, 2016); aggressive words (Bar-Haim et al., 2007; Fox et al., 2001); and aversive sounds (Massar et al., 2011; Wang et al., 2019). Previous research has demonstrated that people with high-trait anxiety and\u0026nbsp;anxiety disorders\u0026nbsp;are characterized by facilitated attentional engagement.\u0026nbsp;In other words, attention is more easily and faster drawn\u0026nbsp;to a threat or\u0026nbsp;disengagement difficulty\u0026mdash;that is, the difficulty of releasing attention from a threat\u0026nbsp;and switching attention from the threat to another stimulus\u0026nbsp;(Cisler \u0026amp; Koster, 2010; Fox et al., 2001, 2002; Koster et al., 2004).\u0026nbsp;In contrast, individuals with low trait anxiety have the opposite bias\u0026mdash;to avoid attending to threats\u0026mdash;although this tendency is weak and inconsistent (Bar-Haim et al., 2007).\u003c/p\u003e\n\u003cp\u003eGiven that anxiety can alter the cognitive processing of stimuli, low-trait anxious individuals might also show the same tendency of attentional bias toward negative emotional information as high-trait anxious individuals\u0026nbsp;when their anxiety states are temporarily considerably elevated. To the best of our knowledge, however, few studies have clarified the relationship between state anxiety and the extent, direction, or both of attentional bias.\u0026nbsp;Robinson and colleagues used a threat-of-shock procedure to manipulate state anxiety levels in healthy participants (Robinson et al., 2011). Although this work has not directly examined the effect of increased state anxiety on\u0026nbsp;the extent and direction of attentional bias, its findings can inform predictions.\u0026nbsp;Threat-of-shock conditions enhanced aversive processing in negative emotional cues (e.g., angry faces). Safe conditions without shocks induced bias toward positive emotional cues (e.g., happy faces). Notably, the authors demonstrated that the combination of a threat-of-shock procedure with\u0026nbsp;emotional cues\u0026nbsp;is a useful tool for investigating the attentional bias phenomenon in healthy individuals without anxiety disorders.\u003c/p\u003e\n\u003cp\u003eBesides changing the cognitive processing of stimuli,\u0026nbsp;increased anxiety is known to alter the function of behavioral control and then\u0026nbsp;deteriorate motor performance.\u0026nbsp;For instance, state anxiety affects eye-gaze control during motor tasks. When anxious, performers tend to exhibit less efficient visual search behaviors and\u0026nbsp;shorter duration of visual fixations (e.g., Murray \u0026amp; Janelle, 2003; Vickers \u0026amp; Williams, 2007; Williams et al., 2002),\u0026nbsp;which probably leads to a decreased efficiency of task-relevant information extraction. A high level of state anxiety also interferes with conscious risk-avoidant movement patterns such as walking and running in a conservative direction (Nibbeling et al., 2012). These behavioral changes, reflecting the function of motor processing against threat circumstances, are likely associated with an underlying mechanism whereby anxiety causes freezing and fight-or-flight behaviors. Thus, effective strategies for coping with anxiety are necessary to maintain motor performance. From the therapeutic perspective for social anxiety disorders, Mogg and Bradley (2016) claimed that treatments to remove attentional bias toward threats and encourage threat avoidance may be effective in reducing anxiety (see also MacLeod \u0026amp; Mathews, 2012; Mathews \u0026amp; MacLeod, 2005). This idea has implications for the development of effective methods to prevent the decline in motor performance associated with increased state anxiety. If the degree and direction of attentional bias depend on whether one confronts or avoids threat-related stimuli through voluntary attentional control, changing action goals such as fight or flight may also be an effective way to cope with anxiety.\u0026nbsp;Furthermore, it is important to understand the effect of action goals on attentional control against threats to gain a broader perspective on how anxiety affects human perceptual\u0026ndash;motor behaviors.\u003c/p\u003e\n\u003cp\u003eWith these general issues in mind, the present study aims\u0026nbsp;to\u0026nbsp;determine the relationship between action goals and attentional bias toward threat-related stimuli under increased state anxiety. To this end, we applied a threat-of-shock method\u0026nbsp;for the manipulation of state anxiety\u0026nbsp;while employing\u0026nbsp;a modified version of the visual-probe task.\u0026nbsp;A typical trial of the visual-probe task briefly presents emotional cues (happy faces or angry faces), and then the cues is replaced by a probe. Attentional bias toward an emotional cue is inferred from the quickness to respond to the probe. The modified visual-probe task in this study\u0026nbsp;required hitting or avoiding the probe target as a response mode.