Inhibitory attentional control in anxiety: Manipulating cognitive load in an antisaccade task

Theorists have proposed that heightened anxiety vulnerability is characterised by reduced attentional control performance and have made the prediction in turn that elevating cognitive load will adversely impact attentional control performance for high anxious individuals to a greater degree than low anxious individuals. Critically however, existing attempts to test this prediction have been limited in their methodology and have presented inconsistent findings. Using a methodology capable of overcoming the limitations of previous research, the present study sought to investigate the effect of manipulating cognitive load on inhibitory attentional control performance of high anxious and low anxious individuals. High and low trait anxious participants completed an antisaccade task, requiring the execution of prosaccades towards, or antisaccades away from, emotionally toned stimuli while eye movements were recorded. Participants completed the antisaccade task under conditions that concurrently imposed a lesser cognitive load, or greater cognitive load. Analysis of participants’ saccade latencies revealed high trait anxious participants demonstrated generally poorer inhibitory attentional control performance as compared to low trait anxious participants. Furthermore, conditions imposing greater cognitive load, as compared to lesser cognitive load, resulted in enhanced inhibitory attentional control performance across participants generally. Crucially however, analyses did not reveal an effect of cognitive load condition on anxiety-linked differences in inhibitory attentional control performance, indicating that elevating cognitive load did not adversely impact attentional control performance for high anxious individuals to a greater degree than low anxious individuals. Hence, the present findings are inconsistent with predictions made by some theorists and are in contrast to the findings of earlier investigations. These findings further highlight the need for research into the relationship between anxiety, attentional control, and cognitive load

Psychological intervention in individuals with subthreshold depression:individual participant data meta-analysis of treatment effects and moderators

Background It remains unclear which individuals with subthreshold depression benefit most from psychological intervention, and what long-term effects this has on symptom deterioration, response and remission. Aims To synthesise psychological intervention benefits in adults with subthreshold depression up to 2 years, and explore participant-level effect-modifiers. Method Randomised trials comparing psychological intervention with inactive control were identified via systematic search. Authors were contacted to obtain individual participant data (IPD), analysed using Bayesian one-stage meta-analysis. Treatment-covariate interactions were added to examine moderators. Hierarchical-additive models were used to explore treatment benefits conditional on baseline Patient Health Questionnaire 9 (PHQ-9) values. Results IPD of 10 671 individuals (50 studies) could be included. We found significant effects on depressive symptom severity up to 12 months (standardised mean-difference [s.m.d.] = -0.48 to -0.27). Effects could not be ascertained up to 24 months (s.m.d. = -0.18). Similar findings emerged for 50% symptom reduction (relative risk = 1.27-2.79), reliable improvement (relative risk = 1.38-3.17), deterioration (relative risk = 0.67-0.54) and close-to-symptom-free status (relative risk = 1.41-2.80). Among participant-level moderators, only initial depression and anxiety severity were highly credible (P &gt; 0.99). Predicted treatment benefits decreased with lower symptom severity but remained minimally important even for very mild symptoms (s.m.d. = -0.33 for PHQ-9 = 5). Conclusions Psychological intervention reduces the symptom burden in individuals with subthreshold depression up to 1 year, and protects against symptom deterioration. Benefits up to 2 years are less certain. We find strong support for intervention in subthreshold depression, particularly with PHQ-9 scores ≥ 10. For very mild symptoms, scalable treatments could be an attractive option.</p

Attentional biases to signals of negative information: Reliable measurement across three anxiety domains.

Cognitive models propose that individuals with elevated vulnerability to experiencing negative emotion are characterised by biased attentional responding to negative information. Typically, methods of examining these biases have measured attention to pictures of emotional scenes, emotional faces, or rewarding or feared objects. Though these approaches have repeatedly yielded evidence of anxiety-linked biases, their measurement reliability is suggested to be poor. Recent research has shown that attentional responding to cues signalling negative information can be measured with greater reliability. However, whether such biases are associated with emotion vulnerability remains to be demonstrated. The present study conducted three experiments that recruited participants who varied in trait and state anxiety (N = 134), social anxiety (N = 122), or spider fear (N = 131) to complete an assessment of selective attention to cues signalling emotionally congruent negative information. Analyses demonstrated that anxiety and fear were associated with biased attentional responding to cues signalling negative information, and that such biases could be measured with acceptable reliability (rsplit-half = .69-.81). Implications for research on the relation between emotion and attention are discussed

Reliability and convergence of approach/avoidance bias assessment tasks in the food consumption domain

