The current investigation examined the effects of a differential attentional training task on subsequent emotional reactivity in response to a task that was aimed to either induce positive or negative affectivity. Specifically, the study employed a dot-probe attentional training paradigm to train attention toward positive images (Attend-Positive condition), toward neutral images (Attend-Neutral condition), or to not train attention at all (Control condition). The hypothesis was that individuals whose attention was trained toward positive images would exhibit faster response times toward positive images (compared to the Attend-Neutral and Control conditions) at post assessment, individuals whose attention was trained toward neutral images would exhibit faster response times toward neutral images (compared to the Attend-Positive and Control conditions) at post assessment, and individuals in the Control condition would maintain similar response times from baseline to post assessment, aside from general practice effects. It was also hypothesized that those in the Attend-Positive condition would better regulate emotion, as measured by less negative affect in response to a stress task and more positive affect in response to a positive mood induction task, compared to individuals who have engaged in a control task involving no attentional bias training (Control condition). It was also hypothesized that those in the Attend-Neutral condition would better regulate emotion, as measured by less negative affect in response to a stress task and more positive affect in response to a positive mood induction task, compared to individuals who have engaged in a control task involving no attentional bias training (Control condition). Last, it was hypothesized that individuals in the Attend-Positive condition would report differentially less negative affect in response to the stress task (failure anagrams) than those in the Attend-Neutral condition, and that individuals in the Attend-Positive condition would report differentially more positive affect in response to the positive mood induction task (success anagrams) than those in the Attend-Neutral condition. In all conditions, the dot-probe attentional training did not effectively modify biases in the hypothesized directions. While there was differential affectivity change for individuals who underwent a Failure Anagram task versus a Success Anagram task, there is no way to definitively interpret the meaning of these changes given the failure of the attentional manipulation. The findings from the current investigation provide no evidence for single-session dot-probe attentional bias modification procedures to manipulate attentional bias toward positive stimuli or toward neutral stimuli. Possible explanations for these results, including lack of reliability of the dot-probe task, are discussed.

Attentional bias is commonly associated with emotional disorders. However, potential transdiagnostic mediators of attentional bias, such as repetitive negative thinking (RNT) have been overlooked. The current study examined attentional biases associated with three forms of RNT and tested a proposed mediation model. Participants (N = 249) completed self-report measures, a repetitive thought induction, and an emotional face dot-probe measure of attentional bias. I hypothesized that RNT would be associated with attentional bias to angry, sad, and disgust faces, worry with angry faces, and rumination with sad faces after a negative thought induction. I also hypothesized that attentional bias scores would mediate the association between negative affect and RNT. Overall study hypotheses were not supported. Clinical worry was associated with slower reaction times to sad faces in the negative induction. RNT, worry, and rumination were not associated with attentional bias scores to emotional faces, and the mediation model was not supported.

An attentional bias to threatening stimuli is associated with greater anxiety in children (see Puliafico & Kendall, 2006 for a full review). Attentional control is one factor that may influence the relationship between attentional bias and anxiety in children (Susa, Pitică, Benga, & Miclea, 2012). This current study focused on further exploring the relationship between attentional bias, attentional control, and anxiety. Participants (N = 46) completed a self-report measure of attentional control and anxiety, and an attentional bias task (i.e., the Emotional Go/No-Go). Two models were examined. First, attentional control was examined as a potential moderator in the relationship between attentional bias and anxiety. Second, attentional bias was examined as a potential mediator of the relationship between attentional control and anxiety. The moderation model was significant. However, the findings were not consistent with the literature, as results indicated attentional bias was associated with anxiety only for children with higher attentional control abilities. The moderation model was further examined with different dimensions of anxiety and attentional control. The mediation model was not significant. Explanation of the findings and future directions are discussed.