\u0026nbsp;Based on the review on previous research,\u0026nbsp;we tested the following specific hypotheses:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHypothesis 1\u003c/strong\u003e:\u0026nbsp;Threat conditions with shocks would increase the degree of attentional bias toward threat-related stimuli as compared to safe conditions without shocks.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHypothesis 2\u003c/strong\u003e: If\u0026nbsp;the alteration of action goals affected the degree or direction of attentional bias,\u0026nbsp;the threat condition would have different effects on attentional bias when hitting or avoiding threat-irrelevant targets.\u003c/p\u003e\n\u003cp\u003eFollowing the claim that treatments encouraging threat avoidance are effective in reducing anxiety (as mentioned above), volitional motor control to avoid a target could reduce attentional bias toward task-irrelevant, threat-related stimuli. The present results contradicted this prediction. The avoidance action goal interacted with anxiety, not only enhancing attentional bias toward threat-related stimuli but also inducing attentional bias toward stimuli with lower threatening valence.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cem\u003eParticipants\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThirty-two university students (17 males and 15 females aged 20\u0026ndash;28 years,\u0026nbsp;\u0026nbsp;\u0026nbsp;= 21.7 years) participated in this experiment after providing written\u0026nbsp;informed\u0026nbsp;consent. Participants were unaware of the experimental hypotheses, and all reported having normal or corrected-to-normal vision.\u0026nbsp;The experimental protocol was approved by\u0026nbsp;the Research Ethics Committee of Tokyo University of Agriculture and Technology (Approval No. 200908-0236), and\u0026nbsp;all experiments were conducted in accordance with the Declaration of Helsinki developed by the World Medical Association.\u003c/p\u003e\n\u003cp\u003eThe present experiment was a between-participants design, with two response modes: hitting or avoiding a probe target. Each participant performed either of the two modes in the\u0026nbsp;visual-probe task. The participants completed the trait scale of the Spielberger State-Trait Anxiety Inventory-Japanese version (STAI-JYZ) prior to beginning the experiment. There was no significant difference in the trait anxiety score between the two groups (\u003cem\u003et\u003c/em\u003e(30) = 0.69, \u003cem\u003ep\u003c/em\u003e = .485, Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e = 0.16), with\u0026nbsp;\u0026nbsp;\u0026nbsp;=\u0026nbsp;50.4 and \u003cem\u003eSD\u003c/em\u003e = 8.6 for the hit group and\u0026nbsp;\u0026nbsp;\u0026nbsp;= 48.2 and \u003cem\u003eSD\u003c/em\u003e = 9.8 for the avoidant group. The group means did not significantly differ from those for the Japanese population, with \u003cem\u003e\u0026micro;\u003c/em\u003e = 48.2, \u003cem\u003e\u0026sigma;\u003c/em\u003e = 10.0 (Hinoda et al., 2000) for the hit group (\u003cem\u003eZ\u003c/em\u003e = 0.89, \u003cem\u003ep\u003c/em\u003e = .375) and the avoidant group (\u003cem\u003eZ\u003c/em\u003e = -0.01, \u003cem\u003ep\u003c/em\u003e = .990).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eApparatus and Materials\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWe followed the threat-of-shock procedure delineated in previous studies\u0026nbsp;(e.g., Bublatzky et al., 2017; Clark et al., 2012; Schmitz \u0026amp; Grillon, 2012).\u0026nbsp;A portable constant-current stimulator (USE-100, Unique Medical, Japan) was set to deliver bipolar electric pulses with a duration of 5.0 ms and a frequency of 5.0 Hz. The stimulation intensity was varied between 4 mA and 10 mA. A watch-type heart rate (HR) monitor (Polar Vantage M, Polar, Finland) and three visual analogue scales (VASs) with a line segment of 100 mm to indicate their levels of \u003cem\u003eanxiety\u003c/em\u003e, \u003cem\u003efear\u003c/em\u003e, and \u003cem\u003ehappiness\u003c/em\u003e were used to assess the degree of threat manipulation.\u003c/p\u003e\n\u003cp\u003eThe participants executed the visual-probe task using three buttons on a handmade response box (233 mm long, 187 mm wide, and 50 mm high). The three buttons with a diameter of 20 mm were arranged in a horizontal row with a gap of 25 mm. During the task trials, the participants pressed each button with the index finger while resting their palm on this device.