Theories of motivation posit that people will more readily approach positive or appetitive stimuli, and there has been growing interest in the relationship between biases in approach and avoidance behaviours for food cues and food craving and consumption behaviour. Two paradigms commonly employed by research to investigate this relationship are the approach-avoidance task (AAT) and the stimulus-response compatibility task (SRCT). However, it is yet to be determined whether the measures yielded by these tasks reflect the same processes operating in the food craving and consumption domain. The present study examined the internal reliability and convergence of AAT and SRCT paradigms in their assessment of biased approach to unhealthy compared with healthy food stimuli, and whether the measures yielded by the AAT and SRCT paradigms demonstrated associations with individual differences in food craving and eating behaviour. One hundred twenty-one participants completed an SRCT, an AAT using an arm movement response mode, and an AAT using a key-press response mode. The measures yielded comparable and acceptable levels of internal consistency, but convergence between the different task bias scores was modest or absent, and only approach bias as measured with the AAT task using an arm movement response mode was associated with self-report measures of eating behaviour and trait food craving. Thus, tasks did not converge strongly enough to be considered equivalent measures of approach/avoidance biases, and the AAT task using an arm movement response seems uniquely suited to detect approach biases argued to characterise maladaptive eating behaviour and craving.</p

Attentional control predicts change in bias in response to attentional bias modification

© 2017 Elsevier Ltd Procedures that effectively modify attentional bias to negative information have been examined for their potential to be a source of therapeutic change in emotional vulnerability. However, the degree to which these procedures modify attentional bias is subject to individual differences. This generates the need to understand the mechanisms that influence attentional bias change across individuals. The present study investigated the association between individual differences in attentional control and individual differences in the magnitude of bias change evoked by an attentional bias modification procedure. The findings demonstrate that individual differences in two facets of attentional control, control of attentional inhibition and control of attentional selectivity, were positively associated with individual differences in the magnitude of attentional bias change. The present findings inform upon the cognitive mechanisms underpinning change in attentional bias, and identify a target cognitive process for research seeking to enhance the therapeutic effectiveness of attentional bias modification procedures

Attentional bias mediates the effect of neurostimulation on emotional vulnerability

Transcranial direct current stimulation (tDCS) is a neuromodulatory technique which has garnered recent interest in the potential treatment for emotion-based psychopathology. While accumulating evidence suggests that tDCS may attenuate emotional vulnerability, critically, little is known about underlying mechanisms of this effect. The present study sought to clarify this by examining the possibility that tDCS may affect emotional vulnerability via its capacity to modulate attentional bias towards threatening information. Fifty healthy participants were randomly assigned to receive either anodal tDCS (2 mA/min) stimulation to the left dorsolateral prefrontal cortex (DLPFC), or sham. Participants were then eye tracked during a dual-video stressor task designed to elicit emotional reactivity, while providing a concurrent in-vivo measure of attentional bias. Greater attentional bias towards threatening information was associated with greater emotional reactivity to the stressor task. Furthermore, the active tDCS group showed reduced attentional bias to threat, compared to the sham group. Importantly, attentional bias was found to statistically mediate the effect of tDCS on emotional reactivity, while no direct effect of tDCS on emotional reactivity was observed. The findings are consistent with the notion that the effect of tDCS on emotional vulnerability may be mediated by changes in attentional bias, holding implications for the application of tDCS in emotion-based psychopathology. The findings also highlight the utility of in-vivo eye tracking measures in the examination of the mechanisms associated with DLPFC neuromodulation in emotional vulnerability

Author Correction: Social activity promotes resilience against loneliness in depressed individuals: a study over 14 days of physical isolation during the COVID-19 pandemic in Australia.

Correction to: Scientific Reports https://doi.org/10.1038/s41598-022-11315-4, published online 03 May 2022 The original version of this Article contained errors. In the original version of this Article, the p values in the Results section were swapped. “Results from the mixed-effects model showed a significant independent relationship between Loneliness and Social Activity Frequency with Close Contacts, b = − 0.385, p = 0.544, C.I.95% = [− 0.688; − 0.082], but not between Loneliness and Social Activity Frequency with either Intermediate Contacts, b = − 0.096, p = 0.086, C.I.95% = [− 0.408; 0.215], or with Distant Contacts, b = 0.263, p = 0.013, C.I.95% = [− 0.038; 0.564]. These results indicated that greater social interaction frequency with close contacts was associated with lower loneliness, but social interaction frequency with intermediate or distant contacts was not associated with lower loneliness.” now reads, “Results from the mixed-effects model showed a significant independent relationship between Loneliness and Social Activity Frequency with Close Contacts, b = − 0.385, p = 0.013, C.I.95% = [− 0.688; − 0.082], but not between Loneliness and Social Activity Frequency with either Intermediate Contacts, b = − 0.096, p = 0.544, C.I.95% = [− 0.408; 0.215], or with Distant Contacts, b = 0.263, p = 0.086, C.I.95% = [− 0.038; 0.564]. These results indicated that greater social interaction frequency with close contacts was associated with lower loneliness, but social interaction frequency with intermediate or distant contacts was not associated with lower loneliness.” In addition, the Data Availability section was omitted. It now reads, “Data availability The study’s Open Science Framework can be found at https://osf.io/yfz3n/.” The original Article has been corrected