The primary aim of this thesis was to investigate the relationship between rumination and selective attention, in particular, whether the tendency to ruminate is associated with impaired attentional disengagement from negative information. It is well-established that the tendency to ruminate in response to negative mood is a key vulnerability factor in the development of depression (Nolen-Hoekseman, Wisco, & Lyubomirsky, 2008; Watkins, 2008), but attempts to understand the underlying processes contributing to heightened ruminative disposition have been relatively limited. Recently, a number of researchers have suggested that rumination may be characterised by biased attentional processing of negative information, particularly that individuals with high levels of ruminative disposition may have difficulty disengaging their attention from negative information (e.g., Koster, De Lissnyder, Derakshan, & De Raedt, 2011). Studies One and Two each investigated the relationship between individual differences in ruminative disposition and selective attention for negative information, using a modified dot-probe task designed by Grafton, Watkins, and MacLeod (2012) to enable the discrete assessment of biases in attentional engagement and disengagement. Study One found that heightened levels of dispositional ruminative brooding, as assessed by both the Ruminative Responses Scale (RRS; Nolen-Hoeksema & Morrow, 1991) and an in-vivo assessment of ruminative disposition, were associated with impaired attentional disengagement from negative relative to positive information. Similarly, Study Two also found that heightened levels of ruminative disposition were associated with impaired attentional disengagement from negative information, particularly for depression relevant stimuli presented for 1000ms. Study Three sought to extend these findings using an eye-tracking assessment of selective attention to measure the spontaneous allocation of attention between stimuli. However, ruminative disposition was not significantly associated with any index of attentional bias during the eye-tracking assessment, neither with biased attentional disengagement, nor with biased attentional engagement or maintenance of attention. Study Four then sought to replicate findings from Study Two using a selected sample of individuals with high and low levels of ruminative disposition. Participants in the high rumination group demonstrated greater attentional bias for depression relevant negative stimuli presented for 1000ms in comparison to those in the low rumination group. However, this between group difference reflected a general attentional preference for negative relative to positive stimuli (i.e., composite of attentional engagement and disengagement bias), but no specific difference in attentional disengagement bias or attentional engagement bias was observed. Finally, Study Five took a first step towards investigate the causal relationship between rumination and selective attention by investigating the causal effect of rumination on attentional bias. Although there no main effect of induced rumination on attentional bias was observed, the effect of induced rumination on attentional bias was found to be moderated by ruminative disposition. However, contrary to hypotheses, individuals with low levels of ruminative disposition demonstrated an attentional bias for valence-incongruent stimuli, which shifted to a bias for valence-congruent stimuli as ruminative disposition increased. Overall, there was support across the studies for the primary hypothesis that heightened ruminative disposition is associated with impaired attentional disengagement from negative information. However, the findings do not suggest that ruminative disposition is exclusively associated with attentional disengagement bias, but instead indicate that facilitated attentional engagement may also be involved under some circumstances.

Background: Attention and vigilance is highlighted as an adaptive function which facilitates a faster response to threat. It is also proposed as a maintenance factor in problems with anxiety, and more recently within physical health conditions. Researchers have hypothesised that due to the role of attention in anxiety, modifying this attention will result in a reduction of anxiety levels. In addition, research is now emerging in relation to the role of attention in paediatric health conditions. Due to the importance of early targeting in interventions for both anxiety and physical health conditions, further research is needed in this area. Aims: The research aims were twofold. The first aim was to review the literature and evidence related to the anxiolytic effect of Attention Bias Modification (ABM) in child and adolescent populations. The second aim was to investigate if children with asthma show an attentional bias to different threat related stimuli (asthma, anxiety or general negative emotion) and the relationship between this and other health related factors. Method: A systematic review of the current literature was carried out to address the first aim. This included 10 quantitative studies which all examined the effect of ABM on either child or adolescent anxiety levels. To address the second aim, 36 children aged nine to twelve participated in an empirical study. 18 of the participants had asthma, and 18 were asthma free and both groups were asked to complete a computer task designed to measure attentional bias to the different threat related stimuli. In addition, caregivers completed a questionnaire to measure their own anxiety levels, and the children with asthma completed measures focused on quality of life, coping strategies and inhaler use. Results: Research regarding the effectiveness of ABM for youth anxiety is in its early stages. However, preliminary conclusions can be drawn suggesting that it may be an effective intervention to reduce anxiety levels. Additional, rigorous research is required to standardise treatment protocols and answer further questions. Within the empirical study, repeated measures ANOVA revealed that children with asthma show an attentional bias to asthma cues whereas children without asthma do not. Furthermore, there was no selective attention to general negative words, suggesting that attentional bias was not due to general sensitivity to emotional stimuli. A Pearson’s correlation showed that vigilance to asthma cues was associated with parental anxiety. There was no attentional bias to anxiety symptom words and no significant correlations between bias scores and the measured health related factors. Conclusion: The results from the systematic review provide further evidence for the role of attention in paediatric anxiety problems. In addition, the outcome of the empirical study suggests an unconscious threat association in childhood asthma. Further research may yield a viable computerised treatment for paediatric anxiety. Regardless of this, it will be important to consider the role of attention in clinical practice, both in the treatment of anxiety and complex chronic health problems such as asthma.