\u003c/p\u003e\n\u003cp\u003eA fixation point (black crosslines with a line length of 110 pixels and a line width of 5 pixels), face images, and a probe image were presented in a light grey target frame (1,840 \u0026times; 780 pixels) with a black background. The face images were collected from the FACES database developed by the Center for Lifespan Psychology, Max Planck Institute for Human Development (Ebner et al., 2010). Three face images representing \u003cem\u003eAngry\u003c/em\u003e, \u003cem\u003eHappy\u003c/em\u003e, and \u003cem\u003eNeutral\u003c/em\u003e emotions were selected from two male models (ID: 008 and 114) and two female models (ID: 048 and 140). In total, 12 images were prepared. Irrelevant backgrounds surrounding the faces in the photographs were removed, and the image sizes were adjusted so that the faces fit within a transparent frame of 390 \u0026times; 520 pixels. To minimize the effect of color on the participants\u0026rsquo; responses, all pictures were transformed into grayscale images. A black shadow illustration of a human-like figure was used as a probe target to indicate the start signal and the direction of the response actions. The image size was adjusted to fit within a transparent frame of 520 \u0026times; 520 pixels. All the visual stimuli were presented on a 27-inch LCD system with a 1,920 \u0026times; 1,080 pixels resolution and a refresh rate of 60 Hz. During the experiment, the participants faced the display at a distance of 1.2 m. The visual angle of each face image was then approximately 5.8\u0026deg; \u0026times; 7.5\u0026deg; with a 13.5\u0026deg; disparity between the centers of the two face images.\u003c/p\u003e\n\u003cp\u003eThe presentation of the visual stimuli, collection of participants\u0026rsquo; responses, and trigger of electric shocks were controlled by a personal computer running an application of the visual-probe task that was originally developed using commercial software (LabVIEW ver. 2019 for Windows, National Instruments, USA). The participants\u0026rsquo; responses to manipulating the buttons were acquired at a sampling rate of 1 kHz.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eExperimental Design and Procedure\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eHalf of the participants performed the hit task, and the other half performed the avoidant task. Each action task was block-designed with threat-of-shock conditions (i.e., safe and threat conditions), each of which consisted of three blocks. There were no shocks in the three safe blocks. Electric shocks were delivered after the 10th trial in the 1st threat block and the 30th trial in the 2nd threat block. No shocks were given in the 3rd threat block. Considering two trials after the electric shocks needed to be excluded from the data, two additional trials were added at the end of those blocks. Each of the 6 blocks contained 40 trials, resulting in 240 trials in total. The safe and threat blocks alternated, and the order of the sequence was counterbalanced across the participants within each task group.\u003c/p\u003e\n\u003cp\u003e[Insert Figure 1 about here.]\u003c/p\u003e\n\u003cp\u003eFigure 1 illustrates the sequence of the stimulus presentations and motor responses in each trial. The illustration exemplifies a trial in which the locus of a threat cue (i.e., an angry face) is spatially congruent with the locus of the probe. Each trial began with a beep sound that requested each participant to keep pressing the center button (i.e., the home button) of the response box. Then, the fixation point was displayed at the center of the target frame. It remained visible until each participant pressed either the right or left button (i.e., response buttons). After the presentation of the fixation point, a standby interval of 500 ms followed. Next, a pair of emotional cues (e.g., a pair of happy and neutral faces or a pair of angry and neutral faces from the same model) were simultaneously presented on the left and right sides of the fixation point and remained visible for 200 ms. Next, the probe target appeared on either the left or right side of the fixation point and remained visible for 150 ms. The interstimulus interval was fixed at 350 ms. The hit task was to press the response button that spatially corresponded to the side on which the probe target was presented. The avoidant task was to press the button on the opposite side.\u003c/p\u003e\n\u003cp\u003eBefore beginning the hit or avoidant task, each participant decided on the preferred hand to manipulate the response device. The HR monitor was attached to the contralateral wrist. Two disposable electrodes were placed on the surface of the dorsal skin above the third proximal and third intermediate phalanx bones of the contralateral hand. The shock intensity was calibrated for each participant to a level that was \u0026ldquo;quite unpleasant/uncomfortable but not painful,\u0026rdquo; following the established protocol (Schmitz \u0026amp; Grillon, 2012). The participants were informed that electric shocks might arrive during some of the trials within the threat blocks but never within the safe blocks.