Accentuate the positive: Evidence that context dependent self-reference drives self-bias.

There is abundant evidence of a self-bias in cognition, with prioritised processing of information that is self-relevant. There is also abundant evidence of a positivity-bias in cognition, with prioritised processing of information that is positively valenced (e.g., positive emotional expressions, rewards). While the effects of self-bias and positivity-bias have been well documented in isolation, they have seldom been examined in parallel, so it is unclear whether one or other of these stimulus classes is prioritised or whether they interact. Addressing this gap, the current research aimed to establish the relative primacy of self-bias and positivity-bias using a classification task that paired self-relevant information with emotional expressions (i.e., Expt. 1) or reward information (i.e., Expt. 2). When the self was paired with relatively more positive information (i.e., smiling faces or high reward) we found evidence of a self-bias but no evidence of a positivity-bias. Whereas when the self was paired with relatively less positive information (i.e., neutral faces or low reward) we found evidence of a positivity-bias but no evidence of a self-bias. These results suggest the relative primacy of prioritised processing is flexible, context dependent and might be caused by a drive towards self-enhancement and the self-positivity bias.

Depression screening using a non-verbal self-association task: A machine-learning based pilot study.

BACKGROUND: Effective screening is important to combat the raising burden of depression and opens a critical time window for early intervention. Clinical use of non-verbal depression screening is nascent, yet a promising and viable candidate to supplement verbal screening. Differential self- and emotion-processing in depression patients were previously reported by non-verbal behavioural assessments, corroborated by neuroimaging findings of distinct neuroanatomical markers. Thus non-verbal validated brain-behaviour based self-emotion-related assessment data reflect physiological differences and may support individual level screening of depression. METHODS: In this pilot study (n = 84) we collected two longitudinal sessions of behavioural assessment data in a laboratory setting. Depression was assessed using Beck Depression Inventory II (BDI-II), to explore optimal screening methods with machine-learning, and to establish the validity of adapting a novel behavioural assessment focusing on self and emotions for depression screening. RESULTS: The best machine-learning model achieved high performance in depression screening, 10-Fold cross-validation (CV) Area Under the receiver operating characteristic Curve (AUC) of 0.90 and balanced accuracy of 0.81, using a Gradient Boosting algorithm. Prospective prediction using a model trained with session 1 data to predict session 2 depression status achieved a 10-Fold CV AUC of 0.77 and balanced accuracy of 0.66. We also identified interpretable behavioural signatures for depression patients based on the best model. CONCLUSION: The study supports the utility of using behavioural data as a viable and cost-effective solution for depression screening, with a potential wide range of applications in clinical settings.

Perceiving the Self and Emotions with an Anxious Mind: Evidence from an Implicit Perceptual Task.

Anxiety disorders cause mental distress and low wellbeing in many people worldwide. Theories of anxiety describe negative worldviews and self-views as maintaining factors of the disorders. Recent research in social cognition has found a link between depression and altered perceptual biases to emotions, but the same research on anxiety is still missing. In this study, we measured perceptual biases to emotional and self-related stimuli in sub-clinically anxious participants and healthy controls using a self-emotional shape-label matching task. Results demonstrate that anxious participants had a diminished perceptual self-bias compared with healthy controls. Furthermore, the severity of anxiety was related to an emotional bias towards valanced other-related stimuli. The findings confirm the hypothesis that anxious individuals display an altered self-prioritisation effect in comparison with healthy individuals and that anxiety severity is linked to altered responses to emotionally valanced others. These findings have potential implications for early diagnosis and treatment of anxiety disorders.

A pre-existing self-referential anchor is not necessary for self-prioritisation.

Self-prioritisation effect (SPE) has consistently occurred in perceptual matching tasks in which neutral stimuli are paired with familiar labels representing different identities (e.g., triangle-Self, square-Friend). Participants are faster and more accurate at judging self-related shape-label pairings than the pairings associated with others. Much evidence has suggested that the SPE is driven by the self acting as an integrative hub that enhances stimulus processing (e.g., triangle). However, there is a growing debate as to whether the SPE is genuine or determined by the labels (e.g., 'me', 'you') being pre-existing self-referential anchor points. We investigated this in an adapted perceptual matching task in which participants were instructed to associate arbitrary stimulus pairs (visual features: shape and colour) with different people and then immediately carried out a colour-shape matching task. The results showed the standard pattern of the SPE in this perceptual matching task without familiar labels, indicating that the effect is not critically dependent on familiar labels. Further analysis revealed that the SPE emerged only when the complete shape-colour pairing was presented rather than individual elements (self-shape or self-colour). The theoretical implications of these findings are considered.

Profile Pictures in the Digital World: Self-Photographs Predict Better Life Satisfaction.

Profiles pictures as online identities represent an extension of the user's self in the digital world. Changes in self-representation are responsible for reduced well-being in individuals in the offline world. However, whether profile picture selection predicts the well-being of internet users is unknown. To address this question, we tested the relationship between the type of profile picture (e.g., self-photographs or other pictures) used on social media and the life satisfaction of internet users, accounting for gender and personality traits that have been thought to relate to the selection of profile pictures. The results showed that individuals using self-photographs as profiles reported a higher level of life satisfaction compared to individuals using other pictures as profiles. This effect was influenced by gender, openness, and extraversion. Hierarchical regression and moderation analyses revealed that openness and profile type interacted to predict life satisfaction in women, while openness and profile picture independently predicted life satisfaction in men. Furthermore, extraversion directly predicted life satisfaction in both men and women. These results indicate that the consistency between one's online and offline self-representation may characterize internet users' well-being, with potential implications for digital wellness.