Indiana University-Purdue University Indianapolis (IUPUI) / Depression is an emerging risk factor for obesity; however, it is unclear whether certain depressive symptoms drive this relationship. Recent evidence suggests that atypical major depressive disorder (MDD) – whose key features include the reversed somatic-vegetative symptoms of hyperphagia (increased appetite) and hypersomnia (increased sleep) – is a stronger predictor of future obesity than other MDD subtypes. The present study sought to examine food attentional bias (increased attention to food cues), emotional eating (eating in response to negative emotions), and external eating (eating in response to external food cues) as candidate mechanisms of the depression-to-obesity relationship. This cross-sectional laboratory study hypothesized that total depressive symptom severity, hyperphagia severity, and hypersomnia severity would all be positively associated with measures of food attentional bias, emotional eating, and external eating. Data were collected from a sample of 95 undergraduate students. Depressive symptom severity was measured using the Hopkins Symptom Checklist (SCL-20); two measures of food attentional bias were obtained from eye tracking with high calorie food images: direction bias and duration bias; and emotional eating and external eating were assessed using the Dutch Eating Behavior Questionnaire. Simultaneous regression models (adjusted for age, sex, race/ethnicity, body mass index, and subjective hunger) revealed total depressive symptom severity and hypersomnia severity were not associated with measures of food attentional bias, while hyperphagia severity was negatively associated with direction bias but not associated with duration bias for high and low calorie food images. Findings related to emotional and external eating are consistent with previous literature: total depressive symptom severity and hyperphagia severity were positively associated with both emotional eating and external eating, and the pattern of results suggests that hyperphagia may be driving relationships between depressive symptoms and these eating behaviors. Hypersomnia severity was not associated with emotional eating and external eating, suggesting this symptom does not play an important role in the relationships between depressive symptoms and these eating behaviors. Future studies should examine prospective associations of hyperphagia severity with food attentional bias, emotional eating, and external eating in larger, more representative samples.

Attentional control and attentional bias are important factors that contribute to the development and maintenance of anxiety disorders (Eysenck, Derakshan, Santos, & Calvo, 2007; Van Bockstaele et al., 2014). However, the effects of attentional control and attentional bias on the relationship between anxiety and stress response is understudied. Further, much of the research to date has relied on self-report measures of attentional control and stress response, representing a significant limitation. The current study addressed these problems and examined the relationship between attentional control, attentional bias, anxiety, and stress response. First, this study examined the relationship between self-report and performance-based measures of attentional control and stress response with anxiety. Study results found poor agreement between attentional control measures, good convergence between self-reported distress and physiological distress, and a negative association between anxiety and self-reported attentional control and stress response. Second, results showed that attentional control and attentional bias were not significant moderators of the relationship between anxiety and stress response. Explanation of study findings and future directions are discussed.

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Older adults have been reported to show attentional preference for positive stimuli and attentional avoidance from negative stimuli. The relationship between this pattern of emotional attention and emotion regulation, however, is not well known. The present study aims to replicate the findings of age-related attentional bias for emotional stimuli and investigate the potential relationship between biased attention and emotion regulation/dysregulation in Chinese older adults. 46 older adults and 46 younger adults participated in an attention task, which measured their reaction time towards negative and neutral facial stimuli, and a questionnaire survey, which elicited self-reports of their levels of emotion regulation and dysregulation. Results showed that there was a biased attention for negative faces in older adults, but not in younger adults. There were also differences between emotion regulation/dysregulation measures in the two age groups. When associating the attentional bias score with the emotion dysregulation measures, significant correlations were found between biased attention and overall difficulty in emotion regulation and lack of emotional clarity. The data supported the age-related bias of emotional attention, and revealed potential relationship between biased attention and emotion regulation in older adults. / published_or_final_version / Clinical Psychology / Master / Master of Social Sciences

There are at least two types of response to stimuli: an automatic response that happens before conscious thought (a Type 1 response) and a deliberative, intentional response (a Type 2 response). These responses are related to behavior associated with the affective loading of the stimulus presented. Prior research has shown, for example, that a Type 1 tendency to spend more time looking at fear-provoking stimuli is associated with higher levels of general anxiety, while a Type 2 tendency to spend more time looking away from happy faces is associated with higher levels of depressive symptoms. Some stimuli categories elicit mixed responses, indicated by discrepant Type 1 and Type 2 responses. For example, alcoholics in recovery tend to look toward alcohol-themed pictures in the first 200 milliseconds, then look away. This suggests that alcoholics in recovery have an automatic draw to alcohol that is overridden by the conscious application of a cognitive schema to avoid alcohol. Sexual response studies to date have measured Type 1 and Type 2 responses separately; however, no study has yet measured both types of response within the same person. This study was the first to examine both Type 1 and Type 2 responses to erotic stimuli within the same individual as a test of within-individual variation of attentional responses to sexual stimuli. Results do not support a connection between either attentional bias or conflicting Type 1 and Type 2 responses and sexual desire or distress. Implications of these non-findings are discussed in theoretical and methodological contexts, and future research is suggested.