\u003c/p\u003e\n\u003cp\u003eWhile executing the task, the participants were restricted to using their index fingers alone to press the buttons. They were asked not to release the finger from the home button earlier than the appearance of the probe target and to press the correct response button as quickly and accurately as possible when the probe target was presented. The participants performed 40 practice trials without electric shocks, and then the test trials began. At the beginning of each block, a warning appeared on the display: \u0026ldquo;\u003cem\u003eYou are now safe from shock this next set of trials\u003c/em\u003e\u0026rdquo; in black letters on a blue background for the safe condition blocks and \u0026ldquo;\u003cem\u003eYou may receive an electric shock at some points during the next set of trials\u003c/em\u003e\u0026rdquo; in black letters on a red background for the threat condition blocks. A 3 min break was given between the blocks. Immediately after completing each block, the participants answered the VAS questionnaires about their moods during the block. The experiment took 60 min.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMeasurements and Statistical Analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eHR and VAS scores\u003c/em\u003e\u003cem\u003e.\u0026nbsp;\u003c/em\u003eThe raw time-sequence data of the HR records were averaged during each participant\u0026rsquo;s test block. Next, the average HR and raw VAS scores were averaged among the three test blocks in each of the safe and threat conditions. The participants\u0026rsquo; mean measurements were used to statistically test the effect of anxiety manipulation and the difference in induced anxiety levels between the two action goal groups. Anderson\u0026ndash;Darling tests revealed that deviations from the normal distribution were significant for some of these variables (\u003cem\u003ep\u003c/em\u003e \u0026lt; .05). For variables with a skewed distribution, Wilcoxon signed-rank tests and Wilcoxon rank-sum tests were used to evaluate the effect of anxiety manipulation and the difference between the action goals, respectively. We calculated \u003cem\u003er\u003c/em\u003e (\u003cem\u003eZ\u003c/em\u003e-score divided by the square root of the sample size) as a measure of effect size. For variables with normal distribution, paired \u003cem\u003et\u003c/em\u003e-tests and \u003cem\u003et\u003c/em\u003e-tests were performed to evaluate those effects, respectively. Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e was calculated as a measure of effect size.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eReaction Times.\u0026nbsp;\u003c/em\u003eTask performance was evaluated by measuring the release reaction time (RT), press RT, and total RT. The release RT was defined as the time between the presentation of the probe target and the release of the home button. The press RT was defined as the time between releasing the home button and pressing the right or left response button. The total RT was defined as the sum of the release RT and press RT per trial. Errors, such as pressing the wrong response button, were negligible (8 errors, 0.21% of all hit trials; 16 errors, 0.42% of all avoidant trials). Thus, these error responses were excluded from the full dataset, and the error rates were not statistically analyzed. Trials with release RTs \u0026lt; 100 ms or total RTs \u0026gt; 1,000 ms were eliminated from the analysis as outliers (2.6% of all hit trials and 6.7% of all avoidant trials in the full dataset).\u003c/p\u003e\n\u003cp\u003eAmong each participant dataset, the three RT measurements were averaged within the emotional cue condition (i.e., angry faces and happy faces), threat-of-shock condition (i.e., safe and threat), and spatial congruency condition (i.e., the locus of the angry/happy faces was spatially congruent or incongruent with the locus of the probe target). Then, the degree of attentional bias was assessed using the following equation:\u003c/p\u003e\n\u003cp\u003eRT difference [ms] = RT congruent \u0026ndash; RT incongruent\u003c/p\u003e\n\u003cp\u003eThe individuals\u0026rsquo; mean RT differences were used for statistical testing. Anderson\u0026ndash;Darling tests revealed that the deviations from the normal distribution were not significant (\u003cem\u003ep\u003c/em\u003e \u0026gt; .05). A three-way, mixed-design analysis of variance (ANOVA) with the emotional cue condition and threat-of-shock condition as the within-participant factors and the task group as the between-participant factor was performed for all the RT variables. If the three-way interaction term reached a significant level (\u003cem\u003ep\u003c/em\u003e \u0026lt; .05), two-way repeated measures ANOVA was performed separately for each of the task groups to estimate the effects of the emotional cue and threat-of-shock condition factors. If the two-way interactions of this ANOVA were significant, multiple comparison tests using paired \u003cem\u003et\u003c/em\u003e-tests with the Bonferroni correction were performed separately for each combination of interests between the levels of the factors. A Greenhouse\u0026ndash;Geisser correction was applied when sphericity was violated for the repeated measures. For all the ANOVA tests, the generalized eta squared (\u003cem\u003e\u0026eta;\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eG\u003c/sub\u003e) was calculated as a measure of effect size (Bakeman, 2005). For all multiple comparison tests, Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e was calculated as a measure of effect size.