Distress,wellbeing, and growth amidst COVID-19: Considering the dynamic interplay between positive and negative anticipatory emotions

Although negative anticipatory emotions are typically seen as risk factors for poorer psychological outcomes over COVID-19, emotion theorists suggest that this risk may be attenuated if balanced by the experience of positive emotion. Thus, the current study examined whether interactions between positive and negative anticipatory emotions were concurrently associated with psychological distress and greater personal wellbeing/posttraumatic growth (PTG) at three distinct periods (i.e., pre-lockdown, during lockdown, post-lockdown), and whether associations varied by these three COVID-19 time periods. The study utilizes two large longitudinal Australian samples, surveyed in 2020 prior to, during, and after a strict 4-month lockdown that occurred in Australia. Overall, positive emotions attenuated the adverse psychological outcomes arising from higher levels of negative emotion (i.e., higher psychological distress and lower personal wellbeing). Observed effects varied according to COVID-19 threat exposure. Specifically, the interaction was significantly associated with psychological distress prior to the lockdown for Sample 2, and during the lockdown for both samples. The interaction was significantly associated with wellbeing (Sample 2) prior to, and during, the lockdown but only marginally associated post-lockdown. The interaction, however, was not significantly associated with PTG (Sample 1). The results suggest that it is valuable for future research to consider greater emotional complexity (i.e., mixed emotions) over COVID-19, and other stressors more generally, to encompass a more nuanced understanding of resilience.     

Mapping physical characteristics in face images to social judgements

Sutherland and Young (Br. J. Psychol., 113, 2022, 1056) provide a comprehensive and timely overview of recent developments in research on social judgements of faces, emphasizing the utility of data-driven approaches. Here, we expand on this theme, focusing on how data-driven approaches can provide new insights into the physical characteristics in face images that best predict social judgements.     

We need to move beyond rating scales,white faces and adult perceivers: Invited Commentary on Sutherland & Young (2022), understanding trait impressions from faces

Sutherland and Young's perspective is a timely and rigorous examination of trait impressions based on facial cues. We propose three strtegies to further advance the field: incorporating natural language processing, including diverse facial stimuli, and re-interpreting developmental data.     

A note on McDonald's generalization of principal components analysis

It is shown that McDonald's generalization of classical Principal Components Analysis to groups of variables maximally channels the total variance of the original variables through the groups of variables acting as groups. A useful equation is obtained for determining the vectors of correlations of theL2 components with the original variables. A calculation example is given.