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eManipulation Checks\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere were no significant differences in HR and happiness VAS scores between the safe and threat conditions for either task group (\u003cem\u003ep\u003c/em\u003e \u0026gt; .05). Compared to the safe condition, the anxiety VAS scores increased under the threat condition for the hit group (\u003cem\u003eZ\u003c/em\u003e = 2.74, \u003cem\u003ep\u003c/em\u003e = .006, \u003cem\u003er\u003c/em\u003e = .69) and avoidant group (\u003cem\u003et\u003c/em\u003e(15) = 5.34, \u003cem\u003ep\u003c/em\u003e = .001, \u003cem\u003ed\u003c/em\u003e = 1.00). The fear VAS scores also increased under the threat condition for the hit group (\u003cem\u003et\u003c/em\u003e(15) = 3.79, \u003cem\u003ep\u003c/em\u003e = .002, \u003cem\u003ed\u003c/em\u003e = 2.28) and the avoidant group (\u003cem\u003eZ\u003c/em\u003e = 3.14, \u003cem\u003ep\u003c/em\u003e = .002, \u003cem\u003er\u003c/em\u003e = .78). There were no significant group differences in HR, anxiety scores, and fear scores (\u003cem\u003ep\u003c/em\u003e \u0026gt; .05). The happiness VAS scores of the avoidant group were significantly larger than those of the hit group (\u003cem\u003eZ\u003c/em\u003e = 2.36, \u003cem\u003ep\u003c/em\u003e = .018, \u003cem\u003er\u003c/em\u003e = .42). These results confirm that by providing a very few electric shocks during the task trials, the threat manipulation protocol induced anxiety in the participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTask Performance\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA mixed-design ANOVA test demonstrated a significant three-way interaction effect in the press RT (\u003cem\u003eF\u003c/em\u003e(1,30) = 6.00, \u003cem\u003ep\u003c/em\u003e = .02, \u003cem\u003e\u0026eta;\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eG\u003c/sub\u003e = 0.03) and total RT (\u003cem\u003eF\u003c/em\u003e(1,30) = 6.16, \u003cem\u003ep\u003c/em\u003e = .019, \u003cem\u003e\u0026eta;\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eG\u003c/sub\u003e = 0.05). However, the three-way interaction effect in the release RT did not reach a significant level (\u003cem\u003eF\u003c/em\u003e(1,30) = 0.15, \u003cem\u003ep\u003c/em\u003e = .705, \u003cem\u003e\u0026eta;\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eG\u003c/sub\u003e = 0.00).\u003c/p\u003e\n\u003cp\u003e[Insert Figure 2 about here.]\u003c/p\u003e\n\u003cp\u003eFigure 2 shows the group means and standard errors (SEs) of the RT difference as a function of the emotional cue condition under each of the threat-of-shock levels for the hit group. For the release RT and press RT, the effects of the emotional cue, threat-of-shock, and interaction factors did not reach a significant level (\u003cem\u003ep\u003c/em\u003e \u0026gt; .05). However, the emotional cue had a significant effect on the total RT (\u003cem\u003eF\u003c/em\u003e(1,15) = 4.77, \u003cem\u003ep\u003c/em\u003e = .045, \u003cem\u003e\u0026eta;\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eG\u003c/sub\u003e = 0.09), whereas the effects of threat-of-shock and interaction factors were not significant (\u003cem\u003ep\u003c/em\u003e \u0026gt; .05). The negative cues (angry faces) significantly decreased the mean of total RT compared to the positive cues (happy faces) (\u0026nbsp;\u0026nbsp;= -6.8, \u003cem\u003eSE\u003c/em\u003e = 3.1, 95% CI [-13.5, -0.2]). In sum, Hypothesis 1 was not supported for the hit action mode.\u003c/p\u003e\n\u003cp\u003e[Insert Figure 3 about here.]\u003c/p\u003e\n\u003cp\u003eFigure 3 shows the group means and SEs of the RT difference for the avoidant group. The effects of the emotional cue, threat-of-shock, and interaction factors on the release RT were not significant (\u003cem\u003ep\u003c/em\u003e \u0026gt; .05). On the press RT, the two-way interaction effect was significant (\u003cem\u003eF\u003c/em\u003e(1,15) = 6.26, \u003cem\u003ep\u003c/em\u003e = .024, \u003cem\u003e\u0026eta;\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eG\u003c/sub\u003e = 0.07), whereas the effects of the emotional cue and threat-of-shock factors were not significant (\u003cem\u003ep\u003c/em\u003e \u0026gt; .05). There was a significant difference between the negative/angry and positive/happy emotional cues under the threat condition (\u003cem\u003et\u003c/em\u003e(15) = 3.11, \u003cem\u003ep\u003c/em\u003e = .007, \u003cem\u003ed\u003c/em\u003e = 0.91,\u0026nbsp;\u0026nbsp;\u0026nbsp;= 15.4, \u003cem\u003eSE\u003c/em\u003e = 4.9, 95% CI [4.8, 25.9]). The safe condition did not show a significant difference between the negative/angry and positive/happy emotional cues (\u003cem\u003ep\u003c/em\u003e \u0026gt; .05). For each of the negative/angry and positive/happy emotional cues, no significant differences were found between the safe and threat conditions (\u003cem\u003ep\u003c/em\u003e \u0026gt; .05). On the total RT, there was a significant effect of the emotional cue factor (\u003cem\u003eF\u003c/em\u003e(1,15) = 5.00, \u003cem\u003ep\u003c/em\u003e = .042, \u003cem\u003e\u0026eta;\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eG\u003c/sub\u003e = 0.07) and a significant effect of the interaction (\u003cem\u003eF\u003c/em\u003e(1,15) = 13.20, \u003cem\u003ep\u003c/em\u003e = .002, \u003cem\u003e\u0026eta;\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eG\u003c/sub\u003e = 0.16). The effect of the threat-of-shock factor did not reach significance (\u003cem\u003ep\u003c/em\u003e \u0026gt; .05). For the positive/happy emotional cue, the threat condition significantly decreased the mean of the RT difference against the safe condition (\u003cem\u003et\u003c/em\u003e(15) = 2.63, \u003cem\u003ep\u003c/em\u003e = .019, \u003cem\u003ed\u003c/em\u003e = 0.80,\u0026nbsp;\u0026nbsp;\u0026nbsp;= -12.3, \u003cem\u003eSE\u003c/em\u003e = 4.7, 95% CI [-22.3, -2.3]). In contrast, for the negative/angry emotional cue, the threat condition significantly increased the mean of the RT difference against the safe condition (\u003cem\u003et\u003c/em\u003e(15) = 2.76, \u003cem\u003ep\u003c/em\u003e = .015, \u003cem\u003ed\u003c/em\u003e = 0.80,\u0026nbsp;\u0026nbsp;\u0026nbsp;= 11.0, \u003cem\u003eSE\u003c/em\u003e = 4.0, 95% CI [2.5, 19.5]). There was a significant difference between the positive and negative emotional cues under the threat condition (\u003cem\u003et\u003c/em\u003e(15) = 3.98, \u003cem\u003ep\u003c/em\u003e = .001, \u003cem\u003ed\u003c/em\u003e = 1.28,\u0026nbsp;\u0026nbsp;\u0026nbsp;= 19.0, \u003cem\u003eSE\u003c/em\u003e = 4.8, 95% CI [8.8, 29.2]), whereas no significant difference was found under the safe condition (\u003cem\u003ep\u003c/em\u003e \u0026gt; .05). In sum, Hypothesis 1 was supported for the avoidance action mode. Thus, Hypothesis 2 was supported.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo the best of our knowledge, this was the first attempt to investigate how the alteration of action goals interacts with state anxiety, affecting attentional bias toward threat stimuli in healthy individuals. The\u0026nbsp;present study revealed that during elevated anxiety levels, the difference in behavioral goals of fight or flight, represented by hit or avoidance actions, induces the different characteristics of attentional bias toward threat stimuli.\u003c/p\u003e\n\u003cp\u003eSpecifically, the hit action mode enhanced faster responses to the probe target that appeared in the same location as the angry faces (hereafter, threat-congruent trials) than in the opposite location (hereafter, threat-incongruent trials). This faster response in the threat-congruent trials was independent of the anxiety level. In contrast, when the participants were required to avoid the probe target (i.e., to choose the space opposite to where the probe target was presented), their motor responses were delayed in the threat-congruent trials. Interestingly, the avoidance action mode enhanced faster responses to the probe target that appeared in the same location as the happy faces (hereafter, safe-congruent trials) than in the opposite location (hereafter, safe-incongruent trials). These tendencies were elicited depending on the anxiety level.\u003c/p\u003e\n\u003cp\u003eThe conventional visual-probe task assumes that the faster response to probes in the threat-congruent trials reflects an attentional bias toward threat-related stimuli (Grafton et al., 2012). It is noteworthy that most other studies used the hit mode. An attentional bias toward threat cues occurs not only in anxious adults (Bar-Haim et al., 2007) but also in healthy adults (Holmes et al., 2009) at shorter stimulus durations (\u0026le; 500 ms). In contrast, the attentional bias effect observed at longer stimulus durations (\u0026gt; 500 ms) is still a subject of debate. In the present experiment using an interstimulus duration of 350 ms, the release RT did not reflect a faster (or delayed) response enhanced by the presence of negative emotional stimuli. Theoretically, the release RT measures efficiency in detecting the probe target. When considered together with this methodological basis, the present results suggest that attentional bias toward threat-related stimuli may play an important role in processing the selection and execution of rapid motor response rather than in stimulus detection processing. Notably, such quick motor responses to threats, which appear to be underpinned by an automatic attentional bias, were elicited independently of state anxiety in the hit action mode. In other words, the fight action goal seems to have the effect of increasing reactivity to threat stimuli through the biased attention regardless of anxiety level.\u003c/p\u003e\n\u003cp\u003eRegarding the direction of attentional bias, there are two possible accounts for the results of the avoidance mode. The characteristics of attentional bias in highly anxious individuals can be classified into three observable components: facilitated attentional engagement, disengagement difficulty, and attention avoidance (Cisler \u0026amp; Koster, 2010; Fox et al., 2001, 2002; Koster et al., 2004). If the tendencies of attention avoidance from threats predominated, the general shortening of the RT would occur in threat-incongruent trials. However, attention avoidance has not been reported at shorter stimulus durations (\u0026le; 500 ms) (see Mogg \u0026amp; Bradley, 2016 for a review). Thus, the involvement of attention avoidance is also unlikely to occur in the present experiment.\u003c/p\u003e\n\u003cp\u003eAt the same time, findings from conventional visual-probe tasks have been explained in terms of either facilitated attentional engagement with threat or difficulty in disengaging from threat in anxious individuals (Clarke et al., 2013). If attention is unconsciously engaged with threat-related stimuli prior to the presentation of the probe, this will result in shorter latencies to identify the probe in its vicinity. The release RT showed that the latency to detect the probe was not associated with the threat-congruency and state anxiety levels for either mode of action. It is possible that the participants initially engaged their attention equally with either the threatening or neutral stimuli. This raises the possibility that the attentional bias tendencies observed in the present study could be explained by disengagement difficulty, which results in slowing down to reorient attention away from threatening stimuli once they have been identified rather than facilitating attentional engagement with threatening stimuli (Fox et al., 2001). If this were the case, when attention tends to remain in the vicinity of threatening stimuli, the tendency of disengagement difficulty increased by anxiety would lead to longer latencies in the avoidance action mode in threat-congruent trials. Therefore, the disengagement difficulty hypothesis is a plausible explanation for the present results.\u003c/p\u003e\n\u003cp\u003eThe avoidance action mode revealed another unique phenomenon. Enhanced faster responses to the probe were found in the safe-congruent trials as compared to the safe-incongruent trials. In general,\u0026nbsp;organisms are endowed with mechanisms that automatically regulate approach behavior toward positive objects and avoid negative objects (e.g., Kielmeyer et al., 2010, 2011). The results of the avoidance action mode are inconsistent with what this innate approach\u0026ndash;avoidance control\u0026nbsp;mechanism predicts. One possible explanation for this result is that\u0026nbsp;anxiety can also lead to threat-related interpretations (Bishop, 2007; Blanchette \u0026amp; Richards, 2010). This means that despite visual attention to task-relevant information, this information may be perceived differently or misinterpreted depending on one\u0026rsquo;s current emotions or state (Nieuwenhuys \u0026amp; Oudejans, 2012). To the extent that threat-of-shock led the participants to interpret neutral faces as being more threatening than happy faces, the disengagement difficulty function would work to slow down the redirection of attention away from the neutral stimuli. This might result in the faster responses to the probe in the safe-congruent trials. In any case, this appears to be a specific phenomenon induced by the avoidance action mode.\u003c/p\u003e\n\u003cp\u003eIn conclusion, behavioral goals such as fight or flight, represented by hitting and avoiding a target, were found to interact with state anxiety, leading to different degrees of attentional bias. Avoidance behavioral goals may function to strengthen the link between attentional bias (in this case disengagement difficulty) and anxiety. Furthermore, they\u0026nbsp;may induce a tendency to interpret\u0026nbsp;stimuli with lower threatening valence\u0026nbsp;as threatening. Therefore, it is safe to assume that treatments or instructions that encourage the avoidance of threatening stimuli as an action mode are not effective in reducing state anxiety, at least for healthy individuals. The ironic process theory of mental control predicts that intentional control of actions to avoid unwanted goals will produce counter-intentional errors (Wegner et al., 1998). This seems to be another possible explanatory theory for our result.\u003c/p\u003e\n\u003cp\u003eIn discussing the mechanisms underlying the present findings, three limitations arise, particularly regarding the research methodology. First, this study employed visual-probe tasks; therefore, we cannot fully dissociate the disengagement difficulty component from the facilitated attentional engagement component in anxiety, as reported by Clarke et al. (2013). To elucidate this point, we attempted to measure the latency to detect the presence of the probe stimulus and the latency to choose the response direction separately. This separation evidenced the possibility that disengagement difficulty is involved in threat stimulus-driven process of attentional control for healthy individuals as well. Second, the threat-of-shock protocol in the present study did not induce a high enough level of state anxiety to significantly increase HR, although it did increase the levels of subjective state anxiety. The results showing higher levels of state anxiety to the extent that it manifests itself in physiological responses could aid in elucidating the background mechanism that may explain the present findings. Third, we did not test the effect of the alteration of action goals on biased attention using a within-participants design. In this study, a group comparison design was adopted because the frequent repetition of electric shocks may allow each participant to become accustomed to the stimulus intensity and consequently reduce state anxiety levels. Therefore, future research should focus on developing methods that can consistently induce high state anxiety levels in healthy individuals to advance our understanding in this area.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eMost other studies have employed the hit action mode as a response to a probe stimulus to investigate attentional bias toward threat-related stimuli. We have adopted a different strategy to determine whether the alteration of action goals affects the degree of attentional bias. The present approach provided the first evidence to suggest that the voluntary control process of avoidance behaviors may function to strengthen the link between attentional bias and anxiety. The present findings put forward the hypothesis that when anxiety increases, deliberate efforts to avoid threatening stimuli may actually worsen perceptual and motor performance.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by a Grant-in-Aid for Young Scientists from JSPS (Grant No. 20K19607) awarded to NS and a Grant-in-Aid for Scientific Research (C) from JSPS (Grant No. 22K11631) awarded to HT.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of conflicting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that no conflicts of interest exist.\u003c/p\u003e"},{"header":"References","content":"\u003cp\u003eAnderson, A. K., \u0026amp; Phelps, E. A. (2001). 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The detrimental effects of anxiety on perceptual and motor performance may result in part from this automatic mechanism in which attention is predominantly biased toward threat stimuli, that is, attentional bias. Understanding the relationship between attentional bias and motor control systems is expected to aid in the development of methods to cope with anxiety in athletic situations. With this in mind, the present study investigated how the difference in behavioral goals affects attentional control against threat-related stimuli during induced anxiety. Participants performed a visual probe task, with half responding to the probe target in hit mode and half in avoidance mode. Anxiety levels were manipulated using a threat-of-shock method. Threatening conditions increased the degree of attentional bias toward negative information compared to safe conditions for the avoidance action goal but had no effect on the hit action goal. The differences in fight-or-flight behavioral goals, represented by hit or avoidant actions, were found to interact with state anxiety, resulting in the different degrees of attentional bias toward threat stimuli. Avoidance behavior may strengthen the relationship between attentional bias and anxiety. These findings suggest a hypothesis that when anxiety increases, deliberate efforts to avoid threatening stimuli would rather worsen perceptual and motor performance.\u003c/p\u003e","manuscriptTitle":"Fight, Not Flight! Avoidant Behavior Strengthens Attentional Shift Toward Threat Stimuli During Anxiety","msid":"","msnumber":"","nonDraftVersions":[{"code":2,"date":"2024-01-03 23:00:08","doi":"10.21203/rs.3.rs-3123023/v2","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}},{"code":1,"date":"2023-07-05 14:45:03","doi":"10.21203/rs.3.rs-3123023/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0859eaae-fc04-4239-a48f-49264b45e5bb","owner":[],"postedDate":"January 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":27873090,"name":"Psychology"}],"tags":[],"updatedAt":"2024-12-19T14:48:40+00:00","versionOfRecord":{"articleIdentity":"rs-3123023","link":"https://doi.org/10.3390/psychiatryint5040068","journal":{"identity":"psychiatry-international","isVorOnly":true,"title":"Psychiatry International"},"publishedOn":"2024-12-13 00:00:00","publishedOnDateReadable":"December 13th, 2024"},"versionCreatedAt":"2024-01-03 23:00:08","video":"","vorDoi":"10.3390/psychiatryint5040068","vorDoiUrl":"https://doi.org/10.3390/psychiatryint5040068","workflowStages":[]},"version":"v2","identity":"rs-3123023","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3123023","identity":"rs-3123023","version":["v2"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}